Tesis sobre el tema "Automative diagnosis"
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Sangha, Mahavir Singh. "Intelligent fault diagnosis for automative engines and real data evaluation". Thesis, Liverpool John Moores University, 2008. http://researchonline.ljmu.ac.uk/5867/.
Texto completoWang, Xiaoyu. "A data analytic approach to automatic fault diagnosis and prognosis for distribution automation". Thesis, University of Strathclyde, 2017. http://digitool.lib.strath.ac.uk:80/R/?func=dbin-jump-full&object_id=28772.
Texto completoMourot, Gilles. "Contribution au diagnostic des systèmes industriels par reconnaissance des formes". Vandoeuvre-les-Nancy, INPL, 1993. http://www.theses.fr/1993INPL026N.
Texto completoAxvik, Linda. "Automatic Diagnosis of Breast Tumoursin Ultrasound Images". Thesis, KTH, Tillämpad fysik, 2018. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-233752.
Texto completoDeosthale, Eeshan Vijay. "Model-Based Fault Diagnosis of Automatic Transmissions". The Ohio State University, 2018. http://rave.ohiolink.edu/etdc/view?acc_num=osu1542631227815892.
Texto completoZhong, Binglin. "Model building and machine fault diagnosis". Thesis, Cardiff University, 1994. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.340889.
Texto completoWazaefi, Yanal. "Automatic diagnosis of melanoma from dermoscopic images of melanocytic tumors : Analytical and comparative approaches". Thesis, Aix-Marseille, 2013. http://www.theses.fr/2013AIXM4106.
Texto completoMelanoma is the most serious type of skin cancer. This thesis focused on the development of two different approaches for computer-aided diagnosis of melanoma: analytical approach and comparative approach. The analytical approach mimics the dermatologist’s behavior by first detecting malignancy features based on popular analytical methods, and in a second step, by combining these features. We investigated to what extent the melanoma diagnosis can be impacted by an automatic system using dermoscopic images of pigmented skin lesions. The comparative approach, called Ugly Duckling (UD) concept, assumes that nevi in the same patient tend to share some morphological features so that dermatologists identify a few similarity clusters. UD is the nevus that does not fit into any of those clusters, likely to be suspicious. The goal was to model the ability of dermatologists to build consistent clusters of pigmented skin lesions in patients
Ng, Hoi Sum. "Petri nets for fault diagnosis and distribution automation". Thesis, University of Strathclyde, 1999. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.366530.
Texto completoRibot, Pauline. "Vers l'intégration diagnostic/pronostic pour la maintenance des systèmes complexes". Phd thesis, Université Paul Sabatier - Toulouse III, 2009. http://tel.archives-ouvertes.fr/tel-00450835.
Texto completoLi, Li. "Model-based automatic performance diagnosis of parallel computations /". view abstract or download file of text, 2007. http://proquest.umi.com/pqdweb?did=1335366371&sid=1&Fmt=2&clientId=11238&RQT=309&VName=PQD.
Texto completoTypescript. Includes vita and abstract. Includes bibliographical references (leaves 119-123). Also available for download via the World Wide Web; free to University of Oregon users.
Sinthanayothin, Chanjira. "Image analysis for automatic diagnosis of diabetic retinopathy". Thesis, King's College London (University of London), 1999. https://kclpure.kcl.ac.uk/portal/en/theses/image-analysis-for-automatic-diagnosis-of-diabetic-retinopathy(163f8067-329d-4a48-b214-0ea70ba828d4).html.
Texto completoBOLDT, F. A. "Classifier Ensemble Feature Selection for Automatic Fault Diagnosis". Universidade Federal do Espírito Santo, 2017. http://repositorio.ufes.br/handle/10/9872.
Texto completo"An efficient ensemble feature selection scheme applied for fault diagnosis is proposed, based on three hypothesis: a. A fault diagnosis system does not need to be restricted to a single feature extraction model, on the contrary, it should use as many feature models as possible, since the extracted features are potentially discriminative and the feature pooling is subsequently reduced with feature selection; b. The feature selection process can be accelerated, without loss of classification performance, combining feature selection methods, in a way that faster and weaker methods reduce the number of potentially non-discriminative features, sending to slower and stronger methods a filtered smaller feature set; c. The optimal feature set for a multi-class problem might be different for each pair of classes. Therefore, the feature selection should be done using an one versus one scheme, even when multi-class classifiers are used. However, since the number of classifiers grows exponentially to the number of the classes, expensive techniques like Error-Correcting Output Codes (ECOC) might have a prohibitive computational cost for large datasets. Thus, a fast one versus one approach must be used to alleviate such a computational demand. These three hypothesis are corroborated by experiments. The main hypothesis of this work is that using these three approaches together is possible to improve significantly the classification performance of a classifier to identify conditions in industrial processes. Experiments have shown such an improvement for the 1-NN classifier in industrial processes used as case study."
