Table of Content

12 July 2023, Volume 37 Issue 6 Previous Issue    Next Issue

Vehicle engineering

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Research on nonlinear braking vibration of high-speed trains considering wheel-rail creep 2023, 37 (6):  10-19.  Abstract ( 170 )   PDF (5699KB) ( 64 )   Save The braking system is one of the key components of high-speed trains.It is also the important guarantee for the safe operation of a train.With the continuous increase of high-speed train operation speed and the increasingly complex operating environment,safety issues of the braking system have received widespread attention.During the braking process,relative friction is generated between the brake pads and brake discs,and the friction torque reduces the wheel rotational speed through the wheel-disc relative torsion,eventually generating the braking force between the wheel and the rail to achieve train braking.However,the disc-pad friction can lead to unstable vibration of the braking system,resulting in abnormal wear of brake pads,the fracture of brake clamps and the shortening of the service life of brake discs.In addition,the unstable vibration of brake discs and pads can exacerbate wheel-rail interactions,worsen wheel-rail contact relationships,and weaken the stability of train systems,then posing a threat to the safety of train services.Therefore,it is urgent to study the friction vibration mechanism and methods for suppressing unstable vibration of high-speed train braking systems. Most of the braking system models in the existing researches only include braking devices while neglecting the adhesion relationship between the wheel and the rail when the train brakes.During train actual service,wheel-rail adhesion can lead to more complex vibration of high-speed train braking systems.Therefore,in order to more realistically reproduce the dynamic response of the braking system in the braking process,this paper establishes a three-degree-of-freedom nonlinear dynamic model of a high-speed train braking system considering Polach wheel-rail creep.The correctness of the model is also verified through train line tests.This model not only considers the wheel-disc relative torsion,but also adopts a wheel-rail creep model that can more accurately reflect the impact of wheel-rail interaction on the braking system.Based on this model,the nonlinear dynamic operation of the braking system is studied at relatively low speeds,and the difference between Polach wheel-rail creep model and the linear wheel-rail creep model is analyzed.Further,the effects of average creep rate and rail surface conditions on vibration of the braking system are explored.Finally,the interaction mechanism between the wheel-rail adhesion and the disc-block friction are revealed. The results show that,compared with the linear wheel-rail creep model,Polach wheel-rail creep model,which is related to train running speeds,is more in line with the actual service conditions.With the increase of the average creep rate and the deterioration of the rail surface condition,the chaotic motion is more likely to occur and the vibration of the brake system is more complex.Based on the above analysis results,it can be concluded that the adhesion state of the wheel-rail is greatly influenced by the average creep rate and the rail surface condition.The average creep rate is the initial creep state during braking,which directly affects the magnitude of wheel-rail creep force.The rail surface conditions determine the upper limit of the wheel-rail adhesion coefficient,which directly affects the variation of the creep force.Then,the wheel-disc torsion is affected by the creep force,resulting in a change in the vibration form of the brake disc,ultimately affecting the nonlinear vibration of the braking system through disc-block friction.Similarly,the nonlinear friction of the disc-block interface affects the wheel-rail relative slip through wheel-disc torsion,ultimately affecting the wheel-rail adhesion state. Related Articles | Metrics

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Variable step function compensation method for suppressing harmonic current in vehicle EPS-PMSM 2023, 37 (6):  20-28.  Abstract ( 111 )   PDF (4986KB) ( 67 )   Save Aiming at the harmonic current of a permanent magnet synchronous motor steered by vehicle electric power at a low speed caused by dead time and on-voltage drop of a three-phase inverter,this paper proposes a variable step function compensation method for α and β axis voltages.Firstly,in order to obtain a more accurate three-phase current polarity to avoid compensation voltage perturbation,a current averaging method is proposed to replace the first-order low-pass filter.Secondly,in order to improve the quality of the output waveform and eliminate the zero-current clamping caused by inverter dead time of the motor at a low speed and light load,a variable trapezoid function is proposed for α and β axis voltage compensation.Finally,the harmonic current of a permanent magnet synchronous motor for vehicle electric power steering (EPS-PMSM) is evaluated based on the numerical simulation under three working conditions,including uncompensation,traditional average voltage compensation and variable step function compensation.The results show that,under the condition of a low speed and light load of the motor,compared with the traditional average voltage compensation method,the variable step function compensation method further reduces the total harmonic current distortion by about 23.42%,and eliminates the zero-current clamping. Related Articles | Metrics

