• Journal of the Korean Society for Nondestructive Testing
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• v.32 no.1
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• pp.47-55
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• 2012

A structural health monitoring technique for locating impact position in a plate structure is presented in this paper. The method employs a single sensor and spatial focusing of time reversal (TR) acoustics. We first examine the TR focusing effect at the impact position and its surroundings through simulation and experiment. The imaging results of impact points show that the impact source location can be accurately estimated in any position of the plate. Compared to existing techniques for locating impact or acoustic emission source, the proposed method has the benefits of using a single sensor and not requiring material properties and geometry of structures. Furthermore, it does not depend on a particular mode of dispersive Lamb waves that is frequently used in other ultrasonic testings of plate-like structures.

• Journal of Sensor Science and Technology
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• v.18 no.4
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• pp.294-300
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• 2009

Cardiopulmonary resuscitation(CPR) is performed by artificial ventilation and thoracic compression for the patient under emergent situation to maintain at least the minimum level of respiration and blood circulation for life survival. Quality of the pre-hospital CPR not only significantly affects the patient's survival rate but also minimizes side effects caused by CPR. Good quality CPR requires monitoring respiration, however, traditional respiratory air flow transducers cannot be used because the transducer elements are located on the flow axis. The present study developed a new technique with no physical object on the flow stream but enabling the air flow measurement and easily incorporated with the CPR devices. A turbulence chamber was formed in the middle of the respiratory tube by locally enlarging the cross-sectional area where the flow related turbulence was generated inducing energy loss which was in turn converted into pressure difference. The turbulence chamber was simply an empty enlarged air space, thus no physical object was placed on the flow stream, but still the flow rate could be evaluated. Both inspiratory and expiratory flows were obtained with symmetric measurement characteristics. Quadratic curve fitting provided excellent calibration formula with a correlation coefficient>0.999 (P<0.0001) and the mean relative error<1 %. The present results can be usefully applied to accurately monitor the air flow rate during CPR.

• Smart Structures and Systems
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• v.20 no.6
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• pp.683-696
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• 2017

In this study, the reliability of nonlinear ultrasonic modulation based fatigue crack detection is improved using a feature-level data fusion approach. When two ultrasonic inputs at two distinct frequencies are applied to a specimen with a fatigue crack, modulation components at the summation and difference of these two input frequencies appear. First, the spectral amplitudes of the modulation components and their spectral correlations are defined as individual features. Then, a 2D feature space is constructed by combining these two features, and the presence of a fatigue crack is identified in the feature space. The effectiveness of the proposed fatigue crack detection technique is experimentally validated through cyclic loading tests of aluminum plates, full-scale steel girders and a rotating shaft component. Subsequently, the improved reliability of the proposed technique is quantitatively investigated using receiver operating characteristic analysis. The uniqueness of this study lies in (1) improvement of nonlinear ultrasonic modulation based fatigue crack detection reliability using feature-level data fusion, (2) reference-free fatigue crack diagnosis without using the baseline data obtained from the intact condition of the structure, (3) application to full-scale steel girders and shaft component, and (4) quantitative investigation of the improved reliability using receiver operating characteristic analysis.

• Korean Journal of Fisheries and Aquatic Sciences
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• v.26 no.3
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• pp.205-213
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• 1993

The APHA-MPN procedure is the only officially accepted method for classifying shellfish growing areas in U. S. A. The method estimates the levels of fecal coliforms and E. coli, indicators of the sanitary quality of environmental waters. However, the MPN has several disadvantages requiring far more time, labor and expense for assay, as well as providing relatively poor precision. Several membrane filtration procedures have been developed to enumerate these indicators in waters. Of these, the mTEC technique has been shown to provide recoveries of fecal coliforms and E. coli comparable to those of the MPN method. In an abbreviated sanitary survey for Greenwich Bay in Rhode Island, U. S. A., classified as an approved shellfish growing area, the mTEC and conventional MPN methods were again compared for their recoveries of the indicator bacteria. It was found that the recoveries of fecal coliforms and E. coli provided by the mTEC technique are 1.08 and 1.27 times higher than those produced by MPN for water monitoring, respectively, and that the membrane filtration method appears to be a possible alternative to APHA-MPN.

