Relevant bibliographies by topics / Damage identification and location

Academic literature on the topic 'Damage identification and location'

Author: Grafiati
Published: 10 December 2022
Last updated: 28 January 2023

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Journal articles on the topic "Damage identification and location"

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Fei, Qing Guo, Ai Qun Li, Chang Qing Miao, and Zhi Jun Li. "Structural Damage Identification Using Wavelet Packet Analysis and Neural Network." Key Engineering Materials 324-325 (November 2006): 205–8. http://dx.doi.org/10.4028/www.scientific.net/kem.324-325.205.

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This paper describes a study on damage identification using wavelet packet analysis and neural networks. The identification procedure could be divided into three steps. First, structure responses are decomposed into wavelet packet components. Then, the component energies are used to define damage feature and to train neural network models. Finally, in combination with the feature of the damaged structure response, the trained models are employed to determine the occurrence, the location and the qualification of the damage. The emphasis of this study is put on multi-damage case. Relevant issues are studied in detail especially the selection of training samples for multi-damage identification oriented neural network training. A frame model is utilized in the simulation cases to study the sampling techniques and the multi-damage identification. Uniform design is determined to be the most suitable sampling technique through simulation results. Identifications of multi-damage cases of the frame including different levels of damage at various locations are investigated. The results show that damages are successfully identified in all cases.
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Guan, De Qing, Xiao Lin Zhong, and Hong Wei Ying. "Damage Identification of Arch Bridge Based on Curvature Mode Wavelet Analysis." Applied Mechanics and Materials 166-169 (May 2012): 1176–79. http://dx.doi.org/10.4028/www.scientific.net/amm.166-169.1176.

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Based on the curvature modal damage identification of wavelet analysis principle, the finite element method was applied to analyze the vibration characteristics of the damaged deck arch bridge. Take Haar wavelet as the mother wavelet, through the continuous wavelet transform of curvature mode and then identified the damaged position by the maximum of wavelet coefficients. analyze the damage identification problem under three different damaged conditions (condition 1: only the arch 1 contained one damaged location; condition 2: the arch 1 and the arch 2 contained one damaged location respectively; condition 3: the arch 1 contained two damaged locations and the arch 2 contained one damaged location).This paper provided a valuable reference of damage identification and diagnosis for arch bridge.
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Luo, Xiao Bin, and Yang Zhang. "Jacket Damage Identification Based on ANSYS Design Optimization." Key Engineering Materials 561 (July 2013): 521–26. http://dx.doi.org/10.4028/www.scientific.net/kem.561.521.

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Jacket is the fundamental structure of offshore platform, supporting the deck. It is a space frame truss consisting of hollow legs (pipes) and horizontal and vertical rods used to connect legs. Traditionally, damages of jacket must be detected by diving into various depth which would costs a lot. In this article, ANSYS was used to simulate the identification of damage locations. Element Parametric finite-element models which demonstrated several common damages such as corrosion and bending by changing physical and geometric parameters were analysed. It was found that analysis of node vibration data far from the damage location could identify the damage location with ANSYS design optimization.
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Gorgin, Rahim, and Ziping Wang. "Structural Damage Identification Based on Principal Curvatures of Mode Shape." International Journal of Acoustics and Vibration 25, no. 4 (December 30, 2020): 566–76. http://dx.doi.org/10.20855/ijav.2020.25.41714.

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This paper presents a procedure for damage identification and characterization on plates, based on the principal curvatures of their first mode shape. Each mode shape represents the displacement of the structure at its corresponding natural frequency. Since, variations in the geometry due to cracks or material property degradation, make changes in the mode shapes of the structure, such changes can be used for damage identification methods. The presented procedure only requires the first mode shape of the intact and damaged structure. It is shown that the principal curvatures of the surface defined by the first mode shape of the structure, are sensitive to damage and the maximum principal curvature can be used to highlight damages on the structure. The performance of the developed method is firstly evaluated using finite element analysis. To this aim, the procedure is applied to highlight both single and multi-damages in different locations of the plate with different boundary conditions. It is shown that the location of the maximum curvature variation coincides well with the location of damages and the amount of the maximum curvature change can be used as a parameter to describe damage severity. The accuracy of the proposed method is also experimentally verified by test on an aluminum plate and it is demonstrated that the proposed method remains effective even in experimental condition when only a limited number of measurements are available.
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Liu, Wei Ran, Shou Jun Du, and Li Mei Zhang. "Damage Identification of Plane Truss Structure According to Square Difference in Elemental Modal Strain." Applied Mechanics and Materials 724 (January 2015): 22–27. http://dx.doi.org/10.4028/www.scientific.net/amm.724.22.

