bluuebunny/crossref_metadata_2025_split huggingface dataset:
An approach to bearing fault diagnosis based on ensemble learning and case-based reasoning
Authors: Li Jinjie , Guo Yu , Dou Yajie , Wang JiKai , Qiu Biaobiao , Liu Xi 
Published: June 2024

Abstract
In response to the challenge of multiple fault types and complex diagnostic criteria in bearing fault diagnosis, a case reasoning method based on ensemble learning is proposed. The approach utilizes Case-Based Reasoning (CBR) to construct a case library for vibration-based features of rolling bearings and perform fault diagnosis. Moreover, addressing the issue of determining optimal feature weight ratios when retrieving similar cases in traditional case reasoning methods, a Random Forest algorithm combined with Bayesian Optimization is introduced. This integration allows for adaptive retrieval of similar cases, thereby enhancing the diagnostic capability for bearing faults. The effectiveness of this approach is validated through experimental analysis.
Neural network PID control of spherical permanent magnet based on external magnetic field driving system
Authors: Liu Guancheng , Jiang Renjun , Fan Lei , Lv Qing , Lu Conghui , Wang Pingping 
Published: June 2024

Abstract
The neural network PID control method of the external magnetic field driving system solves the shortcomings of the traditional control method. The controlled object is a spherical permanent magnet. Other detections or operation equipment can be attached to the sphere. In the process of external magnetic field driving, the model-based controller is prone to large fluctuations when the environmental parameters change, which reduces the control performance. The neural network algorithm has good control ability for the highly nonlinear magnetic levitation driving system. PID control system combined with a neural network algorithm has high stability and strong adaptability in the driving process. The test results show that the response output overshoot is 9.322%, and the system fluctuation is low. Self-tuning and adaptive environment changes of PID controller parameters can be realized by neural network control.
Vibration signal acquisition and extraction for cutter wear monitoring
Authors: Zhou Wuxue , Li Jing , Shen Nanyan , Ran Zhuang 
Published: June 2024

Abstract
The cutter wear state is key in manufacturing. During the machining, the vibration signal of the tool spindle will change with the increase of cutter wear, which provides an effective method for cutter wear monitoring. However, due to the popularity of machining centers, the machining trajectory of a cutter is extremely complex in practical production. The complexity includes a single process containing multiple work steps, a step containing random and long non-cutting time, etc., making it difficult to acquire and extract the specific step signal as the effective signal for cutter wear monitoring. Therefore, this paper proposes a system that can synchronously acquire machine parameters and tool spindle vibration signals. Then, two algorithms—the cutting signal recognition algorithm and the step signal similarity detection algorithm—are proposed. The former algorithm is based on sliding window energy, which can accurately identify the instant the cutter begins to cut the workpiece. The step signal similarity detection algorithm based on the Edit Distance on Real (EDR) sequence ensures the correctness of the step extraction. The experimental results show that the system has efficient acquisition of vibration signals and correct step signal extraction, providing a data basis for cutter wear monitoring.
BiLSTM-KNN network for locomotion mode recognition in lower limb exoskeleton robot
Authors: Yu Xiangxiang , Huang Liping , Gao Yifan , Chen Ziyao , Wang Hui , Yang Jiamei , Zheng Jianbin 
Published: June 2024

Abstract
Lower limb exoskeleton robots have become a research hotspot among various enterprises, universities, and institutions. This paper proposes a deep learning network based on the recognition of five movement patterns of lower limb exoskeletons, including walking on level ground, going upstairs, going downstairs, uphill, and downhill. The network uses BiLSTM to capture the forward and backward relationships of time series data, which has better resolution than the original features. In addition, the network uses the KNN algorithm based on shortest-distance voting to improve the recognition accuracy. The network achieved a recognition rate of 99.18% for five motion patterns. In summary, the proposed network has excellent performance in terms of accuracy and generalization.
Research on complex products assembly sequence planning and its application based on PSO-GA
Authors: Ma Jun , Zhou Zhonghua , Meng Lina , Fu Jiawen , Li Xiaoke 
Published: June 2024

