Las Redes de Petri Interpretadas en el Diagnóstico de Fallos de Sistemas Híbridos. Aplicación a un Helicóptero no Tripulado

La seguridad y fiabilidad de los procesos industriales son la principal preocupación de los ingenieros encargados de las plantas industriales. Por lo tanto, desde un punto de vista económico, el objetivo principal es reducir el costo del mantenimiento, el tiempo de inactividad y las pérdidas causadas por los fallos. Por otra parte, la seguridad de los operadores, que afecta a los aspectos sociales y económicos, es el factor más relevante a considerar en cualquier sistema Debido a esto, el diagnóstico de fallos se ha convertido en un foco importante de interés para los investigadores de todo el mundo e ingenieros en la industria. Los principales trabajos enfocados en detección de fallos se basan en modelos de los procesos. Existen diferentes técnicas para el modelado de procesos industriales tales como máquinas de estado, árboles de decisión y Redes de Petri (RdP). Por lo tanto, esta tesis se centra en el modelado de procesos utilizando redes de petri interpretadas. Redes de Petri es una herramienta usada en el modelado gráfico y matemático con la habilidad para describir información de los sistemas de una manera concurrente, paralela, asincrona, distribuida y no determinística o estocástica. RdP son también una herramienta de comunicación visual gráfica útil como lo son las cartas de flujo o diagramas de bloques. Adicionalmente, las marcas de las RdP simulan la dinámica y concurrencia de los sistemas. Finalmente, ellas tienen la capacidad de definir ecuaciones de estado específicas, ecuaciones algebraicas y otros modelos que representan el comportamiento común de los sistemas. Entre los diferentes tipos de redes de petri (Interpretadas, Coloreadas, etc.), este trabajo de investigación trata con redes de petri interpretadas principalmente debido a características tales como sincronización, lugares temporizados, aparte de su capacidad para procesamiento de datos. Esta investigación comienza con el proceso para diseñar y construir el modelo y diagnosticador para detectar fallos definitivos, posteriormente, la dinámica temporal fue adicionada para detectar fallos intermitentes. Dos procesos industriales, concretamente un HVAC (Calefacción, Ventilación y Aire Acondicionado) y un Proceso de Envasado de Líquidos fueron usados como banco de pruebas para implementar la herramienta de diagnóstico de fallos (FD) creada. Finalmente, su capacidad de diagnóstico fue ampliada en orden a detectar fallos en sistemas híbridos. Finalmente, un pequeño helicóptero no tripulado fue elegido como ejemplo de sistema donde la seguridad es un desafío, y las técnicas de detección de fallos desarrolladas en esta tesis llevan a ser una herramienta valorada, desde que los accidentes de las aeronaves no tripuladas (UAVs) envuelven un alto costo económico y son la principal razón para introducir restricciones de volar sobre áreas pobladas. Así, este trabajo introduce un proceso sistemático para construir un Diagnosticador de Fallos del sistema mencionado basado en RdR Esta novedosa herramienta es capaz de detectar fallos definitivos e intermitentes. El trabajo realizado es discutido desde un punto de vista teórico y práctico. El procedimiento comienza con la división del sistema en subsistemas para seguido integrar en una RdP diagnosticadora global que es capaz de monitorear el sistema completo y mostrar las variables críticas al operador en orden a determinar la salud del UAV, para de esta manera prevenir accidentes. Un Sistema de Adquisición de Datos (DAQ) ha sido también diseñado para recoger datos durante los vuelos y alimentar la RdP diagnosticadora. Vuelos reales realizados bajo condiciones normales y de fallo han sido requeridos para llevar a cabo la configuración del diagnosticador y verificar su comportamiento. Vale la pena señalar que un alto riesgo fue asumido en la generación de fallos durante los vuelos, a pesar de eso esto permitió recoger datos básicos para desarrollar el diagnóstico de fallos, técnicas de aislamiento, protocolos de mantenimiento, modelos de