TITLE:
Fault Prediction of Elevator Door System Based on PSO-BP Neural Network
AUTHORS:
Penggao Wen, Meng Zhi, Guangyao Zhang, Shengmao Li
KEYWORDS:
Elevator Door System, Gate System Fault, Fault Prediction, PSO-BP Neural Network
JOURNAL NAME:
Engineering,
Vol.8 No.11,
October
31,
2016
ABSTRACT: Nowadays, the elevator has become an indispensable means of indoor transportation in people’s life, but in recent years this kind of traffic tools has caused many casualties because of the gate system fault. In order to ensure the safe and reliable operation of the elevator, the failure of elevator door system was predicted in this paper. Against the fault type of elevator door system: elevator door opened, excessive vibration when elevator door opened or closed, elevator door did not open or closed when reached the specified level. Three fault types were used as the output of the prediction model. There were 8 reasons for the failure, used them as input. A model based on particle swarm optimization (PSO) and BP neural network was established, using MATLAB to emulation; the results showed that: PSO-BP neural network algorithm was feasible in the fault prediction of the elevator door system.