کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
6595543 458533 2014 47 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
A probabilistic self-validating soft-sensor with application to wastewater treatment
ترجمه فارسی عنوان
یک سنسور نرم با قابلیت اطمینان احتمالی خود را با استفاده از تصفیه فاضلاب
کلمات کلیدی
سنسور نرم فاضلاب، خود تایید، تجزیه و تحلیل اجزای اصلی متغیر بایس، ماشین بردار مربوطه،
موضوعات مرتبط
مهندسی و علوم پایه مهندسی شیمی مهندسی شیمی (عمومی)
چکیده انگلیسی
In the wastewater treatment plants (WWTPs), soft sensors are viewed as a simple signal estimator for hard-to-measure quantities. However, the presence of unreliable data, coupled with increasing demands for measurement quality assurance, has rendered inadequate such a simplistic view. In this paper, a probabilistic self-validating soft-sensor is proposed with the capability of performing self-diagnostics, self-reconstruction and online uncertainty measurement. In this framework, data collecting for soft-sensor modeling (easy-to-measure data) is validated by a Variational Bayesian Principal Component Analysis (VBPCA) model before performing a soft-sensor model construction. By integrating Relevant Vector Machine (RVM) as a predictive model, not only prediction values are obtained, but also the credibility of information for easy-to-measure and hard-to-measure quantities can be generated. The performance of the proposed soft-sensor is validated through two simulation studies of WWTPs with different process characteristics. The results suggest that the proposed strategy significantly improves the prediction performance.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Computers & Chemical Engineering - Volume 71, 4 December 2014, Pages 263-280
نویسندگان
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