• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2012.10a
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• pp.715-722
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• 2012

A structural health monitoring (SHM) technique for locating impact position in a composite plate is presented in this paper. The technique employs a single sensor and spatial focusing properties of time reversal (TR) and inverse filtering (IF). We first examine the focusing effect of back-propagated signal at the impact position and its surroundings through simulation. Impact experiments are then carried out and the localization images are found using the TR and IF signal processing, respectively. Both techniques provide accurate impact location results. Compared to existing techniques for locating impact or acoustic emission source, the proposed methods have the benefits of using a single sensor and not requiring knowledge of material properties and geometry of structures. Furthermore, it does not depend on a particular mode of dispersive Lamb waves that is frequently used in the SHM of plate-like structures.

• Smart Structures and Systems
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• v.8 no.2
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• pp.191-204
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• 2011

A technique for damage localization and assessment based on measurements of both eigenvectors curvatures and eigenfrequencies is proposed. The procedure is based on two successive steps: a model independent localization, based on changes of modal curvatures, and the solution of a one-dimensional minimization problem to evaluate damage intensity. The observability properties of damage parameters is discussed and, accordingly, a suitable change of coordinates is introduced. The proposed technique is illustrated with reference to a cantilever Euler beam endowed with a set of piezoelectric transducers. To assess the robustness of the algorithm, a parametric study of the identification errors with respect to the number of transducers and to the number of considered modal quantities is carried out with both clean and noise-corrupted data.

• Structural Engineering and Mechanics
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• v.42 no.3
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• pp.425-448
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• 2012

In this paper, a new damage detection and quantification method has been presented to perform detection and quantification of structural damage under ambient vibration loadings. To extract modal properties of the structural system under ambient excitation, natural excitation technique (NExT) and eigensystem realization algorithm (ERA) are employed. Sensitivity matrices of the dynamic residual force vector have been derived and used in the parameter subset selection method to identify multiple damaged locations. In the sequel, the steady state genetic algorithm (SSGA) is used to determine quantified levels of the identified damage by minimizing errors in the modal flexibility matrix. In this study, performance of the proposed damage detection and quantification methodology is evaluated using a finite element model of a truss structure with considerations of possible experimental errors and noises. A series of numerical examples with five different damage scenarios including a challengingly small damage level demonstrates that the proposed methodology can efficaciously detect and quantify damage under noisy ambient vibrations.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.23 no.1
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• pp.27-31
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• 2014

This paper describes a tomographic imaging technique for evaluating the thickness reduction of a plate-like structure using a noncontact sensor network based on an electromagnetic acoustic transducer that generates shear horizontal plate waves. Because this technique is based on the effect of mode cutoff and time of flight of guided waves caused by a change in thickness, the tomographic image provides information on the presence of defects in the structure. To verify the performance of the method, artificial defects with various thickness reduction ratios were machined in an aluminum plate, and the tomographic imaging results are reported. The results show that the generated tomographic image displays the thickness reductions and can identify their locations. Therefore, the proposed technique has good potential as a tool for health monitoring of the integrity of plate-like structures.

• Smart Structures and Systems
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• v.25 no.4
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• pp.423-432
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• 2020

In this paper, a novel but practical approach named series/parallel multi-sensing technique was proposed to evaluate the bolt looseness in a bolt group. The smart washers (SWs), which were fabricated by embedding a Lead Zirconate Titanate (PZT) transducer into two flat metal rings, were installed to the bolts group. By series connection of SWs, the impedance signals of different bolts can be obtained through only one sweep. Therefore, once the loosening occurred, the shift of different peak frequencies can be used to locate which bolt has loosened. The proposed multi input single output (MISO) damage detection scheme is very suitable for the structural health monitoring (SHM) of joint with a large number of bolts connection. Another notable contribution of this paper is the proposal of 3-dB bandwidth root mean square deviation (3 dB-RMSD) which can quantitatively evaluate the severity of bolt looseness. Compared with the traditional naked-eye observation method, the equivalent circuit based 3-dB bandwidth can accurately define the calculation range of RMSD. An experiment with three bolted connection specimens that installed the SWs was carried out to validate our proposed approach. Experimental result shows that the proposed 3 dB-RMSD based multi-sensing technique can not only identify the loosened bolt but also monitor the severity of bolt looseness.

• The Journal of the Korea Contents Association
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• v.16 no.3
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• pp.11-21
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• 2016

Recently, structure safety management techniques using cutting-edge technology(Displacement senor, sensor of acceleration) has emerged as an important issue owing to the aging of infrastructure such as bridge and building. In general, the structural monitoring system for structure safety management is based on IT technology and it is expensive to install. In this paper developed an image-based structure dynamic characteristic analysis system prototype to assess the damage of structure in a more cost-effective way than traditional structure health monitoring system. The inspector can take a video of buildings or other structures with digital camera or any other devices that is passible to take video, and then using NCC calculation for image processing technique to get natural frequency. This system is analysis of damage of the structure using a compare between the frequency response ratio and functions when problems are occurs send alarm to administrator. This system is easier to install and remove than previous monitoring sensor in economical way.

