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作 者:李刚毅 LI Gangyi(Guangxi Branch,China Aluminum Co.,Ltd.,Baise 531400,China)
机构地区:[1]中国铝业股份有限公司广西分公司,广西百色531400
出 处:《电器与能效管理技术》2025年第1期23-27,共5页Electrical & Energy Management Technology
摘 要:在开关柜运行过程中,绝缘缺陷可能导致局部放电现象的发生,如果不能及时发现并采取处理措施,就会进一步造成绝缘击穿故障。为了有效诊断局部放电类型,提出一种基于D-S证据理论的多传感信息融合技术,结合反向传播(BP)神经网络进行局部放电类型识别的方案。实验表明,经过多传感信息融合后放电类型识别准确率较单传感器模式平均提高约13%,整体识别准确率达到96.08%,验证所提算法的有效性及合理性。During the operation of the switchgear,the insulation defects may lead to the occurrence of partial discharge.If it can not be found and dealt with measures in time,it will further cause the insulation breakdown failure.In order to effectively diagnose the type of partial discharge,based on the multi-sensor information fusion technology of D-S evidence theory,a scheme combined with BP neural network for the partial discharge pattern recognition is proposed.Experiments show that the accuracy of discharge type recognition with the multi-sensor information fusion is about 13 percentage higher than that of single sensor mode.The overall recognition accuracy is better than 96.08%,which verifies the effectiveness and rationality of the algorithm.
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