Abstract

To reveal the chaotic characteristics of friction vibration, pin–plate wear experiments were carried on a wear tester. Different wear states were designed by changing the amount of lubricating oil and distinguished with the friction coefficient. In order to improve the reliability of the collected data, the fictional vibration signals were denoised using an ensemble empirical mode decomposition (EEMD) method. The method of information entropy was proposed to measure the disorder of frequency energy distribution of friction vibration signals. The information entropy of friction vibration decreases in the running-in wear state, fluctuates steadily in the stable wear state, and increases rapidly in the severe wear state. The variation of information entropy of friction vibration signals is closely related to the surface topography of friction pairs. The results indicate that the information entropy of friction vibration can be applied to monitor and recognize the wear state of friction pairs.

摘要

为了揭示摩擦振动的混沌特性，在磨损测试仪上进行了销板磨损实验。通过改变润滑油的用量设计不同的磨损状态，并通过摩擦系数进行区分。为了提高收集数据的可靠性，使用集合经验模态分解（EEMD）方法对虚构的振动信号进行去噪。提出了信息熵的方法来测量摩擦振动信号频率能量分布的无序性。摩擦振动的信息熵在磨合磨损状态下减小，在稳定磨损状态下平稳波动，在严重磨损状态下迅速增加。摩擦振动信号信息熵的变化与摩擦副表面形貌密切相关。