自适应同步压缩小波变换的风电机组传动链故障诊断方法研究

Study on Fault Diagnosis Method of Wind Turbine Transmission Chain Based on Adaptive SWT

风力发电机组长期处于非稳态、变工况的工作条件下,振动信号时频故障特征的有效提取对其故障诊断具有重要意义。传统时频分析方法在分析过程中容易出现模态混叠现象,从而引起分析误差。针对振动信号,基于瑞利熵获取最优时频参数,提出了自适应同步压缩小波变换的故障诊断方法,提高了时频聚集性和时频能量集中程度;利用最优时频参数计算出瞬时频率,对振动信号进行阶比分析;通过对仿真信号与风电场传动链实测振动信号的分析对比,验证了所提方法的可行性和有效性。

Due to the long-term unsteady and variable working conditions of wind turbine generator system,the effective extraction of time-frequency fault characteristics of vibration signals is of great significance to the fault diagnosis.The traditional time-frequency analysis method is prone to modal aliasing during the analysis,resulting in analysis errors.For the vibration signals,the optimal time-frequency parameters are obtained based on Rayleigh entropy,and a fault diagnosis method of adaptive Synchrosqueezing Wavelet Transform is proposed,which improves the time-frequency aggregation and time-frequency energy concentration.Then the instantaneous frequency is calculated with the optimal time-frequency parameters,and the order analysis of vibration signals is carried out.Finally,the feasibility and effectiveness of the proposed method are verified by analyzing and contrasting the simulation signal with the measured vibration signals of the wind farm transmission chain.