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Academic literature on the topic 'Rupture detection'

Author: Grafiati

Published: 25 May 2024

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Journal articles on the topic "Rupture detection"

Charnock, Mark. "Ultrasound Assessment of an Isolated Rupture of the Medial Bundle of a Bifid Distal Biceps Tendon." Journal of Medical Ultrasound 31, no. 4 (October 7, 2022): 323–26. http://dx.doi.org/10.4103/jmu.jmu_45_22.

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Abstract This case study describes a patient with a clinically ruptured distal biceps tendon, with ultrasound detecting an isolated rupture of the medial bundle of a bifid distal biceps tendon. A 45-year-old male presented to the accident and emergency department with a week-old history of a right elbow injury. The ultrasound scan demonstrated a hypoechoic, corrugated distal biceps tendon with a tendon stump close to the radial tuberosity insertion in keeping with a rupture. However, a small caliber accessory or bifid distal biceps tendon was also identified and was intact. Typically, distal biceps tendon ruptures occur following a traumatic event with most detected clinically although imaging is required to confirm the diagnosis. Ultrasound is utilized to assess these injuries, and several different techniques or approaches are described in the literature. A combination of these approaches is required to make an accurate diagnosis. Detection of bifid distal biceps tendons is important for patient management, especially if a surgical repair is considered. This case highlights the anatomical variant of a bifid distal biceps tendon, which was ruptured clinically. The ultrasound diagnosis of distal biceps tendon ruptures can be challenging, especially when there is limited tendon retraction. This case also demonstrated the importance of dynamic ultrasound in the assessment of tendon ruptures.

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Xing, Liang, Haibo Long, Rui Bo, Xue Gou, Yan He, and Xing Peng. "A Computational Model of Blood D-Dimer, Cystatin C, and CRP Levels Predicts the Risk of Intracranial Aneurysms and their Rupture." Computational Intelligence and Neuroscience 2022 (November 18, 2022): 1–10. http://dx.doi.org/10.1155/2022/2216509.

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Objective. The aim of this study is to construct a computational model of blood D-dimer, cystatin C, and CRP levels and to predict the risk of intracranial aneurysms and their rupture. Methods. A total of 69 intracranial aneurysms patients were selected as the case group, including 28 cases in the ruptured group and 41 cases in the unruptured group. Another 64 non-intracranial aneurysm patients were selected as the control group. The detection results of serum D-dimer, cystatin C, and CRP were collected. The logistic regression computational model was used to analyze the occurrence and risk factors of intracranial aneurysms. The receiver operating curves (ROC) of serum D-dimer, cystatin C, and C reactive protein (CRP) levels for predicting intracranial aneurysms and their rupture were drawn, and the area under the curve (AUC), sensitivity, and specificity were calculated. Results. The serum levels of D-dimer, cystatin C, and CRP in patients with intracranial aneurysms were significantly higher than those in the control group and the differences were statistically significant P < 0.05 . The serum levels of D-dimer, cystatin C, and CRP in patients with ruptured intracranial aneurysms were higher than those in patients with unruptured intracranial aneurysms, and the differences were also statistically significant P < 0.05 . The combined detection of serum D-dimer, cystatin C, and CRP levels has a higher AUC (0.9014) for predicting intracranial aneurysms and higher AUC (0.9412) for predicting ruptured intracranial aneurysms than D-dimer (0.7118 and 0.8750, respectively), cystatin C (0.6489 and 0.6180, respectively), and CRP (0.7764 and 0.6551, respectively) independent detection; the combined detection had a sensitivity of 93.75% and 87.80 for predicting the occurrence and rupture of intracranial aneurysms, and the specificity was 68.12% and 92.86%, respectively. Conclusion. The combined detection of serum D-dimer, cystatin C, and CRP levels is a very valuable indicator for predicting the occurrence and rupture of intracranial aneurysms, and combined detection can provide scientific evidence-based guidance for clinical prediction of the occurrence and rupture of intracranial aneurysms.

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Künsch, Christophe, Lukas Fürer, Martin Steppan, Nathalie Schenk, Kathrin Blum, Michael Kaess, Julian Koenig, Klaus Schmeck, and Ronan Zimmermann. "Withdrawal ruptures in adolescents with borderline personality disorder psychotherapy are marked by increased speech pauses–can minimal responses be automatically detected?" PLOS ONE 18, no. 1 (January 17, 2023): e0280329. http://dx.doi.org/10.1371/journal.pone.0280329.

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Alliance ruptures of the withdrawal type are prevalent in adolescents with borderline personality disorder (BPD). Longer speech pauses are negatively perceived by these patients. Safran and Muran’s rupture model is promising but its application is very work intensive. This workload makes research costly and limits clinical usage. We hypothesised that pauses can be used to automatically detect one of the markers of the rupture model i.e. the minimal response marker. Additionally, the association of withdrawal ruptures with pauses was investigated. A total of 516 ruptures occurring in 242 psychotherapy sessions collected in 22 psychotherapies of adolescent patients with BPD and subthreshold BPD were investigated. Trained observers detected ruptures based on video and audio recordings. In contrast, pauses were automatically marked in the audio-recordings of the psychotherapy sessions and automatic speaker diarisation was used to determine the speaker-switching patterns in which the pauses occur. A random forest classifier detected time frames in which ruptures with the minimal response marker occurred based on the quantity of pauses. Performance was very good with an area under the ROC curve of 0.89. Pauses which were both preceded and followed by therapist speech were the most important predictors for minimal response ruptures. Research costs can be reduced by using machine learning techniques instead of manual rating for rupture detection. In combination with other video and audio derived features like movement analysis or automatic facial emotion detection, more complete rupture detection might be possible in the future. These innovative machine learning techniques help to narrow down the mechanisms of change of psychotherapy, here specifically of the therapeutic alliance. They might also be used to technologically augment psychotherapy training and supervision.

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Dupont, Stefan A., Giuseppe Lanzino, Eelco F. M. Wijdicks, and Alejandro A. Rabinstein. "The use of clinical and routine imaging data to differentiate between aneurysmal and nonaneurysmal subarachnoid hemorrhage prior to angiography." Journal of Neurosurgery 113, no. 4 (October 2010): 790–94. http://dx.doi.org/10.3171/2010.4.jns091932.

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Object In this study, the authors' goal was to minimize false-negative results in the detection of ruptured cerebral aneurysms. Methods The authors retrospectively reviewed the clinical and radiological information in consecutive adult patients admitted with acute subarachnoid hemorrhage (SAH) to their hospital between January 1, 2002, and January 1, 2008. Patients were grouped based on the presence or absence of a ruptured aneurysm, which was detected by catheter angiography. Multivariate logistic regression analysis was used to identify factors predicting detection of aneurysmal rupture by angiography. Results The authors identified 199 patients (121 women [61%]). A ruptured aneurysm was detected in 167 patients (84%). In multivariate analysis, loss of consciousness at the onset of SAH was a strong predictive factor associated with detection of a ruptured aneurysm on subsequent angiography (OR > 100, p = 0.0002). The positive predictive value of loss of consciousness at the onset of SAH for detection of a ruptured aneurysm was 100%. Conclusions Loss of consciousness at the onset of SAH is highly predictive of aneurysm rupture. A negative CT angiography study in these patients may be a false result, and a high-quality catheter angiography should be performed.

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Wada, Kojiro, Hirohiko Arimoto, Hidenori Ohkawa, Toshiki Shirotani, Yohsitaro Matsushita, and Takashi Takahara. "Usefulness of Preoperative Three-Dimensional Computed Tomographic Angiography With Two-Dimensional Computed Tomographic Imaging for Rupture Point Detection of Middle Cerebral Artery Aneurysms." Operative Neurosurgery 62, suppl_1 (March 1, 2008): ONS126—ONS133. http://dx.doi.org/10.1227/01.neu.0000317382.45691.1a.

