bluuebunny/crossref_metadata_2025_split huggingface dataset:
Rotating machinery fault classification based on one-dimensional residual network with attention mechanism and bidirectional gated recurrent unit
Authors: Dong Zhilin , Zhao Dezun , Cui Lingli 
Published: April 2024

Abstract
Conventional convolutional neural networks (CNNs) predominantly emphasize spatial features of signals and often fall short in prioritizing sequential features. As the number of layers increases, they are prone to issues such as vanishing or exploding gradients, leading to training instability and subsequent erratic fluctuations in loss values and recognition rates. To address this issue, a novel hybrid model, termed one-dimensional (1D) residual network with attention mechanism and bidirectional gated recurrent unit (BGRU) is developed for rotating machinery fault classification. First, a novel 1D residual network with optimized structure is constructed to obtain spatial features and mitigate the gradient vanishing or exploding. Second, the attention mechanism (AM) is designed to catch important impact characteristics for fault samples. Next, temporal features are mined through the BGRU. Finally, feature information is summarized through global average pooling, and the fully connected layer is utilized to output the final classification result for rotating machinery fault diagnosis. The developed technique which is tested on one set of planetary gear data and three different sets of bearing data, has achieved classification accuracy of 98.5%, 100%, 100%, and 100%, respectively. Compared with other methods, including CNN, CNN-BGRU, CNN-AM, and CNN with an AM-BGRU, the proposed technique has the highest recognition rate and stable diagnostic performance.
Binder-free all-carbon composite supercapacitors
Authors: Jarrar Sabreen , Hussain Shahzad , Haq Atta Ul , Bhattacharya Gourav , Saadeddin Iyad , Servera Llorenc , Ruiz JM , Janem Alaa , Daraghmeh Allan 
Published: April 2024

Abstract
Carbon-based electrode materials have widely been used in supercapacitors. Unfortunately, the fabrication of the supercapacitors includes a polymeric binding material that leads to an undesirable addition of weight along with an increased charge transfer resistance. Herein, binder-free and lightweight electrodes were fabricated using powder processing of carbon nanofibers (CNFs) and graphene nanoplatelets (GNPs) resulting in a hybrid all-carbon composite material. The structural, morphological, and electrochemical properties of the composite electrodes were studied at different concentrations of GNPs. The specific capacitance (Cs) of the CNFs/GNPs composite was improved by increasing the concentration of GNPs. A maximum Cs of around 120 F g−1 was achieved at 90 wt% GNPs which is around 5-fold higher in value than the pristine CNFs in 1 M potassium hydroxides (KOH), which then further increased to 189 F g−1 in 6 M KOH electrolyte. The energy density of around 20 Wh kg−1 with the corresponding power density of 340 W kg−1 was achieved in the supercapacitor containing 90 wt% GNPs. The enhanced electrochemical performance of the composite is related to the presence of a synergistic effect and the CNFs establishing conductive/percolating networks. Such binder-free all-carbon electrodes can be a potential candidate for next-generation energy applications.
Data classification and parameter estimations with deep learning to the simulated time-domain high-frequency gravitational waves detections
Authors: Shi B , Yuan X L , Zheng H , Wang X D , Li J , Jiang Q Q , Li F Y , Wei L F 
Published: April 2024

