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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Lazaros Iliadis; Chrisina Jayne. 12th Engineering Applications of Neural Networks (EANN 2011) and 7th Artificial Intelligence Applications and Innovations (AIAI), Sep 2011, Corfu, Greece. Springer, IFIP Advances in Information and Communication Technology, AICT-363 (Part I), pp.150-155, 2011, Engineering Applications of Neural Networks. 〈10.1007/978-3-642-23957-1_17〉
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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. Lazaros Iliadis; Chrisina Jayne. 12th Engineering Applications of Neural Networks (EANN 2011) and 7th Artificial Intelligence Applications and Innovations (AIAI), Sep 2011, Corfu, Greece. Springer, IFIP Advances in Information and Communication Technology, AICT-363 (Part I), pp.150-155, 2011, Engineering Applications of Neural Networks. 〈10.1007/978-3-642-23957-1_17〉. 〈hal-01571375〉

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