【摘要】 针对齿轮箱故障微弱信号特征识别问题,设计了一种识别该类信号微弱特征的自适应提升小波包方法。该方法以提升方法为基础,构造了提升小波包分解和重构过程算法,并以分解层信号相邻样本点自相关系数的大小作为目标函数,在每个样本点上选择能够自适应匹配信号局部特性的提升小波包算子,将每个分解频带信号进行重构,识别时域故障微弱信号特征。该方法成功地识别出了某齿轮箱发生摩擦故障时隐含在振动信号中的调制波形和周期性冲击脉冲故障微弱特征。结果表明,自适应提升小波包方法对强噪声背景下故障微弱信号特征的识别效果优于经典小波包方法。更多还原

【Abstract】 Aim.Early identification of weak-signal fault features is obviously highly desirable but highly difficult.We have worked on this difficult problem for a number of years.We now propose using the adaptive lifting scheme packet and apply it to identifying successfully weak-signal fault features of a certain gearbox.In the full paper,we explain in some detail the lifting scheme packet and its application;in this abstract,we just add some pertinent remarks to listing the four topics of explanation.The first topic is: the principles of the lifting scheme packet.In this topic,we present the three steps of its decomposition process: splitting,prediction and updating.The second topic is: the construction of the lifting scheme packet.In this topic,we work out the algorithms for decomposing and reconstructing the lifting scheme packet,as given in eqs.(5) through(8) and eqs.(9) through(16) respectively in the full paper.The third topic is: the calculation and adaptive selection of the operators of the lifting scheme packet.In this topic,we adaptively select at each adjacent sample point the operators of the lifting scheme packet that match the weak-signal fault features through using the auto-correlation coefficients of decomposed signals as objective function and determining the values of their auto-correlation coefficients.The fourth topic is: the analysis of vibrational signals.In this topic,we apply the lifting scheme packet to analyzing the vibrational signals of a certain gearbox.We decompose and reconstruct its vibrational signals to identify the fault features of modulation waveform and cyclic impact or impulse signals,as illustrated in Fig.3 in the full paper.Then we conduct the demodulation analysis,whose results are given in Fig.5 in the full paper,and reach the conclusion that the rotating frequency of the small gear in the high-speed axle is the faulty source modulation frequency.The application results show preliminarily that the adaptive lifting scheme packet is effective for the early identification of weak-signal fault features.更多还原