Research Of Intelligent Wood Drying Control System Based On Multiple Parameter Model

Now,automatic control of wood drying system has many shortages in our country,such as single function,time-consuming,energy-consuming,non-ideal drying effect and so on.Foreign wood drying control system has a high degree of automation and more complete functions.But the system is in a state of monopoly,and it's too expensive.Existing wood drying methods in the domestic and overseas only use dry bulb temperature,wet bulb temperature(or equilibrium moisture content or relative humidity)and moisture content of wood to control the drying process.This method causes the internal and surface cracking problems in the process of drying.This paper introduce wood core temperature control on the basis of existing wood drying methods,use multiple parameters(dry bulb temperature,wet bulb temperature,moisture content of wood,core temperature)synthetically to perform the control process of wood drying.Incorporating with the fuzzy neural network theory,this paper establishes multiple parameter system model,which contains control model and identification model,of wood drying process.According to the wood drying technology and the traditional wood drying kiln,the control model of wood drying process has three inputs of the kiln,namely,kiln temperature,kiln temperature humidity and wood core temperature.The controller adopts six new inputs which are transformed from the above inputs.They are temperature error,humidity error and wood core temperature error of the kiln,and the rate of change of temperature error,humidity error and wood core temperature error of the kiln.And it has four outputs,namely,electric control heating valve,electric control steam injection valve,circulation fan,and wet exhaust fan.And the identification model is modelled using seven inputs,namely,the control variable of circulation fan,wet exhaust fan,electric control heating valve and electric control steam injection valve,and medium temperature,medium moisture,and wood core temperature of wood drying system.The identification model also has three outputs,namely,kiln medium temperature and medium humidity,and wood core temperature.To improve control accuracy,this article merges a variety of intelligent algorithm together.It optimizes the structure and parameter of the multiple parameter system model of wood drying process.Firstly,fuzzy neural network BP algorithm is more dependent on the initial weights of network,takes a long time to complete training,and is easy to fall into the undesired local extremum,so the PSO optimization algorithm that has global optimization performance is adopted.Secondly,in order to avoid the prematurity of the PSO algorithm,the immune mechanism are introduced to perform immune stimulation of low concentration of particles,increase the size of the particle swarm.On the contrary,the immune mechanism suppresses the high concentration of particles and maintain the diversity of particle swarm.Finally,for further importing prior knowledge and experience of problem to be solved,and speeding up the global convergence ability of the algorithm,this article additionally introduces three immune operators,vaccination,immune selection and migration.This paper has designed the hardware and software of intelligent wood drying control system that is based on multiple parameter model.The hardware is designed by using HollySys LE5708 PLC as core controller and HollySys HT8A00 T as host computer's touch screen,at the same time,a variety of anti-jamming measures are used to ensure the stability of the system.The fuzzy neural network that immunes PSO to optimize is applied to the software system,it makes the system has high convergence speed and recognition rate,and has good control effect for uncertain nonlinear system.At last,the proposed system is applied to NO.7 drying kiln of Benxi red leaves furniture manufacturing co.,LTD.It turned out that the proposed method effectively improved the control precision and quality of wood drying,speeded up the wood drying process,and saved drying cost.It lays the technical and theoretical groundwork for wood drying control to realize intelligent,modular,and low carbonization.