Research on soft sensing modeling method of gas turbine’s difficult-to-measure parameters
Author:
Publisher
Springer Science and Business Media LLC
Subject
Mechanical Engineering,Mechanics of Materials
Link
https://link.springer.com/content/pdf/10.1007/s12206-022-0744-z.pdf
Reference25 articles.
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3. P. Kadlec, B. Gabrys and S. Strandt, Data-driven soft sensors in the process industry, Computers and Chemical Engineering, 33(4) (2009) 795–814.
4. M. Tahan, E. Tsoutsanis, M. Muhammad and Z. A. Abdul Karim, Performance-based health monitoring, diagnostics and prognostics for condition-based maintenance of gas turbines: a review, Applied Energy, 198 (2017) 122–144.
5. X. Wang and H. Liu, A knowledge- and data-driven soft sensor based on deep learning for predicting the deformation of an air preheater rotor, IEEE Access, 7 (2019) 159651–159660.
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