Journal of Electronic Research and Application

Standardized Research on High-Voltage Safety of Drive Motor Systems

Bowen Yin — 2025-05-15

This paper focuses on the high-voltage safety of drive motor systems in new energy vehicles and conducts standardized research on functional safety design in the concept phase. In view of the lack of high-voltage hazard analysis for drive motor systems in existing standards, based on theories such as GB/T 34590 and ISO 26262, the safety levels are deeply analyzed. The HAZOP method is innovatively used, and 16 types of guidewords are combined to comprehensively analyze the system functions, identifying vehicle hazards such as high-voltage electric shock caused by functional abnormalities, including high-voltage interlock function failure and abnormal active discharge. Subsequently, safety goals such as preventing high-voltage electric shock are set, functional safety requirements such as accurately obtaining collision signals and timely discharging high-voltage electricity are formulated, and requirements for external signal sources and other technologies are clearly defined, constructing a complete high-voltage safety protection system. The research results provide important technical support and standardized references for the high-voltage safety functional design of drive motor systems in new energy vehicles, and are of great significance for improving the high-voltage safety level of the new energy vehicle industry, expecting to play a key role in subsequent product development and standard improvement.

Fault Diagnosis for Key Components of Metro Vehicles based on Wavelet Threshold Denoising and EEMD

Xichun Luo — 2025-05-15

With the increasing adoption of intelligent operation and maintenance technologies in urban rail transit, most maintenance systems have been equipped with fault diagnosis modules targeting key components of metro vehicles. However, the integration between engineering-level diagnostic algorithms and advanced academic research remains limited. Two major challenges hinder vibration-based fault diagnosis under real-world operating conditions: the complex noise and interference caused by wheel–rail coupling and the typically weak expression of fault features. Considering the widespread application of wavelet transform in noise reduction and the maturity of ensemble empirical mode decomposition (EEMD) in handling nonlinear and non-stationary signals without parameter tuning, this study proposes a diagnostic method that combines wavelet threshold denoising with EEMD. The method was applied to bearing vibration signals collected from an operational subway line. The diagnostic results were consistent with actual disassembly findings, demonstrating the effectiveness and practical value of the proposed approach.

Research on Cybersecurity Threats and Defenses in the Context of Financial Technology

Sishan Li — 2025-05-29

With the rapid development of information technology, the deep integration of the financial sector and the internet has become a key driving force for economic growth. However, while this trend brings convenience, it also poses significant cybersecurity challenges to the financial sector. This study comprehensively analyzes the current state, challenges, and protective measures of cybersecurity in the financial sector, aiming to provide important references for financial institutions in formulating cybersecurity strategies and enhancing risk management.

Research Progress of Standards Supporting Green Development of Industry in the Context of “Carbon Peak and Carbon Neutralization”

Congguang Zhang — 2025-06-05

As an important part of climate change rules, standards are of great significance for supporting sustainable energy, energy conservation, and emission reduction to achieve green and low-carbon transformation and upgrading. Based on the double carbon strategic goal task, current situation of the development of international and domestic standardization, standardization power view of green industry development prospects of new energy, energy storage, carbon sink, carbon trading standardization practice process to study the way to solve problems and feasibility analysis, has been clear about the standard system construction in our country’s low carbon energy transition economies the position and role of the upgrade planning, It provides the important reference value for our country green and sustainable industry’s innovating development.

Research on the Practical Path of Integrating Excellent Traditional Chinese Culture into Curriculum Ideological and Political Education: Taking the Layout Design Course as an Example

Xiaoqian Xu — 2025-06-05

This study focuses on the deepening paths of ideological and political construction of professional courses in higher vocational colleges, taking the layout design course of the digital media technology major as the research object, and explores the integration mechanism of excellent traditional Chinese culture and professional teaching. The curriculum’s ideological and political reform is advanced through three major measures: Reconstructing the role of teachers, innovating teaching methods, and building a cultural infiltration system. Combined with the three-dimensional assessment mechanism of “professional + culture + value” and the transformation of teaching achievements into competitions, it breaks through the limitations of traditional skill training and systematically solves the problems of formalization tendency and insufficient value guidance existing in the practice of curriculum ideology and politics. It responds to the era proposition of “promoting the creative transformation of excellent traditional Chinese culture,” and provides an operable solution for higher vocational colleges to break the predicament of “emphasizing skills while neglecting culture.”

Research on the Development Status and Difficulties of Machine Translation in the Era of Artificial Intelligence

Ruijing Xu — 2025-06-06

Machine translation builds a bridge for cross-language communication by realizing text conversion between different languages. However, there are still many challenges in achieving context-accurate translations. These mainly include how to accurately capture subtle information in context, effectively resolve the ambiguity of polysemous words, properly translate idiomatic expressions, accurately reflect cultural differences, and correctly use terms in specific fields. This article reviews the existing platforms and the latest research results in the field of machine translation, deeply explores the above-mentioned key difficulties, and explores the introduction of artificial intelligence technology. The aim is to improve the overall performance of machine-translation systems, facilitate smoother communication and understanding among people from different cultural backgrounds, further eliminate language barriers, and promote the in-depth integration and development of global multiculturalism.

