收藏切换
Real-Time Dynamic Response Identification for Highway Structural Health Monitoring Data
收藏切换
PDF
Zhixin Qi1, Xin Su1, Yulin Wang1, Zemin Chao1, Zejiao Dong1, Hongzhi Wang1
Data Science and Engineering | 2026, 11(1) : 248 - 259
Less
收藏切换
Data Science and Engineering | 2026, 11(1): 248-259
RESEARCH PAPERS
Real-Time Dynamic Response Identification for Highway Structural Health Monitoring Data
Full
Zhixin Qi1, Xin Su1, Yulin Wang1, Zemin Chao1, Zejiao Dong1, Hongzhi Wang1
Affiliations
Published: 2026-03-01 doi: 10.1007/s41019-025-00336-4
Outline
收藏切换

The high sampling frequency of highway structural health monitoring systems brings a heavy burden on data storage. However, existing dynamic response identification approaches can guarantee either reduced data volume after identification or high accuracy of dynamic response identification. Motivated by this, we propose a real-time dynamic response identification method to filter meaningless data. Our method not only selects effective features from highway structural health monitoring data, but also designs a training data generation strategy for machine learning models within the dynamic response identification framework. Experimental results on real highway structural health monitoring data demonstrate that our proposed approach spends 0.4 ms to process the monitoring data generated in 1 s and saves around 91.63% storage space. Also, the recall value of our method achieves 0.91 on average.

Monitoring data  /  Real-time identification  /  Feature selection  /  Machine learning  /  Model training
Zhixin Qi, Xin Su, Yulin Wang, Zemin Chao, Zejiao Dong, Hongzhi Wang. Real-Time Dynamic Response Identification for Highway Structural Health Monitoring Data[J]. Data Science and Engineering, 2026 , 11 (1) : 248 -259 . DOI: 10.1007/s41019-025-00336-4
  • National Key Research and Development Program of China(2024YFE0214600)
  • National Natural Science Foundation of China(52308449)
Year 2026 volume 11 Issue 1
PDF
51
12
Cite this Article
BibTeX
Article Info
doi: 10.1007/s41019-025-00336-4
  • Receive Date:2025-04-28
  • Online Date:2026-08-06
  • Published:2026-03-01
Article Data
Affiliations
History
  • Received:2025-04-28
  • Revised:2025-10-23
  • Accepted:2025-12-07
Funding
National Key Research and Development Program of China(2024YFE0214600)
National Natural Science Foundation of China(52308449)
Affiliations
    1Harbin Institute of Technology, Huanghe Road 73, Harbin, Heilongjiang, China

Corresponding:

Zhixin Qi 
References
Share
https://castjournals.cast.org.cn/joweb/dse/EN/10.1007/s41019-025-00336-4
Share to
QR

Scan QR to access full text

Cite this article
BibTeX
Citations
表12种不同金属材料的力学参数

Family
属数
Number of
genus
种数
Number of
species
占总种数比例
Percentage of
total species (%)

Genus
种数
Number of
species
占总种数比例
Percentage of total
species (%)
鹅膏菌科Amanitaceae 2 11 5.26 鹅膏菌属 Amanita 10 4.78
小菇科 Mycenaceae 2 12 5.74 丝盖伞属 Inocybe 5 2.39
多孔菌科 Polyporaceae 8 14 6.70 蜡蘑属 Laccaria 5 2.39
红菇科 Russulaceae 3 23 11.00 小皮伞属 Marasmius 6 2.87
小菇属 Mycena 11 5.26
光柄菇属 Pluteus 5 2.39
红菇属 Russula 17 8.13
栓菌属 Trametes 5 2.39
关闭全屏
  • BibTeX
  • EndNote
  • RefWorks
  • TxT