Model-based Predictive Control for Spatially-distributed Systems Using Dimensional Reduction Models

In this paper, a low-dimensional multiple-input and multiple-output (MIMO) model predictive control (MPC) configuration is presented for partial differential equation (PDE) unknown spatially-distributed systems (SDSs). First, the dimension reduction with principal component analysis (PCA) is used to transform the high-dimensional spatio-temporal data into a low-dimensional time domain. The MPC strategy is proposed based on the online correction low-dimensional models, where the state of the system at a previous time is used to correct the output of low-dimensional models. Sufficient conditions for closed-loop stability are presented and proven. Simulations demonstrate the accuracy and efficiency of the proposed methodologies.     

Hsp70 and Hsc70 are preferentially expressed in differentiated epithelial cells in normal human endometrium and ectocervix

This paper addresses parametric system identification of linear and nonlinear dynamic systems by analysis of the input and output signals. Specifically, we investigate the relationship between estimation of the system using a feedforward neural network model and estimation of the system by use of linear and nonlinear autoregressive moving-average (ARMA) models. By utilizing a neural network model incorporating a polynomial activation function, we show the equivalence of the artificial neural network to the linear and nonlinear ARMA models. We compare the parameterization of the estimated system using the neural network and ARMA approaches by utilizing data generated by means of computer simulations. Specifically, we show that the parameters of a simulated ARMA system can be obtained from the neural network analysis of the simulated data or by conventional least squares ARMA analysis. The feasibility of applying neural networks with polynomial activation functions to the analysis of experimental data is explored by application to measurements of heart rate (HR) and instantaneous lung volume (ILV) fluctuations.     

Enhanced Realization∕Identification of Physical Modes

Physical structures are often sufficiently complicated to preclude constructing an accurate mathematical model of the system dynamics from simple analysis using the laws of physics. Consequently, determination of an accurate model requires utilization of (generally noisy) output measurements from dynamic tests. In this paper, we present a robust method for constructing accurate, structural‐dynamic models from discrete time‐domain measurements. The method processes the measurements in order to determine the number of modes present, the damping and frequency of each mode, and the mode shape. The structure may be highly damped. Although the mode‐shape identification is more sensitive to measurement noise than the order, frequency, and damping identification, the method is considerably less sensitive to noise than other leading methods. Accurate detection of the modal parameters and mode shapes is demonstrated for modes with damping ratios exceeding 15%.     

Simultaneous Estimation of System and Input Parameters from Output Measurements

System identification of very large structures is of necessity accomplished by analyzing output measurements, as in the case of ambient vibration surveys. Conventional techniques typically identify system parameters by assuming (arguably) that the input is locally Gaussian white, and in so doing, effectively reduce the number of degrees of freedom of the estimation problem to a more tractable number. This paper describes a new approach that has several novel attributes, among them, elimination of the need for the Gaussian white input assumption. The approach involves a filter applied to an identification problem formulated in the frequency domain. The filter simultaneously estimates both system parameters and input excitation characteristics. The estimates we obtain are not guaranteed to be unique (as is true in all other approaches: simultaneous estimation of both system and input possesses too many degrees of freedom to guarantee uniqueness); but we do, nonetheless, identify system parameters and input excitation characteristics that are physically plausible and intuitively reasonable, without making input excitation assumptions. Simulated and laboratory experimental data are used to verify the algorithm and demonstrate its advantages over conventional approaches.     

平方振型加权模态参数整体识别法

提出了整体频响函数的新概念(GFRF).以振型平方和的形式对全部频响函数进行加权组合,建立了多输入多输出模态参数的识别模型.仿真验算的分析结果表明,该方法具有精度高,一致性好,能分离密集模态和消除随机噪声等优点,可以应用于大型复杂结构的试验模态分析.     

Identification of Structural Systems Using an Evolutionary Strategy

The problem of system identification is an inverse problem of difficult solution. Currently, difficulties lie in the development of algorithms that use measured data from the system to characterize it without significant a priori knowledge of the system. In this paper, a parameter estimation technique based on an evolution strategy (an optimization algorithm inspired by natural evolution) is presented to overcome some of the difficulties encountered in the field. Using this method, a set of direct problems is solved instead of directly tackling the inverse problem. If the uniqueness of the identification solution is guaranteed for the assumed model and the available data, this heuristic method is able to find a solution without incurring restrictions of other classical optimization methods, like the need for reliable initial estimates and convergence to local optima. Some results obtained with this algorithm are presented for the identification of 3 degrees of freedom (DOF) and a 10?DOF structural system under conditions including limited input/output data, noise polluted signals, and no prior knowledge of mass, damping, or stiffness of the system.     

