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6th International Conference on System Reliability and Safety engineering, SRSE 2024

作者： Xiang, Jiaxin Sun, Yongquan Wang, Hao Chen, Hongke Harbin University of Science and Technology School of Measurement and Control Technology and Communication Engineering Harbin China China Institute of Marine Technology & Economy Beijing China Xiamen University Tan Kah Kee College School of Mechanical and Electrical Engineering & Automation Zhangzhou China

ISBN: (纸本)9798350356083

Limited reliability data during the development of cruise ship automation systems often leads to subjective weight allocation. This paper proposes an reliability allocation method based on the Bayesian best-worst method and analytic hierarchy process to address this challenge. By considering the system reliability indices, influencing factors, and units need to be allocated, a hierarchical model is established for reliability allocation based on the analytic hierarchy process. The Bayesian best-worst method compares elements in each layer, generating best and worst matrices based on decision-makers. These matrices determine optimal weights for each layer's elements. The analytic hierarchy process determines relative importance weights among the system reliability index, influencing factors, and units. Consequently, the derived optimal weights are converted into allocation factors, which enable the allocation of reliability for cruise ship automation systems. This fusion-based approach presents a novel and effective method for optimizing reliability allocation during the development stage of complex systems. © 2024 IEEE.

关键词： Decision making

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STRUCTURAL RELIABILITY ANALYSIS BASED ON IMPROVED PARALLEL SAMPLING ALGORITHM 10

STRUCTURAL RELIABILITY ANALYSIS BASED ON IMPROVED PARALLEL S...

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10th International Symposium on Test Automation and Instrumentation, ISTAI 2024

作者： Yu, Yifan Wang, Liyong Zhang, Ximing College of Mechanical & Energy Engineering Beijing University of Technology Beijing China Key Laboratory of Modern Measurement & Control Technology Ministry of Education Beijing China China North Vehicle Research Institute Beijing China

ISBN: (纸本)9781837242672

Aiming at the problem of computational inefficiency of traditional reliability analysis methods when dealing with large-scale structural systems, this paper proposes a reliability analysis method that improves the parallel sample algorithm. The method adopts the Kriging model to fit the performance function and introduces the mean square error to evaluate the uncertainty of the sample points;In addition, the positional relationship between the sample points is taken into consideration to avoid overfitting the model;To improve the efficiency of the model fitting, the sample points are divided into multiple clusters using the Mini batch k-means clustering algorithm in parallel computation. Finally, it is verified by multiple random variable cases that the method can significantly improve the computational efficiency while guaranteeing the relative error compared with other reliability analysis methods. © The Institution of engineering & technology 2024.

关键词： Data reliability

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Architecture design of generic automatic test system runtime platform based on ATML 9

Architecture design of generic automatic test system runtime...

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9th International Symposium on Sensors, Mechatronics, and Automation System, ISSMAS 2023

作者： Jia, Feng Yang, Xiaohui Li, Shilin Cui, Jialu Han, Bing Zhang, Guiying Shaanxi Engineering Laboratory for Transmissions and Controls Northwestern Polytechnical University Xi'an710072 China Avic Beijing Changcheng Aeronautical Measurement and Control Technology Research Institute Beijing101111 China

ISBN: (纸本)9781510672802

In this paper, an Automatic Test System runtime platform based on the ATML standard is designed and implemented. Firstly, the paper analyzes functions and internal relationship of the basic components of TPS based on ATML, and gives the parse method of TPS. Afterwards, the overall architecture design and functional division of the runtime platform were carried out. Realize the execution logic of the runtime platform by generating the Test Operation Tree and analyzing the test purpose of different Operation Type. Then, the software execution process during debugging control and simulation test is given, and finally the method of debugging information monitoring and persistence is explained. In addition, this paper introduces the resource allocation methods when calling the underlying test resources. By using the architecture described in this paper, the interchangeability and test efficiency of test programs can be improved. © 2024 SPIE.

