范文编号:HG132 范文字数:14302,页数:36 摘要:针对干燥过程的一般分析方法的不足,采取了干燥过程正交试验结果的神经网络建摸,并进行了详细的研究,该方法应用BP神经网络建立具有实际意义的干燥过程控制数学模型,并对结果进行一定的分析,从而实现试验结果的最优控制。本文具体阐述了进行旋转闪蒸干燥器干燥啤酒糟试验采集数据的神经网络方法,采用正交实验法进行实验,对不同操作条件下的啤酒糟含水质量分数进行了测试,并对直观分析、方差分析和神经网络方法分析结果的差异进行了概说和原因解释。此外,还对物料的干燥基本单元操作进行了详细解释。 Abstract:Against the general drying process analysis method, the drying process to take orthogonal test results of the neural network modeling, and to conduct a detailed study, The BP neural networks is of practical significance to the drying process control mathematical model, the results are analyzed, thus achieving optimal results of the pilot control. This article gives the flash drying brewer's grain test data collection of neural network methods, orthogonal experiment conducted experiments on different operating conditions of brewer's grain moisture content for the test, as well as visual analysis, variance analysis and neural network analysis of the differences and outlined the reasons. In addition, the drying of materials basic unit operation for a detailed explanation.
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