Research on Governance Strategy of Internet Public Opinion Reversal based on Blockchain Technology

Fei Wang — 2025-06-05

In recent years, the network public opinion reversal governance events have occurred frequently. Over time, the repeated truth of the matter will not only weaken the rational judgment of the public to a certain extent, so that its negative emotions accumulate, but also have a serious impact on the credibility of the media and the government, and may even further intensify social contradictions. Therefore, in the face of such a complex online public opinion space, accurately identifying the truth behind the incident and how to carry out the reversal of online public opinion governance is particularly critical. And blockchain technology, with its advantages of decentralization and immutable information, provides new technical support for the network public opinion reversal governance. Based on this, this paper gives an overview and analysis of blockchain technology and network public opinion reversal, and on this basis introduces the network public opinion reversal governance mechanism based on blockchain technology, aiming to further optimize the network public opinion reversal governance process, for reference only.

Design and Implementation of Sports Social Information Management System based on Spring Boot

Yule Sun — 2025-06-05

To improve the level of sports social management, to achieve standardized management, quick query, scientific statistics of sports social information, and to meet the needs of sports organizers, social platform managers, and other users, this paper introduces a sports social management system based on Spring Boot. The system uses Eclipse for Java Web development, selects MySQL 5.6 database as the background data storage solution, uses Java language to write code, and uses Tomcat server to build the running environment of applications. The system has the function of adding, deleting, changing and checking sports activities, supporting the input, query and statistical analysis of users’ sports results, sports consumption and sports distance, and also allows to add, delete, modify and query the information of sports friends, aiming to provide users with a comprehensive and efficient sports social information management platform.

Application Path Exploration of Intelligent Manufacturing Technology in the Machining Field

Donglai Luan — 2025-06-05

Intelligent manufacturing technology, as the core driving force of the fourth industrial revolution, is profoundly changing the production mode and industrial pattern in the field of mechanical processing. This paper starts from the application background of intelligent manufacturing technology in the field of machining, combined with the limitations of traditional machinery manufacturing technology, systematically analyzes the application status of intelligent manufacturing technology in CNC production, equipment fault diagnosis, sensing technology and industrial robots, and provides theoretical support and practical guidance for the transformation and upgrading of machining industry. The exploration of the application path of intelligent manufacturing technology in the field of machining not only helps to enhance the core competitiveness of the industry but also provides important support for the realization of high-quality development and sustainable development goals of the manufacturing industry.

AI-powered Reform of the Teaching Model for Engineering Practice Courses

Liuchen Liu — 2025-06-05

With the rapid development of information technology, artificial intelligence (AI) has been developing quickly, exerting a wide-ranging and profound impact on various industries. It also shows increasing potential in the field of education. With the continuous deepening of teaching reform and the increasingly complex social environment, the market and society have higher requirements for high-level talents. The traditional teaching model can no longer adapt to this development trend and meet the ever-changing teaching needs of college students. Against this background, this paper focuses on the practical courses of engineering majors in colleges and universities, exploring the effective application of AI technology in the reform of teaching models. Starting from the practical significance of reforming the teaching model of engineering practice courses, it delves into the effective application of AI in this reform. By optimizing the teaching model of engineering practice from various teaching elements, it aims to improve teaching quality and effectiveness, provide students with a better teaching experience and personalized learning paths, cultivate students’ solid theoretical foundation and practical abilities, enhance the comprehensive quality of engineering students, and supply more high-quality engineering talents to related industries.

Drone Digital Twin Is Used for Water Plant Inspection

Ming Li — 2025-06-05

Inspection is a fundamental task for water plants, yet traditional methods are often labor-intensive, time-consuming, and costly. The rapid advancement of drone technology has significantly transformed environmental inspections, particularly in water plant assessments. Digital twins enhance modeling and simulation capabilities by integrating real-time data and feedback. This paper presents an intelligent water plant detection system based on YOLOv10 and drone technology. The system aims to monitor environmental conditions around water facilities and automatically identify anomalies in real time. The design utilizes dataset images of construction vehicles, maintenance hole covers, and pipe leaks collected from publicly accessible websites. The system integrates real-time drone inspection data into a digital twin platform for dynamic monitoring.