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Research review on a magnetorheological mount of automotive powertrain 2023, 37 (6):  29-38.  Abstract ( 215 )   PDF (1850KB) ( 85 )   Save As a semi-active mount,a magnetorheological mount is used in the automotive powertrain vibration isolation system,and its performance directly affects the ride comfort.The structural design,control algorithm and the performance simulation analysis method of the magnetorheological mount are expounded.The performance characteristics of the magnetorheological mount under different structures are introduced,and the influence of structural design and optimization on its vibration isolation performance is highlighted.The advantages and disadvantages of several common control algorithms in control effect are compared and analyzed.It is pointed out that the magnetorheological mount controlled by PID algorithm combined with other algorithms has better vibration isolation performance.The advantages and disadvantages of bond graph theory analysis and finite element simulation analysis are compared.The research status of magnetorheological mounts is summarized.The shortcomings of single mode structure and single algorithm control are pointed out,and some problems encountered in the performance simulation analysis are pointed out.The development prospect of magnetorheological mounts is prospected. Related Articles | Metrics

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Anti-rollover control methods of an SUV based on adaptive multi-population genetic optimization 2023, 37 (6):  39-47.  Abstract ( 146 )   PDF (2694KB) ( 64 )   Save In order to prevent SUV rollover,this paper proposes a linear quadratic regulator (LQR) method optimized by the adaptive multi-population genetic algorithm to generate differential braking.A three-degree-of-freedom vehicle dynamics model is established,including lateral,yaw and roll motions.According to vehicle status parameters,an LQR anti-rollover controller is designed to control the braking force of the four wheels.Then,an adaptive multi-population genetic algorithm is proposed to optimize the LQR parameter matrix.Furthermore,the rollover performance of the SUV is simulated under some typical conditions.The results show that this method can effectively prevent SUV rollover.Compared with the controller with manual parameter adjustment,the LQR anti-rollover controller can more quickly control and stablize the yaw rate,rollover indexes and the roll angle,which improves active safety of the SUV.In addition,the optimized anti-rollover control has good robustness under different conditions. Related Articles | Metrics

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Fixed-time sliding mode control of the steer-by-wire system with fault tolerance 2023, 37 (6):  48-57.  Abstract ( 137 )   PDF (3545KB) ( 69 )   Save Aiming at the angle control problem of the steer-by-wire system with motor torque fault,this paper firstly establishes an equivalent dynamic model and a torque fault model of the steer-by-wire system.Then,in order to improve the response speed and fault-tolerance performance of the system,a non-singular fixed-time sliding mode controller with fault-tolerance performance is designed with the ideal front wheel angle as the tracking target.Besides,aiming at the problem that it is difficult to determine the upper bound of the disturbance and fault in the controller,an adaptive scheme is given by combining the nonsingular sliding mode surface.Finally,based on Lyapunov stability condition,the fixed-time stability of the closed-loop control system is proved.The co-simulation results of Simulink and Carsim show that the proposed control method can make the closed-loop steering system have a faster response speed,and it can still effectively maintain the stability of the system and ensure the tracking accuracy of the steering angle in the case of torque failure and saturation. Related Articles | Metrics

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The fuzzy control strategy of HEV regenerative braking through the particle swarm optimization algorithm 2023, 37 (6):  66-74.  Abstract ( 150 )   PDF (3619KB) ( 74 )   Save In order to improve the recovery rate of HEV braking energy and ensure the braking effect,this paper proposes the particle swarm optimization algorithm to optimize the fuzzy control strategy of HEV regenerative braking.Firstly,considering both braking effect and braking energy recovery,a multi-segment braking force distribution curve between the front and the rear wheels is designed to distribute more braking force to the front wheels as much as possible.Then,by using the fuzzy controller,mechanical braking force and regenerative braking force distributions of the front wheels are achieved.Finally,in order to further improve the braking energy recovery and ensure the braking effect of the vehicle,the braking effect and the braking energy recovery are taken as the optimization objective function,and the fuzzy rules are optimized by using the particle swarm optimization algorithm.The results show that,under LYDC driving conditions,the designed multi-segment front and rear wheel braking force distribution curves and the fuzzy rules optimized by the particle swarm optimization algorithm can effectively improve the regenerative braking energy recovery and meet the requirements of the braking effect. Related Articles | Metrics

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Road feeling feedback and active correction control of the steer-by-wire system 2023, 37 (6):  75-84.  Abstract ( 277 )   PDF (1550KB) ( 49 )   Save Aiming at the problem that the steer-by-wire (SBW) system cannot directly transmit road feeling to the driver through the steering wheel,this paper establishes a dynamic model of steering wheel modules and resetting torque,and designs a comprehensive road feeling simulation control algorithm for the power assist torque,the limit torque,the friction torque and the damping control torque.Considering the defects of insufficient steering wheel correction when the vehicle runs at a low speed,an active correction control algorithm is designed and a specific formula is derived.Finally,the simulation and the hardware-in-the-loop test results show that the designed road feeling simulation control algorithm meets the requirements of light low-speed steering and clear high-speed road feeling,and reduces the positive residual angle of the steering wheel so as to improve the vehicle aligning performance. Related Articles | Metrics

