资源类型

期刊论文 1082

会议视频 8

年份

2023 77

2022 94

2021 74

2020 75

2019 53

2018 48

2017 53

2016 45

2015 58

2014 53

2013 40

2012 47

2011 38

2010 49

2009 48

2008 40

2007 41

2006 29

2005 28

2004 21

展开 ︾

关键词

数学模型 13

模型试验 9

数值模拟 8

模型 7

COVID-19 5

不确定性 5

GM(1 3

计算机模拟 3

1)模型 2

DX桩 2

D区 2

Preissmann格式 2

SARS 2

TRIZ 2

Weibull分布 2

k-ε模型 2

不确定性评估 2

临震信号 2

云模型 2

展开 ︾

检索范围：

排序： 展示方式：

An integrated approach for machine-learning-based system identification of dynamical systems under control: application towards the model predictive control of a highly nonlinear reactor system

《化学科学与工程前沿（英文）》 2022年 第16卷 第2期   页码 237-250 doi: 10.1007/s11705-021-2058-6

摘要： Advanced model-based control strategies, e.g., model predictive control, can offer superior control of key process variables for multiple-input multiple-output systems. The quality of the system model is critical to controller performance and should adequately describe the process dynamics across its operating range while remaining amenable to fast optimization. This work articulates an integrated system identification procedure for deriving black-box nonlinear continuous-time multiple-input multiple-output system models for nonlinear model predictive control. To showcase this approach, five candidate models for polynomial and interaction features of both output and manipulated variables were trained on simulated data and integrated into a nonlinear model predictive controller for a highly nonlinear continuous stirred tank reactor system. This procedure successfully identified system models that enabled effective control in both servo and regulator problems across wider operating ranges. These controllers also had reasonable per-iteration times of ca. 0.1 s. This demonstration of how such system models could be identified for nonlinear model predictive control without prior knowledge of system dynamics opens further possibilities for direct data-driven methodologies for model-based control which, in the face of process uncertainties or modelling limitations, allow rapid and stable control over wider operating ranges.

关键词： nonlinear model predictive control     black-box modeling     continuous-time system identification     machine learning     industrial applications of process control    

HTML PDF 收藏

时滞系统的辨识及NARMA模型的修正

王冬青

《中国工程科学》 2006年 第8卷 第2期   页码 39-43

摘要：

对现有神经网络对非线性时滞系统的时滞辨识方法进行了补充说明和分析，同时指出现有的NARMA模型修正方法对时滞系统的不当之处。以时滞系统神经网络预测控制为例，介绍了NARMA模型的正确修正方法，仿真证明了所提出的修正方法能获得好的控制性能及抗干扰能力。

关键词： 辨识     NARMA模型     神经网络     预测控制    

HTML PDF 收藏

Identification of pollution sources in rivers using a hydrodynamic diffusion wave model and improved

《环境科学与工程前沿（英文）》 2023年 第17卷 第7期 doi: 10.1007/s11783-023-1685-1

摘要：

● A hydrodynamic-Bayesian inference model was developed for water pollution tracking.

关键词： Identification of pollution sources     Water quality restoration     Bayesian inference     Hydrodynamic model     Inverse problem    

HTML PDF 收藏

Blind identification of threshold auto-regressive model for machine fault diagnosis

LI Zhinong, HE Yongyong, CHU Fulei, WU Zhaotong

《机械工程前沿（英文）》 2007年 第2卷 第1期   页码 46-49 doi: 10.1007/s11465-007-0007-9

摘要： A blind identification method was developed for the threshold auto-regressive (TAR) model. The method had good identification accuracy and rapid convergence, especially for higher order systems. The proposed method was then combined with the hidden Markov model (HMM) to determine the auto-regressive (AR) coefficients for each interval used for feature extraction, with the HMM as a classifier. The fault diagnoses during the speed-up and speed-down processes for rotating machinery have been successfully completed. The result of the experiment shows that the proposed method is practical and effective.

