Top Read Articles

    Published in last 1 year |  In last 2 years |  In last 3 years |  All
    Please wait a minute...
    For Selected: Toggle Thumbnails
    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
    Abstract461)      PDF (2268KB)(175)      
    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.
    Reference | Related Articles | Metrics
    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
    Abstract441)      PDF (467KB)(149)      
    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.
    Reference | Related Articles | Metrics
    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
    Abstract336)      PDF (1140KB)(112)      
    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.
    Reference | Related Articles | Metrics
    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
    Abstract326)      PDF (3166KB)(64)      
    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.
    Reference | Related Articles | Metrics
    Integrated Hydraulic-Driven Wearable Robot for Knee Assistance
    ZHAO Yafei (赵亚飞), HUANG Chaoyi (黄超逸), ZOU Yuging(邹玉莹), ZOUKehan(邹可涵), zoU Xiaogang(邹笑阳), XUE .Jiaqi(薛嘉琦), LI Xiaoting(李晓婷), KOH Keng Huat, WANG Xiaojun(王小军), LAI Wai Chiu King(赖伟超), HU Yong(胡勇), XI Ning(席宁), WANG Zheng(王峥)
    J Shanghai Jiaotong Univ Sci    2023, 28 (3): 289-295.   DOI: 10.1007/s12204-023-2602-2
    Abstract326)      PDF (1156KB)(138)      
    Age-related diseases can lead to knee joint misfunction, making knee assistance necessary through the use of robotic wearable braces. However, existing wearable robots face challenges in force transmission and human motion adaptation, particularly among the elderly. Although soft actuators have been used in wearable robots, achieving rapid response and motion control while maintaining portability remains challenging. To address these issues, we propose a soft-robotic knee brace system integrated with multiple sensors and a direct-drive hydraulic actuation system. This approach allows for controlled and rapid force output on the portable hydraulic system. The multi-sensor feedback structure enables the robotic system to collaborate with the human body through human physiological signal and body motion information. The human user tests demonstrate that the knee robot provides assistive torques to the knee joint by being triggered by the electromyography signal and under human motion control.
    Reference | Related Articles | Metrics
    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
    Abstract324)      PDF (1591KB)(53)      
    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.
    Reference | Related Articles | Metrics
    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
    Abstract313)      PDF (1674KB)(106)      
    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.
    Reference | Related Articles | Metrics
    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
    Abstract313)      PDF (2162KB)(52)      
    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.
    Reference | Related Articles | Metrics
    Advances in Medicine-Engineering Crossover in Automated Anesthesia
    XU Tianyi (徐天意), XIA Ming (夏明), JIANG Hong (姜虹)
    J Shanghai Jiaotong Univ Sci    2022, 27 (2): 137-143.   DOI: 10.1007/s12204-021-2329-x
    Abstract288)      PDF (156KB)(118)      
    Medicine-engineering crossover refers to the cross-fertilization of multiple disciplines to meet clinical needs through various means, including engineering, which greatly promotes medical development. In the development of anesthesiology, improvements in anesthesia equipment and continuous innovation of anesthesia technology are all closely related to the integration of medicine and engineering. In recent years, the exploration and development of automated anesthesia equipment has led to closer integration of medicine, engineering, and other disciplines, including the development of robots in anesthesia, automated monitoring and alarm technology,automated perioperative management, and remote anesthesia. Herein, the current status of applications and development of medicine-engineering crossover in the field of automated anesthesia are discussed.
    Reference | Related Articles | Metrics
    Risk Prediction Model of Gallbladder Disease in Shanghai Middle-Aged and Elderly People Based on Neural Networks
    YUAN Xiaoqi (袁筱祺), ZHU Lelan (朱乐兰), XU Qiongfan(徐琼凡), GAO Wei (高玮)
    J Shanghai Jiaotong Univ Sci    2022, 27 (2): 153-159.   DOI: 10.1007/s12204-021-2386-1
    Abstract282)      PDF (345KB)(85)      
    This paper discusses the risk factors related to gallbladder disease in Shanghai, improves the accuracy of risk prediction, and provides a theoretical basis for scientific diagnosis and universality of gallbladder disease.We selected 3 462 data of middle-aged and elderly health check-up patients in a general hospital in Shanghai,and divided into gallbladder disease group according to color doppler ultrasound diagnosis results. Single-factor analysis screened out 8 important risk factors, which were used as an analysis variable of multi-layer perceptron neural network and binary logistic regression to construct the prediction model of gallbladder disease. The prediction accuracy of the multi-layer perceptron neural network risk prediction model is 76%. The area under the receiver operating characteristic curve (AUC) is 0.82, the maximum Youden index is 0.44, the sensitivity is 79.51, and the specificity is 64.23. The prediction accuracy of the multi-layer perceptron neural network model is better than that of the binary logistic regression prediction model. The overall prediction accuracy of the binary logistic regression prediction model is 75.60%, the AUC is 0.81, the maximum Youden index is 0.42, the sensitivity is 74.48, and the specificity is 57.60. In the objective risk prediction of gallbladder disease in middle-aged and elderly people in Shanghai, the risk prediction model based on the multi-layer perceptron neural network has a better prediction performance than the binary logistic regression model, which provides a theoretical basis for preventive treatment and intervention.
