کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
688723 1460366 2016 12 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
A novel process monitoring and fault detection approach based on statistics locality preserving projections
ترجمه فارسی عنوان
نظارت بر فرآیند جدید و روش تشخیص خطا بر اساس آمار مکان حفظ پیش بینی ها
کلمات کلیدی
تجزیه و تحلیل الگوی آمار، محل نگهداری پیش بینی ها، نظارت بر فرآیند، تجزیه و تحلیل موازی، تشخیص گسل
موضوعات مرتبط
مهندسی و علوم پایه مهندسی شیمی تکنولوژی و شیمی فرآیندی
چکیده انگلیسی


• Statistics locality preserving projections (SLPP) is proposed for process monitoring and fault detection.
• SPA is applied to grasp the non-Gaussian statistical property.
• LPP method is used to discover local manifold structure of the process statistics.
• Parallel analysis is introduced to retain the number of latent variables for LPP and SLPP.

Data-driven fault detection technique has exhibited its wide applications in industrial process monitoring. However, how to extract the local and non-Gaussian features effectively is still an open problem. In this paper, statistics locality preserving projections (SLPP) is proposed to extract the local and non-Gaussian features. Firstly, statistics pattern analysis (SPA) is applied to construct process statistics and grasp the non-Gaussian statistical property using high order statistics. Then, locality preserving projections (LPP) method is used to discover local manifold structure of the statistics. In essence, LPP tries to map the close points in the original space to close in the low-dimensional space. Lastly, T2 and squared prediction error (SPE) charts of SLPP model are used to detect process faults. One simple simulated system and the Tennessee Eastman process show that the proposed SLPP method is more effective than principal component analysis, LPP and statistics principal component analysis in fault detection performance.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Journal of Process Control - Volume 37, January 2016, Pages 46–57
نویسندگان
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