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Journal ArticleDOI

Process fault detection based on modeling and estimation methods-A survey

Rolf Isermann
- 01 Jul 1984 - 
- Vol. 20, Iss: 4, pp 387-404
TLDR
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.
About
This article is published in Automatica.The article was published on 1984-07-01. It has received 2367 citations till now. The article focuses on the topics: Fault detection and isolation & Process modeling.

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Citations
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Journal ArticleDOI

Fault Detection and Isolation via the Interacting Multiple Model Approach Applied to Drive-By-Wire Vehicles

TL;DR: In this article, the authors investigate the detection and identification of sensor and actuator faults for a drive-by-wire road vehicle and propose an Interacting Multiple Model approach based on a non-linear vehicle dynamics observer.
Book ChapterDOI

Principles of model-based fault detection

Paul M. Frank
TL;DR: In this article, the authors outline the principles of fault detection and isolation in dynamic systems using a mathematical model of the system and show how structured residuals for the localization of the faults can be generated with the aid of observer schemes.
Journal Article

Multisensor data fusion for automotive engine fault diagnosis

TL;DR: Experiments on a SANTANA AJR engine show that the data fusion method provides good engine fault diagnosis, and the feature-level fusion provides good compromise between the above two methods, which becomes gradually mature.

Improved methods for on-line sensor calibration verification

TL;DR: In this paper, the authors presented several linear and non-linear inferential sensing methods including linear regression and neural networks to predict the drift in a feedwater flow sensor at the Crystal River Nuclear Power Plant.

Identification and supervision of a thermal plant based on multi-layer percetron networks with locally disturbed dynamics

TL;DR: This paper considers the application of neural networks with distributed dynamics to the identification of nonlinear systems by establishing a neural model bank which generates prediction errors which can be treated as analytic symptoms to supervise the plant operating state.
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.
Book

Digital Control Systems

TL;DR: This chapter introduces the z-Transform, a new type of transform that combines Laplace Transforms, z-Transforms and Modified Z-TRANSFORMS with Convolution Integral to achieve state-of-the-art control of Discrete-Data Systems.
Journal ArticleDOI

Correspondence item: An innovations approach to fault detection and diagnosis in dynamic systems

R. K. Mehra, +1 more
- 01 Sep 1971 - 
TL;DR: A general approach to fault detection, diagnosis and prognosis in systems describable by mathematical models is outlined, based on System Theory and Statistical Decision Theory.
Dissertation

Failure accomodation in linear systems through self-reorganization.

TL;DR: In this article, the authors present a model for the first unmanned aerial vehicle (UAV) and demonstrate its performance in the first flight test of the UAV-A1.
Journal ArticleDOI

Parameter estimation for continuous-time models-A survey

TL;DR: The paper reviews the progress of research on parameter estimation for continuous-time models of dynamic systems over the period 1958-1980 and includes a classification system which conforms as closely as possible to that which has arisen naturally over the past two decades.