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A novel fault diagnosis approach based on improved possibilistic C-means clustering and fault vector

机译:一种基于改进的可能性C-Means聚类和故障向量的新型故障诊断方法

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Fault diagnosis approach based on fuzzy clustering is an important data-driven diagnosis approach. It does not need accurate mathematical models and can use a large amount of system historical and online data to extract failure information and to realize fault diagnosis. However, there are still no mature methods and techniques to deal with new faults. This paper proposed a possibilistic C-means clustering and fault vector based fault diagnosis approach to handle this problem. Simulation results have verified the effectiveness of the proposed method.
机译:基于模糊聚类的故障诊断方法是一种重要的数据驱动诊断方法。它不需要准确的数学模型,可以使用大量的系统历史和在线数据来提取故障信息并实现故障诊断。但是,仍然没有成熟的方法和技术来处理新的故障。本文提出了一种可能的C-Means聚类和基于故障向量的故障诊断方法来处理这个问题。仿真结果已验证了该方法的有效性。

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