Inverse Sensitivity Analysis of Singular Solutions of FRF matrix in Structural System Identification

The problem of structural damage detection based on measured frequency response functions of the structure in its damaged and undamaged states is considered. A novel procedure that is based on inverse sensitivity of the singular solutions of the system FRF matrix is proposed. The treatment of possibly ill-conditioned set of equations via regularization scheme and questions on spatial incompleteness of measurements are considered. The application of the method in dealing with systems with repeated natural frequencies and (or) packets of closely spaced modes is demonstrated. The relationship between the proposed method and the methods based on inverse sensitivity of eigensolutions and frequency response functions is noted. The numerical examples on a 5-degree of freedom system, a one span free-free beam and a spatially periodic multi-span beam demonstrate the efficacy of the proposed method and its superior performance vis-a-vis methods based on inverse eigensensitivity.

Structural FRF acquisition via electric impedance measurement applied to damage location

Continuing development of new materials makes systems lighter and stronger permitting more complex systems to provide more functionality and flexibility that demands a more effective evaluation of their structural health. Smart material technology has become an area of increasing interest in this field. The combination of smart materials and artificial neural networks can be used as an excellent tool for pattern recognition, turning their application adequate for monitoring and fault classification of equipment and structures. In order to identify the fault, the neural network must be trained using a set of solutions to its corresponding forward Variational problem. After the training process, the net can successfully solve the inverse variational problem in the context of monitoring and fault detection because of their pattern recognition and interpolation capabilities. The use of structural frequency response function is a fundamental portion of structural dynamic analysis, and it can be extracted from measured electric impedance through the electromechanical interaction of a piezoceramic and a structure. In this paper we use the FRF obtained by a mathematical model (FEM) in order to generate the training data for the neural networks, and the identification of damage can be done by measuring electric impedance, since suitable data normalization correlates FRF and electrical impedance.

Frequency response function based structural damage detection using artificial neural networks

Damage detection in structures has become increasingly important in recent years. While a number of damage detection and localization methods have been proposed, few attempts have been made to explore the structure damage with frequency response functions (FRFs). This paper illustrates the damage identification and condition assessment of a beam structure using a new frequency response functions (FRFs) based damage index and Artificial Neural Networks (ANNs). In practice, usage of all available FRF data as an input to artificial neural networks makes the training and convergence impossible. Therefore one of the data reduction techniques Principal Component Analysis (PCA) is introduced in the algorithm. In the proposed procedure, a large set of FRFs are divided into sub-sets in order to find the damage indices for different frequency points of different damage scenarios. The basic idea of this method is to establish features of damaged structure using FRFs from different measurement points of different sub-sets of intact structure. Then using these features, damage indices of different damage cases of the structure are identified after reconstructing of available FRF data using PCA. The obtained damage indices corresponding to different damage locations and severities are introduced as input variable to developed artificial neural networks. Finally, the effectiveness of the proposed method is illustrated and validated by using the finite element modal of a beam structure. The illustrated results show that the PCA based damage index is suitable and effective for structural damage detection and condition assessment of building structures.

Structural damage identification with noise polluted Frequency Response Functions (FRFs)

Damage detection in structures has become increasingly important in recent years. While a number of damage detection and localization methods have been proposed, very few attempts have been made to explore the structure damage with noise polluted data which is unavoidable effect in real world. The measurement data are contaminated by noise because of test environment as well as electronic devices and this noise tend to give error results with structural damage identification methods. Therefore it is important to investigate a method which can perform better with noise polluted data. This paper introduces a new damage index using principal component analysis (PCA) for damage detection of building structures being able to accept noise polluted frequency response functions (FRFs) as input. The FRF data are obtained from the function datagen of MATLAB program which is available on the web site of the IASC-ASCE (International Association for Structural Control– American Society of Civil Engineers) Structural Health Monitoring (SHM) Task Group. The proposed method involves a five-stage process: calculation of FRFs, calculation of damage index values using proposed algorithm, development of the artificial neural networks and introducing damage indices as input parameters and damage detection of the structure. This paper briefly describes the methodology and the results obtained in detecting damage in all six cases of the benchmark study with different noise levels. The proposed method is applied to a benchmark problem sponsored by the IASC-ASCE Task Group on Structural Health Monitoring, which was developed in order to facilitate the comparison of various damage identification methods. The illustrated results show that the PCA-based algorithm is effective for structural health monitoring with noise polluted FRFs which is of common occurrence when dealing with industrial structures.

