Industrial transfer learning for multivariate time series segmentation: A case study on hydraulic pump testing cycles
S Gaugel, M Reichert - Sensors, 2023 - mdpi.com
Industrial data scarcity is one of the largest factors holding back the widespread use of
machine learning in manufacturing. To overcome this problem, the concept of transfer …
machine learning in manufacturing. To overcome this problem, the concept of transfer …
Autoencoder based anomaly detection and explained fault localization in industrial cooling systems
S Holly, R Heel, D Katic, L Schoeffl, A Stiftinger… - arXiv preprint arXiv …, 2022 - arxiv.org
Anomaly detection in large industrial cooling systems is very challenging due to the high
data dimensionality, inconsistent sensor recordings, and lack of labels. The state of the art …
data dimensionality, inconsistent sensor recordings, and lack of labels. The state of the art …
One-Class Domain Adaptation via Meta-Learning
S Holly - 2024 - repositum.tuwien.at
In recent years, the integration of IoT (Internet of Things) sensor platforms into industrial
plants has opened up new opportunities for applying machine learning models to various …
plants has opened up new opportunities for applying machine learning models to various …
Comparison of Clustering Algorithms for Statistical Features of Vibration Data Sets
Vibration-based condition monitoring systems are receiving increasing attention due to their
ability to accurately identify different conditions by capturing dynamic features over a broad …
ability to accurately identify different conditions by capturing dynamic features over a broad …