检索结果-内蒙古大学图书馆

Semi-Supervised process Data Regression and Application Based on Latent Factor Analysis Model

IEEE Transactions on Instrumentation and Measurement 2023年 72卷 1页

作者： Zheng, Junhua Liu, Yangxuan Liu, Yi Hou, Beiping Yao, Yuan Zhou, Le Zhejiang University of Science and Technology School of Automation and Electrical Engineering Hangzhou310023 China Institute of Process Equipment and Control Engineering Zhejiang University of Technology Hangzhou310023 China National Tsing Hua University Department of Chemical Engineering Hsinchu30013 Taiwan

This article investigates the problem of modeling regression with labeled and unlabeled data samples commonly found in industrial processes. By incorporating additional information on unlabeled data samples, a new semi-supervised latent factor analysis model is developed. Compared with the purely supervised regression models which can only use the information of labeled dataset, the semi-supervised model can efficiently extract useful information for improvement of the regression performance. Furthermore, the proposed basic semi-supervised model has been extended to a mixture form, which is capable of describing data from more complex processes. For predictive modeling for key/mass variables, two soft sensors are constructed based on the semi-supervised models. Then, three case studies are used to evaluate the performance of the proposed soft sensing methods. © 2023 IEEE.

关键词： Regression analysis

来源：评论

学校读者我要写书评

暂无评论

Multimodal Decoupling of Stationarity and Nonstationarity with Deep Cascaded Architecture for Varying-Condition process Monitoring

Multimodal Decoupling of Stationarity and Nonstationarity wi...

引用

第34届中国过程控制会议

作者： Pengyu Song Chunhui Zhao Jinliang Ding Furong Gao College of Control Science and Engineering Zhejiang University State Key Laboratory of Synthetical Automation for Process Industries Northeastern University Department of Chemical and Biological Engineering Hong Kong University of Science and Technology

Nonstationarity,i.e.,the time-varying property of the data distribution,is a typical process characteristic caused by operating condition switching,which can conceal stationarity describing time-invariant process mechanisms and thus bring challenges for explicit process *** achieve full decoupling of stationarity and nonstationarity,this study reveals the following facts:1) the coupling between stationarity and nonstationarity is not uniform but can present time-varying modes,defined as multimodal coupling here;2) diverse coupling modes possess intrinsic association since they essentially stem from definite nonstationary driving forces,namely changeable operating ***,this study proposes a multimodal decoupling representation method for learning explicit representations of stationarity and ***,to capture the basic coupling mode caused by nonstationary driving forces,an information refinement module(IRM) is designed in which a shortcut connection is incorporated into the auto-encoding *** the deep cascading of multiple IRMs,multimodal coupling modes can be fully ***,a compatibility learning algorithm is developed,which can balance the stationarity and reconstruction requirements to form a stationary feature learning module(SFLM).With compatibility learning,IRMs can be induced to capture and filter out nonstationarity and output stationary refined information for *** this way,multimodal decoupling of stationarity and nonstationarity can be fully *** effectiveness of the proposed method is illustrated through a numerical example and an actual industrial process.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Discrete-time Formation control With Attitude Alignment: A Geometric Approach under Ergodic Products

引用

IEEE Transactions on control of Network Systems 2025年

作者： Li, Zhen Tang, Yang Zhang, Wenbing Fan, Yongqing Huang, Tingwen Xi-an University of Posts and Telecommunications School of Automation Xian710121 China East China University of Science and Technology Key Laboratory of Smart Manufacturing in Energy Chemical Process Shanghai200237 China Yangzhou University Department of Mathematics Jiangsu225002 China Shenzhen University of Advanced Technology Faculty of Computer Science and Control Engineering Shenzhen518055 China

Assuming agents possess sensing capabilities and dynamics relative to their body coordinate frames, this paper addresses a displacement-based strategy for discrete-time formation control through attitude synchronization. Unlike the Eulerian approximation, the first challenge lies in developing discrete-time models that capture both position and attitude motions, thereby complementing existing continuous-time systems with a discretized version. Then, two leader-following control protocols are designed, incorporating a jointly-connected topology to relax the connectivity requirements. The analysis of these systems often relies on the Lyapunov function, the existence of which may be hard to guarantee. Consequently, geometric properties of several polytopes are explored under the dynamic topologies and time-varying parameters. By extending the ergodicity results to leader-following scenarios, these properties are characterized as positively invariant sets. This invariance, which is independent of the existence of the Lyapunov function or the solvability of its associated criteria, provides a beneficial tool for analyzing time-variant systems. Utilizing this invariance and some mathematical techniques, the desired formation shape can be achieved in the cases where the attitudes of the followers synchronize with the leader. Finally, a numerical simulation validates the results. © 2014 IEEE.

