Relevant bibliographies by topics / Dynamic crack detection with photogrammetry

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  1. Journal articles
  2. Dissertations / Theses
  3. Book chapters
  4. Conference papers
  5. Reports

Academic literature on the topic 'Dynamic crack detection with photogrammetry'

Author: Grafiati
Published: 4 June 2021
Last updated: 11 February 2022

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Journal articles on the topic "Dynamic crack detection with photogrammetry"

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Merkle, D., A. Schmitt, and A. Reiterer. "SENSOR EVALUATION FOR CRACK DETECTION IN CONCRETE BRIDGES." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLIII-B2-2020 (August 14, 2020): 1107–14. http://dx.doi.org/10.5194/isprs-archives-xliii-b2-2020-1107-2020.

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Abstract. Bridges are one of the most critical traffic infrastructure objects, therefore it is necessary to monitor them at regular intervals. Nowadays, this monitoring is made manually by visual inspection. In recent projects, the authors are developing automated crack detection systems to support the inspector. In this pre-study, different sensors, like different camera systems for photogrammetry, a laser scanner, and a laser triangulation system are evaluated for crack detection based on a defined required minimum crack width of 0.2 mm. The used test object is a blasted concrete plate, sized 70 cm × 70 cm × 5 cm and placed in an outdoor environment. The results of the data acquisition with the different sensors are point clouds, which make the results comparable. The point cloud from the chosen laser scanner is not sufficient for the required crack width even at a low speed of 1 m/s. The RGB or intensity information of the photogrammetric point clouds, even based on a low-cost smartphone camera, contain the targeted cracks. The authors advise against using only the 3D information of the photogrammetric point clouds for crack detection due to noise. The laser triangulation system delivers the best results in both intensity and 3D information. The low weight of camera systems makes photogrammetry to the preferred method for an unmanned aerial vehicle (UAV). In the future, the authors aim for crack detection based on the 2D images, automated by using machine learning, and crack localisation by using structure from motion (SfM) or a positioning system.
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Wang, Jun, and Ruishe Jiang. "Eggshell crack detection by dynamic frequency analysis." European Food Research and Technology 221, no. 1-2 (April 21, 2005): 214–20. http://dx.doi.org/10.1007/s00217-005-1149-9.

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Mohammed, O. D., and M. Rantatalo. "Gear tooth crack detection using dynamic response analysis." Insight - Non-Destructive Testing and Condition Monitoring 55, no. 8 (August 1, 2013): 417–21. http://dx.doi.org/10.1784/insi.2012.55.8.417.

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Qian, G. L., S. N. Gu, and J. S. Jiang. "The dynamic behaviour and crack detection of a beam with a crack." Journal of Sound and Vibration 138, no. 2 (April 1990): 233–43. http://dx.doi.org/10.1016/0022-460x(90)90540-g.

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Belloni, V., A. Sjölander, R. Ravanelli, M. Crespi, and A. Nascetti. "TACK PROJECT: TUNNEL AND BRIDGE AUTOMATIC CRACK MONITORING USING DEEP LEARNING AND PHOTOGRAMMETRY." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLIII-B4-2020 (August 25, 2020): 741–45. http://dx.doi.org/10.5194/isprs-archives-xliii-b4-2020-741-2020.

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Abstract. Civil infrastructures, such as tunnels and bridges, are directly related to the overall economic and demographic growth of countries. The aging of these infrastructures increases the probability of catastrophic failures that results in loss of lives and high repair costs; all over the world, these factors drive the need for advanced infrastructure monitoring systems. For these reasons, in the last years, different types of devices and innovative infrastructure monitoring techniques have been investigated to automate the process and overcome the main limitation of standard visual inspections that are used nowadays. This paper presents some preliminary findings of an ongoing research project, named TACK, that combines advanced deep learning techniques and innovative photogrammetric algorithms to develop a monitoring system. Specifically, the project focuses on the development of an automatic procedure for crack detection and measurement using images of tunnels and bridges acquired with a mobile mapping system. In this paper, some preliminary results are shown to investigate the potential of a deep learning algorithm in detecting cracks occurred in concrete material. The model is a CNN (Convolutional Neural Network) based on the U-Net architecture; in this study, we tested the transferability of the model that has been trained on a small available labeled dataset and tested on a large set of images acquired using a customized mobile mapping system. The results have shown that it is possible to effectively detect cracks in unseen imagery and that the primary source of errors is the false positive detection of crack-like objects (i.e., contact wires, cables and tile borders).
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Miya, K., H. Yanagi, and K. Someya. "A new technique for detection of dynamic crack initiation." Nuclear Engineering and Design 94, no. 3 (July 1986): 281–89. http://dx.doi.org/10.1016/0029-5493(86)90010-5.

