The purpose of this study is to investigate the effect of drying parameters on drying performance in an air-vented tumble dryer, and to optimize its drying performance by adjusting parameters. The critical drying parameters that influenced specific moisture extraction rate (SMER), final moisture content, evenness of drying, and smoothness appearance were determined by the analysis of variance in JMP software, which were rotational speed of the motor and load size, with clearly significant individual effects and binary interactions. In order to improve the applicability of the outcomes obtained in this study and to take into account the interactions between drying parameters and drum structure parameters on drying efficiency, non-dimensional analysis was used and the correlation between drying efficiency and dimensionless variables was studied. The Buckingham Pi theorem was applied to the problem to derive dimensionless Pi terms upon which the drying efficiency depends. A step regression analysis was then conducted to test the assumption that SMER was influenced by the dimensionless parameters based on the standard least squares fitting. Results indicated that the regression model showed an explanatory power of 73.8%. By adjusting the dimensionless parameters in the model, an optimized energy-saving drying program was obtained with the desirability goal of reducing the value of SMER. Compared with the original program, energy efficiency was improved by 32.4%.

中文翻译：

---

国产滚筒式干衣机干燥参数与干燥性能的关系

本研究的目的是研究干燥参数对通风滚筒式干衣机干燥性能的影响，并通过调整参数优化其干燥性能。通过JMP软件中的方差分析确定了影响比水分提取率（SMER）、最终水分含量、干燥均匀度和光滑度的关键干燥参数，即电机转速和负载大小，具有明显的显着性。个体效应和二元相互作用。为了提高本研究结果的适用性，并考虑干燥参数和滚筒结构参数之间对干燥效率的相互作用，采用无量纲分析，研究干燥效率与无量纲变量之间的相关性。Buckingham Pi 定理应用于该问题以推导出干燥效率所依赖的无量纲 Pi 项。然后进行阶跃回归分析以测试基于标准最小二乘拟合的无量纲参数影响 SMER 的假设。结果表明，回归模型的解释力为 73.8%。通过调整模型中的无量纲参数，得到优化的节能干燥程序，其目标是降低SMER值。与原方案相比，能效提高了32.4%。然后进行阶跃回归分析以测试基于标准最小二乘拟合的无量纲参数影响 SMER 的假设。结果表明，回归模型的解释力为 73.8%。通过调整模型中的无量纲参数，得到优化的节能干燥程序，其目标是降低SMER值。与原方案相比，能效提高了32.4%。然后进行阶跃回归分析以测试基于标准最小二乘拟合的无量纲参数影响 SMER 的假设。结果表明，回归模型的解释力为 73.8%。通过调整模型中的无量纲参数，得到优化的节能干燥程序，其目标是降低SMER值。与原方案相比，能效提高了32.4%。