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International Conference on Information, Communication and Networks (ICICN)

作者： Ke Zhang Junzheng Wang Xiang Zhang Yu Shi Ting Wang School of Automation Beijing Institute of Technology Beijing China Science and Technology on Electromechanical Dynamic Control Laboratory Xi’an Institute of Electron-mechanical Information Technology Xi’an China

Time-series data typically contain issues such as missing data and noise, which can impact the model's precision and stability. This paper proposes a Transformer structure-based visual information-guided temporal data modeling algorithm to address the issues as mentioned above. The algorithm effectively captures the time-series structure of the time-series data, thereby enhancing the model's precision and stability. To evaluate the performance of the proposed algorithm, a dataset containing visual information aligned with time-series data is compiled, and a comprehensive quantitative and qualitative analysis is performed. Conduct a comprehensive quantitative and qualitative analysis. The results indicate that visual information can assist time-series data in capturing the intricate dynamics of the time-series data, thereby enhancing the performance of the proposed algorithm and facilitating its comprehension. The results indicate that visual information can assist time-series data in capturing the complex dynamics of time-series data, and thus in comprehending and predicting their behavior and trends. The application of this algorithm will advance research in the field of modeling and predicting time series data. Applying this algorithm will advance research and practice in modeling and forecasting time series data.

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A hybrid piecewise FDD strategy for refrigeration charge fault of airborne vapor-compression cycle system

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INTERNATIONAL JOURNAL OF REFRIGERATION 2022年 135卷 164-173页

作者： Sun, Chengbin Wang, Hexu Jiang, Yanlong Gao, Zanjun Wang, Ju [a]Key Laboratory of Aircraft Environment Control and Life Support MIIT Nanjing University of Aeronautics and Astronautics 29 Yudao St. Nanjing 210016 China [b]Aviation Key Laboratory of Science and Technology on Aero Electromechanical System Integration Nanjing 211106 China

Many researchers have carried out study on refrigerant charge fault for variable refrigerant flow (VRF) airconditioning system, while few pay attention to refrigerant charge fault for vapor-compression refrigerant cycle system (VCS) of enhanced vapor injection (EVI) with a flash tank onboard. To develop a strategy for refrigerant charge fault of the above system, the optimization methods have been implemented to predict the refrigerant charge level (RCL) based on virtual refrigerant charge (VRC) models. Firstly, Pearson correlation coefficient analysis is employed to obtain the characteristic parameters. Secondly, a piecewise modified VRC model with the different characteristic parameters from VRC models is obtained for two cases of RCL < 75% and RCL > 75%. Meanwhile, combined with the principal component analysis (PCA) and the support vector machine (SVM) algorithm, a PCA-SVM model is developed to improve the prediction accuracy, and the average root mean squared error (RMSE) is only 7.8 compared to 14.9 of the modified VRC model when RCL > 75%, meanwhile, the correctly detected ratio is improved from 62.8% to 84.5%. Then, for solving the difficulty of fault detection and diagnosis (FDD) when RCL > 160%, the moving time window average (MA) algorithm is introduced and an online PCA-MA-SVM model is developed. Finally, a hybrid piecewise FDD strategy combined with three models for refrigeration charge fault in airborne VCS of EVI with a flash tank is obtained.

关键词： Vapor-compression refrigeration cycle system Enhanced vapor injection Refrigerant charge fault Support vector machine Moving time window average

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Modeling and validation of key components of thermal management systems

Modeling and validation of key components of thermal managem...

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2024 CSAA/IET International Conference on Aircraft Utility Systems, AUS 2024

作者： Zekun, Mei Shuai, Xu Fanxin, Meng Guangya, Zhu Dalin, Zhang Weijian, Chen Key Laboratory of Aircraft Environment Control and Life Support MIIT Nanjing University of Aeronautics and Astronautics Nanjing China 805th Research Institute of China Aerospace Science and Technology Corporation Shanghai China Aviation Key Laboratory of Science and Technology on Aero Electromechanical System Integration No.33 Shuige Road Nanjing China

ISBN: (数字)9781837242108

In this paper, two key components of thermal management system are modeled by the underlying logic operation of SIMULINK. Simulink-PS signal conversion module is used to connect the electric grid and the calculation part of the heat grid to build the fuel tank heat grid model. The temperature transient simulation model of phase-change heat exchanger was established by using the integral module in Simulink library. Experimental verification and literature data verification are provided for these two components. The results show that the error between simulation results and experimental data is between 0.1% and 3%, which proves the accuracy and feasibility of the system modeling in this paper. It lays a foundation for the simulation of the overall thermal management scheme. © The Institution of Engineering & technology 2024.

