Real-time misfire detection of large gas engine using big data analytics

被引：0
|
作者：
Szabo, Jozsef Z. [1 ]
Bakucz, Peter [1 ]
机构：
[1] Obuda Univ, Donat Banki Fac Mech & Safety Engn, Budapest, Hungary
来源：
2018 IEEE 16TH INTERNATIONAL SYMPOSIUM ON INTELLIGENT SYSTEMS AND INFORMATICS (SISY 2018) | 2018年
关键词：
misfire phenomena; vibration signal; deep learning; fuzzy logic; gas engine;
D O I：
暂无
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
In this work application of fuzzy deep learning algorithm to classify vibration signals of a Deutz MWM 8 cylinder large gas engine is presented. The main contribution is to identify the misfire characteristics in real-time embedded microcontroller environment. The substance of the scheduled fuzzy system is a stratified deep neural network that obtains information from both fuzzy and neural representations. The misfire characteristics learnt from these two various views are convolved, forming the ultimate signal to be classified.
引用
收藏
页码：215 / 220
页数：6
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