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Characterization of the physical origins of acoustic emission (AE) from natural fiber reinforced polymers (NFRPs) machining processes

Article dans une revue avec comité de lecture
Author
WANG, Zimo
301080 Texas A&M University [College Station]
GUO, Ruiqi
MA, Qiyang
ccCHEGDANI, Faissal
211915 Mechanics surfaces and materials processing [MSMP]
301080 Texas A&M University [College Station]
TAI, Bruce
301080 Texas A&M University [College Station]
EL MANSORI, Mohamed
211915 Mechanics surfaces and materials processing [MSMP]
301080 Texas A&M University [College Station]
BUKKAPATNAM, Satish T. S.
301080 Texas A&M University [College Station]

URI
http://hdl.handle.net/10985/23484
DOI
10.1007/s00170-021-07956-w
Date
2021-09-08
Journal
The International Journal of Advanced Manufacturing Technology

Abstract

Natural fiber reinforced polymers (NFRPs) are environmentally friendly and are receiving growing attention in the industry. However, the multi-scale structure of natural fibers and the random distribution of the fibers in the matrix material severely impede the machinability of NFRPs, and real-time monitoring is essential for quality assurance. This paper reports a synchronous in situ imaging and acoustic emission (AE) analysis of the NFRP machining process to connect the temporal features of AE to the underlying dynamics and process instability, all happen within milliseconds during the NFRP cutting. This approach allows directly observing the surface modification and chip formation from a high-speed camera (HSC) during NFRP cutting processes. The analysis of the HSC images suggests that the complex fiber structure and the random distribution introduce an unsteady, almost a freeze-and-release type motion pattern of the cutting tool with varying depths of cut at the machining interface. More pertinently, a prominent burst pattern of AE from time domain was found to emanate due to the sudden penetration of the tool into the surface of the NFRP workpiece (increasing the depth of cut), as well as a release motion of the tool from its momentary freeze position. These findings open the possibility of tracking AE signals to assess the effective specific energy and surface quality that are affected by these unsteady motion patterns.

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