王二旭, 刘怡萌, 刘朝, 解鑫, 刘璐. 基于储能弹簧压力信号的断路器故障诊断方法[J]. 河北电力技术, 2024, 43(4): 70-74.
引用本文: 王二旭, 刘怡萌, 刘朝, 解鑫, 刘璐. 基于储能弹簧压力信号的断路器故障诊断方法[J]. 河北电力技术, 2024, 43(4): 70-74.
WANG Erxu, LIU Yimeng, LIU Zhao, XIE Xin, LIU Lu. Fault Diagnosis Method for Circuit Breakers Based on Energy Storage Spring Pressure Signal[J]. HEBEI ELECTRIC POWER, 2024, 43(4): 70-74.
Citation: WANG Erxu, LIU Yimeng, LIU Zhao, XIE Xin, LIU Lu. Fault Diagnosis Method for Circuit Breakers Based on Energy Storage Spring Pressure Signal[J]. HEBEI ELECTRIC POWER, 2024, 43(4): 70-74.

基于储能弹簧压力信号的断路器故障诊断方法

Fault Diagnosis Method for Circuit Breakers Based on Energy Storage Spring Pressure Signal

  • 摘要: 为了准确评估储能弹簧状态保证断路器可靠动作,提出了一种基于储能弹簧压力信号的断路器故障诊断方法。首先设计了专用夹具对压力信号进行采集,并对受力过程进行了详细分析,然后提取压力冲量、峭度、有效值、波峰因子、裕度指标等作为特征参数,最后采用烟花算法(FWA)对支持向量机(SVM)核参数和惩罚因子进行优化,并将样本数据送入SVM进行断路器状态辨识。实验结果表明:采用压力信号进行故障诊断,准确率达到了96.6%。

     

    Abstract: In order to accurately evaluate the state of the energy storage spring and ensure the reliable operation of the circuit breaker,this article proposes a circuit breaker fault diagnosis method based on the energy storage spring pressure signal.Firstly,a dedicated fixture was designed to collect pressure signals,and a detailed analysis of the stress process was conducted.Then,the pressure impulse,kurtosis,effective value,peak factor,and margin index were extracted as feature parameters.Finally,the Fireworks Algorithm(FWA) was used to optimize the kernel parameters and penalty factors of the Support Vector Machine(SVM),and the sample data was fed into the SVM for state identification.The experimental results show that the accuracy of using pressure signals for fault diagnosis reached 96.6%,which has broad application value.

     

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