骆晓雨,方伦彬,袁小虎,乔翔,赖建平,余家欣.基于回归分析的Mar M247镍基高温合金喷砂工艺预测与优化[J].表面技术,2024,53(17):176-185, 195.
LUO Xiaoyu,FANG Lunbin,YUAN Xiaohu,QIAO Xiang,LAI Jianping,YU Jiaxin.Prediction and Optimization of Sandblasting Process for Mar M247 Nickel-based Superalloy Based on Regression Analysis[J].Surface Technology,2024,53(17):176-185, 195 |
| 基于回归分析的Mar M247镍基高温合金喷砂工艺预测与优化 |
| Prediction and Optimization of Sandblasting Process for Mar M247 Nickel-based Superalloy Based on Regression Analysis |
| 投稿时间：2023-09-21 修订日期：2024-03-04 |
| DOI：10.16490/j.cnki.issn.1001-3660.2024.17.016 |
| 中文关键词: 镍基高温合金 喷砂工艺 表面质量 数理统计 回归分析 工艺预测 |
| 英文关键词:nickel-based superalloy sandblasting surface quality mathematical statistics regression analysis process optimization |
| 基金项目:国家科技重大专项(2019-711-0007-0147);国家重点研发计划(2020YFB2010402);西南科技大学研究生创新基金(24ycx2044);清洁高效透平动力装备全国重点实验室开放课题(DEC8300CG202319357EE280491) |
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| Author | Institution |
| LUO Xiaoyu | School of Manufacturing Science and Engineering, Southwest University of Science and Technology, Sichuan Mianyang 621010, China ;State Key Laboratory of Clean and Efficient Turbomachinery Power Equipment, Sichuan Deyang 618000, China |
| FANG Lunbin | State Key Laboratory of Clean and Efficient Turbomachinery Power Equipment, Sichuan Deyang 618000, China |
| YUAN Xiaohu | State Key Laboratory of Clean and Efficient Turbomachinery Power Equipment, Sichuan Deyang 618000, China;School of Materials Science and Engineering, Chongqing University, Chongqing 400044, China |
| QIAO Xiang | Market Supervision Administration of Changsha County, Changsha 410100, China |
| LAI Jianping | School of Manufacturing Science and Engineering, Southwest University of Science and Technology, Sichuan Mianyang 621010, China |
| YU Jiaxin | School of Manufacturing Science and Engineering, Southwest University of Science and Technology, Sichuan Mianyang 621010, China |
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| 中文摘要: |
| 目的 针对燃机叶片用Mar M247镍基高温合金，建立多因素喷砂工艺的高精度预测模型，筛选出粗糙度较高而夹砂率较低的工艺组合。方法 采用国产精工自动化精控喷砂系统制备试样。使用便携式表面粗糙度仪、激光显微镜和扫描电子显微镜进行检测。基于数理统计的分析方法，建立喷砂工艺与表面质量之间的函数关系。结果 当喷砂角度从30°增至90°时，粗糙度和夹砂率都单调递增，且夹砂率在低角度(30°~60°)比在高角度(60°~90°)增加的速率更高。喷枪移动速度从1 mm/s增至20 mm/s，粗糙度呈现先减少后增加再减少的趋势;夹砂率呈现先增加后减少的趋势。对于粗糙度，线性回归模型的预测误差率为5.97%，多项式回归模型的预测误差率为5.15%;对于夹砂率，线性回归模型的预测误差率为5.76%，多项式回归模型的预测误差率为3.08%。结论 基于现有的数据，采用多项式和线性2种回归模型进行预测，多项式回归模型的预测精度比线性回归模型更高。结合现有的数据和多项式回归模型的预测数据得出了最佳工艺范围，喷砂压力为0.2~0.3 MPa，喷砂角度为45°~60°，喷枪移动速度为15~20 mm/s。在该条件下，得到了较高的粗糙度和较低的夹砂率，有利于获得高的涂层/基材界面结合强度。 |
| 英文摘要: |
| The work aims to establish a high-precision model of the multivariate sandblasting process for Mar M247 Ni-based superalloy used as gas turbine blade and used it to design the process combination that can realize surface quality of high roughness and low fraction of retained grit. |
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