Title :
Research on parameters identification based on adline neural network for characteristic equation of pump
Author :
Wu, Qinghui ; Yu, Zhongdang ; Ding, Shuo ; Yang, Youlin
Author_Institution :
Coll. of Eng., Bohai Univ., Jinzhou, China
Abstract :
The digitization of the pump characteristic curve between lift and flow rate is crucial for state detection, fault diagnosis and optimal control of large watering and drainage system in modern industry. In this paper, the characteristic equation of pump is analyzed, an adline neural network is designed for parameters identification for the pump characteristic equation. The proposed scheme solves the question how to measure the characteristic equation in arbitrary speed, raises the identification precise with adaptive filtering, learning, and approaching function of adline neural network. The experiment results confirm its feasibility and effectiveness.
Keywords :
mechanical engineering computing; neural nets; parameter estimation; pumps; adaptive filtering; adline neural network; drainage system; fault diagnosis; learning; optimal control; parameters identification; pump characteristic curve; pump characteristic equation; state detection; watering system; Biological neural networks; Equations; Fitting; Frequency measurement; Pumps; Training; Vectors;
Conference_Titel :
Advanced Computational Intelligence (IWACI), 2011 Fourth International Workshop on
Conference_Location :
Wuhan
Print_ISBN :
978-1-61284-374-2
DOI :
10.1109/IWACI.2011.6160070