scholarly journals Sensitivity of Parameter Changes in Structural Damage Detection

1997 ◽  
Vol 4 (1) ◽  
pp. 27-37 ◽  
Author(s):  
C. H. Jenkins ◽  
L. Kjerengtroen ◽  
H. Oestensen
Keyword(s):  
Damage Detection ◽  
Structural Damage ◽  
Structural Response ◽  
Theoretical Models ◽  
Modal Parameters ◽  
Complex Structures ◽  
Static Deflection ◽  
Structural Damage Detection ◽  
Dynamic Measurements ◽  
Static Deflection Measurements

Structural damage detection by nondestructive methods is highly desirable. Changes in modal parameters such as frequency, damping, and mode shape are particularly inviting. Evidence is presented here that reveals that static deflection can, in many cases, be a more sensitive predictor of structural damage than frequency. The reasons for this are illuminated within, and hinge on very fundamental issues about the very nature of structural response. Furthermore, static deflection measurements are often easier to make, with higher levels of accuracy than dynamic measurements. Comparisons are made between theoretical models and experimental results for simple structures, with extensions given to more complex structures.

Photogrammetry-based structural damage detection by tracking a visible laser line

2019 ◽  
Vol 19 (1) ◽  
pp. 322-336 ◽  
Author(s):  
Yongfeng Xu
Keyword(s):  
Finite Element ◽  
Damage Detection ◽  
Structural Damage ◽  
Detection Method ◽  
Element Model ◽  
Target Line ◽  
Laser Line ◽  
Modal Parameters ◽  
Structural Damage Detection ◽  
Visible Laser

Research works on photogrammetry have received tremendous attention in the past few decades. One advantage of photogrammetry is that it can measure displacement and deformation of a structure in a fully non-contact, full-field manner. As a non-destructive evaluation method, photogrammetry can be used to detect structural damage by identifying local anomalies in measured deformation of a structure. Numerous methods have been proposed to measure deformations by tracking exterior features of structures, assuming that the features can be consistently identified and tracked on sequences of digital images captured by cameras. Such feature-tracking methods can fail if the features do not exist on captured images. One feasible solution to the potential failure is to artificially add exterior features to structures. However, painting and mounting such features can introduce unwanted permanent surficial modifications, mass loads, and stiffness changes to structures. In this article, a photogrammetry-based structural damage detection method is developed, where a visible laser line is projected to a surface of a structure, serving as an exterior feature to be tracked; the projected laser line is massless and its existence is temporary. A laser-line-tracking technique is proposed to track the projected laser line on captured digital images. Modal parameters of a target line corresponding to the projected laser line can be estimated by conducting experimental modal analysis. By identifying anomalies in curvature mode shapes of the target line and mapping the anomalies to the projected laser line, structural damage can be detected with identified positions and sizes. An experimental investigation of the damage detection method was conducted on a damaged beam. Modal parameters of a target line corresponding to a projected laser line were estimated, which compared well with those from a finite element model of the damaged beam. Experimental damage detection results were validated by numerical ones from the finite element model.

scholarly journals Structural Damage Identification Based on the Minimum System Realization and Sensitivity Analysis

2014 ◽  
Vol 2014 ◽  
pp. 1-12
Author(s):  
W. R. Li ◽  
Y. F. Du ◽  
S. Y. Tang ◽  
L. J. Zhao
Keyword(s):  
Sensitivity Analysis ◽  
Damage Detection ◽  
Structural Damage ◽  
Damage Identification ◽  
Structural Information ◽  
Structural Response ◽  
Frame Structure ◽  
Structural Damage Detection ◽  
System Realization ◽  
Minimum System

