Title :
Application Research on Fault Diagnosis System of Mine Rotating Machinery Based on ANN
Author :
Wenshang, Xu ; Qingming, Yu ; Feng, Zhang ; Yanliang, Sun
Author_Institution :
ICEE Shan Dong Univ. of Sci. & Technol., Qingdao
Abstract :
This paper improves the basic LMBP algorithm with numerical analysis method and brings it into the mine rotating machinery fault diagnosis system. Compared with the basic algorithm, the improved algorithm can ameliorates the training speed and diagnosis reliability. On this basis, we introduce the designation scheme of data collection board based on ARM and VxWorks and the operation interface based on Borland C++ Builder summarily; and take the hydraulic station of one rotating machinery of Xin-ji company as the research object to carry through the spot simulations in the lab. The simulated results indicate that the stability of hardware, the training speed of ANN and the diagnosis capacities are good.
Keywords :
electric machines; fault diagnosis; mining equipment; neural nets; ANN; ARM; Borland C++ Builder; LMBP algorithm; VxWorks; data collection; designation scheme; diagnosis capacities; fault diagnosis system; mine rotating machinery; numerical analysis; spot simulations; Algorithm design and analysis; Diagnostic expert systems; Fault diagnosis; Fuzzy control; Instruments; Machinery; Neural networks; Product safety; Stability; Wavelet analysis; LMBP; rotating machinery; square root method;
Conference_Titel :
Electronic Measurement and Instruments, 2007. ICEMI '07. 8th International Conference on
Conference_Location :
Xi´an
Print_ISBN :
978-1-4244-1136-8
Electronic_ISBN :
978-1-4244-1136-8
DOI :
10.1109/ICEMI.2007.4350973
