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数据挖掘技术在油中气体分析和故障诊断中的应用研究 被引量:3

RESEARCH ON OIL-DISSOLVED GAS ANALYSIS AND FAULT DIAGNOSIS BY DATA MINING TECHNOLOGY
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摘要 对数据挖掘技术在故障诊断中的应用做了尝试研究。通过对变压器故障和检修记录中的油色谱数据进行挖掘处理,建立了变压器运行状态与各种气体含量之间的直观联系。所建立的模型具有较高的预测准确度,可以作为变压器运行状态诊断的判断依据。研究表明,数据挖掘技术在电力系统中具有很好的应用前景。 Research is attempted to use data mining technology in fault diagnosis of electrical apparatus. By employing the DataCruncher tool to process the accumulated data from fault and maintenance documents of transformers, the correlation between the state of operation and the oil-dissolved gases is modeled. The formulated model has a high precision in prediction of the operation state. It may be used as a criterion in diagnosing the service state of transformers. This research implies that the data mining technology has a bright future in application to electrical power engineering.
出处 《高压电器》 CAS CSCD 北大核心 2003年第3期39-41,共3页 High Voltage Apparatus
关键词 变压器 故障诊断 数据挖掘 绝缘油 气体分析 数据库 数据处理 data mining transformer fault model dissolved gas analysis (DGA)
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