CAJ | 학술논문

由于机械系统的振动信号能有效反映系统特征，对其进行盲解卷积能提供由混合信号中分离出源信号的可能性，为此提出机械系统振动卷积模型；将多通道盲最小均方差与缩减盲源方法结合提出MBLMS-TDS组合算法，且利用该算法对卷积混合信号进行盲解卷积验证算法的合理性；用该算法对柴油机表面混合振动信号进行分离，获得活塞撞击缸体信号与柴油机燃烧信号。
유우궤계계통적진동신호능유효반영계통특정，대기진행맹해권적능제공유혼합신호중분리출원신호적가능성，위차제출궤계계통진동권적모형；장다통도맹최소균방차여축감맹원방법결합제출MBLMS-TDS조합산법，차이용해산법대권적혼합신호진행맹해권적험증산법적합이성；용해산법대시유궤표면혼합진동신호진행분리，획득활새당격항체신호여시유궤연소신호。
The mechanical system vibration signals effectively reflect the characteristics of the system and its blind deconvolution can provide the possibility of separation of source signals from mixed signals.A convolution model of the mechanical system vibration was proposed and the method of Multi-Channel Blind Least Mean Squares was combined with the method of Deflation Source so as to form the MBLMS-TDS algorithm.For verifing the reasonableness of the algorithm, it was applied in the blind deconvolution of some simulated mixed sources.As a practical example,the piston-slap signal and combustion signal of a diesel engine were extracted from the mixed vibration signal on the surface of the diesel engine piston by using the MBLMS-TDS algorithm.