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design and Analysis of Terminal Guidance Law for Kinetic Interceptors based on Pulse Engine

Journal of Electronic Research and Application 2024年第5期8卷 95-108页

作者： Shixin Li Jia Ma Shuai Yue School of Mechanical Engineering Nanjing University of Science and TechnologyNanjing 210094China Aerospace System Engineering Shanghai Shanghai 201100China Shanghai Key Laboratory of Spacecraft Mechanism Shanghai 201108China National Key Laboratory of Space Intelligent Control Beijing 100048China

A new terminal guidance law is proposed based on a solid propellant pulse engine and an improved proportional navigation method to address the terminal guidance issue for kinetic *** this basis,the start-stop curve of the pulse motor during the terminal guidance process is designed,along with its start-up *** effectiveness of the proposed guidance strategy is verified through simulation.

关键词： Pulse engine Terminal guidance law Kinetic interceptor Proportional navigation method

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Noninvasive Data-Driven Prediction of reactor Power Field: An MLP-Based Approach

Noninvasive Data-Driven Prediction of Reactor Power Field: A...

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Smart World Congress (SWC), IEEE

作者： Binhui Shi Qi Qiu Helin Gong Qing Li Yang Luo School of Computer University of South China Hengyang China ParisTech Elite Institute of Technology Shanghai Jiao Tong University Shanghai China Science and Technology on Reactor System Design Technology Laboratory Nuclear Power Institute of China Chengdu China

The reactor Operation Digital Twin (RODT) is a numerical representation method designed for the operational phase of nuclear reactors, aiming to solve forward problems (such as state prediction) based on input parameters and inverse problems (such as parameter identification) utilizing additional measurement data, in order to enhance the economic benefits and safety of nuclear power. In this paper, we propose a solution for the forward problem in RODT based on a Multilayer Perceptron (MLP) approach, where the MLP is used to directly learn the mapping relationship from low-dimensional inputs to high-dimensional outputs. Compared to previous methods, the proposed approach shows improved prediction accuracy, especially in situations with limited training data, demonstrating superior generalization capabilities and accuracy. To validate our contributions, we conducted a comparative experiment based on a engineering case, namely the reactor core simulation in the life cycle of a real-world nuclear ractor, which confirmed the effectiveness of the proposed method.

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Evaluation of the Dynamic Performance of a Novel Egg-shaped Underwater Robot

Evaluation of the Dynamic Performance of a Novel Egg-shaped ...

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IEEE International Conference on Mechatronics and Automation

作者： Jipeng Long Shuxiang Guo Chunying Li National Engineering Laboratory for Big Data System Computing Technology Shenzhen University Shenzhen China The Department of Electronic and Electrical Engineering Southern University of Science and Technology Shenzhen China The Aerospace Center Hospital School of Life Science and the Key Laboratory of Convergence Medical Engineering System and Healthcare Technology Ministry of Industry and Information Technology Beijing Institute of Technology Beijing China

ISBN: (数字)9798350388077

ISBN: (纸本)9798350388084

With the increasing demand for ocean exploration and underwater operations, the development of new autonomous underwater vehicles (AUVs) to adapt to specific marine environments has become crucial. This paper designed an innovative Egg-shaped Underwater Robot (EUR) aiming to optimize its mobility, stability and operational efficiency in complex underwater environments. Compared to traditional simulation robots of various types, the structure possessed the stability of a ball-shaped robot and the characteristics of a streamlined robot. The EUR adopted a unique elliptic structure to reduce underwater drag, improve maneuverability and enhance load capacity. Then, the overall design of the EUR was presented with detailed descriptions of the mechanical structure and electrical system respectively. Next, various motion states of the EUR and experimental validation were simulated by Computational Fluid Dynamics (CFD), and the experimental results showed that the motion characteristics of the EUR are acceptable, and the design was worthy of further study.

