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3rd International Conference on Electronic Information Engineering and Computer science, EIECS 2023

作者： Yue, Jian Zhu, Pan Yan, Lijun Aviation Key Laboratory of Science and Technology on Flight Test Chinese Flight Test Establishment Xi'an710089 China

ISBN: (纸本)9798350316674

The main way to measure the aerodynamic characteristics of aircraft is to carry out ground test. However, due to the great difference between the static aerodynamic data of actual flight and ground test, such as the ever-changing flight meteorological conditions and environment, the test data of flight test show multiple distribution, so it is difficult to analyze aerodynamic characteristics of aircraft. In this paper, a large number of flight data are analyzed by using cluster analysis and MATLAB software. In order to consider the variation of multi variables, the hierarchical clustering analysis of flight test data was used. The results show that the data with great changes in the measurement process can be classified properly, and the effective and reliable data are extracted, and the practicability of clustering analysis in data extraction is proved. © 2023 IEEE.

关键词： cluster analysis data extraction flight test

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Early fire detection technology based on improved transformers in aircraft cargo compartments

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Journal of Safety science and Resilience 2024年第2期5卷 194-203页

作者： Hongzhou Ai Dong Han Xinzhi Wang Quanyi Liu Yue Wang Mengyue Li Pei Zhu College of Civil Aviation Safety Engineering Civil Aviation Flight University of ChinaGuanghan618307China CivilAircraf Fire Science and Safety Enginring Key Laboratory of Sichuan CivilAviation Flight University of ChinaGuanghan 618307China School of Computer Engineering and Science Shanghai UniversityShanghai 200444China Key Laboratory of Civil Aviation Emergency Science&Technology Nanjing University of Aeronautics and AstronauticsNanjing 210000China

The implementation of early and accurate detection of aircraft cargo compartment fire is of great significance to ensure flight *** current airborne fire detection technology mostly relies on single-parameter smoke detection using infrared *** often results in a high false alarm rate in complex air transportation *** traditional deep learning model struggles to effectively address the issue of long-term dependency in multivariate fire *** paper proposes a multi-technology collaborative fire detection method based on an improved transformers ***-wavelength optical sensors,flue gas analyzers,and other equipment are used to carry out multi-technology collaborative detection methods and characterize various feature dimensions of fire to improve detection *** improved Transformer model which integrates the self-attention mechanism and position encoding mechanism is applied to the problem of long-time series modeling of fire information from a global perspective,which effectively solves the problem of gradient disappearance and gradient explosion in traditional RNN(recurrent neural network)and CNN(convolutional neural network).Two different multi-head self-attention mechanisms are used to classify and model multivariate fire information,respectively,which solves the problem of confusing time series modeling and classification modeling in dealing with multivariate classification tasks by a single attention ***,the output results of the two models are fused through the gate *** research results show that,compared with the traditional single-feature detection technology,the multi-technology collaborative fire detection method can better capture fire *** with the traditional deep learning model,the multivariate fire pre-diction model constructed by the improved Transformer can better detect fires,and the accuracy rate is 0.995.

关键词： Deep learning Aircraft cargo compartment Attentionmechanism Firedetection Multi-sourcedata fusion

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A Review of Machine Learning Methods to Solve flight Scheduling Research 4

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

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4th International Conference on Big Data Engineering and Education, BDEE 2024

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

ISBN: (纸本)9798350388268

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. © 2024 IEEE.

关键词： Neural networks

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Research on power control algorithm of wireless sensor based on Nash bargaining solution

Research on power control algorithm of wireless sensor based...

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2022 International Conference on Algorithms, Microchips and Network Applications

作者： Yue, Jian Zhu, Pan Yu, Dongzhe Chinese Flight Test Establishment Aviation Key Laboratory of Science and Technology on Flight Test Xian710089 China

ISBN: (纸本)9781510653290

For the wireless sensor network of airborne test system in flight test, in order to obtain better communication performance and improve the signal interference to noise ratio, the sensor nodes in the network will increase the transmission power, which will lead to the aggravation of the interference between the nodes, and bring negative impact to the wireless sensor network, finally cause the decline of overall network performance, and energy waste of sensor nodes. In order to solve this problem, this paper introduces the balance factor and designs the utility function considering a distance factor based on the Nash bargaining solution cooperative game theory. At the same time, a new power control algorithm is derived. The simulation results show that the proposed algorithm is simple to convergence, which could effectively improve the power consumption and the overall performance of wireless sensor network system, in addition, prolong the service life of sensor and achieve higher network utility. © COPYRIGHT SPIE. Downloading of the abstract is permitted for personal use only.

