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A data-based inverse problem-solving method for predicting structural orderings

Frontiers of Structural and Civil Engineering 2025年第1期19卷 22-33页

作者： Yiwen LI Jianlong CHEN Guangyan LIU Zhanli LIU Kai ZHANG School of Aerospace Engineering Beijing Institute of TechnologyBeijing 100081China Applied Mechanics Laboratory Department of Engineering MechanicsSchool of AerospaceTsinghua UniversityBeijing 100084China Tangshan Research Institute Beijing Institute of TechnologyTangshan 063000China

Inverse problem-solving methods have found applications in various fields,such as structural mechanics,acoustics,and non-destructive ***,accurately solving inverse problems becomes challenging when observed data are ***,advancements in computer science have paved the way for data-based methods,enabling the discovery of nonlinear relationships within diverse data *** this paper,a step-by-step completion method of displacement information is introduced and a data-driven approach for predicting structural parameters is *** accuracy of the proposed approach is 23.83%higher than that of the Genetic Algorithm,demonstrating the outstanding accuracy and efficiency of the data-driven *** work establishes a framework for solving mechanical inverse problems by leveraging a data-based method,and proposes a promising avenue for extending the application of the data-driven approach to structural health monitoring.

关键词： mechanical inverse problem displacement information completion digital structural orderings data-based method genetic algorithm

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data-based analysis of discrete-time linear systems in noisy environment: Controllability and observability

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INFORMATION SCIENCES 2014年第1期288卷 314-329页

作者： Liu, Derong Yan, Pengfei Wei, Qinglai Chinese Acad Sci Inst Automat State Key Lab Management & Control Complex Syst Beijing 100190 Peoples R China

In this paper, a data-based method is developed for analyzing the controllability and observability of discrete-time linear systems in noisy environment. This method uses measured data to estimate the controllability matrix and the observability matrix without identifying system models. The unbiasedness and consistency of this estimate with measurement noise and system noise are proven, respectively. As the estimated error of system parameters will not accumulate in calculating the controllability matrix and observability matrix, this method has a higher precision than traditional methods, especially in high-dimensional state space. In the simulation, the advantages of the data-based method in accuracy and convergence are illustrated. (C) 2014 Elsevier Inc. All rights reserved.

关键词： Controllability Observability Discrete-time linear system data-based method Noisy environment

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data-based controllability analysis of discrete-time linear time-delay systems

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INTERNATIONAL JOURNAL OF SYSTEMS SCIENCE 2014年第11期45卷 2411-2417页

作者： Liu, Yang Chen, Hong-Wei Lu, Jian-Quan Zhejiang Normal Univ Dept Math Jinhua 321004 Peoples R China Southeast Univ Dept Math Nanjing 210096 Jiangsu Peoples R China

In this paper, a data-based method is used to analyse the controllability of discrete-time linear time-delay systems. By this method, one can directly construct a controllability matrix using the measured state data without identifying system parameters. Hence, one can save time in practice and avoid corresponding identification errors. Moreover, its calculation precision is higher than some other traditional approaches, which need to identify unknown parameters. Our methods are feasible to the study of characteristics of deterministic systems. A numerical example is given to show the advantage of our results.

关键词： controllability time-delay linear discrete-time system data-based method

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The influence of frequency content on the performance of artificial neural network-based damage detection systems tested on numerical and experimental bridge data

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STRUCTURAL HEALTH MONITORING-AN INTERNATIONAL JOURNAL 2021年第3期20卷 1331-1347页

作者： Neves, Ana C. Gonzalez, Ignacio Karoumi, Raid Leander, John KTH Royal Inst Technol Div Struct Engn & Bridges Brinellvagen 23 S-10044 Stockholm Sweden

The method herein proposed provides a novel perspective about data processing within structural health monitoring, which is essential for automated real-time monitoring and assessment of civil engineering structures. The low- and high-frequency contents of the forced vibration response of a structure are used to train and test artificial neural networks for the purpose of damage detection. In the context of several damage scenarios, the different versions of the networks are compared with each other with the aim of verifying which are the most efficient regarding novelty detection (one-class classification). The data related with the high-frequency response showed to contain more useful information for the proposed damage detection algorithm, when compared with the low-frequency response data (typically modal). In view of that, high frequencies should be given more attention in future research about their application in connection with structural health monitoring systems.

