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分级是山杏核采后加工利用的最初操作步骤。利用响应面分析对踏板式山杏核分级机机械参数和分级操作(以尺寸为标准)进行优化设计。采用3因素(踏板速度、进料速度和含水率)3水平(速度60、70和80 r/min,进料速度275、300和375 kg/h,含水率10.5%、12.5%和14.5%)研究分级效率(%)和分级能力(kg/h)。为得到自变量最优解,对试验数据进行分析。开发了全二阶模型用于预测反应(分级效率和分级能力),并且研究了各个参数及其相互作用。试验结果表明,分级效率和分级能力分别为75.9%~82.4%和270~325 kg/h。在踏板速度75 r/min,进料速度325 kg/h和核含水率14.5%时,分级机可以达到最大分级效率和分级能力。
Grading is the initial step of apricot kernel post-harvest processing and utilization. Response surface analysis of the mechanical parameters of grading apricot grading machine and grading operation (size as standard) for optimal design. Three levels (pedal speed, feed rate and moisture content) of 3 levels (speeds 60, 70 and 80 rpm, feed rates 275, 300 and 375 kg / h, water contents 10.5%, 12.5% and 14.5% Studied grading efficiency (%) and grading capacity (kg / h). In order to obtain the optimal solution of the independent variables, the experimental data are analyzed. All second-order models were developed for predicting reactions (grading efficiency and grading ability), and various parameters and their interactions were studied. The test results show that the classification efficiency and grading ability are 75.9% ~ 82.4% and 270 ~ 325 kg / h, respectively. At a pedal speed of 75 r / min, a feed rate of 325 kg / h and a nuclear moisture content of 14.5%, the classifier achieves maximum classification efficiency and classification capability.