    Reference | Related Articles | Metrics
    Switched Three-Dimensional Decoupling Stabilization of Underactuated Autonomous Underwater Vehicles
    FANG Haolin (房浩霖), ZHANG Jiawen (张家闻), LI Jiawang∗ (李家旺)
    J Shanghai Jiaotong Univ Sci    2022, 27 (3): 383-392.   DOI: 10.1007/s12204-022-2446-1
    Abstract265)      PDF (897KB)(32)      
    A three-dimensional stabilization problem for underactuated autonomous underwater vehicles (AUVs) is addressed in this paper. A novel coordinate transformation form consisting of state modifications and input transformations is introduced such that the whole system is divided into two decoupled one-order subsystems. Some switching functions are presented to further decouple the underactuated dynamics and to produce persis tently exciting (PE) signals for those underactuated states. Based on the aforementioned results, a quite simple control law is designed to achieve global three-dimensional asymptotic convergence of all states of underactuated AUVs. Comparative simulations are carried out to validate the effectiveness and performance of the proposed control scheme.
    Reference | Related Articles | Metrics
    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
    Abstract263)      PDF (1635KB)(29)      
    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.
    Reference | Related Articles | Metrics
    Design of Twin-Screw Compressor Rotor Tooth Profile with Meshing Clearance Based on Graphic Method and Alpha Shape Algorithm
    YANG Jian, ∗ (杨 剑), XU Mingzhao (徐明照), LU Zheng (陆 征)
    J Shanghai Jiaotong Univ Sci    2023, 28 (2): 243-254.   DOI: 10.1007/s12204-021-2396-z
    Abstract261)      PDF (1955KB)(45)      
    Rotor clearance is necessary for the safe operation of twin-screw compressors, and it has a major impact on the performance of twin-screw compressors. The purpose of this study was to obtain a rotor tooth profile with reasonable meshing clearance on the rotor end surface, so that the clearance on the rotor contact line would be uniform and the rotor could be smoothly meshed. Under ideal conditions, the rotor of a screw compressor should have no clearance or interference. However, owing to assembly errors, thermal compression, stress deformation, and other factors, a rotor without backlash modification will inevitably produce interference during operation. A new design method based on the Alpha shape solution was proposed to achieve an efficient and high-precision design of the clearance of the twin-screw rotor profile. This method avoids the complex analytical calculations in the traditional envelope principle. The best approximation of the points on the rotor conjugate motion sweeping surface in the points is illuminated using a specific color. The sweeping surface of the screw rotor single-tooth profile is roughly scanned to capture the base point set of the sweeping surface boundary points. The chord length and tilt angle of each interval are calculated using the value of the base point set to adjust the position, phase, and magnification of each interval sweeping surface. Finally, the data point set is converted to the same coordinate system to generate the conjugated rotor profile. An example was used to verify the feasibility and adaptability of this method. Based on the equidistant profile method, the clearance between male and female rotors of a screw compressor was obtained under actual operation conditions. Therefore, this study provides a basis for the meshing clearance design in the machining of twin-screw compressor rotors.
    Reference | Related Articles | Metrics
    Application of Digital Medicine in Addiction
    WU Xiaojun (吴萧俊), DU Jiang (杜江), JIANG Haifeng (江海峰), ZHAO Min (赵敏)
    J Shanghai Jiaotong Univ Sci    2022, 27 (2): 144-152.   DOI: 10.1007/s12204-021-2391-4
    Abstract261)      PDF (185KB)(100)      
    Digital medicine plays an important role in disease assessment, psychological intervention, and relapse management in mental illnesses. Patients with substance use disorders can be easily affected by the environment and negative emotions, inducing addiction and relapse. However, due to social discrimination, stigma, or economic issues, they are unwilling to go to the hospital for treatment, making it difficult for health workers to track their health changes. Additionally, mental health resources in China are insufficient. Digital medicine aims to solve these problems. This article reviews digital medicine in the field of addiction, hoping to provide a reference for the future exploration of more individualized and effective digital medicine.
