Articles in press have been peer-reviewed and accepted, which are not yet assigned to volumes /issues, but are citable by Digital Object Identifier (DOI).
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2024, 38(3): 231-239.
doi: 10.12299/jsues.23-0199
Abstract:
By using the field-route coupling method, the causes and main components of the high frequency radial electromagnetic force characteristic frequency of permanent magnet synchronous motor were studied. The generation mechanism and harmonic characteristics of harmonic current were analyzed by analytical method, and verified by numerical simulation. The characteristic frequency distribution of high frequency radial electromagnetic force was analyzed by means of the magnetomotive force permeability method and Maxwell tensor method. The air gap magnetic field obtained by finite element calculation was decomposed in time and space, and the high frequency radial electromagnetic force generated by magnetic field interaction was calculated by Maxwell tensor method. The results show that the high frequency radial electromagnetic force of PMSM driven by frequency conversion is mainly generated by the interaction between the harmonic magnetic field and the stator fundamental magnetic field introduced by the harmonic current of the frequency converter, which has certain guiding significance for the research of PMSM.
By using the field-route coupling method, the causes and main components of the high frequency radial electromagnetic force characteristic frequency of permanent magnet synchronous motor were studied. The generation mechanism and harmonic characteristics of harmonic current were analyzed by analytical method, and verified by numerical simulation. The characteristic frequency distribution of high frequency radial electromagnetic force was analyzed by means of the magnetomotive force permeability method and Maxwell tensor method. The air gap magnetic field obtained by finite element calculation was decomposed in time and space, and the high frequency radial electromagnetic force generated by magnetic field interaction was calculated by Maxwell tensor method. The results show that the high frequency radial electromagnetic force of PMSM driven by frequency conversion is mainly generated by the interaction between the harmonic magnetic field and the stator fundamental magnetic field introduced by the harmonic current of the frequency converter, which has certain guiding significance for the research of PMSM.
2024, 38(3): 240-249.
doi: 10.12299/jsues.23-0190
Abstract:
Traditional machining techniques often result in damage to the aluminum honeycomb. In order to improve the surface quality of aluminum honeycomb machining, the numerical and simulation models of cutting force in ultrasonic-assisted machining of aluminum honeycomb were established. The influence of mesh size on simulation results was investigated to determine an appropriate mesh size. Furthermore the cutting forces and surface morphology were analyzed for different machining parameters. After a thorough evaluation, a mesh of 0.2 mm was chosen for the simulation. The results show that there is a clear reduction in machining damage with increasing the feed rate, spindle speed, and cutting width values. This conclusion can provide reference for mathematical model, simulation and experiment of ultrasonic-assisted machining of aluminum honeycomb.
Traditional machining techniques often result in damage to the aluminum honeycomb. In order to improve the surface quality of aluminum honeycomb machining, the numerical and simulation models of cutting force in ultrasonic-assisted machining of aluminum honeycomb were established. The influence of mesh size on simulation results was investigated to determine an appropriate mesh size. Furthermore the cutting forces and surface morphology were analyzed for different machining parameters. After a thorough evaluation, a mesh of 0.2 mm was chosen for the simulation. The results show that there is a clear reduction in machining damage with increasing the feed rate, spindle speed, and cutting width values. This conclusion can provide reference for mathematical model, simulation and experiment of ultrasonic-assisted machining of aluminum honeycomb.
2024, 38(3): 250-256.
doi: 10.12299/jsues.23-0216
Abstract:
In order to improve obstacle avoidance accuracy of intelligent wheelchair, a control algorithm of intelligent wheelchair based on fuzzy PID control was proposed. The kinematics model of intelligent wheelchair was established, and the intelligent wheelchair control system based on Fuzzy PID control was designed on the basis of traditional PID control method. Matlab was used to construct simulation tests, the fuzzy controller was designed and constructed in Simulink, and the obstacle avoidance performances of traditional and fuzzy PID control were simulated. The experimental results show that the control algorithm can optimize the obstacle avoidance error of intelligent wheelchair, and it has advantages of small overshoot, fast response, and higher accuracy compared with the traditional PID control algorithm.
In order to improve obstacle avoidance accuracy of intelligent wheelchair, a control algorithm of intelligent wheelchair based on fuzzy PID control was proposed. The kinematics model of intelligent wheelchair was established, and the intelligent wheelchair control system based on Fuzzy PID control was designed on the basis of traditional PID control method. Matlab was used to construct simulation tests, the fuzzy controller was designed and constructed in Simulink, and the obstacle avoidance performances of traditional and fuzzy PID control were simulated. The experimental results show that the control algorithm can optimize the obstacle avoidance error of intelligent wheelchair, and it has advantages of small overshoot, fast response, and higher accuracy compared with the traditional PID control algorithm.
