To detect and estimate the faults of discrete linear time-varying uncertain systems, a discrete learning strategy is applied to fault diagnosis, and a new fault-detection and estimation algorithm is proposed. The algorithm adopts the threshold-limit technology. In the selected optimal time domain, a residual signal is used to perform iterative learning correction for the introduced virtual faults so that the virtual faults in an actual system approach the actual faults. The same method is repeated in the remaining optimal time domain to achieve the objective of fault diagnosis. The algorithm not only completes the fault detection and estimation of a discrete linear time-varying uncertain system but also improves the reliability of fault detection and reduces the false alarm rate. Finally, the simulation results verify the effectiveness of the proposed algorithm.

为了检测和估计离散线性时变不确定系统的故障，将离散学习策略应用于故障诊断，提出了一种新的故障检测与估计算法。该算法采用阈值限制技术。在所选择的最佳时域中，使用残差信号对引入的虚拟故障执行迭代学习校正，以使实际系统中的虚拟故障逼近实际故障。在剩余的最佳时域中重复相同的方法以实现故障诊断的目的。该算法不仅完成了离散线性时变不确定系统的故障检测和估计，而且提高了故障检测的可靠性，降低了误报率。最后，