Results 1 to 10 of about 52,653 (304)
Sensor Fault Diagnostics Using Physics-Informed Transfer Learning Framework [PDF]
Sensors, 2022 The field of smart health monitoring, intelligent fault detection and diagnosis is expanding dramatically in order to maintain successful operation in many engineering applications.
Furkan Guc, Yangquan Chen
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Digital Twin for Training Bayesian Networks for Fault Diagnostics of Manufacturing Systems [PDF]
Sensors, 2022 Smart manufacturing systems are being advocated to leverage technological advances that enable them to be more resilient to faults through rapid diagnosis for performance assurance.
Toyosi Ademujimi, Vittaldas Prabhu
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A Deep Learning Method for Bearing Cross-Domain Fault Diagnostics Based on the Standard Envelope Spectrum [PDF]
SensorsIntelligent fault diagnostics based on deep learning provides a favorable guarantee for the reliable operation of equipment, but a trained deep learning model generally has low prediction accuracy in cross-domain diagnostics.
Lubin Zhai +3 more
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Machines, 2022 Autonomous underwater vehicle (AUV) is one of the most important exploration tools in the ocean underwater environment, whose movement is realized by the underwater thrusters, however, the thruster fault happens frequently in engineering practice.
Qunhong Tian +3 more
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Sensors and Fault Diagnostics in Power System. [PDF]
Sensors (Basel)The adequate technical condition assessment of key apparatuses is a crucial assumption in the delivery of reliable and continuous electric power to customers [...]
Kunicki M, Fulneček J, Rozga P.
europepmc +4 more sources
Fault Diagnostics Based on the Analysis of Probability Distributions Estimated Using a Particle Filter [PDF]
SensorsThis paper proposes a monitoring procedure based on characterizing state probability distributions estimated using particle filters. The work highlights what types of information can be obtained during state estimation and how the revealed information ...
András Darányi, János Abonyi
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Fault Diagnostics by Conceptors-Aided Clustering [PDF]
Proceedings of the 30th European Safety and Reliability Conference and 15th Probabilistic Safety Assessment and Management Conference, 2020 Fault diagnostics in practice faces the challenge of dealing with unlabelled time series that have long-term temporal dependencies. Inspired by the idea of representing temporal patterns by a mechanism of neurodynamical pattern learning, called Conceptors, we propose an unsupervised clustering method for identifying the degradation state of industrial ...
Xu M., Baraldi P., Zio E.
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Spatial-Temporal Recurrent Graph Neural Networks for Fault Diagnostics in Power Distribution Systems
IEEE Access, 2023 Fault diagnostics are extremely important to decide proper actions toward fault isolation and system restoration. The growing integration of inverter-based distributed energy resources imposes strong influences on fault detection using traditional ...
Bang L. H. Nguyen +4 more
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Machines, 2023 This paper addresses the diagnostics of stator faults in three-phase line-start permanent magnet synchronous motors. More traditional fault diagnostic methodologies are unable to properly diagnose stator inter-turn short-circuit faults in three-phase ...
D. S. B. Fonseca +2 more
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System fault diagnostics using fault tree analysis [PDF]
Proceedings of the Institution of Mechanical Engineers, Part O: Journal of Risk and Reliability, 2007 Over the last 50 years, advances in technology have led to an increase in the complexity and sophistication of systems. More complex systems can be harder to maintain and the root cause of a fault more difficult to isolate. Downtime resultin from a system failure can be dangerous or expensive, depending on the type of system.
E. E. Hurdle +2 more
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