一种具有自适应特性的风电机组齿轮箱振动信号预处理算法的研究

摘要

采用自适应窄带干扰消除和改进软阈值去噪算法,实现对风电机组振动信号的滤波处理,凸显表征故障特征的源振动信号.风电机组的振动信号由设备正常运转产生的周期性信号、故障源振动信号及噪声信号相互混合而产生.自适应窄带干扰消除算法可合理消除振动信号中的周期性成分,改进软阈值去噪技术可有效剔除背景噪声,结合两种技术特点提出一种具有自适应特性的信号预处理算法,凸显表征故障源振动特性的信号模型.试验结果表明:添加自适应特性能有效提高信号预处理算法的鲁棒性和泛化能力.%Adaptive narrowband interference elimination technology and improved soft threshold denoising algorithm were used to process vibration signal of wind turbine,highlighting its fault characteristics.The vibration signal of wind turbines was mixed with periodic signal generated by the normal vibration source,fault vibration signal and noise signal.The periodic component of vibration signal could be eliminated reasonably by using the adaptive narrowband interference elimination algorithm.Then the background noise could be eliminated with improved soft threshold denoising technique.At last,the source signal with characterization of fault was highlighted.Tests show that the robustness and the generalization ability of the signal pretreatment algorithms are improved after considering adaptive characteristics.It lays solid foundation for further signal processing.