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Abstract Objective: We report the technique of three-dimensional computed tomographic (CT) angiography with a two-dimensional CT image aiding in the early operation of ruptured middle cerebral artery aneurysms. This combined image allows the prediction of the rupture point in the aneurysm and may reduce the risk of rupture during early clipping surgery. Methods: The findings for 14 patients with 14 middle cerebral artery ruptured aneurysms who underwent subsequent early clipping were analyzed. The average aneurysm size was 8.5 mm, and there were two large and one giant aneurysms. CT examinations were performed by means of a multidetector CT scanner (Aquilion M16; Toshiba Medical Systems, Tokyo, Japan) and reconstructed with a workstation (ZIO M900 QUADRA; Amin Co., Ltd., Tokyo, Japan). We constructed an operating view through three-dimensional CT angiography for a lateral transsylvian approach with a two-dimensional CT image (nonshaded volume-rendering image), which was perpendicular to the direction of the surgical approach. Using this combined image, we predicted the rupture point of the aneurysm and successfully performed clipping surgery through a lateral transsylvian approach. Rupture points were confirmed at the time of surgery. Rupture points of 13 out of 14 aneurysms appeared as we expected, but one differed; all aneurysms were successfully clipped. Thirteen of the 14 patients could be clipped without rupture at surgery, but the remaining patient experienced rupture just after craniotomy. Conclusion: The combination of three-dimensional CT angiography and two-dimensional CT images may help improve the surgical outcome by indicating aneurysmal rupture points, leading to the prevention of rupture.

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Nenezić, Dragoslav, and Igor Kocijancic. "The value of the sagittal-oblique MRI technique for injuries of the anterior cruciate ligament in the knee." Radiology and Oncology 47, no. 1 (January 1, 2013): 19–25. http://dx.doi.org/10.2478/raon-2013-0006.

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Abstract Background. Complete rupture of the anterior cruciate ligament (ACL) does not represent a diagnostic problem for the standard magnetic resonance (MR) protocol of the knee. Lower accuracy of the standard MR protocol for partial rupture of the ACL can be improved by using additional, dedicated MR techniques. The study goal was to draw a comparison between sagittal-oblique MR technique of ACL imaging versus flexion MR technique of ACL imaging and, versus ACL imaging obtained with standard MR protocol of the knee. Patients and methods. In this prospective study we included 149 patients who were referred to magnetic resonance imaging (MRI) examination due to knee soft tissues trauma during 12 months period. MRI signs of ACL trauma, especially detection of partial tears, number of slices per technique showing the whole ACL, duration of applied additional protocols, and reproducibility of examination were analysed. Results. Accuracy of standard MRI protocol of the knee comparing to both additional techniques is identical in detection of a complete ACL rupture. Presentations of the partial ruptures of ACL using flexion technique and sagittaloblique technique were more sensitive (p<0.001) than presentation using standard MR protocol. There was no statistically significant difference between MRI detection of the ruptured ACL between additional techniques (p> 0.65). Sagittal-oblique technique provides a higher number of MRI slices showing the whole course of the ACL and requires a shorter scan time compared to flexion technique (p<0.001). Conclusions. Both additional techniques (flexion and sagittal-oblique) are just as precise as the standard MR protocol for the evaluation of a complete rupture of the ACL, so they should be used in cases of suspicion of partial rupture of the ACL. Our study showed sagittal-oblique technique was superior, because it did not depend on patient’s ability to exactly repeat the same external rotation if standard MR protocol was used or to repeat exactly the same flexion in flexion MR technique in further MR examinations. Sagittal-oblique technique does not require the patient’s knee to be repositioned, which makes this technique faster. We propose this technique in addition to the standard MR protocol for detection of partial ACL tears.

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Dowden, Richard V. "Detection of Gel Implant Rupture." Plastic and Reconstructive Surgery 91, no. 3 (March 1993): 548–50. http://dx.doi.org/10.1097/00006534-199303000-00025.

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Ng, Beng Kwang, Pei Shan Lim, Mohamad Nasir Shafiee, Nur Azurah Abdul Ghani, Nor Azlin Mohamed Ismail, Mohd Hashim Omar, and Muhammad Abdul Jamil Muhammad Yassin. "Comparison between Amnisure Placental Alpha Microglobulin-1 Rapid Immunoassay and Standard Diagnostic Methods for Detection of Rupture of Membranes." BioMed Research International 2013 (2013): 1–7. http://dx.doi.org/10.1155/2013/587438.

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Objective. To determine the diagnostic accuracy of placental alpha microglobulin-1 assay and standard diagnostic methods for detecting rupture of membrane.Study Design. Prospective diagnostic study, between June 2011 to November 2011 at a tertiary centre. Initial evaluation included both the standard diagnostic methods for rupture of membranes and placental alpha microglobulin-1 immunoassay. The actual rupture of membranes was diagnosed on review of the medical records after delivery (absence of membrane or a positive pad chart).Main Outcome Measures. Placental alpha microglobulin-1 immunoassay and standard diagnostic methods for diagnosis of rupture of membrane.Results. A total of 211 patients were recruited. At initial presentation, 187 patients (88.6%) had ruptured membranes, while 24 patients (11.4%) had intact membranes. Placental alpha microglobulin-1 immunoassay confirmed rupture of membranes at initial presentation with a sensitivity of 95.7% (179 of 187), specificity of 100% (24 of 24), positive predictive value of 100% (179 of 179), and negative predictive value of 75.0% (24 of 32). By comparison, the conventional standard diagnostic methods had a sensitivity of 78.1% (146 of 187), specificity of 100% (24 of 24), positive predictive value of 100% (146 of 146), and negative predictive value of 36.9% (24 of 65) in diagnosing rupture of membrane.Conclusion. Placental alpha-microglobulin-1 immunoassay is a rapid and accurate method for confirming the diagnosis of rupture of membrane. It was superior to conventional standard diagnostic methods (pooling, nitrazine, and ferning), the nitrazine test alone or fern test alone.

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Jukovic, Mirela, Tijana Kokovic, Dragan Nikolic, Dalibor Ilic, and Viktor Till. "Lower back pain - silent symptom of chronic infrarenal abdominal aneurysm rupture." Medical review 69, no. 3-4 (2016): 115–17. http://dx.doi.org/10.2298/mpns1604115j.

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Introduction. The rupture of infrarenal abdominal aortic aneurysm is a surgical emergency condition with a high rate of mortality before the patients arrive at hospital. The signs and symptoms of abdominal aortic aneurysm rupture into the retroperitoneal cavity are pulsatile mass, abdominal pain, hypotension and shock, but sometimes silent symptoms also hide a dangerous and life threatening condition, such as chronic aneurysm rupture of abdominal aorta into the retroperitoneal cavity. Case Report. We present a patient having had the lower back pain for 4 months, which had been recognized and treated as lumbar ischialgia but which was eventually diagnosed to be chronic infrarenal abdominal aortic aneurysm rupture by computed tomography angiography. The surgical intervention was successful and the patient was discharged from hospital after 6 days without any clinical complications. Preoperative imaging by computed tomography angiography of ruptured abdominal aortic aneurysm is highly sensitive for detection of several specific signs for rupture. This condition leads to urgent vascular surgery.

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Harris, K. M., M. A. Ganott, K. C. Shestak, H. W. Losken, and H. Tobon. "Silicone implant rupture: detection with US." Radiology 187, no. 3 (June 1993): 761–68. http://dx.doi.org/10.1148/radiology.187.3.8497626.

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Dissertations / Theses on the topic "Rupture detection"

Fu, Jiyuan. "Using Thermographic Image Analysis in Detection of Canine Anterior Cruciate Ligament Rupture Disease." Thesis, Southern Illinois University at Edwardsville, 2015. http://pqdtopen.proquest.com/#viewpdf?dispub=1582920.

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Anterior cruciate ligament (ACL) rupture is a common trauma which frequently happens in overweight dogs. Veterinarians use MRI (Magnetic resonance imaging) as the standard method to diagnose this disease. However MRI is expensive and time-consuming. Therefore, it is necessary to find an alternative diagnostic method. In this research, thermographic images are utilized as a prescreening tools for the detection of ACL rupture disease. Meanwhile, a quantitative comparison is made of new feature vectors based on Gabor filters with different frequencies and orientations.

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Sim, Alisia Mara. "Detection of calcification in atherosclerotic plaques using optical imaging." Thesis, University of Edinburgh, 2018. http://hdl.handle.net/1842/33151.

