bluuebunny/crossref_metadata_2025_split huggingface dataset:
Numerical simulation of two droplets impacting on the wall continuously
Authors: Liu C C 
Published: October 2022

Abstract
The application of spray system has been widely used in the industry. The impact of droplets between the wall impact has become one of the important studies of spray system. The investigation is to develop a numerical code for the simulation of two water droplets impinging continuously upon the wall. In the code, the structured single-block and staggered grid system are adopted for discretization of the space domain, while the finite volume method is applied to solve iteratively the governing equations of mass and momentum. The interconnection between the velocities and pressure is dealt by SIMPLER methods. In order to capture the boundary of the deformation of droplets, a level set function method is considered due to the advantage of handling the incorporation and breakup of the boundary easily. In the paper, the numerical verification of a water droplet impinged upon the wall are very accurate with the experimental values. Subsequently, a forward droplet with different Reynolds number of 100, 200, 400 and a backward droplet with the fixed Reynolds number of 200 vertically impact the wall continuously. According to the calculation results a forward droplet with smaller the Reynolds number shows the larger the maximum spread distance after merging. In impact process of different angles, the merged droplet moves along the wall, and produces also oscillates back and forth asymmetrically. As for the maximum horizontal spread distance of the merged droplet, the impact angle of 30 degrees is the smallest, and the impact angle of 60 degrees is the largest.
Design and performance analysis of a high-efficiency Y3 induction motor
Authors: Ntawiheba J d’Amour , Qiao L , De Dieu Niyonteze J 
Published: October 2022

Abstract
Induction motors have been applied in industrial domain, agriculture, transportation, national defence industry and other industries because of their advantages of simple structure, small inertia, low cost and long time working at high speed and high temperature. In this paper, particle swarm optimization algorithm (PSO) is applied to the optimal design of Y3 series asynchronous motors to achieve the highest efficiency. Secondly, the RMxprt module of Ansoft was used to design a Y3 high-efficiency induction motor with a certain power level using particle swarm optimization (PSO). Maxwell module was used to carry out finite element analysis to calculate the magnetic density and flux distribution of stator and rotor. The simulation results of stator current, flux, induction voltage and transient torque show that the performance indexes of Y3 induction motor designed in this paper meet the design requirements which verify the rationality of the design.
Research on optimization of cutting force in AISI D2 hardened steel ultrasonic vibration-assisted turning
Authors: Huang W T , Wu Z X 
Published: October 2022

Abstract
This study utilized the self-developed ultrasonic vibration-assisted turning system to conduct turning experiments on AISI D2 hardened steel. The investigation is carried out by the Robust Design method via controlling different ultrasonic vibration-assisted turning factors and levels, including feed rate, spindle speed, depth of cut, and the magnitude of amplitude of the ultrasonic vibration tool tip. This study is carried out with optimal cutting force by the Robust Design goals. The optimal combination is A1 (0.5 mm depth of cut) B1 (0.08 mm/rev feed rate) C3 (20 μm amplitude) D2 (885 rpm spindle speed). The cutting force is 119.85 N which hugely decreased 28.6% by comparing with the lowest group. Through analysis of variance, the depth of cut and feed rate play a dominant role in cutting force. These two factors are used for obtaining the difference of cutting force and tool wear by comparing the two factors at different levels. The experimental results show that the optimal depth of cut and feed rate can be reduced by 15.8% and 28.4% in cutting force, and 72% and 81% in tool wear compared with other levels. When turning AISI D2 hardened steel, ultrasonic vibration-assisted turning systems can greatly improve the turning efficiency.
Preforming strategies in correcting the spring-back from the U-shape bending
Authors: Lin H S , Lin H W 
Published: October 2022

