In-Process Surface Roughness Estimation Model for Compliant Abrasive Belt Machining Process

Vigneashwara Pandiyan, Tegoeh Tjahjowidodo, Meena Periya Samy
2016 Procedia CIRP  
Surface roughness inspection in robotic abrasive belt machining process is an off-line operation which is time-consuming. An in-process multisensor integration technique comprising of force, accelerometer and acoustic emission sensor was developed to predict state of the surface roughness during machining. Time and frequency-domain features extracted from sensor signals were correlated with the corresponding surface roughness to train the Support vector machines (SVM's) in Matlab toolbox and a
more » ... tlab toolbox and a classification model was developed. Prediction accuracy of the classification model shows proposed in-process surface roughness recognition system can be integrated with abrasive belt machining process for capping lead-time and is reliable.
doi:10.1016/j.procir.2016.03.126 fatcat:3utwp7plozel3hw3sj5o5afxia