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    Sealing Performance of Pressure-Adaptive Seal
    LI Yuanfeng (李元丰), WANG Yiling (王怡灵), ZHANG Wanxin∗ (张万欣), LIU Jinian (刘冀念), MA Jialu (马加炉)
    J Shanghai Jiaotong Univ Sci    2022, 27 (6): 747-756.   DOI: 10.1007/s12204-022-2510-x
    Abstract395)      PDF (2268KB)(161)      
    A pressure-adaptive seal is developed to meet the demands of quick assembling and disassembling for an individual protection equipment in aerospace. The analysis model, which reflects the main characteristics of the seal structure, is built based on the finite element method and the Roth’s theory of rubber seal, and verified by the prototype test. The influences of precompression ratio, hardness of the sealing ring rubber, and friction coefficient on the sealing performance are investigated by variable parameter method. Results show that the model can describe the essential characteristics of the pressure-adaptive seal structure, which has good follow-up to the cavity pressure to achieve the purpose of pressure self-adaptive. The leakage rate correlates negatively with the precompression ratio of the sealing ring and the hardness of the sealing ring material, while is positively related to the friction coefficient between the sealing ring and the sealing edge. The maximum contact stress on sealing surface has negative correlation with the precompression ratio of the sealing ring, and positive correlation with the hardness of the seal ring material. The damage risk of the sealing ring increases with the increases of the precompression ratio of sealing ring, hardness of sealing ring material, and friction coefficient.
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    Travel Intention of Electric Vehicle Sharing based on Theory of Multiple Motivations
    BAO Lewen (鲍乐雯), MIAO Rui, ∗ (苗 瑞), CHEN Zhihua (陈志华), ZHANG Bo (张 博), GUO Peng (郭 鹏), MA Yuze (马宇泽)
    J Shanghai Jiaotong Univ Sci    2023, 28 (1): 1-9.   DOI: 10.1007/s12204-023-2563-5
    Abstract268)      PDF (467KB)(107)      
    Determining the travel intention of residents with shared electric vehicles (EVs) is significant for promoting the development of low-carbon transportation, considering that common problems such as high idle rate and lack of attractiveness still exist. To this end, a structural equation model (SEM) based on the theory of multiple motivations is proposed in this paper. First, the influencing motivations for EV sharing are divided into three categories: consumer-driven, program-driven, and enterprise-driven motivations. Then, the intentions of residents in Shanghai to travel with shared EVs are obtained through a survey questionnaire. Finally, an SEM is constructed to analyze quantitatively the impact of different motivations on the travel intention. The results show that consumer-driven motivations with impact weights from 0.14 to 0.63 have the overwhelming impact on travel intention, compared to program-driven motivations with impact weights from ?0.14 to 0.15 and enterprise-driven motivations with impact weights from 0.02 to 0.06. In terms of consumer-driven motivations, the weight of green travel awareness is the highest. The implications of these results on the policy to enable large-scale implementation of shared EVs are discussed from the perspectives of the resident, enterprise, and government.
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    Physical Characterization of Ionic Liquid-Modified Polyvinyl Alcohol and Sodium Thiocyanate Polymer Electrolytes for Electrochemical Double-Layer Capacitor Application
    AZEMTSOP Manfo Theodore , MEHRA Ram Mohan , KUMAR Yogesh , GUPTA Meenal
    J Shanghai Jiaotong Univ Sci    2023, 28 (2): 161-171.   DOI: 10.1007/s12204-021-2397-y
    Abstract235)      PDF (1140KB)(94)      
    Novel gel polymer electrolytes (GPEs) composed of polyvinyl alcohol (PVA) and sodium thiocyanate were developed via a solution casting technique. An ionic liquid (IL), 1-ethyl-3-methyl-imidazolium tricyanomethanide ([EMIM][TCM]), was doped into a polymer–salt complex system (PVA + NaSCN) to further enhance the conductivity. IL-doped polymer electrolyte (ILDPE) films were characterized using X-ray diffraction (XRD), polarized optical microscopy (POM), Fourier-transform infrared (FTIR) spectroscopy, and conductivity measurements. XRD was performed to check the degree of crystallinity and amorphicity of the ILDPE films, and the amorphicity of GPEs increased with the increase of the IL content. POM was employed to evaluate the changes in the surface morphology due to the inclusion of salt and IL in the PVA. The compositional nature of the GPE films was examined via FTIR studies. The electrical and electrochemical properties were characterized by cyclic voltammetry and electrochemical impedance spectroscopy. The maximum conductivity for the GPE film was estimated to be 1.10 × 10-5 S/cm for 6% (mass fraction) of IL in the polymer–salt complex. The ionic transference number was approximately 0.97. An electrochemical double-layer capacitor (EDLC) was built from optimized GPE films and reduced graphene oxide-based electrodes. The specific capacitance calculated from the cyclic voltammograms of the EDLC cells was 3 F/g.
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    Adaptive Human-Robot Collaboration Control Based on Optimal Admittance Parameters
    YU Xinyi (禹鑫燚), WU Jiaxin (吴加鑫), XU Chengjun (许成军), LUO Huizhen (罗惠珍), OU Linlin∗ (欧林林)
    J Shanghai Jiaotong Univ Sci    2022, 27 (5): 589-601.   DOI: 10.1007/s12204-022-2460-3
    Abstract224)      PDF (1674KB)(91)      
    In order to help the operator perform the human-robot collaboration task and optimize the task performance, an adaptive control method based on optimal admittance parameters is proposed. The overall control structure with the inner loop and outer loop is first established. The tasks of the inner loop and outer loop are robot control and task optimization, respectively. Then an inner-loop robot controller integrated with barrier Lyapunov function and radial basis function neural networks is proposed, which makes the robot with unknown dynamics securely behave like a prescribed robot admittance model sensed by the operator. Subsequently, the optimal parameters of the robot admittance model are obtained in the outer loop to minimize the task tracking error and interaction force. The optimization problem of the robot admittance model is transformed into a linear quadratic regulator problem by constructing the human-robot collaboration system model. The model includes the unknown dynamics of the operator and the task performance details. For relaxing the requirement of the system model, the integral reinforcement learning is employed to solve the linear quadratic regulator problem. Besides, an auxiliary force is designed to help the operator complete the specific task better. Compared with the traditional control scheme, the security performance and interaction performance of the human-robot collaboration system are improved. The effectiveness of the proposed method is verified through two numerical simulations. In addition, a practical human-robot collaboration experiment is carried out to demonstrate the performance of the proposed method.