Abstract
Bending accuracy is difficult to predict in multiple profile-rolling because of the complexity in the distribution of the residual stress. The adjustment of the individual rolls is usually time-consuming. Therefore, coining and embossing processes can be implemented as the preforming measures to correct the spring-back or spring-forward defect. In this work, U-shape bending preformed with coining and embossing was investigated for the validity of the correction of the bending accuracy. Both hot-dip galvanized steel SGC 340 and aluminium alloy AA 6016 plates, with a thickness of 1 mm, were tested. Preforming with coining or embossing was conducted on the inner or the outer corner of the plates. Both the FE simulation and experiment were carried out. The result shows that preforming with coining on the inner or outer corners can increase the amount of spring-back. Preforming with embossing on the inner corner can also increase the amount of spring-back. However, the amount of spring-back reduces or even spring-forward occurs in preforming with embossing on the outer corner. Attributed to the distribution of residual stress is discrete after U-shape bending, a steady trend of the correction for spring-back was not observed.
Optimization of milling parameters based on five-axis machining for centrifugal impeller with titanium alloy
Authors: Chen T H , Lee J N , Tsai M H , Shie M J , Lin C Y 
Published: October 2022

Abstract
The centrifugal impeller is the core component of a turbojet engine. Due to its complex geometry, it is difficult to generate machining paths. Moreover, a lot of material is removed between the blades during the manufacturing process. This study investigates the optimization parameters of a titanium alloy centrifugal impeller for five-axis milling. Rough grooving toolpaths are obtained using Siemens NX software, and the NC program is obtained after post-processing conversion. VERICUT can perform cutting simulations to determine whether there is an interference or collision. During the initial cutting parameter experiment, a sensory tool holder is used to measure the tool bending moment during milling. After milling, a 3D digital microscope is used to observe the flank and face of the cutter to analyze the cutting bending moment and tool wear. Finally, the optimal cutting parameters are determined through a full-factor experiment, and the tool life parameters are verified. According to the cutting parameter experiment, the cutting depth is 1 mm, the cutting speed and feed rate is the same, and the maximum bending moment increases proportionally with depth. In addition, a tool life experiment is performed using the optimal cutting parameters: cutting speed of 50 m/min, feed rate of 250 mm/min, and cutting depth of 2 mm. The maximum cutting moment is below the wear limit of 27 Nm. The tool could cut seven grooves, and the machining time is 41 min 46 s.
Intelligent music accompaniment system based on discrete wavelet transform
Authors: Zhang Y T , Cheng Y L , Wu H X , Liao Y P 
Published: October 2022

Abstract
Instrument players usually play music with an unstable tempo. However, most of the robotic accompaniment systems are designed with a fixed beat. They can’t adjust their tempo to players’ tempo automatically. Therefore, we propose an adaptive accompaniment system for a soloist that can follow the tempo of a guitar player. The system includes a sound signal receiving element, an audio processing module, a robotic drumming system, and an information display device. The guitar signal is processed with the discrete wavelet transform, audio feature extraction, and peak detection to estimate the tempo of a piece of music, also known as the Beats Per Minute (BPM). In this research, the Daubechies Wavelet (db) is used for signal extraction and reconstruction. The experimental results validate wavelet five (db5) was the effective signal processing method. At the same time, the pedals are also designed to allow the guitarist to change the combination of bass drum and snare drum according to the performance needs. In the research, the guitar signal can be efficiently processed by Discrete Wavelet Transform and then control the drum to follow the guitarist’s tempo.
Study on the application of a granite composite material in five-axis CNC-VMC machine Tool
Authors: Chuang H C , Chen C R 
Published: October 2022

