Time–frequency analysis for concrete dam safety control: Correlation between the daily variation of structural response and air temperature

Mata, Juan; Castro, A. Tavares de; Costa, J.M. Sá da

doi:10.1016/j.engstruct.2012.12.013

Cited by 54 publications

(30 citation statements)

References 19 publications

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“…The functional model can then be extended by sinusoidal functions with estimated frequencies of underlying periodicities. Depending on the type of data, the Fourier transform can be used for the data sets with evenly spaced data, otherwise the Lomb–Scargle normalised periodogram (LSNP), and least squares spectral analysis (LSSA) are proposed in previous studies …”

Section: Introductionmentioning

confidence: 99%

Analysis of periodicities in long‐term displacement time series in concrete dams

Gamse

Henriques

Oberguggenberger

et al. 2019

Struct Control Health Monit

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The hydrostatic-season-time (HST) model is a widely used method in the safety assessment of dams and for the estimation of reversible and irreversible deformations due to different load scenarios. After implementing an optimal HST-model to observational data, the residual time series can still expose some underlying periodicities. In our contribution, the underlying periodicities and their contribution to residual minimisation are further analysed by the Lomb-Scargle normalised periodogram frequency method. The extended HST-model, obtained by adding additional sinusoidal terms for the statistically most significant frequencies, presents a slight statistical improvement on the optimal HST-model. Statistically significant frequencies may not be justified or correlated to some physical process of the dam, but they make it possible to identify a pattern in the analysed period. The analyses are performed for the radial direction of long-term displacement time series measured at the topmost reading station of an inverted pendulum system in the central cantilever of the Alqueva concrete arch dam. KEYWORDSconcrete arch dam, false alarm probability, hydrostatic-season-time model, Lomb-Scargle normalised periodogram, multiple linear regression

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Section: Introductionmentioning

confidence: 99%

Analysis of periodicities in long‐term displacement time series in concrete dams

Gamse

Henriques

Oberguggenberger

et al. 2019

Struct Control Health Monit

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“…Previous studies have utilized principal component analysis,() artificial neural networks,() blind source separation,() artificial immune algorithm,() independent component regression,() cointegration theory,() and time‐varying Bayesian approach() to model and predict the dam responses. Time‐frequency analysis (short‐time Fourier transform) was employed by Mata et al() to identify the effect of daily variations of air temperature on the structural response of a concrete dam. In their study, short‐time Fourier transform was used to identify the influence of the daily variation of air temperature on the horizontal displacement of concrete dams and to track its variation as a function of time, which was then used to predict the future dam performance.…”

Section: Introductionmentioning

confidence: 99%

Initial service life data towards structural health monitoring of a concrete arch dam

Prakash

Sadhu

Narasimhan

et al. 2017

Struct Control Health Monit

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SummaryThis paper presents a statistical framework to monitor the performance of an operational concrete arch dam using sensory data acquired during its initial service life.One of the major challenges in dealing with a newly constructed dam is to predict its long-term behaviour by forecasting appropriate thresholds using limited data exhibiting nonstationarity. In this paper, a hybrid model is implemented to predict dam responses using environmental-hydrostatic, seasonal, and temperature-as well as age-related variables. The data from multiple sensors are first analyzed using principal component analysis to incorporate overall dam behaviour into a prediction model. The proposed prediction framework is then employed to estimate the residuals and control limits required to calculate thresholds under nonstationary operating conditions during its initial service life. The dam performance is then monitored using statistical control charts and anomalies are detected by comparing the test statistics, square prediction error, and Hotelling T-squared, calculated from the residuals with the preset control limits. The issue of limited data is addressed by updating the model parameters and thresholds periodically, which is aimed at minimizing the false alarm rate. The proposed method is demonstrated using a 130-m-high double-arch concrete dam located in Bulgaria.

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“…Therefore, the frequency domain can be used to study the performance of structures based on strain measurements [24]. The traffic should be taken into account when studying the performance of bridges vibration [13,15]. In this study, the residuals of strain measurements between measured and smoothed data are used.…”

Section: Frequency Correlation Analysismentioning

confidence: 99%

“…In this study, the residuals of strain measurements between measured and smoothed data are used. In addition, the correlation analysis of power spectrum density (PSD) for the monitored points is used to estimate the stability and dynamic performance safety of structures [15,25]. A MATLAB code is written to design the frequency technique based on the P-Welch method to estimate the power-spectral density [26], while for the Welch-based estimation of the PSDs, a 256 sample-long Hamming window with 50% overlapping and a sampling frequency of 25 Hz is used.…”

Section: Frequency Correlation Analysismentioning

confidence: 99%

See 1 more Smart Citation

Time-Series and Frequency-Spectrum Correlation Analysis of Bridge Performance Based on a Real-Time Strain Monitoring System

Kaloop

Elbeltagi

2016

IJGI

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Abstract:Monitoring bridges' performance is a vital task to ensure their safety and to plan their maintenance operations. Therefore, it is very important to monitor bridges' behavior and to analyze their measured data. In this study, the time-series and frequency-spectrum correlation analyses are used to study the performance of Fu-Sui Bridge under harsh environmental and traffic loads. It investigates the bridge performance based on a real-time strain monitoring system, and the ambient environmental and traffic loads are studied and discussed. Furthermore, a simplified method based on signal processing is developed and used to estimate the traffic volumes. The results of this study reveal that the traffic loads influence on static strain is obviously lower than that of air temperature and temperature changes of the bridge cross-section; the non-linearity behavior of the bridge during summer time is more than winter time; and the stability of the whole bridge during winter time is more than during summer time. The time-series and vibration analyses also show that the bridge performance in terms of its rigidity and stability is higher during winter time.

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Time–frequency analysis for concrete dam safety control: Correlation between the daily variation of structural response and air temperature

Cited by 54 publications

References 19 publications

Analysis of periodicities in long‐term displacement time series in concrete dams

Analysis of periodicities in long‐term displacement time series in concrete dams

Initial service life data towards structural health monitoring of a concrete arch dam

Time-Series and Frequency-Spectrum Correlation Analysis of Bridge Performance Based on a Real-Time Strain Monitoring System

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