Stator winding fault diagnosis in three-phase synchronous and asynchronous motors, by the extended Park's vector approach

2002 ◽  
Author(s):  
S.M.A. Cruz ◽  
A.J. Marques Cardoso
Keyword(s):  
Fault Diagnosis ◽  
Stator Winding ◽  
Asynchronous Motors ◽  
Three Phase ◽  
Vector Approach

scholarly journals A Discrete Wavelet transform based Protection Scheme for Three Phase Induction Motor

2019 ◽  
Vol 8 (3) ◽  
pp. 6366-6370
Keyword(s):  
Wavelet Transform ◽  
Fault Diagnosis ◽  
Induction Motor ◽  
High Frequency ◽  
Discrete Wavelet ◽  
Stator Winding ◽  
Universal Model ◽  
Matlab Simulation ◽  
Protection Scheme ◽  
Three Phase

This paper has proposed an approachwhich detects the stator turn to turn faults and phase to ground faults in stator winding of three induction motor. This method proposes analysis of stator winding currents for both normal and fault conditions. High frequency universal model of three phase induction motor used for MATLAB simulation. By using the wavelet MRA technique, the approximate and detailed coefficients of the faulty voltage and current waveforms of the machine are generated under different fault conditions. From the approximate coefficients the type of the fault has been identified. Depending on the energies of the signal the fault diagnosis can be done. The proposed protection scheme is reliable and fast for various fault inception angles

scholarly journals Mutual Information and Meta-Heuristic Classifiers Applied to Bearing Fault Diagnosis in Three-Phase Induction Motors

2020 ◽  
Vol 11 (1) ◽  
pp. 314
Author(s):  
Gustavo Henrique Bazan ◽  
Alessandro Goedtel ◽  
Marcelo Favoretto Castoldi ◽  
Wagner Fontes Godoy ◽  
Oscar Duque-Perez ◽  
...  
Keyword(s):  
Fault Diagnosis ◽  
Mutual Information ◽  
Induction Motors ◽  
Operating Conditions ◽  
Industrial Systems ◽  
Bearing Fault Diagnosis ◽  
Bee Colony ◽  
Three Phase ◽  
C4.5 Decision Tree ◽  
The Time Domain

Three-phase induction motors are extensively used in industrial processes due to their robustness, adaptability to different operating conditions, and low operation and maintenance costs. Induction motor fault diagnosis has received special attention from industry since it can reduce process losses and ensure the reliable operation of industrial systems. Therefore, this paper presents a study on the use of meta-heuristic tools in the diagnosis of bearing failures in induction motors. The extraction of the fault characteristics is performed based on mutual information measurements between the stator current signals in the time domain. Then, the Artificial Bee Colony algorithm is used to select the relevant mutual information values and optimize the pattern classifier input data. To evaluate the classification accuracy under various levels of failure severity, the performance of two different pattern classifiers was compared: The C4.5 decision tree and the multi-layer artificial perceptron neural networks. The experimental results confirm the effectiveness of the proposed approach.

Virtual Instrumentation Based Analysis of Induction Motor

2014 ◽  
Vol 984-985 ◽  
pp. 970-976
Author(s):  
Memala W. Abitha ◽  
V. Rajini
Keyword(s):  
Induction Motor ◽  
Life Time ◽  
Open Circuit ◽  
Virtual Instrumentation ◽  
Repair Work ◽  
Three Phase ◽  
Stationary Reference Frame ◽  
Stator Fault ◽  
Motor Failure ◽  
Vector Approach

The three phase induction motor is a popularly used machine in many of the industries, which is well known for its robustness, reliability, cost effectiveness, efficient and safe operation. The unnoticed manufacturing failure, mistakes during repair work, exceeding life time may be some of the causes of the induction motor failure, which may lead to the unknown shut down time of the industry. The condition monitoring plays important role as it has the influence on the production of materials and profit. In our work, the induction motor is modelled using stationary reference frame and analysed for single phasing stator fault. The techniques used in detecting the single phasing (open circuit) failures are Park’s vector approach and Fast Fourier Transform (FFT). Park’s vector approach is used for detecting the faults occurring at various phases and FFT is used for detecting the faults of the induction motor working under no load and varying loading conditions.

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