Nowakowski, Samuel. "Diagnostic dans les systèmes complexes". Habilitation à diriger des recherches, Université Henri Poincaré - Nancy I, 1996. http://tel.archives-ouvertes.fr/tel-00922030.
Texto completoKhemis, Kamila. "Imagerie de fluorescence en cancérologie : spectroscopie, traitement du signal et gestion automatisée pour l'optimisation du diagnostic des tumeurs précoces". Vandoeuvre-les-Nancy, INPL, 1998. http://docnum.univ-lorraine.fr/public/INPL_T_1998_KHEMIS_K.pdf.
Texto completoAfnouch, Marwa. "Machine Learning Applications in Medical Diagnosis, case study : bone metastasis". Electronic Thesis or Diss., Valenciennes, Université Polytechnique Hauts-de-France, 2023. http://www.theses.fr/2023UPHF0039.
Texto completoMetastases are a group of abnormal cells that develop outside the original organ bound aries and spread to other organs. In particular, bone metastases originate in one organ of the body, such as the breast, lung, or prostate, and spread to the bone. Although this disease was discovered more than a century ago, it is still not well defined, and exist ing treatments are weakly effective, possibly because it is difficult and time-consuming to detect. To help physicians, new machine learning technologies promise to improve overall accuracy. This dissertation aims to help radiologists routinely detect bone metas tases using machine learning algorithms. The discovery of methodological biases in studies of bone metastasis diagnosis and the lack of consensus on the interpretability of machine learning have shifted the focus of this dissertation. It now focuses primarily on data collection and overcoming the challenges of validation and interpretability of machine learning. In order to properly assess the ability of machine learning to detect bone metastases, three experimental studies were conducted. The first proposing a novel segmentation approach supported by an attention mechanism to localize bone lesions. The second is a study of machine learning methods for identifying bone metastases cases. Finally, the last study highlights the lack of robustness of classification using machine learning methods and proposes a method to improve accuracy based on both CNN and Transformer approaches. The experimental results of this dissertation are evaluated on our introduced BM-Seg dataset, which is the first benchmark dataset for bone metasta sis segmentation and classification using CT-scans. This novel open-source dataset was used to improve the reproducibility of machine learning experiments. The results of the various preliminary studies are encouraging and promising
CAPONETTI, FABIO. "Detection and diagnosis techniques for hybrid systems". Doctoral thesis, Università Politecnica delle Marche, 2010. http://hdl.handle.net/11566/242228.
Texto completoCheng, Yu-Chung. "Automating cross-layer diagnosis of enterprise 802.11 wireless networks". Connect to a 24 p. preview or request complete full text in PDF format. Access restricted to UC campuses, 2007. http://wwwlib.umi.com/cr/ucsd/fullcit?p3277523.
Texto completoTitle from first page of PDF file (viewed October 10, 2007). Available via ProQuest Digital Dissertations. Vita. Includes bibliographical references (p. 85-89).
Veizaga, Arevalo Maria. "Automation of power quality diagnosis of industrial electrical grids". Electronic Thesis or Diss., université Paris-Saclay, 2022. http://www.theses.fr/2022UPAST158.
Texto completoThe demand for power quality analysis has increased over the past decades. Voltage sags are the most frequent and impactful disturbances in industrial power grids, leading to high financial losses for industrial clients. The core of this thesis work is dedicated to the classification of voltage sag causes and their relative location to the monitoring point. The solution uses voltage and current waveforms as input to identify the causes of voltage sags in LV industrial grids. The methodology is based on four-dimension time series signatures, obtained through the application of the Short-Time Fourier Transform (STFT) and the Fortescue Transform. The source of a voltage sag is identified using a distance-based classification strategy with a custom distance measure based on the Dynamic Time Warping algorithm (DTW). In addition, the soft-DTW algorithm is used to reduce the size of the signature training database and increase speed. The performance of the method was analyzed in terms of class separability, prediction efficiency (accuracy and robustness to noise), and sensitivity to fundamental frequency variations. The proposal is resilient regarding noise levels up to an SNR = 15 dB and fundamental frequency variations up to +/- 0.5 Hz. Moreover, a confidence index on the prediction is proposed, increasing the algorithm's reliability. The proposal offers an easy implementation in industrial applications with no previous recorded data. It has the benefit of using a reduced-size reference database, entirely composed of synthetic data. The main advantages of the proposed method are its generalization capabilities and the possibility of raising an alert based on the confidence index. The obtained classification accuracy on synthetic data with seven causes is 100%. The method reaches a classification F1-score higher than 99% with field measurements representing five classes obtained from three different industrial sites. Finally, we also study the impact of voltage sags on industrial equipment. We propose a methodology to estimate the self-disconnected load composition following a voltage sag. The results showed some limitations in terms of harmonic interaction among the loads. Some of the limits of this approach are discussed, and several proposals to improve the load composition estimation for future work are made
Emad, Ahmed Anwar Hasanin. "Development and assessment of strategies for non-invasive prenatal diagnosis using fetal cells in maternal blood". Thèse, Université de Sherbrooke, 2014. http://hdl.handle.net/11143/5855.
