Fusion System And Simulation Technology Studies On On-line Detection Of Lumber Moisture Content

The lumber is the widely broadest engineering applied material,the only green material that may regenerate and circulate now in the four big raw materials(steel products,cement, lumber,plastic) of the world.Wood drying is one of basic researches in wood machining and using.The world forest resources reduce day by day,which brings the questions on environmental protection and ecology,in the wood drying process the outside environment parameter and the lumber itself physical parameter all possibly affects the change of lumber moisture content(LMC).To establish corresponding relations fast and effectively between each parameter and moisture content,that's one of important basic research contents,and also that's the precondition to realize the completely automatic control,improve the dry quality, reduce the energy consumption and reduce the drying time.Wood drying is a complex strong coupling,non-linear dynamic system,lumber moisture content parameter detection is the key. In recent years,the multi-sensor fusion technology already became an important research area along with its theory and the application engineering research fast development.In view of question of LMC detection,the multi-sensor information fusion overcomes low accuracy,big data variation,inferior integrity and systematic in the sole sensor online detection.This research namely takes this as a point,which has studied the multi-sensor information fusion method and application on the moisture content online detection.On the foundation of absorbing developed country and domestic advanced technology, taking the lumber moisture content examination as the basis,comparing and selecting the sensors,has designed the monolithic integrated circuit as core lumber moisture content examination electric circuit and control system hardware systems.The structure is designed by using the double CPU,which simplifies the hardware electric circuit,completes the construction of LMC test system and realizes the hardware design of moisture content online examination system.It analyses the wood drying mechanism and the strong coupling relations in the process, depends on the multi-sensor information fusion technology and constructs on-line detection hierarchical fusion system of the lumber moisture content accord with the wood drying process. Uses the multi-sensor data to carry on the goal the state estimation,seeks best-fit state vector with the observation data through mathematics method,Carries on the multi-ranks,multi-aspect, multi-level processing to the multi-sensor data,this process carries on the examination, the union,the correlation,the estimate and the combination to the multiple source data, achieves the precise state estimation and the status estimate.In drying kiln bad factor such as high temperature,humidity as well as air blower movement directly influence LMC sensor examination values,which can cause deviation between the thick data examination value and the actual value,in the LMC fusion system,the data level fusion uses detection data from the bottom layer sensor(temperature sensor and humidity sensor) and the state estimation,it's proposed that superior estimate method Kalman filter which is different from the conventional filter implication and the method and the wavelet packet transformation method by the reputation for the harmonic analysis history in "mathematics microscope" is proposed.From the simulation analysis of Kalman filter and wavelet packet transformation method,obviously, the wavelet packet has a very big superiority advantage to examine sudden change signal,but also the Kalman filter has the very good effect in the processing for real-time data.In characteristic level processing the data after the data level processing uses the data fusion algorithm include the improvement least square support vector machines(LSSVM) and partial least squares(PLS) regression,obtains the forecast of wood drying moisture content, and carries on the simulation and the error analysis to the forecast model,finally indicates that PLS regression can be possible to realize the very good forecast effect.Regarding non-linear regression question similar with wood drying,support vector machines algorithm based on nuclear is available.The SVM has the basis limited sample training to obtain good exude ability,and it's an general learning machine,it maps the original space into high dimensional characteristic space,makes the original classified question become a linear separable question in the characteristic space.Because the change of LMC and many kinds of parameters are related,input and output model influenced lumber moisture content change is establish by the improvement SVM algorithm,simultaneously,the parameter which is really small to the LMC change influence or does not affect is rejected.Finally,based on system basic diagram of the online detection lamination fusion system in wood drying process and Matlab graphical user interface(GUI),a LMC online detection experiment simulation platform is built.The development of data fusion technology and artificial intelligence is a new effective way enhanced the LMC real-time online detection,through the research of environment parameter and physical parameter affected the lumber moisture content,a hierarchical fusion system and function model on LMC online detection are established,The organic combination of data fusion technology,artificial intelligence theory and SVM algorithm has the important reality significance and scientific value to enhance the control system intellectualized degree and the wood drying quality and drying rate in our country and the lumber use factor.