IPSW方法及其在变工况滚动轴承退化状态跟踪中的应用

IPSW method and its application in the state tracking of rotating bearing degradation under variable working conditions

感知获取的一维快变信号不仅受工况变化的影响,且无法避免地受到噪声干扰,此时传统的相空间曲变(PSW)方法提取的健康指数(HI)将无法胜任变工况下的滚动轴承退化趋势跟踪。针对这一问题,提出了改进的相空间曲变法(IPSW)。从确保PSW分量的独立性及其信息最大化的角度出发,通过高维重构分量间的综合平均互信息局部极小化和互信息熵局部极大化,避免高维重构相空间相轨迹发生扭曲和缠绕,并对慢变损伤趋势项与工况变化干扰项进行解耦,实现独立于工况变化的、反映故障演化趋势的HI提取。仿真及实验信号验证结果表明:基于IPSW方法提取的HI能够有效避免转速变化的影响,对轴承损伤退化趋势进行有效跟踪。

The health indicator(HI) extracted by the traditional phase space warping(PSW) method cannot track the degradation trend of rolling bearings under the variable working conditions. To solve this issue, the improved phase space warping(IPSW) is proposed in this study. From the perspective of ensuring the independence of PSW components and maximizing their information, the high-dimensional reconstruction of the phase space phase trajectory distortion and entanglement can be avoided by the integrated average mutual information local minimization and mutual information entropy local minimization between the high-dimensional reconstruction components. The slow-changing damage trend item and the working condition change interference item are decoupled to realize the HI extraction that is independent of the working condition change and reflects the fault evolution trend. Simulation and experimental signal verification results show that the extracted HI with the IPSW method can effectively avoid the influence of speed change and track the bearing damage degradation trend effectively.