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Time-Frequency Analysis of Hot Rolling Using Manifold Learning

Abstract : In this paper, we propose a method to compare and visualize spectrograms in a low dimensional space using manifold learning. This approach is divided in two steps: a data processing and dimensionality reduction stage and a feature extraction and a visualization stage. The procedure is applied on different types of data from a hot rolling process, with the aim to detect chatter. Results obtained suggest future developments and applications in hot rolling and other industrial processes.
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https://hal.inria.fr/hal-01571375
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Submitted on : Wednesday, August 2, 2017 - 11:42:01 AM
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Francisco García, Ignacio Díaz, Ignacio Álvarez, Daniel Pérez, Daniel Ordonez, et al.. Time-Frequency Analysis of Hot Rolling Using Manifold Learning. 12th Engineering Applications of Neural Networks (EANN 2011) and 7th Artificial Intelligence Applications and Innovations (AIAI), Sep 2011, Corfu, Greece. pp.150-155, ⟨10.1007/978-3-642-23957-1_17⟩. ⟨hal-01571375⟩

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