Simplification and improvement of cable tension identification based on effective vibration length estimated from multiple sensors located near one support

• The effective vibration lengths of the first three orders are basically the same. • The cable before and after adding mass have the same effective vibration length. • Modal characteristics of cables with added masses are essentially consistent with those of S-S beams with the same masses. • The above findings can be used to simplify and improve the original method based on effective vibration length. • The proposed methods can improve identification accuracy when measurements are distributed near one cable end. Effective vibration length (EVL) has been proposed and found able to accurately identify tension force in short cables with unknown boundaries. However, EVL estimation accuracy is degraded when measurements are distributed only near the cable-deck end. This study investigates the EVL and modal characteristics of cables under different factors using a finite element model. The corresponding conclusions are then utilized to simplify and improve the original method. Method 1 is proposed by simplifying the original method using a fixed EVL for different modes. Method 2 is developed by enhancing Method 1 with additional tests where masses are attached on the cable near the sensors. In numerical experiments with 1 % random noise, the proposed methods achieve 70 %–80 % of results with errors less than 5 % while 1 % of results from the original method achieve this level of accuracy. Full-scale cable experiments have further validated the effectiveness of the proposed methods.

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Publication Details

Journal
Measurement
Published
2024-09-14
DOI
https://doi.org/10.1016/j.measurement.2024.115755
Citations
8
Primary Topic
Structural Health Monitoring Techniques
Type
article
Field-Weighted Citation Impact
2.09
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article

Simplification and improvement of cable tension identification based on effective vibration length estimated from multiple sensors located near one support

Yuanzhao Chen, Yiqing Zou, Lin Chen, Limin Sun et al.
8 citations
Measurement
Structural Health Monitoring Techniques
2.09
article

Simplification and improvement of cable tension identification based on effective vibration length estimated from multiple sensors located near one support

Yuanzhao Chen, Yiqing Zou, Lin Chen, Limin Sun, Sijia Chen, Lei Qin
article en
8 citations

Abstract

• The effective vibration lengths of the first three orders are basically the same. • The cable before and after adding mass have the same effective vibration length. • Modal characteristics of cables with added masses are essentially consistent with those of S-S beams with the same masses. • The above findings can be used to simplify and improve the original method based on effective vibration length. • The proposed methods can improve identification accuracy when measurements are distributed near one cable end. Effective vibration length (EVL) has been proposed and found able to accurately identify tension force in short cables with unknown boundaries. However, EVL estimation accuracy is degraded when measurements are distributed only near the cable-deck end. This study investigates the EVL and modal characteristics of cables under different factors using a finite element model. The corresponding conclusions are then utilized to simplify and improve the original method. Method 1 is proposed by simplifying the original method using a fixed EVL for different modes. Method 2 is developed by enhancing Method 1 with additional tests where masses are attached on the cable near the sensors. In numerical experiments with 1 % random noise, the proposed methods achieve 70 %–80 % of results with errors less than 5 % while 1 % of results from the original method achieve this level of accuracy. Full-scale cable experiments have further validated the effectiveness of the proposed methods.

MeasurementVol. 242
Ningbo University (CN), Tongji University (CN), Ningbo University of Technology (CN), Guangxi University of Science and Technology (CN), ShangHai JiAi Genetics & IVF Institute (CN)
Affordable and clean energy
Openalex Percentile: Top 14%
Structural Health Monitoring Techniques
2.09
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