این سایت در حال حاضر پشتیبانی نمی شود و امکان دارد داده های نشریات بروز نباشند
International Journal of Engineering، جلد ۳۴، شماره ۳، صفحات ۷۲۸-۷۳۶
عنوان فارسی
چکیده فارسی مقاله
کلیدواژه‌های فارسی مقاله
عنوان انگلیسی A Life Clustering Framework for Prognostics of Gas Turbine Engines under Limited Data Situations
چکیده انگلیسی مقاله The reliability of data driven prognostics algorithms severely depends on the volume of data. Therefore in case of limited data availability, life estimations usually are not acceptable; because the quantity of run to failure data is not sufficient to train prognostics model efficiently. To board this problem, a life clustering prognostics (LCP) framework is proposed. LCP regenerates the train data at different ages and outcomes to increment of the training data volume. So, the method is useful for limited data conditions. In this research, initially LCP performance is studied in normal situation is; successively robustness of the framework under limited data conditions is considered. For this purpose, a case study on turbofan engines is performed. The accuracy for the proposed LCP approach is 71% and better than other approaches. The prognostics accuracy is compared in various situations of data deficiency for the case study. The prognostic measures remain almost unchanged when the training data is even one third. Successively, prognostics accuracy decreases with a slight slope; so that when the training data drops from 100 to 5%, the accuracy of the results drops 26%. The results indicates the robustness of the proposed algorithm in limited data situation. The main contribution of this paper include: (1) The effectiveness of life clustering idea for use in prognostics algorithms is proven; (2) A step-by-step framework for LCP is provided; (3) A robustness analysis is performed for the proposed prognostics algorithm.
کلیدواژه‌های انگلیسی مقاله Prognosis and health management,Remaining useful life estimation,robustness,Limited data
نویسندگان مقاله A. Mahmoodian |
Mechanical Engineering Department, Sharif University of Technology, Tehran, Iran

M. Durali |
Mechanical Engineering Department, Sharif University of Technology, Tehran, Iran

M. Saadat |
ECE Faculty, Tehran University, Tehran, Iran

T. Abbasian |
ECE Faculty, Tehran University, Tehran, Iran

نشانی اینترنتی https://www.ije.ir/article_126153_84f36c3a7591909a534a45cdd50b85a0.pdf
فایل مقاله فایلی برای مقاله ذخیره نشده است
کد مقاله (doi)
زبان مقاله منتشر شده en
موضوعات مقاله منتشر شده
نوع مقاله منتشر شده
برگشت به: صفحه اول پایگاه   |   نسخه مرتبط   |   نشریه مرتبط   |   فهرست نشریات