Research on Multistage Rotor Assembly Optimization Methods for Aeroengine Based on the Genetic Algorithm
The coaxiality and unbalance are the two important indexes to evaluate the assembly quality of an aeroengine. It often needs to be tested and disassembled repeatedly to meet the double-objective requirements at the same time. Therefore, an intelligent assembly method is urgently needed to directly p...
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| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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Wiley
2021-01-01
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| Series: | Complexity |
| Online Access: | http://dx.doi.org/10.1155/2021/8847690 |
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| _version_ | 1832559963558379520 |
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| author | Yue Chen Jiwen Cui Xun Sun Shihai Cui |
| author_facet | Yue Chen Jiwen Cui Xun Sun Shihai Cui |
| author_sort | Yue Chen |
| collection | DOAJ |
| description | The coaxiality and unbalance are the two important indexes to evaluate the assembly quality of an aeroengine. It often needs to be tested and disassembled repeatedly to meet the double-objective requirements at the same time. Therefore, an intelligent assembly method is urgently needed to directly predict the optimal assembly orientations of the rotors at each stage to meet the double-objective requirements simultaneously. In this study, an assembly optimization method for the multistage rotor of an aeroengine is proposed based on the genetic algorithm. Firstly, a spatial location propagation model is developed to accurately predict the spatial position of each rotor after assembly. The alignment process of the assembly screw holes of the adjacent rotors is considered for the first time. Secondly, a new assembly optimization strategy is proposed to select different assembly data for the specific values of the coaxiality and unbalance, respectively. Finally, a double-objective fitness function is constructed based on the coaxiality and unbalance. The simulation and experimental results show that the assembly optimization method proposed in this study can be utilized to achieve synchronous optimization of the coaxiality and unbalance of an aeroengine during preassembly. |
| format | Article |
| id | doaj-art-49d1621416754aee969d3b46f667fc47 |
| institution | Kabale University |
| issn | 1076-2787 1099-0526 |
| language | English |
| publishDate | 2021-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Complexity |
| spelling | doaj-art-49d1621416754aee969d3b46f667fc472025-02-03T01:28:44ZengWileyComplexity1076-27871099-05262021-01-01202110.1155/2021/88476908847690Research on Multistage Rotor Assembly Optimization Methods for Aeroengine Based on the Genetic AlgorithmYue Chen0Jiwen Cui1Xun Sun2Shihai Cui3Centre of Ultra-precision Optoelectronic Instrument Engineering, Harbin Institute of Technology, Harbin 150080, ChinaCentre of Ultra-precision Optoelectronic Instrument Engineering, Harbin Institute of Technology, Harbin 150080, ChinaCentre of Ultra-precision Optoelectronic Instrument Engineering, Harbin Institute of Technology, Harbin 150080, ChinaCollege of Mechanical Engineering, Tianjin University of Science & Technology, Tianjin 300222, ChinaThe coaxiality and unbalance are the two important indexes to evaluate the assembly quality of an aeroengine. It often needs to be tested and disassembled repeatedly to meet the double-objective requirements at the same time. Therefore, an intelligent assembly method is urgently needed to directly predict the optimal assembly orientations of the rotors at each stage to meet the double-objective requirements simultaneously. In this study, an assembly optimization method for the multistage rotor of an aeroengine is proposed based on the genetic algorithm. Firstly, a spatial location propagation model is developed to accurately predict the spatial position of each rotor after assembly. The alignment process of the assembly screw holes of the adjacent rotors is considered for the first time. Secondly, a new assembly optimization strategy is proposed to select different assembly data for the specific values of the coaxiality and unbalance, respectively. Finally, a double-objective fitness function is constructed based on the coaxiality and unbalance. The simulation and experimental results show that the assembly optimization method proposed in this study can be utilized to achieve synchronous optimization of the coaxiality and unbalance of an aeroengine during preassembly.http://dx.doi.org/10.1155/2021/8847690 |
| spellingShingle | Yue Chen Jiwen Cui Xun Sun Shihai Cui Research on Multistage Rotor Assembly Optimization Methods for Aeroengine Based on the Genetic Algorithm Complexity |
| title | Research on Multistage Rotor Assembly Optimization Methods for Aeroengine Based on the Genetic Algorithm |
| title_full | Research on Multistage Rotor Assembly Optimization Methods for Aeroengine Based on the Genetic Algorithm |
| title_fullStr | Research on Multistage Rotor Assembly Optimization Methods for Aeroengine Based on the Genetic Algorithm |
| title_full_unstemmed | Research on Multistage Rotor Assembly Optimization Methods for Aeroengine Based on the Genetic Algorithm |
| title_short | Research on Multistage Rotor Assembly Optimization Methods for Aeroengine Based on the Genetic Algorithm |
| title_sort | research on multistage rotor assembly optimization methods for aeroengine based on the genetic algorithm |
| url | http://dx.doi.org/10.1155/2021/8847690 |
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