A Comparative Study of Signal Processing Techniques for Monitoring and Diagnostics

Abstract

This paper presents a brief review of the signal processing techniques being used in industrial condition monitoring and diagnostics. Four main types of monitoring methods are discussed; Neural Networks, Wavelets, Time-Frequency methods, and Non-linear series. References to existing applications are also included throughout the paper. This aims to introduce the most common techniques which are being used today, namely the multilayer perceptron network, orthogonal and non-orthogonal wavelets, spectrogram, Wigner and Choi-Williams distributions, and Volterra series.