Milling force coefficients-based tool wear monitoring for variable parameter milling

Tool wear is an important factor that affects the quality and machining accuracy of aeronautical structural parts in milling process. It essential to monitor tool titanium alloy machining. The traditional features such as root mean square (RMS), kurtosis, wavelet packet energy spectrum are related not only status but also parameters, thus monitoring under fixed parameters. This paper proposes a new method online using force coefficients. instantaneous cutting model used extract coefficients which independent principal component analysis (PCA) algorithm fuse Furthermore, support vector machine (SVM) states. Experiments with different parameters were conducted verify effectiveness this for monitoring. results show compared features, dependent on can effectively transition point cutters from normal severe (tool failure).