Autoregressive Modeling in Orthogonal Cutting of Glass Fiber Reinforced Composites

2차원 GFRC절삭에서 AR모델링에 관한 연구

  • Gi Heung Choi (Department of Mechanical Systems Engineering, Hansung University)
  • Published : 2001.03.01

Abstract

This study discusses frequency analysis based on autoregressive (AR) time series model, and process characterization in orthogonal cutting of a fiber-matrix composite materials. A sparsely distributed idealized composite material, namely a glass reinforced polyester (GFRP) was used as workpiece. Analysis method employs a force sensor and the signals from the sensor are processed using AR time series model. The resulting pattern vectors of AR coefficients are then passed to the feature extraction block. Inside the feature extraction block, only those features that are most sensitive to different types of cutting mechanisms are selected. The experimental correlations between the different chip formation mechanisms and AR model coefficients are established.