检索结果-内蒙古大学图书馆

2022 IEEE International Conference on Unmanned Systems, ICUS 2022

作者： Wu, Xinlong Wang, Feng Qi, Shengjun Chinese Flight Test Establishment Aeronautical Science and Technology Simulation Key Laboratory Xi'an China

ISBN: (数字)9781665484565

ISBN: (纸本)9781665484565

Autonomous aerial refueling could improve the range, endurance and deployment capability of UAV, and its control strategy is the key factor to ensuring the success of UAV aerial refueling. Hence, it is quite necessary and crucial to develop an effective control strategy for autonomous aerial refueling. In this paper, the research status of autonomous aerial refueling for UAV was firstly reviewed, and the differences between manned-aircraft and UAV in aerial refueling were also introduced. Then, a feasible design method of optimal route for autonomous aerial refueling was proposed in light of Dubins Curve. Furthermore, a control strategy of autonomous aerial refueling in the rendezvous and formation stage was raised, including the corresponding mission instructions and control laws. The strategy was both verified through simulation and flight test, which was designed and fulfilled by two small UAVs. The results showed that the proposed control strategy was reasonable and reliable, which would provide technical support for autonomous aerial refueling in the future. © 2022 IEEE.

关键词： Unmanned aerial vehicles (UAV)

来源：评论

学校读者我要写书评

暂无评论

A Joint Framework for Knowledge Extraction from flight Training Comments 17th

A Joint Framework for Knowledge Extraction from Flight Tra...

引用

17th CCF Conference on Computer Supported Cooperative Work and Social Computing, ChineseCSCW 2022

作者： Zhang, Yuxuan Shang, Jiaxing Zheng, Linjiang Wu, Quanwang Cao, Weiwei Sun, Hong College of Computer Science Chongqing University Chongqing China Key Laboratory of Dependable Service Computing in Cyber Physical Society Ministry of Education Chongqing University Chongqing China Key Laboratory of Flight Techniques and Flight Safety Civil Aviation Flight University of China Guanghan China Flight Technology and Flight Safety Research Base Civil Aviation Flight University of China Guanghan China

ISBN: (纸本)9789819923557

The flight training comments are textual evaluation from the instructor to the flight training students. Extracting the assessment experience and knowledge from the flight training comments can help improve the flight training level. To this end, a joint extraction framework is proposed in this paper. For the model input, we use an end-to-end grid tagging scheme as the decoding algorithm to extract aspect terms, opinion terms and opinion pairs simultaneously. Considering the continuity of terms, we propose WoBERT as encoder, which modifies the pre-trained word segmentation based on BERT, and realizes Chinese word segmentation at word-level granularity. We conduct extensive experiments on a real flight training comments dataset. The results show that the model with WoBERT as the encoder achieves the best performance with a F1-score of 0.647, which can be used for the task of knowledge extraction from the flight training comments. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Extraction

来源：评论

学校读者我要写书评

暂无评论

A super resolution target separation and reconstruction approach for single channel sar against deceptive jamming

引用

Defence technology（防务技术） 2023年第3期21卷 164-175页

作者： Shi-qi Liu Bing Li Bo Zhao Lei Huang Yue-zhou Wu Wei-min Bao Guangdong Key Laboratory of Intelligent Information Processing College of Electronic and Information EngineeringShenzhen UniversityShenzhen518060China School of Electrical Engineering Southwest Jiaotong UniversityChengdu611756China State Key Laboratory of Millimeter Waves Southeast UniversityNanjing210096China School of Computer Science Civil Aviation Flight University of ChinaGuanghan618307China China Aerospace Science and Technology Corporation Beijing100048China

The excellent remote sensing ability of synthetic aperture radar(SAR)will be misled seriously when it encounters deceptive jamming which possesses high fidelity and *** this paper,the dynamic synthetic aperture(DSA)scheme is used to extract the difference between the true and false targets.A simultaneous deceptive jamming suppression and target reconstruction method is proposed for a single channel SAR system to guarantee remote sensing *** system model is formulated as a sparse signal recovery problem with an unknown parametric dictionary to be *** iterative reweighted method is employed to jointly handle the dictionary parameter learning and target reconstruction problem in an majorization-minimization framework,where a surrogate function majorizing the Gaussian entropy in the objective function is introduced to circumvent its *** dictionary parameter learning,the grid mismatching problem in a fixed grid based method is ***,the proposed method can reap a super resolution ***,a simple yet effective DSA section scheme is developed for the SAR data excerpting,in which only two DSAs are *** results about location error and reconstruction power error reveal that the proposed method is able to achieve a good performance in deceptive jamming suppression.

