Eugene Yamamoto 2024a - Revision history

https://www.scipedia.com/wd/index.php?action=history&feed=atom&title=Eugene_Yamamoto_2024a Eugene Yamamoto 2024a - Revision history 2026-05-05T14:50:00Z Revision history for this page on the wiki MediaWiki 1.27.0-wmf.10 https://www.scipedia.com/wd/index.php?title=Eugene_Yamamoto_2024a&diff=305863&oldid=prev Scipediacontent at 07:41, 3 July 2024 2024-07-03T07:41:52Z

<p></p> <table class="diff diff-contentalign-left" data-mw="interface"> <col class='diff-marker' /> <col class='diff-content' /> <col class='diff-marker' /> <col class='diff-content' /> <tr style='vertical-align: top;' lang='en'> <td colspan='2' style="background-color: white; color:black; text-align: center;">← Older revision</td> <td colspan='2' style="background-color: white; color:black; text-align: center;">Revision as of 07:41, 3 July 2024</td> </tr><tr><td colspan="2" class="diff-lineno" id="mw-diff-left-l5" >Line 5:</td> <td colspan="2" class="diff-lineno">Line 5:</td></tr> <tr><td class='diff-marker'> </td><td style="background-color: #f9f9f9; color: #333333; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #e6e6e6; vertical-align: top; white-space: pre-wrap;"></td><td class='diff-marker'> </td><td style="background-color: #f9f9f9; color: #333333; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #e6e6e6; vertical-align: top; white-space: pre-wrap;"></td></tr> <tr><td class='diff-marker'> </td><td style="background-color: #f9f9f9; color: #333333; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #e6e6e6; vertical-align: top; white-space: pre-wrap;"><div>== Full Paper ==</div></td><td class='diff-marker'> </td><td style="background-color: #f9f9f9; color: #333333; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #e6e6e6; vertical-align: top; white-space: pre-wrap;"><div>== Full Paper ==</div></td></tr> <tr><td class='diff-marker'>−</td><td style="color:black; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #ffe49c; vertical-align: top; white-space: pre-wrap;"><div><pdf>Media:<del class="diffchange diffchange-inline">Draft_Sanchez Pinedo_92397386887</del>.pdf</pdf></div></td><td class='diff-marker'>+</td><td style="color:black; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div><pdf>Media:<ins class="diffchange diffchange-inline">Eugene_Yamamoto_2024a_8798_Hybrid structure health monitoring technique for enhancing modal parameter identification accuracy</ins>.pdf</pdf></div></td></tr>  </table>

Scipediacontent https://www.scipedia.com/wd/index.php?title=Eugene_Yamamoto_2024a&diff=305516&oldid=prev JSanchez: JSanchez moved page Draft Sanchez Pinedo 923973868 to Eugene Yamamoto 2024a 2024-07-01T11:01:15Z

<p>JSanchez moved page <a href="/public/Draft_Sanchez_Pinedo_923973868" class="mw-redirect" title="Draft Sanchez Pinedo 923973868">Draft Sanchez Pinedo 923973868</a> to <a href="/public/Eugene_Yamamoto_2024a" title="Eugene Yamamoto 2024a">Eugene Yamamoto 2024a</a></p> <table class="diff diff-contentalign-left" data-mw="interface"> <tr style='vertical-align: top;' lang='en'> <td colspan='1' style="background-color: white; color:black; text-align: center;">← Older revision</td> <td colspan='1' style="background-color: white; color:black; text-align: center;">Revision as of 11:01, 1 July 2024</td> </tr><tr><td colspan='2' style='text-align: center;' lang='en'><div class="mw-diff-empty">(No difference)</div> </td></tr></table>

JSanchez https://www.scipedia.com/wd/index.php?title=Eugene_Yamamoto_2024a&diff=305515&oldid=prev JSanchez at 11:01, 1 July 2024 2024-07-01T11:01:10Z

