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Theory analysis and system identification methods on thermal dynamics characteristics of ballscrews

XIA Junyong, HU Youmin, WU Bo, SHI Tielin

《机械工程前沿（英文）》 2008年第3卷第4期页码 408-415 doi: 10.1007/s11465-008-0061-y

摘要： Empirical model of machine tools on thermal error has been widely researched, which can compensate for thermal error to some extent but not suitable for thermal dynamic errors produced by dynamic heat sources. The thermoelastic phenomenon of unidimensional heat transfer of ballscrews influenced by changeable heat sources is analyzed based on the theory of heat transfer. Two methods for system identification (the least square system identification and BP artificial neural network (ANN) system identification) are put forward to establish a dynamic characteristic model of thermal deformation of ballscrews. The model of thermal error of the axis in a feed system of DM4600 vertical miller is established with a fine identification effect. Comparing the results of the two identification methods, the BP ANN system identification is more precise than the least square system identification.

关键词： square system network vertical miller transfer ANN

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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

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Variational mode decomposition based modal parameter identification in civil engineering

Mingjie ZHANG, Fuyou XU

《结构与土木工程前沿（英文）》 2019年第13卷第5期页码 1082-1094 doi: 10.1007/s11709-019-0537-3

摘要： An out-put only modal parameter identification method based on variational mode decomposition (VMD) is developed for civil structure identifications. The recently developed VMD technique is utilized to decompose the free decay response (FDR) of a structure into to modal responses. A novel procedure is developed to calculate the instantaneous modal frequencies and instantaneous modal damping ratios. The proposed identification method can straightforwardly extract the mode shape vectors using the modal responses extracted from the FDRs at all available sensors on the structure. A series of numerical and experimental case studies are conducted to demonstrate the efficiency and highlight the superiority of the proposed method in modal parameter identification using both free vibration and ambient vibration data. The results of the present method are compared with those of the empirical mode decomposition-based method, and the superiorities of the present method are verified. The proposed method is proved to be efficient and accurate in modal parameter identification for both linear and nonlinear civil structures, including structures with closely spaced modes, sudden modal parameter variation, and amplitude-dependent modal parameters, etc.

关键词： modal parameter identification variational mode decomposition civil structure nonlinear system closely spaced modes

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Parameter identification of interconnected power system frequency after trip-out of high voltage transmission

Xuzhan ZHOU,Shanshan LIU,Mingkun WANG,Yiping DAI,Yaohua TANG

《能源前沿（英文）》 2014年第8卷第3期页码 386-393 doi: 10.1007/s11708-014-0323-9

摘要： Accurate modeling and parameters of high voltage (HV) grid are critical for stability research of system frequency. In this paper, simulation modeling of the system frequency was conducted of an interconnected power system with HV transmission lines in China. Based on recorded tripping data of the HV transmission lines, system parameters were identified by using genetic algorithm (GA). The favorable agreement between simulation results and recorded data verifies the validity of gird models and the accuracy of system parameters. The results of this paper can provide reference for the stability research of HV power grid.

关键词： high voltage (HV) grid frequency stability parameter identification primary frequency regulation (PFR)

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Variable identification and automatic tuning of the main module of a servo system of parallel mechanism

YANG Zhiyong, XU Meng, HUANG Tian, NI Yanbing

《机械工程前沿（英文）》 2007年第2卷第1期页码 82-88 doi: 10.1007/s11465-007-0014-x

摘要： The variables of the main module of a servo system for miniature reconfigurable parallel mechanism were identified and automatically tuned. With the reverse solution module of the translation, the module with the exerted translation joint was obtained, which included the location, velocity and acceleration of the parallelogram carriage-branch. The rigid dynamic reverse model was set as the virtual work principle. To identify the variables of the servo system, the triangle-shaped input signal with variable frequency was adopted to overcome the disadvantages of the pseudo-random number sequence, i.e., making the change of the vibration amplitude of the motor dramatically, easily impact the servo motor and make the velocity loop open and so on. Moreover, all the variables including the rotary inertia of the servo system were identified by the additive mass. The overshoot and rise time were the optimum goals, the limited changing load with the attitude was considered, and the range of the controller variables in the servo system was identified. The results of the experiments prove that the method is accurate.