Texto completoLu, Jingxian. "L'auto-diagnostic dans les réseaux autonomes : application à la supervision de services multimédia sur réseau IP de nouvelle génération". Thesis, Bordeaux 1, 2011. http://www.theses.fr/2011BOR14461/document.
Texto completoThe autonomic networks show certain interest to manufacturers and operators of telecommunications. The self-diagnosis, the detection of failure and malfunction, is a critical issue in the context of these networks.We choose based-model diagnosis because it allows an automatic diagnosis, and is suitable to distributed network architecture. This diagnosis is based on an explicit modeling of normal and abnormal behavior of the system. We then use a generic diagnostic algorithm that uses this modeling to perform self-diagnosis. The modeling used is based on causal graph. It is an intuitive and efficient representation of causal relationships between observations and failures.The self-diagnosis algorithm we proposed based on the use of causal graphs. The principle is: when an alarm is triggered, the algorithm is run and, with the causal relationships between alarms and causes, the principal causes will be located. Since the causal graph modeling allows a modular and extensible model, it is possible to separate or merge according to the needs of services and communication architectures. This feature allows us to propose a distributed algorithm that adapts to autonomic network architecture. We have thus proposed a self-diagnosis algorithm that allows for the diagnosis corresponding to the autonomic network architecture to realize a global diagnosis.We have implemented this algorithm on a platform OpenIMS, and we showed that our self-diagnostic algorithm could be used for different types of services. The results of implement correspond to what is expected
Huang, Ke. "Modélisation de fautes et diagnostic pour les circuits mixtes/RF nanométriques". Phd thesis, Université de Grenoble, 2011. http://tel.archives-ouvertes.fr/tel-00670338.
Texto completoBarrera, Núñez Víctor Augusto. "Automatic diagnosis of voltage disturbances in power distribution networks". Doctoral thesis, Universitat de Girona, 2012. http://hdl.handle.net/10803/80944.
Texto completoEn esta tesis se propone una metodología para la identificación de la localización relativa (aguas arriba/abajo) y la causa de una perturbación eléctrica. La metodología utiliza las ondas trifásicas de tensión y de corriente registradas en redes de distribución radial sin presencia de generación distribuida. La metodología es validada utilizando perturbaciones eléctricas reales y simuladas. La metodología involucra atributos que han sido concebidos basándose en principios eléctricos e hipótesis de acuerdo a cada uno de los fenómenos eléctricos analizados. Se propusieron atributos tanto basados en la forma de onda como en la fecha de ocurrencia de la perturbación. La cantidad de información contenida y/o explicada por cada atributo es valorada mediante la aplicación del análisis multivariante de la varianza y algoritmos de extracción automática de reglas de decisión. Los resultados de clasificación muestran que la metodología propuesta puede ser utilizada para el diagnóstico automático de perturbaciones eléctricas registradas en redes de distribución radial. Los resultados de diagnóstico pueden ser utilizados para apoyar las tareas de operación, mantenimiento y planeamiento de las redes de distribución.
Lu, Dingran. "Multi-circle Detections for an Automatic Medical Diagnosis System". DigitalCommons@CalPoly, 2012. https://digitalcommons.calpoly.edu/theses/735.
Texto completoDiez, Lledo Edouard. "Diagnostic et Pronostic de défaillances dans des composants d'un moteur d'avion". Phd thesis, Université Paul Sabatier - Toulouse III, 2008. http://tel.archives-ouvertes.fr/tel-00319675.
Texto completoArsan, Murad Ismet. "Observateurs et diagnostic automatique de pannes". Toulouse, ENSAE, 1994. http://www.theses.fr/1994ESAE0019.
Texto completoKarboub, Kaouter. "Contribution à l'amélioration des performances des services médicaux urgents appliquant l'IoT et l'intelligence artificielle". Electronic Thesis or Diss., Université de Lorraine, 2022. http://www.theses.fr/2022LORR0093.