关键词： channel resolution separation

来源：评论

学校读者我要写书评

暂无评论

Research on the Construction and Applicability of Fatigue Management Model for flight-Line Maintenance Personnel 24th

Research on the Construction and Applicability of Fatigue Ma...

引用

24th Conference on Man-Machine-Environment System Engineering, MMESE 2024

作者： Li, Guocai Zhang, Gewen State Key Laboratory of Fire Science University of Science and Technology of China Anhui Hefei230026 China Development Planning and Discipline Building Division Civil Aviation University of China Tianjin300300 China Flight School Civil Aviation University of China Tianjin300300 China

ISBN: (纸本)9789819771387

In order to strengthen the fatigue management ability for flight-line maintenance personnel and ensure the safe operation of civil aviation aircrafts, the paper identifies 19 correlation indexes related to the fatigue of line maintenance personnel by analyzing the questionnaire answers of 829 line maintenance personnel in China. Then the AHP-entropy method is used to determine the weighting system of fatigue indexes for line maintenance personnel. Based on this, a fatigue management model for line maintenance personnel is established with the recognition thresholds set up for different fatigue states. It is found out through verification that, the fatigue management model for line maintenance personnel established in this paper is over 80% accurate in recognizing fatigue, proving to be reliable in fatigue recognition. The study provides decision support for the fatigue management of line maintenance personnel, and enables airlines to develop management software that carries out the whole process fatigue management of line maintenance personnel. © Beijing KeCui Man-Machine-Environment System Engineering technology Research Academy 2024.

关键词： Civil aviation

来源：评论

学校读者我要写书评

暂无评论

A Review of Machine Learning Methods to Solve flight Scheduling Research

A Review of Machine Learning Methods to Solve Flight Schedul...

引用

Big Data Engineering and Education (BDEE), International Conference on

作者： Yanbin Pan Haiwen Xu Jide Qian Mengtao Chu Hao Yan Faculty of Science Civil Aviation Flight University of China Guanghan China Key Laboratory of Civil Aviation Flight Technology and Flight Safety Civil Aviation Flight University of China Guanghan China

ISBN: (数字)9798350388268

ISBN: (纸本)9798350376463

The crew scheduling problem is a crucial component of airline operations planning. Using traditional operations research optimization methods to optimize the crew scheduling process can enhance the scientific and accurate nature of the plan, significantly impacting the airline's operational efficiency, cost savings, and ensuring the safety of flight operations. However, due to the increasing number and complexity of modern flight schedules, traditional combinatorial optimization algorithms face enormous computational pressure and cost. Additionally, the need for timely recovery of problem flights imposes limitations on traditional methods. Therefore, by reviewing recent algorithms that use machine learning to address combinatorial optimization problems, this research explores and examines the integration methods, algorithmic logic, and areas for improvement. It also investigates the potential of these methods for solving flight scheduling issues, providing insights and references for future applications of machine learning in addressing flight scheduling problems.

关键词： Schedules Machine learning algorithms Costs Operations research Reviews Processor scheduling Optimization methods Machine learning Safety Airline industry

来源：评论

学校读者我要写书评

暂无评论

EQUIVALENT CALCULATION METHOD OF FLYOVER NOISE LEVEL OF CUTBACK TAKE-OFF FOR CIVIL JET AIRPLANE AIRWORTHINESS CERTIFICATION 33

EQUIVALENT CALCULATION METHOD OF FLYOVER NOISE LEVEL OF CUTB...