Abstract
High-frequency gravitational wave (HFGW) detection is a great challenge, as its signal is significantly weak compared with the relevant background noise in the same frequency bands. Therefore, besides designing and running the feasible installation for the experimental weak-signal detection, developing various effective approaches to process the big detected data for extracting the information about the GWs is also particularly important. In this paper, we focus on the simulated time-domain detected data of the electromagnetic response of the GWs in high-frequency band, typically such as Gigahertz. Specifically, we develop an effective deep learning method to implement the classification of the simulated detection data, which includes the strong electromagnetic background noise in the same frequency band, for the parameter estimations of the HFGWs. The simulatively detected data is generated by the transverse first-order electromagnetic responses of the HFGWs passing through a high stationary magnetic field biased by a high-frequency Gaussian beam. We propose a convolutional neural network model to implement the classification of the simulated detection data, whose accuracy can reach more than 90%. With these data being served as the positive sample datasets, the physical parameters of the simulatively detected HFGWs can be effectively estimated by matching the sample datasets with the noise-free template library one by one. The confidence levels of these extracted parameters can reach 95% in the corresponding confidence interval. Through the multiple data experiments, the effectiveness and reliability of the proposed data processing method are verified. The proposed method could be generalized to big data processing for the detection of experimental HFGWs in the future.
Improvement of high sensitivity ICR characteristics and its application in OFDR
Authors: Qi Gaohan , Zhang Shengxiang , Feng Shijie , Fu Yanfeng 
Published: April 2024

Abstract
Coherent optical sensing technology faces significant challenges in practical applications due to the extremely weak signal light, necessitating highly sensitive coherent receivers. A high-sensitivity, highly integrated, and low-noise coherent receiver module based on germanium-silicon photonic chips has been developed. A testing system was constructed to assess the performance of the coherent receiver module, revealing a reception sensitivity of -70dBm, with physical dimensions of 33×40×8.6 mm3 and an output noise voltage of ±4mV. Additionally, a distributed sensing system based on optical frequency domain reflectometry (OFDR) was established to verify the module’s application in OFDR systems, achieving a spatial resolution of 1mm.
Research on transmission and crosstalk characteristics of a new type of through silicon via and multilayer through silicon via
Authors: Su Zhiyuan , Wang Weimin , Wu Yongle 
Published: April 2024

Abstract
In this work, a new type of bar-coaxial ring TSV (B-coaxial ring TSV) structure was proposed. This study used three-dimensional electromagnetic simulation software for analysis. Firstly, the conventional Bar-TSV (B-TSV) structure and the B-coaxial ring TSV structure were modeled, and their S-parameter results were compared. Our results indicated that the B-coaxial ring TSV structure had better transmission characteristics and crosstalk resistance. Secondly, by simulating of the B-coaxial ring TSV structure and the coaxial ring-tapered TSV structure, we proposed how to choose different structures for different application scenarios. Thirdly, the influence of some structural parameters of the B-coaxial ring TSV structure on the transmission performance was studied. Finally, the multilayer TSV structures of conventional B-TSV, B-coaxial ring TSV and coaxial ring-tapered TSV were studied respectively, and their performance was compared and analyzed.
Algorithm Selection and Application for Robot Path Planning Problems
Authors: Chen Xiaojiao , Chen Ling , Fu Lantian , Wang Chengliang 
Published: April 2024

Abstract
This article primarily delves into the investigation of robotic path planning in the presence of obstacles, aiming to ascertain optimal traversal routes. It conducts a thorough categorization and discussion of two critical aspects: the ascertainability of the overall map and the regularity of obstacles. In addressing this inquiry, two obstacle scenarios, namely regular and irregular, are posited. The article scrutinizes the path planning and obstacle circumvention techniques for both scenarios. Regarding regular obstacles, a comparative assessment of the A* algorithm, Floyd’s algorithm, and Dijkstra’s algorithm was conducted, culminating in the selection of the A* algorithm for its superior efficiency. For irregular obstacles, the article proposes a pre-processing approach involving the utilization of Matlab’s iterative pixel point traversal to assess obstacle proportions within nodes, subsequently converting irregular obstacles into a regularized format. To summarize, in scenarios with a known overall map, the article advocates employing the A* algorithm for proficient path planning. In situations where the map is undisclosed but obstacles exhibit regularity, the D* algorithm is recommended. For instances involving irregular obstacles and an undisclosed map, a dynamic method for handling newly incorporated nodes into the map is proposed. This article presents tailored solutions for robotic path planning across diverse conditions, offering concise yet effective problem-solving strategies. In conclusion, this study offers a comprehensive array of solutions for robot path planning in obstructed environments, enabling the selection of apt methodologies based on varying conditions and exigencies.
Development of ultra-low emission prediction model for steel enterprises based on ARIMA
Authors: Li Shaoming , Yue Bin , Ye Maosheng 
Published: April 2024

