http://www.loc.gov/mods/v3 http://www.loc.gov/standards/mods/v3/mods-3-2.xsd
Supervision and safety of complex systems
1 online resource (xxii, 335 pages) : illustrations.
This book presents results of projects carried out by both scientific and industry researchers into the techniques to help in maintenance, control, supervision and security of systems, taking into account the technical environmental and human factors. This work is supported by the Scientific Group GIS 3SGS. It is a collaborative work from 13 partners (academic and industrial) who have come together to deal with security problems. The problems and techniques discussed mainly focus on stochastic and dynamic modeling, maintenance, forecasting, diagnosis, reliability, performance, organiza.
Cover; Supervision and Safety of Complex Systems; Title Page; Copyright Page; Table of Contents; Foreword; Foreword; Introduction; PART 1. INDUSTRIAL ISSUES; Chapter 1. Safety and Performance of Electricity Production Facilities; Chapter 2. Monitoring of Radioactive Waste Disposal Cells in Deep Geological Formation; 2.1. Context; 2.2. Monitoring of the environment; 2.3. Monitoring of geological repository structures; 2.4. Conclusion and perspectives; Chapter 3. Towards Fourth-generation Nuclear Reactors; 3.1. Context; 3.2. Surveillance and acoustic detection; 3.3. Inspection during operation.
3.3.1. The case of acoustic measurements3.4. Conclusion; PART 2. SUPERVISION AND MODELING OF COMPLEX SYSTEMS; Chapter 4. Fault-tolerant Data-fusion Method: Application on Platoon Vehicle Localization; 4.1. Introduction; 4.2. Review; 4.3. Bayesian network for data fusion; 4.3.1. Bayesian network and Kalman filter; 4.4. Localization of a single vehicle: multisensor data fusion with a dynamic Bayesian network; 4.4.1. Presentation of the approach developed; 4.4.2. Inference in switching Kalman filter; 4.4.3. Detailed synopsis of the method based on Bayesian networks.
4.4.4. Example of management of multi-hypotheses by a Bayesian network4.4.5. Illustration of the map localization method using SKF; 4.5. Multi-vehicle localization; 4.5.1. The problem studied; 4.5.2. Communication within the convoy; 4.5.3. Sensors used on each vehicle in the convoy; 4.5.4. Bayesian network for the localization of a chain of vehicles; 4.5.5. Extension of the approach: modeling and localization of a chain of vehicles; 4.5.6. The issue with this model; 4.5.7. New model for the localization of a chain of vehicles; 4.5.8. Proportional commands.
4.5.9. Functional analysis of models of the convoy4.6. Conclusions and perspectives; 4.7. Bibliography; Chapter 5 Damage and Forecast Modeling; 5.1. Introduction; 5.1.1. Operational level; 5.1.2. Strategic level; 5.2. Preliminary study of data; 5.2.1. Structure of the database; 5.2.2. Performance criterion for the prognostic; 5.2.3. Definition of a deterioration indicator; 5.3. Construction of the deterioration indicator; 5.3.1. Study of the failure space with PCA; 5.3.2. Damage indicator defined as a distance; 5.4. Estimation of the residual life span (RUL).
5.4.1. Simple approach based on the life span5.4.2. Stochastic deterioration model; 5.5. Conclusion; 5.6. Bibliography; Chapter 6. Diagnosis of Systems with Multiple Operating Modes; 6.1. Introduction; 6.2. Detection of faults for a class of switching systems; 6.2.1. Introduction; 6.2.2. Structure of the residual generator and observer design; 6.2.3. Simulation and results; 6.2.4. Conclusions; 6.3. Analytical method to obtain a multiple model; 6.3.1. Introduction; 6.3.2. Setting the problem; 6.3.3. Transformation in multiple-model form; 6.3.4. Conclusion.
edited by Nada Matta, Yves Vandenboomgaerde, Jean Arlat.
Includes bibliographical references and index.
London : ISTE ; Hoboken, NJ : John Wiley & Sons, Inc, 2012, ♭2012