Motor Fault Detection by Displacement Detection and LSSVM

Journal Title: 河南科技大学学报(自然科学版) - Year 2018, Vol 39, Issue 2

Abstract

Displacements between stators and rotors were the main reasons for induction motor faults.8 detection coils were pre-placed into the notch grooves of stator core tooth for displacement detection, and they were configured into 6 groups.The differential output of each group was sensitive to the displacements between stator and rotor.The least squares support vector machine ( LSSVM) was combined with the detection coils for online fault detection of motors. A transformer pump motor was used for field test. The test results show that the combimation of displacement detection and LSSVM can detect the pump motor faults precisely. The proposed sparseness approach for LSSVM has the ability to keep a high fault detection rate and generalization performance while reducing the number of the support vectors and the online computation requirement. The sparse LSSVM models is suitable for online detection of motor fault.

Authors and Affiliations

Fangfang ZHANG, Shirong ZHANG, Qin CHENG

Keywords

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  • EP ID EP464871
  • DOI -
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How To Cite

Fangfang ZHANG, Shirong ZHANG, Qin CHENG (2018). Motor Fault Detection by Displacement Detection and LSSVM. 河南科技大学学报(自然科学版), 39(2), -. https://europub.co.uk/articles/-A-464871