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A method based on the square difference of elemental modal strain was proposed to determine the damage location and damage degree. The square difference of elemental modal strain was expressed damage before and after. Simulation results show that: this method is effective to locate the single, multiple damages and light, severe damage with low-order modal information. Damage degrees can be initially determined by the values of the square difference of damaged-element modal strain. Furthermore, the result also shows that this method can accurately identify the damage location of plane truss structures with noise.
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Peng, Xi, Cunkang Tian, and Qiuwei Yang. "Structural Damage Identification Using the Optimal Achievable Displacement Variation." Materials 15, no. 23 (November 26, 2022): 8440. http://dx.doi.org/10.3390/ma15238440.

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To ensure the safe use of structures, it is essential to develop efficient damage identification techniques. In this paper, a brand-new approach to identifying structural deterioration based on static displacement is proposed. First, the relationship between the displacement variation and the damaged element is derived from the static response equations before and after damage. Subsequently, the optimal achievable displacement variation is defined to determine the damage location in the structure. A progressive elimination strategy is suggested to identify the real damaged parts and weed out the pseudo-damaged elements by measuring the distance between the measured and the best possible displacement variation. After determining the damage location, the corresponding damage extent can be calculated by a system of linear equations. The proposed approach has been tested on a beam structure and truss structure using simulated and experimental data. Compared with the existing static sensitivity method, the suggested method does not result in misjudgment and has higher identification accuracy. It has been demonstrated that the suggested approach is effective at locating and assessing the extent of structural damage.
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Hou, Yanfang, Weibing Hu, Xin Wang, Tingting Hou, and Congli Sun. "Damage Identification of Ancient Timber Structure Based on Autocorrelation Function." Advances in Civil Engineering 2021 (July 5, 2021): 1–12. http://dx.doi.org/10.1155/2021/6683666.

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A damage location method for the autocorrelation peak value change rate based on the vibration response of a random vibration structure is established. To calculate the autocorrelation function of the vibration response of each measurement point, we transformed the maximum values into an autocorrelation peak vector. Under a good condition, the autocorrelation peak vector has a fixed shape; hence, it can be used as a basis for structural damage identification. The two adjacent measurement points with the largest change corresponding to the two nodes of the damage unit and the damage location are determined to calculate the change rate of the autocorrelation peak values between damaged and intact structures. When the degree of damage is 5%, the autocorrelation peak value change rate of the acceleration response on the two nodes of the damage unit is significantly greater than that of the other points, which can accurately determine the damage location, indicating that the damage location index constructed has good damage sensitivity. The damage location index can determine a single damage, as well as a double damage. The antinoise capability of the damage location index gradually improves with an increase in the degree of damage. At 45% degree of damage and signal-to-noise ratio (SNR) of 0 dB, the damage location index can still accurately determine the damage location, which has good antinoise interference capability. The Xi’an Bell Tower is used as a case study, and the feasibility of this method is verified, which provides a new method for the study of damage location of ancient timber structures.
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Li, Zhenhu, and Francis Tat Kwong Au. "Damage Detection of Bridges Using Response of Vehicle Considering Road Surface Roughness." International Journal of Structural Stability and Dynamics 15, no. 03 (March 8, 2015): 1450057. http://dx.doi.org/10.1142/s0219455414500576.

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This paper presents a genetic algorithm (GA)-based method to identify the damage of girder bridges from the response of a vehicle moving over the bridge. The continuous wavelet transform-based method works when the surface is smooth but the identification becomes difficult when the road surface is rough. To deal with this problem, the identification process is formulated as an optimization problem and a guided GA is used to search for the global optimal value. The vertical accelerations of the vehicle running over the bridge at the intact and damaged states are used to identify the occurrence and location of the damage. Frequencies of the bridge at the intact and damaged states can be extracted from these responses, from which the frequency-based method can roughly estimate the possible locations of the damage. These locations are not unique as frequencies alone are insufficient to identify the damage location. However these initial results can be used to narrow down the search region on which the GA can focus. Numerical study shows that the strategy can identify the damage location for simply supported and continuous girder bridges even though road surface roughness and measurement noise are taken into account.
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Zhang, Jian Wei, Yi Na Zhang, and Sheng Zhao Cheng. "Damage Diagnosis of Radial Gate Based on Modal Strain Energy." Applied Mechanics and Materials 71-78 (July 2011): 4240–43. http://dx.doi.org/10.4028/www.scientific.net/amm.71-78.4240.

