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Journal Articles

Accelerometer-Based Combustion Metrics Reconstruction With Radial Basis Function Neural Network for a 9 L Diesel Engine

Libin Jia, Jeffrey Naber, Jason Blough, Seyed Alireza Zekavat
Journal: Journal of Engineering for Gas Turbines and Power
Publisher: ASME
Article Type: Research-Article
J. Eng. Gas Turbines Power. March 2014, 136(3): 031507.
Paper No: GTP-13-1231
https://doi.org/10.1115/1.4025886
Published Online: November 19, 2013
... that the modified Gram–Schmidt method achieved much more accurately estimated combustion metrics with the highest efficiency. On the basis of this study, a real-time closed-loop control strategy was proposed with the feedback provided based on the application of the trained RBFNN. diesel engine acceleration...
View Articletitled, Accelerometer-Based Combustion Metrics Reconstruction With Radial Basis Function Neural Network for a 9 L Diesel Engine
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Topics: Accelerometers, Combustion, Diesel engines, Radial basis function networks, Signals, Engines, Cylinders, Noise (Sound), Pressure