A current monitoring system for diagnosing electrical failures in induction motors
TL;DR: In this paper, the authors present an on-line current monitoring system that uses both techniques for fault detection and diagnosis in the stator and in the rotor of three phase induction motors.
About: This article is published in Mechanical Systems and Signal Processing.The article was published on 2006-05-01. It has received 127 citations till now. The article focuses on the topics: Induction motor & Stator.
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TL;DR: Overall, this paper includes review of system signals, conventional and advance signal processing techniques; however, it mainly covers, the selection of effective statistical features, AI methods, and associated training and testing strategies for fault diagnostics of IMs.
220 citations
TL;DR: In this paper, the power output of a variable-speed wind turbine generator is monitored using a wavelet in order to extract the strength of particular frequency components, characteristic of faults.
Abstract: With an increasing number of wind turbines being erected offshore, there is a need for cost-effective, predictive, and proactive maintenance. A large fraction of wind turbine downtime is due to bearing failures, particularly in the generator and gearbox. One way of assessing impending problems is to install vibration sensors in key positions on these subassemblies. Such equipment can be costly and requires sophisticated software for analysis of the data. An alternative approach, which does not require extra sensors, is investigated in this paper. This involves monitoring the power output of a variable-speed wind turbine generator and processing the data using a wavelet in order to extract the strength of particular frequency components, characteristic of faults. This has been done for doubly fed induction generators (DFIGs), commonly used in modern variable-speed wind turbines. The technique is first validated on a test rig under controlled fault conditions and then is applied to two operational wind turbine DFIGs where generator shaft misalignment was detected. For one of these turbines, the technique detected a problem 3 months before a bearing failure was recorded.
190 citations
TL;DR: A broad outlook on rotor fault monitoring techniques for the researchers and engineers can be found in this paper, where the authors review and summarize the recent researches and developments performed in condition monitoring of the induction machine with the purpose of rotor faults detection.
189 citations
TL;DR: In this article, a fault diagnosis method based on adaptive neuro-fuzzy inference system (ANFIS) in combination with decision trees is presented, which is one of the decision tree methods is used as a feature selection procedure to select pertinent features from data set.
Abstract: This paper presents a fault diagnosis method based on adaptive neuro-fuzzy inference system (ANFIS) in combination with decision trees. Classification and regression tree (CART) which is one of the decision tree methods is used as a feature selection procedure to select pertinent features from data set. The crisp rules obtained from the decision tree are then converted to fuzzy if-then rules that are employed to identify the structure of ANFIS classifier. The hybrid of back-propagation and least squares algorithm are utilized to tune the parameters of the membership functions. In order to evaluate the proposed algorithm, the data sets obtained from vibration signals and current signals of the induction motors are used. The results indicate that the CART-ANFIS model has potential for fault diagnosis of induction motors.
188 citations
TL;DR: A neural approach to detect and locate automatically an interturn short-circuit fault in the stator windings of the induction machine by a feedforward multilayer-perceptron neural network trained by back propagation.
Abstract: This paper presents a neural approach to detect and locate automatically an interturn short-circuit fault in the stator windings of the induction machine. The fault detection and location are achieved by a feedforward multilayer-perceptron neural network (NN) trained by back propagation. The location process is based on monitoring the three-phase shifts between the line current and the phase voltage of the machine. The required data for training and testing the NN are experimentally generated from a three-phase induction motor with different interturn short-circuit faults. Simulation, as well as experimental, results are presented in this paper to demonstrate the effectiveness of the used method.
173 citations
References
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Book•
01 Jan 1986
TL;DR: In this paper, the authors focus on the areas of electric power and electric drives and emphasize analysis and formulation for control applications and computer simulation, and present an industry reference for these areas.
Abstract: Originally published in 1986 by McGraw-Hill. Focusing on the areas of electric power and electric drives, this advanced text and industry reference emphasizes analysis and formulation for control applications and computer simulation. Annotation copyright Book News, Inc. Portland, Or.
2,574 citations
TL;DR: In this paper, the industrial application of motor current signature analysis (MCSA) to diagnose faults in three-phase induction motor drives is discussed, which is a noninvasive, online monitoring technique for the diagnosis of problems in induction motors.
Abstract: Three-phase induction motors are the "workhorses" of industry and are the most widely used electrical machines. In an industrialized nation, they can typically consume between 40 to 50% of all the generated capacity of that country. This article focuses on the industrial application of motor current signature analysis (MCSA) to diagnose faults in three-phase induction motor drives. MCSA is a noninvasive, online monitoring technique for the diagnosis of problems in induction motors. Reliability-based maintenance (RBM) and condition-based maintenance (CBM) strategies are now widely used by industry, and health monitoring of electrical drives is a major feature in such programs.
1,054 citations
"A current monitoring system for dia..." refers background or methods in this paper
...However, as the MCSA has been used for so long, giving enough proofs of utility at industrial environments [20], it is the approach selected in this work for detecting and diagnosing rotor electrical faults....
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...From the stator spectral analysis (MCSA) it is possible to detect rotor as well as stator winding faults, as presented in [20]....
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03 Jun 1991
TL;DR: In this article, the authors attempt to identify the various causes of stator and rotor failures in three-phase squirrel cage induction motors, and a specific methodology is proposed to facilitate an accurate analysis of these failures.
Abstract: The authors attempt to identify the various causes of stator and rotor failures in three-phase squirrel cage induction motors. A specific methodology is proposed to facilitate an accurate analysis of these failures. It is noted that, due to the destructive nature of most failures, it is not easy, and is sometimes impossible, to determine the primary cause of failure. By a process of elimination, one can usually be assured of properly identifying the most likely cause of the failure. It is pointed out that the key point in going through this process of elimination is to use the basic steps of analyzing the failure class and pattern, noting the general motor appearance, identifying the operating condition at the time of failure, and gaining knowledge of the past history of the motor and application. >
603 citations
TL;DR: In this paper, a computer-based noninvasive broken bar fault detector for squirrel-cage rotors of induction motors is presented, which can be applied to existing motors without disassembly or shutdown and has the sensitivity to diagnose the presence of a single broken bar or an open end ring.
Abstract: A description is given of a computer-based noninvasive broken bar fault detector for squirrel-cage rotors of induction motors. The detector can be applied to existing motors without disassembly or shutdown and has the sensitivity to diagnose the presence of a single broken bar or an open end ring. It is suitable for monitoring the trend of the motor signature, or it can be used as a one-time diagnostic tool. >
535 citations
01 May 1986
TL;DR: In this paper, a study carried out to detect air gap eccentricity in large 3-phase induction motors was carried out and the philosophy of using a unified online monitoring strategy was presented and the reasons for selecting line current and frame vibration as the monitored parameters are discussed.
Abstract: The paper reports on a study carried out to detect airgap eccentricity in large 3-phase induction motors. The philosophy of using a unified online monitoring strategy is presented and the reasons for selecting line current and frame vibration as the monitored parameters are discussed. A theoretical analysis is presented which predicts the presence of unique signature patterns in the current and vibration spectra which are only characteristic of eccentricity. The theoretical predictions are verified by experimental results from a special fault producing test rig and on-site tests in a power station.
508 citations
"A current monitoring system for dia..." refers background in this paper
...References for coils to monitor the motor axial flux may be found in [7], vibration measurement, in [8,9]....
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