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Research On Theory And Technology Of Surface Polishing Based On Multi-Axis Micro-Motion Tool System

Posted on:2022-10-15Degree:MasterType:Thesis
Country:ChinaCandidate:H ChenFull Text:PDF
GTID:2481306329991029Subject:Mechanical engineering
Abstract/Summary:PDF Full Text Request
The manufacturing industry is the main body of the national economy,the foundation of the country,the tool for rejuvenating the country,and the foundation for a strong country.Following the proposal of the"Made in China 2025"plan.The demand for free-form parts with high surface quality in military and civilian fields such as national defense,aerospace,biomedicine,and optical machinery is also increasing.Therefore,how to manufacture free-form surfaces with high precision and high efficiency has always been the focus of research institutions at home and abroad.Polishing is considered to be one of the most effective ways to improve the surface quality of free-form surfaces.In the polishing process,since most CCOS polishing equipment mainly achieves grinding and polishing removal by changing the residence time,it inevitably has disadvantages such as low efficiency.This paper mainly addresses the problems of low polishing efficiency and poor accuracy in the deterministic polishing process of optical curved surfaces,and proposes a polishing method that controls the contact pressure in real time.1.This article first determines the weights of polishing pressure,spindle rotation speed,and residence time on the depth of removal.In order to analyze the weight of the above three influencing factors on the depth of cut,an orthogonal test table of12(61×42)was designed.During the machining process,the depth of cut is measured at different machining times,different cutting forces and different spindle speeds.The processed data was perfected to the orthogonal test table and the conclusion was reached:the maximum and average cutting depth were used as the evaluation criteria.The most important influencing factor was residence time,followed by polishing force,and finally the spindle rotation speed.2.After drawing the conclusion,establish the removal model of fixed-point polishing based on Preston's equation.According to the Herz contact theory and other contact mechanics,the pressure distribution is analyzed.According to the position and posture of the polishing head when it is in contact with the surface of the workpiece,the speed analysis of each point in the polishing contact area is carried out.And according to the pressure distribution and velocity distribution,the material removal model of the tool head polishing along different trajectories is established.3.In order to realize the force control of the tool system,this paper uses Simulink real-time toolbox to build a traditional PID force control program and a force control program based on fuzzy neural network PID(FNN-PID)on the workstation.Then the polishing force control experiment was carried out using the control program.The control experiment where the input signal is a constant force signal,the control experiment where the input signal is a stepped force signal,and the control experiment where the input signal is a sinusoidal force signal all show that compared to the traditional PID control strategy,the fuzzy neural network PID control strategy has a small Lag,fast response,fast callback and other advantages.4.Finally,experiment with the multi-axis micro-motion tool system developed in the laboratory.First,the spiral polishing track is designed based on the multi-axis micro-motion tool system.During the experiment,the machine tool is responsible for clamping the workpiece and moving the workpiece by moving the X,Y,and Z axes until the workpiece is in contact with the tool head.The main rod in the tool system is responsible for controlling the size of the polishing pressure,and the remaining three rods are responsible for making the tool head move in accordance with the established trajectory.The experimental results better verify the feasibility of the method.
Keywords/Search Tags:Free-form surface, Fuzzy neural network, Semi-physical simulation control, Material removal depth
PDF Full Text Request
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