Numerical Simulation And Experimental Research For The Determination Of Deposition Parameters For A Cold Sprayer

The cold sprayer is an efficient equipment for chemical plant protection in greenhouse agriculture. The droplets generated by cold sprayer can distribute uniformly in the sealed space due to the small droplets, such as the volume medium diameter (VMD) around30μm. As the great development of greenhouse horticulture in the recent years, a bright prospect for the research and popularization of cold sprayers could be expected.Based on the cold sprayer that was designed by the research group and the author is one of the members, the airflow velocity field was simulated and droplet deposition distribution model was established. The airflow variation as the sprayer moving was also simulated via dynamic meshing technology. Experiments were carefully designed and conducted for the verification of the simulated models. A droplet detecting system was developed for the droplet distribution measurement and served as simulation evaluation.The research topics are listed as follows,(1) Simulation and verification of airflow field for cold sprayer.Pre-experiments indicated that the distribution of velocity of the airflow was highly related to the spraying height and the initial airflow velocity. Based on k-ε turbulence model, a numerical model for airflow field was built for the spraying under working conditions of spraying height from0.5m to2.5m and initial air velocity from5m/s to25m/s. An experiment was designed and conducted to verify the simulated results. Due to the simulation and verification, positive linear correlation was discovered between air blowing distance and initial air velocity of the air assistant system by the cold sprayer. Also, the air blowing distance was significantly affected by the distance between the symmetry axis of cold sprayer and the wall of the greenhouse walls.(2) Simulation and model verification for the model of deposition distribution of the cold sprayer.Based on the Euler-Lagrange multiphase flow model, a model of droplet deposition distribution was built by adding droplet discrete particles into the airflow model. Also, the verification experiment was designed and conducted for the model analysis and model error measurement. Analysis showed that the relative error of the simulated deposition and experimental results was between15%and35%. Compared with the similar simulation reports, the model was regarded to be reliable. Besides, a droplet deposition detection system was used to analyze the impact of spraying height and airflow velocity on droplets deposited density and diameter distribution. Optimized working parameters were suggested depending on the data analysis of the detected results by the system.(3) Exploration and analysis of cold sprayer’s airflow field distribution under motivated spraying. Due to the simulation and verification experiments of both airflow field and droplet deposition, the air assistant distance limitation was discovered. Therefore, the auto-moving spraying mode was developed to improve the droplets spread more uniformity throughout the greenhouse. In this section, dynamic meshing method was introduced to simulation. The simulated results showed that airflow swirls were generated when the air assistant equipment moved with the sprayer. And the direction of rotation would change with the working position of the sprayer. Under this situation, the droplets were proved misting significantly better.(4) Designation of droplet detection system using image processing technology.Digital pictures of droplet deposition on water sensitive paper were captured with a high definition scanner. Due to the comparison of the grayer pictures of each dimension under different color spaces (RGB, YIQ, HSI), I dimension under YIQ color model was selected for droplet segmentation. Under this dimension, the droplets could be obviously distinguished from the initial paper background, as well as the vein of the water sensitive paper could be effectively erased. The segmentation was processed under methods of Otsu threshold and gray value histogram. The results indicated that the droplets were extracted better using Otsu threshold method. Amount and diameter of droplet spots were calculated as the detected parameters at last. A standard deposition card with droplets number and diameter distribution was detected with the system. Then the accuracy was judged by comparing the results with the original parameters. As the result informed, the identification ratio of droplet density was higher than95%, and the error for diameter distribution was less than10%. Considering its mobility, this system can greatly help the researchers to do the measurement in both labs and fields.