Online Monitoring and Analysis of Lube Oil Degradation for Gas Turbine Engine using Recurrent Neural Network (RNN)
Lubrication is one of the important aspects of the engine that will impact the overall performance of the gas turbine engine. Degradation of oil is usually known by offline analysis that use oil sample to check some properties and contaminant. The offline analysis will take a longer time, as needed...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
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Program Studi Teknik Informatika Universitas Trilogi
2022-06-01
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| Series: | JISA (Jurnal Informatika dan Sains) |
| Subjects: | |
| Online Access: | https://trilogi.ac.id/journal/ks/index.php/JISA/article/view/1108 |
| Summary: | Lubrication is one of the important aspects of the engine that will impact the overall performance of the gas turbine engine. Degradation of oil is usually known by offline analysis that use oil sample to check some properties and contaminant. The offline analysis will take a longer time, as needed to collect the sample, send it to the laboratory, analyze the sample and create the report. The purpose of this research is to analyze oil parameters in real-time so can predict oil degradation. Sensors and transducers installed on the lube oil system can read some parameters of the oil then transmit easily to the server. The method that will use in this paper is Recurrent Neural Network (RNN) with multi-step Long Short Term Memory (LSTM). The result of this paper will predict oil degradation on the future operation of gas turbine engine. |
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| ISSN: | 2776-3234 2614-8404 |