Stage identification and process optimization for fast drilling EDM of film cooling holes using KBSI method

IF 4.2 2区 工程技术 Q2 ENGINEERING, MANUFACTURING Advances in Manufacturing Pub Date : 2023-03-01 DOI:10.1007/s40436-022-00434-w
Jian Wang, Xue-Cheng Xi, Ya-Ou Zhang, Fu-Chun Zhao, Wan-Sheng Zhao
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引用次数: 1

Abstract

Fast drilling electrical discharge machining (EDM) is widely used in the manufacture of film cooling holes of turbine blades. However, due to the various hole orientations and severe electrode wear, it is relatively intricate to accurately and timely identify the critical moments such as breakout, hole completion in the drilling process, and adjust the machining strategy properly. Existing breakout detection and hole completion determination methods are not suitable for the high-efficiency and fully automatic production of film cooling holes, for they almost all depend on preset thresholds or training data and become less appropriate when machining condition changes. As the breakout and hole completion detection problems can be abstracted to an online stage identification problem, in this paper, a kurtosis-based stage identification (KBSI) method, which uses a novel normalized kurtosis to denote the recent changing trends of gap voltage signals, is developed for online stage identification. The identification accuracy and generalization ability of the KBSI method have been verified in various machining conditions. To improve the overall machining efficiency, the influence of servo control parameters on machining efficiency of each machining stage was analyzed experimentally, and a new stage-wise adaptive control strategy was then proposed to dynamically adjust the servo control parameters according to the online identification results. The performance of the new strategy is evaluated by drilling film cooling holes at different hole orientations. Experimental results show that with the new control strategy, machining efficiency and the machining quality can be significantly improved.

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基于KBSI方法的薄膜冷却孔快速电火花加工阶段识别与工艺优化
快速钻孔电火花加工(EDM)广泛应用于涡轮叶片气膜冷却孔的制造。然而,由于孔取向多样,电极磨损严重,在钻孔过程中准确、及时地识别出漏孔、完孔等关键时刻,并适当调整加工策略是比较复杂的。现有的漏孔检测和完孔确定方法,几乎都依赖于预设的阈值或训练数据,当加工条件发生变化时,就不太适用于膜冷孔的高效全自动生产。由于突破和完井检测问题可以抽象为在线分段识别问题,本文提出了一种基于峰度的分段识别方法(KBSI),该方法利用一种新的归一化峰度来表示间隙电压信号的近期变化趋势,用于在线分段识别。在各种加工条件下验证了KBSI方法的识别精度和泛化能力。为了提高整体加工效率,实验分析了伺服控制参数对各加工阶段加工效率的影响,提出了一种新的阶段自适应控制策略,根据在线辨识结果动态调整伺服控制参数。通过在不同井眼方位钻膜冷却孔,对新策略的性能进行了评价。实验结果表明,该控制策略能显著提高加工效率和加工质量。
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来源期刊
Advances in Manufacturing
Advances in Manufacturing Materials Science-Polymers and Plastics
CiteScore
9.10
自引率
3.80%
发文量
274
期刊介绍: As an innovative, fundamental and scientific journal, Advances in Manufacturing aims to describe the latest regional and global research results and forefront developments in advanced manufacturing field. As such, it serves as an international platform for academic exchange between experts, scholars and researchers in this field. All articles in Advances in Manufacturing are peer reviewed. Respected scholars from the fields of advanced manufacturing fields will be invited to write some comments. We also encourage and give priority to research papers that have made major breakthroughs or innovations in the fundamental theory. The targeted fields include: manufacturing automation, mechatronics and robotics, precision manufacturing and control, micro-nano-manufacturing, green manufacturing, design in manufacturing, metallic and nonmetallic materials in manufacturing, metallurgical process, etc. The forms of articles include (but not limited to): academic articles, research reports, and general reviews.
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