Relevant bibliographies by topics / Damage Detection

Academic literature on the topic 'Damage Detection'

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Published: 4 June 2021
Last updated: 23 February 2024

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Journal articles on the topic "Damage Detection"

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Vafaei, Mohammadreza, Azlan bin Adnan, and Mohammadreza Yadollahi. "Seismic Damage Detection Using Pushover Analysis." Advanced Materials Research 255-260 (May 2011): 2496–99. http://dx.doi.org/10.4028/www.scientific.net/amr.255-260.2496.

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Inter-story drift ratio is a general damage index which is being used to detect damaged stories after severe ground motions. Since this general damage index cannot detect damaged elements also the severity of imposed damages on elements, a new real-time seismic damage detection method base on artificial neural networks was proposed to overcome this issue. This approach considers nonlinear behaviour of structures and not only is capable of detecting damaged elements but also can address the severity of imposed damages. Proposed algorithm was applied on a 3-story concrete building .The obtained results confirmed accuracy and robustness of this method.
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Raj, R. Melvin, Jyosthna R, Ramya Madhuri N, Akshay Sunny R, and Pratima A. "Damage Detection of An Automobile." International Journal of Engineering Research in Computer Science and Engineering 9, no. 10 (October 13, 2022): 61–64. http://dx.doi.org/10.36647/ijercse/09.10.art014.

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As a result of the proliferation of automobile in- dustries today. There have been an increasing number of car accidents, not all of which are serious, but the automobile is damaged. Detecting automobile damage at the site of an accident using images is exceptionally beneficial as it may significantly lower the cost of processing the insurance reimbursement process while also providing more convenience to automobile users. In most cases, this damage is detected and assessed manually from the car’s images during the car evaluation process. In this paper, we worked on the problem of automation of vehicle damage detection which can be used by insurance companies to automate the process of vehicle insurance claims in a rapid fashion. The recent advances in computer vision largely due to the adoption of fast, scalable, and end-to-end trainable Convolutional Neural Networks make it technically feasible to recognize vehicle damages using semantic segmentation. We manually collected and annotated images from various online sources containing different types of vehicle damages and we used U-NET architec- ture to detect the damage of an automobile.
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Zhang, Yu, Xin Feng, Zhe Fan, Shuang Hou, Tong Zhu, and Jing Zhou. "Experimental investigations on seismic damage monitoring of concrete dams using distributed lead zirconate titanate sensor network." Advances in Structural Engineering 20, no. 2 (July 28, 2016): 170–79. http://dx.doi.org/10.1177/1369433216660002.

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Seismic damage detection of concrete dams has always attracted much attention in hydraulic structure community. In this article, a novel seismic damage detection system was developed to perform seismic damage monitoring in concrete dams. As its importance in achieving the dam damage detection, the arrangement of a distributed lead zirconate titanate sensor network was introduced in detail. A dam model system with a distributed lead zirconate titanate sensor network was used as an object for verification. A shaking table was used to simulate the earthquake ground motion for the object to be tested. The seismic damage detection system could be used in not only the seismic damage process monitoring by measuring the dynamic stress history but also the distributed detecting of the dam damaged region. By analyzing the sensor signals, the emergence and development of the structural damages could be monitored timely. A damage index matrix was presented to evaluate the damage status of the dam in different paths. The experimental results verified the timeliness and the effectiveness of the proposed method.
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NASERALAVI, S. S., S. GERIST, E. SALAJEGHEH, and J. SALAJEGHEH. "ELABORATE STRUCTURAL DAMAGE DETECTION USING AN IMPROVED GENETIC ALGORITHM AND MODAL DATA." International Journal of Structural Stability and Dynamics 13, no. 06 (July 2, 2013): 1350024. http://dx.doi.org/10.1142/s0219455413500247.

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This paper addresses a proficient strategy for detection of structural damages in details using the variations of eigenvalues and eigenvectors. There are two concerns in this study. First, the severity of damage can vary within the damaged elements; second, it is possible that the damage extents do not exactly match the pre-generated finite element mesh. The first concern forms the motivation for employing the proper damage functions to model the elemental damages, and the second for considering the nodal positions as design variables. To obtain the design variables, an improved genetic algorithm is introduced in which two new operators are embedded. This strategy is applied to a beam and a plate structure as the cases of study. The results demonstrate the applicability and efficiency of the proposed algorithm in elaborate damage detections.
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Park, Sang-Eun, and Yoon Taek Jung. "Detection of Earthquake-Induced Building Damages Using Polarimetric SAR Data." Remote Sensing 12, no. 1 (January 1, 2020): 137. http://dx.doi.org/10.3390/rs12010137.

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Remote sensing, particularly using synthetic aperture radar (SAR) systems, can be an effective tool in detecting and assessing the area and amount of building damages caused by earthquake or tsunami. Several studies have provided experimental evidence for the importance of polarimetric SAR observations in building damage detection and assessment, particularly caused by a tsunami. This study aims to evaluate the practical applicability of the polarimetric SAR observations to building damage caused by the direct ground-shaking of an earthquake. The urban areas heavily damaged by the 2016 Kumamoto earthquake in Japan have been investigated by using the polarimetric PALSAR-2 data acquired in pre- and post-earthquake conditions. Several polarimetric change detection approaches, such as the changes of polarimetric scattering powers, the matrix dissimilarity measures, and changes of the radar scattering mechanisms, were examined. Optimal damage indicators in the presence of significant natural changes, and a novel change detection method by the fuzzy-based fusion of polarimetric damage indicators are proposed. The accuracy analysis results show that the proposed automatic classification method can successfully detect the selected damaged areas with a detection rate of 90.9% and false-alarm rate of 1.3%.
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Carminati, M., and S. Ricci. "Structural Damage Detection Using Nonlinear Vibrations." International Journal of Aerospace Engineering 2018 (September 25, 2018): 1–21. http://dx.doi.org/10.1155/2018/1901362.

