东北大学学报:自然科学版 ›› 2016, Vol. 37 ›› Issue (4): 472-477.DOI: 10.12068/j.issn.1005-3026.2016.04.004

• 信息与控制 • 上一篇    下一篇

基于模型预测和溯因推理网络的电网故障诊断方法

刘晓琴, 王大志, 张翠玲, 宁一   

  1. (东北大学 信息科学与工程学院, 辽宁 沈阳110819)
  • 收稿日期:2015-03-08 修回日期:2015-03-08 出版日期:2016-04-15 发布日期:2016-04-05
  • 通讯作者: 刘晓琴
  • 作者简介:刘晓琴(1975-),女,辽宁辽阳人,东北大学博士研究生; 王大志(1963-),男,辽宁锦州人,东北大学教授,博士生导师.
  • 基金资助:
    国家自然科学基金青年基金资助项目(51207069); 辽宁省科技创新重大专项(201309001).

Method of Power Grid Fault Diagnosis Based on Model Prediction and Abductive Reasoning Network

LIU Xiao-qin, WANG Da-zhi, ZHANG Cui-ling, NING Yi   

  1. School of Information Science & Engineering, Northeastern University, Shenyang 110819, China.
  • Received:2015-03-08 Revised:2015-03-08 Online:2016-04-15 Published:2016-04-05
  • Contact: LIU Xiao-qin
  • About author:-
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摘要: 考虑电网出现故障时,仅依靠开关量状态信息进行诊断,诊断信息冗余度低,复杂故障情况下会影响诊断结果的准确性.引入电气量信息,提出了模型预测和数据清洗方法,建立电网故障诊断系统.利用模型预测得到准确的电气量信息,建立清洗规则和逻辑推理规则,分别对开关量进行数据清洗和验证故障信息.在此基础上,利用溯因推理网络(abductive reasoning network,ARN)对故障信息进行诊断,得出候选故障.仿真结果验证了该方法的有效性和准确性.

关键词: 故障, 诊断, 数据清洗, 模型预测, 溯因推理网络

Abstract: Considering the power grid fault, the diagnostic information redundancy is low based only on protective relays and circuit breakers(switch) for diagnosis, and the accuracy of diagnosis will be affected under complex fault cases. The electric data information was introduced to propose the model prediction and data cleaning method, as well as to establish the power network fault diagnosis system. By using the model to predict the electric quantity information accurately, the cleaning rules and the logical inference rules were established, and the data cleaning and verification of the switch were carried out respectively. On this basis, the abductive reasoning network (ARN) was used to diagnose the fault information, and the candidate faults were obtained. The simulation results verified the validity and accuracy of this method.

Key words: fault, diagnosis, data cleaning, model prediction, abductive reasoning network

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