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A Review of Machine Tool Motorized Spindle Variable Pressure Preload technology Research

Recent Patents on engineering 2025年第5期19卷

作者： Dai, Ye Deng, Hao Pan, Gaofeng Chen, Xinda Key Laboratory of Advanced Manufacturing and Intelligent Technology Ministry of Education School of Mechanical and Power Engineering Harbin University of Science and Technology Harbin150080 China School of College of Measurement and Control Technology and Communication Engineering Harbin University of Science and Technology Harbin150080 China

High-precision spindles are a vital study topic because of the growing demand for high-speed, high-precision, reliable, and long-lasting machine tools. Bearing preload is the primary means of improving the accuracy of the spindle rotor system. This patent study aims to summarize the research results, systematically analyze and evaluate the machine tool motorized spindle variable pressure preload technology, and provide a scientific basis for the practical application of the motor spindle variable pressure preload technology. This study is an in-depth analysis of the basic principles of the electric spindle preloading technology, the study of its influence mechanism on the thermal deformation, stiffness, slewing error, and life of the spindle system, and a discussion of the current shortcomings in the field of spindle preloading to provide a reference for the subsequent optimization. In the spindle system, the performance of rolling bearings and the design of bearing preload have an important impact on the spindle's accuracy and stability. The traditional preload method has yet to meet the requirements of modern high-speed machine tools. Real-time controllable preload has become the new direction of development, but the current preload technology still has certain limitations and needs to be further improved. In the future, the spindle bearing variable pressure preload technology will be more efficient and intelligent. © 2025 Bentham Science Publishers.

关键词： Machine tools

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OS-SEI: Open-Set Specific Emitter Identification Based on Outlier Exposure and Label Smoothing

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IEEE Internet of Things Journal 2025年

作者： Wang, Juzhen Wang, Hanhong Wang, Wei Zha, Haoran Hangzhou Dianzi University School of Communication Engineering Hangzhou310018 China Binjiang Institute of Artificial Intelligence of Zhejiang University of Technology Hangzhou310052 China Science and Technology on Communication Information Security Control Laboratory Jiaxing314033 China Harbin Engineering University College of Information and Communication Engineering Harbin150009 China

Specific Emitter Identification (SEI), based on the inevitable hardware imperfections of emitters, plays a crucial role in physical layer security, independent of upper-layer cryptographic methods. In recent years, SEI combined with deep learning has demonstrated exceptional performance and considerable potential. However, most SEI methods are designed for closed, independent identically distributed environments, which contrasts with real-world open scenarios. This discrepancy leads to significant security vulnerabilities when deploying models in practical applications. To address this challenge, we propose a novel Open-Set SEI (OS-SEI) framework, Outlier Exposure with Label Smoothing (OELS), which utilizes partial exposure to auxiliary anomalous data during the training phase and introduces specific loss functions to mitigate the open-set risk. By constructing smooth decision boundaries through label smoothing and applying thresholds to class confidence, our SEI framework demonstrates robust open-set authentication capabilities. Extensive experiments conducted on ADS-B and WiFi datasets show that the OELS method achieves outstanding open-set recognition performance, with F1 scores of 83.77% and 93.14% at an openness level of 0.10557. Furthermore, ablation experiments confirm the effectiveness and potential of our framework’s components. By increasing the diversity of auxiliary unknown data, we further improve performance in OS-SEI tasks. © 2014 IEEE.

关键词： Hardware security

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Multiclass Classification of Remote Sensing Images Using Deep Learning Techniques

Multiclass Classification of Remote Sensing Images Using Dee...

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IEEE International Symposium on Geoscience and Remote Sensing (IGARSS)

作者： Tahir Arshad Zhang Junping Qingyan Wang School of Electronics and Information Engineering Harbin Institute of Technology China School of Measurement-Control and Communication Engineering Harbin University of Science and Technology

Deep learning has strong learning ability to extract the features from Image datasets. In recent years, deep networks especially deep convolutional neural networks have revolutionized this field. When exposed to a huge number of datasets and their labels, deep learning techniques like Convolutional Neural Networks (CNNs) can produce precise categorization results. However, employing CNNs with scant labeled data might have a number of issues, including the problem of heavy overfitting. Convolutional Neural Networks are the backbone of modern deep learning architectures for the purpose of image classification. We solved image classification problem with different architectures and compare their performances. The objective of this work lies in the approach to study the given datasets. We use domain adaptation approach to highlight the underlying characteristics of these datasets and the different parameters (activation function, weights, regularization, neural simulation etc.) associated with these architectures. In our work, we use three datasets—RS19, UC Merced, and EuroSat images—were utilized in the CNN implementation to training the suggested model. The obtained results effectively demonstrate the local representation capacity of CNNs. Furthermore, this work shows that transfer learning improves classification outcomes in optical remote sensing images, particularly when the training sample is small.

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A Collaborative Jamming Algorithm Based on Multi-UAV Scheduling 23

A Collaborative Jamming Algorithm Based on Multi-UAV Schedul...