关键词： Autonomous underwater vehicles Mechatronics Computational fluid dynamics Oceans Propulsion Stability analysis Vectors

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Study on the Path Planning Based on A* Algorithm for Vascular Intervention Robots

Study on the Path Planning Based on A* Algorithm for Vascula...

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IEEE International Conference on Mechatronics and Automation

作者： Huiyin Xu Shuxiang Guo Chunying Li Sheng Cao National Engineering Laboratory for Big Data System Computing Technology Shenzhen University Shenzhen China The Department of Electronic and Electrical Engineering Southern University of Science and Technology Shenzhen China The Aerospace Center Hospital School of Life Science and the Key Laboratory of Convergence Medical Engineering System and Healthcare Technology Ministry of Industry and Information Technology Beijing Institute of Technology Beijing China

ISBN: (数字)9798350388077

ISBN: (纸本)9798350388084

In vascular interventional surgery, accurate path planning is essential to improve surgical success and reduce risk. This paper aimed to verify the effectiveness and practicability of the A* algorithm in the shortest path planning of vascular interventional surgical robot systems. Computed tomography angiography (CTA) vascular images were processed in advance to extract features and calibrate obstacles, simulating the path planning problem in vascular interventional surgery. The A* algorithm was then employed to search for the shortest path from the starting point to the endpoint. Based on the planned path, assistance could be provided to surgeons during operative procedures. The experimental results indicated that the A* algorithm effectively navigated obstacles and identified the shortest path. Moreover, through user-interactive design, this paper offered an intuitive operational experience, allowing users to interactively choose start and end points and display the algorithm’s search process and outcomes in real-time. This paper demonstrated the potential application of the A* algorithm within vascular structures and laid the groundwork for the future development of more efficient and intelligent systems for planning and navigating vascular interventional surgeries.

关键词： Medical robotics Mechatronics Navigation Computed tomography Surgery Feature extraction Path planning

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Deep Learning Based Fault Diagnosis for Chemical Process with Statistical Feature Fusion

Deep Learning Based Fault Diagnosis for Chemical Process wit...

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Chinese Control Conference (CCC)

作者： Lei Zhang Hao Xia Bao Cha School of Control Science and Control Engineering Dalian University of Technology Dalian P. R. China Science and Technology on Reactor System Design Technology Laboratory Nuclear Power Institute of China Chengdu P. R. China

The existing fault diagnosis methods based on deep neural networks mostly rely on process data for fault classification and diagnosis, which makes it difficult to distinguish minor faults with similar data features. Therefore, this paper proposes a deep learning-based fault diagnosis model that combines statistical indicators and neural networks. By analyzing and calculating the relevant information entropy to screen the statistical signal features of time domain and frequency domain, we can extract more hidden information from the raw data, and use the convolutional autoencoder to compress the statistical indicators for feature extraction, and use CNN network to extract features from raw data. Finally, the two sets of features are fused and input into the LSTM network to obtain temporal information for fault diagnosis. Tests conducted on the Tennessee Eastman (TE) process show that the proposed model outperforms typical classifiers and improves the diagnostic accuracy of minor faults.

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Effect of ECAP process on liquid distribution of AZ80M alloy during semi-solid isothermal heat treatment

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Transactions of Nonferrous Metals Society of china 2021年第6期31卷 1599-1611页

作者： Ling-ling FAN Ming-yang ZHOU Yang-yang GUO Yu-wen-xi ZHANG Gao-feng QUAN Key Laboratory of Advanced Technologies of Materials Ministry of EducationSchool of Materials Science and EngineeringSouthwest Jiaotong UniversityChengdu 610031China Science and Technology on Reactor System Design Technology Laboratory Nuclear Power Institute of ChinaChengdu 610213China

Two kinds of semi-solid samples of AZ80−0.2Y−0.15Ca(wt.%)(AZ80M)magnesium alloy were prepared by semi-solid isothermal heat treatment of materials with and without equal channel angular pressing(ECAP)*** microstructures of initial and semi-solid treated samples were compared and *** results showed a significant difference in the liquid phase distribution between three-pass ECAP processed(3P)and as-received samples during the isothermal heating *** semi-solid 3P sample showed a more uniform liquid distribution due to its smaller dihedral ***,the coarsening processes of solid grains of as-received and 3P samples were dominated by the coalescence and Ostwald ripening mechanism,*** difference of coarsening processes was mainly related to the proportion of the high-angle grain boundaries in materials,which further affected the evolution behavior of the liquid pools.

