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Vibration-based structural health monitoring via deep learning techniques: A review

Vibration-based structural health monitoring via deep learni...

引用

2023 international conference on cyber-Physical Social Intelligence, ICCSI 2023

作者： Wang, Hao Wang, Baoli Jing, Yunge Wang, Pengling Yuncheng University School of Mathematics and Information Technology Yuncheng China Taiyuan Normal University School of Computer Science and Technology Jinzhong China

ISBN: (纸本)9798350312492

The vibration signal is closely related to abnormal states, which is an effective diagnostic tool in structural health monitoring (SHM) fields. Deep learning methods have got remarkable success in the detection of damage through vibration signals. This paper presents a systematic review of deep learning methods for SHM that utilizes vibration signal data from different model perspective. In recent years, there has been a tremendous increase in the number of research involving deep learning for vibration-based structural health monitoring. The accuracy of such works is equivalent to that of traditional machine learning approaches, and a better result could be achieved by integrating multiple approaches. Furthermore, we found that transfer learning methods yield the promising results when limited data is utilized to train the model. This paper provides a comprehensive review of existing deep learning research in SHM using vibration signal data from multiple perspectives and fulfills the gap that existing reviews lack in the discussion of transfer learning for SHM by presenting the highlights of the transfer learning. Finally, we summarize the contents of the paper and analyze the challenges of existing research to make recommendations for future work. © 2023 ieee.

关键词： Structural health monitoring

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Enhancing DDoS Attack Detection in SDN with a Stacked Model Framework Utilizing Deep Neural Networks

Enhancing DDoS Attack Detection in SDN with a Stacked Model ...

引用

2025 ieee international conference on Consumer Electronics, ICCE 2025

作者： Sharma, Aishita Singh, Sunil K. Kumar, Sudhakar Pan, Shin Hung Gupta, Brij B. Chui, Kwok Tai Department of CSE Chandigarh College of Engineering and Technology Chandigarh India Department of Information Management Asia University Taiwan Department of Computer Science and Information Engineering Asia University Taiwan University of Economics and Human Sciences Warsaw Poland Hong Kong Metropolitan University Hong Kong

ISBN: (纸本)9798331521165

Software Defined Networking enhances network management and security through centralized control, vital for the growth of consumer electronics. With the rise of smart devices and IoT systems, the demand for scalable network management has intensified. While SDN streamlines network operations and supports essential technologies, it remains vulnerable to DDoS attacks that can disrupt these services. However, SDN environments are vulnerable to Distributed Denial of Service (DDoS) attacks, posing significant risks to operational integrity. This paper analyzes the performance of various machine learning models at the individual level, providing insights into their effectiveness in detecting DDoS attacks. Based on these findings, a hybrid model is introduced, utilizing stacking techniques with a Deep Neural Network (DNN) as the meta-learner. The hybrid approach achieves a remarkable accuracy of 99.09%. The results underscore the crucial role of machine learning, particularly deep learning methodologies, in safeguarding SDN networks against cyber threats. As reliance on complex networked systems in consumer electronics increases, enhancing the security of SDN environments becomes essential for maintaining seamless operations. © 2025 ieee.

关键词： Machine learning

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Research on Stamping control System of Fixed Hole Based on PLC 3

Research on Stamping Control System of Fixed Hole Based on P...

引用

3rd international conference on Computer Science, Electronic Information Engineering and intelligent control technology, CEI 2023

作者： Meng, Panpan Jin, Xiaoyi Hu, Conghui Shanghai University of Engineering Science Shanghai201620 China

ISBN: (纸本)9798350372052

This article provides further analysis on the design, layout, and working principle of the automatic punching snake vertebra fixed hole conveyor line, and conducts research on the system control of the automatic punching snake vertebra fixed hole conveyor line based on PLC. With the objective of achieving automatic operation of the punching conveyor line, a punching control system flow is established. The Siemens S7-1200 PLC[1] is selected, and the TIA Portal V16 software is used for program design and coding. The program structure is built to realize the sorting of snake vertebrae in a specific direction by the vibrating disk, the feeding of the guide rail by the straight vibrator, the separation of individual snake vertebrae by the feeding mechanism, and the feeding, material retrieval, and punching by the robotic arm[2]. The analysis shows that the punching conveyor line can achieve manual/automatic operation and automatic alarm functions in the PLC control. © 2023 ieee.

关键词： control systems

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Cross-border Data Security Risk Analysis and Development Suggestions of the Protection Technologies for intelligent Connected Vehicles 5

Cross-border Data Security Risk Analysis and Development Sug...

