Feature Selection for Complex Systems Monitoring: an Application using Data Fusion
TypeCommunications avec actes
Emergence of automated and flexible production means leads to the need of robust monitoring systems. Such systems are aimed at the estimation of the production process state by deriving it as a function of critical variables, called features, that characterize the process condition. The problem of feature selection, which consists, given an original set of features, in finding a subset such the estimation accuracy of the monitoring system is the highest possible, is therefore of major importance for sensor-based monitoring applications. Considering real-world applications, feature selection can be tricky due to imperfection on available data collections: depending on the data acquisition conditions and the monitored process operating conditions, they can be heterogeneous, incomplete, imprecise, contradictory, or erroneous. Classical feature selection techniques lack of solutions to deal with uncertain data coming from different collections. Data fusion provides solutions to process these data collections altogether in order to achieve coherent feature selection, even in difficult cases involving imperfect data. In this work, condition monitoring of the tool in industrial drilling systems will serve as a basis to demonstrate how data fusion techniques can be used to perform feature selection in such difficult cases.
Fichier(s) constituant cette publication
Cette publication figure dans le(s) laboratoire(s) suivant(s)
Visualiser des documents liés par titre, auteur, créateur et sujet.
LE MOAL, G; MORARU, George; VERON, Philippe; DOUILLY, M; RABATE, Patrice (Proceedings of the 14th International Conference on Information Fusion - FUSION, 2011)This paper addresses the problem of robust detection of signal singularity in hostile environments using multisensor data fusion. Measurement uncertainty is usually treated in a probabilistic way, assuming lack of ...
LE MOAL, G; RABATE, Patrice; MORARU, George; VERON, Philippe; DOUILLY, M (IK4, 2012)Acoustic Emission (AE) is considered an efficient tool for monitoring of machining operations, for both tool condition and working piece integrity. However, the use of AE is more challenging in case of drilling, due to ...
MORARU, George; VERON, Philippe; RABATE, Patrice (OMPI (Organisation Mondiale de la Propriété Intellectuelle), 2010)The invention relates to a drilling head with an axial oscillation generator, based on the use of piezoelectric ceramic actuators.
MORARU, George; RABATE, Patrice (OMPI (Organisation Mondiale de la Propriété Intellectuelle), 2009)To improve machining quality and performances by material removal, an active chip breaker is proposed, in order to fragment the chips while machining.
PERNOT, Jean-Philippe; MORARU, George; VERON, Philippe (Taylor & Francis, 2007)The Reverse Engineering process consists of a succession of operations that aim at creating a digital representation of a physical model. The reconstructed geometric model is often a triangle mesh built from a point cloud ...