银杏果粗加工关键技术研究
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摘要
脱壳是银杏果粗加工中最复杂、最关键的加工环节。目前，银杏果脱壳机械化和自动化仍处于起步阶段，为了研发出脱壳率高、破仁率低的银杏果脱壳机，以提高银杏果加工的生产效率，增加银杏果仁的商品价值。本论文在研究了银杏果物理力学特性和银杏果热风干燥特性的基础上，提出了银杏果脱壳工艺路线；设计了一台滚筒-栅条式银杏果脱壳机，并进行了脱壳和清选性能试验；利用响应面分析法分析了热风温度、热风速度、装载量对干燥品质的综合影响，滚筒转速、滚筒直径、栅条间隙对脱壳率、破仁率的影响，以及喂入量、风速、出风口倾角对损失率和清洁率的影响；采用函数期望寻优法对脱壳机的结构参数进行了优化。取得的主要研究结论如下：
（1）银杏果热干燥过程主要集中在恒速和降速干燥两个阶段，升速不明显。在试验范围内，热风温度、装载量对失水速率影响均显著而热风风速影响不显著，热风温度对失水速率影响最大，热风风速影响最小。经拟合发现银杏果热风干燥过程符合Page模型。
（2）通过对银杏果传热系数的计算可知：银杏果热风干燥条件下的扩散系数大约在（0.492～2.158）×10~(-6)m~2/s范围内，扩散系数随着气体温度的升高及风速的增加而增加。银杏果热风薄层干燥的活化能在（21.816～33.811） kJ/mol，这与其组织结构、形状、大小及组成等因素有关。
（3）通过本项目研究发现：热风温度、装载量和风速对银杏果热风干燥平均能耗、平均干燥速率、蛋白质保存率以及感官评分等评价指标有极显著影响，而且不同干燥因素对不同干燥评价指标的影响程度也不同。利用多目标非线性优化分析及函数期望寻优法对干燥工艺进行优化，得到银杏果热风干燥最佳工艺参数组合，即热风温度为68℃、热风速度为1.15m/s及装载量为15.58kg/m~2。此时平均能耗为11.86kW.h/kg、平均干燥速率为9.77%/h、蛋白质保存率为90.30%、感官评分为8.57分。
（4）对银杏果压缩力学试验研究可知：含水率、施压方向对破碎力、变形量及能耗有极显著影响（P<0.10）。破碎力、变形量及能耗与银杏果含水率之间存在二次非线性的函数关系。经过正交试验多重比较分析可知：银杏施压方向、施压速率、银杏含水率与银杏果综合评分均为显著相关，要使银杏压缩脱壳质量最佳时，最优水平组合为银杏施压方向为Y向、挤压速率为55mm/min、含水率23.72%。
（5）采用滚筒-栅条式对银杏果进行脱壳试验可知在：试验范围内，银杏果脱壳率和破仁率随着转子转速和滚筒直径的增加而逐渐增大，随着栅条间隙的增大而减小。对脱壳率的影响强度依次是：转子转速>滚筒直径>栅条间隙。对破仁率的影响强度依次是：滚筒直径>转子转速>栅条间隙。通过多目标优化法脱壳装置最优组合：转子速度为180r/min、滚筒直径为182mm、栅条间隙为10.5mm，此时，银杏脱壳率为92.80%，破仁率为8.10%。能够满足银杏果脱壳工艺的要求。
（6）通过本项目试验结果表明，建立了喂入量A、风速B、出风口倾角C对损失率Y_1和清洁率Y_2的二次多项式回归模型。损失率Y_1的二次多项式回归模型：Y_1=5.69+0.60A+6.99B-0.95C+1.00AB-0.63AC-0.32BC-0.30A~2+4.79B~2-1.23C~2。并由各影响因素的贡献率可知：在试验范围内各结构参数对损失率的影响强度次序为：风速>出风口的倾角>喂入量。清洁率Y_2的二次多项式回归模型：Y_2=95.32-0.40A+3.54B-0.77C-1.20AB-0.20AC+0.37BC-0.55A~2-1.63B~2-0.25C~2。并由各影响因素的贡献率可知：在试验范围内各结构参数对清洁率的影响强度次序为：风速>喂入量>出风口的倾角。
（7）采用多目标函数优化得出银杏果最佳组合条件为：喂入量为270kg/h、风速为9.3m/s、出风口倾角为17°，此时可得：损失率为1.68%、清洁率为95.68%。能够满足银杏果脱壳后清选工艺的要求。
As the mechanization and the automation of ginkgo shelling are still under itsinfancy, the comprehensive use of ginkgo is at the low level now. In order to improvethe production efficiency of ginkgo’s processing, increase the value of the kernels, weneed to excogitate a new ginkgo sheller which has the high husking and the low level ofdamage. Based on the study of ginkgo’s physical characteristics and the theories of thehulling, the article puts forward a process route for ginkgo shelling. It can deeplyresearch on ginkgo air drying properties and the optimization of the process parameterswith the help of the self-made hot-air-drying equipment. And the synthetic effects of thehot–air temperature, hot-air velocity and loading capacity on the average drying energyconsumption and the average drying rate is analysed.
