外文翻譯--- 關于工藝參數(shù)對熱擠壓鎂合金影響的研究

1、 關于工藝參數(shù)對熱擠壓鎂合金影響的研究1Investigation of the influence of process parameters onhot extrusion of magnesium alloy tubesAbstract: During the hot extrusion of magnesium alloy, the change of process parameters will affect the m

2、echanical properties of extruded products. In this study, Taguchi method and analysis of variance (ANOVA) are applied to analyze the influence of process parameters on the hot extrusion of magnesium alloy tubes under ext

3、rusion ratio of 21.05. The experiments are arranged by orthogonal array method in which magnesium alloys AZ31and AZ61 are used as outer arrays, the factors selected as inner arrays are the billet heating temperature, th

4、e initial extrusion speed, the container temperature and the lubricants. The extruded tubes will be carried out tensile test and flattening test, the test results are analyzed by the quality measurement of Taguchi metho

5、d to find the relationship between the process parameters and mechanical properties of the products, and to acquire the optimal combination of parameters. Then based on the results obtained from the additive model, conf

6、irmatory experiments are performed. Besides, the microstructures of extruded tubes are observed to clarify the influence of process parameters on the grain size. Finally, with the same extrusion condition, the variation

7、s in tensile strength and flattening strength due to different compositions are discussed.© 2007 Elsevier B.V. All rights reserved.Keywords: Hot extrusion tube; Magnesium alloy; Mechanical properties; Taguchi metho

8、d; Orthogonal array1. IntroductionMagnesium alloy has low specific gravity, high specific strength, good ventilation and shock absorption. It is also opaque to electromagnetic waves and recycle. In recent years, magnes

9、ium alloy has begun to replace steel, aluminum and plastic as products have become increasingly miniaturized. Magnesium alloy is 35% and 77% less dense than aluminum alloy and steel, respectively. Therefore, as lightwei

10、ght products, environmental protection and recyclability become increasingly important, the demand for magnesium alloy has increased and been extensively applied to the automobile industry, the bicycle industry, the ae

11、rospace and national defense industries, the civic product manufacturing industry and the 3C (computer, communication and consumer electronic) electronic industry.At present, die casting is the main method for forming a

12、nd processing magnesium alloy.Wu and Chang used the Taguchi method in the die casting of magnesium alloy to produce a cover for a personal data assistant (PDA), and thus to identify the optimal process parameters. Taku

13、daetal adopted the finite element method to analyze the formability of AZ31 magnesium base material during deep drawing. Finite 關于工藝參數(shù)對熱擠壓鎂合金影響的研究3properties. S/N ratios are one of the three forms – the normal-the-best,

14、 the smaller-the-better and the larger-the-better. The mechanical property discussed herein is tensile strength. It is the larger-the-better characteristic. Therefore, an S/N ratio that is the larger-the-better is used

15、, and is given in Eq. (1).(1)in the equation, n stands the total number of measurements, and yi the measured quality value. The i in the suffix refers to the number of the experiment in the plan based on orthogonal arra

16、ys, and the calculated S/N ratio is used in the factor response statistical analysis, and the optimal combination of process parameters can be obtained.2.2. Application of analysis of varianceThe statistical analysis of

17、variance (ANOVA), used in the Taguchi method, is adopted mainly to evaluate the significance level of experimental errors and every factor response. The equationsused in the ANOVA statistical analysis in this study are a

18、s follows. (1) Sum of squares of the factor effect vector, SSfactor(2)where n is the number of times the experiment is performed, r is the number of times the experiment is repeated, L is the number of factor levels, yk

19、is the response value of that factor at level k, and ym is the average of all experimental data.(2) Sum of squares of the total variation vector, SStotal(3)where yij stands for the j experiment data of the its set of exp

20、eriment. (3) Error sums of squares, SSe SSe = SStotal – SSfactor (4)(4) Degree of freedom of the factor effect vector, DOFfactor DOFfactor = L ? 1 (5)(5) Degree of fre

21、edom of the total variation vector noises, DOfactor DOfactor = n × r ? 1 (6)(6) Variance of the factor, Vi(7)iii DOFSS V ?(7) Distribution of the predicted values of the two variances, F(8