模糊推理系统在笼形感应电动机转子偏心诊断中的应用

M. Sułowicz, T. Sobczyk
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引用次数: 8

摘要

提出了一种基于自适应网络模糊推理系统(ANFIS)的笼型异步电动机转子偏心诊断方法。为了评估转子的偏心,将提供所选感应电动机诊断推理块的结构和工作原理。所提出的诊断推理块的输入数据将由代表静态和动态偏心的两个偏心指标的值组成。在求解笼型感应电动机多次谐波数学模型的基础上,对各电机进行了指标设置。提出的系统将评估相对偏心水平。在系统的输出端,将获得有关相对偏心水平(静态和动态)总和的信息。所开发的诊断推理块提供的偏心诊断的实例就诊断的正确性和准确性进行了解释。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Application of Fuzzy Inference System for Cage Induction Motors Rotor Eccentricity Diagnostic
This paper presents a diagnostic method of the eccentricity of the rotor of the cage induction motor, using a diagnostic inference block, based on ANFIS (adaptive-network-based fuzzy inference system). A construction and principle of work of the diagnostic inference block for a selected induction motor will be provided, in order to assess the eccentricity of the rotor. The input data for the proposed diagnostic inference block will consist of the values of two eccentricity indicators, representing the static and the dynamic eccentricity. The indicators are set for every motor on the basis of the solution of multi-harmonics mathematical model of the cage induction motor. The proposed system will assess relative eccentricity levels. At the output of the system, information regarding the sum of the relative eccentricity levels (both static and dynamic) will be available. Examples of the eccentricity diagnosis supplied by the developed diagnostic inference block are interpreted with regard to the diagnosis correctness and accuracy.
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