Multi-objective variable parameter optimization algorithm for spiral bevel gear tooth surface considering meshing efficiency and contact performance
Abstract A multi-objective variable parameter optimization method that considers meshing efficiency and contact performance simultaneously is proposed to optimize the tooth surface of spiral bevel gears to achieve higher contact performance and transmission efficiency. First, the tooth surface equat...
Ausführliche Beschreibung
Gespeichert in:
| Autor*in: |
Li, Fei [verfasserIn] |
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| Format: |
E-Artikel |
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| Sprache: |
Englisch |
| Erschienen: |
2022 |
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| Schlagwörter: |
Multi-objective variable parameter optimization |
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| Anmerkung: |
© The Korean Society of Mechanical Engineers and Springer-Verlag GmbH Germany, part of Springer Nature 2022 |
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| Übergeordnetes Werk: |
Enthalten in: Journal of mechanical science and technology - Berlin : Springer, 2005, 36(2022), 7 vom: Juli, Seite 3547-3559 |
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| Übergeordnetes Werk: |
volume:36 ; year:2022 ; number:7 ; month:07 ; pages:3547-3559 |
| Links: |
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| DOI / URN: |
10.1007/s12206-022-0631-7 |
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| Katalog-ID: |
SPR050851608 |
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| 245 | 1 | 0 | |a Multi-objective variable parameter optimization algorithm for spiral bevel gear tooth surface considering meshing efficiency and contact performance |
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| 520 | |a Abstract A multi-objective variable parameter optimization method that considers meshing efficiency and contact performance simultaneously is proposed to optimize the tooth surface of spiral bevel gears to achieve higher contact performance and transmission efficiency. First, the tooth surface equations of the spiral bevel gear are established in line with the gear cutting process, and the deviation of tooth surface is analyzed and controlled. Second, the machine tool parameters with the greatest impact on the tooth surface are selected on the basis of the sensitivity analysis approach as the optimization design variables, and the relationship between the machine tool parameters, contact performance, and meshing efficiency is established. Third, the multi-objective variable parameter optimization algorithm is applied to determine the final optimal machine parameters, and the multi-objective optimization algorithm for the tooth surface of spiral bevel gear is formed. Finally, the correctness and effectiveness of the algorithm are verified by numerical simulation and experiment. | ||
| 650 | 4 | |a Multi-objective variable parameter optimization |7 (dpeaa)DE-He213 | |
| 650 | 4 | |a Spiral bevel gear |7 (dpeaa)DE-He213 | |
| 650 | 4 | |a Error control of tooth surface |7 (dpeaa)DE-He213 | |
| 650 | 4 | |a Meshing efficiency |7 (dpeaa)DE-He213 | |
| 650 | 4 | |a Contact performance |7 (dpeaa)DE-He213 | |
| 700 | 1 | |a Wang, Sanmin |4 aut | |
| 700 | 1 | |a Chen, Peng |4 aut | |
| 700 | 1 | |a Li, Zhibin |4 aut | |
| 700 | 1 | |a Li, Linlin |4 aut | |
| 700 | 1 | |a Peng, Qi’an |4 aut | |
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10.1007/s12206-022-0631-7 doi (DE-627)SPR050851608 (SPR)s12206-022-0631-7-e DE-627 ger DE-627 rakwb eng Li, Fei verfasserin aut Multi-objective variable parameter optimization algorithm for spiral bevel gear tooth surface considering meshing efficiency and contact performance 2022 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Korean Society of Mechanical Engineers and Springer-Verlag GmbH Germany, part of Springer Nature 2022 Abstract A multi-objective variable parameter optimization method that considers meshing efficiency and contact performance simultaneously is proposed to optimize the tooth surface of spiral bevel gears to achieve higher contact performance and transmission efficiency. First, the tooth surface equations of the spiral bevel gear are established in line with the gear cutting process, and the deviation of tooth surface is analyzed and controlled. Second, the machine tool parameters with the greatest impact on the tooth surface are selected on the basis of the sensitivity analysis approach as the optimization design variables, and the relationship between the machine tool parameters, contact performance, and meshing efficiency is established. Third, the multi-objective variable parameter optimization algorithm is applied to determine the final optimal machine parameters, and the multi-objective optimization algorithm for the tooth surface of spiral bevel gear is formed. Finally, the correctness and effectiveness of the algorithm are verified by numerical simulation and experiment. Multi-objective variable parameter optimization (dpeaa)DE-He213 Spiral bevel gear (dpeaa)DE-He213 Error control of tooth surface (dpeaa)DE-He213 Meshing efficiency (dpeaa)DE-He213 Contact performance (dpeaa)DE-He213 Wang, Sanmin aut Chen, Peng aut Li, Zhibin aut Li, Linlin aut Peng, Qi’an aut Enthalten in Journal of mechanical science and technology Berlin : Springer, 2005 36(2022), 7 vom: Juli, Seite 3547-3559 (DE-627)58714016X (DE-600)2467571-4 1976-3824 nnns volume:36 year:2022 number:7 month:07 pages:3547-3559 https://dx.doi.org/10.1007/s12206-022-0631-7 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 36 2022 7 07 3547-3559 |
