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A constant quasi-zero stiffness isolator with tension springs to isolate vibrations with ultralow frequency

International Journal of Non-Linear Mechanics 2025年 175卷

作者： Zhao, Feng Ji, J.C. Cao, Shuqian Zheng, Jingyang Luo, Quantian Department of Mechanics Tianjin University Tianjin300354 China Tianjin Key Laboratory of Nonlinear Dynamics and Control National Key Laboratory of Vehicle Power System Tianjin300354 China College of Mechanical and Electrical Engineering Henan Key Laboratory of Intelligent Manufacturing of Mechanical Equipment Zhengzhou University of Light Industry Zhengzhou450002 China School of Mechanical and Mechatronic Engineering University of Technology Sydney NSW2007 Australia College of Vehicle and Traffic Engineering Henan University of Science and Technology Luoyang471003 China

Many types of quasi-zero stiffness (QZS) isolators have been developed to isolate vibrations with low frequencies. However, isolating vibrations with ultralow frequency as low as 1 Hz is still a great challenge even in laboratory tests due to the high damping of QZS prototypes. To address this issue, a novel isolator with intrinsically light damping is proposed by configurating tension springs and oblique bars. The linear or nonlinear negative stiffness generated by the horizontal tension springs and oblique bars counteracts the linear positive stiffness of the vertical tension springs to obtain the QZS-related features including nonlinear QZS, constant positive or negative dynamic stiffness, constant QZS, and constant zero stiffness. Two QZS conditions are derived and the influence of parameters on QZS is thoroughly studied. The proposed isolator with tension springs has obvious differences from the previous isolator with compression springs in terms of QZS conditions, as well as force and stiffness expressions. Then, the displacement transmissibility is calculated by using the increment harmonic balance method and the continuous arc-length algorithm, which is verified by the classical harmonic balance method. These methods have the same prediction result. Finally, a prototype is fabricated and tested. The smoother force curves with constant QZS and the higher transmissibility amplitude can be obtained in tests compared to the previous isolator with compression springs under the same configuration parameters, which verifies the theoretical formulations of the proposed isolator with light damping. The prototype is further improved by replacing linear bearings with sliders to reduce the frictional effects. As a result, vibrations with ultralow frequencies lower than 1 Hz are successfully isolated. The proposed isolator has a wider frequency band and lower transmissibility than the previous isolator with compression springs. This study offers an effective method of de

关键词： Damping

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The Detection of Typical Targets under the Background of Land War 29

The Detection of Typical Targets under the Background of Lan...

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第29届中国控制与决策会议

作者： Xiaowen Wu Wenjie Chen Yingying Qin State Key Laboratory of Intelligent Control and Decision Complex System Beijing Institute of Technology

ISBN: (纸本)9781509046584

This paper investigates whether advanced neural network techniques can be applied to the detection and identification of typical targets in the context of land warfare. We collected 13 typical targets and built a detection data set. Based on the Faster R-CNN framework, we improve the detection accuracy by two ways. First, we design a neural network model with strong local modeling capabilities. Second, we combine middle layers and the last layer of feature maps as the detection features to enhance the detection ability and improve the detection accuracy.

关键词： Deep Learning Convolutional Neural Network Local Modeling Capability Object Detection

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Echo state network based symbol detection in chaotic baseband wireless communication

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Digital Communications and Networks 2023年第6期9卷 1319-1330页

作者： Huiping Yin Chao Bai Haipeng Ren Shaanxi Key Laboratory of Complex System Control and Intelligent Information Processing Xi'an University of TechnologyXi'an710048China Xi'an Key Laboratory of Intelligent Equipment Xi'an Technological UniversityXi'an710021China

The Chaotic Baseband Wireless Communication system(CBWCS)is expected to eliminate the Inter-Symbol Interference(ISI)caused by multipath propagation by using the optimal decoding threshold that is the sum of the ISI caused by past decoded bits and the ISI caused by future transmitting ***,the current technique is only capable of removing partial effects of the ISI,because only past decoded bits are available for the suboptimal decoding threshold *** unavailability of the future information needed for the optimal decoding threshold is an obstacle to further improve the Bit Error Rate(BER)*** contrast to the previous method using Echo State Network(ESN)to predict one future bit,the proposed method in this paper predicts the optimal decoding threshold directly using *** proposed ESN-based threshold prediction method simplifies the symbol decoding operation by avoiding the iterative prediction of the output waveform points using ESN and accumulated error caused by the iterative *** this approach,the calculation complexity is reduced compared to the previous ESN-based *** proposed method achieves better BER performance compared to the previous *** reason for this superior result is ***,the proposed ESN is capable of using more future symbols information conveyed by the ESN input to obtain more accurate threshold rather than the previous method in which only one future symbol was ***,the proposed method here does not need to estimate the channel information using Least Squared(LS)method,which avoids the extra error caused by inaccurate channel information *** results and experiment based on a wireless open-access research platform under a practical wireless channel show the effectiveness and superiority of the proposed method.

