Modelling of turbine blade vibrations via computational intelligence methods

التفاصيل البيبلوغرافية
العنوان:	Modelling of turbine blade vibrations via computational intelligence methods
بيانات النشر:	KTH, Kraft- och värmeteknologi 2017
تفاصيل مُضافة:	Norton, S. Ramsay, T. Karatzas, K. Fridh, Jens E. Petrie-Repar, Paul
نوع الوثيقة:	Electronic Resource
مستخلص:	A method for modelling turbomachine blade vibration events is proposed, based on computational intelligence algorithms. The method utilises steady thermodynamic data and blade tip-timing data to identify high amplitude vibration events and to draw underlying relationships between steady-thermodynamic input channels and resultant blade motion characteristics. Several computational studies probe specific process aspects in order to improve model prediction accuracy and several methods of data-feature reduction are established to further enhance vibration predictions. Overall, the study shows promise of what prediction capabilities can be achieved with seemingly limited instrumentation. Drawbacks in matters of tip-timing interpretation, quality/quantity of data and process limitations are discussed. Consequential future objectives are outlined to envisage onward predictive accuracy. QC 20170815
مصطلحات الفهرس:	Blade tip timing, Blade vibration prediction, Computational intelligence, Health monitoring, Energy Engineering, Energiteknik, Conference paper, info:eu-repo/semantics/conferenceObject, text
DOI:	10.29008.etc2017-083
URL:	http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-211881 12th European Conference on Turbomachinery Fluid Dynamics and Thermodynamics, ETC 2017
الإتاحة:	Open access content. Open access content info:eu-repo/semantics/restrictedAccess
ملاحظة:	English
أرقام أخرى:	UPE oai:DiVA.org:kth-211881 doi:10.29008/etc2017-083 Scopus 2-s2.0-85085849505 1235078500
المصدر المساهم:	UPPSALA UNIV LIBR From OAIster®, provided by the OCLC Cooperative.
رقم الأكسشن:	edsoai.on1235078500
قاعدة البيانات:	OAIster

الوصف
DOI:	10.29008.etc2017-083