Standing Wave Difference Method for Leak Detection in Pipeline Systems

The current paper focuses on leakage detection in pipe systems by means of the standing wave difference method (SWDM) used for cable fault location in electrical engineering. This method is based on the generation of a steady-oscillatory flow in a pipe system, by the sinusoidal maneuver of a valve, and the analysis of the frequency response of the system for a certain range of oscillatory frequencies. The SWDM is applied to several configurations of pipe systems with different leak locations and sizes. A leak creates a resonance effect in the pressure signal with a secondary superimposed standing wave. The pressure measurement and the spectral analysis of the maximum pressure amplitude at the excitation site enable the identification of the leak frequencies and, consequently, the estimation of the leak approximate location. Practical difficulties of implementation of this technique in real life systems are discussed.     

Cross-Modal Strain Energy Method for Estimating Damage Severity

A newly developed damage severity estimation method, termed as cross-modal strain energy (CMSE) method, which is capable of accurately estimating the damage magnitude of multiple damaged members, is presented. While all existing damage severity estimation methods that utilize modal strain energy are either employing an iterative solution procedure or involving significant approximations, the CMSE method is an exact, noniterative solution method. Furthermore, the development of the CMSE method is under the assumption that the mass distributions of the baseline and damaged structures are unknown, but identical. Implementing this method requires only the information of a few modes measured from the damaged structure. Numerical studies are demonstrated for a three-dimensional five-story frame structure based on synthetic data generated from finite element models.     

System Identification through Model Composition and Stochastic Search

System identification methodologies are useful for identifying characteristics of structural systems using measurement data. However, incorrect systems might be identified when many combinations of system characteristics result in the same predicted responses at measured locations. The reliability of identification is affected by a number of factors that most previous work has overlooked. This paper presents a system identification methodology that explicitly treats factors that affect the success of identification. Rather than simply determining parametric values, this methodology also involves identification of model characteristics including boundary conditions. Due to inevitable modeling errors, models that provide absolute minimum differences between predictions and measurements are rarely correct models. In such situations, the challenge is to define a population of candidate models that result in such differences being below threshold values that are determined by the magnitude of modeling errors. The methodology is illustrated using a case study in civil engineering. This work contributes to providing engineers with general strategies to meet interpretation challenges associated with sensor data.     

Identification of the Soil–Structure Interaction System Using Earthquake Response Data

This paper demonstrates how system identification techniques can be successfully applied to a soil–structure interaction system using the earthquake response data. The parameters identified are the shear moduli of several near-field soil regions and Young’s moduli of the shell sections of the structure. The soil–structure interaction system is modeled by the finite element method combined with the infinite element formulation for the unbounded layered soil medium. The simulated earthquake responses using the identified parameters are shown to be in excellent agreement with the observed response data. Prediction of the responses is also carried out for a larger earthquake event using the identified parameters as the initial properties in the equivalent linearization procedure. It has been found that the predicted responses are also compared very well with the measured responses.     

Ambient Vibration Data Analysis for Structural Identification and Global Condition Assessment

System identification is an area which deals with developing mathematical models to characterize the input-output behavior of an unknown system by means of experimental data. Structural health monitoring (SHM) provides the tools and technologies to collect and analyze input and output data to track the structural behavior. One of the most commonly used SHM technologies is dynamic testing. Ambient vibration testing is a practical dynamic testing method especially for large civil structures where input excitation cannot be directly measured. This paper presents a conceptual and reliable methodology for system identification and structural condition assessment using ambient vibration data where input data are not available. The system identification methodology presented in this study is based on the use of complex mode indicator functions (CMIFs) coupled with the random decrement (RD) method to identify the modal parameters from the output only data sets. CMIF is employed for parameter identification from the unscaled multiple-input multiple-output data sets generated using the RD method. For condition assessment, unscaled flexibility and the deflection profiles obtained from the dynamic tests are presented as a conceptual indicator. Laboratory tests on a steel grid and field tests on a long-span bridge were conducted and the dynamic properties identified from these tests are presented. For demonstrating condition assessment, deflected shapes obtained from unscaled flexibility are compared for undamaged and damaged laboratory grid structures. It is shown that structural changes on the steel grid structure are identified by using the unscaled deflected shapes.     

