bluuebunny/crossref_metadata_2025_split huggingface dataset:
Research on assembly constraints reconstruction based on Unreal Engine
Authors: Tang Lei , Wang Daiyong , Mou Zixin , Li Ling , Long Yang , Li Dong 
Published: October 2024

Abstract
In the process of digital twin modeling, the assembly constraints of the model in the Unreal Engine usually requires manual intervention. To realize the intelligence and high efficiency of digital twin modeling, an Unreal Engine based assembly constraints reconstruction method is proposed. The method explores the high-fidelity assembly constraints mapping from the modeling software to the Unreal Engine, divides the model in the modeling software into two parts: the entity structure and the assembly constraints, and reconstructs the assembly constraints in the Unreal Engine, to realize the transformation from the modeling software model to the Unreal Engine model. Finally, the proposed method is applied to the digital twin engineering of various institutions to verify its rapidity and effectiveness in practical application scenarios.
Research on parameter deviation modelling of dual LCC wireless power transfer system
Authors: Yang Kaiying 
Published: October 2024

Abstract
In this paper, parameter deviation modelling analysis is performed based on the dual LCC compensation network of wireless power transfer (WPT) system. Firstly, the mutual inductive coupling model of the dual LCC compensation circuit is derived based on the fundamental wave analysis method; secondly, the parameter deviation is introduced into the circuit model for the errors existing in the inductive and capacitive components of the compensation network circuit of the actual wireless charging system, and the relation between the deviation and the amplitude of the branch currents, the phase angle and the output characteristics of system are obtained through the establishment of derivation model and the resistive deviation correction term is introduced; finally, the parameter deviation is verified through the simulation. The establishment of parameter deviation model increases the accuracy of the whole circuit model and provides the theoretical basis to reduce the negative influence of parameter deviation on transmission characteristics. The value of parameter deviation can be inverted through the phase angle, thus providing a basis for adjusting the resonant state of the compensation circuit.
Analysis of the influence of nonlinear energy sink parameters applicable to helicopter main reduction systems
Authors: Dai Zhixiong , Feng Zhizhuang , Qian Feng , Lu Xing , Xing Longtao 
Published: October 2024

Abstract
In response to the vibration problem of helicopter fuselage caused by continuous rotor periodic excitation force, a nonlinear energy sink is considered to be installed on the main reduction transmission channel to reduce the vibration level of the fuselage. This article conducts an analysis of the influence of nonlinear energy sink structure parameters under harmonic excitation force, establishes a coupled dynamic model of helicopter main reduction/absorber/fuselage, and uses harmonic balance method and stability analysis theory to analyze the periodic solution and stability of the system. Using the vibration amplitude of the system as the evaluation criterion, the influence of damping, stiffness, and mass ratio on the vibration suppression effect of the nonlinear energy sink was explored. The results showed that as the damping of the nonlinear energy sink increased, the resonance frequency of the coupled system shifted to the left, and the vibration amplitude of the main reduction system increased; As the stiffness of the nonlinear energy sink increases, the vibration amplitude of the coupled system will first decrease and then increase, gradually approaching the vibration amplitude of the system without coupled dampers; The influence of mass ratio on system amplitude follows the same trend as the influence of stiffness. By optimizing, the structural parameters of the nonlinear absorber with good vibration suppression effect are ultimately obtained.
Critical lines dynamic identification for grid-connected wind power system under N-k contingency based on Oscillating equations
Authors: Li Lijuan , Lv Zhiqiang , He Hao , Ouyang Wenzhao , Liu Renai 
Published: October 2024

