检索结果-内蒙古大学图书馆

Power, Electrical Engineering, Electronics and control (PEEEC), International conference on

作者： Yanli Cai Wuhan Qingchuan University Wuhan Hubei China

data fusion technology is an information processing discipline that just emerged in the 1990s, and its application range is very wide, while target tracking and recognition is still the most important subject of data fusion technology research. And with the development of sports research, it has become an inevitable trend to pursue the accuracy of intelligent sports data measurement. In order to obtain accurate sports data, motion capture technology is an important means to obtain sports data. For this reason, based on the systematic analysis of the current human motion modeling and simulation research methods, this paper proposes a multi-data fusion-based intelligent New ideas for sports data measurement. With the help of a variety of modern signal analysis and processing methods, the feature extraction and motion pattern classification of EMG signals in the process of human movement are studied in detail. Compared with the image-based method, the accuracy of sports target tracking is further improved. In order to meet the requirement of similarity retrieval from large-scale database, the similarity measure of different human body movements and postures is defined. Display and manage human movement data and evaluation results, so as to facilitate the storage and query of historical movement records.

关键词：

来源：评论

学校读者我要写书评

暂无评论

A MBD-based bidirectional data-driven 3D CAPP Platform 5

A MBD-based bidirectional data-driven 3D CAPP Platform

引用

5th International conference on Mechatronics and Computer Technology Engineering, MCTE 2022

作者： Wang, Xiaogang Bai, Yuewei Zeng, Fenfang Mu, Hua Qiu, Jianping College of Intelligent Manufacturing and Control Engineering Shanghai Polytechnic University Jinhai Road 2360 Pudong New Distrtict Shanghai China Wuhan KAIMU Information Technology Co. Ltd Building A5 Software New Town 1# New Technology Development Zone Hongshan District Hubei Wuhan China Co. Ltd No. 1 Xifei Avenue Yanliang District Shaanxi Xi'an China

ISBN: (纸本)9781510661073

For a full three-dimensional process design manufacturing technology platform for product collaborative design and process design requirements, this paper introduces a kind of MBD based 3 d technology platform, platform based on MBD technology and knowledge base system, build the information processing technology and the mapping relationship between information modeling, and design the grouping based on the characteristics of the process of the full three-dimensional design process. Under the support of a knowledge base, the platform realizes the optimization of product design and manufacturability inspection analysis and drawing compliance inspection, found that as early as possible in the design of manufacturing related problems, to avoid disconnection between design and manufacturing in the traditional design method and make the design of the products meet the requirements of the product's functionality, manufacturability, etc. It is of great significance for enterprises to implement 3D digital process design and integration technology. © 2022 SPIE.

关键词： Product design

来源：评论

学校读者我要写书评

暂无评论

An Internal Model control Method Based on Reversible Residual Neural Network Model Applied to Turntable Servo Systems

An Internal Model Control Method Based on Reversible Residua...

引用

data Driven control and Learning Systems (DDCLS)

作者： Cheng Xie Ting Chen Yang Liu Songlin Chen Control and Simulation Center School of Astronautics Harbin Institute of Technology Harbin P. R. China Institute for Micro Nano Satellites Innovation Academy for Microsatellites of CAS Shanghai P. R. China

ISBN: (数字)9798350361674

ISBN: (纸本)9798350361681

To meet the special requirements of high dynamic and performance for turntable servo systems, an internal model control (IMC) method based on reversible residual neural network model is proposed in this paper. In order to improve the accuracy and modeling efficiency of the forward and inverse models in the internal model controller and ensure the correlation between these two models, a reversible residual neural network model based on the forward and inverse dynamic characteristics of turntable servo systems is proposed. Through the special design of the network structure, the forward and inverse models can be obtained by one-way training. Then, the forward and inverse models are applied to the traditional IMC algorithm framework, the IMC method based on the reversible network model is obtained, and the stability of the control system is proved. The simulation results show that the proposed IMC method has better nonlinear compensation ability, tracking effect, and dynamic performance than the traditional IMC method. In addition, the design process of the proposed internal model controller is simpler and more practical. The method described in this paper has important value and significance for the intelligent development of traditional servo control.

