Development Of Intelligent Saw Cutting Equipment For Burr Sawn Timber

This article combines the school-enterprise cooperation project"Roundwood automated processing and sorting and palletizing integrated equipment development".For the status quo concerning the semiautomatic processing and manual inspection of sawdust in the country and based on the research results of relevant woodworking equipment at home and abroad,combining the inspection and sawing requirements of burr sawn timber,with the aim of maximizing the utilization ratio of materials and maximizing economic efficiency,the machine vision inspection technology,virtual instrument technology and mechatronics technology are used to design a set of intelligent sawing equipment for burr sawing which is designed to intelligently process raw sawn timber into spliced raw materials for sawn timber,and to solve the problems of traditional visual inspection methods,such as processing of raw burr saw materials,high labor intensity,low material yield,and low efficiency.Through series of tests,the feasibility and high efficiency of the intelligent sawing equipment for the set of burr saws were verified.In terms of mechanical structure,based on the process of burr sawing,sawing and sorting,the 550-25-3D mechanical flash edge sawing machine was used as the design basis,and the modular design concept was used to design the raw edge sawn materials.The posture adjustment device achieves a good posture state when the burr sawing material is being sawed intelligently.A dynamic woodworking multi-segment saw with selfadjustable distance between adjacent circular saw blades was designed to realize intelligent sawing processing of burr saw materials within a certain width specification range.A mobile sorting device was designed to efficiently sort the burrs and parallel edged lumber generated during the later sawing period.And use CREO software to model the key structure of the equipment.In the visual inspection system,the Lab VIEW software and the VDM vision development platform are used to establish a machine vision inspection system,which performs image pre-processing,burr straight edge detection,edge intersection detection,and effective sawing range operations on the burr sawn material image in turn,thereby realizing a burr saw non-contact,multi-objective real-time detection of material dimensions,pose states,and burr morphology.A sawing control system for the "PC+PLC+Driver" frame structure was designed.Through Lab VIEWPLC joint control,the burr lumber orientation was adjusted to the target loading position on the sawn timber position adjustment structure,and then the adjacent circle was aligned.The dynamic woodworking multi-segment saw with independently adjustable saw blade spacing is used for intelligent sawing of burr saw materials.Finally,automatic sorting of raw edges and effective sawn materials is performed.The machine vision motion control system can realize intelligent processing of different kinds of raw edge lumber according to users requirements through presetting.In terms of test analysis,test analysis was conducted from three aspects:mechanical structure,edge detection,and control system.Through CREO virtual prototype motion simulation,it is confirmed that there is no interference phenomenon in the motion process of each mechanism.Through the self-designed machine vision inspection test platform,the key technologies of the visual inspection and control system are verified.The test platform has good effect on the image processing of the raw edge lumber.The absolute error between the three measurements of the effective sawn timber width and the manual vernier caliper is not more than 2mm.During the test process,the image processing process and the control system of the human-machine interaction interface are all displayed normally,the interface operation is convenient and smooth,the profibus communication between the upper and lower position machines is good,and the system can effectively execute the preset instructions.The maximum production efficiency of the equipment theory is 12 blocks/min,which is significantly improved compared to the mechanical edge machine with a processing efficiency of 6.2 blocks/min.