2024, 38(3): 257-263.
doi: 10.12299/jsues.23-0212
Abstract:
Passenger boarding and alighting time is an important part of the dwelling time and operation diagram of urban rail transit trains, and is also a vital link that affect the operation efficiency and safety of rail transit lines. In this paper, the passenger boarding and alighting process was divided into two independent processes. Based on survey data, the influencing factors of the maximum passenger flow and the average boarding and alighting time were analyzed. Additionally, estimation submodel of the maximum passenger flow and the average boarding and alighting time of passengers were established. On this basis, the estimation model of train boarding and alighting time for rail transit stations was constructed. Taking Shanghai rail transit station as an example, the analysis showed that the deviation between the measured values of boarding and alighting time and the estimated value of the model is within 11.89%, which verified the effectiveness and practicability of the model. The research results have important practical value for improving the matching degree between the actual and planned boarding and alighting time of rail transit trains, enhancing train stopping efficiency, and ensuring passenger boarding and alighting safety.
Passenger boarding and alighting time is an important part of the dwelling time and operation diagram of urban rail transit trains, and is also a vital link that affect the operation efficiency and safety of rail transit lines. In this paper, the passenger boarding and alighting process was divided into two independent processes. Based on survey data, the influencing factors of the maximum passenger flow and the average boarding and alighting time were analyzed. Additionally, estimation submodel of the maximum passenger flow and the average boarding and alighting time of passengers were established. On this basis, the estimation model of train boarding and alighting time for rail transit stations was constructed. Taking Shanghai rail transit station as an example, the analysis showed that the deviation between the measured values of boarding and alighting time and the estimated value of the model is within 11.89%, which verified the effectiveness and practicability of the model. The research results have important practical value for improving the matching degree between the actual and planned boarding and alighting time of rail transit trains, enhancing train stopping efficiency, and ensuring passenger boarding and alighting safety.
2024, 38(3): 264-271.
doi: 10.12299/jsues.23-0210
Abstract:
A target recognition method based on curve coordinate transformation was proposed to address the challenge of misidentification in existing automatic emergency braking (AEB) systems under curved conditions. The geometric information of the road model could be reflects through sensors, the curve coordinate transformation method was used to locate the position of the main vehicle and the target vehicle, the relative distance between vehicles were calculated, and the dangerous target vehicle was determined by using the logic gate restriction method. A longitudinal collision avoidance control strategy combining the Honda algorithm and TTC algorithm were proposed to address the traditional collision avoidance algorithms based on the safe distance model or time-to-collision (TTC) algorithm, which cannot balance the safety and comfort issues during the braking process. Using the TTC algorithm as a forward collision warning strategy, and the autonomous emergency braking strategy was designed based on the optimized Honda algorithm. The simulation results show that the proposed method based on curve coordinate transformation can accurately calculate the distance between the main vehicle and the target vehicle, accurately and efficiently identify dangerous target vehicles. The fusion algorithm based on the collaborative control of the safety distance algorithm and TTC algorithm can effectively avoid longitudinal car following collisions, and take into account the safety and comfort of the emergency braking process.
A target recognition method based on curve coordinate transformation was proposed to address the challenge of misidentification in existing automatic emergency braking (AEB) systems under curved conditions. The geometric information of the road model could be reflects through sensors, the curve coordinate transformation method was used to locate the position of the main vehicle and the target vehicle, the relative distance between vehicles were calculated, and the dangerous target vehicle was determined by using the logic gate restriction method. A longitudinal collision avoidance control strategy combining the Honda algorithm and TTC algorithm were proposed to address the traditional collision avoidance algorithms based on the safe distance model or time-to-collision (TTC) algorithm, which cannot balance the safety and comfort issues during the braking process. Using the TTC algorithm as a forward collision warning strategy, and the autonomous emergency braking strategy was designed based on the optimized Honda algorithm. The simulation results show that the proposed method based on curve coordinate transformation can accurately calculate the distance between the main vehicle and the target vehicle, accurately and efficiently identify dangerous target vehicles. The fusion algorithm based on the collaborative control of the safety distance algorithm and TTC algorithm can effectively avoid longitudinal car following collisions, and take into account the safety and comfort of the emergency braking process.
2024, 38(3): 272-277.
doi: 10.12299/jsues.23-0195
Abstract:
A virtual simulation training platform based on Unity3D trackside signaling equipment was developed, and three main functional modules of three-dimensional display, animation demonstration and interactive evaluation were designed. Firstly, Autodesk Revit was used to model the trackside signaling equipment in detail, and the C# scripting language was used in the Unity3D engine to control the three-dimensional display of the model. Then, the open-source animation component Animator Controller was used to create a multi-scene mission demonstration animation. Finally, the 3D model was spliced and assembled by using the collision detection principle and the mouse drag event, and the equipment replacement process was evaluated. Research result shows that the training platform can overcome problems of low efficiency poor sense of space of two-dimensional drawings of traditional teaching and training, enhance the sense of immersion, meet the needs of maintenance personnel for knowledge training and simulation training, which provides a new means for trackside signal equipment training.
