Bridge Damage Detection Using Quasi-Static Component of Moving Vehicle-Induced Dynamic Response

2020 ◽  
pp. 2042001
Author(s):  
Zhiwei Chen ◽  
Yigui Zhou ◽  
Wen-Yu He ◽  
Mengqi Liu
Keyword(s):  
Dynamic Response ◽  
Damage Detection ◽  
Detection Method ◽  
Damage Index ◽  
Frequency Component ◽  
Critical Signal ◽  
Moving Vehicle ◽  
Damage Scenarios ◽  
Static Component ◽  
Bridge Damage

The critical signal component extracted from the bridge response caused by a moving vehicle is normally used to construct damage index for damage detection. The dynamic response of bridges subjected to moving vehicle includes several components, among which the quasi-static component reflects the inherent characteristics of the bridge. In view of this, this paper presents a bridge damage detection method based on quasi-static component of the moving vehicle-induced dynamic response. First, damage-induced changes of the natural-frequency component, moving-frequency component and quasi-static component responses are investigated via a simply-supported beam bridge. The quasi-static component response is proved to be less sensitive to the moving velocity of the load and more suitable for damage detection. Subsequently, a quasi-static component response extraction method is proposed based on analytical mode decomposition (AMD) and moving average filter (MAF). The extracted quasi-static component response is further employed to localize and quantify damages. Finally, numerical simulations are conducted to examine the feasibility, accuracy and advantages of the proposed damage detection method. The results indicated that the proposed method performs well in different damage scenarios and is insensitive to the moving velocity of the load and road roughness.

scholarly journals Mode Shape-Based Damage Detection Method (MSDI): Experimental Validation

2021 ◽  
Vol 11 (10) ◽  
pp. 4589
Author(s):  
Ivan Duvnjak ◽  
Domagoj Damjanović ◽  
Marko Bartolac ◽  
Ana Skender
Keyword(s):  
Boundary Conditions ◽  
Damage Detection ◽  
Mode Shape ◽  
Experimental Validation ◽  
Detection Method ◽  
Dynamic Properties ◽  
Damage Index ◽  
Main Principle ◽  
The Difference ◽  
Different Levels

The main principle of vibration-based damage detection in structures is to interpret the changes in dynamic properties of the structure as indicators of damage. In this study, the mode shape damage index (MSDI) method was used to identify discrete damages in plate-like structures. This damage index is based on the difference between modified modal displacements in the undamaged and damaged state of the structure. In order to assess the advantages and limitations of the proposed algorithm, we performed experimental modal analysis on a reinforced concrete (RC) plate under 10 different damage cases. The MSDI values were calculated through considering single and/or multiple damage locations, different levels of damage, and boundary conditions. The experimental results confirmed that the MSDI method can be used to detect the existence of damage, identify single and/or multiple damage locations, and estimate damage severity in the case of single discrete damage.

A Round Robin Study: Detection of Damage in a Composite Plate With a Real-Time Moving Sensor Measurement Technique

2018 ◽  
Author(s):  
Da-Ming Chen ◽  
Y. F. Xu ◽  
W. D. Zhu
Keyword(s):  
Damage Detection ◽  
Real Time ◽  
Composite Plate ◽  
Detection Method ◽  
Damage Index ◽  
Laser Doppler Vibrometer ◽  
Composite Plates ◽  
Round Robin ◽  
Velocity Response ◽  
Demodulation Method

A worldwide round robin study is sponsored by the Society of Experimental Mechanics to detect damage in a composite plate with a scanning laser Doppler vibrometer (SLDV). The aim of this round robin study is to explore the potential of a SLDV for detection of damage in composite plates. In this work, a curvature-based damage detection method with use of a continuously SLDV (CSLDV) is proposed. A CSLDV can be regarded as a real-time moving sensor, since the laser spot from the CSLDV continuously moves on a structure surface and measures velocity response. An operating deflection shape (ODS) of the damaged composite plate can be obtained from velocity response by the demodulation method. The ODS of the associated undamaged composite plate is obtained by using polynomials to fit the ODS of the damaged plate. A curvature damage index (CDI) using differences between curvatures of ODSs (CODSs) associated with the ODSs from the demodulation method and the polynomial fit is proposed to detect damage. With the proposed curvature-based damage detection method, locations of two possible damage are detected in areas with consistently high CDI values at two excitation frequencies, which are in good agreement with prescribed damage locations.

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

Sensors ◽  
2020 ◽  
Vol 20 (7) ◽  
pp. 1983 ◽  
Author(s):  
Hadi Kordestani ◽  
Chunwei Zhang
Keyword(s):  
Damage Detection ◽  
Detection Method ◽  
Moving Load ◽  
Velocity Variation ◽  
Trend Line ◽  
Damage Scenarios ◽  
Acceleration Data ◽  
Before And After ◽  
Output Only ◽  
Direct Use

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.