    Reference | Related Articles | Metrics
    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
    Abstract259)      PDF (2037KB)(38)      
    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.
    Reference | Related Articles | Metrics
    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
    Abstract256)      PDF (775KB)(84)      
    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.
    Reference | Related Articles | Metrics
    Topology Optimization Method for Calcaneal Prosthesis
    LIU Xiaoying* (刘晓颖), YUE Yong(岳勇), WANG Chongning (王宠宁), HUANG Jiazan (黄家赞),HUANG Xianwei(黄贤伟), HAO Yanhua(郝艳华)
    J Shanghai Jiaotong Univ Sci    2022, 27 (2): 240-249.   DOI: 10.1007/s12204-021-2324-2
    Abstract253)      PDF (1932KB)(39)      
    With the development of economy and the progress of medical science and technology, artificial prosthesis replacement has become an important means to improve the dysfunction caused by human bone diseases.However, there are still some loose phenomena caused by stress shielding. To solve the complications of aseptic loosening after calcaneal prosthesis replacement, an optimal design method for the prosthesis was proposed. The prosthesis was designed and optimized according to the real bone shape and the replacement requirements by the combination of computed tomography (CT) technology, computer-aided design, finite element analysis, and power flow theory. CT data were imported into MIMICS and Geomagic Studios. UG was used to obtain the geometric model of the human skeleton. Then, the 3D finite element model of the prosthesis was established by combining the finite element software Abaqus, and a series of finite element analysis was carried out. The prosthesis was topologically optimized and filled with a porous structure. The prosthesis was implanted by computer simulation.Finally, the power flow method was used to compare the dynamic performance and energy transfer before and after the prosthesis replacement to verify the rationality of the prosthesis design. In this paper, this method was used to optimize the design of the calcaneal prosthesis, and the research shows that this method can reduce the stress shielding effect of the calcaneal prosthesis. From the case of calcaneal prosthesis optimization, this method is not only a supplement to the contemporary biomechanical theory but also can guide the design of bone prosthesis in bone prosthesis replacement surgery.
    Reference | Related Articles | Metrics
    Dynamic Stability Analysis of Backhoe Dredger Based on Time Domain Method
    CHEN Yihua1 (陈熠画), CHEN Xinquan1∗ (陈新权), YANG Qi1,2 (杨 启), OUYANG Yiping1 (欧阳义平)
    J Shanghai Jiaotong Univ Sci    2022, 27 (3): 339-345.   DOI: 10.1007/s12204-021-2272-x
    Abstract252)      PDF (1221KB)(32)      
    When incidents happen with the positioning spud of a backhoe dredger, the hull loses stability, heels significantly, and may even capsize under extreme conditions. Coupling the hydrodynamics and spud vibrations, this paper investigates the dynamic stability of a backhoe dredger after spud failure based on the time domain method. The maximum dynamic heeling angle verifies the stability of the backhoe dredger. To identify the influences of environmental load, operating conditions, and spud-soil interactions, numerical motion simulations were conducted in the time domain. The main conclusions on dynamic stability consider the influences of relative environmental and operational factors. This study provides a powerful and efficient approach to analyze the dynamic stability of backhoe dredgers and to design flooding angles.
