发电机传动轴承的异常振动谱特征提取算法
CSTR:
作者:
作者单位:

广州华立科技职业学院广州511325

中图分类号:

TH134TN98


Abnormal vibration spectrum feature extraction algorithm for generator drive bearing
Author:
Affiliation:

Guangzhou Huali Science and Technology Vocational College, Guangzhou 511325, China

  • 摘要
  • | |
  • 访问统计
  • |
  • 参考文献 [13]
  • |
  • 相似文献 [20]
  • | | |
  • 文章评论
    摘要:

    对发电机传动轴承的异常振动特征的准确提取是实现机械运行状态检测和发电机动轴承疲劳损伤预测的基础。当前对发电机传动轴承的异常振动的特征提取采用功率谱密度特征提取方法,由于功率谱密度特征具有非高斯性,对交变温度下发电机传动轴承异常振动的跟随性能不好。提出一种基于Hilbert变换的发电机传动轴承的异常振动谱特征提取算法。建立一个多参量的发电机传动轴承动力学模型,进行轴承的振动分析模型构建,采用经验模态分解和Hilbert谱提取方法把发电机异常振动进行多分量分解,提取发电机传动轴承的异常振动的Hilbert谱特征,计算接触轴承所产生的轴承力的响应幅值和时间滞后值,实现对振动特征的横向、扭转的定位和检测。以此为基础优化传动系统的结构和动力学参数,进行齿轮的啮合异常修正。仿真结果表明,该方法稳定可靠、性能优越,提高了发电机传动轴承的状态监测和损伤预测能力。

    Abstract:

    The accurate extraction of the abnormal vibration characteristics of generator drive bearing is the basis of realizing the mechanical running state detection and prediction of the fatigue damage of motor bearing. At present, the feature extraction method of the abnormal vibration of generator drive bearing is obtained by using the method of power spectrum density feature extraction. Because of the characteristic of power spectral density, the following performance is not good for the abnormal vibration of generator bearing transmission bearing under the alternating temperature. An abnormal vibration spectrum feature extraction algorithm based on Hilbert transform for generator bearing is proposed. The dynamic model of a multi parameter generator is established, and the vibration analysis model of bearing is built.The abnormal vibration of generator is decomposed by empirical mode decomposition and Hilbert spectrum. The Hilbert spectrum of the abnormal vibration of generator is extracted. Based on the structure and dynamic parameters of the drive system, the gear mesh modification is carried out. Simulation results show that the method is stable, reliable, and performance is superior, and the state monitoring and damage prediction ability of generator is improved.

    参考文献
    [1]闫清东,穆洪斌,魏巍,等. 双循环圆液力缓速器叶形参数优化设计[J]. 兵工学报, 2015, 36(3): 385-390.
    [2]李鹏,马建军,李文强,等.一类不确定非线性系统的改进积分型滑模控制[J].控制与决策,2009, 24(10):1463-1472.
    [3]STAN C, CRISTESCU C P, DIMITRIU D G. Analysis of the intermittent behavior in a low-temperature discharge plasma by recurrence plot quantification[J]. Physics of Plasmas, 2010, 17(4): 1-6.
    [4]陈捷,陈克安,孙进才.基于多重分形的舰船噪声特征提取[J].西北工业大学学报,2000,18(2): 241- 244.
    [5]冯松, 毛军红, 谢友柏. 齿面磨损对齿轮啮合刚度影响的计算与分析[J]. 机械工程学报, 2015, 51(15): 27-32.
    [6]王庆,张以都. 二级圆柱斜齿轮系统耦合动态响应分析[J]. 振动与冲击,2012,31(10):87-91.
    [7]AN S L, JIN W H. Prediction of maximum unbalance responses of a gear-coupled two-shaft rotor-bearing system[J]. Journal of Sound and Vibration, 2005, 283(3-5): 507-523.
    [8]任朝晖,谢吉祥,周世华,等. 斜齿轮-转子-轴承弯扭轴耦合振动特性分析[J]. 机械工程学报, 2015, 51(15): 75-89.
    [9]郜浩冬, 张以都. 含摩擦的汇流传动齿轮非线性动力学分析[J]. 振动、测试与诊断,2014, 34(4): 737-743.
    [10]郭静波, 谭博,蔡雄. 基于反相双峰指数模型的微弱瞬态极低频信号的估计与检测[J]. 仪器仪表学报,2015,36(8):1682-1691.
    [11]张冀,徐科军. 自动生成转速参考曲线的电动执行器定位方法[J]. 电子测量与仪器学报 , 2014,28(11):1222-1234.
    [12]黄朝,许鑫,刘敦歌,等. 基于多传感器的微弱磁异常信号提取方法研究[J].电子测量技术,2015,38(10):91-95.
    [13]郭太平,裘进浩,程军,等. 高频电磁涡流检测系统及实验研究[J].国外电子测量技术,2015, 34 (11):4-9.
    引证文献
    网友评论
    网友评论
    分享到微博
    发 布
引用本文

陈运胜.发电机传动轴承的异常振动谱特征提取算法[J].国外电子测量技术,2016,35(5):20-23

复制
分享
文章指标
  • 点击次数:1081
  • 下载次数: 1670
  • HTML阅读次数: 0
  • 引用次数: 0
历史
  • 在线发布日期: 2016-06-08
文章二维码
×
《国外电子测量技术》
2025年投稿方式有变