引用

33rd Congress of the International Council of the Aeronautical sciences, ICAS 2022

作者： Song, Yahui Zhang, Xiaoliang Liu, Qiuhong Zhang, Yuelin Institute of Aircraft Flight Test Technology Chinese Flight Test Establishment Xi'an710089 China National Key Laboratory of Science and Technology on Aerodynamic Design and Research Northwestern Polytechnical University Xi'an710072 China

ISBN: (纸本)9781713871163

The airworthiness regulations permit the use of engine power cutback take-off procedure to demonstrate the compliance of flyover noise level for large civil subsonic jet airplane. In this paper, we propose a high-precision and widely applicable equivalent method for calculating the flyover noise of engine power cutback for large subsonic jet airplane type airworthiness certification. Firstly, based on the Noise-Power-Distance (N-P-D) database established by the equivalent flight test procedure, the tone-corrected perceived noise level adjusted for reference conditions PNLTr versus power and distance database is constructed for the equivalent calculation of engine power cutback flyover noise. Secondly, the construction method of PNLTr history and time interval corresponding to the reference flight track are derived. Then the equivalent calculation method of the flyover noise level is carried out based on the constructed PNLTr history. Finally, the method is verified by using flight test results of civil subsonic jet airplane ARJ21-700, and the optimal control method of flyover noise level is analyzed. The results show that the proposed method meets the airworthiness regulations and can be used to obtain the equivalent flyover noise level for any engine power cutback condition based on the N-P-D database, and can be directly used for flyover noise optimization. © 2022 ICAS. All Rights Reserved.

关键词： Database systems

来源：评论

学校读者我要写书评

暂无评论

A Method for Classification and Evaluation of Pilot’s Mental States Based on CNN

引用

Computer Systems science & Engineering 2023年第8期46卷 1999-2020页

作者： Qianlei Wang Zaijun Wang Renhe Xiong Xingbin Liao Xiaojun Tan Chengdu Institute of Computer Application Chinese Academy of SciencesChengdu610041SichuanChina School of Computer Science and Technology University of Chinese Academy of SciencesBeijing 100080China Key Laboratory of Flight Techniques and Flight Safety Civil Aviation Flight University of ChinaGuanghan618307SichuanChina School of Air Traffic Management Civil Aviation Flight University of ChinaGuanghan618307SichuanChina Neurology Department Deyang Second People’s HospitalGuanghan618307SichuanChina

How to accurately recognize the mental state of pilots is a focus in civil aviation *** mental state of pilots is closely related to their cognitive ability in *** the cognitive ability meets the standard is related to flight ***,the pilot’s working state is unique,which increases the difficulty of analyzing the pilot’s mental *** this work,we proposed a Convolutional Neural Network(CNN)that merges attention to classify the mental state of pilots through electroencephalography(EEG).Considering the individual differences in EEG,semi-supervised learning based on improvedK-Means is used in themodel training to improve the generalization ability of the *** collected the EEG data of 12 pilot trainees during the simulated flight and compared the method in this paper with other methods on this *** method in this paper achieved an accuracy of 86.29%,which is better than 4D-aNN and HCNN *** emotion will increase the probability of fatigue appearing,and emotion recognition is also meaningful during the *** we conducted experiments on the public dataset SEED,and our method achieved an accuracy of 93.68%.In addition,we combine multiple parameters to evaluate the results of the classification network on a more detailed level and propose a corresponding scoring mechanism to display the mental state of the pilots directly.

关键词： Pilot mental state EEG attention CNN semi-supervised learning

来源：评论

学校读者我要写书评

暂无评论

DGAN: flight data anomaly detection based on dual-view graph attention network

引用

IEEE Sensors Journal 2025年第11期25卷 20956-20969页

作者： Yan, Wenlong Li, Xu Zheng, Linjiang Shang, Jiaxing Wu, Lin Liu, Hongtao Li, Xiuyi Qian, Yu Chongqing University College of Computer Science Chongqing400044 China Chongqing University Key Laboratory of Dependable Service Computing in Cyber Physical Society Ministry of Education Chongqing400044 China Zhuhai Xiangyi Aviation Technology Co. Ltd Zhuhai519030 China Shanghai Jiaotong University School of Aeronautics and Astronautics Minhang District Shanghai200240 China Civil Aviation Flight University of China School of Flight Technology Guanghan618307 China

