一种改进的局部倒频谱分析方法

张西宁; 李兵; 雷威

doi:10.7652/xjtuxb201608001

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一种改进的局部倒频谱分析方法

更新时间：2025-05-08

- 一种改进的局部倒频谱分析方法
- An Improved Local Cepstrum Analysis Method
- 西安交通大学学报 2016年50卷第8期页码：1-5+14
- 作者机构：
  
  西安交通大学机械制造系统工程国家重点实验室,西安,710049
- 作者简介：
- 基金信息：
  
  : 2016-03-23。作者简介: 张西宁(1965-),男,教授,博士生导师。基金项目: 国家自然科学基金资助项目(51275379);国家自然科学基金创新研究群体资助项目(51421004);陕西省科学技术研究发展计划资助项目(K11-16)
- DOI：10.7652/xjtuxb201608001
  中图分类号： TH17
- 网络首发：2016-08-10，
  
  纸质出版：2016
- 稿件说明：
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张西宁, 李兵, 雷威. 一种改进的局部倒频谱分析方法[J]. 西安交通大学学报, 2016,50(8):1-5+14.

An Improved Local Cepstrum Analysis Method[J]. 2016, 50(8): 1-5+14.
张西宁, 李兵, 雷威. 一种改进的局部倒频谱分析方法[J]. 西安交通大学学报, 2016,50(8):1-5+14. DOI： 10.7652/xjtuxb201608001.

An Improved Local Cepstrum Analysis Method[J]. 2016, 50(8): 1-5+14. DOI： 10.7652/xjtuxb201608001.

摘要

针对倒频谱分析难以实现从低信噪比信号中检测故障的问题

在对局部倒频谱分析的基础上

提出了一种改进的局部倒频谱分析方法

并给出了改进局部倒频谱分析的原理和算法。该方法通过在时域引入相关消噪处理

降低时域原始信号中的非周期性分量的干扰

在频域引入相关消噪处理

降低频谱上非周期性谱峰影响

实现了频谱上周期性故障特征向零频率附近的聚集。改进的局部倒频谱分析方法解决了局部倒频谱方法存在的计算频带难以选择的问题

同时消除了对故障频域内周期性特征局部化分布的限制

扩展了应用范围。将该方法用于仿真信号以及故障齿轮实验测试信号的分析

结果表明

与传统倒频谱和局部倒频谱方法相比

提出的改进局部倒频谱分析方法具有强的抗噪能力

实验中较传统倒频谱和局部倒频谱方法分别多提供了8.05 bit和1.11 bit的诊断信息。该方法可用于实现从低信噪比信号中检测故障。

Abstract

The traditional cepstrum analysis is difficult to realize fault detection from low SNR signal. An enhanced local cepstrum analysis method is proposed on the basis of analysis of local cepstrum analysis method

the corresponding principles and algorithm are given. The theory of interference reduction of aperiodic components in original signal of time domain is expounded emphatically by introducing the related de-noising processing in time domain. The rules of interference reduction of aperiodic components of spectral peaks in frequency domain and the realization of convergence of periodic fault features near the zero frequency by adopting the related de-noising processing in frequency domain are also explained. The frequency band selection difficulty in the calculation of local cepstrum analysis method is solved

and the limitation of highly localized distribution of periodic fault features in spectrum is eliminated by frequency domain related de-noising processing. The proposed method is employed to analyze both simulated signal and vibration signal of a fault gear. Compared with the traditional cepstrum and local cepstrum methods

the proposed method has strong ability to resist noise and is able to provide 8.05 bit and 1.11 bit more information respectively for fault diagnosis in experiment.

关键词

Keywords

references

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