Identification of time-varying system and energy-based optimization of adaptive control in seismically excited structure

The combination of structural health monitoring and vibration control is of great importance to provide components of smart structures.While synthetic algorithms have been proposed,adaptive control that is compatible with changing conditions still needs to be used,and time-varying systems are required to be simultaneously estimated with the application of adaptive control.In this research,the identification of structural time-varying dynamic characteristics and optimized simple adaptive control are integrated.First,reduced variations of physical parameters are estimated online using the multiple forgetting factor recursive least squares(MFRLS)method.Then,the energy from the structural vibration is simultaneously specified to optimize the control force with the identified parameters to be operational.Optimization is also performed based on the probability density function of the energy under the seismic excitation at any time.Finally,the optimal control force is obtained by the simple adaptive control(SAC)algorithm and energy coefficient.A numerical example and benchmark structure are employed to investigate the efficiency of the proposed approach.The simulation results revealed the effectiveness of the integrated online identification and optimal adaptive control in systems.

Quantitative Identification of Delamination Damage in Composite Structure Based on Distributed Optical Fiber Sensors and Model Updating

Delamination is a prevalent type of damage in composite laminate structures.Its accumulation degrades structural performance and threatens the safety and integrity of aircraft.This study presents a method for the quantitative identification of delamination identification in composite materials,leveraging distributed optical fiber sensors and a model updating approach.Initially,a numerical analysis is performed to establish a parameterized finite element model of the composite plate.Then,this model subsequently generates a database of strain responses corresponding to damage of varying sizes and locations.The radial basis function neural network surrogate model is then constructed based on the numerical simulation results and strain responses captured from the distributed fiber optic sensors.Finally,a multi-island genetic algorithm is employed for global optimization to identify the size and location of the damage.The efficacy of the proposed method is validated through numerical examples and experiment studies,examining the correlations between damage location,damage size,and strain responses.The findings confirm that the model updating technique,in conjunction with distributed fiber optic sensors,can precisely identify delamination in composite structures.

Structure identification for compound I separated and purified from taxoids-produced endophytic fungi (Alternaria. alternata var. taxi 1011)

Endophytic fungi are widely found in almost all kinds of plants. Many endophytic fungi can produce some physio-logical active compounds, which are same to or analog to those isolated from their hosts. Producing physiological active com-pounds through microbial fermentation can give a new way to resolve resource limitation and to find out alternative source. Through the methods of organic solvent extraction, thin layer chromatography (TLC) and column chromatography, compound I was isolated, purified from the liquid fermentation metabolites of the taxoids-produced endophytic fungi (Alternaria. alternata var. taxi 1011 Y. Xiang et LU An-guo) that was screened from the bark of Taxus. cuspidata Sieb.et Zucc.. Compound I was identified as one kind of taxoids type III, based on the analyzing results by using the methods of ultraviolet spectroscopy (UV), infrared spectroscopy (IR), mass spectrometry (MS) and nuclear magnetic resonance spectroscopy (NMR). This study provides a com-pleted method for separation and purification of the endophytic fungi as well as structure identification of its fermentation me-tabolite

SYSTEM IDENTIFICATION OF ADAPTIVE TRUSS STRUCTURES USING PIEZOELECTRIC ACTIVE MEMBERS

Adaptive truss structures are a new kind of structures with integrated active members,whose dynamic characteristies can be beneficially modified to meet mission requirements.Active members containing actuating and sensing units are the major components of adaptive truss structures.Modeling of adaptive truss structures is a key step to analyze the structural dynamic characteristics.A new experimental modal analysis approach,in which active members are used as excitatiDn sources for modal test,has been proposed in this paper.The excitation forces generated by the active members, which are different from the excitation forces exerted on structures in the conventional modal test,are internal forces for the truss structures.The relation between internal excitation forces and external forces is revealed such that the traditional identification method can be adopted to obtain modal parameters of adaptive structures.Placement problem of the active member in adaptive truss structures is also discussed in this work. Modal test and analysis are conducted with a planar adaptive truss structure by using piezoelectric active members in order to verify the feasibility and effectiveness of the proposed method.

Structural Health Monitoring by Accelerometric Data of a Continuously Monitored Structure with Induced Damages

The possibility of determining the integrity of a real structure subjected to non-invasive and non-destructive monitoring,such as that carried out by a series of accelerometers placed on the structure,is certainly a goal of extreme and current interest.In the present work,the results obtained from the processing of experimental data of a real structure are shown.The analyzed structure is a lattice structure approximately 9 m high,monitored with 18 uniaxial accelerometers positioned in pairs on 9 different levels.The data used refer to continuous monitoring that lasted for a total of 1 year,during which minor damage was caused to the structure by alternatively removing some bracings and repositioning them in the structure.Two methodologies detecting damage based on decomposition techniques of the acquired data were used and tested,as well as a methodology combining the two techniques.The results obtained are extremely interesting,as all the minor damage caused to the structure was identified by the processing methods used,based solely on the monitored data and without any knowledge of the real structure being analyzed.The results use 15 acquisitions in environmental conditions lasting 10 min each,a reasonable amount of time to get immediate feedback on possible damage to the structure.