<p></p> <table class="diff diff-contentalign-left" data-mw="interface"> <col class='diff-marker' /> <col class='diff-content' /> <col class='diff-marker' /> <col class='diff-content' /> <tr style='vertical-align: top;' lang='en'> <td colspan='2' style="background-color: white; color:black; text-align: center;">← Older revision</td> <td colspan='2' style="background-color: white; color:black; text-align: center;">Revision as of 11:01, 1 July 2024</td> </tr><tr><td colspan="2" class="diff-lineno" id="mw-diff-left-l3" >Line 3:</td> <td colspan="2" class="diff-lineno">Line 3:</td></tr> <tr><td class='diff-marker'> </td><td style="background-color: #f9f9f9; color: #333333; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #e6e6e6; vertical-align: top; white-space: pre-wrap;"></td><td class='diff-marker'> </td><td style="background-color: #f9f9f9; color: #333333; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #e6e6e6; vertical-align: top; white-space: pre-wrap;"></td></tr> <tr><td class='diff-marker'> </td><td style="background-color: #f9f9f9; color: #333333; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #e6e6e6; vertical-align: top; white-space: pre-wrap;"><div>SHM relies on the possibility of estimating structural modal parameters, such as mode shapes, natural frequencies, and damping, from the structure’s measured data. Nevertheless, modal parameter estimation still faces accuracy problems. The identification of bridge and/or vehicle system parameters and vibration characteristics have been studied both numerically and experimentally. The knowledge of bridge vibration characteristics and vehicle system parameters is crucial to the maintenance of bridges. The issue is that the techniques used to identify bridge and vehicle system parameters usually work very well with numerical simulation but present accuracy issues with experimental data due to environmental noise. Traditionally, measured data were obtained by instrumenting bridges with connected sensor systems, which had issues such as high cost, maintenance problems, safety concerns, and traffic disruption. More recently, indirect SHM (iSHM) methods, such as drive-by using passing instrumented vehicles, have been researched[1,2]. However, these methods still struggle with the accuracy of modal parameter identification, particularly for higher vibration modes sensitive to localized bridge damage, limiting the widespread adoption of iSHM methodologies[1,3]. A combination of indirect and direct monitoring methods is proposed to address these limitations. This approach aims to improve modal parameter identification, including higher vibration modes, for localized damage detection and structural assessment. The proposed method uses GPS-time synchronized sensors for simultaneous measurement of vehicle and bridge vibration data and is verified through numerical simulation assuming multiple runs over the same bridge. The study highlights the potential of this hybrid SHM technique to significantly improve the accuracy of indirect structural health monitoring, providing more reliable and precise modal parameter estimates, especially for higher vibration modes, allowing for the identification of localized bridge damage.</div></td><td class='diff-marker'> </td><td style="background-color: #f9f9f9; color: #333333; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #e6e6e6; vertical-align: top; white-space: pre-wrap;"><div>SHM relies on the possibility of estimating structural modal parameters, such as mode shapes, natural frequencies, and damping, from the structure’s measured data. Nevertheless, modal parameter estimation still faces accuracy problems. The identification of bridge and/or vehicle system parameters and vibration characteristics have been studied both numerically and experimentally. The knowledge of bridge vibration characteristics and vehicle system parameters is crucial to the maintenance of bridges. The issue is that the techniques used to identify bridge and vehicle system parameters usually work very well with numerical simulation but present accuracy issues with experimental data due to environmental noise. Traditionally, measured data were obtained by instrumenting bridges with connected sensor systems, which had issues such as high cost, maintenance problems, safety concerns, and traffic disruption. More recently, indirect SHM (iSHM) methods, such as drive-by using passing instrumented vehicles, have been researched[1,2]. However, these methods still struggle with the accuracy of modal parameter identification, particularly for higher vibration modes sensitive to localized bridge damage, limiting the widespread adoption of iSHM methodologies[1,3]. A combination of indirect and direct monitoring methods is proposed to address these limitations. This approach aims to improve modal parameter identification, including higher vibration modes, for localized damage detection and structural assessment. The proposed method uses GPS-time synchronized sensors for simultaneous measurement of vehicle and bridge vibration data and is verified through numerical simulation assuming multiple runs over the same bridge. The study highlights the potential of this hybrid SHM technique to significantly improve the accuracy of indirect structural health monitoring, providing more reliable and precise modal parameter estimates, especially for higher vibration modes, allowing for the identification of localized bridge damage.</div></td></tr> <tr><td colspan="2"> </td><td class='diff-marker'>+</td><td style="color:black; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div><ins style="font-weight: bold; text-decoration: none;"></ins></div></td></tr> <tr><td colspan="2"> </td><td class='diff-marker'>+</td><td style="color:black; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div><ins style="font-weight: bold; text-decoration: none;">== Full Paper ==</ins></div></td></tr> <tr><td colspan="2"> </td><td class='diff-marker'>+</td><td style="color:black; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div><ins style="font-weight: bold; text-decoration: none;"><pdf>Media:Draft_Sanchez Pinedo_92397386887.pdf</pdf></ins></div></td></tr>  </table>