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Nonlinear vibrations emerging from damaged structures are suitable indicators for detecting defects. When a crack arises, its behavior could be approximated like a bilinear stiffness. According to this scheme, typical nonlinear phenomena as the presence of superharmonics in the dynamic response and the variation of the oscillation frequency in time emerge. These physical consequences give the opportunity to study damage detection procedures with relevant improvements with respect to the typical strategies based on linear vibrations, such as high sensitivity to small damages, no need for an accurate comparison model, and behavior not influenced by environmental conditions. This paper presents a methodology, which aims at finding suitable nonlinear phenomena for the damage detection of three contact-type damages in a panel representing a typical aeronautical structural component. At first, structural simulations are executed using MSC Nastran models and reduced dynamic models in MATLAB in order to highlight relevant nonlinear behaviors. Then, proper experimental tests are developed in order to look for the nonlinear phenomena identified: presence of superharmonics in the dynamic response and nonlinear behavior of the lower frequency of vibration, computed using the CWT (continuous wavelet transform). The proposed approach exhibits the possibility to detect and localize contact-type damages present in a realistic assembled structure.
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Stoykov, Stanislav, Emil Manoach, and Maosen Cao. "Vibration Based Damage Detection of Rotating Beams." MATEC Web of Conferences 148 (2018): 14008. http://dx.doi.org/10.1051/matecconf/201814814008.

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The early detection and localization of damages is essential for operation, maintenance and cost of the structures. Because the frequency of vibration cannot be controlled in real-life structures, the methods for damage detection should work for wide range of frequencies. In the current work, the equation of motion of rotating beam is derived and presented and the damage is modelled by reduced thickness. Vibration based methods which use Poincaré maps are implemented for damage localization. It is shown that for clamped-free boundary conditions these methods are not always reliable and their success depends on the excitation frequency. The shapes of vibration of damaged and undamaged beams are shown and it is concluded that appropriate selection criteria should be defined for successful detection and localization of damages.
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Amina Saouab, Hajar Chouiyakh, Mustafa Faqir, Kenza Bouchaala, Fathi Ghanameh, and Elhachmi Essadiqi. "Study of Multistage Damage Detection Method Based on Lamb Waves and Thermal Effect." Journal of Advanced Research in Fluid Mechanics and Thermal Sciences 93, no. 1 (March 25, 2022): 200–211. http://dx.doi.org/10.37934/arfmts.93.1.200211.

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Non-destructive testing has been implemented in many industries to ensure structural safety and reliability by detecting defects. In this study, Lamb waves are used for early damage detection and characterization. The aim of this research work is to develop a methodology for damage characterization (detection, localization, severity, and life estimation). Different problems associate with Lamb waves propagation as their dispersive behavior, and the effect of varying temperature on the amplitude and arrival time of the wave. Current study focuses on investigating the multistage damage detection method based on Lamb waves. It uses a network of transducers to improve damage detection and localization. It is aimed to validate the present technique by ellipse method to improve damage localization of the previously detected damages. To model the first stage of the technique, numerical simulations were performed on an 800x800x1.293 mm aluminum plate, using FE software ABAQUS explicit. Obtained signals from the simulation can detect s the presence of damage by comparing the baseline signal with damaged signals. The corresponding delays have been validated and compared with those of literature to improve the estimation of damage position.
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Riddihough, G. "Damage Detection." Science Signaling 1, no. 24 (June 17, 2008): ec227-ec227. http://dx.doi.org/10.1126/scisignal.124ec227.

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Al Duhayyim, Mesfer, Areej A. Malibari, Abdullah Alharbi, Kallekh Afef, Ayman Yafoz, Raed Alsini, Omar Alghushairy, and Heba Mohsen. "Road Damage Detection Using the Hunger Games Search with Elman Neural Network on High-Resolution Remote Sensing Images." Remote Sensing 14, no. 24 (December 8, 2022): 6222. http://dx.doi.org/10.3390/rs14246222.

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Roads can be significant traffic lifelines that can be damaged by collapsed tree branches, landslide rubble, and buildings debris. Thus, road damage detection and evaluation by utilizing High-Resolution Remote Sensing Images (RSI) are highly important to maintain routes in optimal conditions and execute rescue operations. Detecting damaged road areas through high-resolution aerial images could promote faster and effectual disaster management and decision making. Several techniques for the prediction and detection of road damage caused by earthquakes are available. Recently, computer vision (CV) techniques have appeared as an optimal solution for road damage automated inspection. This article presents a new Road Damage Detection modality using the Hunger Games Search with Elman Neural Network (RDD–HGSENN) on High-Resolution RSIs. The presented RDD–HGSENN technique mainly aims to determine road damages using RSIs. In the presented RDD–HGSENN technique, the RetinaNet model was applied for damage detection on a road. In addition, the RDD–HGSENN technique can perform road damage classification using the ENN model. To tune the ENN parameters automatically, the HGS algorithm was exploited in this work. To examine the enhanced outcomes of the presented RDD–HGSENN technique, a comprehensive set of simulations were conducted. The experimental outcomes demonstrated the improved performance of the RDD–HGSENN technique with respect to recent approaches in relation to several measures.
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Dissertations / Theses on the topic "Damage Detection"

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Cockerill, Aaron. "Damage detection of rotating machinery." Thesis, Cardiff University, 2017. http://orca.cf.ac.uk/105671/.

