In recent years, with the popularization of the Internet, the network has penetrated into all aspects of individuals and society. Internet technology has made people's daily lives more intelligent and convenient, but the accompanying network security issues cannot be ignored. Network vulnerabilities and illegal intrusions can affect internet security, and even affect the construction of national infrastructure, critical defense systems, and even military systems. This article selects 50000 sets of data from the KDD99 cybersecurity dataset provided by the National Security Administration of the United States. Each sample in the dataset includes 41 feature attributes and 1 decision attribute. We constructed a model based on the random forest algorithm, using 30% of the total sample data as the test set and the remaining 70% of the data as the training set. Then, 100 sets of data were taken for model training. After the training was completed, the detection model successfully predicted 98 intrusions out of 100 detections, and the final score of the test set was 0.982, basically achieving the effect of intrusion detection. A machine learning algorithm model is provided for detecting network intrusions.
In recent years, the development of electric vehicles has been rapid nationwide, resulting in a strong demand for charging infrastructure. Ensuring orderly charging and providing real-time updates on the availability and utilization of charging stations along the upcoming driving routes, as well as determining efficient charging routes with high timeliness, are crucial challenges that need to be addressed. The cloud-based coordination of intelligent charging services plays a significant role in the integration and development of the intelligent automotive transportation industry. By utilizing cloud-based monitoring of charging station statuses, comprehensive analysis of vehicle navigation routes, and the practical application of intelligent advanced driver assistance systems, the paper aims to collectively solve the charging demand issue for electric vehicles during road travel. Building upon the foundation of vehicle-road-cloud coordination technology with deep learning methods, this paper proposes a novel "vehicle-road-electricity-cloud" framework for intelligent connected vehicles. The research findings presented in this paper contribute to the advancement of vehicle-road-cloud coordination technology in the field of intelligent connected vehicles, offering cost-effective road selection solutions.
Aiming at the problems of large amount of permanent magnet and difficult installation of stator winding in traditional non-iron core disk motor, a disk motor with PCB stator winding is studied and its rotor permanent magnet array is optimized. The stator windings are designed by CAD software and combined with the motor rotor established by 3D finite element simulation software to get the motor model. Then the motor structure is parameterized and multi-objective optimization is carried out by genetic algorithm. The optimized motor reduces the amount of permanent magnet and increases the back potential and torque amplitude. Under the premise of ensuring the performance of the motor, replacing part of the permanent magnet with silicon steel sheet can reduce the manufacturing cost of the motor, and provide a certain reference for the design of the disk motor.
In order to achieve typical fault identification and effective detection of switchgear, the detection methods for circuit breaker machinery, temperature, and partial discharge are analyzed. Firstly, a typical fault simulation platform for circuit breakers that can measure the opening and closing coil current is established, and a typical fault model for circuit breakers is constructed to explore the correlation between the opening and closing coil current of circuit breakers and the operating state of circuit breakers; Further analyze the surface acoustic wave based temperature detection method for switchgear, explore the feasibility of passive wireless temperature measurement technology used to assist in analyzing the status of switchgear, and propose a method for arranging surface acoustic wave sensors in the switchgear; Finally, a typical defect model simulation platform for switchgear is established to measure and analyze the partial discharge signals caused by different defects, and analyze the applicability of partial discharge detection methods for identifying different types of defects.
The flexible Direct Current (DC) transmission system, rooted in High Voltage Direct Current (HVDC) technology, stands as a pivotal means of power transmission, facilitating extensive reach and substantial capacity with inherent advantages of flexibility, reliability, and heightened energy efficiency. Its applications in long-distance transmission, power grid interconnection, and offshore wind power surpass conventional Alternating Current (AC) transmission systems. However, operational challenges in stability and damping suppression persist. Dynamic factors such as uncertainties in parameters, load fluctuations, fault disturbances, and other elements introduce vulnerability to stability decline and potential oscillation issues. Additionally, deleterious harmonic and resonance phenomena exacerbate stability concerns. This paper conducts a comprehensive investigation into ensuring the steadfast operation of the flexible DC transmission system. Through an exploration of stability control and damping suppression strategies, the research proposes meticulous control algorithms to achieve stability control and oscillation mitigation within the system. Empirical evidence from conducted experiments underscores the efficacy of implementing flexible DC transmission based on Modular Multilevel Converters (MMC). This approach proves instrumental in mitigating stability issues inherent in system operation, consequently enhancing overall system performance and reliability. The research contributes to scholarly understanding while advancing the practical application and development of this transformative technology in power transmission, thereby addressing critical challenges in stability for the flexible DC transmission system. CCS CONCEPTS • General and reference∼Cross-computing tools and techniques∼Experimentation
