方捆苜蓿热风循环干燥工艺实验研究

针对北方苜蓿(alfalfa)二茬收获量大且与雨季相遇,易出现干燥不及时导致贮藏过程品质变差问题,使用热风循环干燥技术,可克服方捆苜蓿热风干燥过程成本高、效率低、品质下降的技术瓶颈。结合热风循环干燥特性和捡拾打捆工艺,研究苜蓿草捆合理干燥工艺参数。利用5HY-Ⅱ热风实验台配合温湿度传感器检测方捆中各点温湿度状况,研究方捆内温度、水分传递规律。以苜蓿外观品质和单位能耗为评价指标,利用正交实验设计方法,确定高水分苜蓿方草捆干燥工艺参数。结果表明,得到的方捆苜蓿干燥实验特性曲线分为预热阶段、等速干燥阶段、稳定阶段。依据色泽和气味的感官评价为评价指标发现方捆长度和干燥温度与感官评价指标作用显著,且成负相关;依据单位能耗作为评价指标得出方捆长度和密度与单位能耗指标作用显著,且成负相关。使用Neuro shell结合实经济效益进行神经元网络预测分析,得出热风循环干燥工艺最佳参数组合,即:草捆长度285.7 mm,密度238.38 kg/m3,干燥温度60.48℃,风速1.73 m/s,耗能0.203 k J/kg H2O。该预测干燥工艺研究可为人工辅助干燥贮藏苜蓿草捆作指导。

Bundle Alfalfa Experimental Study on Hot Air Circulation Drying Process

Because the large harvest of second crop of alfalfa in the north and the meeting with the rainy season, the quality of storage process become worse due to the lack of drying time. The heat-air circulate drying technology can overcome the technical bottleneck of high cost, low efficiency and degraded quality of the bundle drying process. Combined with the heat-air circulate drying characteristics and the picking and bundling technology, this paper studied the reasonable drying technology parameters of the alfalfa bundles. The 5HY-Ⅱ heat-air test bench was used with the temperature and humidity sensor to detect the temperature and humidity of each point in the bundle to explore the temperature and moisture transfer rules in the bundles. Taking the appearance quality and unit energy consumption of the alfalfa as the evaluation index, the orthogonal test design method was used to determine the drying technology parameters of the high moisture alfalfa bundles. The test results indicated that the obtained experimental characteristics of the square bundle drying experiment are divided into preheating stage, constant speed drying stage and stable stage. According to the sensory evaluation of color and odor, the evaluation of the bundle length and the drying temperature and the sensory evaluation index were significant and negatively correlated. According to the unit energy consumption as the evaluation index, the length and density of the bundles had significant effects on the unit energy consumption index and were negatively correlated. Using the Neuro shell combined with the real economic benefit to predict the neural network, the optimal combination of parameters for the heat-air circulate drying technology was obtained, namely: the bundle length was 285.7 mm, the drying process parameter density was 238.38 kg/m3, the drying temperature was 60.48°C, the air velocity was 1.73 m/s, and the energy consumption was 0.203 kJ/kg H2O. The study of the predicted drying technology could be used as a guide for artificially assisted dry storage of alfalfa bundles.