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Acoustic emission (AE) is an emerging technique for the condition monitoring of rotating machinery components, including both rolling element bearings and gears. Due to the high frequency range over which AE is sensitive to, AE potentially offers advantages for detection of incipient damage at an early stage of failure when compared to traditional techniques such as vibration. This thesis first investigates the effects of increased speed and load on the generation of AE within cylindrical roller bearings, and determines similarities and differences between AE and vibrational data. A traditional AE sensor was used in conjunction with a Dual Function Sensor (DFS) capable of recording both low frequency AE and vibration. It was shown that increasing speed has the greatest influence on the AE signals produced whereas the effect of load was limited. Order analysis of both AE and vibrational data also demonstrated that characteristic bearing defect frequencies are visible in the AE spectrum but not in the vibrational spectrum. Bearings with seeded defects upon the outer raceway were investigated under a fixed speed and it was found that load increased the energy within the signal frequency spectrum as the damaged increased. Two bearing life tests were also conducted, one accelerated to 12 hours and the second extended to over 2800 hours however as damage detection only occurred after significant damage had developed, it is concluded that AE of seeded defects indicate a false sensitivity. Both life tests were able to demonstrate that signal levels increase as damage propagates over the bearing raceway however it was not possible to determine any advantage of using AE over vibration. AE sensors were also applied to test rigs of increased complexity, including the monitoring a wind turbine planet bearing and a helical gear pair. AE was able to detect cracking of the shaft surface within the wind turbine bearing test rig which was mistaken for being an inner raceway failure, highlighting the difficulty in damage location. A tooth failure occurred during the testing of the helical gear pair however AE was not able to detect growing damage, instead only increasing in amplitude after the tooth had sheared off, similar to the detection from vibrational signals.
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Dissanayake, Amal S. "Electrostatic discharge damage detection method." Thesis, Kansas State University, 1997. http://hdl.handle.net/2097/13512.

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Al, Jailawi Samer Saadi Hussein. "Damage detection using angular velocity." Diss., University of Iowa, 2018. https://ir.uiowa.edu/etd/6539.

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The present work introduces novel methodologies for damage detection and health monitoring of structural and mechanical systems. The new approach uses the angular velocity inside different mathematical forms, via a gyroscope, to detect, locate, and relatively quantify damage. This new approach has been shown to outperform the current state-of-the-art acceleration-based approach in detecting damage on structures. Additionally, the current approach has been shown to be less sensitive to environmental acoustic noises, which present major challenges to the acceleration-based approaches. Furthermore, the current approach has been demonstrated to work effectively on arch structures, which acceleration-based approaches have struggled to deal with. The efficacy of the new approach has been investigated through multiple forms of structural damage indices. The first methodology proposed a damage index that is based on the changes in the second spatial derivative (curvature) of the power spectral density (PSD) of the angular velocity during vibration. The proposed method is based on the output motion only and does not require information about the input forces/motions. The PSD of the angular velocity signal at different locations on structural beams was used to identify the frequencies where the beams show large magnitude of angular velocity. The curvature of the PSD of the angular velocity at these peak frequencies was then calculated. A damage index is presented that measures the differences between the PSD curvature of the angular velocity of a damaged structure and an artificial healthy baseline structure. The second methodology proposed a damage index that is used to detect and locate damage on straight and curved beams. The approach introduces the transmissibility and coherence functions of the output angular velocity between two points on a structure where damage may occur to calculate a damage index as a metric of the changes in the dynamic integrity of the structure. The damage index considers limited-frequency bands of the transmissibility function at frequencies where the coherence is high. The efficacy of the proposed angular-velocity damage-detection approach as compared to the traditional linear-acceleration damage-detection approach was tested on straight and curved beams with different chord heights. Numerical results showed the effectiveness of the angular-velocity approach in detecting damage of multiple levels. It was observed that the magnitude of the damage index increased with the magnitude of damage, indicating the sensitivity of the proposed method to damage intensity. The results on straight and curved beams showed that the proposed approach is superior to the linear-acceleration-based approach, especially when dealing with curved beams with increasing chord heights. The experimental results showed that the damage index of the angular-velocity approach outweighed that of the acceleration approach by multiple levels in terms of detecting damage. A third methodology for health-monitoring and updating of structure supports, which resemble bridges’ bearings, is introduced in this work. The proposed method models the resistance of the supports as rotational springs and uses the transmissibility and coherence functions of the output response of the angular velocity in the neighborhood of the bearings to detect changes in the support conditions. The proposed methodology generates a health-monitoring index that evaluates the level of deterioration in the support and a support-updating scheme to update the stiffness resistance of the supports. Numerical and experimental examples using beams with different support conditions are introduced to demonstrate the effectiveness of the proposed method. The results show that the proposed method detected changes in the state of the bearings and successfully updated the changes in the stiffness of the supports.
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Gharibnezhad, Fahit. "Robust damage detection in smart structures." Doctoral thesis, Universitat Politècnica de Catalunya, 2014. http://hdl.handle.net/10803/277544.

