Study Results from Shanghai University of Electric Power in the Area of Machine Learning Reported (A Novel Machine Learning Based Fault Diagnosis Method for All Gas-path Components of Heavy Duty Gas Turbines With the Aid of Thermodynamic Mo del)

Robotics & Machine Learning Daily News2024，Issue(MAY.14) ：42-43.

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Study Results from Shanghai University of Electric Power in the Area of Machine Learning Reported (A Novel Machine Learning Based Fault Diagnosis Method for All Gas-path Components of Heavy Duty Gas Turbines With the Aid of Thermodynamic Mo del)

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Abstract

By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News - Researchers detail new data in Machine Learning. According to news reporting originating from Shanghai, People’s Repub lic of China, by NewsRx correspondents, research stated, “Heavy-duty gas turbine s are key engines for clean energy utilization and efficient conversion in natur al gas power plants. Gas-path components are the components with the highest fai lure rate in gas turbines, and their faults are highly hidden and destructive.”

Key words

Shanghai/People’s Republic of China/As ia/Cyborgs/Emerging Technologies/Machine Learning/Shanghai University of Ele ctric Power

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出版年

2024

Robotics & Machine Learning Daily News

ISSN：

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