bluuebunny/crossref_metadata_2025 huggingface dataset:
Quantum exploration of high-dimensional canyon landscapes
Authors: Urbani Pierfrancesco
Published: August 2024

Canyon landscapes in high dimension can be described as manifolds of small, but extensive dimension, immersed in a higher dimensional ambient space and characterized by a zero potential energy on the manifold. Here we consider the problem of a quantum particle exploring a prototype of a high-dimensional random canyon landscape. We characterize the thermal partitionfunction and show that around the point where the classical phase space has a satisfiability transition so that zero potential energy canyons disappear, moderate quantum fluctuations have a deleterious effect: they induce glassy phasesat temperature where classical thermal fluctuations alone would thermalize the system. Surprisingly we show that even when, classically, diffusion is expected to be unbounded in space, the interplay between quantum fluctuations and the randomness of the canyon landscape conspire to have a confining effect.
Dynamic fluctuations of current and mass in nonequilibrium mass transport processes
Authors: Hazra Animesh , Mukherjee Anirban , Pradhan Punyabrata
Published: August 2024

We study steady-state dynamic fluctuations of current and mass in several variants of random average processes on a ring of L sites. These processes violate detailed balance in the bulk and have nontrivial spatial structures: their steady states are not described by the Boltzmann–Gibbs distribution and can have nonzero spatial correlations. Using a microscopic approach, we exactly calculate the second cumulants, or the variance,

⟨

Q

i
2

(
T
)

⟩
c

and

⟨

Q

sub

2

(
l
,
T
)

⟩
c

, of cumulative (time-integrated) currents up to time T across the ith bond and across a subsystem of size l (summed over bonds in the subsystem), respectively. We also calculate the (two-point) dynamic correlation function of the subsystem mass. In particular, we show that, for large

L
≫
1

, the second cumulant

⟨

Q

i
2

(
T
)

⟩
c

of the cumulative current up to time T across the ith bond grows linearly as

⟨

Q

i
2

⟩
c

∼
T

for initial times

T
∼

O

(
1
)

, subdiffusively as

⟨

Q
i
2

⟩
c

∼

T

1

/

2

for intermediate times

1
≪
T
≪

L
2

, and then again linearly as

⟨

Q

i
2

⟩
c

∼
T

for long times

T
≫

L
2

. The scaled cumulant

lim

l
→
∞
,
T
→
∞

⟨

Q

sub

2

(
l
,
T
)

⟩
c

/

2
l
T

of current across the subsystem of size l and up to time T converges to the density-dependent particle mobility

χ
(
ρ
)

when the large subsystem-size limit is taken first, followed by the large-time limit; when the limits are reversed, it simply vanishes. Remarkably, regardless of the dynamical rules, the scaled current cumulant

D
⟨

Q

i
2

(
T
)

⟩
c

/

2
χ
L
≡

W

(
y
)

as a function of scaled time

y
=
D
T

/

L
2

can be expressed in terms of a universal scaling function

W

(
y
)

, where D is the bulk-diffusion coefficient; interestingly, the intermediate-time subdiffusive and long-time diffusive growths can be connected through a single scaling function

W

(
y
)

. The power spectra for current and mass are also exactly characterized by the respective scaling functions. Furthermore, we provide a microscopic derivation of equilibrium-like Green–Kubo and Einstein relations that connect the steady-state current fluctuations to an ‘operational’ mobility (i.e. the response to an external force field) and mass fluctuation, respectively.
Manufacturing and testing of pliers to weld 3D printing filaments
Authors: Török J , Kočiško M , Pollák M , Vandžura R
Published: August 2024

The advent of affordable three-dimensional printers has unlocked new possibilities for small business owners and hobbyists to convert their digital designs into tangible objects. However, during the production process, a lot of material ends up as waste because of improper storage or unused plastic fibers. This paper discusses the existing market products that aim to tackle these issues. Additionally, we introduce a specially designed pair of welding tongs that make it effortless to join plastic fibers utilized in fused deposition modeling printers. The paper presents a prototype of the tongs and provides a summary of the optimal welding temperatures for different printing materials. Finally, the conclusion evaluates the strength of the fibers after the welding process based on the results obtained from a testing mechanism.
Study on the morphology and mechanical properties of dissimilar Al/Al-Li alloy T-joints by friction stir welding
Authors: Zuo D Q , Han Y J , Fu H R , Jin S Q , Ye T , Fu Y M
Published: August 2024

Friction stir welding is an emerging solid-state joining technology. With the advantages of small post-weld deformation and high connection performance, it is widely used in the aerospace field. In this paper, the FSW welding process of 7055-T61 Al and 2197-T8 Al-Li dissimilar T-shaped stiffened panel was investigated. The purpose of this paper is to analyze the influence of tool shoulder structure and welding parameters on the morphology and mechanical properties of T-joints. It is found that compared with the shoulder inner concave surface without spiral, the weld defects of shoulder inner concave surface with spiral are less. When the welding speed v is 60 mm/min, the rotation speed w is 350 r/min and the plunge depth h is 0.21 mm, the transverse tensile strength of T-joint is 408 MPa, which reaches respectively 68.0% and 71.6% of the base materials 7055-T61 and 2197-T8. It shows that the welding quality of T-joints is better when it is implemented under the optimal combination of welding process parameters.
Investigation of anti-windup Proportional-Integral controller with semi-decoupled tuning gains in motor speed control
Authors: Lai Chun Haw , Hoo Choon Lih
Published: August 2024