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Non-destructive testing and safety monitoring of structure has been a hot and difficult engineering research problems, and an effective extraction of damage characteristic factor is a critical and theoretical research on structural damage detection and monitoring technology. The basic theory of modal strain energy and the steps to damage diagnosis are discussed in the paper.A a radial gate with different damaged locations and damaged degree is studied,and the results show that modal strain energy can be used as structural damage location sensitive factor,and that the indicator can be a very good identification of the location and extent of structural damage,and that the results of damage diagnosis are clear and reliable.
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Sun, Yi, Kun Ma, Dongfa Sheng, Dewen Liu, and Bihui Dai. "Research on Bridge Structural Damage Identification." Scientific Programming 2022 (March 16, 2022): 1–14. http://dx.doi.org/10.1155/2022/5095966.

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The traditional identification methods have limited ability to identify damage location of bridge structures. Therefore, a bridge structural damage location identification method based on deep learning is proposed. In addition, the sigmoid function is the activation function, and the cross entropy is the cost function. Meanwhile, take the Gaussian noise as the addition method and take the softmax as the classifier. So the constructed SDAE deep learning model can realize damage location identification of the simply supported the continuous beam bridges. Compared with the traditional identification methods of bridge structures, namely BP network and SVM, the proposed method shows higher identification accuracy and antinoise performance. Here, the average identification accuracy of the method for continuous beam bridge is 99.8%. As can be seen that the proposed method is more suitable for practical bridge structure damage location identification.
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Dissertations / Theses on the topic "Damage identification and location"

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Bandara, Arachchillage Rupika Priyadarshani. "Damage identification and condition assessment of building structures using frequency response functions and neural networks." Thesis, Queensland University of Technology, 2013. https://eprints.qut.edu.au/61196/4/Rupika_Bandara_Thesis.pdf.

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This thesis investigated the viability of using Frequency Response Functions in combination with Artificial Neural Network technique in damage assessment of building structures. The proposed approach can help overcome some of limitations associated with previously developed vibration based methods and assist in delivering more accurate and robust damage identification results. Excellent results are obtained for damage identification of the case studies proving that the proposed approach has been developed successfully.
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Kelly, Brendan T. "A Newly Proposed Method for Detection, Location, and Identification of Damage in Prestressed Adjacent Box Beam Bridges." Ohio University / OhioLINK, 2012. http://rave.ohiolink.edu/etdc/view?acc_num=ohiou1339520527.

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Tappert, Peter M. "Damage identification using inductive learning." Thesis, This resource online, 1994. http://scholar.lib.vt.edu/theses/available/etd-05092009-040651/.

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Al-Tamimi, Adnan N. J. "Damage location in structures by monitoring vibration characteristics." Thesis, Aston University, 1985. http://publications.aston.ac.uk/11848/.

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The aim of this work was to investigate the feasibility of detecting and locating damage in large frame structures where visual inspection would be difficult or impossible. This method is based on a vibration technique for non-destructively assessing the integrity of structures by using measurements of changes in the natural frequencies. Such measurements can be made at a single point in the structure. The method requires that initially a comprehensive theoretical vibration analysis of the structure is undertaken and from it predictions are made of changes in dynamic characteristics that will occur if each member of the structure is damaged in turn. The natural frequencies of the undamaged structure are measured, and then routinely remeasured at intervals . If a change in the natural frequencies is detected a statistical method. is used to make the best match between the measured changes in frequency and the family of theoretical predictions. This predicts the most likely damage site. The theoretical analysis was based on the finite element method. Many structures were extensively studied and a computer model was used to simulate the effect of the extent and location of the damage on natural frequencies. Only one such analysis is required for each structure to be investigated. The experimental study was conducted on small structures In the laboratory. Frequency changes were found from inertance measurements on various plane and space frames. The computational requirements of the location analysis are small and a desk-top micro computer was used. Results of this work showed that the method was successful in detecting and locating damage in the test structures.
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Yamamoto, Kyosuke. "Bridge Damage Identification Using Vehicle Response." 京都大学 (Kyoto University), 2012. http://hdl.handle.net/2433/159406.

