Study of variable spray control system based on machine vision

Author(s):  
Rui Zhang ◽  
Lepeng Song
2018 ◽  
pp. 143-149 ◽  
Author(s):  
Ruijie CHENG

In order to further improve the energy efficiency of classroom lighting, a classroom lighting energy saving control system based on machine vision technology is proposed. Firstly, according to the characteristics of machine vision design technology, a quantum image storage model algorithm is proposed, and the Back Propagation neural network algorithm is used to analyze the technology, and a multi­feedback model for energy­saving control of classroom lighting is constructed. Finally, the algorithm and lighting model are simulated. The test results show that the design of this paper can achieve the optimization of the classroom lighting control system, different number of signals can comprehensively control the light and dark degree of the classroom lights, reduce the waste of resources of classroom lighting, and achieve the purpose of energy saving and emission reduction. Technology is worth further popularizing in practice.


Author(s):  
Ce Bian ◽  
Fengzhi Dai ◽  
Meili Li ◽  
Yuxing Ouyang ◽  
Yiqiao Qin ◽  
...  

2019 ◽  
Vol 62 (4) ◽  
pp. 899-911
Author(s):  
Tingting Yan ◽  
Heping Zhu ◽  
Li Sun ◽  
Xiaochan Wang ◽  
Peter Ling

Abstract. Precision variable-rate spraying technology is needed for controlled-environment plant production in greenhouses. An experimental spray system for greenhouse applications was developed for real-time control of individual nozzle outputs. The system mainly consisted of a high-speed laser scanning sensor, 12 individual variable-rate nozzles, an embedded computer, a spray control unit, and a 3.6 m long mobile spray boom. Each nozzle was coupled with a pulse-width modulated solenoid valve to discharge sprays at variable rates based on target presence and plant canopy structure. Laboratory tests were conducted to evaluate the accuracy of the spray control system in respect to spray delay time, nozzle activation, and spray volume using four target objects of different regular geometrical shapes and surface textures and two artificial plants of different canopy structures. Other experimental variables included three detection heights from 0.5 to 1.0 m and five sensor travel speeds from 1.6 to 4.8 km h-1. A high-speed video camera was used to determine the delay time and nozzle activation in discharging sprays on target objects after the laser sensor had detected the objects. The detection height and travel speed were found to have slight influence on the timing of nozzle activation. The nozzles started spraying in a range between 33 and 83 mm before reaching the target objects and stopped spraying between 13 and 84 mm after passing the objects, ensuring that the objects were fully covered by the spray. Spray volume corresponded to the object sizes well, and the spray control system performed with higher accuracy at lower travel speeds. Differences between the calculated spray volume based on the sensor detection and the actual spray volume ranged from 1.9 to 2.7 mL per object among all tested objects. The variable-rate control system reduced spray volume by 29.3% to 51.4% for all the objects compared with conventional constant-rate spraying. At the same time, the nozzles could be activated precisely by the object presence. Consequently, this experimental laser-guided system was implemented on a boom system in a commercial greenhouse for future investigations of its accuracy in variable-rate spraying to save pesticides, water, and nutrients. Keywords: Automation, Intelligent sprayer, Pesticide, Precision spray technology, Boom spray equipment.


2019 ◽  
Vol 43 (2) ◽  
pp. 164-173 ◽  
Author(s):  
Ömer Barış ÖZLÜOYMAK ◽  
Ali BOLAT ◽  
Ali BAYAT ◽  
Emin GÜZEL

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