基于集隶属椭球和移动窗口的在线主动故障检测

Junde Wang, Jing Wang, Jinglin Zhou
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引用次数: 3

摘要

为了解决在线故障检测问题,提出了基于集隶属度椭球技术的在线主动故障检测方法及其优化问题。辅助输入信号的设计应满足两个条件:信号幅度足够小,对系统无明显影响,并能在正常和故障运行时同时分离系统输出。在集合隶属度的框架下,我们将输出集描述为一个椭球。基于奇偶空间建立了移动窗口的系统模型,并在此基础上求解辅助输入信号的等效优化设计。该方法大大降低了优化计算的复杂度,方便了辅助输入信号的在线获取。通过比较实际系统的输出椭球与识别正常(或故障)模型的输出椭球的分离程度,可以更直观地检测系统故障。一般算例的仿真结果验证了所提方法的有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
On-line Active Fault Detection Based on Set-membership Ellipsoid and Moving Window
On-line active fault detection (AFD) and its optimization problems are proposed based on the set-membership ellipsoid technique in order to solve the problem of on-line fault detection. The design of auxiliary input signal should satisfy two conditions: the signal amplitude is small enough without obvious impact on the system, and it simultaneously separates the system output in the normal and fault operation. Here we describe the output set as an ellipsoid under the framework of set-membership. The system model of moving window is established based on the parity space, and the equivalent optimization design of auxiliary input signal is solved based on this model. The proposed method can significantly reduce the complexity of the optimization calculation and conveniently obtain the auxiliary input signal on-line. The system fault is detected more intuitively by comparing the degree of separation between the output ellipsoid of the actual system and that of the identification normal (or fault) model. The simulation results on a general example verify the effectiveness of the proposed method.
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