dc.contributor | Asia Turbomachinery & Pump Symposium (2nd : 2021) | |
dc.creator | Ahmad Asnawi, Khairul Fata b | |
dc.creator | Omar, Azreel Zairee b | |
dc.date.accessioned | 2023-02-23T20:10:39Z | |
dc.date.available | 2023-02-23T20:10:39Z | |
dc.date.issued | 2021 | |
dc.identifier.uri | https://hdl.handle.net/1969.1/197481 | |
dc.description | Technical Briefs | |
dc.description.abstract | There is abundance of machinery performance data available nowadays due to recent development ofsensors and computational powerUsually those data left to complex/ advance tools (special software) and technique (AI, MachineLearning) for analysisHowever, operator also should be able to practically manipulate and analyze those data to come-outwith useful information to help decision processThis presentation elaborate how to perform data driven analysis on available data with existing tooland knowledge | |
dc.format.medium | Electronic | |
dc.format.mimetype | application/pdf | |
dc.language.iso | en | |
dc.publisher | Turbomachinery Laboratory, Texas A&M Engineering Experiment Station | |
dc.relation.ispartof | Asia Turbomachinery & Pump Symposia. 2021 Proceedings | |
dc.title | TB14: A Practical Data-Driven Analysis Case Studies for Gas Turbine Operators | |
dc.type.genre | conference publication | |
dc.type.material | Text | |
dc.format.digitalOrigin | born digital | |