A virtual simulation training platform based on Unity3D trackside signaling equipment was developed, and three main functional modules of three-dimensional display, animation demonstration and interactive evaluation were designed. Firstly, Autodesk Revit was used to model the trackside signaling equipment in detail, and the C# scripting language was used in the Unity3D engine to control the three-dimensional display of the model. Then, the open-source animation component Animator Controller was used to create a multi-scene mission demonstration animation. Finally, the 3D model was spliced and assembled by using the collision detection principle and the mouse drag event, and the equipment replacement process was evaluated. Research result shows that the training platform can overcome problems of low efficiency poor sense of space of two-dimensional drawings of traditional teaching and training, enhance the sense of immersion, meet the needs of maintenance personnel for knowledge training and simulation training, which provides a new means for trackside signal equipment training.
2024, 38(3): 278-283.
doi: 10.12299/jsues.23-0236
Abstract:
Accurate passenger flow forcast is the basis of the optimization of passenger transportation organization and an effective way to improve operational safety and transportation efficiency. Taking the annual passenger flow data of Jiangmen East Railway Station as research object, and the ARIMA time series model and the LSTM neural network model were constructed respectively. From the perspectives of forecast accuracy, calculation speed, error index evaluation, and model adaptability, the differences in passenger flow forecast results of two forecast models were analyzed. The results show that the LSTM model has better forecast accuracy and fitting accuracy, and the ARIMA model has faster calculation speed. This study result can provide significant practical implications for the selection of passenger flow forecast methods.
Accurate passenger flow forcast is the basis of the optimization of passenger transportation organization and an effective way to improve operational safety and transportation efficiency. Taking the annual passenger flow data of Jiangmen East Railway Station as research object, and the ARIMA time series model and the LSTM neural network model were constructed respectively. From the perspectives of forecast accuracy, calculation speed, error index evaluation, and model adaptability, the differences in passenger flow forecast results of two forecast models were analyzed. The results show that the LSTM model has better forecast accuracy and fitting accuracy, and the ARIMA model has faster calculation speed. This study result can provide significant practical implications for the selection of passenger flow forecast methods.
2024, 38(3): 284-290.
doi: 10.12299/jsues.23-0191
Abstract:
In wind energy storage microgrids, accurately predicting the actual output power of wind farms in advance can effectively improve the stability of grid integration regulation. To address the low prediction accuracy of existing models for wind power characteristic parameters, a wind power characteristic parameter prediction method based on improved whale optimization algorithm of extreme learning machine (IWOA-ELM) was proposed. By optimizing the parameters of the extreme learning machine using an improved whale optimization algorithm, a IWOA-ELM wind power characteristic parameter prediction model based on time series was established to predict the characteristic parameters of future wind power. Model performance was evaluated using metrics such as root mean square error and mean absolute error. Experimental results show that the proposed prediction method has a root mean square error of 5.488% and a mean absolute error of 3.72% for wind speed prediction, and a root mean square error of 19.354% and a mean absolute error of 12.46% for wind direction prediction. The prediction accuracy is significantly higher than that of other wind power prediction models such as WOA-ELM, PSO-ELM, BP, and ELM.
In wind energy storage microgrids, accurately predicting the actual output power of wind farms in advance can effectively improve the stability of grid integration regulation. To address the low prediction accuracy of existing models for wind power characteristic parameters, a wind power characteristic parameter prediction method based on improved whale optimization algorithm of extreme learning machine (IWOA-ELM) was proposed. By optimizing the parameters of the extreme learning machine using an improved whale optimization algorithm, a IWOA-ELM wind power characteristic parameter prediction model based on time series was established to predict the characteristic parameters of future wind power. Model performance was evaluated using metrics such as root mean square error and mean absolute error. Experimental results show that the proposed prediction method has a root mean square error of 5.488% and a mean absolute error of 3.72% for wind speed prediction, and a root mean square error of 19.354% and a mean absolute error of 12.46% for wind direction prediction. The prediction accuracy is significantly higher than that of other wind power prediction models such as WOA-ELM, PSO-ELM, BP, and ELM.
