考虑传感器故障与环境影响的结构损伤识别方法研究

项目名称： 考虑传感器故障与环境影响的结构损伤识别方法研究

项目编号： No.51278127

项目类型： 面上项目

立项/批准年度： 2013

项目学科： 建筑科学

项目作者： 姜绍飞

作者单位： 福州大学

项目金额： 80万元

中文摘要： 现行结构损伤检测方法在分析实测响应时，仅考虑环境、荷载对损伤的影响，而没有考虑传感器由于时间与环境的变化导致其性能退化乃至发生故障，这严重地影响了损伤诊断率也增加了检测的难度。本项目拟采用硬件冗余性的原理，结合概率统计与数据融合理论，首先研究传感器失效、环境、损伤引起的结构响应异常与区分技术研究，获得检测、分离故障传感器与损伤的技术；其次研究考虑传感器性能退化与实测环境干扰的海量数据处理技术；最后，运用群体智能优化技术，研究考虑环境干扰与传感器性能退化下不完备数据的结构损伤检测方法。通过研究，可部分解决传感器故障与损伤混淆、错误报警，和考虑环境影响及传感器性能退化/故障下不完备数据损伤检测方法等健康监测领域的技术瓶径,获得具有自主知识产权的核心技术,为大型结构健康监测系统真正发挥防灾减灾作用提供技术支持。

中文关键词： 传感器性能退化；结构损伤识别；改进多粒子群协同进化算法；数据重构；非线性结构

英文摘要： In present damage detection methods, only the effect of loading and environment on damage is considered for the measured responses. Due to the fact that the sensor is deteriorated and is even in fault with the variation of time and environment, this seriously influences the diagnosis ratio and increases the detection difficulty. On the basis of the principle of hardware redundancy, this project employs the probability and data fusion theory to investigate the following problems. Firstly, the techniques of response novelty and distinguishing them are studied for the responses caused by the environment, sensor fault and damage, and thus the detection and distinguishing methods between the sensor fault and damage are obtained. Secondly, the data processing technique is investigated for a large volume of measured data under the case of environmental effect and sensor deterioration. Finally, a damage detection method is developed by using the swarm intelligent optimization technique, which is applicable to the incomplete measured data under the environmental effect and sensor deterioration. Through this project, some technical bottleneck problems can be solved in the community of structural health monitoring, such as misclassifying the sensor fault and damage,the damage detection method for incomplete measured data u

英文关键词： Sensor degradation；structural damage identification；IMPSCO；data recovery；non-linear structure