应用于轴承故障诊断的LMS自适应滤波器及其FPGA实现
The LMS Adaptive Filter Applied to the Fault Diagnosis of Bearings and Its FPGA Implementation
  
中文关键词:轴承故障诊断  自适应滤波器  最小均方算法  FPGA
英文关键词:fault diagnosis of bearings  adaptive filter  least mean square algorithm  FPGA
基金项目:
作者单位
胡鑫磊 石家庄铁道大学电气与电子工程学院河北石家庄050043 
何绍玮 石家庄铁道大学电气与电子工程学院河北石家庄050043 
白雪飞 石家庄铁道大学电气与电子工程学院河北石家庄050043 
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中文摘要:
      在轴承信号当中,能反映轴承运行状态的信号总是掺杂着各种噪声,给故障特征的提取带来困难,基于最小均方(LMS)算法的自适应滤波器是去除噪声的首选方法。根据轴承故障信号的特点,以轴承故障信号的延时信号作为参考值,实时自适应调整滤波器不同时刻输出的权值来实现对轴承故障信号中噪声的滤除,并在此基础上给出了一种基于现场可编程门阵列(FPGA)的实现方案。仿真结果表明,该方案对于轴承信号的降噪效果良好,应用于FPGA后,运行速率也得到了很大的提升,可以在实际的轴承故障诊断工程中加以运用。
英文摘要:
      Among the signals of bearings, the signals that can reflect the operating state of the bearings are always doped with various noises, which make the extraction of the fault features difficult. The adaptive filter based on the least mean square (LMS) algorithm is the preferred method to remove noises. According to the characteristics of the fault signal of the bearings, and with the delay signal of the fault signals of the bearings as the referential value, the weighted values of the filter output at different times are adaptively adjusted to realize the filtering of the noise in the fault signal of the bearings, upon the basis of which an implementation scheme based on the field programmable gate array (FPGA) is presented in the paper. The simulated results show that the scheme is very effective in reducing the noise of the signals of bearings. After being applied to FPGA, the operating efficiency is also greatly improved, and thus it can be applied to other actual fault diagnosis projects of bearings.
胡鑫磊,何绍玮,白雪飞.应用于轴承故障诊断的LMS自适应滤波器及其FPGA实现[J].国防交通工程与技术,2021,19(1):34~36,79
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