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A Novel Transformer Fault Diagnosis Model Based on Integration of Fault Tree and Fuzzy Set

机译:基于故障树和模糊集集成的变压器故障诊断模型

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This paper presents a new transformer fault diagnosis model based on the integration of fault tree analysis (FTA) and fuzzy set theory. In practical application, FTA is a frequently used technique in hazard identification. However, in conventional FTA, fuzzy information and uncertain logical relationship cannot be handled efficiently because of lack of fuzzy processing capability. Moreover, due to deficiency in data, the failure rates of the system components and the occurrence probability of undesired events cannot be obtained easily. In order to overcome these disadvantages, an integration of FTA and the fuzzy set theory is proposed to establish a fault diagnosis model, taking advantages of both methods. The analytic hierarchy process (AHP) is applied to determine the weights of tree node variables. The proposed model has been applied successfully and the result indicates the fuzzy fault tree analysis method (FFTA) has great potential in transformer fault diagnosis field.
机译:本文结合故障树分析(FTA)和模糊集理论,提出了一种新的变压器故障诊断模型。在实际应用中,FTA是危险识别中常用的技术。然而,在常规的FTA中,由于缺乏模糊处理能力,不能有效地处理模糊信息和不确定的逻辑关系。此外,由于数据不足,不能容易地获得系统组件的故障率和不期望事件的发生概率。为了克服这些缺点,提出了将FTA与模糊集理论相结合的方法,以建立两种方法的优点,建立故障诊断模型。应用层次分析法(AHP)确定树节点变量的权重。该模型已成功应用,结果表明模糊故障树分析方法(FFTA)在变压器故障诊断领域具有很大的潜力。

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