Discrimination of Synchronous Machines Rotor Faults in Electrical Signature Analysis Based on Symmetrical Components

作者:Salomon Camila Paes*; Santana Wilson Cesar; Lambert Torres Germano; Borges da Silva Luiz Eduardo; Bonaldi Erik Leandro; de lacerda de Oliveira Levy Ely; Borges da Silva Jonas Guedes; Pellicel Alexandre Luiz; Figueiredo Goncalo Cassio; Araujo Lopes Marco Aurelio
来源:IEEE Transactions on Industry Applications, 2017, 53(3): 3146-3155.
DOI:10.1109/TIA.2016.2613501

摘要

Electrical signature analysis (ESA) has been successfully applied to predictive maintenance of synchronous machines. The fault diagnosis is performed by analyzing failure patterns in the current or voltage spectra, which allow the discrimination of a healthy and a faulty condition on the monitored machine. Generally, the failure patterns are a function of the line frequency, rotor rotation frequency, and some structure features of the machine. The rotor rotation frequency pattern, for instance, is indicative of rotor mechanical problems and rotor winding interturn short-circuit. An increase of this frequency component magnitude may indicate the incipience of a rotor fault but may not discriminate the nature of the fault (electrical or mechanical). Thus, it is necessary to distinguish the effects of electrical and mechanical faults in these components in order to get a reliable diagnosis of the machine. No works have been found in the literature approaching this specific issue. This paper proposes a simple and innovative methodology to distinguish the effect of electrical and mechanical faults in the mentioned ESA failure patterns based on the method of symmetrical components. Its effectiveness is validated by experiments performed on a synchronous generator test rig. The proposed condition monitoring system is simple, low cost, and low intrusive, as it only relies on stator electrical quantities. Moreover, it is in operation in a Brazilian 404-MW thermal power station.

  • 出版日期2017-6