A large number of flight data is collected by various sensors during flight, including altitude, speed, pitch, etc. flight unsafe events, such as hard landings, can be reflected in flight anomaly data. Thus, flight data anomaly detection is crucial for aviation safety, enabling the identification of deviations from normal operations. However, due to the complexity and high dimensionality of the flight data, existing methods often fail to adequately extract temporal and variable information. As a result, these methods exhibit poor detection performance, especially when the anomaly data is scarce. To address these issues, we propose a novel Dual-view Graph Attention Network (DGAN) model for flight data anomaly detection. Specifically, two parallel Graph Attention (GAT) layers are employed to create embeddings that are rich in temporal correlations and variable dependencies. And TCN-based autoencoder module is proposed for data augmentation on these embeddings to extract two views consistent with the underlying data patterns. Furthermore, DGAN constructs pairs of positive and negative samples both within a single view and between different views. A dual-view contrastive training strategy is proposed to construct contrastive loss, which can learn a good representation of flight sequence and ensure effective anomaly detection even in cases of scarce anomaly data. We conduct experiments on a dataset comprising 44,808 real-world flight samples from the Airbus A321. The results demonstrate that the performance of DGAN exceeds state-of-the-art (SOTA) models. Moreover, we examine the effectiveness of DGAN through further visualizations and case studies. © 2001-2012 IEEE.

关键词： Training aircraft

来源：评论

学校读者我要写书评

暂无评论

Social Information Popularity Prediction based on Heterogeneous Diffusion Attention Network 34

Social Information Popularity Prediction based on Heterogene...

引用

34th International Conference on Software Engineering and Knowledge Engineering, SEKE 2022

作者： Jia, Xueqi Shang, Jiaxing Zheng, Linjiang Liu, Dajiang Cao, Weiwei Sun, Hong College of Computer Science Chongqing University Chongqing China Key Laboratory of Flight Techniques and Flight Safety Civil Aviation Flight University of China Guanghan China Flight Technology and Flight Safety Research Base Civil Aviation Flight University of China Guanghan China

ISBN: (纸本)1891706543

Information popularity prediction on social media platforms is a valuable and challenging issue. However, existing studies either neglect the correlation among different cascades, or lack a comprehensive consideration of user behavioral proximity and preference with respect to different messages. In this paper we propose a graph neural network-based framework named HeDAN (heterogeneous diffusion attention network), which comprehensively considers various factors affecting the information diffusion to predict the information popularity more accurately. Specifically, we first construct a heterogeneous diffusion graph with two types of nodes (user and message) and three types of relations (Friendship, Interaction, and Interest). Among them, Friendship reflects the strength of social relationship between users, Interaction reflects the behavioral proximity between users, and Interest reflects user preference to messages. Next, a graph neural network model with hierarchical attention mechanism is proposed to learn from these relations. Specifically, at the node-level, we utilize the graph attention network to learn the subgraph structure and generate the representations of nodes under each specific relationship. At the semantic-level, we distinguish the importance of different nodes in different relations via multi-head self-attention mechanism. Extensive experimental results on three datasets show the superior performance of our proposed model over the state-of-the-arts. © 2022 Knowledge Systems Institute Graduate School. All rights reserved.

关键词： Forecasting

来源：评论

学校读者我要写书评

暂无评论

Design and Optimization of a Samara-Inspired Lightweight Monocopter for Extended Endurance

引用

IEEE Robotics and Automation Letters 2025年第7期10卷 7214-7221页

作者： Xinyu Cai Shangkun Zhong Tee Meng Tan Wei Jun Ang Shaohui Foong Engineering Product Development Pillar Singapore University of Technology and Design (SUTD) Singapore Aviation Key Laboratory of Science and Technology on Flight Control AVIC Xi'an Automatic Flight Control Research Institute Xi'an China

Small multirotors demonstrate significant potential due to their simple airframe and human-friendly operation. However, the reduced size results in substantially higher energy consumption, which severely limits their flight endurance and restricts their range of applications. Ornithopters, while offering better aerodynamic efficiency, experience energy losses due to the mechanical complexity required to generate reciprocating motion. In this work, inspired by the samara, we present a lightweight aircraft with an exceptionally simple design featuring a single actuator and a mono airfoil. To optimize the flight configuration for minimal power consumption, we employed a Surrogate optimization method that integrates spinning airfoil dynamics, motor-propeller efficiency, and hovering equilibrium. As a result, the proposed vehicle achieves position-controlled hovering flight for up to 26 minutes with a takeoff weight of only 32 grams. Its superior power efficiency is demonstrated by a high power loading of 9.1 grams per watt. Compared to state-of-the-art systems, the proposed design shows significant improvements in both flight endurance and power efficiency. The reliable and stable position-holding flight over an extended period further validates the effectiveness of the proposed methods and the practical applicability of the fabricated prototype.

关键词： Actuators Aerodynamics Automotive components Robots Propellers Torque Spinning Power demand Atmospheric modeling Payloads

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：