关键词： Fuel tanks

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Self-Supervised Sparse Direct Visual Odometry with Half-Geometric Correspondence Network 13

Self-Supervised Sparse Direct Visual Odometry with Half-Geom...

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13th International Conference on Electronics, Communications and Networks, CECNet 2023

作者： Zhang, Tenglong Li, Qing Zhou, Miaosheng Yu, Fei Beijing Information Science & Technology University Beijing100192 China Beijing Key Laboratory of High Dynamic Navigation Technology Beijing100192 China Ministry of Education Key Laboratory of Modern Measurement & Control Technology Beijing100192 China Beijing SinsTek Measurement & Control Co. Ltd. Beijing101300 China Beijing Star Network Yuda Technology Co Beijing100097 China

ISBN: (纸本)9781643684802

Current mainstream visual odometry method often suffers from tracking lost in low texture and motion blur scenarios due to fewer effective features and difficulty in getting stable matches. And feature matching process affects the overall real-time performance. For the fast localization task in low texture environments, this paper proposes an efficient self-supervised direct visual odometry framework based on keypoint extraction network, HGCN-VO. First we build the half-geometric correspondence network, HGCN, for fast extraction of robust keypoints in images. During training, we propose training method which uses basic shape elements to render generated simulated images with pseudo-labels as well as random homography transformations on real images for pre-training and migration learning and optimizing the keypoint loss from forward and reverse perspective transformed images. Finally we optimize the inter-frame position using a multilayer sparse direct method combined with bundle adjustment to improve the robustness of the method in low texture environments while increasing the processing speed. We evaluated the proposed method in KITTI, TUM, and challenging low-texture real-world scenarios and compared it with the current mainstream visual odometry methods, and the results show that the algorithm is sufficiently robust and accurate in low-texture environments and has a fast processing speed. © 2024 The authors and IOS Press.

关键词： Textures

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Fuze Echo Recognition Based on Improved V-G Convolutional Neural Network 13

Fuze Echo Recognition Based on Improved V-G Convolutional Ne...

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13th International Symposium on Antennas, Propagation and EM Theory, ISAPE 2021

作者： Huang, Dengdian Tian, Bo Li, Tie Hou, Yali Science and Technology on Electromechanical Dyamic Control Laboratory Xity China

ISBN: (纸本)9781665418126

In order to solve the problem that it is difficult for the traditional fuse target recognition algorithm to recognize the object with the same size as the target under the condition of ground object coupling and low signal-to-noise ratio, the V-G convolution neural network is used for Fuse echo The improved V-G convolution neural network is used in this method, and the data of laser and radio fuse missile target rendezvous is used as The improved V-G convolution neural network is used in this method, and the data of laser and radio fuse missile target rendezvous is used as the training library to identify the targets outside the library and classify the targets inside the library. The simulation results show that the recognition accuracy is more than 95%, and the fuse echo recognition can be carried out efficiently. © 2021 IEEE.

关键词： Convolution

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NUMERICAL SIMULATION AND EXPERIMENTAL RESEARCH ON TAYLOR COUETTE FLOW CHARACTERISTICS IN AIR GAP OF AVIATION MOTOR

NUMERICAL SIMULATION AND EXPERIMENTAL RESEARCH ON TAYLOR COU...

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2024 CSAA/IET International Conference on Aircraft Utility Systems, AUS 2024

作者： Ma, Hui Liang, Shuyue Zhan, Hongbo Qi, Lin Chen, Weijian Aviation Key Laboratory of Science and Technology on Aero Electromechanical System Integration No.33 Shuige Road Nanjing China Key Laboratory of Aircraft Environment Control and Life Support MIIT Nanjing University of Areonautics and Astronautics No.29 Yudao Street Nanjing China

A test bench with PIV technology was built and visualization research on Taylor vortex between concentric rotating cylinders was carried out to explore the flow morphology within the annular gap by changing the rotational speed of the inner cylinder. The numerical method and accuracy were verified by experiments. The selected turbulence model was then applied for numerical simulation of the Taylor Couette flow in a simplified air gap model of an aviation motor with smooth inner and outer walls. The Taylor Couette flow characteristics in the air gap under varying rotational speed were studied, and simulation results were given for flow with axial flow and without axial flow. © The Institution of Engineering & technology 2024.

关键词： Axial flow

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Use Anchor-Free Based Object Detectors to Detect Surface Defects

Use Anchor-Free Based Object Detectors to Detect Surface Def...

