An optimization algorithm for locomotive secondary spring load adjustment based on artificial immune
In order to control the locomotive wheel （axle） load distribution, a shimming process to adjust the locomotive secondary spring loads was heretofore developed. An immune dominance clonal selection multi-objective algorithm based on the artificial immune system was presented to further improve the pe...
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| Veröffentlicht in: | Journal of Central South University 2013-12, Vol.20 (12), p.3497-3503 |
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| container_title | Journal of Central South University |
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| creator | 潘迪夫 王梦格 朱亚男 韩锟 |
| description | In order to control the locomotive wheel （axle） load distribution, a shimming process to adjust the locomotive secondary spring loads was heretofore developed. An immune dominance clonal selection multi-objective algorithm based on the artificial immune system was presented to further improve the performance of the optimization algorithm for locomotive secondary spring load adjustment, especially to solve the lack of control on the output shim quantity. The algorithm was designed into a two-level optimization structure according to the preferences of the problem, and the priori knowledge of the problem was used as the immune dominance. Experiments on various types of locomotives show that owing to the novel algorithm, the shim quantity is cut down by 30%-60% and the calculation time is about 90% less while the secondary spring load distribution is controlled on the same level as before. The application of this optimization algorithm can significantly improve the availability and efficiency of the secondary spring adjustment process. |
| doi_str_mv | 10.1007/s11771-013-1874-3 |
| format | Article |
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An immune dominance clonal selection multi-objective algorithm based on the artificial immune system was presented to further improve the performance of the optimization algorithm for locomotive secondary spring load adjustment, especially to solve the lack of control on the output shim quantity. The algorithm was designed into a two-level optimization structure according to the preferences of the problem, and the priori knowledge of the problem was used as the immune dominance. Experiments on various types of locomotives show that owing to the novel algorithm, the shim quantity is cut down by 30%-60% and the calculation time is about 90% less while the secondary spring load distribution is controlled on the same level as before. The application of this optimization algorithm can significantly improve the availability and efficiency of the secondary spring adjustment process.</description><identifier>ISSN: 2095-2899</identifier><identifier>EISSN: 2227-5223</identifier><identifier>DOI: 10.1007/s11771-013-1874-3</identifier><language>eng</language><publisher>Berlin/Heidelberg: Springer Berlin Heidelberg</publisher><subject>Engineering ; Metallic Materials ; 人工免疫系统 ; 优化算法 ; 克隆选择 ; 弹簧 ; 机车车轮 ; 负荷调整 ; 负载分布 ; 载荷分布</subject><ispartof>Journal of Central South University, 2013-12, Vol.20 (12), p.3497-3503</ispartof><rights>Central South University Press and Springer-Verlag Berlin Heidelberg 2013</rights><rights>Copyright © Wanfang Data Co. Ltd. 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Cent. South Univ</addtitle><addtitle>Journal of Central South University of Technology</addtitle><description>In order to control the locomotive wheel （axle） load distribution, a shimming process to adjust the locomotive secondary spring loads was heretofore developed. An immune dominance clonal selection multi-objective algorithm based on the artificial immune system was presented to further improve the performance of the optimization algorithm for locomotive secondary spring load adjustment, especially to solve the lack of control on the output shim quantity. The algorithm was designed into a two-level optimization structure according to the preferences of the problem, and the priori knowledge of the problem was used as the immune dominance. Experiments on various types of locomotives show that owing to the novel algorithm, the shim quantity is cut down by 30%-60% and the calculation time is about 90% less while the secondary spring load distribution is controlled on the same level as before. The application of this optimization algorithm can significantly improve the availability and efficiency of the secondary spring adjustment process.