Journal ArticleDOI
Diagnosis of continuous dynamic systems: integrating consistency based diagnosis with machine-learning techniques
Belarmino Pulido,Juan José Rodríguez Diez,Carlos Alonso González,Oscar J. Prieto,Esteban R. Gelso +4 more
TLDR
In this article, an integrated approach to diagnosis of complex dynamic systems, combining model based diagnosis with machine learning techniques, is proposed, and a simple framework to make them cooperate, hence improving the diagnosis capabilities of each individual method.About:
This article is published in IFAC Proceedings Volumes.The article was published on 2005-01-01. It has received 5 citations till now. The article focuses on the topics: Fault detection and isolation.read more
Citations
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Journal Article
Early fault classification in dynamic systems using case-based reasoning
Anibal Bregon,M. Aranzazu Simon,Juan J. Rodríguez,Carlos J. Alonso,Belarmino Pulido,Isaac Moro +5 more
TL;DR: A computational framework to deal with the problem of early fault classification using Case-Based Reasoning is presented and different techniques for case retrieval and reuse that have been applied at different times of fault evolution are illustrated.
Book ChapterDOI
Early fault classification in dynamic systems using case-based reasoning
Anibal Bregon,M. Aranzazu Simon,Juan J. Rodríguez,Carlos J. Alonso,Belarmino Pulido,Isaac Moro +5 more
TL;DR: In this article, the authors present a computational framework to deal with the problem of early fault classification using Case-Based Reasoning, which has been tested for a set of fourteen fault classes simulated in a laboratory plant.
Book ChapterDOI
Stacking Dynamic Time Warping for the Diagnosis of Dynamic Systems
TL;DR: Experimental results show that the former Stacking configuration is quite competitive, compare to other methods like tree induction, Support Vector Machines or even K-NN and Naive Bayes as stand alone methods.
Proceedings Article
A comparison of two machine-learning techniques to focus the diagnosis task
Oscar J. Prieto,Anibal Bregon +1 more
TL;DR: This work considers a time series classification task: fault identification in dynamic systems and two methods are compared: i) Boosting and ii) K-Nearest Neighbors with Dynamic Time Warping distance.
Proceedings ArticleDOI
Focusing fault localization in model-based diagnosis with case-based reasoning
Anibal Bregon,Belarmino Pulido,M. Aranzazu Simon,Isaac Moro,Oscar J. Prieto,Juan José Rodríguez Diez,Carlos J. Alonso-González +6 more
TL;DR: This work study the combination of a consistency-based diagnosis system together with a Case-based Reasoning system that will perform fault detection and localization and the CBR system provides accurate indication of the most probable fault mode, at early stages of the localization process.
References
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Book
C4.5: Programs for Machine Learning
TL;DR: A complete guide to the C4.5 system as implemented in C for the UNIX environment, which starts from simple core learning methods and shows how they can be elaborated and extended to deal with typical problems such as missing data and over hitting.
Proceedings Article
A brief introduction to boosting
TL;DR: The boosting algorithm AdaBoost is introduced, and the underlying theory of boosting is explained, including an explanation of why boosting often does not suffer from overfitting.
Journal ArticleDOI
A neural network methodology for process fault diagnosis
TL;DR: A neural-network-based methodology for providing a potential solution to the preceding problems in the area of process fault diagnosis is proposed and compared with the knowledge-based approach.
Journal ArticleDOI
Conflicts versus analytical redundancy relations: a comparative analysis of the model based diagnosis approach from the artificial intelligence and automatic control perspectives
Marie-Odile Cordier,Philippe Dague,François Lévy,Jacky Montmain,Marcel Staroswiecki,Louise Travé-Massuyès +5 more
TL;DR: A formal framework is proposed in order to compare the two approaches and the theoretical proof of their equivalence together with the necessary and sufficient conditions is provided.