关键词： speed-up     classifier     practical     extraction     experiment    

HTML PDF 收藏

Finite element model updating of a large structure using multi-setup stochastic subspace identification

Reza KHADEMI-ZAHEDI, Pouyan ALIMOURI

《结构与土木工程前沿（英文）》 2019年 第13卷 第4期   页码 965-980 doi: 10.1007/s11709-019-0530-x

摘要： In the present contribution, operational modal analysis in conjunction with bees optimization algorithm are utilized to update the finite element model of a solar power plant structure. The physical parameters which required to be updated are uncertain parameters including geometry, material properties and boundary conditions of the aforementioned structure. To determine these uncertain parameters, local and global sensitivity analyses are performed to increase the solution accuracy. An objective function is determined using the sum of the squared errors between the natural frequencies calculated by finite element method and operational modal analysis, which is optimized using bees optimization algorithm. The natural frequencies of the solar power plant structure are estimated by multi-setup stochastic subspace identification method which is considered as a strong and efficient method in operational modal analysis. The proposed algorithm is efficiently implemented on the solar power plant structure located in Shahid Chamran university of Ahvaz, Iran, to update parameters of its finite element model. Moreover, computed natural frequencies by numerical method are compared with those of the operational modal analysis. The results indicate that, bees optimization algorithm leads accurate results with fast convergence.

关键词： operational modal analysis     solar power plant structure     multi-setup stochastic subspace     bees optimization algorithm     sensitivity analysis    

HTML PDF 收藏

Kinematic Model Building and Servo Parameter Identification of 3-HSS Parallel Mechanism

YANG Zhi-yong, WU Jiang, HUANG Tian, NI Yan-bing

《机械工程前沿（英文）》 2006年 第1卷 第1期   页码 60-66 doi: 10.1007/s11465-005-0019-2

摘要：

Aiming at a parallel mechanism with three degrees of freedom, a method for dynamic model building and the parameter identification of its servosystem is presented. First, the reverse solution models of position, velocity, and acceleration of parallelogram branch structure are deduced, and then, its dynamic model of a rigid body is set up by using the virtual work principle. Based on the above model, a method to identify the servo parameter of the parallel mechanism is put up. In this method, the triangle-shaped input with variable frequency is adopted to offset the disadvantages of pseudorandom number sequence in parameter identification, such as dramatically changing the vibration amplitude of the motor, easily impacting the motor that results in its velocity loop to easily open, and so on. Moreover, the rotary inertia can also be identified by the additive mass. The abovementioned data will lay a solid foundation for the optimum performance of the system in the whole workspace.

关键词： building     acceleration     additive     workspace     optimum performance    

HTML PDF 收藏

The study of hybrid model identification, computation analysis and fault location for nonlinear dynamic

XIE Hong, HE Yi-gang, ZENG Guan-da

《机械工程前沿（英文）》 2006年 第1卷 第2期   页码 233-237 doi: 10.1007/s11465-006-0003-5

摘要： This paper presents the hybrid model identification for a class of nonlinear circuits and systems via a combination of the block-pulse function transform with the Volterra series. After discussing the method to establish the hybrid model and introducing the hybrid model identification, a set of relative formulas are derived for calculating the hybrid model and computing the Volterra series solution of nonlinear dynamic circuits and systems. In order to significantly reduce the computation cost for fault location, the paper presents a new fault diagnosis method based on multiple preset models that can be realized online. An example of identification simulation and fault diagnosis are given. Results show that the method has high accuracy and efficiency for fault location of nonlinear dynamic circuits and systems.

