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中文摘要：
为了获得期望特性的特征小波，采用提升模式构造了一种新小波。在提升模式的框架下，以3次B样条小波变换的低通滤波器作为初始滤波器，采用插值细分原理设计提升算子，一次提升之后获得了新的小波。这种小波继承了初始滤波器的低通滤波的特性，又具有提取瞬态冲击特征的能力。对提升模式框架进行等效易位变换，再去除抽样算子，提出了一种基于提升模式的非抽样小波变换算法。采用新小波的非抽样小波变换较好地提取了压缩机齿轮箱摩擦和高压缸碰摩的故障特征。工程实践证明，与传统离散小波变换相比，非抽样小波变换分解结果能够提供更加丰富的诊断信息。
英文摘要：
In order to get a characterized wavelet with expected properties of fault features extraction, by using the lifting scheme （LS）, a new wavelet is constructed. The low-pass filter of cubic B-splines wavelet transform is employed as an initial filter, and on the basis of the principle of interpolating subdivision, a lifting operator is designed, and then the new wavelet is obtained through one lifting step according to the LS framework. The wavelet inherits the property of low-pass filtering that the initial filter possessed, and has the ability to extract transient impulse component. By making an equivalent exchange to the LS framework and removing the decimator, an algorithm for undecimated wavelet transform （UWT） based on LS is proposed, through which, fault features of friction in a compressor gearbox and impact-rub in a pressure cylinder were effectively extracted. Engineering applications show that decomposition results of UWT can provide much more plenty diagnostics information than the classical wavelet transform.
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