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Advanced signal processing for misfire detection in automotive engines

机译:用于汽车发动机失火检测的高级信号处理

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The paper presents an application of artificial neural networks to the reliable detection of misfires in automotive engines. By government regulations, automobiles an required to be equipped with instrumentation to detect engine misfires and to alert the driver whenever the misfire rate has the potential to affect the health of emission control systems. A relevant model for the powertrain dynamics is developed as well as an explanation of the instrumentation. The basis for using a neural network to detect these misfires is explained and experimental system performance data (including error rates) an given. It is shown that the present method has the potential to meet the government mandated requirements.
机译:本文提出了人工神经网络在汽车发动机失火的可靠检测中的应用。根据政府规定,要求汽车配备有检测发动机失火的仪器,并在失火率可能影响排放控制系统健康的情况下向驾驶员发出警报。开发了动力总成动力学的相关模型以及对仪表的解释。解释了使用神经网络检测这些失火的基础,并给出了实验系统性能数据(包括错误率)。结果表明,本方法有可能满足政府规定的要求。

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