Study on Fault Diagnosis of Mining Tape Conveyor Based on MPGA-BP

2018 4th International Conference on Environmental Science and Material Application

生态环境科学;材料科学

Yang, Yong^1 ; Cui, Chenchen^1 ; Guo, Xiucai^1

Xi'An University of Science and Technology, Xi'an

710054, China^1

关键词: BP neural networks;    Fast convergence speed;    Fault diagnosis model;    Genetic neural network;    Global search ability;    Multiple swarms;    Protection systems;    Slow convergences;   

Others  :  https://iopscience.iop.org/article/10.1088/1755-1315/252/5/052039/pdf
DOI  :  10.1088/1755-1315/252/5/052039

来源: IOP

【 摘 要 】

In order to detect the malfunction of the mine tape transporter drive device imely, a fault diagnosis model of mine tape transporter based on multiple group genetic neural networks is established by combining multiple swarm genetic algorithms with BP neural network algorithm. The simulation results show that the algorithm can effectively solve the problems such as the easy fall of BP neural network into local minimum value and too many training times, which leads to too slow convergence. The fault diagnosis model has strong global search ability, high training precision and fast convergence speed, and can supplement and perfect the protection system of mine tape conveyor.