Abstract
A PSO-GA-based method is proposed to improve the efficiency of complex product assembly sequence planning. We minimize total assembly time by optimizing the assembly sequence, considering the number of tool changes and assembly direction changes as evaluation criteria. A genetic algorithm (GA) is introduced into particle swarm optimization (PSO) to solve and verify assembly sequence planning. Finally, the effectiveness and rationality of the hybrid algorithm are verified by taking a certain type of gear pump as an example.
Improvement methods for feature matching in Basalt SLAM
Authors: Shi Leilei , Tan Junguang , Xu Bin 
Published: June 2024

Abstract
Visual simultaneous localization and mapping (SLAM) is widely used to provide localization information for mobile robots, but most visual SLAM algorithms lack effective data association methods, resulting in unstable position tracking results. In this paper, relevant improvement schemes for global feature matching in the Basalt SLAM algorithm are proposed to enhance the effectiveness of its data association method. Firstly, the more efficient box average difference (BAD) descriptor is used instead of the ORB descriptor. Secondly, secondary matching is performed by narrowing the matching range with the epipolar geometric constraint to expand matching pairs. Finally, grid-based motion statistics (GMS) and histogram-based rotation consistency constraints are introduced to eliminate false matches. Experiments on the EuRoC dataset demonstrate that the proposed methods significantly enhance the effectiveness and stability of visual data association and improve the localization accuracy of the Basalt SLAM system.
Parameters identification and application of composite plate reinforcement mesh based on DXF data
Authors: Yin Haibin , Cai Zhixiang , Zhou Zepeng , Shi Dongxing , Yu Jiajun , Li Zhongwei 
Published: June 2024

Abstract
This paper presents an algorithm for identifying the process parameters of a laminated plate reinforcement mesh. To accommodate the actual production needs, the computer software of the production line is employed for the identification of parameters and data processing of the DXF steel mesh file. In this context, a C++ programming algorithm is utilized for the identification of the parameters of the imported DXF file, as per the production line’s processing requirements. DXF is an AutoCAD vector graphics exchange file that is available in two storage formats: ASCII format and binary format. The ASCII format is easily readable and therefore, DXF is widely used, with most CAD software capable of reading or outputting DXF files. This paper initially scrutinizes the structural attributes of DXF files, normalizes the design standard of graphics files, and then reads the coordinates of each point of the POLYLINE entity. A parameter identification algorithm is devised to address the issue of steel bar bending in drawings, with the program designed to verify its accuracy.
A comprehensive study on the romax-based comprehensive shaping method for skewed cylindrical gears
Authors: Ma Jingyu , Wang Shufen 
Published: June 2024

Abstract
Tooth profile modification is one of the effective ways to solve the vibration and noise problems in gear transmission. This article is based on the dynamic Romax Designer software for simulation and studies the micro modification problem of helical cylindrical gears in a certain reducer. Based on the analysis of the limitations of tooth profile modification and tooth orientation modification methods, a comprehensive tooth profile modification method is proposed. The simulation results show that the transmission error, load distribution, meshing situation, and service life of the gear have improved after adopting the comprehensive modification method, thereby improving the transmission accuracy, reliability, and durability of the gear. This method can provide reference and reference for gear modification of reducers.
Research on the scheduling of steel mesh production line based on the improved grey wolf algorithm
Authors: Yin Haibin , Feng Yu , Xie Junyong , Zhou Xiangqun , Zhang Yushun , Shi Dongxing , Li Zhongwei 
Published: June 2024