The cylinder-barrier type Ginkgo shelling machine and cleaning machine weredesigned, and the shelling and cleaning performance tests were carried out.
The response surface analysis was used to analyse the comprehensive influence ofthe hot-air temperature, air velocity and loading capacity on the drying quality, theinfluence of the rolling-speed, rolling diameter and size of screen mesh grid on thehulling rate and the breaking rate, and the influence of the feeding amount、wind speedand outlet angle on the quality of the cleaning effect.
The function optimization method was used to optimize the structure parameters ofthe shelling machine and the cleaning machine. Here are the main conclusions:
（1）Ginkgo hot-drying process mainly depends on the two sections: the constant-speed drying part and the falling-speed drying part while it is not obvious in theraising-speed part. In this experiment, hot-air temperature and the loading capacitymade a great effect on the drying process while the speed of hot-air made littledifference. The hot-air temperature affected the water-losing rate most while the hot-airspeed did the least. The experiment proves that the ginkgo hot-air-drying process fit onthe Page model.
（2）Through calculating the heat transfer coefficient of ginkgo, we can know thatthe effective diffusion coefficient is related with the organized structure, the varietiesand the shape （geometric size） of ginkgo. Ginkgo’s effective diffusion coefficient issome （0.492～2.158）×10~(-6)m~2/s under the hot-air and it will increase along with theincreasing of the gas temperature and the wind speed. Ginkgo’s activation energy of thin-layer hot air drying is some （21.816～33.811） kJ/mol, which is related to itsconstruction, shape, size and so on.
（3） Through studying, it is found that the hot-air temperature、air velocity andloading capacity make a great effect on the average energy consumption, the averagedrying rate and sensory ratings,and the influences of different factors on the averagedrying rate of drying, average drying energy consumption are different. We canoptimoize the drying process with the help of multi-objective nonlinear optimizationanalysis and function optimization method to get the best process parameterscombination: the hot-air temperature is68℃, hot-air speed is1.15m/s and the loadingcapacity is15.58kg/m~2. Under these conditions, the average energy consumption is11.86kW.h/kg, the average drying speed rate is9.77%/h, protein retention rate is90.30%and the sensory score is8.57.
（4） Through the compression experiment of ginkgo, it can be known that waterratio and pressure direction make a great difference on the breaking force, deflectionsand energy consumption（P＜0.10）. And there is a second order nonlinear functionalrelationship between the brake power、deflections、energy consumption and the waterratio. Through a comprehensive scoring method and the orthogonal experiment, weknow: The Ginkgo’s pressure direction, pressure rate, moisture content make a greatdifference on gingko’s compression comprehensive score. To get the best shellingquality, the optimal shelling parameters are pressure direction of Y, pressure rate of55mm/min, moisture content rate of23.72%.
（5） Through the roller-grid shelling experiment, It is obtained that: gingko’shelling rate and the broken kernels rate increase along with the increase of the rotorspeed and diameter of roller, but go down along with the increase of sieve net clearance.The order of the factors is found: speed, drum diameter, screen space. The gingkokernel’s breaking rate increase along with the increase of the rotor speed and rollerdiameter, but decrease with the increase of screen space. The order of the factors isfound: rolller diameter, speed, screen space. Through the multi-objective optimizationmethod, the best process parameters shelling device are found: the rotor speed is180r/min, the roller diameter is182mm, screen space is10.5mm, Under theseconditions, the gingko’s shelling rate is92.80%and the broken kernels rate is8.10%. Itmeets the requirements of shelling technology of Ginkgo fruit.
（6）Through the experiment results of the project, the quadratic polynomialregression model about the feed quantity、wind speed、air outlet inclination rate and the shell content in kernel、 the kernel content in shell were established. The quadraticpolynomial regression model of is Y_1=5.69+0.60A+6.99B-0.95C+1.00AB-0.63A-0.32BC-0.30A~2+4.79B~2-1.23C~2. From the contribution ratio of every factor, we know:within the scope of experiment, the order of the factors which influence the loss rate inshell is: wind speed, feed quantity, air outlet inclination. the order of the factors whichinfluence the shell content in kernel is: wind speed, air outlet inclination, feed quantity.The quadratic polynomial regression model of the cleaning percentage is Y_2=95.32-0.40A+3.54B-0.77C-1.20AB-0.20AC+0.37BC-0.55A~2-1.63B~2-0.25C~2. From thecontribution ratio of every factor, we know: within the scope of experiment, the order ofthe factors which influence the cleaning percentage in shell is: wind speed, feed quantity,air outlet inclination.