Frequency response function based damage identification using principal component analysis and pattern recognition technique

Pattern recognition is a promising approach for the identification of structural damage using measured dynamic data. Much of the research on pattern recognition has employed artificial neural networks (ANNs) and genetic algorithms as systematic ways of matching pattern features. The selection of a damage-sensitive and noise-insensitive pattern feature is important for all structural damage identification methods. Accordingly, a neural networks-based damage detection method using frequency response function (FRF) data is presented in this paper. This method can effectively consider uncertainties of measured data from which training patterns are generated. The proposed method reduces the dimension of the initial FRF data and transforms it into new damage indices and employs an ANN method for the actual damage localization and quantification using recognized damage patterns from the algorithm. In civil engineering applications, the measurement of dynamic response under field conditions always contains noise components from environmental factors. In order to evaluate the performance of the proposed strategy with noise polluted data, noise contaminated measurements are also introduced to the proposed algorithm. ANNs with optimal architecture give minimum training and testing errors and provide precise damage detection results. In order to maximize damage detection results, the optimal architecture of ANN is identified by defining the number of hidden layers and the number of neurons per hidden layer by a trial and error method. In real testing, the number of measurement points and the measurement locations to obtain the structure response are critical for damage detection. Therefore, optimal sensor placement to improve damage identification is also investigated herein. A finite element model of a two storey framed structure is used to train the neural network. It shows accurate performance and gives low error with simulated and noise-contaminated data for single and multiple damage cases. As a result, the proposed method can be used for structural health monitoring and damage detection, particularly for cases where the measurement data is very large. Furthermore, it is suggested that an optimal ANN architecture can detect damage occurrence with good accuracy and can provide damage quantification with reasonable accuracy under varying levels of damage.

A Kalman filter based strategy for linear structural system identification based on multiple static and dynamic test data

The problem of identification of stiffness, mass and damping properties of linear structural systems, based on multiple sets of measurement data originating from static and dynamic tests is considered. A strategy, within the framework of Kalman filter based dynamic state estimation, is proposed to tackle this problem. The static tests consists of measurement of response of the structure to slowly moving loads, and to static loads whose magnitude are varied incrementally; the dynamic tests involve measurement of a few elements of the frequency response function (FRF) matrix. These measurements are taken to be contaminated by additive Gaussian noise. An artificial independent variable τ, that simultaneously parameterizes the point of application of the moving load, the magnitude of the incrementally varied static load and the driving frequency in the FRFs, is introduced. The state vector is taken to consist of system parameters to be identified. The fact that these parameters are independent of the variable τ is taken to constitute the set of ‘process’ equations. The measurement equations are derived based on the mechanics of the problem and, quantities, such as displacements and/or strains, are taken to be measured. A recursive algorithm that employs a linearization strategy based on Neumann’s expansion of structural static and dynamic stiffness matrices, and, which provides posterior estimates of the mean and covariance of the unknown system parameters, is developed. The satisfactory performance of the proposed approach is illustrated by considering the problem of the identification of the dynamic properties of an inhomogeneous beam and the axial rigidities of members of a truss structure.

