Research on Frame-structure Damage Detection Based on Multi-resolution Entroy

2010 ◽  
Author(s):  
Dong Xiaoma
Keyword(s):  
Damage Detection ◽  
Frame Structure ◽  
Structure Damage

Structure Damage Detection via the Behavior of Substructure

1991 ◽  
Author(s):  
J. H. Wang ◽  
C. S. Liou
Keyword(s):  
Damage Detection ◽  
Mechanical System ◽  
Dynamic Behavior ◽  
Structural Damage ◽  
Structure Damage

Abstract A mechanical system generally consists of many substructures. However, it is impossible to observe the dynamic behavior of any substructure directly when the whole structure is in operation. A method was proposed in this work to determine the FRFs of a substructure by using the measured FRFs of the whole structure and the priorly known FRFs of another substructure With this method, one can detect the structural damage more easily by observing the change of the FRFs of the damaged substructure.

A hybrid methodology for structure damage detection uniting FEM and 1D-CNNs: Demonstration on typical high-pile wharf

2022 ◽  
Vol 168 ◽  
pp. 108738
Author(s):  
Yujue Zhou ◽  
Yonglai Zheng ◽  
Yongcheng Liu ◽  
Tanbo Pan ◽  
Yubao Zhou
Keyword(s):  
Damage Detection ◽  
Structure Damage ◽  
Hybrid Methodology

Signal processing and damage detection in a frame structure excited by chaotic input force

2003 ◽  
Author(s):  
Liming W. Salvino ◽  
Darryll J. Pines ◽  
Michael D. Todd ◽  
Jonathan Nichols
Keyword(s):  
Signal Processing ◽  
Damage Detection ◽  
Frame Structure ◽  
Input Force

A Vibration-Based Structural Damage Detection Method and its Applications to Engineering Structures

2011 ◽  
Author(s):  
K. He ◽  
W. D. Zhu
Keyword(s):  
Damage Detection ◽  
Iterative Algorithm ◽  
Structural Damage ◽  
Detection Method ◽  
New Physics ◽  
Logistic Function ◽  
Frame Structure ◽  
Engineering Structures ◽  
System Equations ◽  
Extent Of Damage

Two major challenges associated with a vibration-based damage detection method using changes in natural frequencies are addressed: accurate modeling of structures and the development of a robust inverse algorithm to detect damage, which are defined as the forward and inverse problems, respectively. To resolve the forward problem, new physics-based finite element modeling techniques are developed for fillets in thin-walled beams and for bolted joints, so that complex structures can be accurately modeled with a reasonable model size. To resolve the inverse problem, a logistic function transformation is introduced to convert the constrained optimization problem to an unconstrained one, and a robust iterative algorithm using the Levenberg-Marquardt method is developed to accurately detect the locations and extent of damage. The new methodology can ensure global convergence of the iterative algorithm in solving under-determined system equations and deal with damage detection problems with relatively large modeling error and measurement noise. It is applied to various engineering structures including lightning masts, a space frame structure and one of its components, and a pipeline. The exact locations and extent of damage can be detected in the numerical simulation, and the locations and extent of damage can be successfully detected in experimental damage detection.

Research for Structural Damage Identification Method Based on Stable Time Series and Principal Component Analysis

2014 ◽  
Vol 578-579 ◽  
pp. 1020-1023
Author(s):  
Jing Zhou Lu ◽  
Jia Chen Wang ◽  
Xu Zhu
Keyword(s):  
Principal Component Analysis ◽  
Time Series ◽  
Damage Detection ◽  
Structural Damage ◽  
Computing Time ◽  
Principal Component ◽  
Component Analysis ◽  
Identification Accuracy ◽  
Frame Structure ◽  
Ar Model

In this paper, we introduce a set of techniques for time series analysis based on principal component analysis (PCA). Firstly, the autoregressive (AR) model is established using acceleration response data, and the root mean squared error (RMSE) of AR model is calculated based on PCA. Then a new damage sensitive feature (DSF) based on the AR coefficients is presented. To test the efficacy of the damage detection and localization methodologies, the algorithm has been tested on the analytical and experimental results of a three-story frame structure model of the Los Alamos National Laboratory. The result of the damage detection indicates that the algorithm is able to identify and localize minor to severe damage as defined for the structure. It shows that the suggested method can lead to less amount of computing time, high suitability and identification accuracy.

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.

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