2024, 38(3): 291-297.
doi: 10.12299/jsues.23-0189
Abstract:
Aiming at the dewatering of deep excavation pit in complex and thick confined aquifers, relied on an engineering case in Shanghai, the measured data of pumping test before excavation were verified by numerical simulation, the hydrogeological parameters of each aquifer were obtained through the inversion and verification of the measured data. The ground settlement caused by dewatering with the preliminary designed diaphragm wall was predicted by the verified model, and the comparison of groundwater drawdown and ground settlement under four different diaphragm wall depths was analyzed. The results indicate that ground settlement caused by pumping is large with the existed design of the diaphragm wall depths. The greater the depth of the diaphragm wall, the smaller the ground settlement caused by dewatering. When the diaphragm wall depth is greater than the pumping well depth, the variation of the ground settlement caused by dewatering is small. Considering the environmental effects and the diaphragm wall cost, the optimal depth determined is 48.8 m for the diaphragm wall.
Aiming at the dewatering of deep excavation pit in complex and thick confined aquifers, relied on an engineering case in Shanghai, the measured data of pumping test before excavation were verified by numerical simulation, the hydrogeological parameters of each aquifer were obtained through the inversion and verification of the measured data. The ground settlement caused by dewatering with the preliminary designed diaphragm wall was predicted by the verified model, and the comparison of groundwater drawdown and ground settlement under four different diaphragm wall depths was analyzed. The results indicate that ground settlement caused by pumping is large with the existed design of the diaphragm wall depths. The greater the depth of the diaphragm wall, the smaller the ground settlement caused by dewatering. When the diaphragm wall depth is greater than the pumping well depth, the variation of the ground settlement caused by dewatering is small. Considering the environmental effects and the diaphragm wall cost, the optimal depth determined is 48.8 m for the diaphragm wall.
2024, 38(3): 298-303.
doi: 10.12299/jsues.23-0194
Abstract:
In order to minimize energy consumption while maintaining thermal comfort, an indoor thermal comfort system based on wireless sensor network and simplified predicted mean vote (PMV) index was designed. The scatter layout method was used to determine the best measurement nodes of indoor sensors, and the collected data was transmitted to the system through ZigBee communication. In the system, the thermal comfort perception of indoor environment was evaluated by simplified PMV index. Finally, fuzzy control with fuzziness and non-linearity was used to regulate the operation of the air conditioner. The results show that the data collected by the scatter sensor is more stable and accurate. Simplified PMV index can effectively replace the PMV index in evaluating human thermal comfort perception. The thermal comfort system can not only control the indoor environment within the thermal comfort range, but also play a good energy-saving effect.
In order to minimize energy consumption while maintaining thermal comfort, an indoor thermal comfort system based on wireless sensor network and simplified predicted mean vote (PMV) index was designed. The scatter layout method was used to determine the best measurement nodes of indoor sensors, and the collected data was transmitted to the system through ZigBee communication. In the system, the thermal comfort perception of indoor environment was evaluated by simplified PMV index. Finally, fuzzy control with fuzziness and non-linearity was used to regulate the operation of the air conditioner. The results show that the data collected by the scatter sensor is more stable and accurate. Simplified PMV index can effectively replace the PMV index in evaluating human thermal comfort perception. The thermal comfort system can not only control the indoor environment within the thermal comfort range, but also play a good energy-saving effect.
2024, 38(3): 304-312, 327.
doi: 10.12299/jsues.23-0193
Abstract:
The spatial quality of urban waterfront areas is an important indicator of the level of urban development and construction. Traditional research on spatial quality has problems such as limited spatial scale, strong subjectivity, and single research perspective. Based on Open Street Map road data, Baidu Map street views, and Baidu Map point-of-interest (POI) data, combing with machine learning technology, the spatial quality of waterfront area along the Suzhou River in Shanghai was measured. MGWR2.2.1 software was used to establish a multi-scale geographically weighted regression model for influencing factors of spatial quality. The result shows that the western Putuo District, western Changning District, and the north bank of Suzhou River in Jingan District have low spatial quality in the study area, which should be prioritized during optimization. The eastern part of the study area is suitable for improving spatial quality through measures such as planting trees, building pedestrian paths, and opening pedestrian streets, while the western part should focus on developing leisure and consumer industries such as catering, shopping, and entertainment, as well as conjunct them with existing park green space resources, more trees should be planted, pocket parks are also necessary. The study results can provide a reference for optimizing the spatial quality of the Suzhou River waterfront area.
2024, 38(3): 313-320.
