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

Vibration ◽  
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.

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.

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

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.

FEM Free Damage Detection of Beam Structures Using the Deflections Estimated by Modal Flexibility Matrix

2021 ◽  
pp. 2150128
Author(s):  
Wen-Yu He ◽  
Wei-Xin Ren ◽  
Lei Cao ◽  
Quan Wang
Keyword(s):  
Damage Detection ◽  
Structural Damage ◽  
Damage Index ◽  
Element Model ◽  
Mode Shapes ◽  
Beam Structures ◽  
Flexibility Matrix ◽  
Damage Quantification ◽  
Modal Flexibility ◽  
The Cost

The deflection of the beam estimated from modal flexibility matrix (MFM) indirectly is used in structural damage detection due to the fact that deflection is less sensitive to experimental noise than the element in MFM. However, the requirement for mass-normalized mode shapes (MMSs) with a high spatial resolution and the difficulty in damage quantification restricts the practicability of MFM-based deflection damage detection. A damage detection method using the deflections estimated from MFM is proposed for beam structures. The MMSs of beams are identified by using a parked vehicle. The MFM is then formulated to estimate the positive-bending-inspection-load (PBIL) caused deflection. The change of deflection curvature (CDC) is defined as a damage index to localize damage. The relationship between the damage severity and the deflection curvatures is further investigated and a damage quantification approach is proposed accordingly. Numerical and experimental examples indicated that the presented approach can detect damages with adequate accuracy at the cost of limited number of sensors. No finite element model (FEM) is required during the whole detection process.

scholarly journals Use of Time- and Frequency-Domain Approaches for Damage Detection in Civil Engineering Structures

2014 ◽  
Vol 2014 ◽  
pp. 1-9 ◽  
Author(s):  
V. H. Nguyen ◽  
J. Mahowald ◽  
S. Maas ◽  
J.-C. Golinval
Keyword(s):  
Damage Detection ◽  
Frequency Domain ◽  
Prestressed Concrete ◽  
Civil Engineering ◽  
Damage Identification ◽  
Real Life ◽  
Hankel Matrix ◽  
Principal Component ◽  
Engineering Structures ◽  
Civil Engineering Structures

The aim of this paper is to apply both time- and frequency-domain-based approaches on real-life civil engineering structures and to assess their capability for damage detection. The methodology is based on Principal Component Analysis of the Hankel matrix built from output-only measurements and of Frequency Response Functions. Damage detection is performed using the concept of subspace angles between a current (possibly damaged state) and a reference (undamaged) state. The first structure is the Champangshiehl Bridge located in Luxembourg. Several damage levels were intentionally created by cutting a growing number of prestressed tendons and vibration data were acquired by the University of Luxembourg for each damaged state. The second example consists in reinforced and prestressed concrete panels. Successive damages were introduced in the panels by loading heavy weights and by cutting steel wires. The illustrations show different consequences in damage identification by the considered techniques.

Damage Detection in Rods Using Wave Propagation and Regression Analysis

1999 ◽  
Author(s):  
K. T. Feroz ◽  
S. O. Oyadiji
Keyword(s):  
Wave Propagation ◽  
Regression Analysis ◽  
Damage Detection ◽  
Numerical Study ◽  
Time History ◽  
Ball Impact ◽  
Spherical Ball ◽  
Time Histories ◽  
Measured Strain ◽  
Force Time

Abstract The phenomena of wave propagation in rods was studied both numerically and experimentally. The finite element (FE) code ABAQUS was used for the numerical study while PZT (lead zirconium titanate) sensors and a 50 MHz transient recorder were used experimentally to monitor and to capture the propagation of stress pulses. For the study of damage detection in the rods the analyses and the experiments were repeated by introducing slots in a fixed axial location of the rod. A longitudinal wave was induced in the rod via collinear impact which was modelled in the FE analyses using the force-time history computed from the classical Hertz contact theory. In the experimental measurements this was achieved by a spherical ball impact at one plane end of the rods. It is shown that the predicted and measured strain-time histories for the defect-free rod and for the rods with defect correlate quite well. These results also show that defects can be located using the wave propagation phenomena. A regression analysis technique of the predicted and measured strain histories of the defect free rod and of the rod with defect was also performed. The results show that this technique is more efficient for smaller defects. In particular, it is shown that the area enclosed by the regression curve increases as the defect size increases.

Study on Damage Location of Spatial Structures Based on Wavelet Analysis of Model Strain Energy

2013 ◽  
Vol 639-640 ◽  
pp. 1033-1037
Author(s):  
Yong Mei Li ◽  
Bing Zhou ◽  
Guo Fu Sun ◽  
Bo Yan Yang
Keyword(s):  
Wavelet Analysis ◽  
Damage Detection ◽  
Structural Damage ◽  
Strain Energy ◽  
Damage Identification ◽  
Damage Index ◽  
Structural Damage Detection ◽  
Modal Strain Energy ◽  
Wavelet Method ◽  
Long Span

The research to identify and locate the damage to the engineering structure mainly aimed at some simple structure forms before, such as beam and framework. Damage shows changes of local characteristics of the signal, while wavelet analysis can reflect local damage traits of the signal in time domain and frequency domain. For confirming the validity and applicability of structural damage identification methods, wavelet analysis is used to spatial structural damage detection. The wavelet analysis technique provides new ideas and methods of spatial steel structural damage detection. Based on the theory of wavelet singularity detection，with the injury signal of modal strain energy as structural damage index，the mixing of the modal strain energy and wavelet method to identify and locate the damage to the spatial structure is considered. The multiplicity of the bars and nodes can be taken into account, and take the destructive and nondestructive modal strain energy of Kiewitt-type reticulated shell with 40m span as an example of numerical simulation，the original damage signal and the damage signal after wavelet transformation is compared. The location of the declining stiffness identified by the maximum of wavelet coefficients，analyzed as signal by db1 wavelet，and calculate the graph relation between coefficients of the wavelets and the damage to the structure by discrete or continuous wavelet transform, and also check the accuracy degree of this method with every damage case. Finally，the conclusion is drawn that the modal strain energy and wavelet method to identify and locate the damage to the long span reticulated shell is practical, effective and accurate, that the present method as a reliable and practical way can be adopted to detect the single and several locations of damage in structures.