关键词： Training Learning systems Simulation process control control systems data models Stability analysis

来源：评论

学校读者我要写书评

暂无评论

Hydraulic-Fracture-Width Inversion Using Low-Frequency Distributed-Acoustic-Sensing Strain data-Part I: Algorithm and Sensitivity analysis

引用

SPE JOURNAL 2021年第1期26卷 359-371页

作者： Liu, Yongzan Jin, Ge Wu, Kan Moridis, George Texas A&M Univ College Stn TX 77843 USA Colorado Sch Mines Golden CO 80401 USA Lawrence Berkeley Natl Lab Berkeley CA USA

Low-frequency distributed-acoustic-sensing (LF-DAS) data, which can be treated as linear-scaled strain variations, have been used recently to monitor hydraulic-fracturing treatments. Forward geomechanical modeling has been the subject of recent research efforts to better interpret the observed signatures of field LF-DAS data. To the best of our knowledge, there is no study that attempts to quantitatively characterize fracture geometries by directly inverting the LF-DAS strain data. In this study, we propose an inversion algorithm, in which the strains monitored by LF-DAS along an offset well are related to the fracture widths through a Green function. A 3D displacement-discontinuity method is used to construct the Green function. The least-squares method is first used to solve the linear system of equations. Regularization might be needed to stabilize the underdetermined system. Then, Markov-chain Monte Carlo (MCMC) simulations are conducted to generate fracture-width samples from the target distribution of LF-DAS strain data and to quantify uncertainties associated with the inverted widths. The inversion results obtained by the least-squares method are nonunique, heavily depending on the a priori regularization information. Regardless of the additional constraints imposed on the linear system, the inverted fracture width at the monitor-well location is always consistent with the true value because the LF-DAS data show a dominant sensitivity of fracture width near the monitor well. MCMC simulation results confirm that the LF-DAS strain data can only impose constraints on fracture segments near the monitor well. Moreover, the average value of the inverted widths in the vicinity of the monitor well is usually the same as the width right at the monitor well, except for the very early time after fracture hit when there are sharp width variations near the fracture tip. Therefore, it is efficient to use a single width for each fracture during the inversion process. The pr

关键词： production monitoring hydraulic fracturing reservoir surveillance upstream oil & gas production control production logging machine learning inversion result fracture element unconventional resource technology conference Hydraulic Fracturing Information Management and Systems Production logging Well & Reservoir Surveillance and Monitoring

来源：评论

学校读者我要写书评

暂无评论

Safe Reinforcement Learning-Based Adaptive Hierarchical control Approach for Virtual Coupling Trains

Safe Reinforcement Learning-Based Adaptive Hierarchical Cont...

引用

IEEE International conference on Networking, Sensing and control

作者： Lei Zhang Gaoyun Cheng Wei Wang Key Laboratory of Big Data & Artificial Intelligence in Transportation (Ministry of Education) Beijing Jiaotong University Beijing China Traffic Control Technology Co. Ltd. Beijing China

ISBN: (数字)9798350365221

ISBN: (纸本)9798350365238

Virtual coupling presents a promising solution for enhancing urban rail transit efficiency through collaborative operations facilitated by information communication rather than physical connections. However, effectively controlling virtual coupling trains presents substantial challenges, particularly in managing implicit and nonlinear safety constraints. This paper proposes a novel adaptive hierarchical control approach to address these challenges, modeling the control problem as a Constrained Markov Decision process (CMDP). The proposed approach integrates an upper controller utilizing safe reinforcement learning (RL) and a lower controller employing Proportional Integral Derivative (PID). Safe RL incorporates an unrolling safety layer (USL) into the RL algorithm, effectively addressing safety constraints inherent in the system. Additionally, dynamic adjustment of PID parameters based on the state of the virtual coupling trains enables precise control of train operations. This hierarchical architecture capitalizes on the adaptability of safe RL while leveraging the stability of PID, facilitating dynamic strategy adjustments in response to environmental changes to ensure virtual coupling stability and reliability. Simulation experiments validate the efficacy of the proposed approach, demonstrating significant advantages in controlling virtual coupling trains and thereby enhancing operational efficiency and safety.