Abstract
As the penetration rate of wind power and other renewable energy sources increases, power systems are more prone to experiencing multiple component failures, known as N-k contingency Identifying and then closely monitoring and protecting critical components during N-k contingency can effectively prevent widespread cascading failures. The primary task in identifying critical components is to model the power system; A refined model better captures the time-varying characteristics of electrical components. Therefore, a dynamic model of line power flow decay and oscillation based on swing equations is established; it introduces time-varying saturated cut-set and transfer margin indices to identify critical lines. Simulations on the IEEE-118 nodes system, along with MATCASC cascading failure simulations, demonstrate that targeting identified critical lines as deliberate attack points in the grid results in a normalized remaining load demand decrease to 50% of the original.
Research on ultra-high temperature sensor and cold end compensation error
Authors: Wang Zhenting , Liu Baowei , Qi Na , He Tianhao , Wang Yuanwei , Wang Mingqian 
Published: October 2024

Abstract
An ultra high temperature sensor and cold end compensation error are proposed. Aiming at the ultra-high temperature and relatively complex harsh environment of spacecraft, a sensor probe structure which can withstand the high temperature of 2500°C is presented in this paper. According to the practical application characteristics of the sensor with high measurement accuracy, the author proposed a high-precision cold end compensation method. Through this compensation technology, the ultra-high temperature sensor maintains high-precision temperature measurement in the full temperature range. The simulation analysis of the sensor structure and temperature test show that the sensor can not only realize temperature measurement at ultra-high temperature, but also control the nonlinear error to 0.6% of the full scale. The accuracy of the whole temperature range is controlled within 0.92% of the full scale, which meets the practical requirements.
Chaotic dynamics of a delayed fractional order MLNCML system
Authors: Liu Liyan 
Published: October 2024

Abstract
We present a delayed fractional order spatiotemporal dynamical system using the mixed linear-nonlinear coupling connections between lattices. In the simulation experiments, the dynamical characteristics of the proposed model are looked into and analyzed by using bifurcation diagrams and metric entropy density. The proposed model has fewer periodic windows in its bifurcation diagrams, large key space and strong ergodicity due to the delay. These excellent properties are of great significance in encryption. Moreover, the parameter μ breaks its fixed range in the traditional logistic map, which can contribute to enlarge the key space of cryptosystem. Through numerical simulations and security analysis, it is found that the proposed model is applied for encryption.
Design and realization of multifunctional energy meter calibration station under extreme conditions
Authors: Chen Qian , Chen Yunpeng , Liu Jianbo , Yang Mei , Sun Xiao Jie , Zhao Gege , Cao Baohua 
Published: October 2024

Abstract
This paper designs a multifunctional calibration station that can be installed inside the temperature box in order to adapt to some of the special test requirements, which can be used for the testing of most types of energy meters on the market. Extreme environments such as high and low temperatures can easily cause cracks in equipment welds, aging of material insulation, and functionally cause sensitive components to drift affecting the accuracy of testing during the life cycle of the calibrator. This multifunctional calibration station designed and implemented in this paper is capable of maintaining its functionality without being destroyed under repeated experiences of extreme conditions. In this paper, a multifunctional calibration station is designed and realised. In order to verify the influence of the calibrator on the calibration error of the energy meter after repeatedly experiencing extreme conditions, a comparison test of 40 cycles was carried out by comparing the calibrator with the one placed at room temperature, and the difference between the two calibrators’ measurement results did not show a regular growth trend with the increase in the number of measurement cycles, which proves that the calibrator is able to keep its function undamaged under the repeated experience of extreme conditions.
Numerical analysis of flexural behaviour of UHPC-CFTS columns as enclosure supports for electrical substations
Authors: Yan Yan , Gao Xian , Chen Xilong 
Published: October 2024

