A Novel Multiple Feature-Based Engine Knock Detection System using Sparse Bayesian Extreme Learning Machine-Reference-Cited by-同舟云学术

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A Novel Multiple Feature-Based Engine Knock Detection System using Sparse Bayesian Extreme Learning Machine

Published:2022-01-19 Issue:2 Volume:14 Page:828-851
ISSN:1866-9956
Container-title:Cognitive Computation
language:en
Short-container-title:Cogn Comput

Author:

Yang Zhao-Xu,Rong Hai-Jun,Wong Pak Kin,Angelov Plamen,Vong Chi Man,Chiu Chi Wai,Yang Zhi-Xin

Funder

Fundo para o Desenvolvimento das Ciencias e da Tecnologia

National Natural Science Foundation of China

Natural Science Basic Research Program of Shaanxi Province

Macao Youth Scholars Program

University of Macau Distinguished Visiting Scholar Program

Multi-Year Research Grant from the University of Macau

Publisher

Springer Science and Business Media LLC

Subject

Cognitive Neuroscience,Computer Science Applications,Computer Vision and Pattern Recognition

Link

https://link.springer.com/content/pdf/10.1007/s12559-021-09945-3.pdf

Reference40 articles.

1. Zhen X, Wang Y, Xu S, Zhu Y, Tao C, Xu T, Song M. The engine knock analysis-an overview. Appl Energy. 2012;92:628–36.

2. Galloni E. Dynamic knock detection and quantification in a spark ignition engine by means of a pressure based method. Energy Convers Manage. 2012;64:256–62.

3. Abu-Qudais M. Exhaust gas temperature for knock detection and control in spark ignition engine. Energy Conversion and Management. 1996;37(9):1383–1392.

4. Ollivier E, Bellettre J, Tazerout M, Roy CG. Detection of knock occurrence in a gas SI engine from a heat transfer analysis. Energy Conv Manage. 2006;47(7-8):879–893.

5. Pan J, Shu G, Wei H. Interaction of flame propagation and pressure waves during knocking combustion in spark-ignition engines. Combust Sci Technol. 2014;186(2):192–209.

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