CAJ | 학술논문

为了分离装载机的噪声源,采用集合经验模态分解(EEMD)、独立分量分析(ICA)和连续小波变换(CWT)技术相结合的方法,对装载机司机位置处噪声信号进行了盲源分离和声源识别研究.针对单一通道噪声信号进行盲源分离,将其分解成一系列独立分量.在削弱了传统经验模态分解(EMD)算法处理噪声信号时产生的模态混叠现象的同时,克服了独立分量分析方法要求传感器数目必须大于等于分离出分量数目的限制;借助连续小波变换良好的时频定位特性,对ICA分离结果进行时频分析.结合时频分析结果和各噪声源信号的频谱结构,确定了各独立分量与装载机不同噪声源的对应关系.结果表明,这些独立分量分别对应着装载机的燃烧噪声、冷却风扇辐射噪声及排气噪声等噪声源.
위료분리장재궤적조성원,채용집합경험모태분해(EEMD)、독립분량분석(ICA)화련속소파변환(CWT)기술상결합적방법,대장재궤사궤위치처조성신호진행료맹원분리화성원식별연구.침대단일통도조성신호진행맹원분리,장기분해성일계렬독립분량.재삭약료전통경험모태분해(EMD)산법처리조성신호시산생적모태혼첩현상적동시,극복료독립분량분석방법요구전감기수목필수대우등우분리출분량수목적한제;차조련속소파변환량호적시빈정위특성,대ICA분리결과진행시빈분석.결합시빈분석결과화각조성원신호적빈보결구,학정료각독립분량여장재궤불동조성원적대응관계.결과표명,저사독립분량분별대응착장재궤적연소조성、냉각풍선복사조성급배기조성등조성원.
In order to separate noise sources of loader,ensemble empirical mode decomposition(EEMD), independent component analysis(ICA)and continuous wavelet transform(CWT)technologies were used to study the blind source separation and noise source identification of loader driver location noise. Blind source separation for sin-gle-channel noise signal was adopted to obtain a series of independent components. This method overcame the prob-lem that the number of sensors must be larger than or equal to the number of separated components. At the same time,it weakened the model mix superposition problem which usually occurs when processing noise signal with the algorithm of empirical mode decomposition(EMD). Continuous wavelet transform was used for its better time-frequency localization features to analyze the time-frequency characteristics of ICA results. Combining the results with different noise source frequency spectrums,the corresponding relationship was determined. Results show that these independent components correspond to combustion noise,fans noise and exhaust noise of the loader respectively.