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PET imaging, using the bone tracer Na18F, allows the non-invasive location of atherosclerotic plaques that are at risk of rupture. However, the spatial resolution of PET is only 4-5 mm, limiting the mechanistic information this technique can provide. In this thesis, the use of fluorescence and Raman imaging to elucidate the mechanism of micro-calcification within atherosclerotic plaques has been investigated. A number of fluorescent probes to detect fluoride and calcium have been synthesised. One of the fluoride probes has been shown to be selective for fluoride however, the concentration of fluoride required to activate the probe is order of magnitudes higher than the amount of Na18F used for PET imaging making it problematic to use for future studies. On the other hand, a calcium probe has been shown to: selectively bind to hydroxyapatite (HAP); permit visualisation and quantification of HAP in both vascular and bone cell models; and effectively stain cultured aortic sections and whole mouse aorta for OPT imaging. Building on these preliminary data, fluorescence imaging and immunohistochemistry (IHC) imaging of both healthy and atherosclerotic tissue that were previously subjected to PET imaging, were successfully carried out showing the ability of the probe to detect HAP in human vascular tissue. IHC staining for Osteoprotegerin (OPG) and Osteopontin (OPN), two bone proteins recently detected in vascular tissue, showed the co-localization of OPG with the probe. Conversely, the OPN was shown to localize in areas surrounding high OPG and probe signal. To determine the exact composition of vascular calcification, Raman spectroscopy was also used. It is believed that the biosynthetic pathway to HAP passes through a series of transitional states; each of these has different structural characteristics which can be studied using Raman spectroscopy. In particular, HAP has a strong characteristic Raman peak at 960 cm-1. An increase in HAP concentration has been detected by Raman in both calcified cell models and aortic sections. When human vascular tissue was analysed, an additional peak at 973 cm-1 was present suggesting the presence of whitlockite (WTK) in this tissue as well as HAP.

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Taillade, Thibault. "A new strategy for change detection in SAR time-series : application to target detection." Thesis, université Paris-Saclay, 2020. http://www.theses.fr/2020UPAST050.

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La détection de cibles telles que des navires ou des véhicules dans les images SAR (Synthetic Aperture radar) est un défi important pour la surveillance et la sécurité. Dans certains environnements tels que les zones urbaines, portuaires ou les forêts observées à basses fréquences radar, la détection de ces objets devient difficile en raison des propriétés de rétrodiffusion élevées de l'environnement. Pour résoudre ce problème, la détection de changement (CD) entre différentes images SAR permet de supprimer l'effet de l'environnement et ainsi une meilleur détection des cibles. Cependant, dans différents environnements à forte fréquentation, un chevauchement temporel des cibles peut se produire et génère une erreur d'interprétation possible car l'issue de la détection de changement repose sur une différence relative entre des objets de tailles ou de propriétés différentes. C'est un problème critique lorsque le but est de visualiser et d'obtenir le nombre d'objets à une acquisition donnée, dans les zones à fortes fréquentations comme les ports ou les zones urbaines. Idéalement, cette détection de changement devrait se réaliser entre une image constituée seulement de l'environnement et une image contenant les cibles d’intérêts. Grâce à l'accessibilité actuelle aux séries temporelles d'images SAR, nous proposons de générer une scène de référence (Frozen Background Image - FBR) qui n'est constituée que de l'environnement temporellement statique. La détection de changement entre une image SAR et cette image FBR vise donc a obtenir une map de détection des cibles éphémères présentes. Cette stratégie a été mise en œuvre pour la détection des navires en milieu portuaire et dans le contexte de véhicules cachés sous couvert forestier
The detection of targets such as ships or vehicles in SAR (Synthetic Aperture Radar) images is an essential challenge for surveillance and security purpose. In some environments such as urban areas, harbor areas or forest observed at low radar frequencies, detecting these objects becomes difficult due to the high backscattering properties of the surrounding background. To overcome this issue, change detection (CD) between SAR images enables to cancel the background and highlight successfully targets present within the scene. However, in several environments, a temporal overlapping of targets may occur and generates possible misinterpretation because the outcome relies on the relative change between objects of different sizes or properties. This is a critical issue when the purpose is to visualize and obtain the number of targets at a specific day in high attendance areas such as harbors or urban environments. Ideally, this change detection should occur between a target-free image and onewith possible objects of interest. With the current accessibility to SAR time-series, we propose to compute a frozen background reference (FBR) image that will consists only in the temporally static background. Performing change detection from this FBR image and any SAR image aim to highlight the presence of ephemeral targets. This strategy has been implemented for ship detection in harbor environment and in the context of vehicles hidden under foliage

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LAGRANGE, DOMINIQUE. "Estimation de la date et de l'amplitude d'une rupture conditionnellement a sa detection par une carte cusum." Paris, Institut national d'agronomie de Paris Grignon, 1997. http://www.theses.fr/1997INAP0045.

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Les cartes de controle sont des outils d'amelioration de la qualite des produits. Lorsque la carte de controle signale que le processus est hors-controle, cela signifie que le processus de production est deregle, cependant elle n'indique ni l'importance du dereglage ni quand il a commence. L'estimation de la date et de l'amplitude de la rupture revet donc un grand interet pratique : elle permet de savoir a partir de quand et de combien la production s'est deterioree et ainsi de prendre des decisions adequates. Le responsable de la qualite peut decider quelle partie de la production est suspecte, c'est a dire quelle partie a ete realisee dans des conditions de processus non standard. Au vu des proprietes d'optimalite asymptotique, nous nous sommes interesses au schema de surveillance de type cusum. Nous nous interessons a l'estimation de la date et de l'amplitude du dereglage sachant la detection d'une rupture par une carte cusum. Nous proposons deux methodes d'estimation de la date et de l'amplitude d'une rupture : la methode induite par la definition de la regle de decision cusum, et celle du maximum de vraisemblance. Nous etudions et comparons, pour ces deux methodes, les estimateurs de la date et de l'amplitude du dereglage apres qu'une carte cusum en ait detecte la presence. En posant l'hypothese de distribution gaussienne, nous comparons, par des simulations les estimateurs obtenus par les deux methodes en etudiant leur biais et leur ecart quadratique moyen. Nous determinons la distribution conditionnelle de l'estimateur cusum de la date du dereglage sachant sa detection par la carte cusum, ainsi que celle de l'estimateur de l'amplitude du dereglage, ainsi que leur marginale. Les densites de probabilite obtenues verifient des relations de recurrence qui se resolvent par des methodes numeriques. En posant l'hypothese de distribution gaussienne, nous obtenons de maniere theorique la distribution conditionnelle de l'estimateur du maximum de vraisemblance de la date du dereglage sachant sa detection par la carte cusum. Cependant, a cause de la complexite du domaine d'integration, nous avons eu recours a trois methodes d'integration numerique : la methode de monte-carlo, une variante de celle-ci, et une methode d'integration directe basee sur un maillage ; nous comparons ces methodes en etudiant leur vitesse de convergence. Compte tenu de la complexite des formules des distributions nous proposons une approche bayesienne empirique pour la construction de region hpd -credible de la date et de l'amplitude du dereglage et nous decrivons le logiciel que nous avons realise qui permet a un utilisateur de construire la region de confiance. Nous nous interessons ensuite au cas ou on dispose de plusieurs mesures simultanees sur le processus, il est interessant de tenir compte conjointement de toutes les informations. Nous proposons plusieurs strategies pour le faire et nous comparons leurs efficacites. Dans un dernier temps nous adaptons les resultats des distributions conditionnelles des estimateurs de la date et de l'amplitude d'une rupture dans le cas ou la carte de controle utilisee est une carte de type ewma ou ewma tronquee.

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Dahal, Rohini. "Bilateral Thermographic Image Comparison Software Tool for Pathology Detection in Canines with Application to Anterior Cruciate Ligament (ACL) Rupture." Thesis, Southern Illinois University at Edwardsville, 2017. http://pqdtopen.proquest.com/#viewpdf?dispub=10276314.

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Introduction: The bilaterally symmetry property in animals can be used to detect pathologies where body parts on both sides can be compared. For any pathological disorder, thermal patterns differ compared to the normal body parts. A software application for veterinary clinics is under development to input two thermograms of body parts on both sides, one normal and the other unknown, and the application compares them on the basis of extracted features and appropriate similarity and difference measures and outputs the likelihood of pathology. Previous research has been used to determine the appropriate image processing, feature extraction and comparison metrics to be used. The comparison metrics used are the vector inner product, Tanimoto, Euclidean, city block, Minkowski and maximum value metric. Also, results from experiments with comparison tests are used to derive a potential threshold values which will separate normal from abnormal images for a specific pathology.

Objectives: The main objective of this research is to build a comparison software tool application by combining the concepts of bilateral symmetrical property in animals and IR thermography that can be for prescreening in veterinary clinics.