doi: 10.12299/jsues.23-0227
Abstract:
Real-time sampling and updating of data to optimize obstacle avoidance strategies for unmanned aerial vehicle (UAV) is an urgent issue in applying deep reinforcement learning (DRL) to collision prevention. In response to this problem, a dynamic obstacle avoidance navigation algorithm based on offline DRL was proposed. The combination of an offline DRL algorithm and velocity obstacle (VO) algorithm was introduced to address the issue of the high real-time interaction data required by online DRL algorithms. Performance enhancement of the offline DRL algorithm was achieved by imposing constraints on policy updates. A reward function based on VO was developed, which could enable the UAV to consider both time consumption and the shortest path while avoiding dynamic obstacles. Simulation verification in a three-dimensional obstacle navigation environment show that this method can surpass online deep reinforcement learning obstacle avoidance algorithms in terms of path length, flight time, and obstacle avoidance success rate. It will effectively address the problem of DRL requiring continuous input of online data for efficient policy updates
Real-time sampling and updating of data to optimize obstacle avoidance strategies for unmanned aerial vehicle (UAV) is an urgent issue in applying deep reinforcement learning (DRL) to collision prevention. In response to this problem, a dynamic obstacle avoidance navigation algorithm based on offline DRL was proposed. The combination of an offline DRL algorithm and velocity obstacle (VO) algorithm was introduced to address the issue of the high real-time interaction data required by online DRL algorithms. Performance enhancement of the offline DRL algorithm was achieved by imposing constraints on policy updates. A reward function based on VO was developed, which could enable the UAV to consider both time consumption and the shortest path while avoiding dynamic obstacles. Simulation verification in a three-dimensional obstacle navigation environment show that this method can surpass online deep reinforcement learning obstacle avoidance algorithms in terms of path length, flight time, and obstacle avoidance success rate. It will effectively address the problem of DRL requiring continuous input of online data for efficient policy updates
2024, 38(3): 321-327.
doi: 10.12299/jsues.23-0197
Abstract:
Most of the existing literature on the problem of positive edge consensus of multi-agent systems has mainly focused on undirected graphs or strongly connected directed graphs. To extend it to the directed networks containing spanning trees, since the Laplacian matrix of a directed network containing spanning trees may be complex, its analysis may become very difficult. Using positive system theory and graph theory, the necessary and sufficient conditions for edge system to achieve positive consensus under a directed network containing spanning trees were given. The results were further optimized by improving the bounds on the eigenvalues of the Laplace matrix, sufficient conditions involving only the number of edge number of the nodal network were obtained. Riccati inequality was solved and a semidefinite programming algorithm was developed to obtain the solution. Finally, the validity of the obtained results was verified by numerical simulation.
Most of the existing literature on the problem of positive edge consensus of multi-agent systems has mainly focused on undirected graphs or strongly connected directed graphs. To extend it to the directed networks containing spanning trees, since the Laplacian matrix of a directed network containing spanning trees may be complex, its analysis may become very difficult. Using positive system theory and graph theory, the necessary and sufficient conditions for edge system to achieve positive consensus under a directed network containing spanning trees were given. The results were further optimized by improving the bounds on the eigenvalues of the Laplace matrix, sufficient conditions involving only the number of edge number of the nodal network were obtained. Riccati inequality was solved and a semidefinite programming algorithm was developed to obtain the solution. Finally, the validity of the obtained results was verified by numerical simulation.
2024, 38(3): 328-333.
doi: 10.12299/jsues.23-0022
Abstract:
Aiming at the problem that traditional cross-efficiency model cannot handle both input and output data containing negative numbers, an integrated cross-efficiency model based on directional distance function and information entropy was proposesed. First of all, the idea of direction distance function was used to deal with negative numbers. Secondly, the complete ranking of decision units was realized by combining cross efficiency. Then, with the help of the variation coefficient of information entropy, a set of public weights for cross-efficiency integration were obtained to avoid the weight deviation of the traditional model and retain the decision information in the evaluation process. Finally, the effectiveness and practicability of the proposed model were verified by a numerical example, and the research scope and application scenarios of the cross-efficiency model were extended.
Aiming at the problem that traditional cross-efficiency model cannot handle both input and output data containing negative numbers, an integrated cross-efficiency model based on directional distance function and information entropy was proposesed. First of all, the idea of direction distance function was used to deal with negative numbers. Secondly, the complete ranking of decision units was realized by combining cross efficiency. Then, with the help of the variation coefficient of information entropy, a set of public weights for cross-efficiency integration were obtained to avoid the weight deviation of the traditional model and retain the decision information in the evaluation process. Finally, the effectiveness and practicability of the proposed model were verified by a numerical example, and the research scope and application scenarios of the cross-efficiency model were extended.
2024, 38(3): 334-340, 348.
doi: 10.12299/jsues.23-0209
Abstract:
At present, intelligent nursing robots for secondary defecation only rinse the bucket with a constant amount of water after defecation, without corresponding cleanliness testing. The remaining feces can easily cause air odor and bacterial growth, and even spread diseases. In response to this, two visual based cleanliness detection methods were proposed: one is to evaluate the cleanliness of the toilet by calculating the proportion of dirty pixels, and the other is to use image template matching method to detect the cleanliness of the toilet. Experimental results show that by using adaptive threshold segmentation to calculate the proportion of dirty pixels, it can effectively overcome the influence of background shadows and accurately distinguish photo groups with different levels of pollution, thus achieving the goal of detecting the cleanliness of the toilet.
