Vibration and control optimization of pressure reducer based on genetic algorithm
A research challenge of vibration and control optimization of pressurized reducer is solved in this article; a method based on genetic algorithm (GA) is proposed to optimize the vibration and control of reducer. Considering the bending strength of helical gear root and tooth surface contact fatigue...
| Main Authors: | , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
De Gruyter
2023-04-01
|
| Series: | Paladyn |
| Subjects: | |
| Online Access: | https://doi.org/10.1515/pjbr-2022-0091 |
| _version_ | 1797422367774867456 |
|---|---|
| author | HuangFu Ruiyun Zhao Yongyan |
| author_facet | HuangFu Ruiyun Zhao Yongyan |
| author_sort | HuangFu Ruiyun |
| collection | DOAJ |
| description | A research challenge of vibration and control optimization of pressurized reducer is solved in this article; a method based on genetic algorithm (GA) is proposed to optimize the vibration and control of reducer. Considering the bending strength of helical gear root and tooth surface contact fatigue strength as constraints, the improved GA is used to solve it, and the optimal parameter combination is obtained. The size of center distance is reduced by 9.59% compared with that before. Based on the optimized results, the vibration becomes weaker with the increase of the load at the output end of the reducer, and its maximum value is only 1/8 of that when the load is 550 N. The experimental results show the optimized surface load distribution of driving gear teeth. The maximum normal load per unit length of the optimized output stage driving gear surface is 521.321 N/mm, which is significantly lower than the 662.455 N/mm before optimization. At the same time, the tooth surface load is evenly distributed. The larger tooth surface load is mainly distributed in the middle of the tooth surface with strong bearing capacity, which effectively solves the problem of unbalanced load before optimization and improves the bearing capacity of gear transmission. It is proved that GA can effectively realize the vibration and control optimization of pressurized reducer. |
| first_indexed | 2024-03-09T07:32:16Z |
| format | Article |
| id | doaj.art-7018e270d2db48b2be2cbcc952cce729 |
| institution | Directory Open Access Journal |
| issn | 2081-4836 |
| language | English |
| last_indexed | 2024-03-09T07:32:16Z |
| publishDate | 2023-04-01 |
| publisher | De Gruyter |
| record_format | Article |
| series | Paladyn |
| spelling | doaj.art-7018e270d2db48b2be2cbcc952cce7292023-12-03T06:08:13ZengDe GruyterPaladyn2081-48362023-04-01141p. 168781401983510453110.1515/pjbr-2022-0091Vibration and control optimization of pressure reducer based on genetic algorithmHuangFu Ruiyun0Zhao Yongyan1Xinxiang Vocational and Technical College, Xinxiang, Henan, 453006, ChinaXinxiang Vocational and Technical College, Xinxiang, Henan, 453006, ChinaA research challenge of vibration and control optimization of pressurized reducer is solved in this article; a method based on genetic algorithm (GA) is proposed to optimize the vibration and control of reducer. Considering the bending strength of helical gear root and tooth surface contact fatigue strength as constraints, the improved GA is used to solve it, and the optimal parameter combination is obtained. The size of center distance is reduced by 9.59% compared with that before. Based on the optimized results, the vibration becomes weaker with the increase of the load at the output end of the reducer, and its maximum value is only 1/8 of that when the load is 550 N. The experimental results show the optimized surface load distribution of driving gear teeth. The maximum normal load per unit length of the optimized output stage driving gear surface is 521.321 N/mm, which is significantly lower than the 662.455 N/mm before optimization. At the same time, the tooth surface load is evenly distributed. The larger tooth surface load is mainly distributed in the middle of the tooth surface with strong bearing capacity, which effectively solves the problem of unbalanced load before optimization and improves the bearing capacity of gear transmission. It is proved that GA can effectively realize the vibration and control optimization of pressurized reducer.https://doi.org/10.1515/pjbr-2022-0091genetic algorithmretarderlqr control algorithmoptimizationadams |
| spellingShingle | HuangFu Ruiyun Zhao Yongyan Vibration and control optimization of pressure reducer based on genetic algorithm Paladyn genetic algorithm retarder lqr control algorithm optimization adams |
| title | Vibration and control optimization of pressure reducer based on genetic algorithm |
| title_full | Vibration and control optimization of pressure reducer based on genetic algorithm |
| title_fullStr | Vibration and control optimization of pressure reducer based on genetic algorithm |
| title_full_unstemmed | Vibration and control optimization of pressure reducer based on genetic algorithm |
| title_short | Vibration and control optimization of pressure reducer based on genetic algorithm |
| title_sort | vibration and control optimization of pressure reducer based on genetic algorithm |
| topic | genetic algorithm retarder lqr control algorithm optimization adams |
| url | https://doi.org/10.1515/pjbr-2022-0091 |
| work_keys_str_mv | AT huangfuruiyun vibrationandcontroloptimizationofpressurereducerbasedongeneticalgorithm AT zhaoyongyan vibrationandcontroloptimizationofpressurereducerbasedongeneticalgorithm |