Abstract
To solve the scheduling problem of a flexible production line of reinforced mesh, a mathematical model of flexible production line scheduling of reinforced mesh was established to minimize the maximum completion time. The Improved Gray Wolf Algorithm (IGWO) was designed, and the improvement measures of the Gray Wolf Algorithm (GWO) were proposed from the population initialization method, key parameter improvement, and search mechanism. Through the example verification, the Improved Grey Wolf Algorithm is applied to the scheduling problem of the flexible steel production line. The problem of the flexible production line of steel mesh and the results of the Improved Grey Wolf Algorithm, Grey Wolf Algorithm, Genetic Algorithm (GA), and artificial scheduling are compared. The results verify that the results of the enhanced Grey Wolf Algorithm have better quality and can better guide the production line to carry out efficient and energy-saving production.
Research on optimal dispatch of 5G base station VPP with standby energy storage
Authors: Chen Tongxuan , Zhang Zaiyi , Ma Xiufan 
Published: June 2024

Abstract
With the rapid increase in the construction of 5G base stations, the backup battery of 5G base stations will be a huge potential energy storage resource. China’s electricity market reform is constantly advancing, and the study of 5G base stations’ standby energy storage to participate in power optimization dispatch is an effective way to realize the reciprocal benefits of power grids and telecommunication operators. Considering the special characteristics of 5G base station backup energy storage to participate in the power market, the article establishes a virtual power plant of 5G base station considering the backup energy storage. Then, the 5G base station VPP is added to the operation of the power grid as an adjustable resource, and the dual-5G base station VPP optimization matrix is built. Finally, a numerical example verifies that the standby energy storage of the 5G base station contains rich schedulable capacity and that the 5G base station VPP can validly improve the economy of power grid operation.
Research on coordinated control technology of hybrid energy storage under grid-connected/off-grid dual mode
Authors: Sun Rui , Gu Cailian , Xue Shuai , Cai Chaohao 
Published: June 2024

Abstract
Aiming at the multi-time scale intermittency of renewable energy in microgrids and frequent power fluctuations will lead to a series of power quality issues. So, it is necessary to propose appropriate strategies for controlling the energy storage systems of microgrids to ensure energy balance. In microgrids, two types of battery energy storage are used to form a hybrid energy storage system, namely, zinc-bromine flow battery for energy storage and lithium titanate battery for energy storage. By analyzing the functionality of various energy storage systems in the grid-connected/off-grid dual style, the operation objectives of the hybrid energy storage system in different modes are proposed. In the meantime, the control strategy is formulated by combining the smoothing fluctuation characteristics of power-type energy storage and the peak load shifting features of energy-type energy storage. Finally, the efficiency of the hybrid energy system control strategy is checked by the simulation software in the connected/off-the-grid mode.
Resilience-oriented critical load restoration for railway distribution systems in remote areas by coordination of photovoltaics and energy storage systems
Authors: Wang Ying , Liu Weizhi , Ma Yingtao 
Published: June 2024

Abstract
The utility power infrastructure is relatively weak and susceptible to extreme conditions in remote areas, so the resilience enhancement of the railway distribution system is essential to ensure the service to critical loads, such as communication and signal devices, to prevent undesirable crash events. After extreme events, distributed resources such as distributed photovoltaics (PVs) and energy storage systems (ESSs) can be coordinated to restore critical loads as soon as possible. In this paper, a critical load restoration method for railway distribution systems in remote areas is proposed. The PVs and ESSs are coordinated to restore the critical loads distributed along the railway line. The problem is formulated as a mixed integer linear program and solved by off-the-shelf solvers. Finally, the effectiveness of the method is validated through a real-world case in China.
A comprehensive energy flow analysis method based on hydrogen energy to electric energy conversion
Authors: Bian Jiayu , Zhou Zhuan , Yu Jin , Shi Xiaochao , Huang Ping , Du Wenzhe 
Published: June 2024

