Table of Content

06 May 2023, Volume 37 Issue 4 Previous Issue    Next Issue

Vehicle engineering

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Intelligent vehicle path tracking method based on AFS and DYC coordinated control 2023, 37 (4):  1-9.  Abstract ( 272 )   PDF (2802KB) ( 283 )   Save The continuous development of vehicle intelligence and electronic technology has greatly promoted the vigorous development of the automotive industry. How to improve path tracking accuracy, driving safety and stability of intelligent vehicles has become a focus of research for many automotive companies. Both Active Front-wheel Steering (AFS) and Direct Yaw-moment Control (DYC) can greatly assist in the stability performance of intelligent vehicles. AFS controls a vehicle in the yaw direction by changing the front wheel angle, while DYC applies additional longitudinal force (braking or driving force) to the wheels to improve the stability of a vehicle’s motion. However, both AFS and DYC have their limitations when controlled separately. Therefore, compared with individual control, coordinated control of AFS and DYC can fully consider the interactions between various subsystems, and has the advantages of high flexibility, good fault tolerance and high control accuracy. In this paper, a coordinated control method for intelligent vehicle path tracking based on AFS and DYC is proposed to improve the path tracking ability and driving stability of intelligent vehicles under complex road conditions. Based on a two-degree-of-freedom vehicle model and a single point preview model, the preview time is controlled to change adaptively, aiming to ensure the tracking accuracy and driving stability of the vehicle under complex road conditions; in the design of DYC controller, considering different dimensions of yaw rate and sideslip angle, a dimensionless sliding mode controller for the addition yaw moment is designed and a single wheel braking method is used to distribute the additional yaw moment to the corresponding wheel; at the same time, in order to fully utilize the working effects of AFS and DYC, the critical steering angle of the front wheels at the edge of the vehicle’s losing stability is calculated, and a weighted distribution function is used to ensure stability and smoothness of the coordinated control, while also taking ride comfort into account. Experimental simulations based on Carsim-Simulink are carried out under Fishhook and double line change conditions and compared with those under AFS and DYC control. The experimental results show that coordinated control can effectively improve the handling stability of intelligent vehicles while simultaneously meeting the accuracy of path tracking under complex road conditions, and has better robustness. Related Articles | Metrics

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Variable weight adaptive cruise control strategy for cut-in scenes 2023, 37 (4):  10-18.  Abstract ( 158 )   PDF (3325KB) ( 235 )   Save In order to solve the problem of driver comfort reduction or even dangerous situations due to late recognition of the cut-in of side-lane vehicles of the adaptive cruise control system, this paper proposes a control strategy based on a support vector machine (SVM) to recognize cut-in vehicles and adjust the weight parameters of the model predictive control (MPC) in real time. Firstly, lane change characteristics of real traffic vehicles are extracted, and the SVM algorithm is used to train the recognition model of the cut-in front vehicle. Then, the weight adjustment mechanism is designed based on the fuzzy control theory, and the MPC controller is optimized to obtain the expected acceleration. Finally, a hardware-in-the-loop test platform is set up in Prescan, Matlab/Simulink and NI real-time system environments, and different cut-in working conditions are compared and analyzed. The results show that the adaptive cruise control strategy can switch the following target in advance, reduce the fluctuation of longitudinal acceleration and avoid forced vehicle braking, which improves the comfort and safety of the system. Related Articles | Metrics

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Research on adaptive cruise control of pure electric vehicles 2023, 37 (4):  19-26.  Abstract ( 205 )   PDF (2163KB) ( 241 )   Save In this paper, a four-wheel hub motor-driven electric vehicle is selected as the research object, and the adaptive cruise control system is studied by using Matlab/Simulink and CarSim 2020. Firstly, the overall architecture of the adaptive cruise control system of the pure electric vehicle is developed, and the longitudinal dynamics of the vehicle is analyzed. Subsequently, a suitable safety distance model is selected to ensure the safety of vehicle driving, and the necessary radar and hub motor models are built through Simulink. Next, CarSim 2020 is used to build a vehicle model of the self and front vehicles as well as the simulation environment. Then, the upper-level controllers of cruise control and distance keeping are respectively built based on PID control algorithm and Linear Quadratic Regulator (LQR), and the lower-level controllers are built through vehicle longitudinal dynamics. Finally, a joint simulation model is built by Matlab/Simulink and CarSim 2020 to simulate the cruise control and the distance-keeping controller under acceleration and deceleration conditions. The simulation results show that the control system designed in this paper can realize the function of constant speed cruise and distance keeping better, and has good practicality and effectiveness. Related Articles | Metrics

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LQR lateral tracking control strategy based on ALO algorithm 2023, 37 (4):  27-38.  Abstract ( 177 )   PDF (5513KB) ( 204 )   Save In order to solve the problem of poor vehicle tracking accuracy and poor stability caused by poor adaptability of a linear quadratic regulator (LQR) to the large curvature reference path under the traditional fixed weight coefficient, this paper designs an adaptive weight coefficient LQR controller with preview feedforward angle compensation to track the path laterally based on ant lion optimization (ALO) algorithm. Firstly, a classical LQR controller is designed based on the lateral tracking error model of two-degree-of-freedom vehicle dynamics. Secondly, the preview feedforward control is used to eliminate the steady state error caused by error model simplification. Then, an adaptive LQR weight coefficient correction strategy based on ALO is proposed, which takes lateral distance deviation, heading angle deviation and output front wheel angle as the evaluation functions. Finally, through the real vehicle test, the control effect of the controller in the real vehicle environment is verified. The results show that the designed controller can adapt to the large curvature reference path, take into account of the path tracking accuracy and driving stability, and perform well in robustness at different vehicle speeds. Related Articles | Metrics

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Research on the local trajectory planning method for intelligent vehicles in a complex traffic environment 2023, 37 (4):  39-49.  Abstract ( 191 )   PDF (4004KB) ( 297 )   Save To cope with the problem of real-time trajectory dynamic planning for intelligent vehicles in complex traffic settings, this paper proposes a local trajectory planning algorithm based on Frenet coordinates. Firstly, the road center line is fitted to obtain the road reference line by utilizing a cubic spline curve. Then, according to the initial and target configuration, the sets of quartic and quintic polynomial candidate trajectories are generated by sampling. Additionally, multi-objective cost functions containing safety, trajectory comfortability and trajectory offset are designed to evaluate the trajectory cost by considering the effects of vehicle safety, the lateral and longitudinal acceleration changes of candidate trajectories and the global trajectory tracking ability. Ultimately, the simulation results reveal that the proposed method can obtain a real-time comfortable and safe trajectory. Furthermore, various types of roads are designed to test the approach, including a two-lane continuous curve with a single constant-speed or variable-speed obstacle, and a three-lane curve with multiple constant-speed obstacles or variable-speed obstacles. The test results show that the algorithm can effectively improve obstacle avoidance in complex dynamic environments. Related Articles | Metrics