    Reference | Related Articles | Metrics
    Modification Method of Longitudinal Bow Structure for Ice-Strengthened Merchant Ship
    DING Shifeng (丁仕风), ZHOU Li∗ (周 利), GU Yingjie (顾颖杰), ZHOU Yajun (周亚军)
    J Shanghai Jiaotong Univ Sci    2022, 27 (3): 298-306.   DOI: 10.1007/s12204-022-2442-5
    Abstract252)      PDF (5084KB)(67)      
    Merchant ships, which are quite different from icebreakers, usually require the light ice-strengthened bow under the floe-ice condition. According to ice-class B, requirements of China Classification Society (CCS), intermediate frames and thick hull plates are necessary for the ice belt area to resist floe-ice impact. However, due to the limited space, it is not practical to set so many intermediate longitudinals from manufacture point of view. In this paper, a modification method is proposed to solve the problem by maintaining the frame spacing and increasing the plate thickness. The aim is to make sure that the bow owns the equivalent ice-bearing capacity with the original frame spacing. At first, a bulk carrier with ice-class B is used for case study. According to the requirements of the ice class rule, a designed ice thickness is used to calculate the ice load acting on the bow area due to the impact of ice floe. Two structural models are presented to perform the strength analysis under ice load, including the out-shell plate model and the longitudinal model. The results show that increasing the plate thickness is helpful to remove the negative effect induced by enlarging the spacing of the longitudinal. A reasonable curve is presented to modify the bow for the ice-strengthened merchant ship, which shows the relationship between the increase of plate thickness and the spacing of longitudinal. Moreover, a model test of floe-ice–ship interaction is conducted to measure the dynamic ice load, based on which nonlinear dynamic FE analysis is used to verify the presented plate-thickness–longitudinal spacing curve. The results show that the proposed method can be used to improve the ice-strengthened bow structure effectively, which provides theoretical foundation to modify the requirement of CCS’s ice class rule.
    Reference | Related Articles | Metrics
    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
    Abstract248)      PDF (2934KB)(116)      
    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.
    Reference | Related Articles | Metrics
    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
    Abstract245)      PDF (1607KB)(81)      
    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.
    Reference | Related Articles | Metrics
    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
    Abstract244)      PDF (1035KB)(29)      
    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.
    Reference | Related Articles | Metrics
    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
    Abstract240)      PDF (1302KB)(27)      
    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.
    Reference | Related Articles | Metrics
    Design and Overall Strength Analysis of Multi-Functional Elastic Connections Floating Breakwater System
    HUO Fali∗ (霍发力), YANG Hongkun (杨宏坤), GUO Jianting (郭建廷), JI Chunyan (嵇春艳), NIU Jianjie (牛建杰), WANG Ke (王 珂)
    J Shanghai Jiaotong Univ Sci    2022, 27 (3): 326-338.   DOI: 10.1007/s12204-022-2413-x
    Abstract236)      PDF (3201KB)(38)      
    As a new type of marine structure, floating breakwater can provide suitable water area for coastal residents. In this paper, a multi-module floating breakwater with three cylinders was designed. According to the characteristics of each module, the elastic connector was created. The cabins with functions such as living, generating electricity and entertainment were arranged. A linear spring constrained design wave (LSCDW) method for strength analysis of floating marine structures with multi-module elastic connections was proposed. The numerical model was verified by 1 : 50 similarity ratio in the test tank. According to the analysis of design wave and extreme wave conditions, considering the mooring loads and environmental loads and connector loads, the overall strength of breakwater was analyzed by LSCDW method. These studies can provide new insights and theoretical guidance for the design of multi-module floating structures.
    Reference | Related Articles | Metrics
    A 12-bit 80 MS/s 2 mW SAR ADC with Deliberated Digital Calibration and Redundancy Schemes for Medical Imaging
    HAN Gang* (韩刚), WU Bin (吴斌), PU Yilin (蒲钇霖)
    J Shanghai Jiaotong Univ Sci    2022, 27 (2): 250-255.   DOI: 10.1007/s12204-021-2377-2
    Abstract235)      PDF (1130KB)(41)      
    In this article, we presented a 12-bit 80MS/s low power successive approximation register (SAR)analog to digital converter (ADC) design. A simplified but effective digital calibration scheme was exploited to make the ADC achieve high resolution without sacrificing more silicon area and power efficiency. A modified redundancy technique was also adopted to guarantee the feasibility of the calibration and meantime ease the burden of the reference buffer circuit. The prototype SAR ADC can work up to a sampling rate of 80MS/s with the performance of > 10.5 bit equivalent number of bits (ENOB), < ±1 least significant bit (LSB) differential nonlinearity (DNL) & integrated nonlinearity (INL), while only consuming less than 2mA current from a 1.1V power supply. The calculated figure of merit (FoM) is 17.4 fJ/conversion-step. This makes it a practical and competitive choice for the applications where high dynamic range and low power are simultaneously required,such as portable medical imaging.