关键词： Couplings Rails Adaptive systems Reinforcement learning Systems modeling Stability analysis Safety Sensors Reliability Optimization

来源：评论

学校读者我要写书评

暂无评论

Research on Dynamic control Model of Multi-Scenario Synchronization in Aircraft Suspension Lifting System

Research on Dynamic Control Model of Multi-Scenario Synchron...

引用

China International Electrical and Energy conference (CIEEC)

作者： WenQing Guan Xin Kou ManFeng Dou ShiYuan Chao School of Automation Northwestern Polytechnical University Xian China Lanzhou Wanli Aero Electro-Mechanism Limited Corporation Co .Ltd. Lanzhou China Gansu Key Laboratory of Aeronautical electro-mechanical actuator Lanzhou China

ISBN: (数字)9798350359558

ISBN: (纸本)9798350359565

The airborne suspension lifting system is a typical rigid-flexible coupling system. The coupling effect is easily generated by the excitation of the rigid transmission mechanism on the flexible cable composed of steel wire ropes. Meanwhile, the multi-operating conditions and unbalanced characteristics of the load further exacerbate the complexity of synchronous control. In this paper, aiming at the synchronous control problem under multiple operating conditions, a multi-body dynamics model of the airborne suspension lifting system based on the generalized Hamiltonian principle is established. Differential equations of the tension of steel wire ropes are proposed, and dynamic analysis under multiple operating conditions is conducted in combination with experimental data. The influence of unbalanced loads on the tension of the cable is studied, and the variation law of cable tension response during the lifting process of the system is obtained, providing data support and theoretical basis for the design of synchronous control of the lifting system.

关键词： Couplings Vibrations Atmospheric modeling Differential equations Mathematical models Communication cables Wire

来源：评论

学校读者我要写书评

暂无评论

Wind fractional modeling by spectral analysis 9

Wind fractional modeling by spectral analysis

引用

9th International conference on Systems and control (ICSC)

作者： Hajjem, Mohamed Victor, Stephane Melchior, Pierre Lanusse, Patrick Thomas, Lara Univ Bordeaux IMS UMR 5218 CNRS Talence France Safran Data Syst La Teste De Buch France

ISBN: (纸本)9781665407823

This paper deals with wind turbulence modeling by using spectral analysis, in order to have a real-time wind simulator for dynamic models of parabolic tracking antennas. Indeed, such a realistic wind speed is needed to make dynamic models more complete and to design robust controls. The wind speed can be decomposed into two components: a long-term one representing the wind mean speed and a short-term one corresponding to the wind turbulence. Fast wind turbulence is a stochastic process and is difficult to model in time domain. For this reason, the models presented in this paper are based on the wind spectral characteristics. The most used Von Karman model well approximates the power spectral density of the wind turbulence. However, this model lacks precision in middle range frequency. Indeed, the Von Karman model was originially designed for aircrafts, and consequently for high altitudes and moving systems. In our case, tracking antennas are used under different conditions: low altitude and slow moving systems. Therefore, there is a need in more precisely modeling wind turbulence under these specific conditions. As Von Karman's model expression uses fractional calculus, other models with the same range of parameter number are proposed to better approximate the wind power spectral density by using Cole-Cole and Havriliak-Negami fractional models. The proposed fractional models will enable generating realistic random wind speed turbulence from a random white noise input.

关键词： Dynamic models

来源：评论

学校读者我要写书评

暂无评论

Hierarchical Clustering Approach for Information-Extreme Machine Learning of Hand Brush Prosthesis 5

Hierarchical Clustering Approach for Information-Extreme Mac...

