Review of Machine Learning Approaches In Fault Diagnosis applied to IoT System

International audienceWith increasing complex systems, low production costs, and changing technologies, for this reason, the automatic fault diagnosis using artificial intelligence (AI) techniques is more in more applied. In addition, with the emergence of the use of reconfigurable systems, AI can assist in self-maintenance of complex systems. The purpose of this article is to summarize the diagnosis research of systems using AI approaches and examine their application particularly in the field of diagnosis of complex systems. It covers articles published from 2002 to 2018 using Machine Learning tools for fault diagnosis in industrial systems

Sur le diagnostic interactif

Cette thèse étudie les problèmes de diagnostic itératif et propose des outilsd aide au diagnostic interactif. Différents processus de diagnostic où des outils interactifshomme-automate sont utiles, sont présentés. Ces outils permettent de résoudre des difficultésliées à la représentation d un grand nombre d éléments d un système, des difficultés liées àla représentation du comportement et du fonctionnement d un système et des difficultés liéesà l explicitation de l expertise. Nos travaux ont conduit à la conception de différents typesd outils interactifs d aide au diagnostic. Le premier permet d exploiter des représentationsstructuro-fonctionnelles pour construire et résoudre progressivement un problème de diagnostic.Le second outil interactif permet d exploiter des modèles de comportement construitau fur et à mesure de la résolution d un problème de diagnostic. Enfin, un dernier outil a étéproposé pour montrer qu il est possible de prendre compte la connaissance implicite d unexpert dans la résolution de problème de diagnostic. Un problème de diagnostic est doncprésenté comme un processus itératif avec des interactions homme-automate.This PhD thesis studies the iterative diagnosis problems and provides thecomputer-aided diagnostic tool for interactive diagnosis. Different diagnosis processes wherethe tool to support human-machine interaction are useful, are presented. These tools help totackle difficulties related to the representation of a large number of elements in a system,difficulties related to the representation of the behavior functioning of a system and difficultiesencountered while expliciting the expertise. Our work led to the design of different interactivetools to support the diagnosis process. The first tool allows to exploit the structural-functionalmodeling to build and solve progressively a diagnosis problem. The second interactive toolallows to exploit the behavioral models built step by step in the diagnosis process and tosolve the diagnosis problem. The final tool was proposed to show that it is possible to takeinto account the implicit knowledge of an expert in order to solve the diagnosis problem.A diagnosis problem is therefore presented as an iterative process with human-machineinteractions.SAVOIE-SCD - Bib.électronique (730659901) / SudocGRENOBLE1/INP-Bib.électronique (384210012) / SudocGRENOBLE2/3-Bib.électronique (384219901) / SudocSudocFranceF

Diagnostic de systèmes hybrides incertains par génération automatique de relations de redondance analytique symboliques évaluées par approche ensembliste

Les activités industrielles peuvent induire des risques de nature diverse, voire conduire à des événements catastrophiques. De façon à réduire ces risques à des niveaux acceptables, à en limiter les coûts aussi bien humains, matériels que financiers et à respecter la réglementation, il est crucial d en prévenir la survenue (prévention) et à identifier des situations anormales en fonction d informations récupérées sur le terrain. Ceci nécessite de résoudre deux points essentiels : détecter l anomalie et faire un diagnostic, d où l importance des modèles de bon comportement qui modélisent des systèmes physique réels et les méthodes associées permettant d effectuer la surveillance en continu. L approche la plus utilisée dans la communauté FDI est l approche structurelle qui consiste à construire des relations de redondance analytique (RRA). Le principe de l approche structurelle est de prendre en compte seulement l existence des relations entre les variables induites par les équations du modèle. En basant sur cette approche, ma thèse consiste à trouver une réponse qui satisfait un triple objectif :1. Extraire les relations valides à partir du modèle de bon comportement d'un système afin de prendre en compte l'évolution du système en éliminant les relations et des mesures invalides ayant pour but d'effectuer le diagnostic en ligne2. Construire, en utilisant une analyse symbolique couplée avec la théorie des graphes, les relations de redondance analytique symboliques (RRAS) pour la détection des défauts dans le système.3. Evaluer ces RRAS en utilisant le calcul par intervalle, an de prendre en compte les incertitudes présents dans les mesures, lors des tests de cohérence.Large-scale complex process plants are safety-critical systems where the real-time diagnosis is very important. In a model based systems engineering approach, the structured development process from the concept to the production to the operation phase is organized around a coherent model of the system. This model contains, in particular, relations about the behavior of the system that could have been used for simulation in the design phase. The objective of this work is to use this information to design automatically on-line diagnosis algorithms using the hybrid dynamical information part and sensor measurements of the system model. In this thesis, the proposed approach allows:To extract the valid relations of system behavior to take into account system evolution by eliminating invalid constraints and measurements for establishing an on-line diagnosisTo build, using symbolic analysis and graph path search, analytical redundancy relations for the various system configurationsTo evaluate these ARRs in using set valued computations (interval arithmetic) to take into account model and measurements uncertaintiesSAVOIE-SCD - Bib.électronique (730659901) / SudocGRENOBLE1/INP-Bib.électronique (384210012) / SudocGRENOBLE2/3-Bib.électronique (384219901) / SudocSudocFranceF

