Prediction Method of Monitoring Data Based on Data Correlation in Civil Engineering
Wireless intelligent health monitoring has been widely used in civil engineering. However, ill-conditioned data could be generated due to the vulnerability to external interference sometimes. The ill-conditioned data have great influence on damage identification and condition assessment. Hence, the...
Gespeichert in:
Veröffentlicht in: | IOP conference series. Earth and environmental science 2020-09, Vol.567 (1), p.12017 |
---|---|
Hauptverfasser: | , , , , , |
Format: | Artikel |
Sprache: | eng |
Schlagworte: | |
Online-Zugang: | Volltext |
Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
Zusammenfassung: | Wireless intelligent health monitoring has been widely used in civil engineering. However, ill-conditioned data could be generated due to the vulnerability to external interference sometimes. The ill-conditioned data have great influence on damage identification and condition assessment. Hence, the prediction method of monitoring data based on data correlation was presented in this paper. The correlation degree between multi-channels data was established by BP neural network. Then the ill-conditioned data was predicted and corrected by the correlation degree between the data, and verified by the measured data. The results indicated that high accuracy and engineering requirement could be achieved using BP neural network prediction method considering the correlation degree between multi-channels data. |
---|---|
ISSN: | 1755-1307 1755-1315 |
DOI: | 10.1088/1755-1315/567/1/012017 |