Wave propagation analysis in carbon nanotube embedded composite using wavelet based spectral finite elements

In this paper, elastic wave propagation is studied in a nanocomposite reinforced with multiwall carbon nanotubes (CNTs). Analysis is performed on a representative volume element of square cross section. The frequency content of the exciting signal is at the terahertz level. Here, the composite is modeled as a higher order shear deformable beam using layerwise theory, to account for partial shear stress transfer between the CNTs and the matrix. The walls of the multiwall CNTs are considered to be connected throughout their length by distributed springs, whose stiffness is governed by the van der Waals force acting between the walls of nanotubes. The analyses in both the frequency and time domains are done using the wavelet-based spectral finite element method (WSFEM). The method uses the Daubechies wavelet basis approximation in time to reduce the governing PDE to a set of ODEs. These transformed ODEs are solved using a finite element (FE) technique by deriving an exact interpolating function in the transformed domain to obtain the exact dynamic stiffness matrix. Numerical analyses are performed to study the spectrum and dispersion relations for different matrix materials and also for different beam models. The effects of partial shear stress transfer between CNTs and matrix on the frequency response function (FRF) and the time response due to broadband impulse loading are investigated for different matrix materials. The simultaneous existence of four coupled propagating modes in a double-walled CNT-composite is also captured using modulated sinusoidal excitation.

Does the Term Spread play a role in the FED's reaction function? An Empirical Investigation

Using US data for the period 1967:5-2002:4, this paper empirically investigates the performance of a Fed’s reaction function (FRF) that (i) allows for the presence of switching regimes, (ii) considers the long-short term spread in addition to the typical variables, (iii) uses an alternative monthly indicator of general economic activity suggested by Stock and Watson (1999), and (iv) considers interest rate smoothing. The estimation results show the existence of three switching regimes, two characterized by low volatility and the remaining regime by high volatility. Moreover, the scale of the responses of the Federal funds rate to movements in the rate of inflation and the economic activity index depends on the regime. The estimation results also show robust empirical evidence that the importance of the term spread in the FRF has increased over the sample period and the FRF has been more stable during the term of office of Chairman Greenspan than in the pre-Greenspan period.

Caracterização físico-química e ações farmacológicas hepatoprotetora, antiinflamatória, pró-angiogênica, antioxidante e anticoagulante da fração rica em fucana 0,8FRF 0,8 da alga marrom Lobophora variegata

This study examines the physical and chemical composition and the pharmacological effects of brown seaweed FRF 0.8 Lobophora variegata. Fractionation of the crude extract was done with the concentration of 0.8 volumes of acetone, obtaining the FRF 0.8. The physicochemical characterization showed that it was a fucana sulfated. Anti-inflammatory activity was assessed by paw edema model by the high rates of inhibition of the edema and the best results were in the fourth hour after induction (100 ± 1.4% at the dose of 75 mg / kg) and by the strong inhibitory activity of the enzyme myeloperoxidase (91.45% at the dose of 25 mg / kg). The hepataproteção was demonstrated by measurements of enzymatic and metabolic parameters indicative of liver damage, such as bilirubin (reduction in 68.81%, 70.68% and 68.21% for bilirubin total, direct and indirect, respectively at a dose of 75 mg / kg), ALT, AST and γ-GT (decrease of 76.93%, 44.58% and 50% respectively at a dose of 75 mg / kg) by analysis of histological slides of liver tissue, confirming that hepatoprotective effect the polymers of carbohydrates, showing a reduction in tissue damage caused by CCl4 and the inhibition of the enzyme complex of cytochrome P 450 (increasing sleep time in 54.6% and reducing the latency time in 71.43%). The effectiveness of the FRF 0.8 angiogenesis was examined in chorioallantoic membrane (CAM) of fertilized eggs, with the density of capillaries evaluated and scored, showing an effect proangigênico at all concentrations tested FRF (10 mg- 1000 mg). The FRF showed antioxidant activity on free radicals (by inhibiting Superoxide Radical in 55.62 ± 2.10%, Lipid Peroxidation in 100.15 ± 0.01%, Hydroxyl Radical in 41.84 ± 0.001% and 71.47 Peroxide in ± 2.69% at concentration of 0.62 mg / mL). The anticoagulant activity was observed with prolongation of activated partial thromboplastin time (aPTT) at 50 mg (> 240 s), showing that its action occurs in the intrinsic pathway of the coagulation cascade. Thus, our results indicate that these sulfated polysaccharides are an important pharmacological target