关键词： Equipment Design and modelling control systems Logic Data storage Signal processing Device simulation Switches Virtual reality Automated test equipment

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Image motion and experimental study of a 0.1″space pointing measuring instrument for micro-vibration conditions

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Chinese Journal of Aeronautics 2023年第2期36卷 191-200页

作者： Lin LI Li YUAN Li WANG Miaomiao WANG Xiaoxue GONG Jie SUI Yanpeng WU Ran ZHENG Space Optoelectronic Measurement and Perception Lab. Beijing Institute of Control EngineeringBeijing 100190China China Academy of Space Technology Beijing 100094China Science and Technology on Space Intelligent Control Laboratory Beijing 100094China University of Chinese Academy of Sciences Beijing 100049China Changchun Institute of Optics Fine Mechanics and PhysicsChinese Academy of SciencesChangchun 130033China Chang Guang Satellite Technology Co. Ltd.Changchun130102China

There exists an increasing need for Milli-Arc-Seconds(MAS)accuracy pointing measurement for current and future space *** meet the 0.1″space pointing measurement accuracy requirements of spacecraft in future,the influence of spacecraft micro-vibration on a 0.1″Space Pointing Measuring Instrument(SPMI)is studied.A Quasi-Zero Stiffness Device(QZSD)with adaptive adjustment and variable stroke was ***,a series of micro-vibration experiments of the SPMI were carried *** influence of the micro-vibration generated by Guidance Navigation control(GNC)attitude control components under different attitudes on the SPMI was *** spread function of image motion in micro-vibration was also ***,the changes of image motion under the micro-vibration environment were evaluated by extracting the gray centroid of the images,and the experiment processes and results are deeply *** results show that the firstorder frequency of the QZSD system is 0.114 Hz,and it is induced by a double pendulum system;the image motion of single flywheel spinning reached 0.015 pixels;whilst the image motion reached 0.03 pixels when three flywheels are combined *** latest findings provide a beneficial theoretical and technical support for the development of spacecraft with 0·1″pointing accuracy.

关键词： Image motion Micro-vibration Milli-arc-seconds Quasi-zero stiffness device Space pointing measuring instrument

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In-Vehicle Network Injection Attacks Detection Based on Feature Selection and Classification

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Automotive Innovation 2024年第1期7卷 138-149页

作者： Haojie Ji Liyong Wang Hongmao Qin Yinghui Wang Junjie Zhang Biao Chen Key Laboratory of Modern Measurement and Control Technology Ministry of EducationBeijing Information Science and Technology UniversityBeijing 100192China State Key Laboratory of Advanced Design and Manufacturing for Vehicle Body College of Mechanical and Vehicle EngineeringHunan UniversityChangsha 410082China School of Transportation Science and Engineering Beihang UniversityBeijing 100191China Hefei Innovation Research Institute Beihang UniversityHefei 230012China

Detecting abnormal data generated from cyberattacks has emerged as a crucial approach for identifying security threats within in-vehicle *** transmission of information through in-vehicle networks needs to follow specific data for-mats and communication protocols ***,statistical algorithms are employed to learn these variation rules and facilitate the identification of abnormal ***,the effectiveness of anomaly detection outcomes often falls short when confronted with highly deceptive in-vehicle network *** this study,seven representative classification algorithms are selected to detect common in-vehicle network attacks,and a comparative analysis is employed to identify the most suitable and favorable detection *** consideration of the communication protocol characteristics of in-vehicle networks,an optimal convolutional neural network(CNN)detection algorithm is proposed that uses data field characteristics and classifier selection,and its comprehensive performance is *** addition,the concept of Hamming distance between two adjacent packets within the in-vehicle network is introduced,enabling the proposal of an enhanced CNN algorithm that achieves robust detection of challenging-to-identify abnormal *** paper also presents the proposed CNN classifica-tion algorithm that effectively addresses the issue of high false negative rate(FNR)in abnormal data detection based on the timestamp feature of data *** experimental results validate the efficacy of the proposed abnormal data detection algorithm,highlighting its strong detection performance and its potential to provide an effective solution for safeguarding the security of in-vehicle network information.