Integral windup refers to a prevalent phenomenon that can occur in Proportional-Integral-Derivative (PID) control systems that employ integral control where the control output generated exceeds the operating limit of an actuator. Despite the system’s inability to respond further due to control output limitations, the integral controller perseveres in accumulating errors. The accumulation of error can lead to system instability and undesirable oscillations. Additionally, the dynamic response of the PID controller is also limited by the coupled tuning gain characteristics, complicating the process of gain tuning. The coupling and decoupling of the tuning gains are depending on the separation of the gains in the error dynamics of the system. In this study, a concept of semi-decoupled tuning gains in anti-windup controllers is proposed. The performance of the proposed controller was investigated through hardware simulation against conventional PI and existing anti-windup schemes and has demonstrated an overall improvement in its dynamic behaviour such as faster settling time and its ability to tune the system without significantly altering its damping ratio.
Numerical investigation on the performance of combinational spike and transpiration cooling concept for nose cone under hypersonic conditions
Authors: Lei J M , Guo J , Zhang L Y , Sun G Y , Zhang Y G
Published: August 2024

Aiming at solving the thermal protection problems of the nose cone for hypersonic vehicles, a novel combinational spike and transpiration cooling concept is proposed in this paper. Although the temperature of the nose cone structure can be effectively reduced by traditional transpiration cooling, the cooling effect is not ideal due to the extremely high heat flux and pressure near the stagnation point. In the combinational configuration, the bow shock wave at the leading edge of the nose cone is pushed away by the spike, so that the pressure and heat flux along the nose cone surface are reduced obviously, and the cooling effect is also improved significantly. The flow field generated by this innovative concept has been thoroughly examined through numerical simulations employing the compressible Reynolds-Averaged Navier-Stokes (RANS) equations in conjunction with the shear stress transport (SST) k-ω turbulence model. The fluid-thermal interaction is considered by using the conjugate heat transfer approach. The performance of three configurations based on the nose cone are numerically investigated, including transpiration cooling, spike, combinational spike and transpiration cooling. The numerical results show that, compared with the traditional transpiration cooling, the temperature at the stagnation point of the nose cone for the combinational configuration is reduced by about 64%, which proves the feasibility and high efficiency of the novel combinational concept. With the increase of coolant mass flow, the temperature along the nose cone surface for combinational configuration decreases, while the magnitude of the temperature reduction decreases. Therefore, under certain incoming flow conditions, the appropriate coolant mass flow should be considered to achieve better thermal protection effect.
Quantitative Analysis of the Hsu-Nielsen Source through Advanced Measurement and Simulation Techniques
Authors: Abolle-Okoyeagu C J , Fatukasi Oluseyi , Droubi Ghazi , Reuben R L
Published: August 2024

This paper presents the results from conducting a series of experiments with a Hsu-Nielsen Source, accompanied by corresponding numerical simulations on a solid block. The aim being to illustrate a Finite Element Analysis (FEA) approach for simulating Acoustic Emission (AE) wave propagation in a Hsu-Nielsen Source, by employing virtual sensors to enhance existing AE research methodologies. The objective was to examine and establish the actual unload rate derived from Pencil Lead Breaks (PLBs) by comparing results from simulations and experimental trials. These experiments and simulations were conducted using a solid cylindrical steel block, capturing the propagating Acoustic AE waves from both sources over a two-second span. When comparing the experimental data with the simulation results, it is evident that replicating the structure of an impulsive AE source is feasible for brief durations. Furthermore, both the experimental and simulated signals on the steel cylinder displayed comparable patterns in the initial 25-30 µs. The methodology presented in this study demonstrates the effectiveness of Finite Element Analysis (FEA) in precisely identifying the specific modes present in AE wave propagation, including the actual unload rates affecting the AE signals recorded.
Development of a novel PCB electric field sensor with high-resolution
Authors: Li Jinyang , Lai Yi-Horng , Qu Lijie
Published: August 2024

Electric field sensors with high resolution and high sensitivity have an important engineering application. Developing a compact, cost-effective Electric Field Sensor (EFS) for aerospace applications, this study introduces a novel use of PCB parallel board probes, enhancing affordability and simplicity. A uniquely designed three-stage adaptive signal amplification module quickly adjusts amplification factors, ensuring high sensitivity and resolution even in complex electric field environments. Due to the non-linear response characteristics of the PCB probes in complex electric field environments, the GTEM cells and the high voltage parallel plate method are used to simulate the complex electric field scenarios. In the weak electric field experiment, the proposed EFS achieved a high resolution of 10 mV/m. In the strong electric field experiment, the linearity of fitting between the proposed EFS and commercial NBM-550EFS reached 0.9999. Finally, based on RBFNN, the overall measurement model of EFS achieves the dynamic measurement range of 0-1 kV/m.
Characterization of underwater manipulator based on the fluid-structure interaction under pulsating flow
Authors: Li Yongqi , Liu Xia , Duan Derong
Published: August 2024

