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A Condition Monitoring Method of Hydraulic Gear Pumps Based on Multilevel Mechanism-Data Fusion 基于多级机制-数据融合的液压齿轮泵状态监测方法
IF 1.4 4区 工程技术 Q2 Engineering Pub Date : 2024-04-25 DOI: 10.1155/2024/5587168
Linlin Ren, Hongbo Ma, Wen Zhou, Shuhan Huang, Xueying Wu
Pumps are important components in aviation fuel hydraulic systems, and thanks to the development of sensor technology and industrial intelligence technology, it is possible to achieve efficient state monitoring of pumps. However, when data quality is poor or the amount of data is small, a single data-driven model may not be able to meet diagnostic accuracy. A condition monitoring method for hydraulic gear pumps based on mechanism-data fusion is proposed. The method combines a mechanism model based on the volumetric efficiency formula with a data-driven model based on vibration signals. First, the parameters of volumetric efficiency are solved by fitting the pressure–flow relationship. Subsequently, a multichannel fusion and multikernel function-weighted ensemble support vector classification (MCMK-SVC) is developed, to establish a data-driven model. Finally, through data-level fusion, feature-level fusion, and decision-level fusion, a condition monitoring model based on mechanism-data fusion is built. Experimental verification shows that the accuracy of the three levels of fusion models exceeds 96.9%. Compared to the single data-driven model or other traditional data-driven models, the accuracy of the proposed method has improved by 3% to 33%, demonstrating the effectiveness of the mechanism-data fusion model.
泵是航空燃油液压系统中的重要组件,由于传感器技术和工业智能技术的发展,实现泵的高效状态监测成为可能。然而,当数据质量较差或数据量较小时,单一的数据驱动模型可能无法满足诊断精度的要求。本文提出了一种基于机构-数据融合的液压齿轮泵状态监测方法。该方法将基于容积效率公式的机构模型与基于振动信号的数据驱动模型相结合。首先,通过拟合压力-流量关系求解容积效率参数。随后,开发了多通道融合和多核函数加权集合支持向量分类(MCMK-SVC),以建立数据驱动模型。最后,通过数据级融合、特征级融合和决策级融合,建立了基于机制-数据融合的状态监测模型。实验验证表明,三级融合模型的准确率超过 96.9%。与单一数据驱动模型或其他传统数据驱动模型相比,所提方法的准确率提高了 3% 至 33%,证明了机制-数据融合模型的有效性。
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引用次数: 0
Multidisciplinary Design Optimization of Reentry-Powered Hypersonic Vehicles Based on Surrogate Model 基于代理模型的再入动力高超音速飞行器多学科优化设计
IF 1.4 4区 工程技术 Q2 Engineering Pub Date : 2024-04-20 DOI: 10.1155/2024/5557153
Shoudong Ma, Yuxin Yang, Yesi Chen, Hua Yang, Weifang Chen
Two problems exist in the study of the trajectory optimization problem of powered hypersonic gliding vehicles (HGVs) due to insufficient consideration of the overall design constraints as well as the strong couplings among relevant disciplines: (1) the engine and thrust models are not compatible with the existing HGV; (2) configuration parameters of the HGV are not included as design variables during trajectory optimization (i.e., propulsion discipline is decoupled in the process of the HGV configuration design), thus failing to fully explore the effect of power to improve the performance of the HGV. Therefore, the application of multidisciplinary design optimization (MDO) in the overall design of powered HGVs should be investigated. First, a MDO task analysis and a multidisciplinary model analysis are carried out for the powered HGV. Second, the multidisciplinary optimization problem is defined, and the couplings between disciplines of the powered HGV are analyzed so that a six-discipline model is established that is suitable for the overall design process, including the parameterized configuration geometry, aerodynamics, propulsion, mass properties, trajectory, and aerodynamic heat/thermal protection system (TPS). Finally, a surrogate model is used to replace the time-consuming accurate model, and numerical optimization examples verify the effectiveness of the method. The optimization results show that the method has a good convergence speed, which increases the gliding range of the optimized vehicle by 8.37%. In addition, by decoupling the propulsion discipline, the validation shows that the coupled propulsion discipline during the overall design can increase the range of the powered HGV by 3.87% compared to the powered HGV optimized with the decoupled propulsion discipline. The work done in this paper provides a new design idea for the overall design of a powered HGV.
