Research On Intelligent Compensation Control System For Feeding Platform Of Woodworking Band Saw

The feeding platform of woodworking band saw is a new type of artificial intelligent processing equipment.All kinds of errors caused by the movement of the platform will affect the sawing accuracy,due to the different thickness and hardness of material,the required cutting force is also different,resulting in the need of adjusting the speed of motor and the feed rate of the platform.Therefore,it is very important to study a dynamic error-compensation-control system adapted to the feeding platform.Therefore,this paper analyzes the various errors and control parameters in the process of installation and movement of the feeding platform,and studies the compensation control algorithm of the feeding platform,so as to improve the machining accuracy of the curve band saw and the feeding platform.According to the manual feeding action,this paper analyzes the overall kinematic relationship of the curve feeding platform of woodworking band saw and the causes of the error types.According to the relationship between the position error of the lead screw and the position error of the slide bar in X direction and the position error of the slide bar in Y direction.Using the characteristics of Codesys platform supporting multi environment programming and the functions of communication and data acquisition,two control strategies are given.On this basis,a control strategy of improving genetic algorithm and optimizing recurrent neural network is proposed.The control system structure diagram is drawn,and the control system principle and the realization of intelligent processing are explained.A simulation experiment was carried out in Matlab to improve genetic algorithm and optimize the parameters of the recurrent neural network.The experimental results show that the optimized network control is more effective,and it is more suitable to use this algorithm as the feeding platform error compensation control algorithm.Use Solidworks to establish the three-dimensional modeling of the feeding platform,then import the established model into Adams.Matlab and Adams are combined to carry out simulation experiments and simulated processing experiments for several proposed error compensation strategies with the feeding platform as the control object.The results are analyzed,and the dynamic adjustment table of the motor speed of each optimized algorithm are given.The experimental prototype of the feeding platform and band saw machine and the complete control system are built,and the program's running and operation interface in Codesys are given.The error compensation control system of the feeding platform has been experimentally verified.The results show that the three control strategies of genetic,recursive neural network and genetically optimized recursive neural network can compensate for the error,but the compensation effect of the last control strategy is the best,which can effectively improve the processing accuracy of the feeding platform and make the processing results achieve the desired results.These indicate that the feeding platform designed in this paper and the compensation control strategy proposed in this paper are feasible.The relationship between the error and the number of motor revolutions of different materials is given,which proves that the control system proposed in this paper is more intelligent and superior than the traditional control system.