Exploring the Impact of AI-Enhanced Classroom Instruction on Learning Outcomes of College Students

Bing Li — 2025-06-06

In recent years, artificial intelligence (AI) has been increasingly integrated into educational settings worldwide. This study aims to explore the effectiveness of AI classroom teaching for Chinese undergraduate students, focusing on its influence on learning outcomes and student engagement. The research uses a quantitative approach, utilizing surveys and academic performance data to evaluate two main objectives: (1) the impact of AI teaching methods on academic performance compared to traditional instruction; (2) the level of student engagement and satisfaction with AI-based learning tools. The study sample includes undergraduate students from multiple universities in China, allowing for a diverse representation of various disciplines. Data will be collected through standardized tests, questionnaires, and academic records, ensuring the reliability and validity of the results. The findings will provide insights into the potential advantages and challenges of AI integration in higher education and inform future strategies for adopting AI in Chinese classrooms. By exploring both the academic and practical aspects of AI-driven education, this research aims to contribute valuable knowledge to the growing field of AI in education, particularly in the context of Chinese higher education. The results are expected to have implications for educators, policymakers, and AI developers interested in enhancing the effectiveness of educational technologies.

The Latest Research Progress of Attention Mechanism in Deep Learning

Xu Jiang — 2025-05-29

With the development of artificial intelligence and deep learning, the attention mechanism has become a key technology for enhancing the performance of complex tasks. This paper reviews the evolution of attention mechanisms, including soft attention, hard attention, and recent innovations such as multi-head latent attention and cross-attention. It focuses on the latest research outcomes, such as lightning attention, the PADRe polynomial attention replacement algorithm, the context anchor attention module, and improvements in attention mechanisms for large models. These advancements improve the efficiency and accuracy of models, expanding the application potential of attention mechanisms in fields such as computer vision, natural language processing, and remote sensing object detection, aiming to provide readers with a comprehensive understanding and stimulate innovative thinking.

AI-Enabled Computer Programming Course Teaching Reform

Yao Dai — 2025-06-06

With the rapid development of modern science and technology, the era of artificial intelligence has quietly come. Against the background of the new era, students’ learning needs, learning resource acquisition methods, teachers’ teaching concepts, teaching tools, and so on have changed significantly. How to carry out teaching reform based on this change has become one of the important issues facing educators, and the same is true for the teaching of computer programming courses. This paper focuses on the teaching reform of AI-enabled computer programming courses, analyzes its basic problems, and puts forward corresponding reform countermeasures to provide a useful reference for front-line teachers.

Exploring the Nuclear Power DCS Network Security Management Method and Its Application

Yu Chen — 2025-06-05

Given the grave local and international network security landscape, a national strategic level analysis indicates that the modernization and advancement within the Industry 4.0 era are closely correlated with overall competitive strength. Consequently, China proposed a strategy for the integration of industrialization and informatization, optimizing and adjusting its industrial structure to swiftly achieve transformation and upgrading in the Industry 4.0 era, thereby enhancing the sophistication of intelligent industrial control systems. The distributed control system in a nuclear power plant functions as an industrial control system, overseeing the operational status of the physical process. Its ability to ensure safe and reliable operation is directly linked to nuclear safety and the cybersecurity of the facility. The management of network security in distributed control systems (DCS) is crucial for achieving this objective. Due to the varying network settings and parameters of the DCS implemented in each nuclear power plant, the network security status of the system sometimes diverges from expectations. During system operation, it will undoubtedly encounter network security issues. Consequently, nuclear power plants utilize the technical criteria outlined in GB/T 22239 to formulate a network security management program aimed at enhancing the operational security of DCS within these facilities. This study utilizes existing network security regulations and standards as a reference to analyze the network security control standards based on the nuclear power plant’s control system. It delineates the fundamental requirements for network security management, facilitating integration with the entire life cycle of the research, development, and application of the nuclear power plant’s distributed control system, thereby establishing a network security management methodology that satisfies the control requirements of the nuclear power plant. Initially, it presents DCS and network security management, outlines current domestic and international network security legislation and standards, and specifies the standards pertinent to the administration of DCS in nuclear power plants. Secondly, the design of network security management for DCS is executed in conjunction with the specific context of nuclear power plants. This encompasses the deployment of network security apparatus, validation of the network security management strategy, and optimization adjustments. Consequently, recommendations beneficial to the network security management of nuclear power plants are compiled, aimed at establishing a management system and incorporating the concept of full life cycle management, which is predicated on system requirements, system design, and both software and hardware considerations. Conversely, it presents the notion of comprehensive life cycle management and suggests network security management strategies encompassing system requirements, system architecture, detailed hardware and software design and implementation, procurement, internal system integration, system validation and acceptance testing, system installation, operational maintenance, system modifications, and decommissioning. We will consistently enhance the performance and functionality of DCS in nuclear power plants, establish a safe and secure operational environment, and thereby facilitate the implementation of DCS in nuclear facilities while ensuring robust network security in the future.