</description><subject>Engineering</subject><subject>Metallic Materials</subject><subject>人工免疫系统</subject><subject>优化算法</subject><subject>克隆选择</subject><subject>弹簧</subject><subject>机车车轮</subject><subject>负荷调整</subject><subject>负载分布</subject><subject>载荷分布</subject><issn>2095-2899</issn><issn>2227-5223</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2013</creationdate><recordtype>article</recordtype><recordid>eNp9kE1PAyEURSdGExvtD3CHazPKg_lcNo1fSRM3uiYwwJRmBipMte2vl8k0unMDJNzzbt5JkhvA94Bx-RAAyhJSDDSFqsxSepbMCCFlmhNCz-Mb13lKqrq-TOYhGIEpkIIWdTFL5MIitx1Mb458MM4i3rXOm2HdI-086lzjejeYL4WCapyV3B9Q2Hpj2_jHJeJyswtDr-yABA9KonGEH4w2jeEdMn2_s-o6udC8C2p-uq-Sj6fH9-VLunp7fl0uVmlDczykQGrCsRaQ5bLQueJCFISTUtVaN1wpKhoppcgIaJwJDrTJY5iUOKt0BkVJr5K7ae43t5rblm3cztvYyI62Pcj9XjBFoiWIx5iGKd14F4JXmsW9-rggA8xGr2zyyiLBRq-MRoZMzORA-b-K_6DbU9Ha2fYzcr9NWZVnNVQ5_QHR-Ykk</recordid><startdate>20131201</startdate><enddate>20131201</enddate><creator>潘迪夫 王梦格 朱亚男 韩锟</creator><general>Springer Berlin Heidelberg</general><general>School of Traffic and Transportation Engineering, Central South University, Changsha 410075, China</general><scope>2RA</scope><scope>92L</scope><scope>CQIGP</scope><scope>W92</scope><scope>~WA</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>2B.</scope><scope>4A8</scope><scope>92I</scope><scope>93N</scope><scope>PSX</scope><scope>TCJ</scope></search><sort><creationdate>20131201</creationdate><title>An optimization algorithm for locomotive secondary spring load adjustment based on artificial immune</title><author>潘迪夫 王梦格 朱亚男 韩锟</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c350t-1292a0fb145d6f5eabb62a27e9ffcaee3bcdddb421f04ba13c5fb127048f41673</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2013</creationdate><topic>Engineering</topic><topic>Metallic Materials</topic><topic>人工免疫系统</topic><topic>优化算法</topic><topic>克隆选择</topic><topic>弹簧</topic><topic>机车车轮</topic><topic>负荷调整</topic><topic>负载分布</topic><topic>载荷分布</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>潘迪夫 王梦格 朱亚男 韩锟</creatorcontrib><collection>中文科技期刊数据库</collection><collection>中文科技期刊数据库-CALIS站点</collection><collection>中文科技期刊数据库-7.0平台</collection><collection>中文科技期刊数据库-工程技术</collection><collection>中文科技期刊数据库- 镜像站点</collection><collection>CrossRef</collection><collection>Wanfang Data Journals - Hong Kong</collection><collection>WANFANG Data Centre</collection><collection>Wanfang Data Journals</collection><collection>万方数据期刊 - 香港版</collection><collection>China Online Journals (COJ)</collection><collection>China Online Journals (COJ)</collection><jtitle>Journal of Central South University</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>潘迪夫 王梦格 朱亚男 韩锟</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>An optimization algorithm for locomotive secondary spring load adjustment based on artificial immune</atitle><jtitle>Journal of Central South University</jtitle><stitle>J. Cent. South Univ</stitle><addtitle>Journal of Central South University of Technology</addtitle><date>2013-12-01</date><risdate>2013</risdate><volume>20</volume><issue>12</issue><spage>3497</spage><epage>3503</epage><pages>3497-3503</pages><issn>2095-2899</issn><eissn>2227-5223</eissn><abstract>In order to control the locomotive wheel （axle） load distribution, a shimming process to adjust the locomotive secondary spring loads was heretofore developed. An immune dominance clonal selection multi-objective algorithm based on the artificial immune system was presented to further improve the performance of the optimization algorithm for locomotive secondary spring load adjustment, especially to solve the lack of control on the output shim quantity. The algorithm was designed into a two-level optimization structure according to the preferences of the problem, and the priori knowledge of the problem was used as the immune dominance. Experiments on various types of locomotives show that owing to the novel algorithm, the shim quantity is cut down by 30%-60% and the calculation time is about 90% less while the secondary spring load distribution is controlled on the same level as before. The application of this optimization algorithm can significantly improve the availability and efficiency of the secondary spring adjustment process.</abstract><cop>Berlin/Heidelberg</cop><pub>Springer Berlin Heidelberg</pub><doi>10.1007/s11771-013-1874-3</doi><tpages>7</tpages></addata></record> |
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| ispartof | Journal of Central South University, 2013-12, Vol.20 (12), p.3497-3503 |
| issn | 2095-2899 2227-5223 |
| language | eng |
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| source | Alma/SFX Local Collection; SpringerLink Journals - AutoHoldings |
| subjects | Engineering Metallic Materials 人工免疫系统 优化算法 克隆选择 弹簧 机车车轮 负荷调整 负载分布 载荷分布 |
| title | An optimization algorithm for locomotive secondary spring load adjustment based on artificial immune |
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