Predictors of hospital discharge and mortality in patients with diabetes and COVID-19: updated results from the nationwide CORONADO study

AIMS/HYPOTHESIS: This is an update of the results from the previous report of the CORONADO (Coronavirus SARS-CoV-2 and Diabetes Outcomes) study, which aims to describe the outcomes and prognostic factors in patients with diabetes hospitalised for coronavirus disease-2019 (COVID-19). METHODS: The CORONADO initiative is a French nationwide multicentre study of patients with diabetes hospitalised for COVID-19 with a 28-day follow-up. The patients were screened after hospital admission from 10 March to 10 April 2020. We mainly focused on hospital discharge and death within 28 days. RESULTS: We included 2796 participants: 63.7% men, mean age 69.7 ± 13.2 years, median BMI (25th-75th percentile) 28.4 (25.0-32.4) kg/m(2). Microvascular and macrovascular diabetic complications were found in 44.2% and 38.6% of participants, respectively. Within 28 days, 1404 (50.2%; 95% CI 48.3%, 52.1%) were discharged from hospital with a median duration of hospital stay of 9 (5-14) days, while 577 participants died (20.6%; 95% CI 19.2%, 22.2%). In multivariable models, younger age, routine metformin therapy and longer symptom duration on admission were positively associated with discharge. History of microvascular complications, anticoagulant routine therapy, dyspnoea on admission, and higher aspartate aminotransferase, white cell count and C-reactive protein levels were associated with a reduced chance of discharge. Factors associated with death within 28 days mirrored those associated with discharge, and also included routine treatment by insulin and statin as deleterious factors. CONCLUSIONS/INTERPRETATION: In patients with diabetes hospitalised for COVID-19, we established prognostic factors for hospital discharge and death that could help clinicians in this pandemic period. TRIAL REGISTRATION: Clinicaltrials.gov identifier: NCT04324736

Risk Analysis

International audienceAn overview of the methods used for risk analysis in a variety of industrial sectors, with a particular focus on the consideration of human aspects, this book provides a definition of all the fundamental notions associated with risks and risk management, as well as clearly placing the discipline of risk analysis within the broader context of risk management processes. The author begins by presenting a certain number of basic concepts, followed by the general principle of risk analysis. He then moves on to examine the ISO31000 standard, which provides a specification for the implementation of a risk management approach. The ability to represent the information we use is crucial, so the representation of knowledge, covering both information concerning the risk occurrence mechanism and details of the system under scrutiny, is also considered. The different analysis methods are then presented, firstly for the identification of risks, then for their analysis in terms of cause and effect, and finally for the implementation of safety measures. Concrete examples are given throughout the book and the methodology and method can be applied to various fields (industry, health, organization, technical systems)

Cybersécurité des systèmes industriels

International audienc

A modelling framework for model based risk analysis

International audienceTraditionally, risk analysis projects use a document based approach: the description of the system and the result of the analysis are expressed in a textual way or in drawings without an explicit semantics. The consistency and the relationships between documents are difficult to assess and it is rather difficult to extract and manipulate needed information for validation or for another purposes, or to capitalize knowledge. An approach to overcome these limitations is to use a model based approach for risk analysis. This would allow to represent knowledge in a consistent manner, easy to manipulate and to transform In this work, we present an approach for model based risk analysis, which can be used with any classical methods such as PHA, HAZOP and FMEA

Cybersécurité des installations industrielles- SCADA et Industrial IoT

National audienc

Risk Analysis

International audienceAn overview of the methods used for risk analysis in a variety of industrial sectors, with a particular focus on the consideration of human aspects, this book provides a definition of all the fundamental notions associated with risks and risk management, as well as clearly placing the discipline of risk analysis within the broader context of risk management processes. The author begins by presenting a certain number of basic concepts, followed by the general principle of risk analysis. He then moves on to examine the ISO31000 standard, which provides a specification for the implementation of a risk management approach. The ability to represent the information we use is crucial, so the representation of knowledge, covering both information concerning the risk occurrence mechanism and details of the system under scrutiny, is also considered. The different analysis methods are then presented, firstly for the identification of risks, then for their analysis in terms of cause and effect, and finally for the implementation of safety measures. Concrete examples are given throughout the book and the methodology and method can be applied to various fields (industry, health, organization, technical systems)