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Liu, Xuefeng. "Vibration-based structural damage identification techniques." Thesis, University of Bristol, 2007. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.445826.

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Xing, Shutao. "Structural Identification and Damage Identification using Output-Only Vibration Measurements." DigitalCommons@USU, 2011. https://digitalcommons.usu.edu/etd/1067.

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This dissertation studied the structural identification and damage detection of civil engineering structures. Several issues regarding structural health monitoring were addressed. The data-driven subspace identification algorithm was investigated for modal identification of bridges using output-only data. This algorithm was tested through a numerical truss bridge with abrupt damage as well as a real concrete highway bridge with actual measurements. Stabilization diagrams were used to analyze the identified results and determine the modal characteristics. The identification results showed that this identification method is quite effective and accurate. The influence of temperature fluctuation on the frequencies of a highway concrete bridge was investigated using ambient vibration data over a one-year period of a highway bridge under health monitoring. The data were fitted by nonlinear and linear regression models, which were then analyzed. The substructure identification by using an adaptive Kalman filter was investigated by applying numerical studies of a shear building, a frame structure, and a truss structure. The stiffness and damping were identified successfully from limited acceleration responses, while the abrupt damages were identified as well. Wavelet analysis was also proposed for damage detection of substructures, and was shown to be able to approximately locate such damages. Delamination detection of concrete slabs by modal identification from the output-only data was proposed and carried out through numerical studies and experimental modal testing. It was concluded that the changes in modal characteristics can indicate the presence and severity of delamination. Finite element models of concrete decks with different delamination sizes and locations were established and proven to be reasonable. Pounding identification can provide useful early warning information regarding the potential damage of structures. This thesis proposed to use wavelet scalograms of dynamic response to identify the occurrence of pounding. Its applications in a numerical example as well as shaking table tests of a bridge showed that the scalograms can detect the occurrence of pounding very well. These studies are very useful for vibration-based structural health monitoring.
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Moaveni, Babak. "System and damage identification of civil structures." Connect to a 24 p. preview or request complete full text in PDF format. Access restricted to UC campuses, 2007. http://wwwlib.umi.com/cr/ucsd/fullcit?p3284170.

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Thesis (Ph. D.)--University of California, San Diego, 2007.
Title from first page of PDF file (viewed January 14, 2008). Available via ProQuest Digital Dissertations. Vita. Includes bibliographical references.
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Wang, Dexin. "Structural damage identification in the frequency domain." Diss., The University of Arizona, 1999. http://hdl.handle.net/10150/284350.

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This study presents novel approaches for direct damage identification of structures in the frequency domain. Relations between structural stiffness variations and measured system responses are formulated, thus opening the possibility of locating structural damage in terms of the reduction in the local stiffness when analytical baseline models are not available. After this, the related identifiability is discussed under the noise-free condition. In identifying damage in structural points, generic joint elements with only translational degrees of freedom are defined to parameterize the stiffness variations in the joints. Since ill-conditioning is a common problem in system identification and damage detection, a solution regularization based on parameter subset selection is proposed and used with least squares methods. A substructure-based parameter-recursive algorithm is developed for selecting parameter subsets to make use of the fact that the damage is local in structures. The proposed methods are verified by various simulated examples in which systematic modeling errors are present. Finally, the methods are also applied to the degradation identification of a vehicle structure.
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El-Gamal, Mohamed A. "Fault location and parameter identification in analog circuits." Ohio : Ohio University, 1990. http://www.ohiolink.edu/etd/view.cgi?ohiou1172776742.

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Books on the topic "Damage identification and location"

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Koh, Chan Ghee. Structural identification and damage detection using genetic algorithms. Boca Raton: CRC Press, 2010.

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Koh, Chan Ghee. Structural identification and damage detection using genetic algorithms. Boca Raton: CRC Press, 2010.