关键词： AZ80M equal channel angular pressing semi-solid microstructure liquid phase distribution coarsening mechanism

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Research on Data Optimization technology of Multi-Source Sensing Signal in Nuclear Power Plants

SSRN

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SSRN 2023年

作者： Liu, Yongchao Li, Tong Xiao, Kai Chen, Jie Tan, Xin Cheng, Jiahao Tan, Sichao Wang, Bo He, Zhengxi Shen, Jihong Gao, Puzhen Tian, Ruifeng College of Nuclear Science and Technology Harbin Engineering University Harbin150001 China Heilongjiang Provincial Key Laboratory of Nuclear Power System & Equipment Harbin Engineering University Harbin150001 China Science and Technology on Reactor System Design Technology Laboratory Nuclear Power Insitute of China Chengdu610213 China College of Mathematical Sciences Harbin Engineering University Harbin150001 China

The sensor signals collected by the nuclear power plant system equipment are mixed with complex noise information. The uncertainty of sensing data directly affects the application effect of artificial intelligence on nuclear power data mining. Traditional denoising methods have poor adaptability to different noisy data, are highly dependent on researchers, and take a long time. This paper proposes a data optimization technology based on a hybrid adaptive real-time denoising model, which can realize data distribution self-adaptation and algorithm super-parameter self-optimization according to the characteristics of noisy source data. Partition denoising processing of source data. The application of examples and simulation experiments show that this technology can effectively realize the optimization of nuclear power operation data, and provide important technical support for the engineering application of artificial intelligence technology in the complex noise environment of nuclear power plants. © 2023, The Authors. All rights reserved.

关键词： Nuclear energy

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NumbOD: A Spatial-Frequency Fusion Attack Against Object Detectors

arXiv

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arXiv 2024年

作者： Zhou, Ziqi Li, Bowen Song, Yufei Yu, Zhifei Hu, Shengshan Wan, Wei Zhang, Leo Yu Yao, Dezhong Jin, Hai National Engineering Research Center for Big Data Technology and System China Services Computing Technology and System Lab China Cluster and Grid Computing Lab Hubei Engineering Research Center on Big Data Security China Hubei Key Laboratory of Distributed System Security China School of Computer Science and Technology Huazhong University of Science and Technology China School of Cyber Science and Engineering Huazhong University of Science and Technology China School of Information and Communication Technology Griffith University Australia

With the advancement of deep learning, object detectors (ODs) with various architectures have achieved significant success in complex scenarios like autonomous driving. Previous adversarial attacks against ODs have been focused on designing customized attacks targeting their specific structures (e.g., NMS and RPN), yielding some results but simultaneously constraining their scalability. Moreover, most efforts against ODs stem from image-level attacks originally designed for classification tasks, resulting in redundant computations and disturbances in object-irrelevant areas (e.g., background). Consequently, how to design a model-agnostic efficient attack to comprehensively evaluate the vulnerabilities of ODs remains challenging and unresolved. In this paper, we propose NumbOD, a brand-new spatial-frequency fusion attack against various ODs, aimed at disrupting object detection within images. We directly leverage the features output by the OD without relying on its internal structures to craft adversarial examples. Specifically, we first design a dual-track attack target selection strategy to select high-quality bounding boxes from OD outputs for targeting. Subsequently, we employ directional perturbations to shift and compress predicted boxes and change classification results to deceive ODs. Additionally, we focus on manipulating the high-frequency components of images to confuse ODs' attention on critical objects, thereby enhancing the attack efficiency. Our extensive experiments on nine ODs and two datasets show that NumbOD achieves powerful attack performance and high stealthiness. Copyright © 2024, The Authors. All rights reserved.

