Simulation of Flow-Induced Vibration and Dynamic Performance of Circular-Arc Helical Gear Pump under Background of Machine Learning
At present, with the continuous development and great improvement of mechanical manufacturing, processing, and assembly technology, mechanical flow-induced vibration (FIV) with a relatively concentrated frequency domain can be controlled by active and passive noise reduction methods. However, whethe...
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Wiley
2022-01-01
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| Series: | International Transactions on Electrical Energy Systems |
| Online Access: | http://dx.doi.org/10.1155/2022/9513357 |
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| author | Xiaoling Wei Yongbao Feng Xiaoxia Han Zhenxin He |
| author_facet | Xiaoling Wei Yongbao Feng Xiaoxia Han Zhenxin He |
| author_sort | Xiaoling Wei |
| collection | DOAJ |
| description | At present, with the continuous development and great improvement of mechanical manufacturing, processing, and assembly technology, mechanical flow-induced vibration (FIV) with a relatively concentrated frequency domain can be controlled by active and passive noise reduction methods. However, whether it is active noise reduction or passive noise reduction, they all focus on how to suppress the transmission of sound waves and cannot solve the problems of flow leakage, obvious temperature rise, and noise excitation from the root cause. Therefore, it is necessary to determine the location of the primary and secondary excitation sound sources of FIV, the identification of true and false sounds, and the characteristic relationship between flow and noise. This provides a theoretical basis and engineering application direction for the mechanism of noise reduction of FIV. The numerical calculation part of the acoustics in this paper is solved by the hybrid method, and the flow field is discretely calculated by the large eddy simulation (LES) module in the Fluent software. When the calculated flow field is stable, the velocity field of one impeller rotation period is selected to be output as the iterative value of the sound field and imported into ACTRAN for Fourier transform. Then, the sound field calculation is carried out, and the result of the spatial and temporal variation of the sound field is finally obtained. Through experiments, it was found that when the load of the gear pump is 8 MPa, the volumetric efficiency of the optimized circular-arc helical gear pump of the sliding bearing was improved by about 4%. When the rotation speed is 2100°r/min, the arc helical gear pump reduced the surface temperature rise by 2.5°C. This verified that the optimized performance of the sliding bearing in the arc helical gear pump is significantly improved. Through the theoretical model of the temperature rise of the sliding bearing, the phenomenon that the surface temperature of the prototype gear pump was not significantly increased with the loading in the low pressure region is explained. |
| format | Article |
| id | doaj-art-00323cb3157a4999aa8125bf32bfcf86 |
| institution | Kabale University |
| issn | 2050-7038 |
| language | English |
| publishDate | 2022-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | International Transactions on Electrical Energy Systems |
| spelling | doaj-art-00323cb3157a4999aa8125bf32bfcf862025-02-03T06:13:35ZengWileyInternational Transactions on Electrical Energy Systems2050-70382022-01-01202210.1155/2022/9513357Simulation of Flow-Induced Vibration and Dynamic Performance of Circular-Arc Helical Gear Pump under Background of Machine LearningXiaoling Wei0Yongbao Feng1Xiaoxia Han2Zhenxin He3Department of Missile EngineeringDepartment of Missile EngineeringDepartment of Missile EngineeringDepartment of Missile EngineeringAt present, with the continuous development and great improvement of mechanical manufacturing, processing, and assembly technology, mechanical flow-induced vibration (FIV) with a relatively concentrated frequency domain can be controlled by active and passive noise reduction methods. However, whether it is active noise reduction or passive noise reduction, they all focus on how to suppress the transmission of sound waves and cannot solve the problems of flow leakage, obvious temperature rise, and noise excitation from the root cause. Therefore, it is necessary to determine the location of the primary and secondary excitation sound sources of FIV, the identification of true and false sounds, and the characteristic relationship between flow and noise. This provides a theoretical basis and engineering application direction for the mechanism of noise reduction of FIV. The numerical calculation part of the acoustics in this paper is solved by the hybrid method, and the flow field is discretely calculated by the large eddy simulation (LES) module in the Fluent software. When the calculated flow field is stable, the velocity field of one impeller rotation period is selected to be output as the iterative value of the sound field and imported into ACTRAN for Fourier transform. Then, the sound field calculation is carried out, and the result of the spatial and temporal variation of the sound field is finally obtained. Through experiments, it was found that when the load of the gear pump is 8 MPa, the volumetric efficiency of the optimized circular-arc helical gear pump of the sliding bearing was improved by about 4%. When the rotation speed is 2100°r/min, the arc helical gear pump reduced the surface temperature rise by 2.5°C. This verified that the optimized performance of the sliding bearing in the arc helical gear pump is significantly improved. Through the theoretical model of the temperature rise of the sliding bearing, the phenomenon that the surface temperature of the prototype gear pump was not significantly increased with the loading in the low pressure region is explained.http://dx.doi.org/10.1155/2022/9513357 |
| spellingShingle | Xiaoling Wei Yongbao Feng Xiaoxia Han Zhenxin He Simulation of Flow-Induced Vibration and Dynamic Performance of Circular-Arc Helical Gear Pump under Background of Machine Learning International Transactions on Electrical Energy Systems |
| title | Simulation of Flow-Induced Vibration and Dynamic Performance of Circular-Arc Helical Gear Pump under Background of Machine Learning |
| title_full | Simulation of Flow-Induced Vibration and Dynamic Performance of Circular-Arc Helical Gear Pump under Background of Machine Learning |
| title_fullStr | Simulation of Flow-Induced Vibration and Dynamic Performance of Circular-Arc Helical Gear Pump under Background of Machine Learning |
| title_full_unstemmed | Simulation of Flow-Induced Vibration and Dynamic Performance of Circular-Arc Helical Gear Pump under Background of Machine Learning |
| title_short | Simulation of Flow-Induced Vibration and Dynamic Performance of Circular-Arc Helical Gear Pump under Background of Machine Learning |
| title_sort | simulation of flow induced vibration and dynamic performance of circular arc helical gear pump under background of machine learning |
| url | http://dx.doi.org/10.1155/2022/9513357 |
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