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5th international conference on Information Science, Parallel and Distributed systems, ISPDS 2024

作者： Huang, Xiaolong Xin, Chongshi Ji, Haojie Lu, Wangdong He, Peng Chen, Yupeng State Key Laboratory of Intelligent Vehicle Safety Technology Chongqing China Key Laboratory of Modern Measurement & Control Technology Ministry of Education Beijing Information Science & Technology University Beijing China China Automotive Engineering Research Institute Co. Ltd Chongqing China

ISBN: (纸本)9798350352719

In recent years, intelligent connected vehicles (ICVs) have developed quickly and have been progressively introduced into the international market. Nevertheless, the operation of ICVs produces a large amount of important data coming from driving vehicle and necessitating cross-border transit. As the imperfections of the regulatory framework and the infancy of protective solutions for the ICV data, these data are vulnerable to the threats like eavesdropping and tampering during cross-border transmission. The private information, especially the data barred from leaving the country, will be probably leaked to other nations, endangering individual privacy and national security. Thus, the purpose of this manuscript is to analyze the security risks of cross-border data in ICVs and provide risk mitigation strategies. The legal requirements and pertinent cross-border materials need to be sorted out firstly to establish a thorough technical process for cross-border compliance of ICV data. Additionally, the ICV data risk analyses will be performed at every stage of the cross-border process. Furthermore, some efficient risk mitigation methods need to be offered to improve the security and dependability of the across-border data of ICVs. To address the problems associated with cross-border data pertaining to ICVs, a classification method for the cross-border data of ICVs will be presented according to current rules and data categorization schemes. Finally, this manuscript provides theoretical underpinnings and useful references for building a cross-border data security protection system, as well as a thorough analysis of the development patterns of cutting-edge technologies for cross-border data. © 2024 ieee.

关键词： cross-border data data security protection technology risk analysis

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Research and Application of Intermediate Experiment Digitization Basic Platform 5

Research and Application of Intermediate Experiment Digitiza...

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5th international conference on Consumer Electronics and Computer Engineering, ICCECE 2025

作者： Cao, Jian Zhao, Feng Liu, Ziming Tong, Deshui Wang, Yuanfang Wang, Shu Oil Production Technology Research Institute PetroChina Liaohe Oilfield Liaoning China

ISBN: (纸本)9798331533113

This paper focuses on the development and application of an intelligent basic platform for intermediate experiments, serving the oil production process. Through a series of methods such as hardware intelligent upgrading and transformation, establishing connections between programmable logic controllers and hardware devices based on Modbus protocol, designing configuration software to read and control display data in real time, the intelligent basic platform for intermediate experiments has been successfully developed. The research and development achievements include the design and completion of three sets of configuration systems, intelligent control of hardware working status, and real-Time data reading and graphical display, providing efficient and intelligent platform support for experimental research in the industry. © 2025 ieee.

关键词： data extraction digitization oil extraction plc software

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Trajectory Generation and Tracking Based on Energy Minimization for a Four-Link Brachiation Robot

Trajectory Generation and Tracking Based on Energy Minimizat...

引用

2023 ieee international conference on Unmanned systems, ICUS 2023

作者： Ji, Zishang Zhang, Xuanyu Wang, Xuanzhe Huang, Yan School of Mechatronical Engineering Beijing Institute of Technology Beijing China School of Mechantronical Engineering Beijing Institute of Technology Beijing China Beijing Advanced Innovation Center for Intelligent Robots and Systems Beijing Institute of Technology Beijing China Key Laboratory of Biomimetic Robots and Systems Ministry of Education Beijing China

ISBN: (纸本)9798350316308

Aiming to mimic the brachiation locomotion of primates, we establish a brachiation robot model capable of swinging between different bars. The robot's design is based on a four-link underactuated structure. We propose an offline trajectory generator with optimization for minimizing energy consumption, which is implemented by direct collocation method to generate joint-space trajectories. We also propose a linear Model Predictive control (MPC) algorithm as the feedback controller. The proposed MPC concurrently tracks both trajectories in joint space and Cartesian space. In simulation experiments, we analyzed the influence of lower-to-upper arm length ratio and swing time on the motion performance. The simulation results also demonstrate that the robot has satisfied ability in trajectory tracking, obstacle avoidance and robustness. © 2023 ieee.

关键词： Model predictive control

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Pioneering Privacy-First Approaches in IoT Healthcare with Secure Wearable Monitoring systems

Pioneering Privacy-First Approaches in IoT Healthcare with S...

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2025 international conference on intelligent control, Computing and Communications, IC3 2025

作者： Najm, Rusul Awasthy, Neeta Kumari, E.N.Vijaya Lakhannal, Sorabh Sharma, Tarunika Singh, Anurag Prashanthi, Bh. College of Medical Technology The Islamic University Radiology Techniques Department Najaf Iraq Gl Bajaj Group of Institutions Department of Computer Science and Engineering U.P. Mathura India Mlr Institute of Technology Department of Computer Science and Engineering Telangana Hyderabad India Lovely Professional University Phagwara India New Horizon College of Engineering Department of Applied Sciences Bangalore India Galgotias university Department of Electrical Electronics & Communication Engineering Uttar Pradesh Gerater Noida203201 India Griet Department of Cse Telangana Hyderabad India

ISBN: (纸本)9798331527495

In the world of IoT healthcare right now, protecting the privacy of patients' medical data collected by wearable tracking devices is an urgent and important issue. It is very important that this condition be met. The Secure Health Data Aggregation and Homomorphic Encryption (SHAHE) method is being thought about as a possible alternative while this investigation is going on. We thought about the need for processing, data collection, and access control as we worked on the SHAHE approach. We can fully reach this goal by using homomorphic cryptography and safe aggregation methods. The main goal of the program is to protect people's privacy by making data value analysis better and reducing unauthorized access to important health information. This is the reason why the program was made. © 2025 ieee.