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10.1007/s12206-022-0631-7 doi (DE-627)SPR050851608 (SPR)s12206-022-0631-7-e DE-627 ger DE-627 rakwb eng Li, Fei verfasserin aut Multi-objective variable parameter optimization algorithm for spiral bevel gear tooth surface considering meshing efficiency and contact performance 2022 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Korean Society of Mechanical Engineers and Springer-Verlag GmbH Germany, part of Springer Nature 2022 Abstract A multi-objective variable parameter optimization method that considers meshing efficiency and contact performance simultaneously is proposed to optimize the tooth surface of spiral bevel gears to achieve higher contact performance and transmission efficiency. First, the tooth surface equations of the spiral bevel gear are established in line with the gear cutting process, and the deviation of tooth surface is analyzed and controlled. Second, the machine tool parameters with the greatest impact on the tooth surface are selected on the basis of the sensitivity analysis approach as the optimization design variables, and the relationship between the machine tool parameters, contact performance, and meshing efficiency is established. Third, the multi-objective variable parameter optimization algorithm is applied to determine the final optimal machine parameters, and the multi-objective optimization algorithm for the tooth surface of spiral bevel gear is formed. Finally, the correctness and effectiveness of the algorithm are verified by numerical simulation and experiment. Multi-objective variable parameter optimization (dpeaa)DE-He213 Spiral bevel gear (dpeaa)DE-He213 Error control of tooth surface (dpeaa)DE-He213 Meshing efficiency (dpeaa)DE-He213 Contact performance (dpeaa)DE-He213 Wang, Sanmin aut Chen, Peng aut Li, Zhibin aut Li, Linlin aut Peng, Qi’an aut Enthalten in Journal of mechanical science and technology Berlin : Springer, 2005 36(2022), 7 vom: Juli, Seite 3547-3559 (DE-627)58714016X (DE-600)2467571-4 1976-3824 nnns volume:36 year:2022 number:7 month:07 pages:3547-3559 https://dx.doi.org/10.1007/s12206-022-0631-7 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 36 2022 7 07 3547-3559 |
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10.1007/s12206-022-0631-7 doi (DE-627)SPR050851608 (SPR)s12206-022-0631-7-e DE-627 ger DE-627 rakwb eng Li, Fei verfasserin aut Multi-objective variable parameter optimization algorithm for spiral bevel gear tooth surface considering meshing efficiency and contact performance 2022 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Korean Society of Mechanical Engineers and Springer-Verlag GmbH Germany, part of Springer Nature 2022 Abstract A multi-objective variable parameter optimization method that considers meshing efficiency and contact performance simultaneously is proposed to optimize the tooth surface of spiral bevel gears to achieve higher contact performance and transmission efficiency. First, the tooth surface equations of the spiral bevel gear are established in line with the gear cutting process, and the deviation of tooth surface is analyzed and controlled. Second, the machine tool parameters with the greatest impact on the tooth surface are selected on the basis of the sensitivity analysis approach as the optimization design variables, and the relationship between the machine tool parameters, contact performance, and meshing efficiency is established. Third, the multi-objective variable parameter optimization algorithm is applied to determine the final optimal machine parameters, and the multi-objective optimization algorithm for the tooth surface of spiral bevel gear is formed. Finally, the correctness and effectiveness of the algorithm are verified by numerical simulation and experiment. Multi-objective variable parameter optimization (dpeaa)DE-He213 Spiral bevel gear (dpeaa)DE-He213 Error control of tooth surface (dpeaa)DE-He213 Meshing efficiency (dpeaa)DE-He213 Contact performance (dpeaa)DE-He213 Wang, Sanmin aut Chen, Peng aut Li, Zhibin aut Li, Linlin aut Peng, Qi’an aut Enthalten in Journal of mechanical science and technology Berlin : Springer, 2005 36(2022), 7 vom: Juli, Seite 3547-3559 (DE-627)58714016X (DE-600)2467571-4 1976-3824 nnns volume:36 year:2022 number:7 month:07 pages:3547-3559 https://dx.doi.org/10.1007/s12206-022-0631-7 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 36 2022 7 07 3547-3559 |