comportamiento, etc. Finalmente, un resumen de la validación de resultados obtenidos durante las pruebas de vuelo es también incluido. Un extensivo uso de esta herramienta mejorará los protocolos de mantenimiento para UAVs (especialmente helicópteros) y permite establecer recomendaciones en regulaciones. El uso del diagnosticador usando redes de petri es considerado un novedoso enfoque. ABSTRACT Safety and reliability of industrial processes are the main concern of the engineers in charge of industrial plants. Thus, from an economic point of view, the main goal is to reduce the maintenance downtime cost and the losses caused by failures. Moreover, the safety of the operators, which affects to social and economic aspects, is the most relevant factor to consider in any system. Due to this, fault diagnosis has become a relevant focus of interest for worldwide researchers and engineers in the industry. The main works focused on failure detection are based on models of the processes. There are different techniques for modelling industrial processes such as state machines, decision trees and Petri Nets (PN). Thus, this Thesis is focused on modelling processes by using Interpreted Petri Nets. Petri Nets is a tool used in the graphic and mathematical modelling with ability to describe information of the systems in a concurrent, parallel, asynchronous, distributed and not deterministic or stochastic manner. PNs are also useful graphical visual communication tools as flow chart or block diagram. Additionally, the marks of the PN simulate the dynamics and concurrence of the systems. Finally, they are able to define specific state equations, algebraic equations and other models that represent the common behaviour of systems. Among the different types of PN (Interpreted, Coloured, etc.), this research work deals with the interpreted Petri Nets mainly due to features such as synchronization capabilities, timed places, apart from their capability for processing data. This Research begins with the process for designing and building the model and diagnoser to detect permanent faults, subsequently, the temporal dynamic was added for detecting intermittent faults. Two industrial processes, namely HVAC (Heating, Ventilation and Air Condition) and Liquids Packaging Process were used as testbed for implementing the Fault Diagnosis (FD) tool created. Finally, its diagnostic capability was enhanced in order to detect faults in hybrid systems. Finally, a small unmanned helicopter was chosen as example of system where safety is a challenge and fault detection techniques developed in this Thesis turn out to be a valuable tool since UAVs accidents involve high economic cost and are the main reason for setting restrictions to fly over populated areas. Thus, this work introduces a systematic process for building a Fault Diagnoser of the mentioned system based on Petri Nets. This novel tool is able to detect both intermittent and permanent faults. The work carried out is discussed from theoretical and practical point of view. The procedure begins with a division of the system into subsystems for further integration into a global PN diagnoser that is able to monitor the whole system and show critical variables to the operator in order to determine the UAV health, preventing accidents in this manner. A Data Acquisition System (DAQ) has been also designed for collecting data during the flights and feed PN Diagnoser. Real flights carried out under nominal and failure conditions have been required to perform the diagnoser setup and verify its performance. It is worth noting that a high risk was assumed in the generation of faults during the flights, nevertheless this allowed collecting basic data so as to develop fault diagnosis, isolations techniques, maintenance protocols, behaviour models, etc. Finally, a summary of the validation results obtained during real flight tests is also included. An extensive use of this tool will improve preventive maintenance protocols for UAVs (especially helicopters) and allow establishing recommendations in regulations. The use of the diagnoser by using Petri Nets is considered as novel approach.