关键词： Structural health monitoring artificial neural networks damage detection data-based method high-frequency response analysis

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data-based short-term prognostics for proton exchange membrane fuel cells

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INTERNATIONAL JOURNAL OF HYDROGEN ENERGY 2017年第32期42卷 20791-20808页

作者： Liu, Hao Chen, Jian Hou, Ming Shao, Zhigang Su, Hongye Zhejiang Univ Coll Control Sci & Engn State Key Lab Ind Control Technol Hangzhou 310027 Zhejiang Peoples R China Chinese Acad Sci Dalian Inst Chem Phys Fuel Cell Syst & Engn Lab 457 Zhongshan Rd Dalian 116023 Peoples R China

Prognostics is an important tool in the life and cost management of the proton exchange membrane fuel cells (PEMFCs). In this paper, we propose a data-based short-term prognostics method based on the group method of data handling and the wavelet analysis. In particular, this method first decomposes the original voltage sequence of PEMFCs into multiple sub-waveforms. Then, prognostics are made for the sub-waveforms and are combined for the overall prognostics of PEMFCs. Moreover, the proposed method is validated by the experimental datasets from real aging tests. Simulation results demonstrate that, compared with the existing approaches, this proposed method not only can achieve accurate short-term prognostics for PEMFCs in different load conditions, but also can directly use the original experimental data with large disturbances. (c) 2017 Hydrogen Energy Publications LLC. Published by Elsevier Ltd. All rights reserved.

关键词： Prognostics data-based method Group method of data handling Wavelet analysis Proton exchange membrane fuel cells

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Prediction of Axial DNBR Distribution in a Hot Fuel Rod Using Support Vector Regression Models

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IEEE TRANSACTIONS ON NUCLEAR SCIENCE 2011年第4期58卷 2084-2090页

作者： Kim, Dong Su Lee, Sim Won Na, Man Gyun Chosun Univ Dept Nucl Engn Kwangju 501759 South Korea

The departure from nucleate boiling ratio (DNBR) is one of the most critical parameters in the safety issues of a nuclear reactor. Most reactor core protection systems of current nuclear power plants calculate the minimum DNBR at a pseudo hot fuel rod position to prevent the departure from nucleate boiling (DNB). On the other hand, it gives rise to a more conservative result, which reduces the operating margin of nuclear power plants. In this paper, the axial DNBR distribution at the actual hot fuel rod position was predicted based on the support vector regression (SVR) model, which is a data-based method using a number of measured signals from the reactor coolant system. SVR models were developed using a learning data set and validated by an independent test data set. These models were applied to the first fuel cycle of the Yonggwang unit 3 nuclear power plant. The root mean square (RMS) error averaged for 13 axial locations of the hot rod was 0.87%. The SVR models estimate DNBR values more accurately at central parts that have relatively lower DNBR values, which are more important in terms of safety. This algorithm can predict the DNBR accurately at each time step and provide reliable protection and monitoring information for nuclear power plant (NPP) operation.

关键词： Critical heat flux data-based method departure from nucleate boiling ratio (DNBR) hot fuel rod support vector regression (SVR)

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data-based controllability analysis for generalised linear discrete-time system

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INTERNATIONAL JOURNAL OF SYSTEMS SCIENCE 2017年第10期48卷 2104-2110页

作者： Wang, Fengjun Zhang, Qingling Liu, Wanquan Northeastern Univ Inst Syst Sci Shenyang Peoples R China Northeastern Univ State Key Lab Synthet Automat Proc Ind Shenyang Peoples R China Curtin Univ Dept Comp Perth WA Australia

In this paper, we aim to propose a data-based method to testify whether the system is a normal linear system or a generalised linear system and then analyse its controllability via the measured state data and the control input satisfying certain condition. For this purpose, we first describe a linear discrete-time system in a general form and derive a necessary and sufficient condition for the equivalent condition of complete controllability with a normal linear discrete time system. Second, we check whether the system is normal or singular, and then construct the controllability matrices only based on the input and measured state data. Third, the controllability of the corresponding system is investigated thoroughly based on available data without identifying system parameters. Finally, a numerical example and a stock price example are used to show the effectiveness and feasibility of the proposed data-based method.

