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检索条件"任意字段=2023 6th International Conference on Advanced Algorithms and Control Engineering, ICAACE 2023"

共 292 条记录，以下是191-200 订阅

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A Trajectory Tracking Method using Dynamic Sliding Mode control with Parameter Optimization for Autonomous Underwater Vehicles

A Trajectory Tracking Method using Dynamic Sliding Mode Cont...

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Industrial Cyber-Physical Systems (ICPS)

作者： Weiliang Li Xuzhi Lai Sheng Du Chengda Lu Yawu Wang Zonghuan Chen Min Wu School of Automation China University of Geosciences Wuhan China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan China Ministry of Education Engineering Research Center of Intelligent Technology for Geo-Exploration Wuhan China Guangzhou Marine Geological Survey Guangzhou China

Autonomous underwater vehicles (AUVs) must be able to track a particular trajectory when performing various tasks. Sometimes, the widely used control method in actual marine engineering, the proportional integral derivative (PID) control method cannot meet the accuracy requirements of AUVs' trajectory tracking. In this paper, a dynamic surface sliding mode controller for trajectory tracking is designed. A nonlinear disturbance observer is used to compensate for environmental interference, and an improved particle swarm optimization with dynamic inertia weight is applied to optimize the control parameter. Simulation experiments are based on the mathematical model of an underwater robot BLUEROV2, and the control and optimization algorithms are designed.

关键词： Autonomous underwater vehicles Trajectory tracking Heuristic algorithms Mathematical models Trajectory Vehicle dynamics Particle swarm optimization

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A Foreign Object Detection Method for Railway Overhead Lines Based on Few-Shot Learning 1

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6th international conference on Electrical engineering and Information Technologies for Rail Transportation, EITRT 2023

作者： Yu, Hang Qin, Yong Cao, Zhiwei Lian, Lirong Gao, Yang Bai, Jie Ge, Xuanyu State Key Laboratory of Advanced Rail Autonomous Operation Beijing Jiaotong University Beijing100044 China School of Traffic and Transportation Beijing Jiaotong University Beijing100044 China Key Laboratory of Railway Industry of Proactive Safety and Risk Control Beijing100044 China Beijing Rolling Stock Depot Beijing Group Co. Ltd Beijing100039 China

ISBN: (数字)9789819993192

ISBN: (纸本)9789819993185

It often occurs that foreign objects hang on railway overhead lines especially in windy days, which may lead to the delay of train, and even cause loss of life and property. With the gradual maturity of computer vision, railway foreign object detection has made great progress. this paper focuses on foreign object in railway overhead lines, and proposes a foreign object detection method based on few-shot learning. the proposed method consists of two stages: general training and fine-tuning training. In the first stage, the data-abundant common classes dataset is used to train the entire detector to obtain the underlying model parameters. In the fine-tuning stage, we make a balanced dataset consisting of common classes and enhanced railway classes, and fine-tune the last layer of the detector to accomplish few-shot foreign object detection. Finally, this proposed method is tested on images of overhead lines intrusions taken in actual railway scenario, and achieves 79% mAP in railway classes. © 2024, Beijing Paike Culture Commu. Co., Ltd.

关键词： Object detection

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6th international conference on Electrical engineering and Information Technologies for Rail Transportation, EITRT 2023

作者： Lian, Lirong Qin, Yong Cao, Zhiwei Gao, Yang Bai, Jie Ge, Xuanyu Yu, Hang State Key Laboratory of Advanced Rail Autonomous Operation Beijing Jiaotong University Beijing100044 China School of Traffic and Transportation Beijing Jiaotong University Beijing100044 China Key Laboratory of Railway Industry of Proactive Safety and Risk Control Beijing100044 China

ISBN: (数字)9789819993192

ISBN: (纸本)9789819993185

Real-time awareness of the service status of facilities and equipment in metro tunnels is essential for the safe movement of trains. For low illumination underground tunnel environments where objects have high similarity characteristics and are difficult to distinguish, this paper proposes a framework for tracking high similarity objects along the rail line based on on-board visual perception devices. the framework mainly consists of two stages: object detection and object association. In the first stage, an object detection algorithm is used to detect potentially faulty objects in the video, and this paper takes the continuous occurrence of insulated steel supports on the line as the high similarity research object. In the second stage a matching strategy is used to associate the same object in the video sequence and assign the same ID (identity document). Finally, the proposed framework was tested on metro tunnel video and achieved an accuracy of 95.64 and a detection performance of 25 FPS (frames per second), 82.17 MOTA (multiple object tracking accuracy) and 88.46 MOTP (multiple object tracking precision) tracking performance. © 2024, Beijing Paike Culture Commu. Co., Ltd.

