Condition monitoring of the feed drive system of a machine tool based on long-term operational modal analysis. (November 2019)

• Record Type: Journal Article
• Authors: Jia, Pingjia; Rong, Youmin; Huang, Yu
• Is Part Of: International journal of machine tools & manufacture. Volume 146(2019)
• Publication Date: 2019-11
• Subjects: Condition monitoring -- Life cycle assessment -- Feed drive system -- Operational modal analysis -- Machining process; Machine-tools -- Periodicals; Manufacturing processes -- Periodicals; Machines-outils -- Périodiques; Fabrication -- Périodiques; Electronic journals; 621.902
• DOI: 10.1016/j.ijmachtools.2019.103454
• Languages: English
• ISSNs: 0890-6955

Abstract

Abstract: High speed and high reliability are important characteristics and are part of the inevitable development trend in many machining production lines such as those in the automotive industry and electronic manufacturing. In high-speed machining, the linear axe feed drive system is an important component that moves the cutting tool and workpiece to their desired positions for part production. Because of the long amount of time or the high power continuous machining, gradual wear of the ball screw easily occurs, which will deteriorate its performance. However, due to time-varying factors during the machining process, such as the feeding speed, cutting force and table position, condition monitoring and health assessment of the feed drive system in the long-term running status are complicated. To solve this problem, the statistical characteristics of the dynamics of the feed drive system are introduced in this paper to develop a method to long-term condition monitoring and life cycle assessment. In this method, the modal parameters are estimated from the free-vibration response excited by the inertial force of the feed drive system during its high-speed acceleration or deceleration movement. Then, the long-term statistical characteristics of the dynamics are analysed, and their effects on the machining process are further studied. The spindle current in the milling process is monitored by the current sensor and evaluated using the sparse feature vector. The results show that the variance of the modal parameter increases with the wear of the screw, which will worsen the machining process fluctuations and significantly accelerate the wear rate of the cutting tool. Therefore, the health condition of the feed drive system of the machine tool can be accurately monitored by both the statistical characteristics of modal parameters and the sparse vectors of the cutting current. Highlights: Life cycle health assessment of the feed drive system is conducted using operational modal analysis. Product consistency is monitored by sparse feature vector similarity of the cutting current. Dynamics uncertainties can increase the fluctuations of the cutting process, and worsen the working condition.