At present, intelligent nursing robots for secondary defecation only rinse the bucket with a constant amount of water after defecation, without corresponding cleanliness testing. The remaining feces can easily cause air odor and bacterial growth, and even spread diseases. In response to this, two visual based cleanliness detection methods were proposed: one is to evaluate the cleanliness of the toilet by calculating the proportion of dirty pixels, and the other is to use image template matching method to detect the cleanliness of the toilet. Experimental results show that by using adaptive threshold segmentation to calculate the proportion of dirty pixels, it can effectively overcome the influence of background shadows and accurately distinguish photo groups with different levels of pollution, thus achieving the goal of detecting the cleanliness of the toilet.
2024, 38(3): 341-348.
doi: 10.12299/jsues.23-0241
Abstract:
An improved dragonfly algorithm based on chaotic mapping and differential evolution was proposed to address several issues encountered in the original algorithm. The initial population’s significant randomness and the difficulty in adjusting algorithmic weight parameters led to low convergence accuracy. Additionally, later-stage population contraction restrictions resulted in decreased vitality and slow convergence speed. By employing Tent chaotic mapping, the population’s initial distribution was made more uniform. The alignment, clustering, and inertia weights were adjusted to enhance convergence speed and accuracy. The introduction of the differential evolution algorithm aimed to accelerate convergence at the final stages. Finally, nine test functions were selected for comparative simulation experiments. The results demonstrated that, compared to the basic dragonfly algorithm and the differential evolution dragonfly algorithm, the improved dragonfly algorithm based on chaotic mapping and differential evolution has significantly improved convergence speed and accuracy, avoiding getting stuck in local optima and obtaining stable and reliable global optimal solutions.
An improved dragonfly algorithm based on chaotic mapping and differential evolution was proposed to address several issues encountered in the original algorithm. The initial population’s significant randomness and the difficulty in adjusting algorithmic weight parameters led to low convergence accuracy. Additionally, later-stage population contraction restrictions resulted in decreased vitality and slow convergence speed. By employing Tent chaotic mapping, the population’s initial distribution was made more uniform. The alignment, clustering, and inertia weights were adjusted to enhance convergence speed and accuracy. The introduction of the differential evolution algorithm aimed to accelerate convergence at the final stages. Finally, nine test functions were selected for comparative simulation experiments. The results demonstrated that, compared to the basic dragonfly algorithm and the differential evolution dragonfly algorithm, the improved dragonfly algorithm based on chaotic mapping and differential evolution has significantly improved convergence speed and accuracy, avoiding getting stuck in local optima and obtaining stable and reliable global optimal solutions.
2017, 31(2): 174-177,182.
doi: 10.3969/j.issn.1009-444X.2017.02.016
摘要：
随着纺织印染行业的不断发展,纺织印染废水成分也日益复杂,大大增加了废水处理难度.针对纺织印染废水的来源和水质特点,综述了国内外纺织印染废水处理技术的研究进展,包括物理处理法、化学处理法和生物处理法,分析了各类处理方法的机制、处理效果及其优缺点.对纺织印染废水处理技术的发展前景进行了展望,指出优化组合废水处理工艺可提高纺织印染废水处理效果及综合回用率.
随着纺织印染行业的不断发展,纺织印染废水成分也日益复杂,大大增加了废水处理难度.针对纺织印染废水的来源和水质特点,综述了国内外纺织印染废水处理技术的研究进展,包括物理处理法、化学处理法和生物处理法,分析了各类处理方法的机制、处理效果及其优缺点.对纺织印染废水处理技术的发展前景进行了展望,指出优化组合废水处理工艺可提高纺织印染废水处理效果及综合回用率.
2018, 32(1): 64-67.
doi: 10.3969/j.issn.1009-444X.2018.01.014
摘要：
交通数据质量是影响交通控制方法有效实施的关键因素之一.为进一步提升交通数据的准确性和时效性,对比分析交通预处理方法,采用标准差公式对拉依达准则进行优化,设计一种适用于交通异常数据检测和修复的优化方法,并结合上海城市快速路实际数据对模型有效性和时效性进行检验.结果表明,基于拉依达准则的数据处理优化方法能够有效、实时地检测交通异常数据、改善数据质量,为道路交通状况的监测和预警提供数据支持.
交通数据质量是影响交通控制方法有效实施的关键因素之一.为进一步提升交通数据的准确性和时效性,对比分析交通预处理方法,采用标准差公式对拉依达准则进行优化,设计一种适用于交通异常数据检测和修复的优化方法,并结合上海城市快速路实际数据对模型有效性和时效性进行检验.结果表明,基于拉依达准则的数据处理优化方法能够有效、实时地检测交通异常数据、改善数据质量,为道路交通状况的监测和预警提供数据支持.
