Artificial Intelligence for Fault Diagnosis of Induction Motors in Manufacturing (Monitoring 4.0)

In many industrial sectors, the proper functioning of the production chain is a major issue to ensure better competitiveness in the market, so productivity gains are a major concern for companies. For this, a set of industrial performance indicators allow an optimization of the systems, namely: reliability, maintainability, safety and risk control. Nowadays, system diagnostics, which has been strongly developed in the industrial world, represents one of the most important tools to obtain a better productivity gain and to avoid unavoidable material and/or physical damages. And in this context and for several decades, scientific research and technologies have been launched worldwide to develop and improve diagnostic methods. A number of innovative companies have started to implement IoT by exploiting smart connected devices in their factories (this is called smart factories or Industry 4.0). Therefore, this research project will introduce an intelligent system into an Industry 4.0 production environment. The proposed work is based on artificial intelligence applied to the diagnostic methods of three-phase Induction machines for the early detection of defects that may appear in these machines. The use of this type of electrical machine, mainly due to their simplicity of construction, their low cost of purchase and manufacture, their robustness, we find them in all industrial areas.