Underwater manipulators are taking on an increasingly significant function in marine biological fishing operations. Under the action of the ocean flow field, vortex-induced vibration will be induced, which will cause fatigue damage or even fracture of the underwater manipulator. Based on the Ansys fluid-solid coupling software, this paper simulates the vortex-induced vibration response characterizations of underwater manipulators under pulsating flow conditions. The pulsation flow at the entrance is realized by changing the velocity amplitude and pulsation frequency. The influence laws of pulsating frequency and amplitude on the CL
, CD,
and wake vortex shedding are investigated. The results showed that the CL
and CD
of the underwater manipulator increased by 133.33 % and 39.18 %, respectively, with an increase in the pulsation parameter. Additionally, with the increase of pulsating frequency, the banded vortex behind the underwater manipulator is gradually obvious, and the energy in the vortex is also increasing.
Modeling and motion simulation study of a three-dimensional sewing device
Authors: Xu Shaohua , Xin Daxin , Yang Ming , Zhang Ying
Published: August 2024

In response to the sewing demands of steering wheels and their unique shapes, a multi-robot arm cooperative three-dimensional sewing device was designed to achieve efficient and precise sewing operations. Utilizing SolidWorks, a collaborative three-dimensional sewing device involving multiple robotic arms was engineered, and its mechanism model was established in ADAMS software for motion simulation analysis to evaluate the device’s performance and motion characteristics. This three-dimensional sewing device is capable of fulfilling the sewing requirements of special curved surface items such as steering wheels, enhancing production efficiency and saving labor. Taking the constructed physical prototype as the research subject, motion experiments simulating the sewing process were conducted. Combined with the simulation results, curves, and three-dimensional motion effects, the feasibility of the design was successfully verified, providing a foundation for subsequent sewing trajectory planning and motion control of the device.
Lightweight design and additive manufacturing of one-piece rotating arm axle box for high-speed locomotives
Authors: Zhao Fuyuan , Wang Xinlin , Guan Tianmin
Published: August 2024

Against the background of the continuous increase in the operating speed of the rolling stock, the working environment of the axlebox is becoming more and more severe. To meet the increasing operational demand, the strength and quality requirements of the axle box are also increased accordingly. To realize lightweight design to ensure structural strength, the traditional casting process has the problems of low densities of molded parts, long processing cycles, etc. In contrast, the laser selective melting technology can mold the workpiece with excellent mechanical properties and realize complex structures, effectively solving the above problems. In this paper, the one-piece rotary arm axle box is selected as the research object, its extraordinary load conditions are calculated, and the feasibility of the SLM axle box is verified by hydrostatic simulation. On this basis, the topology optimization design of the axle box is further optimized, and the optimized structural strength and vibration performance are verified by static and modal simulation. SLM technology is used to print components that are ten times smaller in size, and based on the compression experiments, it is verified that its strength meets the design requirements after printing, and the mass of the optimized components is reduced by about 15.4%.
Research on thermal characteristics of double-nut ball screw
Authors: He Pingping
Published: August 2024

Preload, external load, and feed speed have significant effects on thermal characteristics of ball screws. In this paper, ground on friction heat generation theory and Hertz contact theory, a thermodynamic modeling of the double-nut ball screw is established, heat generation under different preload forces and feed speeds is analyzed, and temperature field is estimated based on finite difference method. The results show that preload and feed speed have a obvious impact on screw nuts temperature. The finite difference method makes numerical calculation of temperature field more convenient.
Integrated torque sensors for humanoid robot joints
Authors: Zhao Hongwang , Bo Lin , Peng Changyan , Gu Weikai , Wang Peng , Chen Bingkui
Published: August 2024

Torque sensors are becoming increasingly important in the joints of humanoid robots, serving as an indispensable part of the joint system. This paper designs a strain-based torque sensor integrated into the output flange of a cycloidal reducer. Through mechanical analysis, the relationship between strain and torque is derived. Then, through model simulation analysis, the optimal placement for the strain gauge is determined. A combination of experimental design and response surface analysis is used to optimize the structure’s parameters. Finally, finite element simulation is conducted using ANSYS to obtain the optimized performance parameters. Subsequent steps include the static calibration of the integrated sensor. Based on the measured data points, a linear relationship between the sensor’s output signal and torque is established.
Study on ballast test of underwater pile gripper
Authors: Zhang Dawei , Chen Jinyu , Zhang Meng , Yin Yongqiang , Zhao Xiaolei
Published: August 2024

