叶片型面机器人磨抛加工机理及工艺技术研究

The proposal establishes a robot grinding and polishing system for blade surface based on the mixed effects of time-varying pressure-temperature (TVPT), and systematically studies the robot belt grinding and polishing techniques both from the theoretical and experimental aspects. Combined with the contact kinematics theory and belt grinding and polishing process, an optimization algorithm of arc length fully considering the curved local curvature constraints is deduced, and then the cutter location point and surface methodology vector are obtained for the workpiece attitude control. On this basis, driven by the objective physical properties and manufacturing quality of the blade, the grinding and polishing pressure model on the intake and exhaust side of blade and the temperature distribution model in the local minimal region are established to characterize the blade surface accuracy. These two models are based on the low-friction guide and small contact force control. Meanwhile, considering the significant belt abrasive wear in grinding and polishing, the traditional constant pressure grinding and polishing is converted into time-varying pressure grinding and polishing, for the establishment of an optimization model which directly characterizing the belt thickness variation, and then controlling the removal margin by pressure control aims to achieve the blade surface correction. Finally, based on the I-kaz method of signal processing, a mapping model between the grinding and polishing pressure - temperature mixed-signal and the belt wear volume is built, which can be used for the real-time online monitoring of the belt - workpiece functional surface morphology, eventually establishes and develops a complete set of key technology, theoretic method and technology program for robot grinding and polishing.

本项目建立一套基于时变压力-温度(TVPT)混合影响的叶片型面机器人磨抛加工系统，从理论和实验两方面研究机器人砂带磨抛加工技术。结合接触运动学理论和砂带磨抛工艺，提出一种考虑曲面局部曲率约束条件问题的弧长优化方法，进而得到用于工件姿态控制的刀位点及曲面法矢量。在此基础上，以叶片的目标物理性能与制造品质要求为驱动，建立基于低摩擦导向与小接触力控制的叶片进排气边磨抛压力模型和局部狭小区域温度分布模型来表征叶片型面精度。同时，考虑磨抛加工中显著的砂带磨粒磨损影响，将传统恒压力磨抛问题转换为时变压力磨抛，建立直接表征砂带厚度变化的优化模型，并通过压力控制去除余量来实现对叶片型面的修正。最后，基于信号处理I-kaz方法，建立磨抛压力-温度混合信号与砂带磨损量之间的映射模型，实现对砂带-工件功能表面形貌的实时在线监控，最终建立和发展一整套面向叶片机器人磨抛的关键技术、理论方法和工艺方案。

本项目以汽轮机叶片和航空发动机叶片为研究对象，从接触运动学驱动的磨抛机器人离线编程、质量与效率驱动的砂带磨抛加工、功能表面形貌驱动的砂带磨损在线监控三个方面展开系统而摄入的基础研究，重点揭示复杂叶片曲面磨抛路径优化算法、装备-工艺过程交互作用规律以及砂带-工件表面微形貌可控原理，创立叶片型面高品质制造的机器人磨抛新原理、新方法和新工艺。在项目执行期间，完成了对叶片机器人砂带磨抛路径优化算法、轨迹规划、加工仿真、加工工艺优化等研究，并开展了大量叶片机器人磨抛加工试验。相比传统人工磨抛方式，机器人磨抛后的叶片型面精度从±0.15mm提高到±0.06mm，表面粗糙度从Ra0.8提升到Ra0.4。研究成果应用于企业批量生产，极大地提升叶片加工质量、加工一致性以及生产效率，并显著改善作业环境，将工人从恶劣的环境中解放出来，体现了智能制造的特点。