Structural Damage Identification Method Based on Displacement Data

2014 ◽  
Vol 610 ◽  
pp. 241-245
Author(s):  
Hong Yue Sun ◽  
Fan Wen
Keyword(s):  
Finite Element ◽  
Structural Damage ◽  
Model Building ◽  
Damage Identification ◽  
Measurement Data ◽  
Structure Model ◽  
Structure Damage ◽  
Finite Element Software ◽  
Structural Damage Identification ◽  
Identification Theory

Structural damage identification is a hot research topic in the field of building structural health monitoring, according to the problem of building structural damage is difficult to accurately identify, conducting the research of the abnormal monitoring data. In the summary and the research on the basis of the current domestic construction structure damage identification theory, this paper proposes a combined with finite element method based on displacement measurement data of structural damage identification methods, verified by the structure model building in PKPM finite element software, the method has higher recognition accuracy and operability and effectiveness.

Review on Damage Identification and Diagnosis Research of Civil Engineering Structure

2014 ◽  
Vol 1006-1007 ◽  
pp. 34-37 ◽  
Author(s):  
Hong Ni ◽  
Ming Hui Li ◽  
Xi Zuo
Keyword(s):  
Structural Damage ◽  
Civil Engineering ◽  
Damage Identification ◽  
Engineering Structures ◽  
Engineering Structure ◽  
Civil Engineering Structure ◽  
Structure Damage ◽  
Development Direction ◽  
Structural Damage Identification ◽  
Civil Engineering Structures

This paper first describes the importance of structural damage identification and diagnosis in civil engineering, and introduces domestic and foreign status of damage identification and diagnosis methods, and on the basis of this, it also introduces all kinds of methods for damage identification and diagnosis of civil engineering structures, and finally puts forward the development direction of civil engineering structure damage identification and diagnosis.

scholarly journals Development and application of a deep learning–based sparse autoencoder framework for structural damage identification

2018 ◽  
Vol 18 (1) ◽  
pp. 103-122 ◽  
Author(s):  
Chathurdara Sri Nadith Pathirage ◽  
Jun Li ◽  
Ling Li ◽  
Hong Hao ◽  
Wanquan Liu ◽  
...  
Keyword(s):  
Dimensionality Reduction ◽  
Structural Damage ◽  
Damage Identification ◽  
Experimental Studies ◽  
Measurement Data ◽  
Frame Structure ◽  
Stiffness Reduction ◽  
Highly Nonlinear ◽  
Structural Damage Identification ◽  
Sparse Autoencoder

This article proposes a deep sparse autoencoder framework for structural damage identification. This framework can be employed to obtain the optimal solutions for some pattern recognition problems with highly nonlinear nature, such as learning a mapping between the vibration characteristics and structural damage. Three main components are defined in the proposed framework, namely, the pre-processing component with a data whitening process, the sparse dimensionality reduction component where the dimensionality of the original input vector is reduced while preserving the required necessary information, and the relationship learning component where the mapping between the compressed dimensional feature and the stiffness reduction parameters of the structure is built. The proposed framework utilizes the sparse autoencoders based deep neural network structure to enhance the capability and performance of the dimensionality reduction and relationship learning components with a pre-training scheme. In the final stage of training, both components are jointly optimized to fine-tune the network towards achieving a better accuracy in structural damage identification. Since structural damages usually occur only at a small number of elements that exhibit stiffness reduction out of the large total number of elements in the entire structure, sparse regularization is adopted in this framework. Numerical studies on a steel frame structure are conducted to investigate the accuracy and robustness of the proposed framework in structural damage identification, taking into consideration the effects of noise in the measurement data and uncertainties in the finite element modelling. Experimental studies on a prestressed concrete bridge in the laboratory are conducted to further validate the performance of using the proposed framework for structural damage identification.

scholarly journals Sensitivity Analysis Using a Reduced Finite Element Model for Structural Damage Identification

Materials ◽  
2021 ◽  
Vol 14 (19) ◽  
pp. 5514
Author(s):  
Qiuwei Yang ◽  
Xi Peng
Keyword(s):  
Sensitivity Analysis ◽  
Finite Element ◽  
Finite Element Model ◽  
Structural Damage ◽  
Damage Identification ◽  
Generalized Inverse ◽  
Linear Equations ◽  
Element Model ◽  
Eigenvalues And Eigenvectors ◽  
Structural Damage Identification