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    Path Planning and Optimization of Humanoid Manipulator in Cartesian Space
    LI Shiqi (李世其), LI Xiao∗ (李肖), HAN Ke (韩可), XIONG Youjun (熊友军), XIE Zheng (谢铮), CHEN Jinliang (陈金亮)
    J Shanghai Jiaotong Univ Sci    2022, 27 (5): 614-620.   DOI: 10.1007/s12204-022-2416-7
    Abstract214)      PDF (1591KB)(41)      
    To solve the problems of low efficiency and multi-solvability of humanoid manipulator Cartesian space path planning in physical human-robot interaction, an improved bi-directional rapidly-exploring random tree algorithm based on greedy growth strategy in 3D space is proposed. The workspace of manipulator established based on Monte Carlo method is used as the sampling space of the rapidly-exploring random tree, and the opposite expanding greedy growth strategy is added in the random tree expansion process to improve the path planning efficiency. Then the generated path is reversely optimized to shorten the length of the planned path, and the optimized path is interpolated and pose searched in Cartesian space to form a collision-free optimized path suitable for humanoid manipulator motion. Finally, the validity and reliability of the algorithm are verified in an intelligent elderly care service scenario based on Walker2, a large humanoid service robot.
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    Airframe Damage Region Division Method Based on Structure Tensor Dynamic Operator
    CAI Shuyu∗ (蔡舒妤), SHI Lizhong (师利中)
    J Shanghai Jiaotong Univ Sci    2022, 27 (6): 757-767.   DOI: 10.1007/s12204-022-2498-2
    Abstract191)      PDF (1607KB)(76)      
    In order to improve the accuracy of damage region division and eliminate the interference of damage adjacent region, the airframe damage region division method based on the structure tensor dynamic operator is proposed in this paper. The structure tensor feature space is established to represent the local features of damage images. It makes different damage images have the same feature distribution, and transform varied damage region division into consistent process of feature space division. On this basis, the structure tensor dynamic operator generation method is designed. It integrates with bacteria foraging optimization algorithm improved by defining double fitness function and chemotaxis rules, in order to calculate the parameters of dynamic operator generation method and realize the structure tensor feature space division. And then the airframe damage region division is realized. The experimental results on different airframe structure damage images show that compared with traditional threshold division method, the proposed method can improve the division quality. The interference of damage adjacent region is eliminated. The information loss caused by over-segmentation is avoided. And it is efficient in operation, and consistent in process. It also has the applicability to different types of structural damage.
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    Automatic Removal of Multiple Artifacts for Single-Channel Electroencephalography
    ZHANG Chenbei (张晨贝), SABOR Nabil, LUO Junwen (罗竣文), PU Yu (蒲 宇), WANG Guoxing (王国兴), LIAN Yong∗ (连 勇)
    J Shanghai Jiaotong Univ Sci    2022, 27 (4): 437-451.   DOI: 10.1007/s12204-021-2374-5
    Abstract190)      PDF (2934KB)(98)      
    Removing different types of artifacts from the electroencephalography (EEG) recordings is a critical step in performing EEG signal analysis and diagnosis. Most of the existing algorithms aim for removing single type of artifacts, leading to a complex system if an EEG recording contains different types of artifacts. With the advancement in wearable technologies, it is necessary to develop an energy-efficient algorithm to deal with different types of artifacts for single-channel wearable EEG devices. In this paper, an automatic EEG artifact removal algorithm is proposed that effectively reduces three types of artifacts, i.e., ocular artifact (OA), transmission- line/harmonic-wave artifact (TA/HA), and muscle artifact (MA), from a single-channel EEG recording. The effectiveness of the proposed algorithm is verified on both simulated noisy EEG signals and real EEG from CHB- MIT dataset. The experimental results show that the proposed algorithm effectively suppresses OA, MA and TA/HA from a single-channel EEG recording as well as physical movement artifact.
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    Generation Approach of Human-Robot Cooperative Assembly Strategy Based on Transfer Learning
    LÜ Qibing (吕其兵), LIU Tianyuan (刘天元), ZHANG Rong (张荣), JIANG Yanan (江亚南), XIAO Lei (肖雷), BAO Jingsong∗ (鲍劲松)
    J Shanghai Jiaotong Univ Sci    2022, 27 (5): 602-613.   DOI: 10.1007/s12204-022-2493-7
    Abstract167)      PDF (3845KB)(45)      
    In current small batch and customized production mode, the products change rapidly and the personal demand increases sharply. Human-robot cooperation combining the advantages of human and robot is an effective way to solve the complex assembly. However, the poor reusability of historical assembly knowledge reduces the adaptability of assembly system to different tasks. For cross-domain strategy transfer, we propose a human-robot cooperative assembly (HRCA) framework which consists of three main modules: expression of HRCA strategy, transferring of HRCA strategy, and adaptive planning of motion path. Based on the analysis of subject capability and component properties, the HRCA strategy suitable for specific tasks is designed. Then the reinforcement learning is established to optimize the parameters of target encoder for feature extraction. After classification and segmentation, the actor-critic model is built to realize the adaptive path planning with progressive neural network. Finally, the proposed framework is verified to adapt to the multi-variety environment, for example, power lithium batteries.
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    Construction on Aerodynamic Surrogate Model of Stratospheric Airship
    QIN Pengfei (秦鹏飞), WANG Xiaoliang∗ (王晓亮)
    J Shanghai Jiaotong Univ Sci    2022, 27 (6): 768-779.   DOI: 10.1007/s12204-022-2494-6
    Abstract167)      PDF (3866KB)(54)      
    Stratospheric airship can stay at an altitude of 20 km for a long time and carry various loads to achieve long-term stable applications. Conventional stratospheric airship configuration mainly includes a low-resistance streamline hull and inflatable “X”-layout fins that realize the self-stabilization. A fast aerodynamic predictive method is needed in the optimization design of airship configuration and the flight performance analysis. In this paper, a predictive surrogate model of aerodynamic parameters is constructed for the stratospheric airship with “X” fins based on the neural network. First, a geometric shape parameterized model, and a flow field parameterized model were established, and the aerodynamic coefficients of airships with different shapes used as the training and test samples were calculated based on computational fluid dynamics (SA turbulence model). The improved Bayesian regularized neural network was used as the surrogate model, and 20 types of airships with different shapes were used to test the effectiveness of network. It showed that the correlation coefficients of Cx, Cy, Cz, CM,x, CM,y, CM,z were 0.928 7, 0.991 7, 0.991 9, 0.958 2, 0.986 1, 0.984 2, respectively. The aerodynamic coefficient distribution contour at different angles of attack and sideslip angles is used to verify the reliability of the method. The method can provide an effective way for a rapid estimation of aerodynamic coefficients in the airship design.