Abstract
This study establishes a finite element analysis model of ultra-high-performance concrete (UHPC) encased concrete filled steel tube (CFST) composite columns under combined compression and bending. Appropriate constitutive models and element types are selected as the basis. The finite element model simulates the test results of steel-concrete composite columns, and the applicability of the model is verified by comparison with existing test data of UHPC encased CFSTs. On the basis of demonstrating model reliability, the full-range load-deformation curves of UHPC encased CFSTs with different concrete strengths under compression-bending are compared. The failure modes and material stress distributions are analyzed to elucidate the influence mechanism of the UHPC on the flexural performance of UHPC encased CFSTs under combined compression and bending. The results show that compared to normal concrete, UHPC can effectively improve the flexural capacity of UHPC encased CFST columns. Owing to the addition of steel fibers, the failure mode of UHPC encased CFSTs under combined compression and bending is more integral compared to normal concrete. The research results of this study can provide references for the performance evaluation and design of UHPC encased CFSTs in the structural enclosures for electrical equipment in high/low voltage substations.
Development and application of carbon dioxide direct mineralization technology and emission reduction device
Authors: Li Dongfang , Zheng Zhang , Huang Zengyang 
Published: October 2024

Abstract
This study analyzes the principles and methods of carbon dioxide mineralization fixation to address the challenges posed by global climate and ecological changes, achieve carbon neutrality goals, and solve carbon utilization issues in the development of the fluorosilicon new material industry. The research focuses on the direct mineralization reaction system of carbon dioxide flue gas and the development of a carbon dioxide emission reduction device utilizing wet mineralized gas treatment technology. To implement alkaline waste management for industrial solid waste. The research shows that the wet carbon dioxide mineralization and emission reduction device can make the alkaline solution better mineralize carbon dioxide, avoid the gas discharge too fast and affect the reaction rate. At the same time, the solution is mixed and the exhaust linkage is carried out to further improve the reaction rate, and provide a reference for the development of large-scale carbon dioxide utilization technology suitable for high energy consumption industries.
Research on coupling analysis and decoupling control of two-degree-of-freedom PTZ system
Authors: Gao Jianshu , Zhao Lei 
Published: October 2024

Abstract
With the development of technology, especially in areas such as robotics, aerospace, photography, and videography, gimbal systems, as an important stabilization device, have been widely used. However, the two-degree-of-freedom gimbal system also faces a series of challenges in practical applications. Among them, one of the most critical issues is the internal coupling phenomenon in the system. The coupling phenomenon refers to the mutual influence and a constraint relationship between different degrees of freedom in the system, which may increase the complexity of the system’s dynamic characteristics and make the design and implementation of control strategies difficult. This study aims at explore more advanced and practical decoupling control strategies through in-depth analysis of the coupling characteristics of the two-degree-of-freedom gimbal system, providing new ideas and methods for the further optimization and application of the gimbal system.
Research on Calibration device of gas leakage alarm system and uncertainty analysis
Authors: Liu Xing , Qin Maoyuan , Yang Zhongzhi , Xiang Yang , Liu Wei 
Published: October 2024

Abstract
This paper studies the calibration device and method of the gas leakage alarm system, and evaluates the uncertainty of the measurement results. Firstly, it analyzes the important components, parameters, and working principles of the gas leakage alarm system. Then, it designs a set of inhalation-type gas leakage alarm system calibration devices to test the indication error, repeatability, and response time of the alarm system, and evaluates the uncertainty of the calibration device. The study concludes that the relative expanded measurement uncertainty of the device calibrating the alarm system is 2.6%, which meets the accuracy requirements of national standards for calibration devices. The main factors affecting the measurement results are the resolution and repeatability of the alarm system being tested. By improving the performance of the alarm system sensor, the measurement results of the alarm system can be made closer to the true value, reducing misjudgment and improving the accuracy of the system. And during calibration, the measurement capability of the device can be enhanced by using higher grade gas standard substances.
Study on bearsing capacity and rigidity of surface throttling bearing
Authors: Song Lihua , Kang Junyuan 
Published: October 2024

Abstract
Based on the lubrication principle and Reynolds theory, the influence of the pressure field and structural parameters on the bearing characteristics of the surface throttle bearing is analyzed and studied by using the finite difference method. The results show that the surface throttling bearing has obvious static bearing characteristics when the shaft is not rotating; The dynamic pressure effect of oil wedge load can be seen obviously when the shaft rotates. With the increase of radius gap h0, the bearing capacity and rigidity will decrease significantly. The increase of oil supply pressure will reduce bearing capacity and rigidity. With the increase of length-diameter ratio