Application of Big Data Technology in User Behavior Analysis of E-commerce Platforms

Yanzhao Jia — 2025-05-29

With the rapid development of the Internet and e-commerce, e-commerce platforms have accumulated huge amounts of user behavior data. The emergence of big data technology provides a powerful means for in-depth analysis of these data and insight into user behavior patterns and preferences. This paper elaborates on the application of big data technology in the analysis of user behavior on e-commerce platforms, including the technical methods of data collection, storage, processing and analysis, as well as the specific applications in the construction of user profiles, precision marketing, personalized recommendation, user retention and churn analysis, etc., and discusses the challenges and countermeasures faced in the application. Through the study of actual cases, it demonstrates the remarkable effectiveness of big data technology in enhancing the competitiveness of e-commerce platforms and user experience.

Study on Smart Telematics Cache Optimization Strategy Based on Edge Computing

Yangbo Cheng — 2025-05-29

With the rapid development of intelligent transportation systems, vehicular networks (VANETs) have become an essential part of the intelligent transportation infrastructure. Due to the high dynamics of efficient vehicular network nodes and the low latency requirement of data interaction, the traditional cloud computing model makes it difficult to meet the real-time and performance criteria, and the storage optimization strategy based on edge computing can effectively improve the data access efficiency and system response. This paper explores optimizing the data caching mechanism of intelligent telematics using edge computing to reduce network latency, improve data availability, and enhance overall system performance.

Research on the Practical Strategy of 5G Mobile Communication Technology in Power Communication

Wanshen Peng — 2025-06-05

With the acceleration of the intelligent transformation of power systems, the requirements for communication technology are increasingly stringent. The application of 5G mobile communication technology in power communication is analyzed. In this study, 5G technology features, application principles, and practical strategies are discussed, and methods such as network slicing, customized deployment, edge computing collaborative application, communication equipment integration and upgrading, and multi-technology collaboration and complementation are proposed. It aims to effectively improve the efficiency, reliability, and security of power communication, solve the problem that traditional communication technology is difficult to meet the diversified needs of power business, and achieve the effect of optimizing the power communication network and supporting the intelligent development of the power system.

Weed Detection in The Field Environment Based on Faster R-CNN

Jianing Liu — 2025-06-05

Accurate weed identification in farmland is crucial for enhancing intelligent weeding precision. This study focuses on weeds in maize seedling fields and builds an accurate identification model using the Faster-RCNN deep-learning algorithm. An image database is created, and the VGG-16 network extracts labeled datasets for weed feature extraction. By calculating random candidate region scores, a neural network training model is established to determine weed positions and types. This model achieves an average accuracy of 81.25% and an identification rate of 94.3% in weed identification. To test the model’s performance in the field, it is evaluated under different conditions, such as lighting, field of view, and occlusion. Occlusion has the most significant impact on the identification rate. Without occlusion, the precision is 94.4%, dropping to 79.2% when the occlusion rate exceeds 50%. However, adjusting the shooting angle can increase the precision to 97.1%. In real-world conditions, considering all factors, the weed identification precision is 94.3%. The results show that this technology is highly adaptable in the field with fast image detection. With GPU acceleration, the average detection speed per image is 50 milliseconds, and the video stream can reach 20 frames per second. This technology can adapt to complex environments, detect accurately, and has a short calculation time. It provides key support for automated mechanical weeding and holds great promise for practical applications in agricultural production.

Enterprise Digital Planning and Architecture Based on the Industrial Internet Platform

Li Wang — 2025-05-29

Under the current background of an information society, the digital transformation of enterprises has become a necessary means to enhance the competitiveness of enterprises. This article is based on the industrial Internet platform, the digital planning and architecture of enterprises research. First, we analyze the current challenges of digital transformation and the development opportunities brought by the industrial Internet. Then, we propose a digital planning method based on the industrial Internet platform, which takes the full connectivity of people, machine and things and intelligent decision making as the core, takes data collection, processing, analysis and application as the main line, and finally forms the top-level design of the digital transformation of enterprises. At the same time, we also built an industrial Internet platform architecture model, including the previous end perception layer, network transmission layer, platform service layer, and application innovation layer for four levels, to support enterprises in innovative applications and decision support under the industrial Internet environment. Research shows that this kind of enterprise digital planning and architecture based on an industrial Internet platform can effectively promote enterprises to achieve business model innovation, system innovation, and strengthen the flexibility and agility of enterprises to respond to market changes. The results of this research not only have important theoretical and practical significance for guiding enterprises to carry out digital planning and build an industrial Internet platform, but also provide useful reference for relevant policy formulation.

Research on the Application of MWorks Simulation Software in Circuit Fundamentals Courses in Vocational Colleges

Mingyue Ren — 2025-06-05

This article focuses on the teaching of circuit foundation courses in vocational colleges and explores in depth the application of MWorks simulation software. By analyzing the limitations of traditional circuit foundation course teaching, this article elaborates on the advantages of MWorks software in teaching, including intuitive presentation of circuit principles, provision of rich component libraries, and powerful analysis functions. Detailed teaching practice cases based on the software were introduced, such as simple circuit construction and analysis, complex circuit fault troubleshooting, etc., and the application effect was demonstrated by comparing actual teaching data. The results show that MWorks simulation software effectively enhances students’ learning interest, practical ability, and theoretical knowledge mastery, providing strong support for the improvement of the teaching quality of circuit foundation courses in vocational colleges.