关键词： Lyapunov functions

来源：评论

学校读者我要写书评

暂无评论

LBM modeling of three-dimensional mixed convection in CZ crystal growth on curvilinear coordinates system

引用

Results in Physics 2024年 61卷

作者： Zhang, Ni Liu, Ding The Department of Automation Xi'an Key Laboratory of Advanced Control and Intelligent Process Xi'an University of Posts and Telecommunications Xi'an 710121 China The Shaanxi Key Laboratory of Complex System Control and Intelligent of Information Processing Xi'an University of Technology Xi'an 710048 China

A three-dimensional (3D) thermal lattice Boltzmann model of crystal growth is presented to study the magneto-hydrodynamics (MHD) mixed convection in the melt of Czochralski silicon single crystal growth in this paper. In order to solve the problem of lattice Boltzmann method's difficulty in solving the flow of 3D cylindrical cavity, the 3D physical model of crystal growth is transformed from the Cartesian coordinate system to the Curvilinear coordinate system. And the irregular grids in the Cartesian coordinate system are transformed into regular grids in the Curvilinear coordinate system to facilitate the establishment of the Lattice Boltzmann model. Under the above operations, two coupled distribution functions are established to solve the governing equations. Two D3Q19 models are adopted to solve the melt velocity and temperature. And the 3D lattice Boltzmann modeling of crystal growth with cylinder boundary is realized by interpolation in Curvilinear coordinate system. The comparison with the experiment and other references proves that the proposed model and boundary treatment scheme is correct and it proposes a new way for studying the 3D crystal growth or other similar 3D cylindrical cavity simulations. Furthermore, the unstable melt flow for two cases are also simulated in this paper and the critical Reynolds number are also obtained. Results show that the introduction of the transverse magnetic field enhances the stability of the crystal growth system and increases the adjustable range of crystal rotation parameter. The obtained conclusion has an important reference for adjusting the process parameters during the CZ crystal growth. © 2024 The Author(s)

关键词： 3D mixed convection Computer simulation Heat transfer Lattice Boltzmann Method Silicon single crystal growth

来源：评论

学校读者我要写书评

暂无评论

Sparse Causality Analysis Approach with Time-varying Parameters for Root Cause Localization of Nonstationary process 4

Sparse Causality Analysis Approach with Time-varying Paramet...

引用

4th International Conference on Industrial Artificial Intelligence, IAI 2022

作者： Song, Pengyu Zhao, Chunhui Huang, Biao Ding, Jinliang College of Control Science and Engineering Zhejiang University State Key Laboratory of Industrial Control Technology Hangzhou310027 China University of Alberta Department of Chemical and Materials Engineering EdmontonABT6G 2G6 Canada Northeastern University State Key Laboratory of Synthetical Automation for Process Industries Shenyang110819 China

ISBN: (数字)9781665451208

ISBN: (纸本)9781665451208

Root cause diagnosis (RCD) is an important technique for maintaining the safe operation of industrial processes. Traditional RCD methods usually require stationarity assumptions. However, the process inevitably shows nonstationarity due to factors such as switching of operating conditions. Although there have been some previous studies trying to overcome the challenge of nonstationarity, these methods fail to guarantee the significance of the extracted causalities and lead to redundant relationships. To address the above issues, a sparse causal analysis model with time-varying parameters is extracted in this study. First, we propose an end-to-end information fusion and prediction task to characterize predictive relationships between variables and avoid repeated modeling. Second, we design time-varying parameters for the information fusion mechanism to cope with nonstationarity and automatically identify significant causality through sparse parameter updates. We design an update strategy that constrains the gradient information to guarantee sparsity. Finally, a causal metric is constructed for the time-varying predictive relationship to comprehensively obtain the overall causal relationship, which further guarantees causal significance. The validity of the proposed method is illustrated through a real industrial example collected from a thermal power plant. © 2022 IEEE.

关键词： Information fusion

来源：评论

学校读者我要写书评

暂无评论

Demand Response Optimization for the Enhancement of the Distribution System's Operation

Demand Response Optimization for the Enhancement of the Dist...

