Application of Improved Empirical Mode Decomposition and Analytic Energy Operator in Motor Bearing Fault Detection
Aimed at the shortage of motor bearing fault weak signal energy,it is easily overshadowed by noise interferences,mo-tor bearing fault characteristic extraction methods are carried out to be investigated.This paper proposes an improved empirical mode decomposition approach for diagnosing motor bearing faults,including the envelope spectrum kurtosis indicator and the improved em-pirical mode decomposition technique combined with a newly developed analytical energy operator.The background noise interference is removed from motor bearing fault signals through practical testing and application,thereby ensuring the successful extraction of weak fault features from the motor bearing.The proposed method has the effectiveness and superiority compared with conventional motor bearing fault diagnosis methods,which provides a new idea for motor bearing fault diagnosis.
motor bearingfault diagnosisimproved empirical mode decomposition methodenvelope spectrum kurtosisanalytic energy operator
NETL
NSTL
万方数据
