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TshFNA-Examiner: A Nuclei Segmentation and Cancer Assessment Framework for Thyroid Cytology Image KE Jing1(柯晶), ZHU Junchao2 (朱俊超), YANG Xin1(杨鑫), ZHANG Haolin3 (张浩林), SUN Yuxiang1(孙宇翔), WANG Jiayi1(王嘉怡), LU Yizhou4(鲁亦舟), SHEN Yiqing5(沈逸卿), LIU Sheng6(刘晟), JIANG Fusong7(蒋伏松), HUANG Qin8(黄琴) J Shanghai Jiaotong Univ Sci    2024, 29 (6): 945-957.   DOI: 10.1007/s12204-024-2743-y Abstract （98）      PDF（pc） （2836KB）（61）       Knowledge map    Save Examining thyroid fine-needle aspiration (FNA) can grade cancer risks, derive prognostic information, and guide follow-up care or surgery. The digitization of biopsy and deep learning techniques has recently enabled computational pathology. However, there is still lack of systematic diagnostic system for the complicated gigapixel cytopathology images, which can match physician-level basic perception. In this study, we design a deep learning framework, thyroid segmentation and hierarchy fine-needle aspiration (TshFNA)-Examiner to quantitatively profile the cancer risk of a thyroid FNA image. In the TshFNA-Examiner, cellular-intensive areas strongly correlated with diagnostic medical information are detected by a nuclei segmentation neural network; cell-level image patches are catalogued following The Bethesda System for Reporting Thyroid Cytopathology (TBSRTC) system, by a classification neural network which is further enhanced by leveraging unlabeled data. A cohort of 333 thyroid FNA cases collected from 2019 to 2022 from I to VI is studied, with pixel-wise and image-wise image patches annotated. Empirically, TshFNA-Examiner is evaluated with comprehensive metrics and multiple tasks to demonstrate its superiority to state-of-the-art deep learning approaches. The average performance of cellular area segmentation achieves a Dice of 0.931 and Jaccard index of 0.871. The cancer risk classifier achieves a macro-F1-score of 0.959, macro-AUC of 0.998, and accuracy of 0.959 following TBSRTC. The corresponding metrics can be enhanced to a macro-F1-score of 0.970, macro-AUC of 0.999, and accuracy of 0.970 by leveraging informative unlabeled data. In clinical practice, TshFNA-Examiner can help cytologists to visualize the output of deep learning networks in a convenient way to facilitate making the final decision. Reference | Related Articles | Metrics | Comments（0）

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Motor Imagery Classification Based on Plain Convolutional Neural Network and Linear Interpolation LI Mingai1, 2∗ (李明爱), WEI Lina1 (魏丽娜) J Shanghai Jiaotong Univ Sci    2024, 29 (6): 958-966.   DOI: 10.1007/s12204-022-2486-6 Abstract （64）      PDF（pc） （859KB）（50）       Knowledge map    Save Deep learning has been applied for motor imagery electroencephalogram (MI-EEG) classification in brain-computer system to help people who suffer from serious neuromotor disorders. The inefficiency network and data shortage are the primary issues that the researchers face and need to solve. A novel MI-EEG classification method is proposed in this paper. A plain convolutional neural network (pCNN), which contains two convolution layers, is designed to extract the temporal-spatial information of MI-EEG, and a linear interpolation-based data augmentation (LIDA) method is introduced, by which any two unrepeated trials are randomly selected to generate a new data. Based on two publicly available brain-computer interface competition datasets, the experiments are conducted to confirm the structure of pCNN and optimize the parameters of pCNN and LIDA as well. The average classification accuracy values achieve 90.27% and 98.23%, and the average Kappa values are 0.805 and 0.965 respectively. The experiment results show the advantage of the proposed classification method in both accuracy and statistical consistency, compared with the existing methods. Reference | Related Articles | Metrics | Comments（0）

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Universal Modeling Method of Electrical Impedance Response During Respiration LIU Enkang1 (刘恩康), MA Yixin1, 2∗ (马艺馨), BAI Zixuan1 (白子轩), ZHOU Xing1 (周星), ZHANG Mingzhu1 (张明珠), JIANG Zeyi1 (江泽裔) J Shanghai Jiaotong Univ Sci    2024, 29 (6): 967-978.   DOI: 10.1007/s12204-023-2593-z Abstract （42）      PDF（pc） （1004KB）（25）       Knowledge map    Save In recent years, significant progress has been made through impedance pneumography (IP) in diagnosing pulmonary function. Since there is no need to measure inhalation and exhalation air flow through a pipeline, IP does not increase respiratory resistance and poses no risk of cross-infection, which makes it superior to existing gas flowmeter-based spirometers in clinics. However, the changes in thoracic impedance caused by pulmonary ventilation present significant individual variability. The ratio between pulmonary ventilation volume change (ΔV ) and thoracic impedance change (ΔZ), noted as kΔV/ΔZ , differs among people. IP has to be calibrated for each person by flowmeter-type spirometer before it can be used for quantitative diagnosis. This study aimed to develop a universal model for kΔV/ΔZ using individual parameters such as body height, body mass, body mass index, body fat rate, and chest circumference. The experimental procedure, the way to identify factors for multiple regression via significance analysis and the comparison among different models are presented. This paper demonstrates the possibility of establishing a universal regression model for kΔV/ΔZ , to lay the foundation for the clinical application of IP-based pulmonary function test. Reference | Related Articles | Metrics | Comments（0）

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Application and Prospect of Two-Part Tariff Mechanism in Context of Transmission and Distribution Price Reform REN Xijun, SONG Zhumeng, WANG Bao, YE Yutong, PAN Sijia, WANG Mengyuan, XU Xiaoyuan Journal of Shanghai Jiao Tong University    2024, 58 (10): 1479-1488.   DOI: 10.16183/j.cnki.jsjtu.2023.102 Abstract （412）   HTML （37）    PDF（pc） （1057KB）（458）       Knowledge map    Save In the context of the reform of transmission and distribution tariff mechanism, the drawbacks of the existing two-part tariff system which cannot reasonably reflect the real cost of electricity consumption by power users have gradually emerged. The two-part tariff mechanism is responsible for allocating the space for electricity generation, transmission, distribution and sale tariffs, and regulating the resources of the power system. Therefore, it is urgent to improve the existing two-part tariff mechanism. This paper, focusing on the two-part tariff mechanism, first, introduces the basic theory and billing ratio of the two-part tariff, and studies the method of apportioning transmission and distribution costs based on different load rates and voltage levels. Then, it summarizes the electricity tariff mechanisms such as load rate packages and time-of-use tariffs and the basic tariff mechanisms such as tariff, load adjustments, and improved billing ratios respectively for the collection methods of two-part tariffs. Afterwards, it analyzes the implementation mode of two-part tariff mechanism theory by combining the practical experience of two-part system in the United States, France, Japan, and other foreign countries. Finally, it proposes the future development direction and suggestions of China’s two-part tariff mechanism. Table and Figures | Reference | Related Articles | Metrics | Comments（0）

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Spatio-Temporal Adaptation Assessment of Key Technologies of New Distribution Network Based on 3D Space LIU Dongming, ZENG Qingbin, ZHANG Yongjun, ZHANG Jun, FAN Wei, LIU Yu Journal of Shanghai Jiao Tong University    2024, 58 (10): 1489-1499.   DOI: 10.16183/j.cnki.jsjtu.2023.053 Abstract （210）   HTML （9）    PDF（pc） （3873KB）（188）       Knowledge map    Save In the context of the development of new power systems, a three-dimensional spatio-temporal adaptation assessment model based on grid satisfaction, spatio-temporal resources, and effectiveness improvement is proposed to address the problems of distribution network planning and construction, the adaptability of key distribution network technologies to the space and time in which they are applied, and the difficulty of quantifying application defects. Subjective assignment in hierarchical analysis is improved using continuous interval ordered weighted average operator, and the problem of bias of the single assignment method is solved by the introduction of a subjective-objective combination assignment method constructed by the conflicting correlation among criteria method. The degree of affiliation of each indicator is determined using the fuzzy integrated evaluation method and the evaluation level is then obtained. The case studies show that the proposed method can quantify the degree of fit between the key technologies of the distribution network and the space-time, identify the adaptability of the key technologies to different space-times and the degree of satisfaction of the application of the technologies in different space-times, and reveal the weaknesses of the key technologies of the distribution network, which can help improve the efficiency and effectiveness of the investment in the distribution network and better serve the high-quality development of the economy and society. Table and Figures | Reference | Related Articles | Metrics | Comments（0）

