Incipient fault detection in nonlinear non-Gaussian noisy environment

Incipient fault detection in real-time nonlinear closed-loop systems in the presence of unwanted stochastic terms remains a challenging issue, especially in mixed Gaussian and non-Gaussian environments. This paper is concerned with incipient-fault detection in such systems. To this goal, based on the autocorrelation of the windowed residual signal and the reasonable assumptions in the nonlinear system, an online incipient fault detection with acceptable computational efforts and an adaptive-robust residual scheme is provided. Also, a closed-loop form of the three-tank system (DTS200) has been devised and simulated to demonstrate the effectiveness of the proposed solution.

Automated summary

This paper addresses the challenging issue of incipient fault detection in real-time nonlinear closed-loop systems in mixed Gaussian and non-Gaussian environments. An online incipient fault detection method with acceptable computational efforts and an adaptive-robust residual scheme is proposed, based on the autocorrelation of the windowed residual signal and reasonable assumptions in nonlinear systems. The effectiveness of the proposed solution is demonstrated through the design and simulation of a closed-loop form of the three-tank system (DTS200).