An Approach to Polynomial NARX/NARMAX Systems Identification in a Closed-loop with Variable Structure Control

Many physical processes have nonlinear behavior which can be well represented by a polynomial NARX or NARMAX model. The identification of such models has been widely explored in literature. The majority of these approaches are for the open-loop identification. However, for reasons such as safety and production restrictions, open-loop identification cannot always be done. In such cases, closed-loop identification is necessary. This paper presents a two-step approach to closed-loop identification of the polynomial NARX/NARMAX systems with variable structure control （VSC）. First, a genetic algorithm （GA） is used to maximize the similarity of VSC signal to white noise by tuning the switching function parameters. Second, the system is simulated again and its parameters are estimated by an algorithm of the least square （LS） family. Finally, simulation examples are given to show the validity of the proposed approach.

Structure identification of an uncertain network coupled with complex-variable chaotic systems via adaptive impulsive control

In this paper, structure identification of an uncertain network coupled with complex-variable chaotic systems is in- vestigated. Both the topological structure and the system parameters can be unknown and need to be identified. Based on impulsive stability theory and the Lyapunov function method, an impulsive control scheme combined with an adaptive strategy is adopted to design effective and universal network estimators. The restriction on the impulsive interval is relaxed by adopting an adaptive strategy. Further, the proposed method can monitor the online switching topology effectively. Several numerical simulations are provided to illustrate the effectiveness of the theoretical results.

Purification and Structure Identification of Hyaluronic Acid

Polysaccharide produced by mutated strain of Streptococcus zooepidemicus was purified by the procedures including Savage method, quaternary ammonium compound precipitation, DEAE-cellulose(DE52) chromatography and Sephadex G-75 gel filtration. The structure of the purified polysaccharide has been characterized by means of chemical composition analysis,13C NMR spectrum, infrared spectrum and circular dichroism (CD). All the results showed that the purified polysaccharide was hyaluronic acid (HA). The single helix conformation of the purified HA was determined by Congo red experiment. The molecular weight of the HA was about 1.16×106D, which was measured by viscosity method.

Identification of Modal Parameters with Linear Structure under Non-stationary Ambient Excitation

Empirical mode decomposition (EMD) is proposed to identify linear structure under non-stationary excitation,and non-white noise coefficient is introduced under the assumption of random signals consisting of white noise and non-white noise signals. The cross-correlation function of response signal is decomposed into mode functions and residue by EMD method. The identification technique of the modal parameters of single freedom degree is applied to each mode function to obtain natural frequencies, damping ratios and mode shapes. The results of identification of the five-degree freedom linear system demonstrate that the proposed method is effective in identifying the parameters of linear structures under non-stationary ambient excitation.

Inverse Load Identification in Stiffened Plate Structure Based on in situ Strain Measurement

For practical engineering structures,it is usually difficult to measure external load distribution in a direct manner,which makes inverse load identification important.Specifically,load identification is a typical inverse problem,for which the models(e.g.,response matrix)are often ill-posed,resulting in degraded accuracy and impaired noise immunity of load identification.This study aims at identifying external loads in a stiffened plate structure,through comparing the effectiveness of different methods for parameter selection in regulation problems,including the Generalized Cross Validation(GCV)method,the Ordinary Cross Validation method and the truncated singular value decomposition method.With demonstrated high accuracy,the GCV method is used to identify concentrated loads in three different directions(e.g.,vertical,lateral and longitudinal)exerted on a stiffened plate.The results show that the GCV method is able to effectively identify multi-source static loads,with relative errors less than 5%.Moreover,under the situation of swept frequency excitation,when the excitation frequency is near the natural frequency of the structure,the GCV method can achieve much higher accuracy compared with direct inversion.At other excitation frequencies,the average recognition error of the GCV method load identification less than 10%.

Structures, Fields and Methods of Identification of Nonlinear Static Systems in the Conditions of Uncertainty

The field of structures on set of secants is offered and methods of its construction for various classes of one-valued nonlinearities of static systems are considered. The analysis of structural properties of system is fulfilled on specially generated set of data. Representation on which modification it is possible to judge to nonlinear structure of static systems is introduced. It is shown, that structures of nonlinear static systems have a special V-point. The adaptive algorithm of an estimation of structure of nonlinearity on a class poly-nomial function is offered.

Identification of the Concealed Structures in the Beiya Area of Western Yunnan

The interpretation of regional gravity and magnetic data, especially the extracted information about concealed targets and structures, provide important evidence for geological structure research, oil-gas resource assessment, mineral potential forecast and prospective area delineation. Several interpretation methods have been proposed to determine structural boundary, including vertical derivative, horizontal first-order derivative, total horizontal derivative, total gradient modulus, tilt derivative, and theta graph, and each have their advantages and disadvantages. This study used the tilt derivate method to obtain bouguer gravity anomalies in the Beya area, as shown in Fig. 1a.

Crosscumulants Based Approaches for the Structure Identification of Volterra Models

In this paper, we address the problem of structure identification of Volterra models. It consists in estimating the model order and the memory length of each kernel. Two methods based on input-output crosscumulants are developed. The first one uses zero mean independent and identically distributed Caussian input, and the second one concerns a symmetric input sequence. Simulations are performed on six models having different orders and kernel memory lengths to demonstrate the advantages of the proposed methods.