关键词： Power control

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A model for aircraft cabin evacuation considering passenger type

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Journal of Safety science and Resilience 2024年第1期5卷 83-90页

作者： Yaping Ma Jinfeng Yuan Lingling Tan Quanyi Liu Mengling Li Civil Aircraft Fire Science and Safety Engineering Key Laboratory of Sichuan Province Civil Aviation Flight University of ChinaGuanghan 618307China School of Safety Science and Emergency Management Wuhan University of TechnologyWuhan 430070China

Pedestrian safety evacuation in aircraft cabins has been a challenging problem because of the aircraft’s unique characteristics,such as the diversity of passengers and the restricted evacuation *** is difficult to reproduce evacuation activities in aircraft cabin due to safety concerns and cost *** fill this gap,an improved cellular automaton model of crowd evacuation for aircraft cabin is established by incorporating the characteristics of cabin space structures and passenger *** are divided into healthy individual passengers and disabled-healthy group passengers,whose movement mechanisms are *** on the constructed model,simulation experiments are conducted using the configuration cabin layout of B737-800 as an *** results show that the evacuation time is prolonged with increased passenger density and the number of disabled ***,the overall evacuation time is insignificantly affected by whether disabled-healthy group passengers’seats are close to the aisle or window,and the evacuation efficiency is best when their seats are evenly distributed in the *** evacuation time is the shortest when all cabin doors are open,and pedestrians are evacuated the slowest when the central emergency doors are *** study pro-vides valuable insights into effective strategies for pedestrian evacuation and crowd emergency management of civil aircraft.

关键词： Aircraft cabin evacuation Passenger type Cellular automaton model Pedestrian distribution Evacuation efficiency

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YOLOv8-EMSC:A lightweight fire recognition algorithm for large spaces

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Journal of Safety science and Resilience 2024年第4期5卷 422-431页

作者： Deng Li Tan Yang Zhou Jin Wu Si-qi Liu Quan-yi College of Civil Aviation Safety Engineering Civil Aviation Flight University of ChinaGuanghan618307China Civil Aircraft Fire Science and Safety Engineering Key Laboratory of Sichuan Province Guanghan 618307China Sichuan Key Technology Engineering Research Center for All-electric Navigable Aircraft Guanghan618307China

Stringent fire prevention requirements are imperative in expansive environments. Fire detection in diverse large-scale settings typically relies on sensor-based or AI-driven target detection methods. Traditional fire detectors often suffer from false alarms and missed detections, failing to meet the fire safety requirements of large-scale structures. Many existing target detection algorithms are characterized by substantial model sizes. Some detection terminals in large structures face challenges deploying these models due to constrained computational resources. To address this issue, we propose a lightweight model, YOLOv8-EMSC, derived from YOLOv8n. The incorporation of C2f_EMSC, replacing the C2f module, significantly reduces the model parameters in the enhanced YOLOv8-EMSC model compared to YOLOv8n, thereby enhancing model inference speed. Extensive testing and validation using a custom-built large-scale infrared fire dataset demonstrates a 9.6 % reduction in parameters compared to the baseline model for YOLOv8-EMSC, achieving an average precision of 95.6 %, surpassing both the baseline and mainstream models and significantly enhancing fire detection accuracy in expansive environments.

关键词： Fire detection Large space Lightweight YOLOv8 YOLOv8-EMSC

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An architecture decomposition method of pneumatic catapult system based on OPM and DSM

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Chinese Journal of Aeronautics 2023年第8期36卷 168-181页

作者： Lu GAN Gang YANG Xianhui LI Enze ZHU Hu CHEN Xiaohui WEI State Key Laboratory of Mechanics and Control of Aerospace Structures Nanjing University of Aeronautics and AstronauticsNanjing 210016China Key Laboratory of Fundamental Science for National Defense-Advanced Design Technology of Flight Vehicle Nanjing University of Aeronautics and AstronauticsNanjing 210016China College of General Aviation and Flight Nanjing University of Aeronautics and AstronauticsNanjing 210016China

