Artificial neural network for screw life prediction

The life change of the screw in High-end CNC machine tool in the process has some features such as non-linear, dynamic and uncertainty. A screw online life prediction system was designed to monitor the performance of lead screw by vibration sensors and temperature sensors which installed at different locations of Lead Screw Pair and reflected the trend of changes of different processing conditions, lifting wavelet transform was used to extract the most sensitive characteristics of screw performance. RBF neural network was used to build the non-linear relationship between screw vibration signal changes and screw life. Eventually constructed screw life prediction model based on RBF neural network bring into effect of effective assessment of residual life of lead screw. The results show that the performance degradation model can predict the remaining life of screw effectively.