Research On Mechanical Vibration Monitoring And Recognition System Of Motorized Spindle

As the core component of machine tools,the health status of motorized spindle directly affects the machining accuracy of parts and even the operation of machine tools.When the motorized spindle is hit due to improper operation,it may cause damage to the bearings or spindle inside the spindle.Therefore,building a collision protection system for motorized spindles can avoid serious economic losses caused by collisions due to human errors.The intelligent measurement and control system of motorized spindle can not only improve the processing quality of products and reduce energy consumption,but also avoid serious economic losses caused by human operation errors.When the motorized spindle is damaged due to collision or internal damage caused by long time high load work,the machining accuracy of the motorized spindle will be affected.Therefore,it is necessary to build the health identification system of the motorized spindle to timely understand the health status of the motorized spindle and maintain it.Aiming at the spindle collision protection and health identification of motorized spindle,this thesis studies a measurement and control system based on vibration signal integrated in motorized spindle,which is used to measurement and control motorized spindle.This thesis first analyzes and studies the dynamic characteristics of the motorized spindle.The spindle system and the structural characteristics of the spindle are introduced,and the dynamic characteristics of the spindle are analyzed using Workbench based on the spindle structure.The influence of different conditions of motorized spindle on vibration time domain signal is discussed.The vibration of motorized spindle in various states is simulated and the relevant data are obtained.Based on the spindle collision vibration signal of motorized spindle,a monitoring method of spindle collision is proposed.Aiming at the problem of high timeliness requirement for collision response and avoidance,the timeliness of identification of spindle collision parameters was analyzed.By comparing the recognition efficiency of acceleration signal and current signal through experimental data,the experimental results show that the current signal has a delay of about 35 ms relative to acceleration vibration signal.By establishing transfer function model,the influence of motorized spindle speed on vibration was analyzed,and a set of collision protection method was designed by using moving average value algorithm.Based on the characteristics of vibration signals,a method of health status identification of motorized spindle is proposed in this thesis.In view of the complex practical working environment of motorized spindle,a fault detection method is proposed.The main steps are to extract the time domain characteristics,frequency domain characteristics and time-frequency domain characteristics of motorized spindle vibration signal,and screen the characteristic values.The Generalized Regression Neural Network(GRNN)was used to identify the motorized spindle under different health conditions,and the effectiveness of the proposed method was verified.This study establishes and verifies the motorized spindle monitoring and recognition system.According to the functional requirements of the motorized spindle monitoring and recognition system,the hardware for building the system is selected,and the system program is written and the communication between the data is completed,and the mechanical vibration monitoring and recognition system of motorized spindle is built..Motorized spindle knock experiment and motorized spindle fault data identification experiment verify the timeliness of the motorized spindle collision monitoring method and the effectiveness of the motorized spindle health status identification method.