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    System Life and Reliability Modeling of a Multiple Power Takeoffs Accessory Gearbox Transmission
    WANG Kai∗ (汪 凯), WANG Xianliang (王宪良), ZHU Jiazan (朱加赞), OU Daisong (欧代松), PAN Daifeng (潘代锋)
    J Shanghai Jiaotong Univ Sci    2022, 27 (6): 855-866.   DOI: 10.1007/s12204-022-2473-y
    Abstract158)      PDF (1635KB)(23)      
    A mathematical model for system life and reliability of a multiple power takeoffs aeroengine accessory gearbox transmission is presented. The geometry model of gear train is distributed into several subsystems by different transmitted powers. The lives of each component are combined to determine the units, subsystems and entire system lives sequentially according to a strict series probability model. The unit and subsystem interface models are defined to dispose the loads of common components. The algorithm verification is presented and a numerical example is given to illustrate the use of this program. The initial design could not fulfill the life requirement. A design modification shows that the gear train has a more balanced life distribution by strengthening the weak parts, and the overall life of entire system is increased above the design requirement. This program can help the designer to approach an optimal accessory gearbox transmission design efficiently.
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    Gram Matrix-Based Convolutional Neural Network for Biometric Identification Using Photoplethysmography Signal
    WU Caiyu, (吴彩钰), SABOR Nabil, ZHOU Shihong, (周世鸿), WANG Min, (王 敏), YING Liang (应 亮), WANG Guoxing∗ (王国兴)
    J Shanghai Jiaotong Univ Sci    2022, 27 (4): 463-472.   DOI: 10.1007/s12204-022-2426-5
    Abstract158)      PDF (1049KB)(30)      
    As a kind of physical signals that could be easily acquired in daily life, photoplethysmography (PPG) signal becomes a promising solution to biometric identification for daily access management system (AMS). State- of-the-art PPG-based identification systems are susceptible to the form of motions and physical conditions of the subjects. In this work, to exploit the advantage of deep learning, we developed an improved deep convolutional neural network (CNN) architecture by using the Gram matrix (GM) technique to convert time-serial PPG signals to two-dimensional images with a temporal dependency to improve accuracy under different forms of motions. To ensure a fair evaluation, we have adopted cross-validation method and “training and testing” dataset splitting method on the TROIKA dataset collected in ambulatory conditions. As a result, the proposed GM-CNN method achieved accuracy improvement from 69.5% to 92.4%, which is the best result in terms of multi-class classification compared with state-of-the-art models. Based on average five-fold cross-validation, we achieved an accuracy of 99.2%, improved the accuracy by 3.3% compared with the best existing method for the binary-class.
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    Intelligent Driving Assistance System for Safe Expressway Driving in Rainy and Foggy Weather based on IoT
    YAN Beirui (燕北瑞), FANG Cheng (方 成), QIU Hao (邱 昊), ZHU Wenfeng∗ (朱文峰)
    J Shanghai Jiaotong Univ Sci    2023, 28 (1): 10-19.   DOI: 10.1007/s12204-023-2564-4
    Abstract157)      PDF (2162KB)(32)      
    The feature bends and tunnels of mountainous expressways are often affected by bad weather, specifically rain and fog, which significantly threaten expressway safety and traffic efficiency. In order to solve this problem, a vehicle–road coordination system based on the Internet of Things (IoT) is developed that can share vehicle–road information in real time, expand the environmental perception range of vehicles, and realize vehicle–road collaboration. It helps improve traffic safety and efficiency. Further, a vehicle–road cooperative driving assistance system model is introduced in this study, and it is based on IoT for improving the driving safety of mountainous expressways. Considering the influence of rain and fog on driving safety, the interaction between rainfall, water film, and adhesion coefficient is analyzed. An intelligent vehicle–road coordination assistance system is constructed that takes in information on weather, road parameters, and vehicle status, and takes the stopping sight distance model as well as rollover and sideslip model as boundary constraints. Tests conducted on a real expressway demonstrated that the assistance system model is helpful in bad weather conditions. This system could promote intelligent development of mountainous expressways.
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    Bending Prediction Method of Multi-Cavity Soft Actuator
    HUO Qianjun (霍前俊), LIU Sheng∗ (刘胜), XU Qingyu (徐青瑜), ZHANG Yuanfei (张远飞), ZHANG Yaoyao (张耀耀), LI Xu (李旭)
    J Shanghai Jiaotong Univ Sci    2022, 27 (5): 631-637.   DOI: 10.1007/s12204-021-2334-0
    Abstract155)      PDF (1302KB)(20)      
    The multi-cavity soft actuator is assembled from single-cavity soft actuator through a reasonable geometric distribution. It has the characteristic that the pneumatic soft actuator is driven by its own deformation and has more degrees of freedom. Pneumatic soft actuator is widely used as an emerging discipline and its strong compliance has been greatly developed and applied. However, as the most application potential type of soft actuators, there is still a lack of simple and effective deformation prediction methods for studying the spatial deformation of multi-cavity soft actuators. To solve this problem, a vector equation method is proposed based on the analysis of the principle of the space deformation of the two-cavity, three-cavity and four-cavity soft actuators. Furthermore, a nonlinear mathematical model of the air pressure, space position and deformation trajectory of the soft actuator end is established by combining the vector equation method. Finally, the three-channel soft actuator is verified through experiments. The results show that the mathematical model can better predict the space deformation trajectory of the soft actuator, which provides a new research method for studying the space deformation of the multi-channel soft actuator.
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    Action-aware Encoder-Decoder Network for Pedestrian Trajectory Prediction
    FU Jiawei∗ (傅家威), ZHAO Xu (赵 旭)
    J Shanghai Jiaotong Univ Sci    2023, 28 (1): 20-27.   DOI: 10.1007/s12204-023-2565-3
    Abstract150)      PDF (775KB)(46)      
    Accurate pedestrian trajectory predictions are critical in self-driving systems, as they are fundamental to the response- and decision-making of ego vehicles. In this study, we focus on the problem of predicting the future trajectory of pedestrians from a first-person perspective. Most existing trajectory prediction methods from the first-person view copy the bird’s-eye view, neglecting the differences between the two. To this end, we clarify the differences between the two views and highlight the importance of action-aware trajectory prediction in the first-person view. We propose a new action-aware network based on an encoder-decoder framework with an action prediction and a goal estimation branch at the end of the encoder. In the decoder part, bidirectional long short-term memory (Bi-LSTM) blocks are adopted to generate the ultimate prediction of pedestrians’ future trajectories. Our method was evaluated on a public dataset and achieved a competitive performance, compared with other approaches. An ablation study demonstrates the effectiveness of the action prediction branch.
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    Strength-Toughness Improvement of 15-5PH Stainless Steel by Double Aging Treatment
    TE Rigele (特日格乐), ZHANG Yutuo, ∗ (张玉妥)
    J Shanghai Jiaotong Univ Sci    2023, 28 (2): 270-279.   DOI: 10.1007/s12204-021-2390-5
    Abstract149)      PDF (3166KB)(46)      
    To obtain better strength-toughness balance of 15-5PH stainless steel, a double aging treatment is proposed to investigate the mechanical properties and microstructure evolution. In this study, Cu precipitates and reversed austenite played a determining role to improve strength-toughness combination. The microstructure was observed using electron backscattered diffraction, transmission electron microscopy and scanning transmission electron microscopy. The volume fractions of Cu precipitates and reversed austenite were calculated with Thermo-Calc software and measured by X-ray diffraction. The results showed that the reversed austenite is formed at the martensitic lath boundaries and its volume fraction also increases with the increase of the aging temperature. At the same time, the size of the Cu precipitates gradually increases. Compared with the traditional single aging and double aging treatment, double aging treatment of 15-5PH stainless steel can increase the toughness while retaining the necessary strength. During double aging of 550 ℃ × 4 h + 580 ℃ × 1 h, 15-5PH stainless steel has the best strength and low-temperature (- 40 ℃) toughness match. Its yield strength, ultimate tensile strength and the Charpy impact energy are 1.037 GPa, 1.086 GPa and 179 J, respectively.
