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	基于缸盖振动信号的活塞环腔压力径向基神经网络识别研究
	孟凡明 ; 张优云 ; MENG Fan-ming ; ZHANG You-yun
	2010-06-08 ; 2010-06-08
关键词	内燃机 活塞环 气体压力 识别 缸盖振动 径向基网络 ARMA时间序列 I.C.Engine Piston Ring Gas Pressure Identification Cylinder Head Vibration RBF Neural Network ARMA Time Series TK421
其他题名	RBF Neural Network Identification for Inner-Rings Gas Pressure Based on Cylinder Head Vibration Signal
中文摘要	介绍了利用气缸盖振动信号,借助径向基神经网络(RBFNN),进行活塞环腔气体压力识别的方法。以1100柴油机为试验对象,测得其缸盖振动位移和气缸内气体燃烧压力,将缸盖振动信号作为识别的输入信号,利用径向基神经网络和ARMA时间序列分析法对气缸燃烧压力和环腔内气体压力进行了识别。结果表明:利用径向基网络和ARMA时间序列分析法,均能较为准确地识别活塞环环腔气体压力和气缸内气体燃烧压力;径向基神经网络的识别方法比ARMA时间序列识别方法更加准确。; A new method identifying gas pressure in inner rings in an ICE was presented.An experiment was carried out on a 1100-typediesed engine,and the vibration signal from the cylinder head and combustion gas pressure in the cylinder were obtained.By the use of radial basic function neural network(RBFNN),the gas pressure in inner rings was identified.The validity of the new method,compared with that by the ARMA time series analysis method,was demonstrated.The results show that the proposed method is valid in identifying gas pressure in inner rings,and will become a useful one in this way.; 国家自然科学基金资助(50375115)
语种	中文 ; 中文
内容类型	期刊论文
源URL	[http://hdl.handle.net/123456789/48702]
专题	清华大学
推荐引用方式 GB/T 7714	孟凡明,张优云,MENG Fan-ming,等. 基于缸盖振动信号的活塞环腔压力径向基神经网络识别研究[J],2010, 2010.
APA	孟凡明,张优云,MENG Fan-ming,&ZHANG You-yun.(2010).基于缸盖振动信号的活塞环腔压力径向基神经网络识别研究..
MLA	孟凡明,et al."基于缸盖振动信号的活塞环腔压力径向基神经网络识别研究".(2010).

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