关键词： block-pulse function     nonlinear     multiple     diagnosis     combination    

HTML PDF 收藏

State identification of home appliance with transient features in residential buildings

《能源前沿（英文）》 2022年 第16卷 第1期   页码 130-143 doi: 10.1007/s11708-022-0822-z

摘要： Nonintrusive load monitoring (NILM) is crucial for extracting patterns of electricity consumption of household appliance that can guide users’ behavior in using electricity while their privacy is respected. This study proposes an online method based on the transient behavior of individual appliances as well as system steady-state characteristics to estimate the operating states of the appliances. It determines the number of states for each appliance using the density-based spatial clustering of applications with noise (DBSCAN) method and models the transition relationship among different states. The states of the working appliances are identified from aggregated power signals using the Kalman filtering method in the factorial hidden Markov model (FHMM). Thereafter, the identified states are confirmed by the verification of system states, which are the combination of the working states of individual appliances. The verification step involves comparing the total measured power consumption with the total estimated power consumption. The use of transient features can achieve fast state inference and it is suitable for online load disaggregation. The proposed method was tested on a high-resolution data set such as Labeled hIgh-Frequency daTaset for Electricity Disaggregation (LIFTED) and it outperformed other related methods in the literature.

关键词： nonintrusive load monitoring (NILM)     load disaggregation     online load disaggregation     Kalman filtering     factorial hidden Markov model (FHMM)     Labeled hIgh-Frequency daTaset for Electricity Disaggregation (LIFTED)    

HTML PDF 收藏

Identification of structural parameters and boundary conditions using a minimum number of measurement

Ali KARIMPOUR, Salam RAHMATALLA

《结构与土木工程前沿（英文）》 2020年 第14卷 第6期   页码 1331-1348 doi: 10.1007/s11709-020-0686-4

摘要： This article proposes a novel methodology that uses mathematical and numerical models of a structure to build a data set and determine crucial nodes that possess the highest sensitivity. Regression surfaces between the structural parameters and structural output features, represented by the natural frequencies of the structure and local transmissibility, are built using the numerical data set. A description of a possible experimental application is provided, where sensors are mounted at crucial nodes, and the natural frequencies and local transmissibility at each natural frequency are determined from the power spectral density and the power spectral density ratios of the sensor responses, respectively. An inverse iterative process is then applied to identify the structural parameters by matching the experimental features with the available parameters in the myriad numerical data set. Three examples are presented to demonstrate the feasibility and efficacy of the proposed methodology. The results reveal that the method was able to accurately identify the boundary coefficients and physical parameters of the Euler-Bernoulli beam as well as a highway bridge model with elastic foundations using only two measurement points. It is expected that the proposed method will have practical applications in the identification and analysis of restored structural systems with unknown parameters and boundary coefficients.

关键词： structural model validation     eigenvalue problem     response surface     inverse problems    

HTML PDF 收藏

基于实测时间序列的非线性系统恢复力识别

许斌,贺佳

《中国工程科学》 2011年 第13卷 第9期   页码 76-82

摘要：

提出一种完全基于激励和结构响应实测数据的结构动力系统非线性恢复力识别方法，并通过在一个4层钢结构模型中引入具有非线性特性的磁流变阻尼器（MR）模拟非线性恢复力，基于此模型结构在不同的激励方式下的动力响应测量数据，验证了该方法的有效性。对于结构的各自由度均受到激励的情况，运用最小二乘拟合算法识别出等效线性系统的物理参数（质量、刚度和阻尼矩阵），进而得到模型结构振动过程中MR阻尼力随时间变化情况并与实验实测结果进行了比较。针对结构仅在有限自由度上受到激励的情况，对以上方法进行了改进，提出了一种非线性系统恢复力的非参数化识别方法，利用结构中弹性恢复力的对称关系，分步确定了结构各层间恢复力模型，从而得到MR恢复力的大小并与实测结果进行了比较。结果表明，基于时域实测信号的非线性系统恢复力识别法在完整激励和非完整激励下均能有效地识别结构的非线性恢复力特性。文章所述方法可以运用于工程结构在动力荷载作用下的损伤发生发展过程的监测与识别。

