Tool condition monitoring by SVM classification of machined surface images in turning

Progressive cutting tool wear detection from machined surface images using Voronoi tessellation method

(2013) A. Datta et al.   JOURNAL OF MATERIALS PROCESSING TECHNOLOGY

Correlation study of tool flank wear with machined surface texture in end milling

(2013) S. Dutta et al.   MEASUREMENT

Detection of tool condition from the turned surface images using an accurate grey level co-occurrence technique

(2012) S. Dutta et al.   PRECISION ENGINEERING-JOURNAL OF THE INTERNATIONAL SOCIETIES FOR PRECISION ENGINEERING AND NANOTECHNOLOGY

Effect of SVM kernel functions on classification of vibration signals of a single point cutting tool

(2011) M. Elangovan et al.   EXPERT SYSTEMS WITH APPLICATIONS

Tool wear estimation using an analytic fuzzy classifier and support vector machines

(2010) Danko Brezak et al.   JOURNAL OF INTELLIGENT MANUFACTURING

Support vector machines models for surface roughness prediction in CNC turning of AISI 304 austenitic stainless steel

(2010) Ulaş Çaydaş et al.   JOURNAL OF INTELLIGENT MANUFACTURING

Design of multisensor fusion-based tool condition monitoring system in end milling

(2009) Sohyung Cho et al.   INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY

Investigation of the cutting conditions in milling operations using image texture features

(2008) E S Gadelmawla et al.   PROCEEDINGS OF THE INSTITUTION OF MECHANICAL ENGINEERS PART B-JOURNAL OF ENGINEERING MANUFACTURE

State classification of CBN grinding with support vector machine

(2007) Neng-Hsin Chiu et al.   JOURNAL OF MATERIALS PROCESSING TECHNOLOGY

Evaluation of surface roughness based on monochromatic speckle correlation using image processing

(2007) B. Dhanasekar et al.   PRECISION ENGINEERING-JOURNAL OF THE INTERNATIONAL SOCIETIES FOR PRECISION ENGINEERING AND NANOTECHNOLOGY