Shanghai Jiao Tong University
Recent publications
Meniscus is a wedge-shaped fibrocartilaginous tissue, playing important roles in maintaining joint stability and function. Meniscus injuries are difficult to heal and frequently progress into structural breakdown, which then leads to osteoarthritis. Regeneration of heterogeneous tissue engineering meniscus (TEM) continues to be a scientific and translational challenge. The morphology, tissue architecture, mechanical strength, and functional applications of the cultivated TEMs have not been able to meet clinical needs, which may due to the negligent attention on the importance of microenvironment in vitro and in vivo. Herein, we combined the 3D (three-dimensional)-printed gradient porous scaffolds, spatiotemporal partition release of growth factors, and anti-inflammatory and anti-oxidant microenvironment regulation of Ac2-26 peptide to prepare a versatile meniscus composite scaffold with heterogeneous bionic structures, excellent biomechanical properties and anti-inflammatory and anti-oxidant effects. By observing the results of cell activity and differentiation, and biomechanics under anti-inflammatory and anti-oxidant microenvironments in vitro, we explored the effects of anti-inflammatory and anti-oxidant microenvironments on construction of regional and functional heterogeneous TEM via the growth process regulation, with a view to cultivating a high-quality of TEM from bench to bedside.
Curved parts are widely used in aerospace, automotive and energy industries. The profile and thickness accuracy are both critical to some curved parts such as hollow blades. Improving the profile accuracy while ignoring the wall thickness error will reduce the qualified rate of these curved parts, and vice versa. This paper proposes a comprehensive compensation method with constraints of both profile and thickness tolerances for the machining of curved parts. The actual geometry and wall thickness of the parts are obtained by on-machine measurement system after rough machining. Both touch-trigger probe and thickness gage are used to reconstruct the actual outer and inner surface of the workpiece. Then, the comprehensive constraint considering both profile and thickness constraints is established based on the reconstructed workpiece geometry. With the comprehensive constraint, a new target outer surface is constructed. The machining error is calculated from the target surface and compensated via toolpath adjustment. At last, machining experiments are conducted to verify the feasibility of the proposed method.
Most existing deep learning (DL)-based health prognostic methods assume that the training and testing datasets are from identical machines operating under similar conditions requiring massive labelled condition monitoring (CM) data to guarantee the prediction accuracy and generalisation capacity. However, these strict restrictions significantly hinder the deployment of the dl-based prognostic methods in real industries. In this paper, a Bayesian semi-supervised transfer learning with active querying-based intelligent fault prognostic framework is developed for remaining useful life (RUL) prediction across completely different machines under limited data. The proposed method strategically integrates the advantages of transfer learning (TL) and active learning in the Bayesian deep learning (BDL) framework. In the proposed framework, Bayesian neural networks with Monte Carlo dropout inference are utilised to quantify RUL prediction uncertainty, which is further leveraged to develop an active querying-based training data selection mechanism. Moreover, TL is simultaneously embedded into the BDL framework to relieve data distribution discrepancies existing among the completely different machines. The experimental verifications from open-sourced bearing datasets and lab testing-based lithium-ion battery degradation datasets demonstrate that the proposed framework can effectively and reliably achieve bi-directional transfer fault prognostic tasks under limited labelled CM data in target domain. Finally, generalisation and superiority of the proposed method are also validated by comparing with other state-of-the-art methods.
The emerging radar-based vibration measurement technology has attracted much interest in a wide spectrum of applications, such as mechanical test, structural health monitoring, machine diagnosis and vital sign detection. Advances in large monitoring range, high accuracy and excellent test efficiency and environmental adaptability have allowed radar-based vibration measurement method to perform enough superiority over traditional contact measurements like accelerometers or optical ways such as laser triangulation sensors or video/image-based measurements. However, the state of the art for radar vibration measurements mostly focuses on the quantification of one-dimensional vibrational measurement. This paper aims to present an accurate three-dimensional (3D) vibration measurement approach using three microwave radars via linear frequency modulated continuous wave (LFMCW) radars. The system overview and fundamental concept are illustrated firstly. To achieve 3D space trajectory and displacement of a vibrating target, we show the detailed procedures about coordinate system establishment and 3D displacement reconstruction process. Moreover, the error factors and analysis involved in our method are also discussed, allowing robust and accurate measurement for practical applications. Simulation and experimental validations are provided for demonstrating the performance of the method, offering a desired approach for contactless 3D vibration and displacement measurement.