关键词： 非线性恢复力     磁流变阻尼器     最小二乘拟合     等效线性系统     非参数化模型    

HTML PDF 收藏

多目标自适应优化模型预测控制——降低氧化锌回转窑的碳排放 Article

Ke Wei, Keke Huang, Chunhua Yang, Weihua Gui

《工程（英文）》 2023年 第27卷 第8期   页码 96-105 doi: 10.1016/j.eng.2023.01.017

摘要：

The zinc oxide rotary kiln, as an essential piece of equipment in the zinc smelting industrial process, is presenting new challenges in process control. China's strategy of achieving a carbon peak and carbon neutrality is putting new demands on the industry, including green production and the use of fewer resources; thus, traditional stability control is no longer suitable for multi-objective control tasks. Although researchers have revealed the principle of the rotary kiln and set up computational fluid dynamics (CFD) simulation models to study its dynamics, these models cannot be directly applied to process control due to their high computational complexity. To address these issues, this paper proposes a multi-objective adaptive optimization model predictive control (MAO-MPC) method based on sparse identification. More specifically, with a large amount of data collected from a CFD model, a sparse regression problem is first formulated and solved to obtain a reduction model. Then, a two-layered control framework including real-time optimization (RTO) and model predictive control (MPC) is designed. In the RTO layer, an optimization problem with the goal of achieving optimal operation performance and the lowest possible resource consumption is set up. By solving the optimization problem in real time, a suitable setting value is sent to the MPC layer to ensure that the zinc oxide rotary kiln always functions in an optimal state. Our experiments show the strength and reliability of the proposed method, which reduces the usage of coal while maintaining high profits. 

关键词： Zinc oxide rotary kiln     Model reduction     Sparse identification     Real-time optimization     Model predictive control     Process control    

HTML PDF 收藏

Identification of cancer stem cells provides novel tumor models for drug discovery

null

《医学前沿（英文）》 2012年 第6卷 第2期   页码 112-121 doi: 10.1007/s11684-012-0199-1

摘要：

Cancer stem cells (CSCs) have received considerable attention from the research community since they were first reported in human acute myeloid leukemia 15 years ago. Accumulating evidence suggests that CSCs are responsible for tumor initiation and progression, drug resistance, and metastasis in both liquid and solid tumors. These findings lead to the development of novel compounds targeting CSC populations that is becoming increasingly important for eradicating CSCs in heterogeneous tumor masses and to cure the cancer. Since 2003, we have participated in CSC studies and encountered crucial early events in the field. This article reviews the history of CSC biology, clarifies the term and its definition, and further addresses the issue of how to utilize CSCs in therapeutic target discovery and drug development based on our substantial experience.

关键词： cancer stem cell     tumor model     drug discovery    

HTML PDF 收藏

Variable stiffness and damping magnetorheological isolator

Yang ZHOU, Xingyu WANG, Xianzhou ZHANG, Weihua LI

《机械工程前沿（英文）》 2009年 第4卷 第3期   页码 310-315 doi: 10.1007/s11465-009-0039-4

摘要： This paper presents the development and characterization of a magnetorheological (MR) fluid-based variable stiffness and damping isolator. The prototype of the MR fluid isolator is fabricated, and its dynamic behavior is measured under various applied magnetic fields. The parameters of the model under various magnetic fields are identified, and the dynamic performance of the isolator is evaluated in simulation. Experimental results indicate that both the stiffness and damping capability of the developed MR isolator can be controlled by an external magnetic field.

关键词： magnetorheological (MR) fluid     stiffness     damping     mathematical model     dynamic performance     parameter identification    

HTML PDF 收藏

General expression for linear and nonlinear time series models

Ren HUANG, Feiyun XU, Ruwen CHEN

《机械工程前沿（英文）》 2009年 第4卷 第1期   页码 15-24 doi: 10.1007/s11465-009-0015-z

摘要： The typical time series models such as ARMA, AR, and MA are founded on the normality and stationarity of a system and expressed by a linear difference equation; therefore, they are strictly limited to the linear system. However, some nonlinear factors are within the practical system; thus, it is difficult to fit the model for real systems with the above models. This paper proposes a general expression for linear and nonlinear auto-regressive time series models (GNAR). With the gradient optimization method and modified AIC information criteria integrated with the prediction error, the parameter estimation and order determination are achieved. The model simulation and experiments show that the GNAR model can accurately approximate to the dynamic characteristics of the most nonlinear models applied in academics and engineering. The modeling and prediction accuracy of the GNAR model is superior to the classical time series models. The proposed GNAR model is flexible and effective.

