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Adaptive modeling, integrated optimi...

Li, Jia.

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Adaptive modeling, integrated optimization, and control of automotive paint spray processes.

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Adaptive modeling, integrated optimization, and control of automotive paint spray processes./
作者:	Li, Jia.
面頁冊數:	98 p.
附註:	Source: Masters Abstracts International, Volume: 42-06, page: 2266.
Contained By:	Masters Abstracts International42-06.
標題:	Engineering, Chemical. -
電子資源:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=1419690
ISBN:	0496244429

Adaptive modeling, integrated optimization, and control of automotive paint spray processes.
Li, Jia.

Adaptive modeling, integrated optimization, and control of automotive paint spray processes. - 98 p.

Source: Masters Abstracts International, Volume: 42-06, page: 2266.

Thesis (M.S.)--Wayne State University, 2004.

In this thesis, neural network based adaptive modeling, integrated optimization, and control methods are developed specially for improving paint spray operations. A group of data-driven models, which are based on Artificial Neural Networks (ANN), are developed to characterize the complicated process. In modeling, three methodologies are introduced. First, a distribution matrix is developed to divide the large-scale system into a number of subsystems based on vehicle body geometry. Thus, the complex system can be decomposed into a number of sub-tasks in manageable dimensions. Second, a data processing method based on cluster analysis is used to minimize the involvement of large disturbances in training data to enhance the model robustness. Third, an adaptive approach with sample selection function is presented to update the models to fit the time variant operation.

ISBN: 0496244429Subjects--Topical Terms:

1018531
Engineering, Chemical.

Adaptive modeling, integrated optimization, and control of automotive paint spray processes.
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300 $a 98 p.
500 $a Source: Masters Abstracts International, Volume: 42-06, page: 2266.
500 $a Adviser: Yinlun Huang.
502 $a Thesis (M.S.)--Wayne State University, 2004.
520 $a In this thesis, neural network based adaptive modeling, integrated optimization, and control methods are developed specially for improving paint spray operations. A group of data-driven models, which are based on Artificial Neural Networks (ANN), are developed to characterize the complicated process. In modeling, three methodologies are introduced. First, a distribution matrix is developed to divide the large-scale system into a number of subsystems based on vehicle body geometry. Thus, the complex system can be decomposed into a number of sub-tasks in manageable dimensions. Second, a data processing method based on cluster analysis is used to minimize the involvement of large disturbances in training data to enhance the model robustness. Third, an adaptive approach with sample selection function is presented to update the models to fit the time variant operation.
520 $a In addition to modeling, a model-based integrated optimization system is developed for paint spray optimization. The objective function is defined for improving the filmbuild quality and paint transfer efficiency for all the panels on vehicle simultaneously. (Abstract shortened by UMI.)
590 $a School code: 0254.
650 4 $a Engineering, Chemical. $3 1018531
650 4 $a Engineering, Automotive. $3 1018477
650 4 $a Engineering, Industrial. $3 626639
650 4 $a Artificial Intelligence. $3 769149
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