Paper Info
Title
Tool Wear Estimation And Visualization Using Image Sensors In Micro Milling Manufacturing
Abstract
This paper presents a reliable machine vision system to automatically estimate and visualize tool wear in micro milling manufacturing. The estimation of tool wear is very important for tool monitoring systems and image sensors configure a cheap and reliable solution. This system provides information to decide whether a tool should be replaced so the quality of the machined piece is ensured and the tool does not collapse. In the method that we propose, we first delimit the area of interest of the micro milling tool and then we delimit the worn area. The worn area is visualized and estimated while errors are computed against the ground truth proposed by experts. The method is mainly based on morphological operations and k-means algorithm. Other approaches based on pure morphological operations and on Otsu multi threshold algorithms were also tested. The obtained result (a harmonic mean of precision and recall 90.24 (+/- 2.78)%) shows that the machine vision system that we present is effective and suitable for the estimation and visualization of tool wear in micro milling machines and ready to be installed in an online system.
Year
DOI
Venue
2018
10.1007/978-3-319-92639-1_33
HYBRID ARTIFICIAL INTELLIGENT SYSTEMS (HAIS 2018)
Keywords
Field
DocType
Tool wear, Micro milling, Wear estimation, Wear visualization
Computer vision,Image sensor,Monitoring system,Pattern recognition,Computer science,Harmonic mean,Visualization,Precision and recall,Ground truth,Tool wear,Artificial intelligence,Area of interest
Conference
Volume
ISSN
Citations 
10870
0302-9743
0
PageRank 
References 
Authors
0.34
2
6
Name
Order
Citations
PageRank
Laura Fernández-Robles15412.95
Noelia Charro200.34
Lidia Sánchez-González327.88
Hilde Pérez428.56
Manuel Castejón-Limas557.26
Javier Alfonso-Cendón6147.12