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TEPEN International Workshop on Fault Diagnostics and Prognostics, TEPEN-IWFDP 2024

作者： Liu, Jiaxue Zhang, Chao Li, Jianjun College of Mechanical Engineering Inner Mongolia University of Science and Technology Baotou014000 China Inner Mongolia Autonomous Region Key Laboratory of Intelligent Diagnosis and Control of Electromechanical Systems Baotou014010 China College of Information Engineering Inner Mongolia University of Science and Technology Baotou014000 China

ISBN: (纸本)9783031702341

Many anchor-based object detectors have limitations in the detection process because of the presence of anchors. Therefore, in recent years, many researchers have shifted their focus to designing anchor-free object detectors. In this paper, we initially employ several common anchor-free detectors (CenterNet, FCOS, YOLOX-S, and YOLOV8-S) to detect surface defects in the hot-rolled strip datasets from Northeastern University (NEU-DET). Following experimental comparisons, YOLOV8-S demonstrates the best detection performance (mAP is 78.04% and the FPS is 8.45). Secondly, we utilize transfer learning to mitigate the overfitting problem that large models can induce on small datasets. Finally, we conduct a large number of experimental comparisons to verify the effectiveness of the model. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.

关键词： Transfer learning

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Intelligent multi-component fault diagnosis method driven by vibration-mapped images of mechanical transmission system

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Zhendong yu Chongji/Journal of Vibration and Shock 2025年第12期44卷 201-211页

作者： Fan, Hongwei Zhang, Teng Xu, Haowen Li, Qingshan Chen, Buran Li, Pengfei School of Mechanical Engineering Xi'an University of Science and Technology Xi'an710054 China Key Laboratory of Intelligent Detection and Control of Mining Electromechanical Equipment of Shaanxi Province Xi'an710054 China

In order to realize the intelligent multi-component fault diagnosis of bearings, rotors and gears in a mechanical transmission system under low speed, weak faults and few measurement points, a fault diagnosis method based on improved vibration-mapped gray texture images (GTIs) and multi-scale lightweight convolutional neural network was proposed. An improved gray texture image with enhanced features was obtained by robust local binary pattern (RLBP) on the traditional gray image. Based on the standard convolutional neural network (CNN), a multi-scale lightweight CNN (MSLCNN) model was constructed by adding batch normalization, multi-scale convolution and simplified full connection layer. The fault diagnosis experiment under 700 r/min and a single measurement point was designed, and seven typical faults of bearings, rotors and gears were simulated. The investigation shows that the model parameters of the proposed fault diagnosis method are 0.30 M, the floating point operations (FLOPs) are 127.22 M, the model size is 1. 17 MB, and the average diagnostic accuracy is 98.42%. It provides a new feasible approach for the data-driven multi-component fault diagnosis of the mechanical transmission system based on the deep learning. © 2025 Chinese Vibration Engineering Society. All rights reserved.

关键词： Convolutional neural networks

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UAV Training control and Evaluation Method Based on dynamic Task Construction 17th

UAV Training Control and Evaluation Method Based on Dynamic ...

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17th Chinese Intelligent Systems Conference, CISC 2021

作者： Tong, Jiahui Zhang, Qing Ran, Jian Science and Technology on Complex System Control and Intelligent Agent Cooperation Laboratory Beijing China Beijing Electromechanical Engineering Institute Beijing China

ISBN: (纸本)9789811663277

In view of the problems such as high cost, low training efficiency and lack of versatility, a design scheme of UAV simulation training system based on dynamic mission construction is proposed, and the reproducing dynamic mission environment simulation technology and UAV training control and result evaluation and method are described in detail. The evaluation system of UAV simulation training results based on multi-factor influence data is constructed, which can effectively guide the simulation training of multi-type UAV and improve the overall training effect of UAV operators by synthesizing historical training data and real-time training data. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Unmanned aerial vehicles (UAV)

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Research on Simulation Method of Space-Ground Consistency for UAV Cluster Combat

Research on Simulation Method of Space-Ground Consistency fo...

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International Conference on Autonomous Unmanned Systems, ICAUS 2021

作者： Qing, Zhang Jing, Li Jiahui, Tong Jian, Han Science and Technology on Complex System Control and Intelligent Agent Cooperation Laboratory Beijing China Beijing Electromechanical Engineering Institute Beijing China

ISBN: (纸本)9789811694912

The Space-ground consistency of the unmanned aerial vehicle (UAV) cluster combat distributed interactive simulation system is the fundamental guarantee to simulate and reproduce the authenticity and correctness of UAV cluster combat mission, combat environment and combat process. This paper analyzes the common inconsistency problems of UAV cluster combat distributed simulation system, gives the technical connotation of the space-ground consistency of UAV cluster combat simulation, deeply analyzes all kinds of factors that affect the consistency of UAV cluster combat simulation space and ground, and puts forward the control methods of time-space consistency of UAV cluster combat simulation system, the control strategies and suggestions of model consistency and service consistency. It provides a theoretical basis and technical support for the construction of distributed interactive simulation system for UAV cluster combat. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Unmanned aerial vehicles (UAV)

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