引用

5th International conference on Computational Linguistics and Intelligent Systems (COLINS)

作者： Dovbysh, Anatoliy Piatachenko, Vladyslav Sumy State Univ 2 Rymskogo Korsakova St UA-40007 Sumy Ukraine

The article discusses a machine learning method for a control system for a hand limb prosthesis with a non-invasive biosignal reading system, which operates in the mode of agglomerative hierarchical clustering of electromyographic data. The method was developed within the framework of information-extreme intelligent data analysis technology, which is based on maximizing the information capacity of the system in the process of machine learning. In contrast to the existing methods of data mining, the method of information-extreme machine learning is developed as part of a functional approach to modeling cognitive processes inherent in human formation and decision-making. This approach makes it possible to endow the prosthesis control system with the properties of adaptability to arbitrary conditions for the formation of input signals and flexibility in retraining the system due to the expansion of the alphabet of recognition classes. In addition, the decision rules based on the geometric parameters of the hyperspherical containers of the recognition classes obtained in the process of machine learning are invariant to the multidimensionality in the feature space. Based on the proposed categorical model, a machine learning algorithm using an agglomerative hierarchical data structure has been developed. As a criterion for optimizing the parameters of machine learning, a modification of the Kullback information measure is used, which is a functional of the exact characteristics of classification decisions. The results of physical modeling confirm the high functional efficiency for the proposed hierarchical information-extreme machine learning method of the hand with a non-invasive system for reading biosignals prosthesis control system.

关键词： information-extreme intellectual technology hierarchial clustering machine learning information criterion control system prosthesis electromyographic sensor

来源：评论

学校读者我要写书评

暂无评论

Research on Accelerated Degradation Test and Reliability Evaluation Method of Electromechanical Products 33

Research on Accelerated Degradation Test and Reliability Eva...

引用

33rd Chinese control and Decision conference (CCDC)

作者： Wang, Yi Syst Engn Res Inst Beijing 100094 Peoples R China Nanjing Univ Aeronaut & Astronaut Nanjing 210016 Peoples R China

ISBN: (纸本)9781665440899

According to the characteristics of long life and high reliability of aviation electromechanical products, the reliability of electromechanical products was evaluated by designing step down stress accelerated degradation test (SDSADT) and modeling analysis of performance degradation data. An accelerated degradation test scheme combining pre-test and formal test was proposed. Based on the degradation data of product performance, a nonlinear Wiener process degradation model with measurement error was established. The random drift parameters and random initial values caused by individual differences were considered. A multi-stage parameter estimation method was proposed and the product failure time distribution was derived. The simulation results were compared with the traditional Wiener model. Finally, the test verification and life evaluation of a certain type of resolver were carried out, and the reliability curve of this type of resolver under normal temperature storage environment was obtained. The results show that the proposed accelerated degradation test scheme can significantly shorten the test time, improve the test efficiency and data validity, the performance degradation model used is more accurate than the traditional Wiener model, and the reliability evaluation results are reliable.

关键词： Electromechanical Products Accelerated Degradation Test Wiener process Reliability

来源：评论

学校读者我要写书评

暂无评论

Occupancy Grid Artefact Removal and Error Correction using GANs

Occupancy Grid Artefact Removal and Error Correction using G...

引用

Computer, control and Robotics (ICCCR), International conference on

作者： Leon Davies Baihua Li Mohamad Saada Simon S⊘lvsten Qinggang Meng Department of Computer Science Loughborough University Loughborough United Kingdom European Center for Risk & Resilience Studies University of Southern Denmark Esbjerg Denmark

ISBN: (数字)9798350373141

ISBN: (纸本)9798350373158

Occupancy Grid Mapping is a form of Simultaneous Localisation and Mapping (SLAM) in which the world around a robot is visually represented as a grid map. This form of map can be compared to a floor plan in which features within an environment such as walls are labelled in place. Certain issues such as noise, artefacts, linear error, angular error, and incomplete rooms make this representation difficult to appropriate. Generative Adversarial Networks (GAN) [1] in the past have proven successful in and reliable methods for noise reduction, artefact removal [2], and partial observation completion [3]. We demonstrate a novel data creation process to mass produce samples of erroneous and ideal occupancy grid maps. We use this data to build two GAN models based on well-known frameworks CycleGAN [4] and CUT [5] for the task of occupancy grid cleaning. We demonstrate the generalisability of our models through making predictions of ‘clean’ maps on samples of real data from the Radish dataset [6].

关键词： Visualization Simultaneous localization and mapping Computational modeling Generative adversarial networks data models Reliability Task analysis

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：