农业工程学报
農業工程學報
농업공정학보
2013年
3期
265-272
,共8页
烘干%模型%农产品%籽棉%热风干燥
烘榦%模型%農產品%籽棉%熱風榦燥
홍간%모형%농산품%자면%열풍간조
drying%models%agricultural products%seed cotton%hot-air drying
为了使机采籽棉在清棉、轧花等加工前把水分控制到合适的范围以提高加工质量,需要对籽棉进行一定的烘干处理,并对烘干过程进行实时控制.该文设计了籽棉热风烘干的三因素三水平正交回归旋转试验,研究了喂花量、籽棉初始干基含水率和热风温度这3个因素对籽棉烘干后干基含水率的影响.试验结果表明喂花量、籽棉初始干基含水率和热风温度对籽棉干燥速率都有较明显的影响,烘干过程的前15 s 干燥速率变化较快,之后趋于平缓.分别使用单项式扩散模型、Page 模型和二次多项式模型进行拟合,发现单项式扩散模型拟合效果最好,决定系数 R2均值为0.9549.该模型应用于实际生产中籽棉烘干的实时控制.效果表明使用该模型后烘干效率更高,籽棉烘干后干基含水率一致性更好.
為瞭使機採籽棉在清棉、軋花等加工前把水分控製到閤適的範圍以提高加工質量,需要對籽棉進行一定的烘榦處理,併對烘榦過程進行實時控製.該文設計瞭籽棉熱風烘榦的三因素三水平正交迴歸鏇轉試驗,研究瞭餵花量、籽棉初始榦基含水率和熱風溫度這3箇因素對籽棉烘榦後榦基含水率的影響.試驗結果錶明餵花量、籽棉初始榦基含水率和熱風溫度對籽棉榦燥速率都有較明顯的影響,烘榦過程的前15 s 榦燥速率變化較快,之後趨于平緩.分彆使用單項式擴散模型、Page 模型和二次多項式模型進行擬閤,髮現單項式擴散模型擬閤效果最好,決定繫數 R2均值為0.9549.該模型應用于實際生產中籽棉烘榦的實時控製.效果錶明使用該模型後烘榦效率更高,籽棉烘榦後榦基含水率一緻性更好.
위료사궤채자면재청면、알화등가공전파수분공제도합괄적범위이제고가공질량,수요대자면진행일정적홍간처리,병대홍간과정진행실시공제.해문설계료자면열풍홍간적삼인소삼수평정교회귀선전시험,연구료위화량、자면초시간기함수솔화열풍온도저3개인소대자면홍간후간기함수솔적영향.시험결과표명위화량、자면초시간기함수솔화열풍온도대자면간조속솔도유교명현적영향,홍간과정적전15 s 간조속솔변화교쾌,지후추우평완.분별사용단항식확산모형、Page 모형화이차다항식모형진행의합,발현단항식확산모형의합효과최호,결정계수 R2균치위0.9549.해모형응용우실제생산중자면홍간적실시공제.효과표명사용해모형후홍간효솔경고,자면홍간후간기함수솔일치성경호.
The initial moisture content (dry basis) of seed cotton picked by machine is very high, occasionally exceeding 18%. However, research has shown that the moisture content between 6.5% and 8.5% is optimal for processing seed cotton. To obtain a higher drying efficiency and better drying quality of seed cotton before cleaning and ginning, it is necessary to control drying conditions within a narrow range. However, many cotton gins currently set and control the temperature of seed-cotton drying equipment based on personal judgments, which is inaccurate and risky. Based on a large number of experiments on hot air drying characteristics, this paper developed a hot-air drying model of seed cotton and solved the above problem. We used quadratic regression in a 3×3 factorial experimental design to model the effects on the final moisture content of three factors (hot air temperature, seed cotton feed rates and initial moisture content) and three levels of each factor. Results show that all three factors significantly influence the drying rate of seed cotton. In addition, the first 15 s of the drying process exhibits a faster drying rate, after which the drying rate rapidly decreases. Curve fitting with a monomial diffusion model, Page’s drying model, and a quadratic polynomial model, we found that the monomial diffusion model fit the data more closely (R2=0.9549) than the other models. Analyzing the drying process more closely, we determined that our hot-air drying model of seed cotton could provide a theoretical basis for adjusting the control parameters in real time on the drying equipment. Of the three control parameters tested, the final moisture content of seed cotton is most sensitive to (a) the initial moisture content, (b) cotton feed rate, and (c) hot-air temperature, in decreasing order of sensitivity. The hot-air drying model developed in this paper has been applied in real-time control of seed cotton drying in actual production, confirming its utility in process effectiveness and consistency, energy efficiency, and net economic benefit to the ginner.