Comparison Software Tool Development: The comparison software tool was developed for veterinary clinics as a prescreening tool for pathology detection using the concepts of thermography and bilateral symmetry property in animals. The software tool has a graphical user interface (GUI) that allows ease of use for the clinical technician. The technician inputs images or raw temperature data csv files and compares thermographic images of bilateral body parts. The software extracts features from the images and calculates the difference between the feature vectors with distance and/or similarity metrics. Based upon these metrics, the percentage deviation is calculated which provides the deviation of the unknown (test) image from the known image. The percentage deviation between the thermograms of the same body parts on either side provides an indication regarding the extent and impact of the disease [Poudel; 2015]. The previous research in veterinary thermography [Liu; 2012; Subedi; 2014, Fu; 2014, Poudel; 2015] has been combined with the real world veterinary clinical scenario to develop a software tool that can be helpful for researchers as well as for the clinical technicians in prescreening of pathologies.

Experimental Results and Discussion: Experiments were performed on ACL thermograms to determine a threshold that can separate normal and abnormal ACL images. 18-colored Meditherm images had poor results and could not suggest any threshold value. But results were positive for temperature remapped 256 gray level Meditherm images which suggested the 40% of percentage deviation could produce a separation. The total number of Normal - Normal pairs were greater than total number of Normal – Abnormal pairs below 40% deviation. Similarly, total number of Normal –Abnormal pairs of images were greater than total number of Normal – Normal pairs above 40%. This trend was consistent for Euclidean distance, maximum value distance and Minkowski distance for both texture distances of 6 and 10. The performance in terms of sensitivity and specificity was poor. The best sensitivity of 55% and best specificity of 67% was achieved. This indicates better results for predicting the absence of ACL rupture then actually finding the disease. In this case the software could be used by the clinician in conjunction with other diagnostic methods.

Conclusion: The Experiments, results and analysis show that the comparison software tool can be used in veterinary clinics for the pre-screening of diseases in canines and felines to estimate the extent and impact of the disease based upon the percentage deviation. However, more research is necessary to examine its efficacy for specific pathologies. Note that the software can be used by researchers to compare any two images of any formats. For ACL experimentation, there are indication that a threshold value is possible to separate normal from abnormal and the spectral, texture and spectral features suggested by researches [Subedi; 2014, Liu; 2012, Fu; 2014, Poudel; 2015] are not sufficient to determine that threshold with the given image database.

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Le, bars Batiste. "Event detection and structure inference for graph vectors." Thesis, université Paris-Saclay, 2021. http://www.theses.fr/2021UPASM003.

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Cette thèse aborde différents problèmes autour de l'analyse et la modélisation de signaux sur graphes, autrement dit des données vectorielles observées sur des graphes. Nous nous intéressons en particulier à deux tâches spécifique. La première est le problème de détection d'événements, c'est-à-dire la détection d'anomalies ou de ruptures, dans un ensemble de vecteurs sur graphes. La seconde tâche consiste en l'inférence de la structure de graphe sous-jacente aux vecteurs contenus dans un ensemble de données. Dans un premier temps notre travail est orienté vers l'application. Nous proposons une méthode pour détecter des pannes ou des défaillances d'antenne dans un réseau de télécommunication.La méthodologie proposée est conçue pour être efficace pour des réseaux de communication au sens large et tient implicitement compte de la structure sous-jacente des données. Dans un deuxième temps, une nouvelle méthode d'inférence de graphes dans le cadre du Graph Signal Processing est étudiée. Dans ce problème, des notions de régularité local et global, par rapport au graphe sous-jacent, sont imposées aux vecteurs. Enfin, nous proposons de combiner la tâche d'apprentissage des graphes avec le problème de détection de ruptures. Cette fois, un cadre probabiliste est considéré pour modéliser les vecteurs, supposés ainsi être distribués selon un certain champ aléatoire de Markov. Dans notre modélisation, le graphe sous-jacent aux données peut changer dans le temps et un point de rupture est détecté chaque fois qu'il change de manière significative
This thesis addresses different problems around the analysis and the modeling of graph signals i.e. vector data that are observed over graphs. In particular, we are interested in two tasks. The rst one is the problem of event detection, i.e. anomaly or changepoint detection, in a set of graph vectors. The second task concerns the inference of the graph structure underlying the observed graph vectors contained in a data set. At first, our work takes an application oriented aspect in which we propose a method for detecting antenna failures or breakdowns in a telecommunication network. The proposed approach is designed to be eective for communication networks in a broad sense and it implicitly takes into account the underlying graph structure of the data. In a second time, a new method for graph structure inference within the framework of Graph Signal Processing is investigated. In this problem, notions of both local and globalsmoothness, with respect to the underlying graph, are imposed to the vectors.Finally, we propose to combine the graph learning task with the change-point detection problem. This time, a probabilistic framework is considered to model the vectors, assumed to be distributed from a specifc Markov Random Field. In the considered modeling, the graph underlying the data is allowed to evolve in time and a change-point is actually detected whenever this graph changes significantly

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Do, Van Long. "Sequential detection and isolation of cyber-physical attacks on SCADA systems." Thesis, Troyes, 2015. http://www.theses.fr/2015TROY0032/document.

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Cette thèse s’inscrit dans le cadre du projet « SCALA » financé par l’ANR à travers le programme ANR-11-SECU-0005. Son objectif consiste à surveiller des systèmes de contrôle et d’acquisition de données (SCADA) contre des attaques cyber-physiques. Il s'agit de résoudre un problème de détection-localisation séquentielle de signaux transitoires dans des systèmes stochastiques et dynamiques en présence d'états inconnus et de bruits aléatoires. La solution proposée s'appuie sur une approche par redondance analytique composée de deux étapes : la génération de résidus, puis leur évaluation. Les résidus sont générés de deux façons distinctes, avec le filtre de Kalman ou par projection sur l’espace de parité. Ils sont ensuite évalués par des méthodes d’analyse séquentielle de rupture selon de nouveaux critères d’optimalité adaptés à la surveillance des systèmes à sécurité critique. Il s'agit donc de minimiser la pire probabilité de détection manquée sous la contrainte de niveaux acceptables pour la pire probabilité de fausse alarme et la pire probabilité de fausse localisation. Pour la tâche de détection, le problème d’optimisation est résolu dans deux cas : les paramètres du signal transitoire sont complètement connus ou seulement partiellement connus. Les propriétés statistiques des tests sous-optimaux obtenus sont analysées. Des résultats préliminaires pour la tâche de localisation sont également proposés. Les algorithmes développés sont appliqués à la détection et à la localisation d'actes malveillants dans un réseau d’eau potable
This PhD thesis is registered in the framework of the project “SCALA” which received financial support through the program ANR-11-SECU-0005. Its ultimate objective involves the on-line monitoring of Supervisory Control And Data Acquisition (SCADA) systems against cyber-physical attacks. The problem is formulated as the sequential detection and isolation of transient signals in stochastic-dynamical systems in the presence of unknown system states and random noises. It is solved by using the analytical redundancy approach consisting of two steps: residual generation and residual evaluation. The residuals are firstly generated by both Kalman filter and parity space approaches. They are then evaluated by using sequential analysis techniques taking into account certain criteria of optimality. However, these classical criteria are not adequate for the surveillance of safety-critical infrastructures. For such applications, it is suggested to minimize the worst-case probability of missed detection subject to acceptable levels on the worst-case probability of false alarm and false isolation. For the detection task, the optimization problem is formulated and solved in both scenarios: exactly and partially known parameters. The sub-optimal tests are obtained and their statistical properties are investigated. Preliminary results for the isolation task are also obtained. The proposed algorithms are applied to the detection and isolation of malicious attacks on a simple SCADA water network

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Davis, Elizabeth H. "Detection of rupture-repair sequences in patterns of alliance development the effects of client vs. therapist raters and therapist training status /." Ohio : Ohio University, 2005. http://www.ohiolink.edu/etd/view.cgi?ohiou1133405084.

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Davis, Elizabeth Helen. "Detection of Rupture-Repair Sequences in Patterns of Alliance Development: The Effects of Client vs. Therapist Raters and Therapist Training Status." Ohio University / OhioLINK, 2005. http://rave.ohiolink.edu/etdc/view?acc_num=ohiou1133405084.

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Allab, Nedjmeddine. "Détection d'anomalies et de ruptures dans les séries temporelles. Applications à la gestion de production de l'électricité." Thesis, Paris 6, 2016. http://www.theses.fr/2016PA066658.