在动力高超声速滑翔飞行器(HGV)的轨迹优化问题研究中,由于对总体设计约束条件考虑不足以及相关学科间的强耦合性,存在两个问题:(1)发动机和推力模型与现有HGV不兼容;(2)轨迹优化过程中未将HGV的构型参数作为设计变量(即在HGV构型设计过程中推进学科被解耦了),从而无法充分挖掘动力对提高HGV性能的作用。因此,应研究多学科设计优化(MDO)在动力重型卡车总体设计中的应用。首先,对动力重型卡车进行了 MDO 任务分析和多学科模型分析。其次,定义了多学科优化问题,并分析了动力桓车各学科之间的耦合关系,从而建立了适合总体设计过程的六学科模型,包括参数化构型几何、空气动力学、推进、质量特性、轨迹和空气动力热/热保护系统(TPS)。最后,使用代用模型取代耗时的精确模型,并通过数值优化实例验证了该方法的有效性。优化结果表明,该方法收敛速度快,优化后飞行器的滑行距离增加了 8.37%。此外,通过解耦推进学科,验证结果表明在整体设计过程中耦合推进学科可使动力重型车辆的续航里程比采用解耦推进学科优化的动力重型车辆增加 3.87%。本文所做的工作为动力重型车辆的总体设计提供了一种新的设计思路。
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引用次数: 0
Grouping Formation and Obstacle Avoidance Control of UAV Swarm Based on Synchronous DMPC 基于同步 DMPC 的无人机群编队和避障控制
IF 1.4 4区 工程技术 Q2 Engineering Pub Date : 2024-04-12 DOI: 10.1155/2024/4934194
Yunfeng He, Xianjun Shi, Jianhua Lu, Chaolun Zhao, Guorong Zhao
This paper focuses on the grouping formation control problem of unmanned aerial vehicle (UAV) swarms in obstacle environments. A grouping formation and obstacle avoidance control algorithm based on synchronous distributed model predictive control (DMPC) is proposed. First, the UAV swarm is divided into several groups horizontally and into a leader layer and a follower layer vertically. Second, tracking is regarded as the objective, and collision avoidance and obstacle avoidance are considered as constraints. By combining the velocity obstacle method with synchronous DMPC and providing corresponding terminal components, a leader layer control law is designed. The control law can enable the UAV swarm to track the target while avoiding collisions and dynamic obstacles. Then, considering the formation maintenance term, based on different priorities, member-level obstacle avoidance and group-level obstacle avoidance strategies are proposed, and the corresponding follower layer control laws are provided. Furthermore, the stability of the UAV swarm system under the control algorithm is demonstrated based on the Lyapunov theory. Finally, the effectiveness of the designed algorithm and its superiority in obstacle avoidance are verified through simulations.
