Deep Learning based Fault Diagnosis in Electrical Machinery in Industrial Sector based on Data Mining Techniques

The rise in the industrialization and digitalization has introduced numerous equipment. However, the equipment must be properly monitored and maintained. Any deviation leads to the occurrence of fault. Fault detection at initial conditions are highly important to maintain the stability and performance efficiency of the system. To overcome the drawbacks of the conventional systems, the proposed fault diagnosis system is implemented. This is done by incorporating artificial intelligence techniques. Here, the deep learning techniques are used for the detection of fault in the rotating machinery. The faults must be predicted earlier to avoid the overall damage in the system by protecting them from both soft and hard faults. Thus, the initial prediction of fault helps to maintain the reliability and stability of the system. In general, the faults are identified through data mining techniques proceeded with feature extraction and image processing techniques. This includes the early prediction by providing the accurate causes for the occurrence of fault in the system.