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Meng, G., and E. J. Hahn. "Dynamic Response of a Cracked Rotor With Some Comments on Crack Detection." Journal of Engineering for Gas Turbines and Power 119, no. 2 (April 1, 1997): 447–55. http://dx.doi.org/10.1115/1.2815595.

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By considering time-dependent terms as external excitation forces, the approximate dynamic response of a cracked horizontal rotor is analyzed theoretically and numerically. The solution is good for small cracks and small vibrations in the stable operating range. For each steady-state harmonic component, the forward and backward whirl amplitudes, the shape and orientation of the elliptic orbit, and the amplitude and phase of the response signals are analyzed, taking into account the effect of crack size, crack location, rotor speed, and unbalance. It is found that the crack causes backward whirl, the amplitude of which increases with the crack. For a cracked rotor, the response orbit for each harmonic component is an ellipse, the shape and orientation of which depend on the crack size. The influence of the crack on the synchronous response of the system can be regarded as an additional unbalance whereupon, depending on the speed and the crack location, the response amplitude differs from that of the uncracked rotor. The nonsynchronous response provides evidence of crack in the subcritical range, but is too small to be detected in the supercritical range. Possibilities for crack detection over the full-speed range include the additional average (the constant) response component, the backward whirl of the response, the ellipticity of the orbit, the angle between the major axis and the vertical axis, and the phase angle difference between vertical and horizontal vibration signals.
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Haldar, A., R. Martinez-Flores, and H. Katkhuda. "Crack detection in existing structures using noise-contaminated dynamic responses." Theoretical and Applied Fracture Mechanics 50, no. 1 (August 2008): 74–80. http://dx.doi.org/10.1016/j.tafmec.2008.04.007.

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Hampel, U., and H. G. Maas. "Cascaded image analysis for dynamic crack detection in material testing." ISPRS Journal of Photogrammetry and Remote Sensing 64, no. 4 (July 2009): 345–50. http://dx.doi.org/10.1016/j.isprsjprs.2008.12.006.

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Plachy, Tomáš, Jakub Okénka, Pavel Tesárek, and Michal Polák. "Damage Detection and Localization on Cement Specimens." Applied Mechanics and Materials 617 (August 2014): 229–32. http://dx.doi.org/10.4028/www.scientific.net/amm.617.229.

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This paper is focused on cement specimen testing by impact excitation non-destructive technique. The impulse excitation method was used for measuring of the natural frequencies and modes of longitudinal, transversal and torsional vibration of the specimens. The objective was to find dynamic properties of the specimens without a crack, with a crack and with a healed crack by cement paste and based on their comparison detect and localize the crack.
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Dissertations / Theses on the topic "Dynamic crack detection with photogrammetry"

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Hampel, Uwe, and Hans-Gerd Maas. "Dynamische Rissdetektion mittels photogrammetrischer Verfahren – Entwicklung und Anwendung optimierter Algorithmen." Saechsische Landesbibliothek- Staats- und Universitaetsbibliothek Dresden, 2009. http://nbn-resolving.de/urn:nbn:de:bsz:14-ds-1244047882026-24052.

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Die digitale Nahbereichsphotogrammetrie ermöglicht eine effiziente Erfassung dreidimensionaler Objektoberflächen bei experimentellen Untersuchungen. Besonders für die flächenhafte Erfassung von Verformungen und die Rissdetektion sind photogrammetrische Verfahren – unter Beachtung entsprechender Randbedingungen – prinzipiell geeignet. Der Beitrag geht unter Einbeziehung aktueller Untersuchungen an textilbewehrten Betonproben auf die Problematik der Rissdetektion ein und gibt einen Überblick über den Entwicklungsstand und das erreichbare Genauigkeitspotential. In Bezug auf die praktische Anwendung der vorgestellten Verfahren wird abschließend auf verschiedene Möglichkeiten der Optimierung eingegangen.
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Casey, Cody. "Crack detection in a rotor dynamic system by vibration monitoring." Thesis, Georgia Institute of Technology, 2000. http://hdl.handle.net/1853/17838.

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Haji, Zyad. "Dynamic analysis and crack detection in stationary and rotating shafts." Thesis, University of Manchester, 2016. https://www.research.manchester.ac.uk/portal/en/theses/dynamic-analysis-and-crack-detection-in-stationary-and-rotating-shafts(2e9dcab4-685d-4c20-8f9d-55b6892b8149).html.

