Author
Listed:
- Jie Xiao
- Wanjie Kang
- Guofeng He
- Xiangchen Li
- Genglong Yan
- Amandeep Kaur
Abstract
In the cold season, wine aids in maintaining body temperature and is advised for military officers. This paper proposes a study on the multimotor drive control method of the upper-retort-robot based on machine vision for wine brewing automation to meet the demand of military areas located in cold regions, as wine is recommended to keep soldiers’ body temperatures normal in China’s extremely cold regions. Based on machine vision, the target is converted into an image signal by an image pickup device and is sent to the image processing system. Pixel distribution, brightness, color, and other data are transformed to digital signals, and target attributes are retrieved to control the field equipment’s operations. The Monte-Carlo approach is used to generate joint variables at random within each joint’s fluctuation range. The positive aspects of kinematics model are utilized and the working space of the upper-retort-robot is calculated using multimotor drive control method. The multimotor drive compensates the harmonic ripple torque and establishes the fault-tolerant automatic control of the system to maintain quality of the liquor. The results of the experiments reveal that the robot arm can reach any place within the barrel’s set range. To control the quality of the liquor, the robot will function in an automatic manner. The robot’s transmission performance is capable of meeting the requirements for automated liquor quality control during the production of wine from grapes. The results show that the suggested multimotor drive control (MMDCM) approach is robust and viable in terms of robot transmission performance and dexterity.
Suggested Citation
Jie Xiao & Wanjie Kang & Guofeng He & Xiangchen Li & Genglong Yan & Amandeep Kaur, 2022.
"Multimotor Drive Control Method of Upper-Retort-Robot Based on Machine Vision,"
Mathematical Problems in Engineering, Hindawi, vol. 2022, pages 1-10, August.
Handle:
RePEc:hin:jnlmpe:4034874
DOI: 10.1155/2022/4034874
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