2020, 34(3): 238-246.
doi: 10.3969/j.issn.1009-444X.2020.03.006
摘要：
针对机械臂关节空间轨迹规划的时间优化问题,结合机械臂运动约束,提出基于非线性动态改变惯性权重的粒子群优化(NPSO)算法.根据传统3-5-3多项式插值方法,采用改进粒子群算法寻求最短关节运动时间,研究线性递减改变惯性权重(LPSO)算法和NPSO算法的性能,选用NPSO算法完成关节运动时间最优求解.研究结果显示,经时间优化后的3-5-3插值曲线连续光滑且具备更好的运动特性,整体运动时间缩短约26%,证实提出的方法具有可行性.
针对机械臂关节空间轨迹规划的时间优化问题,结合机械臂运动约束,提出基于非线性动态改变惯性权重的粒子群优化(NPSO)算法.根据传统3-5-3多项式插值方法,采用改进粒子群算法寻求最短关节运动时间,研究线性递减改变惯性权重(LPSO)算法和NPSO算法的性能,选用NPSO算法完成关节运动时间最优求解.研究结果显示,经时间优化后的3-5-3插值曲线连续光滑且具备更好的运动特性,整体运动时间缩短约26%,证实提出的方法具有可行性.
2017, 31(4): 371-375.
doi: 10.3969/j.issn.1009-444X.2017.04.017
摘要：
老年人参与各项社会活动,能够延缓衰老,促进身体健康、提高生活质量.通过开展调研探究了老年人的社会参与意愿及其影响因素.调查发现,城市老年人对经济、政治、社区、文化等各项活动的参与意愿都较高,但是多数的参与停留在被动层面;年龄、性别、文化程度、健康状况等因素会影响参与意愿,且不同活动受影响的程度不同;参与意愿会受到现实条件的约束,如照看小孩,料理家务等.
老年人参与各项社会活动,能够延缓衰老,促进身体健康、提高生活质量.通过开展调研探究了老年人的社会参与意愿及其影响因素.调查发现,城市老年人对经济、政治、社区、文化等各项活动的参与意愿都较高,但是多数的参与停留在被动层面;年龄、性别、文化程度、健康状况等因素会影响参与意愿,且不同活动受影响的程度不同;参与意愿会受到现实条件的约束,如照看小孩,料理家务等.
Numerical Simulation Analysis on Air Distribution of Inter-Column Air Conditioning in a Machine Room
2018, 32(3): 244-249.
doi: 10.3969/j.issn.1009-444X.2018.03.009
摘要：
以上海某数据中心机房为研究对象,针对机房服务器散热量大的特点及传统封闭冷通道存在的问题,提出适合该机房的封闭热通道方案.采用计算流体动力学(CFD)模拟的方法,分析机房内封闭热通道与传统封闭冷通道的温度场和速度场分布特性.通过模拟分析得出:大散热量机房列间空调采用封闭热通道形式效果更佳.
以上海某数据中心机房为研究对象,针对机房服务器散热量大的特点及传统封闭冷通道存在的问题,提出适合该机房的封闭热通道方案.采用计算流体动力学(CFD)模拟的方法,分析机房内封闭热通道与传统封闭冷通道的温度场和速度场分布特性.通过模拟分析得出:大散热量机房列间空调采用封闭热通道形式效果更佳.
2021, 35(3): 237-242.
摘要：
针对传统光流法处理视频序列时存在运行效率低及跟踪偏移问题，结合粒子滤波模型提出一种改进光流法的视频目标跟踪技术. 该技术首先通过遍历法搜索运动点，采用质心定位方式捕获目标质心坐标，然后将得到的视频序列进行光流处理，最后经粒子滤波求解质心运动信息，以实现对视频中目标的精确检测与追踪. 在不同场景下对不同数量、不同类型目标进行仿真跟踪试验，并与光流法、ViBe算法及YOLO算法进行比较. 仿真结果表明，该跟踪技术可使目标跟踪的精准率有效提高5.2%，跟踪效率提高13.7%，同时表现出较好的鲁棒性.
针对传统光流法处理视频序列时存在运行效率低及跟踪偏移问题，结合粒子滤波模型提出一种改进光流法的视频目标跟踪技术. 该技术首先通过遍历法搜索运动点，采用质心定位方式捕获目标质心坐标，然后将得到的视频序列进行光流处理，最后经粒子滤波求解质心运动信息，以实现对视频中目标的精确检测与追踪. 在不同场景下对不同数量、不同类型目标进行仿真跟踪试验，并与光流法、ViBe算法及YOLO算法进行比较. 仿真结果表明，该跟踪技术可使目标跟踪的精准率有效提高5.2%，跟踪效率提高13.7%，同时表现出较好的鲁棒性.
