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Journal ArticleDOI

Model-Based Methods for Fault Diagnosis: Some Guide-Lines

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TLDR
In this article, a review of model-based fault diagnosis techniques is provided, starting from basic principles, the properties and limitations of different methods are discussed, and the problems encountered in both the residual generation and evaluation stages of fault diagnosis have been outlined.
Abstract
This paper provides a review of model-based fault diagnosis techniques. Starting from basic principles, the properties and limitations of different methods are discussed. The main aim is to give some guide-lines for the use of model-based methods. Accordingly, the problems encountered in both the residual generation and evaluation stages of fault diagnosis have been outlined. A comparison of quantitative and qualitative methods is also given. Finally, the limitation of model-based methods and the alternative and supplementary use of heuristic knowledge are discussed.

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Citations
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Journal ArticleDOI

Neural network-based software sensor: training set design and application to a continuous pulp digester

TL;DR: A neural network-based strategy for detection of feedstock variations in a continuous pulp digester with a feedforward two-layer perceptron network trained to detect and isolate unmeasured variations in the feedstock.
Journal ArticleDOI

An advanced neural-network-based instrument fault detection and isolation scheme

TL;DR: An advanced scheme for instrument fault detection and isolation is proposed, based on artificial neural networks, organized in layers and handled by knowledge-based analytical redundancy relationships.

A Review of Diagnostic Techniques for ISHM Applications

TL;DR: There is no "one-size-fits-all" approach to building diagnostic and health monitoring capabilities for a system, and striking the correct balance between automated and human-performed tasks is a vital concern.
Journal ArticleDOI

Fault diagnostic systems for agricultural machinery.

TL;DR: In this paper, a systematic and comparative study of various fault diagnostic methods, from an agricultural machinery perspective, is provided in which the authors emphasize the importance of introducing more advanced multivariate fault diagnostic systems on agricultural machinery.
Proceedings ArticleDOI

A DSP-based FFT-analyzer for the fault diagnosis of rotating machine based on vibration analysis

TL;DR: A DSP-based measurement system dedicated to the vibration analysis on rotating machines highlights high promptness in detecting faults, low false alarm rate, and very good diagnostic performance.
References
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Journal ArticleDOI

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

Paul M. Frank
- 01 May 1990 - 
TL;DR: 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.
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

Rolf Isermann
- 01 Jul 1984 - 
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

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.