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2007

A systematic approach for soft sensor development

8 years 9 months ago
A systematic approach for soft sensor development
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 i...
Bao Lin, Bodil Recke, Jørgen K. H. Knudsen,
Added 12 Dec 2010
Updated 12 Dec 2010
Type Journal
Year 2007
Where CCE
Authors Bao Lin, Bodil Recke, Jørgen K. H. Knudsen, Sten Bay Jørgensen
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