Recent Techniques to Identify the Stator Fault Diagnosis in Three Phase Induction Motor

2016 ◽  
pp. 309-325
Author(s):  
K. Vinoth Kumar ◽  
S. Suresh Kumar ◽  
A. Immanuel Selvakumar ◽  
R. Saravana Kumar
Keyword(s):  
Fault Diagnosis ◽  
Life Span ◽  
Induction Motor ◽  
Induction Motors ◽  
Early Stage ◽  
Decomposition Technique ◽  
Maintenance Schedule ◽  
Three Phase ◽  
Stator Fault ◽  
Financial Losses

Induction motors have gained its popularity as most suitable industrial workhorse, due to its ruggedness and reliability. With the passage of time, these workhorses are susceptible to faults, some are incipient and some are major. Such fault can be catastrophic, if unattended and may develop serious problem that may lead to shut down the machine causing production and financial losses. To avoid such breakdown, an early stage prognosis can help in preparing the maintenance schedule, which will lead to improve its life span. Scientist and engineers worked with different scheme to diagnose the machine faults. In this paper, the authors diagnose the turn-to-turn faults condition of the stator through symmetrical component analysis. The results of the analysis also verified through Power Decomposition Technique (PDT) in Matlab /SIMULINK. The results are compatible with the published results for known faults.

Recent Techniques to Identify the Stator Fault Diagnosis in Three Phase Induction Motor

2012 ◽  
Vol 1 (4) ◽  
pp. 106-120
Author(s):  
K. Vinoth Kumar ◽  
S. Suresh Kumar ◽  
A. Immanuel Selvakumar ◽  
R. Saravana Kumar
Keyword(s):  
Fault Diagnosis ◽  
Life Span ◽  
Induction Motors ◽  
Early Stage ◽  
Decomposition Technique ◽  
Maintenance Schedule ◽  
Three Phase ◽  
Symmetrical Component ◽  
Stator Fault ◽  
Financial Losses

Induction motors have gained its popularity as a suitable industrial workhorse, due to its ruggedness and reliability. With time, these workhorses are susceptible to faults, some are incipient and some are major. Such fault can be catastrophic, if unattended and may develop serious problems that may lead to shutdown to the machine causing production and financial losses. To avoid such breakdown, an early stage prognosis can help in preparing the maintenance schedule, which will lead to an improve life span. Scientist and engineers worked with different scheme to diagnose the machine faults. The authors diagnose the turn-to-turn faults condition of the stator through symmetrical component analysis. The results of the analysis are also verified through Power Decomposition Technique (PDT) in Matlab /SIMULINK. The results are compatible with the published results for known faults.

Application of Probabilistic Neural Networks in Fault Diagnosis of Three-Phase Induction Motors

2013 ◽  
Vol 433-435 ◽  
pp. 705-708 ◽  
Author(s):  
Shuo Ding ◽  
Xiao Heng Chang ◽  
Qing Hui Wu
Keyword(s):  
Neural Network ◽  
Fault Diagnosis ◽  
Induction Motors ◽  
Probabilistic Neural Network ◽  
Short Circuit ◽  
Model And Simulation ◽  
Fast Training ◽  
Three Phase ◽  
Short Circuits ◽  
Stator Fault

In fault diagnosis of three-phase induction motors, traditional methods usually fail because of the complex system of three-phase induction motors. Short circuit is a very common stator fault in all the faults of three-phase induction motors. Probabilistic neural network is a kind of artificial neural network which is widely used due to its fast training and simple structure. In this paper, the diagnosis method based on probabilistic neural network is proposed to deal with stator short circuits. First, the principle and structure of probabilistic neural network is studied in this paper. Second, the method of fault setting and fault feature extraction of three-phase induction motors is proposed on the basis of the fault diagnosis of stator short circuits. Then the establishment of the diagnosis model based on probabilistic neural network is illustrated with details. At last, training and simulation tests are done for the model. And simulation results show that this method is very practical with its high accuracy and fast speed.

scholarly journals Fault Diagnosis of Three Phase Induction Motor Using Current Signal, MSAF-Ratio15 and Selected Classifiers