Abstract
A five-axis CNC-VMC machine tool generally has a high-speed spindle spinning at a maximum rotation of 50,000 rpm, under which the machine tool bed will violently vibrate that leads to poor machining precision and surface quality of workpiece. The gray cast iron, as the typical material of a machine tool, exhibits poor dynamic suppression of vibration that its processing yield and quality can no longer satisfy the product demand of current market. Consequently, in this study, we proposed granite composite material (GCM) in place of gray cast iron for the structure of machine tool, which would be mixed with main ingredients of high-strength epoxy resin and cemented carbon fibers and fillers to maximize the structural properties of the machine tool. The sample of granite composite material would first be tested for its mechanical properties. The results showed that the GCM cast with only 1/3 density of gray cast iron could withstand a maximum compressive stress of 125.8 MPa. With this granite composite material used in a digitally controlled machine tool bed, the maximum stress and the maximum strain exerted on the machine tool were reduced by 68.93% and 72.6%, respectively, when compared with the cast iron, while the 1st to the 6th-order natural frequencies of the machine tool of mineral composite was significantly increased by 20% to 30%, giving it more resistance to vibration than the gray cast iron. The stability and precision of the machine tool were shown to have been drastically improved by using the granite composite material.
Study on significant factors of stable dynamic stiffness and advanced assembly for precision fastening system by Taguchi method
Authors: Chen C M , Chang H L , Yulianto H 
Published: October 2022

Abstract
Precision assembly fastening is an indispensable part of technology. The clamping force of the precision fastening system maybe remain Table or decrease when the assembly is subjected to axial vibration. In the meantime, rotating for a long time at a very high speed will produce a very high temperature. When the temperature rises, it will greatly reduce the overall performance and accuracy of the precision fasten system. With the background of this problem, this research was started. In this study, experiments were carried out with a rotation dynamic percussion testing machine, and the Taguchi method was used to discuss the assembly of the precision fasten system with different parameters and conditions. The experimental control factors are the fitting clearance, bearing contact angles, and the viscosity of the lubricating oil. After getting the test value, the next step is a statistical analysis using the Taguchi method in stages to get the final optimal results of the experiment. The results showed that the bearing contact angle and the viscosity of the lubricating oil are important factors affecting the temperature rise of the bearing. The results of this experiment can be applied as a basis for assembling machine tools for the advanced manufacturing industry, aircraft industry, automotive light vehicles to heavy vehicles in the mining world, etc. This also aims to improve the accuracy and stability of the precision fastening system.
Research and design of flow standard device for field service master meter method
Authors: Li Bin , Zhuo Haoran , Chen Jie , Wang Tao 
Published: October 2022

Abstract
Most of the traditional flow standard devices are fixed, with very large volumes. When the enterprise has the measurement demand, the client needs to remove all the flowmeters and send them to the location of the standard device, take them back after testing and reinstall them on the production line, resulting in low production efficiency. However, while pursuing the mobility of the device, the overall space, weight, and layout of the device are bound to be limited, thus affecting the stability of the water source and measurement accuracy. Therefore, this paper analyzes the characteristics of mobile devices, in the pursuit of lightweight at the same time design and building water source loop, branch, the overall electrical system, and write the host computer calibration software, and finally through the automatic adjustment of the solenoid valve with PID control scheme to adjust the flow, to improve the stability of water sources.
Research on Diesel Engine Speed Control Based on BPNN Self-tuning PID Controller
Authors: Li Xuemin , Zhu Cunxi , Zhang Qihang , Gu Ziyang , Shu Haoyu , Zhang Jingjing , Liu Mingyao , Zheng Chengjie , Han Yuting 
Published: October 2022

Abstract
As a more efficient power machine, diesel engine is widely used in industry, large vehicles, ships, power generation and other industries. Because of its high thermal efficiency, low fuel consumption, strong power and long service life, diesel engine will continue to occupy a leading position in its application field in the coming decades. Therefore, the speed control of diesel engine has always been a hot research topic. However, there are some disadvantages if only using PID controller for diesel engine speed control. This paper studies the structure of diesel engine speed control and the form of neural network. The combination of BPNN (Back Propagation Neural Network) and PID control makes it adjust the PID parameters in real time according to the speed error and achieve the tracking of actual speed and ideal speed. The realization of this method solves the problem of difficult PID parameters selection to a certain extent. And it has the characteristic of automatically adjusting parameters under variable working conditions. So that the engine can still maintain the desired speed under variable working conditions.
Thread Wire Head Size Detection System Based on ZYNQ
Authors: He Zongfeng , Ma Xiaocheng , Zhang Kai , Xiao Jian 
Published: October 2022

