【作者】 王霞；

【导师】 毕凤荣；

【作者基本信息】 天津大学 ， 车辆工程， 2010， 硕士

【摘要】 随着人们对车辆NVH性能要求的不断提高,内燃机的振动噪声问题也逐渐成为国内内燃机学科研究的热点问题和重要方向。如何准确、快捷的识别内燃机的主要噪声源是内燃机噪声控制的重要前提。内燃机振动的多激励性和各种激励的时变性使其外在表现出的振动噪声现象非常复杂。传统的数学工具在描述内燃机的振动噪声特性上都有一定的局限性。近年来,数字信号处理技术的迅速发展为内燃机振动噪声信号分析提供了更加丰富的手段。本文针对内燃机辐射噪声信号的特点,研究利用噪声测试技术、独立分量分析、小波变换技术及盲分离不确定性消除等现代测试技术与信号分析方法,从复杂的噪声信号中分离和识别内燃机的主要噪声源及其对整机噪声的贡献度。主要研究内容如下:1.阐述了内燃机噪声产生的机理,揭示了内燃机噪声的主要激励源及其在内燃机结构内部的传递路径。激励的时变性和传递路径的时变性决定了其振动噪声信号的非平稳性特征。总结了内燃机噪声源的主要识别方法。2.根据独立分量分析方法的基本原理,以某四缸柴油机为研究对象,对其不同工况下的噪声信号进行了统计独立性和高斯性分析,结果表明,噪声信号基本满足独立分量分析的前提条件。采用基于负熵极大地快速独立分量分析(FastICA)算法,对该内燃机表面辐射噪声信号进行分离,得到一系列独立分量。3.为进一步识别分离得到的各独立分量与内燃机噪声源的对应关系,采用傅里叶变换和小波变换技术对各个分量进行特征分析,结合时频分析的结果和内燃机辐射噪声产生的机理,确定了各独立分量对应的激励源。4.为消除ICA(BSS)估计的不确定性,采用基于快速傅里叶变化与最大相关准则分析的ICA(BSS)估计源自适应校正方法,对分离得到的各独立噪声源信号进行处理,实现了源噪声信号波形的恢复。5.通过计算分离得到的各独立分量噪声信号的声功率以及整机辐射噪声声功率,得到了各激励源对整机辐射噪声声功率的贡献度,明确了主要的噪声源及其特征,提出了控制主要噪声源的措施,为进一步控制整机噪声奠定了基础。试验结果验证了本文所研究的内燃机噪声盲源分离技术的正确性。更多还原

【Abstract】 The study on noise and vibration of internal combustion engine were paid more attention rencently by internal researchers for the improving requirement of vehicles′NVH (noise vibration and harshness) performance. The identifications of the main noise source and the research on mechanism of engine noise emission are also critical for both noise control engineer and fault diagnose. The vibration and noise emission from engine is complicated for there are too many internal excitations of engine, and the excitations are also time variable signals from I.C. engine show their limitation in describing the complexity. The digital signal processing (DSP) technique had got great achievement in recent twenty years.Base on the characteristics of internal-combustion engine noise signal, the noise test measurement, wavelet transform, independent component analysis and eliminating blind uncertainty of ICA estimation to the research of vibration and noise signals from I.C. engine was deeply investigated. The main noise source of the engine and the contribution are separated and identified from the complex noise. The main research contents are as follows:1. The mechanism of internal-combustion engine noise was expounded. The main excitations and the path of noise transmission in the internal parts of the engine were revealed. The noise and vibration signal was no-stationary induced by both the time-variable excitations and time-dependent transmission path. The methods of identification of internal combustion engine were reviewed.2. Basic on the principle of independent component analysis. The statistical independence and guassianity of noise signals at different operatation conditions of a four cylinder diesel engine was analysed. The result has shown that noise signals meet the preconditions of ICA. The negative entropy enormously fast independent component analysis (FastICA) algorithm was adopted to separate noise signals, and a series of independent components were obtained.3. In order to identify eath independent component further, combining with the feature of time-frequency analysis results and the mechanism of the engine radiation noise, the FFT and the wavelet transform are used to determine the relationship between different independent components and different noise source of the engine.4. In order to eliminate blind uncertainty of ICA estimation, a adaptive method for revision of ICA estimate was adopted bsed on combination of FFT-MCC. Thus, blind uncertainty of ICA was eliminated and the waveforms of sources were restored correctly.5. Through the calculation of the sound power radiated of the separated singnal from noise signal of independent component analysis and the whole engine, the contribution of noise source and characteristics were obtained. The main noise source control measures were put forward as a foundation to control the whole engine noise. Experimental results verified the correction of the research about the internal combustion engine noise blind source separation technology.更多还原