公开(公告)号：US20250085315A1

公开(公告)日：2025-03-13

申请号：US18567382

申请日：2022-12-29

Applicant: SOUTHEAST UNIVERSITY

Inventor： Qinsong QIAN ,  Song DING ,  Chunyan NIE ,  Yuanhang ZHOU ,  Weifeng SUN ,  Longxing SHI

IPC: G01R19/00 ,  H02M1/00 ,  H02M3/335

Abstract: A lossless exciting current sampling circuit for an isolated converter includes first and second voltage sampling circuits and a subtraction circuit formed by an operational amplifier. The two sampling circuits sample voltages of the primary winding of an isolation transformer, with outputs fed into the subtracter. The subtracter output is the circuit's output. RC low-pass filters with large time constants are used as primary voltage sampling circuits, realizing integration of voltage differences between the exciting inductance terminals, enabling lossless current sampling without resistors or transformers. The current sampling result is utilized for volt-second balance control, realized along with a hold circuit and comparator which compares the sampling hold result with the current sampling result to generate a control signal.

公开(公告)号：US20250084805A1

公开(公告)日：2025-03-13

申请号：US18957936

申请日：2024-11-25

Applicant: SOUTHEAST UNIVERSITY

Inventor： Huiyan ZHANG ,  Yinhai SU ,  Bo PENG ,  Sheng CHU ,  Yujie TAO ,  Qi CAO ,  Rui XIAO

IPC: F02G5/04

Abstract: The provided is energy storage method and device for biomass cascade pyrolysis coupled with new energy power generation. The key point of the technical solution is that, with inexpensive, clean and safe biomass as energy storage medium, the redundant unstable electric energy is converted by a cascade pyrolysis energy storage system into an easy-to-store liquid and solid chemical energy in biomass pyrolytic products, and based on use requirements, can be further converted into clean fuels for power generation or exported renewable chemicals, so as to realize continuous stable output of the new energy power generation systems. Furthermore, the cascade pyrolysis energy storage system can, based on the principle of “energy level matching”, fully recover and utilize the electric energy, high-temperature heat energy and low-temperature heat energy generated in pyrolysis processes, thereby maximizing the energy utilization efficiency of the system.

公开(公告)号：US20250080250A1

公开(公告)日：2025-03-06

申请号：US18816830

申请日：2024-08-27

Applicant: Southeast University ,  PURPLE MOUNTAIN LABORATORIES

Inventor： Chengxiang WANG ,  Yingjie XU ,  Yingzhuo SUN ,  Jialing HUANG ,  Lijian XIN ,  Jie HUANG

IPC: H04B17/309 ,  H04B7/10

Abstract: A method for estimating channel parameters of a reconfigurable intelligent surface based on a spherical wave assumption includes the following steps. In Step 1, a signal transmission model of a RIS-assisted near-field communication is constructed based on the spherical wave assumption; in Step 2, channel measurement data in different RIS transmission modes are obtained; in Step 3, a delay, an angle of arrival, an angle of departure, a Doppler shift and a polarization matrix of multipath in channels are estimated based on a space-alternating generalized expectation maximization algorithm, and angle parameters, distance parameters and coupling polarization matrices of the multipath at a RIS end are estimated based on a maximum likelihood principle; and in Step 4, the estimated parameters are updated and iterated subsequently. The method can estimate all important channel parameters in the RIS-assisted near-field communication scenario more accurately.

公开(公告)号：US20250080192A1

公开(公告)日：2025-03-06

申请号：US18816232

申请日：2024-08-27

Applicant: Southeast University ,  PURPLE MOUNTAIN LABORATORIES

Inventor： Chengxiang WANG ,  Lin HOU ,  Hengtai CHANG ,  Jie HUANG

IPC: H04B7/06 ,  H04B7/0413

Abstract: A method for estimating a beam domain channel in a spatial non-stationary massive MIMO system includes constructing a beam domain channel model for the spatial non-stationary massive MIMO system by using a visibility region; transforming a problem for estimating the beam domain channel into a problem for reconstructing a sparse channel based on a sparsity of beam domain channel and an influence of power leakage; proposing a beam domain structure-based sparsity adaptive matching pursuit scheme according to a cross-block sparse structure and a power ratio threshold of the beam domain channel; and verifying that the proposed scheme has a lower pilot overhead, a higher accuracy and a higher effectiveness compared to the traditional schemes in simulation results. The method can be effectively applied to communication channel estimation with non-stationary characteristics, and has obvious advantages in estimation accuracy and complexity.