Abstract
Aiming at the problems of slow detection speed and low integration of machine vision threaded wire head, this paper designs a threaded wire head size detection system on the ZYNQ (FPGA+ARM) platform based on the idea of software and hardware collaborative design. First, the functions of image data acquisition, image preprocessing and edge detection are realized on the FPGA side; then the processed data is transferred to the ARM side through VDMA, and the current frame image in the DDR is intercepted by external triggering; finally, the PS side is designed Feature point screening and size calculation algorithms. The experimental results show that the parameter measurement error of this system is small, and it can meet the task requirements of the size detection of the threaded steel wire head.
Research of ship cooling system outlet temperature prediction based on CEEMD-ARIMA-LSTM model
Authors: Liu S , Sang W , Cao H , Ai Z 
Published: October 2022

Abstract
In order to further optimize the predict of the ship cooling system working state and prolong the working life of the system. The CEEMD-ARIMA-LSTM prediction model is used to predict the working state. Through the complementary integrated empirical mode filtering process the fresh water outlet temperature data is divided into the data that can be used for prediction and environmental noise, then predicted by the long and short period neural network (LSTM) and differential sliding autoregressive time series (ARIMA). The result shows that the data predicted by neural network and time series are stable, and the error is more than 50% less than the original method. It lays a foundation for better diagnosis the fault of ship cooling system.
RGB photoelastic method based on gradient-square inversion correction
Authors: Wang Ziwei , Lei Zhenkun , Zhao Honghua 
Published: October 2022

Abstract
Automatic photoelastic method focuses on the recognition of stress field. RGB photoelastic method has the advantages of low condition requirements and accurate low-level fringe recognition, but it is easy to be disturbed by image noise, color repetition and other factors, resulting in recognition errors. In this study, the combination of gradient-square inversion and RGB photoelastic technology can not only effectively eliminate the error points introduced by color repetition, but also greatly reduce the scope of look-up table, shorten the calculation time and quickly analyze the stress field. The effectiveness of the proposed RGB photoelastic method based on gradient-square inversion correction is verified by photoelastic experiments.
Lane Detection Using Q-net Model
Authors: Zheng Qinyuan , Shi Yingjie , Zhao Naidong , Wang Ziling , Li Hongbiao 
Published: October 2022

AbstractWith the development of the automobile industry and artificial intelligence, exploring more practical and efficient lane line detection methods has a significant role in advanced driver assistance. Lane detection applies for environmental perception, to detect lane areas or lane lines by different types of equipment. In this paper, we propose a Q-net model for lane detection. In Q-net, we propose a backbone network named QCNN for feature extracting and adopt a classification layer for post-processing. Besides, we propose the JSSR method for predicting the lane line position with high accuracy and acceptable speed. We conduct comprehensive experiments on Q-net, and the experiment results show that (1) Q-net is robust to various road environments, ranging from curves and obstacles; (2) Q-net can provide real-time lane detection, with 96.9% accuracy and 68.7 fps.
Study on a Real-time Work Assistance Method for Substation Based on Petri Net Model
Authors: Gao Qi , Jin Wei , Chen Zhao , Zhang Xun , Liu Lu , Lin Chunlong 
Published: October 2022

Abstract
Work assistance is one of the important means to improve work efficiency. This paper focuses on substation work and proposes a real-time work assistance method based on petri net model. The work assistance includes two aspects, termed as, workflow guidance and operation prompt. Particularly, the workflow constructed by the petri net includes sequence, inhibition, concurrency and conflict structures to declare the correlations between work steps. Further, different forms of operation prompts at each step are designed, considering real-time responses of workers including skip, replay, pause and restart. The effectiveness of the method is well validated by an application of the work assistance on measuring the grounding current of transformer core and clamp. It is demonstrated that the unified assistance method built by the petri net successfully instructs standardized working process, helps avoid potential risks, and provides flexible operation prompts in real time.
Reconfigurable Stochastic neurons for Restricted Boltzmann Machine
Authors: Wang Yuanxi , Xu Fufang , Wang Jie , Cui Xutai , Yi Teng 
Published: October 2022