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Perry, M. J. (Michael J.), 1981-, ed. Structural identification and damage detection using genetic algorithms. Boca Raton: CRC Press, 2010.

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Koh, Chan Ghee. Structural identification and damage detection using genetic algorithms. Boca Raton: CRC Press, 2010.

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Su, Zhongqing, and Lin Ye. Identification of Damage Using Lamb Waves. London: Springer London, 2009. http://dx.doi.org/10.1007/978-1-84882-784-4.

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Al-Tamimi, Adnan Naji Jamel. Damage location in structures by monitoring vibration characteristics. Birmingham: University of Aston. Department of Mechanical and Production Engineering, 1985.

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Staszewski, Wiesław Jerzy. Wavelets for mechanical and structural damage identification. Gdańsk: Wydawn. Instytutu Maszyn Przepływowych, 2000.

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Jackson, Christine. Aberdare Park tree identification and location survey. (Aberdare): (Cynon Valley Borough Council), 1985.

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Jegley, Dawn C. Effect of low-speed impact damage and damage location on behavior of composite panels. Hampton, Va: Langley Research Center, 1992.

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Florida's fossils: Guide to location, identification, and enjoyment. 2nd ed. Sarasota, Fla: Pineapple Press, 1996.

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Book chapters on the topic "Damage identification and location"

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Lu, Wen Xiu, Fu Lei Chu, and Dan Guo. "Genetic Algorithms Based Rubbing Location Identification in a Rotor System." In Damage Assessment of Structures VI, 417–24. Stafa: Trans Tech Publications Ltd., 2005. http://dx.doi.org/10.4028/0-87849-976-8.417.

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Zhou, Zhengang, Dejun Liu, and Xiujie Lv. "Vibration-Based Damage Joint Identification Method for Superstructure and Substructure of Piles-Supported Frame Structure." In Lecture Notes in Civil Engineering, 209–25. Singapore: Springer Singapore, 2022. http://dx.doi.org/10.1007/978-981-19-1260-3_19.

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AbstractIn order to jointly identify the damage locations of superstructure and substructure of the piles-supported frame structures, a damage identification method based on vibration is proposed. Firstly, the high-efficiency modes which are sensitive to the damage of the piles-supported frame structures are determined. Then, the element modal strain energy difference functions of the corresponding high-efficiency modes are calculated before and after the damage, and finally the damage locations are identified by the average values of the absolute values of the wavelet transform coefficients of the element modal strain energy difference functions of high-efficiency modes. The effectiveness of the method is studied by numerical simulation. Numerical results show that the method can identify the damage location of the single damage or multiple damage of the piles-supported frame structures. Although the adjacent effect exists, the damage areas can be effectively located. At the same time, the method can effectively identify the damage locations of the hidden pile foundation.
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Limongelli, Maria Pina, Emil Manoach, Said Quqa, Pier Francesco Giordano, Basuraj Bhowmik, Vikram Pakrashi, and Alfredo Cigada. "Vibration Response-Based Damage Detection." In Structural Health Monitoring Damage Detection Systems for Aerospace, 133–73. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-72192-3_6.

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AbstractThis chapter aimed to present different data driven Vibration-Based Methods (VBMs) for Structural Health Monitoring (SHM). This family of methods, widely used for engineering applications, present several advantages for damage identification applications. First, VBMs provide continuous information on the health state of the structure at a global level without the need to access the damaged elements and to know their location. Furthermore, damage can be identified using the dynamic response of the structure measured by sensors non-necessarily located in the proximity of damage and without any prior knowledge about the damage location. By principle, VBMs can identify damage related to changes in the dynamic properties of structures, such as stiffness variations due to modifications in the connections between structural elements, or changes in geometric and material properties. A classification of different VBMs was presented in this chapter. Furthermore, several case studies were presented to demonstrate the potential of these methods.
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Natke, H. G., and J. T. P. Yao. "Detection and Location of Damage Causing Non-linear System Behavior." In Safety Evaluation Based on Identification Approaches Related to Time-Variant and Nonlinear Structures, 188–203. Wiesbaden: Vieweg+Teubner Verlag, 1993. http://dx.doi.org/10.1007/978-3-322-89467-0_11.