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10.1007/s12206-022-0631-7 doi (DE-627)SPR050851608 (SPR)s12206-022-0631-7-e DE-627 ger DE-627 rakwb eng Li, Fei verfasserin aut Multi-objective variable parameter optimization algorithm for spiral bevel gear tooth surface considering meshing efficiency and contact performance 2022 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Korean Society of Mechanical Engineers and Springer-Verlag GmbH Germany, part of Springer Nature 2022 Abstract A multi-objective variable parameter optimization method that considers meshing efficiency and contact performance simultaneously is proposed to optimize the tooth surface of spiral bevel gears to achieve higher contact performance and transmission efficiency. First, the tooth surface equations of the spiral bevel gear are established in line with the gear cutting process, and the deviation of tooth surface is analyzed and controlled. Second, the machine tool parameters with the greatest impact on the tooth surface are selected on the basis of the sensitivity analysis approach as the optimization design variables, and the relationship between the machine tool parameters, contact performance, and meshing efficiency is established. Third, the multi-objective variable parameter optimization algorithm is applied to determine the final optimal machine parameters, and the multi-objective optimization algorithm for the tooth surface of spiral bevel gear is formed. Finally, the correctness and effectiveness of the algorithm are verified by numerical simulation and experiment. Multi-objective variable parameter optimization (dpeaa)DE-He213 Spiral bevel gear (dpeaa)DE-He213 Error control of tooth surface (dpeaa)DE-He213 Meshing efficiency (dpeaa)DE-He213 Contact performance (dpeaa)DE-He213 Wang, Sanmin aut Chen, Peng aut Li, Zhibin aut Li, Linlin aut Peng, Qi’an aut Enthalten in Journal of mechanical science and technology Berlin : Springer, 2005 36(2022), 7 vom: Juli, Seite 3547-3559 (DE-627)58714016X (DE-600)2467571-4 1976-3824 nnns volume:36 year:2022 number:7 month:07 pages:3547-3559 https://dx.doi.org/10.1007/s12206-022-0631-7 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 36 2022 7 07 3547-3559 |
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10.1007/s12206-022-0631-7 doi (DE-627)SPR050851608 (SPR)s12206-022-0631-7-e DE-627 ger DE-627 rakwb eng Li, Fei verfasserin aut Multi-objective variable parameter optimization algorithm for spiral bevel gear tooth surface considering meshing efficiency and contact performance 2022 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © The Korean Society of Mechanical Engineers and Springer-Verlag GmbH Germany, part of Springer Nature 2022 Abstract A multi-objective variable parameter optimization method that considers meshing efficiency and contact performance simultaneously is proposed to optimize the tooth surface of spiral bevel gears to achieve higher contact performance and transmission efficiency. First, the tooth surface equations of the spiral bevel gear are established in line with the gear cutting process, and the deviation of tooth surface is analyzed and controlled. Second, the machine tool parameters with the greatest impact on the tooth surface are selected on the basis of the sensitivity analysis approach as the optimization design variables, and the relationship between the machine tool parameters, contact performance, and meshing efficiency is established. Third, the multi-objective variable parameter optimization algorithm is applied to determine the final optimal machine parameters, and the multi-objective optimization algorithm for the tooth surface of spiral bevel gear is formed. Finally, the correctness and effectiveness of the algorithm are verified by numerical simulation and experiment. Multi-objective variable parameter optimization (dpeaa)DE-He213 Spiral bevel gear (dpeaa)DE-He213 Error control of tooth surface (dpeaa)DE-He213 Meshing efficiency (dpeaa)DE-He213 Contact performance (dpeaa)DE-He213 Wang, Sanmin aut Chen, Peng aut Li, Zhibin aut Li, Linlin aut Peng, Qi’an aut Enthalten in Journal of mechanical science and technology Berlin : Springer, 2005 36(2022), 7 vom: Juli, Seite 3547-3559 (DE-627)58714016X (DE-600)2467571-4 1976-3824 nnns volume:36 year:2022 number:7 month:07 pages:3547-3559 https://dx.doi.org/10.1007/s12206-022-0631-7 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 AR 36 2022 7 07 3547-3559 |
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Li, Fei @@aut@@ Wang, Sanmin @@aut@@ Chen, Peng @@aut@@ Li, Zhibin @@aut@@ Li, Linlin @@aut@@ Peng, Qi’an @@aut@@ |
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| author |
Li, Fei |
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Li, Fei misc Multi-objective variable parameter optimization misc Spiral bevel gear misc Error control of tooth surface misc Meshing efficiency misc Contact performance Multi-objective variable parameter optimization algorithm for spiral bevel gear tooth surface considering meshing efficiency and contact performance |
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Multi-objective variable parameter optimization algorithm for spiral bevel gear tooth surface considering meshing efficiency and contact performance Multi-objective variable parameter optimization (dpeaa)DE-He213 Spiral bevel gear (dpeaa)DE-He213 Error control of tooth surface (dpeaa)DE-He213 Meshing efficiency (dpeaa)DE-He213 Contact performance (dpeaa)DE-He213 |
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misc Multi-objective variable parameter optimization misc Spiral bevel gear misc Error control of tooth surface misc Meshing efficiency misc Contact performance |
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misc Multi-objective variable parameter optimization misc Spiral bevel gear misc Error control of tooth surface misc Meshing efficiency misc Contact performance |
