کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
173091 458575 2011 12 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Multivariate statistical monitoring of the aluminium smelting process
موضوعات مرتبط
مهندسی و علوم پایه مهندسی شیمی مهندسی شیمی (عمومی)
پیش نمایش صفحه اول مقاله
Multivariate statistical monitoring of the aluminium smelting process
چکیده انگلیسی

This paper describes the development of a new ‘cascade’ monitoring system for the aluminium smelting process that uses latent variable models. This system is based on the changes of variability patterns within a feeding cycle which are used to provide indications of faults and their possible causes. The system has been tested offline using 31 data sets. The performance of the system to detect an anode effect has been compared with a typical latent variable model that monitors the change of behaviour at every time instant. The results show that the ‘cascade’ monitoring system is able to detect abnormal events. It was possible to relate each event with specific patterns associated with abnormalities thus facilitating later fault diagnosis.


► Early detection of an anode spike.
► Prediction of an anode effect.
► Detections of problems that may have caused anode effects.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Computers & Chemical Engineering - Volume 35, Issue 11, 15 November 2011, Pages 2457–2468
نویسندگان
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