本文主要研究无人机群在障碍物环境中的编队控制问题。本文提出了一种基于同步分布式模型预测控制(DMPC)的编队和避障控制算法。首先,将无人机群横向分为若干组,纵向分为领导层和跟随层。其次,跟踪被视为目标,避免碰撞和避开障碍物被视为约束条件。通过将速度障碍法与同步 DMPC 相结合,并提供相应的终端组件,设计了领导层控制法则。该控制法则可使无人机群在避免碰撞和动态障碍物的同时跟踪目标。然后,考虑到编队维持项,根据不同的优先级,提出了成员级避障和群组级避障策略,并提供了相应的跟随层控制法则。此外,基于李雅普诺夫理论,证明了控制算法下无人机蜂群系统的稳定性。最后,通过仿真验证了所设计算法的有效性及其在避障方面的优越性。
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引用次数: 0
UAV Detect and Avoid from UTM-Dependent Surveillance UTM-依赖性监视的无人机探测与规避
IF 1.4 4区 工程技术 Q2 Engineering Pub Date : 2024-04-09 DOI: 10.1155/2024/7328971
C. E. Lin, P. C. Shao, J. Y. Bai, Y. Y. Lin, H. T. Bui
A hierarchical unmanned aircraft system (UAS) traffic management (UTM) system has deployed 45 ground transceiver stations (GTS) for UAS services in Taiwan. This UTM system covers most areas for UAV-dependent surveillance using ADS-B Like technology. UTM Controller can monitor all UAV flights under transparent surveillance in low airspace. Controller-initiated UAV “detect and avoid” (DAA) mechanism assists UAV separation to ensure flight safety on UTM for small multirotor UAVs. From similar concept to traffic alert and collision avoidance system (TCAS) for the manned aircraft system, the UTM software executes DAA functions to generate approach alerts to UTM Controller. Conflict is detected by heading arrow extrapolation from multiple approaching UAVs by their time to conflict (TTC) on icons. Traffic advisory (TA) and resolution advisory (RA) are pronounced on UTM console to controllers. The less priority UAV pilot will receive the controller-pilot communication (CPC) to perform avoidance resolution. In UTM, the surveillance data period is broadcasting at 5~8 seconds on LoRa (long-range wide-area network) chip. Referring to seconds and seconds, the signal delay in ADS-B Like system to UTM server is about 0.5 seconds and CPC response is measured about 3~5 seconds. From real flight tests, the RA is enough for the less priority pilot to maneuver UAV for avoidance. From real flight tests
分层式无人机系统(UAS)交通管理(UTM)系统已在台湾部署了 45 个无人机系统服务地面收发站(GTS)。该UTM系统采用ADS-B Like技术,覆盖了大部分无人机监控区域。UTM 控制器可在低空透明监视下监控所有无人机飞行。控制员启动无人机 "侦测与避让"(DAA)机制,协助无人机分离,确保小型多旋翼无人机在UTM上的飞行安全。与有人驾驶飞机系统的交通警报和防撞系统(TCAS)概念类似,UTM 软件执行 DAA 功能,向 UTM 控制员发出进场警报。通过图标上的冲突时间(TTC)从多个接近的无人机中推断出航向箭头来检测冲突。在 UTM 控制台上向管制员发出交通警告(TA)和解决警告(RA)。优先级较低的无人机飞行员将收到管制员-飞行员通信(CPC),以执行避让决议。在UTM中,监控数据周期在LoRa(远程广域网)芯片上以5~8秒的速度播报。以秒为单位,ADS-B Like 系统到 UTM 服务器的信号延迟约为 0.5 秒,CPC 响应时间约为 3~5 秒。从实际飞行测试来看,RA 足够让优先级较低的飞行员操纵无人机进行规避。从实际飞行测试来看,基于 UTM 依赖性监视的 DAA 机制在解决多进近问题上是可行的。利用 ADS-B Like 技术开发的 UTM 系统还具有高可用性、冗余可靠性和性能稳定性,可确保飞行安全。
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引用次数: 0
ACP-Based Space Systems: Design, Development, and Operation 基于 ACP 的空间系统:设计、开发和运行
IF 1.4 4区 工程技术 Q2 Engineering Pub Date : 2024-03-27 DOI: 10.1155/2024/4650731
Yingkai Cai, Qingliang Meng, Zhaokui Wang
In the context of the rapid advancements in space technology and the increasing complexity of space missions, there is a growing need for efficient and effective approaches to tackle the multifaceted challenges faced by space systems. Traditional methods often fall short in providing comprehensive support throughout the entire life cycle of space systems. To address these challenges, this paper presents a novel parallel space system architecture based on ACP (artificial systems, computational experiments, and parallel execution) and explores its applications in the design, development, and operation of space systems. The proposed architecture integrates artificial systems with actual space systems and employs computational experiments to generate extensive sample data. This approach enhances the accuracy of the artificial systems’ model and optimizes the performance of the real systems, facilitating parallel advancements between the two. The design, development, and operation processes of Q-Sat, implemented using the ACP framework, serve as a case study to illustrate the advantages of parallel space systems. Following adjustments made to the discrepancies between parallel systems under the ACP-based space system framework, the accuracy of missing orbit compensation improved by 86.5%, and the 24-hour forecast positional error was reduced by approximately 65 m. Furthermore, this paper discusses future trends, emphasizing the increasing efficiency and reliability of digitized, integrated, and adaptive space systems. The findings contribute to the understanding of parallel space systems and provide valuable insights for further advancements in the field.
