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检索条件"机构=National Key Laboratory of Science and Technology on Reactor System Design Technology in China"

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Optimal design of reactor for 12 Pulse Three-Level Rectifier 16th

Optimal Design of Reactor for 12 Pulse Three-Level Rectifier

引用

16th Annual Conference of china Electrotechnical Society, ACCES 2021

作者： Zhang, Xiangming Deng, Chen Chen, Junquan Zhao, Zhihua Zhang, Lei National Key Laboratory of Science and Technology on Vessel Integrated Power System Naval University of Engineering Wuhan China

ISBN: (纸本)9789811915314

Based on the analysis of the current characteristics of the DC side of the 12 pulse three-level rectifier, a common-model integrated reactor is proposed to suppress the DC ripple. Through magnetic-circuit coupling, the reactor can enhance the filtering effect of the main harmonic and cancel out the DC main magnetic flux in the core of the reactor, thus greatly reducing the volume, weight and cost of the reactor. Based on the theoretical analysis, a common model integrated reactor is designed and manufactured. The test results show that the proposed method not only ensures the harmonic suppression effect, but also reduces the volume, weight and cost of the reactor by more than 70% compared with the discrete filtering method. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Magnetism

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Feature Pyramid Network Based on Skip Connect for Vehicle Prediction 2

Feature Pyramid Network Based on Skip Connect for Vehicle Pr...

引用

2nd International Conference on Robotics, Automation and Intelligent Control, ICRAIC 2022

作者： Li, Peixin Liu, Jiaqi Yang, Lu Tianjin Key Laboratory for Advanced Mechatronic System Design and Intelligent Control School of Mechanical Engineering Tianjin University of Technology Tianjin300384 China National Demonstration Center for Experimental Mechanical and Electrical Engineering Education Tianjin University of Technology China

The trajectory prediction of the target vehicle can improve the perception ability of autonomous driving vehicles in the open world environment and is an essential technology for realizing high-level fully automatic driving. The traditional vehicle trajectory prediction model based on image input is sensitive to the image style of the dataset and has weak generalization ability. The prediction model based on intermediate features can overcome the problem of different dataset styles. However, there are relatively few explorations on building models based on intermediate semantic features. Inspired by the feature pyramid in image processing, this paper proposes an FPSP (Feature Pyramid network based on Skip connect for vehicle Prediction) network. By adding the pyramid feature branch, the original network is improved. The initial coarse information is hierarchically introduced into corresponding abstract high-dimensional features. Experiments on the KITTI dataset prove that FPSP achieves considerable improvement with only a slight increase in time consumption. © Published under licence by IOP Publishing Ltd.

关键词： Forecasting

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Real Time Surgical Instrument Object Detection Using YOLOv7 1

引用

6th EAI International Conference on Robotics and Networks, EAI ROSENET 2022

作者： Zheng, Laiwang Liu, Zhenzhong Tianjin Key Laboratory for Advanced Mechatronic System Design and Intelligent Control School of Mechanical Engineering Tianjin University of Technology Tianjin China National Demonstration Center for Experimental Mechanical and Electrical Engineering Education Tianjin University of Technology Tianjin China

ISBN: (数字)9783031338267

ISBN: (纸本)9783031338250

With the rapid development of minimally invasive surgery (MIS) in the medical field, surgical robot technology has developed rapidly. Human-machine combined assisted surgical technology has begun to bring good news to the majority of doctors and patients who need surgery. It has gradually become a common medical treatment. Minimally invasive surgery can overcome the shortcomings of traditional surgery. MIS has the advantages of less trauma, less impact on patients, faster recovery, less intraoperative blood loss, and so on. For surgical robots, surgical instruments are important execution components that have been widely concerned and studied in recent years. One of the core technologies of surgical robots is the detection of surgical equipment based on deep learning, which can effectively assist doctors to complete the surgery. Current surgical instrument detection methods need to be improved in real-time performance and accuracy. Therefore, this paper proposes a new real-time detection algorithm, which is based on the deep learning object detection system YOLOv7. The real dataset, which contained information on seven surgical instruments, was selected for training and validation. Experiments show that the method has good precision, recall rate, and mAP, which can be used to improve the ability of robot-assisted doctors to identify instruments during surgery. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Object recognition

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Trajectory Optimization and Control Method Based on Multistage Nonlinear Model Predictive Control 4

Trajectory Optimization and Control Method Based on Multista...