Texto completoInternet of Things (IoT) and Artificial Intelligence (AI)are two advancing technological areas utilizing the capabilities of performing hands free tasks and intelligent data analysis. These technologies are showing promising potentials of improving the Human-to-Machine interactions in clinical workflow, create a better foundation of clinical decision-making, and improve the accessibility of clinical data. The novel aspect, rapid advancement, and new application possibilities of IoT and AI are in the initial phases. Hence, the thesis research has the objectives of identifying and investigating the potential, challenges, and possibilities of using IoT and AI to assess clinical settings.From the other hand, Various organizations claim that increasing attention should be put on an efficient use of healthcare resources. The internationally rising life expectancy and population size is accompanied by hospitals that are relying more on short admissions, and thus on limited bed capacity. The international World Health Report published by the World Health Organization shows that 20-40% of all healthcare resources are not being sufficiently utilized. Thus, tools that benefit an efficient healthcare system is greatly relevant to the present society. The goal of this thesis is to expand methods in the field of IoT and AI and modeling and optimization to hospital patient flow with a view to provide management and planners with a range of decision tools for improving the utilization of hospital resources. We elaborate on several relevant hospital optimization problems which relate to decision making on both the strategic, tactical and operational level. In addition, we focus on various types of patient flow, from inpatient to outpatient admissions, which has led to many different research studies. Methodologically we mainly focus on evaluating the different instances of patient flow but specifically on patients with cardiovascular diseases (CVD) based on Markov chain modeling.Mainly, the focus was on separating the patient stay in the hospital into three main phases. Each phase in an interdependent, time varying and function of the other phase. The core of the contribution is to assess and give every step of the process of admitting, treating, and discharging patients with solutions that can help physicians take decisions in short time but also take them efficiently. These techniques used IoT in order to collect electrocardiogram signals (ECG) from patients with different CVD pathologies and to transfer these data into a platform that can preprocess it and store it. AI that is used to automatically classify these signals along with three MIT dataset and decide which patients have cardiovascular diseases with no physician intervention. Then AI was used to efficiently predict which patients need to be discharged based on their epidemiological, physiological signals and characteristics and also based on their Length of Stay (LOS) and on their admission and transfer history. Finally, comes the role of using metaheuristic optimization. This last one, into account the admission, treatment trajectory and first survival analysis of these patients to decide which patients will be allocated to a bed in which ward mainly in the Intensive Care Unit (ICU).The proposed system for studying and optimizing the patients flow in a health care facility show high performance based on the different performance metrics we are using in this research project
Bazilo, C. V. y Yu A. Petrushko. "Electroacoustic Transducers for Diagnostic Automatic Systems". Thesis, Sumy State University, 2016. http://essuir.sumdu.edu.ua/handle/123456789/46400.
Texto completoNASIM, AMNAH. "Adaptation of the Segmented Beat Modulation Method to support diagnosis of cardiovascular disorders using electrocardiographic tracings acquired by wearable sensors". Doctoral thesis, Università Politecnica delle Marche, 2021. http://hdl.handle.net/11566/285589.
Texto completoAbstract Designing automatic cardiovascular disease (CVD) diagnostic systems specifically for signals acquired using wearable electrocardiogram (ECG) sensors becomes a challenge specifically requiring solutions for signal distortions caused by high level of motion artifacts and efficient CVD diagnosis. Hence the aim of this thesis is to develop an adaptation of Segmented Beat Modulation Method (SBMM, a template-based method for denoising of ECG signals) using wearable ECG data to additionally account for non-sinus rhythms and to increase the usability of modern wearable sensors in comparison to traditional in-clinic machines for CVD diagnosis. SBMM has currently failed to work with abnormal or arrhythmic (rare but critical events often leading to sudden cardiac death) heartbeats which hugely limits its applicability to cardiovascular disease diagnosis in a real-world scenario. To this aim, this work presents Extended Segmented Beat Modulation Method with a heartbeat classification function using convolutional neural network (CNN) that first separates the normal (N) from supraventricular (S) and ventricular (V) heartbeats and secondly uses separate median representative templates to denoise and reconstruct the clean ECG recording. Overall, the CNN classification accuracy (Ac) was 91.5% while the positive predictive (PP) values were 92.8%, 95.6%, and 83.6%, for N, S, and V beat classes, respectively. Eventually, signal-to-noise (SNR) improvement was less than 2 dB in the absence of noise but increased in the presence of noise until exceeding 5 dB in the presence of electrode motion artifacts. Hence, ESBMM proved to be a reliable tool to classify cardiac beats into N, S, and V classes and to denoise ECG tracings characterized by both sinus and non-sinus rhythms maintaining the morphological variability in the pseudo-periodic ECG signal. Other improvements proposed to SBMM are a preliminary compression test using discrete cosine transform. The method is evaluated using SNR and compression ratio (CR) considering varying levels of signal energy in the reconstructed ECG signal. For denoising, an average SNR of 4.56 dB was achieved representing an average overall decline of 1.68 dBs (37.9%) as compared to the uncompressed signal processing while 95% of signal energy is intact and quantized at 6 bits for signal storage (CR=2) compared to the original 12 bits, hence resulting in 50% reduction in storage size. Another improvement dynamic-template SBMM adapts SBMM to heart rate and generates the template in a dynamic fashion every 20 seconds and is particularly targeted and tested for long-term ECG data acquisitions. Another presented improvement adapts SBMM to modern fast hardware using vectorization technique and graphical processing units called GPU-SBMM. GPU-SBMM application yielded a significant increase of SNR (from 1±5 dB to 19±5 dB; p<10E-10). Additionally, a considerable speed up in the algorithm runtime (3.56x on average on an NVIDIA GeForce GPU) was achieved. In a secondary domain, an automated arrhythmia detection system is presented that is designed to produce maximum diagnostic accuracy with minimum amount of data (removing redundant and noisy data) using differential evolution (DE) and a less computationally intense probabilistic neural network (PNN). All tests are performed for ambulatory and long term ECG signals acquired using wearable sensing modality. The proposed DE-PNN scheme provides better classification accuracy considering 8 classes with only 41 features optimized from a 253 element feature set implying an 83.7% reduction in direct amplitude features compared to the other evolutionary and statistical schemes. In conclusion, this work has proved beneficial for improving the quality and efficiency of automatic cardiovascular disease diagnosis system on a modern and evolving cardiovascular health monitoring platform i.e. wearable ECG sensors.
