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Received:July 04, 2017 Revised:July 20, 2017
Received:July 04, 2017 Revised:July 20, 2017
中文摘要: 为了解决电力调度自动化系统中故障、安全监测不到位，尤其是缺少精确定位和关联分析等问题，利用改进的SOM神经网络提出了一种故障诊断模型.首先，在分析调度系统历史数据基础上，提取故障的特征向量，建立学习样本.接着通过算法训练输入和输出间的内在联系，供后续测试验证使用.最后，在已具备数据内在映射关系的网络中，测试待检测数据，验证其故障诊断的效果.最后的结果表明，此模型对不同类型故障识别和诊断能力较强，是一种行之有效的人工智能诊断方法.
Abstract:A fault diagnosis model is proposed by using improved SOM neural network for the purpose of improving fault and safety monitoring, especially when it lacks accurate positioning and correlation analysis in power dispatching automation system. Firstly, based on the analysis of the historical data of the dispatching system, the feature vector of the fault is extracted and the learning sample is established. And then the connection with input and output for the subsequent test is trained for verification through the algorithm. Finally, the experiment which tests the data and verifies the effectiveness of its fault diagnosis is in the network with the inherent mapping of the data. The final results show that this model is an effective artificial intelligence diagnosis method for different types of fault recognition and diagnosis.
keywords: SOM neural network LVQ neural network electric power dispatching automation fault diagnosis
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基金项目:国科控股企业技术创新引导基金（2015XS0356）
引用文本：
刘兆炜,王汉军,李丹,周心圆.改进SOM神经网络在电力调度故障诊断中的应用.计算机系统应用,2018,27(3):179-185
LIU Zhao-Wei,WANG Han-Jun,LI Dan,ZHOU Xin-Yuan.Application of Improved SOM Neural Network in Fault Diagnosis of Electric Power Dispatching.COMPUTER SYSTEMS APPLICATIONS,2018,27(3):179-185
刘兆炜,王汉军,李丹,周心圆.改进SOM神经网络在电力调度故障诊断中的应用.计算机系统应用,2018,27(3):179-185
LIU Zhao-Wei,WANG Han-Jun,LI Dan,ZHOU Xin-Yuan.Application of Improved SOM Neural Network in Fault Diagnosis of Electric Power Dispatching.COMPUTER SYSTEMS APPLICATIONS,2018,27(3):179-185
