# zbMATH — the first resource for mathematics

Neural-network based fault diagnosis of hydraulic forging presses in China. (English) Zbl 0913.90136
Summary: 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.

##### MSC:
 90B30 Production models 90B25 Reliability, availability, maintenance, inspection in operations research 68T05 Learning and adaptive systems in artificial intelligence
##### Keywords:
neural networks; fault diagnosis; hydraulic forging presses
Full Text:
##### References:
 [1] DOI: 10.1002/aic.690351210 [2] KNAPP G. M., International Journal of Production Research 30 pp 811– (1992) [3] DOI: 10.1002/aic.690351106 [4] DOI: 10.1007/BF01748629
This reference list is based on information provided by the publisher or from digital mathematics libraries. Its items are heuristically matched to zbMATH identifiers and may contain data conversion errors. It attempts to reflect the references listed in the original paper as accurately as possible without claiming the completeness or perfect precision of the matching.