    Reference | Related Articles | Metrics
    Improvement of Physical Fitness Test Assessment Criteria Based on fNIRS Technology: Taking Pull-Up as an Example
    GONG Bin(巩斌), YU Xianghua(禹香华), FANG Yu (方宇), WANG Zheng (王正), YANG Hao (杨皓), CHEN Guodong (陈国栋), L Ü Na (吕娜)
    J Shanghai Jiaotong Univ Sci    2022, 27 (2): 219-225.   DOI: 10.1007/s12204-021-2367-4
    Abstract234)      PDF (1855KB)(85)      
    Pull-up, as an important physical fitness test event of the “National Student Physical Health Standard”, is known as a difficult physical fitness test event. To improve the assessment criteria of pull-ups, this paper uses the functional near-infrared spectroscopy (fNIRS) to monitor the changes and activation of oxyhemoglobin (HbO) signals in the brain motor cortex of people with different body mass indexes (BMIs) during the pullup assessment. Then the relationship between BMIs and evaluation criteria is discussed. After collecting and analyzing experimental data of 18 recruited college students, it is found that the number of pull-ups performed by people with different BMIs is different when they reach the peak state of brain activation. The results of the study indicate that different assessment criteria should be adopted for different BMI groups. It is suggested that the BMI should be introduced as one of the test indexes in the examination of pull-ups event in “National Student Physical Health Standard”.
    Reference | Related Articles | Metrics
    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
    Abstract234)      PDF (3866KB)(71)      
    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.
    Reference | Related Articles | Metrics
    Foreground Segmentation Network with Enhanced Attention
    JIANG Rui1*(姜﹐锐),ZHU Ruiriang1(朱瑞祥),CAI Xiaocui1(蔡萧萃),SU Hu2(苏虎)
    J Shanghai Jiaotong Univ Sci    2023, 28 (3): 360-369.   DOI: 10.1007/s12204-023-2603-1
    Abstract234)      PDF (734KB)(34)      
    Moving object segmentation (MOS) is one of the essential functions of the vision system of all robots,including medical robots. Deep learning-based MOS methods, especially deep end-to-end MOS methods, are actively investigated in this field. Foreground segmentation networks (FgSegNets) are representative deep end-to-end MOS methods proposed recently. This study explores a new mechanism to improve the spatial feature learning capability of FgSegNets with relatively few brought parameters. Specifically, we propose an enhanced attention (EA) module, a parallel connection of an attention module and a lightweight enhancement module, with sequential attention and residual attention as special cases. We also propose integrating EA with FgSegNet v2 by taking the lightweight convolutional block attention module as the attention module and plugging EA module after the two Maxpooling layers of the encoder. The derived new model is named FgSegNet v2 EA. The ablation study verifies the effectiveness of the proposed EA module and integration strategy. The results on the CDnet2014 dataset, which depicts human activities and vehicles captured in different scenes, show that FgSegNet v2 EA outperforms FgSegNet v2 by 0.08% and 14.5% under the settings of scene dependent evaluation and scene independent evaluation, respectively, which indicates the positive effect of EA on improving spatial feature learning capability of FgSegNet v2.
    Reference | Related Articles | Metrics
    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
    Abstract232)      PDF (705KB)(43)      
    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.
    Reference | Related Articles | Metrics
    Improved Nonsingular Fast Terminal Sliding Mode Control of Unmanned Underwater Hovering Vehicle
    HE Chenlua (何晨璐), FENG Zhengpinga,b∗ (冯正平)
    J Shanghai Jiaotong Univ Sci    2022, 27 (3): 393-401.   DOI: 10.1007/s12204-022-2447-0
    Abstract232)      PDF (1034KB)(48)      
    An improved nonsingular fast terminal sliding mode manifold based on scaled state error is proposed in this paper. It can significantly accelerate the convergence rate of the state error which is initially far from the origin and achieve the fixed-time convergence. In addition, conventional double power term based reaching law is improved to ensure the convergence of sliding state in the presence of disturbances. The proposed approach is applied to the hovering control of an unmanned underwater vehicle. The controller exhibits both fast convergence and strong robustness to model uncertainty and external disturbances
    Reference | Related Articles | Metrics
    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
    Abstract231)      PDF (988KB)(58)      
    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.
