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    Information & Control
    Application of Improved Whale Optimization Algorithm in Robot Path Planning
    ZHAO Jun-tao, LUO Xiao-chuan, LIU Jun-mi
    2023, 44 (8):  1065-1071.  DOI: 10.12068/j.issn.1005-3026.2023.08.001
    Abstract ( 1020 )   HTML ( 121)   PDF (1305KB) ( 588 )  
    To solve the problem of slow convergence and susceptibility to local optima in solving robot path planning problems using the standard whale optimization algorithm (WOA), an improved whale optimization algorithm (PSO-AWOA) with hybrid particle swarm algorithm and adaptive weights strategy is proposed. By introducing nonlinear inertia weight factors into the standard PSO and WOA algorithms and adaptively updating the weights during the population evolution, the global exploration ability and convergence speed are improved. Meanwhile, by introducing the PSO algorithm with strong optimization-seeking ability into the exploitation stage of the WOA algorithm, the new solution of iteration is guaranteed to be better than the original solution, which enhances the ability to jump out of the local optima. Finally, the PSO-AWOA algorithm is applied to generate the optimal path for the robot in the grid map simulation environment. The results show that the proposed PSO-AWOA algorithm outperforms in terms of optimization accuracy and convergence speed by comparing the time consumption, planning path length, and the number of turning points of the algorithms given, which verifies the effectiveness of the improved algorithm.
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    Resource Allocation Algorithm in Industrial Internet of Things Based on Edge Computing
    WEI Jian-yi, WU Jing-jing
    2023, 44 (8):  1072-1078.  DOI: 10.12068/j.issn.1005-3026.2023.08.002
    Abstract ( 656 )   HTML ( 56)   PDF (1032KB) ( 330 )  
    In order to solve the problems that computing resources and wireless resources of terminal devices in the industrial Internet of things are difficult to meet the quality of service requirements and generate high energy consumption, a distributed deep learning-based resource allocation (DDLRA) algorithm is proposed. Firstly, the optimization problem of joint offloading decision and resource allocation of industrial Internet of things equipment is constructed. Then, the multiple parallel deep neural networks (DNNs) are used to solve the offloading decision and wireless resource allocation. Finally, simulation results show that the proposed DDLRA algorithm can improve task calculation speed and reduce energy consumption of terminal devices compared to the comparative algorithm.
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    Real-Time Driving Ability Evaluation Algorithm for Human-Machine Co-driving Decision
    SU Wei-xing, XUE Feng, WEN Yong-gang, LIU Fang
    2023, 44 (8):  1078-1088.  DOI: 10.12068/j.issn.1005-3026.2023.08.003
    Abstract ( 517 )   HTML ( 36)   PDF (2458KB) ( 211 )  
    To meet the needs of real-time driving ability evaluation for human-machine co-driving decision problems for intelligent assisted driving systems, a method for real-time driving ability evaluation of drivers considering driving skill, driving state and driving style is proposed taking into account the unicity problem of existing driving evaluation researches.Based on the relative and continuous attributes of driving ability, firstly, an objective entropy-weighted relative evaluation model of driving skill is proposed based on the Gaussian kernel function, the relative evaluation model of driving state based on the time scale, and the soft classification model of driving style based on unsupervised decision classification tree. Secondly, a real-time driving ability evaluation mechanism and evaluation model with“punishment”and“affirmation”mechanisms are proposed to achieve real-time driving ability evaluation that meets the needs of human-machine shared decision control.Finally, the experimental comparison analysis shows that the proposed evaluation algorithm can meet the real-time, objective, and comprehensive requirements of human-machine co-driving decision control for drivers driving ability evaluation.
