Research On The Selection Method For Identifying And Eliminating Damaged Potatoes And Impurities

With the introduction of the main grain policy,China’s potato industry has been continuously upgraded and developed,and the degree of mechanization of potato harvesting is gradually increasing.However,mechanized harvesting of potatoes can cause damage and inclusion of impurities such as clods and stones,which not only increases the difficulty of potato storage and processing,but also reduces harvest efficiency,Therefore,it is necessary to eliminate damaged potatoes and impurities before further processing them.In this study,mechanical design,thermal infrared imaging,image processing and other technical means were used to explore the feasibility of applying thermal infrared imaging technology to the removal of damaged potatoes and impurities.The main research contents and conclusions of this paper are as follows:1.Aiming at the problem of detecting and identifying clod and stone inclusions in potatoes,a potato and impurity classification method based on active thermal infrared imaging was proposed.Firstly,a heat transfer model for potatoes and impurities based on the lumped parameter method was established,and the factors that affect the heating effect and lead to temperature differences were obtained: material thermophysical properties,wind speed,wind direction angle,and wind temperature;Then,using finite element simulation experiments,the thermal images of potatoes and impurities under external hot wind excitation were obtained,and the surface temperature of potatoes was significantly higher than that of clods and stones.Four levels of single factor simulation experiments were conducted on wind speed,wind direction angle,and wind temperature,respectively.It was found that the difference in surface temperature between potatoes and impurities was nonlinear and positively correlated with wind speed,wind direction angle,and wind temperature within a certain period of time;Finally,a classification experiment was conducted on the experimental platform for potatoes and impurities.The optimal image recognition processing conditions were wind speed of 4m/s,wind temperature of 40℃,and wind direction angle of 90°.The recognition success rate was 97.08%.2.Aiming at the problem of detecting and recognizing damaged potatoes,a field collaborative recognition method based on thermal infrared imaging of damaged potatoes was proposed to detect and recognize three types of common damaged potatoes.Firstly,a heat transfer model for damaged potatoes based on field synergy theory was established and heat transfer analysis was conducted.It was determined that the reason for the temperature difference between the damaged and intact parts of potatoes was the difference in the convective heat transfer intensity between the two and the hot air and the thermophysical properties of the skin and flesh of potatoes;Then,through finite element simulation tests,the temperature distribution of the damaged potato surface at various hot air inlet angles was obtained.Based on the imaging effect of the thermal image,the optimal inlet angle was determined to be 90 ° vertically.It was found that the temperature of the complete part of the thermal image of the three types of damaged potato surface obtained from the simulation tests was higher than that of the damaged part;Finally,a detection and recognition experiment was conducted on a test rig for damaged potatoes,and the recognition success rate was 98.21%.3.In order to achieve the detection and removal of damaged potatoes and impurities,a potato selection device based on active thermal infrared imaging technology was designed and built on the basis of the above research.Firstly,the software and hardware system of the device is designed,and a removal device is used to remove damaged potatoes and impurities;Then,in order to determine the optimal operating parameters of the cleaning device,an orthogonal combination test was conducted using the error detection rate as an evaluation index,and the conveyor belt speed,hot air speed,and hot air temperature as test factors.The optimal parameter combinations determined through parameter optimization were: conveyor belt speed 0.37m/s,hot air speed 3.5m/s,and hot air temperature 45℃;Finally,a rejection test was conducted on a selective device,and the error detection rate obtained was 2.58%,which met the requirements of national and industry standards for grading and inspection of commercial potatoes.