Abstract
With increasing global concerns about climate change, more and more countries and regions are turning to sustainable energy, and hydrogen energy, as one of the representatives of clean energy, is gradually becoming one of the key areas for development in various countries. Due to its high energy density, easy storage, and pollution-free characteristics, hydrogen energy has been widely used in fields such as automobiles, aviation, and petrochemicals. In the automotive industry, hydrogen energy, as a renewable and clean energy source, has become one of the development directions. Compared to traditional fuel, hydrogen-powered vehicles not only achieve zero emissions but also have higher energy efficiency and can achieve longer range. Currently, multiple countries around the world are accelerating the promotion of hydrogen-powered vehicles and building related infrastructure such as hydrogen refueling stations. In the aviation field, hydrogen energy also has broad application prospects. Traditional aviation fuel contains a lot of hydrocarbons, so the pollution problem of the aviation industry has been a concern. As a clean and renewable energy source, hydrogen energy not only solves the pollution problem in the aviation industry but also has a very high energy density, providing sufficient power to support aircraft flight. In addition to the automotive and aviation fields, hydrogen energy can also be widely used in the petrochemical industry. Currently, traditional petrochemical production processes emit many harmful substances such as carbon dioxide, greatly affecting environmental quality. By using hydrogen energy, harmful substances such as carbon dioxide generated in traditional petrochemical processes can be converted into renewable resources, thus achieving an environmentally friendly, efficient, and sustainable production model.
Multi-objective optimization of an integrated energy system based on enhanced NSGA-II
Authors: Zhao Ziyi , Xiao Xiang , Yang Wentao , Yin Shiwen , Ding Xiangri , Gao Haixiang , Gao Yusong 
Published: June 2024

Abstract
To solve the energy crisis, China has made great efforts to develop an integrated energy system to achieve multi-energy coordination, mutual aid, energy conservation, and carbon reduction. This article mainly studies the multi-objective optimization scheduling problem of a combined cooling, heating, and power system considering wind and solar energy storage. Firstly, from two different perspectives of economy and carbon emissions, an economic objective function and an environmental objective function are established, and a multi-objective optimization configuration model and corresponding constraint conditions for the combined cooling, heating, and power system considering wind and solar energy storage are constructed. Then, an enhanced non-dominated sorting genetic algorithm II (NSGA-II) is proposed, which enhances the efficiency and accuracy of the algorithm by introducing dominance strength and variance factors. Finally, a simulation analysis was conducted on a running cogeneration system in a certain area of western Liaoning to attest to the validity of the model and method proposed in this paper.
Optimization of solar-air source heat pump hybrid heating system
Authors: Zhang Yuxin , Tang Xiaoping , Ji Dongmei 
Published: June 2024

Abstract
In order to construct a versatile, complementary, low-carbon, clean, and efficient heating system, this study explores the potential of a solar-air source heat pump (SAHP) hybrid heating system. A simulation model is established in TRNSYS, and the particle swarm algorithm (PSO) and genetic algorithm (GA) from GENOPT and MATLAB are employed. With the aim of minimizing the annual cost, optimization is conducted on the key parameters and operational strategies of the system. Comparative analysis between the two algorithms reveals that PSO slightly outperforms in cost reduction, while GA exhibits a slight advantage in enhancing system performance. Significantly improved energy savings are achieved by appropriately reducing the rated heating capacity of the air source heat pump and increasing the volume of the water tank.
Thermal analysis of a gas-liquid compressed carbon dioxide energy storage system
Authors: Yu Zhenyue , Li Jiantao , Su Wei , Xu Cheng 
Published: June 2024

Abstract
In recent years, compressed CO2 energy storage (CCES) systems have attracted increasing attention, because the high-pressure storage tanks in the CCES systems are relatively small, thereby reducing investment costs and improving geographic construction flexibility. In this paper, we propose a gas-liquid CCES system that has strong industrial feasibility. A comprehensive thermodynamic evaluation and parametric analysis were performed for this system. The results show that the efficiency is 72.99% and the storage pressure is an important parameter influencing the thermal performance of this system, and the reasons behind it are explored.
An enhanced strategy for new energy generation black-start based on hybrid energy storage system
Authors: Song Zhen , Wang Hongtao , Wang Haobo , Xin Peiqi 
Published: June 2024