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Research on intelligent vehicle path planning based on an improved sparrow search algorithm 2023, 37 (4):  50-56.  Abstract ( 218 )   PDF (1401KB) ( 190 )   Save Aiming at the shortcomings of the sparrow search algorithm such as slow convergence speed and easy falling into local optimum, this paper proposes an improved sparrow search algorithm. Firstly, the ICMIC chaotic mapping function is used to initialize the population and improve the diversity of the population so as to enhance the ability of the sparrow population to explore in unknown environments. Secondly, the position update formula of the sparrow algorithm is modified and optimized to improve its convergence speed. Finally, three different grid maps are designed, and the improved sparrow search algorithm and the original algorithm are compared in this map for path planning to verify the performance of the improved sparrow search algorithm. The experimental results show that the improved sparrow search algorithm has better performance in intelligent vehicle path planning, with faster convergence speed and better optimization ability. Related Articles | Metrics

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Research on the safety risk assessment model of intelligent connected vehicle driving 2023, 37 (4):  57-63.  Abstract ( 244 )   PDF (850KB) ( 343 )   Save With an increasing popularity of intelligent connected vehicles, it is urgent to sort out their safety risk factors during driving. In this paper, SHELL model is applied to the intelligent connected vehicle field, and 22 driving risk factors of intelligent connected vehicles are sorted out according to the human-vehicle-environment-software architecture system. The risk matrix method and Borda order value method are introduced to comprehensively analyze and evaluate the driving safety of intelligent connected vehicles. Through case analysis, nine risk severity levels are obtained and corresponding countermeasures are given, which provides relevant basis for vehicle development, operation and safety design. Related Articles | Metrics

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Research on the intelligent vehicle collision avoidance system under multi-mode braking and steering 2023, 37 (4):  64-76.  Abstract ( 151 )   PDF (6326KB) ( 213 )   Save Aiming at the problem that the safety distance model and the collision avoidance strategy of intelligent vehicles are too simple, this paper proposes a coordinated collision avoidance strategy of vehicle braking and steering under complex working conditions. Firstly, a vehicle system model is constructed based on the three-degree-of-freedom dynamic model combined with the magic tire formula. The advantages and disadvantages of common safety distance models are compared and analyzed, and the optimization is carried out on their basis. For the longitudinal braking mode, four longitudinal safety distance models are established based on different driving states of the vehicle in front; For the lateral lane change mode, a minimum longitudinal distance model for critical collision is established based on the driving state of the front and rear vehicles in the target lane and the safety constraints when the vehicle changes the lanes. For the collaborative collision avoidance mode, a collaborative collision avoidance safety distance model is established based on the vehicle’s high-speed lane-changing extreme conditions. The selection of different collision avoidance modes of the vehicle is based on critical distance division of the safety distance model under different working conditions, and finally a switching collision avoidance strategy that satisfies certain constraints is constructed. In the selection of lane-changing trajectory planning methods, factors such as trajectory error, trajectory curvature and vehicle dynamics constraints of different lane-changing trajectory methods are analyzed, and a quintic polynomial is selected as the reference trajectory for lane-changing. The maximum lateral acceleration of the planned trajectory and the limit value of the side slip angle of the center of mass are determined, and the planned trajectory curve is more in line with the driving trajectory during steering and collision avoidance. Secondly, based on the design of the vehicle collision avoidance controller, the longitudinal control of the vehicle adopts fuzzy logic control. The relative speed and relative distance between the vehicle concerned and the preceding vehicle are used as the input of longitudinal collision avoidance, and the fuzzy rule output of the fuzzy controller corresponds to the expected acceleration. Vehicle lateral control adopts online LQR control algorithm combined with certain constraints. To a certain extent, the tracking effect of this controller is better than that of the model prediction control algorithm. At the same time, in the trajectory tracking process, in order to allow the vehicle to adapt to the speed of different front and rear vehicles, the speed function in the process of vehicle lane changing is designed. Finally, a joint simulation platform of Carsim and Matlab/simulink is built to verify the effectiveness of the controller under three simulation conditions of longitudinal, lateral and cooperative collision avoidance. The longitudinal collision avoidance controller has good collision avoidance ability with different road surface adhesion coefficients and under complex driving conditions. The trajectory tracking controller has good real-time performance and good trajectory tracking effect. Under the conditions of short inter-vehicle distance and high vehicle speed, the cooperative collision avoidance strategy reduces vehicle lateral acceleration and improves vehicle lateral stability. Based on the BAIC new energy real vehicle platform, the campus road test is carried out, and the vehicle collision avoidance tests are set at different speeds and under different modes. The test results show that the effectiveness of the vehicle’s longitudinal and lateral collision avoidance controllers improves the potential of vehicle collision avoidance performance. To sum up, this paper proposes a multi-mode vehicle collision avoidance strategy for the problems that the safety distance model is too simple and the collision avoidance strategy is too weak. Firstly, the traditional safety distance model is improved, and the decision logic for collision avoidance under different working conditions is formulated, which improves the adaptability of the vehicle to different driving conditions. Then, three simulation working conditions are set in the simulation software, and the designed collision avoidance is verified. What is more, the effectiveness of the collision controller provides an effective basis for the real vehicle test. Finally, through two groups of real vehicle tests under different modes, it is verified that the designed collision avoidance system has a good collision avoidance ability and improves the active safety performance of the vehicle. Related Articles | Metrics

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Research on lateral sliding mode variable structure control of intelligent vehicles 2023, 37 (4):  77-84.  Abstract ( 162 )   PDF (1965KB) ( 109 )   Save The nonlinearity of the vehicle model and the uncertainty of road parameters seriously affect the robustness of the intelligent vehicle controller under certain working conditions, causing the intelligent vehicle to deviate from the planned path during driving. According to the vehicle two-degree-of-freedom dynamic model and the lateral error model, this paper establishes the lateral motion state equation, designs the lateral sliding mode control algorithm and uses the neural network to further optimize the control error of the system and external disturbances, with an aim of forming a lateral sliding mode variable structure control strategy. The stability of the control strategy is verified through the theory of Lyapunov stability. The Matlab/Carsim co-simulation model is established to simulate and verify the lateral control strategy of the sliding mode variable structure. The simulation results show that, compared with the single sliding mode control strategy, the maximum lateral control error of the sliding mode variable structure control strategy can be reduced by 38% under the condition of high speed and small turning angle, which shows a good robustness of the control strategy to the change of loads. Related Articles | Metrics