引用

International Conference on Smart Energy Systems and Technologies (SEST)

作者： Maria Fotopoulou George Tsekouras Dimitrios Rakopoulos Vassiliki Kontargyri Department of Electrical and Electronics Engineering University of West Attica Athens Greece Chemical Process and Energy Resources Institute Centre for Research and Technology Hellas Athens Greece Control Systems and Industrial Automation Laboratory National and Kapodistrian University of Athens Athens Greece

ISBN: (数字)9798350386493

ISBN: (纸本)9798350386509

Following the latest energy market trends, active distribution systems incorporate an ascending mix of flexible loads, which can participate in Demand Response (DR) strategies. The purpose of this research paper is to present a DR strategy for the Distribution System Operator (DSO) in order to enhance the system's operation and mitigate power quality issues, such as voltage drops, and congestion. The proposed algorithm aims at smoothing the load curve, taking into consideration the available flexible load and the limitations of the system. The algorithm is demonstrated on a model of the distribution system of Skiathos island, Greece, in the context of ENFLATE, a Horizon Europe project, and future scenarios with photovoltaic (PV) penetration are studied as well. According to the results, the proposed DR algorithm manages to reduce the voltage drop, eliminate the number of events where the voltage drop exceeds the limits and reduce the losses of the distribution system up to 8%-9%, depending on the PV penetration.

关键词： Electric potential Smoothing methods Power quality Europe Voltage Artificial neural networks Transformers Demand response Load modeling Context modeling

来源：评论

学校读者我要写书评

暂无评论

Adaptive Pseudo Inverse control for a Class of Nonlinear Asymmetric and Saturated Nonlinear Hysteretic Systems

引用

IEEE/CAA Journal of Automatica Sinica 2021年第4期8卷 916-928页

作者： Xiuyu Zhang Ruijing Jing Zhiwei Li Zhi Li Xinkai Chen Chun-Yi Su School of Automation Engineering Northeast Electric Power Universityand also with Jilin Province International Research Center of Precision Drive and Intelligent ControlJilin 132012China State Key Laboratory of Synthetical Automation for Process Industries Northeastern UniversityShenyang 110819China Department of Electronic and Information Systems Shibaura Institute of TechnologySaitama 337-8570Japan Department of Mechanical and Industrial Engineering Concordia UniversityQCMontreal H3B 1R6Canada

This paper aims at eliminating the asymmetric and saturated hysteresis nonlinearities by designing hysteresis pseudo inverse compensator and robust adaptive dynamic surface control(DSC)***"pseudo inverse"means that an on-line calculation mechanism of approximate control signal is developed by applying a searching method to the designed temporary control signal where the true control signal is *** main contributions are summarized as:1)to our best knowledge,it is the first time to compensate the asymmetric and saturated hysteresis by using hysteresis pseudo inverse compensator because the construction of the true saturated-type hysteresis inverse model is very difficult;2)by designing the saturated-type hysteresis pseudo inverse compensator,the construction of true explicit hysteresis inverse and the identifications of its corresponding unknown parameters are not required when dealing with the saturated-type hysteresis;3)by combining DSC technique with the tracking error transformed function,the"explosion of complexity"problem in backstepping method is overcome and the prespecified tracking performance is *** of stability and experimental results on the hardware-inloop platform illustrate the effectiveness of the proposed adaptive pseudo inverse control scheme.

关键词： Adaptive dynamic surface control adaptive pseudo inverse control asymmetric and saturated hysteresis robust control

来源：评论

学校读者我要写书评

暂无评论

Enhanced Soft Sensor with Qualified Augmented Data Using Centroid Measurement Criterion

Enhanced Soft Sensor with Qualified Augmented Data Using Cen...

引用

2021 International Conference on Information, Cybernetics, and Computational Social Systems, ICCSS 2021

作者： Dai, Yun Yu, Qing Yang, Tao Yao, Yuan Liu, Yi Zhejiang University of Technology Institute of Process Equipment and Control Engineering Hangzhou310023 China Northeastern University State Key Laboratory of Synthetical Automation for Process Industries Shenyang110819 China National Tsing Hua University Department of Chemical Engineering Hsinchu30013 Taiwan

ISBN: (纸本)9781665402453

Development of reliable soft sensors using limited labeled samples is not an easy task in industrial processes. A selective generative adversarial network (SGAN)-based support vector regression (SGAN-SVR) soft sensor is proposed for quality prediction using limited labeled training data. Specifically, SVR is considered as a base prediction model. The Wasserstein GAN (WGAN) is adopted to capture the distribution of available labeled data and generate virtual candidates. Subsequently, using a proposed similarity measurement strategy, those synthetic data with more information are selected and introduced into the training set. Using the designed data augmentation approach, the SGAN-SVR model can achieve better prediction performance compared with the SVR soft sensor. The quality prediction results on an industrial polyethylene process demonstrate the effectiveness and advantages of the proposed method. © 2021 IEEE.

