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Table 2. The Regression Result of Work Time and Factors 表2 可使用时间数据回归分析结果


Variable 自变量


Constant 常量


Sand grain size 型砂粒度


Addition of resin


树脂加入量(%) Addition of curing agent


固化剂加入量(%) Sand Temperature


砂温(℃) Total acid content of curing agent


固化剂总酸度(%) Ambient temperature


环境温度(℃) Ambient humidity


环境湿度(%) S = 2.52570 R-Sq = 72.6% R-Sq(调整 adjusted) = 72.2%


Note: S denotes standardized residuals. T refers to the deleted t residuals. P refers to the significant level of variables, indicating whether a specific variable is significant in the case of the presence of other variables. R-Sq represents the variability of dependent vari- able. R-Sq (adjusted) is the degree of freedom, as the variable is not a true value.


注: 1、S表示标准化残差; T指删后t化残差; 2、P是指各项自变量的显著性水平, 表示存在其它自 变量的情况下一个特定的变量是否显著; 3、R-Sq 表示方程解释了因变量变异性的百分比; R-Sq(调整): 由于变量没有真实值时的自由度;


-0.55413 -0.07975 0.08450 0.02606 0.01742 0.01313 -21.27 -4.58 6.43 0.000 0.000 0.000


Coefficeints 系数


25.295 0.22573 6.021 -0.29389 -0.53910


Standard Deviation of Coefficients 系数标准误


1.659 0.02029 1.023 0.02007 0.01908 T 15.25 11.12 5.88 -14.64 -28.25 P 0.000 0.000 0.000 0.000 0.000


Time (min) = 25.3 + 0.226 × molding sand grain


size +6.02 × resin addition (%) - 0.294 × curing agent addition(%) - 0.539 × sand temperature (°C) - 0.554 × curing agent total acid content (%) - 0.0798 × ambient temperature (°C) + 0.0845 × ambient humidity (%) Te results after stepwise multiple regressions are listed


in Table 3. Te results show these factors are arranged sequentially


as: sand temperature, the total acid content of curing agent, curing agent addition, molding sand grain size, and environmental humidity, resin addition, and ambient tem- perature from strong to weak where ambient temperature is automatically deleted as it has no significant effect. To verify the accuracy of the stepwise regression, the best subset method was used. The results are listed in Table 4.


By the best subset method, the main factors for work


time rank as sand temperature, addition of curing agent, total acid content of the curing agent from strong to week, which is in agreement with the multiple stepwise regression results. Terefore, time stepwise regression results were veri- fied to be accurate.


Tensile Strength Data Processing Te relationship between tensile strength and factors


such as molding sand grain size, ash content, resin addi- tion, curing agent addition, ambient temperature and ambient humidity was analyzed in Minitab. Te diverse functional relationship between tensile strength and these factors was acquired, and the results are listed in Table 5. Te regression equation is:


加入量、固化剂加入量、砂温、固化剂总酸度、环境温 度、环境湿度关系的试验数据进行回归分析, 其结果如 表2所示。


回归分析后得到可使用时间与各影响因素的多元一次 函数关系式为:


可使用时间(min)=25.3+0.226×型砂粒度 +6.02×树脂加入量(%)- 0.294×固化剂加入量(% )-0.539×砂温(℃)- 0.554×固化剂总酸度(% )-0.0798×环境温度(℃)+0.0845×环境湿度(%) 对数据进行多元逐步回归, 结果表3所示: 由以上结果可知可使用时间各因素影响大小依次为: 砂温、固化剂总酸度、固化剂加入量、型砂粒度、环境 湿度、树脂加入量、环境温度, 其中环境温度影响不显 著, 系统已自动删除。为了验证可使用时间逐步回归的 准确性, 用最佳子集法进行核实, 结果表4所示。 采用最佳子集法得到可使用时间主要影响因素依次为 砂温、固化剂加入量、固化剂总酸度, 结果与多元逐步 回归所得结果一致, 验证了可使用时间逐步回归结果是 准确的。


2.2 抗拉强度数据处理


利用Minitab软件对抗拉强度与型砂粒度、灰分、树 脂加入量、固化剂加入量、环境温度、环境湿度关系的 实验数据进行回归分析, 得到抗拉强度与各影响因素的 多元一次函数关系式。得到的分析结果如表5所示。抗 拉强度与各影响因素的回归方程为:


60 | FOUNDRY-PLANET.COM | MODERN CASTING | CHINA FOUNDRY ASSOCIATION February 2013


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