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2026, Volume 56, Issue 5
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2026,
56(5):
1-13.
doi: 10.3724/j.gyjzG26040206
Abstract:
Taking the renovation project of C10 Laboratory at Tsinghua University’s Nankou Base for State Key Laboratories as the engineering background， this study focused on the core contradiction between industrial heritage conservation and the functional needs of national key laboratories in the adaptive reuse of old industrial buildings， and proposed a full-cycle renovation framework of "Conservation–Reconstruction–Symbiosis". With multi-source heterogeneous data fusion， this study completed a comprehensive diagnosis of the workshop， established a three-level industrial heritage conservation system， and developed integrated renovation technologies for heritage feature preservation and building performance improvement. The project achieved the coordinated goals of industrial context inheritance， scientific research function implementation and low-carbon development， and provided replicable engineering reference for the sci-tech innovation-oriented regeneration of similar old industrial areas.
Taking the renovation project of C10 Laboratory at Tsinghua University’s Nankou Base for State Key Laboratories as the engineering background， this study focused on the core contradiction between industrial heritage conservation and the functional needs of national key laboratories in the adaptive reuse of old industrial buildings， and proposed a full-cycle renovation framework of "Conservation–Reconstruction–Symbiosis". With multi-source heterogeneous data fusion， this study completed a comprehensive diagnosis of the workshop， established a three-level industrial heritage conservation system， and developed integrated renovation technologies for heritage feature preservation and building performance improvement. The project achieved the coordinated goals of industrial context inheritance， scientific research function implementation and low-carbon development， and provided replicable engineering reference for the sci-tech innovation-oriented regeneration of similar old industrial areas.
2026,
56(5):
14-28.
doi: 10.3724/j.gyjzG26022502
Abstract:
The external thermal insulation composite system （ETICS） is crucial for improving building energy efficiency and ensuring building functionality. In recent years， issues such as cracking， hollowing， peeling， and high-altitude falling have occurred frequently， posing a significant threat to public safety. A systematic review was conducted on domestic and international research and engineering practice regarding diagnosis and treatment methods for detection， evaluation， and repair of building ETICS. In terms of detection， non-destructive testing techniques were categorized into four types based on their energy forms and physical mechanisms， namely optical， thermal， electromagnetic， and acoustic. The research progress of various non-destructive testing techniques and commonly used destructive testing techniques was systematically reviewed. A comparative analysis was conducted on the technical points， advantages and disadvantages， and applicable scenarios of various detection techniques. In terms of evaluation， the characteristics and progress of existing evaluation methods were summarized from three aspects： qualitative evaluation， quantitative evaluation， and comprehensive evaluation. In terms of repair， the current development status of existing repair methods was introduced from the perspectives of repair technology， repair materials， and repair strategies. Finally， the deficiencies in the research and engineering practice regarding diagnosis and treatment methods for building ETICS were analyzed， and future research directions were discussed.
The external thermal insulation composite system （ETICS） is crucial for improving building energy efficiency and ensuring building functionality. In recent years， issues such as cracking， hollowing， peeling， and high-altitude falling have occurred frequently， posing a significant threat to public safety. A systematic review was conducted on domestic and international research and engineering practice regarding diagnosis and treatment methods for detection， evaluation， and repair of building ETICS. In terms of detection， non-destructive testing techniques were categorized into four types based on their energy forms and physical mechanisms， namely optical， thermal， electromagnetic， and acoustic. The research progress of various non-destructive testing techniques and commonly used destructive testing techniques was systematically reviewed. A comparative analysis was conducted on the technical points， advantages and disadvantages， and applicable scenarios of various detection techniques. In terms of evaluation， the characteristics and progress of existing evaluation methods were summarized from three aspects： qualitative evaluation， quantitative evaluation， and comprehensive evaluation. In terms of repair， the current development status of existing repair methods was introduced from the perspectives of repair technology， repair materials， and repair strategies. Finally， the deficiencies in the research and engineering practice regarding diagnosis and treatment methods for building ETICS were analyzed， and future research directions were discussed.
2026,
56(5):
29-36.
doi: 10.3724/j.gyjzG26030304
Abstract:
Aiming at the problems of low efficiency， strong reliance on manual labor， high risk of high-altitude work， and secondary damage that is easily caused by contact detection in traditional methods for building exterior wall disease detection， this paper proposes an intelligent non-destructive detection method based on machine vision and deep learning. This method enables rapid identification of three types of apparent diseases： spalling， hollowing， and cracking. Using UAV high-precision collection equipment， disease images were collected from typical exterior wall types such as tiles， paint， and cement mortar. A building exterior wall disease image database containing 1018 images of three types of diseases was constructed. Through LabelMe software， disease annotation was performed， forming 1168 spalling labels， 1619 hollowing labels， and 1515 cracking labels. Based on the deep learning YOLO11n model， multiple training schemes were implemented on the training set. This study found that， with 300 training epochs， an image size of 1280 pixels， and data augmentation enabled， a detection performance of mAP50 = 0.753 was achieved. This model relatively accurately identified the three types of apparent diseases： spalling， hollowing， and cracking. Finally， engineering instance applications were carried out in multiple residential communities in the Chengdu area， further proving that the model has good generalization ability and can provide a new technology for non-destructive rapid detection of building exterior wall diseases.
Aiming at the problems of low efficiency， strong reliance on manual labor， high risk of high-altitude work， and secondary damage that is easily caused by contact detection in traditional methods for building exterior wall disease detection， this paper proposes an intelligent non-destructive detection method based on machine vision and deep learning. This method enables rapid identification of three types of apparent diseases： spalling， hollowing， and cracking. Using UAV high-precision collection equipment， disease images were collected from typical exterior wall types such as tiles， paint， and cement mortar. A building exterior wall disease image database containing 1018 images of three types of diseases was constructed. Through LabelMe software， disease annotation was performed， forming 1168 spalling labels， 1619 hollowing labels， and 1515 cracking labels. Based on the deep learning YOLO11n model， multiple training schemes were implemented on the training set. This study found that， with 300 training epochs， an image size of 1280 pixels， and data augmentation enabled， a detection performance of mAP50 = 0.753 was achieved. This model relatively accurately identified the three types of apparent diseases： spalling， hollowing， and cracking. Finally， engineering instance applications were carried out in multiple residential communities in the Chengdu area， further proving that the model has good generalization ability and can provide a new technology for non-destructive rapid detection of building exterior wall diseases.
2026,
56(5):
37-46.
doi: 10.3724/j.gyjzG26013007
Abstract:
The To elucidate the propagation laws of vibrations generated during the operation of variable-frequency equipment and the influence of such vibrations on building structures， an engineering project incorporating such equipment was investigated through field vibration measurements. Vibration response data were collected at the equipment source， along multiple propagation paths， and on different floors of the building， enabling an examination of the effects of excitation frequency， propagation distance， and spatial direction. The results indicated that the vibration propagation in soil exhibited obvious frequency-dependent characteristics， with the vertical acceleration transmissibility decreasing as the operating frequency increased. Notably， the vibration propagation showed significant directional anisotropy， with the horizontal transmissibility 30% to 50% higher than the vertical one. Vibration amplitude decayed approximately exponentially as the propagation distance increased. Based on the measured data， a quantitative relationship between vertical acceleration transmissibility and propagation distance considering excitation frequency was established. The relationship revealed that vibrations attenuated to the ambient background level at a distance of approximately 200 to 220 m from the vibration source. The vibration distribution inside the building was jointly governed by floor height and structural configuration， and distinct floor vibration response characteristics in different directions were observed due to differences in structural stiffness.