公开(公告)号：US20250078442A1

公开(公告)日：2025-03-06

申请号：US18815320

申请日：2024-08-26

Applicant: Southeast University ,  PURPLE MOUNTAIN LABORATORIES

Inventor： Chengxiang WANG ,  Tong WU ,  Junling LI ,  Chen HUANG

IPC: G06V10/26 ,  G06V10/764 ,  G06V10/774 ,  G06V10/82 ,  G06V20/00

Abstract: The present disclosure discloses a method for predicting a channel based on an image processing and a machine learning, which belongs to the field of the channel prediction. The method introduces an image semantic segmentation technology to identify and segment a scatterer in a scenario image, extracts the effective position information of the scatterer, and identify a scenario in the segmented image. The subsequent feature extraction is performed in a similar scenario through the scenario identification, which facilitates extracting the more tiny environment features. The semantic segmentation images of the known scenarios are jointly input into a feature extraction and channel prediction network to complete the channel prediction. Therefore, the environment information can be input more flexibly through the semantic segmentation technology, so that the accuracy of the model is improved, and the precision higher than that of a traditional channel model is finally obtained, which is beneficial for better satisfying the technical requirement of full coverage for the multi-frequency bands and multi-scenarios in a 6G system.

公开(公告)号：US20250076582A1

公开(公告)日：2025-03-06

申请号：US18563384

申请日：2022-08-23

Applicant: NANJING XIGUANG RESEARCH INSTITUTE FOR INFORMATION TECHNOLOGY CO., LTD ,  WUXI TACLINK OPTOELECTRONICS TECHNOLOGY CO., LTD. ,  Southeast University

Inventor： Weifeng JIANG ,  Xiaohan SUN ,  Xuekang SHAN ,  Sang GUI ,  Ronghua CHI ,  Lei WANG ,  Xianqin LI

IPC: G02B6/293 ,  G02B27/00

Abstract: The present disclosure discloses an asymmetric wavelength multiplexing and demultiplexing chip based on inverse design, which belongs to the technical field of optical components, systems or instrument. The chip includes the first-level asymmetric wavelength multiplexing and demultiplexing unit and the second-level symmetric wavelength multiplexing and demultiplexing unit, which is constructed by silicon based photonics integration technology, includes a substrate, a bottom cladding layer, a core layer and a top cladding layer sequentially stacked from bottom to top. The functional regions inside the first-level unit and the second-level unit are designed based on the inverse design algorithms, and are composed of subunits on the submicron or nanometer scale. The chip provided is capable of covering the all-band in the optical communication system, and implementing the non-uniform wavelength division of the energy across all-band; and has an ultra-compact structure, adjustable wavelength intervals, non-uniform transmittance of each wavelength, low channel interval crosstalk.

公开(公告)号：US20250076349A1

公开(公告)日：2025-03-06

申请号：US18553966

申请日：2022-11-24

Applicant: SOUTHEAST UNIVERSITY

Inventor： Zheng WANG ,  Yinzhen SHEN ,  Yang XU

IPC: G01R19/04 ,  H02M7/537

Abstract: The present invention discloses a prediction method for a crosstalk spike in a half bridge of current-source inverter with silicon carbide devices, where, the prediction method includes calculation of the crosstalk voltage spike in the circuit of current-source type double-pulse test and analysis of the effect of each parameter on the magnitude of the crosstalk spike. The prediction method of the present invention analyzes the horizontal conduction crosstalk mechanism between the gate-source junction of the MOSFET caused by the high-frequency switching action of the silicon carbide (SiC) MOSFET and the SiC Schottky diode connected in series, and derives the prediction model for the crosstalk voltage spike in the half-bridge of current-source inverter. Based on the equivalent circuit of the current-source-type double-pulse test and the crosstalk-induced mechanism, the extreme value of crosstalk voltage spike is accurately predicted, which is helpful to analyze the effects of the drive circuit and the parameters of the power circuit on the crosstalk voltage spike through the prediction model.