关键词： data-based method linear discrete-time system generalised system unknown parameters controllability analysis

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data-based cascade control of permanent magnet synchronous motor with industrial robot application

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JOURNAL OF ENGINEERING-JOE 2018年第17期2018卷 1930-1934页

作者： Xie, Yuanlong Tang, Xiaoqi Song, Bao Tao, Jieyu Li, Hu Ye, Bosheng Huazhong Univ Sci & Technol Natl NC Syst Engn Res Ctr Sch Mech Sci & Engn State Key Lab Digital Mfg Equipment & Technol Luoyu Rd 1037 Wuhan 430074 Hubei Peoples R China

The industrial robot is typically actuated by a permanent magnet synchronous motor (PMSM). In manufacturing applications, the position control performance of the PMSM actuation systems will directly affect the efficiency and precision of the industrial robot. This study proposes a cascade control method to achieve accurate position profile-tracking for a field-bus industrial robot. The proposed method is a data-based method, which implies that only process data is directly used for the controller design without system model information. The cascade position controller optimisation problem is formulated using the collected data from the plant to be controlled. Then, a multiple degrees-of-freedom solution is designed to obtain the optimal control parameters for all actuation PMSM systems. The effectiveness and robustness of the proposed method are demonstrated using an experimental example implemented on the developed field-bus industrial robot.

关键词： robust control optimal control cascade control industrial robots position control machine control permanent magnet motors synchronous motors control system synthesis developed field-bus industrial robot actuation PMSM systems optimal control parameters collected data cascade position controller optimisation problem system model information controller design process data data-based method accurate position profile-tracking cascade control method PMSM actuation systems position control performance manufacturing applications industrial robot application permanent magnet synchronous motor data-based cascade control

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Vibration-based multi-site damage precise localization via the Functional Model based method

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Procedia Engineering 2017年 199卷 2072-2077页

作者： C.S. Sakaris J.S. Sakellariou S.D. Fassois Stochastic Mechanical Systems & Automation (SMSA) Laboratory Department of Mechanical & Aeronautical Engineering University of Patras GR 26504 Patras Greece http://www.smsa.upatras.gr

The problem of multi-site damage precise localization, that is multi-site damage coordinate estimation is addressed via the random vibration based stochastic Functional Model based method (FMBM). Damage detection and precise localization for pairs of damage locations on the wing of a lab-scale Garteur skeleton structure is achieved based on the vibration response measured via a single accelerometer at a low and limited operational frequency bandwidth. The results of the study indicate excellent damage detection and remarkable localization of the considered multi-site damage scenarios.

关键词： Multi-site damage damage precise localization data-based method vibration-based SHM statistical methods statistical time series methods

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A RLS Run-to-Run Control Approach for Semiconductor Manufacturing Process

A RLS Run-to-Run Control Approach for Semiconductor Manufact...

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10th World Congress on Intelligent Control and Automation (WCICA)

作者： Liu, Shujie Zheng, Ying Luo, Ming Wang, Yanwei Univ Huazhong Sci&Technol Dept Control Sci&Engn Wuhan Hubei Peoples R China Univ Huazhong Sci&Technol CAD Ctr Wuhan Hubei Peoples R China

ISBN: (纸本)9781467313988

Exponentially weighted moving average (EWMA) is a commonly used model-based algorithm for semiconductor manufacturing process Run-to-Run (R2R) control. However, it's very difficult to set up the mathematical modeling for the actual semiconductor manufacturing process. Therefore, data-based methods such as Recursive Least Squares(RLS) have received wide attention nowadays. This paper proposes a variable forgetting factor RLS R2R control approach for semiconductor manufacturing process with and without drift disturbance. The variable forgetting factor resolves the drift disturbance well, and this method is much superior to generic RLS algorithm in convergence speed and tracking effect. It has both a strong ability to track parameters, and a small convergence estimate error. Simulation results prove the feasibility and accuracy of the algorithm.

关键词： Run-to-Run control data-based method RLS variable forgetting factor drift disturbance

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