DATA FUSION-BASED STRUCTURAL DAMAGE DETECTION UNDER VARYING TEMPERATURE CONDITIONS

2012 ◽  
Vol 12 (06) ◽  
pp. 1250052 ◽  
Author(s):  
YUEQUAN BAO ◽  
YONG XIA ◽  
HUI LI ◽  
YOU-LIN XU ◽  
PENG ZHANG
Keyword(s):  
Data Fusion ◽  
Damage Detection ◽  
Temperature Effect ◽  
Test Data ◽  
Mode Shapes ◽  
Detection Accuracy ◽  
Modal Data ◽  
Temperature Conditions ◽  
Uncertainty Measurement ◽  
Structural Responses

A huge number of data can be obtained continuously from a number of sensors in long-term structural health monitoring (SHM). Different sets of data measured at different times may lead to inconsistent monitoring results. In addition, structural responses vary with the changing environmental conditions, particularly temperature. The variation in structural responses caused by temperature changes may mask the variation caused by structural damages. Integration and interpretation of various types of data are critical to the effective use of SHM systems for structural condition assessment and damage detection. A data fusion-based damage detection approach under varying temperature conditions is presented. The Bayesian-based damage detection technique, in which both temperature and structural parameters are the variables of the modal properties (frequencies and mode shapes), is developed. Accordingly, the probability density functions of the modal data are derived for damage detection. The damage detection results from each set of modal data and temperature data may be inconsistent because of uncertainties. The Dempster–Shafer (D–S) evidence theory is then employed to integrate the individual damage detection results from the different data sets at different times to obtain a consistent decision. An experiment on a two-story portal frame is conducted to demonstrate the effectiveness of the proposed method, with consideration on model uncertainty, measurement noise, and temperature effect. The damage detection results obtained by combining the damage basic probability assignments from each set of test data are more accurate than those obtained from each test data separately. Eliminating the temperature effect on the vibration properties can improve the damage detection accuracy. In particular, the proposed technique can detect even the slightest damage that is not detected by common damage detection methods in which the temperature effect is not eliminated.

L1 Regularized Model Updating for Structural Damage Detection

2018 ◽  
Vol 18 (12) ◽  
pp. 1850157 ◽  
Author(s):  
Yu-Han Wu ◽  
Xiao-Qing Zhou
Keyword(s):  
Damage Detection ◽  
Structural Damage ◽  
Model Updating ◽  
Regularization Parameter ◽  
Structural Vibration ◽  
Mode Shapes ◽  
Modal Data ◽  
Vibration Data ◽  
Stiffness Reduction ◽  
Regularized Model

Model updating methods based on structural vibration data have been developed and applied to detecting structural damages in civil engineering. Compared with the large number of elements in the entire structure of interest, the number of damaged elements which are represented by the stiffness reduction is usually small. However, the widely used [Formula: see text] regularized model updating is unable to detect the sparse feature of the damage in a structure. In this paper, the [Formula: see text] regularized model updating based on the sparse recovery theory is developed to detect structural damage. Two different criteria are considered, namely, the frequencies and the combination of frequencies and mode shapes. In addition, a one-step model updating approach is used in which the measured modal data before and after the occurrence of damage will be compared directly and an accurate analytical model is not needed. A selection method for the [Formula: see text] regularization parameter is also developed. An experimental cantilever beam is used to demonstrate the effectiveness of the proposed method. The results show that the [Formula: see text] regularization approach can be successfully used to detect the sparse damaged elements using the first six modal data, whereas the [Formula: see text] counterpart cannot. The influence of the measurement quantity on the damage detection results is also studied.

scholarly journals A new approach toward damage localization and quantification of structures under changing temperature condition

2018 ◽  
Vol 39 (3) ◽  
pp. 572-587 ◽  
Author(s):  
William Soo Lon Wah ◽  
Yung-Tsang Chen
Keyword(s):  
Damage Detection ◽  
Temperature Effect ◽  
Detection Methods ◽  
Effect Of Temperature ◽  
Temperature Conditions ◽  
Single Temperature ◽  
Wide Range ◽  
Actual Damage ◽  
Shear Building ◽  
Two Stages

Most damage detection methods developed in the literature cannot give the locations and extent of damages under the presence of varying temperature condition. This is because temperature condition changes the vibration properties of a structure, which are commonly analyzed for damage detection, and temperature gradient throughout the structure makes it difficult to create a baseline for the undamaged structure, as the baseline is generally constructed using features obtained under a wide range of temperature conditions. In this paper, a new insight on how to approach damage detection using only a single temperature condition to create the baseline is proposed. This approach solves the damage detection under changing temperature problem in two stages by first quantifying the change of stiffness of all the elements in a structure due to temperature and damage effects, followed by removing the temperature effect, a global effect, to give the actual damage locations and extent. Using single temperature condition allows new measurements to be compared to a benchmark so that local deviation can be obtained, thus making the damaged elements identifiable. The proposed approach is tested using a beam structure model and a shear building under different gradient temperature conditions, and the results demonstrate that the method successfully eliminates the change in elemental stiffness due to temperature effect and gives correct damage locations and extent. The approach can be implemented with other existing damage detection methods that did not consider the effect of temperature so that structures under varying temperature condition can be analyzed.