HU, YIHUI. "Design of supervisors for active diagnosis in discrete event systems". Doctoral thesis, Università degli Studi di Cagliari, 2021. http://hdl.handle.net/11584/324542.
Texto completoJoin, Cédric. "Une approche algébrique pour la pratique de l'estimation, du diagnostic, de la commande et de la finance". Habilitation à diriger des recherches, Université de Lorraine, 2012. http://tel.archives-ouvertes.fr/tel-00759370.
Texto completoGemmell, Brian David. "A consultative expert system for intelligent diagnosis on steam turbine plant". Thesis, University of Strathclyde, 1995. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.340915.
Texto completoFolkesson, Christer. "Automatic Error Diagnostic for Network Connection Problems". Thesis, Uppsala University, Department of Information Technology, 2009. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-112170.
Texto completoCustomer support inquires about software and network settings takes time and costs money, both for the customer and the vendor giving the support. Doing troubleshooting and problem solving automatically can lower the need for inquires, and when needed, raise the quality of the contact for the customer.
Can a nearly automatic program do sufficient network diagnostic and let an end user alleviating the problem found all on their own?
I surveyed the offerings of such functionality by the current desktop operating system in use. I also developed a prototype that could do automatic error diagnostic of network software settings and the connection to important network services.
The newest operating systems (Windows 7 and Mac OS X Snow Leopard) have good automatic error diagnostic facilities for generic network problems, but older versions like Windows XP has only limited capability. The prototype look at the same problem, but also take it a step further and test the availability and connection quality to a vendor’s specific network service.
For solving generic network problems and when having the newest version of the operating system the benefit of a separate tool is not great. But when a company requires more specific network testing related to their product, and possible retrieve other valuable information for the customer support about the computer setup, a custom developed tool has its benefits.
FARSONI, SAVERIO. "Data-Driven Fault Diagnosis and Fault Tolerant Control of Wind Turbines". Doctoral thesis, Università degli studi di Ferrara, 2016. http://hdl.handle.net/11392/2403501.
Texto completoIn recent years, the increasing demand for energy generation from renewable sources has led to a growing attention on wind turbines. Indeed, they represent very complex systems which require reliability, availability, maintainability, safety and, above all, efficiency on the generation of electrical power. Thus, new research challenges arise, in particular in the context of modeling and control. Advanced sustainable control systems can provide the optimization of energy conversion and guarantee the desired performances even in presence of possible anomalous working condition, caused by unexpected faults and malfunctions. This thesis deals with the fault diagnosis and the fault tolerant control of wind turbines, and it proposes novel solutions to the problem of earlier fault detection and accommodation. The developed fault tolerant controller is mainly based on a fault diagnosis module, that provides the on-line information on the faulty or fault-free status of the system, so that the controller action can be compensated. The design of the fault estimators involves data-driven approaches, as they offer an effective tool for coping with a poor analytical knowledge of the system dynamics, together with noise and disturbances. The first data-driven proposed solution relies on fuzzy Takagi-Sugeno (TS) models, that are derived from a clustering c-means algorithm, followed by an identification procedure solving the noise-rejection problem. Then, a second solution makes use of neural networks to describe the strongly nonlinear relationships between measurement and faults. The chosen network architecture belongs to the Nonlinear AutoRegressive with eXogenous input (NARX) topology, as it can represent a dynamic evolution of the system along time. The training of the neural network fault estimators exploits the backpropagation Levenberg-Marquardt algorithm, that processes a set of acquired target data. The developed fault diagnosis and fault tolerant control schemes are tested by means of two high-fidelity benchmark models, that simulate the normal and the faulty behavior of a single wind turbine and a wind farm, respectively. The achieved performances are compared with those of other control strategies, coming from the related literature. Moreover, a Monte Carlo analysis validates the robustness of the proposed systems against the typical parameter uncertainties and disturbances. Finally, the Hardware In the Loop (HIL) test is carried out, in order to assess the performance in a more realistic real-time framework. The effectiveness shown by the achieved results suggests further investigations on the industrial application of the proposed systems.
Monroy, Chora Isaac. "An investigation on automatic systems for fault diagnosis in chemical processes". Doctoral thesis, Universitat Politècnica de Catalunya, 2012. http://hdl.handle.net/10803/77637.
