The Open Mechanical Engineering Journal

2014, 8 : 916-921
Published online 2014 December 31. DOI: 10.2174/1874155X01408010916
Publisher ID: TOMEJ-8-916

Research of Fault Diagnosis of Belt Conveyor Based on Fuzzy Neural Network

Yuan Yuan , Wenjun Meng and Xiaoxia Sun
School of Transportation & Logistics, Taiyuan University of Science and Technology, Taiyuan 030024, China.

ABSTRACT

To address deficiencies in the process of fault diagnosis of belt conveyor, this study uses a BP neural network algorithm combined with fuzzy theory to provide an intelligent fault diagnosis method for belt conveyor and to establish a BP neural network fault diagnosis model with a predictive function. Matlab is used to simulate the fuzzy BP neural network fault diagnosis of the belt conveyor. Results show that the fuzzy neural network can filter out unnecessary information; save time and space; and improve the fault diagnosis recognition, classification, and fault location capabilities of belt conveyor. The proposed model has high practical value for engineering.

Keywords:

Belt conveyor, BP neural network, fault diagnosis, fuzzy theory.