Volume 32 Issue 9
Sep.  2017
Turn off MathJax
Article Contents
Article Navigation >  Journal of Aerospace Power  > 2017  >  32(9): 2205-2218
Fault sensitivity analysis and fusion technology for vibration features of aero-engine rolling bearings[J]. Journal of Aerospace Power, 2017, 32(9): 2205-2218. doi: 10.13224/j.cnki.jasp.2017.09.020
Citation: Fault sensitivity analysis and fusion technology for vibration features of aero-engine rolling bearings[J]. Journal of Aerospace Power, 2017, 32(9): 2205-2218. doi: 10.13224/j.cnki.jasp.2017.09.020
shu

Fault sensitivity analysis and fusion technology for vibration features of aero-engine rolling bearings

doi: 10.13224/j.cnki.jasp.2017.09.020
  • Received Date: 2016-01-13
  • Publish Date: 2017-09-28
    Abstract
  • A method of multifeatures fusion based on normalized Euclidean distance was proposed to meet the requirement of monitoring aeroengine rolling bearing real time condition. Firstly, the bearing fault simulation experiments were carried out while the fault sensitivity of the features before and after fusion was analysed by introducing a quantitative evaluation index of fault sensitivity. Then, the proposed method was compared with the principal component analysis, support vector data description and support vector distribution estimation. Finally, the bearing fatigue accelerated experiment was carried out, and the proposed fusion method was applied to the aeroengine rolling bearing condition monitoring. Experimental results show that compared with principal component analysis, support vector data description and support vector distribution estimation, the fault sensitivity of fusion value based on normalized Euclidean distance is higher. For different types and different stages of the bearing fault, the fusion value obtained by proposed method is more sensitive, which is more suitable to be an index of the bearing condition monitoring, compared with the effective value.

     