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The sustainability, smooth operation and operational life of rotating machinery significantly rely on the techniques that detect the symptoms of incipient faults. Among the faults in rotating systems, the presence of a crack is one of the most dangerous faults that dramatically decreases the safety and operational life of the rotating systems, thereby leading to catastrophic failure and potential injury to personnel if it is undetected. Although many valuable techniques and models have been developed to identify a crack (or cracks) in stationary and rotating systems, finding an efficient technique (or model) that can identify a unique vibration signature of the cracked rotor is still a great challenge in this field. This is because of the unceasing necessity to develop high performance rotating machines and driving towards significant reduction of the time and cost of maintenance. Most of the crack identification techniques and models in the available literature are based on vibration-based methods. The main idea of the vibration-based method is that the presence of a crack in a rotor induces a change in the mass, damping, and stiffness of the rotor, and consequently detectable changes appear in the modal properties (natural frequencies, modal damping, and mode shapes). Among all these modal properties, the choice of the modal natural frequency change is more attractive as a tool for crack identification. The changes in natural frequencies due to a crack can be conveniently measured from just a few accessible points on the cracked rotor. Furthermore, measuring the natural frequencies does not require expensive measuring instruments, and the natural frequency data is normally less contaminated by experimental noise. However, the change that a crack induces in the natural frequencies is usually very small and can be buried in the ambient noise. Moreover, the natural frequencies are not affected if the crack is located at the nodes of modes or far from the location of inertia force and out-of-unbalance force that the disc generates in the shaft. To overcome these problems (or limitations), therefore, this study is conducted using the idea of the roving mass (roving disc in rotor case). The modal natural frequencies are used for the identification and location of cracks of various severities at different locations in both stationary and rotating shafts. The fundamental idea of the roving disc is that an extra inertia force is traversed along the cracked rotor to significantly excite the dynamics of the rotor near the crack locations. In other words, the location of a crack can be anywhere on the shaft which is contrary to the developed techniques in the available literature in which the location of a crack should be close to the disc. Along with the roving disc idea, three crack identification techniques are developed in this study using the natural frequencies of the cracked and intact shafts. Each of these techniques has its merits and limitations for crack identification. These techniques are implemented using data that are numerically generated by the finite element method based on the Bernoulli-Euler shaft elements and experimentally validated in the laboratory environment. The numerical and experimental results clearly demonstrate the capability of the suggested approach for the identification and location of cracks in stationary and rotating shafts.
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Neeli, Yeshwanth Sai. "Use of Photogrammetry Aided Damage Detection for Residual Strength Estimation of Corrosion Damaged Prestressed Concrete Bridge Girders." Thesis, Virginia Tech, 2020. http://hdl.handle.net/10919/99445.