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A Prediction Method of New Power System Frequency Characteristics Based on Convolutional Neural Network LU Wen’an, ZHU Qingxiao, LI Zhaowei, LIU Hui, YU Yiping Journal of Shanghai Jiao Tong University    2024, 58 (10): 1500-1512.   DOI: 10.16183/j.cnki.jsjtu.2023.071 Abstract （374）   HTML （10）    PDF（pc） （2722KB）（501）       Knowledge map    Save In order to solve the problems existing in the traditional frequency analysis method for the frequency analysis of grids with a high proportion of new energy, such as the large amount of calculation, the difficulty of modeling, and the prominent contradiction between the calculation speed and the calculation accuracy, this paper proposes a new frequency characteristic prediction method for the new power system based on convolutional neural network (CNN). First, the main frequency indexes of the power system with a high proportion of new energy under power disturbances are predicted using one-dimensional CNN, including the initial frequency change rate, frequency extremum, and frequency steady-state value. The prediction accuracy is improved by setting reasonable input characteristics and optimizing the parameters of the neural network. Then, the impact of disturbance location and disturbance type is further considered, and the power system characteristic data set containing disturbance information is established by the method of data dimensionality reduction. The input characteristics are constructed by using the principle of three primary channels for reference, and the extended two-dimensional CNN is used to predict the frequency security index, which improves the adaptability of CNN in the frequency analysis of grids with a high proportion of new energy. Finally, the method is verified by an example in the improved BPA 10-machine 39-node model, and the results are compared with the prediction results of the recurrent neural network, which proves that the proposed method has a high accuracy and adaptability. Table and Figures | Reference | Related Articles | Metrics | Comments（0）

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Multi-Energy Flow Modeling and Optimization of Electric-Gas-Thermal Integrated Energy System LI Bingjie, YUAN Xiaoyun, SHI Jing, XU Huachi, LUO Zixuan Journal of Shanghai Jiao Tong University    2024, 58 (9): 1297-1308.   DOI: 10.16183/j.cnki.jsjtu.2022.494 Abstract （3338）   HTML （32）    PDF（pc） （8902KB）（423）       Knowledge map    Save In view of the fact that the conversion of various energy forms such as electricity, gas, and heat in the regional integrated energy system (RIES) seriously affects the economy of the system operation, a mathematical model and an optimization model of RIES energy flow are established to improve the economy of the system and the absorption of renewable energy. First, the mathematical models of all kinds of energy conversion equipment in the system are established to determine the constraints of three kinds of energy transmission networks, namely electricity, natural gas, and heat. Then, taking economic operation as the primary objective, and taking into account the objective function of low carbon emissions and increasing the uptake rate of renewable energy, the RIES multi-energy flow optimization model is constructed. Finally, based on the large-scale integrated energy system, the load side demand response is introduced and the simulation model is established. The simulation results show that the introduction of demand response improves the flexibility of system scheduling, reduces the dependence of the system on energy storage equipment, and effectively reduces the energy consumption cost of users. Table and Figures | Reference | Related Articles | Metrics | Comments（0）

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Shared Energy Storage Multi-Objective Allocation Strategy Considering Integrated Energy Microgrid Access to Active Distribution Network MI Yang, CHEN Yuyang, CHEN Boyang, HAN Yunhao, YUAN Minghan Journal of Shanghai Jiao Tong University    2024, 58 (9): 1309-1322.   DOI: 10.16183/j.cnki.jsjtu.2023.021 Abstract （1793）   HTML （12）    PDF（pc） （4556KB）（171）       Knowledge map    Save In order to give full play to the advantages of shared energy storage in improving economy and energy utilization, while considering the role of multi-energy complementation and coupling of integrated energy microgrids in active distribution networks, a multi-objective optimal allocation strategy of shared energy storage is proposed for the active distribution network connected with integrated energy microgrid. First, the optimization objectives of the economy and voltage stability of the distribution network and the configuration capacity of the shared energy storage are analyzed, the coordinated operation of the source-net-load side multi-flexible resources of the active distribution network is considered, and the active distribution network and the integrated energy microgrid are modeled. Then, the model is solved based on the Pareto optimal multi-objective particle swarm algorithm. Finally, the optimization algorithm of shared energy storage configuration is established in conjunction with the IEEE 33-node distribution system to verify the effectiveness of the proposed configuration strategy. Table and Figures | Reference | Related Articles | Metrics | Comments（0）

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Robust Optimal Scheduling of Micro Energy Grid Considering Multi-Interval Uncertainty Set of Source-Load and Integrated Demand Response MI Yang, FU Qixin, ZHAO Haihui, MA Siyuan, WANG Yufei Journal of Shanghai Jiao Tong University    2024, 58 (9): 1323-1333.   DOI: 10.16183/j.cnki.jsjtu.2023.022 Abstract （1934）   HTML （6）    PDF（pc） （1898KB）（194）       Knowledge map    Save Aiming at the uncertainty of the source and load in micro energy grid, a robust optimal scheduling model considering multi-interval uncertainty set of source-load and integrated demand response is proposed. First, considering the uncertainty of wind power, photovoltaic output and electric, and thermal and cooling loads in the micro energy grid, a multi-interval uncertainty set of source-load is established. Then, in order to fully tap the potential of load side dispatching, an integrated demand response model is established, which includes reducible electric load, transferable electric load, flexible cooling, heating load, and replaceable load, based on which, the uncertainty of integrated demand response is considered. Afterwards, with the lowest dispatching cost of micro energy grid as the objective function, a two-stage robust optimal scheduling model of micro energy network is constructed, which considers the multi-interval uncertainty set of source load and the integrated demand response. The model is solved by the column and constraint generation algorithm, the strong duality theory, and the large M method. Finally, the rationality and effectiveness of the proposed model are verified through the analysis of numerical examples. Table and Figures | Reference | Related Articles | Metrics | Comments（0）

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Ship Pipe Layout Optimization Based on Improved Particle Swarm Optimization LIN Yan1, 2(林焰), BIAN Xuanyi1(卞璇屹), DONG Zongran3(董宗然) J Shanghai Jiaotong Univ Sci    2024, 29 (5): 737-746.   DOI: 10.1007/s12204-022-2530-6 Abstract （148）      PDF（pc） （1456KB）（92）       Knowledge map    Save Ship pipe layout optimization is one of the difficulties and hot spots in ship intelligent production design. A high-dimensional vector coding is proposed based on the research of related pipe coding and ship pipe route features in this paper. The advantages of this coding method are concise structure, strong compatibility, and independence from the gridding space. Based on the proposed coding, the particle swarm optimization algorithm is implemented, and the algorithm is improved by the pre-selected path strategy and the branch-pipe processing strategy. Finally, two simulation results reveal that the proposed coding and algorithm have feasibility and engineering practicability. Reference | Related Articles | Metrics | Comments（0）

