基于EEMD和ICA方法的驾驶室内噪声源时频分析

为有效控制工程机械驾驶室内噪声,利用集合经验模态分解(ensemble empirical mode decomposition, EEMD)后的本征模函数作为稳定独立成分分析(independent component analysis, ICA)算法中的多个虚拟通道,提出了基于EEMD和ICA相结合的驾驶室内噪声盲源分离方法。通过分析仿真信号验证了EEMD-ICA方法研究复杂非平稳信号可行。结合相干分析、时频分析方法研究推土机驾驶室内噪声特性。结果表明,柴油机的1／2阶、1阶转动频率是驾驶室内相关零部件的振动辐射噪声的主要激励来源,柴油机的燃烧噪声也是室内噪声的来源。通过相干分析与时频分析相结合的技术可较准确实现噪声源定位,结合测试对象的相关常识可实现对噪声类型判别、噪声传入途径等复杂的问题进行研究,为进一步实现驾驶室内噪声治理、故障诊断,提供经济实用的分析手段。

Time-frequency analysis of cabin noise based on ensemble empirical mode decomposition and independent component analysis#br#

In order to effectively control cabin noise and improve noise quality, combined techniques of ensemble empirical mode decomposition (EEMD) and an improvement of independent component analysis (ICA) were applied to analysze cabin noise. Intrinsic mode functions resulting from EEMD analysis were used as the virtual channels of ICA, which solved an undetermined problem of blind source identification from single sampling signal. The feasibility of EEMD-ICA method for complex non-stationary signals was verified by analyzing the simulated signals. With the experiment and coherence analysis for cabin interior and outside noise and vibration signals of a bulldozer, the technique of EEMD-ICA was effective on the noise source separation and identification. Meanwhile, techniques of coherence analysis and time-frequency analysis were used for accurate noise sources identification. The results showed that the main cabin noise source was combustion noise of diesel engine and mechanical radiation noise of cabin parts caused by 1／2 order and 1 order rotation frequency of the diesel engine. And generation details of noise source, transmission paths of air-borne or structure-borne noise were well analyzed in order to control the interior noise and identify faults by the techniques of coherence analysis and time-frequency analysis.