（7）By applying membership comprehensive score, we got optimal combinationsof maximum comprehensive points: feed quantity is270kg/h, wind speed is9.3m/s, airoutlet inclination is17°. Under these conditions，the loss rate is1.68%, the cleaningpercentage is95.68%. It meets the requirements of cleaning technology after shelling ofGinkgo fruit.
（1）银杏果热干燥过程主要集中在恒速和降速干燥两个阶段，升速不明显。在试验范围内，热风温度、装载量对失水速率影响均显著而热风风速影响不显著，热风温度对失水速率影响最大，热风风速影响最小。经拟合发现银杏果热风干燥过程符合Page模型。
（2）通过对银杏果传热系数的计算可知：银杏果热风干燥条件下的扩散系数大约在（0.492～2.158）×10~(-6)m~2/s范围内，扩散系数随着气体温度的升高及风速的增加而增加。银杏果热风薄层干燥的活化能在（21.816～33.811） kJ/mol，这与其组织结构、形状、大小及组成等因素有关。
（3）通过本项目研究发现：热风温度、装载量和风速对银杏果热风干燥平均能耗、平均干燥速率、蛋白质保存率以及感官评分等评价指标有极显著影响，而且不同干燥因素对不同干燥评价指标的影响程度也不同。利用多目标非线性优化分析及函数期望寻优法对干燥工艺进行优化，得到银杏果热风干燥最佳工艺参数组合，即热风温度为68℃、热风速度为1.15m/s及装载量为15.58kg/m~2。此时平均能耗为11.86kW.h/kg、平均干燥速率为9.77%/h、蛋白质保存率为90.30%、感官评分为8.57分。
（4）对银杏果压缩力学试验研究可知：含水率、施压方向对破碎力、变形量及能耗有极显著影响（P<0.10）。破碎力、变形量及能耗与银杏果含水率之间存在二次非线性的函数关系。经过正交试验多重比较分析可知：银杏施压方向、施压速率、银杏含水率与银杏果综合评分均为显著相关，要使银杏压缩脱壳质量最佳时，最优水平组合为银杏施压方向为Y向、挤压速率为55mm/min、含水率23.72%。
（5）采用滚筒-栅条式对银杏果进行脱壳试验可知在：试验范围内，银杏果脱壳率和破仁率随着转子转速和滚筒直径的增加而逐渐增大，随着栅条间隙的增大而减小。对脱壳率的影响强度依次是：转子转速>滚筒直径>栅条间隙。对破仁率的影响强度依次是：滚筒直径>转子转速>栅条间隙。通过多目标优化法脱壳装置最优组合：转子速度为180r/min、滚筒直径为182mm、栅条间隙为10.5mm，此时，银杏脱壳率为92.80%，破仁率为8.10%。能够满足银杏果脱壳工艺的要求。
（6）通过本项目试验结果表明，建立了喂入量A、风速B、出风口倾角C对损失率Y_1和清洁率Y_2的二次多项式回归模型。损失率Y_1的二次多项式回归模型：Y_1=5.69+0.60A+6.99B-0.95C+1.00AB-0.63AC-0.32BC-0.30A~2+4.79B~2-1.23C~2。并由各影响因素的贡献率可知：在试验范围内各结构参数对损失率的影响强度次序为：风速>出风口的倾角>喂入量。清洁率Y_2的二次多项式回归模型：Y_2=95.32-0.40A+3.54B-0.77C-1.20AB-0.20AC+0.37BC-0.55A~2-1.63B~2-0.25C~2。并由各影响因素的贡献率可知：在试验范围内各结构参数对清洁率的影响强度次序为：风速>喂入量>出风口的倾角。
（7）采用多目标函数优化得出银杏果最佳组合条件为：喂入量为270kg/h、风速为9.3m/s、出风口倾角为17°，此时可得：损失率为1.68%、清洁率为95.68%。能够满足银杏果脱壳后清选工艺的要求。
As the mechanization and the automation of ginkgo shelling are still under itsinfancy, the comprehensive use of ginkgo is at the low level now. In order to improvethe production efficiency of ginkgo’s processing, increase the value of the kernels, weneed to excogitate a new ginkgo sheller which has the high husking and the low level ofdamage. Based on the study of ginkgo’s physical characteristics and the theories of thehulling, the article puts forward a process route for ginkgo shelling. It can deeplyresearch on ginkgo air drying properties and the optimization of the process parameterswith the help of the self-made hot-air-drying equipment. And the synthetic effects of thehot–air temperature, hot-air velocity and loading capacity on the average drying energyconsumption and the average drying rate is analysed.
The cylinder-barrier type Ginkgo shelling machine and cleaning machine weredesigned, and the shelling and cleaning performance tests were carried out.