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Research on accuracy improvement of vehicle positioning and navigation with an improved support vector machine 2023, 37 (4):  85-94.  Abstract ( 183 )   PDF (2674KB) ( 167 )   Save Vehicle positioning and navigation is the basis of realizing environment perception of intelligent vehicles. To solve the error problem of intelligent vehicles under SINS/GPS integrated navigation, this paper proposes a method of improving vehicle positioning and navigation accuracy based on an improved support vector machine with ant colony algorithm. Firstly, an extended Kalman filter with state transformation is proposed to reduce noise of the integrated navigation system. Secondly, the support vector machine and the neural network aided navigation are proposed to solve the problem of large position error and the influence on navigation effect in the integrated navigation. Then, the support vector machine is improved by ant colony algorithm, and the kernel function parameters of the support vector machine are optimized iteratively. Finally, it is compared with the neural network assistance in the real vehicle collection data set. The results show that the neural network can reduce the root mean square value of error by 72.88%, 68.66% and 63.87% in the three directions of east, north and up (ENU), while the improved support vector machine can achieve 82.09%, 79.62% and 90.14%. The improved support vector machine can help optimize the position error of the integrated navigation and improve the accuracy of vehicle positioning and navigation. Related Articles | Metrics

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Dynamic lane-changing trajectory planning for intelligent trucks considering roll stability 2023, 37 (4):  95-104.  Abstract ( 119 )   PDF (5202KB) ( 96 )   Save To realize automated lane-changing maneuvers for intelligent trucks in the actual traffic environment, this paper proposes a dynamic lane-changing trajectory planning strategy considering roll stability. Considering dynamic stiffness of the suspension and nonlinear characteristics of the tires, the TruckSim software vehicle dynamics model is applied to conduct orthogonal simulation experiments of different vehicle speeds, road adhesion coefficients and longitudinal length of lane-changing, and establish a mathematical model of the critical minimum longitudinal length of lane-changing. According to the dynamic changes of the surrounding vehicles, the safe lane-changing boundaries are obtained by performing obstacle avoidance detection. Objective functions like lane-changing efficiency and vehicle stability for the intelligent trucks are designed to obtain the optimal lane-changing trajectory. The co-simulation platform of Matlab/Simulink and TruckSim is built to conduct simulation analysis of planning strategies. The simulation results reveal that the proposed lane-changing planning strategy can ensure the intelligent trucks to effectively avoid collisions with the surrounding dynamic vehicles and complete the lane-changing. Besides, roll stability of the intelligent trucks can also be guaranteed during the lane-changing. Related Articles | Metrics

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Reliability evaluation method of closed test fields for intelligent connected vehicles 2023, 37 (4):  105-114.  Abstract ( 149 )   PDF (2782KB) ( 222 )   Save In order to study the reliability of automatic driving performance tests of intelligent connected vehicles by using a closed test field, this study establishes 18 test conditions that conform to four typical test scenarios in a closed intelligent connected environment. The evaluation system of the intelligent connected vehicle test field is constructed by Analytic Hierarchy Process, and the weight coefficients corresponding to the 18 test conditions in the four typical test scenarios are calibrated by expert questionnaire method. The reliability evaluation method for the closed intelligent connected vehicle test field is then proposed by introducing the evaluation indexes such as vehicle saturation in tests, single test pass rate, comprehensive test pass rate and test reliability coefficient. Taking Da’an intelligent connected vehicle test field as the research object, the proposed evaluation method is verified based on some software for virtual scene construction and co-simulation, such as Prescan simulation, SketchUp 3D drawing and Matlab/Simulink modeling. The results show that the evaluation method has good applicability to the design improvement and test evaluation of closed test fields for intelligent connected vehicles. According to the evaluation results, the test vehicle can be guided to choose the appropriate field road, and the improvement measures and optimization suggestions can be put forward for the design and construction of the test field. Related Articles | Metrics

Machinery and materials

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Research and optimization of impact resistance for thermoplastic fiber metal laminates 2023, 37 (4):  115-122.  Abstract ( 153 )   PDF (3823KB) ( 99 )   Save In order to study the impact resistance of thermoplastic fiber metal laminates, this paper measures the mechanical properties of the composites through tensile tests, and provides the material parameters for finite element simulation modeling. The orthogonal layered thermoplastic fiber metal laminates are prepared by using 2024-T3 aluminum alloy and reinforced glass fiber modified polyamide six composite prepregs. A numerical simulation model is established by LS-DYNA, and the errors between the simulation results and the experimental results are controlled within 10%, which proves the accuracy of the modeling method and material parameters. Impact peak force (PCF), energy absorption of equal thickness (TEA) and laminate mass (M) are selected as the objective functions to carry out multi-objective optimization design of the fiber metal laminates according to the thickness of each layer of the aluminum plates and the number of layers of the composite materials. The results show that the impact resistance and lightweight indexes of the optimized fiber metal laminates improve effectively, which provides a reference for practical engineering application. Related Articles | Metrics

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Study on liquid-phase plasma electrolysis carbon-boronizing on piston ring surface 2023, 37 (4):  123-132.  Abstract ( 90 )   PDF (3705KB) ( 87 )   Save Strengthening the surface of a piston ring can reduce friction and wear of the piston ring cylinder liner and improve engine efficiency, which is an important way and guarantee for the realization of the low-carbon strategy of commercial vehicles. In order to improve the performance of the piston ring, this paper carries out a research on the surface modification of the piston ring by means of liquid-phase Plasma Electrolytic Carburizing and Boronizing (PEC/B) technology. Then, the effects of the operating parameters on the surface morphology, hardness, phase composition, cross-sectional morphology, element distribution and tribological properties of the workpieces are systematically explored. The research results show that the modified PEC/B layer is mainly composed of a boronized layer and a carburized transition layer. The main composition phase of the boronized layer is Fe2B, and that of the carburized transition layer is Fe3C. Boronizing efficiency can be effectively improved by carburizing treatment. The maximum thickness of the modified layer can reach more than 15 μm, and the maximum hardness of the boronized layer can reach 1 460HV. After PEC/B modification treatment, the friction factor and weight loss rate of the workpieces are about 11% and 7% of those of the untreated ones, and the tribological performance significantly improves. It shows that liquid-phase PEC/B can provide a feasible technical way to improve the performance of piston rings. Related Articles | Metrics

