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Dissertations / Theses on the topic 'Microprocessor-based prognostic and diagnostic system'

Author: Grafiati
Published: 28 May 2022
Last updated: 30 July 2025

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1

Нагорний, Володимир В`ячеславович, Владимир Вячеславович Нагорный та Volodymyr Viacheslavovych Nahornyi. "Контроль динамического поведения металлообрабатывающих технологических систем и метод определения их ресурса". Thesis, Изд-во СумГУ, 2015. http://essuir.sumdu.edu.ua/handle/123456789/42598.

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Робота присвячена актуальній проблемі розвитку методів контролю динамічної поведінки металообробних технологічних систем та розробки методу визначення їх ресурсу. У роботі вперше поставлене і вирішене науково-технічне завдання визначення ресурсу обробної системи безпосередньо в процесі її роботи в умовах, коли «Норми…» , яки регламентують ступінь критичності динамічної поведінки для даних систем, відсутні. Це завдання вирішене за рахунок того, що розроблена у роботі прогнозна модель вигідно відрізняється від прийнятих тим, що ресурс, який шукається, включено до її математичної структури і в
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2

Kumar, Sachin. "Development of diagnostic and prognostic methodologies for electronic systems based on Mahalanobis distance." College Park, Md.: University of Maryland, 2009. http://hdl.handle.net/1903/9921.

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Thesis (Ph. D.) -- University of Maryland, College Park, 2009.<br>Thesis research directed by: Reliability Engineering Program. Title from t.p. of PDF. Includes bibliographical references. Published by UMI Dissertation Services, Ann Arbor, Mich. Also available in paper.
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3

Isaksson, Olle. "Model-based Diagnosis of a Satellite Electrical Power System with RODON." Thesis, Linköping University, Linköping University, Vehicular Systems, 2009. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-16763.

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<p>As space exploration vehicles travel deeper into space, their distance to earth increases.The increased communication delays and ground personnel costs motivatea migration of the vehicle health management into space. A way to achieve thisis to use a diagnosis system. A diagnosis system uses sensor readings to automaticallydetect faults and possibly locate the cause of it. The diagnosis system usedin this thesis is a model-based reasoning tool called RODON developed by UptimeSolutions AB. RODON uses information of both nominal and faulty behavior ofthe target system mathematically formulated
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4

KOTHAMASU, RANGANATH. "INTELLIGENT CONDITION BASED MAINTENANCE - A SOFT COMPUTING APPROACH TO SYSTEM DIAGNOSIS AND PROGNOSIS." University of Cincinnati / OhioLINK, 2006. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1141339344.

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5

Krupa, Miroslav. "Metody technické prognostiky aplikovatelné v embedded systémech." Doctoral thesis, Vysoké učení technické v Brně. Fakulta elektrotechniky a komunikačních technologií, 2012. http://www.nusl.cz/ntk/nusl-233568.

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Hlavní cílem dizertace je poskytnutí uceleného pohledu na problematiku technické prognostiky, která nachází uplatnění v tzv. prediktivní údržbě založené na trvalém monitorování zařízení a odhadu úrovně degradace systému či jeho zbývající životnosti a to zejména v oblasti komplexních zařízení a strojů. V současnosti je technická diagnostika poměrně dobře zmapovaná a reálně nasazená na rozdíl od technické prognostiky, která je stále rozvíjejícím se oborem, který ovšem postrádá větší množství reálných aplikaci a navíc ne všechny metody jsou dostatečně přesné a aplikovatelné pro embedded systémy.
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6

Patrick-Aldaco, Romano. "A Model Based Framework for Fault Diagnosis and Prognosis of Dynamical Systems with an Application to Helicopter Transmissions." Diss., Georgia Institute of Technology, 2007. http://hdl.handle.net/1853/16266.

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The thesis presents a framework for integrating models, simulation, and experimental data to diagnose incipient failure modes and prognosticate the remaining useful life of critical components, with an application to the main transmission of a helicopter. Although the helicopter example is used to illustrate the methodology presented, by appropriately adapting modules, the architecture can be applied to a variety of similar engineering systems. Models of the kind referenced are commonly referred to in the literature as physical or physics-based models. Such models utilize a mathematical descr
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7

Saha, Bhaskar. "A model-based reasoning architecture for system-level fault diagnosis." Diss., Atlanta, Ga. : Georgia Institute of Technology, 2008. http://hdl.handle.net/1853/22653.

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Thesis (Ph. D.)--Electrical and Computer Engineering, Georgia Institute of Technology, 2008.<br>Committee Chair: Vachtsevanos, George; Committee Member: Liang, Steven; Committee Member: Michaels, Thomas; Committee Member: Vela, Patricio; Committee Member: Wardi, Yorai.
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8

Brown, Douglas W. "A prognostic health management based framework for fault-tolerant control." Diss., Georgia Institute of Technology, 2011. http://hdl.handle.net/1853/41132.

