Fault Diagnosis Method for Mining Explosion-proof Motor Bearings Based on Improved SVM
WANG Yiqing
Abstract：A fault diagnosis method for mining explosion-proof motor bearings based on improved SVM was proposed and designed to address the problem of poor conventional fault diagnosis results caused by interference from factors such as temperature,humidity,dust,and vibration during signal acquisition of explosion-proof motor bearings.Firstly,the fault characteristics of the explosion-proof motor bearings used in mining were extracted,the motor operation data were analyzed and processed,and characteristic parameters were obtained,such as bearing vibration,sound,temperature,etc.SVM theory was introduced and its SVM kernel function was improved to construct a fault diagnosis model for explosion-proof motor bearings.Particle swarm optimization algorithm was used to solve the model and achieve fault diagnosis of mining explosion-proof motor bearings.The comparative experimental results showed that the diagnostic accuracy of this method was higher,and preliminary experimental analysis showed that it had certain feasibility.
Keywords：improved SVMexplosion-proof electric motorbearing faultdiagnostic method
Publication Date：2025-02-28
Online Publishing Date：2025-08-15(First online date of this platform, not the publication date of the document)
Pages：5( 78-82 )