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Continental est l'outil de référence utilisé par EDF pour la gestion d'électricité à long terme. il permet d'élaborer la stratégie d'exploitation du parc constitué de centrales réparties sur toute l'europe. l'outil simule sur chaque zone et chaque scénario plusieurs variables telles que la demande d'électricité, la quantité générée ainsi que les coûts associés. nos travaux de thèse ont pour objectif de fournir des méthodes d'analyse de ces données de production afin de faciliter leur étude et leur synthèse. nous récoltons un ensemble de problématiques auprès des utilisateurs de continental que nous tentons de résoudre à l'aide des technique de détection d'anomalies et de ruptures dans les séries temporelles
Continental is the main tool that edf uses for the long-term management of electricity. It elaborates the strategy exploitation of the electrical parc made up by power plants distributed all over europe. the tool simulates for each zone and each scenario several variables, such as the electricity demand, the generated quantity as well as the related costs. our works aim to provide methods to analyse the data of electricity production in order to ease their discovery and synthesis. we get a set of problmatics from the users of continental that we tent to solve through techniques of outliers and changepoints detection in time series

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Books on the topic "Rupture detection"

Lelic, Simon. Rupture. Oxford: ISIS Large Print, 2011.

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Coben, Harlan. Rupture de contrat. Paris: Le Grand livre du mois, 2003.

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Carpenter, Philip, Morgan Henrie, and R. Edward Nicholas. Pipeline Leak Detection Handbook. Elsevier Science & Technology Books, 2016.

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Pipeline Leak Detection Handbook. Elsevier Science & Technology Books, 2016.

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DeBruhl, Nanette D., and Nazanin Yaghmai. Breast Implants. Edited by Christoph I. Lee, Constance D. Lehman, and Lawrence W. Bassett. Oxford University Press, 2018. http://dx.doi.org/10.1093/med/9780190270261.003.0060.

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The presence of breast implants limits the amount of tissue that can be visualized on mammography and tomosynthesis. The proper mammographic positioning of the breasts of women with implants requires special training. More tissue can be visualized in women with sub-pectoral implants than in women with sub-glandular implants. Women with implants are recommended to have age-appropriate routine interval screening mammography for detection of cancer. If an implant rupture is suspected, ultrasound and MRI are used as adjunct imaging modalities. This chapter, appearing in the section on breast implants, reviews the key imaging and clinical features, imaging protocols and pitfalls, and management recommendations for breast implants. Topics discussed include types of implants, imaging findings of intact implants, and signs of ruptured implants, using mammography, ultrasound, and magnetic resonance imaging.

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Detecting Chinese Modernities: Rupture and Continuity in Modern Chinese Detective Fiction. BRILL, 2020.

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Rupture. Gallimard Education, 2012.

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Lelic, Simon. Rupture. Picador, 2010.

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Rupture. Picador, 2016.

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Lelic, Simon. Rupture. Picador, 2010.

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Book chapters on the topic "Rupture detection"

Jain, Kartik. "CADA Challenge: Rupture Risk Assessment Using Computational Fluid Dynamics." In Cerebral Aneurysm Detection, 75–86. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-72862-5_8.

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Ivantsits, Matthias, Leonid Goubergrits, Jan Brüning, Andreas Spuler, and Anja Hennemuth. "Intracranial Aneurysm Rupture Prediction with Computational Fluid Dynamics Point Clouds." In Cerebral Aneurysm Detection, 104–12. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-72862-5_11.

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Ivantsits, Matthias, Markus Huellebrand, Sebastian Kelle, Titus Kuehne, and Anja Hennemuth. "Intracranial Aneurysm Rupture Risk Estimation Utilizing Vessel-Graphs and Machine Learning." In Cerebral Aneurysm Detection, 93–103. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-72862-5_10.

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Azaïs, Romain, Anne Gégout-Petit, and Florine Greciet. "Rupture Detection in Fatigue Crack Propagation." In Statistical Inference for Piecewise-deterministic Markov Processes, 173–207. Hoboken, NJ, USA: John Wiley & Sons, Inc., 2018. http://dx.doi.org/10.1002/9781119507338.ch6.

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Liu, Yanfei, Yunqiao Yang, Yi Lin, Yuexiang Li, Dong Wei, Kai Ma, and Yefeng Zheng. "Cerebral Aneurysm Rupture Risk Estimation Using XGBoost and Fully Connected Neural Network." In Cerebral Aneurysm Detection, 87–92. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-72862-5_9.

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Doyle, Barry J., Timothy M. McGloughlin, Eamon G. Kavanagh, and Peter R. Hoskins. "From Detection to Rupture: A Serial Computational Fluid Dynamics Case Study of a Rapidly Expanding, Patient-Specific, Ruptured Abdominal Aortic Aneurysm." In Computational Biomechanics for Medicine, 53–68. New York, NY: Springer New York, 2014. http://dx.doi.org/10.1007/978-1-4939-0745-8_5.

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Yang, S. W., A. Widodo, W. Caesarendra, J. S. Oh, M. C. Shim, S. J. Kim, B. S. Yang, and W. H. Lee. "Support vector machine and discrete wavelet transform method for strip rupture detection based on transient current signal." In Engineering Asset Lifecycle Management, 671–78. London: Springer London, 2010. http://dx.doi.org/10.1007/978-0-85729-320-6_78.

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Schaefer, Pamela W., and Myriam Edjlali. "Nontraumatic Intracranial Hemorrhage." In IDKD Springer Series, 49–68. Cham: Springer Nature Switzerland, 2024. http://dx.doi.org/10.1007/978-3-031-50675-8_5.

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AbstractSpontaneous ICH is usually intraparenchymal or subarachnoid in location. Intraparenchymal hemorrhages, encompassing lobar or centrally located hematomas, have diverse underlying causes, with cerebral amyloid angiopathy, characterized by lobar hemorrhage, being the most common. Hypertension is the second most common cause with a predilection for the basal ganglia, pons, and cerebellum. Subarachnoid hemorrhage is linked to aneurysm rupture in 85% of cases. Other relatively common causes of spontaneous intracranial hemorrhage include hemorrhagic conversion of ischemic infarction, cerebral arteriovenous malformations, dural arteriovenous fistulas, venous sinus thrombosis, cavernous malformations, reversible cerebral vasoconstriction syndrome, coagulopathy, and underlying tumors.Computed tomography followed by CT angiography is used for initial assessment of spontaneous ICH. However, MRI is more sensitive than CT for the detection of ICH and plays an important role in their etiology characterization. In this paper, the authors present a logical approach to imaging spontaneous intracranial hemorrhage including identifying prognostic factors, determining etiology, and establishing treatment.

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Andrianov, Ivan K., M. Kara Balli, Miron S. Grinkrug, and Nikita A. Novgorodov. "Finite Element Calculation of the Limiting Pressure for Rupture of Capsules with an Active Substance in the Crack Detection System of Gas Turbine Blades." In Software Engineering Research in System Science, 757–68. Cham: Springer International Publishing, 2023. http://dx.doi.org/10.1007/978-3-031-35311-6_72.

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Hughes, J. R., and S. F. Byrne. "Detection of posterior ruptures in opaque media." In Documenta Ophthalmologica Proceedings Series, 333–42. Dordrecht: Springer Netherlands, 1987. http://dx.doi.org/10.1007/978-94-009-3315-6_54.

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Conference papers on the topic "Rupture detection"

Bowles, Edgar B., Thomas B. Morrow, Cecil R. Sparks, and John G. Gregor. "Gas Pipeline Rupture Detection and Control." In 1996 1st International Pipeline Conference. American Society of Mechanical Engineers, 1996. http://dx.doi.org/10.1115/ipc1996-1924.

