کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
10385744 | 882661 | 2005 | 11 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Fault Diagnosis by Qualitative Trend Analysis of the Principal Components
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کلمات کلیدی
موضوعات مرتبط
مهندسی و علوم پایه
مهندسی شیمی
تصفیه و جداسازی
پیش نمایش صفحه اول مقاله
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چکیده انگلیسی
Qualitative trend analysis (QTA) is a data-driven semi-quantitative technique that has been used for process monitoring and fault detection and diagnosis (FDD). Though QTA provides quick and accurate diagnosis-the increase in computational complexity of QTA with the increase in the number of sensors used for diagnosis-may prohibit its real-time application for very large-scale plants. In most of the chemical plants, the measurements are highly redundant and this redundancy can be exploited by performing principal component analysis (PCA) on the measured data. In this paper, we present a PCA-QTA technique for fault diagnosis (FD) in large-scale plants. Essentially, QTA is applied on the principal components rather than on the sensor data. The proposed approach is tested on the Tennessee Eastman (TE) process. The reduction in computational complexity in trend-extraction is about 40%. This reduction in computational complexity is expected to increase considerably for larger processes.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Chemical Engineering Research and Design - Volume 83, Issue 9, September 2005, Pages 1122-1132
Journal: Chemical Engineering Research and Design - Volume 83, Issue 9, September 2005, Pages 1122-1132
نویسندگان
M.R. Maurya, R. Rengaswamy, V. Venkatasubramanian,