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Experimental Study and Numerical Simulation of Evacuation in an Offshore Platform ZHANG Jingjinga (张菁菁), ZHAO Jinchenga, b, c∗(赵金城), SONG Zhensena, b, c (宋振森), DUAN Lipinga, b, c(段立平) J Shanghai Jiaotong Univ Sci    2024, 29 (5): 747-758.   DOI: 10.1007/s12204-023-2629-4 Abstract （100）      PDF（pc） （4007KB）（42）       Knowledge map    Save With the rapid development of marine oil and gas exploitation, the evacuation of offshore platforms has received more attention. First, an experimental investigation of the evacuation process of 120 participants in a real offshore platform is performed, and then simulation results provided by Pathfinder are validated against the measurement results. Second, four typical evacuation scenarios on the platform referring to IMO guidelines are investigated by Pathfinder with the speed values achieved in experiments. The simulation results show that both the utilization of exits and evacuation efficiency of people on the offshore platform need to be further improved. Last, the evacuation routes of people under the four scenarios are optimized, and the improvement of the evacuation performance after the optimization is evaluated by several mathematical indicators. Final results show that the evacuation with the optimized route design prompts the use efficiency of exits and further reduces the evacuation time. The present study provides a useful advice for potentially revising the IMO guidelines in future and provides efficient evacuation strategies for planning the emergency evacuation on offshore platforms. Reference | Related Articles | Metrics | Comments（0）

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Knowledge-Based Curved Block Construction Scheduling and Application in Shipbuilding JIANG Zuhua1∗(蒋祖华), ZHOU Hongming2(周宏明), TAO Ningrong3(陶宁蓉), LI Baihe1(李柏鹤) J Shanghai Jiaotong Univ Sci    2024, 29 (5): 759-765.   DOI: 10.1007/s12204-022-2544-0 Abstract （72）      PDF（pc） （1037KB）（22）       Knowledge map    Save To increase efficiency in fierce competition, it is necessary and urgent to improve the standard of production planning for shipbuilding. The construction of curved blocks is the bottleneck to improve the efficiency of shipbuilding. Thus it is a key breakthrough for higher shipbuilding productivity to study the curved block production. By analyzing the scheduling problem in curved blocks production, we propose an intelligent curved block production scheduling method and its system based on a knowledge base, and show the main process of the system. The functions of the system include data management, assembly plan generation, plan adjustment, and plan evaluation. In order to deal with the actual situation and inherit the empirical knowledge, the system extracts some rules to control block selecting, algorithm selection, and evaluation thresholds to build a production decision-making knowledge base in the curved block scheduling system. The proposed knowledge base could be referred and modified by users, especially after a few interactions between the users and the knowledge base. The final assembly plan can be visualized and evaluated to facilitate the observation of plan implementation and effects of the decisions in the process. Finally, the system is verified by a large shipyard in Shanghai using real data and the results illustrate that the proposed method can perform the knowledge-based scheduling for curved blocks construction effectively. Reference | Related Articles | Metrics | Comments（0）

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Experimental Study of Influence of Secondary Combustion on Combustion Characteristics of Axial Staged Combustor SUI Yongfeng, ZHANG Yuming, ZANG Peng, JIA Yuliang, HENG Sijiang, FU Yanni, GE Bing Journal of Shanghai Jiao Tong University    2024, 58 (8): 1139-1147.   DOI: 10.16183/j.cnki.jsjtu.2023.076 Abstract （342）   HTML （29）    PDF（pc） （4916KB）（579）       Knowledge map    Save In order to obtain the influencing rule of secondary combustion on emissions and combustion oscillation characteristics of gas turbine axial staged combustor in non-premixed combustion mode and explore a load increasing mode with stable low emission, an axial staged combustor for F-class gas turbines is selected for experimental study. The results show that CO consumption is restrained and CO emission increases sharply when secondary fuel is added at a lower combustor outlet temperature. The addition of secondary fuel and the increase of secondary equivalence ratio lead to the reduction of NOx emission, but the increase of load can weaken the ability of secondary fuel to reduce NOx emission. The addition of secondary fuel and the increase of secondary equivalence ratio restrain the combustion oscillation in the low frequency band (75—90 Hz). When the secondary equivalence ratio is higher than a certain threshold (0.19), the addition of secondary fuel can restrain higher frequency(175—210 Hz) combustion oscillation. In addition, by comprehensively considering the influence of secondary combustion on emissions and combustion oscillation, the operating range and load increasing mode of low emissions and stable combustion of axial staged combustor in the higher load range (20%—50% load) are obtained, which provides a reference for stable low emission operation of the unit during load increasing. Table and Figures | Reference | Related Articles | Metrics | Comments（0）

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Droplets Evaporation Characteristics of Diesel from Direct and Indirect Coal Liquefaction and Their Blends SHEN Yukun, WANG Jigang, QIAO Xinqi Journal of Shanghai Jiao Tong University    2024, 58 (8): 1148-1155.   DOI: 10.16183/j.cnki.jsjtu.2023.195 Abstract （168）   HTML （10）    PDF（pc） （4746KB）（216）       Knowledge map    Save To study the evaporation characteristics of diesel from direct coal liquefaction (DDCL), diesel from indirect coal liquefaction (DICL), and their blended fuel droplets at different ambient temperatures (500, 600 and 700 ℃), a droplet evaporation test apparatus based on the suspension method was used to suspend droplets using crossed quartz wires, and a fuel with very similar physicochemical properties to diesel was obtained by blending of DDCL and DICL at a mass ratio of 29∶21 by using the fuel design method. It is shown that the evaporation pattern of DDCL, DICL, and their blended fuel droplets is similar to that of diesel fuel, and they all show a two-stage evaporation. The deviation from the classical d2 law is large below 600 ℃, and the deviation from the d2 law gradually decreases with the increase of ambient temperature. At all three ambient temperatures, the blended fuel droplets exhibit a better evaporation performance than diesel, with 27.2%, 46.3%, and 19.6% higher average evaporation rates than diesel, respectively, providing supporting data for the application of coal liquefied diesel in diesel engines. Table and Figures | Reference | Related Articles | Metrics | Comments（0）

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Temperature Control Scheme for Gas Turbine of Combined Cycles with Exhaust Gas Recirculation LI Keying, CHEN Kun, JIANG Zepeng, LI Chao, GUO Xiaoguo, ZHANG Shijie Journal of Shanghai Jiao Tong University    2024, 58 (8): 1156-1166.   DOI: 10.16183/j.cnki.jsjtu.2023.126 Abstract （205）   HTML （12）    PDF（pc） （3707KB）（229）       Knowledge map    Save Under partial-load conditions, the combined application of exhaust gas recirculation of heat recovery steam generator and compressor inlet guide vane adjustment (EGR-IGVC) can effectively improve the performance of gas turbine combined cycle. However, if this strategy is combined with the temperature control scheme of constant T3(turbine inlet temperature)-T4m(maximum allowable turbine exhaust temperature), which is often adopted in gas turbine combined cycles under part-load conditions, it would cause a large bottoming cycle exergy destruction and a significant decrease in bottoming cycle power output at relatively lower loads. In this paper, a constant T3-T4m-T4d (the design value of turbine exhaust temperature) scheme suitable for the EGR-IGVC strategy is proposed, the PG9351FA gas turbine combined cycle unit is taken as the research object, and the partial-load performance of combined cycle under the two temperature control schemes is compared and investigated based on energy and exergy analysis. The results show that the combination of the EGR-IGVC strategy with the constant T3-T4m scheme is still the best at the ambient temperature of 15 ℃ and the partial-load rate of above 80%. At a load of 30%—80%, compared with the constant T3-T4m scheme, the EGR-IGVC strategy combined with the constant T3-T4m-T4d scheme can increase the gas turbine efficiency by 0.15%—0.47%, and decrease the exergy destruction of the heat recovery steam generator by more than 0.51%(2.15 MW). The results also show that adopting the constant T3-T4m-T4d scheme can always obtain higher combined cycle efficiency when the ambient temperature varies between 0 and 40 ℃. In addition, the increase in partial-load efficiency becomes more evident with the rise of ambient temperature. Table and Figures | Reference | Related Articles | Metrics | Comments（0）