在空间技术突飞猛进和空间飞行任务日益复杂的背景下,越来越需要高效和有效的方法来应对空间系统面临的多方面挑战。传统方法往往无法为空间系统的整个生命周期提供全面支持。为应对这些挑战,本文提出了一种基于 ACP(人工系统、计算实验和并行执行)的新型并行空间系统架构,并探讨了其在空间系统设计、开发和运行中的应用。所提出的架构将人工系统与实际空间系统集成在一起,并利用计算实验生成大量样本数据。这种方法提高了人工系统模型的准确性,优化了实际系统的性能,促进了两者之间的并行发展。使用 ACP 框架实施的 Q-Sat 的设计、开发和运行过程作为案例研究,说明了并行空间系统的优势。在基于 ACP 的空间系统框架下对并行系统之间的差异进行调整后,缺失轨道补偿的精确度提高了 86.5%,24 小时预报位置误差减少了约 65 米。此外,本文还讨论了未来趋势,强调数字化、集成化和自适应空间系统的效率和可靠性将不断提高。研究结果有助于人们对并行空间系统的理解,并为该领域的进一步发展提供了宝贵的见解。
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引用次数: 0
Fault-Tolerant Control for Carrier-Based Aircraft Automatic Landing Subject to Multiple Disturbances and Actuator Faults 受多重干扰和执行器故障影响的航母舰载机自动着陆的容错控制
IF 1.4 4区 工程技术 Q2 Engineering Pub Date : 2024-03-26 DOI: 10.1155/2024/2054883
Qilong Wu, Qidan Zhu
This paper introduces a fault-tolerant control scheme for the automatic carrier landing of carrier-based aircraft using direct lift control. The scheme combines radial basis function neural network and active disturbance rejection control (RBF-ADRC) to overcome the impact of actuator failures and external disturbances. First, the carrier-based aircraft model, the carrier air-wake model, and the actuator fault model were established. Secondly, ADRC is designed to estimate and compensate for actuator faults and disturbances in real time. RBFNN adjusts the ADRC controller parameters based on the system state. Then, the Lyapunov function is constructed to prove the stability of the closed-loop system. The controller is applied to the direct lift control channel, auxiliary attitude channel, and approach power compensation system. The direct lift control improves the performance of fixed-wing aircraft. Finally, comparative simulations were conducted under various actuator failures. The results demonstrate the remarkable fault tolerance of the RBF-ADRC scheme, enabling precise tracking of the desired glide path by the shipboard aircraft even in the presence of actuator failures.
本文介绍了一种利用直接升力控制实现舰载机自动着陆的容错控制方案。该方案将径向基函数神经网络和主动干扰抑制控制(RBF-ADRC)相结合,以克服作动器故障和外部干扰的影响。首先,建立了舰载机模型、舰载机空中晃动模型和作动器故障模型。其次,设计了 ADRC 来实时估计和补偿作动器故障和干扰。RBFNN 根据系统状态调整 ADRC 控制器参数。然后,构建 Lyapunov 函数来证明闭环系统的稳定性。该控制器适用于直接升力控制通道、辅助姿态通道和进场功率补偿系统。直接升力控制提高了固定翼飞机的性能。最后,对各种作动器故障进行了比较模拟。结果表明,RBF-ADRC 方案具有出色的容错能力,即使在致动器出现故障的情况下,舰载机也能精确跟踪所需的滑行路径。
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引用次数: 0
Research on the Simulation Method for Equivalent Stiffness of Bolted Connection Thin Plate Structures 螺栓连接薄板结构等效刚度模拟方法研究
IF 1.4 4区 工程技术 Q2 Engineering Pub Date : 2024-03-26 DOI: 10.1155/2024/8648996
Zhe Chen, Qi-jun Zhao, Guo-chen Zhou
Bolted connections are widely used in assembly structures, and their dynamic characteristics are often affected by stiffness, damping, excitation, and other factors. In order to solve the problems of low computational efficiency of fine modeling and large computational error of linearized equivalent modeling of bolted structures, this paper proposes a dynamic characteristic parameter identification method for bolted structures based on the multiscale method and considering the influence of nonlinear factors. In this method, the bolted connection characteristics are simulated in the form of a combination of shear stiffness, torsional stiffness, nonlinear stiffness, and viscous damping coefficient and identified according to the test measurement frequency and frequency response function. At the same time, by establishing the nonlinear dynamic model of bolted structure, the influence of different bolt preloads and excitation forces on the dynamic characteristics of bolted structure is studied.
