检索结果-内蒙古大学图书馆

Understanding Mass Transfer Directions via data-driven Models with Application to Mobile Phone data

SIAM JOURNAL ON APPLIED DYNAMICAL SYSTEMS 2020年第2期19卷 1372-1391页

作者： Alla, Alessandro Balzotti, Caterina Briani, Maya Cristiani, Emiliano Pontificia Univ Catolica Rio de Janeiro Dept Matemat BR-22451900 Rio de Janeiro Brazil Sapienza Univ Roma Dipartimento Sci Base & Applicate Ingn Rome Italy CNR Ist Applicaz Calcolo M Picone Rome Italy

The aim of this paper is to solve an inverse problem which regards a mass moving in a bounded domain. We assume that the mass moves following an unknown velocity field and that the evolution of the mass density can be described by a partial differential equation, which is also unknown. The input data of the problems are given by some snapshots of the mass distribution at certain times, while the sought output is the velocity field that drives the mass along its displacement. To this aim, we put in place an algorithm based on the combination of two methods: first, we use the dynamic mode decomposition to create a mathematical model describing the mass transfer;second, we use the notion of Wasserstein distance (also known as earth mover's distance) to reconstruct the underlying velocity field that is responsible for the displacement. Finally, we consider a real-life application: the algorithm is employed to study the travel flows of people in large populated areas using, as input data, density profiles (i.e., the spatial distribution) of people in given areas at different time instants. These kinds of data are provided by the Italian telecommunication company TIM and are derived by mobile phone usage.

关键词： data-driven methods dynamic mode decomposition Wasserstein distance earth mover's distance cellular data presence data

来源：评论

学校读者我要写书评

暂无评论

A Two-Stage data-driven Approach for Image-Based Wind Turbine Blade Crack Inspections

引用

IEEE-ASME TRANSACTIONS ON MECHATRONICS 2019年第3期24卷 1271-1281页

作者： Wang, Long Zhang, Zijun Luo, Xiong Univ Sci & Technol Beijing Sch Comp & Commun Engn Beijing 100083 Peoples R China City Univ Hong Kong Sch Data Sci Kowloon Hong Kong Peoples R China

A two-stage approach for precisely detecting wind turbine blade surface cracks via analyzing blade images captured by unmanned aerial vehicles (UAVs) is proposed in this paper. The proposed approach includes two main detection procedures, the crack location and crack contour detection. In locating cracks, a method for extracting crack windows based on extended Haar-like features is introduced. A parallel sliding window method is developed to scan images and the cascading classifier is developed to classify sliding windows into two classes, crack and noncrack. Based on detected windows containing cracks, a novel clustering algorithm, the parallel Jaya K-means algorithm, is developed to assign each pixel in crack windows into crack and noncrack segments. Crack contours are obtained based on boundaries of crack segments. The effectiveness and efficiency of the proposed crack detection approach are validated by executing it on a personal computer and an embedded device with UAV-taken images collected from a commercial wind farm. Computational results demonstrate that the proposed approach can successfully identify both the blade crack locations and crack contours in UAV taken images.

关键词： Blade crack detection condition monitoring data-driven methods wind energy Jaya K-means

来源：评论

学校读者我要写书评

暂无评论

data-driven digital twin technology for optimized control in process systems

引用

ISA TRANSACTIONS 2019年 95卷 221-234页

作者： He, Rui Chen, Guoming Dong, Che Sun, Shufeng Shen, Xiaoyu China Univ Petr East China COEST 66 Changjiang West Rd Qingdao Shandong Peoples R China

Due to the installation of various apparatus in process industries, both factors of complex structures and severe operating conditions could result in higher accident frequencies and maintenance challenges. Given the importance of security in process systems, this paper presents a data-driven digital twin system for automatic process applications by integrating virtual modeling, process monitoring, diagnosis, and optimized control into a cooperative architecture. For unknown model parameters, the adaptive system identification is proposed to model closed-loop virtual systems and residual signals with fault-free case data. Performance indices are improved to make the design of robust monitoring and diagnosis system to identify the apparatus status. Soft-sensor, parameterization control, and model-matching reconfiguration are ameliorated and incorporated into the optimized control configuration to guarantee stable and safe control performance under apparatus faults. The effectiveness and performance of the proposed digital twin system are evaluated by using different simulations on the Tennessee Eastman benchmark process in the presence of realistic fault scenarios. (C) 2019 ISA. Published by Elsevier Ltd. All rights reserved.