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Corrosion damage reduces the load-carrying capacity of bridges which poses a threat to passenger safety. The objective of this research was to reduce the resources involved in conventional bridge inspections which are an important tool in the condition assessment of bridges and to help in determining if live load testing is necessary. This research proposes a framework to link semi-automated damage detection on prestressed concrete bridge girders with the estimation of their residual flexural capacity. The framework was implemented on four full-scale corrosion damaged girders from decommissioned bridges in Virginia. 3D point clouds of the girders reconstructed from images using Structure from Motion (SfM) approach were textured with images containing cracks detected at pixel level using a U-Net (Fully Convolutional Network). Spalls were detected by identifying the locations where normals associated with the points in the 3D point cloud deviated from being perpendicular to the reference directions chosen, by an amount greater than a threshold angle. 3D textured mesh models, overlaid with the detected cracks and spalls were used as 3D damage maps to determine reduced cross-sectional areas of prestressing strands to account for the corrosion damage as per the recommendations of Naito, Jones, and Hodgson (2011). Scaling them to real-world dimensions enabled the measurement of any required dimension, eliminating the need for physical contact. The flexural capacities of a box beam and an I-beam estimated using strain compatibility analysis were validated with the actual capacities at failure sections determined from four destructive tests conducted by Al Rufaydah (2020). Along with the reduction in the cross-sectional areas of strands, limiting the ultimate strain that heavily corroded strands can develop was explored as a possible way to improve the results of the analysis. Strain compatibility analysis was used to estimate the ultimate rupture strain, in the heavily corroded bottommost layer prestressing strands exposed before the box beam was tested. More research is required to associate each level of strand corrosion with an average ultimate strain at which the corroded strands rupture. This framework was found to give satisfactory estimates of the residual strength. Reduction in resources involved in current visual inspection practices and eliminating the need for physical access, make this approach worthwhile to be explored further to improve the output of each step in the proposed framework.
Master of Science
Corrosion damage is a major concern for bridges as it reduces their load carrying capacity. Bridge failures in the past have been attributed to corrosion damage. The risk associated with corrosion damage caused failures increases as the infrastructure ages. Many bridges across the world built forty to fifty years ago are now in a deteriorated condition and need to be repaired and retrofitted. Visual inspections to identify damage or deterioration on a bridge are very important to assess the condition of the bridge and determine the need for repairing or for posting weight restrictions for the vehicles that use the bridge. These inspections require close physical access to the hard-to-reach areas of the bridge for physically measuring the damage which involves many resources in the form of experienced engineers, skilled labor, equipment, time, and money. The safety of the personnel involved in the inspections is also a major concern. Nowadays, a lot of research is being done in using Unmanned Aerial Vehicles (UAVs) like drones for bridge inspections and in using artificial intelligence for the detection of cracks on the images of concrete and steel members. Girders or beams in a bridge are the primary longitudinal load carrying members. Concrete inherently is weak in tension. To address this problem, High Strength steel reinforcement (called prestressing steel or prestressing strands) in prestressed concrete beams is pre-loaded with a tensile force before the application of any loads so that the regions which will experience tension under the service loads would be subjected to a pre-compression to improve the performance of the beam and delay cracking. Spalls are a type of corrosion damage on concrete members where portions of concrete fall off (section loss) due to corrosion in the steel reinforcement, exposing the reinforcement to the environment which leads to accelerated corrosion causing a loss of cross-sectional area and ultimately, a rupture in the steel. If the process of detecting the damage (cracks, spalls, exposed or severed reinforcement, etc.) is automated, the next logical step that would add great value would be, to quantify the effect of the damage detected on the load carrying capacity of the bridges. Using a quantified estimate of the remaining capacity of a bridge, determined after accounting for the corrosion damage, informed decisions can be made about the measures to be taken. This research proposes a stepwise framework to forge a link between a semi-automated visual inspection and residual capacity evaluation of actual prestressed concrete bridge girders obtained from two bridges that have been removed from service in Virginia due to extensive deterioration. 3D point clouds represent an object as a set of points on its surface in three dimensional space. These point clouds can be constructed either using laser scanning or using Photogrammetry from images of the girders captured with a digital camera. In this research, 3D point clouds are reconstructed from sequences of overlapping images of the girders using an approach called Structure from Motion (SfM) which locates matched pixels present between consecutive images in the 3D space. Crack-like features were automatically detected and highlighted on the images of the girders that were used to build the 3D point clouds using artificial intelligence (Neural Network). The images with cracks highlighted were applied as texture to the surface mesh on the point cloud to transfer the detail, color, and realism present in the images to the 3D model. Spalls were detected on 3D point clouds based on the orientation of the normals associated with the points with respect to the reference directions. Point clouds and textured meshes of the girders were scaled to real-world dimensions facilitating the measurement of any required dimension on the point clouds, eliminating the need for physical contact in condition assessment. Any cracks or spalls that went unidentified in the damage detection were visible on the textured meshes of the girders improving the performance of the approach. 3D textured mesh models of the girders overlaid with the detected cracks and spalls were used as 3D damage maps in residual strength estimation. Cross-sectional slices were extracted from the dense point clouds at various sections along the length of each girder. The slices were overlaid on the cross-section drawings of the girders, and the prestressing strands affected due to the corrosion damage were identified. They were reduced in cross-sectional area to account for the corrosion damage as per the recommendations of Naito, Jones, and Hodgson (2011) and were used in the calculation of the ultimate moment capacity of the girders using an approach called strain compatibility analysis. Estimated residual capacities were compared to the actual capacities of the girders found from destructive tests conducted by Al Rufaydah (2020). Comparisons are presented for the failure sections in these tests and the results were analyzed to evaluate the effectiveness of this framework. More research is to be done to determine the factors causing rupture in prestressing strands with different degrees of corrosion. This framework was found to give satisfactory estimates of the residual strength. Reduction in resources involved in current visual inspection practices and eliminating the need for physical access, make this approach worthwhile to be explored further to improve the output of each step in the proposed framework.
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Alekseychuk, Oleksandr. "Detection of crack-like indications in digital radiography by global optimisation of a probabilistic estimation function." Doctoral thesis, Saechsische Landesbibliothek- Staats- und Universitaetsbibliothek Dresden, 2006. http://nbn-resolving.de/urn:nbn:de:swb:14-1154450084263-67485.