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A temporary road detection method based on an improved Delaunay triangulation 2023, 37 (6):  85-92.  Abstract ( 129 )   PDF (3330KB) ( 45 )   Save For temporary roads guided by traffic cones,this paper proposes an improved Delaunay triangulation algorithm to implement road detection in this special scene.YOLOv4 algorithm is used to recognize traffic cones in the images.Besides,the image information and the point cloud information of the traffic cones obtained by laser radar are fused,and the fused traffic cone information is Delaunay triangulated to propose a Delaunay triangulation filtering algorithm and the local optimization strategy,which calculates the weight and the loss value of the Delaunay triangulation in real time according to the change of road conditions and effectively filters out the triangular edges whose sum of the loss values fails to match the conditions.The proposed method reduces the noise constraint in the Delaunay triangulation and effectively implements the rapid planning and real-time updating of lane lines and drivable paths.The real vehicle experiment results show that the average time consumption of the proposed method is 35.4 ms.The absolute trajectory error of the detected path is 0.2 m,and the accuracy is 97%.Compared with the traditional Delaunay triangulation method,the improved method meets the real-time demand,reduces the path detection error,and improves the path detection accuracy. Related Articles | Metrics

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A confluence method for intelligent vehicles at a highway on-ramp in mixed traffic 2023, 37 (6):  93-101.  Abstract ( 181 )   PDF (3883KB) ( 66 )   Save Vehicle confluence at a highway on-ramp area is a difficult problem for the decision system of intelligent vehicles,among which the mixed confluence of human-driven vehicles and intelligent vehicles has been one of the most complicated cases.In order to improve the vehicle traffic efficiency in the confluence area and reduce the emissions of pollutants,by analyzing the influence of vehicle lane distribution on traffic efficiency,this paper innovates an intelligent vehicle merging model based on Deep Q-Network (DQN) algorithm,and improves the optimization objective function of the algorithm according to the average road space-time utilization.At the same time,according to the real data set,the driving style of vehicles is defined and the mixed traffic simulation scene is established.Finally,the experimental results show that,under three different traffic flow conditions,compared with the Intelligent Driver Model (IDM) model,the DQN-based main lane vehicle change model improves the overall traffic efficiency of the ramp confluent area by 23.10% on average.Fuel consumption per vehicle reduces by an average of 12.7%.The emission of all kinds of polluting gas per vehicle reduces by about 10% to 20%. Related Articles | Metrics

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Optimization of engine intake pipe parameters by combining neural and genetic algorithms 2023, 37 (6):  102-109.  Abstract ( 107 )   PDF (2505KB) ( 44 )   Save Taking the structural parameters of an intake pipe as the research object,this paper proposes an integrated optimization by combining neural and genetic algorithms to improve the power and economic performance of the engine.By building a one-dimensional performance simulation model of the engine,the boundary parameters of the model are modified in combination with the external characteristic performance curve,and the quantitative effects of the length and diameter of the intake pipe on the engine performance are studied.Further,based on the neural network genetic algorithm,the optimal parameters of the intake pipe applicable to different working conditions are analyzed.The results show that the torque increases significantly in an engine speed range of 4 000 to 5 500 r/min,while the specific fuel consumption reduces significantly in an engine speed range of 5 000 to 7 000 r/min.Under the optimization target set in this paper,the maximum torque optimization rate increases by 12.08% and the specific fuel consumption reduces by 1.51%.Based on the one-dimensional system simulation model and the neural network genetic algorithm,the structural parameters of the intake pipe are optimized.The system integration method can provide data basis for the setting of variable intake parameters. Related Articles | Metrics

"Intelligent robot perception, Planning and Application Technology" special column

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Self-adaptive double Re-ID technique for close pedestrian tracking of unmanned vehicles 2023, 37 (6):  110-118.  Abstract ( 180 )   PDF (3988KB) ( 95 )   Save The perception system of intelligent autonomous vehicles,serving as the frontend input,plays a crucial role in the functional application of these vehicles.However,existing sensors have blind spots in their field of view,leading to a lack of sensitivity towards close-range targets,which can potentially cause safety issues.Thus,effective recognition and tracking of near-distance targets have become pressing issues to address.This paper proposes an adaptive dual recognition technique that employs the current mainstream target detectors and trackers and combines them with re-identification technology for real-time tracking of nearby pedestrians.This method compensates for the shortcomings of current deep learning algorithms that are heavily dependent on datasets,improves the versatility of the algorithms,expands the perception range of autonomous vehicles,and enhances their commercial value.Actual vehicle experiments demonstrate that the algorithm can continuously track pedestrians from far to near and vice versa,while maintaining a stable pedestrian ID. Related Articles | Metrics

