Gas Turbine Diagnostic Algorithm Testing Using the Software ProDiMES
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| Format: | Artículo científico |
| Langue: | en |
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Universidad Nacional Autónoma de México
2017
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| _version_ | 1876443851872272384 |
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| author | Salvador Felipe-Altamirano |
| author_facet | Salvador Felipe-Altamirano |
| contents | Gas Turbine Diagnostic Algorithm Testing Using the Software ProDiMES Salvador Felipe-Altamirano Igor Loboda Felipe de Jesús Cisneros-Azuara Juan Luis Pérez-Ruiz Ingeniería multi ProDiMES baseline model layer perceptron fault recognition Since gas turbines are very complex and potentially unreliable machines, the improvement of their monitoring sys- tems becomes an essential part. Considering this necessity, the present paper performs a gas turbine diagnostic al- gorithm testing. The methodology proposed is formed by three stages. In the first stage, the commercial software ProDiMES ( Propulsion Diagnostic Method Evaluation Strategy ) is used to simulate an engine fleet and generate data with fault and no-fault conditions. In the second stage, a baseline model testing is implemented to improve the healthy engine performance approximation. Finally, a fault recognition stage based on a pattern recognition techni - que (Multi-Layer Perceptron) performs the diagnosis and calculates the probability of correct diagnostic decisions. The results obtained show that: a) the software ProDiMES is an easy and convenient tool to evaluate gas turbine diagnostic methods, b) the baseline model testing is a key step because it allows reducing the errors that can negati - vely influence the diagnostic process and c) the algorithm correctly performs the fault recognition task. 2017 artículo científico 1405-7743 https://www.redalyc.org/articulo.oa?id=40449649007 en http://www.redalyc.org/revista.oa?id=404 Ingeniería. Investigación y Tecnología application/pdf Universidad Nacional Autónoma de México Ingeniería. Investigación y Tecnología (México) Num.1 Vol.XVIII |
| format | Artículo científico |
| id | redalyc_40449649007 |
| institution | Redalyc |
| language | en |
| publishDate | 2017 |
| publisher | Universidad Nacional Autónoma de México |
| spellingShingle | Gas Turbine Diagnostic Algorithm Testing Using the Software ProDiMES Salvador Felipe-Altamirano Ingeniería multi ProDiMES baseline model layer perceptron fault recognition Gas Turbine Diagnostic Algorithm Testing Using the Software ProDiMES Salvador Felipe-Altamirano Igor Loboda Felipe de Jesús Cisneros-Azuara Juan Luis Pérez-Ruiz Ingeniería multi ProDiMES baseline model layer perceptron fault recognition Since gas turbines are very complex and potentially unreliable machines, the improvement of their monitoring sys- tems becomes an essential part. Considering this necessity, the present paper performs a gas turbine diagnostic al- gorithm testing. The methodology proposed is formed by three stages. In the first stage, the commercial software ProDiMES ( Propulsion Diagnostic Method Evaluation Strategy ) is used to simulate an engine fleet and generate data with fault and no-fault conditions. In the second stage, a baseline model testing is implemented to improve the healthy engine performance approximation. Finally, a fault recognition stage based on a pattern recognition techni - que (Multi-Layer Perceptron) performs the diagnosis and calculates the probability of correct diagnostic decisions. The results obtained show that: a) the software ProDiMES is an easy and convenient tool to evaluate gas turbine diagnostic methods, b) the baseline model testing is a key step because it allows reducing the errors that can negati - vely influence the diagnostic process and c) the algorithm correctly performs the fault recognition task. 2017 artículo científico 1405-7743 https://www.redalyc.org/articulo.oa?id=40449649007 en http://www.redalyc.org/revista.oa?id=404 Ingeniería. Investigación y Tecnología application/pdf Universidad Nacional Autónoma de México Ingeniería. Investigación y Tecnología (México) Num.1 Vol.XVIII |
| title | Gas Turbine Diagnostic Algorithm Testing Using the Software ProDiMES |
| topic | Ingeniería multi ProDiMES baseline model layer perceptron fault recognition |
| url | https://www.redalyc.org/articulo.oa?id=40449649007 |