| 周俊炎,王竟成,杨小奎,王津梅,周堃,舒畅.基于多层线性模型的铝合金大气腐蚀规律研究[J].装备环境工程,2023,20(6):147-154. ZHOU Jun-yan,WANG Jing-cheng,YANG Xiao-kui,WANG Jin-mei,ZHOU Kun,SHU Chang.Atmospheric Corrosion Rule of Aluminium Alloy Based on Hierarchical Linear Model[J].Equipment Environmental Engineering,2023,20(6):147-154. |
| 基于多层线性模型的铝合金大气腐蚀规律研究 |
| Atmospheric Corrosion Rule of Aluminium Alloy Based on Hierarchical Linear Model |
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| DOI：10.7643/issn.1672-9242.2023.06.019 |
| 中文关键词: 多层线性模型 铝合金 大气腐蚀 腐蚀模型 区域差异 可解释性中图分类号:TG172.3 文献标识码:A 文章编号:1672-9242(2023)06-0147-08 |
| 英文关键词:hierarchical linear model aluminum alloy atmospheric corrosion corrosion model regional difference interpretability |
| 基金项目: |
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| Author | Institution |
| ZHOU Jun-yan | Southwest Institute of Technology and Engineering, Chongqing 400039, China |
| WANG Jing-cheng | Southwest Institute of Technology and Engineering, Chongqing 400039, China |
| YANG Xiao-kui | Southwest Institute of Technology and Engineering, Chongqing 400039, China |
| WANG Jin-mei | Southwest Institute of Technology and Engineering, Chongqing 400039, China |
| ZHOU Kun | Southwest Institute of Technology and Engineering, Chongqing 400039, China |
| SHU Chang | Southwest Institute of Technology and Engineering, Chongqing 400039, China |
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| 中文摘要: |
| 目的 针对不同地区铝合金大气腐蚀差异性和样本数据利用不充分的问题，构建精度更高的铝合金大气腐蚀模型，研究铝合金在不同环境中的大气腐蚀规律。方法 基于多层线性模型，构建具备层次结构的腐蚀率模型。以某型号铝合金腐蚀数据为研究对象，逐步建立零模型、随机系数回归模型、完整模型探究大气腐蚀规律，并进行预测评估。结果 通过交叉验证进行模型评估，多层线性模型(MSE=0.001 3)优于幂函数回归(MSE=0.005 5)，远优于线性回归(MSE=0.031 6)，模型预测精度提升。多层线性模型能有效分解总方差，增强了模型的可解释性。结论 多层线性模型有效结合铝合金腐蚀数据区域差异性特征，能表征大气腐蚀规律，具有一定的实用价值。 |
| 英文摘要: |
| The work aims to establish a more accurate atmospheric corrosion model of aluminum alloy aiming at the difference of atmospheric corrosion of aluminum alloy in different regions and the insufficient use of sample data to study the atmospheric corrosion rule of aluminum alloy in different environments. Based on hierarchical linear model, the corrosion rate model with hierarchical structure was constructed. With corrosion data of a certain type of aluminum alloy as the research object, zero model, random coefficient regression model and complete model were established step by step to explore the atmospheric corrosion rule and make prediction and evaluation. Model evaluation was performed through cross validation and HLM (MSE= 0.001 3) was superior to power function regression (MSE=0.005 5) and far superior to linear regression (MSE=0.031 6), improving the prediction accuracy. HLM could effectively decompose the total variance and enhance the interpretability of the model. The HLM combined with the regional difference characteristics of aluminum alloy corrosion data can effectively characterize the atmospheric corrosion rule, which has certain practical value. |
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