کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
173828 458613 2007 7 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
A systematic approach for soft sensor development
موضوعات مرتبط
مهندسی و علوم پایه مهندسی شیمی مهندسی شیمی (عمومی)
پیش نمایش صفحه اول مقاله
A systematic approach for soft sensor development
چکیده انگلیسی

This paper presents a systematic approach based on robust statistical techniques for development of a data-driven soft sensor, which is an important component of the process analytical technology (PAT) and is essential for effective quality control. The data quality is obviously of essential significance for a data-driven soft sensor. Therefore, preprocessing procedures for process measurements are described in detail. First, a template is defined based on one or more key process variables to handle missing data related to severe operation interruptions. Second, a univariate, followed by a multivariate principal component analysis (PCA) approach, is used to detect outlying observations. Then, robust regression techniques are employed to derive an inferential model. A dynamic partial least squares (DPLS) model is implemented to address the issue of auto-correlation in process data and thus to provide smoother estimation than using a static regression model. The proposed methodology is illustrated through applications to a cement kiln system for estimation of variables related to product quality, i.e., free lime, and to emission quality, i.e., nitrogen oxides (NOx) emission. The case studies reveal the effectiveness of the systematic framework in deriving data-driven soft sensors that provide reasonably reliable one-step-ahead predictions.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Computers & Chemical Engineering - Volume 31, Issues 5–6, May 2007, Pages 419–425
نویسندگان
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