NDLI: Digital signal processing of acoustic emission signals using power spectral density and counts statistic applied to single-point dressing operation

Content Provider	IET Digital Library
Author	Lopes, Wenderson Nascimento Ferreira, Fabio Isaac Alexandre, Felipe Aparecido Ribeiro, Danilo Marcus Santos Junior, Pedro de Oliveira Conceição Aguiar, Paulo Roberto de Bianchi, Eduardo Carlos
Abstract	Dressing is an important operation for the grinding process. Its goal is to recondition the wheel tool to re-establish its cutting characteristics, owing to the wear produced after successive passes. Monitoring systems that use acoustic emission (AE) have been studied to correlate the signals with several tool conditions. This study brings a new approach of processing AE signals with the purpose of identifying the correct moment to stop the dressing, which is essential in an automatic control system. From the AE signals collected in dressing tests with aluminium oxide grinding wheel and single-point dresser, spectral analysis was made through power spectral density, selecting frequencies bands that best characterise the process. The statistical parameter ‘counts’ was applied to the raw signal unfiltered and filtered in the selected bands in order to identify the tool condition and, in turn, towards a monitoring system implementation. Results showed an expressive relation between tool cutting conditions and processed signals in the selected bands. There was a great disparity of the filtered signals in the selected bands and signals unfiltered, reflecting that the filtered ones were more efficient in terms of process automation.
Starting Page	631
Ending Page	636
Page Count	6
ISSN	17518822
Volume Number	11
e-ISSN	17518830
Issue Number	Issue 5, Aug (2017)
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/iet-smt/11/5
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/10.1049/iet-smt.2016.0317
Journal	IET Science, Measurement & Technology
Publisher Date	2017-03-21
Access Restriction	Open
Rights Holder	© The Institution of Engineering and Technology
Subject Keyword	Acoustic Emission Acoustic Emission Signal Processing Acoustic Property (mechanical Engineering) AE Monitoring System AE Signal Processing Aluminium Oxide Grinding Wheel Automatic Control System Correlation Method Cutting Cutting Tools Digital Signal Processing Filtering Method in Signal Processing Filtering Theory Grinding Grinding Machine Grinding Process Industrial Application of IT Machining Mechanical Component Mechanical Engineering Power Spectral Density Process Automation Production Engineering Computing Production Equipment Production Testing Signal Processing Single-point Dresser Single-point Dressing Operation Spectral Analysis Statistical Analysis Statistics Testing Tool Cutting Condition Tribology Wear Wheel Tool Reconditioning Wheels
Content Type	Text
Resource Type	Article
Subject	Atomic and Molecular Physics, and Optics Electrical and Electronic Engineering

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