Avaliação da composição química, atividade antioxidante, antibacteriana, antinoceptiva, antiinflamatória e toxicidade do extrato metanólico e frações de folhas de Spondias sp. (Anacardiaceae)

Spondias sp. (Anacardiaceae), popularly known as cajá-umbu, is an endemic plant from Northeastern Brazil, where their leaves are widely used in folk medicine to treat inflammatory processes, while their fruits have a great agro industrial potential. This study was designed to evaluate hepatoprotective, antinociceptive, antioxidant, antimicrobial and anti-inflammatory properties, as well as the acute toxicity and repeated dose 28, using a methanolic extract (MES), a fraction rich in flavonoids (FRF) and a precipitate from Spondias sp.leaves. The antioxidant activity of them was valued to evaluate their free radical scavenger capacity by DPPH test, whereas MES and FRF were used to evaluate while the preventive action on carbon tetrachloride (CCl4)-induced hepatotoxicity. Seven groups (n=5) of female Wistar rats were used as follows: control group, CCl4-intoxicated group treated with EMS (500 mg/kg) for 7 days, three CCl4-intoxicated groups treated with FRF (25, 50 and 75 mg/kg) for 7 days and the CCl4-intoxicated group treated with Legalon ® (silimarina; (phytotherapeutic reference) (50 mg/kg; 7 days). MES and FRF showed a protective action against liver injury induced by CCl4, being observed a significant reduction of serum enzyme activity marker of liver damage (alanine transaminase and aspartate transaminase). On the other hand, the lipid peroxidation (SRAT) decrease, as well as the increase of glutathione content and enzyme activity of antioxidant defense system (SOD, CAT, GPx) toward near normal values indicated the ability of EMS to restore the oxidative imbalance induced by CCl4. The histological analysis confirmed the hepatoprotection, compared to degenerative changes in CCl4-treated group. This hepatoprotetor effect was similar to that shown by Legalon®. The in vitro high antioxidant capacity of extract (93.16 ± 1.00%) showed analogous results to those obtained by Carduus marianus BHT (reference standard). This fact explains the obtained results in vivo. Although no antimicrobial activity was detected, EMS and FRF promoted the antinociceptive effect induced in the second phase by the intraplantar formalin test, evidencing the anti-inflammatory action; confirmed by the carrageenan-induced peritonitis model. The evaluation of the mechanical allodynia (CFA a 80%) demonstrated the involvement of the Spondias sp. chemical composition in the anti-inflammatory activity toward the acute processes. The acute exposure and repeated dose during 28 days did not produce significant changes in the parameters that evaluate toxicity. Together the experimental results reveal, that Spondias sp. leaf extracts have a promising potential in pharmaceutical area, and due to its non-toxic condition present efficiency and security

Time-domain analysis of piezoelectric impedance-based structural health monitoring using multilevel wavelet decomposition

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Analysis of the effects of damping in the models validation

The search for better performance in the structural systems has been taken to more refined models, involving the analysis of a growing number of details, which should be correctly formulated aiming at defining a representative model of the real system. Representative models demand a great detailing of the project and search for new techniques of evaluation and analysis. Model updating is one of this technologies, it can be used to improve the predictive capabilities of computer-based models. This paper presents a FRF-based finite element model updating procedure whose the updating variables are physical parameters of the model. It includes the damping effects in the updating procedure assuming proportional and non proportional damping mechanism. The updating parameters are defined at an element level or macro regions of the model. So, the parameters are adjusted locally, facilitating the physical interpretation of the adjusting of the model. Different tests for simulated and experimental data are discussed aiming at evaluating the characteristics and potentialities of the methodology.