Wound healing is one of the major global health concerns in patients with diabetes. Overactivation of pro-inflammatory M1 macrophages is associated with delayed wound healing in diabetes. miR-29ab1 plays a critical role in diabetes-related macrophage inflammation. Hence, inhibition of inflammation and regulation of miR-29 expression have been implicated as new points for skin wound healing. In this study, the traditional Chinese medicine, puerarin, was introduced to construct an injectable and self-healing [email protected] ([email protected]) hydrogel. The [email protected] hydrogel promoted diabetic wound healing and accelerated angiogenesis, which were related to the inhibition of the miR-29 mediated inflammation response. Compared to healthy subjects, miR-29a and miR-29b1 were ectopically increased in the skin wound of the diabetic model, accompanied by upregulated M1-polarization, and elevated levels of IL-1β and TNF-α. Further evaluations by miR-29ab1 knockout mice exhibited superior wound healing and attenuated inflammation. The present results suggested that miR-29ab1 is essential for diabetic wound healing by regulating the inflammatory response. Suppression of miR-29ab1 by the [email protected] hydrogel has the potential for improving medical approaches for wound repair.
Virtual rotating array (VRA) beamforming is a robust technique in the identification of rotating sound sources in frequency-domain. Under normal circumstances, the configuration of microphone array is established in ring geometry centered around the rotating axis. Two interpolation methods for arbitrary microphone configurations are proposed by Jekosch and Sarradj (Acoustics 2020). One is to construct a mesh between all stationary microphones using Delaunay-triangulation, another one is a meshless technique based on radial basis function. However, whether other spatial interpolation methods are available in VRA beamforming with arbitrary microphone configurations is still unclear. This paper adds several new spatial interpolation methods in VRA beamforming and detailedly compares the performances of these interpolation methods in simulations. The simulating results demonstrated that all these interpolation methods are successfully applied in VRA beamforming with arbitrary microphone configurations. Inverse distance weighting interpolation method owns the best performance in rotating sound source localization. Additionally, all these interpolation methods have poor spectrum construction capability and sound source strength precision.
It is challenging for control design and parameter optimization of a civil aircraft automatic landing system due to the complex application environment and high tracking precision requirement. In this paper, a parameter optimization method based on the non-dominated sorting genetic algorithm II (NSGA-II) is proposed to reduce the workload of control gain tuning and improve the performance of the autoland system. To facilitate the eventual engineering application, the flying quality indices are explicitly considered when defining the objective function for optimization. The proposed method is applied to design a longitudinal automatic landing system. It greatly simplifies the design process, and simulation results also demonstrate the effectiveness of the method.
The mechanical behaviors of composites subjected to compressive loads are critical concerns in composite structure designs. Misalignment of fiber orientation is a common manufacturing defect and has significant impact on compressive properties. In this paper, a Representative Volume Element (RVE) with misalignment defect is established with the consideration of Periodic Boundary Conditions (PBCs). A unidirectional lamina with misaligned carbon fibers is investigated based on Finite Element Method (FEM) with consideration of matrix plasticity. Drucker–Prager linear plastic model is utilized to describe elastic-to-plastic behavior of matrix. Parameters of Drucker–Prager model influence the formation and shape of kink-band. The mechanism of kink-band formation and propagation is discussed in this study.
The shock wave focusing is a promising detonation initiation method that can greatly shorten the deflagration to detonation transition distance. In this work, we conducted experiments under the constant operating pressure in a conical reflector to explore the shock focusing induced ignition in CH4/O2/Ar mixture. The second ignition is formed in the conical reflector under certain conditions. The introduction of the second ignition brings a higher pressure peak after ignition. By adjusting the incident shock intensity, three modes of ignition are found in the conical reflex. The pressure peak of combustion and the time to induce the second ignition are systematically investigated.