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    Improved Spatial Registration Algorithm for Sensors on Multiple Mobile Platforms
    LÜ Runyan (吕润妍), PENG Na (彭娜), WU Yi (吴怡), CAI Yunze∗ (蔡云泽)
    J Shanghai Jiaotong Univ Sci    2022, 27 (5): 638-648.   DOI: 10.1007/s12204-022-2457-y
    Abstract148)      PDF (1035KB)(20)      
    This paper focuses on the spatial registration algorithm under the earth-centered earth-fixed (ECEF) coordinate system for multiple mobile platforms. The sensor measurement biases are discussed with the platform attitude information taken into consideration. First, the biased measurement model is constructed. Besides, the maximum likelihood registration (MLR) algorithm is discussed to simultaneously estimate the measurement biases and the target state. Finally, an improved online MLR (IMLR) algorithm is proposed through a sliding window of adaptive size. Simulation results demonstrate that the proposed IMLR algorithm effectively improves the realtime ability of the system and can approach similar estimation accuracy to the conventional MLR algorithm.
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    Further Result on the Observer Design for One-Sided Lipschitz Systems
    YANG Ming1 (杨 明), HUANG Jun1∗ (黄 俊), ZHANG Wei2 (章 伟)
    J Shanghai Jiaotong Univ Sci    2022, 27 (6): 817-822.   DOI: 10.1007/s12204-020-2252-6
    Abstract142)      PDF (328KB)(80)      
    This paper investigates the problem of observer design for a class of control systems. Different from current works, the nonlinear functions in the system only satisfy the property of the one-sided Lipschitz (OSL) condition but not quadratic inner-boundedness (QIB). Moreover, the case where the OSL constant is negative is specially investigated. Firstly, a full-order observer is constructed for the original system. Then, a reduced-order observer is also designed by using the decomposition method. The advantage and effectiveness of the proposed design scheme are shown in a numerical simulation.
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    Breast Pathological Image Classification Based on VGG16 Feature Concatenation
    LIU Min (刘 敏), YI Ming (易 鸣), WU Minghu∗ (武明虎), WANG Juan (王 娟), HE Yu (何 宇)
    J Shanghai Jiaotong Univ Sci    2022, 27 (4): 473-484.   DOI: 10.1007/s12204-021-2398-x
    Abstract140)      PDF (5914KB)(23)      
    Breast cancer is one of the malignancies that endanger women’s health all over the world. Considering that there is some noise and edge blurring in breast pathological images, it is easier to extract shallow features of noise and redundant information when VGG16 network is used, which is affected by its relative shallow depth and small convolution kernel. To improve the pathological diagnosis of breast cancers, we propose a classification method for benign and malignant tumors in the breast pathological images which is based on feature concatenation of VGG16 network. First, in order to improve the problems of small dataset size and unbalanced data samples, the original BreakHis dataset is processed by data augmentation technologies, such as geometric transformation and color enhancement. Then, to reduce noise and edge blurring in breast pathological images, we perform bilateral filtering and denoising on the original dataset and sharpen the edge features by Sobel operator, which makes the extraction of shallow features by VGG16 model more accurate. Based on transfer learning, the network model trained with the expanded dataset is called VGG16-1, and another model trained with the image denoising and sharpening and mixed with the original dataset is called VGG16-2. The features extracted by VGG16-1 and VGG16-2 are concatenated, and then classified by support vector machine. The final experimental results show that the average accuracy is 98.44%, 98.89%, 98.30% and 97.47%, respectively, when the proposed method is tested with the breast pathological images of 40×, 100×, 200× and 400× on BreakHis dataset.
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    Reliability Evaluation of Two-Phase Degradation Process with a Fuzzy Change-Point
    LIU Kai1 (刘 凯), DANG Wei1 (党 炜), ZOU Tianji1,2∗ (邹田骥), LÜ Congmin1 (吕从民), LI Peng1,2 (李 鹏), ZHANG Haitao1 (张海涛)
    J Shanghai Jiaotong Univ Sci    2022, 27 (6): 867-872.   DOI: 10.1007/s12204-021-2323-3
    Abstract139)      PDF (484KB)(47)      
    For some products, degradation mechanisms change during testing, and therefore, their degradation patterns vary at different points in time; these points are called change-points. Owing to the limitation of measurement costs, time intervals for degradation measurements are usually very long, and thus, the value of change-points cannot be determined. Conventionally, a certain degradation measurement is selected as the change-point in a two-phase degradation process. According to the tendency of the two-phase degradation process, the change-point is probably located in the interval between two neighboring degradation measurements, and it is a fuzzy variable. The imprecision of the change-point may lead to the incorrect product’s reliability evaluation results. In this paper, based on the fuzzy theory, a two-phase degradation model with a fuzzy change-point and a statistical analysis method are proposed. First, a two-phase Wiener degradation model is developed according to the membership function of the change-point. Second, the reliability evaluation is carried out using maximum likelihood estimation and a fuzzy simulation approach. Finally, the proposed methodology is verified via a case study. The results of the study show that the proposed methodology can achieve more believable reliability evaluation results compared with those of the conventional approach.
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    Game Theory Based Sensor Management in Reducing Target Threat Level Assessment Risk
    PANG Ce∗ (庞策), SHAN Ganlin (单甘霖)
    J Shanghai Jiaotong Univ Sci    2022, 27 (5): 649-659.   DOI: 10.1007/s12204-021-2372-7
    Abstract138)      PDF (822KB)(28)      
    Sensor management schemes are calculated to reduce target threat level assessment risk in this paper. Hidden Markov model and risk theory are combined to build the target threat level model firstly. Then the target threat level estimation risk is defined. And the sensor management schemes are optimized with the smallest target threat level assessment risk. What’s more, the game theory is applied to calculate the optimal sensor management scheme. Some simulations are conducted to prove that the proposed sensor management method is effective.