JSanchez https://www.scipedia.com/wd/index.php?title=Eugene_Yamamoto_2024a&diff=305513&oldid=prev JSanchez at 11:01, 1 July 2024 2024-07-01T11:01:08Z

<p></p> <table class="diff diff-contentalign-left" data-mw="interface"> <col class='diff-marker' /> <col class='diff-content' /> <col class='diff-marker' /> <col class='diff-content' /> <tr style='vertical-align: top;' lang='en'> <td colspan='2' style="background-color: white; color:black; text-align: center;">← Older revision</td> <td colspan='2' style="background-color: white; color:black; text-align: center;">Revision as of 11:01, 1 July 2024</td> </tr><tr><td colspan="2" class="diff-lineno" id="mw-diff-left-l1" >Line 1:</td> <td colspan="2" class="diff-lineno">Line 1:</td></tr> <tr><td colspan="2"> </td><td class='diff-marker'>+</td><td style="color:black; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div><ins style="font-weight: bold; text-decoration: none;">                                </ins></div></td></tr> <tr><td colspan="2"> </td><td class='diff-marker'>+</td><td style="color:black; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div><ins style="font-weight: bold; text-decoration: none;">==Abstract==</ins></div></td></tr> <tr><td class='diff-marker'> </td><td style="background-color: #f9f9f9; color: #333333; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #e6e6e6; vertical-align: top; white-space: pre-wrap;"></td><td class='diff-marker'> </td><td style="background-color: #f9f9f9; color: #333333; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #e6e6e6; vertical-align: top; white-space: pre-wrap;"></td></tr> <tr><td colspan="2"> </td><td class='diff-marker'>+</td><td style="color:black; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div><ins style="font-weight: bold; text-decoration: none;">SHM relies on the possibility of estimating structural modal parameters, such as mode shapes, natural frequencies, and damping, from the structure’s measured data. Nevertheless, modal parameter estimation still faces accuracy problems. The identification of bridge and/or vehicle system parameters and vibration characteristics have been studied both numerically and experimentally. The knowledge of bridge vibration characteristics and vehicle system parameters is crucial to the maintenance of bridges. The issue is that the techniques used to identify bridge and vehicle system parameters usually work very well with numerical simulation but present accuracy issues with experimental data due to environmental noise. Traditionally, measured data were obtained by instrumenting bridges with connected sensor systems, which had issues such as high cost, maintenance problems, safety concerns, and traffic disruption. More recently, indirect SHM (iSHM) methods, such as drive-by using passing instrumented vehicles, have been researched[1,2]. However, these methods still struggle with the accuracy of modal parameter identification, particularly for higher vibration modes sensitive to localized bridge damage, limiting the widespread adoption of iSHM methodologies[1,3]. A combination of indirect and direct monitoring methods is proposed to address these limitations. This approach aims to improve modal parameter identification, including higher vibration modes, for localized damage detection and structural assessment. The proposed method uses GPS-time synchronized sensors for simultaneous measurement of vehicle and bridge vibration data and is verified through numerical simulation assuming multiple runs over the same bridge. The study highlights the potential of this hybrid SHM technique to significantly improve the accuracy of indirect structural health monitoring, providing more reliable and precise modal parameter estimates, especially for higher vibration modes, allowing for the identification of localized bridge damage.</ins></div></td></tr>  </table>

JSanchez https://www.scipedia.com/wd/index.php?title=Eugene_Yamamoto_2024a&diff=305512&oldid=prev JSanchez: Created blank page 2024-07-01T11:01:06Z

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