Abstract
The iron and steel industry is an important raw material industry in the country, but also a large air pollutant emission. In the face of the increasing environmental standards and requirements of the country, promoting the implementation of ultra-low emissions in the steel industry, significantly reducing pollutant emissions, promoting continuous improvement of environmental quality[1], and accelerating green low-carbon transformation and high-quality development are the general trend and industry needs. According to the promotion requirements of ultra-low emission work in Baoshan Base, the ultra-low emission application system was developed to meet the ultra-low emission control requirements. Using the ultra-low emission monitoring data of Nanjing Mei shan the parameters p, d and q were first determined, and then the ultra-low emission differential autoregressive moving average (ARIMA) prediction model was established.
Numerical study on fractal characteristic of blast-induced cracks in deep rock mass
Authors: Wang Peiyu , Zhou Zilong , Fan Jiale , Cheng Ruishan , Cai Xin , Chen Cuigang , Jiao Wencan 
Published: April 2024

Abstract
The quantitative representation on the characteristics of blasting-induced cracks in rock mass is of great significance to guide the fine blasting design in practice. However, the quantitative relation between blasting-induced cracks of rock mass and in-situ stresses is currently lacking. To provide the reference for the fine blasting design to excavate rock mass with different in-situ stresses, the present study adopts the fractal theory to quantitatively represent the characteristics of blasting-induced cracks in rock mass. The effects of in-situ stress levels and lateral coefficients on the modes and fractal dimensions of blasting-induced cracks are investigated by numerical simulation combined with image processing. The results show that with the increase of in-situ stresses and lateral coefficients, the fractal dimensions of blast-induced cracks gradually decrease. In addition, quantitative relations between the fractal dimensions of blasting-induced cracks and in-situ stresses are established to provide the reference for the design of rock blasting.
Optimization and Upgrading of Key Technologies for Lead Electrolysis Equipment Sets
Authors: Peng H D , Deng A M , Zong Y J , Xiong J Z 
Published: April 2024

Abstract
In response to the current key issues in the production of existing lead electrolysis equipment, such as poor verticality of lead cathode, inferior welding quality, short service life of conductive rod and high contact resistance, we have developed several technologies based on the principles of elastoplastic mechanics, bending and shaping, resistance spot welding and neural network control.These technologies include the stiffness-enhanced plate surface embossing, the dynamic multi-eigenvalue fusion of BP neural network resistance welding control, and the efficient rod-plate separation for cathode lead plates and conductive rod. They have been applied in a newly constructed 480kt/a project at a large domestic lead smelting enterprise. The results have demonstrated significant improvements in overall equipment production capacity, reducing the production time from 15s/plate to 11.5s/plate, decreasing the short-circuit rate caused by cathode verticality to 0.43%, and extending the service life of conductive rod by 12.8%.
Increasing of the unit capacity of MF process at Miike Smelter
Authors: Kubo H , Nishiyama F , Torikai S 
Published: April 2024