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Wang, Maoqiang. "Identification of damage locations in long-span continuous rigid frame bridges by using support vector machines." In Advances in Civil Function Structure and Industrial Architecture, 637–44. London: CRC Press, 2022. http://dx.doi.org/10.1201/9781003305019-88.

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Shekhar, Shashi, and Hui Xiong. "WLAN Location Identification." In Encyclopedia of GIS, 1274. Boston, MA: Springer US, 2008. http://dx.doi.org/10.1007/978-0-387-35973-1_1501.

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Vestroni, Fabrizio, and Annamaria Pau. "Dynamic Characterization and Damage Identification." In Dynamical Inverse Problems: Theory and Application, 151–78. Vienna: Springer Vienna, 2011. http://dx.doi.org/10.1007/978-3-7091-0696-9_5.

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Patan, Maciej. "Sensor Location under Parametric and Location Uncertainty." In Optimal Sensor Networks Scheduling in Identification of Distributed Parameter Systems, 183–206. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-28230-0_7.

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Xu, Wenjie, Zhonghai Wang, and Seyed A. Reza Zekavat. "An Introduction to NLOS Identification and Localization." In Handbook of Position Location, 523–55. Hoboken, NJ, USA: John Wiley & Sons, Inc., 2011. http://dx.doi.org/10.1002/9781118104750.ch16.

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Ravikumar, Pranav, Jobin John, Megha Daga, and Abdul Razak. "Novel Algorithm for Mobile Location Identification." In Lecture Notes in Electrical Engineering, 903–8. New Delhi: Springer India, 2013. http://dx.doi.org/10.1007/978-81-322-1157-0_90.

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Conference papers on the topic "Damage identification and location"

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Scaletta, Brent, and Richard Green. "Critical Location Identification for Multi-Mechanistic Damage Modes Using Damage Interaction Charts." In ASME Turbo Expo 2020: Turbomachinery Technical Conference and Exposition. American Society of Mechanical Engineers, 2020. http://dx.doi.org/10.1115/gt2020-14678.

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Abstract Damage in gas turbine engines can accumulate from multiple damage mechanisms including creep, fatigue, and oxidation. Each damage mechanism is influenced by various parameters which typically occur during different portions of engine operation. For instance, fatigue is influenced by large stress/strain ranges that occur during startup and shutdown transient conditions while creep is affected by sustained stress and temperature at dwell conditions. In some cases, the maximum damage location for one mechanism could experience negligible contribution in damage from any other mechanism, but in most cases, there is some degree of influence from two or three mechanisms. In those instances, damage will accumulate at various rates during separate portions of operation under different damage mechanisms. Since some applications require engines to dwell for long periods of time while other applications favor more frequent cycling, every engine will accumulate damage differently at each location. Therefore, it is difficult to estimate which location is critical to durability, rendering it necessary to capture all possible critical locations so that damage can be estimated for each application. This paper suggests a method by which to visualize and select critical locations based on all possible customer use scenarios. Once critical locations are identified, a Reduced Order Model (ROM) can be generated for each point of interest and damage can be estimated and monitored using data collection. Damage mechanisms can be combined if micromechanistic affects are additive, the material response compounds, or the material properties evolve with time. Examples of each case are demonstrated. In addition, the visual representation of damage interaction allows for uncertainty to be visualized and implemented to rank location criticality.
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Wang, Qiu Ping, Xun Guo, and Hong Xing Wang. "Application of Damage Location Vector Method in Structural Damage Identification." In GeoHunan International Conference 2011. Reston, VA: American Society of Civil Engineers, 2011. http://dx.doi.org/10.1061/47634(413)18.

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Naidu, A. S. K., S. Bhalla, C. W. Ong, and C. K. Soh. "DAMAGE LOCATION IDENTIFICATION IN SMART BEAMS USING MODAL PARAMETERS." In Proceedings of the Second International Conference. WORLD SCIENTIFIC, 2002. http://dx.doi.org/10.1142/9789812776228_0109.

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Napolitano, Luca, Paolo Fedele, Massimo Viscardi, and Leonardo Lecce. "Damage identification and location on a typical aeronautical structure." In Non-Destructive Evaluation Techniques for Aging Infrastructure & Manufacturing, edited by Glenn A. Geithman and Gary E. Georgeson. SPIE, 1998. http://dx.doi.org/10.1117/12.305040.

