article·Journal of Manufacturing Systems·Feb 11, 2025Closed access

Swin-fusion: An adaptive multi-source information fusion framework for enhanced tool wear monitoring

KHKailin HouRLRongyi LiCorresponding authorXLXianli LiuCYCaixu YueYWYing Wang

Harbin University of Science and Technology · Chinese University of Hong Kong · +1 more institution

Indexed incrossref

Abstract

No abstract available for this paper.

Citation impact

42
total citations
FWCI
78.66
Percentile
100%
References
43
Citations per year

Authors

7
  • KH
    Kailin Hou

    Harbin University of Science and Technology

  • RL
    Rongyi LiCorresponding

    Harbin University of Science and Technology

  • XL
    Xianli Liu

    Harbin University of Science and Technology, Chinese University of Hong Kong

  • CY
    Caixu Yue

    Harbin University of Science and Technology

  • YW
    Ying Wang

    North University of China

Topics & keywords

Topics
  • Primary topicAnomaly Detection Techniques and Applications97%
  • Industrial Vision Systems and Defect Detection95%
  • Advanced machining processes and optimization94%
Keywords
  • Fusion
  • Information fusion
  • Sensor fusion
  • Computer science
  • Engineering
  • Artificial intelligence
No related works found for this paper.

Funding

  • NN
    National Natural Science Foundation of China
  • NS
    Natural Science Foundation of Heilongjiang Province
  • EY
    Excellent Youth Foundation of Heilongjiang Province of China
  • SA
    Science and Technology Department, Heilongjiang Province