Research on Intelligent Design from the Perspective of Age-Friendly Design: Taking “Remembering” as an Example

Wenrui Xie — 2025-05-29

This study focuses on the elderly memo app “Remembering,” addressing memory decline and operational difficulties. It introduces a progressive interaction system with three core modules: Dynamic font adjustment, intelligent voice reminders, and family warning systems. Health monitoring and remote care functions are also integrated, creating a simple operation process. The research highlights four design dimensions for elderly-friendly products: Usability, security, emotionalization, and personalization. This innovation reduces the digital barrier and provides a model for smart elderly-friendly product development.

Optimization Design of Workshop Painting Parameter Process

Lei Sun — 2025-06-06

Through the analysis of the actual situation and process of painting industrial steel components in Hechang Company, we have modified the mixing ratio of paint, thinner, and curing agent. Additionally, we have effectively adjusted the drying time of various paint types under different seasons and temperatures. Eventually, a painting solution suitable for our company has been developed. According to this process, the painting quality has been significantly improved, costs have been saved, the labor intensity has been reduced, and production efficiency has been remarkably enhanced.

Exploration of the Application of Internet of Things Technology in Real-time Monitoring of Cold Chain Logistics

Huiling Ma — 2025-06-05

The Internet of Things technology provides a comprehensive solution for the real-time monitoring of cold chain logistics by integrating sensors, wireless communication, cloud computing, and big data analysis. Based on this, this paper deeply explores the overview and characteristics of the Internet of Things technology, the feasibility analysis of the Internet of Things technology in the cold chain logistics monitoring, the application analysis of the Internet of Things technology in the cold chain logistics real-time monitoring to better improve the management level and operational efficiency of the cold chain logistics, to provide consumers with safer and fresh products.

An Analysis of the Construction Methods of Multimodal Course Knowledge Graphs

Fulin Li — 2025-06-05

In the context of digitalization, course resources exhibit multimodal characteristics, covering various forms such as text, images, and videos. Course knowledge and learning resources are becoming increasingly diverse, providing favorable conditions for students’ in-depth and efficient learning. Against this backdrop, how to scientifically apply emerging technologies to automatically collect, process, and integrate digital learning resources such as voices, videos, and courseware texts, and better innovate the organization and presentation forms of course knowledge has become an important development direction for “artificial intelligence + education.” This article elaborates on the elements and characteristics of knowledge graphs, analyzes the construction steps of knowledge graphs, and explores the construction methods of multimodal course knowledge graphs from aspects such as dataset collection, course knowledge ontology identification, knowledge discovery, and association, providing references for the intelligent application of online open courses.

Perceptions of Digital Monitoring Technology for Activities of Daily Living (ADLs): A Semi-Structured Interview Study of Older Adults and Informal Caregivers

Zhiyuan Xiao — 2025-06-05

With China’s rapidly aging population and the growing preference for aging in place, digital monitoring technologies have emerged as potential tools to support older adults in managing their activities of daily living (ADLs). This study explores the perceptions and acceptance of these technologies among elderly individuals living alone and their informal caregivers (ICs) in Nanshan District, Shenzhen. Grounded in the Unified Theory of Acceptance and Use of Technology (UTAUT), the study employed semi-structured and photo-elicitation interviews to analyze how performance expectancy, effort expectancy, social influence, and facilitating conditions shape technology adoption. The findings reveal clear intergenerational differences: caregivers show higher acceptance and a better understanding of the benefits and functionalities of wearable and environmental monitoring devices, while older adults often express skepticism due to concerns over privacy, usability, and cost. Many elderly participants also cite discomfort, technical complexity, and lack of training as barriers to adoption. Despite these obstacles, both groups acknowledge the potential safety and health benefits of such technologies. The study highlights the need for privacy-by-design features, customized user interfaces, and enhanced digital literacy programs tailored to both elderly users and their caregivers. The research contributes to a sociotechnical understanding of aging-in-place technologies in China and provides actionable insights for developers, policymakers, and healthcare practitioners aiming to enhance home-based elder care.

AI-Driven Implementation of Universal Control

Zhi Tang — 2025-05-29

Control serves the process technology. Therefore, the optimal implementers of process control should be process engineers rather than control engineers. While process engineers best understand the control requirements of the technology, the inherent complexity of control systems has rendered many process engineers incapable of accomplishing these control tasks ^[1]. The greatest truths are the simplest, from abacus to calculator, from DOS to Windows, each technological revolution has been driven by application-oriented simplification. Can integrated automation in process industries also achieve such extreme simplicity and rapid implementation? This is precisely what this paper aims to explore.