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    Ant Colony Algorithm Path Planning Based on Grid Feature Point Extraction
    LI Erchao∗ (李二超), QI Kuankuan (齐款款)
    J Shanghai Jiaotong Univ Sci    2023, 28 (1): 86-99.   DOI: 10.1007/s12204-023-2572-4
    Abstract134)      PDF (1196KB)(77)      
    Aimed at the problems of a traditional ant colony algorithm, such as the path search direction and field of view, an inability to find the shortest path, a propensity toward deadlock and an unsmooth path, an ant colony algorithm for use in a new environment is proposed. First, the feature points of an obstacle are extracted to preprocess the grid map environment, which can avoid entering a trap and solve the deadlock problem. Second, these feature points are used as pathfinding access nodes to reduce the node access, with more moving directions to be selected, and the locations of the feature points to be selected determine the range of the pathfinding field of view. Then, based on the feature points, an unequal distribution of pheromones and a two-way parallel path search are used to improve the construction efficiency of the solution, an improved heuristic function is used to enhance the guiding role of the path search, and the pheromone volatilization coefficient is dynamically adjusted to avoid a premature convergence of the algorithm. Third, a Bezier curve is used to smooth the shortest path obtained. Finally, using grid maps with a different complexity and different scales, a simulation comparing the results of the proposed algorithm with those of traditional and other improved ant colony algorithms verifies its feasibility and superiority.
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    Target Detection Algorithm Based On Human Judge Mechanism
    SHI Jichao1 (石继超), WANG Ziheng2 (王子恒), ZHAO Xianchao1 (赵现朝), ZHANG Zhinan1∗ (张执南)
    J Shanghai Jiaotong Univ Sci    2022, 27 (5): 660-670.   DOI: 10.1007/s12204-022-2450-5
    Abstract132)      PDF (1795KB)(26)      
    A D-G-YOLOV3 algorithm was proposed to identify and judge recyclables, which introduced a dense feature network to replace the feature pyramid network. The network closely connects and fits the feature maps and simulates human judgment mechanism. A three-stage judgment is made for judgment objects with lower confidence. Based on the judgment of the original image, the second-stage judgment is carried out after the channel contrast is increased. Finally, sampling is performed on the region of interest where the second-stage confidence score wins for the third stage of judgment, and then judgment result is sent to the gated recurrent unit network for final inference. The result shows that through experiments on the same recyclables data set, the algorithm reduces the missed detection rate by 15.54%, and the false detection rate by 0.97%, while improves the accuracy rate by 16.51%.
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    Case Study of a Personalized Scoliosis Brace Based on 3D Printing
    LU Dezhi 1,2‡ (鲁德志), LI Wentao1‡ (李文韬), WANG Xiaowen2 (王孝文), SONG Yan2 (宋 艳), ZHANG Pingping2 (张萍萍), FENG Haiyang2 (冯海洋), WU Yuncheng1 (吴云成), XU Yuanjing3 (许苑晶), LI Tao4 (李 涛), MA Zhenjiang1∗ (马振江), WANG Jinwu1,2∗ (王金武)
    J Shanghai Jiaotong Univ Sci    2022, 27 (4): 528-534.   DOI: 10.1007/s12204-022-2461-2
    Abstract132)      PDF (653KB)(30)      
    We evaluated the effect of a new type of brace (primary material 3300PA) for treating scoliosis, which was produced based on 3D printing technology combined with a non-contact optical mold-taking and computer- aided design. Through the production of a brace for a 13-year-old patient with adolescent idiopathic scoliosis by a multidisciplinary team, the digital design and 3D printing of a personalized scoliosis brace were introduced. Parameters such as the Cobb angle, angle of trunk inclination, spine-coronal plane balance parameters, sagittal vertical axis (SVA), and Scoliosis Research Society-22 score (SRS-22) were measured to evaluate the treatment effect of the brace. The model-taking process of the non-contact optical scanner was successful, data were valid, and personalized scoliosis brace made by the computer-aided design and 3D printing fitted well with the patient. Before wearing, immediate in-brace, and 6 months after wearing, the Cobb angles were 29?, 9?, a n d 1 4?, respectively. The offsets between the C7 vertebra plumb line (C7PL) and central sacral vertical line (CSVL) were 3.2 cm, 2.2 cm, and 2.1 cm, respectively. SVAs were 3.3 cm, 2.9 cm, and 0.3 cm, respectively. Apex vertebral translocations were 4.3 cm, 0.3 cm, and 0.1 cm, respectively. The SRS-22 was 76 before brace application and 91 at the 6-month follow-up. The spine curve returned to normal, and the correction effect was obvious. The scoliosis brace indicates the integration between digital medicine and 3D printing technology, which has personalization and customization as advantages. The brace has good wearing comfort, invisibility, and orthopedic function, follows the psychological needs of teenagers, improves patients’ compliance, and improves the correction of the deformity.
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    Infrastructure-Based Vehicle Localization System for Indoor Parking Lot Using RGB-D Cameras
    CAO Bingquan1,2,3 (曹炳全), HE Yuesheng1,2,3∗ (贺越生), ZHUANG Hanyang4 (庄瀚洋), YANG Ming1,2,3 (杨 明)
    J Shanghai Jiaotong Univ Sci    2023, 28 (1): 61-69.   DOI: 10.1007/s12204-023-2569-z
    Abstract129)      PDF (1606KB)(18)      
    Accurate vehicle localization is a key technology for autonomous driving tasks in indoor parking lots, such as automated valet parking. Additionally, infrastructure-based cooperative driving systems have become a means to realizing intelligent driving. In this paper, we propose a novel and practical vehicle localization system using infrastructure-based RGB-D cameras for indoor parking lots. In the proposed system, we design a depth data preprocessing method with both simplicity and efficiency to reduce the computational burden resulting from a large amount of data. Meanwhile, the hardware synchronization for all cameras in the sensor network is not implemented owing to the disadvantage that it is extremely cumbersome and would significantly reduce the scalability of our system in mass deployments. Hence, to address the problem of data distortion accompanying vehicle motion, we propose a vehicle localization method by performing template point cloud registration in distributed depth data. Finally, a complete hardware system was built to verify the feasibility of our solution in a real-world environment. Experiments in an indoor parking lot demonstrated the effectiveness and accuracy of the proposed vehicle localization system, with a maximum root mean squared error of 5 cm at 15 Hz compared with the ground truth.
