Small Sample Fault Diagnosis Based on Intrinsic Characteristic Encouraged Network for Unmanned Aerial Vehicle Sensors

Fault detection and classification (FDC) of industrial sensors are commonly featured with rare fault cases and demanding diagnostic accuracy. Data-driven diagnostic strategies including signal processing and neural networks prove to be more prominent compared to traditional ways. Most data-driven st...

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Vydané v:	IEEE transactions on instrumentation and measurement Ročník 73; s. 1 - 14
Hlavní autori:	Song, Jia, Wu, Boxuan, Zhao, Chaoyue, Shang, Weize, Liu, Yang, Li, Wenling
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	New York IEEE 2024 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Predmet:	Accelerometers Accuracy Algorithms Autonomous aerial vehicles Data models Encoders-Decoders Fault detection Fault diagnosis Gyroscopes gyroscopes and accelerometers Kinematics Navigation neural network Neural networks Sensor phenomena and characterization Sensors Signal processing small samples unmanned aerial vehicle (UAV) Unmanned aerial vehicles
ISSN:	0018-9456, 1557-9662
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