关键词： Object detection

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Photovoltaic abnormal data cleaning based on fuzzy clustering-quartile algorithm

Photovoltaic abnormal data cleaning based on fuzzy clusterin...

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Industrial Cyber-Physical Systems (ICPS)

作者： Yidong Li Danyun Li School of Automation China University of Geosciences Wuhan China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan China Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education Wuhan China

the irradiance-power curve is an important basis for examining the operating status of photovoltaic power stations. In the actual operation process, sensor failure, abnormal communication and equipment damage will bring a large number of abnormal values to the output data of photovoltaic power plants. It will have a significant impact on a variety of applications based on photovoltaic output data. this paper analyzes the typical outliers on the irradiance-power curve and proposes a photovoltaic output data cleaning method based on fuzzy clustering algorithm and quartile algorithm. By comparing with the quartile method, it is proved that this method can effectively identify abnormal data when there are a large number of outliers in the photovoltaic output data.

关键词： Photovoltaic systems Training Clustering algorithms Prediction algorithms Cleaning Filling Data models

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An Improved Flower Pollination Algorithm based Modelling Method of Photovoltaic Modules 6

An Improved Flower Pollination Algorithm based Modelling Met...

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6th international conference on Mechanical, Electrical and Material Application, MEMA 2023

作者： Li, Xiaofeng Ji Hua Laboratory Foshan China

In recent years, with the acceleration of the global carbon emission reduction process, the sustainable development of clean energy has become the leading role, and the photovoltaic (PV) market has ushered in a hotter market. For accurately estimating the power generation of PV modules under different weather conditions, the modeling of solar cells or PV modules is very important. However, the conventional optimization algorithms cannot satisfy the accuracy of identification of the five parameters in the single diode model. In this paper, an improved FPA is proposed to estimate the five model parameters of the PV modules. In the proposed algorithm, the FPA is improved by considering different updating methods of solution for each pollen, with or without Levy flight. Experimental results validate that the proposed improved FPA can accurately identify the five model parameters and satisfy the modeling demands of PV arrays in engineering applications. © Published under licence by IOP Publishing Ltd.

关键词： Emission control

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6th international conference on Communication, Devices and Networking, ICCDN 2022

6th International Conference on Communication, Devices and N...

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6th international conference on Communication, Devices and Networking, ICCDN 2022

ISBN: (纸本)9789819919826

the proceedings contain 60 papers. the special focus in this conference is on Communication, Devices and Networking. the topics include: Impact of Perceived Social Support on Patient Empowerment: A Study of Online Patient Support Groups;Interfacing of Industrial Inductive Proximity Sensor with NI DAQ and Speed Measurement;design and Implementation of Intelligent Vehicle Dual Vehicle Merging Based on Image Processing and Electromagnetic Induction;shield Tunnel Design Method Based on Constrained Multi-objective Optimization Algorithm;railway Traffic Operation Optimization Method and System Based on Bee Colony Algorithm;A Method and Display System for Interacting with Virtual Scene through VR Device;research on Dance Training System Based on Motion Capture and Virtual Reality;intelligent Motion control Technology of Industrial Robot;Research on GIS Data Maintenance Technology Based on DBSCAN Algorithm;Design and Analysis of an Efficient Novel Multilayer 4:1 MUX Using QCA Technique with Reversibility and Stability;research on Matching Algorithm of Color;multi-band Dual-Polarized Linear-Circular and Linear-Cross Obliquely Stable Reflective Type Polarizer with Mechanically Tunable Reflector Response for K-and Ka-Bands Applications;enrichment of Polarization Purity, Gain and Compactness of Circular Microstrip Antenna;Reconfigurable Dual Polarized Square Patch Antenna for ISM Band with PIN Diode Integration;design and Analysis of an On-Body Microstrip Patch Antenna for Biomedical Application;DHRNN: Deep Hybrid Recurrent Neural Networks for Aquaculture Water Quality Prediction;blockchain-Based Clean and Green Energy (Pico Hydel Power) Monitoring System;a Comparative Analysis to Predict Diabetes Using Classification algorithms;F-DDPT: An Efficient Fuzzy-Based Automated Preprocessing Technique to Support Explainability.