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    Improved Particle Swarm Optimization Algorithm Based on Multiple Strategies
    KANG Yan-song, ZANG Shun-lai
    2023, 44 (8):  1089-1097.  DOI: 10.12068/j.issn.1005-3026.2023.08.004
    Abstract ( 794 )   HTML ( 47)   PDF (832KB) ( 501 )  
    Aiming the problem of slow convergence speed and difficulty in jumping out of the local optimal solution of particle swarm optimization (PSO) algorithm, the standard PSO algorithm is improved with various strategies, and the hybrid dynamic PSO (HDPSO) algorithm is proposed. The algorithm divides particles into dominant particles and inferior particles according to a proportion, and uses different formulas to calculate the inertia weights of each particle respectively. Each particle is assigned a variation coefficient, and the duration of small fitness changes between adjacent particles is recorded. If this duration exceeds a threshold value, the variation coefficient is accumulated and reset to the initial value after reaching the upper limit. The acceleration coefficient is introduced into the position update formula to improve the convergence speed of the algorithm. The standard test functions are used to test the HDPSO algorithm and other PSO algorithms. The results show that HDPSO algorithm has obvious advantages in terms of convergence speed, optimization accuracy and stability, which further proves the effectiveness of the proposed method.
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    EEG Recognition Method for Epileptic Patients Based on RNN Model with Attention Mechanism
    ZHOU Song, GAO Tian-han
    2023, 44 (8):  1098-1103.  DOI: 10.12068/j.issn.1005-3026.2023.08.005
    Abstract ( 456 )   HTML ( 31)   PDF (558KB) ( 366 )  
    A RNN (recurrent neural networks) model based on attention mechanism is proposed for EEG (electroencephalogram) data recognition in epilepsy patients. Traditional EEG feature analysis is time-consuming and excessively dependent on expert experience, which greatly limits the application and popularization of brain activity recognition methods. A new EEG recognition method to solve the above problems is proposed. Firstly, the basic characteristics of EEG from epilepsy patients are analyzed. Then, the RNN model based on attention mechanism is designed to eliminate various interference signals and the XGBoost classifier is used to identify the categories of EEG data, so as to achieve the purpose of automatic refinement and recognition of the original EEG. Finally, a large number of experiments are carried out on the public EEG data set to verify the accuracy of the proposed method. The experimental results show that compared with the mature EEG recognition methods, the proposed method has higher recognition accuracy.
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    Materials & Metallurgy
    Preparation and Properties of Biodegradable Zn-3Cu-xMn Alloys
    ZHANG Ya-jing, WANG Jin-peng, CHEN Xin, WU Hang-yu
    2023, 44 (8):  1104-1110.  DOI: 10.12068/j.issn.1005-3026.2023.08.006
    Abstract ( 513 )   HTML ( 32)   PDF (2084KB) ( 185 )  
    To investigate the feasibility of Zn alloy as biodegradable cardiovascular stent material, Zn-3Cu-xMn(x=0, 0.5%, 1.0%,1.5%)alloy was prepared by casting and reverse hot extrusion. The effects of Mn content on the microstructure and properties of the alloys were studied by optical metallographic microscope, XRD, SEM, tensile test, electrochemical test and SBF solution immersion corrosion. The results showed that the microstructure of Zn-3Cu-xMn alloy is composed of Zn matrix, CuZn5 and MnZn13. With the increase of Mn content in the alloy, the tensile strength increases, and the yield strength and elongation first increase and then decrease. Electrochemical tests and SBF solution immersion corrosion experiments indicated that the corrosion rate of Zn-3Cu-xMn alloy increases from 0.063mm/a to 0.113mm/a with the increase of Mn content in the alloy. The alloy with Mn element meets the mechanical properties of cardiovascular stent material, and the corrosion rate is higher than the requirements of cardiovascular stent material, so Zn alloy has the potential to become biodegradable cardiovascular stent material.
