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- W2732786967 abstract "In this study, an artificial neural network is developed to find an error rapidly on pneumatic system. Also the ANN prevents the system versus the failure. The error on the experimental bottle filling plant can be defined without any interference using analog values taken from pressure sensors and linear potentiometers. The sensors and potentiometers are placed on different places of the plant. Neural network diagnosis faults on plant, where no bottle, cap closing cylinder B is not working, bottle cap closing cylinder C is not working, air pressure is not sufficient, water is not filling and low air pressure faults. The fault is diagnosed by artificial neural network with LVQ. It is possible to find an failure by using normal programming or PLC. The reason offing Artificial Neural Network is to give a information where the fault is. However, ANN can be used for different systems. The aim is to find the fault by using ANN simultaneously. In this situation, the error taken place on the pneumatic system is collected by a data acquisition card. It is observed that the algorithm is very capable program for many industrial plants which have mechatronic systems." @default.
- W2732786967 created "2017-07-14" @default.
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- W2732786967 date "2008-01-01" @default.
- W2732786967 modified "2023-09-24" @default.
- W2732786967 title "PNÖMATİK SİSTEMDE GERÇEK ZAMANLI LVQ YAPAY SİNİR AĞI ALGORİTMASI İLE ARIZA TESPİTİ" @default.
- W2732786967 hasPublicationYear "2008" @default.
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