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4th International Seminar on Artificial Intelligence, Networking and Information technology, AINIT 2023

作者： Zheng, Qingchun Peng, Zhi Zhu, Peihao Zhai, Ran Tianjin University of Technology Tianjin Key Laboratory for Advanced Mechatronic System Design and Intelligent Control Tianjin China School of Mechanical Engineering Tianjin University of Technology Tianjin China Tianjin University of Technology National Demonstration Center for Experimental Mechanical and Electrical Engineering Education Tianjin China

ISBN: (纸本)9798350314526

To improve the trajectory optimization efficiency of robot manipulators, this paper proposes a novel approach for trajectory optimization and control of manipulators based on multistage nonlinear model predictive control (msNLMPC). This approach is realized by using a neural state space model as the prediction model of nonlinear model predictive control (NLMPC). The simulation results show that the actual trajectory of the manipulator in our proposed scheme coincides with the desired trajectory. The manipulator achieves the control task of following the optimal trajectory. Our proposed method improves the trajectory optimization efficiency of the robot manipulator. © 2023 IEEE.

关键词： Model predictive control

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Wideband Adaptive Interference Cancellation in Spread-Spectrum Communication with Subband Bandwidth design 9

Wideband Adaptive Interference Cancellation in Spread-Spectr...

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9th IEEE International Symposium on Microwave, Antenna, Propagation and EMC Technologies for Wireless Communications, MAPE 2022

作者： Zhang, Yunshuo He, Fangmin Lu, Qiaran Li, Zheyu Liu, Hongbo Meng, Jin Naval University of Engineering National Key Laboratory of Science and Technology on Vessel Integrated Power System Wuhan China

ISBN: (数字)9781665427753

ISBN: (纸本)9781665427753

The bandwidth ratio increasing of spread spectrum (SS) communication limits the performance of wideband adaptive interference cancellation (WAIC) for strong wideband interference signal. To improve the interference cancellation radio (ICR), wideband interference signal is divided into subbands to reduce the computational bandwidth of the WAIC algorithm. In this paper, a method that fits the wideband interference signal by multi-tone signals is proposed to explicitly analyze the effect of the signal bandwidth on the cancellation system and quantitatively calculate the analytical solution of the ICR. Basing on the method proposed, the performance can be evaluated by the amplitude and phase difference between the received signals from the main antenna and the auxiliary antenna. Simulations and experiments are conducted to verify the theoretical analysis, and the results are consistent. Therefore, the analytical method proposed in this paper provides the design guidelines between the ICR requirement and subband bandwidth, which can reduce the complexity in the implementation of the WAIC system. © 2022 IEEE.

关键词： Spectroscopy

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Analytical Calculation and Analysis of Nature Frequency of Cylindrical Linear Motor Stator 2

Analytical Calculation and Analysis of Nature Frequency of C...

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2nd International Symposium on Mechanical systems and Electronic Engineering, ISMSEE 2022

作者： Zou, Yufan Wu, Zhenxing Xu, Jin Zhang, Yichao National Key Laboratory of Science and Technology on Vessel Integrated Power System Naval University of Engineering Wuhan China

ISBN: (纸本)9781713854296

Cylindrical linear motors have broad application prospects in the fields of rail transportation, precision medicine, and vertical lifting. At the same time, these occasions require the motor to run smoothly with low noise. Therefore, it is of key significance to analyze the vibration characteristics of the motor, the stator of the new type cylindrical linear motor is composed of multi-layer cylindrical shells, and its vibration characteristics can be obtained by equivalent simplification processing of thin-walled cylindrical shells. This paper constructs the corresponding analysis model for calculation the natural frequency of a thin-walled cylindrical shells. Based on the analytical model, influence of important parameter such as length, wall thickness, and mid-plane diameter of cylindrical linear motor on its vibration characteristics is studied. The relevant analysis and calculation methods and conclusions are verified by finite element simulation, which can provide reference for subsequent design of cylindrical linear motors. © VDE VERLAG GMBH ∙ Berlin ∙ Offenbach.

关键词： Linear motors

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Electrolytic Failure Modeling of Aluminum Electrolytic Capacitor by Finite Element Method

Electrolytic Failure Modeling of Aluminum Electrolytic Capac...

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Power Electronics and Application Symposium (PEAS), IEEE International

作者： Xinrui Chen Ran Yao Hui Li Wei Lai Yuan Min Cheng Yang Zeyu Duan Siyu Chen State Key Laboratory of Power Transmission Equipment Technology Chongqing University Chongqing China Science and Technology on Reactor System Design Technology Laboratory Nuclear Power Institute of China Chengdu China

The failure rate of aluminum electrolytic capacitor (AEC) is high in power electronic systems. Due to the complex structure of AEC, it is difficult to establish an actual model, so experiments are the common way to analyze the failure of AEC. Thus, this paper proposes a finite element method (FEM) for AEC considering electrolytic failure. Firstly, the mechanism of electrolytic failure and changes of characteristic parameters in the AEC are elucidated. Secondly, an equivalent finite element model is established to simulate and analyze the electrolytic failure of AEC. Finally, the effectiveness of the proposed AEC FEM method is verified through capacitor aging experiments.