关键词： linear and nonlinear     autoregressive model     system identification     time series analysis    

HTML PDF 收藏

Ambient vibration testing and updating of the finite element model of a simply supported beam bridge

Ivan Gomez ARAUJO, Esperanza MALDONADO, Gustavo Chio CHO

《结构与土木工程前沿（英文）》 2011年 第5卷 第3期   页码 344-354 doi: 10.1007/s11709-011-0124-8

摘要： An ambient vibration test on a concrete bridge constructed in 1971 and calibration of its finite element model are presented. The bridge is characterized by a system of post-tensioned and simply supported beams. The dynamic characteristics of the bridge, i.e. natural frequencies, mode shapes and damping ratios were computed from the ambient vibration tests by using the Eigensystem Realization Algorithm (ERA). Then, these characteristics were used to update the finite element model of the bridge by formulating an optimization problem and then using Genetic Algorithms (GA) to solve it. From the results of the ambient vibration test of this type of bridge, it is concluded that two-dimensional mode shapes exist: in the longitudinal and transverse; and these experimentally obtained dynamic characteristics were also achieved in the analytical model through updating. The application of GAs as optimization techniques showed great versatility to optimize any number and type of variables in the model.

关键词： modal analysis     parameter identification     ambient vibration test     Eigensystem Realization Algorithm (ERA) method     finite element method    

HTML PDF 收藏

标题 作者 时间 类型 操作

An integrated approach for machine-learning-based system identification of dynamical systems under control: application towards the model predictive control of a highly nonlinear reactor system

期刊论文

时滞系统的辨识及NARMA模型的修正

王冬青

期刊论文

Identification of pollution sources in rivers using a hydrodynamic diffusion wave model and improved

期刊论文

Blind identification of threshold auto-regressive model for machine fault diagnosis

LI Zhinong, HE Yongyong, CHU Fulei, WU Zhaotong

期刊论文

Finite element model updating of a large structure using multi-setup stochastic subspace identification

Reza KHADEMI-ZAHEDI, Pouyan ALIMOURI

期刊论文

Kinematic Model Building and Servo Parameter Identification of 3-HSS Parallel Mechanism

YANG Zhi-yong, WU Jiang, HUANG Tian, NI Yan-bing

期刊论文

The study of hybrid model identification, computation analysis and fault location for nonlinear dynamic

XIE Hong, HE Yi-gang, ZENG Guan-da

期刊论文

State identification of home appliance with transient features in residential buildings

期刊论文

Identification of structural parameters and boundary conditions using a minimum number of measurement

Ali KARIMPOUR, Salam RAHMATALLA

期刊论文

基于实测时间序列的非线性系统恢复力识别

许斌,贺佳

期刊论文

多目标自适应优化模型预测控制——降低氧化锌回转窑的碳排放

Ke Wei, Keke Huang, Chunhua Yang, Weihua Gui

期刊论文

Identification of cancer stem cells provides novel tumor models for drug discovery

null

期刊论文

Variable stiffness and damping magnetorheological isolator

Yang ZHOU, Xingyu WANG, Xianzhou ZHANG, Weihua LI

期刊论文

General expression for linear and nonlinear time series models

Ren HUANG, Feiyun XU, Ruwen CHEN

期刊论文

Ambient vibration testing and updating of the finite element model of a simply supported beam bridge

Ivan Gomez ARAUJO, Esperanza MALDONADO, Gustavo Chio CHO

期刊论文