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Automatic and remotely controlled main line valves are used in natural gas transmission pipelines to provide early shutoff of gas flow in the event of a pipeline rupture. Operating experience, however, shows that these valves and their associated rupture detection and valve operator systems are not always reliable in sensing a line break and in achieving valve closure. There are documented instances of pipeline ruptures going undetected, and of main line valves not closing completely after even a full line break. False valve closures have also occurred, causing pipelines to be shut down unnecessarily. Under sponsorship of the Gas Research Institute (GRI), a technology assessment program was conducted by Southwest Research Institute (SwRI) to define the present state of the art of automatic and remotely controlled main line valves, to evaluate their effectiveness in achieving isolation of a ruptured line, and to identify technology improvements that are needed to improve valve reliability. This study was based on a survey of the U.S. natural gas industry’s experience with line break control equipment, and upon computational modeling of typical pipeline systems to simulate the generation and propagation of pressure and flow transients created by a line break. Line break transients were also compared to the transient levels generated by normal pipeline operations (start-up and shutdown of compressors, branch load changes, etc.). Also during this study, a semi-empirical computer model was developed to calculate pipeline blowdown time as a function of break size, pipeline configuration, and operating conditions, even in cases where valve closure is delayed for some period after the line break occurs. This information can be of value to pipeline engineers and emergency response planners. Results of the technology assessment show that the primary source of unreliability in present day line break control systems lies in their inability to discriminate between a line break transient, and those generated by other pipeline operations. In most cases, automatic control valves (ACV’s) sense the rate of pipeline pressure drop (ROPD) to detect a line break. In many field applications, however, transient pressure signals caused by compressor operations and load changes are stronger than those produced by a line break. In order to avoid false valve closures which could otherwise result, sensitivity of the rupture detection systems is “backed off,” often to the point of inoperability of the ACV. Other fluid transient signals besides pressure drop are also generated in the pipeline during a line break, and these can sometimes be used advantageously to replace or confirm the traditional ROPD signal. In looped parallel pipelines, for example, crossover flow rate is usually a more reliable line break signal when crossovers are open. The resultant line-to-line differential pressure also provides a viable option when crossovers are either open or closed. In general, however, no one detection parameter is optimum for all applications. Of even more importance is the rupture sensor location. The concept of locating additional sensors between the main line valves (rather than just at the valves) provides the most promising approach for enhancing the reliability of present ACV’s and for providing needed line break information to remote controlled valves (RCV’s). In either case (ACV’s or RCV’s), rupture sensor location is much more important than valve location or valve spacing in ensuring reliable rupture isolation. However, valve spacing does affect the volume of gas blown down after shut-in of a ruptured section. This time can often be from 10 to 60 minutes for typical pipeline valve spacings.

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Di Blasi, Martin, and Zhan Li. "Pipeline Rupture Detection Based on Machine Learning and Pattern Recognition." In 2016 11th International Pipeline Conference. American Society of Mechanical Engineers, 2016. http://dx.doi.org/10.1115/ipc2016-64471.

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Pipeline ruptures have the potential to cause significant economic and environmental impact in a short period of time, therefore it is critical for pipeline operators to be able to promptly detect and respond to them. Public stakeholder expectations are high and an evolving expectation is that the response to such events be automated by initiating an automatic pipeline shutdown upon receipt of rupture alarm. These types of performance expectations are challenging to achieve with conventional, model-based, leak-detection systems (i.e. CPM–RTTMs) as the reliability measured in terms of the false alarm rate is typically too low. The company has actively participated on a pipeline-industry task force chaired by the API Cybernetics committee, focused on the development of best practices in the area of Rupture Recognition and Response. After API’s release of the first version of a Rupture Recognition and Response guidance document in 2014, the company has initiated development of its own internal Rupture Recognition Program (RRP). The RRP considers several rupture recognition approaches simultaneously, ranging from improvements to existing CPM leak detection to the development of new SCADA based rupture detection system (RDS). This paper will provide an overview of a specific approach to rupture detection based on the use of machine learning and pattern recognition techniques applied to SCADA data.

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Smith, Joel, Jaehee Chae, Shawn Learn, Ron Hugo, and Simon Park. "Pipeline Rupture Detection Using Real-Time Transient Modelling and Convolutional Neural Networks." In 2018 12th International Pipeline Conference. American Society of Mechanical Engineers, 2018. http://dx.doi.org/10.1115/ipc2018-78426.

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Demonstrating the ability to reliably detect pipeline ruptures is critical for pipeline operators as they seek to maintain the social license necessary to construct and upgrade their pipeline systems. Current leak detection systems range from very simple mass balances to highly complex models with real-time simulation and advanced statistical processing with the goal of detecting small leaks around 1% of the nominal flow rate. No matter how finely-tuned these systems are, however, they are invariably affected by noise and uncertainties in a pipeline system, resulting in false alarms that reduce system confidence. This study aims to develop a leak detection system that can detect leaks with high reliability by focusing on sudden-onset leaks of various sizes (ruptures), as opposed to slow leaks that develop over time. The expected outcome is that not only will pipeline operators avoid the costs associated with false-alarm shut downs, but more importantly, they will be able to respond faster and more confidently in the event of an actual rupture. To accomplish these goals, leaks of various sizes are simulated using a real-time transient model based on the method of characteristics. A novel leak detection model is presented that fuses together several different preprocessing techniques, including convolution neural networks. This leak detection system is expected to increase operator confidence in leak alarms, when they occur, and therefore decrease the amount of time between leak detection and pipeline shutdown.

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Kang, Ju Seok, Nahian Rahman, Sung Min Yoon, Gm Gang Cha, and Min Cheol Lee. "Organ rupture detection algorithm of surgical robot." In 2014 14th International Conference on Control, Automation and Systems (ICCAS). IEEE, 2014. http://dx.doi.org/10.1109/iccas.2014.6987884.

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Nanditha, Hg, Sanjana Sampige, S. N. Shreya, Samyutha Bhaskar, and G. N. Anusha. "Glove Rupture Detection System using skin impedance." In 2023 International Conference on the Confluence of Advancements in Robotics, Vision and Interdisciplinary Technology Management (IC-RVITM). IEEE, 2023. http://dx.doi.org/10.1109/ic-rvitm60032.2023.10434990.

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Mu, Xiuping. "A New Approach to Monitoring Rupture Disc Operation." In ASME 2012 International Mechanical Engineering Congress and Exposition. American Society of Mechanical Engineers, 2012. http://dx.doi.org/10.1115/imece2012-86369.

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Reliable sensors for monitoring rupture disc activation (also known as burst or rupture) are needed in order to provide immediate warning of a ruptured disc resulting from abnormal process overpressure or vacuum conditions. Many rupture discs are operated in harsh and/or hazardous environments, such as high temperature, highly corrosive, or explosive atmospheres. Also for some critical applications rupture discs and accessories with non-fragmentation features are necessary. Conventional or recently emerged sensors are available for burst disc detection, such as generic pressure switches and instruments specifically designed for burst disc detection. However, many of these devices are either mechanically too fragile, economically not practical, or not suitable for critical rupture disc applications. This paper introduces a new approach of monitoring rupture disc activation using flexible membrane sensor technology. Commercially available resistive type flexible sensors were studied and those with good performance in terms of responsive to burst sensing and materials most suitable for harsh environment were prototyped for the development. An algorithm was developed to carry out the signal processing and generate status signals using microcontrollers. With the low cost membrane sensors and increased functionalities and operability of microcontrollers, the method is expected to play an increasingly important role in rupture disc monitoring as well as other dynamic flow detection.

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CLAUSS, FELIX, MARK ALEXANDER AHRENS, and PETER MARK. "DAMAGE WITHOUT INDICATION—DETECTION OF TENDON RUPTURE USING CODA WAVE INTERFEROMETRY." In Structural Health Monitoring 2021. Destech Publications, Inc., 2022. http://dx.doi.org/10.12783/shm2021/36263.

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Pre-stressing is often the decisive feature of concrete bridges. Deterioration of the tendons used to provide pre-stress is thus an immense problem. To detect potential damage, monitoring of the structures promises to be a remedy. However, since the location of damage is seldom known, conventional monitoring systems reach their limits. Then, ultrasound in conjunction with coda wave interferometry becomes promising to monitor entire structures with just a small number of sensors. To demonstrate the general feasibility of detecting tendon rupture, a pre-stressed concrete beam was experimentally investigated. Failure was artificially initiated by cutting a tendon. Ultrasonic and strain measurements recorded stress changes that occurred due to cross-section losses of the tendon. Both the process of pre-stressing and the artificially induced failure has been tracked using the coda wave technique. Based on the relative velocity change of the ultrasound, the internal state change in the (from the outside) still intact specimen could be detected and tracked. These initial results inspire further in-depth investigations into the detection of pre-stressing steel fractures.

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MacDonald, Christopher, Michael Yang, Shawn Learn, Ron Hugo, and Simon Park. "Liquid Pipeline Rupture Detection Using Multiple Artificial Intelligence Classifiers During Steady-State and Transient Operations." In 2020 13th International Pipeline Conference. American Society of Mechanical Engineers, 2020. http://dx.doi.org/10.1115/ipc2020-9237.

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Abstract There are several challenges associated with existing rupture detection systems such as their inability to accurately detect during transient (such as pump dynamics) conditions, delayed responses and their inability to transfer models to different pipeline configurations easily. To address these challenges, we employ multiple Artificial Intelligence (AI) classifiers that rely on pattern recognitions instead of traditional operator-set thresholds. AI techniques, consisting of two-dimensional (2D) Convolutional Neural Networks (CNN) and Adaptive Neuro Fuzzy Interface Systems (ANFIS), are used to mimic processes performed by operators during a rupture event. This includes both visualization (using CNN) and rule-based decision making (using ANFIS). The system provides a level of reasoning to an operator through the use of the rule-based AI system. Pump station sensor data is non-dimensionalized prior to AI processing, enabling application to pipeline configurations outside of the training data set. AI algorithms undergo testing and training using two data sets: laboratory-collected data that mimics transient pump-station operations and real operator data that includes Real Time Transient Model (RTTM) simulated ruptures. The use of non-dimensional sensor data enables the system to detect ruptures from pipeline data not used in the training process.