Desenvolvimento de um método para diagnose de falhas na operação de navios transportadores de gás natural liquefeito através de redes bayesianas.

O Gás Natural Liquefeito (GNL) tem, aos poucos, se tornado uma importante opção para a diversificação da matriz energética brasileira. Os navios metaneiros são os responsáveis pelo transporte do GNL desde as plantas de liquefação até as de regaseificação. Dada a importância, bem como a periculosidade, das operações de transporte e de carga e descarga de navios metaneiros, torna-se necessário não só um bom plano de manutenção como também um sistema de detecção de falhas que podem ocorrer durante estes processos. Este trabalho apresenta um método de diagnose de falhas para a operação de carga e descarga de navios transportadores de GNL através da utilização de Redes Bayesianas em conjunto com técnicas de análise de confiabilidade, como a Análise de Modos e Efeitos de Falhas (FMEA) e a Análise de Árvores de Falhas (FTA). O método proposto indica, através da leitura de sensores presentes no sistema de carga e descarga, quais os componentes que mais provavelmente estão em falha. O método fornece uma abordagem bem estruturada para a construção das Redes Bayesianas utilizadas na diagnose de falhas do sistema.

On sensor network segmentation for urban water distribution monitoring

Identifying water wastage in forms of leaks in a water distribution network of any city becomes essential as droughts are presenting serious threats to few major cities. In this paper, we propose a deployment of sensor network for monitoring water flow in any water distribution network. We cover the issues related with designing such a dedicated sensor network by considering types of sensors required, sensors' functionality, data collection, and providing computation serving as leak detection mechanism. The main focus of this paper is on appropriate network segmentation that provides the base for hierarchical approach to pipes' failure detection. We show a method for sensors allocation to the network in order to facilitate effective pipes monitoring. In general, the identified computational problem belongs to hard problems. The paper shows a heuristic method to build effective hierarchy of the network segmentation.

Echocardiographic detection of congestive heart failure in postinfarction rats

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Detection of muscle wasting in patients with chronic heart failure using C-terminal agrin fragment: results from the Studies Investigating Co-morbidities Aggravating Heart Failure (SICA-HF).

AIMS Skeletal muscle wasting affects 20% of patients with chronic heart failure and has serious implications for their activities of daily living. Assessment of muscle wasting is technically challenging. C-terminal agrin-fragment (CAF), a breakdown product of the synaptically located protein agrin, has shown early promise as biomarker of muscle wasting. We sought to investigate the diagnostic properties of CAF in muscle wasting among patients with heart failure. METHODS AND RESULTS We assessed serum CAF levels in 196 patients who participated in the Studies Investigating Co-morbidities Aggravating Heart Failure (SICA-HF). Muscle wasting was identified using dual-energy X-ray absorptiometry (DEXA) in 38 patients (19.4%). Patients with muscle wasting demonstrated higher CAF values than those without (125.1 ± 59.5 pmol/L vs. 103.8 ± 42.9 pmol/L, P = 0.01). Using receiver operating characteristics (ROC), we calculated the optimal CAF value to identify patients with muscle wasting as >87.5 pmol/L, which had a sensitivity of 78.9% and a specificity of 43.7%. The area under the ROC curve was 0.63 (95% confidence interval 0.56-0.70). Using simple regression, we found that serum CAF was associated with handgrip (R = - 0.17, P = 0.03) and quadriceps strength (R = - 0.31, P < 0.0001), peak oxygen consumption (R = - 0.5, P < 0.0001), 6-min walk distance (R = - 0.32, P < 0.0001), and gait speed (R = - 0.2, P = 0.001), as well as with parameters of kidney and liver function, iron metabolism and storage. CONCLUSION CAF shows good sensitivity for the detection of skeletal muscle wasting in patients with heart failure. Its assessment may be useful to identify patients who should undergo additional testing, such as detailed body composition analysis. As no other biomarker is currently available, further investigation is warranted.

Guidelines for the prevention, detection and management of people with chronic heart failure in Australia 2006

* Chronic heart failure (CHF) is found in 1.5%–2.0% of Australians. Considered rare in people aged less than 45 years, its prevalence increases to over 10% in people aged ≥ 65 years. * CHF is one of the most common reasons for hospital admission and general practitioner consultation in the elderly (≥ 70 years). * Common causes of CHF are ischaemic heart disease (present in > 50% of new cases), hypertension (about two-thirds of cases) and idiopathic dilated cardiomyopathy (around 5%–10% of cases). * Diagnosis is based on clinical features, chest x-ray and objective measurement of ventricular function (eg, echocardiography). Plasma levels of B-type natriuretic peptide (BNP) may have a role in diagnosis, primarily as a test for exclusion. Diagnosis may be strengthened by a beneficial clinical response to treatment(s) directed towards amelioration of symptoms. * Management involves prevention, early detection, amelioration of disease progression, relief of symptoms, minimisation of exacerbations, and prolongation of survival.

