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Research on diagnosis rule acquisition for turbo-generator unit rotor misalignment fault based on rough set

机译:基于粗糙集的汽轮发电机组转子不对中故障诊断规则获取研究

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Aiming at solving the problem of feature information redundancy and its different degree of importance for turbo-generator unit based on rough set, this paper uses an attribute reduction method to get the misalignment fault diagnosis rules. By fuzzifying up and discretizing the misalignment fault characteristic parameters, this article constructs the fault decision table for reduction, and meanwhile removes the redundant information to extract diagnosis rules of misalignment fault from incomplete and inaccurate data by using decision table. The application shows that this method is not only an effective way to obtain the fault diagnosis rules, but also can effectively diagnose the rotor misalignment fault.
机译:针对基于粗糙集的汽轮发电机组特征信息冗余及其重要性程度不同的问题,本文采用一种属性约简的方法来获得失准故障诊断规则。通过对失调故障特征参数进行模糊化和离散化,构造出故障决策表以进行减少,同时去除冗余信息,利用决策表从不完整,不准确的数据中提取失准故障的诊断规则。应用表明,该方法不仅是获得故障诊断规则的有效途径,而且可以有效地诊断转子不对中故障。

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