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This thesis is devoted to present some novel techniques in Structural Health Monitoring (SHM). SHM is a developing field that tries to monitor structures to make sure that they remain in their desired condition to avoid any catastrophe. SHM includes different levels from damage detection area to prognosis field. This work is dedicated to the first level, which might be considered the main and most important level. New techniques presented in this work are based on different statistical and signal processing methods such as Principal Component Analysis and its robust counterpart, Wavelet Transform, Fuzzy similarity, Andrew plots, etc. These techniques are applied on the propagated waves that are activated and captured in the structure using appropriate transducers. Piezoceramic (PZT) devices are chosen in this work to capture the signals due to their special characteristics such as high performance, low energy consumption and reasonable price. To guarantee the efficiency of the suggested techniques, they are tested on different laboratory and real scale test benchmarks, such as aluminum and composite plates, fuselage, wing skeleton, tube, etc. Because of the variety of tested benchmarks, this thesis is called damage detection in smart structures. This variety may promise the ability and capability of the proposed methods on different fields such as aerospace and gas/oil industry. In addition to the normal laboratory conditions, it is shown in this work that environmental changes can affect the performance of the damage detection and wave propagation significantly. As such, there is a vital need to consider their effect. In this work, temperature change is chosen as it is one of the main environmental fluctuation factors. To scrutinize its effect on damage detection, first, the effect of temperature is considered on wave propagation and then all the proposed methods are tested to check whether they are sensitive to temperature change or not. Finally, a temperature compensation method is applied to ensure that the proposed methods are stable and robust even when structures are subjected to variant environmental conditions.
La presente tesis doctoral se dedica a la exploración y presentación de técnicas novedosas para la Monitorización y detección de defectos en estructuras (Structural Health Monitoring -SHM-) SHM es un campo actualmente en desarrollo que pretende asegurarse que las estructuras permanecen en su condición deseada para evitar cualquier catástrofe. En SHM se presentan diferentes niveles de diagnóstico, Este trabajo se concentra en el primer nivel, que se considera el más importante, la detección de los defectos. Las nuevas técnicas presentadas en esta tesis se basan en diferentes métodos estadísticos y de procesamiento de señales tales como el Análisis de Componentes Princpales (PCA) y sus variaciones robustas, Transformada wavelets, lógica difusa, gráficas de Andrew, etc. Estas técnicas de aplican sobre las ondas de vibración que se generan y se miden en la estructura utilizando trasductores apropiados. Dispositivos piezocerámicos (PZT's) se han escogido para este trabajo ya que presentan características especiales tales como: alto rendimiento, bajo consumo de energia y bajo costo. Para garantizar la eficacia de la metodología propuesta,se ha validado en diferentes laboratorios y estructuras a escala real: placas de aluminio y de material compuesto, fuselage de un avión, revestimiento del ala de un avóin, tubería, etc. Debido a la gran variedad de estructuras utilizadas, su aplicación en la industria aeroespacial y/o petrolera es prometedora. Por otra parte, los cambios ambientales pueden afectar al rendimiento de la detección de daños y propagación de la onda significativamente . En este trabajo , se estudia el efecto de las variaciones de temperatura ya que es uno de los principales factores de fluctuación del medio ambiente . Para examinar su efecto en la detección de daños, en primer lugar, todos los métodos propuestos se prueban para comprobar si son sensibles a los cambios de temperatura o no. Finalmente , se aplica un método de compensación de temperatura para garantizar que los métodos propuestos son estables y robustos incluso cuando las estructuras se someten a condiciones ambientales variantes
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Matlack, Kathryn H. "Nonlinear ultrasound for radiation damage detection." Diss., Georgia Institute of Technology, 2014. http://hdl.handle.net/1853/51965.

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Radiation damage occurs in reactor pressure vessel (RPV) steel, causing microstructural changes such as point defect clusters, interstitial loops, vacancy-solute clusters, and precipitates, that cause material embrittlement. Radiation damage is a crucial concern in the nuclear industry since many nuclear plants throughout the US are entering the first period of life extension and older plants are currently undergoing assessment of technical basis to operate beyond 60 years. The result of extended operation is that the RPV and other components will be exposed to higher levels of neutron radiation than they were originally designed to withstand. There is currently no nondestructive evaluation technique that can unambiguously assess the amount of radiation damage in RPV steels. Nonlinear ultrasound (NLU) is a nondestructive evaluation technique that is sensitive to microstructural features such as dislocations, precipitates, and their interactions in metallic materials. The physical effect monitored by NLU is the generation of higher harmonic frequencies in an initially monochromatic ultrasonic wave, arising from the interaction of the ultrasonic wave with microstructural features. This effect is quantified with the measurable acoustic nonlinearity parameter, beta. In this work, nonlinear ultrasound is used to characterize radiation damage in reactor pressure vessel steels over a range of fluence levels, irradiation temperatures, and material composition. Experimental results are presented and interpreted with newly developed analytical models that combine different irradiation-induced microstructural contributions to the acoustic nonlinearity parameter.
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Huethwohl, Philipp Karl. "Bridge damage detection and BIM mapping." Thesis, University of Cambridge, 2019. https://www.repository.cam.ac.uk/handle/1810/285562.

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Bridges are a vitally important part of modern infrastructure. Their condition needs to be monitored on a continuous basis in order to ensure their safety and functionality. Teams of engineers visually inspect more than half a million bridges per year in the US and the EU. There is clear evidence to suggest that they are not able to meet all bridge inspection guideline requirements. In addition, the format and storage of inspection reports varies considerably across authorities because of the lack of standardisation. The availability of a comprehensive and open digital representation of the data involved in and required for bridge inspection is an indispensable necessity for exploiting the full potential of modern digital technologies like big data exploration, artificial intelligence and database technologies. A thorough understanding of bridge inspection information requirements for reinforced concrete bridges is needed as basis for overcoming the stated problem. This work starts with a bridge inspection guideline analysis, from which an information model and a candidate binding to Industry Foundation Classes (IFC) is developed. The resulting bridge model can fully store inspection information in a standardised way which makes it easily shareable and comparable between users and standards. Then, two inspection stages for locating and classifying visual concrete defects are devised, implemented and benchmarked to support the bridge inspection process: In a first stage, healthy concrete surfaces are located and disregarded for further inspection. In a second hierarchical classification stage, each of the remaining potentially unhealthy surface areas is classified into a specific defect type in accordance with bridge inspection guidelines. The first stage achieves a search space reduction for a subsequent defect type classification of over 90% with a risk of missing a defect patch of less than 10%. The second stage identifies the correct defect type to a potentially unhealthy surface area with a probability of 85%. A prototypical implementation serves as a proof of concept. This work closes the gap between requirements arising from established inspection guidelines, the demand for holistic data models which has recently become known as "digital twin", and methods for automatically identifying and measuring specific defect classes on small scale images. It is of great significance for bridge inspectors, bridge owners and authorities as they now have more suitable data models at hand to store, view and manage maintenance information on bridges including defect location and defect types which are being retrieved automatically. With these developments, a foundation is available for a complete revision of bridge inspection processes on a modern, digital basis.
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Malik, Shoaib Ahmad. "Damage detection using self-sensing composites." Thesis, University of Birmingham, 2011. http://etheses.bham.ac.uk//id/eprint/1750/.

