Leakage Detection Based on CEEMDAN Analysis for Hydraulic Cylinder Using Acoustic Emission Technique

Abstract

Abstract The early internal leakage fault characteristics in hydraulic cylinder are very weak and vulnerable to environmental noise, which makes the early internal leakage fault detection very difficult. In comparison with internal leakage detection by the pressure signal, internal leakage by Acoustic emission (AE) signal has higher sensitivity and accuracy. So this paper adapts the algorithms combining complete ensemble empirical mode decomposition with adaptive noise (CEEMDAN) and auto regressive (AR) spectrum. Comparing with the mean value of first intrinsic mode function (IMF1) instantaneous amplitude based on EEMD, The experimental results verify the proposed algorithms based on CEEMDAN distinguish different internal leakage levels obviously and has better performance.