Litcius/Paper detail

A Smart Sensor-Based cEMD Technique for Rotor Bar Fault Detection in Induction Motors

Manzar Mahmud, Wilson Wang

2021IEEE Transactions on Instrumentation and Measurement26 citationsDOI

Abstract

Induction motors (IMs) are commonly used in industrial and domestic applications. Reliable IM fault detection can improve machinery production quality and operation safety and prevent unexpected failures. However, reliable motor fault diagnosis is still a challenging research and development task, especially in real machinery monitoring applications, due to the limitations in data acquisition (DAQ) systems and fault detection techniques. The first objective of this work is to develop a wireless smart sensor DAQ system for the current signal measurement. The second objective is to propose a new correlation empirical mode decomposition (cEMD) technique to detect broken rotor bar faults. The proposed cEMD technique can differentiate the line current and its sideband components from other frequencies and accentuate fault features over intrinsic mode function sidebands so as to improve fault detection accuracy. The effectiveness of the developed smart sensor DAQ system and the cEMD technique is verified experimentally under different motor conditions.

Topics & Concepts

Data acquisitionFault detection and isolationFault (geology)Rotor (electric)EngineeringHilbert–Huang transformInduction motorSidebandCondition monitoringElectronic engineeringComputer scienceControl engineeringElectrical engineeringActuatorVoltageRadio frequencyFilter (signal processing)GeologyOperating systemSeismologyMachine Fault Diagnosis TechniquesNon-Destructive Testing TechniquesGear and Bearing Dynamics Analysis