Correlation-Based Damage Identification and Quantification Using Modal Kinetic Energy Change

2020 ◽  
Vol 20 (10) ◽  
pp. 2042007
Author(s):  
J. T. Joseph ◽  
T. H. T. Chan ◽  
K.-D. Nguyen
Keyword(s):  
Kinetic Energy ◽  
Damage Detection ◽  
Damage Identification ◽  
Numerical Study ◽  
Traditional Approach ◽  
Mass Change ◽  
Algorithm Optimization ◽  
Damage Scenarios ◽  
Simply Supported ◽  
Modal Properties

Many existing damage identification or quantification methods can be employed only if the internal and external mass changes are negligible when tested at two different states of a structure. This paper presents a new Modal Kinetic Energy (MKE)-based method to detect and quantify damage using modal properties of structures, which can be employed even in situations when mass change is not more than a certain extent. A new damage sensitivity parameter has been developed using measured modal characteristics of baseline structure. The MKE change (MKEC) concept is then employed to locate damage and to estimate relative perturbation at each element. The relative damage extent vector is estimated by searching the best correlation between the analytical and experimental MKEC vectors with the help of genetic algorithm optimization tool. The extent of damage is calculated after computing damage scaling coefficient using measured eigenvalue change vector. A numerical study is carried out on a simply supported single span beam to confirm its performance under various test conditions. The robustness of the proposed MKE method and the significance of mass variation in the damage detection approach are evaluated by comparing the damage quantification results with a traditional approach. Finally, the proposed damage detection method is applied on a two-span simply supported beam for single and multiple damage scenarios by extracting the modal properties experimentally. The results revealed that the proposed approach is capable of detecting and estimating single and multiple damages with reasonable accuracy even in moderate noise contaminated and mass change environments.

scholarly journals Structural Damage Diagnosis-Oriented Impulse Response Function Estimation under Seismic Excitations

Sensors ◽  
2019 ◽  
Vol 19 (24) ◽  
pp. 5413
Author(s):  
Jian-Fu Lin ◽  
Junfang Wang ◽  
Li-Xin Wang ◽  
Siu-seong Law
Keyword(s):  
Damage Detection ◽  
Impulse Response ◽  
Response Function ◽  
Structural Damage ◽  
Numerical Study ◽  
Damage Index ◽  
Impulse Response Function ◽  
Function Estimation ◽  
Seismic Excitations ◽  
Transformation Matrices

Impulse response function (IRF) is an ideal structural damage index for the identification of structural damage associated with changes in modal properties. However, IRFs from multiple excitations applied at different degrees-of-freedoms jointly contribute to the dynamic response, and their estimation is often underdetermined. Although some efforts have been devoted to the estimation of IRF for a structure under single excitation, the case under multiple excitations has not been fully investigated yet. The estimation of IRF under multiple excitations is generally an ill-conditioned inverse problem such that an incorrect or non-feasible solution is common, preventing its application to damage detection. This work explores this problem by introducing dimensionality reduction transformation matrices relating two sets of IRFs of a structure with discussions on the performance of the non-unique transformation matrices. Then, the extraction of IRF via wavelet-based and Tikhonov regularization-based methods are compared. Finally, a numerical study with a truss structure is conducted to validate the estimation of the IRFs and to demonstrate their applicability for damage detection under seismic excitations. Both the damage locations and severity are accurately identified, indicating the proposed methodology can enable the IRFs estimation under multiple excitations for successful damage detection.

scholarly journals A cost-effective neural network–based damage detection procedure for cylindrical equipment

2019 ◽  
Vol 11 (7) ◽  
pp. 168781401986694 ◽  
Author(s):  
R Karami-Mohammadi ◽  
M Mirtaheri ◽  
M Salkhordeh ◽  
MA Hariri-Ardebili
Keyword(s):  
Neural Networks ◽  
Damage Detection ◽  
Damage Index ◽  
Principal Component ◽  
Numerical Data ◽  
Cost Effective ◽  
Voltage Transformer ◽  
Detection Model ◽  
The Neural Networks ◽  
Parametric Analyses

This article presents a vibration-based technique for damage detection in the cylindrical equipment. First, a damage index based on the residual frequency responses is defined. This technique uses the principal component analysis for data reduction by eliminating the components that have the minimum contribution to the damage index. Then, the principal components are fed into neural networks to identify the changes in the damage pattern. Furthermore, the efficiency of this technique in the field condition is investigated by adding different noise levels to the output data. This study aims at proposing a cost-effective damage detection model using only one sensor. Therefore, the optimal location of the sensor is also discussed. A case study of capacitive voltage transformer is used for validation of finite element models. The neural networks are trained using numerical data and tested with experimental one. Several parametric analyses are performed to investigate the sensitivity of the model.

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