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A new algorithm for detection of longitudinal crack-like indications in radiographic images is developed in this work. Conventional local detection techniques give unsatisfactory results for this task due to the low signal to noise ratio (SNR ~ 1) of crack-like indications in radiographic images. The usage of global features of crack-like indications provides the necessary noise resistance, but this is connected with prohibitive computational complexities of detection and difficulties in a formal description of the indication shape. Conventionally, the excessive computational complexity of the solution is reduced by usage of heuristics. The heuristics to be used, are selected on a trial and error basis, are problem dependent and do not guarantee the optimal solution. Not following this way is a distinctive feature of the algorithm developed here. Instead, a global characteristic of crack-like indication (the estimation function) is used, whose maximum in the space of all possible positions, lengths and shapes can be found exactly, i.e. without any heuristics. The proposed estimation function is defined as a sum of a posteriori information gains about hypothesis of indication presence in each point along the whole hypothetical indication. The gain in the information about hypothesis of indication presence results from the analysis of the underlying image in the local area. Such an estimation function is theoretically justified and exhibits a desirable behaviour on changing signals. The developed algorithm is implemented in the C++ programming language and testet on synthetic as well as on real images. It delivers good results (high correct detection rate by given false alarm rate) which are comparable to the performance of trained human inspectors
In dieser Arbeit wurde ein neuer Algorithmus zur Detektion rissartiger Anzeigen in der digitalen Radiographie entwickelt. Klassische lokale Detektionsmethoden versagen wegen des geringen Signal-Rausch-Verhältnisses (von ca. 1) der Rissanzeigen in den Radiographien. Die notwendige Resistenz gegen Rauschen wird durch die Benutzung von globalen Merkmalen dieser Anzeigen erzielt. Das ist aber mit einem undurchführbaren Rechenaufwand sowie Problemen bei der formalen Beschreibung der Rissform verbunden. Üblicherweise wird ein übermäßiger Rechenaufwand bei der Lösung vergleichbarer Probleme durch Anwendung von Heuristisken reduziert. Dazu benuzte Heuristiken werden mit der Versuchs-und-Irrtums-Methode ermittelt, sind stark problemangepasst und können die optimale Lösung nicht garantieren. Das Besondere dieser Arbeit ist anderer Lösungsansatz, der jegliche Heuristik bei der Suche nach Rissanzeigen vermeidet. Ein globales wahrscheinlichkeitstheoretisches Merkmal, hier Schätzfunktion genannt, wird konstruiert, dessen Maximum unter allen möglichen Formen, Längen und Positionen der Rissanzeige exakt (d.h. ohne Einsatz jeglicher Heuristik) gefunden werden kann. Diese Schätzfunktion wird als die Summe des a posteriori Informationsgewinns bezüglich des Vorhandenseins eines Risses im jeden Punkt entlang der hypothetischen Rissanzeige definiert. Der Informationsgewinn entsteht durch die Überprüfung der Hypothese der Rissanwesenheit anhand der vorhandenen Bildinformation. Eine so definierte Schätzfunktion ist theoretisch gerechtfertigt und besitzt die gewünschten Eigenschaften bei wechselnder Anzeigenintensität. Der Algorithmus wurde in der Programmiersprache C++ implementiert. Seine Detektionseigenschaften wurden sowohl mit simulierten als auch mit realen Bildern untersucht. Der Algorithmus liefert gute Ergenbise (hohe Detektionsrate bei einer vorgegebenen Fehlalarmrate), die jeweils vergleichbar mit den Ergebnissen trainierter menschlicher Auswerter sind
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Alekseychuk, Oleksandr. "Detection of crack-like indications in digital radiography by global optimisation of a probabilistic estimation function." Doctoral thesis, Technische Universität Dresden, 2005. https://tud.qucosa.de/id/qucosa%3A24919.

