基于提升方法的小波构造及早期故障特征提取

针对机械信号早期故障特征的提取问题，提出了一种根据故障特征波形的特点来构造相应小波的方法．该方法以提升方法为基础，通过对初始双正交滤波器组进行提升和对偶提升，来获得不同的提升算子和对偶提升算子，从而构造出具有理想特性的新小波．提取提升后小波分解的高频细节信号在每个信号工作周期中的模极大值，来确定信号发生微弱突变的时刻和位置．工程振动信号分析表明，同其他类型的小波相比，用提升方法构造的小波能更好地匹配机械信号故障特征波形，因此较理想地提取出了某炼油厂重催机组转子不平衡、轴系不对中和轻微碰摩的故障特征．

Wavelet Construction Based on Lifting Scheme and Incipient Fault Feature Extraction

To extract incipient fault feature of mechanical signal, a new method to construct wavelet according to the fault characteristics is presented. This method is based on lifting scheme, the initial set of finite biorthogonal filters is followed by lifting and dual lifting, and different lifting operators and dual lifting operators are obtained to construct new wavelet with particular properties. Modulus maxima of the detail signal after lifting in every operation cycle is extracted, and the position and time while weak signal singularity occurs are found. The engineering result confirms that the proposed method is better than the other wavelet methods for matching fault feature of mechanical signal, and the weak impact-rub fault caused by the axis misalignment and rotor imbalance of a key rotating machine in an oil refinery are desirably extracted.