کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
6955303 1451858 2016 14 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Sequential state estimation of nonlinear/non-Gaussian systems with stochastic input for turbine degradation estimation
ترجمه فارسی عنوان
تخمین وضعیت توالی سیستم های غیرخطی / غیر غایی با ورودی تصادفی برای تخمین تخریب توربین
کلمات کلیدی
سیستم دینامیک، شناسایی سیستم، ورودی تصادفی، برآورد دولت، فیلتر ذرات چند متغیره، تخریب توربین،
موضوعات مرتبط
مهندسی و علوم پایه مهندسی کامپیوتر پردازش سیگنال
چکیده انگلیسی
Health state estimation of inaccessible components in complex systems necessitates effective state estimation techniques using the observable variables of the system. The task becomes much complicated when the system is nonlinear/non-Gaussian and it receives stochastic input. In this work, a novel sequential state estimation framework is developed based on particle filtering (PF) scheme for state estimation of general class of nonlinear dynamical systems with stochastic input. Performance of the developed framework is then validated with simulation on a Bivariate Non-stationary Growth Model (BNGM) as a benchmark. In the next step, three-year operating data of an industrial gas turbine engine (GTE) are utilized to verify the effectiveness of the developed framework. A comprehensive thermodynamic model for the GTE is therefore developed to formulate the relation of the observable parameters and the dominant degradation symptoms of the turbine, namely, loss of isentropic efficiency and increase of the mass flow. The results confirm the effectiveness of the developed framework for simultaneous estimation of multiple degradation symptoms in complex systems with noisy measured inputs.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Mechanical Systems and Signal Processing - Volumes 72–73, May 2016, Pages 32-45
نویسندگان
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