Using of model updating considering damped frequency response function

The search for better performance in the structural systems has been taken to more refined models, involving the analysis of a growing number of details, which should be correctly formulated aiming at defining a representative model of the real system. Representative models demand a great detailing of the project and search for new techniques of evaluation and analysis. Model updating is one of this technologies, it can be used to improve the predictive capabilities of computer-based models. This paper presents a FRF-based finite element model updating procedure whose the updating variables are physical parameters of the model. It includes the damping effects in the updating procedure assuming proportional and none proportional damping mechanism. The updating parameters are defined at an element level or macro regions of the model. So, the parameters are adjusted locally, facilitating the physical interpretation of the adjusting of the model. Different tests for simulated and experimental data are discussed aiming at defining the characteristics and potentialities of the methodology.

Gastric antiulcer activity of Syngonanthus arthrotrichus SILVEIRA

Syngonanthus arthrotrichus SILVEIRA, popularly known as sempre-vivas mini-saia, is found in mountains of the Espinhaco range in the Brazilian states of Bahia and Minas Gerais. Extracts of this species contain several constituents, including flavonoids which may have antiulcerogenic activity. An ethanolic extract (EEOH), and flavonoid-rich (FRF) and flavonoid-deficient (FDF) fractions obtained from the scapes of S. arthrotrichus were investigated for their ability to prevent ulceration of the gastric mucosa in mice and rats. In the ethanol/HCl-induced ulcer model, lansoprazole (30 mg/kg), EEOH (50, 100, 250 mg/kg) given orally protected the gastric mucosal against injury in mice by 79%, 78%, 73%, and 64% respectively. In the ethanol-induced gastric ulcer model in rats, the lansoprazole (30 mg/kg), FRF and FDF (100 mg/kg) significantly protected the gastric mucosal of rats by 65%, 38% and 25% respectively when compared with the negative control group. In indomethacin/ bethanechol-induced gastric ulcers, cimetidine (100 mg/kg) and the EEOH (100, 250 mg/kg) inhibited gastric ulcer formation by 73%, 55% and 32% respectively. In this exactly model other treatments as cimetidine, FRF and FDF (100 mg/kg) each caused 54%, 36% and 45% inhibition, respectively. In the stress-induced gastric ulcer model, cimetidine (100 mg/kg) and the EEOH (50, 100, 250 mg/kg), inhibited gastric ulcer formation by 63%, 73%, 68% and 69% respectively. In the same model, cimetidine, FRF and FDF (100 mg/kg) significantly protected the gastric mucosal of the mice by 60%, 51% and 47% when compared to the control group. In pylorus-ligated mice, cimetidine (positive control) and FRF significantly decreased gastric acid secretion, increased gastric pH and reduced the acid output when compared to the negative control. FDF had no significant effect on these parameters. The protection provided by FRF probably involved an antisecretory mechanism mediated by flavonoids which were absent in FDF. The amount of adherent mucous in the stomach contents was also evaluated with the treatments carbenoxolone (200 mg/kg), FRF and FDF (100 mg/kg) treatment. Each treatments significantly increased the amount of adherent mucous in the gastric juice (8.67 +/- 1.73, 3.35 +/- 1.59, 2.1 +/- 0.41 mg/g of wet tissue, respectively) compared to the control group, indicating a cytoprotective action on the gastric mucosa. Treatment with FRF plus indomethacin and FDF plus indomethacin reduced the prostaglandin biosyntesis (13.6 +/- 6.5, 27 +/- 5.5 pg/well) by the mucosa, indicating that the cytoprotective action on the gastric mucosa was not related to the level of prostaglandins. Only FDF (38 +/- 17 pg/well) maintained the level of prostaglandins and guaranteed the integrity of the mucosa. The results indicate that the EEOH, FRF and FDF have antisecretory and cytoprotective actions, that may be related to the presence of luteoline in the extract and active fractions.