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Hou J.♦, Li Z.♦, Jankowski Ł., Wang S.♦, Estimation of virtual masses for structural damage identification,
STRUCTURAL CONTROL AND HEALTH MONITORING, ISSN: 1545-2255, DOI: 10.1002/stc.2585, Vol.27, No.8, pp.e2528-1-21, 2020Abstract: Adding a virtual mass is an effective method for damage identification. It can be used to obtain a large amount of information about structural response and dynamics, thereby improving the sensitivity to local damage. In the current research approaches, the virtual mass is determined first, and then the modal characteristics of the virtually modified structure are identified. This requires a wide frequency band excitation; otherwise the crucial modes of the modified structure might be out of the band, which would negatively influence the modal analysis and damage identification. This paper proposes a method that first determines the target frequency and then estimates the corresponding value of the additional virtual mass. The target frequency refers to the desired value of the natural frequency after the virtual mass has been added to the structure. The virtual masses are estimated by tuning the frequency response peaks to the target frequencies. First, two virtual mass estimation methods are proposed. One is to directly calculate the virtual mass, using the frequency‐domain response at the target frequency point only, whereas the second method estimates the mass using a least‐squares fit based on the frequency‐domain response around the target frequency. Both proposed methods utilize merely a small part of the frequency domain. Therefore, an impulse, a simple harmonic, or a narrow spectral excitation can be used for damage identification. Finally, a numerical simulation of a simply supported beam and experiments of a frame structure and a truss structure are used to verify the effectiveness of the proposed method. Keywords: damage identification, frequency response, structural health monitoring (SHM), virtual distortion method (VDM), virtual mass Affiliations:
Hou J. | - | Dalian University of Technology (CN) | Li Z. | - | Dalian University of Technology (CN) | Jankowski Ł. | - | IPPT PAN | Wang S. | - | Dalian University of Technology (CN) |
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Hou J.♦, Wang S.♦, Zhang Q.♦, Jankowski Ł., An improved objective function for modal-based damage identification using substructural virtual distortion method,
Applied Sciences, ISSN: 2076-3417, DOI: 10.3390/app9050971, Vol.9, No.5, pp.971-1-17, 2019Abstract: Damage identification based on modal parameters is an important approach in structural health monitoring (SHM). Generally, traditional objective functions used for damage identification minimize the mismatch between measured modal parameters and the parameters obtained from the finite element (FE) model. However, during the optimization process, the repetitive calculation of structural modes is usually time-consuming and inefficient, especially for large-scale structures. In this paper, an improved objective function is proposed based on certain characteristics of the peaks of the frequency response function (FRF). Traditional objective functions contain terms that quantify modal shapes and/or natural frequencies. Here, it is proposed to replace them by the FRF of the FE model, which allows the repeated full modal analysis to be avoided and thus increases the computational efficiency. Moreover, the efficiency is further enhanced by employing the substructural virtual distortion method (SVDM), which allows the frequency response of the FE model of the damaged structure to be quickly computed without the costly re-analysis of the entire damaged structure. Finally, the effectiveness of the proposed method is verified using an eight-story frame structure model under several damage cases. The damage location and extent of each substructure can be identified accurately with 5% white Gaussian noise, and the optimization efficiency is greatly improved compared with the method using a traditional objective function. Keywords: structural health monitoring (SHM), damage identification, substructure, virtual distortion method (VDM), frequency response Affiliations:
Hou J. | - | Dalian University of Technology (CN) | Wang S. | - | Dalian University of Technology (CN) | Zhang Q. | - | other affiliation | Jankowski Ł. | - | IPPT PAN |
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Hou J.♦, An Y.♦, Wang S.♦, Wang Z.♦, Jankowski Ł., Ou J.♦, Structural Damage Localization and Quantification Based on Additional Virtual Masses and Bayesian Theory,
JOURNAL OF ENGINEERING MECHANICS-ASCE, ISSN: 0733-9399, DOI: 10.1061/(ASCE)EM.1943-7889.0001523, Vol.144, No.10, pp.04018097-1-9, 2018Abstract: In vibration-based damage identification, a common problem is that modal information is not enough and insensitive to local damage. To solve this problem, an effective method is to increase the amount of modal information and enhance the sensitivity of the experimental data to the local damage. In this paper, a damage identification method based on additional virtual masses and Bayesian theory is proposed. First, the virtual structure with optimal additional mass and high sensitivity to local damage is determined through sensitivity analysis, and then a large number of virtual structures can be obtained by adding virtual masses; thus, a lot of modal and statistical information of virtual structures can be obtained. Second, the Bayesian theory is used to obtain the posterior probability distribution of the damage factor when structural a priori information is considered. Third, by finding the extreme value of the probability density function, the damage factor is derived based on the a priori information and the statistical information of virtual structures. Finally, the effectiveness of the proposed method is verified by numerical simulations and experiments of a 3-story frame structure. Experimental and numerical results show that the proposed method can be used to identify the damage severity of each substructure and thus damaged substructures can be localized and quantified; the error in damage factor is basically within 5%, which shows the accuracy of the proposed method. The proposed method can not only provide the structural damage localization and quantification result (i.e., the damage factor), but also the probability distribution of the damage factor; moreover, it has high sensitivity to damage and high accuracy and efficiency. Keywords: Structural health monitoring, Damage identification, Bayesian theory, Virtual distortion method (VDM), Virtual mass Affiliations:
Hou J. | - | Dalian University of Technology (CN) | An Y. | - | Dalian University of Technology (CN) | Wang S. | - | Dalian University of Technology (CN) | Wang Z. | - | Chalco Shandong Engineering Technology Co., Ltd. (CN) | Jankowski Ł. | - | IPPT PAN | Ou J. | - | Dalian University of Technology (CN) |
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