• Smart Structures and Systems
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• v.6 no.5_6
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• pp.749-765
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• 2010

There are on-going efforts to utilize guided waves for structural damage detection. Active sensing devices such as lead zirconate titanate (PZT) have been widely used for guided wave generation and sensing. In addition, there has been increasing interest in adopting wireless sensing to structural health monitoring (SHM) applications. One of major challenges in wireless SHM is to secure power necessary to operate the wireless sensors. However, because active sensing devices demand relatively high electric power compared to conventional passive sensors such as accelerometers and strain gauges, existing battery technologies may not be suitable for long-term operation of the active sensing devices. To tackle this problem, a new wireless power transmission paradigm has been developed in this study. The proposed technique wirelessly transmits power necessary for PZT-based guided wave generation using laser and optoelectronic devices. First, a desired waveform is generated and the intensity of the laser source is modulated accordingly using an electro-optic modulator (EOM). Next, the modulated laser is wirelessly transmitted to a photodiode connected to a PZT. Then, the photodiode converts the transmitted light into an electric signal and excites the PZT to generate guided waves on the structure where the PZT is attached to. Finally, the corresponding response from the sensing PZT is measured. The feasibility of the proposed method for wireless guided wave generation has been experimentally demonstrated.

• Structural Engineering and Mechanics
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• v.78 no.5
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• pp.599-610
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• 2021

Early detection of small concrete crack or reinforcement corrosion is necessary for Structural Health Monitoring (SHM). Global vibration based methods are advantageous over local methods because of simple equipment installation and cost efficiency. Among vibration based techniques, FRF based methods are preferred over modal based methods. In this study, a new coupled method using frequency response function (FRF) and proper orthogonal modes (POM) is proposed by using the dynamic characteristic of a damaged beam. For the numerical simulation, wave finite element (WFE), coupled with traditional finite element (FE) method is used for effectively incorporating the damage related information and faster computation. As reported in literature, hybrid combination of wave function based wave finite element method and shape function based finite element method can addresses the mid frequency modelling difficulty as it utilises the advantages of both the methods. It also reduces the dynamic matrix dimension. The algorithms are implemented on a three-dimensional reinforced concrete beam. Damage is modelled and studied for two scenarios, i.e., crack in concrete and rebar corrosion. Single and multiple damage locations with different damage length are also considered. The proposed methodology is found to be very sensitive to both single- and multiple- damage while being computationally efficient at the same time. It is observed that the detection of damage due to corrosion is more challenging than that of concrete crack. The similarity index obtained from the damage parameters shows that it can be a very effective indicator for appropriately indicating initiation of damage in concrete structure in the form of spread corrosion or invisible crack.

• Journal of Internet Computing and Services
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• v.24 no.6
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• pp.145-153
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• 2023

This study emphasizes the essential need in the military for effective measurement and monitoring of soldiers' physical fitness, health, and exercise capabilities to enhance both their overall fitness and combat effectiveness. The effective assessment of physical fitness is considered a core element of management, aligning with principles of modern management. Particularly, preparing soldiers with robust physical fitness is deemed crucial for adapting to dynamic changes on the battlefield. In this research, the RFM (Recency, Frequency, Monetary) customer analysis and clustering methods, validated in e-commerce, are introduced as a basis for applying an AI-driven customer analysis approach to assess military personnel fitness. To achieve this, the study explores the incorporation of the RSC (Reveal, Sustainable, Control) analysis model. This model aims to effectively categorize and monitor military personnel fitness. The application of the RFM technique in the RSC analysis model quantifies and models military fitness, fostering continuous improvement and seeking strategies to enhance the effectiveness of fitness management. Through these methods, the study develops an AI customer analysis technique applied to the RSC clustering analysis method for improving and sustaining military personnel fitness.

