Add to ORKG17th Australian International Aerospace Congress: AIAC 2017, MelbourneIn this paper we describe the problem of developing sensor fault detection within HUMS instrumentation systems, and solutions based upon machine-learning techniques. We conclude with a report on our proof-of-concept demonstrator, and outline next-steps towards implementation of a autonomous self diagnostic sensor solution.Science Foundation IrelandInsight Research Centr
The ability to diagnose deviations and predict faults effectively is an important task in various in...
In the modern world, systems such as aircraft systems are becoming increasingly complex, often consi...
In order to overcome the complexities encountered in sensing devices with data collection, transmiss...
17th Australian International Aerospace Congress: AIAC 2017, MelbourneIn this paper we describe the ...
8th European Workshop On Structural Health Monitoring (EWSHM 2016). SpainGood data is key to the suc...
This paper describes the hybrid solution, based on artificial neural networks (ANNs), and the produc...
This document presents the work by the group DIagnostic, Supervision et COnduite (DISCO) of the Labo...
Data-driven techniques that extract insights from sensor data reduce the cost of improving system en...
We address the problem of detecting whether an engine is misfiring by using machine learning techniq...
The increasing numbers and complexity of spacecraft is driving a growing need for automated fault de...
The purpose of this work is to perform fault detection and diagnosis regarding the reaction wheels o...
The presence of sensor faults in wireless structural health monitoring can significantly affect the ...
Condition monitoring is a part of the predictive maintenance approach applied to detect and prevent ...
The Tokamak is a device that facilitates nuclear fusion via magnetic confinement of Deuterium and tr...
Health Monitoring strategies rely on tracking the health status of critical engineering structures (...
The ability to diagnose deviations and predict faults effectively is an important task in various in...
In the modern world, systems such as aircraft systems are becoming increasingly complex, often consi...
In order to overcome the complexities encountered in sensing devices with data collection, transmiss...
17th Australian International Aerospace Congress: AIAC 2017, MelbourneIn this paper we describe the ...
8th European Workshop On Structural Health Monitoring (EWSHM 2016). SpainGood data is key to the suc...
This paper describes the hybrid solution, based on artificial neural networks (ANNs), and the produc...
This document presents the work by the group DIagnostic, Supervision et COnduite (DISCO) of the Labo...
Data-driven techniques that extract insights from sensor data reduce the cost of improving system en...
We address the problem of detecting whether an engine is misfiring by using machine learning techniq...
The increasing numbers and complexity of spacecraft is driving a growing need for automated fault de...
The purpose of this work is to perform fault detection and diagnosis regarding the reaction wheels o...
The presence of sensor faults in wireless structural health monitoring can significantly affect the ...
Condition monitoring is a part of the predictive maintenance approach applied to detect and prevent ...
The Tokamak is a device that facilitates nuclear fusion via magnetic confinement of Deuterium and tr...
Health Monitoring strategies rely on tracking the health status of critical engineering structures (...
The ability to diagnose deviations and predict faults effectively is an important task in various in...
In the modern world, systems such as aircraft systems are becoming increasingly complex, often consi...
In order to overcome the complexities encountered in sensing devices with data collection, transmiss...