一种自适应形态滤波算法及其在轴承故障诊断中的应用

张西宁; 唐春华; 周融通; 雷威

doi:10.7652/xjtuxb201812001

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一种自适应形态滤波算法及其在轴承故障诊断中的应用

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- 一种自适应形态滤波算法及其在轴承故障诊断中的应用
- Adaptive Morphological Filtering Algorithm with Applications in Bearing Fault Diagnosis
- 西安交通大学学报 2018年52卷第12期页码：1-8+37
- 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：
  
  : 2018-04-16。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)
- DOI：10.7652/xjtuxb201812001
  中图分类号： TH17
- 网络首发：2018-12-10，
  
  纸质出版：2018
- 稿件说明：
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张西宁, 唐春华, 周融通, 等. 一种自适应形态滤波算法及其在轴承故障诊断中的应用[J]. 西安交通大学学报, 2018,52(12):1-8+37.

Adaptive Morphological Filtering Algorithm with Applications in Bearing Fault Diagnosis[J]. 2018, 52(12): 1-8+37.
张西宁, 唐春华, 周融通, 等. 一种自适应形态滤波算法及其在轴承故障诊断中的应用[J]. 西安交通大学学报, 2018,52(12):1-8+37. DOI： 10.7652/xjtuxb201812001.

Adaptive Morphological Filtering Algorithm with Applications in Bearing Fault Diagnosis[J]. 2018, 52(12): 1-8+37. DOI： 10.7652/xjtuxb201812001.

摘要

针对工程实际中的故障诊断受限于零部件故障先验知识缺乏、振动信号调制及噪声成分复杂等问题

提出了一种滚动轴承故障诊断的自适应形态学滤波方法。在对基本形态算子和组合形态算子原理分析的基础上

利用非线性滤波器幅频响应分析法

获得了不同形态算子的滤波特性

定量分析了结构元素尺度参数对滤波效果的影响。对典型的滚动轴承故障模型及振动信号进行分析

获得了故障轴承运行的主要特征

确定了结构元素尺度参数选定策略

数值仿真实验验证了该方法的可行性。进行滚动轴承实验振动信号分析

结果表明

与参数优化的组合形态滤波差值算子(CMFH)相比

所提方法至少将信号的特征幅值能量比提高了29.8%、算法效率提高了50.0%

可清晰、准确、快速地将滚动轴承外圈和内圈的故障特征呈现出来

进一步证明了该方法在机械故障诊断应用上的可靠性和实用性。

Abstract

Facing the fact that fault diagnosis in engineering practice is limited by many factors

including the lack of prior knowledge of faulty components

modulation of vibration signals and interference due to various noise

an adaptive filtering algorithm based on mathematical morphology is proposed for rolling bearing fault diagnosis. Following the principle of basic and combined morphological operators

characteristics of each kind of morphological operator and the quantitative effect of varying structure element scale on filtering results are revealed by amplitude-frequency response method of non-linear filter. Besides

the main features of running faulty bearing are obtained while a selection strategy of structure element scale is determined after discussion on the physical model and corresponding vibration signal of typical faulty rolling bearing. The feasibility of this method is validated by numerical simulations. Compared with optimal parameter CMFH method

the proposed adaptive method detects the information more quickly

clearly and accurately from signals of rolling bearing with outer or inner race fault. The FAER index of processed signal and efficiency of signal processing are at least heightened by 29.8% and 50.0%

respectively.

关键词

Keywords

references

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