Research On The Key Technologies Of Intelligent Combination Weighing System

With the development of intelligent combination weighing industry becoming more and more intense,nowadays,the packaging of all kinds of complex food products in the market has brought new challenges to the development of intelligent weighing industry.The traditional weighing system which can only realize the combination weighing function has been gradually marginalized,The intelligent weighing system with better comprehensive performance is quietly emerging in the weighing industry.Firstly,this paper analyzed the current development of intelligent weighing system at home and abroad.It is concluded that the domestic intelligent weighing system has a great improvement in the aspects of improving the operation efficiency,reducing the economic cost and improving the weighing accuracy.Based on the present situation,this paper studied the following four aspects of the intelligent weighing system.1.Structural optimization design.Aiming at the improvement of traditional intelligent weighing system,Including improvement of motor drive mode?application of "double row"function poly hopper?the former reduces motor motion lash,the latter saves time in waste disposal;meanwhile corrugating surface of the hopper to reduce friction,improve conveying speed,thus to improve operating efficiency.2.Static model analysis.To system important components-main vibrator feeder,static analysis is carried out in theory,the mathematical model of motion is established,researched the influence of damping on the relative amplitude of the tray and the chassis is analyzed and the condition of material throwing motion.3.Dynamic feature analysis.Dynamic characteristic analysis was based on static analysis,three dimensional digital model of weighing system based on SolidWorks,the modal and hannonic response analysis of the intelligent weighing system is carried out by using ANSYS Workbench software,and simulation analysis using MATLAB/Simulink module,the results show that the device is designed to meet the requirements of resonance and the displacement of the particles;the response curves of displacement and velocity of the particles are in accordance with the requirements of the working conditions.4.Research on error compensation.The nonlinear error is compensated by BP neural network algorithm,had a better compensation effect,relative error controled within ±0.2%,the error value is far less than the hardware error compensation method under the ±0.6%;this method reduces the cost relative to hardware compensation,improved the accuracy.