Multi-objective optimization design of wheat centralized seed feeding device based on particle swarm optimization (PSO) algorithm
In order to solve the problem of interaction between multiple evaluation indexes of seed metering performance under multiple factors of centralized seed feeding device, a multi-objective optimization of structure based on particle swarm optimization (PSO) algorithm was proposed in this paper. The wh...
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| Veröffentlicht in: | International journal of agricultural and biological engineering 2020-11, Vol.13 (6), p.76-84 |
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| container_title | International journal of agricultural and biological engineering |
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| creator | Wang, Qingqing Li, Zhaodong Wang, Weiwei Zhang, Chunling Chen, Liqing Wan, Ling |
| description | In order to solve the problem of interaction between multiple evaluation indexes of seed metering performance under multiple factors of centralized seed feeding device, a multi-objective optimization of structure based on particle swarm optimization (PSO) algorithm was proposed in this paper. The wheat centralized seed feeding device was taken as the research object, and the experimental factors were cone angle of type hole, working speed and seed filling gap. The working process of wheat centralized seed feeding device was simulated by discrete element method (DEM). The average seed number of type hole, the variation coefficient of the average seed number of type hole, and the maximum tangential force between seed and seed feeding mechanism were selected as the evaluation indexes. Through the variance analysis of the evaluation indexes by the experimental factors, the optimization objective function was constructed. Using PSO algorithm, the multi-objective optimization was carried out for the wheat centralized seed feeding device. The optimization results show that the best structural combination parameters of the wheat centralized seed feeding device are the hole cone angle of 31.6° and the seed filling gap of 4.6 mm. The validity of the method was verified by simulation and field test. The results show that the PSO algorithm multi-objective optimization method proposed in this paper can provide a reference for the structural improvement and optimal design of the centralized seed feeding device. |
| doi_str_mv | 10.25165/j.ijabe.20201306.5665 |
| format | Article |
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Anhui Province Engineering Laboratory of Intelligent Agricultural Machinery and Equipment, Hefei 230036, China ; 1. College of Engineering, Anhui Agricultural University, Hefei 230036, China</creatorcontrib><description>In order to solve the problem of interaction between multiple evaluation indexes of seed metering performance under multiple factors of centralized seed feeding device, a multi-objective optimization of structure based on particle swarm optimization (PSO) algorithm was proposed in this paper. The wheat centralized seed feeding device was taken as the research object, and the experimental factors were cone angle of type hole, working speed and seed filling gap. The working process of wheat centralized seed feeding device was simulated by discrete element method (DEM). The average seed number of type hole, the variation coefficient of the average seed number of type hole, and the maximum tangential force between seed and seed feeding mechanism were selected as the evaluation indexes. Through the variance analysis of the evaluation indexes by the experimental factors, the optimization objective function was constructed. Using PSO algorithm, the multi-objective optimization was carried out for the wheat centralized seed feeding device. The optimization results show that the best structural combination parameters of the wheat centralized seed feeding device are the hole cone angle of 31.6° and the seed filling gap of 4.6 mm. The validity of the method was verified by simulation and field test. The results show that the PSO algorithm multi-objective optimization method proposed in this paper can provide a reference for the structural improvement and optimal design of the centralized seed feeding device.</description><identifier>ISSN: 1934-6344</identifier><identifier>EISSN: 1934-6352</identifier><identifier>DOI: 10.25165/j.ijabe.20201306.5665</identifier><language>eng</language><publisher>Beijing: International Journal of Agricultural and Biological Engineering (IJABE)</publisher><subject>Algorithms ; Coefficient of variation ; Design ; Design optimization ; Discrete element method ; Feeding ; Field tests ; Multiple objective analysis ; Nuclear power plants ; Objective function ; Optimization ; Particle swarm optimization ; Performance indices ; Seeds ; Simulation ; Variance analysis ; Velocity ; Wheat</subject><ispartof>International journal of agricultural and biological engineering, 2020-11, Vol.13 (6), p.76-84</ispartof><rights>2020. This work is published under https://creativecommons.org/licenses/by/3.