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A research on the multi-motor drive control method of the upper-retort-robot based on machine vision is proposed in this paper for wine brewing automation to suffice the demand of military areas situated in cold regions as wine is recommended to keep the body temperature of soldiers normal in highly cold regions of China. 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. The pixel distribution, brightness, color and other information are converted into digital signals and the target features are extracted to control the actions of the field equipment. The Monte-Carlo method is exploited to randomly generate joint variables within the variation range of each joint. The positive aspects of kinematics model are utilized and the working space of the upper-retort-robot is calculated using multi-motor drive control method. The multi-motor drive compensates the harmonic ripple torque, and establishes the fault-tolerant automatic control of the system to maintain quality of the liquor. The experimental results show that the robot arm can reach at any position in the barrel within the defined range. The robot will work in an automated mode to control the quality of the liquor. The transmission performance of the robot can meet the requirements of the automated quality control of the liquor during processing of wine from grapes. The results are obtained for robot transmission performance and robot dexterity which proves the robustness and viability of the proposed multi-motor drive control method (MMDCM).

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.