Neural-network based fault diagnosis of hydraulic forging presses in China
- 1 July 1995
- journal article
- research article
- Published by Taylor & Francis in International Journal of Production Research
- Vol. 33 (7) , 1939-1951
- https://doi.org/10.1080/00207549508904791
Abstract
The paper describes the utilization of neural networks for fault diagnosis of hydraulic forging presses which may have an impact on the effective utilization of the over 2000 presses in use in China. The technical descriptions of the presses and the 47 major possible faults are presented. For diagnosing these faults the neural network with 30 000 iteration training was utilized and it provided a 99% accuracy in identifying causes of the failures of hydraulic forging presses.Keywords
This publication has 4 references indexed in Scilit:
- Neural-networks-aided fault diagnosis in supervisory control of advanced manufacturing systemsThe International Journal of Advanced Manufacturing Technology, 1993
- Machine fault classification: a neural network approachInternational Journal of Production Research, 1992
- A neural network methodology for process fault diagnosisAIChE Journal, 1989
- Incipient fault diagnosis of chemical processes via artificial neural networksAIChE Journal, 1989