Frequency-Domain Modeling of Transients in Pipe Networks with Compound Nodes Using a Laplace-Domain Admittance Matrix

An alternative to modeling the transient behavior of pipeline systems in the time domain is to model these systems in the frequency domain using Laplace transform techniques. A limitation with traditional frequency-domain pipeline models is that they are only able to deal with systems of a limited class of configuration. Despite the development of a number of recent Laplace-domain network models for arbitrarily configured systems, the current formulations are designed for systems comprised only of pipes and simple node types such as reservoirs and junctions. This paper presents a significant generalization of existing network models by proposing a framework that allows not only complete flexibility with regard to the topological structure of a network, but also, encompasses nodes with dynamic components of a more general class (such as air vessels, valves, and capacitance elements). This generalization is achieved through a novel decomposition of the nodal dynamics for inclusion into a Laplace-domain network admittance matrix. A symbolic example is given demonstrating the development of the network admittance matrix and numerical examples are given comparing the proposed method to the method of characteristics for 11-pipe and 51-pipe networks.     

Frequency Modeling of Open-Channel Flow

A good model is necessary to design automatic controllers for water distribution in an open-channel system. The frequency response of a canal governed by the Saint-Venant equations can be easily obtained in the uniform case. However, in realistic situations, open-channel systems are usually far from the uniform regime. This paper provides a new computational method to obtain a frequency domain model of the Saint-Venant equations linearized around any stationary regime (including backwater curves). The method computes the frequency response of the Saint-Venant transfer matrix, which can be used to design controllers with classical automatic control techniques. The precision and numerical efficiency of the proposed method compare favorably with classical numerical schemes (e.g., Runge–Kutta). The model is compared in nonuniform situations to the one given by a finite difference scheme applied to Saint-Venant equations (Preissmann scheme), first in the frequency domain, then in the time domain. The proposed scheme can be used, e.g., to validate finite difference schemes in the frequency domain.     

Leak Detection in Pipes by Frequency Response Method

The frequency response method is used to determine the location and rate of leakage in open loop piping systems. A steady-oscillatory flow, produced by the periodic opening and closing of a valve, is analyzed in the frequency domain by using the transfer matrix method, and a frequency response diagram at the valve is developed. For a system with leaks, this diagram has additional resonant pressure amplitude peaks (herein referred to as the secondary pressure amplitude peaks) that are lower than the resonant pressure amplitude peaks (herein called primary amplitude peaks) for the system with no leaks. Several piping systems are successfully analyzed for all practical values of the friction factor to detect and locate individual leaks of up to 0.5% of the mean discharge. The method, requiring the measurement of pressure and discharge fluctuations at only one location, has the potential to detect leaks in real-life pipe systems conveying different types of fluids, such as water, petroleum, and so on.     

Vehicle Condition Surveillance on Continuous Bridges Based on Response Sensitivity

This paper presents the parameter identification of a vehicle moving on a multispan continuous bridge deck modeled as a continuous beam based on dynamic response sensitivity analysis. This technique is for the monitoring of “road-friendliness” of vehicles using the highway pavement. The moving vehicle is modeled as a single degree-of-freedom system comprising three parameters, a two degrees-of-freedom system comprising five parameters, or a four degrees-of-freedom system comprising 12 parameters. The modified beam functions are used to calculate the response of the continuous bridge. Starting with an initial guess on the unknown parameters, the identification can be realized based on least-squares method and regularization technique from measured strain, velocity, or acceleration measurement from as few as a single sensor. Simulation studies and experimental results indicate that the identified results are acceptable, and the responses reconstructed from the identified parameters agree well with the measured responses.     

Free-Vibration Analysis and Material Constants Identification of Laminated Composite Sandwich Plates

Free vibration of symmetrically laminated composite sandwich plates with elastic edge restraints is studied via the Rayleigh–Ritz approach. The proposed Rayleigh–Ritz method is constructed on the basis of the layer-wise linear displacement theory. The accuracy of the method in predicting natural frequencies of composite sandwich plates with different boundary conditions is verified by the results reported in the literature or the experimental data obtained in this study. The proposed method is then applied to the material constant identification of free composite sandwich plates using the first six theoretical natural frequencies of the plates. In the identification process, trial material constants are used in the present method to predict the theoretical natural frequencies, a frequency discrepancy function is established to measure the sum of the squared differences between the experimental and theoretical natural frequencies, and a stochastic global minimization algorithm is used to search for the best estimates of the material constants by making the frequency discrepancy function a global minimum. Applications of the material constant identification technique are demonstrated by means of several examples.     