A MODEL IDENTIFICATION METHOD OF VIBRATING STRUCTURES FROM INCOMPLETE MODAL INFORMATION

The accurate mathematical models for complicated structures are verydifficult to construct.The work presented here provides an identification method for estimating the mass, damping , and stiffness matrices of linear dynamical systems from incompleteexperimental data. The mass, stiffness, and damping matrices are assumed to be real,symmetric, and positive definite. The partial set of experimental complex eigenvalues and corresponding eigenvectors are given. In the proposed method the least squaresalgorithm is combined with the iteration technique to determine systems identified matrices and corresponding design parameters. several illustrative examples, are presented to demonstrate the reliability of the proposed method .It is emphasized thatthe mass, damping and stiffness martices can be identified simultaneously.

A MODEL IDENTIFICATION METHOD OF VIBRATING STRUCTURES FROM INCOMPLETE MODAL INFORMATION

The accurate mathematical models for complicated structures are very difficult to construct.The work presented here provides an identification method for estimating the mass.damping,and stiffness matrices of linear dynamical systems from incomplete experimental data.The mass,stiffness and damping matrices are assumed to be real,symmetric,and positive definite The partial set of experimental complex eigenvalues and corresponding eigenvectors are given.In the proposed method the least squares algorithm is combined with the iteration technique to determine systems identified matrices and corresponding design parameters.Seeveral illustative examples,are presented to demonstrate the reliability of the proposed method .It is emphasized that the mass,damping and stiffness matrices can be identified simultaneously.

System Identification of Heritage Structures Through AVT and OMA:A Review

In this review article,the past investigations carried out on heritage structures using Ambient Vibration Test(AVT)and Operational Modal Analysis(OMA)for system identification(determination of dynamic properties like frequency,mode shape and damping ratios)and associated applications are summarized.A total of 68 major research studies on heritage structures around the world that are available in literature are surveyed for this purpose.At first,field investigations carried out on heritage structures prior to conducting AVT are explained in detail.Next,specifications of accelerometers,location of accelerometers and optimization of accelerometer networks have been elaborated with respect to the geometry of the heritage structures.In addition to this,ambient vibration loads and data acquisition procedures are also discussed.Further,the state of art of performing OMA techniques for heritage structures is explained briefly.Furthermore,various applications of system identification for heritage structures are documented.Finally,conclusions are made towards errorless system identification of heritage structures through AVT and OMA.

Studies on Seismic Identification and Reinforcement Design of Building Structures

China is a country with many earthquakes. Seismic safety monitoring and building earthquake-proofing technique are important means to protect the safety of people’s property in China. However, up to now, China’s seismic reinforcement and identification technology is still not mature enough. In particular, the 2008 Wenchuan earthquake caused great loss of life and safety to the Chinese people. This paper, takes seismic identification and reinforcement technology of building structures as the research object and summarizes the main methods of building structure seismic resistance in China. This paper is based on an in-depth analysis of the main seismic reinforcement and identification techniques in China, deeply analyzes the crux of anti-seismic and reinforcement of building structure combining with the current building seismic reinforcement typical cases, and puts forward some reasonable suggestions and improvement methods for the future development of building seismic identification and reinforcement design.

Influence of System Uncertainties on Structural Damage Identification through Ambient Vibrations of Steel Structures

The practical difficulties presented by forced vibration testing of large steel structures, such as tall buildings, transmission lines or bridges, led to an increased interest in structural monitoring through ambient vibrations, which usually allows the proper identification of modal properties, natural frequencies, damping and modes of vibration. Changes in these modal properties constitute an indication of structural damage, which may then be assessed on the basis of experimental evidence. The authors proposed an approach to determine the so-called damage damping and stiffness matrices, which are essential to identify the location and intensity of damage. No restrictions were introduced on the damping matrix of the system. The approach requires ambient vibration data of all relevant coordinates used in the structural model, which are processed employing the SSI method. In practice, the identification method is seriously hampered by ambient factors such as temperature or humidity. In general those effects must be filtered out in other to obtain a reliable diagnosis of damage, approach that demands long term monitoring. In this paper, an alternative approach is explored, based on the introduction of error damping and stiffness matrices. Data on both matrices is generated on the basis of observed variations of structural member stiffness and damping caused by ambient factors. The influence of this uncertainty on the identified spectral properties is assessed by simulation.

Damage Identification of General Overhead Travelling Crane Structure Based on Model Updating by Sensitivity

A model based damage identification was proposed by facilitating parameter sensitivity analysis and applied to a general overhead travelling crane.As updating reference data,experimental modal frequency was obtained by operational modal analysis(OMA)under ambient excitation.One dimensional damage function was defined to identify the damage by bending stiffness.The results showed that the model updating method could locate the damage and quantitatively describe the structure.The average error of eigenvalues between updated model analysis and the experimental results was less than 4% which proved the accuracy reliable.The comparison of finite element analysis and the test results of the deflection under the capacity load further verified the feasibility of this method.