Research On Best Matching Optimization Method Of Plant Protection Machinery Running Speed And Flow

The intelligent development of plant protection machinery is an important part of the development of modern agriculture.When the plant protection machinery is affected by road conditions,working conditions of its own components,the crops' height changes and the spray system parameters are not set properly during working process,the sprayer is under sprayed or over sprayed.In addition,the drop of the drug droplet does not fall on the leaf surface,which causes problems such as poor spraying distribution uniformity,low spraying quality and low spraying efficiency.In order to improve the quality of spraying,it is of great significance to study the uniformity of spraying of plant protection machinery.The research contents of this thesis are as follows:Firstly,in view of the fact that it is not possible to directly obtain the distribution coefficient of variation value to evaluate the spray quality in actual operations,after analyzing the principle of plant protection machine and the influencing factors of uniformity,the influence of nozzle wear on the uniformity of distribution is considered.Four influencing factors of nozzle wear,working pressure,spray height and operating speed are selected as inputs of model.A deep belief network method is used to establish a soft measuring model for the uniformity of spray distribution,which is used to determine the relationship between the influencing factors and the uniformity of spray distribution,and then evaluate the quality of the spray.Tested and verified the soft measuring model based on the data measured by the plant protection machinery test bench.The results show that the model can accurately predict the variation coefficient of the spray distribution,which proves the validity of the model.Secondly,according to the established soft measuring model of spray uniformity and the way of controlling the flow by pressure in actual operation,the method of neural network inverse model is used to determine the optimal pressure setting value of the spraying system,which depends on the working pressure,spray height,spraying time and distribution coefficient.On this basis,the state space model of the spray system is established,and a pressure controller based on sliding mode control algorithm is designed to ensure that the working pressure can track to the pressure setting value quickly,ensure the uniformity of spray distribution.The simulation results of pressure of different influencing factors verify that the controller designed in this thesis has good tracking control performance and meets the control accuracy required for the operation of the spraying system of theplant protection machinery,ensure the quality of spraying.