Effect of the Denoising on Acoustic Emission Signals

Abstract

The acoustic emission (AE) technology is growing in its applicability to bearing defect diagnosis. Several publications have shown its effectiveness for earlier detection of bearing defects than vibration analysis. In the latter instance, detection and monitoring of defects can be achieved through temporal statistical indicators, which can further be improved by application of denoising techniques. This paper investigates the application of temporal statistical indicators for AE detection of bearing defects on a purposely built test-rig and assesses the effectiveness of various denoising techniques in improving sensitivity to early defect detection. It is concluded that the denoising methods offer significant improvements in identifying defects with AE, especially the self-adaptive noise cancellation method.

Fatigue Damage Evolution and Monitoring of Carbon Fiber Reinforced Polymer Bridge Cable by Acoustic Emission Technique

“…Thus, this condition can be used to evaluate potential defects and the service capabilities of the carbon fiber cable. Kurtosis is calculated as follows [17]:…”

Cyclostationarity of Acoustic Emissions (AE) for monitoring bearing defects

“…Liu et al [12] used the independent components analysis, Liao et al [13] employed wavelets analysis whilstŽvokelj et al [14] and Li et al [15] were interested in the empirical mode decomposition and Gabor transform, respectively, on AE signals. Chiementin et al [16] used time domain indicators RMS, Kurtosis, and proposes to improve the signal-to-noise ratio by applying denoising techniques (wavelet, spectral subtraction, sanc) on experimental acquired AE data. The use of traditional methods of vibration analysis for AE analysis offers yet further techniques for the diagnostician.…”

A signal processing approach for enhanced Acoustic Emission data analysis in high activity systems: Application to organic matrix composites

“…The WT has been used in many studies related to the Structural Health Monitoring (SHM) field [23][24][25][26][27][28]. Some other studies have reported on the use of the WT on AE signals for a denoising purpose [29][30][31][32].…”