The underwater pile gripper plays an important role in the installation of the offshore jacket platform. With the further development of offshore oil, it is gradually moving into deep water. Therefore, people pay more attention to the reliability test of pile grippers. The Gripper of underwater pile gripper is the key component of the supporting pipe pile, which determines the quality of the underwater pile gripper to a great extent. Two sets of underwater pile grippers are made of imported and domestic materials, respectively. The maximum loading capacity is 600 tons. The pile gripper is clamped on the test steel pile, and the load is applied by the hydraulic ballast machine. After the experiment is completed, whether the scratch of the tooth mark of the gripper exceeds the expected amount is detected, so as to prove the clamping performance of the pile gripper. The results show that all the components of the pile gripper are not damaged, the hydraulic components are not leaking, the teeth of the imported material gripper and the domestic material gripper are all intact after testing, and the maximum width of tooth marks on steel piles of the two kinds of grippers is about 4 mm and 5 mm, respectively, less than the requirement of 10 mm. The pile gripper made in China can meet the requirements of the actual project for the holding performance, and the holding effect is good.
Development and application of pressure transmitter based on IMC chip
Authors: Zhao Kean , Hu Mengjie , Chen Yaoqing
Published: August 2024

This paper proposes a design scheme for an FF bus pressure transmitter with a domestic IMC chip, using an ECS-700 instrumentation control system to apply the pressure transmitter in refining and chemical projects. Through planning and designing, configuration, and debugging, it improves the convenience and accuracy of the instrumentation system operation.
An envelope statistic features and MFO-SVM fusion method for tidal stream turbine blades impact fault diagnosis
Authors: Wu Zhen , Wang Tian-zhen
Published: August 2024

The fault diagnosis of a Tidal Stream Turbine (TST) blade impact fault benefits its stable operation. However, when the stream velocity changes, it is hard to distinguish between different fault severities directly by observing the changes in the signal feature. To address this problem, this paper proposes a blade impact fault diagnosis method based on envelope statistical features and MFO-SVM. The method is divided into two parts. In the first part, the Teager-Kaiser energy operator (TKEO) and sliding window technique are introduced to extract the envelope statistic features of the current signal, and then the local outlier factor (LOF) values of fault sample points are calculated to form a new set of feature samples; in the second part, the fault feature samples are input into the support vector machine (SVM) optimized by moth fame optimization (MFO) for fault diagnosis. The experimental results show that the proposed method is more accurate than traditional fault diagnosis methods.
Current status and application of welding automation technology for bridge steel structure
Authors: Ji Jiaying , Wang Xingxing , Li Junyi , Lv Shuaishuai , Ni Hongjun
Published: August 2024

In bridge construction, welding automation technology has become an indispensable and important technical means for developing related industries. The paper mainly introduces the current status of welding automation technology in bridge steel structures, elaborates on its existing technology from the control of welding deformation, U-frame welding process, robot welding technology, etc., and gives full play to the positive role of advanced steel structure welding automation technology, and forms a good working mode and technical system. The difficulties in welding are analyzed, which plays a role in promoting the development of welding automation technology for bridge steel structures.
Nonlinear adaptive robust control with continuous error reduction mapping
Authors: Mou Zongliang , Xu Lei , Chen Jianhua , Zhong Junbai , He Nachuan , Du Changdu , Chen Jun
Published: August 2024

Achieving high stability and high-precision control by traditional control algorithms is difficult due to the strong nonlinearity, parameter uncertainty, and random disturbance characteristics of electro-hydraulic proportional servo systems. Herein, we developed a nonlinear adaptive control algorithm based on Lyapunov functions. By estimating the parameters and converging their errors, this algorithm solved the parameter adaptation problem. Additionally, based on convergence inference from the nonnegativity of the derivative of Lyapunov functions, the algorithm designed a disturbance mapping through the derived function. The random disturbance was reduced through the mapping, improving the stability of the system under random disturbance. Finally, we carried out continuous derivation and moved the mapping relationship out of the intermediate temporary controller. This reduced the complexity of the calculation during controller design, prevented performance degradation of the error convergence algorithm after complex calculation, and enhanced the robustness of the algorithm. The algorithm was verified through the simulation model established by Simulink and experience. Results showed that the nonlinear adaptive control algorithm demonstrates fast response, high accuracy, and strong anti-interference ability compared with the high-gain robust control algorithm. It realizes the adaptation of unknown parameters and reduces the control error introduced by random disturbance.
Research on calibration method for measurement error of multiple rate carrier energy meter
Authors: Zhang Fating , Li Xi , Li Yan , Zhou Zixiang
Published: August 2024

With the rapid development of smart grid technology, the multi-rate carrier watt-hour meter is an important measurement tool in power systems; its accuracy directly affects economic benefits and energy management efficiency. This paper proposes a calibration method of measurement error for a multi-rate carrier watt-hour meter to improve the measurement accuracy and reliability of the watt-hour meter under changing load conditions. The multi-rate carrier energy data is collected in real-time by high-precision data acquisition equipment to ensure the comprehensiveness and accuracy of the data. Using advanced data analysis technology to extract the amplitude characteristics of abnormal metering data, on this basis, the output deviation of equipment without input signal is eliminated, and the metering error calibration of the electric energy meter is completed. The experimental results show that this method can significantly improve the metering accuracy of multi-rate carrier watt-hour meters under different power consumption conditions and has good adaptability and practical value.
Study of self-actuated time-controlled tower microvalves
Authors: Luo Hui , Ren Cuixue , Li Jingmin
Published: August 2024

