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Fuzzy logic application to pre-fault diagnoses of induction motors

机译:模糊逻辑在异步电动机故障前诊断中的应用

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Induction machines, with power ranging from few kW to several MW, are the most used electric actuators in industry applications. Faults occurring in induction machines can negatively influence worker safety and production processes in terms of time delays and quality of the final product. Some anomalies can be detected early in order to predict fault conditions, so allowing optimizing servicing and machine stopping. The method proposed, based on artificial intelligence techniques, allows operating conditions analysis of induction motors. In particular, the fuzzy set theory is used to perform a spectrum analysis of the stator current in order to identify some types of incoming faults.
机译:电源范围从几千瓦到几兆瓦的电源,是工业应用中最常用的电动执行器。在感应机器中发生的故障可以在最终产品的时间延迟和质量方面对工作者安全和生产过程产生负面影响。可以提前检测到一些异常以预测故障条件,因此允许优化维修和机器停止。基于人工智能技术提出的方法允许感应电动机的操作条件分析。特别地,模糊集理论用于执行定子电流的光谱分析,以识别某些类型的传入故障。

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