Molecular basis for porcine parvovirus detection in dead fetuses

Reproductive failures are still common grounds for complaint by commercial swine producers. Porcine parvovirus (PPV) is associated with different clinical reproductive signs. The aim of the present study was to investigate PPV fetal infection at swine farms having ongoing reproductive performance problems. The presence of virus in fetal tissues was determined by nested-polymerase chain reaction assay directed to the conserved NS1 gene of PPV in aborted fetuses, mummies and stillborns. Fetuses show a high frequency of PPV infection (96.4%; N = 28). In 60.7% of the fetuses, PPV were detected in all tissue samples (lung, heart, thymus, kidney, and spleen). Viral infection differed among fetal tissues, with a higher frequency in the lung and heart (P < 0.05). Fetuses with up to 99 days of gestational age and from younger sows showed a higher frequency of PPV (P < 0.05). No significant difference in the presence of PPV was detected among the three clinical presentations. The results suggest that PPV remains an important pathogenic agent associated with porcine fetal death.

Development and evaluation of neural network freeway incident detection models using field data

This paper discusses a multi-layer feedforward (MLF) neural network incident detection model that was developed and evaluated using field data. In contrast to published neural network incident detection models which relied on simulated or limited field data for model development and testing, the model described in this paper was trained and tested on a real-world data set of 100 incidents. The model uses speed, flow and occupancy data measured at dual stations, averaged across all lanes and only from time interval t. The off-line performance of the model is reported under both incident and non-incident conditions. The incident detection performance of the model is reported based on a validation-test data set of 40 incidents that were independent of the 60 incidents used for training. The false alarm rates of the model are evaluated based on non-incident data that were collected from a freeway section which was video-taped for a period of 33 days. A comparative evaluation between the neural network model and the incident detection model in operation on Melbourne's freeways is also presented. The results of the comparative performance evaluation clearly demonstrate the substantial improvement in incident detection performance obtained by the neural network model. The paper also presents additional results that demonstrate how improvements in model performance can be achieved using variable decision thresholds. Finally, the model's fault-tolerance under conditions of corrupt or missing data is investigated and the impact of loop detector failure/malfunction on the performance of the trained model is evaluated and discussed. The results presented in this paper provide a comprehensive evaluation of the developed model and confirm that neural network models can provide fast and reliable incident detection on freeways. (C) 1997 Elsevier Science Ltd. All rights reserved.

Usefulness of MLPA in the detection of SHOX deletions

SHOX haploinsufficiency causes a wide spectrum of short stature phenotypes, such as Leri-Weill dyschondrosteosis (LWD) and disproportionate short stature (DSS). SHOX deletions are responsible for approximately two thirds of isolated haploinsufficiency; therefore, it is important to determine the most appropriate methodology for detection of gene deletion. In this study, three methodologies for the detection of SHOX deletions were compared: the fluorescence in situ hybridization (FISH), microsatellite analysis and multiplex ligation-dependent probe amplification (MLPA). Forty-four patients (8 LWD and 36 DSS) were analyzed. The cosmid LLNOYCO3`M`34F5 was used as a probe for the FISH analysis and microsatellite analysis were performed using three intragenic microsatellite markers. MLPA was performed using commercial kits. Twelve patients (8 LWD and 4 DSS) had deletions in SHOX area detected by MLPA and 2 patients generated discordant results with the other methodologies. In the first case, the deletion was not detected by FISH. In the second case, both FISH and microsatellite analyses were unable to identify the intragenic deletion. In conclusion, MLPA was more sensitive, less expensive and less laborious; therefore, it should be used as the initial molecular method for the detection of SHOX gene deletion. (C) 2010 Elsevier Masson SAS. All rights reserved.