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A new algorithm for detection of longitudinal crack-like indications in radiographic images is developed in this work. Conventional local detection techniques give unsatisfactory results for this task due to the low signal to noise ratio (SNR ~ 1) of crack-like indications in radiographic images. The usage of global features of crack-like indications provides the necessary noise resistance, but this is connected with prohibitive computational complexities of detection and difficulties in a formal description of the indication shape. Conventionally, the excessive computational complexity of the solution is reduced by usage of heuristics. The heuristics to be used, are selected on a trial and error basis, are problem dependent and do not guarantee the optimal solution. Not following this way is a distinctive feature of the algorithm developed here. Instead, a global characteristic of crack-like indication (the estimation function) is used, whose maximum in the space of all possible positions, lengths and shapes can be found exactly, i.e. without any heuristics. The proposed estimation function is defined as a sum of a posteriori information gains about hypothesis of indication presence in each point along the whole hypothetical indication. The gain in the information about hypothesis of indication presence results from the analysis of the underlying image in the local area. Such an estimation function is theoretically justified and exhibits a desirable behaviour on changing signals. The developed algorithm is implemented in the C++ programming language and testet on synthetic as well as on real images. It delivers good results (high correct detection rate by given false alarm rate) which are comparable to the performance of trained human inspectors.
In dieser Arbeit wurde ein neuer Algorithmus zur Detektion rissartiger Anzeigen in der digitalen Radiographie entwickelt. Klassische lokale Detektionsmethoden versagen wegen des geringen Signal-Rausch-Verhältnisses (von ca. 1) der Rissanzeigen in den Radiographien. Die notwendige Resistenz gegen Rauschen wird durch die Benutzung von globalen Merkmalen dieser Anzeigen erzielt. Das ist aber mit einem undurchführbaren Rechenaufwand sowie Problemen bei der formalen Beschreibung der Rissform verbunden. Üblicherweise wird ein übermäßiger Rechenaufwand bei der Lösung vergleichbarer Probleme durch Anwendung von Heuristisken reduziert. Dazu benuzte Heuristiken werden mit der Versuchs-und-Irrtums-Methode ermittelt, sind stark problemangepasst und können die optimale Lösung nicht garantieren. Das Besondere dieser Arbeit ist anderer Lösungsansatz, der jegliche Heuristik bei der Suche nach Rissanzeigen vermeidet. Ein globales wahrscheinlichkeitstheoretisches Merkmal, hier Schätzfunktion genannt, wird konstruiert, dessen Maximum unter allen möglichen Formen, Längen und Positionen der Rissanzeige exakt (d.h. ohne Einsatz jeglicher Heuristik) gefunden werden kann. Diese Schätzfunktion wird als die Summe des a posteriori Informationsgewinns bezüglich des Vorhandenseins eines Risses im jeden Punkt entlang der hypothetischen Rissanzeige definiert. Der Informationsgewinn entsteht durch die Überprüfung der Hypothese der Rissanwesenheit anhand der vorhandenen Bildinformation. Eine so definierte Schätzfunktion ist theoretisch gerechtfertigt und besitzt die gewünschten Eigenschaften bei wechselnder Anzeigenintensität. Der Algorithmus wurde in der Programmiersprache C++ implementiert. Seine Detektionseigenschaften wurden sowohl mit simulierten als auch mit realen Bildern untersucht. Der Algorithmus liefert gute Ergenbise (hohe Detektionsrate bei einer vorgegebenen Fehlalarmrate), die jeweils vergleichbar mit den Ergebnissen trainierter menschlicher Auswerter sind.
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Book chapters on the topic "Dynamic crack detection with photogrammetry"

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Mohammed, Omar D., Matti Rantatalo, and Jan-Olov Aidanpää. "Dynamic Modelling of Gear System with Gyroscopic Effect and Crack Detection Analysis." In Proceedings of the 9th IFToMM International Conference on Rotor Dynamics, 1303–14. Cham: Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-06590-8_106.

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de Oliveira, Lucas Rangel, and Gilberto Pechoto de Melo. "Crack Detection and Dynamic Analysis of a Cracked Rotor with Soft Bearings Using Different Methods of Solution." In Mechanisms and Machine Science, 3–17. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-99268-6_1.

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Han, X., and G. R. Liu. "Computational Inverse Techniques for Crack Detection Using Dynamic Responses." In Inverse Problems in Engineering Mechanics IV, 167–73. Elsevier, 2003. http://dx.doi.org/10.1016/b978-008044268-6/50022-3.

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Ranjan, Rajeev. "Dynamic Behaviour and Crack Detection of a Multi Cracked Rotating Shaft using Adaptive Neuro-Fuzzy-Inference System." In Fuzzy Systems, 1540–51. IGI Global, 2017. http://dx.doi.org/10.4018/978-1-5225-1908-9.ch062.

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The presence of crack changes the physical characteristics of a structure which in turn alter its dynamic response characteristics. So it is important to understand dynamics of cracked structures. Crack depth and location are the main parameters influencing the vibration characteristics of the rotating shaft. In the present study, a technique based on the measurement of change of natural frequencies has been employed to detect the multiple cracks in rotating shaft. The model of shaft was generated using Finite Element Method. In Finite Element Analysis, the natural frequency of the shaft was calculated by modal analysis using the software ANSYS. The Numerical data were obtained from FEA, then used to train through Adaptive Neuro-Fuzzy-Inference System. Then simulations were carried out to test the performance and accuracy of the trained networks. The simulation results show that the proposed ANFIS estimate the locations and depth of cracks precisely.
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Conference papers on the topic "Dynamic crack detection with photogrammetry"

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Peng, Jian-Ping, Jian-Ji Fu, Jian-Ming Zhao, Xiang Zhang, and Hui Yin. "Dynamic Detection of Rail Surface Crack Based on ACFM." In 2020 IEEE Far East NDT New Technology & Application Forum (FENDT). IEEE, 2020. http://dx.doi.org/10.1109/fendt50467.2020.9337521.

