An advanced performance-based method for soft and abrupt fault diagnosis of industrial gas turbines

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dc.contributor.authorChen, Yu-Zhi
dc.contributor.authorZhang, Wei-Gang
dc.contributor.authorTsoutsanis, Elias
dc.contributor.authorZhao, Junjie
dc.contributor.authorTam, Ivan C. K.
dc.contributor.authorGou, Lin-Feng
dc.date.accessioned2025-06-11T14:19:09Z
dc.date.available2025-06-11T14:19:09Z
dc.date.freetoread2025-06-11
dc.date.issued2025-04-15
dc.date.pubOnline2025-03-10
dc.description.abstractIntegrating gas turbines with intermittent renewable energy must operate for prolonged periods under transient conditions. Existing research on fault diagnosis in such systems has concentrated on the primary rotating components in steady-state conditions. There is a gap in investigating the interplay between shaft bearing failure and performance metrics, as well as fault identification under transient conditions. This study aims to identify faults not only in the main rotating components but also in the shaft bearings under transient conditions. Firstly, the performance model and fault propagation model of gas turbines are established, and the influence of bearing fault on the whole engine performance is analysed. Then, the fault diagnosis method is determined and the dynamic effects are compensated in fault identification at each time interval. Finally, the steady-state and transient fault diagnosis are carried out considering the constant and sudden faults for the main rotating components and bearings. The average run time and maximum error during the engine life cycle are 0.1064 s and 0.0086 %. For the proposed dynamic effects compensation method, the average computation time and peak error at every moment are 0.1152 s and 0.0143 %, clearly superior to the benchmark method. These results provide evidence that the proposed method can correctly diagnose the fault of the main rotating components and shaft bearings under transient conditions. Therefore, the findings mark an advancement in real-time fault diagnostic techniques, ultimately enhancing engine availability while upholding secure and affordable energy production.
dc.description.journalNameEnergy
dc.description.sponsorshipThe authors acknowledge the support of the Propulsion and Space Research Center (PSRC) of the Technology Innovation Institute (TII) in Abu Dhabi, United Arab Emirates.
dc.identifier.citationChen Y-Z, Zhang W-G, Tsoutsanis E, et al., (2025) An advanced performance-based method for soft and abrupt fault diagnosis of industrial gas turbines. Energy, Volume 321, April 2025, Article number 135358en_UK
dc.identifier.eissn1873-6785
dc.identifier.elementsID565789
dc.identifier.issn0360-5442
dc.identifier.paperNo135358
dc.identifier.urihttps://doi.org/10.1016/j.energy.2025.135358
dc.identifier.urihttps://dspace.lib.cranfield.ac.uk/handle/1826/24022
dc.identifier.volumeNo321
dc.languageEnglish
dc.language.isoen
dc.publisherElsevieren_UK
dc.publisher.urihttps://www.sciencedirect.com/science/article/pii/S036054422501000X?via%3Dihub
dc.rightsAttribution 4.0 Internationalen
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/
dc.subjectGas turbine deteriorationen_UK
dc.subjectContinuous gas path analysisen_UK
dc.subjectReal-timeen_UK
dc.subjectMain rotating components faulten_UK
dc.subjectShaft bearing faulten_UK
dc.subject4007 Control Engineering, Mechatronics and Roboticsen_UK
dc.subject40 Engineeringen_UK
dc.subject4010 Engineering Practice and Educationen_UK
dc.subject7 Affordable and Clean Energyen_UK
dc.subject13 Climate Actionen_UK
dc.subjectEnergyen_UK
dc.subject4008 Electrical engineeringen_UK
dc.subject4012 Fluid mechanics and thermal engineeringen_UK
dc.subject4017 Mechanical engineeringen_UK
dc.titleAn advanced performance-based method for soft and abrupt fault diagnosis of industrial gas turbinesen_UK
dc.typeArticle
dc.type.subtypeJournal Article
dcterms.dateAccepted2025-02-28

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