• Advances in aircraft and spacecraft science
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• v.4 no.6
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• pp.613-637
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• 2017

The development systems for the Structural Health Monitoring has attracted considerable interest from several engineering fields during the last decades and more specifically in the aerospace one. In fact, the introduction of those systems could allow the transition of the maintenance strategy from a scheduled basis to a condition-based approach providing cost benefits for the companies. The research presented in this paper consists of a definition and next comparison of four methods applied to numerical measurements for the extraction of damage features. The first method is based on the determination of the Structural Intensity field at the on-resonance condition in order to acquire information about the dissipation of vibrational energy throughout the structure. The Damage Quantification Indicator and the Average Integrated Global Amplitude Criterion methods need the evaluation of the Frequency Response Function for a healthy plate and a damaged one. The main difference between these two parameters is their mathematical definition and therefore the accuracy of the scalar values provided as output. The fourth and last method is based on the Mode-shape Curvature, a FRF-based technique which requires the application of particular finite-difference schemes for the derivation of the curvature of the plate. All the methods have been assessed for several damage conditions (the shape, the extension and the intensity of the damage) on two test plates: an isotropic (steel) plate and a 4-plies composite plate.

• Environmental Analysis Health and Toxicology
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• v.18 no.2
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• pp.155-163
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• 2003

Fluoranthene, a common polycyclicaromatic hydrocarbon (PAH), exhibits phototoxicity which may affect aquatic organisms. The eventual goal of this study is to develop a biomarker of Japanese medaka (Oryzias latipes) used in monitoring hazardous chemicals in the ecosystem. In this study we investigated neural toxicity of fluoranthene in Japanese medaka (Oryzias latipes) along with comparative analysis of corresponding behavioral response. The untreated individuals shooed normal behavioral characteristics (i. e., smooth and linear movements). The treated fish, however, showed stopping and abrupt change of orientation (100 ppb), and severely reduced locomotive activity and enhanced surfacing activity (1,000 ppb). Treatment of the medaka fish with fluoranthene caused a significant suppresson of acetycholine esterase (AChE) activities in the body portion but not in the head portion. When fish were exposed to 1,000 ppb of fluoranthene for 24 hr, the body AChE activities decreased from 126.${\pm}$31.89 (nmoles substrate hydrolyzed per min per mg protein) to 49.51${\pm}$11.99. Expressions of tyrosine hydroxylase (TH) protein in the different organs from both head and body portions were comparatively analyzed using an immunohistochemical technique. Five organs of the medaka fish showing a strong TH protein expression were the olfactory bulb, hypothalamus, optic lobe, pons and myelencephalon regions. This study provides molecular and neurobehavioral bases of a biomonitoring system for toxic chemicals using fish as a model organism.

• BMB Reports
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• v.48 no.4
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• pp.209-216
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• 2015

Stress is now recognized as a universal premorbid factor associated with many risk factors of various chronic diseases. Acute stress may induce an individual's adaptive response to environmental demands. However, chronic, excessive stress causes cumulative negative impacts on health outcomes through "allostatic load". Thus, monitoring the quantified levels of long-term stress mediators would provide a timely opportunity for prevention or earlier intervention of stressrelated chronic illnesses. Although either acute or chronic stress could be quantified through measurement of changes in physiological parameters such as heart rate, blood pressure, and levels of various metabolic hormones, it is still elusive to interpret whether the changes in circulating levels of stress mediators such as cortisol can reflect the acute, chronic, or diurnal variations. Both serum and salivary cortisol levels reveal acute changes at a single point in time, but the overall long-term systemic cortisol exposure is difficult to evaluate due to circadian variations and its protein-binding capacity. Scalp hair has a fairy predictable growth rate of approximately 1 cm/month, and the most 1 cm segment approximates the last month's cortisol production as the mean value. The analysis of cortisol in hair is a highly promising technique for the retrospective assessment of chronic stress. [BMB Reports 2015; 48(4): 209-216]

• Journal of the Korean Society for Nondestructive Testing
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• v.31 no.3
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• pp.260-270
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• 2011

The electromechanical impedance(E/M)-based method detects local structural damages based on variations of electrical impedance signatures which are obtained from piezoelectric sensors bonded to the structure and excited in high frequency band. In this method, temperature changes may result in significant impedance variations and lead to erroneous diagnostic results of the structure. To tackle this problem, a new technique providing a 2-dimensional damage feature related to the temperature information is proposed to distinguish the structural damage from the undesirable temperature variation. For experimental tests to validate the proposed method, damages are introduced by bolt loosening to a bolt-jointed steel beam, and impedance signals are measured under varying temperature conditions through a piezoelectric sensor attached on the beam. A freely suspended piezoelectric sensor is additionally utilized to obtain temperature information indirectly from resistance signatures. From a relationship between the damage index (from a constrained sensor) and the temperature (from a freely suspended sensor or a temperature sensor), damages can be detected more clearly under varying temperature compared to other conventional approaches.

• Smart Structures and Systems
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• v.10 no.4_5
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• pp.353-373
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• 2012

The instrumented Canton Tower is a 610 m high-rise structure, which has been considered as a benchmark problem for structural health monitoring (SHM) research. In this paper, an improved automatic modal identification method is presented based on a natural excitation technique in conjunction with the eigensystem realization algorithm (NExT/ERA). In the proposed modal identification method, damping ratio, consistent mode indicator from observability matrices (CMI_O) and modal amplitude coherence (MAC) are used as criteria to distinguish the physically true modes from spurious modes. Enhanced frequency domain decomposition (EFDD), the data-driven stochastic subspace identification method (SSI-DATA) and the proposed method are respectively applied to extract the modal parameters of the Canton Tower under different environmental conditions. Results of modal parameter identification based on output-only measurements are presented and discussed. User-selected parameters used in those methods are suggested and discussed. Furthermore, the effect of environmental conditions on the dynamic characteristics of Canton tower is investigated.

