Drilling task planning and offline programming of a robotic multi-spindle drilling system for aero-engine nacelle acoustic liners

IF 9.1 1区 计算机科学 Q1 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS
Fanqiang Kong , Biao Mei , Yun Fu , Yongtai Yang , Weidong Zhu
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引用次数: 0

Abstract

Aero-engine nacelle acoustic liners are complex curved surface subassemblies with tens of thousands of dense acoustic holes for noise reduction. Traditional robotic drilling systems with a single spindle and conventional teaching programming cannot meet the high-quality and high-efficiency drilling requirements for nacelle acoustic liners. This paper developed a novel robotic multi-spindle drilling system, which integrates standard industrial robots with a multi-spindle drilling end-effector to drill acoustic holes on an acoustic liner. The task planning strategy and offline programming method are investigated for the robotic multi-spindle drilling of the acoustic liner. A dedicated offline programming software capable of quickly generating robotic machining programs has been designed and developed. A precise acoustic hole arrangement applicable to curved drilling zones is demonstrated. The virtual surrogate hole is introduced to target the array layout of the developed end-effector's multiple spindles. A virtual surrogate hole generation method is proposed based on the minimum mutually exclusive set cover and the greedy algorithm. After that, a virtual surrogate hole layout optimization method is developed using an adaptive genetic annealing algorithm. Then, the frame chain is constructed as the kinematic foundation in robotic multi-spindle drilling of a nacelle acoustic liner. The drilling pose planning of the multi-spindle end-effector based on normal vectors and coordinates of acoustic hole points covered by virtual surrogate holes is explored. And a multi-spindle drilling path planning algorithm is developed using the genetic algorithm. To drill the aero-engine nacelle of a large aircraft, an offline programming software for robotic multi-spindle drilling of the nacelle acoustic liner is developed by integrating the methods above. A case study of multi-spindle drilling task planning of a nacelle acoustic liner is carried out. The case study results indicate that, compared to traditional single-spindle robotic drilling systems, the developed multi-spindle drilling system increases drilling efficiency by approximately 347 %. Using the proposed multi-spindle drilling path optimization algorithm, the drilling path has been shortened by 84.8 %. These results validate the effectiveness of the proposed series of drilling task planning methods and the developed offline programming software, which significantly enhance drilling efficiency while meeting the technical requirements for drilling acoustic holes on the acoustic liner.
用于航空发动机短舱隔音衬垫的机器人多主轴钻孔系统的钻孔任务规划和离线编程
航空发动机短舱隔音衬垫是一种复杂的曲面组件,上面有数以万计的密集隔音孔,用于降低噪音。传统的单主轴机器人钻孔系统和传统的示教编程无法满足短舱隔音衬垫高质量、高效率的钻孔要求。本文开发了一种新型机器人多主轴钻孔系统,它将标准工业机器人与多主轴钻孔末端执行器集成在一起,在隔音衬垫上钻孔。研究了声学衬垫机器人多主轴钻孔的任务规划策略和离线编程方法。设计并开发了一种专用离线编程软件,能够快速生成机器人加工程序。演示了适用于弯曲钻孔区域的精确声波孔布置。引入了虚拟代用孔,以针对所开发的末端执行器多主轴的阵列布局。基于最小互斥集覆盖和贪婪算法,提出了一种虚拟代用孔生成方法。之后,利用自适应遗传退火算法开发了一种虚拟代用孔布局优化方法。然后,构建了框架链,作为机舱声衬垫机器人多主轴钻孔的运动学基础。根据虚拟代用孔覆盖的声学孔点的法向量和坐标,探索了多主轴末端执行器的钻孔姿势规划。并利用遗传算法开发了一种多主轴钻孔路径规划算法。针对大型飞机航空发动机短舱的钻孔,综合上述方法开发了短舱声学衬垫机器人多主轴钻孔离线编程软件。对短舱隔音衬垫的多主轴钻孔任务规划进行了案例研究。案例研究结果表明,与传统的单主轴机器人钻孔系统相比,所开发的多主轴钻孔系统可将钻孔效率提高约 347%。利用所提出的多主轴钻孔路径优化算法,钻孔路径缩短了 84.8%。这些结果验证了所提出的一系列钻孔任务规划方法和所开发的离线编程软件的有效性,在满足声学衬垫上声学孔钻孔技术要求的同时,显著提高了钻孔效率。
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来源期刊
Robotics and Computer-integrated Manufacturing
Robotics and Computer-integrated Manufacturing 工程技术-工程:制造
CiteScore
24.10
自引率
13.50%
发文量
160
审稿时长
50 days
期刊介绍: The journal, Robotics and Computer-Integrated Manufacturing, focuses on sharing research applications that contribute to the development of new or enhanced robotics, manufacturing technologies, and innovative manufacturing strategies that are relevant to industry. Papers that combine theory and experimental validation are preferred, while review papers on current robotics and manufacturing issues are also considered. However, papers on traditional machining processes, modeling and simulation, supply chain management, and resource optimization are generally not within the scope of the journal, as there are more appropriate journals for these topics. Similarly, papers that are overly theoretical or mathematical will be directed to other suitable journals. The journal welcomes original papers in areas such as industrial robotics, human-robot collaboration in manufacturing, cloud-based manufacturing, cyber-physical production systems, big data analytics in manufacturing, smart mechatronics, machine learning, adaptive and sustainable manufacturing, and other fields involving unique manufacturing technologies.
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