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An RGB-D camera relocalization method aided by ellipsoidal semantic objects 2023, 37 (6):  119-128.  Abstract ( 128 )   PDF (3112KB) ( 45 )   Save This paper proposes an RGB-D relocalization method based on ellipsoidal semantic objects.Firstly,in the process of camera tracking,this paper initializes the observation object in a single frame through combining the depth point cloud,and describes the observed map object by an ellipsoid.An object-level semantic map represented by an ellipsoid is constructed by associating map objects and the corresponding target detection results by using an object common view.Then,the camera is relocated based on the location of the map object.Finally,Iterative Closest Point (ICP) cloud registration algorithm is used to further optimize the camera pose.The experimental results on the OR10 data set show that the relocation method achieves a high relocation success rate in a large parallax environment where the bag-of-words (BoW) and random ferns (FERNS) methods perform poorly.In addition,the proposed algorithm has a similar running time to the above two methods. Related Articles | Metrics

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Path planning of substation inspection robots based on an improved grey wolf optimizer 2023, 37 (6):  129-135.  Abstract ( 118 )   PDF (2157KB) ( 87 )   Save To further improve the efficiency of intelligent substation inspection robots,this paper proposes an improved grey wolf optimizer for inspection robot path planning,aiming at the problem that the traditional grey wolf optimizer is prone to local optima and has a low convergence efficiency.Based on the impact of different parameters of the grey wolf optimizer on the algorithm performance,a simulation analysis is conducted on the performance of the optimizer in path planning for intelligent substation inspect robots based on the convergence function and population weight parameters respectively after the mixed improvement of the optimizer is conducted.The simulation results show that the mixed improved grey wolf optimizer not only shortens the optimized path of the intelligent substation inspection robot but also improves its path planning efficiency. Related Articles | Metrics

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Research on SLAM accuracy of particle filter optimized by multi-strategy whale algorithm 2023, 37 (6):  136-145.  Abstract ( 129 )   PDF (3497KB) ( 37 )   Save Aiming at the problem that the resampling of the traditional particle filter algorithm leads to particle scarcity and the need to increase the number of particles to improve estimation accuracy,this paper proposes a recombined particle filter algorithm based on multi-strategy whale algorithm optimization.First of all,through the bubble net feeding mechanism of the whale algorithm,the optimal particle guides the particle set to move to the high likelihood region so as to improve the estimation accuracy.Secondly,the particle density near the optimal particle is calculated in real time.When the density is greater than the set random search threshold,the Levy flight strategy is introduced to expand the searching space.When the threshold is greater than the maximum density,the iteration number is adjusted adaptively.Finally,the resampling stage recombines the retained particles after screening and the remaining particles into new particles to increase particle diversity.The simulation experiments are conducted to verify the performance of the improved algorithm in simultaneous localization and mapping (SLAM).The results show that the proposed algorithm has a higher accuracy and better robustness than the standard algorithm does. Related Articles | Metrics

Machinery and materials

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Study on dynamic characteristics of the high-speed gear transmission system 2023, 37 (6):  153-160.  Abstract ( 153 )   PDF (5721KB) ( 144 )   Save Aiming at the impact vibration of the high-speed gear transmission system in the working process,with the gear on the three high-speed shafts in a gear transmission system as the research object,this paper establishes a multi-stage parallel shaft gear transmission system model with bearings by ANSA finite element pre-processing software.The nonlinear dynamic characteristics of spiral bevel gears and involute spur gears in the complex gear train system are studied through transient dynamic simulation and modal analysis.The results show that,in the high-speed gear transmission system,elastic deformation of the shaft,bearing clearance and dynamic excitation from other gear pairs will lead to abnormal phenomena such as unbalanced load,an increase of meshing force,deterioration of meshing stability and low-frequency resonance of the gear pairs Related Articles | Metrics

