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基于智能柔顺控制的航空叶片表面机器人超声强化工艺优化

Process Optimization for Robotic Ultrasonic Strengthening of Aviation Blade Surfaces Based on Intelligent Compliance Control.

作者信息

Fang Shanxiang, Zhu Yukai, Zhang Qinjian, Zhang Yong

机构信息

Department of Strategic and Advanced Interdisciplinary Research, Peng Cheng Laboratory, Shenzhen 518055, China.

Department of Mechanical Engineering, National University of Singapore, Singapore 117575, Singapore.

出版信息

Micromachines (Basel). 2023 Oct 10;14(10):1920. doi: 10.3390/mi14101920.

Abstract

In order to enhance the automation level and achieve high precision in the ultrasonic strengthening of aviation blade surfaces, this study focuses on investigating the intelligent control strategy and optimizing the machining parameters for robotic ultrasonic surface strengthening. By designing an intelligent compliance control method, the end-effector can achieve the compliant output of contact force. The fuzzy PID control method is used to optimize the regulation performance of the compliant force control system. This compliance control strategy enables the optimization of the compliance device, effectively improving the static and dynamic characteristics of the compliance controller. Based on this, an experimental method (RSM) is designed to analyze the interaction effects of contact force, feed rate, and repetition times on the surface quality of the blade. The optimal combination of robotic strengthening parameters is determined, providing a practical reference for the application of robotic compliance control in the ultrasonic strengthening of aviation blade surfaces.

摘要

为了提高航空叶片表面超声强化的自动化水平并实现高精度,本研究着重探究智能控制策略并优化机器人超声表面强化的加工参数。通过设计一种智能柔顺控制方法,末端执行器能够实现接触力的柔顺输出。采用模糊PID控制方法优化柔顺力控制系统的调节性能。这种柔顺控制策略能够优化柔顺装置,有效改善柔顺控制器的静态和动态特性。基于此,设计了一种实验方法(响应曲面法)来分析接触力、进给速度和重复次数对叶片表面质量的交互作用。确定了机器人强化参数的最优组合,为机器人柔顺控制在航空叶片表面超声强化中的应用提供了实际参考。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f6e2/10609334/7a4a62b613a2/micromachines-14-01920-g0A1a.jpg

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