Sparse stacked autoencoder network for complex system monitoring with industrial applications

•A fault classification and isolation method based on SAE is proposed for complex system.•Deep learning model formed by AE with sparse and regular constraints can well extract features.•The fault isolation is conducted by calculating the contribution rate of each variable and choosing the largest one.•High fault classification and isolation accuracy of the proposed method is validated by some typical processes.