Open Access
A survey of design methods for failure detection in dynamic systems
Alan S. Willsky
- Vol. 76, pp 11347
Reads0
Chats0
TLDR
A number of methods for detecting abrupt changes (such as failures) in stochastic dynamical systems are surveyed in this paper, where tradeoffs in complexity versus performance are discussed, ranging from the design of specific failure-sensitive filters, to the use of statistical tests on filter innovations, and the development of jump process formulations.Abstract:
A number of methods for detecting abrupt changes (such as failures) in stochastic dynamical systems are surveyed. The class of linear systems is concentrated on but the basic concepts, if not the detailed analyses, carry over to other classes of systems. The methods surveyed range from the design of specific failure-sensitive filters, to the use of statistical tests on filter innovations, to the development of jump process formulations. Tradeoffs in complexity versus performance are discussed.read more
Citations
More filters
Proceedings ArticleDOI
Neural networks-based scheme for fault diagnosis in fossil electric power plants
TL;DR: This paper presents the development and application of a neural networks-based scheme for fault diagnosis in fossil electric power plants using a full scale simulator reproducing reliably the process behavior.
Proceedings ArticleDOI
Applying parametric fault detection to a mechanical system
TL;DR: In this paper, a model with parametric uncertainty is proposed for parametric fault detection based on the representation of parameter changes as linear fractional transformations (LFT) and a stabilizing controller is chosen and its robustness properties are studied via mu.
Book ChapterDOI
Fault Detection and Estimation in Dynamic Systems
M. Wei,D. Lapucha,H. Martell +2 more
TL;DR: A statistical technique for the detection and estimation of model errors caused by failures in the system model or the measurement model is discussed, which is based on the residual characteristics of the Kalman filter.
Proceedings ArticleDOI
Failure detection via recursive estimation for a class of semi-Markov switching systems
TL;DR: In this article, the authors apply recursive state estimation algorithm for dynamic systems whose state model experiences jumps according to a sojourn-time-dependent Markov (STDM) chain to the problem of failure detection.
Proceedings ArticleDOI
A unified framework for statistical change detection
TL;DR: The authors present a unified parametric statistical framework for both the design and the performance analysis of change detection algorithms, introduced in the simplest case of change in the scalar parameter of the distribution of an independent random sequence.