Digital Twin Enabled Flight Control System Testing: Design, Development, and Implementation

IF 6.4 2区 计算机科学 Q1 AUTOMATION & CONTROL SYSTEMS IEEE Transactions on Automation Science and Engineering Pub Date : 2025-01-22 DOI:10.1109/TASE.2025.3532632
Cheng Ren;Jiaxin Xu;Cailian Chen;Shanying Zhu;Yehan Ma;Xinping Guan
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Abstract

Flight control system testing (FCST) is one of the most important process to check whether flight control surfaces can operate properly according to commands during aircraft assembly. Traditional testing method relies heavily on manual labor, leading to low efficiency and inconsistent quality. In this paper, we apply digital twin (DT) technology to the FCST process for the first time. We firstly design an architecture of DT-enabled FCST including four layers to support further development. Then, we present a triangular mesh alignment-based angle measurement (TMA-AM) algorithm to efficiently collect deflection angle data for DT-enabled FCST. Extensive experiments conducted on a aircraft wing subassembly platform show that the TMA-AM algorithm achieves an average angular measurement error of less than 0.1°, outperforming existing methods. Moreover, we develop a virtual experimental platform named DT-FCST aligned with a real aircraft wing subassembly platform. In addition, TMA-AM algorithm is integrated with the DT-FCST platform. By integrating real-time data from the cockpit, real-time physical-virtual interaction of aircraft control sticks and flight control surfaces are achieved, ensuring consistency between physical and virtual movements. The integration of DT technology with the TMA-AM algorithm enables real-time synchronization, monitoring, and unified data management, significantly enhancing the efficiency and accuracy of the FCST. Note to Practitioners—To address the inefficiencies and low monitoring quality associated with traditional manual testing methods in flight control system testing (FCST), we firstly introduce digital twin (DT) technology to this process. To support effective and accurate measurement during the FCST, we propose a vision-based method tailored to accurately measure deflection angles of flight control surfaces. This method replaces manual measurements with a non-contact approach, significantly improving measurement accuracy and efficiency. We provide a detailed description of the construction process of the DT-FCST platform including requirement analysis, DT model construction, and on-site experiments. This DT-based approach achieves real-time synchronization between virtual and physical testing processes, enhancing monitoring quality and overall testing effectiveness. Specifically, it can achieve a 90% reduction in the number of operators and shorten the single testing time to 16.7% of the traditional testing method.
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数字孪生飞行控制系统测试:设计、开发和实现
飞控系统测试(FCST)是飞机装配过程中检验飞控面是否能按指令正常工作的重要过程之一。传统的检测方法严重依赖人工,导致检测效率低、质量不稳定。本文首次将数字孪生(DT)技术应用于fst工艺。我们首先设计了一个支持dt的FCST架构,包括四层,以支持进一步的开发。然后,我们提出了一种基于三角网格对准的角度测量(TMA-AM)算法,以有效地收集DT-enabled FCST的偏转角度数据。在飞机机翼组件平台上进行的大量实验表明,TMA-AM算法的平均角度测量误差小于0.1°,优于现有方法。此外,我们还开发了一个虚拟实验平台DT-FCST,该平台与真实的飞机机翼组件平台相结合。此外,TMA-AM算法与DT-FCST平台集成。通过集成来自驾驶舱的实时数据,实现了飞机控制杆和飞行控制面的实时物理-虚拟交互,确保了物理和虚拟运动之间的一致性。DT技术与TMA-AM算法的集成,实现了实时同步、监控和统一数据管理,显著提高了FCST的效率和准确性。从业人员注意:为了解决飞行控制系统测试(FCST)中传统手工测试方法的低效率和低监测质量问题,我们首先将数字孪生(DT)技术引入该过程。为了支持在FCST过程中有效和准确的测量,我们提出了一种基于视觉的方法来精确测量飞行控制面偏转角。该方法用非接触式测量方法代替人工测量,显著提高了测量精度和效率。详细描述了DT- fcst平台的构建过程,包括需求分析、DT模型构建和现场实验。这种基于dt的方法实现了虚拟和物理测试过程的实时同步,提高了监控质量和整体测试效率。具体来说,它可以减少90%的操作人员,将单次测试时间缩短到传统测试方法的16.7%。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
IEEE Transactions on Automation Science and Engineering
IEEE Transactions on Automation Science and Engineering 工程技术-自动化与控制系统
CiteScore
12.50
自引率
14.30%
发文量
404
审稿时长
3.0 months
期刊介绍: The IEEE Transactions on Automation Science and Engineering (T-ASE) publishes fundamental papers on Automation, emphasizing scientific results that advance efficiency, quality, productivity, and reliability. T-ASE encourages interdisciplinary approaches from computer science, control systems, electrical engineering, mathematics, mechanical engineering, operations research, and other fields. T-ASE welcomes results relevant to industries such as agriculture, biotechnology, healthcare, home automation, maintenance, manufacturing, pharmaceuticals, retail, security, service, supply chains, and transportation. T-ASE addresses a research community willing to integrate knowledge across disciplines and industries. For this purpose, each paper includes a Note to Practitioners that summarizes how its results can be applied or how they might be extended to apply in practice.
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