L

¯

, the rigidity will be improved.
An improved relative integral capacity-K-means clustering method for capacity pre-sorting of decommissioned power batteries
Authors: Xu Xuntao , Wang Shunli , Liu Donglei , Fernandez Carlos , Blaabjerg Frede 
Published: October 2024

Abstract
Capacity sorting is the primary prerequisite for the stepwise utilization of decommissioned power batteries. This study proposes an improved relative integral capacity-K-means clustering (RIC-KMC) method for preliminary sorting of decommissioned power battery capacity. Firstly, according to the electrochemical aging characteristics of decommissioned power batteries, combined with the ampere-time integration algorithm, a new lossless extraction method of the capacity characteristics of Lithium-ion batteries based on the segment voltage is proposed. Second, to minimize the interference of environmental factors and sampling errors on the charging capacity, the relative amount of charging capacity is introduced. Finally, to complete the capacity sorting before the ladder utilization, an improved RIC-KMC method is proposed, which combines the electrochemical aging feature values of decommissioned power batteries extracted from the segment voltage charging capacity with the K-means clustering algorithm. Using three sets of battery charging and discharging data to validate the sorting algorithm, the capacity sorting errors are reduced by 0.926%, 12.381%, and 10.185%, respectively, which verification the validity of the proposed RIC-KMC method. This study provides a new solution for capacity pre-sorting of decommissioned power batteries for stepwise utilization.
Dyeing scheduling optimization in a multi-machine system with resource constraints
Authors: Gao Shaofeng , Zhang Biyue , Xiao Lei , Zhou Qihong 
Published: October 2024

Abstract
Water consumption is one of the most important concerns for a textile dyeing company in the era of global energy revolution. Different from the traditional production scheduling which focuses on the production efficiency improvement, the dyeing scheduling emphasizes the constraints of resource consumption. Besides, different from the traditional production scheduling where the task relevance is seldomly considered, the colour depth heavily impacts the water consumption and the dyeing scheduling results, which aggravates the uncertainty and complexity when modelling the dyeing scheduling optimization. Therefore, how to select proper dyeing orders among a large number of orders and schedule them for the purpose of generating more profit is challenging. To address the above issue, an optimization model with objective of maximizing profit and consideration of water consumption, delivery due time, and machine capacity, is built, and genetic algorithm is adopted to solve the problem. A numeric experiment is conducted to validate the effectiveness of the proposed method.
Research on deep reinforcement learning-based complex crowd navigation algorithm using risk perception and path selection
Authors: Zhao Tianxiang , Jiang Yang , Chang Jiajun , Zhao Bin 
Published: October 2024

Abstract
Aiming at the Frozen Robot Problem and the poor effect of dynamic obstacle avoidance in traditional navigation methods when encountering dynamic obstacles, a deep reinforcement learning navigation method based on risk perception and path selection is proposed. The core of this method lies in CP (Collision Probability) module and IOU (Intersection over Union) module. The CP module calculates the CP between the robot and the nearby dynamic obstacles in real time, so that the robot can avoid the dangerous obstacles first. At the same time, the intersection-merging ratio module calculates the “pass ability” of the area near the robot in real time, and guides the robot to choose a safer area to pass through. Compared with the DRL method without these two modules, the proposed method achieves the highest navigation success rate in all simulation test environments, and the maximum improvement rate is 11%. At the same time, it still has advantages in navigation time and other indicators.
Optimal inventory decisions of infrequently needed spare parts for maintenance with inaccurate demand forecasts and limited storage space
Authors: Liu Xuanyi , Xu Zhenqi , Zheng Meimei 
Published: October 2024