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Study on preparation and performance of new dry-mixed waterproof mortar 2023, 37 (6):  161-167.  Abstract ( 182 )   PDF (1402KB) ( 36 )   Save In order to improve physical,mechanical and durability properties of dry-mixed waterproof mortar,this paper studies the effects of polycarboxylate superplasticizer,silicone hydrophobic agent,renewable dispersive latex powder and cellulose ether on the physical and mechanical indexes and durability of dry-mixed waterproof mortar through orthogonal tests.Then,range analysis is performed on the results to obtain the optimal mix proportion.XRD and SEM techniques are used to analyze the composition and microstructure of both the mortar with the best mix proportion and the mortar of the reference group without admixture.The results show that the hydration products generated by the former are less than those by the latter,but the microstructure is greatly improved.Compared with those of the mortar of the reference group,all properties of the mortar with the best mix proportion are significantly improved,the water-retention rate increases by 11.7%,and the consistency loss rate reduces by 7.4%.Although the flexural and compressive strength of the mortar slightly reduces,the 14 d tensile bond strength significantly increases to 278.3%,and the impermeability and shrinkage properties are also significantly improved. Related Articles | Metrics

Information and computer science

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An improved semantic segmentation network and its application by using cross-gated fusion 2023, 37 (6):  187-195.  Abstract ( 203 )   PDF (3115KB) ( 60 )   Save This paper proposes an improved semantic segmentation network based on cross-gated fusion due to poor segmentation accuracy caused by small and weak defects such as broken grids,scratches and black spots on the surface of solar cells.Firstly,to address the problem of small defects in solar cells,a cross-gated fusion module is proposed,which selectively fuses multi-scale information in the network through the gating mechanism.The module makes full use of low-level detailed information and high-level semantic information,enhances the feature representation of small defects,and improves the ability to obtain full-text information by combining the context module.Secondly,to further solve the problem of weak edge information of solar cell defects,the PointRend module is introduced to sample the points on the defect edge,and an adaptive subdivision strategy is implemented for the uncertain points on the edge to realize fine segmentation of the defect edge.Finally,the experimental results show that the mIoU of the proposed method on the data set of solar EL component batteries reaches 65.53%.Compared with the existing semantic segmentation algorithm,the proposed method can effectively refine the target boundary and handle small and weak defects better. Related Articles | Metrics

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An infrared pedestrian detection algorithm based on attention and feature fusion 2023, 37 (6):  196-203.  Abstract ( 127 )   PDF (4498KB) ( 96 )   Save Aiming at the problems of high false detection rate of pedestrians in a complex background,a low detection accuracy of dense pedestrians and missed detection of pedestrians with small distant targets in the infrared image pedestrian detection algorithm,this paper proposes an infrared pedestrian detection algorithm based on attention and feature fusion module-you only look once (AFFM-YOLO).Firstly,an attention feature extraction module (AFEM) is proposed,which is integrated into the backbone of the network to suppress irrelevant background information and enhance the extraction of key feature information.Secondly,a multi-scale feature fusion module (MFFM) is designed,which is embedded in the neck of the network to realize the effective fusion of feature information at different scales.Then,a large-scale detection layer is added to strengthen the feature extraction ability of the target detector for pedestrians with small targets in a long distance.Finally,the experimental results on FLIR data set show that the average accuracy of AFFM-YOLO reaches 89.1,which is 2.4% higher than that of the baseline algorithm YOLOv5.AFFM-YOLO has a better performance,with a significant improvement of the pedestrian detection effect in infrared images. Related Articles | Metrics

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Prediction of remaining useful life of rolling bearings by using TCN-HS 2023, 37 (6):  204-211.  Abstract ( 121 )   PDF (2529KB) ( 57 )   Save A rolling bearing is a key component of a rotating machinery,and the accurate prediction of its remaining useful life (RUL) can help maintenance personnel make maintenance plans in time,prolong equipment working time and ensure safety.Because it involves complex physical process to accurately establish a model of bearing degradation process through mathematical modeling,the data-driven method based on deep learning becomes a popular alternative method.This paper proposes an improved temporal convolutional network with hybrid dilated convolution and self-adaptive slope thresholding (TCN-HS) function to predict the RUL of rolling bearings.This model uses hybrid dilated convolution (HDC) to solve the problem of grid effect,and uses self-adaptive slope thresholding functions to further screen features.In order to verify the effectiveness of TCN-HS model,experiments are carried out based on PHM2012 bearing data set.The results show that the improved method upgrades the model and the prediction results are accurate. Related Articles | Metrics