The architecture strategy of the Unmanned Aerial Vehicle(UAV)pneumatic launch system should continue to evolve to adapt to complex and variable operating *** representation,decomposition perspective,and cluster analysis play a vital role in the early phase of system architecture *** order for the system to emerge anticipated and desirable intrinsic functional properties,an architecture decomposition method based on the ObjectProcess Methodology(OPM)and Design Structure Matrix(DSM)is put forward in this *** OPM is proposed to model the UAV launch process formally,and the matrix representation of the architecture of the pneumatic launch system is *** the extension of the definition and operations of DSM,with the Idicula-Gutierrez-Thebeau Algorithm plus(IGTA+)clustering algorithm,the transformation of the pneumatic launch system architecture from process decomposition to function decomposition is demonstrated in this *** analysis shows that the architecture decomposition of the pneumatic launch system meets the functional requirements of stakeholders.

关键词： Architecture decomposition Cluster analysis Design structure matrix Object-process methodology Pneumatic catapult system

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DNN performance optimization based on Gemmini neural network hardware accelerator 4

DNN performance optimization based on Gemmini neural network...

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4th International Conference on Advanced Algorithms and Neural Networks, AANN 2024

作者： Zhao, Denghui He, Jianrui Jing, Xuyu Hou, Xibiao AVIC Xi’an Flight Automatic Control Research Institute Aviation Key Laboratory of Science and Technology on Aircraft Control Xi’an710065 China

ISBN: (纸本)9781510686106

Gemmini is an open-source, full-stack DNN accelerator generator. For an DNN algorithm running on Gemmini, traditional optimizations focus on changing Gemmini's hardware configuration (e.g., changing the size of internal storage and the size of the systolic array). This work proposes an an optimization-test iteration route combining Spike simulation and FPGA simulation under the constraints of unacceptable running speed of verilator simulator and limited FPGA resources. According to this route, this work starts from two aspects of hardware optimization and algorithm optimization. The internal storage size and calculation scale of Gemmini are changed in hardware, and the convolutional layer of Resnet50 neural network algorithm is optimized in algorithm. The experimental results show that for Resnet50 DNN algorithm, Gemmini with basic configuration provides 2000x speedup compared with running on CPU. On the platform of Gemmini accelerator, the optimization of hardware configuration provides 1.59x speedup for Resnet50. On the basis of the hardware optimization, the algorithm optimization provides 1.012x speedup. © 2024 SPIE.

关键词： Mathematical optimization Neural networks Field programmable gate arrays Data storage Evolutionary algorithms Convolution Detection and tracking algorithms Performance modeling Matrices

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flight test Data Extraction Based on Clustering Analysis

Flight Test Data Extraction Based on Clustering Analysis

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Electronic Information Engineering and Computer science (EIECS), 2021 International Conference on

作者： Jian Yue Pan Zhu Lijun Yan Chinese Flight Test Establishment Aviation Key Laboratory of Science and Technology on Flight Test Xi’an China

关键词：

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Design of Dual-Rotor Vehicle Controller Based on Auto Disturbance Rejection 1

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3rd International Conference on Autonomous Unmanned Systems, ICAUS 2023

作者： Sun, Xue Wang, Donghui Zhan, Zhengyong Cui, Yuwei AVIC Xi’an Flight Automatic Control Research Institute Xi’an710065 China Aviation Key Laboratory of Science and Technology On Aircraft Control Xi’an710065 China

ISBN: (数字)9789819710997

ISBN: (纸本)9789819710980

Aiming at the characteristics of dual-rotor vehicle, nonlinear, strong coupling and easy to be interfered, a design method of altitude tracking and attitude stabilization using nonlinear active disturbance rejection controller was proposed. The mathematical model of the dual-rotor vehicle was established through dynamic analysis, and the state coupling was regarded as the internal disturbance. The state observer was used to estimate the state and internal and external disturbance of the system in real time, and then the nonlinear feedback was used to compensate the estimated value of the internal and external disturbance of the model, and the state decoupling control of the dual-rotor vehicle was realized. Finally, through the simulation experiment, and compared with the classical PID control method, the experimental results show that the active disturbance rejection controller can realize the altitude tracking and fast and stable attitude control of the dual-rotor vehicle, and has strong anti-interference and robustness. © Beijing HIWING Scientific and Technological Information Institute 2024.

关键词： Nonlinear feedback

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