The To elucidate the propagation laws of vibrations generated during the operation of variable-frequency equipment and the influence of such vibrations on building structures， an engineering project incorporating such equipment was investigated through field vibration measurements. Vibration response data were collected at the equipment source， along multiple propagation paths， and on different floors of the building， enabling an examination of the effects of excitation frequency， propagation distance， and spatial direction. The results indicated that the vibration propagation in soil exhibited obvious frequency-dependent characteristics， with the vertical acceleration transmissibility decreasing as the operating frequency increased. Notably， the vibration propagation showed significant directional anisotropy， with the horizontal transmissibility 30% to 50% higher than the vertical one. Vibration amplitude decayed approximately exponentially as the propagation distance increased. Based on the measured data， a quantitative relationship between vertical acceleration transmissibility and propagation distance considering excitation frequency was established. The relationship revealed that vibrations attenuated to the ambient background level at a distance of approximately 200 to 220 m from the vibration source. The vibration distribution inside the building was jointly governed by floor height and structural configuration， and distinct floor vibration response characteristics in different directions were observed due to differences in structural stiffness.
2026,
56(5):
47-56.
doi: 10.3724/j.gyjzG25031105
Abstract:
This paper introduces the U.S. standard system for existing buildings， analyzes the seismic evaluation techniques， and focuses on the FEMA P-154-2015 rapid visual screening method and the ASCE/SEI 41-23 three-level evaluation process. The United States adopts a grading mode characterized by “graded screening， differentiated evaluation， and targeted reinforcement” for the governance of existing buildings. This mode offers the advantages of flexibility and high efficiency， while also having certain limitations. By comparing the standards of the two countries and considering China's actual conditions， this paper proposes recommendations， such as defining benchmark buildings to simplify the evaluation process and improving performance-based assessment methods to complement traditional appraisals. It aims to provide technical references for construction projects under “the Belt and Road” initiative， thereby offering insights for the scientific and standardized management of existing buildings as well as for urban renewal.
This paper introduces the U.S. standard system for existing buildings， analyzes the seismic evaluation techniques， and focuses on the FEMA P-154-2015 rapid visual screening method and the ASCE/SEI 41-23 three-level evaluation process. The United States adopts a grading mode characterized by “graded screening， differentiated evaluation， and targeted reinforcement” for the governance of existing buildings. This mode offers the advantages of flexibility and high efficiency， while also having certain limitations. By comparing the standards of the two countries and considering China's actual conditions， this paper proposes recommendations， such as defining benchmark buildings to simplify the evaluation process and improving performance-based assessment methods to complement traditional appraisals. It aims to provide technical references for construction projects under “the Belt and Road” initiative， thereby offering insights for the scientific and standardized management of existing buildings as well as for urban renewal.
2026,
56(5):
57-66.
doi: 10.3724/j.gyjzG25050804
Abstract:
The Shenzhen local standard， Technical Standard for Green Demolition of Buildings， was issued and implemented on January 31， 2025， by the Shenzhen Municipal Standards Committee. Based on this newly compiled standard， the definition， framework， application objectives， and demolition technologies for green demolition were analyzed； the current development status of building demolition methods was summarized and evaluated； and the principles for preparing a special green demolition scheme， which balances the goals of structural dismantling safety and comprehensive utilization of demolition waste， were elaborated. Furthermore， a practical application of the standard was carried out in a building demolition project in the Xinqiao East Area urban renewal project in Shenzhen. The results showed that the technical guidelines established in the standard enabled classified and orderly demolition of existing buildings， leading to classified and graded comprehensive utilization of demolition waste. This achieved an on-site utilization rate of 30% and a comprehensive utilization rate of 100% for the demolition waste， thereby improving the comprehensive utilization level and resource recovery efficiency of the project’s demolition waste. This established a technical paradigm for green demolition of buildings and provided a basis for the promotion and application of green demolition technologies.
The Shenzhen local standard， Technical Standard for Green Demolition of Buildings， was issued and implemented on January 31， 2025， by the Shenzhen Municipal Standards Committee. Based on this newly compiled standard， the definition， framework， application objectives， and demolition technologies for green demolition were analyzed； the current development status of building demolition methods was summarized and evaluated； and the principles for preparing a special green demolition scheme， which balances the goals of structural dismantling safety and comprehensive utilization of demolition waste， were elaborated. Furthermore， a practical application of the standard was carried out in a building demolition project in the Xinqiao East Area urban renewal project in Shenzhen. The results showed that the technical guidelines established in the standard enabled classified and orderly demolition of existing buildings， leading to classified and graded comprehensive utilization of demolition waste. This achieved an on-site utilization rate of 30% and a comprehensive utilization rate of 100% for the demolition waste， thereby improving the comprehensive utilization level and resource recovery efficiency of the project’s demolition waste. This established a technical paradigm for green demolition of buildings and provided a basis for the promotion and application of green demolition technologies.
2026,
56(5):
67-75.
doi: 10.3724/j.gyjzG26040908
Abstract:
The Red Mansion at No. 106 Huangpu Road， Shanghai， was constructed in 1911. It is a three-story brick-wood structure. In its comprehensive protective renovation project， three major challenges were encountered： the simultaneous construction of a complex group of adjacent deep foundation pits， the overall ultra-high jacking by 6.55 m to restore its historical appearance， and the synchronous development of underground space together with the improvement of the building’s seismic performance. To address these challenges， a complete set of key techniques was proposed， integrating underpinning， active deformation control， synchronous high-position jacking， and seismic isolation with story addition. Using an adjustable active underpinning system， the cumulative additional deformation of the Red Mansion during the construction of the surrounding deep foundation pits was controlled within ±5 mm. A relay lifting technique combining "lifting + jacking" was adopted to achieve the ultra-high jacking of 6.55 m， along with the simultaneous high-position rectification of 300 mm. The addition of a seismic isolation layer significantly enhanced the structural seismic performance. After three rounds of whole-process load transfer， the maximum inclination ratio of the building foundation was reduced from the initial 9.12‰ to below 2.5‰， with no new structural cracks generated. This project realized the in-situ preservation， jacking with story addition， and functional upgrading of an outstanding historical building in Shanghai under the condition of simultaneous construction adjacent to a group of deep foundation pits， setting a record for the highest overall jacking height of modern outstanding historical buildings in China.