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A radar echo extrapolation method based on multi-scale mixed attention LSTM 2023, 37 (6):  212-221.  Abstract ( 259 )   PDF (5211KB) ( 89 )   Save Aiming at the problem of low prediction accuracy of short-approaching weather based on radar echo images,this paper proposes a multi-scale mixed attention long short-term memory network model.On the basis of long short-term memory network,on the one hand,an auxiliary branch is introduced to enhance the extraction of global image information.On the other hand,a mixed attention feature extraction module is designed to extract the fine-grained and coarse-grained information of the image data.The experimental results show that the proposed network model is superior to 9 models such as Conv-LSTM,Pred-RNN and RAP-Net on the two indexes of HSS and CSI.Especially,compared with those of the Pred-RNN model in the case of 5 dBz,20 dBz and 40 dBz,the HSS index of the proposed model is improved by 1.02%,2.46% and 7.94% respectively,while the CSI index is improved by 0.54%,2.29% and 4.91%,indicating obvious improvement. Related Articles | Metrics

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COVID-19 image classification based on multi-channel dual attention networks 2023, 37 (6):  222-231.  Abstract ( 136 )   PDF (3592KB) ( 71 )   Save Aiming at the problems of a certain false negative rate and long time consumption in the detection of novel coronavirus pneumonia (COVID-19) by reverse transcription polymerase chain reaction,this paper proposes a multi-channel dual attention network (MDA-Net) based on deep transfer learning to detect lung images.Firstly,under the framework of deep transfer learning,a multi-channel dual attention module is introduced,which utilizes the positional relationship of multiple channels to fuse image features of different scales.Then,the attention mechanism is combined with a lightweight convolutional neural network to expand the MDA-Net receptive field and improve the feature extraction ability of complex and edge regions of the images.Finally,the MDA-Net is tested on different datasets,and the binary-classification task and three-classification task can achieve an average accuracy of 99.25% and 99.39% respectively,showing good classification performance. Related Articles | Metrics

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Multi-information fusion and self-attention identification of phosphorylation sites of SARS-CoV-2 2023, 37 (6):  242-248.  Abstract ( 102 )   PDF (2828KB) ( 30 )   Save The disease caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is threatening people’s health and lives.Identifying phosphorylation sites is an important step in understanding the molecular mechanism of SARS-CoV-2.Due to the limitations of experimental methods,it is very necessary to establish effective prediction models.Therefore,a new SARS-CoV-2 phosphorylation site prediction model,Self-DeepIPs,is proposed.The protein sequence information is converted into digital information using dipeptide composition (DC),enhanced amino acid composition (EAAC),composition,transformation and distribution (CTD) and BLOSUM62.These features are also fused end-to-end,and the mutual information (MI) method is used to remove redundant information.The combination of BILSTM and the self-attention mechanism is used to build a deep learning model to predict the phosphorylation sites of the SARS-CoV-2.Then,five-fold cross-validation is used to test the model.The ACC and AUC values on the training set reach 83.62% and 91.70% respectively,and the ACC and AUC values on the independent test set reach 82.56% and 91.23% respectively.The experimental results show that the Self-DeepIPs method proposed in this paper can effectively identify SARS-CoV-2 phosphorylation sites. Related Articles | Metrics

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Application of an improved deep echo network in air conditioning load forecasting 2023, 37 (6):  249-258.  Abstract ( 123 )   PDF (1312KB) ( 51 )   Save In view of the problems such as too much randomness of input weights,the large number of intermediate states and the determination of key parameters by trial and error in the deep echo state network,this paper uses the grey correlation degree to calculate the correlation between the attributes to determine the input weights.Then,the clustering algorithm is used to simplify the intermediate states,and the coordinate rotation method is used to improve the algorithm by searching for the optimal depth network layers and the number of the reserve pools.Through the experiment of UCI standard data set,the improved algorithm in this paper improves the accuracy and speed of the prediction.Finally,the improved deep echo network is used to predict the air conditioning load of the cigarette factory.Through the internal and external conditions of the current moment,the low prediction efficiency caused by the periodic fluctuation of the load data is solved.The air conditioning load of the next moment is accurately predicted in time,and the operation strategy of the chiller is adjusted in advance to achieve the purpose of air conditioning energy saving. Related Articles | Metrics

Mathematics·Statistics

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Practical synchronization of two-layer networks with parameter mismatch 2023, 37 (6):  268-278.  Abstract ( 116 )   PDF (3169KB) ( 31 )   Save This paper designs a dynamic event trigger pinning controller to solve the synchronization problem of two-layer networks with parameter mismatch and resource waste in the control process.According to Lyapunov stability theory,the sufficient criterion in the matrix form for synchronization with the inter-layer error bound in two-layer networks and the estimation formula for the inter-layer synchronization error bound are derived,which proves that the dynamic event triggering mechanism does not exist Zeno phenomenon.Two numerical examples are used to verify the correctness of the theory in this paper.The effects of parameter mismatch and control gain on the trigger times of the controller and various error bounds are discussed.It is concluded that the controller can reduce the number of updates,save resources and have robustness. Related Articles | Metrics

