Abstract
The development of power grid system not only increases voltage and capacity, but also increases power risk. This paper briefly introduces the feature extraction method of the vibration signal of high voltage circuit breaker and support vector machine (SVM) algorithm and then analyzed the high voltage circuit breaker in three states: normal operation, fixed screw loosening and falling of opening spring, using the SVM based on the above feature extraction method. The results showed that the accuracy and precision rates of fault identification of circuit breaker were the highest by using the wavelet packet energy entropy extraction features, the false alarm rate was the lowest, and the detection time was the shortest.
Highlights
With the rapid development of economic construction, the national demand for electricity is increasing, and the voltage and capacitance of power plants are increasing rapidly [1]
This paper briefly introduced the feature extraction method of the vibration signal of high voltage circuit breaker and support vector machine (SVM) algorithm and analyzed the high voltage circuit breaker in states of normal operation, fixed screw loosening and falling of opening spring using the SVM algorithm based on the above feature extraction method
Where ACC, FAR, DR stand for the accuracy rate, false alarm rate and precision rate, TP stands for the number of faults which are classified as A and belong to A, TN stands for the number of faults which are classified as B and belong to B, FP stands for the number of faults which are classified as B and belong to A, and FN stands for the number of faults which are classified as A and belong to B
Summary
With the rapid development of economic construction, the national demand for electricity is increasing, and the voltage and capacitance of power plants are increasing rapidly [1]. When the high-voltage transmission line fails, the fault area is quickly isolated from and the normal area to ensure the overall safety of the power grid. Its working principle of realizing the isolation of fault and nonfault lines in power grid is that the energy provided by the operating mechanism is transferred to the interrupting element by driving rod when the probe sensing system fails, and the interrupting element realizes the opening and closing of the circuit by the transferred energy. Once the high voltage circuit breaker breaks down in the power operation, the loss will be enormous [2]. Huang et al [3] proposed a mechanical fault diagnosis method for high voltage circuit breaker based on wavelet time-frequency entropy and one-class support vector machine (SVM), optimized the parameters using particle swarm algorithm, and verified the accuracy of the method through experiments. Bing et al [5] removed noise from circuit breaker vibration signal using soft
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