关键词： Classification algorithm Anomaly detection In-vehicle network Feature extraction Injecting attack

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Exploiting the Direct Link in IRS Assisted NOMA Networks with Hardware Impairments

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Computer Modeling in engineering & Sciences 2023年第7期136卷 767-785页

作者： Ziwei Liu Xinwei Yue Shuo Chen Xuliang Liu Yafei Wang Wanwei Tang Key Laboratory of Modern Measurement&Control Technology Ministry of EducationSchool of Information and Communication EngineeringBeijing Information Science and Technology UniversityBeijing100101China The Party Committee Office Yellow River Conservancy Technical InstituteKaifeng475001China Tangshan University Tangshan063000China

Hardware impairments(HI)are always present in low-cost wireless *** paper investigates the outage behaviors of intelligent reflecting surface(IRS)assisted non-orthogonal multiple access(NOMA)networks by taking into account the impact of ***,we derive the approximate and asymptotic expressions of the outage probability for the IRS-NOMA-HI *** on the asymptotic results,the diversity orders under perfect self-interference cancellation and imperfect self-interference cancellation scenarios are obtained to evaluate the performance of the considered *** addition,the system throughput of IRS-NOMA-HI is discussed in delay-limited *** obtained results are provided to verify the accuracy of the theoretical analyses and reveal that:1)The outage performance and system throughput for IRS-NOMA-HI outperforms that of the IRS-assisted orthogonal multiple access-HI(IRS-OMA-HI)networks;2)The number of IRS elements,the pass loss factors,the Rician factors,and the value of HI are pivotal to enhancing the performance of IRS-NOMAHI networks;and 3)It is recommended that effective methods of reducing HI should be used to ensure system performance,in addition to self-interference cancellation techniques.

关键词： Hardware impairments imperfect SIC intelligent reflecting surface non-orthogonal multiple access outage probability

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Design and Implementation of Indoor Visual Autonomous Navigation System for Quadrotor UAV Based on Binocular Camera and IMU 3

Design and Implementation of Indoor Visual Autonomous Naviga...

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3rd International Conference on Computer Science, Electronic Information engineering and Intelligent control technology, CEI 2023

作者： Tang, Jiaze Guo, Tianxing Liudan Li, Junbao Sun, Jinwei Huang, Wenbin Wang, Qisong Electrical Measurement Technology and Intelligent Control Institute School of Instrumention Science and Engineering Harbin Institute of Technology Harbin150080 China Schools of Electronics and Information Engineering Harbin Institute of Technology Harbin150080 China Information Countermeasure Technique Institute School of Computer Science and Technology Harbin Institute of Technology Harbin150080 China

ISBN: (纸本)9798350372052

Addressing the challenge of unmanned aerial vehicles (UAVs) navigating indoors without satellite positioning, this study introduces a novel method combining binocular camera and inertial measurement unit (IMU) data. This approach overcomes the structural differences between visual and inertial information, integrating them effectively for enhanced indoor autonomous navigation. The research presents a gradient-free path planning framework, pivotal for enhancing the UAV's ability to execute efficient and stable flight in intricate indoor settings. The cornerstone of this system is an advanced path planning algorithm, adept at swiftly identifying optimal routes and adapting to environmental shifts. The system's efficacy was rigorously evaluated through simulations and real-world tests, confirming its precision in positioning and path planning without reliance on satellite data. The findings demonstrate the system's capacity for precise localization and effective route determination, utilizing an integration of visual and inertial inputs. This research significantly contributes to the autonomous flight capabilities of UAVs, offering a valuable reference for future UAV autonomous navigation systems. By delving into visual-inertial fusion navigation technology, the study paves the way for expanded indoor UAV applications. © 2023 IEEE.

关键词： Antennas

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Satellite Power System Anomaly Detection based on Spatio-Temporal Uncertainty Fusion

Satellite Power System Anomaly Detection based on Spatio-Tem...

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2023 CAA Symposium on Fault Detection, Supervision and Safety for Technical Processes, SAFEPROCESS 2023

作者： Wang, Zhipeng Gao, Yanjiao Pang, Jingyue Song, Yuchen Peng, Yu Harbin Institute of Technology School of Electronics and Information Engineering Harbin China Harbin University of Science and Technology School of Measurement and Control Technology and Communication Engineering Harbin China Chongqing Technology and Business University School of Artificial Intelligence Chongqing China

