TY - GEN
T1 - Computer Vision Measurement System for Measuring Elasticity Modulus of Straws
AU - Fan, Yindong
AU - Wen, Jingqian
AU - Hu, Yaoguang
N1 - Publisher Copyright:
© 2019 IEEE.
PY - 2019/7
Y1 - 2019/7
N2 - The elasticity modulus of the straw is one of the most important parameters for the adjustment of the reel in the harvester. In order to measure the elasticity modulus of straw rapidly, a computer vision measurement system based on the cantilever beam method has been developed in this research. In the measuring process, the extra weight was suspended on the straw to exert force on the straw. The computer vision measurement system analyzed the image of straw under external force, and worked out the elasticity modulus with the nonlinear deflection differential equation. The computer vision algorithm was implemented using C/C++ with the open source computer vision library (opencv3.1.0) on the platform visual studio 2015. According to the verification experiments, the accuracy of computer vision measurement system was verified. The average error between universal testing machine and computer vision measurement system was 3.735%. The results seems acceptable. What's more, it appears that this system was more efficient than universal testing machine.
AB - The elasticity modulus of the straw is one of the most important parameters for the adjustment of the reel in the harvester. In order to measure the elasticity modulus of straw rapidly, a computer vision measurement system based on the cantilever beam method has been developed in this research. In the measuring process, the extra weight was suspended on the straw to exert force on the straw. The computer vision measurement system analyzed the image of straw under external force, and worked out the elasticity modulus with the nonlinear deflection differential equation. The computer vision algorithm was implemented using C/C++ with the open source computer vision library (opencv3.1.0) on the platform visual studio 2015. According to the verification experiments, the accuracy of computer vision measurement system was verified. The average error between universal testing machine and computer vision measurement system was 3.735%. The results seems acceptable. What's more, it appears that this system was more efficient than universal testing machine.
KW - computer vision measurement system
KW - elasticity modulus
KW - mechanics of materials
KW - straw
UR - http://www.scopus.com/inward/record.url?scp=85084317181&partnerID=8YFLogxK
U2 - 10.1109/ICIVC47709.2019.8981311
DO - 10.1109/ICIVC47709.2019.8981311
M3 - Conference contribution
AN - SCOPUS:85084317181
T3 - 2019 IEEE 4th International Conference on Image, Vision and Computing, ICIVC 2019
SP - 45
EP - 49
BT - 2019 IEEE 4th International Conference on Image, Vision and Computing, ICIVC 2019
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 4th IEEE International Conference on Image, Vision and Computing, ICIVC 2019
Y2 - 5 July 2019 through 7 July 2019
ER -