The Red Mansion at No. 106 Huangpu Road， Shanghai， was constructed in 1911. It is a three-story brick-wood structure. In its comprehensive protective renovation project， three major challenges were encountered： the simultaneous construction of a complex group of adjacent deep foundation pits， the overall ultra-high jacking by 6.55 m to restore its historical appearance， and the synchronous development of underground space together with the improvement of the building’s seismic performance. To address these challenges， a complete set of key techniques was proposed， integrating underpinning， active deformation control， synchronous high-position jacking， and seismic isolation with story addition. Using an adjustable active underpinning system， the cumulative additional deformation of the Red Mansion during the construction of the surrounding deep foundation pits was controlled within ±5 mm. A relay lifting technique combining "lifting + jacking" was adopted to achieve the ultra-high jacking of 6.55 m， along with the simultaneous high-position rectification of 300 mm. The addition of a seismic isolation layer significantly enhanced the structural seismic performance. After three rounds of whole-process load transfer， the maximum inclination ratio of the building foundation was reduced from the initial 9.12‰ to below 2.5‰， with no new structural cracks generated. This project realized the in-situ preservation， jacking with story addition， and functional upgrading of an outstanding historical building in Shanghai under the condition of simultaneous construction adjacent to a group of deep foundation pits， setting a record for the highest overall jacking height of modern outstanding historical buildings in China.
2026,
56(5):
76-86.
doi: 10.3724/j.gyjzG26031407
Abstract:
Dovetail profiled steel sheets are characterized by a unique rib configuration that ensures a flat plate surface. Compared with conventional flat steel plates， they offer higher buckling resistance， greater out-of-plane stiffness， and more effective interaction with concrete. These superior properties render them well-suited for enhancing the mechanical properties of wall claddings， lateral force-resisting components， and steel-concrete composite structures. To clarify their in-plane shear mechanism， pure shear diagonal loading tests were conducted on two dovetail profiled steel sheet specimens： DPS-V with vertically oriented ribs and DPS-D with ribs inclined at 45°. Experimental observations were focused on buckling modes， deformation evolution， and failure modes， while finite element analysis （FEA） was employed to further elucidate the underlying working mechanism. The results indicated that the profiled ribs provided effective boundary restraint to the plate strips， thereby inhibiting global penetrating buckling. Both specimens exhibited localized buckling within the plate strips， with DPS-V undergoing shear buckling and DPS-D experiencing compressive buckling. Owing to the boundary restraint provided by the ribs， the plate strips were capable of developing post-buckling strength； however， the tensile effect induced by the formation of local tension fields ultimately led to flexural-torsional instability of the ribs， resulting in overall failure. The shear resistance of DPS-V was primarily provided by the plate strips， whereas that of DPS-D was derived from the combined action of the plate strips and ribs， exhibiting significant anisotropic behavior—its bearing capacity under diagonal tension was 38% higher than that under diagonal compression. Although the initial stiffness and ultimate bearing capacity of DPS-V were slightly lower than those of DPS-D， DPS-V demonstrated superior ductility and deformability beyond the peak load. Based on the superposition principle， design formulas for predicting the shear capacity of the two types of steel sheets were proposed. The relative error between the calculated and experimental values was within 4%， providing a reliable reference for the engineering design of such components.
Dovetail profiled steel sheets are characterized by a unique rib configuration that ensures a flat plate surface. Compared with conventional flat steel plates， they offer higher buckling resistance， greater out-of-plane stiffness， and more effective interaction with concrete. These superior properties render them well-suited for enhancing the mechanical properties of wall claddings， lateral force-resisting components， and steel-concrete composite structures. To clarify their in-plane shear mechanism， pure shear diagonal loading tests were conducted on two dovetail profiled steel sheet specimens： DPS-V with vertically oriented ribs and DPS-D with ribs inclined at 45°. Experimental observations were focused on buckling modes， deformation evolution， and failure modes， while finite element analysis （FEA） was employed to further elucidate the underlying working mechanism. The results indicated that the profiled ribs provided effective boundary restraint to the plate strips， thereby inhibiting global penetrating buckling. Both specimens exhibited localized buckling within the plate strips， with DPS-V undergoing shear buckling and DPS-D experiencing compressive buckling. Owing to the boundary restraint provided by the ribs， the plate strips were capable of developing post-buckling strength； however， the tensile effect induced by the formation of local tension fields ultimately led to flexural-torsional instability of the ribs， resulting in overall failure. The shear resistance of DPS-V was primarily provided by the plate strips， whereas that of DPS-D was derived from the combined action of the plate strips and ribs， exhibiting significant anisotropic behavior—its bearing capacity under diagonal tension was 38% higher than that under diagonal compression. Although the initial stiffness and ultimate bearing capacity of DPS-V were slightly lower than those of DPS-D， DPS-V demonstrated superior ductility and deformability beyond the peak load. Based on the superposition principle， design formulas for predicting the shear capacity of the two types of steel sheets were proposed. The relative error between the calculated and experimental values was within 4%， providing a reliable reference for the engineering design of such components.
2026,
56(5):
87-98.
doi: 10.3724/j.gyjzG26010801
Abstract:
The Nanjing City Wall represents the pinnacle of ancient Chinese city wall construction and holds significant cultural heritage value. However， due to the deterioration of its structural integrity and external environmental factors， it faces substantial safety concerns requiring urgent restoration and reinforcement. First， this study examined the structural configuration and damage conditions of the section from Jiefang Gate to Xuanwu Gate based on field surveys and literature review. Second， finite element analysis using ANSYS software was conducted on the wall structure. The analysis focused on evaluating the mechanical properties and safety under various combined conditions， including the effects of air-raid shelters and moisture absorption/expansion of internal brick-rubble-soil fill， to identify potential hazards. Finally， adaptive restoration and conservation measures were proposed， balancing both the preservation of historical appearance and the reinforcement of structural safety. This study implemented targeted reinforcement measures for different types and grades of deterioration， including structural strengthening of wall bodies， rampart top surfaces， and arches. Under the premise of preserving historical appearance， the wall structure was reinforced to achieve minimal intervention conservation for cultural heritage buildings， providing valuable insights and references for the preservation and restoration of ancient city walls.
The Nanjing City Wall represents the pinnacle of ancient Chinese city wall construction and holds significant cultural heritage value. However， due to the deterioration of its structural integrity and external environmental factors， it faces substantial safety concerns requiring urgent restoration and reinforcement. First， this study examined the structural configuration and damage conditions of the section from Jiefang Gate to Xuanwu Gate based on field surveys and literature review. Second， finite element analysis using ANSYS software was conducted on the wall structure. The analysis focused on evaluating the mechanical properties and safety under various combined conditions， including the effects of air-raid shelters and moisture absorption/expansion of internal brick-rubble-soil fill， to identify potential hazards. Finally， adaptive restoration and conservation measures were proposed， balancing both the preservation of historical appearance and the reinforcement of structural safety. This study implemented targeted reinforcement measures for different types and grades of deterioration， including structural strengthening of wall bodies， rampart top surfaces， and arches. Under the premise of preserving historical appearance， the wall structure was reinforced to achieve minimal intervention conservation for cultural heritage buildings， providing valuable insights and references for the preservation and restoration of ancient city walls.
2026,
56(5):
99-112.
doi: 10.3724/j.gyjzG26031504
Abstract:
The concrete-filled steel tubular （CFST） column-double laminated slab composite shear wall is a novel composite structural form for prefabricated buildings. A refined three-dimensional finite element model was established using ABAQUS and validated against quasi-static test data. Combined with test and numerical results， the mechanical mechanism under quasi-static loading was revealed， and the shear slip at the precast-cast-in-situ concrete interface was identified as the intrinsic cause of composite action degradation and performance deterioration. On this basis， a trilinear backbone curve model applicable to composite shear walls with a shear span ratio greater than 1.5 was proposed， along with formulas for equivalent stiffness and cross-sectional bearing capacity. Hysteretic rules were established based on a modified Clough model to develop a complete restoring force model. Validation results showed that the theoretical predictions agreed well with the test （numerical） results. Furthermore， an interface strengthening scheme using angle steel shear keys was proposed， which increased the ultimate drift ratio by 34% and the ductility coefficient by 26%， significantly improving the plastic deformation capacity.