Sensitivity analysis is widely used in engineering fields, such as structural damage identification, model correction, and vibration control. In general, the existing sensitivity calculation formulas are derived from th,,,e complete finite element model, which requires a large amount of calculation for large-scale structures. In view of this, a fast sensitivity analysis algorithm based on the reduced finite element model is proposed in this paper. The basic idea of the proposed sensitivity analysis algorithm is to use a model reduction technique to avoid the complex calculation required in solving eigenvalues and eigenvectors by the complete model. Compared with the existing sensitivity calculation formulas, the proposed approach may increase efficiency, with a small loss of accuracy of sensitivity analysis. Using the fast sensitivity analysis, the linear equations for structural damage identification can be established to solve the desired elemental damage parameters. Moreover, a feedback-generalized inverse algorithm is proposed in this work in order to improve the calculation accuracy of damage identification. The core principle of this feedback operation is to reduce the number of unknowns, step by step, according to the generalized inverse solution. Numerical and experimental examples show that the fast sensitivity analysis based on the reduced model can obtain almost the same results as those obtained by the complete model for low eigenvalues and eigenvectors. The feedback-generalized inverse algorithm can effectively overcome the ill-posed problem of the linear equations and obtain accurate results of damage identification under data noise interference. The proposed method may be a very promising tool for sensitivity analysis and damage identification based on the reduced finite element model.

scholarly journals Structural Damage Identification Based on Transmissibility in Time Domain

Sensors ◽  
2022 ◽  
Vol 22 (1) ◽  
pp. 393
Author(s):  
Yunfeng Zou ◽  
Xuandong Lu ◽  
Jinsong Yang ◽  
Tiantian Wang ◽  
Xuhui He
Keyword(s):  
Finite Element ◽  
Finite Element Model ◽  
Time Domain ◽  
Structural Damage ◽  
Damage Identification ◽  
Element Model ◽  
Time Frequency ◽  
Identification Method ◽  
Structural Damage Identification ◽  
The Time Domain

Structural damage identification technology is of great significance to improve the reliability and safety of civil structures and has attracted much attention in the study of structural health monitoring. In this paper, a novel structural damage identification method based on transmissibility in the time domain is proposed. The method takes the discrepancy of transmissibility of structure response in the time domain before and after damage as the basis of finite element model updating. The damage is located and quantified through iteration by minimizing the difference between the measurements at gauge locations and the reconstruction response extrapolated by the finite element model. Taking advantage of the response reconstruction method based on empirical mode decomposition, damage information can be obtained in the absence of prior knowledge on excitation. Moreover, this method directly collects time-domain data for identification without modal identification and frequent time–frequency conversion, which can greatly improve efficiency on the premise of ensuring accuracy. A numerical example is used to demonstrate the overall damage identification method, and the study of measurement noise shows that the method has strong robustness. Finally, the present work investigates the method through a simply supported overhanging beam. The experiments collect the vibration strain signals of the beam via resistance strain gauges. The comparison between identification results and theoretical values shows the effectiveness and accuracy of the method.

Study on Structural Damage Identification Based on Wavelet Analysis

2011 ◽  
Vol 374-377 ◽  
pp. 2588-2592
Author(s):  
Chun Ling Zhang ◽  
Hai Qing Liu
Keyword(s):  
Wavelet Analysis ◽  
Structural Damage ◽  
Damage Identification ◽  
Information Analysis ◽  
Structural Dynamic ◽  
Scale Theory ◽  
Structure Damage ◽  
Multi Scale ◽  
Structural Damage Identification ◽  
Domain Information

This papers deals with wavelet analysis which is as a tool for the complexity of structural damage combing the multi-scale theory and pattern recognition idea. The main subject is as follows multi-scale damage information analysis and numerical simulation and model experiments which is based on wavelet analysis for structural damage identification study. Applying wavelet transform, differential eqution of structural dynamic system are decomposed and dynamic parameters are described on different scales, the dentification of structure damage location is also spatial domain information which determines in the structural damage.

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