Visual monitoring method for atmospheric disturbance of moving objects

2020 ◽  
Vol 49 (8) ◽  
pp. 20190535-20190535
Author(s):  
张月 Yue Zhang ◽  
苏云 Yun Su ◽  
高鹏 Peng Gao ◽  
王旭 Xu Wang ◽  
董士奎 Shikui Dong ◽  
...  
2020 ◽  
Vol 49 (8) ◽  
pp. 20190535-20190535
Author(s):  
张月 Yue Zhang ◽  
苏云 Yun Su ◽  
高鹏 Peng Gao ◽  
王旭 Xu Wang ◽  
董士奎 Shikui Dong ◽  
...  

2021 ◽  
Vol 41 (2) ◽  
pp. 0228002
Author(s):  
张月 Zhang Yue ◽  
王旭 Wang Xu ◽  
苏云 Su Yun ◽  
张学敏 Zhang Xuemin ◽  
邬志强 Wu Zhiqiang ◽  
...  

2020 ◽  
Vol 29 ◽  
pp. 2633366X2093258
Author(s):  
Yibo Sun ◽  
Yuqi Feng ◽  
Pengfei Hu ◽  
Xing Zhao ◽  
Xinhua Yang ◽  
...  

Ultrasonic bonding is a convenient bonding technology, which features sufficient cleanliness, high efficiency, no need for additional bonding aids, and other outstanding advantages. In recent years, it has been introduced into the field of the micro–nano assembly of polymer micro–nano devices, but it is still difficult for current ultrasonic bonding technology to meet the accuracy requirements of the micro–nano assembly. To improve the control accuracy of the hot-melt interface in the process of ultrasonic bonding, an online hot-melt interface monitoring method and an online ultrasonic transmission efficiency detection method are proposed in this article. With these detection methods, the real-time monitoring of the hot-melt interface can be realized on the basis of machine vision, while high-frequency dynamic force sensors can be used to detect the ultrasonic vibration transmitted from the ultrasonic horn to the anvil. Based on these methods, a functional anvil based on visual monitoring and ultrasonic detection is developed, the finite element method has been used to analyze the transmission characteristics of ultrasonic vibration, and experiments are carried out regarding online detection in the process of ultrasonic bonding. The results show that this system can realize the online detection of the hot-melt interface and ultrasonic transmission information, providing a new control method for ultrasonic bonding technology.


2021 ◽  
Vol 2021 ◽  
pp. 1-12
Author(s):  
Xuan Kan ◽  
Deli Cao

The research purpose is to solve the problems of low efficiency, low accuracy, and high cost of traditional environmental landscape mapping and landscape volume measurement methods in the artistic design of college campus landscape and make up the defects that the traditional campus monitoring is vulnerable to adverse weather, which results in low monitoring accuracy. Primarily, a binocular stereo vision measurement based on Scale Invariant Feature Transform (SIFT) matching algorithm is proposed, which can realize accurate collection of environmental spatial information and measurement of landscape volume without contact in the process of campus landscape design. Then, the visual monitoring system of college landscape based on the Internet of Things (IoT) is constructed to realize real-time monitoring and early warning of human damage to campus landscape. The proposed method is verified by actual measurement of different objects and simulation experiments using simulation software. Ultimately, the application of visual sensors in artistic design of college campus landscape is analysed by literature analysis. The results show that (1) the error of the improved binocular stereo vision measurement designed here is 52.32% and 59.69% lower than that of the traditional measurement method when measuring the same object with different volumes and the volumes of different objects, respectively, which indicates that the measurement accuracy of the new method is higher. (2) The proposed landscape visual monitoring method based on IoT improves the image recognition accuracy by 21% compared with the traditional digital image monitoring method. The average recognition time is shortened by 12 ms, which ensures the accuracy and improves the recognition efficiency. (3) Through the analysis of existing literature, it is found that the binocular stereo vision sensor can be used to monitor the whole process of landscape construction in real time. The sensor can be combined with social networks, mobile terminals, and physiological monitoring equipment to comprehensively analyse and evaluate people’s preference for campus landscape. The proposed method has broad application prospects in campus landscape design, construction, and maintenance. The research purpose is to provide important technical support for the improvement of the overall image of the college campus and even the city for the design of landscape environment and the technical upgrading of maintenance work in the college campus.


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