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Analytical Chatter Stability And Robust Optimization Of Milling System

Posted on:2015-05-11Degree:MasterType:Thesis
Country:ChinaCandidate:S LiFull Text:PDF
GTID:2271330482952560Subject:Mechanical design and theory
Abstract/Summary:PDF Full Text Request
High-speed cutting is the prerequisite to ensure the high performance and high precision machining, which is the basis for the optimization. Dynamic modeling, stability prediction, time-domain simulation, experiments and multi-objective optimization about end milling system are analyzed in this article. Some guidelines are made to ensure stable processing in milling.Considering the transient changes of cutting thickness in the process, regression chatter model is built to predict the cutting limit in axial direction. The time finite element method is used to get the stable lobe diagrams of considering and not consider the helix angle of tool. Then the influences of multi-order modal parameters to the stable lobe diagrams are analyzed, and bifurcations of milling system under different situations are obtained.The model of instantaneous cutting thickness is built, and time-domain simulation is carried out to analyze the cutting process. Cutting force coefficient test is carried out on 7050 aluminium alloy, and the results coincide with the simulation results. Through analyzing the cutting force and frequency spectrum signals, different unstable cases are sorted and the efficiency of the model of multi-order stability anticipation is verified.In the last part of the article, taking the maximum material removing rate and the minimum surface location error as optimization objects, multi-objective robust optimization for cutting parameters are made by a robust sensitivity method and the Latin-Hypercube sampling method, and the acquisition of Pareto fronts can be used as the guidelines of high precisely and high efficiently milling.
Keywords/Search Tags:high-speed milling, stability, time finite element method, time-domain simulation, robust optimization
PDF Full Text Request
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