Automatic Condition Monitoring of Industrial Machines Using FSA-Based Hall-Effect Transducer

Abstract

A reliable and swift real-time condition monitoring for an industrial machine is a need of the hour when dealing with critical uncontrollable machine failures such as stator winding insulation failure, which is more prominent while working in robust conditions. Early detection of stator winding faults, especially turn-turn fault, occurred mainly as a short-circuit between the winding of the same phase due to the insulation failure, which can prevent fault propagation and protect winding from further insulation damages. This paper presents steady and transient state analysis of three-phase induction motor using fault signature analyzer based hall-effect transducer under various fault conditions. A numerical model with stator winding faults has been implemented, taking into account two major faults such as stator turn-turn (STTF) and stator phase-neutral fault (SPhN), using finite element method (FEM). FEM obtains the symmetrical current components of the motor under different fault conditions using finite element analysis (FEA). The machine torque has also been modeled and compared in a healthy and faulty condition. The numerical finite element method (FEM) model could identify a healthy and faulty induction machine with 95% accuracy using finite element analysis (FEA) and the same was validated using experimental setup results under the same operating conditions.