In-machine data acquisition for evaluating the conditioning efficiency of resin-bonded super-abrasive grinding wheels
Author:
Affiliation:
1. Faculty of Engineering Bilbao, University of the Basque Country (UPV/EHU), Bilbao, Spain
2. IDEKO, Elgoibar, Spain
Funder
EKOHEGAZ project of the Elkartek program
Scientific models and machine-tool advanced sensing techniques for efficient machining of precision components of Low-Pressure Turbines
laboratory LTC AENIGME
Publisher
Informa UK Limited
Subject
Electrical and Electronic Engineering,Computer Science Applications,Mechanical Engineering,Aerospace Engineering
Link
https://www.tandfonline.com/doi/pdf/10.1080/0951192X.2022.2095673
Reference33 articles.
1. Wear mechanism in high-speed superabrasive grinding of titanium alloy and its effect on surface integrity
2. Texture analysis for grinding wheel wear assessment using machine vision
3. Assessment of grinding wheel conditioning process using machine vision
4. Assessment of vitrified CBN wheels for precision grinding
5. Characterization of grinding wheel topography using a white chromatic sensor
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1. On the evaluation of grinding wheel surface condition under different process parameters via in-machine monitoring;2023-03-28
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