Fault Diagnosis and Detection in Industrial Motor Network Environment Using Knowledge-Level Modelling Technique

Table 4

Description of the implemented ANN.

Tasks	Configuration of the implemented ANN
Network type	Feed Forward Neural Network
Learning method	Back propagation
Training goal	0.01
Input data of each motor for each experiment	The input is the one-dimensional matrix for the ANN of 4 inputs where all data in each sensing point near motor are in a fault index
Number of hidden layer neurons	Different architectures are applied with different neurons. For example, [4 × 3 × 4], [4 × 10 × 4], and [4 × 15 × 4] (see Figure 9)
Vector of classes for the target outputs	Numerical matrices refer to the fault with value 1 or 0