Application of Extreme Learning Machine to Damage Detection of Plate-Like Structures

2017 ◽  
Vol 17 (07) ◽  
pp. 1750068 ◽  
Author(s):  
S. S. Kourehli
Keyword(s):  
Damage Detection ◽  
Extreme Learning Machine ◽  
Damage Identification ◽  
Mode Shapes ◽  
Effective Technique ◽  
Plate Structures ◽  
Modal Data ◽  
Plate Elements ◽  
Damage States ◽  
Learning Machine

An effective method for damage detection of plate structures using the extreme learning machine (ELM) is proposed in this study. With the ELM, the mode shapes and natural frequencies of a damaged plate are treated as the input and the damage states in the plate elements as the output. The proposed method was applied to two numerical examples, namely, a cantilever and a plate with four-fixed supports containing one or several damages with and without noise in the modal data. The results obtained reveal that the methodology can be used as an effective technique for the damage identification of plate structures using the modal data and ELM.

Prediction of Unmeasured Mode Shape Using Artificial Neural Network for Damage Detection

2013 ◽  
Vol 61 (1) ◽  
Author(s):  
L. D. Goh ◽  
N. Bakhary ◽  
A. A. Rahman ◽  
B. H. Ahmad
Keyword(s):  
Neural Network ◽  
Damage Detection ◽  
Mode Shape ◽  
Health Monitoring ◽  
Spline Interpolation ◽  
Measured Data ◽  
Mode Shapes ◽  
Modal Data ◽  
Artificial Neural ◽  
Shape Data

Artificial neural networks (ANNs) have received much attention in the field of vibration–based damage detection since the 1990s, due to their capability to predict damage from modal data. However, the accuracy of this method is highly dependent on the number of measurement points, especially when the mode shape is used as an indicator for damage detection. With a high number of measurement points, more information can be fed to the ANN to detect damage; therefore, more reliable results can be obtained. Nevertheless, in practice, it is uneconomical to install sensors on every part of a structure; thus the capability of ANNs to detect damage is quite limited. In this study, an ANN is applied to predict the unmeasured mode shape data based on a limited number of measured data. To demonstrate the accuracy of the proposed method, the results are compared with the Cubic Spline interpolation (CS) method. A parametric study is also conducted to investigate the sensitivity of the number of measurement points to the proposed method. The results show that the ANN provides more reliable results compared to the CS method as it is able to predict the magnitude of mode shapes at the unmeasured points with a limited number of measurement points. The application of a two–stage ANN showed results with a high potential for overcoming the issue of using a limited number of sensors in structural health monitoring.

scholarly journals Damage Detection in Grid Structures Using Limited Modal Test Data

2017 ◽  
Vol 2017 ◽  
pp. 1-11 ◽  
Author(s):  
Bei-dou Ding ◽  
Da-shuai Feng ◽  
Heng-lin Lv ◽  
Xian Li
Keyword(s):  
Damage Detection ◽  
Test Data ◽  
Column Vector ◽  
Mode Shapes ◽  
Engineering Practice ◽  
Frobenius Norm ◽  
Three Dimension ◽  
Grid Structure ◽  
Modal Strain Energy ◽  
Modal Test

The detection of potentially damaged elements in grid structures is a challenging topic. By using limited measured test data, damage detection for grid structures is developed by the modal strain energy (MSE) method. Two critical problems are considered in this paper in developing the MSE method to detect potential damage to the grid structure by using limited modal test data. First, an updated mode shape expansion method based on the modal assurance criterion is adopted to ensure that the modal shape obtained from the reference baseline model is reliable and has explicit physical meanings. Second, after identifying the location of the element damage by the element MSE method with expanded mode shapes, multivariable parameters denoting element damage severity are simultaneously determined. These parameters are included in the column vector and matched with the corresponding element stiffness matrix while the error tolerance value of the Frobenius norm of the column vector is undercontrolled. Finally, a three-dimension numerical model of the grid structure is used to represent different damage cases and to demonstrate the effectiveness of the present method. The application of the three-dimension physical model to a full-scale grid structure is also verified. Analysis results demonstrate that the presented damage detection method effectively locates and quantifies single- and multimember damage in grid structures and can be applied in engineering practice.

