The Theory of Fuzzy Sets as a Means of Assessing the Periods of Service of Asynchronous Electric Motors

I. Vasilev, A. Hismatullin
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引用次数: 2

Abstract

In modern fuel and energy complexes, the main part of the machinery is represented by induction motors. The operating conditions and design features of engines often impede assessing their technical condition. The most common electrical faults are phase loss, intra-winding short circuits, winding short circuits to the housing, inter-winding short circuits, open rotor rods, open windings or in an external circuit. In addition to the electrical part damage, mechanical damage is also distinguished. It includes bearing damage, poor engine mounts, dynamic and static eccentricity. The paper suggest using the theory of fuzzy sets for the objective assessment of the state of an asynchronous machine. The description of objects and phenomena by fuzzy sets requires the use of linguistic variables. They are described by means of fuzzy sets in a certain domain of definition and by the name of variables. Linguistic assessment uses not only quantitative, but also qualitative data. The material obtained as a result of quantitative assessment methods needs to be used, passing it through some transformations. Information on the probability of an emergency situation can be presented in the form of a range of change, represented as a fuzzy set. As input data, this method uses data recognized by an artificial neural network, which is obtained on the basis of data on amplitudes of odd harmonics from 3-11 inclusively generated by the motor. As a result of the experiments, the range of permissible values of linguistic variables is found. It is found that the change in the harmonic composition of currents and voltages of the motor during damage of various kinds is non-linear. Using the Matlab software, the input data is processed. The actions of the algorithm lead to a quantitative assessment of the technical condition of the electric motor, provide its linguistic description.
模糊集理论在异步电动机服务周期评估中的应用
在现代燃料和能源综合体中,机械的主要部分是由感应电动机代表的。发动机的工作条件和设计特点往往阻碍对其技术状况的评估。最常见的电气故障是缺相、绕组内短路、绕组对外壳的短路、绕组间短路、转子杆开路、绕组开路或在外部电路中。除电气部分损坏外,还区分机械损坏。它包括轴承损坏,发动机支架不良,动态和静态偏心。本文提出用模糊集理论对异步电机的状态进行客观评价。用模糊集描述对象和现象需要使用语言变量。它们是用一定定义域中的模糊集和变量的名称来描述的。语言评估不仅使用定量数据,也使用定性数据。定量评价方法得到的资料需要加以利用,并经过一定的转换。关于紧急情况发生概率的信息可以以变化范围的形式表示,用模糊集表示。该方法使用人工神经网络识别的数据作为输入数据,该数据是根据电机产生的3-11次奇次谐波幅值数据得到的。通过实验,确定了语言变量的允许取值范围。研究发现,在各种损伤过程中,电机电流和电压谐波组成的变化是非线性的。利用Matlab软件对输入数据进行处理。该算法的动作导致电机的技术状况的定量评估,提供其语言描述。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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