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Mamou, J., A. Y. Ammi, L. Bridal, G. I. Wang, and W. D. O�Brien Jr. "2D-2 Automatic Detection of Ultrasound Contrast Microbubble Shell Rupture." In 2006 IEEE Ultrasonics Symposium. IEEE, 2006. http://dx.doi.org/10.1109/ultsym.2006.87.

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Rudland, David L. "Predicting Pipe Rupture Frequencies Using xLPR." In ASME 2020 Pressure Vessels & Piping Conference. American Society of Mechanical Engineers, 2020. http://dx.doi.org/10.1115/pvp2020-21080.

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Abstract Over the last several years, the U.S. Nuclear Regulatory Commission (NRC), in cooperation with the Electric Power Research Institute (EPRI), conducted a multi-year project that focused on the development of a viable method and approach to address the effects of primary water stress corrosion cracking (PWSCC) in primary piping systems approved for leak-before-break (LBB). This project, called eXtremely Low Probability of Rupture (xLPR), defined the requirements necessary for a modular-based probabilistic fracture mechanics assessment tool to directly assess compliance with the regulations. Version 2.0 of this code has been completed and is currently awaiting public release. Since the focus of xLPR Version 2.0 is investigating the impacts of active piping degradation on the leak-before-break behavior of reactor coolant piping, questions have been raised to whether xLPR can be used to confirm pipe rupture frequencies developed in other efforts, such as NUREG-1829, “Estimating Loss-of-Coolant Accident (LOCA) Frequencies Through the Elicitation Process.” This paper discusses an initial study focused on whether xLPR can be used to estimate pipe rupture frequencies. A series of analyses were conducted, based on inputs developed by the xLPR program team, focused on the reactor pressure vessel outlet nozzle geometry of a typical pressurized water reactor. Additional analyses were conducted using the same radius-to-thickness ratio but decreasing the pipe diameter. Due to computer memory restrictions, it was difficult calculating low probability events when considering PWSCC initiation, typical residual stresses, leak detection and in-service inspection. Therefore, to bound the problem, an aggressive weld residual stress was assumed with multiple pre-existing defects. By modifying the size and number of these initial defects, results were generated that indicated the conditional probability of rupture was related to the percentage of the inner circumference cracked and the pipe diameter. Using the PWSCC initiation model from xLPR Version 2, the yearly rupture frequency with leak detection and in-service inspection was calculated. The results indicate that the rupture frequencies in NUREG-1829 appear conservative relative to the results from this study. Due to the limited scope of this study, the assumptions used in these analyses were limited or conservative; therefore, additional analyses are needed for a more robust comparison. However, the results suggest that conducting xLPR analyses with pre-existing defects may be useful in bounding LBB applicability with active degradation.

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Reports on the topic "Rupture detection"

Gangrao, Hota V. S., Udaya B. Halabe, John Zondlo, Mark Skidmore, Ben Imes, Jonas Kavi, Andrew Pacifico, Ronald Alexander, Andrew Cvetnick, and Patrick Sisler. DTPH56-16-HCAP-02 Glass-Polymer Composite High Pressure Pipes and Joints-Design, Manufacture. Chantilly, Virginia: Pipeline Research Council International, Inc. (PRCI), September 2018. http://dx.doi.org/10.55274/r0011841.

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The project focuses on developing glass fiber reinforced polymer (GFRP) composite pipes including a range of joining systems. A few of the many advantages of GFRP composite pipes are their non-corrosiveness, magnetic transparency, and high strength-to-weight ratio. As a part of this project, GFRP pipes and joints were designed, manufactured, and evaluated under static loads. Emphasis was placed in the evaluation of stress-rupture (burst pressure) of GFRP composite pipes that could withstand internal pressures as high as 5000 psi. The report also includes the design and testing of high-pressure composite joints for these pipes. In addition, the report discusses the use of Ground Penetrating Radar (GPR) for successfully detecting the FRP pipes under buried conditions. The report also includes the detection of gas leakage from buried pipes using mass spectroscopy.

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McCallum and Richard. L52247 Human Factors Analysis of Leak Detection and Response Scoping Study. Chantilly, Virginia: Pipeline Research Council International, Inc. (PRCI), February 2004. http://dx.doi.org/10.55274/r0010251.

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There has been a substantial level of effort over the past several decades to understand the role of the human controller/operator in process control industry accidents. This work received a substantial impetus from the Three Mile Island nuclear reactor accident in March 1979, which led to an increased focus on the role of the operator as a decision-maker within the process control system. In response to this focus, industry guidelines were developed to address human factors issues in control room design and plant maintainability, among other issues. During the same period that industry guidelines were being developed in the nuclear industry, the human factors community made significant progress in developing theoretical models of the role of the operator in process control. Models that recognized the importance of operators" cognitive capacities, tendencies, and errors provided additional analytic power in both reconstructing accidents and developing approaches toward new designs. Two alternative near-term research plans were identified, along with the required funds, industry resources, and time. Expected products resulting from two alternative research efforts were outlined. An immediate benefit to industry in supporting the outlined research would be implementation of the Human Factors Operational Review Procedure. This would allow operators to come into compliance with key aspects of the Pipeline Integrity Management rules. More specifically, this guideline would be responsive to the requirement to identify and evaluate preventive and mitigative measures to protect High Consequence Areas, including emergency procedures for responding to spills and ruptures. Human factors critically affect operators" capability to detect and respond to spills, ruptures, and other emergency conditions; and the proposed guideline would directly support these requirements. More generally, it is anticipated that support of this research would result in significant improvement in operational safety, reliability, and efficiency.

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Barton. L51695 Development of Inspection Vehicle to Detect SCC in Natural Gas Lines. Chantilly, Virginia: Pipeline Research Council International, Inc. (PRCI), November 1993. http://dx.doi.org/10.55274/r0010627.

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Stress corrosion cracking (SCC) poses a serious threat to aging underground cathodically protected gas pipelines. As coatings deteriorate, conditions suitable for corrosion and SCC become more common. There have been many ruptures throughout the world attributed to SCC. One of the most important steps in combating failure by SCC is regular, reliable and cost effective monitoring of pipelines. Current methods available (including hydrotesting and magnetic particle testing) are either expensive, time consuming, or not entirely reliable. Regular testing of pipelines and the detailed study of the results will improve the understanding of SCC initiation and propagation. This project evaluates a manual ultrasonic scanning system for detecting SCC in pipelines. This system was used to inspect the lower circumferential section of unpressurized lengths of the Moomba to Sydney gas transmission pipeline operated by The Pipeline Authority (TPA). The manual system successfully located SCC colonies. CWP, in association with The University of Newcastle, then developed a microprocessor controlled system based on piezoelectric wheel probe technology. This system was trialled in Peterborough, South Australia in May 1990. Following the awarding of this research project (PR-198-9108). CWP incorporated the development work into their core business with the creation of the Product Development Section. This section was entirely committed to the development of the system and the PRC project. The redesign of the system included EMAT technology. Although not new, EMATs had not previously been made available to the gas industry in the detection of SCC. This project involved in excess of 13500 development man hours over a 22 month period. This report describes the development of the system and the Newcastle field trials, the Australian field trials and the USA field trials concluding in September 1992. The report also addresses the suitability of each technology in detecting SCC in buriednatural gas pipeline and makes design recommendations for the future. Future developments in the system are planned in the areas of enhancing the reliable detection of SCC, imaging of SCC and enhanced calibration capabilities.

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Barton, Card, and Pope. L51637 Development of an Ultrasonic Stress Corrosion Cracking Detection Vehicle. Chantilly, Virginia: Pipeline Research Council International, Inc. (PRCI), November 1990. http://dx.doi.org/10.55274/r0010608.