The concrete-filled steel tubular （CFST） column-double laminated slab composite shear wall is a novel composite structural form for prefabricated buildings. A refined three-dimensional finite element model was established using ABAQUS and validated against quasi-static test data. Combined with test and numerical results， the mechanical mechanism under quasi-static loading was revealed， and the shear slip at the precast-cast-in-situ concrete interface was identified as the intrinsic cause of composite action degradation and performance deterioration. On this basis， a trilinear backbone curve model applicable to composite shear walls with a shear span ratio greater than 1.5 was proposed， along with formulas for equivalent stiffness and cross-sectional bearing capacity. Hysteretic rules were established based on a modified Clough model to develop a complete restoring force model. Validation results showed that the theoretical predictions agreed well with the test （numerical） results. Furthermore， an interface strengthening scheme using angle steel shear keys was proposed， which increased the ultimate drift ratio by 34% and the ductility coefficient by 26%， significantly improving the plastic deformation capacity.
2026,
56(5):
113-120.
doi: 10.3724/j.gyjzG26030401
Abstract:
Hyperbolic cooling tower shells are mostly cast-in-place reinforced concrete thin-walled structures. Their high-altitude construction poses significant challenges， and geometric imperfections often occur due to issues in construction layout accuracy. Focusing on a specific engineering case， this study employed terrestrial laser scanning （TLS） technology to capture precise geometric imperfection data of the tower shell. Based on the scanned data， finite element models of the hyperbolic cooling tower， both with and without geometric imperfections， were developed using ABAQUS. The effects of geometric imperfections on the mechanical properties of the cooling tower， as well as the sensitivity of different load effects to these imperfections， were systematically investigated. The results indicated that when the actual imperfection magnitude was introduced based on the measured distribution pattern， the bearing capacity and crack resistance of the tower shell decreased significantly. Moreover， no deterioration in mechanical properties was observed when the imperfection magnitude remained below 150 mm. The effects of dead load and external wind pressure were highly sensitive to geometric imperfections， whereas temperature effects remained almost unaffected. Furthermore， the locations along the meridian lines of the tower shell where the maximum external wind suction occurs were identified as critical regions for safety assessment.
Hyperbolic cooling tower shells are mostly cast-in-place reinforced concrete thin-walled structures. Their high-altitude construction poses significant challenges， and geometric imperfections often occur due to issues in construction layout accuracy. Focusing on a specific engineering case， this study employed terrestrial laser scanning （TLS） technology to capture precise geometric imperfection data of the tower shell. Based on the scanned data， finite element models of the hyperbolic cooling tower， both with and without geometric imperfections， were developed using ABAQUS. The effects of geometric imperfections on the mechanical properties of the cooling tower， as well as the sensitivity of different load effects to these imperfections， were systematically investigated. The results indicated that when the actual imperfection magnitude was introduced based on the measured distribution pattern， the bearing capacity and crack resistance of the tower shell decreased significantly. Moreover， no deterioration in mechanical properties was observed when the imperfection magnitude remained below 150 mm. The effects of dead load and external wind pressure were highly sensitive to geometric imperfections， whereas temperature effects remained almost unaffected. Furthermore， the locations along the meridian lines of the tower shell where the maximum external wind suction occurs were identified as critical regions for safety assessment.
2026,
56(5):
121-129.
doi: 10.3724/j.gyjzG26021101
Abstract:
To address the safety disturbance caused by urban rail transit construction to adjacent tall structures， this study conducted a systematic structural safety assessment on a TV tower in the context of construction adjacent to a metro transfer station and a shield tunnel. Field structural inspection， long-term deformation monitoring， and three-dimensional numerical simulation were integrated to assess the current condition of the TV tower structure， the evolution patterns of horizontal and vertical foundation displacements， and the inclination characteristics of the tower body. These methods also accurately quantified the impacts of metro foundation pit excavation and shield tunnel construction on the tower's foundation and superstructure. The results showed that the current concrete strength of the TV tower meets the design requirements， with a historically accumulated foundation inclination ratio of 1.3‰. Numerical simulation predicted that subsequent construction would increase the inclination ratio by 0.31‰， resulting in a total inclination ratio of 1.61‰， which still meets safety requirements. Based on these findings， targeted deformation control standards and engineering recommendations were proposed.
To address the safety disturbance caused by urban rail transit construction to adjacent tall structures， this study conducted a systematic structural safety assessment on a TV tower in the context of construction adjacent to a metro transfer station and a shield tunnel. Field structural inspection， long-term deformation monitoring， and three-dimensional numerical simulation were integrated to assess the current condition of the TV tower structure， the evolution patterns of horizontal and vertical foundation displacements， and the inclination characteristics of the tower body. These methods also accurately quantified the impacts of metro foundation pit excavation and shield tunnel construction on the tower's foundation and superstructure. The results showed that the current concrete strength of the TV tower meets the design requirements， with a historically accumulated foundation inclination ratio of 1.3‰. Numerical simulation predicted that subsequent construction would increase the inclination ratio by 0.31‰， resulting in a total inclination ratio of 1.61‰， which still meets safety requirements. Based on these findings， targeted deformation control standards and engineering recommendations were proposed.
2026,
56(5):
130-140.
doi: 10.3724/j.gyjzG26031403
Abstract:
The stop-hole method is a commonly used technique for repairing fatigue cracks of steel structures in engineering practice； however， it suffers from issues such as unreliable repair effectiveness and damage to the cross-section. By combining externally bonded CFRP plates with the stop-hole to form a combined repair method， the limitations of a single method can be compensated for， achieving efficient repair of fatigue cracks. To investigate the enhancement effect of CFRP plates on stop-hole repair， a numerical analysis of the fatigue performance was conducted on single-edged cracked steel plates repaired with combined stop-hole and CFRP plate， based on the local stress-strain approach and fracture mechanics theory. A two-stage fatigue life assessment method for combined repaired steel plates was established and validated through comparisons with existing experimental studies. The results showed that， compared with the stop-hole repair， the combined repair method significantly reduced the stress around the hole edge and the stress intensity factor after crack re-initiation， thereby delaying crack propagation and significantly reducing the crack growth rate. Compared with CFRP plate repair， the combined repair method provided additional crack initiation life， demonstrating its high repair efficiency.
The stop-hole method is a commonly used technique for repairing fatigue cracks of steel structures in engineering practice； however， it suffers from issues such as unreliable repair effectiveness and damage to the cross-section. By combining externally bonded CFRP plates with the stop-hole to form a combined repair method， the limitations of a single method can be compensated for， achieving efficient repair of fatigue cracks. To investigate the enhancement effect of CFRP plates on stop-hole repair， a numerical analysis of the fatigue performance was conducted on single-edged cracked steel plates repaired with combined stop-hole and CFRP plate， based on the local stress-strain approach and fracture mechanics theory. A two-stage fatigue life assessment method for combined repaired steel plates was established and validated through comparisons with existing experimental studies. The results showed that， compared with the stop-hole repair， the combined repair method significantly reduced the stress around the hole edge and the stress intensity factor after crack re-initiation， thereby delaying crack propagation and significantly reducing the crack growth rate. Compared with CFRP plate repair， the combined repair method provided additional crack initiation life， demonstrating its high repair efficiency.
