Healthiness Analysis and Remaining Useful Life Prediction for Slopes of Water Diversion Projects Based on Safety Monitoring

HUANG Ming; YU Weihai

doi:10.3724/j.gyjzG23033008

Volume 54 Issue 11

Nov. 2024

Turn off MathJax

Article Contents

Article Navigation > INDUSTRIAL CONSTRUCTION > 2024 > 54(11): 61-66

HUANG Ming, YU Weihai. Healthiness Analysis and Remaining Useful Life Prediction for Slopes of Water Diversion Projects Based on Safety Monitoring[J]. INDUSTRIAL CONSTRUCTION, 2024, 54(11): 61-66. doi: 10.3724/j.gyjzG23033008

Citation:

HUANG Ming, YU Weihai. Healthiness Analysis and Remaining Useful Life Prediction for Slopes of Water Diversion Projects Based on Safety Monitoring[J]. INDUSTRIAL CONSTRUCTION, 2024, 54(11): 61-66. doi: 10.3724/j.gyjzG23033008

Citation:

PDF( 2304 KB)

Healthiness Analysis and Remaining Useful Life Prediction for Slopes of Water Diversion Projects Based on Safety Monitoring

doi: 10.3724/j.gyjzG23033008

College of Civil Engineering, Hefei University of Technology, Hefei 230009, China

Received Date: 2023-03-30
Available Online: 2024-12-05

Abstract

Abstract

In order to effectively realize the assessment on healthy status of slopes and failure prediction of diversion projects, a fuzzy evaluation model was constructed to obtain the evaluation affiliation vector of slope status integrating multi-indicator monitored safety information, and then a healthy degree of slope status with higher recognition and more convenient application was proposed; and a prediction method for remaining useful life was established based on the nonlinear Wiener process taking healthy degrees as its performance degradation index; according to calculations of a slope in a water diversion project, the time-dependant healthy degree curve was obtained. The results showed that the method could not only evaluate the healthy status of slopes in diversion projects, but also predict the remaining life, and the prediction accuracy was ideal, which could provide a reliable monitoring method for operation status and preventive maintenance decision-making basis for slopes.
- slopes of water diversion projects,
- fuzzy comprehensive evaluation,
- healthiness,
- the nonlinear wiener process,
- remaining useful life prediction

FullText(HTML)

References(24)

References

[1]	张帅, 贺拿, 钟卫, 等. 基于综合监测的滑坡变形特征的分析[J]. 工业建筑, 2022, 52(2): 90-95.
[2]	邓钟敏, 徐世光, 郭婷婷.边坡稳定性分析评价方法综述[J].矿业工程, 2010, 8(1):14-16.
[3]	DABOUS A S, ZEIADA W, AL-RUZOUQ R, et al. Distress-based evidential reasoning method for pavement infrastructure condition assessment and rating[J]. International Journal of Pavement Engineering, 2021, 22(4): 455-466.
[4]	王新民, 康虔, 秦健春, 等. 层次分析法-可拓学模型在岩质边坡稳定性安全评价中的应用[J]. 中南大学学报(自然科学版), 2013, 44(6):2455-2462.
[5]	蓝燕金, 简文彬, 罗金妹, 等.基于灰色定权聚类模型的公路边坡水毁风险等级评价[J].福州大学学报(自然科学版), 2021, 49(1):101-107.
[6]	黄建文, 李建林, 周宜红.基于AHP的模糊评判法在边坡稳定性评价中的应用[J].岩石力学与工程学报, 2007(增刊1):2627-2632.
[7]	黄有堂.基于模糊综合评价法的高陡边坡稳定性研究[D].大连:大连理工大学, 2014.
[8]	彭宇, 刘大同, 彭喜元.故障预测与健康管理技术综述[J].电子测量与仪器学报, 2010, 24(1):1-9.
[9]	黄铭, 刘俊. 基于故障预测与健康管理的边坡安全监测预警体系[J]. 工业建筑, 2020, 50(5): 66-70 , 43.
[10]	YIN S, OLYANSKIY Y, UYSAL-BIYIKOGLU E. Remote estimation of a Wiener process over a channel with random delay[C/OL]//Proceedings of 2017 IEEE International Symposium on Information Theory.2017[2023-03-30]. https://ieeexplore.ieee.org/document/8006542.
[11]	李明, 黄铭.基于安全监测的水库岸坡PHM系统框架及故障预测技术研究[J].水利科技与经济, 2018, 24(6):84-89.
[12]	冯晓雷, 黄铭.基于损伤力学的维纳过程引水工程边坡剩余寿命预测[J].工程与建设, 2020, 34(5):923-926.
[13]	叶虹娣. 基于多元维纳过程的引水渠道边坡剩余寿命智能预测研究[D]. 合肥:合肥工业大学, 2022.
[14]	何玉凤. 雅西高速瓦厂坪边坡稳定性的监测分析与安全预警研究[D].成都:成都理工大学, 2020.
[15]	舒星, 黄铭, 刘超.基于监测资料的临江岸坡安全性模糊综合评判[J].路基工程, 2017(4):11-15.
[16]	黄明扬. 既有建筑基坑边坡健康评估及工程应用研究[D]. 重庆:重庆大学, 2019.
[17]	吴德娟, 黄铭.海塘渗压安全状态的模糊综合评判[J].人民长江, 2007, 384(11):148-150.
[18]	张卫, 叶青.基于层次分析法的长沙工业遗产评价体系研究[J].工业建筑, 2015, 45(5):30-33.
[19]	朱晓栋, 陈则王.基于维纳过程的电池剩余使用寿命预测[J].机械制造与自动化, 2018, 47(4):197-200.
[20]	南西康, 高文科, 陈旭峰, 等.基于非线性Wiener过程的柱塞泵剩余使用寿命分析[J].液压与气动, 2020(11):45-52.
[21]	张强, 张佳瑶, 吕馥言.基于维纳过程截齿磨损退化预测研究[J].振动与冲击, 2023, 42(1):207-214.
[22]	戴洪德, 李娟, 景博, 等.基于HP滤波与非线性维纳过程的退化建模与失效分布研究[J].仪器仪表学报, 2018, 39(8):63-71.
[23]	BASU A P. The inverse Gaussian distribution[M]. New York:Springer, 1999.
[24]	SUN L, ZHAO F C, BALAKRISHNAN N, et al. A nonlinear Wiener degradation model integrating degradation data under accelerated stresses and real operating environment[J/OL]. Journal of Risk and Reliability, 2021, 235(3)[2023-03-30]. https://doi.org/10.1177/1748006X20978099.