共 2 条
Analysis of the dynamic behavior of structures using the high-rate GNSS-PPP method combined with a wavelet-neural model: Numerical simulation and experimental tests
被引:18
|作者:
Kaloop, Mosbeh R.
[1
,2
,3
]
Yigit, Cemal O.
[4
]
Hu, Jong W.
[1
,2
]
机构:
[1] Incheon Natl Univ, Dept Civil & Environm Engn, Incheon, South Korea
[2] Incheon Natl Univ, Incheon Disaster Prevent Res Ctr, Incheon, South Korea
[3] Mansoura Univ, Publ Works & Civil Engn Dept, Mansoura, Egypt
[4] Gebze Tech Univ, Dept Geomat Engn, Gebze, Turkey
关键词:
GNSS-PPP;
Wavelet;
Neural networks;
Structural dynamics;
SYSTEM-IDENTIFICATION;
PACKET DECOMPOSITION;
GPS RECEIVERS;
NETWORK MODEL;
RECORDS;
D O I:
10.1016/j.asr.2018.01.005
中图分类号:
V [航空、航天];
学科分类号:
08 ;
0825 ;
摘要:
Recently, the high rate global navigation satellite system-precise point positioning (GNSS-PPP) technique has been used to detect the dynamic behavior of structures. This study aimed to increase the accuracy of the extraction oscillation properties of structural movements based on the high-rate (10 Hz) GNSS-PPP monitoring technique. A developmental model based on the combination of wavelet package transformation (WPT) de-noising and neural network prediction (NN) was proposed to improve the dynamic behavior of structures for GNSS-PPP method. A complicated numerical simulation involving highly noisy data and 13 experimental cases with different loads were utilized to confirm the efficiency of the proposed model design and the monitoring technique in detecting the dynamic behavior of structures. The results revealed that, when combined with the proposed model, GNSS-PPP method can be used to accurately detect the dynamic behavior of engineering structures as an alternative to relative GNSS method. (C) 2018 Published by Elsevier Ltd on behalf of COSPAR.
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页码:1512 / 1524
页数:13
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