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    Study on the Electroslag Remelting Slag for H13 Die Steel Containing Ce and Mg
    ZHENG Li-chun, PENG Bo, LOU Jian, JIANG Zhou-hua
    2023, 44 (8):  1111-1118.  DOI: 10.12068/j.issn.1005-3026.2023.08.007
    Abstract ( 390 )   HTML ( 19)   PDF (981KB) ( 203 )  
    RE and Mg co-treatment can significantly improve the cleanliness of steel and refine carbide, but RE and Mg are prone to be burned during electroslag remelting. Therefore, two kinds of electroslags containing Ce2O3 and MgO were designed, which are 55% CaF2-30% Ce2O3-10% MgO-5% Al2O3 (1#) and 60% CaF2-30% Ce2O3-10% MgO (2#), respectively. Ce and Mg co-treatment of H13 die steel was carried out using a resistance-heated tube furnace, and the slag-metal equilibrium behavior between H13 steel and the aforementioned slags at 1873K was studied. The results show that the main inclusions in H13 steel are Ce2O3 and MgO. Some Ce2O3 inclusions are coated with MgO. At 15min after adding Ce and Mg, the dissolved Ce in the steel was almost completely burned, and only insoluble Ce in Ce2O3 inclusions was remained. During the whole deoxidation period, the content of dissolved Mg in steel changed little. The contents of dissolved Mg in 1# and 2# H13 steel at 60min were 0.0034% and 0.0053%, respectively, MgO solubility in 1# and 2# slags are 10.6% and 6.7%, respectively. Due to MgO supersaturation, both slags have very weak absorption capacity for MgO inclusions. The rmodynamic calculation shows that both the Al2O3 component and minor amounts of SiO2 in the slags lead to serious burning loss of Ce and Mg.
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    Study on Localized Emission Factors of Heavy-Duty Diesel Trucks in Mid-Southern Liaoning Urban Agglomerations
    LI Na, GAO Cheng-kang, BA Qiao, NA Hong-ming
    2023, 44 (8):  1119-1127.  DOI: 10.12068/j.issn.1005-3026.2023.08.008
    Abstract ( 389 )   HTML ( 24)   PDF (1426KB) ( 195 )  
    Based on the environmental conditions, driving characteristics and other traffic information, the emission characteristics of heavy-duty diesel trucks in Mid-Southern Liaoning Urban Agglomerations was analyzed, a typical city in low temperature areas. The on-board test results were utilized to localize the emission factors of Guidebook and IVE model, and the emission factor database of heavy-duty diesel trucks in Mid-Southern Liaoning urban agglomerations was obtained. The results show that the average speed of heavy-duty diesel trucks on various road types in winter is higher than in summer, and the traffic flow is the largest on suburban roads, followed by urban roads and highways. The pollutant emission factors of heavy-duty diesel trucks decrease with the increase of emission standards. When the heavy-duty diesel truck is 50% loaded, the pollutant emissions are 1.4~5.5 times that of the no-load state. The emission of pollutants from heavy-duty diesel trucks in winter is 1.31~1.64 times that in summer. For National III heavy-duty diesel trucks, the measured results of CO, NOx and PM emission factors are 0.5~0.8 times and 1.1~1.3 times of Guidebook and IVE model, respectively.
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    Mechanical Engineering
    Reliability Sensitivity Analysis of the Fatigue Life of Wind Turbine Bearings
    HU Bing, HUANG Xian-zhen, DU Shan-shan
    2023, 44 (8):  1128-1135.  DOI: 10.12068/j.issn.1005-3026.2023.08.009
    Abstract ( 523 )   HTML ( 23)   PDF (2138KB) ( 254 )  
    A 2MW wind turbine bearing is taken as an example, and the mathematical model of the fatigue life of cylindrical roller bearings under four degrees of freedom load is given. The accuracy of the model is verified by Romax software analysis results. The limit state equation is established according to the minimum rated life of the bearing, and the adaptive Kriging-Monte Carlo simulation (AK-MCS) method is used to analyze the reliability sensitivity of the bearing′s fatigue life. The results show that the bearing failure probability increases with the increase of bearing clearance, elastic modulus and density. With the increase of bearing pitch and roller finite length, the failure probability of bearings decreases. The influence of clearance on reliability is the most obvious, followed by elastic modulus, density and roller finite length, and the influence of pitch is the least.
