摘要
为定量识别边坡的运行状态、预测其失稳风险,基于故障预测与健康管理(PHM)方法,构建边坡安全监测PHM系统框架;以位移为代表,采用基于性能退化的故障预测思想,定义基于边坡实际位移量的故障率和安全储备度;根据边坡滑动失稳特征,结合斋藤迪孝法及神经网络,建立故障率及安全储备度算式,得到性能退化时间曲线,实现边坡位移故障与安全储备的动态识别及预测,为采取相应治理、防范措施提供直接依据。结合某边坡监测信息,阐述边坡PHM系统位移故障预测的实现过程,建立的分析模型及预测结果与实际情况相符。
In order to quantitatively recognize the operation state of a slope and predict its risk of instability,based on the theory of Prognostic and Health Management(PHM),the framework of slope PHM system was studied considering the monitoring situation.Based on the performance degradation fault forecast method,the Failure Rate(FR)and Residual Safety Degree(RSD)were defined based on the actual displacement of slope.According to the characteristics of slope sliding,combining Saito Michitakanori method and neural networks,the slope slip time and the critical displacement were predicted from the monitoring displacements.The FR and RSD formulas were established,and the performance degradation time curve was drawn to realize the quantitative identification and forecast FR and RSD.They could be used to provide direct guidance for appropriate governance and maintenance.According to the monitoring information of a slope,the FR forecast process of displacement for slope PHM system was explained in detail.Its analytical model and forecasted results were in good agreement with the slope actual situation.
作者
黄铭
刘俊
HUANG Ming;LIU Jun(School of Civil Engineering,Hefei University of Technology,Hefei 230009,China;Key Laboratory of Geological Hazards on Three Gorges Reservoir Area(China Three Gorges University),Ministry of Education,Yichang 443000,China;School of Naval Architecture,Ocean and Civil Engineering,Shanghai Jiaotong University,Shanghai 200240,China)
出处
《工业建筑》
CSCD
北大核心
2020年第5期66-70,43,共6页
Industrial Construction
基金
水利部公益性行业专项(201401063-02)
安徽省科技攻关计划项目(1604a0802106)
三峡库区地质灾害教育部重点实验室开放研究基金资助项目(2015KDZ03)。
