摘要
针对采集的电动机故障信号提取特征频率时产生的噪声干扰,提出了一种新的小波阈值函数,并将其与分层阈值相结合用于故障信号的小波去噪。新阈值函数很好地克服了软、硬阈值函数的缺点,分层阈值符合噪声分解系数随着分解尺度增大而迅速衰减的特点。对仿真信号及实测工程信号的分析结果表明,该算法有良好的去噪效果并有助于提高故障诊断的准确性。
A new threshold function is proposed in the paper for denoising noise produced during extracting the characteristic frequency from motor fault signal collected,and applied in denoising of motor fault signal by wavelet transform,combined with the hierarchical threshold.The shortcoming of the soft and hard threshold function is overcome trough the new threshold function,and the hierarchical threshold is consistent with the characteristics of the noise decomposition coefficient which rapidly fades with the increase of decomposition scale,The results of simulation signal and the actual engineering signal producing show that the algorithm has a good denoising effect and benefits to improve the accuracy of fault diagnosis.
作者
朱明斯
朱希安
Zhu Mingsi;Zhu Xi-an(Electronic and Communication Engineering,Beijing Information Science and Technology University,Beijing 100101,China)
出处
《科技通报》
北大核心
2017年第8期100-104,共5页
Bulletin of Science and Technology
基金
国家科技重大专项煤层气田地面集输信息集成及深度开发技术(2011ZX05039-004-02)
北京市教委创新能力提升项目
关键词
去噪
小波变换
阈值函数
电动机故障诊断
denoising
wavelet transform
threshold function
motor fault diagnosis
