基于多分形特征的枪械自动机裂纹故障诊断

doi:10.3969/j.issn.1000-1093.2018.03.006

兵工学报 ›› 2018, Vol. 39 ›› Issue (3): 457-462.doi: 10.3969/j.issn.1000-1093.2018.03.006

基于多分形特征的枪械自动机裂纹故障诊断

任海锋，潘宏侠

(中北大学机械工程学院，山西太原 030051)

收稿日期:2017-05-08 修回日期:2017-05-08 上线日期:2018-05-07
通讯作者: 潘宏侠(1950—)，男，教授，博士生导师 E-mail:panhx1015@163.com
作者简介:任海锋(1986—)，男，博士研究生。E-mail: ren_haifeng@163.com
基金资助:
国家自然科学基金项目（51675491）

Crack Fault Diagnosis of Gun Automatic Mechanism Based on Multifractal Features

REN Hai-feng, PAN Hong-xia

(School of Mechanical Engineering, North University of China, Taiyuan 030051, Shanxi, China)

Received:2017-05-08 Revised:2017-05-08 Online:2018-05-07

摘要/Abstract

摘要： 为更好地利用振动信号对枪械自动机的裂纹故障进行诊断，提出基于振动信号多分形特征的故障诊断方法。该方法利用Wavelet Leader 来估计振动信号的多分形谱，通过6个特征量描述多分形谱的形态特征以实现多分形谱的降维，并使用基于Mahalanobis距离的分类器对不同的裂纹故障进行分类。应用该方法对某12.7 mm高射机枪自动机闭锁机构的裂纹故障进行了诊断，诊断正确率达到了82.5%，验证了将振动信号的多分形特征用于自动机裂纹故障诊断的可行性。

关键词: 枪械自动机, 多分形特征, WaveletLeader方法, Mahalanobis距离, 裂纹故障诊断

Abstract: In order to make better use of vibration signals to diagnose the crack faults of gun automatic mechanism, a fault diagnosis method based on multifractal features of vibration signals is proposed. The proposed method uses Wavelet Leader to estimate the multifractal spectrum of vibration signals. 6 feature quantities are used to describe the morphological features of multifractal spectrum,and the dimensionality reduction of multifractal spectrum is realized. A classifier based on Mahalanobis distance is used to classify different crack faults. This method is applied to diagnose the crack faults of locking mechanism in a 12.7 mm antiaircraft machine gun, and the diagnostic accuracy is up to 82.5%, which verifies the feasibility of applying the multifractal features of vibration signals to the crack fault diagnosis of gun automatic mechanism. Key

Key words: gunautomaticmechanism, multifractalfeature, WaveletLeadermethod, Mahalanobisdistance, crackfaultdiagnosis

中图分类号:

TJ203⁺.2

任海锋，潘宏侠. 基于多分形特征的枪械自动机裂纹故障诊断[J]. 兵工学报, 2018, 39(3): 457-462.

REN Hai-feng, PAN Hong-xia. Crack Fault Diagnosis of Gun Automatic Mechanism Based on Multifractal Features[J]. Acta Armamentarii, 2018, 39(3): 457-462.

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第39卷
第3期2018 年3月兵工学报ACTA
ARMAMENTARIIVol.39No.3Mar.2018

基于多分形特征的枪械自动机裂纹故障诊断

Crack Fault Diagnosis of Gun Automatic Mechanism Based on Multifractal Features

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