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Rabinovich, Daniel, Dan Givoli, and Shmuel Vigdergauz. "Framework for Flaw Detection: Application to Dynamic Crack Detection in Flat Membranes." In ASME 2008 9th Biennial Conference on Engineering Systems Design and Analysis. ASMEDC, 2008. http://dx.doi.org/10.1115/esda2008-59086.

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A computational framework is developed for the detection of flaws in flexible structures. The framework is based on posing the detection problem as an inverse problem, which requires the solution of many forward problems. Each forward problem is associated with a known flaw; an appropriate cost functional evaluates the quality of each candidate flaw based on the solution of the corresponding forward problem. On the higher level, the inverse problem is solved by a global optimization algorithm. The performance of the computational framework is evaluated by considering the detectability of various types of flaws. In the present context detectability is defined by introducing a measure of the distance between the sought flaw and trial flaws in the space of the parameters characterizing the configuration of the flaw. The framework is applied to crack detection in flat membranes subjected to time-harmonic and transient excitations. The detectability of cracks is compared for these two cases.
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Zhang, Zhao-de, Yong-he Xie, and De-yu Wang. "Crack Detection in Offshore Structures Using Dynamic Characteristics and Wavelet Transform." In ASME 2009 28th International Conference on Ocean, Offshore and Arctic Engineering. ASMEDC, 2009. http://dx.doi.org/10.1115/omae2009-79647.

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Dynamic parameters of offshore structures, such as frequencies, modal shapes, modal strain energy (MSE) and frequency response functions (FRF) are numerically and experimentally studied to detect the crack in the structures. A 3-pile and a 4-pile platform are analyzed. And a model of the 3-pile platform has been constructed for the experimental verification. When a crack occurs, the parameters of the structure will change. The shift of these parameters may be applied to identify the crack, the location and even the crack magnitude. Wavelet transform can be employed to find the singularity of the signal, so as to predict the early crack. The dynamic parameters due to mass change are also evaluated.
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Meng, G., and Eric J. Hahn. "Dynamic Response of a Cracked Rotor With Some Comments on Crack Detection." In ASME 1994 International Gas Turbine and Aeroengine Congress and Exposition. American Society of Mechanical Engineers, 1994. http://dx.doi.org/10.1115/94-gt-029.

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By considering time dependent terms as external excitation forces, the approximate dynamic response of a cracked horizontal rotor is analysed theoretically and numerically. The solution is good for small cracks and small vibrations in the stable operating range. For each steady state harmonic component the forward and backward whirl amplitudes, the shape and orientation of the elliptic orbit and the amplitude and phase of the response signals arc analysed, taking into account the effect of crack size, crack location, rotor speed and unbalance. It is found that the crack causes backward whirl, the amplitude of which increases with the crack. For a cracked rotor, the response orbit for each harmonic component is an ellipse, the shape and orientation of which depends on the crack size. The influence of the crack on the synchronous response of the system can be regarded as an additional unbalance whereupon, depending on the speed and the crack location, the response amplitude differs from that of the uncracked rotor. The nonsynchronous response provides evidence of crack in the sub-critical range, but is too small to be detected in the supercritical range. Possibilities for crack detection over the full speed range include the additional average (the constant) response component, the backward whirl of the response, the ellipticity of the orbit, the angle between the major axis and the vertical axis and the phase angle difference between vertical and horizontal vibration signals.
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Green, Itzhak, and Cody Casey. "Crack Detection in a Rotor Dynamic System by Vibration Monitoring: Part I — Analysis." In ASME Turbo Expo 2003, collocated with the 2003 International Joint Power Generation Conference. ASMEDC, 2003. http://dx.doi.org/10.1115/gt2003-38659.

