Fault detection and experiment research of remanufacturing automatic transmission based on BP neural network

Author

Lin, Qiong ; Dai, Zhong-hao ; Meng, Bin

Author_Institution

Coll. of Mech. Eng., Zhejiang Univ. of Technol., Hangzhou, China

fYear

2011

fDate

16-18 Sept. 2011

Firstpage

191

Lastpage

194

Abstract

Detection and reliability of remanufacturing automatic transmission is an important step in the remanufacturing process, the article draws attention to the vibration detection system based on BP neural network By means of extracting the time-domain characteristic data which are taken as inputs for neural network training, a new detection of remanufacturing is realized. Based on an example of the remanufacturing F4A42 transmission, the study suggests that the system can identify the operation status. The result shows that the system is effective and feasible.

Keywords

backpropagation; fault tolerance; neural nets; power transmission (mechanical); production engineering computing; recycling; reliability; vibrations; BP neural network; F4A42 transmission; backpropagation; fault detection; neural network training; reliability; remanufacturing automatic transmission; remanufacturing detection; remanufacturing process; time-domain characteristic data; vibration detection system; Educational institutions; Fault detection; Feature extraction; MATLAB; Time domain analysis; Training; Vibrations; automatic transmission; neural network; remanufacturing; vibration detection;

fLanguage

English

Publisher

ieee

Conference_Titel

Electrical and Control Engineering (ICECE), 2011 International Conference on

Conference_Location

Yichang

Print_ISBN

978-1-4244-8162-0

Type

conf

DOI

10.1109/ICECENG.2011.6057130

Filename

6057130