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Hydrodynamic Performance of a Barge-Type Floating Offshore Wind Turbine with Moonpool CHEN Yiren, YAO Jinyu, LI Mingxuan, ZHANG Xinshu Journal of Shanghai Jiao Tong University    2024, 58 (7): 965-982.   DOI: 10.16183/j.cnki.jsjtu.2022.521 Abstract （2151）   HTML （12）    PDF（pc） （11548KB）（470）       Knowledge map    Save The hydrodynamic performance of a barge-type floating offshore wind turbine (FOWT) with a moonpool is studied in frequency domain with reference to the Ideol-Floatgen design. The correction of the viscous damping of the moonpool is considered. First, the resonance modes of the moonpool are analyzed. Then, the hydrodynamic coefficients of the FOWT under regular waves and the motion responses under irregular waves are investigated. Finally, the safety of the FOWT is verified with respect to the DNV standards. The results show that the dynamic pitch and nacelle acceleration of the barge-type FOWT meet the safety requirements under both operating and survival conditions. The investigation of the coupling effects of the platform motion and the moonpool resonance shows that the motion of the platform will cause the shift of the piston mode frequency of the moonpool and the reduction of the piston mode response amplitude, the frequency of the sloshing mode is basically unaffected, but the response amplitude of the first-order sloshing mode is increased. The motion responses of the barge-type FOWT with and without the moonpool are compared. It is found that the moonpool can reduce the motion response of the FOWT, and improve the overall hydrodynamic performance of the FOWT. The platform length, moonpool length and platform draught are parametrically analyzed. Surge, heave, pitch response RMS values and the nacelle acceleration response RMS value are used as the indicators of comparison. It is found that the increase of the platform length could effectively reduce the four response RMS values of the FOWT under both operating and survival conditions, the increase of the moonpool length will reduce the four response RMS values of the FOWT under the operating condition, and the increase of the platform draught could significantly reduce the four response RMS values of the FOWT under the survival condition, the heave and pitch response RMS values increase with the augmentation of the draught under the operating condition. Table and Figures | Reference | Related Articles | Metrics | Comments（0）

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Vibration Control of Semi-Submersible Offshore Wind Turbines Using Inerter-Based Absorbers ZENG Weijie, ZHANG Ying, DENG Yanfei, GUO Chuanrui, REN Weixin Journal of Shanghai Jiao Tong University    2024, 58 (7): 983-994.   DOI: 10.16183/j.cnki.jsjtu.2023.019 Abstract （1760）   HTML （10）    PDF（pc） （3460KB）（396）       Knowledge map    Save Compared with fixed offshore wind turbines, the vibration problem of floating offshore wind turbines is particularly prominent, and further reduction of the vibration of floating offshore wind turbines has become an engineering challenge. In order to solve this problem, a novel vibration suppression device, inerter-based absorber (IBA) is introduced, and the vibration control of semi-submersible offshore wind turbines is studied. A comprehensive optimization method, namely the structure-immittance approach, is utilized to design the IBA in a systematic way. In order to search for the optimum vibration suppression performance, a simplified dynamic model of the semi-submersible offshore wind turbine, and the IBA dynamic equations are established using D’Alembert’s principle. Simultaneous suppression of the vibration response of the floating platform and tower of a semi-submersible offshore wind turbine is realized using the dual IBA control strategy. Furthermore, by implementing the optimum IBA in the OpenFAST software, the vibration suppression benefits of the dual IBA compared with the dual tuned mass damper (TMD) are verified under the coupling effects of wind and waves. The results show that the vibration control performance of the dual IBA control strategy is significantly better than that of the single one, and that of the dual IBA is better than that of the dual TMD. In addition, under the condition of achieving the same suppression performance as the TMD, IBA installed at the nacelle and the platform can respectively decrease the required absorber mass by 23.9% and 32.2%, which can greatly reduce the manufacture cost of the device. Table and Figures | Reference | Related Articles | Metrics | Comments（0）

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Depth Distribution Characteristics of Particle Velocity Field Intensity in Shallow Sea ZHANG Haigang, XIE Jinhuai, LIU Jiaqi, GONG Lijia, LI Zhi Journal of Shanghai Jiao Tong University    2024, 58 (7): 995-1005.   DOI: 10.16183/j.cnki.jsjtu.2023.073 Abstract （1518）   HTML （6）    PDF（pc） （6512KB）（1226）       Knowledge map    Save The depth distribution characteristics of particle velocity field intensity have had a significant impact on underwater acoustic detection and estimation. In this paper, based on the approximate conditions of the incoherent normal modes sum transformation to angular integration, the angular integration form of incoherent normal modes of particle velocity was derived, which avoided the complex calculations of eigenvalues and eigenfunctions while revealing the physical mechanism behind the significant variations in particle velocity intensity with source depth and symmetrical depth. The numerical results demonstrate that the analytical expression of the angular integration of incoherent particle velocity can facilitate fast computation and effectively characterize the depth distribution characteristics of particle velocity intensity. Additionally, due to the superposition effect of the amplitude function of normal modes, there are notable differences in the depth distribution of vertical and horizontal particle velocity. Subsequently, focusing on the intensity difference of particle velocity, the study analyzed the effects of parameters such as horizontal distance, source frequency, sound speed profile, and water depth on the depth distribution characteristics of particle velocity field intensity. The findings provide a theoretical basis for passive target depth estimation based on vector fields. Table and Figures | Reference | Related Articles | Metrics | Comments（0）

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Multi-Agent Path Planning Method Based on Improved Deep Q-Network in Dynamic Environments LI Shuyi (李舒逸), LI Minzhe (李旻哲), JING Zhongliang∗ (敬忠良) J Shanghai Jiaotong Univ Sci    2024, 29 (4): 601-612.   DOI: 10.1007/s12204-024-2732-1 Abstract （347）      PDF（pc） （1213KB）（164）       Knowledge map    Save The multi-agent path planning problem presents significant challenges in dynamic environments, primarily due to the ever-changing positions of obstacles and the complex interactions between agents’ actions. These factors contribute to a tendency for the solution to converge slowly, and in some cases, diverge altogether. In addressing this issue, this paper introduces a novel approach utilizing a double dueling deep Q-network (D3QN), tailored for dynamic multi-agent environments. A novel reward function based on multi-agent positional constraints is designed, and a training strategy based on incremental learning is performed to achieve collaborative path planning of multiple agents. Moreover, the greedy and Boltzmann probability selection policy is introduced for action selection and avoiding convergence to local extremum. To match radar and image sensors, a convolutional neural network - long short-term memory (CNN-LSTM) architecture is constructed to extract the feature of multi-source measurement as the input of the D3QN. The algorithm’s efficacy and reliability are validated in a simulated environment, utilizing robot operating system and Gazebo. The simulation results show that the proposed algorithm provides a real-time solution for path planning tasks in dynamic scenarios. In terms of the average success rate and accuracy, the proposed method is superior to other deep learning algorithms, and the convergence speed is also improved. Reference | Related Articles | Metrics | Comments（0）

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Fault-Tolerant Dynamical Consensus of Double-Integrator Multi-Agent Systems in the Presence of Asynchronous Self-Sensing Function Failures WU Zhihai∗ (吴治海), XIE Linbo (谢林柏) J Shanghai Jiaotong Univ Sci    2024, 29 (4): 613-624.   DOI: 10.1007/s12204-024-2716-1 Abstract （96）      PDF（pc） （540KB）（59）       Knowledge map    Save Double-integrator multi-agent systems (MASs) might not achieve dynamical consensus, even if only partial agents suffer from self-sensing function failures (SSFFs). SSFFs might be asynchronous in real engineering application. The existing fault-tolerant dynamical consensus protocol suitable for synchronous SSFFs cannot be directly used to tackle fault-tolerant dynamical consensus of double-integrator MASs with partial agents subject to asynchronous SSFFs. Motivated by these facts, this paper explores a new fault-tolerant dynamical consensus protocol suitable for asynchronous SSFFs. First, multi-hop communication together with the idea of treating asynchronous SSFFs as multiple piecewise synchronous SSFFs is used for recovering the connectivity of network topology among all normal agents. Second, a fault-tolerant dynamical consensus protocol is designed for doubleintegrator MASs by utilizing the history information of an agent subject to SSFF for computing its own state information at the instants when its minimum-hop normal neighbor set changes. Then, it is theoretically proved that if the strategy of network topology connectivity recovery and the fault-tolerant dynamical consensus protocol with proper time-varying gains are used simultaneously, double-integrator MASs with all normal agents and all agents subject to SSFFs can reach dynamical consensus. Finally, comparison numerical simulations are given to illustrate the effectiveness of the theoretical results. Reference | Related Articles | Metrics | Comments（0）

