Model of Drying Process for Combined Side-heat Infrared Radiation and Convection Grain Dryer Based on BP Neural Network
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    Abstract:

    The drying mechanism of combined side-heat infrared radiation and convection (IRC) grain dryer is more complicated compared with that of the traditional convection drying. In order to explore the model of uncertain system like the grain drying and application of BP artificial neural network method, a new intelligent prediction model for the combined side-heated IRC dryer used to predict the outlet core moisture content ratio and drying rate is developed based on BP neural network algorithm. The model which has three layer neural network structures (8-10-1) is trained and tested based on the train data set and test data set by programming the model in Matlab. The model inputs are the eight influence variables of grain dryer, and the model output is the outlet grain moisture ratio of the dryer or the drying rate. The corresponding mathematical expressions of moisture ratio and drying rate model are also given, and the determination coefficients (R2) of model prediction are 0.9989 and 0.9980, and the root mean square errors (RMSE) are 0.009 and 0.0041, respectively. The predicted results are fitted well with the measured data, and the prediction accuracy is high. In addition, combined with the experimental drying conditions, the prediction results of the model are analyzed and summarized. According to the same method, the prediction model of outlet moisture ratio for the counter-current grain drying is also successfully established. By the comparison of predicted performance curves for two types of drying process, it is proved that the combined side-heat IRC drying has faster drying rate and less time to dry to the target moisture value than those of the conventional hot air convection drying. It can be used to predict the drying performance of different drying processes and to realize the comparison of different drying processes. In addition, compared with other grain drying mathematical models, various influence factors of grain drying can be comprehensively considered, which can provide a new modeling method for the complex system like the drying of combined side-heat IRC.

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History
  • Received:July 03,2016
  • Revised:
  • Adopted:
  • Online: March 10,2017
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