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23rd IEEE International Conference on communication technology, ICCT 2023

作者： Jiang, Yixin Zhou, Lingyun Tang, Yijia Tu, Ya Liu, Chunhong Shi, Qingjiang Science and Technology on Communication Information Security Control Laboratory Jiaxing314033 China School of Software Engineering Tongji University Shanghai201804 China Shenzhen Research Institute of Big Data Shenzhen518172 China

ISBN: (纸本)9798350325959

In this paper, we consider the problem of multi-unmanned aerial vehicles' (UAVs), scheduling for cooperative jamming, where UAVs equipped with directional antennas perform collaborative jamming tasks against several targets of interest. To ensure effective jamming towards the targets, we formulate it as an non-convex optimization problem, aiming to minimize the communication performance of the targets by jointly optimizing UAVs' deployment and directional antenna orientations. Due to the unique structure of the problem, we derive an equivalent transformation by introducing a set of auxiliary matrices. Subsequently, we propose an efficient iterative algorithm based on the alternating direction method of multi-pliers (ADMM), which decomposes the problem into multiple tractable subproblems solved in closed-form or by gradient projection method. Extensive simulations validate the efficacy of the proposed algorithm. © 2023 IEEE.

关键词： ADMM improved Gradient Descend jamming system UAV deployment

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Unicast Beamforming in the Presence of a Smart Reactive Jammer: A Stackelberg Game Approach 24

Unicast Beamforming in the Presence of a Smart Reactive Jamm...

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24th IEEE International Workshop on Signal Processing Advances in Wireless communications, SPAWC 2023

作者： Shi, Bai Shao, Huaizhong Lin, Jingran Zhai, Zhikai University of Electronic Science and Technology of China School of Information and Communication Engineering Chengdu China Laboratory of Electromagnetic Space Cognition and Intelligent Control Beijing100083 China Peng Cheng Laboratory Shenzhen518055 China

ISBN: (纸本)9781665496261

The malicious jamming attacks will disrupt legitimate public wireless communication systems, which has become a critical issue that must be considered in modern communication system design. This paper considers an anti-jamming unicast transmit beamforming problem with a smart reactive jammer. We model this problem as a Stackelberg game and formulate a bilevel optimization problem, in which the base station maximizes the minimum signal-to-interference-jamming-noise ratio (SIJNR) of legitimate users and the jammer minimizes the maximum SIJNR. This problem is quite challenging due to its hierarchical structure and nonconvexity. A penalty method is developed to solve this problem, which transforms it into a mathematical program with equilibrium constraint (MPEC) problem after implementing a tight semi-definite relaxation (SDR) method. The numerical results demonstrate its superior performance. © 2023 IEEE.

关键词： Beamforming

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Optimal control Method for On-Ramp Merging on Highways Considering Fairness and Safety

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Journal of Traffic and Transportation engineering(English Edition) 2024年

作者： Sen Xia Haigen Min Yukun Fang Jianqiu Wang Jie Li Xiaobo Qu Xiangmo Zhao School of Information and Engineering， Chang'an University Innovation Center for Western China Traffic Safety and Intelligent Cooperative Control China Mobile (Shanghai) Information and Communication Technology Co.Ltd. Shandong Hi-Speed Information Group Co.Ltd. School of Vehicle and Mobility， Tsinghua University

On-ramp merging can generate a traffic bottleneck due to predictability and coordination issues between vehicles on the main road and those from the ramp， which may result in traffic congestion and accidents. Connected and automated vehicles (CAVs) with vehicle-to-everything(V2X) communication have the potential to improve vehicles coordination and facilitate merging. Current research mainly focuses on enhancing traffic efficiency and reducing fuel consumption， neglecting the importance of fairness in right-of-way allocation and vehicle safety during merging. Thus， in this study， a double-layer optimized ramp-merge control model is proposed， where the upper layer aims to determine the merging sequence considering both fairness and efficiency， and the lower layer focuses on trajectory optimization considering safety constraints. Simulation results show that the proposed method reduces driving delays by 28.88% on average compared with the first-in-first-out method， and decreases unfair delay percentage in the merging sequence by 76.38% on average compared with the short delay method， validating the advantage of the proposed method in both traffic efficiency and fairness. Furthermore， compared with the Hamiltonian analysis method and the boundary adjustment method， the proposed model significantly reduces security risks by 63.47% and 65.14% respectively. Comparison of the results of the proposed method with NGSIM data further demonstrates the effectiveness of the proposed method.