Time-controlled microvalves are vital components of microfluidic systems, primarily used to regulate the sequential or precise introduction of reagents. However, existing time-controlled microvalves face certain limitations. For instance, those driven by magneto-thermal mechanisms require additional control elements, and fabricating some 3D time-controlled microvalves can be complex. To address these challenges, a self-driven time-controlled tower microvalve was designed and fabricated. This study investigates how structural parameters of the time-delay unit affect bubble generation and the time-delay effect. Experimental testing confirmed that the delay time of the time-controlled microvalve increases and then decreases with variations in the trapezoidal aspect ratio (a) and the upper and lower width ratios (b). Additionally, the delay time of a single unit extends as the width of the delay unit increases. The optimal parameters for the time-controlled microvalve were determined as follows: W1
=1, 000 μm, W2
=500 μm, and H=800 μm, achieving an overall delay time of 16.7±0.8 s.
FPGA-based cesium optical pump magnetometer data recording system design
Authors: Teng Da , Hei Guoyu , Wu Yang , Chen Min , Zhao Yue
Published: August 2024

A cesium optical pump magnetometer is a kind of magnetic detection instrument commonly used in geophysical and military fields, which has significant advantages such as high sensitivity, insensitivity to attitude change, and no zero drift. Compared with manned aircraft, rotary-wing UAVs have the advantages of flexible takeoff and landing, low cost, and suitability for small measurement areas, so the aeromagnetic system based on the integration of rotary-wing UAV platforms and cesium optical pump magnetometers has a strong practical value. This paper investigates an FPGA-based CS-3 cesium optical pump magnetometer with a high-precision magnetic field data recording system for building a miniaturized aeromagnetic measurement system based on a rotary-wing unmanned aerial vehicle (UAV) platform, and the system achieves a magnetic field measurement accuracy of 3.4 pT.
Optimization and performance verification of track vehicle multi-friction pair liquid-cooled full-disc brake system
Authors: Yang Dianzhao , Li Zhipeng , Qiu Mingxing , Han Lijin , Han Quanfu
Published: August 2024

The brake system is a crucial component for enhancing the reliability and maneuverability potential of tracked armored vehicles, with a particular emphasis on improving braking performance and reliability. This paper proposes a novel multi-friction pair liquid-cooled full-disc brake system by extending the friction pair and introducing a liquid-cooling structure. Simulation and experimental results demonstrate that the proposed solution significantly accelerates the heat dissipation rate of the full-disc brake system compared to its initial version. Moreover, the presented approach increases the maximum average braking torque by 24.7% and reduces the braking time by 15.2% compared to the original version of the brake system.
Design of control system for seawater total alkalinity in-situ analyzer
Authors: Wang Hongfan , Zhang Yingying , Yuan Da , Wu Bingwei , Zeng Jing , Hao Maotong
Published: August 2024

To address the inadequacies of traditional seawater total alkalinity detection methods, which fail to meet the demands for continuous on-site monitoring at sea, a seawater total alkalinity analyzer based on single-point titration and spectrophotometry has been developed. This paper focuses on the design of the analyzer’s system architecture, hardware, and control systems. The instrument adopts a modular design concept and utilizes microfluidic technology for detection, with the STM32 serving as the control core. Through the design of the control system for the detection instrument, accurate in-situ automatic measurement of seawater total alkalinity is achieved. Laboratory testing and analysis demonstrate that the instrument’s measurement relative error is less than 1%, satisfying the accuracy requirements for seawater total alkalinity measurement. This research provides critical monitoring data support for a timely understanding of marine ecological environments and the marine carbon cycle.
A Markov method for a mechanical system reliability assessment using discrete degradation data
Authors: Shen Hang , Nie Zheng , Xia Jie , Wang Qibin
Published: August 2024

A homogenous continuous-time Markov model (HCTMM) has the advantage of high accuracy and is usually used in reliability analysis. However, the transition intensities (rates) between any two states cannot be accurately obtained due to the discrete data obtained from a mechanical system and little expert knowledge. This paper proposes a method in which the transition intensity matrix of an HCTMM can be obtained indirectly using the actual discrete degradation data of a mechanical system. Firstly, the one-step transition probability matrix can be calculated by a hidden Markov model using the discrete degradation data. Secondly, the unit-time transition intensity matrix can be calculated from the one-step transition probability matrix. At last, an HCTMM is established to assess the reliability of a mechanical system based on the unit-time transition intensity matrix. Moreover, considering the maintenance activities cannot restore a mechanical system as a fire-new one, the random transition of a mechanical system after maintenance is expressed by a quasi-renewal process in this paper. Finally, three cases are studied to validate the proposed method.
Optimization of milling parameters based on GA-BP neural network
Authors: Miao Liqin , Liao Chaoneng , Zhang Dashun , Liang Huaidan , Gao Di
Published: August 2024

