Measurement selections for multicomponent gas path diagnostics using analytical approach and measurement subset concept / Mohd Shahrizal Jasmani in Transactions of the ASME . Journal of engineering for gas turbines and power, Vol. 133 N° 11 (Novembre 2011)  

Public ISBD [article]  inTransactions of the ASME . Journal of engineering for gas turbines and power > Vol. 133 N° 11 (Novembre 2011) . - 10 p. Titre : Measurement selections for multicomponent gas path diagnostics using analytical approach and measurement subset concept Type de document : texte imprimé Auteurs : Mohd Shahrizal Jasmani, Auteur ; Yi-Guang Li, Auteur ; Zaharudin Ariffin, Auteur Année de publication : 2012 Article en page(s) : 10 p. Note générale : Génie Mécanique Langues : Anglais (eng) Mots-clés : Condition monitoring Engines Fault diagnosis Gas turbines Index. décimale : 620.1 Essais des matériaux. Défauts des matériaux. Protection des matériaux Résumé : Gas path analysis (GPA) is a powerful tool to predict gas turbine degradations based on measurement parameters of gas turbine engines. Accordingly, prudent measurement selections are crucial to ensure accurate GPA predictions. This paper is intended to investigate the influence of measurement parameter selection toward the effectiveness of GPA algorithm. An analytical methodology for measurement selection, combined with measurement subset concept, is developed to properly select measurements for multiple component fault diagnosis. The effectiveness of GPA using the measurement sets selected with the introduced measurement selection method are then compared with the results of using standard measurements installed on existing gas turbine engines. A case study applying the new measurement selection method to GPA diagnostic analysis is demonstrated on a three-shaft aeroderivative industrial gas turbine model based on similar unit installed onboard an offshore platform operated by PETRONAS. The engine is modeled and simulated using PYTHIA, a gas turbine performance and diagnostics analysis tool developed by Cranfield University. To validate the findings, nonlinear GPA prediction errors are evaluated in various cases of single and multicomponents faults. As a result, the selected measurements have successfully produced much superior diagnostics accuracies in the fault cases when compared with the standard measurements. These findings proved that proper measurement selection for better GPA diagnostic analysis can be achieved by using the proposed analytical methods. Several engine sensor enhancements are also discussed to accommodate the unique sensor requirements for health diagnostics using GPA. DEWEY : 620.1 ISSN : 0742-4795 En ligne : http://scitation.aip.org/getabs/servlet/GetabsServlet?prog=normal&id=JETPEZ00013 [...] [article] Measurement selections for multicomponent gas path diagnostics using analytical approach and measurement subset concept [texte imprimé] / Mohd Shahrizal Jasmani, Auteur ; Yi-Guang Li, Auteur ; Zaharudin Ariffin, Auteur . - 2012 . - 10 p. Génie Mécanique Langues : Anglais (eng) in Transactions of the ASME . Journal of engineering for gas turbines and power > Vol. 133 N° 11 (Novembre 2011) . - 10 p. Mots-clés : Condition monitoring Engines Fault diagnosis Gas turbines Index. décimale : 620.1 Essais des matériaux. Défauts des matériaux. Protection des matériaux Résumé : Gas path analysis (GPA) is a powerful tool to predict gas turbine degradations based on measurement parameters of gas turbine engines. Accordingly, prudent measurement selections are crucial to ensure accurate GPA predictions. This paper is intended to investigate the influence of measurement parameter selection toward the effectiveness of GPA algorithm. An analytical methodology for measurement selection, combined with measurement subset concept, is developed to properly select measurements for multiple component fault diagnosis. The effectiveness of GPA using the measurement sets selected with the introduced measurement selection method are then compared with the results of using standard measurements installed on existing gas turbine engines. A case study applying the new measurement selection method to GPA diagnostic analysis is demonstrated on a three-shaft aeroderivative industrial gas turbine model based on similar unit installed onboard an offshore platform operated by PETRONAS. The engine is modeled and simulated using PYTHIA, a gas turbine performance and diagnostics analysis tool developed by Cranfield University. To validate the findings, nonlinear GPA prediction errors are evaluated in various cases of single and multicomponents faults. As a result, the selected measurements have successfully produced much superior diagnostics accuracies in the fault cases when compared with the standard measurements. These findings proved that proper measurement selection for better GPA diagnostic analysis can be achieved by using the proposed analytical methods. Several engine sensor enhancements are also discussed to accommodate the unique sensor requirements for health diagnostics using GPA. DEWEY : 620.1 ISSN : 0742-4795 En ligne : http://scitation.aip.org/getabs/servlet/GetabsServlet?prog=normal&id=JETPEZ00013 [...]

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