Investigation on a curvature-based damage detection method using displacement under moving vehicle

2017 ◽  
Vol 25 (1) ◽  
pp. e2044 ◽  
Author(s):  
Zhen Sun ◽  
Tomonori Nagayama ◽  
Mayuko Nishio ◽  
Yozo Fujino
Keyword(s):  
Damage Detection ◽  
Detection Method ◽  
Moving Vehicle

A Method for Damage Detection Based on Correlation Characteristic of Acceleration Response

2013 ◽  
Vol 540 ◽  
pp. 87-98 ◽  
Author(s):  
Wei Ming Yan ◽  
Da Peng Gu ◽  
Yan Jiang Chen ◽  
Wei Ning Wang
Keyword(s):  
Neural Network ◽  
Damage Detection ◽  
Model Test ◽  
Bp Neural Network ◽  
Detection Method ◽  
Damage Index ◽  
Fem Simulation ◽  
Acceleration Response ◽  
Correlation Characteristic ◽  
Experiment Verification

A damage detection method using BP neural network based on a novel damage index, the correlation characteristic of the acceleration response, is proposed, and is evaluated through the FEM simulation and experiment verification. On the basis of achievements in existence, the feasibility of using the correlation characteristic as damage index is validated theoretically. The damage detection for a simple-supported beam using the proposed method was FEM simulated. The results showed that the trained BP neural network can correctly detect the location and extent of damages in both single damage case and multi-damage case. A model test of a reinforced concrete simple-supported beam was performed to verify the validity and efficiency of the damage detection method. From the results of the model test, it is shown that the trained BP neural network can correctly locate the damage mostly detect the extent of damage. A conclusion is given that the novel damage detection method using the correlation characteristic of the acceleration response as damage index is feasible and efficient.

Interpolation Damage Detection Method on a Suspension Bridge Model: Influence of Sensors Disturbances

2013 ◽  
Vol 569-570 ◽  
pp. 734-741 ◽  
Author(s):  
Marco Domaneschi ◽  
Maria Pina Limongelli ◽  
Luca Martinelli
Keyword(s):  
Damage Detection ◽  
Detection Method ◽  
Suspension Bridge ◽  
Longitudinal Axis ◽  
Noise Signal ◽  
Damage Scenarios ◽  
Spatially Correlated ◽  
Bridge Model ◽  
Structural Responses ◽  
Detection And Localization

In this paper the IDDM (Interpolation Damage Detection Method), recently proposed as a speedy damage detection and localization technique, is applied to the numerical model of a cable suspended bridge derived from the ANSYS model of the Shimotsui-Seto Bridge in Japan (940m length of the main span). The wind excitation is simulated as a spatially correlated process acting in the horizontal direction, transversal to the deck. The bridge is assumed to be monitored by sensors located at the nodes of the model along the longitudinal axis, and recording the absolute acceleration of the bridge deck in the transversal direction Noise in recorded responses can reduce the sensitivity of the method to damage. The influence of noise on the results of the damage detection method is herein investigated by adding a white-noise signal to the structural responses. The mutual relationship between level of noise, intensity of damage and lengths of recorded signals is also investigated with reference to various damage scenarios.

A New Damage Index Using FRF Data, 2D-PCA Method and Pattern Recognition Techniques

2017 ◽  
Vol 17 (08) ◽  
pp. 1750090 ◽  
Author(s):  
F. Khoshnoudian ◽  
S. Talaei
Keyword(s):  
Pattern Recognition ◽  
Damage Detection ◽  
Damage Identification ◽  
Damage Index ◽  
Principal Component ◽  
Frame Structure ◽  
Damage Scenarios ◽  
Pattern Recognition Techniques ◽  
Damage Indices ◽  
Truss Bridge

A pattern recognition-based damage detection method using a brand-new damage index (DI) obtained from the frequency response function (FRF) data is proposed in this paper. One major issue of using the FRF data is the large size of input variables. The proposed method reduces the dimension of the initial FRF data and transforms it into new damage indices by applying a data reduction technique called the two-dimensional principal component analysis (2D-PCA). The proposed damage indices can be used as the unique patterns. After introducing the damage indices, a dataset of damage scenarios and related patterns is composed. Pattern recognition techniques such as the artificial neural networks and look-up-table (LUT) method are employed to find the most similar known DI to the unknown DI obtained for the damaged structure. As the result of this procedure, the actual damage location and severity can be determined. In this paper, the 2D-PCA and LUT method for damage detection is introduced for the first time. The damage identification of a truss bridge and a two-story frame structure is performed for verification of the proposed method, considering all single damage cases as well as many multiple damage scenarios. In addition, the robustness of the proposed algorithm to measurement noise was investigated by polluting the FRF data with 5%, 10%, 15% and 20% noises.

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

Sensors ◽  
2019 ◽  
Vol 20 (1) ◽  
pp. 243 ◽  
Author(s):  
Hadi Kordestani ◽  
Chunwei Zhang ◽  
Mahdi Shadabfar
Keyword(s):  
Damage Detection ◽  
Moving Load ◽  
Damage Index ◽  
Velocity Variation ◽  
Simply Supported Beam ◽  
Damage Scenarios ◽  
Simply Supported ◽  
Random Decrement Technique ◽  
Random Decrement ◽  
Output Only

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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