Artificial Neural Networks (ANNs)

Artificial neural network (ANN) often consists of a series of algorithms that work together to recognise underlying relationships in a set of data. This chapter introduces some widely used ANN algorithms that have been used for machine fault diagnosis using vibration signals. It presents essential concepts of ANNs; then describes three different types of ANN (i.e. multilayer perceptron, radial basis function network, and Kohonen network) that can be used for fault classification. In addition, the chapter describes the applications of these methods and several other types of ANN-based methods in machine fault diagnosis. A considerable amount of literature has been published on the application of ANNs and variants in machine fault diagnosis. Most of these studies introduced many preprocessing techniques that include normalisation, feature selection, transformation, and feature extraction. The produced data of the preprocessing step represent the final training set that is used as input to ANNs.