Online Monitoring System Of Spindle Based On Wireless Sensor

The spindle performance has a great influence on the machining accuracy and stability of the machining center.While the bearing is one of the most vulnerable broken parts of the spindle,so the operating statement of the bearing determines the operating statement of the spindle.Through monitoring the conditions of the motorized spindle,it is beneficial to forecast its defects and improve its reliability.At the same time,with the rapid development of wireless technology,the advanced wireless technology can adapt to the complex production environment at the scene and shortten development cycle.This thesis mainly develops a wireless monitoring system for the motorized spindle,which is based on this platform of LabVIEW software and has a high engineering application value.This thesis regards the domestic motorized spindle as the research object in cmv-1100A machine tool,the faulty rate is highest after analyzing the fault mechanism of the motorized spindle.Due to the limitation of experimental conditions,the estimated value is calculated by the empirical formula when the bearing parameters are unknown.According to the impact component of the early fault of the bearing,it is determined that the envelope spectrum based on fast kurtogram extract the fault feature.On the basis of Lab VIEW platform,the overall design of the system is put forward and the hardware parameters are illustrated in detail.Selecting the wireless sensor and transceiver module with low anti-interference ability and low frame rate.Hardware communication module is completed and expresses the system interface,function and program code.According to the comparison of the experimental results,the fast kurtogram spectrum algorithm is used to locate the filtering center frequency and the frequency bandwidth.Comparing with the traditional envelope spectrum,the square envelope spectrum of the cage characteristic frequency and the rolling element characteristic are more obvious.The results indicates that the bearing has early damage and verify that the system can accurately monitor the state of the spindle and fault diagnosis.