TITLE:
Parameters Estimation of an Electric Fan Using ANN
AUTHORS:
Himanshu Vijay, D. K. Chaturvedi
KEYWORDS:
Artificial Neural Networks, Fan System, Mathematical Modeling, Parameters Estimation
JOURNAL NAME:
Journal of Intelligent Learning Systems and Applications,
Vol.2 No.1,
March
1,
2010
ABSTRACT: Electric Fans are very commonly used in the industries, domestic applications and in tunnels for cooling and ventila-tion purposes. Fan parameters estimation is an important task as far as the reliable operation of a fan system is con-cerned. Basically, a fan is mainly consisting of a single phase induction motor and therefore fan system parameters are essentially the electrical parameters e.g. resistances, reactances and some load parameters (fan blades).These parame-ters often change under varying operating conditions and the knowledge of these parameters is necessary to have opti-mum and efficient operation of the system. Therefore, fan system parameters are required to be estimated. Further, fan system parameters estimation is required to ensure the smooth system operation and to avoid any malfunctioning of the system during abnormal working conditions. In this paper, Artificial Neural Networks (ANN) approach has been used for parameter estimation of a fan system. The simulated and experimental results are compared.