As an important approach and tool in model-based system engineering, functional modeling can help engineers to clarify customer requirements, establish functional architecture and generate solution concepts, and it has a wide range of application prospects in the aviation field. However, most existing functional modeling methods do not fully consider how to formalize the generated functional architecture solutions and cannot effectively represent functional logic, especially involved in complex interactions among the system, the user, and the operation environment. Therefore, this paper proposes a scenario-based functional modeling approach for civil aircraft systems. This method combines the concept of scenario in software engineering, builds the aircraft operation scenario model, further establishes the requirement, structure, behavior, and parameter model, and elaborates the functional interaction logic among the aircraft systems. Taking the primary flight control system in the aircraft deceleration on the ground scenario as an example, the functional model of the control spoiler extending and retracting is established and simulated, which demonstrates that the functional modeling approach is applicable to the functional design of civil aircraft system.
The internal flow stability of the compressor in the aeroengine has always been the top priority for the development of the aviation industry. Rotating stall is one of the most common instability problems in compressors, and stall margin is also an important parameter to measure the aerodynamic performance of compressors. In an actual compressor, it is difficult to achieve an ideal uniform inlet air condition, and inlet distortion will affect the operating conditions of the compressor. In this paper, a three-dimensional simulation of rotor 37 is conducted to study the development process of circumferential distortion and the aerodynamic performance of the compressor. The research results show that as the backpressure increases in the channel corresponding to the circumferentially distorted area, the blockage will occur first, and it will develop in the whole channel, leading to a complete stall. From the perspective of aerodynamic performance, circumferential distortion has an impact on stall margin and adiabatic efficiency, and different types of circumferential distortion have different effects on aerodynamic performance.
The research on high-speed impact of microparticles has always been a hot topic in the fields of space protection, additive manufacturing, and medicine. It is the premise of the research to make clear the reliable analysis method of microparticle impact process and get the accurate results of interface response. In this paper, the finite element simulation model is established for the high-speed impact of copper particles on copper substrate, and the accuracy of the finite element model is verified by comparing the analysis results with the results in the literature. Furthermore, the time evolution curve of the response results influenced by factors such as meshing density, initial temperature setting, and particle size are studied under the condition of two-dimensional simulation. Based on this, the influence trend of the process of microparticles impacting the substrate is summarized. This study has a very important reference significance for the research and application of space protection, cold spraying additive manufacturing, medical percutaneous drug delivery, and other fields.
Building change detection in high-resolution remote sensing images is very important for illegal building management and urban supervision. Recently, with the development of neural network and the increase of RS data, there are more and more change detection methods based on deep learning. Most of the existing change detection algorithms based on deep differential feature analysis which detect all semantic changes in two-temporal images, not specifically designed for building change detection and unable to give an accurate mask for building changes area. In this paper, we propose a Siamese U-net with attention mechanism for building change detection in high-resolution bi-temporal remote sensing images. By introducing scene-level building segmentation, we improve the boundary integrity and internal compactness of the final changed building. Our method was applied to WHU dataset and have outstanding building change detection results.
Traditional group delay measurement methods include single carrier phase method and spectrum analysis method based on signal autocorrelation function, but these two methods have their own limitations in GNSS receiver group delay measurement. The single carrier phase method cannot measure the group delay of multi filters and downconverters stage connect channel directly, and the measurement accuracy of group delay of spectrum analysis method based on signal autocorrelation function will deteriorate greatly near the zero point of signal power spectrum. In order to solve the above problems, this paper proposes a BOC (bi-nary offset carrier) signal group delay measurement method, which can realize the simple and accurate measurement of GNSS receiver group delay. In this paper, a group delay measurement method is analyzed and simulated by software, and verifies the feasibility and accuracy of the method are verified by simulation.
Civil aircraft is a typical complex product system. It has the characteristics of high technology intensiveness, strong interdisciplinary, high system integration, long development cycle, large project investment, and complex project management. The development process of civil aircraft usually involves many stakeholders, and each stakeholder will put forward its own requirements for the aircraft development process. Therefore, the number of requirements documents and requirements items summarized in the hands of product suppliers will be very large. One way to solve the above problems is to adopt a structured expression of requirements, so that the subject, object, realization function, attribute parameter, and category involved in each requirement can be clearly expressed in the database. Aiming at the extraction of attributes such as subject and object in the demand, this topic uses the related algorithm of named entity recognition in natural language processing to identify the corresponding entity. I built a word segmentation and NER model based on the Hidden Markov Model, which has achieved good results on the test data set.
