articleScience China Technological SciencesJan 27, 2026Closed access

Unsupervised subdomain contrastive adaptation for elevator fault diagnosis based on time-frequency feature attention mechanism segmentation

CFChenyu FengHSHao SunPXPengcheng XiaCQChengjin QinZZZhinan Zhang

Shanghai Jiao Tong University · Mitsubishi Group (Japan)

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Abstract

No abstract available for this paper.

Citation impact

5
total citations
FWCI
78.16
Percentile
100%
References
31
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Authors

9

Topics & keywords

Topics
Keywords
  • Feature (linguistics)
  • Elevator
  • Pattern recognition (psychology)
  • Fault (geology)
  • Domain (mathematical analysis)
  • Set (abstract data type)
  • Segmentation
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