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Event-Triggered Fixed-Time Consensus of Second-Order Nonlinear Multi-Agent Systems with Delay and Switching Topologies XING Youjing1 (邢优靖), GAO Jinfeng1∗ (高金凤), LIU Xiaoping1, 2 (刘小平), WU Ping1 (吴平) J Shanghai Jiaotong Univ Sci    2024, 29 (4): 625-639.   DOI: 10.1007/s12204-024-2695-2 Abstract （134）      PDF（pc） （1059KB）（56）       Knowledge map    Save To address fixed-time consensus problems of a class of leader-follower second-order nonlinear multiagent systems with uncertain external disturbances, the event-triggered fixed-time consensus protocol is proposed. First, the virtual velocity is designed based on the backstepping control method to achieve the system consensus and the bound on convergence time only depending on the system parameters. Second, an event-triggered mechanism is presented to solve the problem of frequent communication between agents, and triggered condition based on state information is given for each follower. It is available to save communication resources, and the Zeno behaviors are excluded. Then, the delay and switching topologies of the system are also discussed. Next, the system stabilization is analyzed by Lyapunov stability theory. Finally, simulation results demonstrate the validity of the presented method. Reference | Related Articles | Metrics | Comments（0）

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Clinical application value of spinal robot assisted system in MIS-TLIF surgery LIU Yang, LIU Daokuo, LI Changkuan, et al Journal of Tissue Engineering and Reconstructive Surgery    2024, 20 (3): 300-.   Abstract （170）      PDF（pc） （3575KB）（65）       Knowledge map    Save Objective To study the clinical application value of spinal robot assisted system in minimally invasive transforaminal fusion （MIS-TLIF） surgery. Methods From March 2019 to November 2022，78 patients who underwent surgical treatment for lumbar degenerative diseases were divided into traditional MIS-TLIF group （group A，41 cases） and robotic MIS-TLIF group （group B，37 cases） according to different surgical methods. Perioperative indicators （intraoperative bleeding， surgical time， incision length， and fluoroscopy frequency）， postoperative CT findings （screw placement accuracy，screw abduction angle）， functional recovery （VAS， JOA scores）， and perioperative complications were compared between the two groups. Results The intraoperative bleeding volume and fluoroscopy frequency in Group B were less than those in Group A， and the operative time and incision length were shorter than those in Group A （P<0.05） . A total of 164 screws were implanted in Group A，148 in Group B. The acceptable screws in Group B were significantly higher than those in Group A （P< 0.05） . The abduction angle of screws in Group A was 18.12°±7.50°， and that in Group B was 23.56°±6.64°. The abduction angle in Group B was greater than that in Group A （P<0.05） . One month after surgery， the VAS score of the two groupsdecreased compared to that before surgery， while the JOA score increased （P<0.05）.However， there was no statistically significant difference between the two groups （P>0.05）.There were no serious complications such as blood vessels and nerves in both groups； In group A，3 patient had a positioning error and 2 patient had a dural sac tear， all of which recovered after corresponding treatment； Group B had no early complications. The incidence of early complications in Group B was lower than  that in Group A （P<0.05）.Conclusion The spinal robot assisted system can shorten the operation time of MIS-TLIF，reduce intraoperative bleeding， and improve the accuracy of pedicle screw placement. It has high clinical application value. Related Articles | Metrics | Comments（0）

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Status and influencing factors of stigma in patients with port wine stains in the head and neck JIANG Yan, Ran Xuehui, LIN Xiaoxi, et al Journal of Tissue Engineering and Reconstructive Surgery    2024, 20 (3): 335-.   Abstract （140）      PDF（pc） （1050KB）（54）       Knowledge map    Save Objective To explore the current status and influencing factors of stigma in patients with port wine stains （PWS） in the head and neck. Methods Using the convenient sampling method，113 patients with PWS in the head and neck from August 2022 to December 2022 were recruited. The general demographic data questionnaire， stigma scale for chronic illness （SSCI）， social impact scale （SIS） and self-esteem scale （SES） were used to conduct a questionnaire survey. Results The SSCI score of patients with PWS was 50.61±22.2， and the SIS score was 48.71±15.17. Single-factor analysis of variance showed that the influencing factors of stigma were education level， monthly income， treatment times， lesion location， and lesion size （P<0.05）； The SES score of patients with PWS was 24.75±4.92， and single-factor analysis of variance showed that the influencing factors of self-esteem were monthly income and job absence （P<0.05）.SSCI scores andSIS scores were negatively correlated with SES scores （P<0.01）.Conclusion Patients with PWS had a moderate level of stigma and a low level of self-esteem. Both chronic illness stigma and social impact stigma are significantly negatively correlated with the level of self-esteem. Medical staff should provide appropriate guidance to patients during treatment， enhancing patients’ confidence and guiding patients to face the disease positively， and meanwhile， call on the public to give more concern to patients with chronic skin diseases. Related Articles | Metrics | Comments（0）

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Discussion on talent cultivation of plastic surgery in the new era ZHANG Hanrui, HUANG Xin, LI Qingfeng, et al Journal of Tissue Engineering and Reconstructive Surgery    2024, 20 (3): 388-.   Abstract （152）      PDF（pc） （927KB）（85）       Knowledge map    Save Plastic surgery is a specialized branch of surgery that has two main development directions： Reconstructive plastic surgery and aesthetic plastic surgery. In recent years， there has been a growing inclination among young doctors to prioritize aesthetic plastic surgery over reconstructive surgery， which has hindered the sustainable development of plastic surgery. Meanwhile， emerging technology has provided new opportunities for talent cultivation. The education model for young doctors should advance with time. Therefore， the recommendations such as strengthening medical history education， guiding correct understanding， and innovating teaching models， have been proposed to improve the quality and efficiency of talent cultivation. These efforts aim to cultivate highly qualified talents with strong professional skills and a sense of responsibility， who can adapt to the development needs of the discipline. Related Articles | Metrics | Comments（0）

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Review of High Voltage Ride-Through Control Method of Large-Scale Wind Farm WEI Juan, LI Canbing, HUANG Sheng, CHEN Sijie, GE Rui, SHEN Feifan, WEI Lai Journal of Shanghai Jiao Tong University    2024, 58 (6): 783-797.   DOI: 10.16183/j.cnki.jsjtu.2022.416 Abstract （2057）   HTML （16）    PDF（pc） （1884KB）（499）       Knowledge map    Save As the major demand for the development and utilization of new energy, the large-scale development of wind power is a key support in achieving the strategic goal of “cabron peaking and carbon neutrality” for China. The problem of safe and stable operation of wind farms caused by external grid faults has become one of the key bottlenecks restricting the large-scale, clustered, and intelligent development of wind power. This paper mainly focuses on the voltage surge condition of the power grid. First, it analyzes the transient characteristics of high voltage ride-through (HVRT) of the doubly-fed induction generator-wind turbine, permanent magnet synchronous generator-wind turbine, and wind farms. Then, it summarizes the corresponding HVRT and post-fault voltage recovery coordinated optimal control strategies based on the different control areas, and it classifies and compares the working principles and advantages and disadvantages of various control strategies. Afterwards, it recapitulates the principle, advantages and disadvantages, and effects of the existing HVRT control method for large-scale wind farms, and analyzes the differences between the single wind turbine and the large-scale wind farms from the perspective of control structure. Finally, it discusses the development trend and potential research hotspots of wind farm voltage intelligent safety control in the future, aiming to provide reference for improving the large-scale application of wind power and the safe operation of power grids in China. Table and Figures | Reference | Related Articles | Metrics | Comments（0）

