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Fuzzy Pattern Classification Based Detection of Faulty Electronic Fuel Control (EFC) Valves Used in Diesel Engines

机译:基于模糊模式分类的柴油发动机电子燃油控制(EFC)气门故障检测

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摘要

In this paper, we develop mathematical models of a rotary Electronic Fuel Control (EFC) valve used in a Diesel engine based on dynamic performance test data and system identification methodology in order to detect the faulty EFC valves. The model takes into account the dynamics of the electrical and mechanical portions of the EFC valves. A recursive least squares (RLS) type system identification methodology has been utilized to determine the transfer functions of the different types of EFC valves that were investigated in this study. Both in frequency domain and time domain methods have been utilized for this purpose. Based on the characteristic patterns exhibited by the EFC valves, a fuzzy logic based pattern classification method was utilized to evaluate the residuals and identify faulty EFC valves from good ones. The developed methodology has been shown to provide robust diagnostics for a wide range of EFC valves.
机译:在本文中,我们基于动态性能测试数据和系统识别方法,开发了用于柴油发动机的旋转式电子燃油控制(EFC)气门的数学模型,以检测故障的EFC气门。该模型考虑了EFC阀的电气和机械部分的动力学。递归最小二乘(RLS)类型的系统识别方法已用于确定本研究中研究的不同类型的EFC阀门的传递函数。为此目的,频域和时域方法都已被利用。基于EFC阀显示的特征模式,基于模糊逻辑的模式分类方法用于评估残差并从良好的EFC阀中识别出故障的EFC阀。业已证明,开发的方法可为各种EFC阀提供可靠的诊断。

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