Research on Dynamic Measurement System for Bulk Material Based on Machine Vision

Ping Li; Yan Wen Wang; Cong Xu

doi:10.4028/www.scientific.net/AMM.273.768

Paper Titles

A Study of the Linear Quadratic Type’s Optimal Control over the Micro-Vibration of Coupled-Pendulums with the External Force
p.750

A Hardware Design of Fish Tank Intelligent Purification System
p.755

Design of Parameter Adaptive Fuzzy Controller for the Planar Double Inverted Pendulum
p.759

Hybrid Electric Vehicle Energy Management and Control Based on Battery Energy Balance
p.764

Research on Dynamic Measurement System for Bulk Material Based on Machine Vision
p.768

The Application of Artificial Immune System in Mechanical Engineering for Constrained Optimization
p.775

Research of Robocop Simulation Platform for Robot Soccer
p.780

Adaptive Error Concealment Technology Based on H.264 for Digital Satellite Set-Top Boxes
p.784

New Compound Method for Target Recognition and Tracking
p.790

HomeApplied Mechanics and MaterialsApplied Mechanics and Materials Vol. 273Research on Dynamic Measurement System for Bulk...

Research on Dynamic Measurement System for Bulk Material Based on Machine Vision

Abstract:

In order to improve measurement accuracy and reduce maintenance work of dynamic measurement system, research is proposed on non-contract measurement method based on machine vision. To choose real-time measurement system of mining car as test object, and use binocular vision to calculate 3 D coordinates of contour, and obtain the values of volume and weight with material through operation. Test platform and work flow is designed in detail. A calibration method combined the advantages of optical calibration with camera calibration itself is proposed. To simplify the extraction and matching of feature points through using structured light. Test results show that this method can effectively improve the accuracy of dynamic measurement system for bulk material.

You might also be interested in these eBooks

Manufacturing and Engineering Developments

View Preview

Info:

Periodical:

Applied Mechanics and Materials (Volume 273)

Pages:

768-772

DOI:

https://doi.org/10.4028/www.scientific.net/AMM.273.768

Citation:

Cite this paper

Online since:

January 2013

Authors:

Ping Li, Yan Wen Wang, Cong Xu

Keywords:

Bulk Material, Calibration, Dynamic Measurement, Feature Point, Machine Vision

Export:

RIS, BibTeX

Price:

Permissions CCC:

Request Permissions

Permissions PLS:

Request Permissions

Сopyright:

Citation:

References

[1] SUN Ji-ping, DENG Guo-hua, LI Wei: The MT 1082-2008 general technical requirements of the remote monitoring system for the output of coal [S]. Beijing: Coal Industry Press, (2009).

Google Scholar

[2] WANG Wen-qing, WANG Mu, REN An-xiang, TIAN Bo-lin, LI Ping etc.: Measurement and monitoring system of mining car based on image processing: China, ZL 200910242876. 6 [P], 2009-12-18.

Google Scholar

[3] Brown M Z, Burschka D, Hager G D: Advances in computational stereo [J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2003, 25(8): 993-1008.

DOI: 10.1109/tpami.2003.1217603

Google Scholar

[4] Malan Sonka, Vaclav Hlavac, Roger Boyle: Image processing, analysis, and machine vision third edition [M]. Beijing: Tsinghua University Press, (2011).

Google Scholar

[5] Wu Fu-chao, Li Hua, Hu Zhan-yi: A new camera self-calibration method based on active vision system [J]. Chinese Journal of Computers, 2000, 23(11): 1130-1139.

Google Scholar

[6] ZHANG Zheng-you: A flexible new technique for camera calibration [J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2000, 22(11): 1330-1334.

DOI: 10.1109/34.888718

Google Scholar

[7] WU Wen-hui, SU Xiao-long, SUN Tong-feng: Stereo matching algorithm in dynamic image feature space [J]. Computer Engineering and Applications, 2011, 47(11): 178-181.

Google Scholar

[8] Carsten Steger, Markus Ulrich, Christian Wiedemann: Machine vision algorithms and applications [M]. Tsinghua University Press, (2008).

Google Scholar