挖掘机用柴油机噪声源的识别
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摘要
为了有效降低某型液压挖掘机的辐射噪声,对某挖掘机用柴油机的噪声源进行了识别研究。采用声学照相机对挖掘机噪声信号进行了测试,找到最大噪声源区域并记录噪声信号。根据测试环境受到回声与背景噪声干扰的特点,建立了基于快速固定点独立分量分析频域复数算法的噪声分离模型,通过独立分量分析得到了40个独立分量及其主频。为了确定这些主频对应的零部件,对柴油机表面主要零部件进行了模态分析。将在测试噪声方向上振型模态的共振频率与独立分量分析得出的各分量的主频相比较,找到了机体、气门室盖、气缸盖等主要表面噪声源。研究结果表明:运用独立分量分析和模态分析相结合的方法,可以准确识别挖掘机用柴油机表面噪声辐射源。这种方法可以广泛应用于复杂机器噪声源识别以及故障诊断等领域。
To reduce radiated noise of a hybrid excavator effectively,surface noise sources of its diesel engine were investigated.Noise on the diesel engine was tested by an acoustic camera.The field of noise sources was detected and noise signals were recorded.Because there were strong background noise and echoic interference,a noise separation model was built based on fast fixed-point component analysis complex algorithm in frequency domain.Forty independent components and their principle frequencies were obtained.To find out the corresponding parts of these frequencies,modal analysis of main surface parts was doned.By comparing principle frequencies with modal analysis resonant frequencies in the testing direction,main surface noise sources such as cylinder block,valve chamber cap and cylinder head were found.It was showed that by means of independent component analysis and modal analysis,noise sources of an excavator diesel engine can be properly identified.This new approach can be widely applied in the area such as noise identification and fault diagnosis of complex machinery.
To reduce radiated noise of a hybrid excavator effectively,surface noise sources of its diesel engine were investigated.Noise on the diesel engine was tested by an acoustic camera.The field of noise sources was detected and noise signals were recorded.Because there were strong background noise and echoic interference,a noise separation model was built based on fast fixed-point component analysis complex algorithm in frequency domain.Forty independent components and their principle frequencies were obtained.To find out the corresponding parts of these frequencies,modal analysis of main surface parts was doned.By comparing principle frequencies with modal analysis resonant frequencies in the testing direction,main surface noise sources such as cylinder block,valve chamber cap and cylinder head were found.It was showed that by means of independent component analysis and modal analysis,noise sources of an excavator diesel engine can be properly identified.This new approach can be widely applied in the area such as noise identification and fault diagnosis of complex machinery.
引文
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[2]李立民,冯忠绪,姚运仕,等.双钢轮振动压路机噪声源的识别[J].广西大学学报:自然科学版,2011,36(6):900-915.
[3]宋雷鸣,佟复华,刘达德.强背景声场下的声强测量[J].铁道学报,2000,22(2):90-93.
[4]CHAN C M P,ANDERTON D.Correlation between engine block surface vibration and radiated noise of inline dieselengines[J].Noise Control Engineering,1974,2(1):6-24.
[5]袁斌,饶彩超.挖掘机液压系统故障诊断分析[J].机电工程技术,2002,31(3):59-60.
[6]ZHANG Jun-hong,YU Yi-long,HAN Bing.Identification of diesel front sound source based on continuous wave-let trans-form[J].Chinese Journal of Mechanical Engineering,2004,17(2):268-271.
[7]SHAPIRO J M.Embedded image coding using zerotrees of wavelet coefficients[J].IEEE Trans Signal Processing,1993,41(12):3445-3462.
[8]曾生根,朱宁波,包晔,等.一种改进的快速独立分量分析算法及其在图象分离中的应用[J].中国图象图形学报,2003,8(10):1159-1165.
[9]高巧玲,刘辉.一种峭度FastICA改进算法[J].计算机技术与发展,2010,20(11):114-116.
[10]周卫东,贾磊.小波变换和独立分量分析去除脑电信号中的噪声和干扰[J].山东大学学报:医学版,2003,41(2):116-122.
[11]刘喜武,刘洪,李幼铭.独立分量分析及其在地震信息处理中应用初探[J].地球物理学进展,2003,18(1):90-96.
[12]刘月辉,张俊红,郝志勇.基于独立分量分析的内燃机噪声信号分离[J].内燃机学报,2005,23(1):63-66.
[13]陈敏,江云菲,习鑫,等.核独立成分分析在图像处理中的应用[J].计算机应用研究,2008,25(1):297-299.
[14]COMON P.Indepent component analysis─A new concept[J].Signal Processing,1994,36(3):287-314.
[15]HYVARINEN A,KARHUNEN J,OJA E.Independent component analysis[M].New York:Johm Wiley&Sons,2001:152-153.
[16]郝志勇,韩军.小波变换技术在内燃机振声信号分析中的应用[J].内燃机工程,2003,24(6):7-9.
[17]CARDOSO J F,LAHELD B H.Equivariant adaptive source separation[J].IEEE Trans on Signal Processing,1996,44(12):3017-3030.
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