| 引用本文: | 余思锐,宋孟杰,沈俊,孙小琴,王海东,高润淼.低温静止与运动表面结冰特性预测技术研究进展[J].哈尔滨工业大学学报,2024,56(10):150.DOI:10.11918/202402006 |
| YU Sirui,SONG Mengjie,SHEN Jun,SUN Xiaoqin,WANG Haidong,GAO Runmiao.Research progress on icing characteristic prediction technologies for low temperature stationary and moving surfaces[J].Journal of Harbin Institute of Technology,2024,56(10):150.DOI:10.11918/202402006 |
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| 低温静止与运动表面结冰特性预测技术研究进展 |
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余思锐1,宋孟杰1,2,沈俊1,孙小琴3,王海东4,高润淼1
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(1.北京理工大学 机械与车辆学院,北京 100081;2.汉阳大学 机械工程学院,首尔 04763;3.长沙理工大学 能源与动力工程学院,长沙 410004;4.清华大学 航天航空学院,北京 100084)
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| 摘要: |
| 结冰是一种常见的自然现象,在工业生产流程中也广泛存在,且往往对生活生产造成不利影响。有效运用结冰特性预测技术,可显著降低甚至杜绝各行业因结冰导致的潜在危害。既有研究表明,使用结冰特性预测技术后路面交通事故率可降低65%,若进一步结合除冰系统,能在80%的结冰场景下实现表面高效防除冰。为有效规避各行业冰灾问题,分别基于道路、输电线两类静止表面与风机叶片、飞机两类运动表面的既有结冰特性预测技术进行了综述与分析,结果表明,对于静止表面,既有技术对结冰厚度等指标的预测精度可达80%以上,运动表面则可达70%以上。既有结冰特性预测技术依原理差异可分为模型驱动法与数据驱动法两种,其中数据驱动法具有很大发展潜力。基于归纳总结的应用于静止与运动两种状态下4种简单冷表面的结冰预测技术,进一步提出该领域的重点研究方向,以期为各类工程场景中低温表面的防除冰技术开发与优化提供参考借鉴。 |
| 关键词: 结冰特性预测 道路表面 风机叶片 输电线 飞机表面 模型驱动 数据驱动 |
| DOI：10.11918/202402006 |
| 分类号:U492.8 |
| 文献标识码:A |
| 基金项目:国家自然科学基金(52076013)；北京市自然科学基金(3212024)；2023年度中韩青年科学家交流计划 |
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| Research progress on icing characteristic prediction technologies for low temperature stationary and moving surfaces |
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YU Sirui1,SONG Mengjie1,2,SHEN Jun1,SUN Xiaoqin3,WANG Haidong4,GAO Runmiao1
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(1.School of Mechanical Engineering, Beijing Institute of Technology, Beijing 100081, China; 2.School of Mechanical Engineering, Hanyang University, Seoul 04763, Republic of Korea; 3.School of Energy and Power Engineering, Changsha University of Science & Technology, Changsha 410004, China; 4.School of Aerospace Engineering, Tsinghua University, Beijing 100084, China)
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| Abstract: |
| As a common natural phenomenon, icing is widespread in industrial production processes and often causes adverse effects on daily life and production. The potential hazards caused by icing in various industries could be significantly reduced or even eliminated by using ice characteristics prediction technologies. Previous studies have shown that the rate of road traffic accidents can be reduced by 65% after using ice characteristic prediction technology. Furthermore, when combined with the de-icing system, 80% of icing scenarios can be anti-icing or de-icing. To effectively address the issue of ice disasters across various industries, this review provides an overview and analysis of existing icing prediction technologies based on stationary surfaces such as road and transmission line, as well as moving surfaces such as wind turbine blade and aircraft. The results indicate that existing technologies achieve prediciton accuracies of over 80% for indicators such as ice thickness on stationary surfaces and over 70% for moving surfaces. Existing ice characteristic prediction technologies can be divided into two types, model-driven method and data-driven method, with the later showing significant potential for development. Based on the summarized ice prediction technologies applied to four simple cold surfaces under stationary and moving states, this paper further proposes key research directions in this field, aiming to provide reference and guidance for the development and optimization of anti-icing technologies on low-temperature surfaces in various engineering scenarios. |
| Key words: ice characteristic prediction road surface wind turbine blade transmission line aircraft surface model-driven data-driven |
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