基于相位估计与补偿的时域同步平均方法
|
摘要
针对频率未知周期信号的时域平均问题,提出了一种通过相位补偿实现频率未知周期信号时域同步平均的方法。该方法采用FFT估计分段信号相邻段之间的相位差并补偿,使分段信号同步平均。对于多频率分量周期信号,采用自适应notch滤波器从原始信号中消除已增强并估计出频率的信号分量后,对剩余信号重复上述处理过程,可依次实现各频率分量的同步平均处理。计算机仿真表明,该方法不需要对未知信号频率进行搜索,大大提高了计算效率。
A novel time synchronously averaging method using phase compensation was proposed to deal with the periodic signal with unknown frequency.Since the phase difference was the same between adjacent data segments,it might be estimated with FFT(Fast Fourier Transform),and the result can be used to compensate the phase difference between data segments.As a result,all the segments were synchronized in phase and could be time synchronously averaged to enhance the periodic signal to the most.For periodic signal with multi-frequency components,the adaptive notch filter was used to cancel the enhanced signal from the original input signal,and the remained signal could be processed in the same manner repeatedly until all the frequency components were enhanced and extracted.Computer simulations verified that the method did not need to search the unknown frequency extensively,which was more efficient in applications.
A novel time synchronously averaging method using phase compensation was proposed to deal with the periodic signal with unknown frequency.Since the phase difference was the same between adjacent data segments,it might be estimated with FFT(Fast Fourier Transform),and the result can be used to compensate the phase difference between data segments.As a result,all the segments were synchronized in phase and could be time synchronously averaged to enhance the periodic signal to the most.For periodic signal with multi-frequency components,the adaptive notch filter was used to cancel the enhanced signal from the original input signal,and the remained signal could be processed in the same manner repeatedly until all the frequency components were enhanced and extracted.Computer simulations verified that the method did not need to search the unknown frequency extensively,which was more efficient in applications.
引文
[1]相敬林,王海燕.微弱信号检测技术与近感系统[M].西安:西北工业大学出版社,1993.
[2]Mcfadden P D.Application of synchronous averaging to vibration monitoring of rolling element bearings[J].Mechanical Systems and Signal Processing,2000(6):891-906.
[3]余红英,闫宏伟,潘宏侠.齿轮振动信号分解及其在故障诊断中的应用[J].振动,测试与诊断,2005,25(2):109-113.
[4]陈韶华,相敬林.一种改进的时域平均法检测微弱信号研究[J].探测与控制学报,2003,25(4):56-59.
[5]陈新华,孙长瑜,鲍习中.基于相位补偿的时域平均方法[J].应用声学,2011,30(4):268-274.
[6]胡广书.数字信号处理[M].北京:清华大学出版社,1997.
[7]惠俊英,蔡平,马晓民.自适应陷波器应用研究[J].声学学报,1991,16(1):19-24.
[2]Mcfadden P D.Application of synchronous averaging to vibration monitoring of rolling element bearings[J].Mechanical Systems and Signal Processing,2000(6):891-906.
[3]余红英,闫宏伟,潘宏侠.齿轮振动信号分解及其在故障诊断中的应用[J].振动,测试与诊断,2005,25(2):109-113.
[4]陈韶华,相敬林.一种改进的时域平均法检测微弱信号研究[J].探测与控制学报,2003,25(4):56-59.
[5]陈新华,孙长瑜,鲍习中.基于相位补偿的时域平均方法[J].应用声学,2011,30(4):268-274.
[6]胡广书.数字信号处理[M].北京:清华大学出版社,1997.
[7]惠俊英,蔡平,马晓民.自适应陷波器应用研究[J].声学学报,1991,16(1):19-24.