2026,
56(5):
141-147.
doi: 10.3724/j.gyjzG26031503
Abstract:
Many existing rural houses face structural safety hazards due to material performance degradation. This study investigated the residual bearing capacity and the strengthening effect of carbon fiber reinforced polymer （CFRP） sheets on old precast prestressed concrete （PC） hollow-core slabs， using specimens obtained from a demolished 45-year-old rural house in Shanghai. The test involved two PC slabs： one served as the control specimen， and the other was strengthened with CFRP sheets. Static loading tests were conducted to compare and analyze their failure modes， deformation capacity， and energy dissipation capacity. Based on the measured data， the strain development pattern of the CFRP sheets was analyzed. The results showed that the 45-year-old PC hollow-core slabs still had a certain bearing capacity but with a low safety margin， exhibiting a typical brittle flexural failure due to under-reinforcement. After CFRP strengthening， the failure mode changed to shear failure with obvious ductile characteristics， because the CFRP sheets bore the main tensile stress in the later loading stage.
Many existing rural houses face structural safety hazards due to material performance degradation. This study investigated the residual bearing capacity and the strengthening effect of carbon fiber reinforced polymer （CFRP） sheets on old precast prestressed concrete （PC） hollow-core slabs， using specimens obtained from a demolished 45-year-old rural house in Shanghai. The test involved two PC slabs： one served as the control specimen， and the other was strengthened with CFRP sheets. Static loading tests were conducted to compare and analyze their failure modes， deformation capacity， and energy dissipation capacity. Based on the measured data， the strain development pattern of the CFRP sheets was analyzed. The results showed that the 45-year-old PC hollow-core slabs still had a certain bearing capacity but with a low safety margin， exhibiting a typical brittle flexural failure due to under-reinforcement. After CFRP strengthening， the failure mode changed to shear failure with obvious ductile characteristics， because the CFRP sheets bore the main tensile stress in the later loading stage.
2026,
56(5):
148-158.
doi: 10.3724/j.gyjzG26032102
Abstract:
Asphalt pavement joints are prone to distresses such as cracking， faulting， and water infiltration. Existing studies mainly focus on material modification and construction techniques， while systematic design of joint components in asphalt layers remains limited. To improve the structural integrity and service performance of pavement joints， this paper proposes a novel joint component with a telescopic double-tube structure and establishes the corresponding construction technology system. First， based on the principle of load transfer and deformation coordination， a telescopic structure with square steel tubes was designed， and its load transfer efficiency under different parameter combinations was analyzed using the finite element method. Second， field monitoring was conducted on an in-service expressway to investigate the strain response of the component under coupled traffic loading and temperature effects. Finally， the construction process and key control measures were summarized. The results showed that the proposed component exhibited excellent load transfer capability and deformation adaptability， with a load transfer coefficient exceeding 0.88 and a low degree of dispersion. Field monitoring results verified its stable mechanical properties， and its strain response was highly consistent with temperature variations and traffic load distribution. The proposed construction method ensured installation accuracy and long-term durability.
Asphalt pavement joints are prone to distresses such as cracking， faulting， and water infiltration. Existing studies mainly focus on material modification and construction techniques， while systematic design of joint components in asphalt layers remains limited. To improve the structural integrity and service performance of pavement joints， this paper proposes a novel joint component with a telescopic double-tube structure and establishes the corresponding construction technology system. First， based on the principle of load transfer and deformation coordination， a telescopic structure with square steel tubes was designed， and its load transfer efficiency under different parameter combinations was analyzed using the finite element method. Second， field monitoring was conducted on an in-service expressway to investigate the strain response of the component under coupled traffic loading and temperature effects. Finally， the construction process and key control measures were summarized. The results showed that the proposed component exhibited excellent load transfer capability and deformation adaptability， with a load transfer coefficient exceeding 0.88 and a low degree of dispersion. Field monitoring results verified its stable mechanical properties， and its strain response was highly consistent with temperature variations and traffic load distribution. The proposed construction method ensured installation accuracy and long-term durability.
2026,
56(5):
159-166.
doi: 10.3724/j.gyjzG26032606
Abstract:
This study investigated the fatigue life of steel crane beams through fatigue testing and combined finite element analysis to reveal the stress distribution changes at the support of variable-section beams before and after prestress strengthening. In addition， the equivalent structural stress method was employed to predict the fatigue life corresponding to the initiation of 20 mm cracks at the support. The results indicated that prestress strengthening significantly reduced the stress level at critical welds， while the location of maximum stress and the failure mode remained unchanged. With increasing prestress control values， both the overall failure life of the beam and the crack initiation life at the support were significantly extended. Under a prestress control value of 12.5 t， the strengthening effectiveness factors for overall beam failure and visible support cracks reached 4.08 and 4.23， respectively， demonstrating the effectiveness of high-level prestressing.
This study investigated the fatigue life of steel crane beams through fatigue testing and combined finite element analysis to reveal the stress distribution changes at the support of variable-section beams before and after prestress strengthening. In addition， the equivalent structural stress method was employed to predict the fatigue life corresponding to the initiation of 20 mm cracks at the support. The results indicated that prestress strengthening significantly reduced the stress level at critical welds， while the location of maximum stress and the failure mode remained unchanged. With increasing prestress control values， both the overall failure life of the beam and the crack initiation life at the support were significantly extended. Under a prestress control value of 12.5 t， the strengthening effectiveness factors for overall beam failure and visible support cracks reached 4.08 and 4.23， respectively， demonstrating the effectiveness of high-level prestressing.
2026,
56(5):
167-175.
doi: 10.3724/j.gyjzG25111704
Abstract:
This study applied machine learning to predict and optimize the hygrothermal performance of bamboo-woven mud walls， highlighting their potential in addressing environmental challenges. Generative adversarial networks （GANs） were first used to augment limited experimental data， addressing small-sample constraints. A back propagation （BP） neural network was employed to analyze and predict the performance of the wall materials. After optimization via a genetic algorithm （GA）， the model’s R2 improved to 0.77， indicating significantly enhanced predictive performance. These findings confirm the feasibility of using machine learning in the reuse of traditional building materials and provide a digital theoretical basis and technical support for the preservation and renewal of bamboo-woven mud walls.
This study applied machine learning to predict and optimize the hygrothermal performance of bamboo-woven mud walls， highlighting their potential in addressing environmental challenges. Generative adversarial networks （GANs） were first used to augment limited experimental data， addressing small-sample constraints. A back propagation （BP） neural network was employed to analyze and predict the performance of the wall materials. After optimization via a genetic algorithm （GA）， the model’s R2 improved to 0.77， indicating significantly enhanced predictive performance. These findings confirm the feasibility of using machine learning in the reuse of traditional building materials and provide a digital theoretical basis and technical support for the preservation and renewal of bamboo-woven mud walls.
