| The variable and target spray technology is an effect way to reduce the usage of pesticide, which is theoretically significant together with practical value for realization of sustainable agriculture. In order to reduce the pesticide usage in agricultural spray process, a spray robot was designed and optimized with the technology of Pulse Width Modulation (PWM) variable spray and computer vision. In addition, the corresponding agricultural equipment were developed and optimized.The main research contents and results are as follows:1. In order to build model of PWM spray flow online and rapidly, this article set up a PWM precision spray test platform by using high-speed solenoid valve. According to the relationship between pressure near the nozzle and its quantity of flow, the instantaneous flow data was calculated using Kalman filtering algorithm. Then, the average spray flow could be obtained by computing the integral of the instantaneous data. An automatic piecewise linear fitting method was designed to combine the average spray flow after filtering and PWM duty cycle. Finally, we got the PWM spray flow model. The spray flow control experiments were performed with the spray flow models under the spray pressure of0.2MPa,0.3MPa and0.4MPa. The results show that the value of coefficient of determination (R2) for the models above are all bigger than0.995under the three different kinds of spray pressure, and the spray flow control error is within±6%. This method provides a reference for building spraying control model online and rapidly.2. The uniformity of spray is an important factor to evaluate the quality of spray. Because the nozzle took discontinuous operations during the PWM variable spray process, it was difficult to take control of the uniformity of spray, especially the uniformity in the movement direction of the spray machine. A dynamic PWM variable spray experiment platform was built to find the effect on spray uniformity caused by parameters of PWM variable spray technology. The distribution features of droplets in dynamic spray based on this platform was studied. Water-sensitive paper was used to collect droplets under different frequencies and different duty cycles of PWM controlling signals, also different of spray pressure. Image-processing technology was applied to get the coefficient of variation (CV) value coverage rate of droplets within the certain area, which was taken as the evaluation index of the uniformity of dynamic droplets distribution. It was used to evaluate the homogeneity of single nozzle dynamic spraying under different conditions of PWM controlling signal frequency, different PWN duty cycle of controlling signals, and different spray pressure. The research indicates that CV value decreases as the duty cycle of controlling signals increases, the frequency of controlling signals has great influence on homogeneity, CV value decreases as the frequency increases. And what’s more, when pressure turns to be high, CV value becomes large and the influence is weaker compared to other factors.3. In the process of target spray, the solenoid valve is a vital part in the system and it is the only mechanical component. The response time of solenoid valve has a significant impact on the precision of spray. A modified pulse-width modulation (PWM) method was developed through response surface methodology (RSM) to reduce the response time of solenoid valve used in agricultural spraying system. This study was carried out by controlling various PWM parameters, including voltage for driving solenoid valve (10,12and14V), delayed time of PWM (15,40and65ms) and duty cycle of PWM (5,15and25%). The data of nozzle operational pressure was acquired and analyzed to calculate the response time. As a result, the optimum conditions for a minimum response time were as follows:voltage for driving solenoid of12V, delayed time of15ms and the duty cycle of5%, respectively. The test results are corresponding to the predicted value, which shows that21.2%of total response time can be reduced compared to the general control method.4. A target spray platform was built based on computer vision technology. Crop recognition and spray control information was studied using VS2010and OpenCV developmental tools. The communication between host computer and slave computer with STM32F407as the control core was developed by RS232bus. The spray robot and several related parts were designed based on the target spray platform in the laboratory.5. Mechanism study related to target spray was attempted out of interest. We try to change spray parameters to enhance deposition rate. Plant point cloud data was acquired by3D camera and Lagrange particle trajectory calculation method was used to describe a droplet, which was applied to study the discriminant of interaction of particle trajectory and plant point cloud. The spray simulation environment was realized by using Matlab, but the simulation result need to be further researched. |
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