完整後設資料紀錄
DC 欄位語言
dc.contributor.authorYang, S. K.en_US
dc.contributor.authorLiu, T. S.en_US
dc.contributor.authorCheng, Y. C.en_US
dc.date.accessioned2014-12-08T15:11:25Z-
dc.date.available2014-12-08T15:11:25Z-
dc.date.issued2008-06-01en_US
dc.identifier.issn0263-2241en_US
dc.identifier.urihttp://dx.doi.org/10.1016/j.measurement.2007.07.003en_US
dc.identifier.urihttp://hdl.handle.net/11536/8764-
dc.description.abstractAccidents caused by heavy vehicles have been increasing in recent years. This is mainly due to the fact that vehicle overloading results in steering difficulty and long braking distance. Therefore, this work aims to develop an automatic payload measurement for heavy vehicles, so that drivers and police officers can monitor vehicle payload while oil board the measured vehicle. For the ease of installation, high accuracy, and low cost, this work proposes to paste strain gages onto each leaf spring in vehicle suspensions. Based oil measured output voltages of bridge circuits in each suspension, the vehicle payload is calculated. Moreover, for promoting the accuracy of calculated payload, this work develops neural network models to account for nonlinearity in measurement. Finally, this work verifies model accuracy based oil experimental data. (C) 2007 Elsevier Ltd. All rights reserved.en_US
dc.language.isoen_USen_US
dc.subjectpayloaden_US
dc.subjectstrain gageen_US
dc.subjectleaf springen_US
dc.subjectneural networken_US
dc.titleAutomatic measurement of payload for heavy vehicles using strain gagesen_US
dc.typeArticleen_US
dc.identifier.doi10.1016/j.measurement.2007.07.003en_US
dc.identifier.journalMEASUREMENTen_US
dc.citation.volume41en_US
dc.citation.issue5en_US
dc.citation.spage491en_US
dc.citation.epage502en_US
dc.contributor.department機械工程學系zh_TW
dc.contributor.departmentDepartment of Mechanical Engineeringen_US
dc.identifier.wosnumberWOS:000256643200003-
dc.citation.woscount4-
顯示於類別:期刊論文


文件中的檔案:

  1. 000256643200003.pdf

若為 zip 檔案,請下載檔案解壓縮後,用瀏覽器開啟資料夾中的 index.html 瀏覽全文。