2017 ◽  
Vol 62 (4) ◽  
pp. 2413-2419 ◽  
Author(s):  
A. Glowacz ◽  
W. Glowacz ◽  
Z. Glowacz ◽  
J. Kozik ◽  
M. Gutten ◽  
...  
Keyword(s):  
Fault Diagnosis ◽  
Induction Motor ◽  
Induction Motors ◽  
Vibration Signal ◽  
Degradation Process ◽  
Conveyor Belt ◽  
Metallurgical Equipment ◽  
Financial Loss ◽  
Linear Discriminant ◽  
Three Phase

AbstractA degradation of metallurgical equipment is normal process depended on time. Some factors such as: operation process, friction, high temperature can accelerate the degradation process of metallurgical equipment. In this paper the authors analyzed three phase induction motors. These motors are common used in the metallurgy industry, for example in conveyor belt. The diagnostics of such motors is essential. An early detection of faults prevents financial loss and downtimes. The authors proposed a technique of fault diagnosis based on recognition of currents. The authors analyzed 4 states of three phase induction motor: healthy three phase induction motor, three phase induction motor with 1 faulty rotor bar, three phase induction motor with 2 faulty rotor bars, three phase induction motor with faulty ring of squirrel-cage. An analysis was carried out for original method of feature extraction called MSAF-RATIO15 (Method of Selection of Amplitudes of Frequencies – Ratio 15% of maximum of amplitude). A classification of feature vectors was performed by Bayes classifier, Linear Discriminant Analysis (LDA) and Nearest Neighbour classifier. The proposed technique of fault diagnosis can be used for protection of three phase induction motors and other rotating electrical machines. In the near future the authors will analyze other motors and faults. There is also idea to use thermal, acoustic, electrical, vibration signal together.

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.

scholarly journals Windings Design for Single-phase Induction Motors Base on 4-phase Induction Motor (Case study: identical windings design)

2018 ◽  
Vol 215 ◽  
pp. 01023 ◽  
Author(s):  
Zuriman Anthony ◽  
Erhaneli Erhaneli ◽  
Zulkarnaini Zulkarnaini
Keyword(s):  
Induction Motor ◽  
Power Factor ◽  
Single Phase ◽  
Induction Motors ◽  
Three Phase ◽  
Motor Design

A 1-phase induction motor usually has a complicated windings design which compares to polyphase induction motor. In addition, a large capacitor start is required to operate the motor. It is an expensive way to operate the motor if it compare to polyphase induction motor. So, a new innovation method is required to make the motor more simple and cheaper. This research is purposed to study a new winding design for a single-phase capacitor motor. Winding design of the motor was conducted to a simple winding design like a 4-phase induction motor that has four identical windings. The comparator motor that use in this study was a Three-phase induction motor with data 1400 RPM, 1.5 HP, 50Hz, 380/220V, Y/Δ, 2.74/4.7A, 4 poles, that had the same current rating which the proposed method. The result showed that the motor design on this proposed method could be operated at 88.18 % power rating with power factor close to unity.

scholarly journals Experimental Study of Various Parameters during Speed Control of Three-phase Induction Motor Using GPIC and LabVIEW

2021 ◽  
Vol 5 (1) ◽  
pp. 51-62
Author(s):  
Adnan Ahmed ◽  
Abdul Majeed Shaikh ◽  
Muhammad Fawad Shaikh ◽  
Shoaib Ahmed Shaikh ◽  
Jahangir Badar Soomro
Keyword(s):  
Induction Motor ◽  
Induction Motors ◽  
Induction Machine ◽  
Speed Control ◽  
Industrial Applications ◽  
General Purpose ◽  
Three Phase ◽  
Field Programmable ◽  
Input Source ◽  
Open Control

Induction motors are widely used from home to industrial applications. Speed of induction motor plays important role, so to control the speed of induction motor various techniques are adopted and one of these techniques is V/F control, which is adopted in this paper. This technique helps to control the speed in open control system in RPM. Moreover, Control is designed in LabVIEW, it is quite helpful to develop the circuit graphically and code is automatically written in the background to run on Field Programmable Gate Array (FPGA). The aim of this research is to study the impacts on diverse parameters during speed control of three phase induction machine with manipulation of GPIC. Solar technology is used as input source to drive the General-Purpose Inverter Controller (GPIC). Apart of this, impacts of modulation index and carrier frequency influencing the active, reactive and apparent power, temperature and power quality and current overshoot is analysed. MATLAB/Simulink and LabVIEW tools are used for simulation and results along with GPIC, Induction motor and solar panel as hardware.

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