3 - Individual intelligent method-based fault diagnosis

Abstract

This chapter introduces the intelligent diagnosis methods based on individual intelligent techniques. The concept and advantages of intelligent diagnosis are first described, as well as the main steps commonly included in intelligent diagnosis. Second, three methods using artificial neural networks, which are able to learn and generalize nonlinear relationships between input data and output data, are presented for diagnosing the mechanical faults. Then, two diagnosis methods based on statistical learning theory are detailed and they can give better generalization abilities, especially for limited sample cases. Finally, two intelligent diagnosis methods are introduced based on the idea of deep learning, which uses advanced intelligent techniques for both feature extraction and fault classification. The effectiveness of each method is verified by various diagnosis cases, involving intelligent diagnosis of rub faults, bearing faults, and gear faults, and these methods can replace diagnosticians to efficiently process the massive collected signals and automatically diagnose the mechanical faults.