In order to improve the accuracy and efficiency of the fault detection method,the Canopy algorithm and the K-mean algorithm are integrated to improve the cluster-based local outlier factor algorithm and improve the fault detection algorithm of power equipment.The empirical analysis of the improved fault detection algorithm of power equipment shows that the operation time of the algorithm is 118.3 s and the fault detection accuracy is 0.91,which is better than other comparison algorithms.In conclusion,the improved fault detection algorithm of power equipment can improve the accuracy and calculation efficiency of fault detection,and can provide reference for the research and practice in the field of power equipment fault detection.
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