Support Vector Machines and Wavelet Packet Analysis for Fault Detection and Identification

This paper presents a data driven fault detection and identification (FDI) method using Support Vector Machines (SVM) and the Wavelet Packet Transform (WPT). The primary focus of this paper is to present a robust data driven fault diagnosis scheme. The investigated scheme has the capability to detect and identify faulty components of a given system through examination of its output due to a specified input. The use of the wavelet packet transformation serves to draw out those features of the output response which best characterize each of the fault classes for the various components. Support vector machines are used as the diagnosis phase to detect and isolate faults of a given system.