关键词： Chaotic baseband wireless communication system(CBWCS) Inter-symbol interference(ISI) Echo state network(ESN) Threshold prediction

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A Fine-Grained Object Detection Model for Aerial Images Based on YOLOv5 Deep Neural Network

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Chinese Journal of Electronics 2023年第1期32卷 51-63页

作者： ZHANG Rui XIE Cong DENG Liwei Heilongjiang Provincial Key Laboratory of Complex Intelligent System and Integration School of AutomationHarbin University of Science and Technology

Many advanced object detection algorithms are mainly based on natural scenes object and rarely dedicated to fine-grained objects. This seriously limits the application of these advanced detection algorithms in remote sensing object detection. How to apply horizontal detection in remote sensing images has important research significance. The mainstream remote sensing object detection algorithms achieve this task by angle regression, but the periodicity of angle leads to very large losses in this regression method, which increases the difficulty of model learning. Circular smooth label(CSL)solved this problem well by transforming the regression of angle into a classification form. YOLOv5 combines many excellent modules and methods in recent years, which greatly improves the detection accuracy of small *** use YOLOv5 as a baseline and combine the CSL method to learn the angle of arbitrarily oriented targets,and distinguish the fine-grained between instance classes by adding an attention mechanism module to accomplish the fine-grained target detection task for remote sensing images. Our improved model achieves an average category accuracy of 39.2% on the FAIR1M dataset. Although our method does not achieve satisfactory results,this approach is very efficient and simple, reducing the hardware requirements of the model.

关键词： Deep learning Neural networks Object detection Transformers Hardware Classification algorithms Task analysis

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Contact Force Optimization to Enhance Fault-tolerant Motion Stability of a Hexapod Robot

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Journal of Bionic Engineering 2024年第5期21卷 2199-2214页

作者： Bo You Shangdong Shi Chen Chen Jiayu Li Nan Li Liang Ding The Key Laboratory of Intelligent Technology for Cutting and Manufacturing Ministry of Education and the Heilongjiang Provincial Key Laboratory of Complex Intelligent System and Integration Harbin University of Science and TechnologyHarbin150080China The State Key Laboratory of Robotics and System Harbin Institute of TechnologyHarbin150001China

This paper presents a novel method for optimizing the contact force of a hexapod robot to enhance its dynamic motion stability when one of its legs *** proposed approach aims to improve the Force Angle Stability Margin(FASM)and adapt the foot trajectory through contact force optimization to achieve safe and stable motion on various *** foot force optimization approach is designed to optimize the FASM,a factor rarely considered in existing contact force optimization *** formulating the problem of enhancing the motion stability of the hexapod robot as a Quadratic Programming(QP)optimization problem,this approach can effectively address this *** of a hexapod robot using a fault-tolerant gait,along with real field experiments,were conducted to validate the effectiveness and feasibility of the contact force optimization *** results demonstrate that this approach can be used to design a motion controller for a hexapod robot with a significantly improved motion *** summary,the proposed contact force optimization method offers a promising solution for enhancing the motion stability of hexapod robots with single leg failures and has the potential to significantly advance the development of fault-tolerant hexapod robots for various applications.

关键词： Hexapod robot Fault-tolerant Stability margin Contact force optimization

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A survey on Lyapunov-based methods for stability of linear time-delay systems

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Frontiers of Computer science 2017年第4期11卷 555-567页

作者： Jian SUN Jie CHEN School of Automation Beijing Institute of Technology Beijing 100081 China Key Laboratory of Intelligent Control and Decision of Complex System Beijing Institute of Technology Beijing 100081 China

Recently, stability analysis of time-delay systems has received much attention. Rich results have been obtained on this topic using various approaches and techniques. Most of those results are based on Lyapunov stability theories. The purpose of this article is to give a broad overview of stabil- ity of linear time-delay systems with emphasis on the more recent progress. Methods and techniques for the choice of an appropriate Lyapunov functional and the estimation of the derivative of the Lyapunov functional are reported in this ar- ticle, and special attention is paid to reduce the conservatism of stability conditions using as few as possible decision vari- ables. Several future research directions on this topic are also discussed.

关键词： time-delay system,ity delay-dependent stability,Lyapunov-Krasovskii functionaldelay-independent stabil-linear matrix inequality,

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Infrared small target detection algorithm with complex background based on YOLO-NWD 22

Infrared small target detection algorithm with complex backg...

引用

4th International Conference on Image Processing and Machine Vision, IPMV 2022

作者： Zhou, Xiao Jiang, Lang Guan, Xujun Mou, Xingang Wuhan University Of Technology China Science And Technology On Complex System Control And Intelligent Agent Cooperation Laboratory China

ISBN: (纸本)9781450395823

Because of small number of occupied pixels, lacking shape and texture information, the reliability of infrared remote target detection has always been a difficult research topic. To improve the accuracy and precision of detection of infrared small targets under complex background conditions, a deep learning-based infrared small target detection algorithm YOLO-NWD is proposed. According to the characteristics of small and medium targets in infrared images, multi-channel feature fusion image was used as the input of YOLO detection framework combined with image preprocessing method. Combined with SE module and ASPP module, feature weights are explored to improve feature utilization efficiency. Finally, the normalized Wasserstein distance (NWD) loss is used to replace the original IoU calculation loss to reduce the sensitivity of small target position deviation. The experimental results show that the algorithm proposed in this paper improves the accuracy by 2.5% and the recall rate by 4%. © 2022 ACM.

