Autoencoder-Ensemble-Based Unsupervised Selection of Production-Relevant Variables for Context-Aware Fault Diagnosis

Autoencoder-Ensemble-Based Unsupervised Selection of Production-Relevant Variables for Context-Aware Fault Diagnosis

Smart factories are complex; with the increased complexity of employed cyber-physical systems, the complexity evolves further. Cyber-physical systems produce high amounts of data that are hard to capture and challenging to analyze. Real-time recording of all data is not possible due to limited netwo...

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Bibliographic Details
Main Authors: Lukas Kaupp, Bernhard Humm, Kawa Nazemi, Stephan Simons
Format: Article
Language:English
Published: MDPI AG 2022-10-01
Series:Sensors
Subjects:
context-aware diagnosis
outlier detection
cyber-physical systems
pre-training variable selection
autoencoder ensemble
production-relevant variables
Online Access:https://www.mdpi.com/1424-8220/22/21/8259

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https://www.mdpi.com/1424-8220/22/21/8259

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