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Dynamic analysis and simulation of a hyperchaotic system with exponential terms 2023, 37 (6):  279-284.  Abstract ( 142 )   PDF (4664KB) ( 63 )   Save Based on the four-dimensional hyperchaotic systems,this paper studies the dynamical behaviors of a kind of four-dimensional hyperchaotic systems with exponential terms through numerical simulation and theoretical analysis.Dissipativity and the dimension of such a system,Poincaré cross-section,Lyapunov exponent,initial sensitivity,bifurcation diagrams and other properties are found.Bifurcations and chaotic phenomena of four-dimensional hyperchaotic systems are revealed,and valuable conclusions are drawn.This chaotic system has wide application potential and can be used to protect data security and information encryption. Related Articles | Metrics

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Research on influencing factors of departing passenger aggregation in a terminal 2023, 37 (6):  285-293.  Abstract ( 112 )   PDF (1981KB) ( 72 )   Save To clarify the influencing factors and formation mechanism of departing passenger aggregation in a terminal and improve the operational safety and efficiency of the terminal,this paper improves the DEMATEL-AISM by applying partial order set theory to overcome empirical and uncertain threshold determination in the traditional joint modeling.The importance ranking and correlation of the influencing factors are investigated by combining causality-centrality,factor weighting diagrams and antagonistic hierarchical topology diagrams to conduct an in-depth analysis of the causes of passenger aggregation in the terminal.The practicality of the method is also verified by using a major airport in southwest China as an example.The research results show that flight schedule change,extreme weather and peak passenger flow are at the top of the antagonistic hierarchical topology diagram,and the corresponding weights based on the sum of the absolute values of the centrality-causality are 0.16,0.11 and 0.08 respectively,which are the most direct factors influencing the departing passenger aggregation in the terminal.Besides,terminal power supply facilities,passenger flow and aircraft mechanical failures at the bottom of the model are the most fundamental factors.The study shows that it is necessary to improve service awareness and guarantee capabilities of the airport and related entities to cope with large-scale terminal passenger gatherings. Related Articles | Metrics

Energy, power and environment

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Modeling and simulation analysis of air inlet flow in fuel cells 2023, 37 (6):  301-307.  Abstract ( 228 )   PDF (2851KB) ( 64 )   Save When the load current of a proton exchange membrane fuel cell changes,its inappropriate air inlet flow will result in oxygen starvation and reduce the output efficiency of the cell.In this way,a model of the air supply system is built,and the traditional PI control,fuzzy control and fuzzy PI control strategies are used to control the air inlet flow respectively.The difference between the actual and ideal air inlet flow of the cathode is taken as the input of the controller.The voltage of the air compressor is adjusted to control its speed,and then the air inlet flow is controlled to achieve closed-loop control.Taking the peroxide ratio change curve with step current as the observation object,the three control strategies are simulated and analyzed.The simulation results show that the three control strategies can shorten the original control time from 1.5 s to 0.5 s,in which the overshoot of the fuzzy control is the smallest.The energy consumption of the air compressor after fuzzy PI control shows the most significant decrease,which is 1.02% lower than that of the feedforward control. Related Articles | Metrics

