Design Of Rice Variable Spray Information Processing System

Rice is one of the main food crops in China.It has pests and weeds at various developmental stages during the growth period,and the severity of pests and diseases in different areas of farmland is different.The traditional applicator uses a large spraying amount to uniformly apply the entire plot.The problems of excessive use of pesticides,low environmental pollution,resource pressure,and ecological disruption have become more serious.In order to solve the above problems,this paper studies the precise variable spraying technology.Based on the ArcGIS Engine embedded GIS development component and GNSS-RTK technology,the spatial difference distribution map of pests and diseases can be generated,and the space difference can be based on pests and diseases.The sexual distribution and the speed of the applicator are used to carry out the variable injection and intelligent operation information processing system,and realize the “on-demand spraying” in different areas of the farmland.It is of great significance to improve the effective utilization rate of pesticides,enhance the control effect of pests and diseases,and promote the sustainable development of agriculture in China.The main research work and conclusions of this paper are as follows:(1)According to the domestic and international research status of precision agriculture and variable spraying techniques,the overall scheme of rice variable spraying information processing system was analyzed and designed,including spatial data processing,spatial and differential distribution of pests and diseases,and drug spraying decision-making.And spraying control(PWM pulse output).(2)Established the field coordinate representation system,which makes the position display of the operation process more intuitive,and can plan the operation path according to the operation width,which is convenient for the operator to walk.According to the designed field boundary algorithm,the system can calculate the coordinates of the vertex of the field border and project it to the Gaussian plane to establish the field coordinate system with the starting edge of the field as thecoordinate axis.(3)Using high-precision GIS data collector to collect data on rice pests and diseases in the field,and using the inverse distance weight method to realize the interpolation of field pest and disease data.Based on the original sampling data of rice pests and diseases in the field,the original data was converted into a custom field coordinate system by coordinate conversion formula,and the spatial difference distribution map of pests and diseases was generated by interpolating in the frame of the field,and the grid was reclassified and Raster to the surface,and finally generate a vector image in SHP format.(4)The design of the variable spraying control algorithm was completed.The algorithm is based on the fuzzy control theory.The driving speed of the operating unit and the severity of the current position are input.The expert experience and the mamdani reasoning method are used to calculate the PWM duty cycle of the solenoid valve.(5)The system sends the spraying amount to the lower computer through the CAN bus to execute the spraying instruction,and sends the operation status parameter to the remote monitoring center through the data remote transmission module to monitor the state of the spraying operation.The lower position machine changes the duty cycle to change the on-off time of the solenoid valve by the pulse width modulation method without changing the PWM square wave period,and realizes the variable spray.(6)A variable spraying information processing system was installed on the applicator for debugging and experimentation.The experimental results show that the variable spraying information processing system can operate normally and the communication is stable.At the same time,in order to reduce the calculation amount and reduce the system delay,the Gaussian projection conversion formula is optimized.The average calculation accuracy of the optimized formula is about 0.020 m,and the calculation time is reduced by about 0.114ms.