首页> 外文会议>ISECS International Colloquium on Computing, Communication, Control, and Management >Based on data mining electrical equipment condition monitoring and fault diagnosis technology research
【24h】

Based on data mining electrical equipment condition monitoring and fault diagnosis technology research

机译:基于数据挖掘电气设备状态监测和故障诊断技术研究

获取原文

摘要

The electrical equipments operation status monitoring, operating performance analysis and assessment is to ensure the safe operation of its important components. A new trouble pattern analysis was put forward based on thought of data mining. The trouble information dimensionality tables come into being by collecting and cleaning up the fault phenomenon. The association rule dimensionality table was made up of the technique parameters and the trouble causes. We analyzed the trouble information by frequent item set of the Apriori arithmetic based on the trouble information dimensionality table and the association rule dimensionality table. We made sure the causes of the trouble and chose the priority resolving scheme by matching the trouble and building and filtrating the candidates. A process of data mining was designed for status information and fault information, Practical results show that the automation level of the management and diagnosis for electrical equipment is improved and it is of great practical value.
机译:电气设备操作状态监控,操作性能分析和评估是确保其重要组成部分的安全运行。基于数据挖掘思想,提出了一种新的麻烦模式分析。故障信息维度表通过收集和清理故障现象来实现。关联规则维度表由技术参数和故障原因组成。我们通过基于故障信息维度表和关联规则维数表的APRiori算法的频繁项目集分析了故障信息。我们确保了麻烦的原因,并通过匹配麻烦和建设并过滤候选人来选择优先解决方案。设计了数据挖掘过程,专为状态信息和故障信息而设计,实际结果表明,电气设备的管理和诊断的自动化水平得到改善,实用价值很大。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号