Research on Compliance Flight Test Technology of Integrated Modular Avionics (IMA) System

Bo Xu — 2025-05-29

Based on the analysis and research of the airworthiness objective of integrated modular avionics system (IMA), and the characteristics of IMA system’s comprehensive and complex cross-linking with other airborne systems, the extraction strategy of IMA system’s compliance flight test subjects and the selection method of IMA system’s compliance flight test parameters are proposed. The data analysis method based on the abnormal probability matrix of the IMA system is proposed for the first time, and the abnormal state information of the IMA system can be quickly identified. The compliance flight test of the IMA system is completed with limited flight test resources, which achieves the purpose of saving flight test sorties and improving flight test efficiency. This research has been successfully applied to the airworthiness certification flight test of a certain civil transport aircraft in China, and can provide technical support for the subsequent type flight test.

Research on Innovative Design and Preparation Technology of Power Integrated Isolation Structure

Yili Xu — 2025-06-05

Power integrated isolation structures play a crucial role in the field of power electronics, especially in silicon carbide (SiC) devices, where challenges such as high leakage current and insufficient voltage endurance are prevalent. This paper introduces a novel isolation technology based on vanadium ion implantation, achieving high-performance SiC monolithic integration through deep energy level trapping engineering and three-dimensional composite isolation design. The core technologies include: semi-insulating layer + dielectric trench co-isolation, high-precision process control, high-temperature compatibility optimization, ultra-high breakdown field strength, support for 10kV class IGBT/MOSFET integration, and a 30–50% increase in chip area utilization, combining high performance with low-cost advantages.

Fault Detection for Split Pins of Power Transmission Fittings in UAV Inspections via Automatic Image Cropping-based Super-Resolution Reconstruction and Enhanced YOLOv8

Shihao Cui — 2025-05-29

In modern industrial applications, ensuring the reliability of mechanical fittings is critical for maintaining operational safety and efficiency, particularly in power grid systems where split pins serve a pivotal role despite being susceptible to environmental degradation and failure. Existing UAV-based inspection systems are hampered by a low representation of split pin elements and complex backgrounds, leading to challenges in accurate fault detection and timely maintenance. To address this pressing issue, our study proposes an innovative fault detection method for split pins. The approach employs a three-step process: first, cropping operations are used to accurately isolate the fittings containing split pins; second, super-resolution reconstruction is applied to enhance image clarity and detail; and finally, an improved YOLOv8 network, augmented with inner-shape IoU and local window attention mechanisms, is utilized to refine local feature extraction and annotation accuracy. Experimental evaluations on a split pin defect dataset demonstrate robust performance, achieving an accuracy rate of 72.1% and a mean average precision (mAP) of 67.7%, thereby validating the method’s effectiveness under challenging conditions. The proposed approach contributes to the field by specifically targeting the challenges associated with split pin detection in UAV-based inspections, offering a practically applicable and reliably precise method.

Research on Real-Time Object Detection and Tracking for UAV Surveillance Based on Deep Learning

Fei Liu — 2025-06-05

To address the challenges of low accuracy and insufficient real-time performance in dynamic object detection for UAV surveillance, this paper proposes a novel tracking framework that integrates a lightweight improved YOLOv5s model with adaptive motion compensation. A UAV-view dynamic feature enhancement strategy is innovatively introduced, and a lightweight detection network combining attention mechanisms and multi-scale fusion is constructed. The robustness of tracking under motion blur scenarios is also optimized. Experimental results demonstrate that the proposed method achieves a mAP@0.5 of 68.2% on the VisDrone dataset and reaches an inference speed of 32 FPS on the NVIDIA Jetson TX2 platform. This significantly improves the balance between accuracy and efficiency in complex scenes, offering reliable technical support for real-time applications such as emergency response.

Research on the Application of Artificial Intelligence Technology in Mechanical Design and Manufacturing

Yuanping Wang — 2025-06-06

As a product of the new century, artificial intelligence has been continuously developed and advanced. It has been applied to many fields, especially in the field of mechanical design and manufacturing. With the support of artificial intelligence, mechanical design and manufacturing can not only reduce input costs but also significantly reduce the demand for labor, playing a positive role in improving the design efficiency and quality of mechanical manufacturing^[1]. This paper studies how to apply artificial intelligence technology to the mechanical design and production process to achieve greater application and development.

Integrated Innovative Applications of Artificial Intelligence and Electrical Automation Technology

Liu Yang — 2025-06-05

The integrated innovation of artificial intelligence and electrical automation technology not only represents a further innovation of traditional models but also promotes the innovative development of both artificial intelligence and electrical automation technology. This paper delves into the significance of the integrated innovative applications of artificial intelligence and electrical automation technology, as well as the strategies for such applications, aiming to better achieve the intelligent development of electrical automation technology.