Ventricular dysfunction in early diabetic heart disease: detection, mechanisms and significance

The detection of preclinical heart disease is a new direction in diabetes care. This comment describes the study by Vinereanu and co-workers in this issue of Clinical Science in which tissue Doppler echocardiography has been employed to demonstrate subtle systolic and diastolic dysfunction in Type 11 diabetic patients who had normal global systolic function and were free of coronary artery disease. The aetiology of early ventricular dysfunction in diabetes relates to complex intramyocardial and extramyocardial mechanisms. The initiating event may be due to insulin resistance, and involves abnormal myocardial substrate utilization and uncoupling of mitochondrial oxidative phosphorylation. Dysglycaemia plays an important role via the effects of oxidative stress, protein kinase C activation and advanced glycosylation end-products on inflammatory signalling, collagen metabolism and fibrosis. Extramyocardial mechanisms involve peripheral endothelial dysfunction, arterial stiffening and autonomic neuropathy. The clinical significance of the ventricular abnormalities described is unknown. Confirmation of their prognostic importance for cardiac disease in diabetes would justify routine screening for presymptomatic ventricular dysfunction, as well as clinical trials of novel agents for correcting causal mechanisms. These considerations could also have implications for patients with obesity and the metabolic syndrome.

Damage detection and quantification using transmissibility

Structures experience various types of loads along their lifetime, which can be either static or dynamic and may be associated to phenomena of corrosion and chemical attack, among others. As a consequence, different types of structural damage can be produced; the deteriorated structure may have its capacity affected, leading to excessive vibration problems or even possible failure. It is very important to develop methods that are able to simultaneously detect the existence of damage and to quantify its extent. In this paper the authors propose a method to detect and quantify structural damage, using response transmissibilities measured along the structure. Some numerical simulations are presented and a comparison is made with results using frequency response functions. Experimental tests are also undertaken to validate the proposed technique. (C) 2011 Elsevier Ltd. All rights reserved.

Detection and diagnosis solutions for fault-tolerant VSI

This paper presents solutions for fault detection and diagnosis of two-level, three phase voltage-source inverter (VSI) topologies with IGBT devices. The proposed solutions combine redundant standby VSI structures and contactors (or relays) to improve the fault-tolerant capabilities of power electronics in applications with safety requirements. The suitable combination of these elements gives the inverter the ability to maintain energy processing in the occurrence of several failure modes, including short-circuit in IGBT devices, thus extending its reliability and availability. A survey of previously developed fault-tolerant VSI structures and several aspects of failure modes, detection and isolation mechanisms within VSI is first discussed. Hardware solutions for the protection of power semiconductors with fault detection and diagnosis mechanisms are then proposed to provide conditions to isolate and replace damaged power devices (or branches) in real time. Experimental results from a prototype are included to validate the proposed solutions.

FATAL GROUP A STREPTOCOCCAL TOXIC SHOCK-LIKE SYNDROME IN A CHILD WITH VARICELLA: REPORT OF THE FIRST WELL DOCUMENTED CASE WITH DETECTION OF THE GENETIC SEQUENCES THAT CODE FOR EXOTOXINS SPE A AND B, IN SÃO PAULO, BRAZIL

A previously healthy seven-year-old boy was admitted to the intensive care unit because of toxaemia associated with varicella. He rapidly developed shock and multisystem organ failure associated with the appearance of a deep-seated soft tissue infection and, despite aggressive treatment, died on hospital day 4. An M-non-typable, spe A and spe B positive Group A Streptococcus was cultured from a deep soft tissue aspirate. The criteria for defining Streptococcal toxic shock-like syndrome were fulfilled. The authors discuss the clinical and pathophysiological aspects of this disease as well as some unusual clinical findings related to this case.