关键词： Authentication

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Research on the Human-Machine Collaborative Optimisation Algorithm for intelligent Traffic Signal control systems

Research on the Human-Machine Collaborative Optimisation Alg...

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2024 international conference on Computing, Robotics and System Sciences, ICRSS 2024

作者： Li, Zhuoxun Chen, Junju Wu, Kefan Wu, Zhanyi Liu, Qiqi School of Swinburne Shandong University of Science and Technology Shandong Jinan China

ISBN: (纸本)9798331511296

With the worsening of urban traffic congestion, improving traffic flow and resource utilisation efficiency has become an important challenge in the field of intelligent transportation. Traditional traffic signal control systems lack dynamic adaptability and are difficult to cope with complex and ever-changing traffic environments. To address this problem, this paper proposes a bionic ant path planning algorithm based on human-machine collaborative optimisation. The system obtains real-time road traffic data, including information such as signal status, traffic flow and obstacle distribution, through a data acquisition module, and uses an improved ant colony algorithm to achieve global path search and dynamic optimisation. At the same time, a human-machine collaborative interaction mechanism is designed to allow users to adjust path weight parameters in real time according to actual needs, enhancing the flexibility and adaptability of the system. Through simulation experiments, this paper verifies the performance of the proposed algorithm in different scenarios and compares it with traditional path planning algorithms. The results show that the ant colony algorithm based on human-machine collaborative optimisation has significant advantages in terms of convergence speed, path optimisation effect and dynamic environmental adaptability. This study provides an efficient, real-time and flexible path optimisation solution for intelligent traffic signal control systems, which can effectively improve traffic scheduling capabilities in complex dynamic environments. © 2024 ieee.

关键词： Traffic congestion

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Cost-Effective Approach for Data Integration on Tire Stacking Machine Through Real-Time Industrial Machine Monitoring System

Cost-Effective Approach for Data Integration on Tire Stackin...

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2023 international conference on Advanced Mechatronics, intelligent Manufacture and Industrial automation, ICAMIMIA 2023

作者： Indasyah, Enny Yafi, Muhammad Ali Ghofoer, Rachmad Abdhael Frisiawan, Andi Istiqomah, Fivitria Institut Teknologi Sepuluh Nopember Electrical Automation Engineering Surabaya Indonesia Kyushu Institute of Technology Life Science and Systems Engineering Kitakyushu Japan Sunter Assembly Plant Astra Daihatsu Motor Ltd Department of Assembling1 Jakarta Indonesia Dokuz Elylul University Electrical Electrical and Electronic Engineering Izmir Turkey

ISBN: (纸本)9798350309225

The utilization of real-time industrial machinery condition monitoring systems has emerged as an important component in improving operational efficiency, reliability, and equipment life. In specific industrial sectors, manual methods of data storage and retrieval are still used, leading to inefficiencies in data presentation. Widespread problems in these industries arise due to the absence of real-time data access. This research centers on a cost-effective approach to designing and implementing a real-time monitoring system for tire stacking machines. This paper introduces a real-time monitoring system on a tire stacking machine using Node-RED, equipped with integrated storage of stacking data, machine breakdown information, and process cycle time in a web dashboard powered by Grafana. The system can be accessed locally or via an industrial intranet network. © 2023 ieee.

关键词： Digital storage

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Reactive Power Optimization Based on Tent-Chebyshev Switching Mapping Particle Swarm Optimization 4

Reactive Power Optimization Based on Tent-Chebyshev Switchin...

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4th international conference on Energy Engineering and Power systems, EEPS 2024

作者： Zhang, Jinhao Ye, Jianhua Tianjin University of Technology and Education Tianjin Key Laboratory of Information Sensing and Intelligent Control Tianjin China

ISBN: (纸本)9798350366914

The multi-point access of large-scale integration of wind and solar energy has brought negative effects such as voltage over-limit to the operation of the distribution network, which increases the difficulty of reactive power optimization. In order to solve this problem, an improved particle swarm optimization scheme based on Tent-Chebyshev fusion switching is proposed. When the Tent chaotic mapping function is used to calculate the initial position of the particles, the Chebyshev chaotic mapping function is used to introduce random disturbance to the particles trapped in the fixed point in the population, so that they can re-enter the chaotic state. It mitigates the risk of converging into local optima, minimizes the network loss and voltage deviation of the distribution network system. The research results are verified through the ieee33-node example, demonstrating the feasibility and effectiveness of the proposed method in addressing the reactive power optimization problem. © 2024 ieee.

关键词： Particle swarm optimization (PSO)

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