摘要
This paper presents experimental performance and artificial neural network modeling of a large-scale greenhouse solar dryer for drying of natural rubber sheets. The dryer consists of a parabolic roof structure covered with polycarbonate sheets on a concrete floor. The dryer is 9.0 m in width, 27.0 m in length and 3.5 m in height. Nine 15-W DC fans powered by three 50-W PV modules were used to ventilate the dryer. To investigate its performance, the dryer was used to dry six batches of natural rubber sheets. For each batch, 750 kg of rubber sheets were dried in the dryer. Results obtained from the experiments showed that drying temperatures varied from 32 ~C to 55 ~C and the use of the dryer led to a considerable reduction of drying time, as compared to the open air sun drying. In addition, the quality of the product from the dryer was high-quality dried products. A multilayer neural network model was developed to predict the performance of this dryer. The predictive power of the model was found to be high after it was adequately trained.