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Multi-objective variable parameter optimization algorithm for spiral bevel gear tooth surface considering meshing efficiency and contact performance |
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Li, Fei |
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Li, Fei Wang, Sanmin Chen, Peng Li, Zhibin Li, Linlin Peng, Qi’an |
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Li, Fei |
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multi-objective variable parameter optimization algorithm for spiral bevel gear tooth surface considering meshing efficiency and contact performance |
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Multi-objective variable parameter optimization algorithm for spiral bevel gear tooth surface considering meshing efficiency and contact performance |
| abstract |
Abstract A multi-objective variable parameter optimization method that considers meshing efficiency and contact performance simultaneously is proposed to optimize the tooth surface of spiral bevel gears to achieve higher contact performance and transmission efficiency. First, the tooth surface equations of the spiral bevel gear are established in line with the gear cutting process, and the deviation of tooth surface is analyzed and controlled. Second, the machine tool parameters with the greatest impact on the tooth surface are selected on the basis of the sensitivity analysis approach as the optimization design variables, and the relationship between the machine tool parameters, contact performance, and meshing efficiency is established. Third, the multi-objective variable parameter optimization algorithm is applied to determine the final optimal machine parameters, and the multi-objective optimization algorithm for the tooth surface of spiral bevel gear is formed. Finally, the correctness and effectiveness of the algorithm are verified by numerical simulation and experiment. © The Korean Society of Mechanical Engineers and Springer-Verlag GmbH Germany, part of Springer Nature 2022 |
| abstractGer |
Abstract A multi-objective variable parameter optimization method that considers meshing efficiency and contact performance simultaneously is proposed to optimize the tooth surface of spiral bevel gears to achieve higher contact performance and transmission efficiency. First, the tooth surface equations of the spiral bevel gear are established in line with the gear cutting process, and the deviation of tooth surface is analyzed and controlled. Second, the machine tool parameters with the greatest impact on the tooth surface are selected on the basis of the sensitivity analysis approach as the optimization design variables, and the relationship between the machine tool parameters, contact performance, and meshing efficiency is established. Third, the multi-objective variable parameter optimization algorithm is applied to determine the final optimal machine parameters, and the multi-objective optimization algorithm for the tooth surface of spiral bevel gear is formed. Finally, the correctness and effectiveness of the algorithm are verified by numerical simulation and experiment. © The Korean Society of Mechanical Engineers and Springer-Verlag GmbH Germany, part of Springer Nature 2022 |
| abstract_unstemmed |
Abstract A multi-objective variable parameter optimization method that considers meshing efficiency and contact performance simultaneously is proposed to optimize the tooth surface of spiral bevel gears to achieve higher contact performance and transmission efficiency. First, the tooth surface equations of the spiral bevel gear are established in line with the gear cutting process, and the deviation of tooth surface is analyzed and controlled. Second, the machine tool parameters with the greatest impact on the tooth surface are selected on the basis of the sensitivity analysis approach as the optimization design variables, and the relationship between the machine tool parameters, contact performance, and meshing efficiency is established. Third, the multi-objective variable parameter optimization algorithm is applied to determine the final optimal machine parameters, and the multi-objective optimization algorithm for the tooth surface of spiral bevel gear is formed. Finally, the correctness and effectiveness of the algorithm are verified by numerical simulation and experiment. © The Korean Society of Mechanical Engineers and Springer-Verlag GmbH Germany, part of Springer Nature 2022 |
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Multi-objective variable parameter optimization algorithm for spiral bevel gear tooth surface considering meshing efficiency and contact performance |
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https://dx.doi.org/10.1007/s12206-022-0631-7 |
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Wang, Sanmin Chen, Peng Li, Zhibin Li, Linlin Peng, Qi’an |
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Wang, Sanmin Chen, Peng Li, Zhibin Li, Linlin Peng, Qi’an |
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10.1007/s12206-022-0631-7 |
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2024-07-03T18:11:19.886Z |
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| score |
7.4013023 |