| 引用本文: | 黄新波,胡潇文,朱永灿,魏雪倩,周岩,高华.基于卷积神经网络算法的高压断路器故障诊断[J].电力自动化设备,2018,(5): |
| HUANG Xinbo,HU Xiaowen,ZHU Yongcan,WEI Xueqian,ZHOU Yan,GAO Hua.Fault diagnosis of high-voltage circuit breaker based on convolution neural network[J].Electric Power Automation Equipment,2018,(5): |
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| 摘要: |
| 传统的高压断路器故障诊断方法太过于依赖经验，不能准确地反映特征量和故障模式之间的关系，诊断准确度不高。针对这个问题，采用卷积神经网络算法进行高压断路器故障诊断，结合高压断路器分合闸线圈电流特点建立诊断模型，通过输入零点故障特征参数进行学习训练，得到相应故障类型输出。仿真结果表明，所提算法的整体准确率高达93.68%，与其他基于神经网络的算法相比具有很大的优势。 |
| 关键词: 断路器 高压断路器 卷积神经网络 分/合闸线圈电流 故障诊断 |
| DOI：10.16081/j.issn.1006-6047.2018.05.020 |
| 分类号:TM56 |
| 基金项目:国家自然科学基金资助项目(51177115)；陕西省重点科技创新团队计划资助项目(2014KCT-16)；西安工程大学控制科学与工程重点学科建设经费资助项目(107090811) |
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| Fault diagnosis of high-voltage circuit breaker based on convolution neural network |
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HUANG Xinbo, HU Xiaowen, ZHU Yongcan, WEI Xueqian, ZHOU Yan, GAO Hua
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College of Electronics and Information, Xi'an Polytechnic University, Xi'an 710048, China
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| Abstract: |
| The traditional fault diagnosis methods of high-voltage circuit breaker rely too heavily on artificial expe-rience and cannot precisely reflect the relationship between the characteristic parameters and fault types, so their accuracies are low. In order to solve this issue, it is proposed to diagnose the high-voltage circuit breaker fault by CNN(Convolution Neural Network). Combined with the characteristics of breaking coil and closing coil currents in high-voltage circuit breaker, the fault diagnosis model is built and then trained by the null point fault characteristic para-meters to obtain the corresponding fault types. The simulative results show that with the overall accuracy of 93.68%,the proposed algorithm has a great advantage comparing with other algorithms based on the neural network. |
| Key words: electric circuit breakers high-voltage circuit breakers convolution neural network breaking coil and closing coil currents fault diagnosis |
