Abstract
The health of high voltage circuit breaker seriously affects the safe and stable operation of power grid. In this paper, a neural network ensemble model based on time-frequency characteristics of vibration information of high-voltage circuit breaker is proposed in view of the requirement of high-precision circuit breaker fault diagnosis. Firstly, the characteristics of the vibration signal of the high-voltage circuit breaker under the multi-measurement position are analyzed. The generalized energy of the vibration signal and the wavelet energy ratio are described in the feature space. Then, neural network ensemble model is used to divide the feature space, and the fault category is diagnosed. Finally, by comparing the experimental data with various diagnostic methods, it is verified that the diagnosis process described in this article is reasonable and the diagnosis result is accurate, and it is beneficial to the troubleshooting of high voltage circuit breakers.
| Translated title of the contribution | Application of Neural Network Ensemble Model in Mechanical Fault Identification of High Voltage Circuit Breaker |
|---|---|
| Original language | Chinese (Traditional) |
| Pages (from-to) | 217-223 |
| Number of pages | 7 |
| Journal | Gaoya Dianqi/High Voltage Apparatus |
| Volume | 54 |
| Issue number | 7 |
| DOIs | |
| State | Published - 16 Jul 2018 |
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