Magisterarbeit, 2013
78 Seiten
The primary goal of this thesis is to develop a comprehensive method for diagnosing faults in induction motors fed by frequency converters. This is accomplished through a combination of theoretical analysis, practical experimentation, and data analysis. The research focuses on identifying specific faults, including broken rotor bars and short-circuited turns in the stator windings.
This thesis commences with an introduction to the topic, outlining the research objectives and the organization of the thesis. Chapter 2 delves into a comprehensive review of existing literature on motor fault diagnosis, focusing on various monitoring techniques and methodologies. Chapter 3 provides an overview of common faults encountered in induction motors, with an emphasis on rotor faults and short turn faults.
Chapter 4 explores the utilization of signal signature analysis, specifically using FFT techniques, for detecting various motor faults. The chapter discusses the application of FFT for identifying broken rotor bars, stator short circuits, and air gap eccentricity. Chapter 5 focuses on the experimental study of stator and rotor fault diagnosis in a three-phase induction motor, delving into the methodology employed for current spectral analysis. Chapter 6 details the implementation of a LabVIEW program for detecting broken rotor bar faults utilizing FFT techniques.
Chapter 7 presents a thorough analysis and discussion of the results obtained during the experimental study of broken rotor bar faults, examining the variations in motor behavior under various operating conditions. Finally, Chapter 8 examines the application of FFT techniques for diagnosing short-circuited turns fault in stator windings, analyzing the spectral characteristics of the fault under different operating conditions.
The primary keywords encompassing the core concepts and research focus of this thesis include induction motor faults, frequency converter, fault diagnosis techniques, signal signature analysis, FFT (Fast Fourier Transform), LabVIEW, broken rotor bars, short-circuited turns, stator faults, rotor faults, spectral analysis, current signature, and motor monitoring.
The thesis focuses on fault diagnosis, specifically broken rotor bars and short-circuited turns, in induction motors fed by frequency converters using signal signature analysis.
MCSA stands for Motor Current Signature Analysis, a technique used to monitor electrical and mechanical conditions by analyzing current signals.
Frequency converters allow variable speed operation but introduce complex harmonics, requiring specialized spectral signature analysis to identify faults accurately.
The Fast Fourier Transform (FFT) is used to convert time-domain signals into the frequency domain to identify specific "signatures" or peaks that indicate motor abnormalities.
The research implemented a LabVIEW program for real-time data acquisition and spectral analysis of the induction motor's performance.
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