ISBN: (纸本)9798350337754

Satellites have been widely used for military and civil applications. The power system is critical for the satellite's operating safety. However, satellite power system anomaly monitoring is faced with challenges like large amounts of data, insufficient anomaly samples, and complex operating conditions. To address these challenging issues, this paper proposes a data-driven anomaly detection method that fuses the time-related historical data and spatial-associated sub-system monitor data. Firstly, the probabilistic prediction model is used to establish the prediction model based on time and space The corresponding prediction uncertainties of the temporal and spatial models are quantitatively represented. Then, the stochastic distribution model is introduced to fuse the two uncertainties to obtain the predicted mean value and fusion uncertainty of the current power system state. The mean value is taken as the expected result of the state, and the fused uncertainty interval is taken as the threshold of abnormal judgment to realize the detection of the abnormal condition. The telemetry data of the actual satellite power system are used for experimental and comparative analysis. The results show that the false negative rate of anomaly detection results can be effectively reduced, and the detection accuracy can be improved through the fusion of spatio-temporal uncertainty. © 2023 IEEE.

关键词： Anomaly detection

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3D Imaging Sensing and Prediction technology of Large Component Surface with Multi-source Sensing 6

3D Imaging Sensing and Prediction Technology of Large Compon...

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6th Conference on Frontiers in Optical Imaging and technology: Applications of Imaging Technologies

作者： Sun, Jing Li, Lijuan Lin, Xuezhu Guo, Lili Liu, Yue Yan, Dongming Key Laboratory of Optoelectronic Measurement and Control and Optical Information Transmission Technology Ministry of Education College of Optoelectronic Engineering Changchun University of Science and Technology Changchun130022 China Zhongshan Research Institute of Changchun University of Science and Technology Guangdong Zhongshan528400 China

ISBN: (数字)9781510679757

ISBN: (纸本)9781510679740

In order to solve the problem that the surface deformation of large components cannot be photographed in real time due to the influence of assembly stress during assembly, a multi-source sensor surface deformation sensing and 3D imaging prediction technology for large components is proposed, which combined laser tracking, structured light detection and optical fiber sensing monitoring. Firstly, the multi-source sensor system is analyzed, and the multi-source sensor fusion sensing field is constructed. Secondly, the unified model of heterogeneous data is established to complete the accurate conversion of optical fiber monitoring wavelength to space point coordinates. Thirdly, multi-source data fusion is realized based on Gaussian process fusion algorithm to complete 3D imaging prediction of component surface deformation. Finally, a large skin component is taken as an example to simulate the assembly deformation experiment. The results show that the root-mean-square error is less than 0.1mm compared with the actual results. Based on the measured data of structured light scanning and multi-source sensing technology, a real-time sensing and prediction method for surface deformation imaging of large components is proposed. This method not only simplifies the scanning mode of structured light, but also provides a new idea for dynamic model building. © 2024 SPIE.

关键词： Forecasting

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Lightweight recognition method of infrared sensor image based on deep learning method 24

Lightweight recognition method of infrared sensor image base...

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8th International Conference on control engineering and Artificial Intelligence, CCEAI 2024

作者： Ren, Ze Tian, Xinling Qin, Guan Zhou, Dongdong China Energy Group International Engineering Consulting Co. Ltd. Beijing China Optoelectronics Business Department Beijing Institute of Control Engineerin Beijing100190 China Optoelectronic Measurement and Intelligent Perception Zhongguancun Open Lab Space Optoelectronic Measurement and Perception Lab Beijing Institute of Control Engineering Beijing100190 China Collaborative Innovation Center of Steel Technology University of Science and Technology Beijing 30 Xueyuan Road Haidian District Beijing100083 China

ISBN: (纸本)9798400707971

Space infrared sensors have become the "eyes"of space activities, there is currently no established identification method applied to the embedded deployment of space infrared sensor, despite it being a crucial device for aerospace detection due to the influence of deep learning target detection model embedded deployment difficulty, large sample demand, model parameter weight, low computing efficiency, and other factors. In this paper, the YOLOv5 detection model's network structure and activation function are lightened up. Next, the algorithm model's adaptive learning rate optimization algorithm is used to build the lightened-up YOLOv5 infrared image target recognition model. And the image samples were preprocessed with the intention of addressing the poor image quality brought on by background interference and multi-pose acquisition. Then, a method of sample amplification is suggested in light of the issues with the deep learning model. Consequently, the deep learning lightweight model applied in this study is one-third smaller than the conventional model, which dramatically increases target detection speed without significantly lowering detection rate. In addition to investigates ideas for the embedded deployment and recognition of infrared images in small sample space. © 2024 ACM.

关键词： Deep learning

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