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Fuzzy pattern recognition approach with symptom zoom technology to diagnose a slight and incipient fault in a thermodynamic system

机译:具有症状缩放技术的模糊模式识别方法可诊断热力学系统中的轻微和早期故障

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To diagnose a slight or incipient fault in a thermodynamic system correctly and timely, a new fault recognition approach is put forward by joint application of fault symptom zoom technology (SZT) and fuzzy pattern recognition. By studying the rules of the thermal system faults related to energy and mass balance, a fault symptom preprocessing method, which is called "fault symptom zoom technology", is put forward to preprocess the fault characteristic parameters, with which the complexity of the thermal system fault knowledge library can be effectively reduced and the slight fault recognition ability can be greatly enhanced. The fault fuzzy pattern recognition method is introduced, and a new general-purpose fuzzy recognition function is given, which fits for various kinds of fault symptoms and is with favorable fault classifying ability. Some fault diagnostic examples for incipient and slight faults of the thermodynamic system are given, which verify the effectiveness of the method.
机译:为了正确,及时地诊断热力学系统中的轻度或早期故障,结合故障征象放大技术(SZT)和模糊模式识别提出了一种新的故障识别方法。通过研究与能量和质量平衡有关的热系统故障的规律,提出了一种故障征兆预处理方法,称为“故障征候放大技术”,对故障特征参数进行预处理,从而使热力系统复杂化。故障知识库可以有效减少,轻微的故障识别能力可以大大提高。介绍了一种故障模糊模式识别方法,给出了一种新的通用模糊识别功能,该功能可以适应各种故障症状,具有良好的故障分类能力。给出了热力学系统初发和轻度故障的一些故障诊断实例,验证了该方法的有效性。

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