基于红外光谱技术智能识别润滑油的研究进展
Research Progress on Intelligent Identification of Lubricants Based on Infrared Spectroscopy
冯欣 1夏延秋1
作者信息
- 1. 华北电力大学能源动力与机械工程学院,北京 102206
- 折叠
摘要
机器学习作为人工智能发展的核心,在各行业得到快速发展,近年来也成为润滑油领域研究的热点之一,标志着润滑油的研究不再局限于大规模的试验研究,高通量数据、机器学习、优化算法开始应用于润滑油的研究.文章介绍了基于红外光谱技术在润滑油种类鉴别、润滑剂筛选、润滑性能评估和润滑监测等方面的研究进展,并对未来基于红外光谱技术应用于智能识别润滑油的研究进行了展望.
Abstract
Machine learning,as the core of artificial intelligence development,has experienced rapid growth in various indus-tries.In recent years,it has also become one of the hot topics in the field of lubricants,signifying that lubricant research is no longer limited to large-scale experimental studies.High-throughput data,machine learning,and optimization algorithms are now being applied to lubricant research.The paper introduces the research progress in the areas of lubricant type identifica-tion,lubricant selection,lubrication performance evaluation,and lubrication monitoring based on infrared spectroscopy tech-nology.It also provides an outlook on application of intelligent identification of lubricants based on infrared spectroscopy.
关键词
红外光谱/润滑油/添加剂/润滑性能/智能识别Key words
infrared spectroscopy/lubricating oil/additives/lubrication performance/intelligent identification引用本文复制引用
基金项目
北京市自然科学基金(2232066)
固体润滑国家重点实验室开放课题(LSL-2212)
出版年
2024
NETL
NSTL
万方数据