摘要
蓖麻油具有很高的经济价值,现广泛应用于医学、化妆品和工业等领域。直筒式压榨法由于压榨温度易控制、榨取的油脂原生态特性良好等优势,成为提取医用蓖麻油的最佳方式之一。为研究直筒式压榨提取蓖麻油的最佳热榨工艺参数,从而提高压榨效率,利用单轴压榨液压加载装置进行压榨试验分析,采用单因素试验考察保压时间、压榨压力、物料温度、加载速度对直筒式压榨出油率的影响,并运用二次回归通用旋转组合设计分析四因素五水平下的压榨出油效果,得到了一定条件下出油率的变化规律,并根据回归方程利用统计优选法寻优,从而提取直筒式压榨的最佳热榨工艺参数。试验结果表明,各工艺参数对压榨出油率的影响次序为:保压时间>压榨压力>物料温度>加载速度。当设定保压时间为10min、压榨压力为18MPa、物料温度为70℃、加载速度为2mm·s-1时,直筒式压榨达到最大效率,实际出油率为(65.08±0.26)%。理论计算值为65.41%,理论值与试验值的相对误差仅为0.505%,回归模型可靠。
Castor oil has high economic value, widely used in medical, cosmetics and industrial sectors. The cylindrical squeezer proves to be one of the best modes to extract medicinal castor oil for the excellent original ecological characteristics of production and available control of squeezing temperature. To optimize the heating-pressing process parameters of castor's cylindrical pressing, thus improving the pressing efficiency, by the cylindrical hydraulic press, single-factor experiments were used to analyze the influence of pressure-holding time, pressure, material temperature and loading rate on oil yield. The varying pattern of oil yield were obtained by the quadratic regression rotation combination design of five factors and four levels, and the most suitable heating-pressing technological parameters were extracted by Statistical-optimum seeking method on the basis of regression equation. It is shown by test results that the descending order sorted by the effects on oil yield is pressure-holding time, press, material temperature and loading rate. When setting pressureholding time as 10min, press as 18MPa, materiel temperature as 70℃ and loading rate as 2mm ·s-1, the oil yield should be 65.41% according to the regression model and the experimental data is (65.08±0.26)%. The relative error is only 0.505%, which demonstrats the reliability of regression model.
出处
《沈阳农业大学学报》
CAS
CSCD
北大核心
2015年第6期699-705,共7页
Journal of Shenyang Agricultural University
基金
国家林业局林业公益性行业科研专项项目(201304608)
国家科技支撑计划项目(2011BAD22B04)
关键词
蓖麻
直筒式压榨
工艺参数优化
二次回归通用旋转组合设计
castor
cylindrical pressing
the optimization of process parameters
quadratic regression rotation combination design