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2026
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| Online Access: | https://doi.org/10.5281/zenodo.18632870 |
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| _version_ | 1866901499648409600 |
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| author | Pentakota, Lohit kumar BIANCHI, GIACOMO Leonesio, Marco Papananias, Moschos |
| author_facet | Pentakota, Lohit kumar BIANCHI, GIACOMO Leonesio, Marco Papananias, Moschos |
| contents | <p><strong>Title:</strong> Experimental Centreless Grinding Dataset for Monitoring System Development</p> <p><strong>Description:</strong><br>This dataset provides experimental data from centreless grinding operations, intended for the development and validation of monitoring systems.</p> <p><strong>Dataset Contents:</strong><br>The dataset is organized into two ZIP folders and one standalone Excel file:</p> <ol> <li> <p><strong><code>Experimental_Setup.zip</code></strong> – Contains the main experimental dataset:</p> <ul> <li> <p>This ZIP includes two folders:</p> <ul> <li> <p><strong><code>NumericalControl_Data</code></strong> – signals from the internal control drive of the machine.</p> </li> <li> <p><strong><code>Grinded_Workpiece_Data</code></strong> – measurements of ground workpieces, recorded using the Mitutoyo RT2200.</p> </li> </ul> </li> <li> <p>Each Excel file name corresponds to the file name defined in the standalone Excel file used for data collection.</p> </li> </ul> </li> <li> <p><strong><code>Supplementary_Data.zip</code></strong> – Contains supporting files, including:</p> <ul> <li> <p>Data used for training and testing monitoring models.</p> </li> <li> <p>Additional results supporting the main dataset.</p> </li> </ul> </li> <li> <p><strong><code>CentrelessGrinding_DataSet.xlsx</code></strong> – A standalone Excel file containing all process parameters defined in the Numerical Control (NC) system for all experiments.</p> </li> </ol> <p><strong>Usage Notes:</strong></p> <ul> <li> <p>Each Excel file corresponds to a single experiment.</p> </li> <li> <p>The supplementary data can be used to develop predictive models, monitor process performance, or reproduce experimental analyses.</p> </li> <li> <p>All files are ready for analysis using MATLAB, Python, or other data analysis tools supporting Excel inputs.</p> </li> </ul> |
| format | Recurso digital |
| id | zenodo_https___doi_org_10_5281_zenodo_18632870 |
| institution | Zenodo |
| language | |
| publishDate | 2026 |
| publisher | Zenodo |
| record_format | zenodo |
| spellingShingle | CentrelessGrinding_DataSet Pentakota, Lohit kumar BIANCHI, GIACOMO Leonesio, Marco Papananias, Moschos <p><strong>Title:</strong> Experimental Centreless Grinding Dataset for Monitoring System Development</p> <p><strong>Description:</strong><br>This dataset provides experimental data from centreless grinding operations, intended for the development and validation of monitoring systems.</p> <p><strong>Dataset Contents:</strong><br>The dataset is organized into two ZIP folders and one standalone Excel file:</p> <ol> <li> <p><strong><code>Experimental_Setup.zip</code></strong> – Contains the main experimental dataset:</p> <ul> <li> <p>This ZIP includes two folders:</p> <ul> <li> <p><strong><code>NumericalControl_Data</code></strong> – signals from the internal control drive of the machine.</p> </li> <li> <p><strong><code>Grinded_Workpiece_Data</code></strong> – measurements of ground workpieces, recorded using the Mitutoyo RT2200.</p> </li> </ul> </li> <li> <p>Each Excel file name corresponds to the file name defined in the standalone Excel file used for data collection.</p> </li> </ul> </li> <li> <p><strong><code>Supplementary_Data.zip</code></strong> – Contains supporting files, including:</p> <ul> <li> <p>Data used for training and testing monitoring models.</p> </li> <li> <p>Additional results supporting the main dataset.</p> </li> </ul> </li> <li> <p><strong><code>CentrelessGrinding_DataSet.xlsx</code></strong> – A standalone Excel file containing all process parameters defined in the Numerical Control (NC) system for all experiments.</p> </li> </ol> <p><strong>Usage Notes:</strong></p> <ul> <li> <p>Each Excel file corresponds to a single experiment.</p> </li> <li> <p>The supplementary data can be used to develop predictive models, monitor process performance, or reproduce experimental analyses.</p> </li> <li> <p>All files are ready for analysis using MATLAB, Python, or other data analysis tools supporting Excel inputs.</p> </li> </ul> |
| title | CentrelessGrinding_DataSet |
| url | https://doi.org/10.5281/zenodo.18632870 |