关键词： Deep learning

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A Noise-Excitation Generative Adversarial Network for Actuator Fault Diagnosis of Multi-legged Robot

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无人系统（英文） 2023年第2期11卷 159-173页

作者： Liling Ma Jian Guo Jiehao Li Junzheng Wang State Key Laboratory of Complex System Intelligent Control and Decision School of Automation Beijing Institute of TechnologyBeijing 100081P.R.China

This research provides a novel approach for detecting multi-legged robot actuator *** most significant concept is to design the Fault Diagnosis Generative Adversarial Network(FD-GAN)to fully adapt to the fault diagnosis problem with insufficient *** found that it is difficult for methods based on classification and prediction to learn failure patterns without enough data.A straightforward solution is to use massive amounts of normal data to drive the diagnostic *** introduce frequency-domain information and fuse multi-sensor data to increase the features and expand the difference between normal data and fault data.A GAN-based framework is designed to calculate the probability that the enhanced data belongs to the normal *** uses a generator network as a feature extractor,and uses a discriminator network as a fault probability evaluator,which creates a new use of GAN in the field of fault *** the many learning strategies of GAN,we find that a key point that can distinguish the two types of data is to use the hidden layer noise with appropriate discrimination as the *** also design a fault location method based on binary search,which greatly improves the search efficiency and engineering value of the entire *** have conducted a lot of experiments to prove the diagnostic effectiveness of our architecture in various road conditions and working *** compared FD-GAN with popular diagnostic *** results show that our method has the highest accuracy and recall rate.

关键词： Actuator fault diagnosis multi-legged robot generative adversarial network attention mechanism

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Behavior-based cooperative control method for fixed-wing UAV swarm through a virtual tube considering safety constraints

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Chinese Journal of Aeronautics 2025年

作者： Siyi YUE Duo ZHENG Mingjun WEI Zhichen CHU Defu LIN School of Astronautics Engineering Beijing Institute of Technology Beijing 100081 China National Key Laboratory of Complex System Control and Intelligent Agent Cooperation Yungang Street Beijing 100074 China

Unmanned Aerial Vehicle (UAV) swarm collaboration enhances mission effectiveness. However, fixed-wing UAV swarm flights face collaborative safety control problems within a limited airspace in complex environments. Aimed at the cooperative control problem of fixed-wing UAV swarm flights under the airspace constraints of a virtual tube in a complex environment, this paper proposes a behavior-based distributed control method for fixed-wing UAV swarm considering flight safety constraints. Considering the fixed-wing UAV swarm flight problem in complex environment, a virtual tube model based on generator curve is established. The tube keeping, centerline tracking and flight safety behavioral control strategies of the UAV swarm are designed to ensure that the UAV swarm flies along the inside of the virtual tube safety and does not go beyond its boundary. On this basis, a maneuvering decision-making method based on behavioral fusion is proposed to ensure the safe flight of UAV swarm in the restricted airspace. This cooperative control method eliminates the need for respective pre-planned trajectories, reduces communication requirements, and achieves a high level of intelligence. Simulation results show that the proposed behavior-based UAV swarm cooperative control method is able to make the fixed-wing UAV swarm, which is faster and unable to hover, fly along the virtual tube airspace under various virtual tube shapes and different swarm sizes, and the spacing between the UAVs is larger than the minimum safe distance during the flight.

关键词： Unmanned aerial vehicles (UAV) UAV swarm Distributed cooperative control Swarm flight safety Behavior-based method Virtual tube airspace

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Condition Monitoring for Railway Point Machines Based on Sound Analysis and Support Vector Machine

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Chinese Journal of Electronics 2020年第4期29卷 786-792页

作者： SUN Yongkui CAO Yuan XIE Guo WEN Tao School of Electronic and Information Engineering Beijing Jiaotong University National Engineering Research Center of Rail Transportation Operation and Control System Beijing Jiaotong University Shaanxi Key Laboratory of Complex System Control and Intelligent Information Processing Xi'an University of Technology

Railway point machines(RPMS) are one of the key equipments in the railway system to switch different routes for the *** monitoring for RPMs is a vital measure to keep train operation safe and *** convenience and low cost into consideration, a novel intelligent condition monitoring method for RPMs based on sound analysis is ***-domain and frequency-domain features are obtained,and normalized using z-score standardization method to eliminate the influences of different *** particle swarm optimization(BPSO) is utilized to select the most significant discrimination feature *** effects of the selected optimal features are verified using Support vector machine(SVM), 1-Nearest neighbor(1 NN), Random forest(RF), and Naive Bayes(NB).Experiment results indicate SVM performs best on identification accuracy and computing cost compared with the other three *** identification accuracies on normal switching and reverse switching processes reach100% and 99.67%, respectively, indicating the feasibility of the proposed method.

关键词： Condition monitoring Sound analysis Railway point machines(RPMs) Binary particle swarm optimization(BPSO) Support vector machine(SVM)

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