Besides detecting failures and predicting future health conditions of technical systems, fault diagnosis (i.e., fault identification) is a key challenge in the analytic part of prognostics and health management (PHM). In this context, Bayesian networks (BN) has proven to be an effective tool for diagnostic reasoning about faults and effects. Since it is possible to generate such models not only from data but also from expert knowledge or a combination of both (hybrid approach), Bayesian networks are well-suited for many applications and (technical) disciplines. This, in particular, holds for situations where common data-driven approaches (e.g., neural networks, deep learning) suffer from a lack of a reasonable amount of adequate training da...
International audienceIn this article, we have shown an application of a decision support tool which...
The purpose of this article is to present and evaluate the performance of a new procedure for indust...
The purpose of this article is to present a new method for process diagnosis with Bayesian network. ...
International audienceIn the literature, several fault diagnosis methods, qualitative as well quanti...
In an effort to achieve an optimal availability time of induction motors via fault probabilities red...
International audienceIn the literature, several fault diagnosis methods, qualitative as well quanti...
Since multiple failure events associated with derailments could not be identified and derailment pro...
Since multiple failure events associated with derailments could not be identified and derailment pro...
Since multiple failure events associated with derailments could not be identified and derailment pro...
Bayesian Network (BN) models are being successfully applied to improve fault diagnosis, which in tur...
The growing variety of data from condition monitoring of high-speed railways offer unprecedented opp...
This study proposes a Bayesian network (BN) dedicated for the intelligent condition monitoring of ra...
Reliability of the traction system is of critical importance to the safety of CRH (China Railway Hig...
This study proposes a Bayesian network (BN) dedicated for the intelligent condition monitoring of ra...
[[abstract]]© 2005 Inderscience - The Bayesian network is a probabilistic graphical model in which a...
International audienceIn this article, we have shown an application of a decision support tool which...
The purpose of this article is to present and evaluate the performance of a new procedure for indust...
The purpose of this article is to present a new method for process diagnosis with Bayesian network. ...
International audienceIn the literature, several fault diagnosis methods, qualitative as well quanti...
In an effort to achieve an optimal availability time of induction motors via fault probabilities red...
International audienceIn the literature, several fault diagnosis methods, qualitative as well quanti...
Since multiple failure events associated with derailments could not be identified and derailment pro...
Since multiple failure events associated with derailments could not be identified and derailment pro...
Since multiple failure events associated with derailments could not be identified and derailment pro...
Bayesian Network (BN) models are being successfully applied to improve fault diagnosis, which in tur...
The growing variety of data from condition monitoring of high-speed railways offer unprecedented opp...
This study proposes a Bayesian network (BN) dedicated for the intelligent condition monitoring of ra...
Reliability of the traction system is of critical importance to the safety of CRH (China Railway Hig...
This study proposes a Bayesian network (BN) dedicated for the intelligent condition monitoring of ra...
[[abstract]]© 2005 Inderscience - The Bayesian network is a probabilistic graphical model in which a...
International audienceIn this article, we have shown an application of a decision support tool which...
The purpose of this article is to present and evaluate the performance of a new procedure for indust...
The purpose of this article is to present a new method for process diagnosis with Bayesian network. ...