Control of multi-energy drying system: Optimal weighted combination prediction of moisture content and fuzzy compensation of wind speed

In order to monitor the moisture content accurately and improve the drying uniformity of the same batch of materials, an online moisture monitoring approach based on optimal weighted combination model (OWCM) was developed, and a fuzzy control strategy of wind speed compensation was established for multi-field coexistence. The Human Machine Interface (HMI) and remote monitoring modules are designed, which can automatically obtain, view and store environmental parameters on site and mobile devices. The system was loaded into a kelp drying equipment, and moisture content prediction and drying uniformity verification tests were conducted respectively. The results showed that Root Mean Square Error (RMSE) and Mean Absolute Error (MAE) of the OWCM are 0.022 and 0.019, the prediction accuracy was better than that of single model and average weighted combined model (AWCM). The drying time difference between the front and back of the same batch of kelp was shortened from 1 ∼ 1.5 h to 0 ∼ 0.5 h. This study provides theoretical and technical support for the synergistic utilization of multiple energies and the research and development of aquatic products processing equipment.