کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
5004121 1461187 2017 8 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Double-layer ensemble monitoring of non-gaussian processes using modified independent component analysis
ترجمه فارسی عنوان
گروه دو لایه نظارت بر فرآیندهای غزایی با استفاده از تجزیه و تحلیل اجزای مستقل اصلاح شده
کلمات کلیدی
تجزیه و تحلیل جزء مستقل اصلاح شده، تشخیص گسل، یادگیری گروهی
موضوعات مرتبط
مهندسی و علوم پایه سایر رشته های مهندسی کنترل و سیستم های مهندسی
چکیده انگلیسی
The modified independent component analysis (MICA) was proposed mainly to obtain a consistent solution that cannot be ensured in the original ICA algorithm and has been widely investigated in multivariate statistical process monitoring (MSPM). Within the MICA-based non-Gaussian process monitoring circle, there are two main problems, i.e., the selection of a proper non-quadratic function for measuring non-Gaussianity and the determination of dominant ICs for constructing latent subspace, have not been well attempted so far. Given that the MICA method as well as other MSPM approaches are usually implemented in an unsupervised manner, the two problems are always solved by some empirical criteria without respect to enhancing fault detectability. The current work aims to address the challenging issues involved in the MICA-based approach and propose a double-layer ensemble monitoring method based on MICA (abbreviated as DEMICA) for non-Gaussian processes. Instead of proposing an approach for selecting a proper non-quadratic function and determining the dominant ICs, the DEMICA method combines all possible base MICA models developed with different non-quadratic functions and different sets of dominant ICs into an ensemble, and a double-layer Bayesian inference is formulated as a decision fusion method to form a unique monitoring index for online fault detection. The effectiveness of the proposed approach is then validated on two systems, and the achieved results clearly demonstrate its superior proficiency.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: ISA Transactions - Volume 68, May 2017, Pages 181-188
نویسندگان
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