CAJ | 학술논문

针对发动机轴承并发故障信号微弱、相互耦合且易被其他信号淹没的问题，提出了基于平行因子分析的轴承并发故障信号盲源分离方法，利用平行因子分析预测了信号传播路径响应函数，并以此构造了虚拟观测信号，结合实际观测信号，将盲源分离从欠定变为适定或超定，采用自适应平行因子分析算法，得到了反映故障特征的分离信号；实际应用中针对曲轴轴承与连杆轴承并发故障，分离信号的特征频率分布分别对应曲轴轴承和连杆轴承的故障频率，因此，所提出的盲源分离方法能够准确诊断出轴承并发故障。
침대발동궤축승병발고장신호미약、상호우합차역피기타신호엄몰적문제，제출료기우평행인자분석적축승병발고장신호맹원분리방법，이용평행인자분석예측료신호전파로경향응함수，병이차구조료허의관측신호，결합실제관측신호，장맹원분리종흠정변위괄정혹초정，채용자괄응평행인자분석산법，득도료반영고장특정적분리신호；실제응용중침대곡축축승여련간축승병발고장，분리신호적특정빈솔분포분별대응곡축축승화련간축승적고장빈솔，인차，소제출적맹원분리방법능구준학진단출축승병발고장。
For the weak ,mutual coupling and easily-submerged problem of engine bearing concurrent fault signal ,the blind source separation method was proposed based on the parallel factor analysis .The response function of propagation path was predicted with the parallel factor and the virtual observation signal was built .Combining the real observation signals ,the blind source separation became determined or overdetermined from underdetermined .Through the adaptive parallel factor analysis method ,the signals reflecting fault feature were acquired .In the practical application to crankshaft bearing and connecting rod bearing concurrent fault signals ,the feature frequencies of separation signal were corresponding to crankshaft bearing and con-necting rod bearing fault frequency respectively .Accordingly ,the proposed blind source separation method could diagnose the bearing concurrent fault correctly .