Decentralized neural network variable structure controller design for wood drying process
This paper investigates the development and evaluation of a robust control system for a wood drying kiln process incorporating decentralized variable structure control (DVSC) such that the moisture content of lumber will reach and be stabilized at the desired set point. A description of the dynamics of the wood drying process by means of the time-delay neural network is also presented, in which the back-propagation algorithm was implemented for testing, training and validation. Then this identified model is used for simulation purpose and controller design. For comparison purpose, a conventional proportional-integral-derivative (PID) controller is also employed and system performance is evaluated through simulations. The results are evaluated to tune the controller parameters to achieve good performance in the wood-drying kiln and the DVSC strategy promises improved performance. The control system developed in this study may be applied in industrial wood-drying kilns, with a clear potential for improved quality and increased speed of drying.
Investigation of effects of wood variability and rheological properties on lumber drying: application of mathematical models
Abstract Three types of mathematical models (a single board-drying model, a kiln-wide drying model and a drying stress model) have been developed for the simulation of kiln drying of softwood lumber and the simulation of drying stresses. The single board-drying model employs comprehensive heat and moisture mass transfer knowledge and considers the influence of wood physical characteristics and moisture state. The model is used to investigate the influence of lumber variability such as wood density, green moisture content, growth ring pattern, mixture of sapwood and heartwood and thickness variation. The kiln-wide drying model, which was developed for the simulation of the drying of a kiln wide stack, is based on the transfer processes between the wood material and the drying medium. This model is able to examine the influence of varying wood properties and drying schedules on drying rate and moisture content distribution between boards. The stress model has been proposed to predict stress development in drying, and stress relief in final steam conditioning and post-kiln treatment. The stress model considers wood shrinkage, stress–strain relationships, mechano-sorptive behavior, creep and temperature effect. It is found that the rheological properties of wood play an important role in drying stress relief. The stress model is used to optimize drying schedules and to effectively relieve the residual drying stresses.
ANALYSIS AND OPTIMIZATION OF THE CONDITIONING PHASE IN TIMBER DRYING
The conditioning phase of the conventional timber drying process has been investigated. Due to wood shrinkage, tensile stress will develop in the surface layer of the board during drying. This stress combined with the change in MC causes mechano-sorptive creep. If the process is abruptly terminated when the target MC is reached, then there will be a considerable internal MC gradient and the creep deformation will cause distortions in subsequent machining. A conditioning phase is often introduced at the end, in order to reduce these problems. The conditioning phase has been analyzed with a wood drying simulation model. It is shown that traditional conditioning cannot completely reverse the deformations, even at very long conditioning times. An optimizing procedure has thus been used to create a new conditioning “schedule” which gives the best possible result within a given time. Features of such optimized schedules are presented. As the surface layer is elongated during drying, there is a risk that considerable stress develops as the moisture profile levels out. In some cases internal checking will be the result. The optimization procedure is thus modified to avoid such situations and the impact on the conditioning schedule is discussed.