人工神经网络在内燃机中的应用

None Eslam Sayed, Nouby M. Ghazaly
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引用次数: 0

摘要

本研究以火花点火发动机气缸盖为实验装置,采用声发射技术检测内燃机气门故障。研究了三种类型的气门损伤(间隙、半缺口和缺口)对气门泄漏的影响。研究表明声发射技术在时间和频率两方面都是一种有效的阀门损伤检测方法。利用声发射参数特征(声发射数、绝对声发射功率、最大信号幅值和平均信号电平)对神经网络进行时域分析训练。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Application of Artificial Neural Network for Internal Combustion Engines
In this research, acoustic emission (AE) technology is used to detect faults in the valves in the internal combustion engine, where the cylinder head of a spark ignition engine was used as an experimental setup. The study was conducted on three types of valve damage ((clearance, half-notch, and notch) on valve leakage. The study proved that the acoustic emission technique is an effective method in detecting damage to valves in both the time and frequency domain. The neural network was trained based on time domain analysis using AE parametric features (, number, absolute AE power, maximum signal amplitude, and average signal level).
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