Abstract
Neuromorphic implementation of Boltzmann Machine using a network of stochastic neurons can allow non-deterministic polynomial-time (NP) hard combinatorial optimization problems to be efficiently solved. Efficient implementation of such Boltzmann Machine with simulated annealing desires the statistical parameters of the stochastic neurons to be dynamically tunable, however, there has been limited research on stochastic semiconductor devices with controllable statistical distributions. Here, we demonstrate a fully digitized stochastic neurons based on reconfigurable stochastic model that can realize tunable stochastic dynamics in its output sampling characteristics. We emulate the Restricted Boltzmann Machine based on reconfigurable stochastic neurons and leverage the handwritten digits from the MNIST dataset to validate its recognition capabilities and investigate the accuracy of several distinct network parameters.
A new collaborative fault identification strategy using multivariate hierarchical dispersion entropy
Authors: Yang Cheng , Jia Minping , Li Zhinong , Gabbouj Moncef 
Published: October 2022

Abstract
This article presents a fault recognition strategy using multivariate hierarchical dispersion entropy to monitor the conditions of rolling bearing. First, the vibration data would be measured from multi-channel sensors synchronously. Then, the proposed mvHDE is employed to capture fault information from the collected data. Finally, the fault features are input into the ELM classifier to automatically identify fault types of bearing. The feasibility and effectiveness of the presented intelligent fault diagnosis schemes are verified through experimental studies.
Vehicle position prediction systems and performance equalization
Authors: Cui PengHui , Liu Peng , Qian Xinghua 
Published: October 2022

Abstract
This article will first solve the problem of beam prediction for the link between the vehicle and the communication awareness integrated system. The dual-function communication perception integrated signal emitted by the roadside module (RSM) is used for beam tracking. At the same time, the position parameters of the vehicle are estimated through the reflected echo signal. Based on the above estimation, we put forward a method to forecast the location of the cars. After adding the equalization parameter, it determines the weight of the perception and communication performance in the communication perception integrated system. By equalizing the communication signal power and the radar detection power, the system can maintain high detection accuracy while ensuring better communication power. Finally, the effectiveness of the method is verified by simulation experiments, and the experimental results show that this method is better than the traditional scheme in terms of achievable communication rate.
A novel maximum power point tracking technique with improved particle swarm optimization for proton exchange membrane fuel cell
Authors: Zhou C , Liu Z Y , Sun Y N , Mao L 
Published: October 2022

AbstractThe performance of proton exchange membrane fuel cell (PEMFC) can be significantly affected by its operating conditions, i.e. the temperature, membrane water content. Aimed at maximizing the performance of PEMFC, maximum power point tracking (MPPT) technology plays an important role in PEMFC system. Most traditional MPPT algorithms will generate steady-state oscillations, which result in power loss and damage to PEMFC. In addition, most MPPT controllers based on intelligent algorithms need to use PID to track the MPP, which increases the complexity of the controller and makes the tracking result strongly depend on the PID gain. To overcome steady-state oscillation and reduce the complexity of the MPPT controller, a MPPT controller based adaptive particle swarm optimization algorithm (APSO) without a PID controller is developed in this paper. The performance of the presented algorithm is investigated under three cases including stable operating condition, temperature change and membrane water content variation, and compared with traditional particle swarm optimization algorithm (PSO) and perturbation and observation (P&O) method. The obtained results indicate that APSO has faster tracking speed and smaller search oscillation than PSO, and has better stability than P&O. Moreover, the results demonstrate that by using duty cycle as decision variable, simple design of MPPT control system can be obtained, which shows great superiority over PID controller. This not only enables real-time online tracking, but also reduces hardware manufacturing costs.