关键词： acceleration reconfigurable parallel additive sequence parallel mechanism

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南水北调中线工程渠道糙率的系统辨识

杨开林,汪易森

《中国工程科学》 2012年第14卷第11期页码 17-23

摘要：

提出了分析调水工程渠道沿程糙率的系统辨识新方法。依据水力学原理，建立了渠道沿程糙率与粗糙高度ks和水力半径R的函数关系，然后通过数学变换提出了适合最小二乘法进行系统辨识的线性模型。并以南水北调中线工程原型观测资料为基础，考虑渠道断面形状、底坡、渠长变化的影响，应用系统辨识的方法消除水力测量随机误差的干扰,得到了通用的渠道沿程糙率计算公式。

关键词：渠道糙率系统辨识最小二乘法

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仅用结构响应数据识别系统模态参数的方法研究

霍兵勇,易伟建

《中国工程科学》 2015年第17卷第1期页码 151-160

摘要：

随着实验模态分析方法的广泛应用和不断发展，在工程应用中，研究者希望能减少限制条件，增加分析的可靠性。本文发展一种识别系统模态参数的新方法，本方法无需知道系统的输入信息且不用建立系统模型，仅通过对测试记录的响应信号进行频谱分析即可识别系统的模态参数，依据系统中各响应点的信号，先采用离散反卷积方法从各响应点信号中分离出谐波参数作为初步的识别结果，在此基础之上，结合频域空间曲线拟合的方法修正识别结果中受频谱混叠影响而偏差较大的谐波参数，再联合这些已提取的谐波参数得到系统的模态参数。通过对实际结构测试数据的分析，证明本方法只用输出数据识别的模态参数与模态分析软件用传递函数识别的结果一致。

关键词：仅有输出响应；系统模态参数识别；空间曲线拟合；频谱混叠

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Identification of thermal error in a feed system based on multi-class LS-SVM

Chao JIN, Bo WU, Youmin HU, Yao CHENG

《机械工程前沿（英文）》 2012年第7卷第1期页码 47-54 doi: 10.1007/s11465-012-0307-6

摘要：

Research of thermal characteristics has been a key issue in the development of high-speed feed system. The thermal positioning error of a ball-screw is one of the most important objects to consider for high-accuracy and high-speed machine tools. The research work undertaken herein ultimately aims at the development of a comprehensive thermal error identification model with high accuracy and robust. Using multi-class least squares support vector machines (LS-SVM), the thermal positioning error of the feed system is identified with the variance and mean square value of the temperatures of supporting bearings and screw-nut as feature vector. A series of experiments were carried out on a self-made quasi high-speed feed system experimental bench HUST-FS-001 to verify the identification capacity of the presented method. The results show that the recommended model can be used to predict the thermal error of a feed system with good accuracy, which is better than the ordinary BP and RBF neural network. The work described in this paper lays a solid foundation of thermal error prediction and compensation in a feed system.

关键词： least squares support vector machine (LS-SVM) feed system thermal error precision machining

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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

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Ultrasound-guided prostate percutaneous intervention robot system and calibration by informative particle

《机械工程前沿（英文）》 2022年第17卷第1期页码 3-3 doi: 10.1007/s11465-021-0659-x

摘要： Applying a robot system in ultrasound-guided percutaneous intervention is an effective approach for prostate cancer diagnosis and treatment. The limited space for robot manipulation restricts structure volume and motion. In this paper, an 8-degree-of-freedom robot system is proposed for ultrasound probe manipulation, needle positioning, and needle insertion. A novel parallel structure is employed in the robot system for space saving, structural rigidity, and collision avoidance. The particle swarm optimization method based on informative value is proposed for kinematic parameter identification to calibrate the parallel structure accurately. The method identifies parameters in the modified kinematic model stepwise according to parameter discernibility. Verification experiments prove that the robot system can realize motions needed in targeting. By applying the calibration method, a reasonable, reliable forward kinematic model is built, and the average errors can be limited to 0.963 and 1.846 mm for insertion point and target point, respectively.

关键词： ultrasound image guidance prostate percutaneous intervention parallel robot kinematics identification particle swarm optimization informative value

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Non-convex sparse optimization-based impact force identification with limited vibration measurements

《机械工程前沿（英文）》 2023年第18卷第3期 doi: 10.1007/s11465-023-0762-2

摘要： Impact force identification is important for structure health monitoring especially in applications involving composite structures. Different from the traditional direct measurement method, the impact force identification technique is more cost effective and feasible because it only requires a few sensors to capture the system response and infer the information about the applied forces. This technique enables the acquisition of impact locations and time histories of forces, aiding in the rapid assessment of potentially damaged areas and the extent of the damage. As a typical inverse problem, impact force reconstruction and localization is a challenging task, which has led to the development of numerous methods aimed at obtaining stable solutions. The classical

ℓ 2

regularization method often struggles to generate sparse solutions. When solving the under-determined problem,

