Étude de stratégies de diagnostic embarqué des réseaux filaires complexes

Cette étude s’inscrit dans le cadre du diagnostic embarqué des réseaux filaires complexes. Elle vise à détecter et localiser les défauts électriques avec précision. En effet, l’intégration du diagnostic par réflectométrie dans un système embarqué fait apparaître des problèmes d’interférence qui s’aggravent dans le cas d’un réseau complexe où plusieurs réflectomètres sont placés en différents points du réseau. L’objectif est de développer de nouvelles stratégies de diagnostic embarqué des réseaux filaires complexes pour résoudre les problèmes d’interférence d’une part et l’ambiguïté de localisation du défaut d’autre part. La première contribution concerne le développement d’une nouvelle méthode de réflectométrie baptisée OMTDR (Orthogonal Multi-tone Time Domain Reflectometry). Elle utilise des signaux numériques modulés et orthogonaux pour éliminer les interférences. Pour davantage de couverture, la deuxième contribution propose d’intégrer la communication entre les réflectomètres. Elle vise à fusionner les données afin de faciliter la prise de décision. La troisième contribution adresse la problématique de la stratégie de diagnostic, c’est-à-dire, de l’optimisation des performances du diagnostic d’un réseau complexe sous contraintes opérationnelles d’utilisation. L’utilisation des Réseaux Bayésiens permet d’étudier l’impact des différents facteurs et d’obtenir une estimation de la confiance et donc, de la fiabilité du résultat du diagnostic. ABSTRACT : This study addresses embedded diagnosis of complex wired networks. Based on the reflectometry method, it aims at detecting and locating accurately electrical faults. Increasing demand for on-line diagnosis has imposed serious challenges on interference mitigation. It aims at making diagnosis while the target system is running. The interference becomes more critical in the case of complex networks where several reflectometers are injecting their test signals simultaneously. The objective is to develop new embedded diagnosis strategies in complex wired networks that would resolve interference problems and eliminate ambiguity related to the fault location. The first contribution is the development of a new method called OMTDR (Orthogonal Multi-tone Time Domain Reflectometry). It uses orthogonal modulated digital signals for interference mitigation and thereby on-line diagnosis. For better coverage of the network, the second contribution proposes to integrate communication between reflectometers. It uses sensors data fusion to facilitate decision making. The third contribution addresses the problem of the diagnosis strategy, i.e. the optimization of diagnosis performance of a complex network under operational constraints. The use of Bayesian Networks allows us to study the impact of different factors and estimate the confidence level and thereby the reliability of the diagnosis results

Optimisation de Capteurs de Diagnostic de Défauts par Réflectométrie dans les Réseaux Filaires Complexes en utilisant les Réseaux Bayésiens

Cet article presente une strat ' egie de diagnostic ' distribuee par la m ' ethode de r ' eflectom ' etrie dans un r ' eseau ' filaire complexe. L'idee principale consiste ' a injecter un signal ' de test en plusieurs points du reseau et r ' ecup ' erer, ensuite, le ' signal refl' echi afin d'en d ' eduire les caract ' eristiques du d ' efaut ' detect ' e. L'objectif de cet article est d'optimiser le nombre de ' capteurs a impl ' ementer dans le r ' eseau afin de r ' eduire le co ' ut du ˆ systeme tout en garantissant une certaine qualit ' e de diagnostic ' obtenus. L'approche adoptee dans cet article consiste, en phase ' de conception a partir d'un cas d ' eterministe, ' a placer un capteur ' a chaque extr ' emit ' e du r ' eseau puis ' a optimiser l'architecture de ' diagnostic en reduisant le nombre de r ' eflectom ' etres. En phase ' d'exploitation, le reseau de capteurs permettra alors d'estimer ' le niveau de confiance du diagnostic realis ' e

Prevalence of infectious multi-drug resistant bacteria isolated from immunocompromised patients in Tunisia

Objectives: A retrospective study was conducted in the Bone Marrow Transplant Center of Tunisia during a period of 10 years (from 2002 to 2011) in order to report the prevalence of infectious multi-drug resistant bacteria.Methods: Bacterial identification was carried on the basis of biochemical characteristics and API identification systems. Antibiotic susceptibility was tested by disc diffusion method on Muller-Hinton agar.Results: During the study period, 34.5% of 142 Klebsiella pneumoniae strains and 11.46% of 218 Escherichia coli strains were extended-spectrum beta-lactamase (ESBL) producers. Also, 32.8% of 210 strains of Pseudomonas aeruginosa were imipenem and/or ceftazidime resistant and 20.75% of 106 strains of Staphylococcus aureus were methicillin resistant. A rising trend was observed for the prevalence of the selected multidrug resistant bacteria.Conclusion: These findings may have important clinical implications in prophylaxis and selection of antibiotic treatment. Continuous surveillance is needed, especially for onco-hematological patients.Keywords: Infectious multi-drug resistant bacteria, immunocompromised patients, Tunisia

Optimisation de capteurs de diagnostic de défauts par réflectométrie dans les réseaux filaires complexes en utilisant les réseaux bayésiens

