Current Issue : January-March Volume : 2023 Issue Number : 1 Articles : 5 Articles
The advantages of noncontact, high-efficiency, and fully automatic vision measurement technology make it widely used in industrial inspection and other fields. This study is based on the research of machine vision nanoimage automatic measurement and powder metallurgy materials. It aims to apply the machine vision imaging-related image processing technology principle to the automatic measurement of nanoimages and analyze the related properties of powder metallurgy materials and their image applications. This study mainly combines theory and practice to carry out experiments and data acquisition and analysis. On the one hand, it has a theoretical understanding of machine vision imaging principles and image segmentation; it also analyzes the properties and applications of powder metallurgy materials. On the other hand, on the basis of these theories, machine vision technology is fully applied to analyze the related physical properties such as the gap and density between tiny particles. Among them, the image measurement technology of moving targets is applied, and the model of the machine vision system is established. After a series of experimental verifications, the accuracy of the machine vision image measurements was fully guaranteed. The experimental results show that with the aid of machine vision technology, the accuracy of the observed data has been greatly increased; the maximum porosity of powder metallurgy materials has increased from 6.56 to 8.22; the maximum density has increased from 6.46 to 8.40. This demonstrates that automated image measurement based on machine vision technology can greatly improve the accuracy of measurements....
There are some problems in the design and application of the art education exchange platform. In order to further analyze the relevant content of the art education exchange, based on machine vision theory, model calibration, and coordinate change are adopted to modify the original model, so as to obtain the optimized model. This model can be used to analyze the design and application of art education platform. Relevant studies show that, according to the coordinate parameter curve, the parameter α plays a promoting role on the coordinate value, while the parameter β plays a promoting role on the coordinate value first and then plays an inhibiting role. The parameter c also promotes and inhibits coordinate values. The curve corresponding to parameter M1 shows a gradual decline, and the curve of parameter M2 has little influence on coordinate data. The curve corresponding to parameterM3 also shows a linear trend of change. Through analysis, it can be seen thatM3 has the greatest influence on coordinate data. By using machine vision model to design and analyze the communication platform of art education, the changing trend of different indicators can be obtained. It can be seen from the analysis that both language and vocal music have obvious stability in the calculation process, which is an inherent attribute of communication platform. Finally, the accuracy of the optimization model is verified by analyzing and predicting the data. This research can provide theoretical support for the application of machine vision model in other fields....
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.TheMonte-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. Theresults show that the suggested multimotor drive control (MMDCM) approach is robust and viable in terms of robot transmission performance and dexterity....
Due to the lack of accurate modeling information in environment modeling, the traditional path planning algorithm for robot obstacle avoidance is of low accuracy. Therefore, this paper designs an obstacle avoidance path planning algorithm for embedded robot based on machine vision. First, the method of target edge detection is optimized in this paper. The edge detection results are obtained by color space transformation, and the complete target is obtained by edge fusion combined with surrounding pixel attributes. Then, the distance of the obstacle is measured by binocular depth ranging, and the longitudinal positioning of the robot is obtained, and the position of the obstacle is further obtained. Finally, a fuzzy control method for obstacle avoidance path planning is designed to obtain a complete planning scheme. The performance test results of the obstacle avoidance path algorithm show that the obstacle avoidance path planning scheme obtained by the algorithm designed in this paper has better performance in different obstacle avoidance test environments and can successfully avoid obstacles when the robot runs at high speed....
To further improve the perception ability of binocular vision sensor in getting rich environment information and scene depth information, a research method of a robot obstacle recognition and target tracking based on binocular vision was proposed. The method focused on target recognition and obstacle recognition of binocular stereo vision. The system based on obstacles of visual identification was set up. Through the analysis of the Bouguet mathematical model algorithm based on OpenCV, the binocular stereo correction was carried out and the obstacle recognition system was calibrated and corrected. Through the experimental data, it was found that the average error of the obstacle recognition and target tracking algorithm based on binocular vision could be controlled within 50mm within the range of 2100 mm. The average time of obstacle recognition was 0.096 s and the average time consumption of the whole system was 0.466 s, indicating that the robot obstacle recognition and target tracking system based on binocular vision could meet the accuracy and real-timeness requirements of obstacle recognition and detection....
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