    Reference | Related Articles | Metrics
    Evaluation of a Novel Multimodal Guidance Device for Difficult Airway Endotracheal Intubation in Spontaneously Breathing Pigs
    XIA Ming (夏明), XU Tianyi (徐天意), CAO Shuang (曹爽),ZHOU Ren (周韧), JIANG Hong* (姜虹)
    J Shanghai Jiaotong Univ Sci    2022, 27 (2): 256-263.   DOI: 10.1007/s12204-021-2330-4
    Abstract227)      PDF (827KB)(40)      
    End-expiratory carbon dioxide concentrations can be used to assist endotracheal intubation. The novel multimodal endotracheal intubation guidance device combined visualization with an end-expiratory carbon dioxide concentration vectorization algorithm to achieve more accurate placement in difficult airways. The feasibility of a novel multimodal guidance device for the endotracheal intubation of difficult airways was verified in spontaneously breathing Bama miniature pigs. The glottic exposure time, insertion time, and total intubation time were not significantly different between the fiberoptic bronchoscope group and the multimodal guidance device group in regard to the endotracheal intubation of difficult airways. There were also no significant differences in intubation attempts, first success rate, and total success rate. Animals in both groups experienced hypoxemia, hypotension,and esophageal intubation during endotracheal intubation, but there were also no significant differences in the incidence of adverse events between the two devices. The effect on changes in hemodynamics, heart rate, and oxygen saturation during intubation showed no significant difference between the two devices. The results of the present study demonstrated the feasibility and effectiveness of the initial prototype of a multimodal guidance device for the endotracheal intubation of difficult airways in pigs, which is expected to further assist in adequately positioning the airway during difficult endotracheal intubations with spontaneous breathing.
    Reference | Related Articles | Metrics
    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
    Abstract227)      PDF (3845KB)(55)      
    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.
    Reference | Related Articles | Metrics
    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
    Abstract225)      PDF (1518KB)(934)      
    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.
    Reference | Related Articles | Metrics
    Interactive Liver Segmentation Algorithm Based on Geodesic Distance and V-Net
    KANG Jie* (亢洁), DING Jumin (丁菊敏), LEI Tao (雷涛),FENG Shujie (冯树杰), LIU Gang (刘港)
    J Shanghai Jiaotong Univ Sci    2022, 27 (2): 190-201.   DOI: 10.1007/s12204-021-2379-0
    Abstract224)      PDF (3921KB)(71)      
    Convolutional neural networks (CNNs) are prone to mis-segmenting image data of the liver when the background is complicated, which results in low segmentation accuracy and unsuitable results for clinical use. To address this shortcoming, an interactive liver segmentation algorithm based on geodesic distance and V-net is proposed. The three-dimensional segmentation network V-net adequately considers the characteristics of the spatial context information to segment liver medical images and obtain preliminary segmentation results. An artificial algorithm based on geodesic distance is used to form artificial hard constraints to modify the image,and the superpixel piece created by the watershed algorithm is introduced as a sample point for operation, which significantly improves the efficiency of segmentation. Results from simulation of the liver tumor segmentation challenge (LiTS) dataset show that this algorithm can effectively refine the results of automatic liver segmentation,reduce user intervention, and enable a fast, interactive liver image segmentation that is convenient for doctors.
    Reference | Related Articles | Metrics
    Progress in Force-Sensing Techniques for Surgical Robots
    GAO Hongyan1,2(高红岩),AI Xiaojie1,2(艾孝杰),SUN Zhenglong3(孙正隆),CHEN Weidong1,2(陈卫东),GAO Anzhu1,2*(高安柱)
    J Shanghai Jiaotong Univ Sci    2023, 28 (3): 370-381.   DOI: 10.1007/s12204-023-2607-x
    Abstract217)      PDF (1017KB)(70)      
    Force sensing is vital for situational awareness and safe interaction during minimally invasive surgery. Consequently, surgical robots with integrated force-sensing techniques ensure precise and safe operations. Over the past few decades, there has been considerable progress in force-sensing techniques for surgical robots. This review summarizes the existing electrically- and optically-based force sensors for surgical robots, including piezoresistive, piezoelectric, capacitive, intensity/phase-modulated, and fiber Bragg gratings. Their principles, applications, advantages, and limitations are also discussed. Finally, we summarize our conclusions regarding state-of-the-art force-sensing technologies for surgical robotics.
    Reference | Related Articles | Metrics
    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
    Abstract216)      PDF (1606KB)(32)      
    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.
    Reference | Related Articles | Metrics
    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
    Abstract216)      PDF (1196KB)(104)      
    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.
    Reference | Related Articles | Metrics
    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
    Abstract216)      PDF (1134KB)(53)      
    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.
    Reference | Related Articles | Metrics
    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
    Abstract216)      PDF (698KB)(52)      
    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.
    Reference | Related Articles | Metrics