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Study on synthesis and application of lithium carboxymethyl cellulose (CMC-Li) as lithium replenishing binder 2023, 37 (4):  133-140.  Abstract ( 387 )   PDF (2361KB) ( 550 )   Save By using cellulose powder and lithium ethoxide as the raw materials, this paper successfully synthesizes lithium carboxymethyl cellulose (CMC-Li) through IR analysis. With CMC-Li and sodium carboxymethyl cellulose (CMC-Na) being respectively used as the negative electrode binder for lithium-ion batteries, it is found that CMC-Li displays excellent suspension and dispersion performance and does not react with the electrolyte, which shows a good stability. At the same time, under the same conditions, CMC-Li can improve the compaction density of the electrode, increase the liquid absorption rate and amount, reduce the polarization, decrease the internal resistance by about 10% and decrease the physical rebound by about 14.5%. The specific capacity of charge and discharge increases by about 1%, the peeling strength increases by about 9.8%, the first effect increases by about 2%, and the cycle life is extended by about 12%. It has a very excellent lithium supplementation effect. Related Articles | Metrics

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Study on removing Al2O3 inclusions in steel by pulsed magnetic fields 2023, 37 (4):  141-150.  Abstract ( 112 )   PDF (5075KB) ( 160 )   Save In order to explore the effect of a pulsed magnetic field on the removal of Al2O3 inclusions in steel, this paper carries out smelting experiments by using an intermediate frequency induction furnace. Then, numerical simulation of the flow field of molten steel and the removal of inclusions of different sizes under the action of the pulsed magnetic field is carried out through the software COMSOL multi-physics field. Combining the numerical simulation results with the experimental results, the removal mechanism of Al2O3 inclusions in steel under the pulsed magnetic field is discussed. The experimental results show that, after the pulsed magnetic field treatment, the total content of Al2O3 inclusions in steel decreases, the percentage of small-sized Al2O3 inclusions decreases, and the percentage of larger-sized Al2O3 inclusions increases, which indicates that the pulsed magnetic field promotes the removal and the collision growth of Al2O3 inclusions. The numerical simulation results show that, when the pulsed magnetic field is applied, upper and lower double circulations form in the molten steel, which promotes the removal of inclusions. The larger the size of inclusions is, the higher the removal efficiency will be. Meanwhile, most of the inclusions are separated to the wall surface, which is consistent with the experimental results. Related Articles | Metrics

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Effect of tool structure on microstructure and properties of an aluminum/steel friction stir welding joint 2023, 37 (4):  151-156.  Abstract ( 123 )   PDF (2251KB) ( 132 )   Save In order to study the effect of different tool structures on the microstructure and mechanical properties of a joint, this paper carries out friction stir welding butt tests on 3 mm 6061 aluminum alloy and 304 stainless steel. The results show that, with the optimization of the tool from a cylindrical one to a conical plus threaded one, the C-type characteristics are more and more obvious. The threaded tool promotes the flow of the material in horizontal and axial directions, and the steel particles of the joint are evenly and finely distributed at the interface. The changing law of microhardness of the three joints in the welding area is similar, and the hardness in the welding area is higher when the conical plus threaded tool is used. The average tensile strength of the joint of the conical plus threaded tool is 197.2 MPa, which is higher than that of the threadless tool. It breaks at the heat affected zone on the aluminum side, and the fracture shows a typical toughness fracture mode. Related Articles | Metrics

Intelligent Technology

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Research on highway traffic accident detection using feature variable selection and long and short-term memory network 2023, 37 (4):  157-165.  Abstract ( 134 )   PDF (2302KB) ( 149 )   Save In order to improve the effectiveness of highway traffic accident detection, according to the changing characteristics of upstream and downstream traffic flow parameters at the occurrence of traffic accidents, this paper constructs a relatively comprehensive set of initial feature variables for traffic accident detection, and filters out important feature variables by using the Random Forest-Recursive Feature Elimination with Cross Validation (RF-RFECV) algorithm. The long and short-term memory (LSTM) network is trained by using significant feature variables as the input, and the hyperparameters of the LSTM network are optimized by a Bayesian optimization algorithm (BOA). Finally, real highway data are used for validation and comparative analysis, and Borderline-SMOTE is used to solve the imbalance of the traffic dataset. The experimental results show that selecting the important feature variables that are more sensitive to traffic accident detection can improve the detection accuracy, and the detection effect of LSTM is significantly better than that of random forest (RF) and support vector machine (SVM). Related Articles | Metrics

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YOLOv5 traffic light detection algorithm combined with attention mechanism 2023, 37 (4):  166-173.  Abstract ( 381 )   PDF (3497KB) ( 526 )   Save Aiming at the problems that the existing traffic light algorithm has poor detection and recognition effect on small targets and occlusive objects, this paper proposes a YOLOv5 detection algorithm based on feature fusion of attention and multi-scale (AM-YOLOv5). Firstly, by introducing a coordinate attention module into the residual block, the feature extraction ability of small targets is improved. Secondly, a four-scale detection layer is designed to improve the detection performance and accuracy of small-scale targets by introducing more shallower features. Finally, aiming at the problem that the introduction of attention and detection layers leads to an increase in the amount of computation and a decrease in speed, the method of replacing partial trunk convolution with distributed displacement convolution is used to simplify the model and improve the speed. The experimental results show that the average accuracy of the proposed algorithm reaches 90.8% in Lara dataset, which is 2.7% higher than that of the classical YOLOv5 algorithm, and the speed reaches 59.9 FPS. In the BDD100K dataset in a complex and harsh environment, the accuracy increases by 3.6%, and the speed reaches 34.8 FPS, which has a good detection effect and can better meet the real-time detection of traffic lights. Related Articles | Metrics

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Construction and application of the emotion recognition corpus for Chinese MOOC review 2023, 37 (4):  174-181.  Abstract ( 153 )   PDF (1704KB) ( 203 )   Save Emotion recognition in online Chinese educational reviews is largely limited by a lack of annotated data. To solve this problem, this paper constructs a Chinese MOOC emotion recognition corpus from 806 college MOOCs in China by combining automatic and manual methods to ensure corpus balance and extensive subject coverage, including a total of 10 340 reviews, of which 5 411 are positive and 4 929 are negative. Firstly, it formulates strategies of corpus collection and pre-processing, annotation specification, annotation system and consistency detection method. Then, a neural network model and an emotion recognition method based on large-scale pre-trained language models are proposed. Finally, the results of emotion recognition are applied to teaching management department and instructors. The corpus lays a data foundation for emotion analysis research of online education reviews, and is of great significance for enabling teaching evaluation and facilitating the intelligent teaching system. Related Articles | Metrics