关键词： data-driven methods Digital twin Process monitoring and diagnosis Optimized control configuration Tennessee Eastman process

来源：评论

学校读者我要写书评

暂无评论

Detection and Localization of Coordinated State-and-Topology False data Injection Attack by Multi-modal Learning

引用

JOURNAL OF ELECTRICAL ENGINEERING & TECHNOLOGY 2022年第5期17卷 2649-2662页

作者： Qin, Zhijun Lai, Yu Guangxi Univ Coll Elect Engn 100 Daxue Rd Nanning 540003 Guangxi Peoples R China

False data injection attack (FDIA) is a typical cyber-attack targeting on power system state estimation. By inserting bias into the power system meter measurements, FDIA can cause errors in state estimation and consequently mislead power system operation. Recently, the coordinated state-and-topology FDIA was developed to falsify both the meter measurements and the topology information to conceal a cyber or physical attack. Conventional machine-learning-based detection methods against FDIA depend on the complete observability of power system topology, therefore cannot detect the coordinated state-and-topology FDIA. To address this challenge, we propose a multi-modal learning model based on Graph Auto-Encoder (GAE) and Residual Neural Networks (ResNet) to detect this type of FDIA. First, GAE is used to learn the compact representation of power system topologies. Then, the obtained topological representation is fused with the measurement to obtain the multi-modal features. Third, ResNet is trained as a multi-label classifier to accept the fused features and generate an array, which can detect attack scenarios and identify the falsified measurements/topologies by coordinated attacks. Comprehensive case studies using IEEE 9-bus, IEEE 57-bus, and IEEE 118-bus systems are presented. The simulation results show that, as compared to single feature methods, the proposed method is more effective in detecting coordinated state-and-topology attacks, and more robust in case of FDIA under unseen topological changes in power system operation.

关键词： Power system cyber security False data injection attack Topology attack Multi-modal learning data-driven methods

来源：评论

学校读者我要写书评

暂无评论

Probabilistic modelling of seasonal energy demand patterns in the transition from natural gas to hydrogen for an urban energy district

引用

INTERNATIONAL JOURNAL OF HYDROGEN ENERGY 2024年第PartD期51卷 398-411页

作者： Manfren, Massimiliano Gonzalez-Carreon, Karla M. Bahaj, AbuBakr S. Univ Southampton Energy & Climate Change Div Sustainable Energy Res Grp Sch Engn Boldrewood Campus Southampton SO16 7QF England

The transition to a low-carbon energy system can be depicted as a "great reconfiguration" from a socio-technical perspective that carries the risk of impact shifts. Electrification with the objective of achieving rapidly deep decarbonisation must be accompanied by effective efficiency and flexibility measures. Hydrogen can be a preferred option in the decarbonisation process where electrification of end-uses is difficult or impractical as well as for long-term storage in energy infrastructure characterised by a large penetration of renewable energy sources. Notwithstanding the current uncertainties regarding costs, environmental impact and the inherent difficulties of increasing rapidly supply capacity, hydrogen can represent a solution to be used in multi-energy systems with combined heat and power (CHP), in particular in urban energy districts. In fact, while achieving carbon savings with natural gas fuelled CHP is not possible when low grid carbon intensity factors are present, it may still be possible to use it to provide flexibility services and to reduce emissions further with switch from natural gas to hydrogen. In this paper, a commercially established urban district energy scheme located in Southampton (United Kingdom) is analysed with the goal of exploring potential variations in its energy demand. The study proposes the use of scalable data-driven methods and probabilistic simulation to generate seasonal energy demand patterns representing the potential short-term and long-term evolution of the energy district. (c) 2023 The Authors. Published by Elsevier Ltd on behalf of Hydrogen Energy Publications LLC. This is an open access article under the CC BY license (http://***/ licenses/by/4.0/).

