Optimization experiment of influence factors on greenhouse vegetable harvest cutting

Abstract: In the developed countries of the West, the greenhouse vegetable industry has become highly mechanized, with a relatively stable mechanization production system and necessary supporting tools. In order to improve the efficiency of harvesting greenhouse vegetables, Beijing University of Technology has designed an innovative vegetable harvester. The cutting tool that is used to remove vegetables from their stems is a critical factor in greenhouse vegetable harvesting and must be optimized to ensure that greenhouse vegetables are harvested effectively. The designed machine can have a better harvest effect and reduce the wear of cutting tool in the process of the work. At present, the mechanical properties of stem-cutting factors affecting crops have been extensively studied with sugar cane, corn stalk, eulaliopsis binata stem and cabbage in China and abroad. This paper detailed the design and study of the SHQG-I greenhouse vegetable harvest cutting experiment platform, which used a response surface method (RSM) to optimize the harvest process through a comprehensive cutting tool that removed vegetables from their stems. The study object of this paper was butter lettuce; the experiment was carried out on the SHQG-I greenhouse vegetable harvest cutting experiment platform, and the working process of greenhouse vegetable harvester was analyzed. According to the butter lettuce growth and the working process conditions, 6 parameters of the harvest cutting process were analyzed: cutting position, way of cutting, cutting speed, cutting angle, clamping distance and clamping angle. Determining the ways in which these parameters affected cutting force was the target of the experiment. The working range of these factors, which could be adjusted on the SHQG-I greenhouse vegetable harvest cutting experiment platform, influenced the cutting force. For the RSM employed in the experiment, generally no more than 4 parameters would be adjusted at a time. Therefore, the experiment first used the factor-screening test to determine the cutting position and cutting way. The cutting position was at 7 mm and the smooth cutting angle was 10°. The results of the experiment were analyzed with the Design-expert software. In addition, the regression equation of the cutting force and the various factors were determined, and lack of fit of the regression equation was found to be insignificant. Next, variance analysis was used to determine the significant factors, which were cutting speed, clamp distance, interaction between cutting speed and cutting angle, and interaction between cutting speed and clamp distance. Then, the curve diagram of significant factors and the response surface figure were drawn. Ultimately, the optimal working parameters were determined: cutting speed was 675 mm/s, cutting angle was 4.85°, clamping distance was 98.5 mm and clamping angle was 64.5°. According to the optimization parameters, the expected cutting force was 17.9 N, and the actual cutting force was 17.4 N (2.8% less than the expected force), which met the demand of the test. The experiment guaranteed a harvest success rate of 100% in all of the cases, as well as effectively reduced the necessary cutting force in the harvest process. After optimization, the harvester machine was in good condition, it produced a good harvest, and the cutting fracture was smooth, which satisfied the engineering requirement. The optimization parameters obtained in the experiment can be applied for the improvement of the actual equipment in the greenhouse vegetable industry field.