Experimental study on bridge structural health monitoring using blind source separation method: arch bridge

Huang, Chaojun; Nagarajaiah, Satish

doi:10.12989/smm.2014.1.1.069

Cited by 16 publications

(13 citation statements)

References 30 publications

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“…Guo et al proposed a damage identification method using wavelet packet transform, and a wavelet packet energy index combined with Shannon entropy was used to localize the damage; a numerical model of Guotai steel arch bridge was established to simulate damage, and the method is demonstrated using the simulation. Huang and Nagarajaiah proposed a method termed wavelet modified second‐order blind identification, which has been experimentally verified on a scaled model of an arch bridge across U.S. highway 59.…”

Section: Recent Progress On Damage Identification Methods For Arch Brmentioning

confidence: 99%

Recent progress and future trends on damage identification methods for bridge structures

Chatzi

Sim

et al. 2019

Struct Control Health Monit

211

112

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Summary Damage identification forms a key objective in structural health monitoring. Several state‐of‐the‐art review papers regarding progress in this field up to 2011 have been published. This paper summarizes the recent progress between 2011 and 2017 in the area of damage identification methods for bridge structures. This paper is organized based on the classification of bridge infrastructure in terms of fundamental structural systems, namely, beam bridges, truss bridges, arch bridges, cable‐stayed bridges, and suspension bridges. The overview includes theoretical developments, enhanced simulation attempts, laboratory‐scale implementations, full‐scale validation, and the summary for each type of bridges. Based on the offered review, some challenges, suggestions, and future trends in damage identification are proposed. The work can be served as a basis for both academics and practitioners, who seek to implement damage identification methods in next‐generation structural health monitoring systems.

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Section: Recent Progress On Damage Identification Methods For Arch Brmentioning

confidence: 99%

Recent progress and future trends on damage identification methods for bridge structures

Chatzi

Sim

et al. 2019

Struct Control Health Monit

211

112

View full text Add to dashboard Cite

show abstract

“…Since the recording of input excitations in a bridge is a difficult task due to practical issues, the output-only BHM is preferred. Transformers [6][7][8][9][10][11], time-domain methods [1,2,[12][13][14][15][16][17], and source separation methods [18][19][20][21][22] are some of the vibration-based BHM approaches which were extensively addressed in the literature.…”

Section: Introductionmentioning

confidence: 99%

Direct Use of the Savitzky–Golay Filter to Develop an Output-Only Trend Line-Based Damage Detection Method

Kordestani

Zhang

2020

Sensors

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The Savitzky–Golay filter (SGF) is a time-domain technique that determines a trend line for a signal. The direct application of SGF for damage localization and quantification is investigated in this paper. Therefore, a single-stage trend line-based damage detection method employing SGF is proposed in which the damage is located and quantified at the bridge under moving load. A simply supported beam under moving sprung mass is numerically simulated to verify the proposed method. Four different velocities and five different single- and multi-damage scenarios are considered. The acceleration data along the beam are obtained, manually polluted with noise and their trend lines are then determined using SGF. The results show that the proposed method can accurately locate and quantify the damage using these trend lines. It is proved that the proposed method is insensitive to the noise and velocity variation in which having a constant velocity is a hard task before and after damage. Additionally, defining a normalization factor and fitting a Gaussian curve to this factor provide an estimation for the baseline and therefore, it categorizes the proposed method as baseline-free method.

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“…Therefore, signal processing is necessary to provide a visible form of these signatures. Some of these signal processing-based methods are transformers [3][4][5][6][7][8], time-domain methods (e.g., random decrement technique (RDT)) [1,2,[9][10][11][12][13][14], and source separation methods (e.g., blind source separation (BSS)) [15][16][17][18][19]. To implement a systematic damage detection procedure, a nested loop of RDT and a Savitzky-Golay filter (SGF) is employed in the present paper.…”

Section: Introductionmentioning

confidence: 99%

“…Loh et al [19] employed SOBI to locate the damage in a bridge structure and compared it with other damage detection methods. Huang and Nagarajaiah [18] combined SOBI with wavelet analysis, improved the performance of SOBI, and successfully found more modal parameters of the bridge with limited sensors.…”

Section: Introductionmentioning

confidence: 99%

Beam Damage Detection Under a Moving Load Using Random Decrement Technique and Savitzky–Golay Filter

Kordestani

Zhang

Shadabfar

2019

Sensors

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In this paper, a two-stage time-domain output-only damage detection method is proposed with a new energy-based damage index. In the first stage, the random decrement technique (RDT) is employed to calculate the random decrement signatures (RDSs) from the acceleration responses of a simply supported beam subjected to a moving load. The RDSs are then filtered using the Savitzky–Golay filter (SGF) in the second stage. Next, the filtered RDSs are processed by the proposed energy-based damage index to locate and quantify the intensity of the possible damage. Finally, by fitting a Gaussian curve to the damage index resulted from the non-damage conditions, the whole process is systematically implemented as a baseline-free method. The proposed method is numerically verified using a simply supported beam under moving sprung mass with different velocities and damage scenarios. The results show that the proposed method can accurately estimate the damage location/quantification from the acceleration data without any prior knowledge of either input load or damage characteristics. Additionally, the proposed method is neither sensitive to noise nor velocity variation, which makes it ideal when obtaining a constant velocity is difficult.

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Experimental study on bridge structural health monitoring using blind source separation method: arch bridge

Cited by 16 publications

References 30 publications

Recent progress and future trends on damage identification methods for bridge structures

Recent progress and future trends on damage identification methods for bridge structures

Direct Use of the Savitzky–Golay Filter to Develop an Output-Only Trend Line-Based Damage Detection Method

Beam Damage Detection Under a Moving Load Using Random Decrement Technique and Savitzky–Golay Filter

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