Since the selection of machining parameters usually relies on the experience of workers or traditional calculation formulas, the traditional prediction method has the disadvantages of a complicated arithmetic process, large prediction deviation, and high consumption cost, making it challenging to meet the increasing demand of production and processing. Therefore, this paper proposes a machining quality prediction model based on the GA-BP neural network. Through experiments, it verifies the data-fitting ability of the prediction model and then takes the prediction model as the optimization objective, culminating in a multi-objective optimization model for process parameters based on the NSGA-II algorithm. Experiments demonstrate that the cutting force and surface roughness obtained by the optimization model are 3.6% and 10.0% lower than those obtained by the empirical parameters, respectively, leading to reductions of 3.6% and 10.6%, which verified the optimization effect of the model.
Comprehensive simulation analysis of wave-induced dynamics and mesh adaptivity on submarine-launched missiles
Authors: Hong Yue , Ju Xiaoqun , Sun Haoyu , Yu Changli , Zhang Xingming
Published: August 2024

Using the ANSYS simulation platform, we constructed a model of the underwater launching environment and submarine-launched vehicle (SLV) motion based on its launching environment and motion characteristics. We conducted numerical simulations using dynamic mesh technology to study the effects of waves on the attitude and pressure distribution of SLV during the launch process and to analyze the changes in its displacement, angle of rotation, force, as well as the perturbation rules of waves on SLV’s attitude during motion. This will provide a theoretical basis for the in-depth study of the impacts of underwater environmental factors on SLV launching.
Multi-task recognition of modulation types and arrival directions of underwater acoustic signals based on convolutional neural networks
Authors: Xu Yangyi , Zhang Youwen
Published: August 2024

Nowadays, underwater acoustic communication reconnaissance technology is of great importance in military, marine science, and resource exploration fields. The fields involve military reconnaissance and intelligence collection, ocean monitoring and security, marine scientific research, and resource exploration. This article mainly focuses on the identification of modulation types and emission angles contained in underwater acoustic signals. Convolutional Neural Networks (CNNs) are used for deep learning to train, validate, and obtain final results on signal data. This network achieves the independent tasks of automatic modulation classification and Direction of Arrival (DOA) estimation of radio signals simultaneously. The model achieves efficient identification and filtering by designing different filter sizes and sizes, as well as different Y-shaped connection structures. It includes one input block and two output blocks, and the two output blocks correspond to the outputs of modulation classification and DOA estimation. At the same time, based on this, the parameters of the network layer are modified to achieve the generalization ability of the neural network. The training and validation data of the network consists of simulation data from underwater acoustic communication emissions and real data from the Songhua Lake experiment in Jilin Province, China, to test the network recognition efficiency.
Online trajectory anomaly detection model based on graph neural networks and variational autoencoder
Authors: Lu Fangbo , Zhang Zhihao , Shui Changsheng
Published: August 2024

To efficiently determine whether an entire trajectory exhibits abnormal behavior, we introduce an online trajectory anomaly detection model known as GeoGNFTOD, which employs graph neural networks for road segment representation, creating a directed graph by mapping trajectories onto the road network. The graph representation is constructed based on the road segments in this directed graph. By utilizing Transformer sequence encoding, the trajectory representation is derived and hierarchical geographic encoding captures the GPS mapping of the original trajectories. Merging these two representations produces the final trajectory representation, serving as input for an LSTM-based variational autoencoder to reconstruct the trajectory representation, facilitating rapid online anomaly detection. Experimental findings on a large-scale taxi trajectory dataset illustrate the superior performance of GeoGNFTOD compared to baseline algorithms.
Research on electromagnetic pulse signal detection method based on intelligent compressed sensing technology
Authors: Wang Yongsheng , Peng Mingbin , Li Hongjie , Dang Yanyang , Zhang Zhengyang , Tan Xiangyu , He Wenzhi , Lyu Fangxing
Published: August 2024

Electromagnetic pulse signal measurement is crucial for national security, scientific research, technological advancement, and emergency preparedness, playing a vital role in various aspects of modern society. In this work, an electromagnetic pulse signal detection approach utilizing compressed sensing technology is suggested. By unitizing three parallel low-frequency analog-to-digital converters, the high-frequency acquisition waveform of the measured electromagnetic pulse signal can be recovered. The compressed sensing effect of the proposed system on electromagnetic pulse signal is tested by simulation, which verifies the feasibility of this method.
Research on multi-data fusion fire detection based on GWO-LSTM regression prediction model
Authors: Li Haoyang , Liu Jianxiang , Cao Zhenkun , Liu Yujun , Ni Ruju
Published: August 2024

