Power Research

D. K. Chaturvedi ¹, Mayank Pratap Singh ¹, Md. Sharif Iqbal ¹, Vikas Pratap Singh ²

Affiliations
1 Department of Electrical Engineering, Dayalbagh Educational Institute, Dayalbagh, Agra, U.P, IN
2 Central Power Research Institute, Bangalore,, IN

Abstract

The induction motor is commonly used in industries due to its rugged construction and almost no maintenance. To precisely control the induction motor, accurate estimation of parameters is required. Artificial Neural Network (ANN) is used in the past for parameter estimation. The conventional ANN has its own problems such as learning issues, unknown size of ANN and its connections, etc. To overcome some of its problems generalized neural network is used in this paper. The GNN is trained to estimate parameters of three phase induction motor. Experimental setup is developed in DEI, which is consisting of a 415 V, 3Φ squirrel cage induction motor, data acquisition system and on-line parameter estimator.

Keywords

Parameter estimation, three phase induction motor, ann , generalized neuron

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D. K. Chaturvedi ¹, Md. Sharif Iqbal ¹, Mayank Pratap Singh ¹, Vikas Pratap Singh ²

Affiliations
1 Dept. of Electrical Engineering, Dayalbagh Educational Institute, Dayalbagh, Agra, U.P., IN
2 Central Power Research Institute, Bangalore, IN

Abstract

Induction motors are popularly used as an electric drives are the critical component in industrial systems. Most of the faults in induction motor are because of excessive heat generated in the machine. In the industrial application a large rating of induction motors are used which produce a significant heat. The heat is produced in the motor due to the different losses accumulated in the machine. Hence a healthy cooling system is always required to dissipate the heat and maintain the motor temperature within acceptable limits. This paper deals with the problem occurred specially in the cooling system under different operating conditions and investigate them. The on-line information is gathered from the machine about temperature, current and vibration signatures at different operating condition and the health of the cooling system is analyzed. Soft computing techniques are utilized for this purpose.

Keywords

Induction motor, cooling system, temperature, current signature, vibration, soft computing.

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D. K. Chaturvedi ¹, Mayank Pratap Singh ², Md. Sharif Iqbal ², Vikas Pratap Singh ³

Affiliations
1 Professor at Department of Electrical Engineering, Dayalbagh Educational Institute, Dayalbagh, Agra, U.P., IN
2 Research Scholar at Department of Electrical Engineering, Dayalbagh Educational Institute, Dayalbagh, Agra, U.P., IN
3 Senior Research Fellow at Central Power Research Institute, Bangalore, IN

Abstract

The parameters of induction motor depends on various factors such as: machine internal state, machine ageing, magnetic saturation, operating conditions, the coupling effect between the internal system and external system. The paper deals with an overview of parameter estimation of three phase induction motor using different soft computing techniques. The soft computing techniques which are considered in the paper are fuzzy system, artificial neural network (ANN), Neuro-Fuzzy, genetic algorithms (GA) and particle swarm optimization (PSO). It is observed that the estimated parameter using soft computing techniques were much closer to actual value.

Keywords

Induction motor, parameter estimation, soft computing techniques, ANN, Neuro-Fuzzy, GA, PSO

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D. K. Chaturvedi ¹, Md. Sharif Iqbal ², Mayank Pratap Singh ², Vikas Pratap Singh ³

Affiliations
1 Professor, Department of Electrical Engineering, DEI Deemed University, Agra, IN
2 PhD Research Scholar, Department of Electrical Engineering, DEI Deemed University, Agra, IN
3 Senior Research Fellow, ERED, CPRI, Bangalore, IN

Abstract

Induction motor is singly excited and brushless,very simple, compact and extremely rugged in construction and most reliable and low cost motor. Although, these motors are reliable but often exposed to hostile environments during its operation which leads to early deterioration leading to the motors failure. Faults and failures of induction machines can lead to excessive downtimes and generate large losses in terms of maintenance and revenues. This paper deals with the study of identification of different type of faults and the health monitoring techniques commonly used in induction motors.

Keywords

Faults, health monitoring, fault diagnostic technique, induction motor.

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