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    Effect of Moving Endwall on Hub Leakage Flow of Cantilevered Stator in a Linear Compressor Cascade
    ZHENG Biaojie (郑标颉), MA Yuchen (马宇晨), TENG Jinfang∗ (滕金芳), JU Zhenzhou (居振州), ZHU Mingmin (朱铭敏)
    J Shanghai Jiaotong Univ Sci    2022, 27 (6): 780-789.   DOI: 10.1007/s12204-022-2468-8
    Abstract127)      PDF (2018KB)(36)      
    The cantilevered stator has the advantages of reducing mass and axial length of highly loaded compressor. The details of the hub leakage flow resulting from the clearance between the high-speed moving hub and the cantilevered stator hub are unclear. In this paper, the effect of a moving endwall on the hub leakage flow of a cantilevered stator in a linear compressor cascade was studied. After the simulation method was verified with the experimental results, the time-averaged results of unsteady Reynolds averaged Navier-Stokes (URANS) were selected to study a case with a hub clearance of 2 mm. The results show that the effect of the moving endwall of the cantilevered cascade on the general characteristics with below 30% span increases the leakage mass flow rate and reduces the static pressure coefficient at three conditions of 0°, 6°, and -7° incidences, and the change is most significant at -7° incidence. The effect of the moving endwall on the total pressure loss coefficient varies with different operating conditions, which decreases by 15.94% at 0° incidence, and increases by 4.77% and 18.51% at 6° incidence and -7° incidence, respectively. The influence of the moving endwall is below 14% span at -7° incidence, below 23% span at 0° incidence, and below 30% span at 6° incidence. These effects correspond to the static pressure coefficient and the difference of static pressure coefficient representing the blade loading. In designing the cantilevered stator and matching between the stages of a multistage compressor, the quantitative research results of this paper have certain guiding significance.
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    Data Driven Model-Free Adaptive Control Method for Quadrotor Trajectory Tracking Based on Improved Sliding Mode Algorithm
    YUAN Dongdong (袁冬冬), WANG Yankai∗ (王彦恺)
    J Shanghai Jiaotong Univ Sci    2022, 27 (6): 790-798.   DOI: 10.1007/s12204-020-2254-4
    Abstract127)      PDF (1004KB)(37)      
    In order to solve the problems of dynamic modeling and complicated parameters identification of trajectory tracking control of the quadrotor, a data driven model-free adaptive control method based on the improved sliding mode control (ISMC) algorithm is designed, which does not depend on the precise dynamic model of the quadrotor. The design of the general sliding mode control (SMC) algorithm depends on the mathematical model of the quadrotor and has chattering problems. In this paper, according to the dynamic characteristics of the quadrotor, an adaptive update law is introduced and a saturation function is used to improve the SMC. The proposed control strategy has an inner and an outer loop control structures. The outer loop position control provides the required reference attitude angle for the inner loop. The inner loop attitude control ensures rapid convergence of the attitude angle. The effectiveness and feasibility of the algorithm are verified by mathematical simulation. The mathematical simulation results show that the designed model-free adaptive control method of the quadrotor is effective, and it can effectively realize the trajectory tracking control of the quadrotor. The design of the controller does not depend on the kinematic and dynamic models of the unmanned aerial vehicle (UAV), and has high control accuracy, stability, and robustness.
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    Semantic Segmentation-Based Road Marking Detection Using Around View Monitoring System
    XU Hanqing (徐汉卿), YANG Ming∗ (杨 明), DENG Liuyuan (邓琉元), LI Hao (李 颢), WANG Chunxiang, (王春香), HAN Weibin (韩伟斌), YU Yuelong (于跃龙)
    J Shanghai Jiaotong Univ Sci    2022, 27 (6): 833-843.   DOI: 10.1007/s12204-021-2401-6
    Abstract126)      PDF (1134KB)(41)      
    Road marking detection is an important branch in autonomous driving, understanding the road information. In recent years, deep-learning-based semantic segmentation methods for road marking detection have been arising since they can generalize detection result well under complicated environments and hold rich pixel-level semantic information. Nevertheless, the previous methods mostly study the training process of the segmentation network, while omitting the time cost of manually annotating pixel-level data. Besides, the pixel-level semantic segmentation results need to be fitted into more reliable and compact models so that geometrical information of road markings can be explicitly obtained. In order to tackle the above problems, this paper describes a semantic segmentation-based road marking detection method using around view monitoring system. A semiautomatic semantic annotation platform is developed, which exploits an auxiliary segmentation graph to speed up the annotation process while guaranteeing the annotation accuracy. A segmentation-based detection module is also described, which models the semantic segmentation results for the more robust and compact analysis. The proposed detection module is composed of three parts: vote-based segmentation fusion filtering, graph-based road marking clustering, and road-marking fitting. Experiments under various scenarios show that the semantic segmentation-based detection method can achieve accurate, robust, and real-time detection performance.
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    Mechanical Analysis Methods of Cantilever Gearbox Housing
    WANG Jue∗ (王 珏), LI Peng (李 朋), SONG Shiyao (宋诗瑶)
    J Shanghai Jiaotong Univ Sci    2023, 28 (2): 233-242.   DOI: 10.1007/s12204-021-2316-2
    Abstract126)      PDF (2037KB)(21)      
    The mechanical state of cantilever gearbox housing is different from ordinary ones due to the long arm of force caused by cantilever structure. Conventional mechanical analysis methods either took cantilever gearbox housing as ordinary ones or cantilever beam. Few published papers have specially focused on mechanical analysis method for cantilever gearbox housing. This paper takes a longwall shearer cutting unit gearbox (SCUG) as an example and the mechanical analysis method is investigated according to the causes of fatigue for SCUG. Force analysis model is established for finding out regions of static fatigue caused by low-frequency loads, and local resonance analysis is used for finding out regions of vibration fatigue caused by high-frequency loads. Not only bending moment but also torque caused by gear meshing forces is taken into account in the force analysis model. Vibration response is obtained from cutting experiment, and dominant frequencies of local resonance are obtained by frequency domain analysis. Finite element model of SCUG is established, and natural frequencies and strain modes are analyzed for obtaining the main vibration modes corresponding to dominant frequencies. Hence, large stress regions caused by low and high frequency loads are obtained. Results show that the worst working condition is oblique cutting, and the stress of B-B in 600 mm cutting depth can reach 166 MPa. Obviously, 950 Hz, 1 250 Hz, and 1 400 Hz are dominant frequencies of SCUG (23rd, 25th and 27th natural frequencies). Generally, this paper proposes some principles for mechanical analysis method of cantilever gearbox housing.
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    A Class of Distributed Variable Structure Multiple Model Algorithm Based on Posterior Information of Information Matrix
    HUANG Yinghao1,2 (黄颖浩), WU Yi3 (吴怡), YAO Lixiu2 (姚莉秀), CAI Yunze1,2∗ (蔡云泽)
    J Shanghai Jiaotong Univ Sci    2022, 27 (5): 671-679.   DOI: 10.1007/s12204-022-2458-x
    Abstract126)      PDF (980KB)(24)      
    The tracking of maneuvering targets in radar networking scenarios is studied in this paper. For the interacting multiple model algorithm and the expected-mode augmentation algorithm, the fixed base model set leads to a mismatch between the model set and the target motion mode, which causes the reduction on tracking accuracy. An adaptive grid-expected-mode augmentation variable structure multiple model algorithm is proposed. The adaptive grid algorithm based on the turning model is extended to the two-dimensional pattern space to realize the self-adaptation of the model set. Furthermore, combining with the unscented information filtering, and by interacting the measurement information of neighboring radars and iterating information matrix with consistency strategy, a distributed target tracking algorithm based on the posterior information of the information matrix is proposed. For the problem of filtering divergence while target is leaving radar surveillance area, a k-coverage algorithm based on particle swarm optimization is applied to plan the radar motion trajectory for achieving filtering convergence.