As designers aim to increase the aerodynamic efficiency, fractal spoiler may be used on wings for its ability of altering turbulence. The study focuses on analyzing and verifying the feasibility of applying fractal spoilers. The flow mechanism of the flow-through fractal grids is simulated using CFD methods. Both the laminar and turbulent conditions are considered when simulating. The simulation of the wing airfoil provides the velocity distribution to the fractal spoiler. The laminar results help us understand the flow mechanism including wakes, jets, and their interaction behind the grids. In the turbulent results, the importance of the parameter wake interaction length is stated, and compared with former papers. The parameters of the fractal grids are related to a number of flow properties including the turbulence intensity, homogeneity, isotropy, and velocity distribution. These special characteristics suggest that it’s feasible to use fractal spoiler on wings as a control method.
In order to build a seamless national PNT infrastructure based on Beidou system, the absence of Beidou in indoor environments has to be dealt with. Although there are other sensors and approaches to indoor positioning, they cannot be merged into Beidou system smoothly. As a ground transmitter that broadcasts GNSS-like signals, pseudolite has a promising future. Despite these superiorities, pseudolite signals more often than not suffer from joint effects of radio frequency interference and near-far problems. Previous work suggests frequency-domain interference mitigation can suppress jamming effectively while Time-Hopped Direct Sequence Code Division Multiple Access (TH-DS-CDMA) signaling is effective in near-far problem. However, there is little research considering both interference and near-far problem in pseudolite. For the purpose of solving these two problems simultaneously, a frequency-domain interference mitigation method based on TH-DS-CDMA within receiver correlators is proposed in this paper. An adaptive interference detection and mitigation method enabled by thresholding is used to separate the interference and signal in terms of signal power effectively. And the synchronization of TH sequence method called Time-Hopping Starting Index (THSI) is achieved according to the time interval of CDMA signals in different subframe. Simulation shows that the proposed interference mitigation method in frequency domain based on TH-DS-CDMA can effectively provide a stop gap for the combined influence of interference and near-far problem, and the receiver can complete signal acquisition and sequence synchronization successfully, which verifies the validity of the proposed algorithm.
A thruster-based attitude control method for zero momentum spinning satellite is proposed in this paper. For the spinning satellite rotating synchronously with the long baseline rotating payload, if the satellite spin axis is required to point to the earth's center in real time, the gyroscopic moment generated by the angular momentum and precession angular velocity of the spinning satellite is difficult to overcome. Therefore, a zero-momentum spinning satellite scheme is proposed to make the large flywheel angular momentum offset the satellite spin angular momentum, making the whole satellite a zero-momentum system. The influence of the whole satellite dynamic unbalance disturbance torque on the attitude stability is analyzed. The attitude control of the spinning satellite is transformed into a three-axis stability control problem by defining the semi fixed reference coordinate system. The effectiveness of the proposed method is verified by mathematical simulation.
Servo systems are widely used in aerospace and other fields. To ensure the safety of the system operation, the fault detection of servo systems is very important. Servo system fault detection often uses comparative differential judgment method, which requires the establishment of a reliable model. On the one hand, servo system models are usually built using mathematical and physical methods by combining the transfer functions of the various components the actual servo system have into an algorithm that calculates the input–output relationship. On the other hand, machine learning algorithms can also be used to model the servo system. In this paper, we address this issue by developing a rocket data prediction model based on the LSTM algorithm using publicly available data provided by Shanghai Aerospace Control Technology Institute. After deriving the results, the results are evaluated by using R-squared metrics and some improvement outlooks are provided for the subsequent research.
With the rapid development of the mega-constellation networks based on the low earth orbit satellites, the shortest path issues in complex networks have gained more and more attention. In this paper, a shortest route solving algorithm based on the hybrid genetic algorithm-simulated annealing algorithm (GA-SA) is proposed. Experimental results show that the proposed hybrid GA-SA method is superior to the single traditional genetic algorithm or simulated annealing algorithm in the computation accuracy while discovering the shortest path between any satellite nodes of different types of topological networks. The new algorithm presents a faster convergence rate and higher accuracy in the simulation of large LEO satellite networks. The proposed algorithm has an advanced global search capability and universal applicability in mega LEO satellite networks.
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31,642 members
Luca Visinelli
  • Department of Physics
Jun Mi
  • Biochemistry & Molecular Cell Biology
Li Song
  • Department of Electrical Engineering
zm Huang
  • School of Medicine
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Zhenbin Yang, Zhongqin Lin
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www.sjtu.edu.cn