This review of the literature looks into the use of vibration and thermal signals for the diagnosis and detection of bearing problems in brushless DC (BLDC) motors. The study highlights the efficacy of current developments in diagnostic algorithms and signal processing approaches in detecting bearing irregularities. The comparative study of vibration and heat monitoring techniques is highlighted, along with a discussion of each method's benefits and drawbacks. The integration of various methods for improved fault detection accuracy is also examined in the paper. The results indicate that a hybrid strategy that combines temperature analysis and vibration provides a reliable way to identify BLDC motor problems early on, which could enhance maintenance plans and operational dependability.
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