Model identification of wood drying and shrinkage processes

Abstract

In the drying process of wood, the controlling quantities are temperature and humidity, which in turn lead to changes in moisture content and further lead to drying of wood to produce dry shrinkage force. In this paper, the ARMA model is used to identify the process of temperature-moisture-moisture content, and then the control model of moisture content and shrinkage force is developed on the basis of the ARMA model. The results show that the combination of the ARMA model and the BP neural network can form a good control model for the drying shrinkage force, which can provide a feasible basis for the application of the ARMA model and the BP neural network in the drying shrinkage force of wood