| 基于能量增强的双斜式轴向柱塞泵滑靴磨损故障诊断方法 |
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| 引用本文： | 乔世昌,许顺海,王少萍,石健,李振坤,刘小平,王伟杰,白林迎.基于能量增强的双斜式轴向柱塞泵滑靴磨损故障诊断方法[J].液压与气动,2023,0(2):62-71. |
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| 作者姓名： | 乔世昌 许顺海 王少萍 石健 李振坤 刘小平 王伟杰 白林迎 |
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| 作者单位： | 1.北京航空航天大学自动化科学与电气工程学院, 北京 100191;2.中铁工程装备集团有限公司, 河南郑州 450016 |
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| 基金项目： | 国家自然科学基金面上项目(51875014) |
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| 摘 要： | 针对盾构机等大型设备用双斜式轴向柱塞泵故障诊断中滑靴磨损故障特征信号易被湮没的问题，提出了一种基于能量增强的双斜式轴向柱塞泵滑靴磨损故障诊断方法。首先，考虑到双斜式柱塞泵滑靴磨损会造成轴向、径向两个方向的振动，对发生滑靴磨损故障下的泵的力学特性进行分析，确定了敏感频率范围；其次，考虑到故障信号易被湮没，将轴向和径向的振动信号分别进行小波包分解，进而得到轴向和径向的振动信号的能量谱，并将轴向与径向敏感频率范围内的能量谱进行叠加，增强故障特征；最后基于试验数据进行验证，对比正常状态与滑靴故障状态下的能量谱，可以有效提高故障诊断的准确度。
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| 关 键 词： | 双斜式柱塞泵 滑靴磨损 能量增强 小波包分解 |
| 收稿时间： | 2022-02-21 |
Diagnosis Method of Slipper Wear Fault of Double-oblique-type Axial Piston Pump Based on Energy Enhancement |
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| QIAO Shi-chang,XU Shun-hai,WANG Shao-ping,SHI Jian,LI Zhen-kun,LIU Xiao-ping,WANG Wei-jie,BAI Lin-ying.Diagnosis Method of Slipper Wear Fault of Double-oblique-type Axial Piston Pump Based on Energy Enhancement[J].Chinese Hydraulics & Pneumatics,2023,0(2):62-71. |
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| Authors: | QIAO Shi-chang XU Shun-hai WANG Shao-ping SHI Jian LI Zhen-kun LIU Xiao-ping WANG Wei-jie BAI Lin-ying |
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| Affiliation: | 1. School of Automation Science and Electrical Engineering, Beihang University, Beijing 100191;2. China Railway Engineering Equipment Group Co., Ltd., Zhengzhou, Henan 450016 |
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| Abstract: | Aiming at the problem that the characteristic signal of sliding shoe wear fault is easily annihilated in the fault diagnosis of double inclined axial piston pump used in large equipment such as shield machine, this paper proposes a sliding shoe of double inclined axial piston pump based on energy enhancement. Wear fault diagnosis method. First, considering that the wear of the sliding shoes of the double inclined plunger pump will cause vibration in both axial and radial directions, the mechanical characteristics of the pump under the fault of sliding shoe wear are analyzed, and the sensitive frequency range is determined. Secondly, considering that the fault signal is easy to be annihilated, the axial and radial vibration signals are decomposed by wavelet packets respectively, and then the energy spectrum of the axial and radial vibration signals is obtained, and the axial and radial sensitive frequency ranges are calculated. The energy spectrum is superimposed to enhance the fault characteristics. Finally, based on the test data, it is verified that comparing the energy spectrum between the normal state and the slipper fault state can effectively improve the accuracy of fault diagnosis. |
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| Keywords: | double-oblique-type axial piston pump sliding shoe wear energy enhancement wavelet packet decomposition |
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