Journal ArticleDOI
Fault diagnosis in dynamic systems using analytical and knowledge-based redundancy—a survey and some new results
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TLDR
In this article, the authors review the state of the art of fault detection and isolation in automatic processes using analytical redundancy, and present some new results with emphasis on the latest attempts to achieve robustness with respect to modelling errors.About:
This article is published in Automatica.The article was published on 1990-05-01. It has received 3313 citations till now. The article focuses on the topics: Fault detection and isolation & Robustness (computer science).read more
Citations
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Journal ArticleDOI
Kalman filters and neural-network schemes for sensor validation in flight control systems
TL;DR: The study reveals that online learning neural architectures have potential for online estimation purposes in a sensor validation scheme, particularly in the case of poorly modeled dynamics.
Proceedings ArticleDOI
Model base fault detection and diagnosis methods
TL;DR: The described methodology was verified by experiments with several technical processes like electric motors, actuators, pumps, machine tools, robots, heat exchangers, combustion engines and vehicles.
Journal ArticleDOI
Innovations generation in the presence of unknown inputs: application to robust failure detection
TL;DR: A method for constructing innovations in the case where the model contains unknown inputs and disturbances is presented and the solution is complete in the sense that it covers ‘singular’ cases.
Posted Content
Sensor Fault Detection, Isolation and Identification Using Multiple Model-based Hybrid Kalman Filter for Gas Turbine Engines
TL;DR: Comparison studies confirm the superiority of the proposed HKF method in terms of promptness of the fault detection, lower false alarm rates, as well as robustness with respect to the engine health parameter degradations.
Journal ArticleDOI
A hidden Markov model-based algorithm for fault diagnosis with partial and imperfect tests
TL;DR: A hidden Markov model (HMM) based algorithm for fault diagnosis in systems with partial and imperfect tests and a method to estimate online the HMM parameters, namely, the state transition probabilities, the instantaneous probabilities of test outcomes given the system state and the initial state distribution.
References
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Journal ArticleDOI
Paper: A survey of design methods for failure detection in dynamic systems
TL;DR: This paper surveys a number of methods for the detection of abrupt changes in stochastic dynamical systems, focusing on the class of linear systems, but the basic concepts carry over to other classes of systems.
Journal ArticleDOI
Process fault detection based on modeling and estimation methods-A survey
TL;DR: This contribution presents a brief summary of some basic fault detection methods, followed by a description of suitable parameter estimation methods for continuous-time models.
Journal ArticleDOI
Analytical redundancy and the design of robust failure detection systems
E. Chow,Alan S. Willsky +1 more
TL;DR: In this article, a robust failure detection and identification (FDI) process is viewed as consisting of two stages: residual generation and decision making, and it is argued that a robust FDI system can be achieved by designing a robust residual generation process.
A survey of design methods for failure detection in dynamic systems
TL;DR: 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.