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一种用于检测鼠笼式电动机气隙不规则性的杂散磁通分量的改进频谱分析方法。

An improved spectral analysis of the stray flux component for the detection of air-gap irregularities in squirrel cage motors.

作者信息

Salah Mohamed, Bacha Khmais, Chaari Abdelkader

机构信息

Control, Monitoring and Reliability of the Systems, Higher School of Sciences and Techniques of Tunis, University of Tunis, 5 Taha Hussein street - Tunis, Postal Box 56, Bab Menara 1008, Tunisia.

出版信息

ISA Trans. 2014 May;53(3):816-26. doi: 10.1016/j.isatra.2014.02.001. Epub 2014 Feb 26.

Abstract

For machines׳ monitoring purpose, the classical motor current signature analysis has shown its weakness in distinguishing the eccentricity occurrence in presence of others mechanical faults. Although Park׳s vector approach can cover this drawback, the high cost due to the requirement to use three current sensors associated with an advanced processing technique, makes it less desired by industrialists. In this paper, we suggest an alternative diagnosis method based on a suitable processing of the stray flux data. The experimental results have revealed the potential of a simple search coil for the detection and the distinction of the accurate eccentricity nature even in presence of similar mechanical faults.

摘要

出于机器监测目的,传统的电机电流特征分析在存在其他机械故障的情况下,已显示出其在区分偏心故障方面的弱点。尽管派克矢量法可以弥补这一缺点,但由于需要使用三个电流传感器并结合先进的处理技术,成本较高,这使得工业界对此不太青睐。在本文中,我们提出了一种基于对杂散磁通数据进行适当处理的替代诊断方法。实验结果表明,即使在存在类似机械故障的情况下,一个简单的搜索线圈也有潜力检测并区分准确的偏心性质。

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