    • FullText(HTML)
  • loading
    • References(20)
  • [1]
    LEE J,WU F,ZHAO W,et al.Prognostics and health management design for rotary machinery systems：reviews,methodology and applications［J］.Mechanical Systems and Signal Processing,2014,42(1/2):314-334.
    [2]
    DUDA R O,HART P E,STORK D G.Pattern classification［M］.New York:John Wiley and Sons,2012.
    [3]
    梅宏斌.滚动轴承振动监测与诊断［M］.北京:机械工业出版社,1995.
    [4]
    廖明夫,马振国,刘永泉,等.航空发动机中介轴承的故障特征与诊断方法［J］.航空动力学报,2013,28(12):2752-2758. LIAO Mingfu,MA Zhenguo,LIU Yongquan,et al.Fault characteristics and diagnosis method of intershaft bearing in aeroengine［J］.Journal of Aerospace Power,2013,28(12):2752-2758.(in Chinese)
    [5]
    陈果.滚动轴承早期故障的特征提取与智能诊断［J］.航空学报,2009,30(2):362-367. CHEN Guo.Feature extraction and intelligent diagnosis for ball bearing early faults［J］.Acta Aeronautica et Astronautica Sinica,2009,30(2):362-367.(in Chinese)
    [6]
    杨宇,王欢欢,程军圣,等.基于LMD的包络谱特征值在滚动轴承故障诊断中的应用［J］.航空动力学报,2012,27(5):1153-1158. YANG Yu,WANG Huanhuan,CHENG Junsheng,et al.Application of envelope spectrum characteristics based on LMD to roller bearing fault diagnosis［J］.Journal of Aerospace Power,2012,27(5):1153-1158.(in Chinese)
    [7]
    CONG Feiyun,CHEN Jin,DONG Guangming,et al.Shorttime matrix series based singular value decomposition for rolling bearing fault diagnosis［J］.Mechanical Systems and Signal Processing,2013,34(1/2):218-230.
    [8]
    向丹,岑健.基于EMD熵特征融合的滚动轴承故障诊断方法［J］.航空动力学报,2015,30(5):1149-1155. XIANG Dan,CEN Jian.Method of roller bearing fault diagnosis based on feature fusion of EMD entropy［J］.Journal of Aerospace Power,2015,30(5):1149-1155.(in Chinese)
    [9]
    郝腾飞,陈果,廖仲坤,等.基于正则化多核判别分析的航空发动机滚动轴承早期故障融合诊断方法［J］.航空动力学报,2013,28(12):2759-2770. HAO Tengfei,CHEN Guo,LIAO Zhongkun,et al.Approach for incipient fusion fault diagnosis of rolling bearing of aeroengine based on regularized multiple kernel discriminant analysis［J］.Journal of Aerospace Power,2013,28(12):2759-2770.(in Chinese)
    [10]
    CHEN S L,CRAIG M,WOOD R J K,et al.Bearing condition monitoring using multiple sensors and integrated data fusion techniques［C］∥Proceedings of the 9th International Conference in Vibrations in Rotating Machinery.Exeter,UK:Chandos Publishing,2008:586-600.
    [11]
    YU Jianbo.Bearing performance degradation assessment using locality preserving projections and Gaussian mixture models［J］.Mechanical Systems and Signal Processing,2011,25(7):2573-2588.
    [12]
    TAX D M J,DUIN R P W.Support vector domain description［J］.Pattern Recognition Letters,1999,20(11):1191-1199.
    [13]
    潘玉娜,陈进.小波包支持向量数据描述在轴承性能退化评估中的应用研究［J］.振动与冲击,2009,28(4):164-167. PAN Yuna,CHEN Jin.Wavelet packagesupport vector data description applied in bearing performance degradation assessment［J］.Journal of Vibration and Shock,2009,28(4):164-167.(in Chinese)
    [14]
    HUANG Runqing,XI Lifeng,LI Xinglin,et al.Residual life predictions for ball bearings based on selforganizing map and back propagation neural network methods［J］.Mechanical Systems and Signal Processing,2007,21(1):193-207.
    [15]
    QIU H,EKLUND N,LUO H,et al.Fusion of vibration and online oil debris sensors for aircraft engine bearing prognosis［R］.AIAA2010-2858,2010.
    [16]
    陈果,郝腾飞,程小勇,等.基于机匣测点信号的航空发动机滚动轴承故障诊断灵敏性分析［J］.航空动力学报,2014,29(12):2874-2884. CHEN Guo,HAO Tengfei,CHENG Xiaoyong,et al.Sensitivity analysis of fault diagnosis of aeroengine rolling bearing based on vibration signal measured on casing［J］.Journal of Aerospace Power,2014,29(12):2874-2884.(in Chinese)
    [17]
    SCHLKOPF B,PLATT J C,SHAWETAYLOR,et al.Estimating the support of a highdimensional distribution［J］.Neural Computation,2001,13(7):1443-1471.
    [18]
    HALL M,FRANK E,HOLMES G,et al.The WEKA data mining software:an update［J］.ACM SIGKDD Explorations Newsletter,2008,11(1):10-18.
    [19]
    CHANG C C,LIN C J.LIBSVM:a library for support vector machines［J］.ACM Transactions on Intelligent Systems and Technology,2011,2(3):389-396.
    [20]
    汪瑾,陈果,王洪伟,等.基于后验概率 SVM的航空发动机滚动轴承状态评估［J］.轴承,2015(5):55-59. WANG Jin,CHEN Guo,WANG Hongwei,et al.Condition assessment for aeroengine rolling bearings based on posterior probability SVM［J］.Bearing,2015(5):55-59.(in Chinese)
    • Relative Articles
    • Supplements(0)
    • Cited By
  • 加载中

Catalog

    通讯作者: 陈斌, bchen63@163.com
    • 1. 

      沈阳化工大学材料科学与工程学院 沈阳 110142

    1. 本站搜索
    2. 百度学术搜索
    3. 万方数据库搜索
    4. CNKI搜索
    Get Citation
    PDF(1436.0KB)
    XML

    Article Metrics

    Article views (1145) PDF downloads(580) Cited by()
    Proportional views
    Related

    Copyright © 《Journal of Aerospace Power》 All Rights Reserved.

    Supported by: Beijing Renhe Information Technology Co., Ltd.  

    /

    DownLoad:  Full-Size Img  PowerPoint
    Return
    Return