• Structural Engineering and Mechanics
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• v.89 no.6
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• pp.589-599
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• 2024

This study presents the usability of the high-rate single-frequency Precise Point Positioning (SF-PPP) technique based on 20 Hz Global Positioning Systems (GPS)-only observations in detecting dynamic motions. SF-PPP solutions were obtained from post-mission and real-time GNSS corrections. These include the International GNSS Service (IGS)-Final, IGS real-time (RT), real-time MADOCA (Multi-GNSS Advanced Demonstration tool for Orbit and Clock Analysis), and real-time products from the Australian/New Zealand satellite-based augmentation systems (SBAS, known as SouthPAN). SF-PPP results were compared with LVDT (Linear Variable Differential Transformer) sensor and single-frequency relative positioning (SF-RP) solutions. The findings show that the SF-PPP technique successfully detects the harmonic motions, and the real-time products-based PPP solutions were as accurate as the final post-mission products. In the frequency domain, all GNSS-based methods evaluated in this contribution correctly detect the dominant frequency of short-term harmonic oscillations, while the differences in the amplitude values corresponding to the peak frequency do not exceed 1.1 mm. However, evaluations in the time domain show that SF-PPP needs high-pass filtering to detect accurate displacement since SF-PPP solutions include trends and low-frequency fluctuations, mainly due to atmospheric effects. Findings obtained in the time domain indicate that final, real-time, and MADOCA-based PPP results capture short-term dynamic behaviors with an accuracy ranging from 3.4 mm to 8.5 mm, and SBAS-based PPP solutions have several times higher RMSE values compared to other methods. However, after high-pass filtering, the accuracies obtained from PPP methods decreased to a few mm. The outcomes demonstrate the potential of the high-rate SF-PPP method to reliably monitor structural and earthquake-induced ground motions and vibration frequencies of structures.

• Journal of Korean Society of Steel Construction
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• v.17 no.6 s.79
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• pp.681-688
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• 2005

This study investigates an existing steel plate girder railroad bridge after superstructure rehabilitation to monitor static and dynamic responses using Fiber Bragg Grating (FBG) sensors. This paper also presents an experimental technique to estimate the vertical deflection of the bridge using FBG sensors. Seven FBG sensors are multiplexed in a single optical fiber and installed in parallel pairs along the length of the bridge, with one set at the top flange and the other at the bottom flange. In addition to FBG sensors, a conventional electric strain gauge and anLVDT are installed at the mid-span of the bridge for comparison. A test train consisting of one locomotive is placed at the center of the bridge to produce the maximum static effect. The train is also made to pass over the bridge at different speeds ranging from 10 km/h to 90 km/h to monitor the dynamic response of the bridge. This study demonstrates that the measured strains using the FBG sensor compared well with the readings from the electric strain gauge. The results show that the proposed instrumentation technique is capable of estimating the vertical deflection of the bridge for various loading conditions, which is crucial in structural health monitoring. Several dynamic characteristics of the bridge were also identified.

• The Journal of the Korea institute of electronic communication sciences
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• v.18 no.5
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• pp.785-796
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• 2023

In this study, a methodology for real-time classification and prediction of defects that may appear in PVDF(Polyvinylidene fluoride) sensors, which are widely used for structural integrity monitoring, is proposed. The types of sensor defects appearing according to the sensor attachment environment were classified, and an impact test using an impact hammer was performed to obtain an output signal according to the defect type. In order to cleary identify the difference between the output signal according to the defect types, the time domain statistical features were extracted and a data set was constructed. Among the machine learning based classification algorithms, the learning of the acquired data set and the result were analyzed to select the most suitable algorithm for detecting sensor defect types, and among them, it was confirmed that the highest optimization was performed to show SVM(Support Vector Machine). As a result, sensor defect types were classified with an accuracy of 92.5%, which was up to 13.95% higher than other classification algorithms. It is believed that the sensor defect prediction technique proposed in this study can be used as a base technology to secure the reliability of not only PVDF sensors but also various sensors for real time structural health monitoring.