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Stress corrosion cracking poses a serious threat to aging underground cathodically protected gas pipelines. As coatings deteriorate, conditions conducive to both corrosion and stress corrosion cracking become more common. There have been many ruptures in various pipelines throughout the world attributed to SCC. One of the most important steps in combating failure by stress corrosion cracking is regular, reliable and cost effective monitoring of the pipelines. Current methods available (including hydrotesting and MT) are either expensive, time consuming, or not entirely reliable. Regular testing of pipes would also improve understanding of stress corrosion cracking initiation and propagation. Field trials of a prototype remote control stress corrosion cracking (SCC) detection vehicle� took place from the May 21st 1990 to the June 1st 1990, at Peterborough in South Australia, as part of an agreement with the Pipeline Research Committee, of the Pipeline Research Council International, Inc. The present vehicle is self-contained, battery powered and is controlled by an on board computer. The vehicle can operate in an evacuated line and maintains a telemetry radio link with a monitoring computer at the pipe entry position. The detection system consists of two piezoelectric ultrasonic wheel probes fired by dedicated electronics. The vehicle is programmed to move through a certain section of pipe to record areas of ultrasonic activity corresponding to SCC in the bottom section of the pipe.

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Wright, Louise, and Louise Crocker. PR-670-183826-R03 Extended Evaluation of LSM-Magnetostrictive Pipe Models. Chantilly, Virginia: Pipeline Research Council International, Inc. (PRCI), May 2021. http://dx.doi.org/10.55274/r0012097.

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Integrity assessment of pipelines is vital to ensure that oil and gas pipes have adequate strength to prevent leaks and ruptures. Regular inspections are conducted to confirm safe operation conditions of pipelines. The industry's principal method for assessing pipelines is in-line inspection (ILI), involving the passing of a device along the inside of a pipe to assess the condition of the pipeline. ILI devices can be fitted with a number of sensors allowing various measurement parameters to be obtained simultaneously. Not all pipelines are suited to ILI for reasons such as small diameter, obstructions within the pipe, or insufficient access to deploy or retrieve the ILI tools. These pipelines are sometimes referred to as 'difficult to inspect'. Alternative methods for examining pipeline condition are required with a range of technologies collectively known as Large Standoff Magnetometry (LSM) offering a promising solution for detection of pipe defects from a distance, reducing the need for excavation. LSM utilizes coupling between defects and changes in the magnetic properties of the pipeline material as a method for evaluation of pipe walls to identify the location of areas that require repair or further monitoring. Trials of existing commercial instruments by the pipeline industry have shown sufficient promise to investigate these technologies further. However, the vendors have supplied limited information on the underpinning physics of both the materials being tested and the instrument technology, meaning that further study is required in order to build confidence in the technique. The purpose of the project is to establish the ability of LSM to detect corrosion in API 5L pipe grades B to X70. The aim of the modelling work has been to use quantitative physics-based modelling techniques to predict the performance of LSM as a defect detection technique in situations that cannot easily be recreated in a laboratory environment, after validating the modelling approach by comparing measurements made in the laboratory to model results.

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Bruce. L51642 Field Nondestructive Examination of ERW Pipe Seams. Chantilly, Virginia: Pipeline Research Council International, Inc. (PRCI), June 1991. http://dx.doi.org/10.55274/r0010587.

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Electric resistance welded (ERW) pipe has been used in the natural gas transmission industry for many years. The Department of Transportation (DOT) has recently expressed interest in the integrity of the weld seam in pipelines made from ERW pipe that was manufactured prior to 1970. Specifically, the DOT has requested that natural gas transmission and hazardous liquid pipeline operators determine whether or not their pipelines that meet this description require hydrostatic proof testing. The initial concern from the DOT was for seam weld selective corrosion, although reference has since been made to growth of manufacturing discontinuities in the ERW seam. Early ERW pipe was manufactured using either direct current or low-frequency alternating current, processes that were prone to producing incomplete fusion discontinuities. These discontinuities (also referred to as cold welds, penetrators, etc.), if present in a pipeline, can grow under normal service or under upset operating conditions resulting in leaks or ruptures. There exists a need for a method that a pipeline operator could use to demonstrate the integrity of pipelines that were made from this older ERW pipe other than hydrostatic testing, which is expensive and potentially harmful to pipeline integrity. The use of a nondestructive-examination (NDE) technique would enable an operator to sample the integrity of a suspect pipeline during other routine in-service maintenance operations without the need for hydrostatic testing. The detection of incomplete fusion discontinuities is difficult if not impossible with conventional NDE techniques. The intimate mechanical contact between compressed surfaces causes a small amount of reflection and a large amount of transmission of ultrasonic signals. Recently however, several ultrasonic techniques have been introduced to study these types of discontinuities in resistance spot welds and inertia friction welds. These new techniques are based on ultrasonic spectroscopy, that is, the frequency dependence of the various ultrasonic interfacial parameters. These parameters include reflection and transmission coefficients and the frequency dependence of ultrasonic volumetric parameters (e.g., velocity and attenuation).

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Finch, Graeme, and Stuart Harmon. PR-670-183826-R01 Assessment of Science Behind LSM for Pipeline Integrity. Chantilly, Virginia: Pipeline Research Council International, Inc. (PRCI), September 2020. http://dx.doi.org/10.55274/r0011803.

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Integrity assessment of pipelines is vital to ensure that oil and gas pipes have adequate strength to prevent leaks and ruptures. Regular inspections are conducted to confirm safe operation conditions of pipelines. The industry's principle method for assessing pipelines is in-line inspection (ILI), involving the passing of a device along the inside of a pipe to assess the condition of the pipeline. ILI devices can be fitted with a number of sensors allowing various measurement parameters to be obtained simultaneously. Not all pipelines are suited to ILI for reasons such as small diameter, obstructions within the pipe, or insufficient access to deploy or retrieve the ILI tools. These pipelines are sometimes referred to as 'difficult to inspect'. Alternative methods for examining pipeline condition are required, with a range of technologies collectively known as Large Standoff Magnetometry (LSM) offering a promising solution for detection of pipe defects from a distance, reducing the need for excavation. LSM utilises the coupling between defects and changes in the magnetic properties of the pipeline material as a method for evaluation of pipe walls to identify the location of areas that require repair or further monitoring. Trials of existing commercial instruments by the pipeline industry have shown sufficient promise to investigate the technologies further. However, vendors have supplied limited information on the underpinning physics of both the materials being tested and the instrument technology. The purpose of the project is to establish the ability of LSM to detect corrosion in API 5L pipe grades B to X70. The aim of Work Package 02 is to review the physics of the agreed pipeline defects and fluxgate type magnetic sensors. The properties of pipeline-specific soft magnetic materials are investigated to understand corrosion, how this alters the material properties and how this can affect the associated magnetic fields surrounding the material. The physics of fluxgate magnetometers and gradiometers are also reviewed to assess the ability of LSM to detect these two features.

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Finch, Graeme, and Stuart Harmon. PR-670-183826-R02 Extended Evaluation of LSM - Magnetic Measurements of Corrosion Flaws. Chantilly, Virginia: Pipeline Research Council International, Inc. (PRCI), November 2021. http://dx.doi.org/10.55274/r0012189.

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Abstract:

Integrity assessment of pipelines is vital to ensure that oil and gas pipes have adequate strength to prevent leaks and ruptures. Regular inspections are conducted to confirm safe operation conditions of pipelines. The industry's principle method for assessing pipelines is in-line inspection (ILI), involving the passing of a device along the inside of a pipe to assess the condition of the pipeline. ILI devices can be fitted with a number of sensors allowing various measurement parameters to be obtained simultaneously. Not all pipelines are suited to ILI for reasons such as small diameter, obstructions within the pipe, or insufficient access to deploy or retrieve the ILI tools. These pipelines are sometimes referred to as 'difficult to inspect'. Alternative methods for examining pipeline condition are required with a range of technologies collectively known as Large Standoff Magnetometry (LSM) offering a promising solution for detection of pipe defects from a distance, reducing the need for excavation. LSM utilises coupling between defects and changes in the magnetic properties of the pipeline material as a method for evaluation of pipe walls to identify the location of areas that require repair or further monitoring. Trials of existing commercial instruments by the pipeline industry have shown sufficient promise to investigate these technologies further. However, the vendors have supplied limited information on the underpinning physics of both the materials being tested and the instrument technology, meaning that further study is required in order to build confidence in the technique. The purpose of the project is to establish the ability of LSM to detect corrosion in API 5L pipe grades B to X70. The aim of Work Package 04 is to measure the magnetic fields of a range of pipe samples containing manufactured corrosion flaws taking into account variables such as standoff distance, pressure, nearby ferromagnetic objects, position of the corrosion flaw around the pipe, track alignment, and orientation with respect to Earth's magnetic field. The results of these measurements will be used to validate computational models, which can be used to predict the magnetic response of a wider range of pipe geometries.

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