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The primary aim of this research programme was to enable damage detection in glass fibre reinforced composites using the reinforcing fibres as the sensing element. In other words, E-glass fibres were used as light guides to detect the fracture of individual fibres, when loaded in tension. This was achieved by monitoring the transmitted light intensity through the reinforcing glass fibres. Two types of glass fibres and matrices were evaluated. In the case of glass fibres, E-glass and custom-made small-diameter (12 µm) optical fibre (SDOF) were used. Three types of low refractive index resin systems with specified failure strains were also used. The basic technology involved illuminating one end of the fibre bundle or composite with a white light or laser source and the opposite end was imaged using a high-speed CCD camera. Acoustic emission monitoring of fibre bundles revealed that there were two types of failures occurring in a bundle, a lower amplitude of the acoustic emission signal (AES) related to the inter-fibre friction and a high amplitude of the AES to fibre fractures. This characteristic was also confirmed by a Weibull statistical analysis where it was demonstrated that a two parameter distribution was present corresponding to two different flaw distributions. In the case of self-sensing composites, it was found that the specific failure modes in the composites (matrix failure, fibre fracture, debonding) generate their characteristic amplitudes of the AES and frequencies. These failure modes were recorded and correlated to the tensile test data. It was demonstrated that the attenuation of transmitted light can be related to the fracture of fibres in the bundle or a composite test specimen. It was found that the image analysis routines were capable of identifying and tracking the survival or fracture of each fibre in the bundle or composite. The results obtained from mechanical loading, acoustic emission and images analysis were cross-correlated.
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Tadros, Nader Nabil Aziz. "Structural damage detection using ambient vibrations." Thesis, Kansas State University, 2014. http://hdl.handle.net/2097/18178.

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Master of Science
Department of Civil Engineering
Hani G. Melhem
The objective of this research is to use structure ambient random vibration response to detect damage level and location. The use of ambient vibration is advantageous because excitation is caused by service conditions such as normal vehicle traffic on a highway bridge, train passage on a railroad bridge, or wind loads on a tall building. This eliminates the need to apply a special impact or dynamic load, or interrupt traffic on a bridge in regular service. This research developed an approach in which free vibration of a structure is extracted from the response of this structure to a random excitation in the time domain (acceleration versus time) by averaging out the random component of the response. The result is the free vibration that includes all modes based on the sampling rate on time. Then this free vibration is transferred to the frequency domain using a Fast Fourier Transform (FFT). Variations in frequency response are a function of structural stiffness and member end-conditions. Such variations are used as a measure to identify the change in the structural dynamic properties, and ultimately detect damage. A physical model consisting of a 20 × 20 × 1670 -mm long steel square tube was used to validate this approach. The beam was tested under difference supports conditions varying from a single- to three-span continuous configuration. Random excitation was applied to the beam, and the dynamic response was measured by an accelerometer placed at various locations on the span. A numerical model was constructed in ABAQUS and the dynamic response was obtained from the finite element model subjected to similar excitation as in the physical model. Numerical results were correlated against results from the physical model, and comparison was made between the different span/support configurations. A subsequent step would be to induce damage that simulates loss of stiffness or cracking condition of the beam cross section, and that would be reflected as a change in the frequency and other dynamic properties of the structure. The approach achieved good results for a structure with a limited number of degrees of freedom. Further research is needed for structures with a larger number of degrees of freedom and structures with damage in symmetrical locations relative to the accelerometer position.
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Asnaashari, Erfan. "Vibration-based damage detection in structures." Thesis, University of Manchester, 2014. https://www.research.manchester.ac.uk/portal/en/theses/vibrationbased-damage-detection-in-structures(09061582-55fb-4fba-846e-2156dd4ef172).html.

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Structural health monitoring systems have a great potential for cost saving and safety improvement in different types of structures. One of the most important tasks of these systems is to identify damage at an early stage of its development. A variety of methods may be used to identify, locate, or quantify the extent of damage or fault in a structural or mechanical component. However, the preferable method is the one which maximises the probability of detecting the flaw, while also considering feasibility of in-situ testing, ease of use and economic factors. Cracks are one of the common defects in structural components that may ultimately lead to failure of structures if not detected. The presence of cracks in a structure brings about local variations in the stiffness of the structure. These variations cause the dynamic behaviour of the cracked structure to be different from that of a healthy one. Vibration-based damage detection methods have attracted considerable attention over the past few decades. These methods generally use changes to the physical properties of structures for the purpose of crack detection. In this thesis, two new vibration-based methods have been developed for damage detection in beam-like and rotor-type structures. The first method performs the entire signal processing required for crack detection in time domain. It is based on assessing the normality of vibration responses using the normal probability plot (NPP). The amount of deviation between the actual and normal distribution of measured vibration responses was calculated along the length of the structure to localise the crack. The second proposed method converts the vibration responses into frequency domain for further processing. Excitation of the cracked structure at a given frequency always generates higher harmonic components of the exciting frequency due to the breathing of the crack. This method uses the operational deflection shape of the structure at the exciting frequency and its higher harmonics to identify the crack location. Avoiding complicated signal processing in frequency domain is the main advantage of the first method. However, more precise identification of crack locations can be obtained through the second method. Generally, both methods have the advantage of being easy, reference-free and applicable to in-situ testing for any structure. The concept and computational approach of both methods along with their validations through numerical and experimental examples have been presented. Moreover, different input excitations have been used to evaluate the capability of the developed methods in detecting the crack location(s).
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Dixit, Akash. "Damage modeling and damage detection for structures using a perturbation method." Diss., Georgia Institute of Technology, 2012. http://hdl.handle.net/1853/43575.