公开(公告)号：US20250073911A1

公开(公告)日：2025-03-06

申请号：US18896856

申请日：2024-09-25

Applicant: SOUTHEAST UNIVERSITY

Inventor： Guangming SONG ,  Feng XIE ,  Juzheng MAO ,  Fei WANG ,  Jun ZHOU ,  Aiguo SONG ,  Gang WU

IPC: B25J11/00 ,  B25J5/00 ,  B25J9/16

Abstract: Disclosed are an embracing crawling robot for detecting an underwater pier of a highway bridge and a detection method therefor. The robot includes a main body, underwater lighting systems, tool compartments, depth metering modules, servo driving wheels, inclination measurement modules, underwater manipulator arms, vision array modules, synchronized stretching and fixing systems, and driven wheels. The robot is capable of crawling around an underwater pier of a highway bridge and operating stably in an underwater environment. After cleaning surface attachments on the underwater pier, the robot performs visual detection of a disease; and after determining type and location information of the disease, the robot will transmit disease information back. The robot is capable of crawling around the underwater pier of the highway bridge stably at any depths, perceiving depth and visual information under high-speed and turbid water conditions, thereby realizing detection of the disease on the underwater pier.

公开(公告)号：US20250072812A1

公开(公告)日：2025-03-06

申请号：US18808099

申请日：2024-08-19

Applicant: SOUTHEAST UNIVERSITY

Inventor： Baoguo XU ,  Zelin GAO ,  Xinhao YANG ,  Aiguo SONG

IPC: A61B5/374 ,  A61B5/00

Abstract: Disclosed is an EEG recognition method for a natural hand movement based on a time-domain and frequency-domain multi-layer brain network, including: (1) acquiring a multi-channel EEG signal of the natural hand movement; (2) preprocessing the multi-channel EEG signal, and extracting a δ wave, a θ wave, a α wave, a β wave, and a γ wave at each time point; (3) constructing a time-domain multi-layer brain network using a wSAR model; (4) calculating the frequency-domain multi-layer brain network using the phase-amplitude coupling; (5) combining the time-domain multi-layer brain network and the frequency-domain multi-layer brain network, and performing standardization; and (6) calculating metrics of the time-domain and frequency-domain multi-layer brain network and a super-adjacency matrix of a decomposed time-domain and frequency-domain multi-layer brain network, inputting the same to a two-layer graph convolutional network (GCN), and fusing manual, shallow, and deep features for analysis.

公开(公告)号：US20250023910A1

公开(公告)日：2025-01-16

申请号：US18548937

申请日：2023-06-26

Applicant: SOUTHEAST UNIVERSITY

Inventor： Hua WU ,  Jinfeng CHEN ,  Guang CHENG ,  Xiaoyan HU

IPC: H04L9/40

Abstract: A method for detecting slow HTTP DoS (SHD) attacks in a backbone network can detect three different types of SHID attacks. The method is divided into an off-line training phase and an on-line detection phase. In the off-line training phase, several types of representative unidirectional traffic features are extracted according to attack characteristics of different SHD types and corresponding feature groups are built, where these features can effectively deal with a large amount of unidirectional traffic in backbone networks; a public backbone network dataset is systematically sampled and data are stored in combination with Count-min Sketch, which greatly minimizes storage and computational overhead required in the backbone networks; and a specific machine learning algorithm is used for training to obtain attack detection models. The method can be used for detecting and warning SHD attacks in mass traffic scenarios such as backbone networks to provide a basis for maintaining network security.