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Keywords: artificial neural network
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Proceedings Papers

Proc. ASME. GT2022, Volume 1: Aircraft Engine; Ceramics and Ceramic Composites, V001T01A009, June 13–17, 2022
Paper No: GT2022-81215
... of artificial neural networks were studied, and parametric models for the representation of performance speedlines were developed. Utilizing the developed approaches, the artificial neural networks were trained for all three compressors to predict their performance with a relative error below 3 %. The trained...
Proceedings Papers

Proc. ASME. GT2021, Volume 6: Ceramics and Ceramic Composites; Coal, Biomass, Hydrogen, and Alternative Fuels; Microturbines, Turbochargers, and Small Turbomachines, V006T19A007, June 7–11, 2021
Paper No: GT2021-58960
... by using open-loop and closed-loop NARX models, which are subsets of artificial neural networks. To set up these models, datasets of significant variables of the gas turbine are used for training, test and validation processes. For this purpose, a comprehensive code is developed in MATLAB programming...
Proceedings Papers

Proc. ASME. GT2020, Volume 5: Controls, Diagnostics, and Instrumentation; Cycle Innovations; Cycle Innovations: Energy Storage, V005T05A023, September 21–25, 2020
Paper No: GT2020-15740
... and prediction of multiple-degraded gas turbine component faults that comprises 3 steps — feature extraction using the Principal Component Analysis (PCA), machine learning classification with a multi-layer perceptron, artificial neural network (MLP-ANN) and model-based fault prediction via the non-linear Gas...
Proceedings Papers

Proc. ASME. GT2004, Volume 2: Turbo Expo 2004, 749-758, June 14–17, 2004
Paper No: GT2004-53914
... 25 11 2008 This paper presents the development of an integrated fault diagnostics model for identifying shifts in component performance and sensor faults using Genetic Algorithm and Artificial Neural Network. The diagnostics model operates in two distinct stages. The first stage uses...