Texto completoLa seguridad de planta es el problema más inquietante para las industrias químicas. Un fallo en planta puede causar pérdidas económicas y daños humanos y al medio ambiente. La mayoría de los fallos operacionales son previstos en la etapa de diseño de un proceso mediante la aplicación de técnicas de Análisis de Riesgos y de Operabilidad (HAZOP). Sin embargo, existe la probabilidad de que pueda originarse un fallo en una planta en operación. Por esta razón, es de suma importancia que una planta pueda detectar y diagnosticar fallos en el proceso y tomar las medidas correctoras adecuadas para mitigar los efectos del fallo y evitar lamentables consecuencias. Es entonces también importante el mantenimiento preventivo para aumentar la seguridad y prevenir la ocurrencia de fallos. La diagnosis de fallos ha sido abordada tanto con modelos analíticos como con modelos basados en datos y usando varios tipos de técnicas y algoritmos. Sin embargo, hasta ahora no existe la propuesta de un sistema general de seguridad en planta que combine detección y diagnosis de fallos ya sea registrados o no registrados anteriormente. Menos aún se han reportado metodologías que puedan ser automatizadas e implementadas en la práctica real. Con la finalidad de abordar el problema de la seguridad en plantas químicas, esta tesis propone un sistema general para la detección y diagnosis de fallos capaz de implementarse de forma automatizada en cualquier industria. El principal requerimiento para la construcción de este sistema es la existencia de datos históricos de planta sin previo filtrado. En este sentido, diferentes métodos basados en datos son aplicados como métodos de diagnosis de fallos, principalmente aquellos importados del campo de “Aprendizaje Automático”. Estas técnicas de aprendizaje han resultado ser capaces de detectar y diagnosticar no sólo los fallos modelados o “aprendidos”, sino también nuevos fallos no incluidos en los modelos de diagnosis. Aunado a esto, algunas técnicas de mantenimiento basadas en riesgo (RBM) que son ampliamente usadas en la industria petroquímica, son también propuestas para su aplicación en el resto de sectores industriales como parte del mantenimiento preventivo. En conclusión, se propone implementar en un futuro no lejano un programa general de seguridad de planta que incluya el sistema de detección y diagnosis de fallos propuesto junto con un adecuado programa de mantenimiento preventivo. Desglosando el contenido de la tesis, el capítulo uno presenta una introducción general al tema de esta tesis, así como también la motivación generada para su desarrollo y el alcance delimitado. El capítulo dos expone el estado del arte de las áreas relacionadas al tema de tesis. De esta forma, los métodos de detección y diagnosis de fallos encontrados en la literatura son examinados en este capítulo. Asimismo, se propone una taxonomía de los métodos de diagnosis que unifica las clasificaciones propuestas en el área de Inteligencia Artificial y de Ingeniería de procesos. En consecuencia, se examina también la evaluación del performance de los métodos de diagnosis en la literatura. Además, en este capítulo se revisa y reporta el estado del arte correspondiente al “Análisis de Riesgos” y a la “Gestión del Mantenimiento” como técnicas complementarias para la toma de medidas correctoras y preventivas. Por último se abordan los casos de estudio considerados como puntos de referencia en el campo de investigación para la aplicación del sistema propuesto. La tercera parte incluye el capítulo siete, el cual constituye el corazón de la tesis. En este capítulo se presenta el esquema o sistema general de diagnosis de fallos propuesto. El sistema es dividido en tres partes: construcción de los modelos de diagnosis, validación de los modelos y aplicación on-line. Además incluye un modulo de detección de fallos previo a la diagnosis y una metodología de detección de anomalías para la detección de nuevos fallos. Por último, de este sistema se desglosan varias metodologías para procesos continuos y por lote. La cuarta parte de esta tesis presenta la validación de las metodologías propuestas. Específicamente, el capítulo ocho presenta la validación de las metodologías propuestas para su aplicación en procesos continuos y el capítulo nueve presenta la validación de las metodologías correspondientes a los procesos por lote. El capítulo diez valida la metodología de detección de anomalías en procesos por lote reales. Primero es aplicada a un intercambiador de calor escala laboratorio y después su aplicación es escalada a un proceso Foto-Fenton de planta piloto, lo cual corrobora el potencial y éxito de la metodología en la práctica real. Finalmente, la quinta parte de esta tesis, compuesta por el capítulo once, es dedicada a presentar y reafirmar las conclusiones finales y las principales contribuciones de la tesis. Además, se plantean las líneas de investigación futuras y se lista el trabajo desarrollado y presentado durante el periodo de investigación.
Nie, Yali. "Automatic Melanoma Diagnosis in Dermoscopic Imaging Base on Deep Learning System". Licentiate thesis, Mittuniversitetet, Institutionen för elektronikkonstruktion, 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:miun:diva-41751.
