New approach of features extraction for rotor faults from continuous wavelet transform scalogram

CHEN Guo; DENG Yan

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New approach of features extraction for rotor faults from continuous wavelet transform scalogram

更新时间：2026-07-07

- New approach of features extraction for rotor faults from continuous wavelet transform scalogram
- Vol. 24, Issue 4, (2009)
- 作者机构：
  
  南京航空航天大学民航学院,南京,210016
- 作者简介：
- 基金信息：
- DOI：
  CLC：
- Published：2009
- 稿件说明：
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CHEN Guo, DENG Yan. New approach of features extraction for rotor faults from continuous wavelet transform scalogram[J]. 2009, 24(4).
DOI：

CHEN Guo, DENG Yan. New approach of features extraction for rotor faults from continuous wavelet transform scalogram[J]. 2009, 24(4). DOI：

摘要

引入图像分析方法

提出了直接从转子故障信号连续小波尺度谱中提取图像纹理特征的新方法.首先

通过转子故障模拟实验台采集了不平衡、不对中、碰摩及油膜涡动等典型故障信号;然后

分析了故障信号尺度谱的差别及所提取出的数字特征对故障的敏感性;最后用结构自适应集成神经网络进行了智能诊断实验

结果表明了本文所提出的尺度谱数字特征对转子故障诊断的有效性.

Abstract

By introducing the image analysis method

this paper proposed a new method of directly extracting the image text features from scalogram of continuous wavelet transform of rotor faults signals.Firstly

the rotor fault experimental rig was used to simulate unbalance

misalignment

rubbing and oil whirling faults

and faults samples were obtained;secondly

the scalograms of typical faults was analyzed

and the sensitivity of digital features of scalograms to faults was studied;finally

the integrated back propagation(BP) neural network was used to carry out the diagnosis based on digital features of scalogram.The results fully show the effectivity of the new digital features of scalogram put forward in this paper.

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Related Institution

西安工业大学机电工程学院

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Key Laboratory of Artificial Intelligence of Yunnan Province， Kunming University of Science and Technology

Faculty of Information Engineering and Automation， Kunming University of Science and Technology

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