A Multi-Working States Sensor Anomaly Detection Method Using Deep Learning Algorithms

The data collected from sensors are subject to the presence of anomaly data. These anomalies may stem from sensor malfunctions or poor communication. Prior to the processing of the data, it is imperative to detect and isolate the anomaly data from the substantial volume of normal data. The utilizati...

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Bibliographic Details
Published in:	Sensors (Basel, Switzerland) Vol. 25; no. 18; p. 5686
Main Authors:	Wu, Di, Koskinen, Kari, Coatanea, Eric
Format:	Journal Article
Language:	English
Published:	Switzerland MDPI AG 12.09.2025
Subjects:	Accuracy Behavior data-driven deep learning Influence LSTM Methods Neural networks Physics sensor anomaly detection Sensors Support vector machines Working conditions sensor anomaly detection deep learning LSTM data-driven
ISSN:	1424-8220, 1424-8220
Online Access:	Get full text
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