This book is downloadable from http://www.irisa.fr/sisthem/kniga/. Many monitoring problems can be stated as the problem of detecting a change in the parameters of a static or dynamic stochastic system. The main goal of this book is to describe a unified framework for the design and the performance analysis of the algorithms for solving these change detection problems. Also the book contains the key mathematical background necessary for this purpose. Finally links with the analytical redundancy approach to fault detection in linear systems are established. We call abrupt change any change in the parameters of the system that occurs either instantaneously or at least very fast with respect to the sampling period of the measurements. Abrupt changes by no means refer to changes with large magnitude; on the contrary, in most applications the main problem is to detect small changes. Moreover, in some applications, the early warning of small - and not necessarily fast - changes is of crucial interest in order to avoid the economic or even catastrophic consequences that can result from an accumulation of such small changes. For example, small faults arising in the sensors of a navigation system can result, through the underlying integration, in serious errors in the estimated position of the plane. Another example is the early warning of small deviations from the normal operating conditions of an industrial process. The early detection of slight changes in the state of the process allows to plan in a more adequate manner the periods during which the process should be inspected and possibly repaired, and thus to reduce the exploitation costs.

Detection of abrupt changes: theory and application

Fault diagnosis in dynamic systems using analytical and knowledge-based redundancy—a survey and some new results

https://users.encs.concordia.ca/~ymzhang/publications/ARC32-2-98Zhang_pp.229-252.pdf

Bibliographical review on reconfigurable fault-tolerant control systems

https://www.ece.lsu.edu/mcu/lawss/add_materials/FaultDetectionPart1.pdf

A Review of Process Fault Detection and Diagnosis Part I : Quantitative Model-Based Methods

This tutorial/survey paper: (1) provides a concise point of departure for researchers and practitioners alike wishing to assess the current state of the art in the control and monitoring of civil engineering structures; and (2) provides a link between structural control and other fields of control theory, pointing out both differences and similarities, and points out where future research and application efforts are likely to prove fruitful. The paper consists of the following sections: section 1 is an introduction; section 2 deals with passive energy dissipation; section 3 deals with active control; section 4 deals with hybrid and semiactive control systems; section 5 discusses sensors for structural control; section 6 deals with smart material systems; section 7 deals with health monitoring and damage detection; and section 8 deals with research needs. An extensive list of references is provided in the references section.

Structural control: past, present, and future

On -line detection of jumps in mean.- Detection of abrupt changes in dynamic systems.- Two examples of application of the GLR method in signal processing.- Advanced methods of change detection: An overview.- III - Design of algorithms for change detection : Likelihood-oriented approaches.- Off-line statistical analysis of change-point models using non parametric and likelihood methods.- The two-models approach for the on-line detection of changes in AR processes.- Sequential detection of changes in stochastic systems.- The local method applied to the robust detection of changes in the poles of a pole-zero system.- Redundancy relations and robust failure detection.- Estimation-based approaches to rhythm analysis in electrocardiograms.- On line segmentation of speech signals without prior recognition.- Application of change detection theory to seismic signal processing.

Detection of Abrupt Changes in Signals and Dynamical Systems

The flutter monitoring problem is investigated from a detection (and not prediction) point of view, and stated as a statistical hypotheses testing problem regarding a specified damping coefficient. Two flutter onset detection algorithms are described. Both tests build on a residual associated with an output-only subspace-based structural identification method, previously introduced by the authors for structural health monitoring. The first test, working batch wise, handles a null and a close alternative statistical hypotheses on the damping. It comes up from variations on a local asymptotic approximation for the residual, combined with the generalized likelihood ratio (GLR) test. The second test, working on-line, is based on non local hypotheses. It builds on a different approximation for the residual, combined with the cumulative sum (Cusum) test of common use in quality control. Numerical results obtained on real data are discussed, which suggest some interesting properties of the on-line test.

/pdf/fast-in-flight-detection-of-flutter-onset-a-statistical-sgzsi7nxzv.pdf

Fast in-flight detection of flutter onset : A statistical approach

A system identification-based approach is presented for damage monitoring and diagnostics of mechanical structures and rotating machinery, under operating conditions. We present in this paper our general approach, together with recent improvements using the so-called subspace methods. Experimental results on a flexible structure are presented to illustrate the validity and effectiveness of the improvements.

In-operation damage monitoring and diagnostics of vibrating structures, with applications to offshore structures and rotating machinery

We address the problem of detecting and isolating faults modeled as changes in the eigenstructure of a linear dynamical system. The purpose of the paper is to describe and analyze new fault detection and isolation algorithms, based on recent stochastic subspace-based identification methods and the statistical local approach to the design of detection algorithms. The application to vibration monitoring of mechanical structures and rotating machines is discussed. A conceptual comparison is made with another detection algorithm based on the instrumental variables identification method, and previously proposed by two of the authors.

https://hal.inria.fr/inria-00073389/document

Subspace-based Fault Detection and Isolation Methods - Application to Vibration Monitoring

Ce rapport a pour but de presenter la demarche generale elaboree a l'IRISA en matiere de surveillance d'installations industrielles pour la maintenance conditionnelle. Cette demarche permet, pour une large classe de modeles, la conception systematique des algorithmes necessaires, a partir de la donnee de la structure du modele adequat pour le systeme surveille. Nous rappelons les deux principaux exemples d'application qui illustrent sa pertinence. Puis nous decrivons les extensions en cours, concernant l'application d'une part aux modeles de type reseaux de neurones ou d'ondelettes, et d'autre part a des modeles dynamiques hybrides numerique/symbolique. Nous indiquons une organisation possible des logiciels correspondants et des commentaires sur les references citees. Puis nous decrivons les fondements theoriques des techniques presidant aux differentes etapes de la conception de l'algorithmique correspondante.

https://hal.inria.fr/inria-00073801/document

Albert Benveniste

Papers

Detection of Abrupt Changes in Signals and Dynamical Systems

Fast in-flight detection of flutter onset : A statistical approach

In-operation damage monitoring and diagnostics of vibrating structures, with applications to offshore structures and rotating machinery

Subspace-based Fault Detection and Isolation Methods - Application to Vibration Monitoring

Surveillance d'installations industrielles: démarche générale et conception de l'algorithmique