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Dynamic Equivalence Modeling of Short-Circuit Faults in Wind Farms Considering Wake Effects YU Hao, LI Canbing, YE Zhiliang, PENG Sui, REN Wanxin, CHEN Sijie, TANG Binwei, CHEN Dawei Journal of Shanghai Jiao Tong University    2024, 58 (6): 798-805.   DOI: 10.16183/j.cnki.jsjtu.2022.476 Abstract （1132）   HTML （10）    PDF（pc） （2071KB）（1385）       Knowledge map    Save Fast and accurate analysis of the short-circuit characteristics of large wind farms has important engineering application value, and the short-circuit characteristics of wind farms under the influence of the wake effect vary greatly. Therefore, it is necessary to establish a wind farm short-circuit fault time equivalence model. A wind farm short-circuit fault dynamic equivalence method considering the effect of wake effect is proposed. First, the wake effect factor is defined to reflect the degree of the unit affected by the wake effect. Then, the wake effect factor is used as the grouping basis to reduce the variability of operating state of the units within the group under the influence of the wake effect. A positive- negative- zero-sequence network equivalence method is analyzed to improve the effectiveness of the equivalence model in asymmetric short-circuit faults. An equivalence method suitable for zero-sequence network is proposed and a platform is built for verification. The simulation results show that the dynamic short-circuit fault equivalence model proposed can accurately reflect the active and reactive short-circuit output characteristics of wind farms under the influence of the wake effect. Table and Figures | Reference | Related Articles | Metrics | Comments（0）

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Short-Term Interval Forecasting of Photovoltaic Power Based on CEEMDAN-GSA-LSTM and SVR LI Fen, SUN Ling, WANG Yawei, QU Aifang, MEI Nian, ZHAO Jinbin Journal of Shanghai Jiao Tong University    2024, 58 (6): 806-818.   DOI: 10.16183/j.cnki.jsjtu.2022.511 Abstract （1579）   HTML （10）    PDF（pc） （2987KB）（276）       Knowledge map    Save Aimed at the intermittency and fluctuation of photovoltaic output power, a short-term interval prediction model of photovoltaic power is proposed. First, the model uses the complete ensemble empirical mode decomposition of adaptive noise (CEEMDAN) to decompose the historical photovoltaic output data into different components and define them as time-series components and random components according to their correlation with time-series features such as declination and time angles. Then, the long short-term memory (LSTM) neural network and the support vector regression (SVR) model optimized by the gravitational search algorithm (GSA) are used to predict the time series components and the random components respectively, and the prediction results of the time series components and the random components are superimposed to obtain the point prediction result. After the error is subjected to Johnson transformation and normal distribution modeling, the photovoltaic power interval prediction result is obtained. Finally, the effectiveness of the method is verified by an example. The comparison of the proposed model with other existing prediction models under different weather conditions suggests that the proposed model has a higher accuracy and a better robustness, which can provide precise confidence intervals based on point prediction values. Table and Figures | Reference | Related Articles | Metrics | Comments（0） Cited: CSCD(1)

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China Alzheimer Report 2024 WANG Gang, QI Jinlei, LIU Xinya, REN Rujing, LIN Shaohui, HU Yisong, LI Haixia, XIE Xinyi, WANG Jintao, LI Jianping, ZHU Yikang, GAO Mengyi, YANG Junjie, WANG Yiran, JING Yurong, GENG Jieli, ZHI Nan, CAO Wenwei, XU Qun, YU Xiaoping, ZHU Yuan, ZHOU Ying, WANG Lin, GAO Chao, LI Binyin, CHEN Shengdi, YUAN Fang, DOU Ronghua, LIU Xiaoyun, LI Xuena, YIN Yafu, CHANG Yan, XU Gang, XIN Jiawei, ZHONG Yanting, LI Chunbo, WANG Ying, ZHOU Maigeng, CHEN Xiaochun, representing the China Alzheimer's Disease Report Writing Group Journal of Diagnostics Concepts & Practice    2024, 23 (03): 219-256.   DOI: 10.16150/j.1671-2870.2024.03.001 Abstract （9431）   HTML （678）    PDF（pc） （3340KB）（6573）       Knowledge map    Save With the sustained growth of economy and significant changes in social demographics, the issue of elderly-related diseases has increasingly drawn attention particularly. Alzheimer's disease (AD),as a representative disease of neurodegenerative diseases has become a major challenge, affecting the health and quality of life among the elderly population severely. In recent years, the incidence, prevalence, and mortality rate of AD increase in China, imposing substantial economic burdens on families, society, and the entire healthcare system. To proactively address this challenge and respond to the national 'Healthy China Action' initiative, leading experts from Renji Hospital, Shanghai Jiao Tong University School of Medicine,and Chinese Center for Disease Control and Prevention Chronic Non-communicable Disease Control Center, Fudan University School of Public Health, Shanghai Mental Health Center, Ruijin Hospital,Shanghai Jiao Tong University School of Medicine, Fujian Medical University, and other authoritative institutions, have jointly authored the 'China Alzheimer Disease Report 2024'. Building upon previous editions of 2021, 2022, and 2023, this report updates epidemiological data on AD in China, thoroughly analyzes the latest economic burdens of the disease, and comprehensively evaluates the current status of AD diagnosis and treatment services, as well as the allocation of public health resources in our country. The release of the 'China Alzheimer Disease Report 2024' not only reflects China's progress and efforts in AD research and prevention, but also underscores the social heightened concern for elderly health issues. It aims to provide scientific and technical guidance and robust data support for the prevention, diagnosis, and treatment of AD, offering a professional basis for the government and relevant departments to formulate targeted health policies and intervention measures. Furthermore, it serves as a platform for promoting academic exchanges and cooperation in this field domestically and internationally. Through the dissemination and application of this report, we anticipate it will not only serve as a reference for professionals but also enhance public awareness of AD, promote active participation across various sectors of society, and jointly advance the development of elderly health care in China, empowering us towards achieving 'healthy aging'. Table and Figures | Reference | Related Articles | Metrics | Comments（0）

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Key Technologies and Applications of Shared Energy Storage SONG Meng, LIN Gujing, MENG Jing, GAO Ciwei, CHEN Tao, XIA Shiwei, BAN Mingfei Journal of Shanghai Jiao Tong University    2024, 58 (5): 585-599.   DOI: 10.16183/j.cnki.jsjtu.2022.360 Abstract （1605）   HTML （36）    PDF（pc） （4173KB）（549）       Knowledge map    Save Under the goal of “carbon peaking and carbon neutrality”, the penetration rate of renewable energy continues to rise, whose volatility, intermittency, and uncertainty pose significant challenges to the safe and stable operation of the power system. As a typical application of the sharing economy in the field of energy storage, shared energy storage (SES) can maximize the utilization of resources by separating the “ownership” and “usage” of energy storage resources, which provides a new solution to the problem of imbalance between supply and demand caused by the large-scale integration of renewable energy into the grid, and has broad development prospects. The business model of SES is explored based on value positioning, cost modeling, and profitability strategies, and a detailed summary of SES trading varieties, operational structure, and engineering applications is discussed. Finally, the future trend of shared energy storage is discussed and envisioned. Table and Figures | Reference | Related Articles | Metrics | Comments（0） Cited: CSCD(1)

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Dynamic Optimization of Carbon Reduction Pathways in Coastal Metropolises Considering Hidden Influence of Decarbonization on Energy Demand XIAO Yinjing, ZHANG Di, WEI Juan, GE Rui, CHEN Dawei, YANG Guixing, YE Zhiliang Journal of Shanghai Jiao Tong University    2024, 58 (5): 600-609.   DOI: 10.16183/j.cnki.jsjtu.2022.437 Abstract （1197）   HTML （16）    PDF（pc） （1733KB）（273）       Knowledge map    Save Setting a reasonable carbon reduction plan in coastal metropolises is the key part to reach the global carbon target. Carbon reduction will change urban climate and influence energy demand, both of which affect the optimization results of carbon reduction pathways. Current generation expansion optimization models consider direct abatement contribution and solve most problems of planning for long-term carbon emission reduction in energy systems. However, the construction of new type power systems also indirectly impacts carbon emissions by changing microclimate factors such as heat island intensity. By combining generation expansion with carbon emission prediction model, the proposed approach in this paper considers the hidden mechanism of carbon and heat emission change on air-conditioning loads and dynamically optimizes the carbon reduction pathways in coastal metropolises. Taking Pudong Area in Shanghai as an example, the estimated cost of carbon reduction is reduced by the proposed approach. Some suggestions for the carbon reduction in coastal metropolises are made according to the simulation results. Table and Figures | Reference | Supplementary Material | Related Articles | Metrics | Comments（0）

