Acoustic Emission Signal Filtering Methods for Identifying Associations Between Diagnostic Parameters of Two Milling Cutter: Experimental Data

Identification of association between diagnostic parameters of AE signals is an important task of nondestructive testing. This article presents the results of applying the previously developed polynomial filtering method for processing AE signals. The operability of this filtering method was analyze...

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Bibliographic Details
Main Authors: Altay, Yeldos A., Fedorov, Aleksey V., Stepanova, Ksenia A., Kuzivanov, Dmitry O.
Format: Conference Proceeding
Language:English
Subjects:
acoustic emission signal
associating
correlation analysis
Cutting tools
diagnostic parameters
Filtering
Instruments
Machine learning
Milling
Noise measurement
Nondestructive testing
polynomial filter
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Summary:Identification of association between diagnostic parameters of AE signals is an important task of nondestructive testing. This article presents the results of applying the previously developed polynomial filtering method for processing AE signals. The operability of this filtering method was analyzed based on 120 noisy AE signals. It has been established that, on average, the filtering method increases the signal-to-noise ratio up to 10 dB and identify a statistically significant association between the diagnostic parameters of a defective and defect-free instrument.
ISSN:2771-697X
DOI:10.1109/EExPolytech56308.2022.9950907