Diesel Engine Turbocharger Monitoring by Processing Accelerometric Signals through Empirical Mode Decomposition and Independent Component Analysis

被引:0
|
作者
Chiavola, Ornella [1 ]
Palmieri, Fulvio [1 ]
Bocchetta, Gabriele [1 ]
Fiori, Giorgia [1 ]
Scorza, Andrea [1 ]
机构
[1] Roma Tre Univ, Dept Ind Elect & Mech Engn, I-00146 Rome, Italy
关键词
diesel engine; combustion process; accelerometer; vibration measurements; combustion control; IN-CYLINDER PRESSURE; COMBUSTION; VIBRATION;
D O I
10.3390/en17174293
中图分类号
TE [石油、天然气工业]; TK [能源与动力工程];
学科分类号
0807 ; 0820 ;
摘要
In this study, a method for the monitoring of internal combustion engine operation by vibration signals is proposed. The work falls within the context of the increasingly stringent standards relating to the environmental impact of engines and the development of monitoring and control techniques to ensure increased engine performance as well as fuel saving and reduction of pollutant emissions. Experimentation was performed on a turbocharged light-duty compression ignition direct-injection engine. Two monoaxial accelerometers were installed on the engine compressor case, the speed of which has been demonstrated to be closely related to the engine operation. Vibration measurements of the engine compressor case have been processed by combining the Empirical Mode Decomposition technique with Independent Component Analysis and Short Time Fourier Transform to indirectly estimate the turbocharger speed. The obtained traces have been compared to the direct turbocharger velocity measures during the stationary running of the engine (speed and load conditions varied in the complete engine's range of operation). The results point out the potentiality of the methodology in algorithms devoted to identifying modifications of the combustion development regarding regular operation via indirect turbocharger speed monitoring.
引用
收藏
页数:17
相关论文
共 50 条
  • [41] Micro-seismic signal denoising method based on empirical mode decomposition and independent component analysis
    Jia Rui-Sheng
    Zhao Tong-Bin
    Sun Hong-Mei
    Yan Xiang-Hong
    CHINESE JOURNAL OF GEOPHYSICS-CHINESE EDITION, 2015, 58 (03): : 1013 - 1023
  • [42] Adaptive cardiopulmonary resuscitation artifacts elimination algorithm based on empirical mode decomposition and independent component analysis
    Yu M.
    Chen F.
    Zhang G.
    Li L.
    Wang C.
    Wang D.
    Zhan N.
    Gu B.
    Wu T.
    Wu, Taihu (wutaihu@vip.sina.com), 2016, West China Hospital, Sichuan Institute of Biomedical Engineering (33): : 834 - 841
  • [43] A Stock Price Forecasting Model Integrating Complementary Ensemble Empirical Mode Decomposition and Independent Component Analysis
    Youwei Chen
    Pengwei Zhao
    Zhen Zhang
    Juncheng Bai
    Yuqi Guo
    International Journal of Computational Intelligence Systems, 15
  • [44] A Stock Price Forecasting Model Integrating Complementary Ensemble Empirical Mode Decomposition and Independent Component Analysis
    Chen, Youwei
    Zhao, Pengwei
    Zhang, Zhen
    Bai, Juncheng
    Guo, Yuqi
    INTERNATIONAL JOURNAL OF COMPUTATIONAL INTELLIGENCE SYSTEMS, 2022, 15 (01)
  • [45] A combined independent component analysis (ICA)/empirical mode decomposition (EMD) method to infer corticomuscular coupling
    McKeown, MJ
    Saab, R
    Abu-Gharbieh, R
    2005 2ND INTERNATINOAL IEEE/EMBS CONFERENCE ON NEURAL ENGINEERING, 2005, : 679 - 682
  • [46] Empirical Mode Decomposition Analysis of Alcohol Withdrawal Tremor Signals
    Norouzi, Narges
    Aarabi, Parham
    Dear, Taylor
    Carver, Sally
    Bromberg, Simon
    Kahan, Mel
    Gray, Sara
    Borgundvaag, Bjug
    2016 IEEE GLOBAL CONFERENCE ON SIGNAL AND INFORMATION PROCESSING (GLOBALSIP), 2016, : 90 - 93
  • [47] Noise-Assisted Data Processing With Empirical Mode Decomposition in Biomedical Signals
    Karagiannis, Alexandros
    Constantinou, Philip
    IEEE TRANSACTIONS ON INFORMATION TECHNOLOGY IN BIOMEDICINE, 2011, 15 (01): : 11 - 18
  • [48] Processing polysomnographic signals, using independent component analysis approaches
    Sameni, R
    Shamsollahi, MB
    Senhadji, L
    PROCEEDINGS OF THE SECOND IASTED INTERNATIONAL CONFERENCE ON BIOMEDICAL ENGINEERING, 2004, : 193 - 196
  • [49] EMG Signal Filtering Based on Independent Component Analysis and Empirical Mode Decomposition for Estimation of Motor Activation Patterns
    Claudio Tapia
    Omar Daud
    Javier Ruiz-del-Solar
    Journal of Medical and Biological Engineering, 2017, 37 : 140 - 155
  • [50] Separation of Heartbeat Waveforms of Simultaneous Two-Subjects Using Independent Component Analysis and Empirical Mode Decomposition
    Chowdhury, Jahid Hasan
    Shihab, Md.
    Pramanik, Sourav Kumar
    Hossain, Md. Shafkat
    Ferdous, Kaisari
    Shahriar, Md.
    Islam, Shekh M. M.
    IEEE MICROWAVE AND WIRELESS TECHNOLOGY LETTERS, 2024, 34 (08): : 1059 - 1062