Yuliza, Yuliza and Muwardi, Rachmat and Widya Pratama, Danang and Santoso, Makmur Heri and Yunita, Mirna (2022) Modification of Control Oil Feeding with PLC Using Simulation Visual Basic and Neural Network Analysis. [Artikel Dosen]
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Modification of Control Oil Feeding with PLC Using Simulation Visual Basic and Neural Network Analysis.pdf - Published Version Restricted to Registered users only Download (1MB) |
Abstract
The oil feeding system is an oil distribution system used in engine lubrication by flowing it directly to the engine parts to be lubricated through pipes. In addition, it is also a raw material for the production process by collecting the oil first in the storage tank, then weighing it on the oil scale before use in the production process. The current control is still using the conventional model. The operating system is still manual, and the absence of identity and damage information makes it difficult for the engineer to troubleshoot. The research method is to modify the oil feeding system control using PLC (Programmable Logic Controller) and Visual Basic to display process information. This process uses the Neural Network (NN) method. The simulation results show that the PLC program and visual basic software can be connected properly. The speed of the data transfer test connection that can be obtained is 32 ms. The prediction process of the oil feeding system using the backpropagation algorithm Neural Network and the activation function, which uses the binary sigmoid function (logsig) with the 17-10-1 architecture having very good performance getting the MSE value below the error value of 0.001 maximum epoch 961 and hidden layer 10 with an MSE value of 0.00099915.
| Item Type: | Artikel Dosen |
|---|---|
| Subjects: | T Technology > TK Electrical engineering. Electronics Nuclear engineering |
| Divisi / Prodi: | Faculty of Industrial Technology (Fakultas Teknologi Industri) > S1-Electrical Engineering (S1-Teknik Elektro) |
| Depositing User: | M.Eng. Alfian Ma'arif |
| Date Deposited: | 30 Jan 2023 05:57 |
| Last Modified: | 30 Jan 2023 05:57 |
| URI: | http://eprints.uad.ac.id/id/eprint/37424 |
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