螺栓连接在装配式结构中应用广泛,其动态特性往往受到刚度、阻尼、激励等因素的影响。为了解决螺栓结构精细建模计算效率低、线性化等效建模计算误差大的问题,本文提出了一种基于多尺度方法并考虑非线性因素影响的螺栓结构动态特性参数识别方法。在该方法中,螺栓连接特性以剪切刚度、扭转刚度、非线性刚度和粘性阻尼系数的组合形式进行模拟,并根据测试测量频率和频率响应函数进行识别。同时,通过建立螺栓结构的非线性动态模型,研究了不同螺栓预紧力和激振力对螺栓结构动态特性的影响。
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引用次数: 0
Multiple Leap Maneuver Trajectory Design and Tracking Method Based on Prescribed Performance Control during the Gliding Phase of Vehicles 基于飞行器滑行阶段预定性能控制的多重跃迁轨迹设计与跟踪方法
IF 1.4 4区 工程技术 Q2 Engineering Pub Date : 2024-03-26 DOI: 10.1155/2024/6618732
Taotao Zhang, Jun Zhang, Sen Shen, Weiyi Chen
A novel standard trajectory design and tracking guidance used in the multiple active leap maneuver mode for hypersonic glide vehicles (HGVs) is proposed in this paper. First, the dynamic equation and multiconstraint model are first established in the flight path coordinate system. Second, the reference drag acceleration-normalized energy (D-e) profile of the multiple active leap maneuver mode is quickly determined by the Newton iterative algorithm with a single design parameter. The range to go error is corrected by the drag acceleration profile update algorithm, and the drag acceleration error of the gliding terminal is corrected by the aerodynamic parameter estimation algorithm. Then, the reference drag acceleration tracking guidance law is designed based on the prescribed performance control method. Finally, the CAV-L vehicle model is used for numerical simulation. The results show that the proposed method can satisfy the design requirements of drag acceleration under multiple active leap maneuver modes, and the reference drag acceleration can be tracked precisely. The adaptability and robustness of the proposed method are verified by the Monte Carlo simulations under various combined deviation conditions.
本文提出了一种用于高超音速滑翔飞行器(HGV)多主动跃迁机动模式的新型标准轨迹设计和跟踪制导。首先,在飞行路径坐标系中建立动态方程和多约束模型。其次,通过牛顿迭代算法,以单一设计参数快速确定多主动跃迁机动模式的参考阻力加速度-归一化能量(D-e)曲线。通过阻力加速度剖面更新算法修正航程误差,通过气动参数估计算法修正滑翔终端的阻力加速度误差。然后,根据规定的性能控制方法设计参考阻力加速度跟踪制导法则。最后,使用 CAV-L 车辆模型进行数值仿真。结果表明,所提出的方法能满足多种主动跃升机动模式下阻力加速度的设计要求,并能精确跟踪参考阻力加速度。在各种组合偏差条件下的蒙特卡罗仿真验证了所提方法的适应性和鲁棒性。
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引用次数: 0
An Iterative Determination Method of an Axial Deployment Force of a Lanyard-Deployed Coilable Mast in Local Coil Mode 局部卷绕模式下系索式可卷绕桅杆轴向展开力的迭代确定方法
IF 1.4 4区 工程技术 Q2 Engineering Pub Date : 2024-03-26 DOI: 10.1155/2024/3503468
Yu Liu, Liang Sun, Hai Huang, Xurui Zhao, Jiahao Liu, Yishi Qiao
The axial deployment force is an indispensable parameter of a lanyard-deployed coilable mast, which reflects its load capacity in practical applications. However, research on the axial deployment force in the literature is very limited, and there are no mature numerical methods to determine this parameter in the design stage of coilable masts. In this paper, a numerical method for determining the axial deployment force of a lanyard-deployed coilable mast in the local coil mode is presented. Through this method, the designer can quickly obtain the estimated value of the axial deployment force in the design stage, which is convenient for the quantitative design of parameters. To verify the correctness of the proposed method, a dynamic simulation of the coilable mast is carried out, and a microgravity test is performed. The comparison results show that the error between the numerical method and the simulation and experimental results is less than 5%, which proves the correctness of the proposed method. In addition, the coilable mast studied in this paper has been verified by an actual microsatellite deployment in orbit.
