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MULTI-OBJECTIVE PARAMETER OPTIMIZATION OF μ-EDM ON GREY RELATIONAL ANALYSIS AND ENTROPY WEIGHT METHOD (MT)
In order to meet the requirements of machining accuracy indexes such as the entry, exit and shape of micro-hole, a multi-objective parameter optimization weigh method for micro electrical discharge machining（EDM） based on grey relational analysis（GRA） and entropy weight method is proposed.By designing orthogonal experiment and processing test for H62 brass, the grey relational coefficient of each index of the experiment result sequence is calculated.The entropy weight method and grey relational analysis method are used to comprehensively evaluate the model, and the grey relational degree of each experiment sequence is obtained, and the mean value analysis is carried out to realize the transformation from multi-objective optimization to single objective optimization.The research results show that the entry Overcut（EnOV）, exit Overcut（ExOV） and taper（TA） of the optimized process parameters are reduced by 8.97%, 4.11% and 8.33% respectively compared with those of the H-22 group with the largest grey relational degree, and the machining accuracy of micropores is improved.
MULTI-OBJECTIVE PARAMETER OPTIMIZATION OF μ-EDM ON GREY RELATIONAL ANALYSIS AND ENTROPY WEIGHT METHOD (MT)
In order to meet the requirements of machining accuracy indexes such as the entry, exit and shape of micro-hole, a multi-objective parameter optimization weigh method for micro electrical discharge machining（EDM） based on grey relational analysis（GRA） and entropy weight method is proposed.By designing orthogonal experiment and processing test for H62 brass, the grey relational coefficient of each index of the experiment result sequence is calculated.The entropy weight method and grey relational analysis method are used to comprehensively evaluate the model, and the grey relational degree of each experiment sequence is obtained, and the mean value analysis is carried out to realize the transformation from multi-objective optimization to single objective optimization.The research results show that the entry Overcut（EnOV）, exit Overcut（ExOV） and taper（TA） of the optimized process parameters are reduced by 8.97%, 4.11% and 8.33% respectively compared with those of the H-22 group with the largest grey relational degree, and the machining accuracy of micropores is improved.
MULTI-OBJECTIVE PARAMETER OPTIMIZATION OF μ-EDM ON GREY RELATIONAL ANALYSIS AND ENTROPY WEIGHT METHOD (MT)
MO YuanDong (author) / LIAN HaiShan (author) / WANG YaZhi (author) / HUANG ShuQi (author) / ZHONG JiaJun (author)
2023
Article (Journal)
Electronic Resource
Unknown
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