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115 results on '"Hu Ji-wei"'

1. Model-based CP Selection Method for Calibration of Airborne InSAR with Sparse GCPs

Author

Hu Ji-wei, Hong Jun, Ming Feng, and Li Liang

Subjects
Airborne Interferometric Synthetic Aperture Radar (InSAR), Interferometric calibration, Bundle adjustment, Control Point (CP), Electricity and magnetism, QC501-766
Abstract

High-precision height acquisition needs to correct the interferometric parameters errors by interferometric calibration for Interferometric Synthetic Aperture Radar (InSAR) system with many Ground Control Points (GCPs). For the situation that some areas probably only have little GCPs or even no GCPs, a new high-precision calibration method for airborne InSAR based on bundle adjustment is needed, in which the Control Points (CP) selection method is a major point which has a crucial influence on the precision of InSAR calibration. A model-based CP selection method for calibration of airborne InSAR with sparse GCPs is proposed in this paper, which adopts the polynomial model fit method to choose CP based on the sensitivity characteristic of inSAR interferometric parameters. A joint calibration is made with the real InSAR data and the results confirm the validity and rationality of the proposed method.

Published
2012
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2. Current Situation and Development Trend of Inflight Antenna Pattern Measurement Techniques of Spaceborne SAR

Author

Hong Jun, Ming Feng, and Hu Ji-wei

Subjects
Synthetic Aperture Radar (SAR), SAR calibration, Inflight measurement of spaceborne SAR antenna patterns, Ground receiver, Rain forest, Electricity and magnetism, QC501-766
Abstract

The antenna pattern uncertainty is the main error of SAR system. The technique for inflight antenna pattern measurement of spaceborne SAR is one of the most important technique of SAR calibration. This paper discusses the development courses of the inflight antenna pattern measurement of spaceborne SAR, analyses its development trend and compares the main inflight antenna pattern measurement techniques. This paper will be an important reference for designing a project of inflight antenna pattern measurement of spaceborne SAR.

Published
2012
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4. Face Recognition Method Based on Edge-Cloud Collaboration

Author

WEI Qin, LI Ying-jiao, LOU Ping, YAN Jun-wei, HU Ji-wei

Subjects
edge-cloud collaboration, face recognition, resnet, arcface, deep separable convolution, Computer software, QA76.75-76.765, Technology (General), T1-995
Abstract

Face recognition is widely used in daily life such as shopping,security check,travel,payment and work attendance.Face recognition systems need strong computing power and large storage space,so face images that need to be recognized are usually transmitted to the cloud platform through the network.Due to the problems of network coverage,congestion and delay,face re-cognition systems are difficult to meet the needs of actual application,and the user experience is poor.Aiming at the problems in face recognition,a face recognition method based on edge-cloud collaboration is proposed.This method combines the processing ability of cloud computing and the real-time performance of edge computing,so that face recognition systems are not constrained by the network status,and its application is more extensive and the user experience is better.In the cloud,the LResNet feature extraction method is proposed to improve the ResNet34 network structure,and the ArcFace face loss function is used to supervise the training process,so that the network can learn more face angle features.At the edge,due to the limited computing resources and storage resources,a SResNet feature extraction method is proposed.Deep separable convolution is used to lighten the LResNet network structure,and it has greatly reduced network parameters and computation.The face recognition experiment on edge-cloud collaboration shows that the system can recognize faces in real time with a high accuracy rate under any network status.

Published
2022
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7. Functional Characterization of p53 in NPC C666-1 Cells by CRISPR-Based Gene Knockout and Transcriptome Sequencing

Author

lei, jing, primary, qin, zhen shu, additional, yu, qian, additional, li, qi guang, additional, zhang, yi, additional, hu, ji wei, additional, hou, yong kang, additional, jing, qi, additional, Lu, Shan-Shan, additional, huang, wei, additional, guan, yong jun, additional, yi, hong, additional, Tang, Yao-Yun, additional, Xiao, Zhi-Qiang, additional, and qin, zhenqi, additional

Published
2022
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13. Notice of Retraction: Fluid Characteristic Research of Cooling-Water on Stator Waterway Blockage in Turbo-generators

Author

Hu Ji-wei and Li Jun-qing

Subjects
Engineering, biology, business.industry, Stator, Turbo, Mechanical engineering, Computational fluid dynamics, biology.organism_classification, Finite element method, Fluid field, law.invention, law, Water cooling, Vector field, business, Overheating (electricity)
Abstract

Blockage of hollow strands' waterway can cause cooling-water flux decreasing, cooling effect falling and stator bar overheating in water-cooling turbo-generators, which could induce generators not to operate normally. It helps to calculate precisely temperature field of generators and diagnose incipiently the plugging fault of cooling-waterway that one study fluid characteristic of cooling-water on hollow strands blocked in turbo-generators. In accordance with generators structure and computational fluid dynamics (CFD), the cooling-water fluid field of turbo-generators stator was studied when the cooling waterway was blocked. Velocity field of cooling-water was researched by applying finite element method(FEM) when the hollow-strands were blocked in different positions and plugging extent. The paper analyzed influence of blockage site and extent on flow characteristic of water in hollow strands. The achievement can be used for calculation of temperature filed and early diagnosis of blockage fault in generators.

Published
2010
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14. RBFNN for fault diagnosis of rotor windings inter-turn short circuit in turbine-Generator

Author

Li Yong-gang, Hu Ji-wei, and Zhao Yan-jun

Subjects
Engineering, Rotor (electric), business.industry, Condition monitoring, Fault (power engineering), law.invention, Vibration, Generator (circuit theory), law, Control theory, Electromagnetic coil, business, Short circuit, Electronic circuit
Abstract

The electromagnetic characteristic and rotor vibration characteristic of turbine-generator are analyzed when rotor windings inter-turn short circuit fault has happened. This paper also gets relevant characteristic parameters. Based on characteristic parameters, RBFNN (radial basis function neural network) can be adequately trained and diagnosis rotor windings inter-turn short circuit. RBFNN is independent on mathematic models and parameters of turbine-generator. Finally practically acquired dynamic experiment data of the MJF-30-6 generator, the results of verification show that the theory analysis is right and the RBFNN can diagnosis rotor fault and estimate fault turns ratio.

Published
2008
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