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    Effects of Elastic Joints on Performances of a Close-Chained Rod Rolling Robot
    ZHAO Chenliang (赵晨亮), ZHANG Xiuli∗ (张秀丽), HUANG Senwei (黄森威), YAO Yan’an (姚燕安)
    J Shanghai Jiaotong Univ Sci    2022, 27 (5): 621-630.   DOI: 10.1007/s12204-021-2289-1
    Abstract126)      PDF (1792KB)(23)      
    In rolling experiments, the performances of spider-like robot are limited greatly by its motors’ driving ability; meanwhile, the ground reaction forces are so great that they damaged the rods. In this paper, we solve above problems both mechanically and by control. Firstly, we design the parameters of the central pattern generator (CPG) network based on the kinematics of the robot to enable a smooth rolling trajectory. And we also analyze the kinematic rolling and dynamic rolling briefly. Secondly, we add torsion springs to the passive joints of the spider-like robot aiming to make use of its energy storage capacity to compensate the insufficient torque. The simulation results show that the optimized CPG control parameters can reduce the fluctuation of the mass center and the ground reaction forces. The torsion spring can reduce the peak torque requirements of the actuated joints by 50%.
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    Indoor Vehicle Positioning Based on Multi-Sensor Data Fusion
    WANG Mingyang (王明阳), SHI Liangren∗ (时良仁), LI Yuanlong (李元龙)
    J Shanghai Jiaotong Univ Sci    2023, 28 (1): 77-85.   DOI: 10.1007/s12204-023-2571-5
    Abstract123)      PDF (705KB)(30)      
    This study proposes a Kalman filter-based indoor vehicle positioning method for cases in which the steering angle and rotation speed of the vehicle’s wheels are unknown. By fusing the position and velocity data from the ultra-wideband sensors and acceleration and orientation data from the inertial measurement unit, we developed two algorithms to estimate the real-time position of the vehicle based on a linear Kalman filter and extended Kalman filter, respectively. We then conducted simulations and experiments to examine the performances of the algorithms. In the experiment, the Kalman filtering hyperparameters are configured, and we then ran the two algorithms to determine the positioning precision and accuracy with the ground truth produced via LiDAR. We verified that our method can improve precision and accuracy compared with the raw positioning data and can achieve desirable effects for indoor vehicle positioning when vehicles travel at low speeds.
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    Air Combat Assignment Problem Based on Bayesian Optimization Algorithm
    FU Lia (傅 莉), LONG Xia∗ (龙 洗), HE Wenbinb (何文斌)
    J Shanghai Jiaotong Univ Sci    2022, 27 (6): 799-805.   DOI: 10.1007/s12204-021-2270-z
    Abstract123)      PDF (519KB)(40)      
    In order to adapt to the changing battlefield situation and improve the combat effectiveness of air combat, the problem of air battle allocation based on Bayesian optimization algorithm (BOA) is studied. First, we discuss the number of fighters on both sides, and apply cluster analysis to divide our fighter into the same number of groups as the enemy. On this basis, we sort each of our fighters’ different advantages to the enemy fighters, and obtain a series of target allocation schemes for enemy attacks by first in first serviced criteria. Finally, the maximum advantage function is used as the target, and the BOA is used to optimize the model. The simulation results show that the established model has certain decision-making ability, and the BOA can converge to the global optimal solution at a faster speed, which can effectively solve the air combat task assignment problem.
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    Impact Angle/Time Constraint Guidance Design Based on Fast Terminal Error Dynamics
    QIN Xuesheng (秦雪升), LIU Yuanhe (刘远贺), LI Kebo (黎克波), LIANG Yangang∗ (梁彦刚)
    J Shanghai Jiaotong Univ Sci    2022, 27 (6): 823-832.   DOI: 10.1007/s12204-022-2509-3
    Abstract121)      PDF (532KB)(34)      
    Considering the problem that the optimal error dynamics can only converge at the terminal time, an impact angle/time constraint missile guidance law with finite-time convergence is designed in this paper, which is based on the pure proportional navigation (PPN) guidance law and the fast terminal error dynamics (FTED) approach. The missile guidance model and FTED equation are given first, and the dynamic equation of impact angle/time error based on PPN is also derived. Then, the guidance law is designed based on FTED, and the guidance error can converge to 0 in a finite time. Furthermore, considering the field of view constraint, the guidance law is improved by using the saturation function mapping method. Finally, a numerical simulation example is given to verify the effectiveness of the guidance law, which shows that the guidance law proposed in this paper can make the missile quickly adjust to the desired states in advance, and effectively relieve the overload saturation pressure of the actuator.
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    Synthesis and Characterization of Copper Doped Zinc Oxide Thin Films Deposited by RF/DC Sputtering Technique
    KHAN Mohibul, ALAM Md. Shabaz, AHMED Sk. Faruque∗
    J Shanghai Jiaotong Univ Sci    2023, 28 (2): 172-179.   DOI: 10.1007/s12204-022-2462-1
    Abstract120)      PDF (698KB)(39)      
    Undoped and copper (Cu) doped zinc oxide (Zn1-xCuxO, where x = 0—0.065) nano crystal thin films have been deposited on glass substrate via RF/DC reactive co-sputtering technique. The aim of this work is to investigate the crystal structure of ZnO and Cu doped ZnO thin films and also study the effect of Cu doping on optical band gap of ZnO thin films. The identification and confirmation of the crystallinity, film thickness and surface morphology of the nano range thin films are confirmed by using X-ray diffractometer (XRD), scanning electron microscope and atomic force microscope. The XRD peak at a diffractive angle of 34.44° and Miller indices at (002) confirms the ZnO thin films. Crystallite size of undoped ZnO thin films is 27 nm and decreases from 27 nm to 22 nm with increasing the atomic fraction of Cu (xCu) in the ZnO thin films from 0 to 6.5% respectively, which is calculated from XRD (002) peaks. The different bonding information of all deposited films was investigated by Fourier transform infrared spectrometer in the range of wave number between 400 cm-1 to 4 000 cm-1. Optical band gap energy of all deposited thin films was analyzed by ultraviolet visible spectrophotometer, which varies from 3.35 eV to 3.19 eV with the increase of xCu from 0 to 6.5% respectively. Urbach energy of the deposited thin films increases from 115 meV to 228 meV with the increase of xCu from 0 to 6.5% respectively.