关键词： Energy transition Hydrogen Urban energy modelling data-driven methods Regression-based approaches Probabilistic modelling

来源：评论

学校读者我要写书评

暂无评论

Probabilistic Color-by-Numbers: Suggesting Pattern Colorizations Using Factor Graphs

引用

ACM TRANSACTIONS ON GRAPHICS 2013年第4期32卷 p37-37:12页

作者： Lin, Sharon Ritchie, Daniel Fisher, Matthew Hanrahan, Pat Stanford Univ Stanford CA 94305 USA

We present a probabilistic factor graph model for automatically coloring 2D patterns. The model is trained on example patterns to statistically capture their stylistic properties. It incorporates terms for enforcing both color compatibility and spatial arrangements of colors that are consistent with the training examples. Using Markov Chain Monte Carlo, the model can be sampled to generate a diverse set of new colorings for a target pattern. This general probabilistic framework allows users to guide the generated suggestions via conditional inference or additional soft constraints. We demonstrate results on a variety of coloring tasks, and we evaluate the model through a perceptual study in which participants judged sampled colorings to be significantly preferable to other automatic baselines.

关键词： Probabilistic modeling factor graphs colorization graphic design data-driven methods Markov Chain Monte Carlo

来源：评论

学校读者我要写书评

暂无评论

Real-Time Implementation of Plug-and-Play Process Monitoring and Control on an Experimental Three-Tank System

引用

IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS 2021年第9期17卷 6448-6456页

作者： Huo, Mingyi Luo, Hao Wang, Xuejiao Yang, Zhengkun Kaynak, Okyay Harbin Inst Technol Dept Control Sci & Engn Harbin 150001 Peoples R China Univ Sci & Technol Beijing Beijing 100083 Peoples R China Bogazici Univ TR-34342 Istanbul Turkey

Three-tank system is an important benchmark in industrial process. However, so far, the research on the three-tank system is mainly limited to simulation studies, and the use of virtual simulators. In this article, a real-time three-tank system setup is used for practical investigations. Differing with the virtual simulator of a three-tank system, the setup can enable the setting of different types of faults (such as cloggings and leaks in the system, sensor faults, and actuator faults) through manual manipulation, users can choose the combinations of different valves and knobs in the setup, which is helpful to evaluate and compare methods for process monitoring and control. The relevant codes or modules can be applied directly that are developed in the MATLAB/Simulink environment. On this setup, two methods are used to verify the effectiveness in this study. One method is to solve the problem of process monitoring and fault detection;due to the fluctuation of the liquid level caused by flow, the input/output (I/O) data are preferred to be decomposed to different subspaces, which aims to identify the data-driven stable kernel representation. Moreover, the original controller of the three-tank system cannot match the system accurately, and therefore, needs to be modified. To solve the problem, a plug-and-play process control method (the other method used in this article) is applied, which adds a stable Youla parameterization matrix on the basis of the original controller. All controllers that internally stabilize the control loop improves the performance of the system without changing the original controller of the three-tank system. The experimental results of the two methods indicate that the proposed approach has strong practicality.

