SVM-based fault detection for double layered tank system by considering ChangeFinder's characteristics. (25th May 2022)

• Record Type: Journal Article
• Authors: Furukawa, Yosuke; Deng, Mingcong
• Is Part Of: International journal of advanced mechatronic systems. Volume 9:Number 4(2022)
• Page Start: 185
• Page End: 192
• Publication Date: 2022-05-25
• Subjects: nonlinear control -- fault detection -- fault tolerance -- ChangeFinder -- support vector machine -- SVM; Mechatronics -- Periodicals; 629.89
• Languages: English
• ISSNs: 1756-8412

Abstract

In this paper, a fault detection scheme for a tank system using support vector machine (SVM) combined with ChangeFinder, which are both machine learning methods, is studied. SVM can detect faults on a nonlinear system, but it can be late because SVM cannot recognise the nature of the time series. Combination with ChangeFinder enables SVM to recognise the nature of time series, and early detection using SVM becomes possible. Simulations and experiments assuming the temperature sensor fault case for the temperature control system of the tank system have been done and 5 s reduction of detection time was confirmed. In addition to the situation of the tank system, the sine wave input showed the effectiveness of the proposed method for general input. In addition, the superiority of the proposed method over ChangeFinder in an experimental environment was confirmed.