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Conference Papers Year : 2011

Time-Frequency Analysis of Hot Rolling Using Manifold Learning

Francisco J. García
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Ignacio Díaz
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Ignacio Álvarez
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Daniel Pérez
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Daniel G. Ordonez
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Manuel Domínguez
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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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Dates and versions

hal-01571375 , version 1 (02-08-2017)





Francisco J. García, Ignacio Díaz, Ignacio Álvarez, Daniel Pérez, Daniel G. 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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