Experiments on a Full-Scale Building Model using Modified Sliding Mode Control

This paper presents a modified sliding mode control (MSMC) method using acceleration feedback to reduce the response of seismic-excited civil buildings. A pre-filter is introduced prior to the control command so that a systematic trade-off between control and structural responses can be achieved. To demonstrate practical implementation of MSMC controllers, extensive shake table experimental tests have been conducted on a full-scale three-story building equipped with active bracing systems at the National Center for Research on Earthquake Engineering, Taiwan. To improve the effectiveness of active control, a nominal system that incorporates the control–structure interaction effect is used in the MSMC controller design. In addition, existing system uncertainties in the nominal system resulting from system identification are considered in the process of controller design and the robustness of control performance and stability is demonstrated through shake table experiments. Experimental results indicate that the MSMC strategy using acceleration feedback for the full-scale building is robust and its performance is quite remarkable. Furthermore, the numerical simulation based on an analytical model that was identified previously by taking into account the control–structure interaction effect was conducted and comparisons are made with the experimental results. It is shown that the correlation between numerical simulation results and experimental data is quite excellent.     

Dynamic Field Test, System Identification, and Modal Validation of an RC Minaret: Preprocessing and Postprocessing the Wind-Induced Ambient Vibration Data

The investigation of dynamic response for civil engineering structures largely depends on a detailed understanding of their dynamic characteristics, such as the natural frequencies, mode shapes, and modal damping ratios. Dynamic characteristics of structures may be obtained numerically and experimentally. The finite-element method is widely used to model structural systems numerically. However, there are some uncertainties in numerical models. Material properties and boundary conditions may not be modeled correctly. There may be some microcracks in the structures, and these cracks may directly affect the modeling parameters. Modal testing gives correct uncertain modeling parameters that lead to better predictions of the dynamic behavior of a target structure. Therefore, dynamic behavior of special structures, such as minarets, should be determined with ambient vibration tests. The vibration test results may be used to update numerical models and to detect microcracks distributed along the structure. The operational modal analysis procedure consists of several phases. First, vibration tests are carried out, spectral functions are produced from raw measured acceleration records, dynamic characteristics are determined by analyzing processed spectral functions, and finally analytical models are calibrated or updated depending on experimental analysis results. In this study, an ambient vibration test is conducted on the minaret under natural excitations, such as wind effects and human movement. The dynamic response of the minaret is measured through an array of four trixial force-balanced accelerometers deployed along the whole length of the minaret. The raw measured data obtained from ambient vibration testing are analyzed with the SignalCAD program, which was developed in MATLAB. The employed system identification procedures are based on output-only measurements because the forcing functions are not available during ambient vibration tests. The ModalCAD program developed in MATLAB is used for dynamic characteristic identification. A three-dimensional model of the minaret is constructed, and its modal analysis is performed to obtain analytical frequencies and mode shapes by using the ANSYS finite-element program. The obtained system identification results have very good agreement, thus providing a reliable set of identified modal properties (natural frequencies, damping ratios, and mode shapes) of the structure, which can be used to calibrate finite-element models and as a baseline in health monitoring studies.     

Structural Damage Diagnosis and Assessment under Seismic Excitations

This study proposes a method of detecting, locating, and quantifying structural damage by directly using structural vibration measurements in the time domain. In this method, the coupling effect of the damage at different locations in the structure on the structural vibratory responses is eliminated by projecting these measured quantities onto some specific subspaces. As a result, the structural system, generally modeled with multiple degree of freedom, is decomposed into several independent single-degree-of-freedom (SDOF) systems, every one of which is only associated with the damage at one certain location or region. A monitor is designed as an observer to detect the structural damage related to each SDOF system. A decision-making scheme is developed to correlate the monitor’s output to the occurrence of the damage. The severity of the damage is estimated with a traditional system identification method in an iterative way. The analysis of the effects of measurement noise is also included. Numerical examples are presented to demonstrate the effectiveness of the proposed method.     

Output-Only System Identification of Posttensioned Segmental Concrete Highway Bridges

This paper discusses the application of system identification of a highway bridge using finite-element method and ambient-vibration testing. The posttensioned Gülburnu Highway Bridge located on the Giresun-Espiye state highway was selected as a case study. A finite-element model of the bridge was developed using SAP2000 software, and dynamic characteristics were obtained analytically. During the test, sources of ambient excitations were provided by the traffic effects over the bridge. Ambient-vibration tests were applied to the bridge to identify dynamic characteristics. The selection of measurement time, frequency span, and effective mode number was considered from similar studies in the literature. Two output-only system identification methods, enhanced frequency domain decomposition and stochastic subspace identification, were used to estimate the dynamic characteristics of the bridge experimentally. The accuracy and efficiency of both methods were investigated and compared with finite-element results. Results suggest that ambient-vibration measurements are sufficient to identify structural modes with a low range of natural frequencies. In addition, the dynamic characteristics obtained from the finite-element model of the bridge have a good correlation with experimental frequencies and mode shapes.