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Bi-Level Optimization Operation Method of Multi-H2-IES Considering Dynamic Carbon Emission Factors FU Wenxi, DOU Zhenlan, ZHANG Chunyan, WANG Lingling, JIANG Chuanwen, XIONG Zhan Journal of Shanghai Jiao Tong University    2024, 58 (5): 610-623.   DOI: 10.16183/j.cnki.jsjtu.2022.225 Abstract （1130）   HTML （19）    PDF（pc） （2901KB）（96）       Knowledge map    Save In the context of achieving “carbon peaking and carbon neutrality”, the low-carbon transformation of the energy system is the development direction in the future. Hydrogen, known for its high calorific value and low pollution, has received extensive attention in recent years. Based on the carbon emission flow theory, a bi-level optimization operation model of multi-integrated energy system with hydrogen (H2-IES) is proposed considering dynamic carbon emission factors. At the upper level, an economic dispatch model is established by the main energy grid based on the principle of optimal benefit, and the energy prices and carbon emission factors of each park are determined and distributed to the lower level. At the lower level, a multi-park low-carbon cooperative operation model is established based on the Nash negotiation theory, and the adaptive alternating direction method of multipliers (A-ADMM) is used for distributed solution to determine the energy demand of each park and provide feedback to the upper level. The coordinated operation of both levels is realized in multiple iterative interactions. To equitably distribute the benefits of cooperation, a revenue distribution method based on comprehensive bargaining power is proposed. The analysis of a case study shows that the bi-level optimization method proposed in this paper can realize the coordinated operation between the upper and lower levels, and take into account the low-carbon and economical properties of multi-parks operation. Because the income is reasonably distributed, the enthusiasm of parks to participate in cooperation can be guaranteed. Table and Figures | Reference | Supplementary Material | Related Articles | Metrics | Comments（0）

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Multi-Robot Task Allocation Using Multimodal Multi-Objective Evolutionary Algorithm Based on Deep Reinforcement Learning MIAO Zhenhua(苗镇华), HUANG Wentao(黄文焘), ZHANG Yilian(张依恋), FAN Qinqin(范勤勤) J Shanghai Jiaotong Univ Sci    2024, 29 (3): 377-387.   DOI: 10.1007/s12204-023-2679-7 Abstract （431）      PDF（pc） （975KB）（212）       Knowledge map    Save The overall performance of multi-robot collaborative systems is significantly affected by the multirobot task allocation. To improve the effectiveness, robustness, and safety of multi-robot collaborative systems,a multimodal multi-objective evolutionary algorithm based on deep reinforcement learning is proposed in this paper. The improved multimodal multi-objective evolutionary algorithm is used to solve multi-robot task allocation problems. Moreover, a deep reinforcement learning strategy is used in the last generation to provide a high-quality path for each assigned robot via an end-to-end manner. Comparisons with three popular multimodal multi-objective evolutionary algorithms on three different scenarios of multi-robot task allocation problems are carried out to verify the performance of the proposed algorithm. The experimental test results show that the proposed algorithm can generate sufficient equivalent schemes to improve the availability and robustness of multirobot collaborative systems in uncertain environments, and also produce the best scheme to improve the overall task execution efficiency of multi-robot collaborative systems. Reference | Related Articles | Metrics | Comments（0）

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Online Multi-Object Tracking Under Moving Unmanned Aerial Vehicle Platform Based on Object Detection and Feature Extraction Network LIU Zengmin (刘增敏), WANG Shentao(王申涛), YAO Lixiu(姚莉秀), CAI Yunze(蔡云泽) J Shanghai Jiaotong Univ Sci    2024, 29 (3): 388-399.   DOI: 10.1007/s12204-022-2540-4 Abstract （203）      PDF（pc） （1105KB）（80）       Knowledge map    Save In order to solve the problem of small object size and low detection accuracy under the unmanned aerial vehicle (UAV) platform, the object detection algorithm based on deep aggregation network and high-resolution fusion module is studied. Furthermore, a joint network of object detection and feature extraction is studied to construct a real-time multi-object tracking algorithm. For the problem of object association failure caused by UAV movement, image registration is applied to multi-object tracking and a camera motion discrimination model is proposed to improve the speed of the multi-object tracking algorithm. The simulation results show that the algorithm proposed in this study can improve the accuracy of multi-object tracking under the UAV platform, and effectively solve the problem of association failure caused by UAV movement. Reference | Related Articles | Metrics | Comments（0）

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Anti-Occlusion Object Tracking Algorithm Based on Filter Prediction CHEN Kun(陈坤), ZHAO Xu(赵旭), DONG Chunyu(董春玉), DI Zichao(邸子超), CHEN Zongzhi(陈宗枝) J Shanghai Jiaotong Univ Sci    2024, 29 (3): 400-413.   DOI: 10.1007/s12204-022-2484-8 Abstract （221）      PDF（pc） （5510KB）（76）       Knowledge map    Save Visual object tracking is an important issue that has received long-term attention in computer vision.The ability to effectively handle occlusion, especially severe occlusion, is an important aspect of evaluating theperformance of object tracking algorithms in long-term tracking, and is of great significance to improving therobustness of object tracking algorithms. However, most object tracking algorithms lack a processing mechanism specifically for occlusion. In the case of occlusion, due to the lack of target information, it is necessary to predict the target position based on the motion trajectory. Kalman filtering and particle filtering can effectively predict the target motion state based on the historical motion information. A single object tracking method, called probabilistic discriminative model prediction (PrDiMP), is based on the spatial attention mechanism in complex scenes and occlusions. In order to improve the performance of PrDiMP, Kalman filtering, particle filtering and linear filtering are introduced. First, for the occlusion situation, Kalman filtering and particle filtering are respectively introduced to predict the object position, thereby replacing the detection result of the original tracking algorithm and stopping recursion of target model. Second, for detection-jump problem of similar objects in complex scenes, a linear filtering window is added. The evaluation results on the three datasets, including GOT-10k, UAV123 and LaSOT, and the visualization results on several videos, show that our algorithms have improved tracking performance under occlusion and the detection-jump is effectively suppressed. Reference | Related Articles | Metrics | Comments（0）

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Attitude Planning Method of Satellite Staring Imaging to Aerial Dynamic Target DU Ning, WU Shufan, CHEN Zhansheng, CHEN Wenhui, WANG Shiyao, XU Jiaguo, QIN Dongdong Journal of Shanghai Jiao Tong University    2024, 58 (4): 411-418.   DOI: 10.16183/j.cnki.jsjtu.2022.425 Abstract （437）   HTML （61）    PDF（pc） （1661KB）（599）       Knowledge map    Save Aimed at the staring imaging requirements of the low earth orbit (LEO) satellite array camera for aerial dynamic targets, a method for target position estimation and staring attitude planning based on image miss-distance of the satellite platform is proposed. Based on the prior knowledge of the flying altitude of the aerial dynamic target, taking the latitude and longitude change rate of the target geography as the state quantity and the central pixel value of the target as the observation, an extended Kalman filter (EKF) is designed to realize the accurate smooth estimation and prediction of the geographical latitude and longitude of the target. On this basis, the attitude and angular velocity of the satellite are planned, the influence of target pixel noise and delay on attitude stability is avoided, and the position estimation of a single satellite to target is realized. The effectiveness of the proposed method is illustrated by a numerical simulation. Table and Figures | Reference | Related Articles | Metrics | Comments（0）