Cet article pr´esente une strat´egie de diagnostic distribuée par la méthode de réflectométrie dans un réseau filaire complexe. L’idée principale consiste à injecter un signal de test en plusieurs points du réseau et récupérer, ensuite, le signal réfléchi afin d’en déduire les caractéristiques du défaut détecté. L’objectif de cet article est d’optimiser le nombre de capteurs à implémenter dans le réseau afin de réduire le coût du système tout en garantissant une certaine qualité de diagnostic obtenus. L’approche adoptée dans cet article consiste, en phase de conception à partir d’un cas déterministe, à placer un capteur à chaque extrémité du réseau puis à optimiser l’architecture de diagnostic en réduisant le nombre de réflectomètres. En phase d’exploitation, le réseau de capteurs permettra alors d’estimer le niveau de confiance du diagnostic réalisé

Ambiguity cancellation for wire fault location based on cable life profile

Although reflectometry is an efficient method to diagnose simple topologies (such as transmission line, Y shape network), it remains limited in the case of complex branched networks due to multipath fading of the test signal during its propagation. Generally, the knowledge of the environment in which the cable operates gives an additional idea about the fault location. The current paper proposes to introduce the cable life profile (such as environmental stress, type, age, noise, etc.) to detect and cancel diagnosis ambiguities and provide a precise location of the fault. Bayesian Network (BN) seems to be a suitable solution to offer a coherent representation of knowledge domain (reflectometry method, cable characteristics and network heterogeneity) under uncertainties (fault(s) location, systems reliability and measurement precision). In this work, a two-stages BN model for diagnosis using reflectometry in branched networks is proposed and simulation results are discussed

Diagnosis sensor fusion for wire fault location in CAN bus systems

This paper proposes a new method for distributed wire diagnosis using reflectometry. It not only uses the reflected part of the test signal to extract information about the fault position, but it also investigates the transmitted part to enable sensors communication. The major novelty is to inject a signal carrying additional information about the fault position as a test signal using Orthogonal Multi-Tone Time Domain Reflectometry (OMTDR) method. While the reflected signal permits to determine the fault position at time , the transmitted one sends the fault position at time (−1) to the master sensor. Finally, the latter takes the location decision based on the information gathered from its slaves. This removing location ambiguities in branched networks. Time Division Multiple Access (TDMA) is used to avoid noise interference

Prevalence of infectious multi-drug resistant bacteria isolated from immunocompromised patients in Tunisia

Objectives: A retrospective study was conducted in the Bone Marrow Transplant Center of Tunisia during a period of 10 years (from 2002 to 2011) in order to report the prevalence of infectious multi-drug resistant bacteria. Methods: Bacterial identification was carried on the basis of biochemical characteristics and API identification systems. Antibiotic susceptibility was tested by disc diffusion method on Muller-Hinton agar. Results: During the study period, 34.5% of 142 Klebsiella pneumoniae strains and 11.46% of 218 Escherichia coli strains were extended-spectrum beta-lactamase (ESBL) producers. Also, 32.8% of 210 strains of Pseudomonas aeruginosa were imipenem and/or ceftazidime resistant and 20.75% of 106 strains of Staphylococcus aureus were methicillin resistant. A rising trend was observed for the prevalence of the selected multidrug resistant bacteria. Conclusion: These findings may have important clinical implications in prophylaxis and selection of antibiotic treatment. Continuous surveillance is needed, especially for onco-hematological patients. DOI: https://dx.doi.org/10.4314/ahs.v19i2.25 Cite as: Mechergui A, Achour W, Mathlouthi S, Hassen AB. Prevalence of infectious multi-drug resistant bacteria isolated from immunocompromised patients in Tunisia. Afri Health Sci.2019;19(2): 2021-2025. https://dx.doi.org/10.4314/ahs.v19i2.2

OMTDR using BER estimation for ambiguities cancellation in ramified networks diagnosis

Nowadays, increasing demands for on-line wire diagnosis using reflectometry have imposed serious challenges on signals processing, bandwidth control and interference mitigation. On-line diagnosis aims at detecting and locating faults ccurately while the target system is running. In this work, a new reflectometry method, named “Orthogonal Multi-Tone Time Domain Reflectometry” (OMTDR), is proposed. OMTDR, based on Orthogonal Frequency Division Multiplexing (OFDM), is a suitable candidate for on-line diagnosis as it permits interference avoidance, bandwidth control and data rate increase thanks to the use of orthogonal tones and guard intervals. Over the diagnosis function, OMTDR adds communication between sensors to more accurately determine faults position in a multi-branch network using a distributed strategy. OMTDR was tested on a branched network consisting of three cables with different lengths, with sensors at each cable end. Here, the sensors signals are carefully constructed using a resource allocation scheme to use frequencies below and above the prohibited bandwidth, used by the target system, for communication and diagnosis. Simulation results show that the proposed method performs well in a branched wiring network as it permits to detect and locate faults accurately even when the target system is operating

On-Line diagnosis using orthogonal multi-tone time domain reflectometry in a coaxial cable

On-Line diagnosis using orthogonal multi-tone time domain reflectometry in a coaxial cabl

A distributed diagnosis strategy using bayesian network for complex wiring networks

In this paper, we propose a distributed diagnosis strategy by using reectometry in highly complex wiring networks. Although the problem of sensors number optimization is greatly studied in the literature, it is not well investigated in complex wiring networks diagnosis. Our proposed approach is based on two principles which are diagnosis sensors number and location optimisation using Bayesian Networks and measure uncertainty estimation. It consists in four steps: (1) sensors implementation in a deterministic case, (2) in uential parameters on diagnosis measure identification, (3) diagnosis measure modelling using Bayesian Networks, (4) sensor number and location optimization. Here, our objective is to minimize both sensors number and a wire diagnosis measure uncertainty