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Shukui, Liu, Wu Ziyan, and Wang Qi'Ang. "Physical Parameters and Damage Location Identification using the Gibbs Sampling." In 5th Asian-Pacific Symposium on Structural Reliability and its Applications. Singapore: Research Publishing Services, 2012. http://dx.doi.org/10.3850/978-981-07-2219-7_p216.

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Kayed, Mohammed O., Mustafa H. Arafa, and Said M. Megahed. "Vibration-Based Damage Detection in Plates Using Damage Location Vectors." In ASME 2011 International Mechanical Engineering Congress and Exposition. ASMEDC, 2011. http://dx.doi.org/10.1115/imece2011-65117.

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Vibration-based techniques are increasingly being recognized as effective non-destructive structural damage identification tools. One promising technique relies on combining a finite element model (FEM) of the structure under investigation with a set of experimental frequency response functions (FRFs) to construct a so-called Damage Location Vector (DLV). This paper aims to assess damage detection using DLVs both theoretically and experimentally. To this end, the method is first studied theoretically on a thin plate using simulated damage. The method is then tested experimentally on a free-free plate provided with several damage cases using impact hammer testing. The main contribution of the present work lies in attempting to improve the DLV techniques through the use of the experimental FRF data of the intact structure in addition to the theoretical FRF from a finite element. The results obtained indicate that the improved algorithm can be used to successfully detect structural damage.
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Lindner, Douglas, and George Kirby. "Location and estimation of damage in a beam using identification algorithms." In Adaptive Structures Forum. Reston, Virigina: American Institute of Aeronautics and Astronautics, 1994. http://dx.doi.org/10.2514/6.1994-1755.

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Cunningham, Paul R., Janice M. Dulieu-Barton, and R. A. Shenoi. "Damage location and identification using infrared thermography and thermoelastic stress analysis." In NDE For Health Monitoring and Diagnostics, edited by Andrew L. Gyekenyesi, Steven M. Shepard, Dryver R. Huston, A. Emin Aktan, and Peter J. Shull. SPIE, 2002. http://dx.doi.org/10.1117/12.470714.

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Arafa, Mustafa H., and Ashraf O. Nassef. "Damage Identification Through Spectral Element Model Updating." In ASME 2009 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. ASMEDC, 2009. http://dx.doi.org/10.1115/detc2009-86418.

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The use of vibration-based damage identification techniques has received considerable attention in recent years. These techniques rely on changes in some structural dynamic characteristics in order to establish a damage indicator. While various damage indicators have been reported in the literature, those relying only on changes in the natural frequencies are appealing in many aspects. Nevertheless, the use of natural frequencies in damage identification has been faced with several difficulties, such as insensitivity and uniqueness concerns. In an attempt to overcome these obstacles, this paper addresses the development of a damage identification scheme based on changes in the natural frequencies of beam structures through a numerical model formulated by the Spectral Element Method (SEM) in conjunction with an optimization algorithm in a model updating approach to predict the location and extent of damage. The use of the SEM significantly reduces the number of design variables, which makes the search algorithm in the inverse problem faster and more efficient. Damage is modeled as a localized reduction in the beam thickness. Three spectral elements are employed to model an elastic beam with a defect and three variables are realized to model the location, size and severity of damage. A stochastic genetic algorithm was developed to facilitate the search for damage based on a set of measured natural frequencies. The use of the proposed formulation is supported experimentally on a set of free-free beams provided with various damage scenarios, and is shown to be a viable tool in damage identification.
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Shen, Ting, Fangyi Wan, Bifeng Song, and Yun Wu. "Damage location and identification of the wing structure with Probabilistic Neural Networks." In 2011 Prognostics and System Health Management Conference (PHM-2011 Shenzhen). IEEE, 2011. http://dx.doi.org/10.1109/phm.2011.5939524.

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Reports on the topic "Damage identification and location"

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Farrar, C. R., S. W. Doebling, M. B. Prime, P. Cornwell, M. Kam, E. G. Straser, and B. C. Hoerst. Neural network based system for damage identification and location in structural and mechanical systems. Office of Scientific and Technical Information (OSTI), November 1998. http://dx.doi.org/10.2172/674673.

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Farrar, C. R., S. W. Doebling, and M. B. Prime. A comprehensive monitoring system for damage identification and location in large structural and mechanical systems. Office of Scientific and Technical Information (OSTI), November 1998. http://dx.doi.org/10.2172/677155.

