An Intelligent and Robust Fault Diagnostics for an Electromechanical System Using Vibration and Current Signals

Abstract

The paper presents the development of an intelligent and robust fault diagnostics for an electromechanical system. The electromechanical system comprised of a three-phase induction motor (IM) with an external rotor–bearing system. The main contribution of this work is to investigate the combined or multiple faults for different machine components of an electromechanical system which is lacking in the literature. In this work, in total ten different combined fault situations are considered, for example, healthy motor with healthy external rotor (HM-HR), healthy motor with external bearing faults (HM-BF), healthy motor with external unbalanced rotor (HM-UR), bearing fault in motor with healthy external rotor (MBF-HR), bearing fault in motor with external bearing fault (MBF-BF), bearing fault in motor with external unbalanced rotor (MBF-UR), stator winding fault with healthy external rotor (SWF-HR), stator winding fault with external unbalanced rotor (SWF-UR), stator winding fault with external bearing fault (SWF-BF) and bearing fault in motor with external bearing fault and unbalanced rotor (MBF-BF-UR). In order to investigate faults in a combined motor–rotor–bearing system, vibration as well a current signals are used here. The critical features obtained from time domain vibration and current signals are utilized to build an intelligent and robust fault diagnosis system based on multiclass support vector machine (MSVM). The results from the present investigations are discussed in result and discussion sections. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.