A Novel Approach to Detecting Machinery Insulation Defects with Electrical and Current Signature Analysis

In this paper we will discuss the use of electrical and current signature analysis on electric machinery for the detection of insulation defects. The project involved the practical study of electric machinery field testing and evaluation at repair facilities. In this paper we will identify the use of both electrical and current signature analysis devices and how insulation system direct and inferred defects are detected. The use of expert and machine learning/AI for this type of analysis will be distinguished. Direct insulation system defects include electrical insulation system breakdown and inferred defects which involves the identification of conditions that lead to breakdown. The study and results also include results from across-the-line clean, high harmonic, and inverter environments.