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A feature description method based on voxel partition in spherical neighborhood space 2023, 37 (4):  182-191.  Abstract ( 106 )   PDF (4448KB) ( 123 )   Save Aiming at low description and stability of 3D feature descriptors in complex interference scenes, this paper proposes a feature description method based on voxel partition in spherical neighborhood space. This method consists of a stable local reference frame (LRF) and a feature descriptor based on voxel expression. For LRF, the Z-axis is calculated through the weighted covariance matrix, the sum of the weighted point cloud projection vectors is taken as the X-axis, and the Y-axis is obtained by the cross multiplication of the two axes. For feature descriptors, the spherical neighborhood is spatially divided, and the voxel label value is determined by judging whether there are points in each spatial voxel. Finally, the feature information of the key points is encoded according to the voxel index. The experiments show that, compared with other descriptors, this method has excellent performance against noise, uneven distribution of point cloud surface, scattered occlusion and other interference, and has good generalization. The registration experiments further verify the effectiveness of this descriptor. Related Articles | Metrics

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Application of TD-LSTM-S model to carbon dioxide concentration prediction 2023, 37 (4):  192-199.  Abstract ( 168 )   PDF (2211KB) ( 186 )   Save To address the problem that traditional prediction models cannot exploit the intrinsic connections among variables of multivariate data, this paper proposes a long and short-term memory (LSTM) neural network model, TD-LSTM-S, which is based on tensor decomposition and sequential least square quadratic programming (SLSQP) optimization. In the model, the data are constructed into tensors and are decomposed and optimized so that the data can retain the intrinsic connections among variables. The SLSQP algorithm is used to optimize the LSTM so that it can effectively use the intrinsic connections among variables to improve the prediction performance of the model. The experimental results show that the proposed TD-LSTM-S model has higher prediction performance than the traditional model. Related Articles | Metrics

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Characteristic optimization method based on maximum information entropy in visual positioning detection 2023, 37 (4):  200-208.  Abstract ( 120 )   PDF (6399KB) ( 315 )   Save In order to improve the ability of mobile robots to perform complex tasks in unknown environments, this paper constructs a visual localization and detection system that combines the concept of maximum information entropy with Simultaneous Localization and Mapping (SLAM). Based on the ORB-SLAM2 detection algorithm, under the premise of uniform distribution, the feature points with the most prioritized information under monocular vision are searched. The first N features with the maximum information entropy are then selected to be re-optimized for fast convergence to achieve high accuracy localization. At the same time, to verify the effectiveness of the algorithm, physical tests are conducted in combination with YOLO-V4 target detection, which can achieve real-time localization and detection in embedded mobile devices. The experimental results show that the localization accuracy of the proposed algorithm in this paper is improved in both TUM and KITTI datasets, and the proposed algorithm is better than the original algorithm in multiple scenarios and devices. Related Articles | Metrics

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Temporal convolutional attention-based network for household electric load disaggregation 2023, 37 (4):  209-216.  Abstract ( 106 )   PDF (2392KB) ( 120 )   Save Aiming at the fact that the accuracy of the traditional deep neural network disaggregation model still cannot meet the actual needs of non-invasive load monitoring, this paper proposes a load disaggregation model based on Temporal Convolutional Attention-based Network (TCAN). The model adopts the sequence-to-point disaggregation method, uses the improved temporal convolutional network as the basis to extract load data characteristics, increases the convolutional kernel sensing field, and obtains more data feature information. The model combines the attention module to extract richer and more valuable feature information, which improves the training efficiency. The experimental results in the UK-dale dataset show that the model has significant improvement in decomposing performance and judging the start-stop state of electrical appliances than the existing disaggregation methods. Related Articles | Metrics

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Blood cell recognition in the residual network based on a multiple attention mechanism 2023, 37 (4):  217-225.  Abstract ( 100 )   PDF (3999KB) ( 123 )   Save In response to low accuracy and slow speed of blood cell recognition in the natural state, this paper proposes a blood cell classification method of the residual network incorporating a multiple attention mechanism. In order to improve the computational speed of the network and enhance the nonlinear representation capability of the model, an attention blending unit module is proposed. In order to improve the representation capability of the model for blood cell features, a multiple attention mechanism is embedded. With an aim to further mitigate network overfitting and enhance the generalization capability of the model, the residual branch structure is optimized. The experimental results show that the model has an accuracy of 95.67% on the blood cell dataset with a parametric number of 13.22 M. In comparison with other networks, the model proposed in this paper has a higher accuracy while maintaining a lower parametric number. Related Articles | Metrics

Electrical and electronic

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Prediction of current control for doubly-fed wind power generation systems based on a two-vector model 2023, 37 (4):  226-234.  Abstract ( 111 )   PDF (5442KB) ( 279 )   Save With an aim to predict current control, this paper proposes a two-vector model to solve the problem of large current fluctuation and torque ripple in the traditional predictive current control model of doubly-fed wind power generation systems. This model performs voltage vector selection twice in one sampling period. The optimal vector of the first stage is used as the initial value of the second stage, and, combined with the action time of the candidate voltage vector, the minimum cost function is calculated. As a result, the range of the candidate voltage vector is expanded and the voltage vector selection is more accurate. The simulation results show that the proposed strategy can achieve effective control of the doubly-fed wind power generation system. At the same time, compared with the vector control and the traditional predictive current control model, the strategy effectively reduces current fluctuation and electromagnetic torque ripple. Related Articles | Metrics

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Research on an improved YOLOv5s self-exploding insulator detection algorithm 2023, 37 (4):  235-244.  Abstract ( 186 )   PDF (3460KB) ( 211 )   Save In the process of insulator defect inspection, it is difficult for traditional algorithms to take into account of detection accuracy and model size at the same time due to complex background. In this paper, an insulator defect detection model based on improved YOLOv5s is proposed. Firstly, a Bottleneck CSP structure and an attention mechanism of lightweight spatial and channel convolution are used to strengthen insulator characteristics and suppress the complex background characteristics. Secondly, an improved BiFPN structure is proposed to achieve multi-scale feature fusion and improve the ability of small object detection. Finally, K-means++ algorithm is used to re-cluster the prior frames, and lightweight GhostC3 and Ghost Conv modules are designed to ensure accuracy of the network and reduce size of the model. The experimental results show that the mAP of the improved algorithm in this paper reaches 92.3% in Insulator2022 dataset, with an increase of 3.6%; the number of parameters reduces by 26.73%, the floating point arithmetic reduces by 23.17%, and the missed detection rate reduces by 5.47%. In the open dataset, the defective insulator mAP reaches 99.5%. All of the evaluation index values are better than those of the mainstream algorithms of Faster-RCNN, SSD, YOLOv3 and YOLOv3-tiny as well as the related algorithms of insulator detection. Related Articles | Metrics