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This thesis is about using structural-dynamics based methods to address the existing challenges in the field of Structural Health Monitoring (SHM). Particularly, new structural-dynamics based methods are presented, to model areas of damage, to do damage diagnosis and to estimate and predict the sensitivity of structural vibration properties like natural frequencies to the presence of damage. Towards these objectives, a general analytical procedure, which yields nth-order expressions governing mode shapes and natural frequencies and for damaged elastic structures such as rods, beams, plates and shells of any shape is presented. Features of the procedure include the following: 1. Rather than modeling the damage as a fictitious elastic element or localized or global change in constitutive properties, it is modeled in a mathematically rigorous manner as a geometric discontinuity. 2. The inertia effect (kinetic energy), which, unlike the stiffness effect (strain energy), of the damage has been neglected by researchers, is included in it. 3. The framework is generic and is applicable to wide variety of engineering structures of different shapes with arbitrary boundary conditions which constitute self adjoint systems and also to a wide variety of damage profiles and even multiple areas of damage. To illustrate the ability of the procedure to effectively model the damage, it is applied to beams using Euler-Bernoulli and Timoshenko theories and to plates using Kirchhoff's theory, supported on different types of boundary conditions. Analytical results are compared with experiments using piezoelectric actuators and non-contact Laser-Doppler Vibrometer sensors. Next, the step of damage diagnosis is approached. Damage diagnosis is done using two methodologies. One, the modes and natural frequencies that are determined are used to formulate analytical expressions for a strain energy based damage index. Two, a new damage detection parameter are identified. Assuming the damaged structure to be a linear system, the response is expressed as the summation of the responses of the corresponding undamaged structure and the response (negative response) of the damage alone. If the second part of the response is isolated, it forms what can be regarded as the damage signature. The damage signature gives a clear indication of the damage. In this thesis, the existence of the damage signature is investigated when the damaged structure is excited at one of its natural frequencies and therefore it is called ``partial mode contribution". The second damage detection method is based on this new physical parameter as determined using the partial mode contribution. The physical reasoning is verified analytically, thereupon it is verified using finite element models and experiments. The limits of damage size that can be determined using the method are also investigated. There is no requirement of having a baseline data with this damage detection method. Since the partial mode contribution is a local parameter, it is thus very sensitive to the presence of damage. The parameter is also shown to be not affected by noise in the detection ambience.
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Books on the topic "Damage Detection"

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Masters, JE, ed. Damage Detection in Composite Materials. 100 Barr Harbor Drive, PO Box C700, West Conshohocken, PA 19428-2959: ASTM International, 1992. http://dx.doi.org/10.1520/stp1128-eb.

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Didenko, Vladimir V., ed. Fast Detection of DNA Damage. New York, NY: Springer New York, 2017. http://dx.doi.org/10.1007/978-1-4939-7187-9.

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E, Masters John, and International Symposium on Damage Detection and Quality Assurance in Composite Materials (1990 : San Antonio, Tex.), eds. Damage detection in composite materials. Philadelphia, PA: ASTM, 1992.

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Didenko, Vladimir V. In Situ Detection of DNA Damage. New Jersey: Humana Press, 2002. http://dx.doi.org/10.1385/1592591795.

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Eftekhar Azam, Saeed. Online Damage Detection in Structural Systems. Cham: Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-02559-9.

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Baruch, Menahem. Damage detection based on reduced measurements. [Haifa]: Technion-Israel Institute of Technology, Faculty of Aerospace Engineering, 1995.

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Center, NASA Glenn Research, ed. Damage detection using holography and interferometry. Cleveland, Ohio: National Aeronautics and Space Administration, Glenn Research Center, 2003.

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Decker, Arthur J. Damage detection using holography and interferometry. Cleveland, Ohio: National Aeronautics and Space Administration, Glenn Research Center, 2003.

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Center, NASA Glenn Research, ed. Gear damage detection using oil debris analysis. [Cleveland, Ohio]: National Aeronautics and Space Administration, Glenn Research Center, 2001.

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Morassi, Antonino, and Fabrizio Vestroni, eds. Dynamic Methods for Damage Detection in Structures. Vienna: Springer Vienna, 2008. http://dx.doi.org/10.1007/978-3-211-78777-9.

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Book chapters on the topic "Damage Detection"

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Hirao, Masahiko, and Hirotsugu Ogi. "Creep Damage Detection." In Electromagnetic Acoustic Transducers, 337–45. Tokyo: Springer Japan, 2016. http://dx.doi.org/10.1007/978-4-431-56036-4_17.

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Xu, You-Lin, and Jia He. "Structural damage detection." In Smart Civil Structures, 333–88. Boca Raton : Taylor & Francis, CRC Press, 2017.: CRC Press, 2017. http://dx.doi.org/10.1201/9781315368917-15.

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Ghosh, Bidisha, Michael O’Byrne, Franck Schoefs, and Vikram Pakrashi. "Surface damage detection." In Image-Based Damage Assessment for Underwater Inspections, 97–126. Boca Raton : Taylor & Francis, a CRC title, part of the Taylor & Francis imprint, a member of the Taylor & Francis Group, the academic division of T&F Informa, plc, [2018]: CRC Press, 2018. http://dx.doi.org/10.1201/9781351052580-6.

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Frangopol, Dan M., and Sunyong Kim. "Probabilistic Damage Detection." In Life-Cycle of Structures Under Uncertainty, 51–71. Boca Raton, FL : CRC Press, 2019. | “A science publishers book.”: CRC Press, 2019. http://dx.doi.org/10.1201/9780429053283-3.

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Uhl, Tadeusz, Tadeusz Stepinski, and Wieslaw Staszewski. "Introduction." In Advanced Structural Damage Detection, 1–15. Chichester, UK: John Wiley & Sons, Ltd, 2013. http://dx.doi.org/10.1002/9781118536148.ch1.