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Research on Topology design and Configuration optimization of Hybrid Energy Storage system 5

Research on Topology Design and Configuration optimization o...

引用

5th IEEE International Electrical and Energy Conference, CIEEC 2022

作者： Wu, Zhicheng Zhu, Junjie Sun, Xingfa Han, Yi Xu, Jin Yuan, Jingxin Naval University of Engineering National Key Laboratory of Science and Technology on Vessel Integrated Power System Wuhan China

ISBN: (数字)9781665411042

ISBN: (纸本)9781665411042

When hybrid energy storage technology is applied in different occasions, there are key problems in topology design and configuration optimization. For electromagnetic emission application scenarios with strict volume-weight constraints and large power-energy requirements, a hybrid energy storage group chopper discharge topology is designed, and its working principle and operation boundary are introduced. Then, taking the single maximum power demand, continuous maximum energy demand and multiple constraints of the transmitting load as the design input, the optimal con-figuration of supercapacitor and lithium battery is carried out. Taking the weight, volume and cost as the comprehensive optimization objectives, iterative approximation is carried out, and finally the optimal configuration solution of the hybrid energy storage system is obtained. The effectiveness of the topology is verified by simulation. © 2022 IEEE.

关键词： Choppers (circuits)

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A Transformer-Based Time Series Prediction Model with Contrastive Learning for Nuclear Power system State Monitoring

A Transformer-Based Time Series Prediction Model with Contra...

引用

Prognostics and system Health Management Conference (PHM-Qingdao)

作者： Pengfei Gou Daiwei Zheng Lei Tang Mengjuan Liu School of Information and Software Engineering University of Electronic Science and Technology of China UESTC Chengdu China Science and Technology on Reactor System Design Technology Laboratory Nuclear Power Institute of China NPIC Chengdu China

ISBN: (数字)9798350354010

ISBN: (纸本)9798350354027

Prognostics and Health Management (PHM) is currently the mainstream solution for the condition monitoring and maintenance of industrial systems. In PHM, the system condition is monitored by monitoring the operational status parameters of the system to diagnose equipment faults, predict the remaining useful life, etc. Utilizing sequential operational status parameters to complete prediction and classification tasks is usually modeled as a time series processing task. Therefore, a high-performance time series prediction model is crucial for PHM. This paper focuses on the use of time series prediction models to achieve the prediction of key state parameters of the nuclear power system. However, there are still some challenges when directly applying existing time series prediction models to industrial systems. First, obtaining operational data on the nuclear power system is relatively difficult, resulting in a small amount of training data, which causes many models to face the risk of insufficient training or overfitting. Second, most of the existing time series prediction models are composed of high- and low-frequency decoupling modules, while the operational data of nuclear power systems often have fewer high-frequency components, making it difficult for many existing SOTA models to achieve good results. In order to address these challenges, we have developed a Transformer-based time series prediction model with contrastive learning for monitoring the status of nuclear power systems. We evaluated the new model on three nuclear power simulation datasets and four power transformer datasets. The experimental results show that the new model's performance is superior to baseline models. We also proved the effectiveness of our improvement through ablation experiments.

关键词： Training Time series analysis Training data Contrastive learning Predictive models Data models Power systems Power transformers Prognostics and health management Monitoring

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An IGBT Device Health Status Assessment Method Considering the Influence of Operating Conditions

An IGBT Device Health Status Assessment Method Considering t...

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IEEE/IAS Industrial and Commercial Power system Asia (I&CPS Asia)

作者： Cheng Yang Zeyu Duan Ran Yao Hui Li Wei Lai Yuan Min Yannan Yuan Wenxing Han State Key Laboratory of Power Transmission Equipment & System Security and New Technology Chongqing University Chongqing China Science and Technology on Reactor System Design Technology Laboratory Nuclear Power Institute of China ChengDu China

The Insulated Gate Bipolar Transistor (IGBT) is a critical component of power electronic equipment, and its health is of utmost importance to ensure the reliability and stability of the entire system. This paper proposes a method for assessing the health status of IGBT device under various operating conditions. Firstly, a finite element model of the IGBT device is established to analyze the influence of solder layer void and bond line detachment on the saturation voltage of the device. Secondly, the device parameters are simulated under different working conditions, and an adaptive neural network algorithm is used to establish the IGBT equipment health state evaluation model. Finally, the results of the model are analyzed, and the prediction results under random conditions are compared with the simulation results. The results show that this method effectively evaluates the health status of IGBT devices.

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