摘要
针对SPWVD存在中心信号频率能量发散、干扰信号能量波形及模态混叠现象未得到有效抑制的缺点,提出一种最小均方滤波算法(LMS)和平滑伪维格纳威尔分布(SPWVD)相结合的时频分析方法(LMS-SPWVD).首先,采用LMS算法对模拟非平稳振动信号测试函数进行抑噪处理,获取最优输出信号测试函数时域波形;然后采用SPWVD对最优输出信号测试函数时域波形进行分析,构建LMS-SPWVD算法时频分布模型;最后将该方法与SPWVD、LMS-STFT、LMS-WVD进行对比。结果表明,该方法具有较好的时频分辨率与时频聚集性、模态混叠及干扰信号抑制效果。
In view of the shortcomings of SPWVD,such as the energy divergence of the center signal,the energy waveform and the mode mixing of the interference signal are not effectively suppressed,a time-frequency analysis method(LMS-SPWVD)are proposed by combining the Least Mean Square Filtering algorithm(LMS)and the Smoothing Pseudo Wigner distribution(SPWVD).Firstly,the LMS algorithm is used to de-noise the test function of the simulated non-stationary vibration signal,and the time domain waveform of the test function of the optimal output signal is obtained.Then,SPWVD is used to analyze the time-domain waveform of the test function of the optimal output signal,and the time-frequency distribution model of LMS-SPWVD fusion algorithm is constructed.Finally,the proposed method is compared with SPWVD,LMS-STFT and LMS-WVD.The results show that this method has good time-frequency resolution,time-frequency aggregation,mode mixing and interference suppression effect.
作者
武鹏
李占龙
李虹
秦园
王瑶
WU Peng;LI Zhan-long;LI Hong;QIN Yuan;WANG Yao(School of Electronic Information Engineering,Taiyuan University of Science and Technology,Taiyuan 030024,China;School of Vehicle and Transportation Engineering,Taiyuan University of Science and Technology,Taiyuan 030024,China)
出处
《太原科技大学学报》
2023年第4期285-290,共6页
Journal of Taiyuan University of Science and Technology
基金
国家自然科学基金(52272401)
山西省基础研究计划项目(202203021211185)
贵州省科技计划项目(CXTD[2022]015)。
关键词
自适应LMS算法
平滑伪维格纳威尔分布
融合算法
非平稳振动信号
时频分析
adaptive LMS algorithm
smoothed pseudo wigner ville distribution
fusion algorithm
nonstationary vibration signal
time-frequency analysis
