基于量子Hadamard变换的滚动轴承振动信号分析方法

针对传统的滚动轴承振动信号分析方法在对信号降噪过程中容易产生的噪声信号与非噪声信号混杂的问题，提出一种基于量子Hadamard变换的信号分析方法。该方法通过将单个采样点信号量子化，深入分析每一个采样点内部信息，实现信号降噪的同时，完成对振动信号故障信息的突出表达，改善了振动信号的分析效果。实验结果表明，与传统的基于数学形态学的分析方法相比，基于量子Hadamard变换的分析方法能够有效提升滚动轴承信号的降噪效果，故障特征信号得到有效凸显。
Abstract：Based on the traditional analysis method for rolling bearing vibration signals,in the process of de-noising it is easy to confuse noises and non-noises.To solve the problem,an analysis method based on the quantum Hadamard transform was proposed.In the method the inner information was analysed deeply at every sampling point by using the quantum transform.Then the fault information in fault vibration signals was highlighted during the signal de-noising.In the data processing,the analysis effects were improved by virtue of the quantum theory.The experiment results show that comparing with the traditional mathematical morphology analysis algorithm,the method based on the quantum Hadamard transform can better improve the effect of de-noising and enhance the fault signals for rolling bearings.