The response surface analysis was used to analyse the comprehensive influence ofthe hot-air temperature, air velocity and loading capacity on the drying quality, theinfluence of the rolling-speed, rolling diameter and size of screen mesh grid on thehulling rate and the breaking rate, and the influence of the feeding amount、wind speedand outlet angle on the quality of the cleaning effect.
The function optimization method was used to optimize the structure parameters ofthe shelling machine and the cleaning machine. Here are the main conclusions:
（1）Ginkgo hot-drying process mainly depends on the two sections: the constant-speed drying part and the falling-speed drying part while it is not obvious in theraising-speed part. In this experiment, hot-air temperature and the loading capacitymade a great effect on the drying process while the speed of hot-air made littledifference. The hot-air temperature affected the water-losing rate most while the hot-airspeed did the least. The experiment proves that the ginkgo hot-air-drying process fit onthe Page model.
（2）Through calculating the heat transfer coefficient of ginkgo, we can know thatthe effective diffusion coefficient is related with the organized structure, the varietiesand the shape （geometric size） of ginkgo. Ginkgo’s effective diffusion coefficient issome （0.492～2.158）×10~(-6)m~2/s under the hot-air and it will increase along with theincreasing of the gas temperature and the wind speed. Ginkgo’s activation energy of thin-layer hot air drying is some （21.816～33.811） kJ/mol, which is related to itsconstruction, shape, size and so on.
（3） Through studying, it is found that the hot-air temperature、air velocity andloading capacity make a great effect on the average energy consumption, the averagedrying rate and sensory ratings,and the influences of different factors on the averagedrying rate of drying, average drying energy consumption are different. We canoptimoize the drying process with the help of multi-objective nonlinear optimizationanalysis and function optimization method to get the best process parameterscombination: the hot-air temperature is68℃, hot-air speed is1.15m/s and the loadingcapacity is15.58kg/m~2. Under these conditions, the average energy consumption is11.86kW.h/kg, the average drying speed rate is9.77%/h, protein retention rate is90.30%and the sensory score is8.57.
（4） Through the compression experiment of ginkgo, it can be known that waterratio and pressure direction make a great difference on the breaking force, deflectionsand energy consumption（P＜0.10）. And there is a second order nonlinear functionalrelationship between the brake power、deflections、energy consumption and the waterratio. Through a comprehensive scoring method and the orthogonal experiment, weknow: The Ginkgo’s pressure direction, pressure rate, moisture content make a greatdifference on gingko’s compression comprehensive score. To get the best shellingquality, the optimal shelling parameters are pressure direction of Y, pressure rate of55mm/min, moisture content rate of23.72%.
（5） Through the roller-grid shelling experiment, It is obtained that: gingko’shelling rate and the broken kernels rate increase along with the increase of the rotorspeed and diameter of roller, but go down along with the increase of sieve net clearance.The order of the factors is found: speed, drum diameter, screen space. The gingkokernel’s breaking rate increase along with the increase of the rotor speed and rollerdiameter, but decrease with the increase of screen space. The order of the factors isfound: rolller diameter, speed, screen space. Through the multi-objective optimizationmethod, the best process parameters shelling device are found: the rotor speed is180r/min, the roller diameter is182mm, screen space is10.5mm, Under theseconditions, the gingko’s shelling rate is92.80%and the broken kernels rate is8.10%. Itmeets the requirements of shelling technology of Ginkgo fruit.
（6）Through the experiment results of the project, the quadratic polynomialregression model about the feed quantity、wind speed、air outlet inclination rate and the shell content in kernel、 the kernel content in shell were established. The quadraticpolynomial regression model of is Y_1=5.69+0.60A+6.99B-0.95C+1.00AB-0.63A-0.32BC-0.30A~2+4.79B~2-1.23C~2. From the contribution ratio of every factor, we know:within the scope of experiment, the order of the factors which influence the loss rate inshell is: wind speed, feed quantity, air outlet inclination. the order of the factors whichinfluence the shell content in kernel is: wind speed, air outlet inclination, feed quantity.The quadratic polynomial regression model of the cleaning percentage is Y_2=95.32-0.40A+3.54B-0.77C-1.20AB-0.20AC+0.37BC-0.55A~2-1.63B~2-0.25C~2. From thecontribution ratio of every factor, we know: within the scope of experiment, the order ofthe factors which influence the cleaning percentage in shell is: wind speed, feed quantity,air outlet inclination.
（7）By applying membership comprehensive score, we got optimal combinationsof maximum comprehensive points: feed quantity is270kg/h, wind speed is9.3m/s, airoutlet inclination is17°. Under these conditions，the loss rate is1.68%, the cleaningpercentage is95.68%. It meets the requirements of cleaning technology after shelling ofGinkgo fruit.
引文
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