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c331t-8c0938333a10b0039afda5dcd878bdec732d59f7d3cdbef6228a0a3f2a648ffa3</citedby></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>314,780,784,27923,27924</link.rule.ids></links><search><creatorcontrib>Wang, Qingqing</creatorcontrib><creatorcontrib>Li, Zhaodong</creatorcontrib><creatorcontrib>Wang, Weiwei</creatorcontrib><creatorcontrib>Zhang, Chunling</creatorcontrib><creatorcontrib>Chen, Liqing</creatorcontrib><creatorcontrib>Wan, Ling</creatorcontrib><creatorcontrib>2. Anhui Province Engineering Laboratory of Intelligent Agricultural Machinery and Equipment, Hefei 230036, China</creatorcontrib><creatorcontrib>1. College of Engineering, Anhui Agricultural University, Hefei 230036, China</creatorcontrib><title>Multi-objective optimization design of wheat centralized seed feeding device based on particle swarm optimization (PSO) algorithm</title><title>International journal of agricultural and biological engineering</title><description>In order to solve the problem of interaction between multiple evaluation indexes of seed metering performance under multiple factors of centralized seed feeding device, a multi-objective optimization of structure based on particle swarm optimization (PSO) algorithm was proposed in this paper. The wheat centralized seed feeding device was taken as the research object, and the experimental factors were cone angle of type hole, working speed and seed filling gap. The working process of wheat centralized seed feeding device was simulated by discrete element method (DEM). The average seed number of type hole, the variation coefficient of the average seed number of type hole, and the maximum tangential force between seed and seed feeding mechanism were selected as the evaluation indexes. Through the variance analysis of the evaluation indexes by the experimental factors, the optimization objective function was constructed. Using PSO algorithm, the multi-objective optimization was carried out for the wheat centralized seed feeding device. The optimization results show that the best structural combination parameters of the wheat centralized seed feeding device are the hole cone angle of 31.6° and the seed filling gap of 4.6 mm. The validity of the method was verified by simulation and field test. The results show that the PSO algorithm multi-objective optimization method proposed in this paper can provide a reference for the structural improvement and optimal design of the centralized seed feeding device.</description><subject>Algorithms</subject><subject>Coefficient of variation</subject><subject>Design</subject><subject>Design optimization</subject><subject>Discrete element method</subject><subject>Feeding</subject><subject>Field tests</subject><subject>Multiple objective analysis</subject><subject>Nuclear power plants</subject><subject>Objective function</subject><subject>Optimization</subject><subject>Particle swarm optimization</subject><subject>Performance indices</subject><subject>Seeds</subject><subject>Simulation</subject><subject>Variance analysis</subject><subject>Velocity</subject><subject>Wheat</subject><issn>1934-6344</issn><issn>1934-6352</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2020</creationdate><recordtype>article</recordtype><sourceid>ABUWG</sourceid><sourceid>AFKRA</sourceid><sourceid>AZQEC</sourceid><sourceid>BENPR</sourceid><sourceid>CCPQU</sourceid><sourceid>DWQXO</sourceid><sourceid>GNUQQ</sourceid><recordid>eNpVkFtLw0AQhYMoWKt_QRZ80YfUzU42SR-leINKBfV5meyl3ZBL3d222Df_ubFVwZczw3DmDPNF0XlCR4wnGb-uRrbCUo8YZTQBmo14lvGDaJCMIY0z4Ozwr0_T4-jE-4rSLC2AD6LPp1UdbNyVlZbBrjXplsE2dovBdi1R2tt5SzpDNguNgUjdBoe13WpFvO7F9GLbeW9cW6lJib4f9otLdMHKWhO_Qdf8D718fpldEaznnbNh0ZxGRwZrr89-6jB6u7t9nTzE09n94-RmGkuAJMSFpGMoAAATWlIKYzQKuZKqyItSaZkDU3xscgVSldpkjBVIEQzD_lNjEIbRxT536br3lfZBVN3Ktf1JwdKcATDOae_K9i7pOu-dNmLpbIPuQyRU7HCLSuxwi1_c4hs3fAEi5Xgb</recordid><startdate>20201101</startdate><enddate>20201101</enddate><creator>Wang, Qingqing</creator><creator>Li, Zhaodong</creator><creator>Wang, Weiwei</creator><creator>Zhang, Chunling</creator><creator>Chen, Liqing</creator><creator>Wan, Ling</creator><general>International Journal of Agricultural and Biological Engineering (IJABE)</general><scope>AAYXX</scope><scope>CITATION</scope><scope>3V.