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    Effect of the Size of Artificial Vertebral Body on the Mechanical Properties of Cervical Spine
    ZHANG Dong-xiang, ZHANG Chi, FAN Wei, GUO Li-xin
    2023, 44 (8):  1136-1143.  DOI: 10.12068/j.issn.1005-3026.2023.08.010
    Abstract ( 414 )   HTML ( 20)   PDF (2726KB) ( 182 )  
    Based on the finite element method, the effects of the size of artificial vertebral body (AVB) on the biomechanical properties of the reconstructed structure of vertebral body replacement and fusion (VBRF) was studied. Firstly, an Abaqus plug-in was developed, which could parametrically establish the three-dimensional model of AVB, and cooperate with the finite element model of the cervical spine to establish the finite element model of VBRF. Secondly, the finite element analysis was given to various VBRF models (different sizes of AVB). Finally, Pease value, an important index closely related to implant and vertebral fusion, was introduced and compared. The results showed that there is no significant difference in the Pease value under the condition of the same size of AVB and different wall thickness, but the size of AVB has a significant effect on the Pease value. The Pease value is relatively higher when the outer radius of AVB is in the range of 4~6mm, which is more conducive to the fusion of implants and vertebrae.
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    Vehicle State Parameter Estimation Based on Graded Series Extended Kalman Filter Method
    CHEN Long , LIU Qiao-bin, TAO Lei
    2023, 44 (8):  1144-1151.  DOI: 10.12068/j.issn.1005-3026.2023.08.011
    Abstract ( 435 )   HTML ( 22)   PDF (1345KB) ( 258 )  
    Accurate and efficient vehicle state estimation is the prerequisite for intelligent vehicles to achieve precise control, thus there is an urgent need to carry out research on fast and accurate state estimation algorithms. To this end, a graded series extended Kalman filter (GS-EKF) method of vehicle state parameter estimation is proposed, which aims to improve the computational efficiency and robustness of the algorithm while ensuring the estimation accuracy. Firstly, based on the graded series idea, the result of the primary extended Kalman filter estimation is used as the measurable control input signal of the secondary state estimation to realize the hierarchical cascading state estimation. Then, a 3-degree-of-freedom nonlinear dynamic vehicle state parameter estimation is established which takes the steering wheel angle and longitudinal/lateral acceleration as input variables and observation variables. Finally, a joint simulation verification platform is built to compare and analyze the accuracy, robustness and efficiency of four different algorithms. The results show that the proposed algorithm can achieve the effect of particle filter in terms of accuracy and robustness, and the efficiency is 41. 2% higher than that of particle filter.
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    Experimental Study on Single-Excitation 3-D Ultrasonic Turning Technology
    ZHANG Jia-hao, ZOU Ping, WEI Shi-yu, LIANG Fu-qiang
    2023, 44 (8):  1152-1159.  DOI: 10.12068/j.issn.1005-3026.2023.08.012
    Abstract ( 315 )   HTML ( 15)   PDF (2047KB) ( 176 )  
    The surface machining mechanism of 3-D ultrasonic turning technology is studied by using the single-excitation 3-D ultrasonic assisted vibration device. Firstly, the simulation model suitable for 3-D ultrasonic cutting is designed by establishing the trajectory equation of the tool tip, and the simulation orthogonal experiment is designed. The influence of spindle speed, cutting depth and feed rate on surface morphology in 3-D ultrasonic turning process is studied by the multiple comparative analyses of variance. Then, the surface processing quality of 3-D ultrasonic turning and ordinary turning is compared through experiments, and the influence of processing parameters on 3-D ultrasonic turning and the optimal parameters are studied. The results show that compared with ordinary turning, 3-D ultrasonic turning can obtain better surface processing quality, and the influence of feed rate on surface roughness is the most significant. The optimal processing parameters are spindle speed 200r/min, cutting depth 0.12mm, and feed rate 0.18mm/r.
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    Resources & Civil Engineering
    Study on Numerical Calculation Model of Hydraulic Fracture for Heterogeneous Rock Materials Based on PHF-SFM
    LI Ming, ZHOU Shi-kang, LIU Shi-yi, LIANG Li
    2023, 44 (8):  1160-1167.  DOI: 10.12068/j.issn.1005-3026.2023.08.013
    Abstract ( 540 )   HTML ( 38)   PDF (1516KB) ( 172 )  
    Based on the permeability-based hydraulic fracture (PHF) model, a statistical fracture model (SFM) is introduced to capture the influence of the micro non-uniform distribution of rock materials on the macroscale characteristics of hydraulic fracture. The Weibull probability model is adopted to account for the discreteness of characteristics of these characteristics. By assuming that the permeability of rock material is a function of the mean effective stress, the PHF-SFM model is proposed based on the Biot consolidation theory. The model incorporates the Mohr-Coulomb elastoplastic constitutive model and Darcy’s law to represent mechanical behaviors for the solid and liquid phase of rock material in pre- and post-failure part. The verification is carried out by comparing the simulated results with those of the KGD model. Breakdown pressure, equivalent fracture height and fracture width were studied by varying the Weibull modulus and scale parameters in the SFM model and material properties of rock. The simulation results indicate that including the SFM model does not affect the breakdown pressure, but does vary the fracture geometry. When the Weibull modulus decreases or the scale parameter increases, the discreteness of fracture geometry features increases.
