Research On Vibration Characteristics Of Machining Center Spindle And Online Monitoring Method

With the development of intelligent machine tools,adding sensors to machine tools to expand their perception capabilities has become a general trend in machine tool design and manufacturing.The spindle system is a key component of the machine tool,and its work performance affects the overall machining accuracy of the machine tool.In this paper,by installing a vibration sensor on the spindle to monitor the spindle,the real-time monitoring of the spindle vibration characteristics during the machining process is realized.By designing the G code of the spindle self-checking,the machine tool response data is collected regularly,and the change process of the spindle vibration characteristics is continuously monitored.Finally,it was applied and verified on the intelligent high-speed five-axis machine tool HNC-200i/5a.The main contents of this paper are as follows:First,the preprocessing method and feature extraction method of the spindle vibration signal were studied.Aiming at the characteristics of noise interference in the vibration signal,the interference of the sensor wiring method on the vibration data and the influence of the trend item and noise on the integration process of acceleration signal were analyzed.The vibration signal is denoised and integrated by digital filtering and detrending.The feature extraction methods of vibration signal in time domain,frequency domain,and timefrequency domain were studied.By extracting the root mean square,kurtosis,power spectrum and wavelet packet decomposition energy distribution of vibration data,the vibration signal of the spindle was monitored.Second,the evaluation method of the vibration characteristics of the spindle in the nonmachining state was studied in this paper.The different speed was used as an excitation to analyze the vibration characteristics of the spindle.Vibration tests are carried out regularly to collect data on changes in the vibration characteristics of the spindle during the entire life cycle,and evaluate the characteristics of the spindle by the similarity evaluation method based on Euclidean distance.Third,the online monitoring method of spindle vibration signal is studied.The aluminum alloy milling test was carried out on a five-axis machining center.The machining state was divided into different levels according to the surface quality of the workpiece,and the characteristics of the vibration signal were analyzed.A two-level vibration monitoring model for the machining process is determined,and different characteristic thresholds are used to monitor the global and part of the G-code machining process separately.At last,on the secondary development platform of HNC9 system,a real-time monitoring system for spindle vibration status was developed based on the Linux environment and Qt.The acquisition of vibration data and internal data of the machine tool,time-frequency domain feature extraction,vibration status monitoring and spindle failure warning are realized.