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The emergence of complex and autonomous systems, such as modern aircraft, unmanned aerial vehicles (UAVs) and automated industrial processes is driving the development and implementation of new control technologies aimed at accommodating incipient failures to maintain system operation during an emergency. The motivation for this research began in the area of avionics and flight control systems for the purpose to improve aircraft safety. A prognostics health management (PHM) based fault-tolerant control architecture can increase safety and reliability by detecting and accommodating impending fa
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9

Kothamasu, Ranganath. "Intelligent condition based maintenance a soft computing approach to system diagnosis and prognosis /." Cincinnati, Ohio : University of Cincinnati, 2005. http://www.ohiolink.edu/etd/view.cgi?acc%5Fnum=ucin1141339344.

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Thesis (Ph. D.)--University of Cincinnati, 2005.<br>Title from electronic thesis title page (viewed Apr. 13, 2006). Includes abstract. Keywords: Condition Based Maintenance, Model based maintenance, Neuro-Fuzzy, Backpropagation, Information Entropy, Model selection. Includes bibliographical references.
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10

Davari, Ardakani Hossein. "Prognostics and Health Management of Engineering Systems Using Minimal Sensing Techniques." University of Cincinnati / OhioLINK, 2016. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1467987980.

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11

Orchard, Marcos Eduardo. "A Particle Filtering-based Framework for On-line Fault Diagnosis and Failure Prognosis." Diss., Georgia Institute of Technology, 2007. http://hdl.handle.net/1853/19752.

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This thesis presents an on-line particle-filtering-based framework for fault diagnosis and failure prognosis in nonlinear, non-Gaussian systems. The methodology assumes the definition of a set of fault indicators, which are appropriate for monitoring purposes, the availability of real-time process measurements, and the existence of empirical knowledge (or historical data) to characterize both nominal and abnormal operating conditions. The incorporation of particle-filtering (PF) techniques in the proposed scheme not only allows for the implementation of real time algorithms, but also provides
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12

Abbas, Manzar. "System-level health assessment of complex engineered processes." Diss., Georgia Institute of Technology, 2010. http://hdl.handle.net/1853/37260.

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Condition-Based Maintenance (CBM) and Prognostics and Health Management (PHM) technologies aim at improving the availability, reliability, maintainability, and safety of systems through the development of fault diagnostic and failure prognostic algorithms. In complex engineering systems, such as aircraft, power plants, etc., the prognostic activities have been limited to the component-level, primarily due to the complexity of large-scale engineering systems. However, the output of these prognostic algorithms can be practically useful for the system managers, operators, or maintenance personnel
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13

Khawaja, Taimoor Saleem. "A Bayesian least squares support vector machines based framework for fault diagnosis and failure prognosis." Diss., Georgia Institute of Technology, 2010. http://hdl.handle.net/1853/34758.

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A high-belief low-overhead Prognostics and Health Management (PHM) system is desired for online real-time monitoring of complex non-linear systems operating in a complex (possibly non-Gaussian) noise environment. This thesis presents a Bayesian Least Squares Support Vector Machine (LS-SVM) based framework for fault diagnosis and failure prognosis in nonlinear, non-Gaussian systems. The methodology assumes the availability of real-time process measurements, definition of a set of fault indicators, and the existence of empirical knowledge (or historical data) to characterize both nominal and abn
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14

Zhang, Zhenyou. "Data Mining Approaches for Intelligent Condition-based Maintenance : A Framework of Intelligent Fault Diagnosis and Prognosis System (IFDPS)." Doctoral thesis, Norges teknisk-naturvitenskapelige universitet, Institutt for produksjons- og kvalitetsteknikk, 2014. http://urn.kb.se/resolve?urn=urn:nbn:no:ntnu:diva-25148.

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Condition-based Maintenance (CBM) is a maintenance policy that take maintenance action just when need arises with real-time condition monitoring. Intelligent CBM means a CBM system is capable of understanding and making maintenance decisions without human intervention. To achieve this objective, it is needed to detect current conditions of mechanical and electrical systems and predict the fault of the systems accurately. What’s more, the maintenance scheduling need to be optimized to reduce the maintenance cost and improve the reliability, availability and safety based on the results of fault
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15

Gaudel, Quentin. "Approche intégrée de diagnostic et de pronostic pour la gestion de santé des systèmes hybrides sous incertitude." Thesis, Toulouse, INSA, 2016. http://www.theses.fr/2016ISAT0019/document.