Abstract
In modern manufacturing workshops, maintaining adequate inventory for spare parts is an effective strategy to satisfy maintenance requirements. However, due to the stochastic nature of failures, spare parts often have characteristics of infrequent usage and inaccurate forecasted demand. Additionally, the multitude diversity of spare parts and limited storage space in warehouse poses challenges to inventory decisions regarding the types and quantity of spares. Thus, this paper investigates the inventory decision optimization problem of infrequently needed spare parts for maintenance within limited storage space and inaccurate forecasted demand. This paper constructed an integer programming model based on chance constraints to address the uncertainty of the storage space occupied by the spare parts. The main contributions of this paper are as follows. First, we investigate the inventory decision optimization problem within limited storage space and inaccurate forecasted demand, which are rarely considered in the optimization problem of the spare parts for maintenance. Second, we proposed a method for simplifying the computation of chance constraints based on a transformation of the Central Limit Theorem. Third, we proposed a heuristic iterate algorithm to search the optimal inventory decision by minimizing the overall downtime and storage costs. Using data from the workshop of an automotive enterprise, a case study is conducted by comparison with the Genetic Algorithm.
Failure analysis and life extension of mechanical products under multiple service conditions
Authors: Chen Shangong , Ren Jiadong , Shi Peng , He Hongdou , Hao Xiaobing , Huang Guoyan 
Published: October 2024

Abstract
During the service of engineering machinery products, the interaction of mechanical load, service environment and other conditions leads to the diversity and uncertainty of failure modes. Mechanism analysis is difficult to accurately calculate the dynamic changes of performance. Most existing machine learning methods only focus on the remaining useful life, without considering the internal mechanism and connection of multiple failure modes. In this paper, a resistance degradation model is established based on the data of multiple service cycles. According to the service data under different working conditions, a dynamic resistance degradation model based on classification and regression tree (CART) and a product service life enhancement strategy based on working condition sequence optimization are proposed. Firstly, the characteristics of different working conditions are analysed. Secondly, the data of multiple sensors are fused, and CART is used to fit the degradation model. Finally, a product service life optimization problem is designed to increase the life. Experiments show that the proposed method can fit the resistance degradation process, and can significantly improve the life of mechanical products.
High-accuracy gearbox fault detection using deep learning on vibrational data
Authors: Arshad Mayo Sohaib , Rehman Saud , Cai Zhiqiang 
Published: October 2024

Abstract
In the face of escalating demands for reliability in industrial machinery, this study introduces an advanced deep-learning model aimed at the early detection of faults in rotating gear systems. Addressing the need for timely fault diagnosis to prevent operational disruptions and financial setbacks, our work utilizes a novel neural network approach applied to vibrational data from Kaggle’s Gearbox Fault Diagnosis Dataset. The methodology involves data preprocessing steps, including normalization and one-hot encoding, followed by training a sequential neural network with multiple dense layers and dropout for regularization. The model, trained using the Adam optimizer and evaluated over 50 epochs, significantly outperforms traditional machine learning techniques, achieving a remarkable 98.63% accuracy in distinguishing between healthy and compromised gear conditions. This research marks a significant stride in predictive maintenance, providing a robust foundation for future development toward prognostic health management systems that anticipate maintenance needs and ensure uninterrupted industrial productivity.
Television and Academic Achievement: Evidence from the Digital Television Transition in the UK
Authors: Nieto Castro Adrián 
Published: October 2024

Abstract
This paper exploits exogenous variation in the transition date from an analogue to digital television signal in the UK across more than 32,000 geographical units to examine the causal impact of television on academic performance and potential mechanisms. Using a large administrative dataset on the universe of students in public education in England, I show that the switchover increased pupil test scores and that the effect is driven by economically disadvantaged students. Using TV market data and a child survey dataset, I investigate possible mechanisms. I show that the digital transition considerably increased TV viewing time and displaced forms of socialisation associated with risky behaviour for disadvantaged children.