Abstract
MF (Mitsui Furnace) is a half shaft blast furnace developed by Mitsui Miike Smelter in the 1960’s to treat vertical retort residue. Currently MF mainly treats various secondary wastes (EAF dust, Secondary Fly Ash, etc.) and recovers zinc and lead as crude zinc oxide, copper and silver as matte, meanwhile other elements such as FeO, CaO, SiO2, Al2O3 are concentrated in slag.
There are two steps in the MF process. The first step is pretreatment. In this process, various waste materials are blended in a certain proportion with reductant and dried adding binder in a rotary dryer, then grinded in a rod mill. The grinded materials are made into an oval briquette by briquetting machine. The second step is treatment process. The briquettes fed into the MF are smelted and reduced by blowing air through the tuyeres. By enriching the tuyere air with oxygen generated by the VSA (Vacuum Swing Adsorption) oxygen generator in 2005 and 2012, we have improved the throughput of wastes.
By the improvement of oxygen enrichment in the MF, the unit capacity increased significantly. However shortage of the drying capacity in the pretreatment process became a problem. To ensure sufficient drying capacity, we installed one more rotary drier in series in 2016. Additionally in 2018, we installed a granulator after the rod mill to improve the bulk density in briquette. As a result of these efforts, the treatment amount in the whole MF process has increased.
The MF can treat various kinds of materials containing various non-ferrous metal-valuables. Through these process improvements, we promote the treatment of wastes containing heavy metals and contributes significantly to the recycling of metal resources.
Life cycle assessment and product carbon footprint for SHG zinc production
Authors: Grund Sabina C. , Genderen Eric van 
Published: April 2024

Abstract
The industry’s environmental impact has moved into focus at global level. Regulators, supply chains, and the financial sector need credible, standardized, and transparent information for multiple reasons. These include regulatory targets for limiting emissions, downstream user optimizations, and developing science-based emission reduction strategies. By characterizing environmental impacts, companies can satisfy stakeholder demands and measure progress towards goals. In this paper, an introduction to life cycle assessment (LCA) for reporting on environmental impacts, including the product carbon footprint as global warming potential is given. Average results from the most recent global LCA update for special high-grade zinc production are summarized. Resulting carbon footprint information is then used to derive the zinc industry’s baseline carbon footprint as the starting point for the decarbonization roadmap for the global zinc industry.
A Post-processing Computational Fluid Dynamics System for Turbomachinery
Authors: Chen Jiawei , Pan Zihao , Butala Mark David 
Published: April 2024

Abstract
Computational fluid dynamics applied to the turbomachinery domain require specialized post-processing functionality. For computational fluid dynamics turbomachinery, we have developed a lightweight post-processing software. We have developed a system utilizing the Visualization Toolkit (VTK) for rendering and the Qt toolkit as the cross-platform graphical user interface platform. The system is lightweight, which implements the fundamental postprocessing functions such as iso-surface and cut plane visualization and determines the meridional plane and the constant blade/van height plane. We designed and evaluated two different methods to determine the meridional plane and the constant blade/van height plane and used VTK filters in VTK to obtain necessary scene information. Finally, we visualized these planes by using the VTK visualization pipeline.
Design and implementation of firefighting reconnaissance robot control system based on master-slave control
Authors: Jiang Jiayi , Li Jinqiu , Qin Heran , Ran Yixun , Huang Jiajun , Liu Ruiran 
Published: April 2024

Abstract
In response to issues related to casualties and property damage caused by fires, this paper primarily investigates a deformable wheeled firefighting reconnaissance robot with functions such as fire source detection, obstacle avoidance, and map transmission. The control system of the robot is elaborated, with the main motion control system utilizing STM32 technology. Tests were conducted on the robot’s two motion capabilities (wheeled and legged), obstacle avoidance ability, reconnaissance capability, etc. The results indicate compliance with the design requirements.
Intelligent robotic arm for human pose recognition based on teleoperation system
Authors: Li Mingyue , Qiu Xiangya , Zhu Simeng , Sheng Zeyu , Liu Yi , Zhao Yuxuan , Zhao Xin , You Ran , Wang Siyang , Bi Dexue 
Published: April 2024

