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Vibration Fault Diagnosis for Hydraulic Generator Units with Pattern Recognition and Cluster Analysis

机译:基于模式识别和聚类分析的水轮发电机组振动故障诊断

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摘要

For reducing the economic losses of hydraulic generator units, fault detection and diagnosis is fundamental. A technique is presented that uses pattern recognition and cluster analysis. Faults of hydraulic generator units are classified from the characteristic parameters using statistical analysis methods. A characteristic parameter matrix of standard faults has been developed for identifying the vibration faults. The cluster technique is carried out in a real case. Results demonstrated that the proposed method is a good candidate to be used as an online diagnosis tool for hydraulic generator units.
机译:为了减少水力发电机组的经济损失,故障检测和诊断至关重要。提出了一种使用模式识别和聚类分析的技术。使用统计分析方法根据特征参数对水轮发电机组的故障进行分类。已经开发出标准故障的特征参数矩阵来识别振动故障。群集技术是在实际情况下执行的。结果表明,该方法是水力发电机组在线诊断工具的良好选择。

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