关键词： Object detection

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Dual-Polarized Wideband Wide-Beam Millimeter-Wave Magneto-Electric Dipole Antenna

Dual-Polarized Wideband Wide-Beam Millimeter-Wave Magneto-El...

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Cross Strait Quad-Regional Radio science and Wireless technology Conference (CSRWTC)

作者： Linglong Gou Jing Ma Bin Shi Zhongbo Zhu Lin Peng Key laboratory of Microwave and Optical Wave Application Technology Guilin University of Electronic Technology Guilin Guangxi China The Science and Technology on special system simulation laboratory Beijing Simulation Center Beijing China The National Key Laboratory of Science and Technology on Space Microwave Xi'an China

In this manuscript, a dual-polarized wideband wide beamwidth magneto-electric (ME) dipole antenna for millimeter-wave mobile communication is proposed. As can be seen from the simulation results, this design exhibits excellent performance. Owing to the mutual resonances of the magnetic dipole and the electric dipole, large bandwidths of 64.8% and 59% (18.4 GHz-33 GHz and 17.29 GHz-33.9 GHz) are obtained for the two polarizations, respectively. The isolation between the two ports is greater than 25 dB. By loading metal vias, the antenna's beamwidth is widened to more than 100° through the whole operating band. The antenna size is $\mathbf{5}\mathbf{mm}\times \mathbf{5}\mathbf{mm}\times \mathbf{1.72}\mathbf{mm}$ , and this compact structure is quite suitable for using in beam scanning antennas.

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Breaking Barriers in Physical-World Adversarial Examples: Improving Robustness and Transferability via Robust Feature

arXiv

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arXiv 2024年

作者： Wang, Yichen Chou, Yuxuan Zhou, Ziqi Zhang, Hangtao Wan, Wei Hu, Shengshan Li, Minghui National Engineering Research Center for Big Data Technology and System China Services Computing Technology and System Lab China Cluster and Grid Computing Lab China Hubei Engineering Research Center on Big Data Security China Hubei Key Laboratory of Distributed System Security China School of Cyber Science and Engineering Huazhong University of Science and Technology China School of Computer Science and Technology Huazhong University of Science and Technology China School of School of Software Engineering Huazhong University of Science and Technology China

As deep neural networks (DNNs) are widely applied in the physical world, many researches are focusing on physical-world adversarial examples (PAEs), which introduce perturbations to inputs and cause the model’s incorrect outputs. However, existing PAEs face two challenges: unsatisfactory attack performance (i.e., poor transferability and insufficient robustness to environment conditions), and difficulty in balancing attack effectiveness with stealthiness, where better attack effectiveness often makes PAEs more perceptible. In this paper, we explore a novel perturbation-based method to overcome the challenges. For the first challenge, we introduce a strategy Deceptive RF injection based on robust features (RFs) that are predictive, robust to perturbations, and consistent across different models. Specifically, it improves the transferability and robustness of PAEs by covering RFs of other classes onto the predictive features in clean images. For the second challenge, we introduce another strategy Adversarial Semantic Pattern Minimization, which removes most perturbations and retains only essential adversarial patterns in AEs. Based on the two strategies, we design our method Robust Feature Coverage Attack (RFCoA), comprising Robust Feature Disentanglement and Adversarial Feature Fusion. In the first stage, we extract target class RFs in feature space. In the second stage, we use attention-based feature fusion to overlay these RFs onto predictive features of clean images and remove unnecessary perturbations. Experiments show our method’s superior transferability, robustness, and stealthiness compared to existing state-of-the-art methods. Additionally, our method’s effectiveness can extend to Large Vision-Language Models (LVLMs), indicating its potential applicability to more complex tasks. Copyright © 2024, The Authors. All rights reserved.

关键词： Deep neural networks

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