Abstract
With the rapid development of skeleton recognition, machine learning and other technologies, we will find that there are great drawbacks in the control of manipulators. Robot teleoperation refers to the inclusion of human operation in the control loop of robot control. When robots deal with complex perception and a large number of tasks, teleoperation is far superior to intelligent programming when making decisions quickly and dealing with extreme situations. The goal of this paper is to build a robotic arm teleoperation system for human motion capture, so as to solve the problems that the control accuracy of the end of the robotic arm is not high and the motion of the robotic arm is greatly affected by the difference between the human arm in the current related research, the master-slave human motion mapping algorithm is designed and extended with machine learning algorithms. We use inertial motion capture to realize teleoperation, so as to avoid the use of the terminal position and orientation control method of the hand controller to form the control command of the remote robot after tedious calculation, and it is convenient for the operator to complete the attitude tracking task in real time. The obtained attitude information has a larger range, higher sensitivity and better dynamic performance.
Application of K-Core analysis based on complex network community structure to rolling bearing fault diagnosis
Authors: Sun Ming , Cai Xin , Gao Bingpeng , Zhang Yongxing 
Published: April 2024

AbstractA complex network is a method to analyze nonlinear time series on multiple temporal and spatial scales. K-core analysis of several typical nonlinear series was studied, and then based on this, a fast algorithm method was employed to divide the community structure. According to the definition of k-core, the rolling bearings complex network was divided into different cores at the router level, and the main characteristic quantities such as degree distribution and clustering coefficient of every k-core can be analyzed. The results show that there is a corresponding relationship between the characteristic parameters and the community structure of the bearing. The analysis results show that compared with the traditional method, the method of complex network community structure and k-core analysis has a better diagnosis effect.
Research on brake torque design of civil aircraft
Authors: Lu Weiming , Wang Ziyang 
Published: April 2024

Abstract
Brake torque is one of the key parameters of aircraft brake system design. When braking, hydraulic oil enters the brake actuator assembly, the piston on the brake actuator is extended under the action of liquid pressure, the rotor and static brake discs are pressed together, and the friction between the brake discs forms the brake torque. The design of brake torque is too small, which will increase the deceleration distance of the aircraft and can not meet the requirements of the aircraft design field. Excessive brake torque will make the aircraft pause and transition during braking, make passengers feel uncomfortable, and make the aircraft carry unnecessary weight. Generally, the combined torque between the tire and the runway during the RTO or landing stage is called the dynamic brake torque. The torque required to satisfy 25.735 (d)parking brake item in airworthiness CCAR-25-R4 is called the static brake torque. Brake system designers need to calculate the dynamic brake torque and static brake torque requirements, and design brake actuator assembly to meet these requirements.
Design and optimization of high-speed permanent magnet synchronous motors
Authors: Feng Lin , Liu Weibin , Chen Xinwei , Ding Yinshu , Yu Wentao , Li Hongwei 
Published: April 2024

Abstract
In this paper, a 30 kW and 60, 000 r/min high-speed permanent magnet synchronous motor (HSPMSM) was studied. We use the knowledge of motor design to determine the structural dimensions and materials of each part of the machine to create the electromagnetic design of the motor. The FEM model of the motor was created by finite element software, and the no-load and load characteristics for the motor were modeled and analyzed, which verifies the reasonableness of the design of the motor. A genetic algorithm was applied to carry out multi-objective optimization of the motor to obtain the optimized design solution, and the performance of the high-speed motor before and after the optimized design was compared. The simulation results indicate that the rated torque of the motor has been increased through the optimization, while the torque pulsation and the groove torque of the motor have been decreased, which effectively enhances the magnetic characteristic of the designed machine.
Flywheel rotor cross-filter tracking feedback control
Authors: Liu Weibin , Feng Lin , Chen Xinwei , Ding Yinshu , Yu Wentao , Li Hongwei 
Published: April 2024

Abstract
In light of the matter that the fixed-parameter cross-filter circuit cannot satisfy the phase compensation requirement in the full speed range, a cross-feedback tracking control method based on cross-filter feedback, in which the high-pass cutoff frequency varies with the nutation frequency, is proposed. The stability analysis of the designed control method is carried out by using the phase angle margin and the root trajectory diagram, and the results show that the cross-feedback tracking control can increase the phase angle margin and significantly enhance the stability of the system. Simulation results of the magnetic levitation rotor system show that the designed control method possesses the benefits of high stability, rapid response time, and strong anti-jamming ability.