The article delves into real-time data processing methods for monitoring tool wear in computer numerical control (CNC) machine tools, with the aim of improving the overall accuracy of the tool monitoring system. The article also systematically reviews several mainstream data processing methods, including power spectrum analysis, wavelet transform, artificial neural network technology, and multi-sensor information fusion technology. Although these methods have their own advantages and disadvantages, a single method often fails to achieve ideal results when dealing with data in complex and changing processing environments. To overcome this challenge, this paper proposes a multi-sensor information fusion data processing method based on hybrid intelligent algorithms

computer numerical control machine tools  /  tool wear and tear  /  data processing  /  intelligent manufacturing  /  multi sensor fusion