• Smart Structures and Systems
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• v.26 no.2
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• pp.157-174
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• 2020

The guided wave technique is commonly used in structural health monitoring as the guided waves can propagate far in the structures without much energy loss. The guided waves are conventionally generated by the surface-mounted piezoelectric wafer active sensor (PWAS). However, there is still lack of understanding of the wave propagation in layered structures, especially in structures made of anisotropic materials such as carbon fiber reinforced polymer (CFRP) composites. In this paper, the Rayleigh-Lamb wave strain tuning curves in a PWAS-mounted unidirectional CFRP plate are analytically derived using the normal mode expansion (NME) method. The excitation frequency spectrum is then multiplied by the tuning curves to calculate the frequency response spectrum. The corresponding time domain responses are obtained through the inverse Fourier transform. The theoretical calculations are validated through finite element analysis and an experimental study. The PWAS responses under the free, debonded and bonded CFRP conditions are investigated and compared. The results demonstrate that the amplitude and travelling time of wave packet can be used to evaluate the CFRP bonding conditions. The method can work on a baseline-free manner.

• Journal of the Korean Society for Nondestructive Testing
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• v.36 no.2
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• pp.138-148
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• 2016

Measurement of elastic constants is crucial for engineering aspects of predicting the behavior of materials under load as well as structural health monitoring of material degradation. Ultrasonic velocity measurement for material properties has been broadly used as a nondestructive evaluation method for material characterization. In particular, pulse-echo method has been extensively utilized as it is not only simple but also effective when only one side of the inspected objects is accessible. However, the conventional technique in this approach measures longitudinal and shear waves individually to obtain their velocities. This produces a set of two data for each measurement. This paper proposes a simultaneous sensing system of longitudinal waves and shear waves for elastic constant measurement. The proposed system senses both these waves simultaneously as a single overlapped signal, which is then analyzed to calculate both the ultrasonic velocities for obtaining elastic constants. Therefore, this system requires just half the number of data to obtain elastic constants compared to the conventional individual measurement. The results of the proposed simultaneous measurement had smaller standard deviations than those in the individual measurement. These results validate that the proposed approach improves the efficiency and reliability of ultrasonic elastic constant measurement by reducing the complexity of the measurement system, its operating procedures, and the number of data.

• Smart Structures and Systems
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• v.7 no.3
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• pp.229-240
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• 2011

Recent developments in Smart Structures with very large scale embedded sensors and actuators have introduced new challenges in terms of data processing and sensor fusion. These smart structures are dynamically classified as a large-scale system with thousands of sensors and actuators that form the musculoskeletal of the structure, analogous to human body. In order to develop structural health monitoring and diagnostics with data provided by thousands of sensors, new sensor informatics has to be developed. The focus of our on-going research is to develop techniques and algorithms that would utilize this musculoskeletal system effectively; thus creating the intelligence for such a large-scale autonomous structure. To achieve this level of intelligence, three major research tasks are being conducted: development of a Bio-Inspired data analysis and information extraction from thousands of sensors; development of an analytical technique for Optimal Sensory System using Structural Observability; and creation of a bio-inspired decision-making and control system. This paper is focused on the results of our effort on the first task, namely development of a Neuro-Morphic Engineering approach, using a neuro-symbolic data manipulation, inspired by the understanding of human information processing architecture, for sensor fusion and structural diagnostics.

• Earthquakes and Structures
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• v.8 no.4
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• pp.843-857
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• 2015

System identification is regarded as the most basic technique for structural health monitoring to evaluate structural integrity. Although many system identification techniques extracting mode information (e.g., mode frequency and mode shape) have been proposed so far, it is also desired to identify physical parameters (e.g., stiffness and damping). As for high-rise buildings subjected to long-period ground motions, system identification for evaluating only the shear stiffness based on a shear model does not seem to be an appropriate solution to the system identification problem due to the influence of overall bending response. In this paper, a system identification algorithm using a shear-bending model developed in the previous paper is revised to identify both shear and bending stiffnesses. In this algorithm, an ARX (Auto-Regressive eXogenous) model corresponding to the transfer function for interstory accelerations is applied for identifying physical parameters. For the experimental verification of the proposed system identification framework, vibration tests for a 3-story steel mini-structure are conducted. The test structure is specifically designed to measure horizontal accelerations including both shear and bending responses. In order to obtain reliable results, system identification theories for two different inputs are investigated; (a) base input motion by a modal shaker, (b) unknown forced input on the top floor.

• Structural Engineering and Mechanics
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• v.41 no.5
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• pp.663-673
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• 2012

A number of mode shape-based structure damage identification methods have been verified by numerical simulations or experiments for on-line structure health monitoring (SHM). However, many of them need a baseline mode shape generated by the healthy structure serving as a reference to identify damages. Otherwise these methods can hardly perform well when multiple cracks conditions occur. So it is important to solve the problems above. By aid of the fractal dimension method (FD), Qiao and Wang proposed a generalized fractal dimension (GFD) to detect the delamination damage. As a modification of GFD, Qiao and Cao proposed the approximate waveform capacity dimension (AWCD) technique to simplify the calculation of fractal and overcome the false peak appearing in the high mode shapes. Based on their valued work, this paper combined and applied the AWCD method and curvature mode shape data to detect multiple damages in beam. In the end, the identification properties of the AWCD for multiple damages have been verified by groups of Monte Carlo simulations and experiments.