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Comparative analysis and experimental study on the structure of dual stator brushless doubly-fed wind generators 2023, 37 (4):  245-252.  Abstract ( 193 )   PDF (5905KB) ( 250 )   Save Due to the influence of its rotor structure, a brushless doubly-fed generator has a limited magnetic field modulation ability, resulting in its low efficiency and low power density. In order to improve the performance of the generator, this paper proposes a new type of dual-stator brushless doubly-fed wind generator with cage-barrier rotors. Two different topological structure design ideas and assembly schemes are presented, and two different mechanical structures and assembly modes are described. Then, the precise physical models of “moving shaft + front rotor bracket” and “static shaft + housing rear end cover” in the structure are established, and the stress and deformation under rated loads are simulated and compared by using the finite element method. Two prototypes with different structures at a rated power of 50 kW and a rated speed of 360 r/min are developed, and no-load and load experiments are carried out respectively. The research results show that the design ideas of “static shaft double-end support” and “moving shaft + integration design of front rotor bracket” can be extended to other dual stator motors. Related Articles | Metrics

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The high-precision ultrasonic liquid temperature measurement system 2023, 37 (4):  253-259.  Abstract ( 124 )   PDF (2452KB) ( 282 )   Save This paper designs an ultrasonic temperature measurement system for liquid media to achieve rapid and high-precision measurement of liquid temperature. An optimized threshold comparison method is proposed. To more precisely define the end moment of ultrasonic wave propagation, the pulse width of the signal is determined based on the conventional threshold comparison method. At the same time, the TDC structure design based on the tap delay chain is utilized to improve the resolution of time measurement, and the relationship between ultrasonic wave propagation speed and liquid temperature is established to achieve accurate temperature measurement. According to the experimental findings, the system is capable of measuring temperature at a resolution of 0.001 ℃ by reaching the time measurement resolution of 10-12 s, with an average measurement error of 0.008×10-9 s. It also has a faster response speed and a higher sensitivity than conventional thermometers. Related Articles | Metrics

Mathematics·Statistics

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Volume variational formulae for the Calabi geometry of hypersurface and the stability 2023, 37 (4):  260-269.  Abstract ( 124 )   PDF (996KB) ( 258 )   Save This paper firstly investigates the geometric structure of parametrized hypersurface under the Calabi normalization. Then, it is proved that the Calabi geometry of the general parametrized hypersurface is locally equivalent to the canonical Calabi normalization of the graphs of the convex functions. It is also proved that Hessian manifolds can be locally expressed as the typical Calabi geometry of the graphs with the convex functions. For parametrized hypersurface, the first volume variational formula and the second variational formula of the Calabi geometry are established. As a consequence, it is proved that any extreme Calabi surface with non-positive 2-dimensional Gauss curvature is stable, and the affine area functional obtains local maximum on such surfaces. Related Articles | Metrics

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Regional scientific and technological innovation level and total factor productivity of the manufacturing industry: an empirical research based on a spatial panel data model 2023, 37 (4):  270-276.  Abstract ( 130 )   PDF (956KB) ( 102 )   Save Based on the analysis of the mechanism of scientific and technological innovation affecting total factor productivity of the manufacturing industry, this paper uses provincial panels to construct an index system to reflect the development level of regional scientific and technological innovation, and empirically tests the effect of scientific and technological innovation on total factors of the manufacturing industry. The research shows that scientific and technological innovation plays a significant role in promoting total factor productivity of the manufacturing industry. By dividing the region into eastern, central and western regions, this paper then finds that the impact of scientific and technological innovation on total factor productivity of the manufacturing industry has regional heterogeneity, showing a greater promoting role in the central and western regions than in the eastern region. Further, a spatial panel data model is constructed to show that this significantly promoting role lies not only in local areas, but also in the surrounding areas through the spatial spillover effect. Finally, according to the research conclusion, this paper puts forward countermeasures and suggestions to improve the level of scientific and technological innovation to enhance total factor productivity of the manufacturing industry. Related Articles | Metrics

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Effects of habitat loss patterns on the outcome of competitive system invasion 2023, 37 (4):  277-285.  Abstract ( 112 )   PDF (2549KB) ( 166 )   Save In recent years, most studies on the impact of habitat loss and biological invasion on species diversity have focused on a single factor. In fact, events such as habitat loss and biological invasion do not always occur independently, but may coexist and have a combined effect on species coexistence. This study focuses on a three-species competition system after biological invasion to explore the survival conditions of species under different invasion modes, and introduces the habitat loss process after invasion to clarify the impact mechanism of different habitat loss modes on the outcome of the invasion. It uses a spatially explicit cellular automaton simulation method to carry out the innovative research, fully considers statistical randomness and spatial relevance, and analyzes the simulation results. The results show that: When the loss process tends to be anthropogenic, such as the loss pattern of large farmland ponds and road villages, habitat loss will intensify the diffusion and competitive invasion of alien species. When the loss process tends to be naturally destructed, such as random loss or gradient pattern loss, habitat loss will inhibit the diffusion and competitive invasion of species, thus alleviating the harm of native species invasion to some extent. Finally, the effect of habitat loss on the outcome of competitive diffusion invasion is opposite to that of diffusion invasion and competitive invasion. The results of this study provide inspirations and theoretical guidance for the research and policy implementation of biological invasion control. Related Articles | Metrics