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Numerical Study of Deformation and Breakup Processes of Water Droplets in Air Flow SANG Xu, JIN Zheyan, YANG Zhigang, YU Fang Journal of Shanghai Jiao Tong University    2024, 58 (4): 419-427.   DOI: 10.16183/j.cnki.jsjtu.2022.414 Abstract （389）   HTML （24）    PDF（pc） （2771KB）（434）       Knowledge map    Save Aimed at the problem that water droplets are easy to break up during the acceleration process in icing wind tunnel experiment, which makes it difficult for the particle size distribution of water droplets in the test section to conform to the icing weather conditions, the deformation and breakup regime of water droplets with a diameter of 100, 200, 400, 600, 800, 1 000 and 1 200 μm under the action of different air velocities(20, 50, and 80 m/s) are simulated by using the volume of fluid (VOF) method. The results show that under the action of 20 m/s air flow, the water droplet with a diameter of 600 μm does not break. Under the action of 50 m/s air flow, the water droplet with a diameter of 100 μm does not break. With the increase of Weber number, the wavelength of the most destructive wave also increases, and the breakup regime of water droplets changes from bag breakup to bag-plume breakup, to plume-shear breakup, and to shear breakup successively. The droplet breakup regime, including the bag breakup, bag/plume breakup, the plume/sheet-thinning breakup, and the shear breakup, has a significant effect on the ratio of the area of the largest droplet to the initial droplet. Under the condition that the initial drop diameter is the same, as the inlet velocity increases, the area ratio after breakup increases. Table and Figures | Reference | Related Articles | Metrics | Comments（0）

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Vibration Characteristics of Cylindrical Membrane HUANG Tao, HE Zeqing, SONG Lin Journal of Shanghai Jiao Tong University    2024, 58 (4): 428-437.   DOI: 10.16183/j.cnki.jsjtu.2022.396 Abstract （294）   HTML （32）    PDF（pc） （4517KB）（283）       Knowledge map    Save Based on the principle of D’Alembert, the nonlinear vibration equation of cylindrical membrane is established, and the analysis and experimental verification of it are conducted. The control equation system for cylindrical membrane vibration problems is established, and the equation system according to the physical equations and boundary conditions of thin diaphragms is simplified and solved, the analytical solution of nonlinear vibration frequency of cylindrical membrane is obtained, and the linear analytical solution is verified by finite element simulation, which shows that the error between theoretical calculation and numerical simulation is small, and the applicability of finite element method to the modal analysis of flexible membrane structure is verified. A 3D laser scanning vibration measurement system is used to test the vibration frequency of cylindrical membranes in the air environment. The finite element analysis software is used to obtain the dry mode and wet mode vibration frequencies of cylindrical membranes and extract the additional mass coefficients of air. The results showed that the test results of the vibration in wet mode have a good consistency with the numerical analysis results, and the influence of the additional quality of the ground air on the cylindrical membrane is in the same order of magnitude as its own mass. Table and Figures | Reference | Related Articles | Metrics | Comments（0）

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Operation Parameters of Air-Cooled Fuel Cell Based on In-Situ Testing of Reaction State CHEN Minxue, QIU Diankai, PENG Linfa Journal of Shanghai Jiao Tong University    2024, 58 (3): 253-262.   DOI: 10.16183/j.cnki.jsjtu.2022.318 Abstract （404）   HTML （39）    PDF（pc） （25048KB）（381）       Knowledge map    Save The internal reaction state of air-cooled proton exchange membrane fuel cell (PEMFC) is the key factor affecting the output performance and stability of the cell. By developing an in-situ testing device for the reaction state of air-cooled fuel cell, the real-time measurement of cell temperature and current density is realized, and the influence mechanism of hydrogen outlet pulse interval, hydrogen inlet pressure and cathode wind speed on the performance of the cell is revealed. The results show that the distribution of temperature and current density in air-cooled cells is uneven. The temperature difference can reach 20 °C, and the current density difference reaches 400 mA/cm2 when the average current density is 500 mA/cm2. As the interval between pulses decreases and the inlet pressure increases, the performance of the hydrogen outlet area and the uniformity of the distribution increase, which can reduce the fluctuation of current density in the cells and improve output stability. If the cathode wind speed is too low, the temperature in central areas is high, and the temperature distribution uniformity is reduced. However, excessive wind speed causes the generating water to be blown away. The water content of the proton exchange membrane thus decreases, and the uniformity of the current density distribution deteriorates. Table and Figures | Reference | Related Articles | Metrics | Comments（0）

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SOH Online Estimation of Lithium-Ion Batteries Based on Fusion Health Factor and Integrated Extreme Learning Machine QU Keqing, DONG Hao, MAO Ling, ZHAO Jinbin, YANG Jianlin, LI Fen Journal of Shanghai Jiao Tong University    2024, 58 (3): 263-272.   DOI: 10.16183/j.cnki.jsjtu.2022.306 Abstract （222）   HTML （17）    PDF（pc） （3259KB）（171）       Knowledge map    Save Online estimation of the state of health (SOH) of lithium-ion batteries (LIB) is crucial for the security and stability operation of battery management systems. In order to overcome the problem such as long training time, large amount of computation, and complex debugging process of the LIB SOH estimation methods based on traditional data-driven, an LIB SOH estimation method based on fusion health factor (HF) and integrated extreme learning machine is proposed. The interval data with a high correlation with the SOH was found by analyzing the dQ/dV and dT/dV curves of the battery. Multi-dimensional HFs are extracted from the interval data, and the indirect HF are obtained by principal component analysis. The stochastic learning algorithm of extreme learning machine is used to establish the nonlinear mapping relationship between indirect HF and SOH. Considering the unstable output of a single model, an integrated extreme learning machine model is proposed. The unreliable output is eliminated by setting credibility evaluation rules for the estimation results, and the estimation accuracy of the model is improved. Finally, the method proposed in this paper is validated using the NASA LIB aging dataset and the LIB aging dataset of Oxford University. The results show that the average absolute percentage error of SOH estimation method proposed is less than 1%, and it has a high accuracy and reliability. Table and Figures | Reference | Related Articles | Metrics | Comments（0） Cited: CSCD(1)

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Interval Estimation of State of Health for Lithium Batteries Considering Different Charging Strategies ZHANG Xiaoyuan, ZHANG Jinhao, YANG Lixin Journal of Shanghai Jiao Tong University    2024, 58 (3): 273-284.   DOI: 10.16183/j.cnki.jsjtu.2022.347 Abstract （329）   HTML （14）    PDF（pc） （3204KB）（579）       Knowledge map    Save State of health (SOH) estimation of lithium-ion (Li-ion) batteries is of great importance for battery use, maintenance, management, and economic evaluation. However, the current SOH estimation methods for Li-ion batteries are mainly targeted at specific charging strategies by using deterministic estimation models, which cannot reflect uncertain information such as randomness and fuzziness in the battery degradation process. To this end, a method for estimating the SOH interval of Li-ion batteries applicable to different charging strategies is proposed, which extracts multiple feature parameters from the cyclic charging and discharging data of batteries with different charging strategies, and automatically selects the optimal combination of feature parameters for a specific charging strategy by using the cross-validation method. In addition, considering the limited number of cycles in the whole life cycle of Li-ion batteries as a small sample, support vector quantile regression (SVQR), which integrates the advantages of support vector regression and quantile regression, is proposed for the estimation of SOH interval of lithium-ion batteries. Li-ion battery charge/discharge cycle data with deep discharge degree is selected as the training set for offline training of the SVQR model, and the trained model is used for online estimation of the SOH of Li-ion batteries of different charging strategies. The proposed method is validated using three datasets with different charging strategies. The experimental results show that the proposed method is applicable to different charging strategies and the estimation results are better than those of quantile regression, quantile regression neural network and Gaussian process regression. Table and Figures | Reference | Related Articles | Metrics | Comments（0）

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