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基于边频相对能量和的柱塞泵磨损状态识别

何兆民 王少萍

何兆民, 王少萍. 基于边频相对能量和的柱塞泵磨损状态识别[J]. 北京航空航天大学学报, 2014, 40(2): 183-187.
引用本文: 何兆民, 王少萍. 基于边频相对能量和的柱塞泵磨损状态识别[J]. 北京航空航天大学学报, 2014, 40(2): 183-187.
He Zhaomin, Wang Shaoping. Wear status recognition of piston pump based on side frequency relative energy summation[J]. Journal of Beijing University of Aeronautics and Astronautics, 2014, 40(2): 183-187. (in Chinese)
Citation: He Zhaomin, Wang Shaoping. Wear status recognition of piston pump based on side frequency relative energy summation[J]. Journal of Beijing University of Aeronautics and Astronautics, 2014, 40(2): 183-187. (in Chinese)

基于边频相对能量和的柱塞泵磨损状态识别

基金项目: 国家重点基础研究发展计划资助项目(2014CB046402);国家自然科学基金资助项目(51175014);111计划资助项目;国防基金资助项目(9140A17050113HK01233)
详细信息
  • 中图分类号: TH322

Wear status recognition of piston pump based on side frequency relative energy summation

  • 摘要: 摩擦磨损是飞机柱塞泵典型的渐进性故障,因磨损量难以直接测量,通常采用振动信号进行间接测量.磨损引起的振动信号故障特征微弱,对磨损状态进行准确地识别比较困难.针对上述问题,提出了基于谐波分量边频相对能量和的磨损状态识别方法,该方法对壳体振动信号进行Hilbert包络解调消除高频周期干扰,得到清晰的谐波分量,在各谐波分量的特定边频区间内计算最大能量与平均能量的比值并求和,将该值作为新的特征量来表征柱塞泵的不同磨损状态,利用网格法对边频区间范围寻优.结果表明,边频相对能量和相比传统的特征频率能量对磨损状态的区分度更高,适于磨损状态识别.

     

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出版历程
  • 收稿日期:  2013-10-15
  • 网络出版日期:  2014-02-20

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