Approximation Model Development and Dynamic Characteristic Analysis Based on Spindle Position of Machining Center.

Area of Science:

• Mechanical Engineering
• Vibration Analysis
• Machine Tool Dynamics

Background:

• Accurate evaluation of machine tool spindle dynamic characteristics is essential for precision manufacturing.
• Understanding resonant frequencies and dynamic stiffness across all spindle positions is critical for performance optimization.
• Existing methods may lack comprehensive accuracy in predicting these dynamic properties.

Purpose of the Study:

• To evaluate the dynamic characteristics of a machine tool's main spindle at various positions.
• To develop and validate an approximation model for predicting resonant frequency and dynamic stiffness.
• To assess the accuracy of different modeling techniques, including kriging and polynomial regression.

Main Methods:

• A full factorial design was employed to select experimental points for vibration testing.
• Vibration tests were conducted to measure dynamic characteristics across the spindle.
• Regression and interpolation methods (kriging, polynomial regression) were used to create and evaluate approximation models.

Main Results:

• Resonant frequencies were found to be distributed between approximately 236 Hz and 242 Hz.
• The kriging method achieved approximately 89% accuracy for resonant frequency prediction.
• Polynomial regression demonstrated the highest accuracy for dynamic stiffness at 81%.
• Model verification at additional points showed maximum errors of 1.6% for resonant frequency and 7.1% for dynamic stiffness.

Conclusions:

• The developed approximation models provide reliable predictions of machine tool spindle dynamic characteristics.
• The kriging and polynomial regression methods offer valuable tools for understanding spindle behavior.
• The study validates the models' accuracy, supporting their use in machine tool design and analysis.