Safety Risks and Countermeasures of Lithium-ion Battery Energy Storage Power Station

Lifei Lian — 2025-06-06

With the continuous emergence of new energy storage technology innovation in the field of electrochemical energy storage in China, different megawatt-grade lithium-ion battery energy storage projects have been implemented, promoting the high-quality development of the energy storage industry. In the context of vigorously promoting the energy consumption revolution and enhancing the green transformation and development momentum, strengthening the safety construction of lithium-ion battery energy storage is of great importance to realize the transformation of energy structure and improve the utilization efficiency of renewable energy. However, in recent years, frequent safety accidents of lithium-ion battery energy storage power stations, such as fires, have aroused the public’s high attention to the construction of lithium-ion battery energy storage power stations, affecting the large-scale development of energy storage power stations. Based on this, this paper analyzes the safety risks of lithium-ion battery energy storage power stations and focuses on how to improve their safety performance.

Research on the Problem of Autonomous Collision Avoidance and Risk Avoidance of Ships

Qiang Tan — 2025-05-29

This paper deeply explores the autonomous collision avoidance algorithm for intelligent ships, aiming to enhance the intelligence level and safety of ship collision avoidance by integrating navigation experience. An autonomous collision avoidance algorithm based on navigation experience is designed, a collision avoidance experience database is constructed, a quantitative model is established, and specific algorithm steps are implemented. The algorithm is verified and analyzed through simulation tests. The results show that the algorithm can effectively achieve autonomous ship collision avoidance in different scenarios, providing new ideas and methods for the development of intelligent ship collision avoidance technology.

Design of Mechanical Automation Control System Based on Artificial Intelligence

Zhen Sun — 2025-06-05

Aiming at the problems of poor adaptability and insufficient fault prediction of traditional mechanical automation control systems in complex working conditions, a mechanical automation control system based on artificial intelligence is designed. This design integrates expert control, fuzzy control, and neural network control technologies, and builds a hierarchical distributed architecture. Fault warning adopts threshold judgment and dynamic time warping pattern recognition technologies, and state monitoring realizes accurate analysis through multi-source data fusion and Kalman filtering algorithm. Practical applications show that this system can reduce the equipment failure rate by more than 30%. With the help of intelligent scheduling optimization, it can significantly improve production efficiency and reduce energy consumption, providing a reliable technical solution and practical path for the intelligent upgrade of the mechanical automation field.

Research on the Output Performance of a Solar-Cooled PV/T System

Yaolin Zhu — 2025-05-29

Owing to their high practicability, solar PV/T (photovoltaic/thermal) collectors have attracted considerable attention from researchers in both photovoltaic and solar-thermal fields worldwide. In this study, we designed and constructed a novel solar-cooled PV/T system. Through experimental methods, we conducted an in-depth investigation of its thermal and electrical output characteristics and developed mathematical models for both thermal performance and electrical performance. Finally, we validated the experimental data against simulations. The results demonstrate that the designed solar-cooled PV/T system exhibits excellent thermal and electrical output performance. The utilization rate of waste heat from the PV module’s back plate reached 18.59%, and the system’s electrical efficiency improved by 1.92% compared to a conventional PV/T system. This work provides theoretical and experimental guidance for the further optimization and improvement of the solar-cooled PV/T system.

Global Terminal Switching Sliding Mode Control of Robot Manipulators Based on Entire Fixed-Time Disturbance Observer

Fengning Zhang — 2025-05-29

This paper presents an entire fixed-time disturbance observer-based global terminal switching sliding mode control of robot manipulators, which has inner and external uncertainties. The entire fixed-time disturbance observer-based global terminal switching sliding mode control has the global finite-time reaching characteristic, the property that system convergence time can be prescribed, and the global robustness to uncertainties, with the entire fixed-time disturbance observer that accurately estimates uncertainties after a fixed time, despite the initial state. The joints of the control system can arrive at the prescribed joint angular position at the predefined joint angular speed at the prescribed time.

Design of a Fuzzy Adaptive PID Control System for Quadrotor UAVs

Jiangwei Zhao — 2025-06-05

During flight operations, quadrotor UAVs are susceptible to interference from environmental factors such as wind gusts, battery depletion, and obstacles, which may compromise flight stability. This study proposes a fuzzy adaptive PID controller (Fuzzy PID) combining PID control with fuzzy logic to achieve self-adaptive adjustment of PID parameters in UAV flight control systems, thereby enhancing system robustness. A quadrotor UAV control model was developed in Simulink, and a Fuzzy PID control system was constructed by integrating fuzzy control logic for simulation and experimental validation. Test results demonstrate that UAVs governed by Fuzzy PID control exhibit faster regulation speed and improved stability when subjected to disturbances.