轴向展开力是系索式可卷绕桅杆不可或缺的参数,它反映了桅杆在实际应用中的承载能力。然而,文献中关于轴向展开力的研究非常有限,在可卷绕桅杆的设计阶段也没有成熟的数值方法来确定该参数。本文提出了一种数值方法,用于确定局部线圈模式下系索式可卷绕桅杆的轴向展开力。通过该方法,设计人员可以在设计阶段快速获得轴向展开力的估算值,方便参数的定量设计。为了验证所提方法的正确性,对可卷绕桅杆进行了动态模拟,并进行了微重力试验。对比结果表明,数值方法与仿真和实验结果之间的误差小于 5%,证明了所提方法的正确性。此外,本文所研究的可卷曲桅杆还通过在轨道上实际部署微型卫星得到了验证。
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引用次数: 0
Aeroengine Remaining Life Prediction Using Feature Selection and Improved SE Blocks 利用特征选择和改进的 SE 块预测航空发动机剩余寿命
IF 1.4 4区 工程技术 Q2 Engineering Pub Date : 2024-03-25 DOI: 10.1155/2024/6465566
Hairui Wang, Shijie Xu, Guifu Zhu, Ya Li
Aeroengines use numerous sensors to detect equipment health and ensure proper operation. Currently, filtering useful sensor data and removing useless data is challenging in predicting the remaining useful life (RUL) of an aeroengine using deep learning. To reduce computational costs and improve prediction performance, we use random forest to evaluate the feature importance of sensor data. Based on the size of the feature corresponding to the Gini index, we select the appropriate sensor. This helps us to determine which sensor to use and ensures that the computational resources are not wasted on unnecessary sensors. Considering that the RUL of equipment changes in a progressively more complex manner as the equipment is used over time, we propose an improved squeeze and excitation block (SSE) and combine it with a convolutional neural network (CNN). By enhancing the feature selection ability of CNN through segmented squeeze and excitation block, the model can focus on important information within features to effectively improve prediction performance. We compared our experiments with other RUL experiments on the CMAPSS aeroengine dataset and then conducted ablation experiments to verify the critical role of the methods we used.
航空发动机使用大量传感器来检测设备健康状况并确保正常运行。目前,在使用深度学习预测航空发动机剩余使用寿命(RUL)时,过滤有用的传感器数据并去除无用数据是一项挑战。为了降低计算成本并提高预测性能,我们使用随机森林来评估传感器数据的特征重要性。根据基尼指数对应的特征大小,我们选择合适的传感器。这有助于我们确定使用哪个传感器,并确保计算资源不会浪费在不必要的传感器上。考虑到随着设备使用时间的推移,设备的 RUL 会以逐渐复杂的方式发生变化,我们提出了一种改进的挤压和激励块(SSE),并将其与卷积神经网络(CNN)相结合。通过分段挤压和激励块来增强 CNN 的特征选择能力,该模型可以聚焦于特征中的重要信息,从而有效提高预测性能。我们在 CMAPSS 航空发动机数据集上将我们的实验与其他 RUL 实验进行了比较,然后进行了烧蚀实验,以验证我们所用方法的关键作用。
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引用次数: 0
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International Journal of Aerospace Engineering
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