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Composite Fault Signal Detection Method of Electromechanical Equipment Based on Empirical Mode Decomposition 1

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6th European-Alliance-for-Innovation (EAI) international conference on advanced Hybrid Information Processing (ADHIP)

作者： Fu, Guolong Yin, Jintian Wu, Shengyi Liu, Li Peng, Zhihua Shaoyang Univ Hunan Prov Key Lab Grids Operat & Control Multi Power Sources Area Shaoyang 422000 Peoples R China Shaoyang Univ Sch Elect Engn Shaoyang 422000 Peoples R China

ISBN: (数字)9783031288678

ISBN: (纸本)9783031288661;9783031288678

Aiming at the problem of low detection accuracy when the traditional method is used to detect the composite fault signal of electromechanical equipment, a method for detecting the composite fault signal of electromechanical equipment based on empirical mode decomposition is proposed. In this paper, the operation information of the electromechanical equipment is collected first, and then the complex signal is identified based on the empirical mode decomposition theory, and the location of the complex fault area of the electromechanical equipment is completed to improve the detection accuracy. Finally, experiments are used to prove the advanced nature of the proposed method. the experimental results show that the fault diagnosis accuracy of the proposed method for electromechanical equipment is higher than 75%, the response time is less than 40 ms, and the memory occupation is less than 5500 kB, all of which are superior to the traditional method and have certain application value.

关键词： Empirical mode decomposition Electromechanical equipment Fault signal Fault detection

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Estimation of Minimum Miscibility Pressure in Impure/Pure N2 Based Enhanced Oil Recovery Process: A Comparative Study of Statistical and Machine Learning algorithms

Estimation of Minimum Miscibility Pressure in Impure/Pure N2...

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Robotics, control and Automation engineering (RCAE), international conference on

作者： Xiuli Zhu Seshu Kumar Damarla Biao Huang Department of Control University of Shanghai for Science and Technology Shanghai China Department of Chemical and Materials Engineering University of Alberta Alberta Canada

Minimum miscibility pressure (MMP) prediction plays an important role in design and operation of nitrogen based enhanced oil recovery processes. In this work, a comparative study of statistical and machine learning methods used for MMP estimation is carried out. these methods include weighted k-nearest neighbors, wavelet neural network, general regression neural network, extreme learning machine, regression trees (RTs), random forest, bagging RTs, boosting RTs and Gaussian process regression. Most of the predictive models developed in this study exhibited superior performance over predictive models reported in literature.

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Intelligent control test platform system design based on PID control algorithm

Intelligent control test platform system design based on PID...

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6th international conference on Intelligent Computing and Signal Processing (ICSP)

作者： Jiaqi Xu School of Electrical and Mechanical Engineering Xi’an Polytechnic University Xi’an China

this study explores the control application of incremental PID control algorithms in an intelligent control experimental platform and verifies its feasibility. Based on the control model of the intelligent control experiment platform, we deeply analyze the impact of the digital incremental PID algorithm on the tracking and stable output waveform in the closed-loop control process. the results show that the algorithm is simple to implement, has good control effect and is less prone to oscillation.

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Overview of Traction System Testing Indicators for Rail Transit Equipment 6th

Overview of Traction System Testing Indicators for Rail Tran...

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6th international conference on Electrical engineering and Information Technologies for Rail Transportation, EITRT 2023

作者： Liao, Jiaxin Xie, Zhengyu School of Traffic and Transportation Beijing Jiaotong University Beijing100044 China State Key Laboratory of Advanced Rail Autonomous Operation State Beijing Jiaotong University Beijing100044 China Key Lab of Proactive Safety and Risk Control in Railway Operation Beijing100044 China Beijing Research Center of Urban Traffic Information Sensing and Service Technologies Beijing100044 China

ISBN: (纸本)9789819993185

With the rapid development of China’s high-speed rail and other rail transit systems, the evaluation and quantitative assessment of traction performance have become increasingly significant. Traction systems, which are responsible for the propulsion of trains, play a crucial role in ensuring the efficiency, reliability, and safety of rail transportation. In this context, this study delves into the composition equipment and evaluation standards of traction systems, providing a valuable academic contribution to the design, manufacturing, and operation of new vehicle models. the paper extensively discusses the various components that constitute a traction system, including motors, control systems, power converters, and auxiliary equipment. It emphasizes the importance of evaluating the traction system’s performance and provides a comprehensive understanding of the evaluation criteria. Among these criteria, the paper focuses on three crucial aspects: no-load tests, load tests, and temperature rise *** addition to discussing the evaluation criteria for traction systems, the paper also introduces and explores the testing indicators specific to rail transit equipment. these indicators encompass factors such as tractive effort, energy efficiency, traction-to-weight ratio, and acceleration capability. By providing a comprehensive overview of these indicators, the paper offers valuable insights and guidance for researchers and practitioners in the field of rail transportation. © 2024, Beijing Paike Culture Commu. Co., Ltd.

关键词： Auxiliary equipment

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