Texto completoRound, Andrew John. "Texture and colour for automatic image-based skin lesion analysis". Thesis, Bangor University, 1998. https://research.bangor.ac.uk/portal/en/theses/texture-and-colour-for-automatic-imagebased-skin-lesion-analysis(6f44bc07-d680-4aee-941b-49ba4ddd5314).html.
Texto completoHallgren, Dan y Håkan Skog. "Distributed Fault Diagnosis for Networked Embedded Systems". Thesis, Linköping University, Department of Electrical Engineering, 2005. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-5229.
Texto completoIn a system like a Scania heavy duty truck, faultcodes (DTCs) are generated and stored locally in the ECUs when components, e.g. sensors or actuators, malfunction. Tests are run periodically to detect failure in the system. The test results are processed by the diagnostic system that tries to isolate the faulty components and set local faultcodes.
Currently, in a Scania truck, local diagnoses are only based on local diagnostic information, which the DTCs are based upon. The diagnosis statement can, however, be more complete if diagnoses from other ECUs are considered. Thus a system that extends the local diagnoses by exchanging diagnostic information between the ECUs is desired. The diagnostic information to share and how it should be done is elaborated in this thesis. Further, a model of distributed diagnosis is given and a few distributed diagnostic algorithms for transmitting and receiving diagnostic information are presented.
A basic idea that has influenced the project is to make the diagnostic system scalable with respect to hardware and thereby making it easy to add and remove ECUs. When implementing a distributed diagnostic system in networked real-time embedded systems, technical problems arise such as memory handling, process synchronization and transmission of diagnostic data and these will be discussed in detail. Implementation of a distributed diagnostic system is further complicated due to the fact that the isolation process is a non deterministic job and requires a non deterministic amount of memory.
Sévigny, Johanne. "Méthode de diagnostic automatique pour les systèmes d'asservissement". Thesis, University of Ottawa (Canada), 1989. http://hdl.handle.net/10393/5605.
Texto completoAhriz, Hatem. "Modélisation automatique de systèmes physiques : application au diagnostic". Chambéry, 1998. http://www.theses.fr/1998CHAMS013.
Texto completoPastor, Laetitia. "Système automatique d'aide au diagnostic en tomodensitométrie pulmonaire". Besançon, 2004. http://www.theses.fr/2004BESA2026.
Texto completoLetellier, Clément. "Diagnostic robuste des systèmes incertains. Application à un système mécatronique pour l'automobile". Phd thesis, Université de Rouen, 2012. http://tel.archives-ouvertes.fr/tel-00747981.
Texto completoJaziri, Samy. "Automate sur les structures temporisée". Thesis, Université Paris-Saclay (ComUE), 2019. http://www.theses.fr/2019SACLN039/document.
Texto completoDigital system are now part of our society. They are used in a wide range of domainsand in particular they have to handle delicate tasks. Already used in domainssuch as transportation, surgery or economy, we speak now of using digital systemsfor social or political matters : electronic vote, selection algorithms, electoralprofilingdots For task handled by algorithm, the responsibility is moved from theexecutioner to the designer, developer and tester of those algorithms. It is alsothe responsibility of computer scientists who study those algorithms to proposereliable techniques of verification which will be applicable in the design, thedevelopment or the testing phase. Formal verification methods provide mathematicaltools to prevent executions error in all phases. Among them, fault-diagnosis consiston the construction of a diagnoser based on a formal model of the system we aim tocheck. The diagnoser runs in parallel with the real system and emit a warning anytime it detect a dangerous behavior. For systems modeled by timed automata, it isnot always possible to construct a timed automaton to diagnose it. Indeed timed automata,introduce in the nineties by cite{AD94} and widely studied and used since to modeltimed systems, are not determinizable. A machine, more powerful than a timed automaton,can still be used to construct the diagnoser of a timed automaton as it is done incite{Tripakis02}. This thesis work aim at constructing a diagnoser for any one-clocktimed automata. This diagnoser is constructed with the help of a machine more powerfulthan timed automata, following the idea of cite{Tripakis02}. Part~I of this thesisintroduce a formal framework for the modeling of quantitative systems and the study oftheir determinization. In this framework we introduce automata on timed structures,the model used to construct the diagnoser. Part~II study the determinization problemof automata on timed structures, and particularly the one of timed automatadeterminization in this framework. Part~III illustrate how automata on timed structurescan be used to construct in a generic way a diagnoser for one clock timed automata.This technique is implemented in a tool, DOTA , and is compared to the technique usedin cite{Tripakis02}
Pascarella, Pietro. "Fault detection e diagnosis di macchine automatiche con tecniche di data mining". Master's thesis, Alma Mater Studiorum - Università di Bologna, 2017.
Buscar texto completoRayhane, Hassan. "Surveillance des systèmes de production automatisés : détection et aide au diagnostic". Phd thesis, Grenoble INPG, 2004. http://tel.archives-ouvertes.fr/tel-00169988.
