PUMA publications for /tag/Learning%20xlrhttps://puma.ub.uni-stuttgart.de/tag/Learning%20xlrPUMA RSS feed for /tag/Learning%20xlr2024-03-29T14:01:57+01:00Estimation of stability lobe diagrams in milling with continuous learning algorithmshttps://puma.ub.uni-stuttgart.de/bibtex/28c494972705666f29df6c2d8f9c80392/isw-bibliothekisw-bibliothek2016-03-21T15:25:16+01:00Learning Milling Neural Process Support algorithms machines myown network stability vector xfh xlr xvl <span data-person-type="author" class="authorEditorList "><span><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Jens Friedrich" itemprop="url" href="/person/18f7522f978b23c86bce7a9d182e5dae6/author/0"><span itemprop="name">J. Friedrich</span></a></span>, </span><span><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Christoph Hinze" itemprop="url" href="/person/18f7522f978b23c86bce7a9d182e5dae6/author/1"><span itemprop="name">C. Hinze</span></a></span>, </span><span><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Anton Renner" itemprop="url" href="/person/18f7522f978b23c86bce7a9d182e5dae6/author/2"><span itemprop="name">A. Renner</span></a></span>, </span><span><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Alexander Verl" itemprop="url" href="/person/18f7522f978b23c86bce7a9d182e5dae6/author/3"><span itemprop="name">A. Verl</span></a></span>, </span> and <span><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Armin Lechler" itemprop="url" href="/person/18f7522f978b23c86bce7a9d182e5dae6/author/4"><span itemprop="name">A. Lechler</span></a></span></span>. </span><span class="additional-entrytype-information"><span itemtype="http://schema.org/PublicationIssue" itemscope="itemscope" itemprop="isPartOf"><em><span itemprop="journal">Robotics and Computer-Integrated Manufacturing</span>, </em> </span>(<em><span>2015<meta content="2015" itemprop="datePublished"/></span></em>)</span>Mon Mar 21 15:25:16 CET 2016Robotics and Computer-Integrated Manufacturing - Estimation of stability lobe diagrams in milling with continuous learning algorithms 2015Learning Milling Neural Process Support algorithms machines myown network stability vector xfh xlr xvl Abstract The productivity of milling processes is limited by the occurrence of chatter vibrations. The correlation of the maximum stable cutting depth and the spindle speed can be shown in a stability lobe diagram (SLD). The stability is different for different width of cut and can change with the axis positions. Today it is already a great effort to estimate the \{SLD\} only for one position. Many experiments are necessary to measure the \{SLD\} or derive a detailed mathematical model to calculate the SLD. Moreover not only the cutting depth, but also the cutting width should be represented in the SLD. This paper presents a new approach to assess the process stability based on measured acceleration signals. The multidimensional stability lobe diagram (MSLD) are derived during the production using two new continuously learning algorithms. In this paper the application of a continuous learning support vector machine and a continuous neural network is shown. The support vector machine and the neural network are extended to make them capable for continuous learning and time-variant systems. A new trust criterion is introduced, which gives information about the prediction quality of the output for the selected input region. The learned \{MSLDs\} are evaluated against analytically calculated \{MSLDs\} and the learning algorithms can reproduce the analytical results very well. Continuous learning support vector machine to estimate stability lobe diagrams in millinghttps://puma.ub.uni-stuttgart.de/bibtex/2575e20fd8faadd0adcf43a69e8eea13b/isw-bibliothekisw-bibliothek2016-03-21T15:22:24+01:00Learning Milling Process Support algorithm isw machines myown stbaility vector xfh xlr xvl <span data-person-type="author" class="authorEditorList "><span><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Jens Friedrich" itemprop="url" href="/person/17561a08748c744e594f0573293e6ba66/author/0"><span itemprop="name">J. Friedrich</span></a></span>, </span><span><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Henning Hartmann" itemprop="url" href="/person/17561a08748c744e594f0573293e6ba66/author/1"><span itemprop="name">H. Hartmann</span></a></span>, </span><span><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Alexander Verl" itemprop="url" href="/person/17561a08748c744e594f0573293e6ba66/author/2"><span itemprop="name">A. Verl</span></a></span>, </span> and <span><span itemtype="http://schema.org/Person" itemscope="itemscope" itemprop="author"><a title="Armin Lechler" itemprop="url" href="/person/17561a08748c744e594f0573293e6ba66/author/3"><span itemprop="name">A. Lechler</span></a></span></span>. </span><span class="additional-entrytype-information"><span itemtype="http://schema.org/Book" itemscope="itemscope" itemprop="isPartOf"><em><span itemprop="name">Proceedings of the 24th International Conference on Flexible Automation & Intelligent Manufacturing</span>, </em></span><em><span itemprop="publisher">University of Texas at San Antonio</span>, </em>(<em><span>2014<meta content="2014" itemprop="datePublished"/></span></em>)</span>Mon Mar 21 15:22:24 CET 2016Proceedings of the 24th International Conference on Flexible Automation {\&} Intelligent ManufacturingContinuous learning support vector machine to estimate stability lobe diagrams in milling2014Learning Milling Process Support algorithm isw machines myown stbaility vector xfh xlr xvl