Fault Diagnosis of Induction Motor Based on Multi-Sensor Data Fusion

Abstract:

For the conclusions of single parameter fault feature diagnosis has some uncertainty, in induction motor early fault, we proposed the use of multi-sensor data fusion technology, acted signal processing to the collected current, vibration and temperature, extracted feature information failure, fused the evidence independent with each other using D-S evidence fusion rules. According to the final combination results of all the evidence, combined with intermediate results of the evidence combination, we achieved the accurate identification of induction motor rotor early failures and composite fault. The diagnosis examples show that the use of multi-sensor data fusion technology can significantly improve the accuracy and reliability of early fault diagnosis.

• Periodical: Applied Mechanics and Materials (Volumes 651-653)
• Pages: 729-732
• DOI: https://doi.org/10.4028/www.scientific.net/AMM.651-653.729
• Online since: September 2014
• Authors: Shu Ying Li*, Mu Qin Tian, Lei Xue
• Keywords: D-S Evidential Theory, Fault Diagnosis, Multi-Sensor Data Fusion

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