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Rahmani, Mehran, Xintong Ji, and Sovann Reach Kiet. Damage Detection and Damage Localization in Bridges with Low-Density Instrumentations Using the Wave-Method: Application to a Shake-Table Tested Bridge. Mineta Transportation Institute, September 2022. http://dx.doi.org/10.31979/mti.2022.2033.

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This study presents a major development to the wave method, a methodology used for structural identification and monitoring. The research team tested the method for use in structural damage detection and damage localization in bridges, the latter being a challenging task. The main goal was to assess capability of the improved method by applying it to a shake-table-tested prototype bridge with sparse instrumentation. The bridge was a 4-span reinforced concrete structure comprising two columns at each bent (6 columns total) and a flat slab. It was tested to failure using seven biaxial excitations at its base. Availability of a robust and verified method, which can work with sparse recording stations, can be valuable for detecting damage in bridges soon after an earthquake. The proposed method in this study includes estimating the shear (cS) and the longitudinal (cL) wave velocities by fitting an equivalent uniform Timoshenko beam model in impulse response functions of the recorded acceleration response. The identification algorithm is enhanced by adding the model’s damping ratio to the unknown parameters, as well as performing the identification for a range of initial values to avoid early convergence to a local minimum. Finally, the research team detect damage in the bridge columns by monitoring trends in the identified shear wave velocities from one damaging event to another. A comprehensive comparison between the reductions in shear wave velocities and the actual observed damages in the bridge columns is presented. The results revealed that the reduction of cS is generally consistent with the observed distribution and severity of damage during each biaxial motion. At bents 1 and 3, cS is consistently reduced with the progression of damage. The trends correctly detected the onset of damage at bent 1 during biaxial 3, and damage in bent 3 during biaxial 4. The most significant reduction was caused by the last two biaxial motions in bents 1 and 3, also consistent with the surveyed damage. In bent 2 (middle bent), the reduction trend in cS was relatively minor, correctly showing minor damage at this bent. Based on these findings, the team concluded that the enhanced wave method presented in this study was capable of detecting damage in the bridge and identifying the location of the most severe damage. The proposed methodology is a fast and inexpensive tool for real-time or near real-time damage detection and localization in similar bridges, especially those with sparsely deployed accelerometers.
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Farrar, Charles R., Keith Worden, Michael D. Todd, Gyuhae Park, Jonathon Nichols, Douglas E. Adams, Matthew T. Bement, and Kevin Farinholt. Nonlinear System Identification for Damage Detection. Office of Scientific and Technical Information (OSTI), November 2007. http://dx.doi.org/10.2172/922532.

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Moore, Christina J. Development of an Integrated Robotic Radioisotope Identification and Location System. Fort Belvoir, VA: Defense Technical Information Center, May 2009. http://dx.doi.org/10.21236/ada548792.

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Balanis, Constantine A., and Mark Frank. Modeling and Reconstruction Algorithms for Detection, Location, and Identification of Subsurface Anomalies. Fort Belvoir, VA: Defense Technical Information Center, June 1990. http://dx.doi.org/10.21236/ada224358.

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Burnham, A., M. Runkel, L. Chase, S. Demos, M. Staggs, and W. Siekhaus. Identification and Elimination of Mechanisms Leading to UV Damage of DKDP. Office of Scientific and Technical Information (OSTI), March 2001. http://dx.doi.org/10.2172/15006507.

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A.L. Cundy. Use of Response Surface Metamodels in Damage Identification of Dynamic Structures. Office of Scientific and Technical Information (OSTI), May 2003. http://dx.doi.org/10.2172/812182.

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Zollweg, James E. Detection, Location, and Identification of Regional Seismic Events Using a Small Broadband Array. Fort Belvoir, VA: Defense Technical Information Center, March 2002. http://dx.doi.org/10.21236/ada400518.

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Hartke, Paul M., Steven C. Gustafson, Theresa A. Tuthill, and Shing P. Chu. Neural Network Technology for the Rapid Identification of Corrosion Damage in Aging Aircraft. Fort Belvoir, VA: Defense Technical Information Center, May 1997. http://dx.doi.org/10.21236/ada328369.

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