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    Uniaxial Compressive Strength Model of Rock Using Measurement While Drilling (MWD) Data
    WANG Yu-heng, YU Qing-lei, NIU Peng, LI You
    2023, 44 (8):  1168-1176.  DOI: 10.12068/j.issn.1005-3026.2023.08.014
    Abstract ( 521 )   HTML ( 28)   PDF (2039KB) ( 322 )  
    The uniaxial compressive strength (UCS) of rock is an important factor in drilling and blasting operations, and it is closely related to measurement while drilling (MWD) data. A series of rock drilling tests were carried out under different thrusts using a self-built MWD test platform to investigate the correlation between UCS and MWD data. The results show that slope of thrust and cutting depth (Fe), the slope of torque and cutting depth (Te), and the ratio of normal force to tangential force per unit size of bit (ζ) are positively correlated with rock UCS and not affected by test conditions. Based on the fact that Fe and Te can characterize rock drillability and mechanical specific energy, respectively, a model was developed to estimate rock UCS by Fe and Te. Additionally, the validity of the model was preliminarily verified using a different type of rock. The research provids a new method for estimating rock UCS during drilling process.
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    Deformation Damage Characteristics and Energy Evolution Mechanism of Granite Under Mining Stress Path
    YOU Shuang, LI Hu-zhen, HOU Xiao-xu, GENG Qian-cheng
    2023, 44 (8):  1177-1187.  DOI: 10.12068/j.issn.1005-3026.2023.08.015
    Abstract ( 451 )   HTML ( 21)   PDF (2465KB) ( 130 )  
    Considering the stress paths of kilometer-deep granite during mining, the triaxial loading and unloading experiments are performed on granite under three stress paths: ascending axial pressure and fixed confining pressure, ascending axial pressure and unloading confining pressure, and fixed axial pressure and unloading confining pressure. The aim is to obtain the deformation and failure characteristics and energy evolution law of rock under mining and unloading conditions. The research results show that under the high confining pressure levels, rock stores more energy before reaching peak failure, and the deformation energy released during failure has a more significant impact on the rock structure, leading to brittle failure of the rock sample. The unloading effect weakens the radial restraint of the confining pressure on the rock sample, causing an increase in radial expansion, and failure occurs at a lower stress level. Furthermore, the rock deformation modulus and generalized Poisson’s ratio reach the extreme point faster, determined by the expansion point, the turning point at which the proportion of elastic energy of the rock sample changes from increasing to decreasing. Compared with the ascending axial pressure and fixed confining pressure test, the ratio of elastic energy to dissipated energy is higher under the unloading conditions, resulting in more severe in rock damage.
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    Effect of Roughness on Floatability of Dolomite in Sodium Oleate System and Its Mechanism
    ZHAO Xu, YIN Wan-zhong, YAO Jin, ZHU Zhang-lei
    2023, 44 (8):  1188-1194.  DOI: 10.12068/j.issn.1005-3026.2023.08.016
    Abstract ( 545 )   HTML ( 20)   PDF (1095KB) ( 117 )  
    In order to study the influence of surface physical properties on mineral floatability, two kinds of dolomite particles with different surface roughness were obtained by ultrasonic pretreatment. In sodium oleate system, the influence of surface roughness on the recovery rate of dolomite flotation was investigated by single mineral flotation test, and atomic force microscope(AFM), BET, SEM-EDS, XPS, ultraviolet spectrophotometer and contact angle measuring instrument were used. The mechanism of the impact of surface roughness on mineral flotation behavior was discussed. The results show that ultrasonic treatment increases the surface roughness of dolomite particles and the content of active sites (Ca2+ and Mg2+) on the surface of rough particles is higher than that on the surface of smooth particles. This contributes to the adsorption of sodium oleate on mineral surface, enhancing its hydrophobicity and floatability.