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Cette étude s’inscrit dans le domaine de la gestion de santé des systèmes, qui vise à développer des outils d’aide à la maintenance, mais également à améliorer les prises de décision en autonomie des systèmes en cas de pannes. Dans ce cadre, des techniques de diagnostic déterminent si et pourquoi le système est en panne, alors que des techniques de pronostic déterminent quand les pannes vont survenir et leurs conséquences. Si elles semblent être corrélées, elles sont généralement étudiées séparément, car les échelles de temps manipulées par les deux processus sont très différentes.Ces travaux
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16

Saadawia, Mahmud-Sami [Verfasser], and Dirk [Akademischer Betreuer] Söffker. "Application of Wavelets-based SVM Classification for Automated Fault Diagnosis and Prognosis of Mechanical Systems / Mahmud-Sami Saadawia. Betreuer: Dirk Söffker." Duisburg, 2016. http://d-nb.info/1109745753/34.

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17

Saadawia, Mahmud-Sami Verfasser], and Dirk [Akademischer Betreuer] [Söffker. "Application of Wavelets-based SVM Classification for Automated Fault Diagnosis and Prognosis of Mechanical Systems / Mahmud-Sami Saadawia. Betreuer: Dirk Söffker." Duisburg, 2016. http://d-nb.info/1109745753/34.

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18

Le, Thanh Trung. "Contribution to deterioration modeling and residual life estimation based on condition monitoring data." Thesis, Université Grenoble Alpes (ComUE), 2015. http://www.theses.fr/2015GREAT099/document.

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La maintenance prédictive joue un rôle important dans le maintien des systèmes de production continue car elle peut aider à réduire les interventions inutiles ainsi qu'à éviter des pannes imprévues. En effet, par rapport à la maintenance conditionnelle, la maintenance prédictive met en œuvre une étape supplémentaire, appelée le pronostic. Les opérations de maintenance sont planifiées sur la base de la prédiction des états de détérioration futurs et sur l'estimation de la vie résiduelle du système. Dans le cadre du projet européen FP7 SUPREME (Sustainable PREdictive Maintenance for manufacturin
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19

Parisi, Luca. "Machine Learning-based Feature Selection and Optimisation for Clinical Decision Support Systems. Optimal Data-driven Feature Selection Methods for Binary and Multi-class Classification Problems: Towards a Minimum Viable Solution for Predicting Early Diagnosis and Prognosis." Thesis, University of Bradford, 2019. http://hdl.handle.net/10454/18417.

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This critical synopsis of prior work by Luca Parisi is submitted in support of a PhD by Published Work. The work focuses on deriving accurate, reliable and explainable clinical decision support systems as minimum clinically viable solutions leveraging Machine Learning (ML) and evolutionary algorithms, for the first time, to facilitate early diagnostic predictions of Parkinson's Disease and hypothermia in hospitals, as well as prognostic predictions of optimal postoperative recovery area and of chronic hepatitis. Despite the various pathological aetiologies, the underlying capabil
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20

PILLAI, Vinoshene. "Intravital two photon clcium imaging of glioblastoma mouse models." Doctoral thesis, Scuola Normale Superiore, 2021. http://hdl.handle.net/11384/109211.

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21

Garvey, Dustin R. "An Integrated Fuzzy Inference Based Monitoring, Diagnostic, and Prognostic System." 2007. http://trace.tennessee.edu/utk_graddiss/172.

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To date the majority of the research related to the development and application of monitoring, diagnostic, and prognostic systems has been exclusive in the sense that only one of the three areas is the focus of the work. While previous research progresses each of the respective fields, the end result is a variable "grab bag" of techniques that address each problem independently. Also, the new field of prognostics is lacking in the sense that few methods have been proposed that produce estimates of the remaining useful life (RUL) of a device or can be realistically applied to real-world systems
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22

Fonseca, Maria Inês Ferreira. "Diagnosis and Prognosis of Aircraft Systems State." Master's thesis, 2020. http://hdl.handle.net/10316/92097.

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Dissertação de Mestrado em Engenharia Informática apresentada à Faculdade de Ciências e Tecnologia<br>With the evolution of technology there is a need to improve the world, taking advantage of it. And the aviation industry is no exception. As time went by, the need arose to extend the useful life of a system or component, through an analysis based on its health state (CBM). With the implementation of this type of methodologies it is also possible to predict when it will fail, calculating the life left until this event. This is one of the approaches that needs to be improved, once the timely de
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23

Azevedo, Daniel Romário Gomes. "Condition-Based Maintenance for Diagnosis and Prognosis in Aircraft Systems - Application in the Air Bleed System of Boeing 747." Master's thesis, 2019. http://hdl.handle.net/10316/87984.

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Dissertação de Mestrado em Engenharia Informática apresentada à Faculdade de Ciências e Tecnologia<br>A manutenção de aviões é um tema importante no campo aeronáutico e, à medida que mais informação útil é recolhida e processada, melhoramentos nesta área são valiosos para a indústria da aviação. Neste tópico em particular, CBM pode ser útil, já que pode ajudar a prever quando é que uma falha vai ocorrer baseando-se na condição de saúde dos componentes de avião. Usando CBM, uma abordagem PHM pode ser elaborada com o objetivo de identificar o comportamento de degradação
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