Research On Variable Speed Control Of De-mixing Fan Based On Soft Measurement Of Sugarcane Machinery Harvest Quality

Sugarcane combine harvester is an important equipment in the mechanized production process of sugarcane.The quality of harvest directly determines the application and promotion of mechanized harvesting of sugarcane.However,the harvest quality of sugarcane is difficult to measure directly through the sensor.The soft measurement method is an effective means to solve this problem.The method uses the auxiliary variables that are relatively easy to measure directly.Through the calculation of the mathematical model,the estimated values of the main variables that are difficult to measure or cannot be measured at all are obtained,and then the estimated values of the main variables are obtained.Feedback,designing a real-time controller.In this paper,the softness measurement method of mechanized harvesting quality of sugarcane was studied by using the impurity index and loss rate as the quality index.The influence of different working parameters on the mechanical harvest quality of sugarcane was studied,and the corresponding control strategy and variable speed control system of the fan was proposed.The main work of the thesis is as follows:1.The factors affecting the impurity content and loss rate of the segmented sugarcane combine harvester were studied by single factor test and orthogonal test.The research shows that the sugarcane combine harvester eliminates the fan speed,walking speed and sugarcane variety on the sugarcane combination machine.The harvest quality has significant effects,and the influence of the primary and secondary relationships is fan speed>walking speed>sugarcane variety,and planting density has no significant effect on harvest quality.With the increase of walking speed,the impurity content showed an upward trend,and the loss rate showed a downward trend.With the increase of fan speed,the impurity content showed a downward trend and the loss rate showed an upward trend.2.During the test,the load pressure signal and the speed signal of the sugarcane combine harvester cutting mechanism,the traveling mechanism,the cutting mechanism and the fan mechanism were collected,and the collected signals were filtered and extracted.The characteristic signal is used as the input signal of the soft-measurement model.The mean square error(MSE)and the decision coefficient(R2)are used as evaluation indicators.The harvest quality of the sugarcane combine harvester based on BP neural network and support vector regression machine(SVR)is established.The model was measured and the soft measurement accuracy was studied.The results show that when the BP neural network hidden layer uses 8 neurons and SVR kernel function to adopt the radial basis kernel function(RBF),the harvest quality soft measurement model has higher precision.At this time,the MSE is 0.115 and 0.055,the R2is 0.869 and 0.912.3.The genetic algorithm(GA)is used to optimize the weight and threshold of the established BP neural network,and the penalty function C and nuclear radius of the established SVR are optimized.The soft measurement of GA-BP and GA-SVR cane harvest quality is obtained.model.By comparing and analyzing the MSE and R2 of the two models,the GA-SVR model with better comprehensive performance was selected to softly measure the impurity content and loss rate during the field test,and the quality of harvest based on walking speed and fan speed was established.Based on the mapping relationship,the shift control strategy of the fan is proposed.4.According to the control strategy,the electro-hydraulic proportional control system for the speed of the hydraulic motor of the hybrid fan was designed,including the design of hardware,software and human-computer interaction interface.Finally,the field verification test was carried out.The results are as follows:The sugarcane combine harvester is equipped with an electro-hydraulic proportional control system based on soft measurement of harvest quality.The fan speed can be automatically adjusted according to the change of walking speed.Compared with the industry Standard,the sugar content and loss rate of sugarcane are reduced by 3.12%and 6.54%;The response time of the fan to the target speed command is 0.6s.After 0.6s,the speed tracking error is less than 2%.