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Intelligent Fault Diagnosis of HVCB with Feature Space Optimization-Based Random Forest
2018
Sensors
Mechanical faults of high-voltage circuit breakers (HVCBs) always happen over long-term operation, so extracting the fault features and identifying the fault type have become a key issue for ensuring the security and reliability of power supply. Based on wavelet packet decomposition technology and random forest algorithm, an effective identification system was developed in this paper. First, compared with the incomplete description of Shannon entropy, the wavelet packet time-frequency energy
doi:10.3390/s18041221
pmid:29659548
pmcid:PMC5948935
fatcat:lx3bjv27krbojde42u4wkklq6e