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Kohut, Piotr, and Krzysztof Holak. "Vision-Based Monitoring System." In Advanced Structural Damage Detection, 279–320. Chichester, UK: John Wiley & Sons, Ltd, 2013. http://dx.doi.org/10.1002/9781118536148.ch10.

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Paćko, Paweł. "Numerical Simulation of Elastic Wave Propagation." In Advanced Structural Damage Detection, 17–56. Chichester, UK: John Wiley & Sons, Ltd, 2013. http://dx.doi.org/10.1002/9781118536148.ch2.

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Gallina, Alberto, Paweł Paćko, and Łukasz Ambroziński. "Model Assisted Probability of Detection in Structural Health Monitoring." In Advanced Structural Damage Detection, 57–72. Chichester, UK: John Wiley & Sons, Ltd, 2013. http://dx.doi.org/10.1002/9781118536148.ch3.

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Klepka, Andrzej. "Nonlinear Acoustics." In Advanced Structural Damage Detection, 73–107. Chichester, UK: John Wiley & Sons, Ltd, 2013. http://dx.doi.org/10.1002/9781118536148.ch4.

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Mańka, Michał, Mateusz Rosiek, and Adam Martowicz. "Piezocomposite Transducers for Guided Wavess." In Advanced Structural Damage Detection, 109–39. Chichester, UK: John Wiley & Sons, Ltd, 2013. http://dx.doi.org/10.1002/9781118536148.ch5.

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Conference papers on the topic "Damage Detection"

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Lestari, W., and S. Hanagud. "Damage Detection Using Experimental Data Based Methods." In ASME 2000 International Mechanical Engineering Congress and Exposition. American Society of Mechanical Engineers, 2000. http://dx.doi.org/10.1115/imece2000-1724.

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Abstract The objective of this work is to develop a damage detection algorithm, which is based on experimentally identified data and a mathematical relation between the damage information and the changes in structural dynamic characteristics. The relation is derived in the form of a differential equation, which relate the damage information, natural frequency changes, and the modes of the undamaged and damaged structure. The curvature mode is chosen in this method due to its sensitivity to the presence of the damage and its localized information. The detection algorithm enables one to locate the damages and to obtain the corresponding magnitudes simultaneously. For illustration of the methods numerical simulation on damaged beams were conducted. The damages were considered as point damages. Numerical simulation results are presented.
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Gawronski, Wodek, and Jerzy T. Sawicki. "Structural Damage Detection Using Modal Norms." In ASME 1999 Design Engineering Technical Conferences. American Society of Mechanical Engineers, 1999. http://dx.doi.org/10.1115/detc99/vib-8374.

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Abstract A modal H2 norm is used to detect structural damages. The norm is determined for each sensor location, and for modal modes of interest. The sensor norm detects the damage location, the modal norm detect the most damaged mode.
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Ghazi, Reza Mohammadi, James Long, and Oral Buyukozturk. "Structural Damage Detection Based on Energy Transfer Between Intrinsic Modes." In ASME 2013 Conference on Smart Materials, Adaptive Structures and Intelligent Systems. American Society of Mechanical Engineers, 2013. http://dx.doi.org/10.1115/smasis2013-3022.

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In this study, a new damage detection algorithm for specific types of damages such as breathing cracks, which are called “active discontinuities” in this paper, is proposed. The algorithm is based on the nonlinear behavior of this class of damages and hence, is more precise and sensitive to damage compared to other common linear methods. The active discontinuities can be regarded as additional degrees of freedom (DOFs) which need energy to be excited. Because the input energy of both the intact and the damaged structures is finite, the energy content of vibrating modes will be changed due to damage. Thus, the properties of distribution of energy between vibrating modes can be used as indices for detecting damage. An essential detectability condition using this concept is decomposing a signal such that no spurious mode imposed to its expansion. In order to satisfy this condition, Empirical Mode decomposition (EMD) is used to extract the vibrating modes since all nonlinearities in a signal are preserved while no spurious mode or assumption of stationarity is imposed on the problem. Prevention of mode mixing, which is an important drawback of EMD, is another necessary condition for robustness of the algorithm. A solution is proposed in this paper to satisfy this condition in which special constraints are imposed on the normal procedure of EMD. Then, the fourth central moment, kurtosis, is used to compare the distribution of energy between the modified vibrating modes. The algorithm is verified through experimental testing of a simple steel cantilever structure under various damage scenarios. Results demonstrate the efficacy of the method for detecting discontinuities in a real structure.
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Feng, Wei, Qiaofeng Li, and Qiuhai Lu. "A Hierarchical Bayesian Method for Time Domain Structure Damage Detection." In ASME 2019 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. American Society of Mechanical Engineers, 2019. http://dx.doi.org/10.1115/detc2019-97026.

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Abstract A time domain structural damage detection method based on hierarchical Bayesian framework is proposed. Due to local stiffness reductions, the responses of damaged structures vary from those in undamaged status under the same external excitation. In this paper, the responses of damaged structures are assumed as the result of a summation of known external forces and unknown virtual forces exerted on corresponding undamaged structures. The damages can thus be detected, located, and quantified by the identification of associated virtual forces. A hierarchical Bayesian formulation considering all undetermined damage-related variables is adopted for the identification of virtual forces. The reasonable values of the variables and their uncertainties are depicted by their posterior distributions, sampled by Markov chain Monte Carlo method. Compared with traditional Bayesian formulations, manual choice of prior parameters is avoided and less prior information is required. The proposed virtual force indicator provides a more intuitive perspective for damage detection tasks and is potentially more operable in engineering practice. These advantages are illustrated by simulation of a cantilever beam under various damage conditions.
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Wimmer, Stephanie A., and Virginia G. DeGiorgi. "Damage detection using wavelets." In NDE for Health Monitoring and Diagnostics, edited by Tribikram Kundu. SPIE, 2003. http://dx.doi.org/10.1117/12.483820.