Abstract
In the past few years, the connection of extensive power grids with a substantial influx of renewable energy has resulted in a growing hazard of significant power failures. Conventional black-start systems are inadequate in promptly and adaptively recuperating from such outages. Consequently, the emergence of new energy generation integrated with energy storage technology to deliver black-start services has become a prevailing trajectory. In this research article, hybrid energy storage is implemented for the wind and solar power generation system to address the issue of inadequate inertia support capacity during the black-start process. The system incorporates a virtual synchronizer to manage and replicate its inertia and damping features, thereby enhancing the black-start capability of renewable energy generation. The effectiveness of the proposed strategy is verified through simulation in Matlab/Simulink.
Research on robust optimization of the integrated energy system in industrial parks based on adaptive genetic algorithm
Authors: Jia Xiaoqiang , Yang Yongbiao , Du Jiao , Gan Haiqin 
Published: June 2024

Abstract
As the core energy supply mode of the future park, the operation strategy will have an enormous impact on the operating cost and energy efficiency of the park. To further enhance the economic and robustness of the park’s integrated energy system (IES), an optimization model for the operation is established based on robust algorithms and adaptive genetic algorithms (GA). The results show that the optimized carbon neutral park’s comprehensive energy system achieves full consumption of renewable energy, and the utilization rate of new energy reaches 100%. Cool storage is used when the energy price is low, on the contrary, cooling is supplied. After considering the consumption indicators of new energy, the improvement of the new energy utilization rate can raise the system’s efficiency.
Risk assessment of the high percentage of distributed renewable energy access to the grid
Authors: Zhang Jianing , Zhang Xin , Cao Xiangyang , Bo Qibin , Wei Jia , Yu Shunxiang 
Published: June 2024

Abstract
Randomness and uncertainty are the outstanding characteristics of renewable energy, and the extremely high proportion of distributed renewable energy connected to the grid is bound to cause a serious impact. To comprehensively consider the uncertainty of renewable energy, the probability density function of distributed new energy is used to represent its output level. In addition, due to the geographical proximity of distributed new energy sources, there is a correlation between the output of distributed renewable energy sources. The copula function is used to denote the relation between their generation. Then, the method is verified by the IEEE 34-bus system.
An optimal configuration method of energy storage system considering source-load matching
Authors: Jiang Ruofei , Liu Hongwei , Peng Haojie 
Published: June 2024

Abstract
With the introduction of the dual-carbon goals, renewable energy sources have experienced rapid growth. However, due to the intermittent, stochastic, and fluctuating nature of renewable energy, a high penetration of these renewable energy sources poses significant challenges to grid stability. To address this issue, this paper presents an optimization configuration method for the energy storage system (ESS) that considers source-load matching. Firstly, the evaluation index of source-charge matching and the economic index of energy storage system are put forward. Then, an energy storage optimization configuration model considering source-load matching is established. The optimization objective of this model is to minimize the daily average comprehensive cost of energy storage and the penalty cost of source-load matching deviation. Finally, the Gurobi solver is invoked on Matlab platform for simulation analysis, and the results show that the energy storage optimization configuration model proposed in this paper can effectively improve the source-load matching.
A comprehensive power quality assessment method based on data envelopment analysis method and mutation decision-making
Authors: Zhou Hangyu , Li Sicheng , Ma Xiufan 
Published: June 2024

Abstract
As the construction of new power systems continues to advance, integrating a high percentage of new energy sources into the grid and the massive application of power electronic equipment brings serious power quality problems. At the same time, power quality assessment is the basis for solving power quality problems. A comprehensive power quality assessment method combining data envelopment analysis and mutation decision-making is proposed in this paper. Firstly, a power quality governance efficiency model using data envelopment analysis is constructed. Secondly, a power quality assessment method is proposed, combining governance results and mutation decision-making. Finally, the efficiency value and power quality value of each assessment point are obtained to realize the governance efficiency and power quality ranking of the assessment points. The example results prove the effectiveness of the proposed method.