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Weak Signal Detection based on Beta Divergence 24

Weak Signal Detection based on Beta Divergence

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24th IEEE International Workshop on Signal Processing Advances in Wireless communications, SPAWC 2023

作者： Liu, Jiahao Liu, Haoxuan Pu, Wenqiang Zhou, Rui You, Ming-Yi Shi, Qingjiang Science and Technology on Communication Information Security Control Laboratory Jiaxing China The Chinese University of HongKong Shenzhen Research Institute of Big Data Shenzhen China Tongji University School of Software Engineering Shanghai China

ISBN: (纸本)9781665496261

Among different electromagnetic spectrum monitoring tasks, a fundamental one is detecting the presence of weak communication signal under non-cooperative setting. Various detection methods have been studied in the literature. These detection methods usually construct a proper hypothesis testing metric to distinguish the signal-plus-noise and noise-only signals. Information entropy based metric has recently been studied and shown its superiority over traditional energy based metrics. We find that it can be explained as a realization of the general Kullback-Leibler divergence. Inspired by that, in this paper, we propose to detect the signal using a statistic divergence called β-divergence. Different choices of β will lead to several well known divergences, e.g., Itakura-Saito divergence and Euclidean distance. We study its detection performance for non-cooperative signal sources. Both simulation and real experiments demonstrate that β-divergence can improve detection performance for various modulation types of communication signals. © 2023 IEEE.

关键词： Cooperative communication

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The Anti-Interference Algorithm of BPSK Spread Spectrum Signal Based on Generative Adversarial Networks 7

The Anti-Interference Algorithm of BPSK Spread Spectrum Sign...

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7th International Conference on Signal and Image Processing, ICSIP 2022

作者： Han, Yu Zhang, Minghong Shen, Lei Wang, Lijun The 36th Research Institute of China Electronics Technology Group Corporation Science and Technology on Communication Information Security Control Laboratory Jiaxing China Hangzhou Dianzi University School of Communication Engineering Hangzhou China

ISBN: (数字)9781665495639

ISBN: (纸本)9781665495639

In order to avoid the problem of unsatisfactory anti-jamming effect when the interference feature extraction of traditional anti-jamming algorithm is inaccurate, this paper takes BPSK spread spectrum signal as the research object, and proposes an anti-jamming algorithm for BPSK spread spectrum signal based on generative adversarial network. The algorithm firstly despreads the spread spectrum signal, and then images the despread signal, and uses the known disturbed despread signal set and undisturbed signal set for network training. The mapping relationship between the disturbed despread signal image and the undisturbed despread signal image is constructed by generative adversarial network, so as to achieve the purpose of interference suppression. Experiments show that the signal anti-jamming algorithm based on generative adversarial network proposed in this paper has better interference suppression ability than the frequency-domain notch anti-jamming algorithm under multi-tone interference and narrow-band noise interference. © 2022 IEEE.

关键词： Frequency domain analysis

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Influence of Physical Parameters on Echo Spectrum of Underwater Target

Influence of Physical Parameters on Echo Spectrum of Underwa...

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IEEE/OES China Ocean Acoustics (COA)

作者： Yunfei Chen Dapeng Yu Bing Jia Zhenshan Wang Jintao Yong Yanjie Wang School of Information and Communication Engineering Dalian University of Technology Dalian China Science and Technology on Underwater Test and Control Laboratory Dalian China

ISBN: (数字)9798350340297

ISBN: (纸本)9798350340303

The elastic scattering features of the underwater target scattering wave depend on the physical parameters of the target, such as the material and structure. Intuitively evaluating the influence of the elastic scattering wave on the characteristics of the whole scattering wave signal is difficult due to the coupling and superposition of the elastic scattering wave and the geometric scattering wave of the target. Based on the different modulation characteristics of broadband echo spectrum produced by target geometry scattering and elastic scattering wave, this paper characterizes and studies the modulation features of echo spectrum and tests the influence of physical parameters on the echo spectrum of underwater target using several simple cylindrical targets with different physical parameters. Moreover, the geometric scattering wave and the elastic scattering wave of the simple target echo are extracted using the fractional Fourier transform (FrF $T$ ) domain filtering method, and the influence of physical parameters on the echo spectrum is quantitatively analyzed.

关键词： Geometry Couplings Fourier transforms Filtering Oceans Scattering Modulation Feature extraction Acoustics Broadband communication

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Frequency Agile Strategy Design of Radar Network for Wideband Sweep Jamming via Coalition Formation Game

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IEEE Transactions on Aerospace and Electronic Systems 2025年

作者： Liao, Maosen Xiong, Kui Zhang, Long Yu, Xianxiang Cui, Guolong University of Electronic Science and Technology of China School of Information and Communication Engineering Chengdu611731 China Laboratory of Electromagnetic Space Cognition and Intelligent Control Technology Beijing100089 China School of Information and Communication Engineering Chengdu611731 China UESTC Shenzhen Institute for Advanced Study Chengdu611731 China

This article proposes an intelligent frequency agile design strategy for radar network using coalition game theory to counter wideband sweep jamming, which is formulated as a two-stage decision-making problem. In the first stage, the entire frequency agile range is divided into several non-overlapping agile subrange, and each radar selects a frequency agile subrange to join, which is solved by the coalition formation algorithm. Then, after achieving a stable coalition partition, a distributed multi-agent reinforcement learning algorithm is developed to address the specific carrier frequency selection problem within each coalition. By combining these two stages of the frequency agile design strategy, a joint coalition formation game and distributed Q-learning algorithm (CFDQ) is proposed. Finally, numerical simulations are conducted to illustrate the superiority of the proposed algorithm over several typical frequency agile strategies. © 1965-2011 IEEE.

关键词： Jamming

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