Homogneous time resolved fluorescence: a new technique for detection and quantifications of infliximab in autoimmune patients

RESUMO:As terapias biológicas revolucionaram o tratamento das doenças autoimunes nos últimos anos. Tipicamente têm como alvos mediadores importantes no mecanismo das doenças. Os antagonistas do fator de necrose tumoral-α (TNF-α) são um grupo de agentes biológicos muito prescrito, pois estão indicados no tratamento de doenças imuno-mediadas comuns, tais como artrite reumatoide, artrite idiopática juvenil, artrite psoriática, espondilite anquilosante, doença de Crohn e colite ulcerosa. Com o uso frequente de inibidores do TNF-α, tem-se tornado evidente que estes agentes têm um potencial imunogénico importante, que pode comprometer o prognóstico a longo prazo dos doentes cronicamente tratados. A produção de anticorpos anti-fármaco parece causar falência terapêutica secundária em muitos doentes. Um dos efeitos dos anticorpos anti-fármaco é o aumento da eliminação do fármaco. A eliminação do fármaco, por sua vez, varia entre indivíduos, refletindo diferentes perfis farmacocinéticos. A determinação dos níveis séricos mínimos do agente anti-TNF-α é assim muito informativa e pode auxiliar nas decisões terapêuticas. Contudo, os testes imunológicos para determinar as concentrações séricas do fármaco não estão facilmente disponíveis na prática clínica. De forma a investigar uma nova técnica potencialmente fidedigna e prática para a deteção e quantificação dos agentes biológicos anti-TNF-α, foi testada a técnica por HTRF (homogeneous time-resolved fluorescence resonance energy transfer) para a determinação de concentrações séricas de infliximab. Apesar de apresentar algumas limitações relacionadas com as condições de leitura da fluorescência, esta técnica provou obter resultados próximos das concentrações obtidas por ELISA (enzyme-linked immunosorbent assay) bridging. Adicionalmente, tem a vantagem de ser de execução muito mais fácil e rápida. Deste modo, a técnica por HTRF poderá ser otimizada e tornar-se uma valiosa ferramenta laboratorial para orientar as decisões terapêuticas em doentes autoimunes com falência da terapêutica anti-TNF-α.--------- ABSTRACT: Biologic therapies revolutionized the treatment of autoimmune diseases in the last years. Typically, they target important disease mediators. Tumor necrosis factor-alpha (TNF-α) antagonists constitute a very prescribed group of biologic agents as they are indicated for the treatment of common immune-mediated diseases, such as rheumatoid arthritis, juvenile idiopathic arthritis, psoriatic arthritis, ankylosing spondylitis, Crohn’s disease and ulcerative colitis. With the increasing use of TNF-α inhibitors it has been noticed that they have an important immunogenic potential that can compromise long-term outcomes in chronically treated patients. The production of anti-drug antibodies seems to cause secondary therapeutic failure in many patients. One of the effects of anti-drug antibodies is the enhancement of drug clearance. Drug clearance, in turn, varies among individuals, reflecting different pharmacokinetic profiles. Determination of serum anti-TNF-α drug trough levels is though very informative and could support treatment decisions. However, immunologic assays to determine drug serum concentrations are not readily available in clinical practice. In order to investigate a potentially reliable and practical new technique for detection and quantification of anti-TNF-α biologic agents, homogeneous time-resolved fluorescence resonance energy transfer (HTRF) technique was tested for determination of serum infliximab concentrations. Although presenting some limitations related with fluorescence reading conditions, this technique proved to give results close to the concentrations obtained by the widely used bridging enzyme-linked immunosorbent assay (ELISA). In addition, it has the advantage of being much easier and faster to perform. Thus, HTRF technique can be optimized and become a valuable laboratorial tool to guide treatment decisions in autoimmune patients with anti-TNF-α therapy failure.