2017, 31(1): 90-94.
doi: 10.3969/j.issn.1009-444X.2017.01.019
摘要：
针对我国黄金期货价格预测问题,对影响我国黄金期货价格的5项指标进行灰色关联度分析,得出我国黄金期货价格与美国黄金期货价格之间的关联度最高.建立反向传播(BP)神经网络模型对我国黄金期货价格预测,并与GM(1,1)方法和ARIMA(0,2,1)模型下的预测结果进行对比.结果显示:与后两个模型相比,BP神经网络模型在黄金期货价格预测方面的精确性更高,具有较好的实用价值.
针对我国黄金期货价格预测问题,对影响我国黄金期货价格的5项指标进行灰色关联度分析,得出我国黄金期货价格与美国黄金期货价格之间的关联度最高.建立反向传播(BP)神经网络模型对我国黄金期货价格预测,并与GM(1,1)方法和ARIMA(0,2,1)模型下的预测结果进行对比.结果显示:与后两个模型相比,BP神经网络模型在黄金期货价格预测方面的精确性更高,具有较好的实用价值.
2018, 32(3): 214-220.
doi: 10.3969/j.issn.1009-444X.2018.03.004
摘要：
介绍功能纺织品的分类,分析功能纺织品的开发途径,主要阐述国内现代功能纺织品研究及开发进展,包括纳米光触媒多功能纺织品、防电磁辐射纺织品、超疏水多功能纺织品、阻燃纺织品、防蚊虫纺织品,并指出采用高新技术开发生态安全高附加值多功能纺织品是功能性纺织品的发展趋势.
介绍功能纺织品的分类,分析功能纺织品的开发途径,主要阐述国内现代功能纺织品研究及开发进展,包括纳米光触媒多功能纺织品、防电磁辐射纺织品、超疏水多功能纺织品、阻燃纺织品、防蚊虫纺织品,并指出采用高新技术开发生态安全高附加值多功能纺织品是功能性纺织品的发展趋势.
2017, 31(1): 20-24.
doi: 10.3969/j.issn.1009-444X.2017.01.005
摘要：
介绍了水性工业涂料用丙烯酸酯、聚氨酯、环氧和醇酸4种树脂水性化的最新研究进展.对水性工业涂料的成膜机制进行了总结,并对水分散型、水稀释型等工业涂料的成膜机制做出进一步探讨.总结了水性工业涂料在应用过程中出现的问题并提出解决办法,展望了工业涂料水性化技术面临的挑战与机遇.
介绍了水性工业涂料用丙烯酸酯、聚氨酯、环氧和醇酸4种树脂水性化的最新研究进展.对水性工业涂料的成膜机制进行了总结,并对水分散型、水稀释型等工业涂料的成膜机制做出进一步探讨.总结了水性工业涂料在应用过程中出现的问题并提出解决办法,展望了工业涂料水性化技术面临的挑战与机遇.
2017, 31(2): 126-130.
doi: 10.3969/j.issn.1009-444X.2017.02.007
摘要：
为满足读者的个性化需求,为其提供内容精准推送服务,有效提升期刊论文的传播与交流,设计了《计算机工程》内容精准推送系统.基于期刊采编系统的大量学者信息,利用语义分析及智能分词等技术,将读者—文章—标准关键词库进行匹配和过滤,为潜在读者主动推送相关论文摘要及下载链接.每期推送邮件约7 000封,发送成功率达99％,论文被下载次数较未运行该系统前明显增多,其中下载排名前列的均为已推送论文.科技期刊采用精准推送平台不仅可以为领域学者提供高效便捷的知识服务,也能够增强期刊论文的有效传播力度.
为满足读者的个性化需求,为其提供内容精准推送服务,有效提升期刊论文的传播与交流,设计了《计算机工程》内容精准推送系统.基于期刊采编系统的大量学者信息,利用语义分析及智能分词等技术,将读者—文章—标准关键词库进行匹配和过滤,为潜在读者主动推送相关论文摘要及下载链接.每期推送邮件约7 000封,发送成功率达99％,论文被下载次数较未运行该系统前明显增多,其中下载排名前列的均为已推送论文.科技期刊采用精准推送平台不仅可以为领域学者提供高效便捷的知识服务,也能够增强期刊论文的有效传播力度.
2003, 17(2): 83-86.
doi: 10.3969/j.issn.1009-444X.2003.02.001
Abstract:
2019, 33(3): 283-284,288.
doi: 10.3969/j.issn.1009-444X.2019.03.017
Abstract:
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Chinese Quarterly
Supervisor: Shanghai Municipal Education Commission
Sponsors by: Shanghai University of Engineering Science
Publisher: Editorial Department of Journal of Shanghai University of Engineering Science
Editor-in-Chief: WANG Yansong
Email: xuebao@sues.edu.cn
ISSN1009-444X
CN31-1598/T
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