DocumentCode
2569698
Title
Inverse Process Combined with Grey Prediction Model for Estimating the Inner Surface Geometry of Furnace Wall
Author
Su, Chin-Ru ; Liu, Wei-Long ; Chen, Cha O-Kuang
Author_Institution
Dept. of Mech. & Comput.-Aided Eng., Nat. Formosa Univ., Yunlin, Taiwan
fYear
2009
fDate
15-17 May 2009
Firstpage
848
Lastpage
852
Abstract
In this work the inner surface geometry of a cylindrical furnace wall is estimated using inverse process method combined with grey prediction model. In estimating process a virtual area extended from the inner surface of furnace wall is used for analysis. The heat conduction equation and the boundary condition are first discretized by finite difference method to form a linear matrix equation; the inverse model is then optimized by linear least-squares error method and the temperatures of virtual boundary are obtained from a few of measured temperatures in furnace wall using the linear inverse model; and finally the temperature distribution of system is got by direct process and the inner surface geometry of furnace wall can be estimated accordingly. The result shows that using inverse process combined with grey prediction model the geometry can be exactly estimated from relatively small number of measured temperatures.
Keywords
finite difference methods; furnaces; grey systems; heat conduction; least squares approximations; matrix algebra; cylindrical furnace; finite difference method; furnace wall; grey prediction model; heat conduction equation; inner surface geometry; inverse process method; linear least-squares error method; linear matrix equation; Boundary conditions; Difference equations; Finite difference methods; Furnaces; Geometry; Inverse problems; Predictive models; Solid modeling; Temperature distribution; Temperature measurement; Grey prediction; Inverse heat conduction; Reverse matrix; Virtual area;
fLanguage
English
Publisher
ieee
Conference_Titel
2009 International Conference on Signal Processing Systems
Conference_Location
Singapore
Print_ISBN
978-0-7695-3654-5
Type
conf
DOI
10.1109/ICSPS.2009.149
Filename
5166910
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