Circuit Breaker Fault Detection Based on OOA-VMD-SVM

DOI: https://doi.org/10.62517/jes.202502110

Author(s)

Zhaohui Liu*

Affiliation(s)

Inner Mongolia Power (Group) Co., Ltd, Hohhot Power Supply Branch, Hohhot, Inner Mongolia, China *Corresponding Author.

Abstract

To extract the fault characteristic signal of circuit breaker, a fault detection method based on Osprey optimization algorithm (OOA) optimization variable modal decomposition (VMD) and support vector machine (SVM) parameters is proposed. First, use OOA to determine the parameters of VMD. Secondly, Utilize the OOA-VMD to decompose the circuit breaker signals, take the energy entropy as the fault analysis feature vector. The obtained components are used as the samples of SVM for fault analysis. Experiments show that OOA-VMD-SVM model can better extract the fault characteristics of each sample, and has good fault diagnosis effect. Compared with other models, this model has higher diagnostic accuracy and better generalization ability.

Keywords

Osprey Optimization Algorithm; Variational Modal Decomposition; Support Vector Machine; Circuit Breaker; Fault Detection

References

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