کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
10403550 | 892345 | 2005 | 6 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
USE OF AN AUTOASSOCIATIVE NEURAL NETWORK FOR DYNAMIC DATA RECONCILIATION
دانلود مقاله + سفارش ترجمه
دانلود مقاله ISI انگلیسی
رایگان برای ایرانیان
کلمات کلیدی
موضوعات مرتبط
مهندسی و علوم پایه
سایر رشته های مهندسی
مکانیک محاسباتی
پیش نمایش صفحه اول مقاله
![عکس صفحه اول مقاله: USE OF AN AUTOASSOCIATIVE NEURAL NETWORK FOR DYNAMIC DATA RECONCILIATION USE OF AN AUTOASSOCIATIVE NEURAL NETWORK FOR DYNAMIC DATA RECONCILIATION](/preview/png/10403550.png)
چکیده انگلیسی
The technique of dynamic data reconciliation has been previously studied in the literature and shown to be an effective tool to better estimate the true values of process variables by using information from both measured values and process models. Real-time implementation of dynamic data reconciliation involves solving complex optimization problem, leading to large computation time. This paper presents a study on the use of a dynamic Autoassociative Neural Network (AANN) for dynamic data reconciliation. Once trained, the AANN can be directly used for online signal validation. Closed-loop performance of the AANN for both linear and nonlinear processes was evaluated using simulations of two storage tank processes. The AANN provided accurate estimates of measured values for the two processes studied in this investigation.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: IFAC Proceedings Volumes - Volume 38, Issue 1, 2005, Pages 65-70
Journal: IFAC Proceedings Volumes - Volume 38, Issue 1, 2005, Pages 65-70
نویسندگان
Shuanghua Bai, Jules Thibault, David D. McLean,