变压器故障样本多维诊断及结果可信度分析

doi:10.19595/j.cnki.1000-6753.tces.210070

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Abstract Power transformer is the core equipment of power system, and its safe and stable operation is of great significance to power system. Online fault diagnosis of power transformers is an important method to realize real-time status analysis of power transformers. At present, the selection of features subset for transformer fault diagnosis mainly adopts heuristic-based method, which simplifies the selection process compared to traversal algorithms, but it still consumes a lot of computing power. Moreover, the research of hybrid fault diagnosis motheds for power transformer focuses on the improvement of the diagnosis effect in all samples, and does not pay attention to the credibility analysis of the diagnosis results in single sample. In order to solve this problem, this paper proposed a transformer state analysis method that combines autonomous discretization and optimization of data distribution signs, and single-event multi-model fusion analysis. Proved by examples, this method can effectively analyze the data distribution of each feature, perform feature optimization, and can get the operating status and reliability of the transformer from the perspective of a single event.

Key words： Optimized discrete feature selection result credibility auxiliary analysis

Received: 15 January 2021

PACS:

TM41

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	Li Dianyang
	Zhang Yujie
	Feng Jian
	Wang Shanyuan

Cite this article:

Li Dianyang,Zhang Yujie,Feng Jian等. Multi-Dimensional Diagnosis of Transformer Fault Sample and Credibility Analysis[J]. Transactions of China Electrotechnical Society, 2022, 37(3): 667-675.

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https://dgjsxb.ces-transaction.com/EN/10.19595/j.cnki.1000-6753.tces.210070 OR https://dgjsxb.ces-transaction.com/EN/Y2022/V37/I3/667

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