Turbine back pressure identification and optimization with learning neural networks

Anoop Mathur, Tariq Samad, Ken Anderson, R. Jerome Brandt, Dan Nordell, Linda Pieper

Research output: Contribution to journalConference articlepeer-review

2 Scopus citations


Neural networks have recently generated much interest because of their adaptability, massive parallelism and robustness. The interest is no longer confined to academic research; several applications have been fielded. The features of neural networks could provide desirable characteristics for many applications in the utility industry. We first provide a general overview of neural network technology, focussing on the aspect most relevant for near-term applications - supervised learning. Then we discuss in some detail a particular application of supervised learning neural networks that we are jointly investigating - the identification and optimization of exhaust condenser pressure of steam turbines.

Original languageEnglish (US)
Pages (from-to)229-236
Number of pages8
JournalAdvances in Instrumentation, Proceedings
Issue numberpt 1
StatePublished - Dec 1 1990
EventProceedings of the ISA '90 International Conference and Exhibition Part 4 (of 4) - New Orleans, LA, USA
Duration: Oct 14 1990Oct 18 1990


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