Improved damage detection method based on Element Modal Strain Damage Index using sparse measurement

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.

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

Volume 8: 30th Conference on Mechanical Vibration and Noise ◽

10.1115/detc2018-86160 ◽

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.

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

International Journal of Computational Methods ◽

10.1142/s0219876220420013 ◽

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.

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

Key Engineering Materials ◽

10.4028/www.scientific.net/kem.540.87 ◽

2013 ◽

Vol 540 ◽

pp. 87-98 ◽

Cited By ~ 1

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.

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Research on Two-Step Damage Detection Method for Complex Gird Truss Structure under Wind Load

Applied Mechanics and Materials ◽

10.4028/www.scientific.net/amm.256-259.1131 ◽

2012 ◽

Vol 256-259 ◽

pp. 1131-1138

Author(s):

Hui Liu ◽

Xue Liang Wang ◽

Wei Lian Qu

Keyword(s):

Spectral Density ◽

Damage Detection ◽

Power Spectral Density ◽

Detection Method ◽

Damage Index ◽

Truss Structure ◽

Truss Structures ◽

Detection Methods ◽

Modal Strain Energy ◽

Power Spectral

Considering characteristics of gird truss structure, the suitable two-step damage detection method for these structures is proposed in the paper. The acceleration power spectral density sensibility of structural nodes is obtained by analyzing their acceleration power spectral density value caused every damaged structural bar. According to sensibility value, the range of influence of damaged structural bar is determined, then structural sub regions are divided and accelerators are distributed. The first step damage detection methods is identifying damaged bar occurrence region, it is extracting damage index to identify the damage occurrence region based on changes of acceleration response power spectral density of structure damaged after and before. The second step damage detection methods is located damaged bar in the region, it is completed by finding the damaged bar based on the theory of dissipation ratio of modal strain energy damage detection method. At last, taking the gird truss structure as numerical example, it shows the method has the capability to detect the damage of complex gird truss structures successfully.

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Seismic Damage Detection Using Pushover Analysis

Advanced Materials Research ◽

10.4028/www.scientific.net/amr.255-260.2496 ◽

2011 ◽

Vol 255-260 ◽

pp. 2496-2499 ◽

Cited By ~ 5

Author(s):

Mohammadreza Vafaei ◽

Azlan bin Adnan ◽

Mohammadreza Yadollahi

Keyword(s):

Damage Detection ◽

Detection Method ◽

Ground Motions ◽

Pushover Analysis ◽

Damage Index ◽

Seismic Damage ◽

Nonlinear Behaviour ◽

Method Base ◽

Concrete Building ◽

Story Drift

Inter-story drift ratio is a general damage index which is being used to detect damaged stories after severe ground motions. Since this general damage index cannot detect damaged elements also the severity of imposed damages on elements, a new real-time seismic damage detection method base on artificial neural networks was proposed to overcome this issue. This approach considers nonlinear behaviour of structures and not only is capable of detecting damaged elements but also can address the severity of imposed damages. Proposed algorithm was applied on a 3-story concrete building .The obtained results confirmed accuracy and robustness of this method.

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Elimination of outlier measurements for damage detection of structures under changing environmental conditions

Structural Health Monitoring ◽

10.1177/1475921721998476 ◽

2021 ◽

pp. 147592172199847

Author(s):

William Soo Lon Wah ◽

Yining Xia

Keyword(s):

Damage Detection ◽

Multiple Regression ◽

Natural Frequencies ◽

Detection Method ◽

Detection Methods ◽

Structure Model ◽

Bridge Structure ◽

Beam Structure ◽

Dependent Variables ◽

The Difference

Damage detection methods developed in the literature are affected by the presence of outlier measurements. These measurements can prevent small levels of damage to be detected. Therefore, a method to eliminate the effects of outlier measurements is proposed in this article. The method uses the difference in fits to examine how deleting an observation affects the predicted value of a model. This allows the observations that have a large influence on the model created, to be identified. These observations are the outlier measurements and they are eliminated from the database before the application of damage detection methods. Eliminating the outliers before the application of damage detection methods allows the normal procedures to detect damage, to be implemented. A multiple-regression-based damage detection method, which uses the natural frequencies as both the independent and dependent variables, is also developed in this article. A beam structure model and an experimental wooden bridge structure are analysed using the multiple-regression-based damage detection method with and without the application of the method proposed to eliminate the effects of outliers. The results obtained demonstrate that smaller levels of damage can be detected when the effects of outlier measurements are eliminated using the method proposed in this article.

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Development of a Novel Damage Detection Framework for Truss Railway Bridges Using Operational Acceleration and Strain Response

Vibration ◽

10.3390/vibration4020028 ◽

2021 ◽

Vol 4 (2) ◽

pp. 422-445

Author(s):

Md Riasat Azim ◽

Mustafa Gül

Keyword(s):

Damage Detection ◽

Damage Identification ◽

Numerical Study ◽

Damage Index ◽

Strain Analysis ◽

Time History ◽

Principal Component ◽

Element Model ◽

Railway Bridges ◽

Truss Bridge

Railway bridges are an integral part of any railway communication network. As more and more railway bridges are showing signs of deterioration due to various natural and artificial causes, it is becoming increasingly imperative to develop effective health monitoring strategies specifically tailored to railway bridges. This paper presents a new damage detection framework for element level damage identification, for railway truss bridges, that combines the analysis of acceleration and strain responses. For this research, operational acceleration and strain time-history responses are obtained in response to the passage of trains. The acceleration response is analyzed through a sensor-clustering-based time-series analysis method and damage features are investigated in terms of structural nodes from the truss bridge. The strain data is analyzed through principal component analysis and provides information on damage from instrumented truss elements. A new damage index is developed by formulating a strategy to combine the damage features obtained individually from both acceleration and strain analysis. The proposed method is validated through a numerical study by utilizing a finite element model of a railway truss bridge. It is shown that while both methods individually can provide information on damage location, and severity, the new framework helps to provide substantially improved damage localization and can overcome the limitations of individual analysis.

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Structural Damage Assessment Using Output-Only Measurement: Localization and Quantification

Volume 2: Mechanics and Behavior of Active Materials; Structural Health Monitoring; Bioinspired Smart Materials and Systems; Energy Harvesting ◽

10.1115/smasis2013-3008 ◽

2013 ◽

Author(s):

Chin-Hsiung Loh ◽

Min-Hsuan Tseng ◽

Shu-Hsien Chao

Keyword(s):

Damage Detection ◽

Damage Assessment ◽

Structural Damage ◽

Damage Identification ◽

Model Updating ◽

Null Space ◽

Singular Spectrum Analysis ◽

Damage Index ◽

Computation Efficiency ◽

Output Only

One of the important issues to conduct the damage detection of a structure using vibration-based damage detection (VBDD) is not only to detect the damage but also to locate and quantify the damage. In this paper a systematic way of damage assessment, including identification of damage location and damage quantification, is proposed by using output-only measurement. Four level of damage identification algorithms are proposed. First, to identify the damage occurrence, null-space and subspace damage index are used. The eigenvalue difference ratio is also discussed for detecting the damage. Second, to locate the damage, the change of mode shape slope ratio and the prediction error from response using singular spectrum analysis are used. Finally, to quantify the damage the RSSI-COV algorithm is used to identify the change of dynamic characteristics together with the model updating technique, the loss of stiffness can be identified. Experimental data collected from the bridge foundation scouring in hydraulic lab was used to demonstrate the applicability of the proposed methods. The computation efficiency of each method is also discussed so as to accommodate the online damage detection.

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