ℓ 2

regularization often identifies false forces in non-loaded regions, interfering with the accurate identification of the true impact locations. The popular

ℓ 1

sparse regularization, while promoting sparsity, underestimates the amplitude of impact forces, resulting in biased estimations. To alleviate such limitations, a novel non-convex sparse regularization method that uses the non-convex

ℓ 1 − 2

penalty, which is the difference of the

ℓ 1

and

ℓ 2

norms, as a regularizer, is proposed in this paper. The principle of alternating direction method of multipliers (ADMM) is introduced to tackle the non-convex model by facilitating the decomposition of the complex original problem into easily solvable subproblems. The proposed method named

ℓ 1 − 2 -ADMM

is applied to solve the impact force identification problem with unknown force locations, which can realize simultaneous impact localization and time history reconstruction with an under-determined, sparse sensor configuration. Simulations and experiments are performed on a composite plate to verify the identification accuracy and robustness with respect to the noise of the

ℓ 1 − 2 -ADMM

method. Results indicate that compared with other existing regularization methods, the

ℓ 1 − 2 -ADMM

method can simultaneously reconstruct and localize impact forces more accurately, facilitating sparser solutions, and yielding more accurate results.

关键词： impact force identification inverse problem sparse regularization under-determined condition alternating direction method of multipliers

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Identification of cancer gene fusions based on advanced analysis of the human genome or transcriptome

null

《医学前沿（英文）》 2013年第7卷第3期页码 280-289 doi: 10.1007/s11684-013-0265-3

摘要：

Many gene fusions have been recognized as important diagnostic and/or prognostic markers in human malignancies. In recent years, novel gene fusions have been identified in cases without prior knowledge of the genetic background. Accompanied by a powerful computational data analysis method, new genome-wide screening approaches were used to detect cryptic genomic aberrations. This review focused on advanced genome-wide screening approaches in fusion gene identification, such as microarray-based approaches, next-generation sequencing, and NanoString nCounter gene expression system. The fundamental rationale and strategy for fusion gene identification using each biotech platform are also discussed.

关键词： gene fusion cancer microarray next-generation sequencing NanoString nCounter system

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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

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The research on structural damage identification using rough set and integrated neural network

Juelong LI, Hairui LI, Jianchun XING, Qiliang YANG

《机械工程前沿（英文）》 2013年第8卷第3期页码 305-310 doi: 10.1007/s11465-013-0259-5

摘要：

A huge amount of information and identification accuracy in large civil engineering structural damage identification has not been addressed yet. To efficiently solve this problem, a new damage identification method based on rough set and integrated neural network is first proposed. In brief, rough set was used to reduce attributes so as to decrease spatial dimensions of data and extract effective features. And then the reduced attributes will be put into the sub-neural network. The sub-neural network can give the preliminary diagnosis from different aspects of damage. The decision fusion network will give the final damage identification results. The identification examples show that this method can simplify the redundant information to reduce the neural network model, making full use of the range of information to effectively improve the accuracy of structural damage identification.

关键词： rough set integrated neural network damage identification decision making fusion

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射频识别在可视化后勤系统中的应用

王爱明,穆晓曦,李艾华

《中国工程科学》 2006年第8卷第8期页码 65-68

摘要：

射频识别技术是一种新型自动识别技术，具有可靠性高、保密性强，方便快捷、非接触等特点。将射频识别技术应用于后勤可视化系统，可以实时获取保障对象的需求及物资供应的类型、数量和流向等信息，从而实现全时段、全方位、全过程的供应保障。介绍了射频识别系统结构及工作原理，同时研究了射频识别技术在后勤可视化系统中的应用，所提出的在运物资可视化系统是根据贴在集装箱和装备上的射频识别标签实现的。

关键词：可视化后勤射频识别在运可视化系统

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标题作者时间类型操作

Theory analysis and system identification methods on thermal dynamics characteristics of ballscrews

XIA Junyong, HU Youmin, WU Bo, SHI Tielin

期刊论文

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

Variational mode decomposition based modal parameter identification in civil engineering

Mingjie ZHANG, Fuyou XU

期刊论文

Parameter identification of interconnected power system frequency after trip-out of high voltage transmission

Xuzhan ZHOU,Shanshan LIU,Mingkun WANG,Yiping DAI,Yaohua TANG

期刊论文

Variable identification and automatic tuning of the main module of a servo system of parallel mechanism

YANG Zhiyong, XU Meng, HUANG Tian, NI Yanbing

期刊论文

南水北调中线工程渠道糙率的系统辨识

杨开林,汪易森