On the Identification of Localized Losses of Stiffness in Structures

1993 ◽  
Author(s):  
Ulrich Pabst ◽  
Peter Hagedorn
Keyword(s):  
Mathematical Model ◽  
Damage Detection ◽  
Mode Shape ◽  
Measurement Errors ◽  
Mode Shapes ◽  
Shape Functions ◽  
Modal Data ◽  
Order Of Magnitude ◽  
Eigen Frequencies ◽  
Local Stiffness

Abstract In damage detection it is common to use measured modal data and a mathematical model in connection with system identification. The part of the system undergoing the largest stiffness decrease is defined to contain damage. This approach is very sensitive to measurement errors. The measurement errors are much larger for mode shape functions than for the eigen-frequencies. The errors in the mode shapes are often of the same order of magnitude as the variations due to damage leading to poor results in damage detection. Thus, the use of the mode shape functions themselves instead of their small damage induced variations would dearly be preferable. In this paper we examine the relation between the changes in the eigenfrequencies, the local stiffness losses and the mode shape functions of the undamaged system. This relation is then utilized in a damage detection procedure.

scholarly journals Identification of Damage in a Beam Structure by Using Mode Shape Curvature Squares

2010 ◽  
Vol 17 (4-5) ◽  
pp. 601-610 ◽  
Author(s):  
S. Rucevskis ◽  
M. Wesolowski
Keyword(s):  
Damage Detection ◽  
Mode Shape ◽  
Dynamic Structure ◽  
Mode Shapes ◽  
Difference Approximation ◽  
Laser Vibrometer ◽  
Beam Structure ◽  
Central Difference ◽  
Modal Data ◽  
Healthy State

During the last decades a great variety of methods have been proposed for damage detection by using the dynamic structure characteristics, however, most of them require modal data of the structure for the healthy state as a reference. In this paper the applicability of the mode shape curvature squares determined from only the damaged state of the structure for damage detection in a beam structure is studied. To establish the method, two aluminium beams containing different-size mill-cut damage at different locations are tested by using the experimentally measured modal data. The experimental modal frequencies and the corresponding mode shapes are obtained by using a scanning laser vibrometer with a PZT actuator. From the mode shapes, mode shape curvatures are obtained by using a central difference approximation. With the example of the beams with free-free and clamped boundary conditions, it is shown that the mode shape curvature squares can be used to detect damage in the structures. Further, the extent of a mill-cut damage is identified via modal frequencies by using a mixed numerical-experimental technique. The method is based on the minimization of the discrepancy between the numerically calculated and experimentally measured frequencies.

scholarly journals VIBRATION-BASED DAMAGE DETECTION IN A BEAM STRUCTURE WITH MULTIPLE DAMAGE LOCATIONS

Aviation ◽  
2009 ◽  
Vol 13 (3) ◽  
pp. 61-71 ◽  
Author(s):  
Sandris Ručevskis ◽  
Miroslaw Wesolowski ◽  
Andris Chate
Keyword(s):  
Damage Detection ◽  
Mode Shape ◽  
Failure Modes ◽  
Mode Shapes ◽  
Difference Approximation ◽  
Laser Vibrometer ◽  
Shape Information ◽  
Modal Data ◽  
Damage Indices ◽  
Damage Extent

During the last two decades structural damage identification using dynamic parameters of the structure has become an important research area for civil, mechanical, and aerospace engineering communities. The basic idea of the vibration‐based damage detection methods is that a damage as a combination of different failure modes in the form of loss of local stiffness in the structure alters its dynamic characteristics, i.e., the modal frequencies, mode shapes, and modal damping values. A great variety of methods have been proposed for damage detection by using dynamic structure parameters; however, most of them require modal data of the healthy state of structure as a reference. In this paper a vibration‐based damage detection method, which uses the mode shape information determined from only the damaged state of the structure is proposed. To establish the method, two aluminium beams containing different sizes of mill‐cut damage at a single location as well as two aluminium beams containing different sizes of mill‐cut damage at multiple locations are examined. The experimental modal frequencies and the corresponding mode shapes for the first 15 flexural modes are obtained by using a scanning laser vibrometer with a PZT actuator. From the mode shapes, mode shape curvatures are obtained by using a central difference approximation. In order to exclude the influence of measurement noise on the modal data and misleading damage indices, it is proposed to use the sum of mode shape curvature squares for each mode. With the example of the beams with free‐free and clamped boundary conditions, it is shown that the mode shape curvature squares can be used to detect damage in the structures. The extent of mill‐cut damage is identified via the modal frequencies by using mixed numerical‐experimental technique. The method is based on the minimization of the discrepancy between the numerically calculated and the experimentally measured frequencies. The numerical frequencies are calculated by employing a finite‐element model for beam with introduced damage. Further, by using the response surface approach, a relationship (second‐order polynomial function) between the modal frequencies and the damage extent is constructed. The damage extent is obtained by solving the minimization problem. Santrauka Tyrimo metu buvo ieškomos sijines konstrukcijos pažeidimo frezuojant vietos, apimtis ir pažeidimo dydis pagal atlikto vibraciju eksperimento dinamines charakteristikas. Pažeidimo padetis ir apimtis buvo nustatomi pagal išlinkio formos virpesiu kvadrato dydi. Pažeidimo dydis buvo nustatomas skaitiniu‐eksperimentiniu metodu, taikant modalinius dažnius. Šio metodo efektyvumas ir patikimumas parodytas tiriant dvi aliuminio sijas, kurios buvo pažeistos frezos vienoje vietoje ir kurios buvo pažeistos skirtingose vietose.

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