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Abdalla, M., and M. Qtaishat. "Damage Detection Using Emi." In 2022 6th European Conference on Electrical Engineering & Computer Science (ELECS). IEEE, 2022. http://dx.doi.org/10.1109/elecs55825.2022.00015.

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Myers, Oliver J., and Sourav Banerjee. "Coupled Damage Precursor Detection." In ASME 2015 Conference on Smart Materials, Adaptive Structures and Intelligent Systems. American Society of Mechanical Engineers, 2015. http://dx.doi.org/10.1115/smasis2015-8950.

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This conceptual research focuses on identifying damage precursors in carbon fiber reinforced polymer laminates. By coupling integrated in situ sensing elements (magnetostrictive particles) and multi-scale ultrasonic inspection (Quantitative Ultrasonic Imaging) with minimum hardware the authors are able to capture and gain an understanding of damage precursors. Preliminary damage precursors can be identified and quantified and correlated to a particular failure mode(s) and/or fabrication process accelerating the need for a sensing/repair strategy that could be implemented to capture the specific precursor prior to the onset of cracks. Capturing and mitigating damage precursors ahead of micro-crack formulation will slow the evolution of the damage precursors to micro-cracks, mitigate adverse loading environment, and develop techniques to reduce stress and loading below the endurance limit to keep it from being fatigued.
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Zhong, Shuncong, and S. Olutunde Oyadiji. "Wavelet-Based Structural Damage Detection." In ASME 2007 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. ASMEDC, 2007. http://dx.doi.org/10.1115/detc2007-35632.

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In this paper, a new wavelet-based approach for crack identification in beam-like structures is presented and applied to simply-supported beams with single or multiple cracks. A novel damage index, based on finding the difference between two sets of detail coefficients obtained by the use of the Stationary Wavelet Transform (SWT) of two reconstructed sets of modal displacement data of the cracked beam-like structure, is proposed for single crack detection or multiple crack detection. These two sets of mode shape data represent the left half and the modified right half of the modal data of the structure. Currently, SWT is widely used in the field of image processing for image noise reduction and image quality improvement. However, because it can provide an accurate estimate of the variances at each scale and facilitate the identification of salient features in a signal, SWT has great potential in the field of structural damage detection. In this paper, the modal responses of the damaged simply supported beams used are computed using the finite element method (FEM). The modal data generate is decomposed by SWT into a smooth curve, called approximation coefficient, and detail coefficient. It is shown that the detail coefficient includes crack information that is useful for structural damage detection. Therefore, a novel damage index, the difference of the SWT detail coefficients of two reconstructed sets of modal displacement data, is proposed and employed. The numerical simulation results show that the proposed wavelet-based method has a good anti-noise ability and it does not require the modal parameters of an intact structure as a baseline for crack detection. Therefore, it can be recommended for real applications in structural health monitoring and damage detection.
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Douti, Dam-Bé L., Sherazade Aknoun, Serge Monneret, Christophe Hecquet, Mireille Commandré, and Laurent Gallais. "In-line quantitative phase imaging for damage detection and analysis." In SPIE Laser Damage, edited by Gregory J. Exarhos, Vitaly E. Gruzdev, Joseph A. Menapace, Detlev Ristau, and MJ Soileau. SPIE, 2014. http://dx.doi.org/10.1117/12.2068178.

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Adachi, Yukio, Shigeki Unjoh, Masuo Kondoh, and Michio Ohsumi. "Nondestructive damage detection and evaluation technique for seismically damaged structures." In Nondestructive Evaluation Techniques for Aging Infrastructures & Manufacturing, edited by Steven B. Chase. SPIE, 1999. http://dx.doi.org/10.1117/12.339935.

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Reports on the topic "Damage Detection"

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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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Miller, Tim, and R. Lasser. Composite Damage Detection Using Novel Experimental Methods. Fort Belvoir, VA: Defense Technical Information Center, September 2002. http://dx.doi.org/10.21236/ada407271.

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Hartman, George A. Infrared Damage Detection System (IDDS) for Real-Time, Small-Scale Damage Monitoring. Fort Belvoir, VA: Defense Technical Information Center, January 2007. http://dx.doi.org/10.21236/ada467885.

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Miller, T. C., Bob Lasser, and Burt VanderHeiden. Composite Damage Detection Using a Novel Ultrasonic Method. Fort Belvoir, VA: Defense Technical Information Center, January 2003. http://dx.doi.org/10.21236/ada410224.

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Mishra, Pranay, Asha Hall, and Michael Coatney. Embedded Carbon Nanotube Networks for Damage Precursor Detection. Fort Belvoir, VA: Defense Technical Information Center, January 2014. http://dx.doi.org/10.21236/ada599174.

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Haworth, W. L. Fatigue Damage Detection in Steels by Optical Correlation. Fort Belvoir, VA: Defense Technical Information Center, March 1985. http://dx.doi.org/10.21236/ada155830.

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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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Bily, Mollie A., Young W. Kwon, and Randall D. Pollak. Damage Detection in Composite Interfaces through Carbon Nanotube Reinforcement. Fort Belvoir, VA: Defense Technical Information Center, February 2010. http://dx.doi.org/10.21236/ada516359.

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Islam, Abu S., and Kevin Craig. Damage Detection and Mitigation of Composite Structures using Smart Materials. Fort Belvoir, VA: Defense Technical Information Center, January 1993. http://dx.doi.org/10.21236/ada261121.

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Clark, G., C. Robbins, K. Wade, and P. Souza. Cable Damage Detection System and Algorithms Using Time Domain Reflectometry. Office of Scientific and Technical Information (OSTI), March 2009. http://dx.doi.org/10.2172/971773.

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