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Research On On-line Monitoring And Control Of Surface Roughness In Composite Drilling

Posted on:2018-06-13Degree:MasterType:Thesis
Country:ChinaCandidate:Q Y SongFull Text:PDF
GTID:2321330542481225Subject:(degree of mechanical engineering)
Abstract/Summary:PDF Full Text Request
With the extensive application of Carbon Fiber Reinforced Plastics(CFRP)in aviation and aerospace field,the current drilling process of CFRP can’t achieve uniformity of machining quality and efficiency,meanwhile,that offline optimization of the cutting parameters causes the uncertain factors in processing is becoming increasingly prominent.Based on the above consideration,quality monitoring online and control technology of drilling process for CFRP are used in this paper.Firstly,by analyzing the drilling results of the composite materials,the effects of tool wear,feed rate and the coupling effect on the roughness of the hole wall are obtained.A tool wear monitoring method with variable cutting parameters based on reference cutting force support vector machine regression identification model was proposed,and on-line monitoring of hole wall roughness was realized.Secondly,in order to ensure the quality of drilling processing.In view of the unavoidable error of the roughness monitoring process,a quality-first decision method is used to determine the quality of the roughness when determining the roughness quality state,and the "omission problem" which may occur in the most commonly used principle of accuracy.It has been verified that the method can effectively avoid the "omission problem." Thirdly,when the monitoring subsystem determines that the hole wall roughness is unqualified,the simulated annealing algorithm is used to optimize the cutting parameters under the present tool wear condition.Finally,based on the proposed method in this paper,roughness adaptive control software was developed based on the mixed programming of LabVIEW and MATLAB.The results of this paper show that the roughness adaptive control system composed of Support Vector machine Regression and Simulated Annealing algorithm for cutting parameters optimization can realize the monitoring and controlling roughness.It is a good solution to solve the problem of compromising the quality and efficiency in drilling process of CFRP in the aerospace field.
Keywords/Search Tags:Carbon fiber reinforced plastics, Tool wear, Hole wall roughness, Support vector regression, Simulated annealing
PDF Full Text Request
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