推进技术 ›› 2018, Vol. 39 ›› Issue (5): 1134-1141.

• 测试 试验 控制 • 上一篇    下一篇

基于SSD-HT时频阶比跟踪的变转速转子故障诊断

唐贵基,庞 彬,何玉灵   

  1. 华北电力大学 能源动力与机械工程学院,河北 保定 071003,华北电力大学 能源动力与机械工程学院,河北 保定 071003,华北电力大学 能源动力与机械工程学院,河北 保定 071003
  • 发布日期:2021-08-15
  • 作者简介:唐贵基,男,博士,教授,研究领域为动力机械状态监测及故障诊断、信号处理。
  • 基金资助:
    国家自然科学基金(51307058);河北省自然科学基金(E2014502052);中央高校基本科研业务费专项资金

Time-Frequency Order Tracking for Rotor Fault Diagnosis under Variable Speed Conditions Based on SSD-HT

  1. School of Energy,Power and Mechanical Engineering,North China Electric Power University,Baoding 071003,China,School of Energy,Power and Mechanical Engineering,North China Electric Power University,Baoding 071003,China and School of Energy,Power and Mechanical Engineering,North China Electric Power University,Baoding 071003,China
  • Published:2021-08-15

摘要: 为解决变转速工况下转子故障特征难以提取的问题,提出一种基于SSD-HT时频阶比跟踪的转子故障诊断方法。应用一种新的信号分解方法—奇异谱分解对转子故障振动信号进行分解,得到包含故障特征信息的奇异谱分量。运用希尔伯特变换计算各个有效奇异谱分量的瞬时频率,获取故障信号的时频分布。根据时频分布中的转频信息对原始振动信号进行阶比跟踪分析,提取直观的阶次特征。仿真分析与实验分析结果表明,在无转速测量装置条件下,所述方法可准确判别变转速工况的转子故障模式,相对于传统分析方法表现出一定的先进性。

关键词: 奇异谱分解;希尔伯特变换;阶比跟踪;变转速;转子;故障诊断

Abstract: In order to solve the problem that fault features of rotors under variable speed conditions are hard to extract, a time-frequency order tracking fault diagnosis method for rotors based on SSD-HT was proposed. First, a novel signal decomposition method, singular spectrum decomposition method was used to decompose the rotor fault vibration signal into singular spectrum components that contained the fault feature information. Then, Hilbert transform was applied to calculate the instantaneous frequency of every effective singular spectrum component to get the time-frequency distribution of the fault signal. Finally, the original vibration signal was subjected to order tracking according to the shaft frequency information to extract the intuitive order characteristics. The simulated analysis and experimental analysis results show that the proposed method can judge the rotor fault modes of variable speed conditions without using speed measurements and shows advanced natures to the traditional analysis methods.

Key words: Singular spectrum decomposition;Hilbert transform;Order tracking;Variable speed conditions;Rotor;Fault diagnosis