[HTML][HTML] PrecTime: A deep learning architecture for precise time series segmentation in industrial manufacturing operations
S Gaugel, M Reichert - Engineering Applications of Artificial Intelligence, 2023 - Elsevier
S Gaugel, M Reichert
Engineering Applications of Artificial Intelligence, 2023•ElsevierThe fourth industrial revolution creates ubiquitous sensor data in production plants. To
generate maximum value out of these data, reliable and precise time series-based machine
learning methods like temporal neural networks are needed. This paper proposes a novel
sequence-to-sequence deep learning architecture for time series segmentation called
PrecTime which tries to combine the concepts and advantages of sliding window and dense
labeling approaches. The general-purpose architecture is evaluated on a real-world industry …
generate maximum value out of these data, reliable and precise time series-based machine
learning methods like temporal neural networks are needed. This paper proposes a novel
sequence-to-sequence deep learning architecture for time series segmentation called
PrecTime which tries to combine the concepts and advantages of sliding window and dense
labeling approaches. The general-purpose architecture is evaluated on a real-world industry …
Abstract
The fourth industrial revolution creates ubiquitous sensor data in production plants. To generate maximum value out of these data, reliable and precise time series-based machine learning methods like temporal neural networks are needed. This paper proposes a novel sequence-to-sequence deep learning architecture for time series segmentation called PrecTime which tries to combine the concepts and advantages of sliding window and dense labeling approaches. The general-purpose architecture is evaluated on a real-world industry dataset containing the End-of-Line testing sensor data of hydraulic pumps. We are able to show that PrecTime outperforms five implemented state-of-the-art baseline networks based on multiple metrics. The achieved segmentation accuracy of around 96% shows that PrecTime can achieve results close to human intelligence in operational state segmentation within a testing cycle.
Elsevier