Study on Data Fusion Algorithms of Hot-Pressing Measurement Process of Wood-Based Panels

Hai Ying Yu; Jun Hua; Xiu Li Zhou; Jiu Yang Hou

doi:10.4028/www.scientific.net/AMM.740.547

Paper Titles

A Study of 3d Coordinate Measuring Based on Binocular Stereo Vision
p.531

Headlight Detection and Error Correction of Measurement Data
p.535

Measuring Method on the Relative Position between the Rack and the Missile with T-Drawbar
p.539

Review of Vision Inspection Technology for Surface Defect of Steel Bar
p.543

Study on Data Fusion Algorithms of Hot-Pressing Measurement Process of Wood-Based Panels
p.547

Study on Examination Method of Striation Marks Based on Fractal Theory
p.553

Exciting Force Source Identification Technology for Underwater Elastic Structure by MFP
p.557

An Improved l₁ Tracker for Transportation Vehicle Tracking
p.562

Development of New Temperature Sensing Cable and Wireless Data Acquisition System
p.568

HomeApplied Mechanics and MaterialsApplied Mechanics and Materials Vol. 740Study on Data Fusion Algorithms of Hot-Pressing...

Study on Data Fusion Algorithms of Hot-Pressing Measurement Process of Wood-Based Panels

Abstract:

Measurement error often exists during hot pressing of the wood-based panels due to the complex mechanism of the process, technological conditions, environment noises and performance of the sensors. Multi-sensor technology is used for mat temperature and pressure data processing to improve the precision and reliability of data. By determining the information weight coefficient with the corresponding measurement variance of each sensor the weighted least square algorithm is applied to achieve high accuracy of overall estimation. The precision of overall estimation value is preferable than the partial estimation of each sensor. A target recognition frame of control strategy is set, and D-S evidence combination principles and reasoning theory are introduced to select the object of greatest credibility for decision making. The results of experiment demonstrate the effectiveness and reliability of the algorithm.

You might also be interested in these eBooks

View Preview

Info:

Periodical:

Applied Mechanics and Materials (Volume 740)

Pages:

547-552

DOI:

https://doi.org/10.4028/www.scientific.net/AMM.740.547

Citation:

Cite this paper

Online since:

March 2015

Authors:

Hai Ying Yu, Jun Hua*, Xiu Li Zhou, Jiu Yang Hou

Keywords:

Control Strategy Recognition Frame, D-S Evidence Combination, Multi-Sensor Data Fusion, Weighted Least Square Algorithm, Wood-Based Panel

Export:

RIS, BibTeX

Price:

Permissions CCC:

Request Permissions

Permissions PLS:

Request Permissions

Сopyright:

Citation:

* - Corresponding Author

References

[1] Hua Jun, and Hu Wanyi. Wood based panels machinery (In Chinese. Northeast Forestry University Press, Harbin, China 2007).

Google Scholar

[2] Chen Tianquan. Study on hot-pressing temperature, pressure and moisture content variation of large particleboard (In Chinese. Beijing Forestry University, China 2006).

Google Scholar

[3] Peng Dongliang, Wen Chenglin, and Xue Anke. Theory and application of multisensor information fusion. (In Chinese. Science Press, Beijing 2010).

Google Scholar

[4] LUO R C, LIN M, SCHERP R S: IEEE Journal of Robotics and Automation, 1988, 4 (4), p.386–396.

Google Scholar

[5] G. Shafer. A Mathematical Theory of Evidence. (Princeton University Press, Princeton 1976).

Google Scholar