基于倒频谱技术的滚动轴承故障诊断应用研究  

Application Research on Fault Diagnosis of Rolling Bearings Based on Cepstrum Technology

作　　者：唐卫辉 TANG Wei-hui(Longyuan(Beijing)New Energy Engineering Technology Co.,Ltd.,Beijing 100034,China;National Research and Development Center for Energy and Wind Power Technology,Xi'an 710117,China)

机构地区：[1]龙源(北京)新能源工程技术有限公司,北京100034 [2]国家能源风电运营技术研发(实验)中心,西安710117

出　　处：《价值工程》2024年第23期108-111,共4页Value Engineering

摘　　要：滚动轴承广泛应用在风电装备领域,当滚动轴承出现故障时,实际采集的振动信号是复杂的非平稳信号,传统的傅里叶变换在提取谐波、边频带等周期成分时显的力不从心,不能有效检测微弱的周期激励信号。本文提出一种倒频谱分析技术,能对周期性异常振动信号进行分离,通过对轴承内圈损伤的诊断,结果表明,倒频谱分析技术能对风电装备滚动轴承的复杂的振动信号进行诊断并准确定位,在检测故障信号周期成分方面有显著优势。Rolling bearings are widely used in the field of wind power equipment.When the rolling bearings fail,the actual collected vibration signals are complex non-stationary signals.Traditional Fourier transform shows insufficient force in extracting harmonic,sideband and other periodic components,and cannot effectively detect weak periodic excitation signals.This paper proposes a cepstral analysis technique that can separate periodic abnormal vibration signals.Through the diagnosis of bearing inner ring damage,the results show that cepstral analysis technique can diagnose and accurately locate complex vibration signals of rolling bearings in wind power equipment,and has significant advantages in detecting the periodic components of fault signals.

关 键 词：倒频谱 功率谱 滚动轴承 故障诊断 

分 类 号：TH113[机械工程—机械设计及理论]