Energy, power and environment

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Optimal structure design of exhaust manifolds of internal combustion engines in a natural gas generator under transient fluid-structure coupling 2023, 37 (4):  286-293.  Abstract ( 116 )   PDF (3956KB) ( 104 )   Save Nowadays, the development of efficient and clean low-carbon energy equipment is the main direction of energy and power development in China. Currently, diesel fuel is generally used as the main fuel for generator units, which has higher particulate matter and hydrocarbon content in internal combustion engine diesel emissions compared with natural gas. After the conversion of the automotive diesel engine into a gas-fired internal combustion engine, the exhaust temperature is higher due to its long operating time. In order to further improve the fuel economy and increase the reliability of an exhaust manifold, this article optimizes the exhaust manifold structure by means of a 3D simulation modeling. Before the modification, the exhaust manifold of the original machine is designed with a short diameter in order to take into account of the performance at a low speed. In addition, the exhaust back pressure at a speed of 1 500 r/min is high, which is not suitable for the modified gas powered internal combustion engine. Through GT-Power one-dimensional numerical calculation, gas consumption in a single working condition can be reduced by optimizing the pipe diameter. After the manifold diameter increases from 35 mm to 40 mm, the power of the whole machine increases by 2.3 kW, the pump gas loss reduces by 5 kPa, and the gas consumption rate reduces by 1.7 g/(kW·h). Secondly, by using the inverse modeling method and Fluent UDF module, a transient fluid-structure coupling simulation model is established, and the heat transfer coefficient of the fluid domain wall and the heat deformation of the exhaust manifold area at three time points in five working cycles are calculated. The coupling time points are 180° CA, 540° CA and 720° CA. Based on the numerical results, two structural optimization methods for exhaust manifolds are proposed. The first optimization plan removes part of the stiffeners and connecting plates, and the second plan adds two stiffeners. After the heat load analysis and comparison in the transient process of temperature discharge, the results show that although the first scheme can save material use, the thermal stress is not obviously improved. The second scheme of adding reinforced bars can further reduce the amount of thermal deformation. The maximum thermal stress at the three coupling calculation points reduces by 2.7% compared with the results before the modification, and the amount of thermal deformation at the bending and joint of the tube reduces by 10%. The stiffener structure can restrain the deformation of the manifold to some extent. Overall, the optimization schemes are beneficial to improving the service life of the exhaust manifold and meeting the design requirements of gas-fired internal combustion engines. The modeling and optimization methods in this article can provide reference and guidance for the design of reformulated exhaust manifolds for gas-fired internal combustion engines. Related Articles | Metrics

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The cusp-mutation theory in determining traffic state in the adjacent weaving segments 2023, 37 (4):  294-303.  Abstract ( 86 )   PDF (5415KB) ( 157 )   Save Traffic variation tendency has a significant impact on the efficiency and safety of urban traffic operations. To explore and improve its traffic efficiency in adjacent weaving segments (AWS) near a ramp of an urban rapid road, this paper proposes an adaptive traffic state discrimination method combining the cusp-mutation theory and Gaussian-mixture model. With an aim of reducing traffic congestion, the optimal combination matching of the cusp-mutation theory and Gaussian-mixture model is discussed to establish a more practical determining model for the actual traffic operation status of the AWS in this paper. This method focuses on the AWS of urban rapid roads, takes the AWS as the research object, and studies the Gaussian-mixture distribution of the average speed and time occupancy under different spacing conditions. At the same time, it takes the advantage of the cusp-mutation theory to analyze the trend of traffic variation in the AWS and uses the Gaussian-mixture model to identify and classify the congestion distribution pattern of the traffic operation status in the AWS. Determining traffic is the theoretical basis, which provides necessary theoretical and technical support for traffic control in the AWS by establishing the traffic flow model and the state discrimination model of AWS. Besides the integration of the cusp-mutation theory and the Gaussian-mixture model, a method for estimation of traffic state parameters is proposed to solve the problem that the congestion state discrimination criteria of the AWS are affected by the weaving interval distance. Through investigating the actual road structure and traffic volume, the real-time traffic operation status and its changes under the condition of an increasing traffic flow are simulated and analyzed using the VISSIM traffic simulation software for the selected AWS at the interchange of Haixia Road and Sigongli Road in Chongqing. It is verified that the cusp-mutation theory is applicable to discriminating operating status of the AWS, and the critical state of traffic is a key to evaluating level of traffic congestion, which changes along with different distances between the two weaving segments. The experimental results show that the critical congestion velocity varies significantly when the spacing between two AWS is less than 150 m, and stabilizes when it is greater than 150 m. The critical congestion rate varies significantly when the spacing between two AWS is less than 200 m, and stabilizes when the spacing is greater than 200 m. This study highlights the importance of an adaptive traffic state discrimination method that combines the cusp-mutation theory and the Gaussian-mixture model to study the traffic flow in the AWS. The effectiveness of the proposed method in analyzing traffic state change is also demonstrated experimentally, which helps to study traffic control and traffic flow in the AWS, provides a strong theoretical basis for analyzing the trend of traffic state change in the AWS, and offers valuable insights into the effect of different spacing conditions on the critical congestion speed and rate. The study can help traffic managers to formulate better traffic control strategies and improve the traffic efficiency of the AWS. Related Articles | Metrics

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Short-term wind power interval prediction based on Aquila optimization algorithm 2023, 37 (4):  304-314.  Abstract ( 113 )   PDF (3428KB) ( 246 )   Save To solve the problems that the pre-set parameters of the random forest algorithm depend on empirical settings and the randomness of wind power deterministic prediction is difficult to describe, this paper proposes an interval prediction method based on a combination of the Aquila optimizer (AO), Random Forest (RF) and nonparametric kernel density estimation (NKDE). Firstly, the AO is combined with RF for power single-point value prediction, on which basis NKDE is introduced for wind power interval prediction to provide more information for grid scheduling and optimal allocation. According to the proposed method, a comparison experiment is then conducted on the wind speed data derived from a wind farm in Rudong County, Jiangsu Province using WRF model forecasts. The experiments show that the AO-RF-NKDE interval prediction model can provide wind power fluctuation intervals with a better comprehensive performance, which has a higher application value for reducing wind power uncertainty and weakening grid fluctuation. Related Articles | Metrics

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Study on liquid phase oxidation leaching of chromite by microwave enhanced roasting 2023, 37 (4):  315-320.  Abstract ( 104 )   PDF (1837KB) ( 104 )   Save In order to shorten the high pressure oxidation leaching time of chromite in a high concentration of sodium hydroxide aqueous solution, this paper pretreats chromite ore by microwave roasting. The effect of microwave roasting on the structure and leaching of chromite is investigated. The results show that, after microwave roasting at 800 ℃, a large number of cracks appear on the surface of chromite, the structure is no longer dense, and the particle size of the chromite greatly reduces. Under the reaction conditions of a temperature of 240 ℃, O2 partial pressure of 2.2 MPa, NaOH-to-ore ratio of 4∶1, stirring speed of 700 r/min and NaOH concentration of 60 wt.%, the chromium leaching rate reaches over 97.81% after a reaction time of 120 min. The results show that using microwave roasted chromite for pressure oxidation leaching can greatly improve chromium leaching efficiency. Related Articles | Metrics

