Structural Damage Identification Method Based On Transmissibility in Time Domain

2021 ◽  
Author(s):  
Yunfeng Zou ◽  
Xuandong Lu ◽  
Jinsong Yang ◽  
Xuhui He ◽  
Tiantian Wang
Keyword(s):  
Time Domain ◽  
Structural Damage ◽  
High Efficiency ◽  
Damage Identification ◽  
Identification Accuracy ◽  
Reconstruction Method ◽  
Fe Model ◽  
Time Frequency ◽  
Identification Method ◽  
Structural Damage Identification

Abstract 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 novelty structural damage identification method based on the transmissibility in time domain is proposed. The method takes the discrepancy of transmissibility of structure response in time domain before and after damage as the basis of finite element model modification. The damage location and damage degree are obtained through iteration by minimizing the difference between the measurements at gauge locations and the reconstruction response extrapolated by FE model. Taking the advantage of the response reconstruction method based on empirical mode decomposition, the damage information is possible to obtain in the absence of prior knowledge on external excitation information. Moreover, this method is carried out in the time domain, without the need to identify the modal parameters and perform time-frequency analysis, which simplicity ensures the high efficiency of damage identification. The effectiveness and accuracy of the proposed method are studied by simulation, including reconstruction error and measurement noise. The identification results demonstrate that the proposed structural damage identification method improves the calculation effectiveness considerably and ensures the identification accuracy.

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.

Local Mass Addition and Data Fusion for Structural Damage Identification Using Approximate Models

2020 ◽  
Vol 20 (11) ◽  
pp. 2050124
Author(s):  
Jilin Hou ◽  
Zhenkun Li ◽  
Qingxia Zhang ◽  
Łukasz Jankowski ◽  
Haibin Zhang
Keyword(s):  
Data Fusion ◽  
Objective Function ◽  
Structural Damage ◽  
Damage Identification ◽  
Structural Parameters ◽  
Identification Accuracy ◽  
Fe Model ◽  
Local Damage ◽  
Approximate Models ◽  
Structural Damage Identification

In practical civil engineering, structural damage identification is difficult to implement due to the shortage of measured modal information and the influence of noise. Furthermore, typical damage identification methods generally rely on a precise Finite Element (FE) model of the monitored structure. Pointwise mass alterations of the structure can effectively improve the quantity and sensitivity of the measured data, while the data fusion methods can adequately utilize various kinds of data and identification results. This paper proposes a damage identification method that requires only approximate FE models and combines the advantages of pointwise mass additions and data fusion. First, an additional mass is placed at different positions throughout the structure to collect the dynamic response and obtain the corresponding modal information. The resulting relation between natural frequencies and the position of the added mass is sensitive to local damage, and it is thus utilized to form a new objective function based on the modal assurance criterion (MAC) and [Formula: see text]-based sparsity promotion. The proposed objective function is mostly insensitive to global structural parameters, but remains sensitive to local damage. Several approximate FE models are then established and separately used to identify the damage of the structure, and then the Dempster–Shafer method of data fusion is applied to fuse the results from all the approximate models. Finally, fractional data fusion is proposed to combine the results according to the parametric probability distribution of the approximate FE models, which allows the natural weight of each approximate model to be determined for the fusion process. Such an approach circumvents the need for a precise FE model, which is usually not easy to obtain in real application, and thus enhances the practical applicability of the proposed method, while maintaining the damage identification accuracy. The proposed approach is verified numerically and experimentally. Numerical simulations of a simply supported beam and a long-span bridge confirm that it can be used for damage identification, including a single damage and multiple damages, with a high accuracy. Finally, an experiment of a cantilever beam is successfully performed.

scholarly journals A Mahalanobis Distance Cumulant-Based Structural Damage Identification Method with IMFs and Fitting Residual of SHM Measurements

2020 ◽  
Vol 2020 ◽  
pp. 1-17
Author(s):  
Chuang Chen ◽  
Yinhui Wang ◽  
Tao Wang ◽  
Xiaoyan Yang
Keyword(s):  
Mahalanobis Distance ◽  
Structural Damage ◽  
Damage Identification ◽  
Feature Vector ◽  
Recursive Algorithm ◽  
Intrinsic Mode Functions ◽  
Data Set ◽  
Identification Method ◽  
Structural Damage Identification ◽  
Emd Method

Data-driven damage identification based on measurements of the structural health monitoring (SHM) system is a hot issue. In this study, based on the intrinsic mode functions (IMFs) decomposed by the empirical mode decomposition (EMD) method and the trend term fitting residual of measured data, a structural damage identification method based on Mahalanobis distance cumulant (MDC) was proposed. The damage feature vector is composed of the squared MDC values and is calculated by the segmentation data set. It makes the changes of monitoring points caused by damage accumulate as “amplification effect,” so as to obtain more damage information. The calculation method of the damage feature vector and the damage identification procedure were given. A mass-spring system with four mass points and four springs was used to simulate the damage cases. The results showed that the damage feature vector MDC can effectively identify the occurrence and location of the damage. The dynamic measurements of a prestress concrete continuous box-girder bridge were used for decomposing into IMFs and the trend term by the EMD method and the recursive algorithm autoregressive-moving average with the exogenous inputs (RARMX) method, which were used for fitting the trend term and to obtain the fitting residual. By using the first n-order IMFs and the fitting residual as the clusters for damage identification, the effectiveness of the method is also shown.

scholarly journals A Steel-Concrete Composite Beam Element for Structural Damage Identification

2020 ◽  
Vol 20 (10) ◽  
pp. 2042015
Author(s):  
Faraz Sadeghi ◽  
Jianchun Li ◽  
Xinqun Zhu
Keyword(s):  
Composite Beam ◽  
Composite Structures ◽  
Structural Damage ◽  
Damage Identification ◽  
Beam Element ◽  
Bonding Interface ◽  
Fe Model ◽  
Static Responses ◽  
Structural Damage Identification ◽  
Interface Layers

The composite action between the layers of steel and concrete is governed by the shear connection. Because of the complicated interconnection behavior of these composite layers, it is difficult to detect damage in the composite structures, especially, the interfacial integrity of the two layers. In this paper, anovel method has been developed for structural damage identification of composite structures based on a steel-concrete composite beam element with bonding interface. In displacement-based finite element (FE) formulation, three damage indicators have been embedded into stiffness matrix of the composite beam that are defined as a stiffness reduction in the concrete, steel and interface layers. An algorithm-based on recursive quadratic programming has been proposed to identify structural damage in the composite beam from static measurements. The analytical FE model is validated by adapting its static responses in undamaged state with those obtained from an equal experimental model as well as a FE model developed in commercial software ABAQUS. A convergence study is conducted to determine the number of the composite beam FEs. To verify the proposed method, the static responses of the FE model with different damage cases at a given loading are calculated, and the measurements are simulated by adding different levels of white noise. Then, the proposed algorithm is applied to identify damage of the composite beam. The effects of measurement noise, loading location and amplitude, measurement numbers and the sizes of FE mesh on the identified results have been investigated. The numerical results show that this method is efficient and accurate to separately identify small damage in the concrete slab, and the steel girder and bonding interface of the composite beam.

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