</scope><scope>7QL</scope><scope>7QO</scope><scope>7SN</scope><scope>7ST</scope><scope>7T7</scope><scope>7TM</scope><scope>7U9</scope><scope>7X2</scope><scope>8FD</scope><scope>8FE</scope><scope>8FG</scope><scope>8FH</scope><scope>8FK</scope><scope>ABJCF</scope><scope>ABUWG</scope><scope>AEUYN</scope><scope>AFKRA</scope><scope>ATCPS</scope><scope>AZQEC</scope><scope>BBNVY</scope><scope>BENPR</scope><scope>BGLVJ</scope><scope>BHPHI</scope><scope>BVBZV</scope><scope>C1K</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>FR3</scope><scope>GNUQQ</scope><scope>H94</scope><scope>HCIFZ</scope><scope>L6V</scope><scope>LK8</scope><scope>M0K</scope><scope>M7N</scope><scope>M7P</scope><scope>M7S</scope><scope>P64</scope><scope>PIMPY</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PRINS</scope><scope>PTHSS</scope><scope>RC3</scope><scope>SOI</scope></search><sort><creationdate>20201101</creationdate><title>Multi-objective optimization design of wheat centralized seed feeding device based on particle swarm optimization (PSO) algorithm</title><author>Wang, Qingqing ; Li, Zhaodong ; Wang, Weiwei ; Zhang, Chunling ; Chen, Liqing ; Wan, Ling</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c331t-8c0938333a10b0039afda5dcd878bdec732d59f7d3cdbef6228a0a3f2a648ffa3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2020</creationdate><topic>Algorithms</topic><topic>Coefficient of variation</topic><topic>Design</topic><topic>Design optimization</topic><topic>Discrete element method</topic><topic>Feeding</topic><topic>Field tests</topic><topic>Multiple objective analysis</topic><topic>Nuclear power plants</topic><topic>Objective function</topic><topic>Optimization</topic><topic>Particle swarm optimization</topic><topic>Performance indices</topic><topic>Seeds</topic><topic>Simulation</topic><topic>Variance analysis</topic><topic>Velocity</topic><topic>Wheat</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Wang, Qingqing</creatorcontrib><creatorcontrib>Li, Zhaodong</creatorcontrib><creatorcontrib>Wang, Weiwei</creatorcontrib><creatorcontrib>Zhang, Chunling</creatorcontrib><creatorcontrib>Chen, Liqing</creatorcontrib><creatorcontrib>Wan, Ling</creatorcontrib><creatorcontrib>2. 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Anhui Province Engineering Laboratory of Intelligent Agricultural Machinery and Equipment, Hefei 230036, China</aucorp><aucorp>1. College of Engineering, Anhui Agricultural University, Hefei 230036, China</aucorp><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Multi-objective optimization design of wheat centralized seed feeding device based on particle swarm optimization (PSO) algorithm</atitle><jtitle>International journal of agricultural and biological engineering</jtitle><date>2020-11-01</date><risdate>2020</risdate><volume>13</volume><issue>6</issue><spage>76</spage><epage>84</epage><pages>76-84</pages><issn>1934-6344</issn><eissn>1934-6352</eissn><abstract>In order to solve the problem of interaction between multiple evaluation indexes of seed metering performance under multiple factors of centralized seed feeding device, a multi-objective optimization of structure based on particle swarm optimization (PSO) algorithm was proposed in this paper. The wheat centralized seed feeding device was taken as the research object, and the experimental factors were cone angle of type hole, working speed and seed filling gap. The working process of wheat centralized seed feeding device was simulated by discrete element method (DEM). The average seed number of type hole, the variation coefficient of the average seed number of type hole, and the maximum tangential force between seed and seed feeding mechanism were selected as the evaluation indexes. Through the variance analysis of the evaluation indexes by the experimental factors, the optimization objective function was constructed. Using PSO algorithm, the multi-objective optimization was carried out for the wheat centralized seed feeding device. The optimization results show that the best structural combination parameters of the wheat centralized seed feeding device are the hole cone angle of 31.6° and the seed filling gap of 4.6 mm. The validity of the method was verified by simulation and field test. The results show that the PSO algorithm multi-objective optimization method proposed in this paper can provide a reference for the structural improvement and optimal design of the centralized seed feeding device.</abstract><cop>Beijing</cop><pub>International Journal of Agricultural and Biological Engineering (IJABE)</pub><doi>10.25165/j.ijabe.20201306.5665</doi><tpages>9</tpages><oa>free_for_read</oa></addata></record> |
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| subjects | Algorithms Coefficient of variation Design Design optimization Discrete element method Feeding Field tests Multiple objective analysis Nuclear power plants Objective function Optimization Particle swarm optimization Performance indices Seeds Simulation Variance analysis Velocity Wheat |
| title | Multi-objective optimization design of wheat centralized seed feeding device based on particle swarm optimization (PSO) algorithm |
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