关键词： Real-time systems Matlab Fault detection Liquids Process control Control systems data-driven methods plug-and-play (PnP) process monitoring real-time control

来源：评论

学校读者我要写书评

暂无评论

data-driven Model Reduction and Transfer Operator Approximation

引用

JOURNAL OF NONLINEAR SCIENCE 2018年第3期28卷 985-1010页

作者： Klus, Stefan Nuske, Feliks Koltai, Peter Wu, Hao Kevrekidis, Ioannis Schuette, Christof Noe, Frank Free Univ Berlin Dept Math & Comp Sci Berlin Germany Princeton Univ Dept Chem & Biol Engn Princeton NJ 08544 USA Princeton Univ Program Appl & Computat Math Princeton NJ 08544 USA Zuse Inst Berlin Berlin Germany

In this review paper, we will present different data-driven dimension reduction techniques for dynamical systems that are based on transfer operator theory as well as methods to approximate transfer operators and their eigenvalues, eigenfunctions, and eigenmodes. The goal is to point out similarities and differences between methods developed independently by the dynamical systems, fluid dynamics, and molecular dynamics communities such as time-lagged independent component analysis, dynamic mode decomposition, and their respective generalizations. As a result, extensions and best practices developed for one particular method can be carried over to other related methods.

关键词： Koopman operator Perron-Frobenius operator Model reduction data-driven methods

来源：评论

学校读者我要写书评

暂无评论

data-driven Model Reduction of Monotone Systems by Nonlinear DC Gains

引用

IEEE TRANSACTIONS ON AUTOMATIC CONTROL 2020年第5期65卷 2094-2106页

作者： Kawano, Yu Besselink, Bart Scherpen, Jacquelien M. A. Cao, Ming Hiroshima Univ Grad Sch Engn Higashihiroshima 7398527 Japan Univ Groningen Bernoulli Inst Math Comp Sci & Artificial Intelli NL-9700 AK Groningen Netherlands Univ Groningen Jan C Willems Ctr Syst & Control NL-9700 AK Groningen Netherlands Univ Groningen Fac Sci & Engn NL-9700 AK Groningen Netherlands

In this paper, we develop data-driven model reduction methods for monotone nonlinear control systems based on a nonlinear version of the dc gain. The nonlinear dc gain is a function of the amplitude of the input and can be used to evaluate the importance of each state variable. In fact, the nonlinear dc gain is directly related to the infinity-induced norm of the system as well as a notion of output reachability. Given the dc gain, model reduction is performed by either truncating not-so-important state variables or aggregating state variables having similar importance. Under such truncation and clustering, monotonicity and boundedness of the nonlinear dc gain are preserved;moreover, these two operations can be approximately performed based on simulation or experimental data alone. This empirical model reduction approach is illustrated by an example of a gene regulatory network.

关键词： Reduced order systems Nonlinear systems Mathematical model Linear systems data models Stability analysis Control systems data-driven methods dc gains model reduction monotone systems nonlinear systems

来源：评论

学校读者我要写书评

暂无评论

Tunable linear feedback control of urban drainage systems using models defined purely from data

引用

WATER SCIENCE AND TECHNOLOGY 2024年第11期89卷 3147-3162页

作者： Dantzer, Travis Adrian Kerkez, Branko Univ Michigan Dept Civil & Environm Engn 2350 Hayward St Ann Arbor MI 48109 USA

Real-time and model-predictive control promises to make urban drainage systems (UDS) adaptive, coordinated, and dynamically optimal. Though early implementations are promising, existing control algorithms have drawbacks in computational expense, trust, system-level coordination, and labor cost. Linear feedback control has distinct advantages in computational expense, interpretation, and coordination. However, current methods for building linear feedback controllers require calibrated software models. Here we present an automated method for generating tunable linear feedback controllers that require only system response data. The controller design consists of three main steps: (1) estimating the network connectivity using tools for causal inference, (2) identifying a linear, time-invariant (LTI) dynamical system which approximates the network, and (3) designing and tuning a feedback controller based on the LTI urban drainage system approximation. The flooding safety, erosion prevention, and water treatment performance of the method are evaluated across 190 design storms on a separated sewer model. Strong results suggest that the system knowledge required for generating effective, safe, and tunable controllers for UDS is surprisingly basic. This method allows near-turnkey synthesis of controllers solely from sensor data or reduction of process-based models.

关键词： causal inference data-driven methods gray-box models linear feedback control model discovery real-time control

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：