Vibration Recognition Based on Feature Extraction by Deep Autoencoder-Reference-Cited by-同舟云学术

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Vibration Recognition Based on Feature Extraction by Deep Autoencoder

Published:2023-04-14 Issue: Volume:201 Page:79-84
ISSN:
Container-title:Proceedings of the 2023 International Conference on Frontiers of Artificial Intelligence and Machine Learning
language:
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Author:

Xiong Qingsong¹^ORCID,Yuan Cheng²^ORCID,Ji Keyan²^ORCID,He Chang²^ORCID,Xiong Hai Bei²^ORCID

Affiliation:

1. State Key Laboratory of Disaster Reduction in Civil Engineering, Tongji University, Shanghai, China, China and Department of Civil and Environmental Engineering, The Hong Kong Polytechnic University, Hong Kong

2. State Key Laboratory of Disaster Reduction in Civil Engineering, Tongji University, Shanghai, China, China

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3616901.3616919

Reference12 articles.

1. Giordano PF Quqa S Limongelli MP. The value of monitoring a structural health monitoring system. Structural Safety. 2023;Vol.100:102280

2. Kijewski-Correa T, Kwon DK, Kareem A, Bentz A, Guo Y, Bobby S SmartSync: An Integrated Real-Time Structural Health Monitoring and Structural Identification System for Tall Buildings. Journal of Structural Engineering. 2013;139:1675-87

3. Lecture Notes in Networks and Systems2021;Gureev PM

4. Qi Q, Tao F. Digital Twin and Big Data Towards Smart Manufacturing and Industry 4.0: 360 Degree Comparison. IEEE Access. 2018;6:3585-93

5. Cheng Z Liao W Chen X Lu X. A vibration recognition method based on deep learning and signal processing. Engineering mechanics. 2021;38:230-46

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