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    Dynamic Modeling and Performance Evaluation of a Novel Humanoid Ankle Joint
    LI Yanbiao∗ (李研彪), CHEN Ke (陈 科), SUN Peng (孙 鹏), WANG Zesheng (王泽胜)
    J Shanghai Jiaotong Univ Sci    2022, 27 (4): 570-578.   DOI: 10.1007/s12204-022-2422-9
    Abstract119)      PDF (1322KB)(17)      
    Aimed at the problems of design difficulty and weak kinematic performance caused by spherical joint, a novel PRC+PRCR+RR humanoid ankle joint based on the partially decoupled spherical parallel mechanism is proposed. According to screw theory, the degree of freedom and decoupling characteristics of this mechanism are analyzed. Based on Klein formula and virtual work principle, the kinematic expressions of each link and dynamic model are established. The correctness of the dynamic model is verified by combining the virtual prototype software and the ankle pose function obtained by gait planning and Fourier fitting. The workspace of this mechanism is mapped into a two-dimensional polar coordinate system with the azimuth and elevation angles of the spherical coordinate system as parameters. The motion/force transmission index and constraint index of this mechanism are evaluated and expressed in the workspace, showing this mechanism with excellent kinematic characteristics.
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    Electric vehicle charging situation awareness for charging station ultra-short-term load forecast
    SHI Yiwei1 (史一炜), LIU Zeyu1 (刘泽宇), FENG Donghan1∗ (冯冬涵), ZHOU Yun1∗ (周 云), ZHANG Kaiyu2 (张开宇), LI Hengjie3 (李恒杰)
    J Shanghai Jiaotong Univ Sci    2023, 28 (1): 28-38.   DOI: 10.1007/s12204-023-2566-2
    Abstract117)      PDF (1518KB)(27)      
    Electric vehicles (EVs) are expected to be key nodes connecting transportation–electricity–communication networks. Advanced automotive electronics technologies enhance EVs’ perception, computing, and communication capacity, which in turn can boost the operational efficiency of intelligent transportation systems (ITSs). EVs couple the ITS to the power system, providing a promising solution to charging congestion and transformer overload via navigation and forecasting approaches. This study proposes a privacy-preserving EV charging situation awareness framework and method to forecast the ultra-short-term load of charging stations. The proposed method only relies on public information from commercial service providers. In the case study, data are powered by the Baidu LBS cloud and EV-SGCC platform, and the experiment is conducted within an area of Pudong New District in Shanghai. Based on the results, the charging load of charging stations can be adequately forecasted more than 1 min ahead with low communication and computing power requirements. This research provides the basis for further studies on operation optimization and electricity market transaction of charging stations.
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    Multi-UAV Route Re-Generation Method Based on Trajectory Data
    YUAN Dongdong (袁冬冬), WANG Yankai∗ (王彦恺), BAI Jiaqi (白嘉琪)
    J Shanghai Jiaotong Univ Sci    2022, 27 (6): 806-816.   DOI: 10.1007/s12204-021-2332-2
    Abstract116)      PDF (1409KB)(47)      
    A large quantity of unmanned aerial vehicle (UAV) trajectory data related to air traffic information has important value in engineering fields. However, the cost of data and trajectory processing limits the applications, and as the number of UAVs increases rapidly, future UAVs’ path data will be very large. Therefore, this paper designs a multi-UAV route re-generation method based on trajectory data, which can realize the UAVs’ path data compression, de-aggregation, and regeneration tasks. Based on the trajectory data, the three-dimensional Douglas-Peucker algorithm is used to compress the trajectory data to reduce the storage space. The improved B-spline path smoothing algorithm based on the reversing control point is used to depolymerize and smooth the path. Simulation experiments show that the above multi-UAV route re-generation algorithm can obtain a more optimized path while maintaining the important characteristics of the original path.
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    Lidar-Visual-Inertial Odometry with Online Extrinsic Calibration
    MAO Tianyang (茅天阳), ZHAO Wentao (赵文韬), WANG Jingchuan∗ (王景川), CHEN Weidong (陈卫东)
    J Shanghai Jiaotong Univ Sci    2023, 28 (1): 70-76.   DOI: 10.1007/s12204-023-2570-6
    Abstract115)      PDF (988KB)(39)      
    To achieve precise localization, autonomous vehicles usually rely on a multi-sensor perception system surrounding the mobile platform. Calibration is a time-consuming process, and mechanical distortion will cause extrinsic calibration errors. Therefore, we propose a lidar-visual-inertial odometry, which is combined with an adapted sliding window mechanism and allows for online nonlinear optimization and extrinsic calibration. In the adapted sliding window mechanism, spatial-temporal alignment is performed to manage measurements arriving at different frequencies. In nonlinear optimization with online calibration, visual features, cloud features, and inertial measurement unit (IMU) measurements are used to estimate the ego-motion and perform extrinsic calibration. Extensive experiments were carried out on both public datasets and real-world scenarios. Results indicate that the proposed system outperforms state-of-the-art open-source methods when facing challenging sensor-degenerating conditions.
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    Inverse Kinematics Analysis of a 6-DOF Manipulator Using Spherical Geometry Method
    LIU Qunpo1,3 (刘群坡), LIU Guanghui1∗ (刘广辉), FEI Shumin2,3 (费树岷), WANG Haixing1 (王海星), ZHANG Jianjun1,3 (张建军)
    J Shanghai Jiaotong Univ Sci    2022, 27 (5): 680-687.   DOI: 10.1007/s12204-022-2425-6
    Abstract114)      PDF (923KB)(22)      
    A 6-DOF cooperative manipulator is used for human spinal deformity detection. In order to ensure the scanning quality of spinal deformity and improve the solution rate and speed of inverse motion solution of the manipulator, an inverse kinematics analytical method based on spherical geometry is proposed in this paper. We take the AUBO-i5 collaborative manipulator as the research object, which combines the rapidity of analytical solution with the flexibility of spherical solution. In the Robot Operating System, the simulation experiment solves the inverse kinematics of 10 000 sets of randomly generated postures. The success rate and time-consuming of the solution are calculated. Compared with the two commonly used inverse kinematics solving algorithms, TRAC-IK and KDL, this method has obvious advantages in terms of success rate and average time-consuming.
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    Deformable Registration Algorithm via Non-subsampled Contourlet Transform and Saliency Map
    CHANG Qing∗ (常 青), YANG Wenyou (杨文友), CHEN Lanlan (陈兰岚)
    J Shanghai Jiaotong Univ Sci    2022, 27 (4): 452-462.   DOI: 10.1007/s12204-022-2428-3
    Abstract113)      PDF (4867KB)(31)      
    Medical image registration is widely used in image-guided therapy and image-guided surgery to esti- mate spatial correspondence between planning and treatment images. However, most methods based on intensity have the problems of matching ambiguity and ignoring the influence of weak correspondence areas on the overall registration. In this study, we propose a novel general-purpose registration algorithm based on free-form defor- mation by non-subsampled contourlet transform and saliency map, which can reduce the matching ambiguities and maintain the topological structure of weak correspondence areas. An optimization method based on Markov random fields is used to optimize the registration process. Experiments on four public datasets from brain, car- diac, and lung have demonstrated the general applicability and the accuracy of our algorithm compared with two state-of-the-art methods.
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