弱刚度刀具微细顺铣加工误差快速预测方法
By simplifying the stiffness model of the micro-milling cutter and introducing the concept of equivalent elastic modulus, and combining data from laser sensors and force gauges, the error of micro-climb milling can be predicted quickly and accurately, solving the problem of low computational efficiency in existing technologies and achieving efficient error prediction.
CN116384006BActive Publication Date: 2026-07-17NORTHWESTERN POLYTECHNICAL UNIV
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Patents(China)
- Current Assignee / Owner
- NORTHWESTERN POLYTECHNICAL UNIV
- Filing Date
- 2023-04-15
- Publication Date
- 2026-07-17
AI Technical Summary
Technical Problem
Existing technologies have low computational efficiency in predicting errors in micro-climb milling with weak stiffness tools, making it difficult to predict errors quickly and accurately.
Method used
The stiffness model of the micro-milling cutter is simplified by adopting the concept of equivalent elastic modulus. Through a simplified iterative algorithm, combined with material accumulation and work hardening phenomena, machining errors are quickly predicted. Laser sensors and force gauges are used to measure tool deformation and force data.
Benefits of technology
Without compromising accuracy, it significantly improves the efficiency of error prediction in micro-climb milling, simplifies the theoretical modeling process, and shortens the calculation time.
✦ Generated by Eureka AI based on patent content.
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Figure CN116384006B_ABST
Abstract
本发明涉及一种弱刚度刀具微细顺铣加工误差快速预测方法，属于机械加工技术领域。该方法引入了等效弹性模量概念，在保证精度前提下，大幅简化了微铣刀刚度模型；同时对材料堆积与加工硬化现象进行了近似化处理，大幅简化了微细顺铣的理论建模过程。与所给文献相比，本方法避免了复杂的循环与迭代算法，可有效提高弱刚度刀具微细顺铣加工误差的预测效率。
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