About: Quality monitoring in milling of unidirectional CFRP through wavelet packet transform of force signals

Facets (new session)
Description
Metadata
Settings
- owl:sameAs
- Inference Rule:

About: Quality monitoring in milling of unidirectional CFRP through wavelet packet transform of force signals Goto Sponge NotDistinct Permalink

An Entity of Type : schema:ScholarlyArticle, within Data Space : covidontheweb.inria.fr associated with source document(s)

Attributes	Values
type	Academic Article research paper schema:ScholarlyArticle
isDefinedBy	Covid-on-the-Web dataset
title	Quality monitoring in milling of unidirectional CFRP through wavelet packet transform of force signals
Creator	Mamidala, Ramulu Pahuja, Rishi
source	Elsevier
abstract	Abstract Machining of CFRP is challenging and necessitates efficient and robust process monitoring techniques to minimize the machining induced damage such as fiber pullouts and delamination. In this study, wavelet packet transform of forces signals was used to monitor the surface quality of CFRP subjected to conventional edge trimming. Conventional milling experiments were performed on unidirectional CFRP machined at differ fiber orientation angles - 0°, 45°, 90° and 135°. The feed rate was varied between 0.025 and 0.75 mm/tooth. Depending on the fiber orientation, the ten point average roughness Rz varied between 2.9 and 104.1 µm. A novel algorithm using Wavelet Packet Decomposition was proposed to identify the signal features that could effectively establish a correlation between signal features, process variables (feed and speed) and surface roughness Rz. A bank of 35 different mother wavelets with decomposition levels up to 10 was explored. Seven different features were calculated for the wavelet packets obtained upon decomposition. Optimal wavelet parameters were identified based on the regression statistics. Among others, two features – standard deviation and energy-entropy coefficient were identified as primary candidates which resulted in roughness prediction with R2>91%. In addition, the morphology and removal mechanisms of the machined surfaces was examined using scanning electron microscopy. The nexus between those surfaces and signals was established which corroborated the utility of the proposed algorithm.
has issue date	2020-12-31(xsd:dateTime)
bibo:doi	10.1016/j.promfg.2020.05.061
has license	els-covid
sha1sum (hex)	84aaab7060d8f7094dd590fbffe44ced5dc88581
schema:url	https://doi.org/10.1016/j.promfg.2020.05.061
resource representing a document's title	Quality monitoring in milling of unidirectional CFRP through wavelet packet transform of force signals
schema:publication	Procedia Manufacturing
resource representing a document's body	covid:84aaab7060d8f7094dd590fbffe44ced5dc88581#body_text
is schema:about of	named entity 'speed' named entity 'monitoring' named entity 'mother' named entity 'algorithm' named entity 'surfaces' »more»

Faceted Search & Find service v1.13.91 as of Mar 24 2020

Alternative Linked Data Documents: Sponger | ODE Content Formats:

RDF

ODATA

Microdata

About

OpenLink Virtuoso version 07.20.3229 as of Jul 10 2020, on Linux (x86_64-pc-linux-gnu), Single-Server Edition (94 GB total memory)
Data on this page belongs to its respective rights holders.
Virtuoso Faceted Browser Copyright © 2009-2025 OpenLink Software