• 主题
高级搜索  >
历史搜索 清空历史
首页> 外文期刊>Applied Acoustics >De-noising of wayside acoustic signal from train bearings based on variable digital filtering
【24h】

De-noising of wayside acoustic signal from train bearings based on variable digital filtering

机译：基于可变数字滤波的列车轴承路边声信号降噪

获取原文
获取原文并翻译 | 示例
           
页面导航
  • 摘要
  • 著录项
  • 相似文献
  • 相关主题

摘要

In the wayside Acoustic Defective Bearing Detector (ADBD) system, the recorded signal usually includes both the sound from train bearings and the other disturbance sources. The fact of heavy noise corruption and the Doppler Effect of multi-source acoustic signals would badly reduce the effectiveness of online defect detection of the ADBD system. In order to extract useful information from the multi-source signal with Doppler Effect, this paper proposes an effective de-noising method based on the variable digital filter (VDF) for the ADBD system. Specifically, the ridge extraction based on Short-Time Fourier Transform (STFT) is applied to estimate the instantaneous frequencies (IFs), with which the fitting IF curves based on the Morse theory of theoretical acoustics could be achieved by using the nonlinear curve-fitting so that the parameters of the initial position of the acoustic sources could be calculated. By the aid of these parameters, the IFs according to the target train bearing could be then extracted. After that, the FIR variable digital filters could be designed with all the IFs which match the Morse theory with Doppler Shift so that the noise from the other parts could be effectively restrained after filtering the original signal. The effectiveness of this method is verified by means of a simulation with multi-frequency signals and applications to diagnosis of train roller bearing defects. Results indicate that the proposed method is effective.
机译：在路边的轴承缺陷检测器（ADBD）系统中，记录的信号通常既包括火车轴承发出的声音，也包括其他干扰源。严重的噪声破坏和多源声信号的多普勒效应将严重降低ADBD系统在线缺陷检测的效率。为了利用多普勒效应从多源信号中提取有用信息，本文提出了一种基于可变数字滤波器（VDF）的ADBD系统有效降噪方法。具体来说，采用基于短时傅立叶变换（STFT）的岭提取来估计瞬时频率（IFs），利用该频率可以通过使用非线性曲线拟合来实现基于理论莫尔斯理论的拟合IF曲线。这样就可以计算出声源初始位置的参数。借助于这些参数，然后可以提取根据目标列车轴承的IF。此后，可以使用所有符合摩尔斯理论和多普勒频移的IF设计FIR可变数字滤波器，以便在对原始信号进行滤波之后可以有效地抑制来自其他部分的噪声。该方法的有效性通过使用多频率信号进行仿真验证，并应用于诊断火车滚子轴承缺陷。结果表明，该方法是有效的。

著录项

  • 来源
    《Applied Acoustics》 |2014年第9期|127-140|共14页
  • 作者

    Chao Wang; Fei Hu; Qingbo He; Ao Zhang; Fang Liu; Fanrang Kong;

  • 作者单位

    Department of Precision Machinery and Precision Instrumentation, University of Science and Technology of China, Hefei, Anhui 230026, China;

    Department of Precision Machinery and Precision Instrumentation, University of Science and Technology of China, Hefei, Anhui 230026, China;

    Department of Precision Machinery and Precision Instrumentation, University of Science and Technology of China, Hefei, Anhui 230026, China;

    Department of Precision Machinery and Precision Instrumentation, University of Science and Technology of China, Hefei, Anhui 230026, China;

    Department of Precision Machinery and Precision Instrumentation, University of Science and Technology of China, Hefei, Anhui 230026, China;

    Department of Precision Machinery and Precision Instrumentation, University of Science and Technology of China, Hefei, Anhui 230026, China;

  • 收录信息 美国《科学引文索引》(SCI);美国《工程索引》(EI);
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    Train bearing; Wayside acoustic signal; Doppler Effect; De-noising; Variable digital filtering; Fault diagnosis;

    机译：火车轴承;路边声音信号;多普勒效应;去噪可变数字滤波;故障诊断;

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱：kefu@zhangqiaokeyan.com

京公网安备：11010802029741号 ICP备案号：京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有

  • 客服微信

  • 服务号