2026,
56(5):
176-186.
doi: 10.3724/j.gyjzG26031308
Abstract:
To address the problem of missing multi-source monitoring data of offshore wind turbines caused by sensor failures or communication interruptions under harsh operating conditions， this paper proposes a novel imputation model based on a multi-head gated residual network. This method achieves collaborative fusion of supervisory control and data acquisition （SCADA） data and structural vibration monitoring data through feature concatenation， employs a gated residual network to extract deep nonlinear coupling features， and uses a multi-head parallel output architecture for the independent reconstruction of these two heterogeneous data types. During the training stage， a dynamic masking mechanism combined with a hybrid loss function is adopted to enhance the model’s adaptability to complex aerodynamic operating conditions. Validated with field data from a 10 MW offshore wind turbine， the proposed model achieved a high coefficient of determination under training conditions， enabling accurate reconstruction of missing multi-source data. In generalization tests for non-training periods， although the coefficient of determination of the model’s predictions fluctuated slightly， the model still effectively captured the overall trends of monitoring signals. Notably， the degradation in generalization performance for vibration data was less pronounced than that for SCADA data， demonstrating its greater stability. The proposed method can significantly improve the completeness and reliability of multi-source monitoring data for wind turbines and holds considerable potential for engineering applications.
To address the problem of missing multi-source monitoring data of offshore wind turbines caused by sensor failures or communication interruptions under harsh operating conditions， this paper proposes a novel imputation model based on a multi-head gated residual network. This method achieves collaborative fusion of supervisory control and data acquisition （SCADA） data and structural vibration monitoring data through feature concatenation， employs a gated residual network to extract deep nonlinear coupling features， and uses a multi-head parallel output architecture for the independent reconstruction of these two heterogeneous data types. During the training stage， a dynamic masking mechanism combined with a hybrid loss function is adopted to enhance the model’s adaptability to complex aerodynamic operating conditions. Validated with field data from a 10 MW offshore wind turbine， the proposed model achieved a high coefficient of determination under training conditions， enabling accurate reconstruction of missing multi-source data. In generalization tests for non-training periods， although the coefficient of determination of the model’s predictions fluctuated slightly， the model still effectively captured the overall trends of monitoring signals. Notably， the degradation in generalization performance for vibration data was less pronounced than that for SCADA data， demonstrating its greater stability. The proposed method can significantly improve the completeness and reliability of multi-source monitoring data for wind turbines and holds considerable potential for engineering applications.
2026,
56(5):
187-200.
doi: 10.3724/j.gyjzG26031401
Abstract:
To meet the demand for optimizing long-term maintenance decisions in intelligent bridge operation and maintenance， considering the characteristics of time-varying bridge deterioration under a finite horizon， financial discounting of maintenance costs， and difficulty in long-term reward propagation， a life-cycle maintenance decision model incorporating non-homogeneous deterioration and discounting effects was developed. The bridge deterioration process was characterized by non-homogeneous Markov state transitions. Based on discrete health states and maintenance actions， maintenance costs and risk costs were integrated into a unified cost function， while cash-flow discounting was introduced into the decision-making process. To address the limitations of conventional reinforcement learning methods in handling finite-horizon stage-wise decision tasks， non-homogeneous state transitions， and unstable training， a reinforcement learning framework combining state augmentation and backward curriculum learning was proposed. Expanded state representation enhanced the policy’s capability to capture finite-horizon characteristics， while backward curriculum learning gradually extended the training interval to improve learning stability and convergence efficiency. Numerical results demonstrated that the proposed method effectively adapted to finite-horizon maintenance decision problems under non-homogeneous bridge deterioration and achieved favorable performance in both policy quality and training stability， thereby providing methodological support for maintenance planning in life-cycle bridge operation and maintenance management.
To meet the demand for optimizing long-term maintenance decisions in intelligent bridge operation and maintenance， considering the characteristics of time-varying bridge deterioration under a finite horizon， financial discounting of maintenance costs， and difficulty in long-term reward propagation， a life-cycle maintenance decision model incorporating non-homogeneous deterioration and discounting effects was developed. The bridge deterioration process was characterized by non-homogeneous Markov state transitions. Based on discrete health states and maintenance actions， maintenance costs and risk costs were integrated into a unified cost function， while cash-flow discounting was introduced into the decision-making process. To address the limitations of conventional reinforcement learning methods in handling finite-horizon stage-wise decision tasks， non-homogeneous state transitions， and unstable training， a reinforcement learning framework combining state augmentation and backward curriculum learning was proposed. Expanded state representation enhanced the policy’s capability to capture finite-horizon characteristics， while backward curriculum learning gradually extended the training interval to improve learning stability and convergence efficiency. Numerical results demonstrated that the proposed method effectively adapted to finite-horizon maintenance decision problems under non-homogeneous bridge deterioration and achieved favorable performance in both policy quality and training stability， thereby providing methodological support for maintenance planning in life-cycle bridge operation and maintenance management.
2026,
56(5):
201-207.
doi: 10.3724/j.gyjzG26020903
Abstract:
In order to accurately separate the contributions of foundation settlement and structural damage to the deformation of port approach bridges and realize the physical attribution of structural damage， an integrated framework of "multi-source perception–physical modeling–deviation diagnosis" was adopted to develop a synergistic method combining time-series PS-InSAR-based foundation settlement monitoring， high-resolution optical image shadow analysis， and BIM-based parametric mechanical modeling. First， under a unified spatiotemporal datum， time-series PS-InSAR technology was applied to extract the foundation settlement field， while an improved Normalized Shadow Index （NSI） was used to invert the relative deformation at the tops of bridge piers. Second， an LOD350-level BIM model was converted into a parametric beam-grid mechanical model， and foundation settlement as well as thermal loads were taken as inputs to calculate the theoretical deformation response. Finally， a Damage Risk Index （DRI） was constructed to quantify the deviation between monitored and theoretical deformations， enabling damage early warning and localization. Closed-loop verification was further performed using an actual engineering case. The results showed that the proposed method achieved a mean absolute error （MAE） of approximately 1.14 mm and a root mean square error （RMSE） of approximately 1.46 mm in deformation monitoring， with 88% of data points having an error no greater than 2 mm and a damage identification accuracy of 93.7%. This method also supports the full-chain diagnostic process of "large-scale early warning – localized positioning–on-site verification – repair validation". It is concluded that this method effectively overcomes the limitations of single remote sensing techniques in interpreting deformation causes， achieves the transition from "phenomenon perception" to "mechanism interpretation"， and thus provides a reliable technical paradigm for the intelligent operation and maintenance of long linear steel-structure infrastructures such as port approach bridges.
