A wear debris recognition method based on dual-channel electrostatic signal and prominence of cross-correlation function

Abstract

Electrostatic monitoring is a hot technique used for online wear debris detection. This study presented a recognition method by using a dual-channel electrostatic senor. A signal enhancement model based on an improved Variational Mode Decomposition (VMD) by double screening intrinsic mode function was proposed. Wear debris recognition algorithm and its processes were researched by using the dual-channel signals and the prominence of cross-correlation value. Experiments were conducted on a gear reducer bench, and the results of wear debris recognition between the electrostatic sensor and the inductive sensor were compared. The results show that the suggested algorithm can efficiently recognize signal pulses caused by wear debris, offering an effective analytical approach for early identification of wear status.