Vibration-based feature extraction of determining dynamic characteristic for engine block low vibration design

被引:0
|
作者
Xian-feng Du
Zhi-jun Li
Feng-rong Bi
Jun-hong Zhang
Xia Wang
Kang Shao
机构
[1] Tianjin University,State Key Laboratory of Engines
来源
Journal of Central South University | 2012年 / 19卷
关键词
feature extraction; dynamic characteristic; finite element model; empirical mode decomposition; diesel engine block;
D O I
暂无
中图分类号
学科分类号
摘要
In order to maintain vibration performances within the limits of the design, a vibration-based feature extraction method for dynamic characteristic using empirical mode decomposition (EMD) and wavelet analysis was proposed. The proposed method was verified experimentally and numerically by implementing the scheme on engine block. In the implementation process, the following steps were identified to be important: 1) EMD technique in order to solve the feature extraction of vibration signals; 2) Vibration measurement for the purpose of confirming the structural weak regions of engine block in experiment; 3) Finite element modeling for the purpose of determining dynamic characteristic in time region and frequency region to affirm the comparability of response character corresponding to improvement schemes; 4) Adopting a feature index of IMF for structural improvement based on EMD and wavelet analysis. The obtained results show that IMF of signal is more sensitive to response character corresponding to improvement schemes. Finally, examination of the results confirms that the proposed vibration-based feature extraction method is very robust, and focuses on the relative merits of modification and full-scale structural optimization of engine, together with the creation of new low-vibration designs.
引用
收藏
页码:2238 / 2246
页数:8
相关论文
共 50 条
  • [11] Dynamic characteristics and vibration-based damage inspection of structures with actual fatigue cracks
    Pai, P. Frank
    Liu, Jun
    Sundaresan, Mannur J.
    HEALTH MONITORING OF STRUCTURAL AND BIOLOGICAL SYSTEMS 2013, 2013, 8695
  • [12] Comparison of wind turbine gearbox vibration analysis algorithms based on feature extraction and classification
    Koukoura, Sofia
    Carroll, James
    McDonald, Alasdair
    Weiss, Stephan
    IET RENEWABLE POWER GENERATION, 2019, 13 (14) : 2549 - 2557
  • [13] Feature Extraction of Vibration Signal Based on An Improved Local Wave Analysis
    Wang, Fengli
    Xing, Hui
    Duan, Shulin
    MATERIAL SCIENCE, CIVIL ENGINEERING AND ARCHITECTURE SCIENCE, MECHANICAL ENGINEERING AND MANUFACTURING TECHNOLOGY II, 2014, 651-653 : 575 - 578
  • [14] Feature extraction of vibration of turbine unit based on manifold learning method
    He, Qing
    Xie, Fangfang
    Li, Hong
    Lan, Lan
    He, Qing, 1600, Nanjing University of Aeronautics an Astronautics (34): : 705 - 708
  • [15] An Accurate Integral Method for Vibration Signal Based on Feature Information Extraction
    Zhu, Yong
    Jiang, Wanlu
    Kong, Xiangdong
    Zheng, Zhi
    Hu, Haosong
    SHOCK AND VIBRATION, 2015, 2015
  • [16] Vibration-based incipient surge detection and diagnosis of the centrifugal compressor using adaptive feature fusion and sparse ensemble learning approach
    Hou, Yaochun
    Wang, Yuxuan
    Pan, Yiran
    He, Weiting
    Huang, Wenjun
    Wu, Peng
    Wu, Dazhuan
    ADVANCED ENGINEERING INFORMATICS, 2023, 56
  • [17] Tool Vibration Feature Extraction Method Based on SSA-VMD and SVM
    Cai, Lihong
    Hu, Dong
    Zhang, Chengming
    Yu, Song
    Xie, Jufang
    ARABIAN JOURNAL FOR SCIENCE AND ENGINEERING, 2022, 47 (12) : 15429 - 15439
  • [18] Vibration Feature Extraction Using Audio Spectrum Analyzer based Machine Learning
    Liang, Jyun-Shun
    Wang, Kerwin
    PROCEEDINGS OF THE 2017 IEEE INTERNATIONAL CONFERENCE ON INFORMATION, COMMUNICATION AND ENGINEERING (IEEE-ICICE 2017), 2017, : 381 - 384
  • [19] Tool Vibration Feature Extraction Method Based on SSA-VMD and SVM
    Lihong Cai
    Dong Hu
    Chengming Zhang
    Song Yu
    Jufang Xie
    Arabian Journal for Science and Engineering, 2022, 47 : 15429 - 15439
  • [20] Feature extraction based on vibration signal decomposition for fault diagnosis of rolling bearings
    Hocine Bendjama
    The International Journal of Advanced Manufacturing Technology, 2024, 130 : 821 - 836