基于累积残差贡献率的传感器故障定位方法

为准确定位结构健康监测系统中的故障传感器，提出了基于累积残差贡献率的传感器故障定位方法。基于主元分析的基本原理，将车辆荷载和地脉动激励下传感器采集的数据分为主元空间和残差空间，采用SPE统计量对故障进行识别。在此基础上，通过对残差贡献值的推导，提出了累积残差贡献率指标，改进了现有的残差贡献图，提高了故障定位的准确率，并将单传感器故障定位拓展到两个故障传感器的同时定位。数值模拟结果表明：主元分析法能准确识别出预设的4类常见传感器故障，累积残差贡献率不但能更好地定位单传感器故障，两传感器同时发生故障时也能准确定位。

Sensor fault location method based on cumulative residual contribution rate

In order to accurately locate the fault sensor position in the structural health monitoring system, a sensor fault localization method based on the cumulative residual contribution rate is proposed. Based on the basic principle of principal component analysis, the data collected by the sensor under the vehicle load or the ground pulsation excitation are divided into the main element space and the residual space, and the fault is detected by SPE statistic. Furthermore, the residual contribution value is further deduced, and the cumulative residual contribution rate index is proposed. It improves residual contribution graph, also improves the accuracy of fault location. And sensor fault location is extended to simultaneously locate two fault sensors. The numerical simulation results show that the principal component analysis can accurately identify the four kinds of common sensor faults. The cumulative residual contribution rate not only better locates the single sensor fault, but also accurately locates the faulty position when the two sensors fail simultaneously.