Time-Series and Frequency-Spectrum Correlation Analysis of Bridge Performance Based on a Real-Time Strain Monitoring System
Abstract
:1. Introduction
2. Fu-Sui Bridge and SHM System
3. Data Measurements and Preprocessing
3.1. Temperature and Strain Preprocessing
3.2. Traffic Strain Counter
4. Bridge Performance Assessment
4.1. Performance Due to Affected Loads
4.2. Temperature Correlation Performance Analysis
4.3. Frequency Correlation Analysis
5. Conclusions
- The static strain can be estimated using smoothed strain measurements, while the dynamic strain behavior can be extracted by filtering the strain measurements. Based on this conclusion, the traffic volume can be estimated, and the study reveals that the traffic volume on Fu-Sui Bridge increased during one year by 55%.
- The multi-input single-output robust regression identification model of strain measurements reveals that the influent portion of traffic loads in the static strain is lower than the air temperature and temperature changes, and it can be neglected in the case of studying the performance of the bridge based on the strain monitoring system.
- The time-series correlation analysis of strain and temperature revealed that the winter temperature time has more effect on the upper and lower strain behavior than summer temperature, while the summer time strain behavior is less reliable than winter time, and the behavior of the bridge during winter time is more stable than summer time. Furthermore, the temperature changes of the bridge section affect the lower plate girder more than the upper plate during summer time. This means that the direct air temperature effect is higher than indirect temperature effects. The linear fitting between strain and temperature changes shows that the bridge performance during winter time is more stable than summer time.
- The correlation of frequency spectrum analysis of strain residuals shows that the increased traffic volume on the bridge increases the bridge stability in vibration modes with more controlled bridge vibration. In addition, the air temperature and temperature changes of the bridge sections do not affect the frequency modes and power spectrum density of strain signals. The correlation of power spectrum density reveals that the dynamic performance of the bridge in summer and winter times is safe.
Acknowledgments
Author Contributions
Conflicts of Interest
References
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Model | S = a + b1(T) + b2(DT) + b3(V) | t(T,DT,V) | FPE | R2 |
---|---|---|---|---|
1 | S = −93.726 + 12.306(T) + 11.630(DT) − 0.185(V) | 6.28, 5.76, −1.28 | 33.62 | 0.64 |
2 | S = −307.081 + 12.828(T) + 12.200(DT) | 6.62, 6.12 | 31.16 | 0.66 |
3 | S = −20.775 + 0.913(T) | 4.95 | 35.43 | 0.32 |
Parameter | S19 | S20 | S21 | S22 | To | |||||
---|---|---|---|---|---|---|---|---|---|---|
May | January | May | January | May | January | May | January | May | January | |
S19 | 1.00 | 1.00 | 0.57 | 0.95 | 0.47 | 0.92 | 0.78 | 0.89 | 0.46 | 0.95 |
S20 | 0.57 | 0.95 | 1.00 | 1.00 | 0.98 | 0.98 | 0.04 | 0.97 | 0.93 | 0.97 |
S21 | 0.47 | 0.92 | 0.98 | 0.98 | 1.00 | 1.00 | −0.06 | 0.98 | 0.96 | 0.97 |
S22 | 0.78 | 0.88 | 0.04 | 0.97 | −0.06 | 0.98 | 1.00 | 1.00 | −0.04 | 0.96 |
To | 0.46 | 0.95 | 0.93 | 0.97 | 0.96 | 0.97 | −0.04 | 0.95 | 1.00 | 1.00 |
Parameter | S19 | S20 | S21 | S22 | ||||
---|---|---|---|---|---|---|---|---|
May | January | May | January | May | January | May | January | |
S19 | 1.00 | 1.00 | 0.93 | 0.99 | 0.99 | 0.99 | 0.92 | 0.99 |
S20 | 0.93 | 0.99 | 1.00 | 1.00 | 0.93 | 0.99 | 0.91 | 0.99 |
S21 | 0.99 | 0.99 | 0.93 | 0.99 | 1.00 | 1.00 | 0.92 | 0.99 |
S22 | 0.92 | 0.99 | 0.91 | 0.99 | 0.92 | 0.99 | 1.00 | 1.00 |
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Kaloop, M.R.; Hu, J.W.; Elbeltagi, E. Time-Series and Frequency-Spectrum Correlation Analysis of Bridge Performance Based on a Real-Time Strain Monitoring System. ISPRS Int. J. Geo-Inf. 2016, 5, 61. https://doi.org/10.3390/ijgi5050061
Kaloop MR, Hu JW, Elbeltagi E. Time-Series and Frequency-Spectrum Correlation Analysis of Bridge Performance Based on a Real-Time Strain Monitoring System. ISPRS International Journal of Geo-Information. 2016; 5(5):61. https://doi.org/10.3390/ijgi5050061
Chicago/Turabian StyleKaloop, Mosbeh R., Jong Wan Hu, and Emad Elbeltagi. 2016. "Time-Series and Frequency-Spectrum Correlation Analysis of Bridge Performance Based on a Real-Time Strain Monitoring System" ISPRS International Journal of Geo-Information 5, no. 5: 61. https://doi.org/10.3390/ijgi5050061
APA StyleKaloop, M. R., Hu, J. W., & Elbeltagi, E. (2016). Time-Series and Frequency-Spectrum Correlation Analysis of Bridge Performance Based on a Real-Time Strain Monitoring System. ISPRS International Journal of Geo-Information, 5(5), 61. https://doi.org/10.3390/ijgi5050061