基于集员滤波器的故障诊断

Fault diagnosis based on the set membership filter

针对具有未知但有界故障的时变系统,提出一种集员滤波的故障诊断方法,保证系统的状态、故障信号的值100%包含在上下界内.假设过程噪声、测量噪声和故障信号的值有界,采用S-过程方法和线性矩阵不等式(LMI)方法设计集员滤波器,最后运用递归优化算法对集员滤波器进行优化.所提方法不仅可以对故障大小进行估计,还能够检测出故障信号类型.数值仿真证明了该方法的可行性和有效性.

A method of fault diagnosis with set membership filter sets is proposed for time - varying sys- tems with unknown but bounded faults, which guarantees all the values of state and fault signal between their low bounds and upper bounds in 100% confidence. Assuming the process noise, measurement noise and fault signal are unknown but bounded, then S -procedure and LMI methods are applied to de- sign the set -membership filter. Finally, a recursive algorithm is developed for computing the set membership filter. The method not only can estimate the size of the fault, but also can detect the type of fault signal. The simulation result shows that the method presented is available and effective.