Nonlinear Damage Identification of Transmission Towers Based on AR/ARCH Model Conversion Distance and Its Experimental Research
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摘要: 输电塔等工程钢结构的安全常易受到裂纹等损伤的影响,该类损伤在结构振动中常表现出变刚度的非线性特征。为了解决该类非线性损伤检测问题,提出了一种基于自回归/自回归条件异方差AR/ARCH模型转换距离的非线性损伤识别方法。首先描述了AR/ARCH混合模型的基本组成原理,给出了模型建模的定阶和参数估计方法。然后描述了非线性损伤的时变刚度特性,给出了基于二阶方差指标的非线性损伤识别策略。在此基础上,分析了AR/ARCH模型残差和条件方差与非线性损伤的关联关系,并提出了一种基于AR/ARCH模型的转换距离指标。最后采用三层框架试验验证了指标的有效性,并对输电塔模型进行了损伤识别试验。试验和计算结果表明:基于AR/ARCH模型的转换距离指标明显优于传统的二阶方差指标,其具有更强的非线性损伤识别能力和可靠性。
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关键词:
- 输电塔 /
- 损伤识别 /
- 自回归/自回归条件异方差模型 /
- 非线性 /
- 二阶方差
Abstract: The safety of engineering steel structures such as transmission towers is often affected by cracks and other damages. Such damages often exhibit nonlinear characteristics of variable stiffness in structural vibration. In order to solve this kind of nonlinear damage detection problem, a nonlinear damage identification method based on AR/ARCH model conversion distance was presented. Firstly, the basic theory of AR/ARCH hybrid model was described, and the order determination and parameter estimation methods of modeling were given. Then, the time-varying stiffness characteristics of nonlinear damage were described, and the nonlinear damage identification strategy based on second-order variance index was given. On this basis, the relations between AR/ARCH model residual and condition variance and nonlinear damage was analyzed, and a conversion distance index based on AR/ARCH model was proposed. Finally, the related experimental research was carried out, and the three-layer frame experiment was used to verify the effectiveness of the index, and the damage identification experiment of the transmission tower model was also conducted. The experimental and calculation results showed that the conversion distance index based on AR/ARCH model was obviously superior to the traditional second-order variance index, and it had stronger nonlinear damage identification capability and reliability.-
Key words:
- transmission tower /
- damage identification /
- AR/ARCH model /
- nonlinearity /
- second-order variance
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[1] 钟岱辉,李荣帅,王文明. 输电塔线体系灾变机理研究综述[J]. 四川建筑科学研究, 2020, 46(3): 37-45. [2] 张卓群,李宏男,李士锋,等. 输电塔-线体系灾变分析与安全评估综述[J]. 土木工程学报, 2016, 49(2): 75-88. [3] 瞿伟廉, 秦文科. 输电塔法兰联结节点螺栓松动损伤诊断改进的模糊模式识别方法[J]. 地震工程与工程振动, 2006, 26(6):138-143. [4] 屈成忠, 连旭伟. 基于HHT的输电塔结构损伤识别研究[J]. 华东电力, 2010(11): 1750-1752. [5] 刘纲, 杨溥, 秦阳,等. 酒杯型输电塔损伤定位的识别方法[J]. 振动测试与诊断, 2012, 32(3): 471-476. [6] XU Y L, LIN J F, ZHAN S, et al. Multistage damage detection of a transmission tower: numerical investigation and experimental validation[J]. Structural Control and Health Monitoring, 2019, 26(8): 1-33. [7] LI Y C, JIANG R N, TAPIA J, et al. Structural damage identification based on short-time temporal coherence using free-vibration response signals[J]. Measurement, 2020, 151. DOI: 10.1016/j.measurement.2019.107209. [8] GUO H Y, ZHOU R, ZHANG F. Structural nonlinear damage detection using improved Dempster-Shafer theory and time domain model[J]. Journal of Vibroengineering, 2019, 21(6): 1679-1693. [9] REBILLAT M, HAJRYA R, MECHBAL N. Nonlinear structural damage detection based on cascade of Hammerstein models[J]. Mechanical Systems and Signal Processing, 2014, 48(1/2): 247-259. [10] YU L, ZHU J H. Nonlinear damage detection using higher statistical moments of structural responses[J]. Structural Engineering and Mechanics, 2015, 54(2): 221-237. [11] CHENG J J, GUO H Y, WANG Y S. Structural nonlinear damage detection method using AR/ARCH model[J]. International Journal of Structural Stability and Dynamics, 2017, 17(8). DOI: 10.1142/S0219455417500833. [12] GIACOMETTI R, BERTOCCHI M, RACHEV S T, et al. A comparison of the Lee-Carter model and AR-ARCH model for forecasting mortality rates[J]. Insurance: Mathematics and Economics, 2012, 50(1): 85-93. [13] CHEONG C W. Modeling and forecasting crude oil markets using ARCH-type models[J]. Energy Policy, 2009, 37(6): 2346-2355. [14] 耿海璇,张济民. 基于Yule-Walker AR方法的振动信号除噪研究[J]. 机电一体化, 2016, 22(1): 34-37.
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