In order to accurately separate the contributions of foundation settlement and structural damage to the deformation of port approach bridges and realize the physical attribution of structural damage， an integrated framework of "multi-source perception–physical modeling–deviation diagnosis" was adopted to develop a synergistic method combining time-series PS-InSAR-based foundation settlement monitoring， high-resolution optical image shadow analysis， and BIM-based parametric mechanical modeling. First， under a unified spatiotemporal datum， time-series PS-InSAR technology was applied to extract the foundation settlement field， while an improved Normalized Shadow Index （NSI） was used to invert the relative deformation at the tops of bridge piers. Second， an LOD350-level BIM model was converted into a parametric beam-grid mechanical model， and foundation settlement as well as thermal loads were taken as inputs to calculate the theoretical deformation response. Finally， a Damage Risk Index （DRI） was constructed to quantify the deviation between monitored and theoretical deformations， enabling damage early warning and localization. Closed-loop verification was further performed using an actual engineering case. The results showed that the proposed method achieved a mean absolute error （MAE） of approximately 1.14 mm and a root mean square error （RMSE） of approximately 1.46 mm in deformation monitoring， with 88% of data points having an error no greater than 2 mm and a damage identification accuracy of 93.7%. This method also supports the full-chain diagnostic process of "large-scale early warning – localized positioning–on-site verification – repair validation". It is concluded that this method effectively overcomes the limitations of single remote sensing techniques in interpreting deformation causes， achieves the transition from "phenomenon perception" to "mechanism interpretation"， and thus provides a reliable technical paradigm for the intelligent operation and maintenance of long linear steel-structure infrastructures such as port approach bridges.
2026,
56(5):
208-214.
doi: 10.3724/j.gyjzG26031901
Abstract:
This study investigated the structural response of a 24-year-old， 160 m span concrete-filled steel tubular （CFST） arch bridge after the fracture of a single tie rod. By comparing monitoring data before and after the tie rod fracture， this study systematically analyzed the variation characteristics of key mechanical indicators， including arch foot displacement， suspender cable force， and the alignment of the arch ribs and the bridge deck. Furthermore， it evaluated the influence pattern of the tie rod fracture on the bridge structure. The results showed that after the fracture of a single tie rod， the arch feet underwent outward displacement， and both the arch ribs and the bridge deck experienced downward deflection， with the deformation values on the fractured side being significantly larger than those on the non-fractured side. The suspender cable force showed no obvious change. The deformations of the arch ribs and the deck exhibited an asymmetric distribution： the vertical deflection of the free-end half-span on the fractured side was larger than that of the fixed-end half-span， while the opposite was true for the non-fractured side. Furthermore， a full-bridge finite element model was established to simulate the structural response of the bridge induced by the tie rod fracture， and the calculated results reproduced the monitoring data of the actual bridge well. Based on this model， a dynamic amplification factor was introduced to evaluate the stress state of the remaining tie rods and the arch ribs upon the sudden fracture of multiple tie rods.
This study investigated the structural response of a 24-year-old， 160 m span concrete-filled steel tubular （CFST） arch bridge after the fracture of a single tie rod. By comparing monitoring data before and after the tie rod fracture， this study systematically analyzed the variation characteristics of key mechanical indicators， including arch foot displacement， suspender cable force， and the alignment of the arch ribs and the bridge deck. Furthermore， it evaluated the influence pattern of the tie rod fracture on the bridge structure. The results showed that after the fracture of a single tie rod， the arch feet underwent outward displacement， and both the arch ribs and the bridge deck experienced downward deflection， with the deformation values on the fractured side being significantly larger than those on the non-fractured side. The suspender cable force showed no obvious change. The deformations of the arch ribs and the deck exhibited an asymmetric distribution： the vertical deflection of the free-end half-span on the fractured side was larger than that of the fixed-end half-span， while the opposite was true for the non-fractured side. Furthermore， a full-bridge finite element model was established to simulate the structural response of the bridge induced by the tie rod fracture， and the calculated results reproduced the monitoring data of the actual bridge well. Based on this model， a dynamic amplification factor was introduced to evaluate the stress state of the remaining tie rods and the arch ribs upon the sudden fracture of multiple tie rods.
2026,
56(5):
215-231.
doi: 10.3724/j.gyjzG26033109
Abstract:
Efficient and reliable structural health monitoring is essential for ensuring the safety and extending the service life of steel structures. Owing to the advantages of non-contact nature， high efficiency， and a high degree of automation， computer vision （CV） has gradually become an important technology for the inspection and maintenance of steel structures. Focusing on surface cracks and corrosion damage of steel structures， this review systematically summarizes the recent research progress in CV-based damage detection and outlines the major approaches， including image classification， object detection， and image segmentation. Particular attention is paid to key optimization strategies for small object detection， robustness under complex backgrounds， few-shot learning， and on-site deployment. Existing studies indicate that CV has significantly improved the automation， intelligence， and precision of damage detection for steel structures. However， further advances are still required in dataset standardization， model robustness to interference， generalization capability across scenarios， and lightweight real-time inference.
Efficient and reliable structural health monitoring is essential for ensuring the safety and extending the service life of steel structures. Owing to the advantages of non-contact nature， high efficiency， and a high degree of automation， computer vision （CV） has gradually become an important technology for the inspection and maintenance of steel structures. Focusing on surface cracks and corrosion damage of steel structures， this review systematically summarizes the recent research progress in CV-based damage detection and outlines the major approaches， including image classification， object detection， and image segmentation. Particular attention is paid to key optimization strategies for small object detection， robustness under complex backgrounds， few-shot learning， and on-site deployment. Existing studies indicate that CV has significantly improved the automation， intelligence， and precision of damage detection for steel structures. However， further advances are still required in dataset standardization， model robustness to interference， generalization capability across scenarios， and lightweight real-time inference.
2026,
56(5):
232-238.
doi: 10.3724/j.gyjzG26040802
Abstract:
To address the low efficiency， high risk， and limited quantitative capability of manual inspection for fatigue cracks in steel box girders， a study was conducted on the force analysis and motion control of a magnetic wall-climbing robot for crack inspection. According to the crack inspection requirements for deck plates and diaphragms， a wall-climbing robot equipped with an eddy current testing device was designed， and key parameters including overall dimensions， payload capacity， and operating speed were determined. Static and dynamic models of the robot were established to analyze the minimum magnetic adhesion force and driving torque required on steel plate surfaces. Based on the Webots platform， simulations were carried out to investigate the robot’s motion under different payload and weld obstacle conditions. The results showed that the robot could move continuously between the diaphragm and deck plate. As the payload increased， the start-up time on the diaphragm became longer and speed fluctuation became more pronounced， while the motion on the deck plate remained relatively stable. When crossing a weld， short-term speed fluctuations occurred， and the pitch angle increased significantly with the rising payload. Overall， the robot still maintained good obstacle-crossing capability and motion stability.
To address the low efficiency， high risk， and limited quantitative capability of manual inspection for fatigue cracks in steel box girders， a study was conducted on the force analysis and motion control of a magnetic wall-climbing robot for crack inspection. According to the crack inspection requirements for deck plates and diaphragms， a wall-climbing robot equipped with an eddy current testing device was designed， and key parameters including overall dimensions， payload capacity， and operating speed were determined. Static and dynamic models of the robot were established to analyze the minimum magnetic adhesion force and driving torque required on steel plate surfaces. Based on the Webots platform， simulations were carried out to investigate the robot’s motion under different payload and weld obstacle conditions. The results showed that the robot could move continuously between the diaphragm and deck plate. As the payload increased， the start-up time on the diaphragm became longer and speed fluctuation became more pronounced， while the motion on the deck plate remained relatively stable. When crossing a weld， short-term speed fluctuations occurred， and the pitch angle increased significantly with the rising payload. Overall， the robot still maintained good obstacle-crossing capability and motion stability.
