| In the past few decades,industrial robots have been widely used for various purposes to develop flexible and efficient manufacturing processes,such as material handling,painting,and welding.In recent years,the application and installation of industrial robots in China have been continuously increasing,consistently occupying a leading position in the world.However,as a high value-added application,the application of robot processing systems still has significant limitations,mainly due to the low stiffness of robots,which can cause vibration,resulting in poor quality of robot processed products and low production efficiency.Due to the low stiffness and coupling structure of industrial robots,regenerative effects and modal coupling effects are the main factors contributing to the formation of robot milling chatter.How to monitor and effectively control the occurrence of robot milling chatter in real-time remains a challenging task.Therefore,in response to the problem of chatter in robot milling,this article mainly conducts research on online chatter identification and adaptive chatter suppression methods for robot milling.Firstly,the basic theory of robot based on COMAU SMART5 NJ 165-3.0 six axis industrial robot is analyzed,including the basic structural parameters and coordinate system of the robot used,pose description and D-H kinematics modeling,drive motor modeling and dynamics modeling,etc.The MATLAB simulation model is established,which provides a theoretical basis for robot trajectory planning,inverse dynamics for joint feedforward torque,joint motion control and other research.After that,in response to the issue of real-time monitoring of robot milling chatter occurrence,this article establishes an online chatter identification method for robot milling.The research on online chatter identification methods includes:designing an IIR notch filter based on variable quality factor to solve the real-time and effective problems in signal filtering processing;A signal processing method based on self convolution has been proposed,which can denoise and enhance the chatter characteristics of the signal;A signal adaptive variational mode decomposition method for calculating frequency norm has been established,which can decompose the signal into sub functions with different center frequencies,facilitating the extraction of chatter features;A new energy peak factor considering signal frequency has been constructed as the characteristic value for chatter identification,which can distinguish between chatter signals and stable signals based on threshold indicators;Efficient data sampling based on rolling window sampling strategy.At the same time,simulation experiments,modal hammering experiments,and robot milling experiments were conducted to verify the effectiveness and superiority of the online chatter identification method.Finally,in order to address the issue of chatter suppression after chatter identification,this paper conducts research on a control strategy based on variable feed rate to suppress chatter,including:establishing an average cutting force model and conducting milling force coefficient identification experiments to simulate milling forces;Design a fuzzy adaptive PID controller for six independent joints of the robot,and conduct simulation verification of the controller performance;A variable feed rate chatter suppression method triggered by the characteristic value threshold of chatter recognition has been established.At the same time as the research,a Simulink simulation platform was built,and combined with the online chatter identification method proposed in this paper,the simulation of robot milling chatter suppression was carried out,verifying the effectiveness of the identification method for robot milling chatter and the variable feed rate chatter suppression method proposed in this paper. |
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