A Co-design Distributed Bayesian Approach for Decision and Scheduling of WNCS

International audienceThis paper deals with the problem of co-design of Wireless Networked Control systems (WNCS). The integration of the Wireless Network (WN) in the control loop influences the Quality of Control (QoC) of the system in terms of the Quality of Service (QoS) of the WN. We present a co-design approach for WNCS based on distributed Bayesian Network (BN) and we illustrate it with Khepera III robot. The proposed BN is constructed from the robot experimental data. This approach allows to make decisions to ensure a good QoC for the robot and also ensure that the QoS is always sufficient to maintain a good QoC. Keeping a sufficient QoS depends on the scheduling method used and therefore the proposed approach aims also to determine the proper scheduling method to keep the system's performance. Finally a comparison is performed with the classical time-triggered scheduling. The results obtained with BN scheduling are better in terms of QoS and QoC for WNC

Supervision des procédés complexes

Traité IC2, série systèmes automatisés, ISBN-13: 978-2746214108International audienc

Diagnóstico y monitoreo de procesos industriales complejos fundados en un modelo causal

En este artículo, se describe el uso del razonamiento causal para la supervisión de instalaciones industriales complejas. Primeramente se describe como obtener un modelo causal, ya sea aprovechando la experiencia de los ingenieros o a partir de un sistema de ecuaciones formales. Este modelo puede ser expresado bajo la forma de un grafo orientado. Después, se explica el uso del grafo causal para la detección y la localización de fallas. Varios tipos de residuos pueden ser generados naturalmente por el grafo, sin la necesidad de manejar ecuaciones. Algunos de estos residuos son muy bien adaptados a la localización de fallas, que eventualmente pueden ser múltiples. Otros son útiles para seguir en tiempo real la propagación de la falla. Finalmente, se describe el uso del grafo para fines de monitoreo, así como de explicaciones al operador humano y de consejos de acción

Introduction

Traité Ic2 Série Systèmes Automatisés. Ed. Hermès Sciences, 16 mars 2007. ISBN-13: 978-2746214108International audienc

Surveillance par analyse de tendances

Traité Ic2 Série Systèmes Automatisés. Ed. Hermès Sciences, 16 mars 2007. ISBN-13: 978-2746214108International audienc

Simulation and Implementation of Continuous time Loops

International audienc

Signal based diagnostic algorithm integrating model validity in the decision

International audienceSignal analysis can be used to perform diagnosis: features that define the representation space are extracted with a processing technique. Diagnosis consists in mapping the representation space into fault indicators easily interpreted by operators. This paper proposes two main ideas. Firstly, a limited number of realizations of one signal is considered offline to define the pattern in the representation space. Secondly, the confidence that can be attached to the pattern when the diagnostic decision is computed is taken into account. The diagnostic decision is based on multicriteria fuzzy decision-making: it aggregates the pattern validity and the similarity of the current signal features to this pattern. The proposed methodology is well adapted to FDI of multiple faults. It is illustrated with a STFT for feature generation and gives very encouraging results when applied to industrial data recorded from a roughing mill in the metal industry

Intelligence artificielle et automatique

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On-line adaptive trend extraction of multiple physiological signals for alarm filtering in Intensive Care Units

International audienceThis paper presents an alarm validation system dedicated to patient monitoring in Intensive Care Units. Several physiological signals are continuously acquired and an on-line trend extraction method is implemented for each one. A trend is a succession of contiguous semi-quantitative episodes, expressing the time evolution of a signal with several symbols. The difference between the trend and the signal is considered as a residual. In this paper, trend extraction is based on several thresholds that are adapted on-line, following the signal variations. Multivariate change indices are further deduced from the trends and the residuals. They provide an indication of changes to patient hemodynamic and respiratory state. An alarm validation system based on these indices is then proposed, which uses fuzzy decision making. Whenever a monitoring system sets off an alarm, the system proposed carries out a backward analysis of the physiological variables monitored. The system enables various policies to be implemented: filtering of false alarms due to artifacts, confirmation of true alarms due to a patient state change. The system was tested on more than 50 hours of data recorded on adult patients in an ICU unit, when 105 SpO2 alarms were set off by a fixed threshold alarm system. The comparison between the decision made on-line by the validation system and the decision made by a medical expert for each of these alarms showed that the system is able to recognize 100% of true alarms and filter 50 to 80% of false alarms

Fault detection using parameter estimation applied to a winding machine

International audienceOn line parameter estimation reflects the process state, but physical parameters are not usually easily estimated in the case of complex systems. This paper presents a sensor or actuator fault detection method based on a classical transfer function parameter estimation algorithm in discrete time domain. Redundant discrete time transfer functions are used to improve the residual generation. The increase of information by redundant equations allows the generation of a signature table. The exploitation of this table, achieved by a distance computation, allows the fault detection and isolation (FDI)