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Research on thermal management of heat dissipation component arrangement for on-board PEMFC 2023, 37 (6):  308-316.  Abstract ( 128 )   PDF (3758KB) ( 71 )   Save Based on the heat dissipation requirement of on-board proton exchange membrane fuel cells (PEMFC) under different operating conditions and at different ambient temperatures,this article mainly studies the influence of the arrangement sequence of heat dissipation components on the coolant temperature and output voltage.A dynamic model of the thermal management system for an on-board PEMFC is established using the Matlab/Simulink simulation platform,and the correctness of the model is verified by the vehicle mounted system test.Then,in the two different ambient temperature ranges of 0-10 ℃ and 30-40 ℃ respectively,the on-board PEMFC operates under different conditions,including slow and sudden changes of the load power.Under the above two operating conditions,the change regulations of the coolant temperature and the output voltage of the on-board PEMFC are analyzed under different arrangement sequences of the cooling tank and the radiator,which helps to select different arrangement modes of the cooling components of the thermal management system under different operating conditions. According to the analysis,following results are obtained.Firstly,during the operation of the on-board PEMFC under different operation conditions,different arrangement orders of the cooling components,such as the cooling water tank and the radiator,will directly affect the changes of the corresponding data,like both the inlet and the outlet temperature of the coolant,the temperature difference between the inlet and outlet coolant,and the output voltage.When the ambient temperature changes,if the load power change is relatively uniform,which means that the vehicle runs at a slow or a uniform change in speed,the arrangement sequence of the heat dissipation components (the cooling water tank in the front and the radiator in the rear) is more reasonable,under which condition it is more likely to improve the performance of the fuel cell and maintain the appropriate temperature of the coolant.Accordingly,if the load power change is sharp,which means that the vehicle works at a relatively fast or a sharp change in speed,the arrangement sequence of the heat dissipation components is opposite to the above to achieve a better performance of the fuel cell and keep the requested temperature of the coolant,which means the radiator in the front and the cooling water tank in the rear. Secondly,with other conditions being the same,when the ambient temperature changes in a certain range,such as 0-10 ℃ or 30-40 ℃,the temperature of both the inlet and the outlet of the coolant,and their temperature difference are studied.The research finds that the on-board PEMFC at a high ambient temperature between 30 ℃ and 40 ℃ has a higher temperature at the coolant inlet and outlet,and the their temperature difference than that at a lower ambient temperature between 0 ℃ and 10 ℃.Concretely,at the high ambient temperature range between 30 ℃ and 40 ℃ for the on-board PEMFC,the coolant inlet and outlet temperatures at the cooling loop are higher,the temperature difference between the coolant inlet and outlet is smaller,and the output voltage of the PEMFC thermal management system is higher than those at the low ambient temperature between 0 ℃ and 10 ℃. Thirdly,under the same working condition,different arrangement orders of the cooling water tank and the radiator of the on-board PEMFC thermal management component do not affect the increasing or decreasing trend and the degree of the coolant inlet and outlet temperatures,the temperature difference between the coolant inlet and outlet,or the output voltage of the on-board PEMFC thermal management system at different temperature intervals. Related Articles | Metrics

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Tensor parallel factor analysis and recognition methods of flame images 2023, 37 (6):  317-324.  Abstract ( 120 )   PDF (4462KB) ( 43 )   Save The correct recognition of flame combustion state is a prerequisite for maintaining stable combustion.However,the existing methods have a low intellectual level,strong subjectivity and difficulty in the recognition of the combustion state.Therefore,in order to improve the accuracy of recognition,this paper proposes a flame image recognition method based on tensor decomposition.According to the distribution characteristics of the flame pixels in the RGB color space model,the ascending dimension of the image sequence is constructed into a three-dimensional tensor,and,on this basis,the parallel factor analysis method is used to identify the flame images.The analysis results show that,compared with the traditional regional recognition and feature fusion method of single flame images,the flame image tensor is decomposed directly,which not only finds the relationship between the flame image sequences,but also retains more information to a greater extent to improve the accuracy of image recognition.Compared with the theoretical value,the average error of the new method is within 0.5%,and the accuracy is more than 99.5%.It provides reference for continuous flame image recognition. Related Articles | Metrics

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Influence of inlet humidity on the output performance of proton exchange membrane fuel cells 2023, 37 (6):  325-331.  Abstract ( 156 )   PDF (3703KB) ( 45 )   Save In order to explore the influence of inlet humidity of a Proton Exchange Membrane Fuel Cell (PEMFC) on its output performance,this paper builds a PEMFC analysis model based on COMSOL Multiphysics and Matlab platform.Then,the polarization curve of PEMFC is obtained and the output performance is analyzed.The analysis results show that increasing the inlet humidity is helpful in improving the water content and conductivity of the proton exchange membrane,reducing the ohmic impedance,and increasing the output voltage and power of the cell.The analysis results are also helpful in understanding the influence law of the inlet humidity on the output performance of fuel cells,which provides guiding significance for the practical application of PEMFC. Related Articles | Metrics

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Research on the building algorithm of FSAC track map 2023, 37 (6):  332-339.  Abstract ( 112 )   PDF (3734KB) ( 33 )   Save Aiming at competition items of straight-line acceleration,figure-eight circle and high-speed tracking of Formula Student Autonomous China (FSAC),this paper proposes a cone barrel map construction algorithm based on the fusion of monocular camera and combined inertial guidance.YOLOv3 is used to detect the type of the cone barrel,monocular camera ranging and combined inertial guidance positioning are used to determine the position of the cone barrel,and an improved K-nearest neighbors (KNN) algorithm is used to filter the obtained cone barrel.The experimental results show that,compared with Markov Random Field (MRF),the accuracy of the proposed algorithm increases by 4.3%,the recall rate increases by 2.9%,and the average error of the cone barrel position reduces by 52.8%,which can be used as a reference for the mapping of driverless sensing and positioning.The proposed algorithm also solves the problem of FSAC formula racing map construction well,and provides judgment basis for decision planning of FSAC formula racing. Related Articles | Metrics