The research of soft yoke single point mooring tower system damage identification based on long-term monitoring data

•The damage identification method of soft yoke single point mooring (SPM) tower system based on long-term monitoring data is proposed.•We analyze and compare several damage-sensitive features for the nonlinearity dynamic system under non-stationary environment loads.•The proposed method is applied t...

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Bibliographic Details
Published in:Applied ocean research 2018-07, Vol.76, p.139-147
Main Authors: Tang, Da, Zeng, Xianpeng, Wang, Deyu, Wu, Wenhua, Wang, Yanlin, Yue, Qianjin, Wang, Bingsen, Xie, Bin, Wang, Shisheng, Feng, Jiaguo
Format: Article
Language:English
Subjects:
Algorithms
Autocorrelation
Autocorrelation function
Damage
Damage identification
Data
Frequency spectra
Identification
Methods
Mooring systems
Nonlinear systems
Nonlinearity
Random decrement signature
Soft yoke single point mooring (SPM) tower system
Support Vector Machine (SVM)
Suspended particulate matter
Towers
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Summary:•The damage identification method of soft yoke single point mooring (SPM) tower system based on long-term monitoring data is proposed.•We analyze and compare several damage-sensitive features for the nonlinearity dynamic system under non-stationary environment loads.•The proposed method is applied to the damage identification of soft yoke SPM tower system. In this research, to identify the damage of the nonlinearity system under ambient loads, an intelligent damage identification method based on long-term monitoring data is proposed. The random decrement technique and the autocorrelation function algorithm are used to extract free decay of the structure from long-term monitoring data. The random decrement signatures, autocorrelation function, the frequency of free response and the peak points of the frequency spectrum are used as the features of the structure. These features are then input into the Support Vector Machine (SVM) to classify the current state of the system and their identification accuracy is compared. The simulation experiments results show the extracted features are capable of representing the changes of the system inherent characteristics. Finally, the proposed method is applied to the data analysis of the soft yoke single point mooring (SPM) tower system, and provide the reference for the damage identification of the soft yoke SPM tower system.
ISSN:0141-1187
1879-1549
DOI:10.1016/j.apor.2018.04.017