Applied Technology on Artificial Neural Network in Fault Diagnosis System

Qi Zhu; Jian Li

doi:10.4028/www.scientific.net/AMR.859.448

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HomeAdvanced Materials ResearchAdvanced Materials Research Vol. 859Applied Technology on Artificial Neural Network in...

Applied Technology on Artificial Neural Network in Fault Diagnosis System

Abstract:

This paper combined Rumelhart’s adding inertial impulse and dynamically adjusting the learning rate and proposed an improved algorithm to optimize the Back Propagation (BP) networks with applied technology. This improved BP networks is used to determining membership function and applied in fuzzy diagnosing vapor congealing equipment. The application results prove that the improved BP algorithm is effective and the convergence speed is accelerated and is much faster than the classic BP algorithm. The applied technology is very useful in the application course.

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Periodical:

Advanced Materials Research (Volume 859)

Pages:

448-452

DOI:

https://doi.org/10.4028/www.scientific.net/AMR.859.448

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Online since:

December 2013

Authors:

Qi Zhu, Jian Li

Keywords:

Algorithm (GA), Artificial Neural Network (ANN), BP, Fault Diagnosis

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