研究目的
Investigating the efficiency of rotor speed monitoring for bearing fault diagnosis (BFD) under variable speed and constant load conditions.
研究成果
The proposed RSB-BFD method, utilizing rotor speed signals and AVPCA, offers a cost-effective and simple solution for bearing fault diagnosis under variable speed conditions. Experimental results demonstrate its effectiveness in detecting and diagnosing bearing faults with improved performance over classical PCA and vibration-based methods.
研究不足
The study is limited to bearing faults in rotating electrical machines under constant load conditions. The effectiveness of the method under varying load conditions and different types of motors and bearings needs further investigation.
1：Experimental Design and Method Selection:
The study involves the development of a novel BFD technique, the rotor speed-based BFD (RSB-BFD) method, which uses rotor speed signals for fault detection and diagnosis. The method employs absolute value-based principal component analysis (AVPCA) to improve the performance of classical PCA.
2：Sample Selection and Data Sources:
The experimental setup includes a 750-W brushless direct current (BLDC) motor with artificially damaged ball bearings (NSK 6204) to simulate faults in the outer race, inner race, and ball.
3：List of Experimental Equipment and Materials:
Equipment includes a BLDC motor, TMC-7 BLDC motor driver, incremental encoder type E60H, NI cDAQ-9178 eight-slot USB chassis, and NI9411 module for rotor speed signal measurement.
4：Experimental Procedures and Operational Workflow:
The rotor speed signal was measured under both constant and variable speed conditions. The AVPCA algorithm was applied to the speed signal data for fault detection and diagnosis.
5：Data Analysis Methods:
The performance of the RSB-BFD method was evaluated using the sum square error (SSE) distance between training and test data vectors.
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