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A scheduling algorithm of natural gas pipeline network based on subspace projection 2023, 37 (4):  321-328.  Abstract ( 93 )   PDF (1821KB) ( 89 )   Save This paper establishes a mathematical model for optimizing the operation of the natural gas pipeline network in Chongqing with the maximum production capacity of the system as the objective function, while considering the constraints like pipeline strength, booster stations, dehydration stations, purification plant operation parameters and hydrogen sulfide content. Meanwhile, this paper proposes a natural gas scheduling algorithm based on subspace projection to solve this natural gas scheduling model, which uses an iterative method to find an approximate solution in the subspace, significantly reducing the computational complexity and thus quickly scheduling the natural gas pipeline network. Combined with the case of Chongqing natural gas pipeline network scheduling for calculation and verification, it can be seen that the proposed algorithm can meet the operating conditions of Chongqing natural gas pipeline network and ensure the maximum production capacity. The proposed algorithm is also more effective and practical, which guarantees safe production and efficient operation of Chongqing natural gas pipeline network Related Articles | Metrics

“23rd International Conference of Fluid Power and Mechatronic Control Engineering” Special Column

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Biomechanical effect evaluation for a passive arm-assisted exoskeleton 2023, 37 (4):  329-338.  Abstract ( 268 )   PDF (3737KB) ( 266 )   Save This paper proposes a set of test methods for passive arm-assisted exoskeleton, and evaluates the designed passive arm-assisted exoskeleton. Firstly, a theoretical model of human lifting motion is constructed, and characteristics of the elbow angle and moment are analyzed. Then, repeated lifting and weight-holding standing experiments are designed to respectively measure the electromyographic signals of the main arm muscle groups and the metabolic level of the human body to verify the auxiliary effect of the passive exoskeleton on transportation. In the repeated lifting experiments, wearing the exoskeleton significantly reduces the muscle activity of the arms during elbow flexion. In the weight-holding standing experiments, when a man holds something with a weight of 10 kg, energy consumption of the human body reduces by 18.86% on average; when a man holds something with a weight of 15 kg, energy consumption reduces by 23.87% on average. In addition, the changing trend implies that the assisting effect of the exoskeleton is positively correlated with the changing trend of the material with a weight range of 5 to 15 kg in the weight-holding standing state. The proposed method can effectively evaluate the performance of the passive arm exoskeleton. The passive arm-assisted exoskeleton effectively reduces the muscle activity of the arms during repeated lifting and elbow flexion, and reduces the overall metabolic cost of the wearer during weight-holding standing. Related Articles | Metrics

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Investigations on heat transfer characteristics in helical coils under the effects of secondary flow vortices 2023, 37 (4):  339-347.  Abstract ( 136 )   PDF (4136KB) ( 165 )   Save In order to improve heat transfer efficiency of the traditional helical coil, the turbulent flow and heat transfer characteristics of a helical coil under uniform heating of water flowing are experimentally and numerically investigated. The main study focus is on the characteristics of local secondary flows in the axial cross-section perpendicular to the coil and their heat transfer effects between the working fluid water and the heated coil wall. It is found that the absolute value of the Nusselt number of the simulation results match well with the experimental results although local Nusselt number oscillation of the coil is discovered only in the experiments rather than in the simulation results. The reason may be that, though the secondary flows indeed exist and evolve irregularly along the coil axis, their effects on local heat transfer are almost negligible since the secondary flow velocity is relatively too small compared with the main flow velocity. To further confirm the characteristics of the secondary flows in the coil, a 360°external reverse loop is added to each 180°coil turning. It is found that the additional reverse loops increase the velocity of the secondary flows reflowing into the main coil and increase the number of the secondary flow vortices in a cross-sectional area. Related Articles | Metrics

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Characteristic analysis and structure optimization of labyrinth flow channels with different internal tooth structures 2023, 37 (4):  348-358.  Abstract ( 132 )   PDF (5960KB) ( 114 )   Save With continuous improvement, drip irrigation technology has gradually been widely used in the field of agricultural planting. The emitter is the core component of the drip irrigation system, and the main reason hindering the development of the emitter is that the structure of the emitter flow path is narrow, which increases the amount of its irrigation time. Simultaneously, blockage occurs. The article reports a study on the flow characteristics and clogging causes of labyrinth channels with different internal tooth structures under different conditions, aiming to find a channel structure with better anti-clogging performance. This paper uses FLUENT numerical simulation analysis to compare the velocity and turbulent kinetic energy characteristics of three different internal tooth structures (rectangular, triangular and arc) and different internal tooth combinations (single internal teeth, double internal teeth and combined internal teeth), and, combined with the DPM stochastic orbital model, studies the migration under three different pressure conditions (0.06 MPa, 0.11 MPa and 0.15 MPa) and with three different particle sizes (0.05 mm, 0.085 mm and 0.130 mm). The indicators of the hydraulic performance of the emitter are the turbulent kinetic energy of the flow channel, the intensity of the low-turbulent kinetic energy area or low-velocity area in the flow velocity, and the distribution of the dissipation rate of the turbulent kinetic energy of the flow channel; the indicators of the anti-clogging performance of the emitter are based on the fluid-solid. The particle migration path and particle residence time in the flow channel are obtained from the two-phase (DPM stochastic trajectory model) analysis, and the influence of the parameters of the labyrinth flow channel with different internal tooth structures on the performance of the emitter is studied under numerical simulation. Combined with the above analytic conclusions, a labyrinth flow channel with internal teeth is designed with better performance. The results show that, among different combinations of internal teeth, the combined structure is the best flow channel structure, and the flow channel has the greatest strength in the low turbulent kinetic energy region or low velocity region, indicating that the hydraulic performance of the flow channel is better. However, the migration paths of the large-size particles are fewer, the residence time of the particles in the flow channel is shorter, and the particles are easy to flow out of the flow channel as the water flows so that the flow channel is not easy to be blocked. This study finds that the size of the internal tooth area affects the anti-clogging performance of the internal tooth channel. Combined with the optimal internal tooth combination, the optimal internal tooth structure is triangular (the reference index is consistent with the above-mentioned data). Based on the above research conclusions, it can be seen that the optimal flow channel is a combined triangular internal tooth. On the basis of this research (the reference index is consistent with the above-mentioned data), the improved flow channel not only increases the ability of the fluid to maintain the turbulent state in the flow channel, but also significantly improves the flow velocity and turbulent kinetic energy, making a better particle migration trajectory and better anti-blocking effects. In conclusion, this study provides valuable insights into the flow characteristics and clogging causes of drippers with different internal tooth structures, and identifies flow channel structures with better clogging resistance. The results of this study may be useful for the design and optimization of dripper structures in irrigation systems. Related Articles | Metrics