Aiming at the current situation of unsatisfactory fire prediction index and accuracy, this study obtains the optimal network hyperparameter values for LSTM by introducing the GWO algorithm, obtaining the optimal solution of model parameters through fitness calculation, compensating for the drawback of traditional LSTM easily converging to local optimal solutions, accelerating the convergence speed of LSTM neural networks, and reducing training time. The MATLAB simulation experiments show that the accuracy of the improved LSTM model is 92.54%, 97.04%, and 88.17% respectively, with prediction accuracy improvements of 10.6%, 4.33%, and 22.3%. This significant improvement demonstrates the effectiveness of the improvement method and provides a reference for the development of fire detection technology.
Research and practice of virtualization PLC (vPLC) technology in 5G industrial network
Authors: Sun Ruiqi , Zhang Yan , Liu Liu , Liu Jiawei , Sun Shihai
Published: August 2024

Under the influence of information technology innovation, the empowerment of 5G and industrial internet in the steel industry has gradually expanded from production assistance to industrial control. In this paper, a deep integration network of 5G and industrial control is constructed, and a virtualization PLC(vPLC) system solution deployed on private cloud servers is proposed. Secondly, IoT protocols and security policies for cloud control are designed. Finally, the proposed scheme was successfully applied to the remote control of equipment in the steelmaking production process of a certain steel enterprise. At the same time, the real-time performance, reliability and stability of the 5G-enabled vPLC system were tested. The result indicated that the 5G industrial network can work stably with a delay of less than 10 ms and 99.99% reliability. The vPLC system ran continuously for 2000 hours and maintained stable control functions. This result can provide a research foundation and technical direction for achieving centralized control and one-stop production management in the future.
End-to-end elevator voice command recognition system based on improved convolutional neural network
Authors: Liu Xinyu , Li Jin , Jiang Junbang , Li Tiehong
Published: August 2024

As a common life scenario, the use of voice control in elevator operation can effectively reduce public health risks and improve user experience in the post-epidemic era. However, due to the characteristics of its closure and public space, it is difficult to deploy the elevator. To solve this problem, an end-to-end speech command recognition algorithm based on a new deep neural network is proposed. The algorithm uses the self-built corpus for training, and uses the speech segment interception algorithm to obtain audio segments under the premise of speech stream as input, puts them into the network model in real time for reasoning, and drives the elevator to run according to the output results. The results show that compared with the recognition model using MFCC-CNN, the network has achieved about 10% improvement in accuracy under the premise of smaller computation, and compared with the DTW algorithm, the network has improved the accuracy by about 25%. Finally, a typical deployment environment is constructed to prove the correctness and effectiveness of the method in practical application.
Flow prediction of irrigation well pump based on experimental and big data analytics
Authors: Jiang Rui , Xian Haizhen , Li Fengchong , Su Wenqiang , Wang Ningling , Zhang Yuning
Published: August 2024

Currently, China’s agricultural irrigation consumes a huge amount of water, and traditional agricultural irrigation methods lead to low irrigation efficiency and serious water resource waste. Agricultural irrigation water management is also difficult to achieve refined management due to the lack of accurate monitoring of water use data and information in various irrigation areas. To find a more convenient flow measurement method, this paper proposes using data-driven monitoring of water pump characteristic parameters to predict flow rate. Three big data-based methods for predicting the flow rate of irrigation well pumps were compared, including RBF neural network, Support Vector Machine (SVM), and Extreme Learning Machine (ELM). The results indicate that the Extreme Learning Machine (ELM) model not only has short time consumption but also high prediction accuracy, laying the foundation for the application of big data technology in water management and high-quality irrigation water management that can save water.
Research on grid-related performance laboratory testing for variable speed pumped storage unit
Authors: Yan Yian , Li Shanying , Xie Huan , Wu Tao , Cao Tianzhi , Liang Hao , Liang Beihua , Lu Wenqing
Published: August 2024

Variable speed pumped storage unit is an energy storage device with excellent operation and regulation performance. For the grid-related performance laboratory testing of the AC excitation controller of variable speed pumped storage unit integrated into the power grid, this paper studied the methods of grid-related testing of the AC excitation controller based on actual pumped storage power station data, established semi-physical hardware in the loop simulation platform based on RTDS and its function boards, and proposed the key laboratory testing items for the grid-related test. The simulation testing results verified the functions of the platform.
Electro-hydraulic servo position control of bending machine based on Single Neuron PID
Authors: Miao Linchen , Shu Zhibing
Published: August 2024

Due to the fixed parameters, inadequate dynamic performance, and significant tracking error of the traditional PID control algorithm, it is challenging to satisfy the increasingly stringent precision demands for position control of the slider in the hydraulic servo system of the bending machine. Given the significant impact of external load on the position accuracy of the bending machine’s slider, a single neuron network is employed to dynamically adjust parameters in response to external load interference, thereby compensating for the limitations of traditional algorithms. Consequently, this paper proposes the design of a single neuron PID (SN-PID) controller to enhance system control accuracy. Through multiple simulation comparisons, it is evident that the SN-PID controller system exhibits superior anti-interference capabilities, enhanced adaptability, and reduced following error compared to traditional PID control algorithms in achieving slider position accuracy.
The YOLOv8m road object detection algorithm based on a lightweight design
Authors: Gao Deyong , Chen Taida , Miao Lan
Published: August 2024

