An integrated GPS–accelerometer data processing technique for structural deformation monitoring

Chan, Wai-Sum; Xu, You Lin; Ding, Xiaoli; Dai, Wujiao

doi:10.1007/s00190-006-0092-2

Cited by 100 publications

(58 citation statements)

References 8 publications

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“…When the integrated GNSS and accelerometer system was used for structural dynamic monitoring to improve measurement accuracy and measureable frequency range [3,34,38,41], it has a key difficulty of time synchronization. To solve this problem, a Precise Time Data Logger PTDL (see upper-right of Fig.…”

Section: Ptdl Data Loggermentioning

confidence: 99%

“…Some other errors, such as multipath error and random noise, cannot be removed in the differencing method [30]. Several data processing techniques could be performed to mitigate these residual errors, such as an adaptive filtering (AF) technique [31][32][33], a technique combining Empirical Mode Decomposition (EMD) and AF [34], an improved particle-filtering algorithm [35], a supervised learning technique [36], and a wavelet based multi-step filtering method [37]. In summary, most of the current filtering techniques can identify centimeter level displacements with a millimeter level accuracy.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Identification of dynamic displacements and modal frequencies of a medium-span suspension bridge using multimode GNSS processing

Yu¹,

Meng²,

Shao³

et al. 2014

Engineering Structures

101

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Section: Ptdl Data Loggermentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Identification of dynamic displacements and modal frequencies of a medium-span suspension bridge using multimode GNSS processing

Yu¹,

Meng²,

Shao³

et al. 2014

Engineering Structures

101

View full text Add to dashboard Cite

“…Optimal integration technique can improve the measurement accuracy of reconstructed displacement. Chan et al (2007) proposed an integrated GPS-accelerometer data processing technique based on the empirical mode decomposition (EMD) and adaptive filter techniques [31]. Smyth et al (2007) presented a multi-rate Kalman filtering approach to integrate GPS and accelerometer data at different rates [32], Hwang's research shows the frequency-based displacement extraction method was most appropriate for the GPS/accelerometer data integration [33].…”

Section: Introductionmentioning

confidence: 99%

Analysis of the dynamic response of a long span bridge using GPS/accelerometer/anemometer under typhoon loading

Han

Wang

Meng

et al. 2016

Engineering Structures

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(2016) Analysis of the dynamic response of a long span bridge using GPS/accelerometer/anemometer under typhoon loading. Engineering Structures, 122 (2016 A note on versions:The version presented here may differ from the published version or from the version of record. If you wish to cite this item you are advised to consult the publisher's version. Please see the repository url above for details on accessing the published version and note that access may require a subscription.For more information, please contact eprints@nottingham.ac.uk Analysis of the dynamic response of a long span bridge using GPS/accelerometer/anemometer under typhoon loading AbstractLarge flexible engineering structures, such as long span bridges or tall buildings, are susceptible to quasi-static and dynamic deformations caused by different loading situations, thus accurate displacement measurements are desirable to assess the integrity and reliability of the structure. In this study, an integrated system that includes Global Positioning System (GPS), accelerometer and anemometer was developed to obtain the responses of a long span bridge to the extreme wind loading. Spectral analysis based on the Fast Fourier Transform (FFT) algorithm was first carried out to detect the dominant frequencies of the bridge. Then the noisy GPS displacement measurements and accelerometer data are de-noised using the Vondrak filter, and the low frequency disturbance was separated from GPS displacement time series. A least-squares based displacement reconstruction scheme using noise-mitigated accelerations was employed, and the Tikhonov regularization scheme with optimal selected regularization factor was used to alleviate the ill-posedness. At last, an adaptive recursive least squares (RLS) filter was adopted to separate the slow-varying movements, and the total displacement with enhanced measurement accuracy was obtained from the combined quasistatic and high-frequency dynamic displacements. A field monitoring data set collected on the Erqi Yangtze River Bridge, a three-tower cable-stayed bridge located in Wuhan in China, was used to validate the effectiveness of the proposed integration processing scheme. The GPS/accelerometer/anemometer installed on the center supporting tower was used to characterize the interaction between the responses and the ambient wind loadings. The results demonstrate the proposed technique can significantly improve the measurement accuracy of bridge displacement under strong winds. The deformation with the amplitude of several millimeters can be successfully detected, and the spectrum of the bridge response obtained from both GPS data and accelerometer data reveals the identified first natural frequency of the bridge is 0.172 Hz.

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“…Kaloop and Kim [17] applied wavelet principal component analysis to estimate the behavior of a railway bridge and denoise the GPS measurement error and dynamic noise associated with the structure movements. Moreover, many GPS measurement filtering and smoothing methods are applied to estimate the accurate static and dynamic behavior of structures [13,18,19], and GPS integration with accelerometer measurements is also studied [20][21][22]. Therefore, in this study, three common de-noise filtering and smoothing methods, non-linear Adaptive-Recursive Least Square, EKF, and wavelet principal component analysis, are compared to identify the most suitable approach for extracting structure behavior components in the time and frequency domains.…”

Section: Introductionmentioning

confidence: 99%

Adjustment and Assessment of the Measurements of Low and High Sampling Frequencies of GPS Real-Time Monitoring of Structural Movement

Kaloop

Elbeltagi

2016

IJGI

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Global Positioning System (GPS) structural health monitoring data collection is one of the important systems in structure movement monitoring. However, GPS measurement error and noise limit the application of such systems. Many attempts have been made to adjust GPS measurements and eliminate their errors. Comparing common nonlinear methods used in the adjustment of GPS positioning for the monitoring of structures is the main objective of this study. Nonlinear Adaptive-Recursive Least Square (RLS), extended Kalman filter (EKF), and wavelet principal component analysis (WPCA) are presented and applied to improve the quality of GPS time series observations. Two real monitoring observation systems for the Mansoura railway and long-span Yonghe bridges are utilized to examine suitable methods used to assess bridge behavior under different load conditions. From the analysis of the results, it is concluded that the wavelet principal component is the best method to smooth low and high GPS sampling frequency observations. The evaluation of the bridges reveals the ability of the GPS systems to detect the behavior and damage of structures in both the time and frequency domains.

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An integrated GPS–accelerometer data processing technique for structural deformation monitoring

Cited by 100 publications

References 8 publications

Identification of dynamic displacements and modal frequencies of a medium-span suspension bridge using multimode GNSS processing

Identification of dynamic displacements and modal frequencies of a medium-span suspension bridge using multimode GNSS processing

Analysis of the dynamic response of a long span bridge using GPS/accelerometer/anemometer under typhoon loading

Adjustment and Assessment of the Measurements of Low and High Sampling Frequencies of GPS Real-Time Monitoring of Structural Movement

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