An Improved Lightweight Pest Detection Method Based on YOLOv8

Liling Zhang — 2025-06-05

This study systematically addresses the limitations of traditional pest detection methods and proposes an optimized version of the YOLOv8 object detection model. By integrating the GhostConv convolution module and the C3Ghost module, the Polarized Self-Attention (PSA) mechanism is incorporated to enhance the model’s capacity for extracting pest features. Experimental results demonstrate that the improved YOLOv8 + Ghost + PSA model achieves outstanding performance in critical metrics such as precision, recall, and mean Average Precision (mAP), with a computational cost of only 5.3 GFLOPs, making it highly suitable for deployment in resource-constrained agricultural environments.

Retinal Vessel Segmentation based on Improved PCNN and Gray Wolf Optimization Algorithm

Xingfu Ou — 2025-06-05

Since the problems of branch loss and fracture in retinal blood vessel segmentation algorithms, an image segmentation method is proposed based on improved pulse coupled neural network (PCNN) and gray wolf optimization algorithm (GWO). Simplifying the neuron input domain and neuron connection domain of the PCNN network, increasing the gradient information factor in the internal activity items, reducing the model parameters, enhancing the pulse issuing ability, and the optimal parameters of the network are automatically obtained based on multiple feature evaluation criteria and the GWO algorithm. The test in the public data set drive shows that the sensitivity, accuracy, precision, and specificity of the algorithm are 0.799549, 0.962789, 0.889163, and 0.986552, respectively. The accuracy and specificity are better than the classical segmentation algorithm. It solved the influence of low illumination, optic disc highlight, and foveal shadow on vascular segmentation, and showed excellent performance of vessel connectivity and terminal sensitivity.

Research on Low-Speed Performance Optimization of BLDC without Position Sensors Based on EKF

Wei Liu — 2025-06-06

To obtain real-time rotor information of the brushless DC motor, improve the low-speed performance and anti-interference ability of the motor, a sensorless vector control system model of the brushless DC motor was established. A motor control system based on the EKF algorithm was designed. By combining the EKF observer with the brushless DC motor, a simulation model of the EKF motor control system was built based on Simulink. The simulation results show that the motor control system with the EKF observer operates well. The motor’s low-speed operation performance and rotor position detection are very fast, and the motor’s anti-interference ability is significantly enhanced, effectively improving the dynamic performance of the control system ^[1].

Research on Recommendation Algorithm Based on TrustSVD++ and XGBoost

Gongjin Chen — 2025-05-29

Aiming at the problem that the data in the user rating matrix is missing and the importance of implicit trust between users is ignored when using the TrustSVD model to fill it, this paper proposes a recommendation algorithm based on TrustSVD++ and XGBoost. Firstly, the explicit trust and implicit trust were introduced into the SVD++ model to construct the TrustSVD++ model. Secondly, considering that there is much data in the interaction matrix after filling, which may lead to a rather complex calculation process, the K-means algorithm is introduced to cluster and extract user and item features at the same time. Then, in order to improve the accuracy of rating prediction for target users, an XGBoost model is proposed to train user and item features, and finally, it is verified on the data sets MovieLens-1M and MovieLens-100k. Experiments show that compared with the SVD++ model and the recommendation algorithm without XGBoost model training, the proposed algorithm has the RMSE value reduced by 2.9% and the MAE value reduced by 3%.

Optimization of Multi-Vehicle Routing Problem with Time Windows and Simultaneous Pickup and Delivery

Biao Wang — 2025-06-06

This paper addresses the Multi-Vehicle Routing Problem with Time Windows and Simultaneous Pickup and Delivery (MVRPTWSPD), aiming to optimize logistics distribution routes and minimize total costs. A vehicle routing optimization model is developed based on the operational requirements of the KS Logistics Center, focusing on minimizing vehicle dispatch, loading and unloading, operating, and time window penalty costs. The model incorporates constraints such as vehicle capacity, time windows, and travel distance, and is solved using a genetic algorithm to ensure optimal route planning. Through MATLAB simulations, 34 customer points are analyzed, demonstrating that the simultaneous pickup and delivery model reduces total costs by 30.13%, increases vehicle loading rates by 20.04%, and decreases travel distance compared to delivery-only or pickup-only models. The results demonstrate the significant advantages of the simultaneous pickup and delivery mode in reducing logistics costs and improving vehicle utilization, offering valuable insights for enhancing the operational efficiency of the KS Logistics Center.

An Automatic Charging Method for a 40kV Substation Inspection Robot

Qingsong Liu — 2025-06-06

In a high-voltage environment of 40kV where no one is working, inspection robots must have an automatic charging system to ensure continuous operation. Currently, inspection robots operating in such high-voltage environments mostly use side-by-side alignment for docking. Given the existence of magnetic track navigation errors in robots, this docking method often fails to achieve successful docking. In response to this situation, this paper designs a new docking module.