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Synthetic Diagnosis Model Applying Case-Based Reasoning in Dissolved Gas Analysis of Transformer Oil

Qian Zheng Gao Wensheng Shang Yong Yan Zhang(Xian Jiaotong University 710049 China)  
A synthetic diagnosis model applying case-based reasoning in dissolved gas analysis of transformer oil is utilized to diagnose the fault of power transformer.First,three kinds of retrieving models are adopted to retrieve the set of source case which the symptom is similar to the symptom of suspected transformer,then an algorithm of synthetic estimation is introduced to achieve the optimal one of source cases,the diagnosis result of suspected transformer could be acquired by the comparison of symptoms between the optimal case and the suspected transformer at last.The application results show that the purposed model improves the reliability and practicality.
【Fund】: 国家自然科学基金;; 东北电力集团资助项目
【CateGory Index】: TM4
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