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    Study on Process Mineralogy of a Copper-Molybdenum Mixed Concentrate in Tibet
    GUO Jin-ming, YANG Hong-ying, TONG Lin-lin, MENG Jing
    2023, 44 (8):  1195-1200.  DOI: 10.12068/j.issn.1005-3026.2023.08.017
    Abstract ( 465 )   HTML ( 24)   PDF (1164KB) ( 178 )  
    The process mineralogy of a copper-molybdenum mixed concentrate in Tibet was studied by means of chemical analysis, microscopic analysis and MLA analysis.The research shows that the mixed concentrate contains 19.00% copper and 0.38% molybdenum, and both copper and molybdenum mainly exist in the form of sulfide. Pyrite, chalcopyrite and bornite are the main minerals in the mixed concentrate, with molybdenite present at a content of 1.0%.The grinding fineness of the mixed concentrate is extremely fine, and the degree of dissociation of molybdenite is excellent. Additionally, a small part of molybdenite exists in coexistence with chalcopyrite and pyrite.The research results provide theoretical guidance for on-site copper-molybdenum separation and transformation.
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    Management Science
    Impact of Environmental Regulation Distance on the Efficiency of OFDI
    ZHANG Ya-nan, NING Ye, ZHUANG Zi-yun, ZHANG He
    2023, 44 (8):  1201-1207.  DOI: 10.12068/j.issn.1005-3026.2023.08.018
    Abstract ( 467 )   HTML ( 23)   PDF (1102KB) ( 150 )  
    Based on the stochastic frontier gravity model, the impact of environmental regulation distance on the efficiency of OFDI and the moderating effect of bilateral economic relation as well as the technical efficiency were explored. The result showed that the regulation distance environmental is negatively associated with the efficiency of OFDI, investment flows from high-environment-regulated countries to low-environment-regulated countries based on cost effectiveness, and investment flows from low-environment-regulated countries to high-environment-regulated countries based on innovation effect. When the bilateral economic relations are tight, the greater two countries environmental regulation distance, the lower efficiency of OFDI. Meanwhile, Chinas efficiency of OFDI in different countries and regions is heterogeneous, and it interacts with location selection. Investment efficiency is higher in the developing countries, less developed regions and some developed countries. Efficiency in Asia and Africa is relatively higher when compared to Europe. Therefore, suggestions are provided including reducing the distance of environmental regulation, improving the efficiency of Chinas OFDI, and selecting reasonable investment locations.
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    Research on Risk Warning of Network Public Opinion for Forest Fires from the Perspective for Information Ecology
    ZHU Guo-qing, CHEN Yan, LANG Kun, WANG Shu-tian
    2023, 44 (8):  1208-1216.  DOI: 10.12068/j.issn.1005-3026.2023.08.019
    Abstract ( 480 )   HTML ( 20)   PDF (802KB) ( 188 )  
    To address the risk warning of network public opinion for forest fires under uncertain information, a risk warning evaluation model based on evidential reasoning and intuitionistic fuzziness was established. Firstly, a network public opinion risk evaluation index system of forest fires was identified based on the perspective of the information ecosystem. Secondly, given the uncertainty and incompleteness of the index information in the evaluation process, the number of intuitionistic fuzziness was used to describe multiple index information by fuzzy rules. Then, the weight of the index system was calculated via intuitionistic fuzzy entropy and fuzzy analytic hierarchy process, and evidential reasoning theory was used to complete the integration of index information. Finally, the network public opinion risk level was determined by measuring the distances of intuitionistic fuzziness, and the ranking of network public opinion risks was determined by the utility value method. The practicability and effectiveness of the model were validated through three practical cases, providing new ideas and methods for the risk warning assessment of network public opinion for forest fires.
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