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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
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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
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