基于谐波消除和谱峭度的风电机组主轴承故障诊断  

FAULT DIAGNOSIS OF WIND TURBINE MAIN BEARINGS BASED ON HARMONIC REMOVAL AND SPECTRAL KURTOSIS

作　　者：陈强 钱洵 Chen Qiang;Qian Xun(Guodian United Power Technology Co.,Ltd.,Beijing 100039,China)

机构地区：[1]国电联合动力技术有限公司,北京100039

出　　处：《太阳能学报》2025年第1期1-8,共8页Acta Energiae Solaris Sinica

摘　　要：针对风电机组状态监测中主轴轴承故障特征受到其他传动部件振动谐波干扰且原始振动信号非平稳难以准确提取故障冲击特征频率的问题,提出一种基于谐波干扰消除和谱峭度相结合的分析方法(HR-Fast-Kurtogram)。利用离线角域重采样将非平稳时域信号转换成平稳的角度-阶次信号,在阶次域通过梳状陷波器其去除齿箱啮合成分等干扰阶次,应用基于短时傅里叶变换(STFT)的快速谱峭度图提取峭度峰值所在故障子频带从而提取轴承故障特征。既可避免非周期性冲击的干扰,亦可区分冲击性较小的非轴承幅值调制成分和轴承故障冲击成分。在实际机组轴承故障数据应用中的对比分析结果表明:新方法可提高在秒级短时间尺度提取轴承故障特征和识别故障类型的准确性。Aiming at the problems that the fault features of the main bearings are interfered by the harmonics of other transmission components in wind turbines’condition monitoring and the raw vibration signal is non-stationary,making it difficult to accurately extract the characteristic frequency of fault impacts,a combined method of harmonic removal and spectral kurtosis analysis(HR-Fast-Kurtogram)is proposed.Offline angle domain resampling is used to convert non-stationary time domain signals into stationary angle-order signals.Comb notch filters are introduced in the order domain to remove gear meshing frequencies,and Fast-Kurtogram based on short-time Fourier transfer(STFT)is applied to extract the fault sub-bands where the kurtosis peak is located in order to extract bearing fault features.The combined method is able to avoid the interference of non-periodic impacts and distinguish between non-bearing amplitude modulation components with lower impact and bearing fault impact components.The comparative analysis results in the application of real main bearing fault data shows that the proposed method can improve the accuracy of fault features extraction and fault type identification in a short time scale of seconds.

关 键 词：风电机组 轴承 状态监测 陷波器 谱峭度 

分 类 号：TH165.3[机械工程—机械制造及自动化]