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タイトル
和文: 
英文:Knocking Detection in Gasoline Engines Based on Probability Density Functions: A Mixed Gaussian Distribution Approach 
著者
和文: 伊吹 竜也, 粟井 康裕, 坂柳 佳宏, 三平 満司, 加古 純一.  
英文: Tatsuya Ibuki, Yasuhiro Awai, Yoshihiro Sakayanagi, Mitsuji Sampei, Junichi Kako.  
言語 English 
掲載誌/書名
和文: 
英文:Proceedings of 54th IEEE Conference on Decision and Control 
巻, 号, ページ         pp. 191-196
出版年月 2015年12月15日 
出版者
和文: 
英文:IEEE 
会議名称
和文: 
英文:54th IEEE Conference on Decision and Control 
開催地
和文: 
英文:Osaka 
DOI https://doi.org/10.1109/CDC.2015.7402107
アブストラクト This paper proposes an engine knocking detection approach based on probability density functions (PDFs). In this work, we suppose that the PDF of knocking intensity distribution can be approximated by a mixture of two Gaussian functions due to normal combustion and abnormal one. We first apply EM (Expectation-Maximization) algorithm to actual engine data to show that the knocking intensity probability distribution can be successfully estimated by the mixed Gaussian distribution. We next try to apply the existing online EM algorithm in view of the actual implementation by an engine control unit. However, since the existing algorithm is built for the estimation of a fixed PDF, the effect of new input data is gradually attenuated and vanishes after long time. We thus newly propose a modified online EM algorithm so that the effect of the new input data is not attenuated. Finally, we perform simulations and an actual engine bench test for the validity of the present approach.

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