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Many practical rotor dynamic systems contain shaft/rotor elements that are highly susceptible to transverse cross-sectional cracks due to fatigue. The early detection of mechanical malfunction that can be provided by an effective vibration monitoring system is essential. Two theoretical analyses, global and local asymmetry crack models, are utilized to identify characteristics of the system response that may be directly attributed to the presence of a transverse crack in a rotating shaft. A model consisting of an overhung whirling rotor is utilized to match an experimental test rig. A 2X harmonic component of the system response is shown to be the primary response characteristic resulting from the introduction of a crack. Once the unique characteristics of the system response are identified, they serve then as target observations for the monitoring system.
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Yuan, Peilong, Lisha Huo, Tommaso Seresini, Yang Liu, Sevilia Sunetchiieva, Helge Pfeiffer, Martine Wevers, and Christ Glorieux. "Laser ultrasonic inspection for crack detection in a rotating tube under dynamic load." In 2019 International Congress on Ultrasonics. ASA, 2019. http://dx.doi.org/10.1121/2.0001128.

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Shi-liang Lv and Shao-hua Guo. "Study on the dynamic behavior of thickness-stretch piezoelectric actuators used in crack detection." In 2009 Symposium on Piezoelectricity, Acoustic Waves, and Device Applications (SPAWDA 2009). IEEE, 2009. http://dx.doi.org/10.1109/spawda.2009.5428945.

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Varney, Philip, and Itzhak Green. "Crack Detection in a Rotor Dynamic System by Vibration Monitoring: Analysis and Experimental Results." In ASME/STLE 2012 International Joint Tribology Conference. American Society of Mechanical Engineers, 2012. http://dx.doi.org/10.1115/ijtc2012-61076.

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As the power to weight ratio demand on rotordynamic systems increases, susceptibility to transverse fatigue cracking of the shaft increases as well. The ability to detect cracks in an early stage of progression is imperative for minimizing off-line repair time. A vibration monitoring system proposed prior is developed herein, employing the 2X harmonic response component of the rotor tilt as a signature indicating a transverse shaft crack. To effectively capture the 2X response, the crack model must include the local nature of the crack, the depth of the crack, and the stiffness asymmetry inducing the gravity-forced 2X harmonic response. The transfer matrix technique is well-suited to incorporate these crack attributes due to its modular nature. Two transfer matrix models are proposed to predict the 2X harmonic response. The first model applies local crack flexibility coefficients determined using the strain energy release rate, while the second incorporates the crack as a rectangular notch to emulate a manufactured crack used in the experiments. Analytic results are then compared to experimental measurement of the rotor tilt gleaned from an overhung rotor test rig originally designed to test seal face dynamics. The test rig is discussed, and experimental 2X harmonic amplitudes of the rotor tilt are provided for shafts containing manufactured cracks of depths between zero and 40 percent.
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Avila, Manuel, Stephane Begot, Florent Duculty, and Tien Sy Nguyen. "2D image based road pavement crack detection by calculating minimal paths and dynamic programming." In 2014 IEEE International Conference on Image Processing (ICIP). IEEE, 2014. http://dx.doi.org/10.1109/icip.2014.7025157.

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Ali, Rahmat, Jiangyu Zeng, and Young-Jin Cha. "Deep learning-based crack detection in a concrete tunnel structure using multispectral dynamic imaging." In Smart Structures and NDE for Industry 4.0, Smart Cities, and Energy Systems, edited by Kerrie Gath and Norbert G. Meyendorf. SPIE, 2020. http://dx.doi.org/10.1117/12.2557900.

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Reports on the topic "Dynamic crack detection with photogrammetry"

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Berney, Ernest, Naveen Ganesh, Andrew Ward, J. Newman, and John Rushing. Methodology for remote assessment of pavement distresses from point cloud analysis. Engineer Research and Development Center (U.S.), April 2021. http://dx.doi.org/10.21079/11681/40401.

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The ability to remotely assess road and airfield pavement condition is critical to dynamic basing, contingency deployment, convoy entry and sustainment, and post-attack reconnaissance. Current Army processes to evaluate surface condition are time-consuming and require Soldier presence. Recent developments in the area of photogrammetry and light detection and ranging (LiDAR) enable rapid generation of three-dimensional point cloud models of the pavement surface. Point clouds were generated from data collected on a series of asphalt, concrete, and unsurfaced pavements using ground- and aerial-based sensors. ERDC-developed algorithms automatically discretize the pavement surface into cross- and grid-based sections to identify physical surface distresses such as depressions, ruts, and cracks. Depressions can be sized from the point-to-point distances bounding each depression, and surface roughness is determined based on the point heights along a given cross section. Noted distresses are exported to a distress map file containing only the distress points and their locations for later visualization and quality control along with classification and quantification. Further research and automation into point cloud analysis is ongoing with the goal of enabling Soldiers with limited training the capability to rapidly assess pavement surface condition from a remote platform.
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