To address the issues of low detection accuracy, slow detection speed, and high computational resource consumption in current road object detection algorithms, a lightweight YOLOv8m road object detection algorithm is proposed. Firstly, a lightweight convolution, GSConv, is introduced, and a C2fGSConv module is specifically designed to substitute the Conv and C2f modules within the Neck layer. This substitution effectively decreases the complexity of the algorithm during the feature fusion stage, thereby enhancing the network’s inference speed. Secondly, a lightweight convolution partial convolution (PConv) is introduced to redesign the detection head of YOLOv8, further reducing the model’s parameter size. Lastly, the efficient attention mechanism is integrated into the Backbone layer to enhance the algorithm’s detection accuracy for small road objects. Experimental results on the BDD100K road object detection dataset show that the improved algorithm achieves a 0.5% increase in detection accuracy, a 31.39% reduction in model computation, a 27.4% improvement in detection speed, and outperforms other comparison algorithms in various evaluation metrics, meeting the requirements of road object detection tasks.
Fault diagnosis method for continuous casting machine’s sector segment based on SG-PCA-LSTM
Authors: Pang Aokang , Rong Zhijun , Li Xuelin , Wang Yiheng
Published: August 2024

To address challenges such as the high variability of variables and difficulties in feature extraction during the casting process of the continuous casting machine’s sector segment, a fault diagnosis method based on SG-PCA-LSTM is proposed. This method aims to overcome the issue of fault features obscured by noise in the total tension time series by employing the SG smoothing algorithm for filtering and denoising. By leveraging the inter-segment data correlation and the advantage of PCA in extracting fault feature information, combined with the powerful learning capability of LSTM in modeling, a Principal Component Analysis - Long Short-Term Memory (PCA-LSTM) fault diagnosis model is established. Through comparative analysis against different diagnostic methods in terms of recognition rate, false positive rate, etc., the results obtained by this method are compared against those obtained by using other algorithms. Experimental results demonstrate that the proposed method exhibits good overall performance in terms of accuracy and training time.
Vector control of permanent magnet synchronous motor based on self-disturbance rejection and PI parallel connection
Authors: Shen Wei , Ran Quan , Zhao Shiping
Published: August 2024

Addressing the issue of susceptibility to disturbances in PMSM systems, a vector control system for permanent magnet synchronous motors with a self-disturbance rejection controller and PI parallel connection was designed. Firstly, the system’s speed error, electromagnetic torque, and load error are used as inputs for the self-disturbance rejection controller and PI control, respectively. Then, the self-disturbance rejection controller is connected in parallel with the PI and designed as a speed loop for PMSM to improve system stability. Finally, we use the improved sparrow algorithm to optimize the parameters of ADRC and enhance the overall performance of the system. The simulation results in Simulink indicate that parallel systems have fewer overshoots, higher stability, and better overall performance compared to ADRC and PI control.
Rock lithology classification algorithm based on improved self-attention mechanism VIT
Authors: Liu Hongqi , Shi Shaolong , Ma Tongle
Published: August 2024

When applying VIT to image classification, although good accuracy has been achieved, there is a limitation on the number of stacked layers. The similarity between different tokens increases as the model deepens, leading to low accuracy in shallow VIT models and wasting computational resources in deep VIT models. To address this issue, a multi-valued self-attention mechanism is proposed. By introducing an additional clue “V,” that does not vary arbitrarily, the dot product similarity observes each position in the token sequence more, reducing the depth of the attention mechanism network and avoiding the problem of similarity disappearing between deep tokens. Additionally, the loss function is improved by combining the Focal Loss function with Label Smoothing, enhancing the model’s handling of uncertain images while retaining the category focus of Focal Loss. Experiments are conducted on a rock lithology classification dataset, showing that compared to the VGG model and ResNet-18, the accuracy of the ResNet-50 model improves by 17.6%, 12%, and 4.9%, respectively. This paper also demonstrates the effectiveness of the multi-valued self-attention mechanism, which significantly reduces depth and parameter count while maintaining comparable accuracy. Finally, generalization experiments on the CIFAR-10 dataset further validate these conclusions.
Performance prediction method of solid rocket motor based on the ground test
Authors: Hu Xiaomei , Hua Yuting , Weng Jiahong , Teng Xianshu , Zhang Mingnan
Published: August 2024

Solid rocket motor (SRM) is a core component of rockets. Considering the high cost of solid rocket motors and the high demand for transportation and storage, there is an urgent need to predict the performance of solid rocket motors before the ground ignition test to lower the cost of tests. Using data mining technology to predict various parameters of rocket motors with historical data has become a new development direction. In order to improve the data fitting effect and prediction accuracy, a novel prediction model was proposed, which tries to combine the Whale Optimization Algorithm (WOA) with the Error Correction Gated Recurrent Unit neural network (ECGRU) to correct the basic prediction performance of the Long Short-Term Memory neural network model (LSTM). Compared with traditional methods, experiments showed that the novel model was beneficial in improving the reliability of the prediction of the thrust and specific impulse.