基于联邦扩展卡尔曼滤波的结构损伤识别方法

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振动与冲击 ›› 2017, Vol. 36 ›› Issue (21) : 185-191.

论文

张纯，王路丹，宋固全，徐昌宏，廖群

作者信息 +

Structural Damage Identification Based On Federal Extended Kalman Filter

Zhang Chun, Wang Lu-dan, Song Gu-quan, Xu Chang-hong, Liao Qun

Author information +

文章历史 +

摘要

当结构损伤与传感器故障同时存在时，两者的相互影响会导致损伤识别结果的劣化；为此，提出了一种基于联邦扩展卡尔曼滤波的结构损伤识别算法。利用分散化滤波计算量小、滤波精度高的优点，联邦扩展卡尔曼滤波方法能根据正常的传感器信号准确识别结构的损伤位置与程度，具有良好的鲁棒性；同时利用联邦滤波容错性好的特点，能实现对故障信号的自动检测和剔除，并将剩余的正常子系统进行组合，以继续提供准确的损伤识别结果。梁式结构的数值算例及实验分析验证了本文算法的有效性及对故障传感器信号的检测隔离能力。

Abstract

The interaction of structure damages and sensor faults will deteriorate identified results evidently, so an identification algorithm of structure damages based on Federated Extended Kalman Filter method (FEKF) is proposed by using free vibration signals. The presented method can identify the location and extent of damages accurately, and shows good robustness when the sensors work normally. Combined with the residual chi-square test, FEKF also can eliminate the effects of fault sensors by automatic detection and removal of the fault sensor signal. Numerical simulation and experiments show that FEKF can ensure the accuracy and stability of the damage identification and detect fault signal effectively.

导出引用

张纯，王路丹，宋固全，徐昌宏，廖群. 基于联邦扩展卡尔曼滤波的结构损伤识别方法[J]. 振动与冲击, 2017, 36(21): 185-191

Zhang Chun, Wang Lu-dan, Song Gu-quan, Xu Chang-hong, Liao Qun. Structural Damage Identification Based On Federal Extended Kalman Filter[J]. Journal of Vibration and Shock, 2017, 36(21): 185-191

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