An in-situ real-time tool condition monitoring system for intelligent machine tools

Abstract

As CNC machine tools evolve toward intelligence and precision, tool condition monitoring (TCM) becomes essential for ensuring machining quality, efficiency and cost reduction. To address the limitations of existing studies—such as single function, simplex algorithm and lack of integrated platforms—this paper develops an in-situ real-time TCM system. It integrates multi-source signal acquisition and visualization, rapid anomaly identification, online wear measurement and compensation, and machine tool communication. Hardware adopts the JYTEK PXIe platform for multi-channel force/vibration signal acquisition; Thunderbolt 4 ensures high-speed communication between the acquisition card and host computer, and the controller output board sends commands to the CNC system to form a monitoring-decision-execution closed loop. Software is built on WPF .NET 8 to realize data analysis, anomaly response, wear compensation and tool management. Experiments validate that the system fulfills all preset functions. The proposed system forms a full closed-loop chain from signal acquisition, condition recognition to wear compensation and machine communication, providing a deployable platform for intelligent machine tool monitoring with good engineering prospects.