1. Design of Bacteria Bottle Clamping Elements Based on Regression Models
- Author
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Ding Tianhang, Wenshuo Gao, Wang Jiaoling, and Weidong Song
- Subjects
0209 industrial biotechnology ,business.product_category ,Article Subject ,business.industry ,General Mathematics ,Process (computing) ,Regression analysis ,02 engineering and technology ,Structural engineering ,Fixture ,021001 nanoscience & nanotechnology ,Clamping ,020901 industrial engineering & automation ,Bottle ,QA1-939 ,Robot ,0210 nano-technology ,business ,Labor cost ,Downward displacement ,Mathematics - Abstract
The fixture design of the bacteria bottle plays a vital role in designing a bottled fungus picking robot to save labor cost in the picking process of bottled fungus. This paper proposed a kind of clamping element design method based on regression models. Several sets of clamping elements were designed according to the appearance data of bacteria bottle. A single-factor test was conducted by using these clamping elements, and three levels of every factor were selected to obtain the desired values of clamping elements. Then, a Box–Behnken test was performed by selected levels. The established regression models described a numeric relationship between the variation of vital measurement points and all variation sources under a precise clamping element layout. To solve the problems in obtaining the direct parameters, a response surface method was presented based on the regression models. Finally, a test was used to demonstrate the effect of the optimized clamping elements when clamping a bacteria bottle. Through the related analysis and optimization, it was demonstrated that the holding effect of the clamping elements was the best under these conditions: the inner arc area was 4948 mm2; the downward displacement was 1.48 mm; and the rubber thickness was 3.69 mm. It showed that the proposed method was feasible, and the assembly quality after optimizing had been greatly improved. It can provide a reference for designing the bottle fixture of a picking machine.
- Published
- 2020
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