Results 11 to 20 of about 8,566 (306)
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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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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Sensors, 2021 Diagnosing the condition of rotating machines by non-invasive methods is based on the analysis of dynamic signals from sensors mounted on the machine—such as vibration, velocity, or acceleration sensors; torque meters; force sensors; pressure sensors ...
Iwona Komorska, Andrzej Puchalski
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Applied Sciences, 2021 A review of the fault diagnostic techniques based on machine is presented in this paper. As the world is moving towards industry 4.0 standards, the problems of limited computational power and available memory are decreasing day by day.
Karolina Kudelina +5 more
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Scientific Data, 2021 Measurement(s) fault detection and diagnostics • temperature • pressure • mass flow rate • power Technology Type(s) fault imposition • measurement device Factor Type(s) fault type • fault scenario Sample Characteristic - Environment refrigeration system ...
Jian Sun +5 more
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Fault Isolation in Network of State Automates
Известия высших учебных заведений России: Радиоэлектроника, 2020 Introduction. In the paper a fault isolation problem in the devices combining digital unit by functional diagnostics methods is considered. Networks of state automates are accepted as mathematical models of the devices.
I. V. Bystrova, B. P. Podkopaev
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IEEE Access, 2020 Deep learning methods have promoted the vibration-based machinery fault diagnostics from manual feature extraction to an end-to-end solution in the past few years and exhibited great success on various diagnostics tasks. However, this success is based on
Jian Zhou +3 more
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Quantitative Fault Diagnostics of Hydraulic Cylinder Using Particle Filter
Machines, 2023 Condition-based hydraulic cylinder maintenance necessitates quantitative fault diagnostics. However, existing methods are characterized by either qualitative or limited quantitative capabilities.
Yakun Zhang +3 more
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Deep Learning-Based Machinery Fault Diagnostics
Machines, 2022 In recent years, deep learning has shown its unique potential and advantages in feature extraction and pattern recognition [...]
Hongtian Chen +3 more
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FDD in Building Systems Based on Generalized Machine Learning Approaches
Energies, 2023 Automated fault detection and diagnostics in building systems using machine learning (ML) can be applied to commercial buildings and can result in increased efficiency and savings.
William Nelson, Charles Culp
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