On the basis of the thought that the minimum system realization plays the role as a coagulator of structural information and contains abundant information on the structure, this paper proposes a new method, which combines minimum system realization and sensitivity analysis, for structural damage detection. The structural damage detection procedure consists of three steps: (1) identifying the minimum system realization matrixes A, B, and R using the structural response data; (2) defining the mode vector, which is based on minimum system realization matrix, by introducing the concept of the measurement; (3) identifying the location and severity of the damage step by step by continuously rotating the mode vector. The proposed method was verified through a five-floor frame model. As demonstrated by numerical simulation, the proposed method based on the combination of the minimum realization system and sensitivity analysis is effective for the damage detection of frame structure. This method not only can detect the damage and quantify the damage severity, but also is not sensitive to the noise.

scholarly journals Modal Strain Energy-Based Structural Damage Detection Using Convolutional Neural Networks

2019 ◽  
Vol 9 (16) ◽  
pp. 3376 ◽  
Author(s):  
Shuai Teng ◽  
Gongfa Chen ◽  
Gen Liu ◽  
Jianbin Lv ◽  
Fangsen Cui
Keyword(s):  
Neural Network ◽  
Neural Networks ◽  
Damage Detection ◽  
Structural Damage ◽  
Strain Energy ◽  
Frame Structure ◽  
Modal Parameters ◽  
Structural Damage Detection ◽  
Simulation Data ◽  
Modal Strain Energy

In this paper, a convolutional neural network (CNN) was used to extract the damage features of a steel frame structure. As structural damage could induce changes of the modal parameters of the structure, the convolution operation was used to extract the features of modal parameters, and a classification algorithm was used to judge the damage state of the structure. The finite element method was applied to analyze the free vibration of the steel frame and obtain the first-order modal strain energy for various damage scenarios, which was used as the CNN training sample. Then vibration experiments were carried out, and modal parameters were obtained from the modal analysis of the vibration signals. The experimental data were inputted into the CNN to verify its damage detection capability. The result showed that the CNN was effective in detecting the intact structure, single damage, and multi damages with an accuracy of 100%. For comparison, the same samples were also applied to the traditional back propagation (BP) neural network, which failed to detect the intact structure and multiple-damage cases. It was found that: (1) The proposed CNN could be trained from finite element simulation data and used in real frame structure damage detection, and it performed better in structural damage detection than BP neural networks; (2) the measured data of a real structure could be supplemented by numerical simulation data, and satisfactory results have been demonstrated.

scholarly journals Structural Damage Detection by Using Single Natural Frequency and the Corresponding Mode Shape

2016 ◽  
Vol 2016 ◽  
pp. 1-8 ◽  
Author(s):  
Bo Zhao ◽  
Zili Xu ◽  
Xuanen Kan ◽  
Jize Zhong ◽  
Tian Guo
Keyword(s):  
Damage Detection ◽  
Natural Frequency ◽  
Mode Shape ◽  
Structural Damage ◽  
Bending Moment ◽  
Mode Shapes ◽  
Modal Parameters ◽  
Structural Damage Detection ◽  
Damage Scenarios ◽  
Flexibility Matrix

Damage can be identified using generalized flexibility matrix based methods, by using the first natural frequency and the corresponding mode shape. However, the first mode is not always appropriate to be used in damage detection. The contact interface of rod-fastened-rotor may be partially separated under bending moment which decreases the flexural stiffness of the rotor. The bending moment on the interface varies as rotating speed changes, so that the first- and second-modal parameters obtained are corresponding to different damage scenarios. In this paper, a structural damage detection method requiring single nonfirst mode is proposed. Firstly, the system is updated via restricting the first few mode shapes. The mass matrix, stiffness matrix, and modal parameters of the updated system are derived. Then, the generalized flexibility matrix of the updated system is obtained, and its changes and sensitivity to damage are derived. The changes and sensitivity are used to calculate the location and severity of damage. Finally, this method is tested through numerical means on a cantilever beam and a rod-fastened-rotor with different damage scenarios when only the second mode is available. The results indicate that the proposed method can effectively identify single, double, and multiple damage using single nonfirst mode.

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