SF₆ High Voltage Breaker On-line Monitoring And Vibration Signal Analysis

Practice shows that development of CB (Circuit Breaker) condition monitoring system provides a powerful guarantee on security of power network operation, which is valuable for state detection of circuit breaker in reliable operation of high voltage CB and decreases the cost of human and material resources for planned overhaul. Due to the simplicity of system function and lack in effect state detection etc., an overall SF6 high voltage CB on-line monitoring system is developed by our team and Shanghai electric power corporation.According to the structure of SF6 CB and its operating characteristic, the installation of slip resistance type displacement sensor and piezoelectric acceleration sensor are designed for acquisition of mobile contact travel and vibration signal of CB respectively. The computation of average velocity of CB mobile contact is modified with the detailed operation parameter of CB. The effect of surrounding environment on SF6 moisture content is analyzed, which shows that the effect is not heavy as it was worried about with reference to the operation range of CB SF6 gas state parameters.With analyzing CB field vibration signal by WP (Wavelet Packet) band energy analysis method, the band sensitive to state change most is not regularly distributed on one band or several bands, thus the bands with relative high occurring probability can be chosen as the feature band. According to formula derivation of field data and test results of cited documents, it is proven that CB vibration signal can be considered as stationary stochastic process in normal operation condition or small changes of CB operation condition.It is testified that the method that combining WP band energy and AR model (Auto-Regressive model) PSD (Power Spectrum Density) is not fit for detecting the condition of CB vibration signal because the AR model PSD of the three vibration signals which mechanical work state change is very small is not similar. The effect of field noises is analyzed for the unfitness of the method mentioned above, which can be concluded that the effect of noises on PSD is not the main reason for the mthod unfitness. It is the true reason that the premise of Gaussian linear signal does not match the characteristic of CB vibration signal.The method that combining WP band energy method and bi-spectrum estimation is presented for the condition detection of CB vibration signal in this paper. Although the analysis of field case shows that indirect method used for bi-spectrum estimation on CB feature band signal has certain validity, the analysis result still can not satisfy the actual need. It is testified that either ARMA model (Auto-Regressive Moving Average model) method or AR model method is superior to indirect method. The AR model method which is good at processing the short length signal is more fit for the condition detection of CB vibration signal than ARMA model method, because the relative big estimation error in MA (Moving Average) part of ARMA model wakens the superiority in estimating short length signal.Based on the characteristic of PSD restraining white noise and bi-spectrum restraining Gaussian noise, the PSD method and bi-spectrum estimation is used to analyze the composition of field noise, which show that there is much of non-Gaussian noise in CB field signal and there is much of non-Gaussian white noise concentrated on CB feature band. The conclusion that the nonlinear characteristic exists in almost all the frequency band of CB vibration signal and most of the nonlinear characteristic is in the CB feature band, testifies that the CB feature band includes most of informations sensitive to CB mechanical state change and the extracted characteristic parameter can reflect the changes of CB mechanical state actually.