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 using AVPCA improves fault detection and diagnosis performance by more than 20% in constant-speed cases and by 30% in variable-speed cases compared to classical PCA. The method is beneficial in terms of system cost and simplicity, relying only on rotor speed signals.
研究不足
The study is limited to bearing faults in rotating electrical machines under constant load conditions. The effectiveness of the proposed method under varying load conditions and different types of motors and bearings needs further investigation.
1：Experimental Design and Method Selection:
The study proposes a rotor speed-based BFD (RSB-BFD) method using absolute value-based principal component analysis (AVPCA) for fault detection and diagnosis.
2：Sample Selection and Data Sources:
Experimental setup with a 750-W brushless direct current (BLDC) motor and artificially damaged ball bearings (NSK 6204) to produce flaws on the outer race, inner race, or ball.
3：List of Experimental Equipment and Materials:
BLDC motor, TMC-7 BLDC motor driver, incremental encoder type E60H, NI cDAQ-9178 eight-slot USB chassis, NI9411 module, and MATLAB R2012a for data processing.
4：Experimental Procedures and Operational Workflow:
Rotor speed signals were measured under constant and variable speed conditions, sampled at
5：06 kHz, and processed using AVPCA for fault detection and diagnosis. Data Analysis Methods:
The proposed AVPCA method was used to analyze the rotor speed signals for fault detection and diagnosis, comparing its performance with classical PCA.
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