Texto completoPartant d'un système commandé, le premier objectif est la surveillance des différentes activités de ce système afin d'améliorer sa disponibilité. Ceci se traduit par la minimisation du nombre d'arrêts qui pénalisent la production, en suivant en temps réel, l'état de fonctionnement des différents capteurs du système. Ainsi pour chaque tâche, la surveillance du temps écoulé entre deux événements (l'instant où la commande a donné l'ordre de démarrer une tâche et l'instant où le capteur indique la fin d'exécution de la tâche) permet de détecter au plutôt d'éventuelles défaillances. La deuxième phase correspond au diagnostic qui consiste en la détermination des causes du problème observé.
Jusqu'à présent les approches de surveillance utilisent un modèle de référence basé sur la connaissance à priori de toutes les situations interdites du système. Le modèle de surveillance proposé présente un réel avantage. En effet, la détection d'éventuelles défaillances ne nécessite pas une liste exhaustive de toutes les défaillances possibles du système. En fonction de la catégorie du système de production et de la nature des tâches à surveiller nous introduisons une tolérance sur la durée de la tâche à surveiller. Ainsi, la notion de fonctionnement en ‘ mode dégradé' est introduite. Au-delà de cette tolérance, le système sera effectivement dans un état de ‘défaillance'. Différents exemples illustrent la démarche proposée. Ils permettent de montrer la puissance d'une telle approche. De plus, un algorithme permettant le calcul du seuil optimal de tolérance est proposé, ainsi que l'évaluation des performances du système de surveillance.
Issury, Irwin. "Contribution au développement d'une stratégie de diagnostic global en fonction des diagnostiqueurs locaux : Application à une mission spatiale". Phd thesis, Bordeaux 1, 2011. http://tel.archives-ouvertes.fr/tel-00643548.
Texto completoNgo, Quoc Dung. "Diagnostic de systèmes hybrides incertains par génération automatique de relations de redondance analytique symboliques évaluées par approche ensembliste". Phd thesis, Université de Grenoble, 2012. http://tel.archives-ouvertes.fr/tel-00830791.
Texto completoBaldi, Pietro <1981>. "Fault detection, diagnosis and active fault tolerant control for a satellite attitude control system". Doctoral thesis, Alma Mater Studiorum - Università di Bologna, 2015. http://amsdottorato.unibo.it/6983/1/Baldi_Pietro_tesi.pdf.
Texto completoBaldi, Pietro <1981>. "Fault detection, diagnosis and active fault tolerant control for a satellite attitude control system". Doctoral thesis, Alma Mater Studiorum - Università di Bologna, 2015. http://amsdottorato.unibo.it/6983/.
Texto completoFrizzoni, Giulia. "A New Method for Automatic Actuator Fault Diagnosis for Autonomous Underwater Vehicles". Master's thesis, Alma Mater Studiorum - Università di Bologna, 2020.
Buscar texto completoØdegård, Jan y Anders Østen. "Automatic diagnosis of ultrasound images using standard view planes of fetal anatomy". Thesis, Norwegian University of Science and Technology, Department of Computer and Information Science, 2006. http://urn.kb.se/resolve?urn=urn:nbn:no:ntnu:diva-10078.
Texto completoThe use of ultrasound has revolutionised the area of clinical fetal examinations. The possibility of detecting congenital abnormalities at an early stage of the pregnancy is highly important to maximise the chances of correcting the defect before it becomes life-threatening. The problems related to the routine procedure is its complexity and the fact that it requires a lot of knowledge about fetal anatomy. Because of the lack of training among midwives, especially in less developed countries, the results of the examinations are often limited. In addition, the quality of the ultrasound equipment is often restricted. These limitations imply the need for a standardised procedure for the examination to decrease the amount of time required, as well as an automatic method for proposing the diagnosis of the fetus. This thesis has proposed a solution for automatically making a diagnosis based on the contents of extracted ultrasound images. Based on the concept of standard view planes, a list of predefined images are obtained of the fetus during the routine ultrasonography. These images contain the most important organs to examine, and most common congenital abnormalities are therefore detectable in this set. In order to perform the analysis of the images, medical domain knowledge must be obtained and stored to enable reasoning about the findings in the ultrasound images. The findings are extracted through segmentation and each object is given a unique description. An organ database is developed to store descriptions about existing organs to recognise the extracted objects. Once the organs have been identified, a CBR system is applied to analyse the total contents of one standard view plane. The CBR system uses domain knowledge from the medical domain as well as previously solved problems to identify possible abnormalities in the case describing the standard view plane. When a solution is obtained, it is stored for later retrieval. This causes the reliability of future examinations to increase, because of the constant expansion of the knowledge base. The foundation of standard view planes ensures an effective procedure and the amount of training needed to learn the procedure is minimised due to the automatic extraction and analysis of the contents of the standard view plane. The midwife only has to learn which standard view planes to obtain, not the analysis of their contents.