Tianyao Ji, Lin Yi, Wenhu Tang, 等. Multi-mapping fault diagnosis of high voltage circuit breaker based on mathematical morphology and wavelet entropy[J]. 中国电机工程学会电力与能源系统学报(英文), 2019,5(1):130-138.
Tianyao Ji, Lin Yi, Wenhu Tang, et al. Multi-mapping fault diagnosis of high voltage circuit breaker based on mathematical morphology and wavelet entropy[J]. CSEE Journal of Power and Energy Systems, 2019, 5(1): 130-138.
Tianyao Ji, Lin Yi, Wenhu Tang, 等. Multi-mapping fault diagnosis of high voltage circuit breaker based on mathematical morphology and wavelet entropy[J]. 中国电机工程学会电力与能源系统学报(英文), 2019,5(1):130-138. DOI: 10.17775/CSEEJPES.2017.01060.
Tianyao Ji, Lin Yi, Wenhu Tang, et al. Multi-mapping fault diagnosis of high voltage circuit breaker based on mathematical morphology and wavelet entropy[J]. CSEE Journal of Power and Energy Systems, 2019, 5(1): 130-138. DOI: 10.17775/CSEEJPES.2017.01060.
Multi-mapping fault diagnosis of high voltage circuit breaker based on mathematical morphology and wavelet entropy
Mechanical faults of high voltage circuit breakers (CBs) seriously affect the reliability of their operation
which may cause severe damage to power systems. In order to monitor operational conditions and detect mechanical faults of CBs
a multi-parameter monitoring system is designed and a fault diagnosis method based on multi-mapping is proposed. The paper focuses on the trip/close circuits
the spring-charging mechanism and the transmission mechanism
and obtains four current signals and a vibration signal that can reflect CB conditions. For the current signals
a morphological filter is used to remove noise and then characteristics of the waveforms' shape information are extracted. For vibration signals
the wavelet packet transform is used to decompose the signal into various frequency bands
and the sample entropy of the low frequency bands and the wavelet energy of the high frequency bands are calculated
respectively. Based on these feature parameters
a multi-mapping strategy is proposed for CB fault diagnosis. Laboratory experiments have been conducted to obtain on-site signals under various conditions
and experiment results have verified that monitoring the aforementioned signals and using the corresponding feature extraction and fault diagnosis methods
the mechanical faults of high voltage CBs can be effectively diagnosed.