• Smart Structures and Systems
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• v.6 no.3
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• pp.197-209
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• 2010

The structural state of a bridge is currently examined by visual inspection or by wired sensor techniques, which are relatively expensive, vulnerable to inclement conditions, and time consuming to undertake. In contrast, wireless sensor networks are easy to deploy and flexible in application so that the network can adjust to the individual structure. Different sensing techniques have been used with such networks, but the acoustic emission technique has rarely been utilized. With the use of acoustic emission (AE) techniques it is possible to detect internal structural damage, from cracks propagating during the routine use of a structure, e.g. breakage of prestressing wires. To date, AE data analysis techniques are not appropriate for the requirements of a wireless network due to the very exact time synchronization needed between multiple sensors, and power consumption issues. To unleash the power of the acoustic emission technique on large, extended structures, recording and local analysis techniques need better algorithms to handle and reduce the immense amount of data generated. Preliminary results from utilizing a new concept called Acoustic Emission Array Processing to locally reduce data to information are presented. Results show that the azimuthal location of a seismic source can be successfully identified, using an array of six to eight poor-quality AE sensors arranged in a circular array approximately 200 mm in diameter. AE beamforming only requires very fine time synchronization of the sensors within a single array, relative timing between sensors of $1{\mu}s$ can easily be performed by a single Mote servicing the array. The method concentrates the essence of six to eight extended waveforms into a single value to be sent through the wireless network, resulting in power savings by avoiding extended radio transmission.

• Biomedical Science Letters
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• v.9 no.3
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• pp.139-144
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• 2003

Since water borne infection causes acute diseases and results in spread of diseases by secondary infection, the prevention is very important. Therefore, it is necessary to have a method that is rapid and effective to monitor pathogenic bacteria in drinking water. In this study, we employed a systematic method, Polymerase Chain Reaction-Restriction Fragment Length Polymorphism (PCR-RFLP) analysis, to develop an effective monitoring system for possible bacterial contaminants in drinking water. For this purpose, PCR primers were derived from 992 bp region of the 16s rRNA gene that is highly conserved through the different species of prokaryotes. To test whether the PCR primers designed are indeed useful for detecting all the possible microbial contaminants in the water, the primers were used to amplify 16s rRNA regions of different microbial water-borne pathogens such as E. coli, Salmonella, Yersinia, Listeria, and Staphylococcus. As expected, all of tested microorganisms amplified expected size of PCR products indicating designed PCR primers for 16s rRNA indeed can be useful to amplify all different microbial water-borne pathogens in the water. Furthermore, to test whether these 16s rRNA based PCR primers can detect bacterial populations present in the water, water samples taken from diverse sources, such as river, tap, and sewage, were used for amplification. PCR products were for then subjected for cloning into a T-vector to generate a library containing 16s rRNA sequences from various bacteria. With cloned PCR products, RFLP analysis was done using PCR products digested with restriction enzyme such as Hae III to obtain species-specific RFLP profiles. After PCR-RFLP, the bacterial clones which showed the same RFLP profiles were regarded as the same ones, and the clones which showed distinctive RFLP profiles were subsequently subjected for sequence analysis for species identification. By this PCR-RFLP analysis, we were able to reveal diverse populations of bacteria living in water. In brief, in unsterilized natural river water, over 60 different species of bacteria were found. On the other hand, no PCR products were detected in drinking tap-water. The results from this study clearly indicate that the PCR-RFLP-sequence analysis can be a useful method for monitoring diverse, perhaps pathogenic bacteria contaminated in water in a rapid fashion.

• Asian Pacific Journal of Cancer Prevention
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• v.16 no.14
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• pp.5613-5618
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• 2015

Clinicians should looking for techniques that helps to early diagnosis of cancer, because early cancer detection is critical to increase survival and cost effectiveness of treatment, and as a result decrease mortality rate. Medical images are the most important tools to provide assistance. However, medical images have some limitations for optimal detection of some neoplasias, originating either from the imaging techniques themselves, or from human visual or intellectual capacity. Image processing techniques are allowing earlier detection of abnormalities and treatment monitoring. Because the time is a very important factor in cancer treatment, especially in cancers such as the lung and breast, imaging techniques are used to accelerate diagnosis more than with other cancers. In this paper, we outline experience in use of image processing techniques for lung and breast cancer diagnosis. Looking at the experience gained will help specialists to choose the appropriate technique for optimization of diagnosis through medical imaging.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.29 no.1A
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• pp.61-73
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• 2009

In this paper, hybrid health monitoring techniques using acceleration-impedance features are newly proposed to detect two damage-type in steel plate-girder bridges, which are girder's stiffness-loss and support perturbation. The hybrid techniques mainly consists of three sequential phases: 1) to alarm the occurrence of damage in global manner, 2) to classify the alarmed damage into subsystems of the structure, and 3) to estimate the classified damage in detail using methods suitable for the subsystems. In the first phase, the global occurrence of damage is alarmed by monitoring changes in acceleration features. In the second phase, the alarmed damage is classified into subsystems by recognizing patterns of impedance features. In the final phase, the location and the extent of damage are estimated by using modal strain energy-based damage index method and root mean square deviation (RMSD) method. The feasibility of the proposed hybrid technique is evaluated on a laboratory-scaled steel plate-girder bridge model for which hybrid acceleration-impedance signatures were measured for several damage scenarios. Also, the effect of temperature on the accuracy of the impedance-based damage monitoring results are experimentally examined from combined scenarios of support damage cases and temperature changes.