Cao Meili
ABSTRACT
A machine vision-based automatic controlled dividing plates of a grain separator and its control system are designed. The dividing plates of the sieve are equipped with an adjustment device to adjust the location of the dividing plates. After the sieve is turned on, the machine vision acquires the location of the boundary lines of grain, rice and mixture and the location of the dividing plates on the sieve. Based on the difference between the location of the dividing plates and the dividing lines, two high precision screws are controlled to work to adjust the location of the dividing plates to match the dividing lines. The system can adjust the location of the dividing plates in real time or control the location of the dividing lines according to the pre-set time interval. Finally, the system has been tested and proven to be effective.
- Wang Ruiyuan, Zhu Yongyi, Xie Jian, et al. Current status and outlook of China's rice processing industry[J]. Agricultural Machinery 2011(05):1--5.Google Scholar
- Gu Yaochen. Separation technology and grain particle size analysis of grain roughnes[J]. Cereal and Feed Industry 1987(06):10--14+9.Google Scholar
- Liu Silin, Zhu Wenyuan, Wang Dingjun, et al. Improvement of grain separation process[J]. Cereal and Feed Industry.1993, (3):21--23.Google Scholar
- Cheng Guoqiang, Xie Aimin, Liu Dan. Research and Practice for Grain Rough Separation Technology [J]. Cereal and Feed Industry.2013, (4).Google Scholar
- Yang Hai, Yang Ziqiang. Working principle of the gravity separator and analysis of the movement of the material on the separating plate [J]. Technology and Economics, 2015, (30).Google Scholar
- Chen Jin, Gu Yan, Lian Yi, et al. Machine Vision-Based Approach for Online Identification of Rice Impurities and Broken Seeds [J]. Agricultural Engineering 2018, 34 (13):187--194.Google Scholar
- Li Chao, Sun Jun. Algorithm for Detecting and Classifying Weld Defects Based on Machine Vision Methods [J]. Computer Engineering and Applications, 2018, 54 (6):264--270.Google Scholar
- Vidya M. Ayer;Sheila Miguez and Brian H. Toby. Why scientists should learn to program in Python[J]. POWDER DIFFRACTION, 2014, Vol. (29):S48--S64.Google ScholarCross Ref
- Temirbekova, Zh. E.;Cherykbaeva, L. Sh.;Tulepberdynova. Color manipulation of images opencv in python[J]. Bulletin of Kazakh National Technical University, 2016, (2):482--485.Google Scholar
- ]Parthasarathy, M. K.;Lakshminarayanan, V. Color vision and color spaces(Article)[J]. Optics and Photonics News, 2019, Vol.30(1):44--51.Google ScholarCross Ref
Index Terms
- Design of the Control of Gravity Separator Dividing Plate Based on Machine Vision
Recommendations
Development of a machine vision system for determination of mechanical properties of onions
The contact area and the mechanical properties of two onion cultivars were assessed.It was possible to assimilate the shape of contact area to a circle.The effect of loading direction on Poissons ratio and the loading speed on stress and elasticity ...
The application of BIM technology in variation control of construction material of expressway asphalt pavement under machine vision
In order to improve the working life and service quality of asphalt pavement, this study uses building information modelling (BIM) technology to monitor the screening of asphalt mixtures and uses machine vision to study the composite grading of ...
Rapid entropy-based detection and properties measurement of concrete spalling with machine vision for post-earthquake safety assessments
The current procedures in post-earthquake safety and structural assessment are performed manually by a skilled triage team of structural engineers/certified inspectors. These procedures, and particularly the physical measurement of the damage properties,...
Comments