2026,
56(5):
239-247.
doi: 10.3724/j.gyjzG26033101
Abstract:
A vision-based detection method for bolt missing and loosening using the optimal hexagon rule is proposed. High-quality images are obtained through preprocessing operations such as perspective transformation and distortion correction. Based on the optimal hexagon rule， combined with a regional attention mechanism and a residual efficient layer aggregation network， a keypoint detection algorithm based on YOLOv26 is developed to precisely locate the six vertex coordinates of the head of standard hexagonal-head bolts. The Graham scan algorithm is adopted to obtain the convex hull of the circumcircle of the six bolt vertices. Taking the centroid of the convex hull as the center， the sum of deviations between the actual and estimated values of the six vertices is minimized. The Broyden-Fletcher-Goldfarb-Shanno （BFGS） quasi-Newton optimization algorithm is used to adjust the vertex coordinates and generate optimized regular hexagon vertex coordinates. By comparing the coordinate states of bolts， the rotation angle of the bolt can be calculated. Bolt joint rotation tests using 16-hole three-color bolt heads （gray， blue， and red） showed that within the loosening angle range of 0–60°， the absolute error of the identified bolt loosening angle ranged from -2° to 2°， with a maximum relative error of 8%， demonstrating that the proposed optimal hexagon method provided high detection accuracy and stability.
A vision-based detection method for bolt missing and loosening using the optimal hexagon rule is proposed. High-quality images are obtained through preprocessing operations such as perspective transformation and distortion correction. Based on the optimal hexagon rule， combined with a regional attention mechanism and a residual efficient layer aggregation network， a keypoint detection algorithm based on YOLOv26 is developed to precisely locate the six vertex coordinates of the head of standard hexagonal-head bolts. The Graham scan algorithm is adopted to obtain the convex hull of the circumcircle of the six bolt vertices. Taking the centroid of the convex hull as the center， the sum of deviations between the actual and estimated values of the six vertices is minimized. The Broyden-Fletcher-Goldfarb-Shanno （BFGS） quasi-Newton optimization algorithm is used to adjust the vertex coordinates and generate optimized regular hexagon vertex coordinates. By comparing the coordinate states of bolts， the rotation angle of the bolt can be calculated. Bolt joint rotation tests using 16-hole three-color bolt heads （gray， blue， and red） showed that within the loosening angle range of 0–60°， the absolute error of the identified bolt loosening angle ranged from -2° to 2°， with a maximum relative error of 8%， demonstrating that the proposed optimal hexagon method provided high detection accuracy and stability.
2026,
56(5):
248-257.
doi: 10.3724/j.gyjzG26012002
Abstract:
To enhance the intelligent supervision of photovoltaic （PV） project progress and address the issue of low recognition accuracy caused by component occlusion in complex scenarios， this study proposed an automated recognition approach for key PV components that integrates UAV images with an improved object detection algorithm. In response to common challenges such as small-scale targets and occlusion interference in UAV images， this study developed an optimized non-maximum suppression mechanism and a dynamic screening strategy based on target size and category features. Experimental results showed that the improved model achieved stable convergence of the loss function during training. Its key performance indicators， including detection precision， recall， mAP50， and mAP50-95， reached 94.8%， 93.2%， 94.8%， and 96.5%， respectively. In the practical application of the Anduo PV project in Nagqu， Tibet， the average recognition accuracy for core components such as pile foundations， PV supports， and PV modules exceeded 95%， significantly outperforming traditional manual inspection methods. These findings demonstrated that the proposed approach effectively reduces target omission under occlusion through dynamic detection optimization， providing a feasible technical solution for intelligent progress monitoring in complex PV construction environments and possessing considerable practical engineering value.
To enhance the intelligent supervision of photovoltaic （PV） project progress and address the issue of low recognition accuracy caused by component occlusion in complex scenarios， this study proposed an automated recognition approach for key PV components that integrates UAV images with an improved object detection algorithm. In response to common challenges such as small-scale targets and occlusion interference in UAV images， this study developed an optimized non-maximum suppression mechanism and a dynamic screening strategy based on target size and category features. Experimental results showed that the improved model achieved stable convergence of the loss function during training. Its key performance indicators， including detection precision， recall， mAP50， and mAP50-95， reached 94.8%， 93.2%， 94.8%， and 96.5%， respectively. In the practical application of the Anduo PV project in Nagqu， Tibet， the average recognition accuracy for core components such as pile foundations， PV supports， and PV modules exceeded 95%， significantly outperforming traditional manual inspection methods. These findings demonstrated that the proposed approach effectively reduces target omission under occlusion through dynamic detection optimization， providing a feasible technical solution for intelligent progress monitoring in complex PV construction environments and possessing considerable practical engineering value.
2026,
56(5):
258-264.
doi: 10.3724/j.gyjzG25071403
Abstract:
Local deformation is a common damage to steel structures， and 3D reconstruction is an important approach to evaluate the bearing capacity of locally deformed angle steels. To accurately evaluate the accuracy of the SfM （Structure from Motion）-MVS （Multi-View Stereo） 3D reconstruction algorithm in establishing point cloud models of locally deformed steel components， this study proposed an accuracy evaluation method for angle steel point cloud models based on spatial Euclidean distance. Four types of locally deformed angle steels with two thicknesses were selected as the research objects， and an accuracy verification test was carried out on the digital image models of locally deformed steel components. The iterative closest point algorithm was used to align the test point cloud with the reference point cloud in space， and the accuracy of the point cloud model was quantified according to the Euclidean distance between corresponding points， so as to verify the accuracy of the angle steel point cloud model from a 3D perspective. The results showed that through the accuracy evaluation of the angle steel point cloud model， in the height and width directions， the points within the allowable range of dimensional deviation in the 3D point cloud models of the four types of locally deformed angle steels accounted for approximately 98% of the total number of point clouds in the models； in the thickness direction， the average error of the 5-mm-thick angle steel point cloud model was approximately 1.09 mm， while the average error of the 10-mm-thick angle steel point cloud model was approximately 1.02 mm； in the local deformation area， the average error of the four angle steel point cloud models was approximately 1.00 mm.
Local deformation is a common damage to steel structures， and 3D reconstruction is an important approach to evaluate the bearing capacity of locally deformed angle steels. To accurately evaluate the accuracy of the SfM （Structure from Motion）-MVS （Multi-View Stereo） 3D reconstruction algorithm in establishing point cloud models of locally deformed steel components， this study proposed an accuracy evaluation method for angle steel point cloud models based on spatial Euclidean distance. Four types of locally deformed angle steels with two thicknesses were selected as the research objects， and an accuracy verification test was carried out on the digital image models of locally deformed steel components. The iterative closest point algorithm was used to align the test point cloud with the reference point cloud in space， and the accuracy of the point cloud model was quantified according to the Euclidean distance between corresponding points， so as to verify the accuracy of the angle steel point cloud model from a 3D perspective. The results showed that through the accuracy evaluation of the angle steel point cloud model， in the height and width directions， the points within the allowable range of dimensional deviation in the 3D point cloud models of the four types of locally deformed angle steels accounted for approximately 98% of the total number of point clouds in the models； in the thickness direction， the average error of the 5-mm-thick angle steel point cloud model was approximately 1.09 mm， while the average error of the 10-mm-thick angle steel point cloud model was approximately 1.02 mm； in the local deformation area， the average error of the four angle steel point cloud models was approximately 1.00 mm.