关键词： Generative adversarial networks

来源：评论

学校读者我要写书评

暂无评论

Deep Graph Network for process Soft Sensor Development

Deep Graph Network for Process Soft Sensor Development

引用

2021 International Conference on Information, Cybernetics, and Computational Social Systems, ICCSS 2021

作者： Jia, Mingwei Dai, Yun Xu, Danya Yang, Tao Yao, Yuan Liu, Yi Zhejiang University of Technology Institute of Process Equipment and Control Engineering Hangzhou310023 China Northeastern University State Key Laboratory of Synthetical Automation for Process Industries Shenyang110819 China National Tsing Hua University Department of Chemical Engineering Hsinchu30013 Taiwan

ISBN: (纸本)9781665402453

In the (bio)chemical processes, traditional hardware sensors are difficult to directly measure the quality of critical products due to their time-varying, non-linear, and dynamic characteristics. This makes process soft sensor modeling methods important. Since the process variables can be regarded as natural graph data, this work introduces graphs in the soft sensor modeling area. A soft sensor model based on the graph neural network (GNN) is proposed. The model can learn the topological structure of graph data between each unit variable. Moreover, it characterizes variable relationships from the spatial and temporal dimensions to the output prediction by introducing the spatial-temporal convolutional layer. The effectiveness and advantages of the GNN-based soft sensor model are verified using a simulated fermentation process. © 2021 IEEE.

关键词： Graph neural networks

来源：评论

学校读者我要写书评

暂无评论

In-vitro Hemocompatibility Evaluation of the HeartMate 3 under Realistic Operating Conditions

引用

IEEE Transactions on Biomedical Engineering 2025年 PP卷 PP页

作者： He, Xiangyu Narayanaswamy, Krishnaraj Fischer, Michael B. Schmitt, Leonie Ruthmeier, Teresa Messner, Barbara Jakubek, Stefan Zimpfer, Daniel Granegger, Marcus Medical University of Vienna Christian Doppler Laboratory for Mechanical Circulatory Support Department of Cardiac Surgery Vienna Austria Medical University of Vienna Clinic for Transfusion Medicine and Cellular Therapy Vienna Austria Medical University of Vienna Department of Cardiac Surgery Vienna Austria Vienna University of Technology Division of Control and Process Automation Institute of Mechanics and Mechatronics Vienna Austria

Objective: Operating conditions significantly influence hemolysis generation in rotodynamic blood pumps (RBPs). Previous experiments conducted under constant operating conditions have demonstrated that lower flow rates are associated with a higher normalized index of hemolysis (NIH). However, in clinical scenarios, the pump flow rate fluctuates in response to the residual cardiac function. This study aims to investigate the effects of various pulsatile operating conditions on hemolysis generation and von Willebrand Factor (vWF) degradation of RBP. Methods: To investigate these conditions, pulsatile flow experiments were conducted for 12 hours using HeartMate 3 (HM3, Abbott Inc, USA) in a hybrid mock circulatory loop with citrated human blood from hemochromatosis patients. Three operating conditions (high, low, and no residual cardiac function) were examined under two pump speed settings: normal (5400rpm, 4.3L/min) and low (4800rpm, 2.5L/min). Hemolysis was assessed by measuring delta free hemoglobin every 30 minutes (dfHb30min) and calculating NIH. High molecular weight (HMW) vWF multimer degradation was assessed using immunoblotting. Results: There was no significant difference in dfHb30min (p>0.388), NIH (p>0.382), and HMW vWF multimers degradation (p>0.364) between the three operating conditions, but differences in these parameters were observed between the normal and low speed settings. Meanwhile, a consistent trend in the hemolysis outcomes was observed with slightly elevated hemolysis in no and high pulsatility conditions of both speed settings. Conclusion: Hemocompatibility of the HM3 is not significantly affected by periodic high/low flow or backflows through the pump in in-vitro evaluation but rather by the pump operating condition: flow rate and pump speed. © 1964-2012 IEEE.

关键词： Flow rate

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：