| As an important oil crop,the planting area of peanuts has stabilized at more than 4million hectares nationwide in recent years,with Henan Province ranking first in China.In the two-stage harvesting of peanuts,the problem of dust generated by picking and harvesting is more prominent.How to achieve low-cost,high-efficiency,low-dust mechanized peanut harvesting while ensuring production efficiency has become a high-quality,sustainable development of agriculture,and one of the important challenges in environmental pollution prevention and control.In this study,the dust generation mechanism and migration rules of the peanut harvester were analyzed.On this basis,two dust reduction technology solutions were proposed,namely low air outlet filtration dust reduction technology and long-stem harvesting dust reduction technology.Combined with the development of two experimental models of dust-reducing peanut harvester,an evaluation method for dust generated by peanut harvester was proposed.A dust measurement system based-on drone was developed to obtain the spatial distribution data of dust concentration during peanut harvesting,and the dust reduction effect of two experimental models of dust-reducing peanut harvester was verified through field experiments.The main research contents were as follows:(1)Starting from the mechanism of dust raised by peanut picking and harvesting machines,the basic motion model of dust particles was studied.The method of computational fluid dynamics was used to study the migration rules of dust generated by peanut harvester.A spatial area of 80 m×40 m×20 m was set up as the fluid domain,and a coupled model of gas-solid two-phase flow based on CFD-DPM was constructed.The Euler method was used to describe the air flow and the dust particles were considered as mass points and described by the Lagrangian method.SST k-ωwas used as the experimental turbulence model,and the Rosin-Rammlar distribution method was used to set the particle size.Simulation experiments were conducted on the migration of dust from peanut harvester under different operating parameters and environmental conditions,and the effects of particle size,working speed,outlet wind speed,emission height,and ambient wind on the spatial distribution of dust were researched.The results showed that particle size,emission height,and ambient wind are key factors affecting dust distribution.(2)Based on the movement rules of dust generated by peanut picking and harvesting machines,a technical solution for low air outlet filtration dust reduction was proposed.A cartridge-type dust-reducing grass box was designed,and the height of the air outlet above the ground is reduced from 3.2 m to 0.8 m,and the scope of dust diffusion was reduced by shortening the settling stroke of dust.The dust reduction filter cartridge was designed based on the principle of inertial impactor.The filter cartridge was composed of an inertial impact structure composed of two layers of porous plates with staggered discharge.Multiple filter cartridges were arranged in parallel in the rear space of the grass box to intercept dust particles and reduce dust emissions.By designing a double-layer spoiler device,the flow field inside the grass box is optimized,and simulation experiments were conducted on the dust particles movement inside the grass box before and after optimization.After optimization,the residence time of dust particles inside the grass box becomed longer,which was conducive to increasing the chance of particles deposition in the grass box.By dispersing the air flow,the fluid velocity and pressure distribution on the filter surface of the filter plate and filter cartridge were more uniform,which were able to improve performance of filter devices.(3)Combining the structural characteristics and dust generation mechanism of peanut harvester,and based on the actual utilization of peanut seedlings as feed in Henan Province,a technical solution for dust reduction in long-stem harvesting was proposed.A long-stem lifting device combined with belt and rake was designed for transporting peanut stems.Compared with the pneumatic conveying short-stem type peanut harvester,due to the elimination of structures such as the seedling crushing device,the generation of plant debris was reduced.A self-unloading grass box with bottom discharge was designed to solve the problem of a large amount of dust generated when the grass box was turned over to discharge.The flow field inside the grass box was optimized by designing a spoiler device,and simulation experiments were conducted on the dust particles movement inside the grass box before and after optimization.After optimization,the maximum airflow speed and pressure on the porous plate at the rear end of the grass box were reduced.The distribution was more even,and the height above the ground of the dust emission concentration area was reduced.The lower dust emission height and air flow velocity were able to help to suppress the spread of dust over a wide range.(4)Combined with the evaluation method of dust in peanut harvesting,in order to make up for the shortcomings of the absolute concentration measurement of dust at the emission outlet,which ignored the impact of the emission position on dust diffusion,a drone flight measurement method for real-time measurement of dust emissions from mobile dust sources was innovatively proposed.During harvesting,a multi-dimensional array composed of the total suspended particulates concentration at different spatial points around was used as an evaluation index.A drone measurement system including flight dynamics and control,light scattering particle sensor,position sensor,temperature and humidity sensor,ultrasonic distance sensor,microcontroller,data transmission module,etc.was developed to realize the measurement of PM10 and TSP concentration and obtain the spatial position data and other information of the measurement point.The wireless communication subsystem consisted of a Wi-Fi module,a4G-DTU module and a cloud server and three data transmission modes were designed to ensure reliable transmission of measurement data under different working and network conditions.A dust measurement app based on the Android platform was developed,and various solutions were designed to receive and display detection data in real time on the ground.The reliability was verified through the performance experiments of the dust measurement system.(5)The field experiment used an"M-shaped"path to conduct flight measurement of dust concentration during the operation of peanut harvester,and obtained the dust concentration and longitude and latitude information of characteristic points.Through coordinate transformation,the measured values of dust concentration at characteristic points in the coordinate system of the peanut harvester were obtained.Then,methods including symmetry and spatial interpolation were used to process the measured dust concentration data at characteristic points,and the spatial distribution data of dust concentration during the operation of the three test models were obtained.Compared with the original model without dust reduction design,the dust reduction efficiency of the low air outlet filtration dust reduction experimental model and the long-stem harvesting dust reduction experimenttal model reached 62.55%and 66.97%respectively.The dust concentration values at the same sampling points in the flight measurement and simulation experiment were normalized by the maximum value.The average relative error of the normalized values was 12.78%.The flight measurement results were generally consistent with the simulation experiment.A flight measurement was conducted for PM10 in the environment around the experimental site during the operation of the harvester.In the surrounding area within 60 m from the boundary of the operating site,the concentration of PM10 in the downwind direction was higher;in the area 60 m away,the concentration of PM10 was basically below 150μg/m~3,and the air quality was Level 2 and the risk was low. |
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