• Structural Monitoring and Maintenance
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• v.5 no.1
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• pp.51-65
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• 2018

A number of sensing techniques have been implemented for detecting defects in civil infrastructures instead of onsite human inspections in structural health monitoring. However, the issue of faults in sensors has not received much attention. This issue may lead to incorrect interpretation of data and false alarms. To overcome these challenges, this article presents a deep learning-based method with a new architecture of Stateful Long Short Term Memory Neural Networks (S-LSTM NN) for detecting sensor fault without going into details of the fault features. As LSTMs are capable of learning data features automatically, and the proposed method works without an accurate mathematical model. The detection of four types of sensor faults are studied in this paper. Non-stationary acceleration responses of a three-span continuous bridge when under operational conditions are studied. A deep network model is applied to the measured bridge data with estimation to detect the sensor fault. Another set of sensor output data is used to supervise the network parameters and backpropagation algorithm to fine tune the parameters to establish a deep self-coding network model. The response residuals between the true value and the predicted value of the deep S-LSTM network was statistically analyzed to determine the fault threshold of sensor. Experimental study with a cable-stayed bridge further indicated that the proposed method is robust in the detection of the sensor fault.

• Journal of Biomedical Engineering Research
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• v.29 no.4
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• pp.278-285
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• 2008

In this study the complex-valued continuous wavelet transform (CWT) has been applied in detection of Electrocardiograms (ECG) as response to various signal classification methods such as Fourier transforms and other tools of time frequency analysis. Experiments have shown that CWT may serve as a detector of non-stationary signal changes as ECG. The tested signal is corrupted by short time events. We applied CWT to detect short-time event and the result image representation of the signal has showed us that one can easily find the discontinuity at the time scale representation. Analysis of ECG signal using complex-valued continuous wavelet transform is the first step to detect possible changes and alternans. In the second step, modulus and phase must be thoroughly examined. Thus, short time events in the ECG signal, and other important characteristic points such as frequency overlapping, wave onsets/offsets extrema and discontinuities even inflection points are found to be detectable. We have proved that the complex-valued CWT can be used as a powerful detector in ECG signal analysis.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.20 no.2
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• pp.153-159
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• 2010

This work focuses on finding a method to reduce the noise of a hermetic reciprocating compressor during start-up using an acoustical analysis. The noise of compressor during start-up, which is a higher level than that of a normal operating condition, has transient and non-stationary characteristics. The acoustical analysis of compressor cavity is performed to find an effective method to reduce the noise level. In the acoustical analysis, the shape variations of frequency response function in the neighborhood of resonances are tested for three parameters: the height of remained oil, the suction position of refrigerant and the position of driving part. As a conclusion of this result, to reduce the emission noise of compressor during start-up, the height of remained oil should be kept at 16 mm, the refrigerant should be sucked at the cross point of nodal lines of X and Y directional cavity modes, and the driving part should be positioned in the center of cavity.

• Journal of the Earthquake Engineering Society of Korea
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• v.17 no.4
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• pp.187-195
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• 2013

In this paper, firstly, acceleration-time histories were generated by varying strong motion duration in the frequency domain for application to a seismically isolated nuclear power structure, so as to examine the effects of strong motion duration on the behavior of the structure. Secondly, real recorded earthquakes were modified to match the target response spectrum based on the revised SRP 3.7.1(2007) and the modified time histories were applied to the analysis of a seismically isolated nuclear power structure. The obtained values of acceleration and displacement responses of the structure were, finally, compared with the values obtained in case of applying acceleration-time histories generated in the frequency domain to the structure.

• Journal of the Korea Institute of Military Science and Technology
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• v.5 no.2
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• pp.169-184
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• 2002

In order to extract bearing information from the directional sensors of DIFAR(directional frequency analysis and recording) that is a kind of passive sonobuoy, the cardioid beamforming algorithm applicable to DIFAR system was studied in the frequency domain. the algorithm uses narrow-band signals propagated though the media from the acoustic sources such as ship machineries. The proposed algorithm is expected to give signal to noise ratio of 6dB when it uses the maximum response axis(MRA) among the Cardioid beams. The estimated bearings agree very well with those from GPS data. Assuming the bearings from GPS data to be real values, the estimation errors are analyzed statistically. The histogram of estimation errors in each frequency have Gaussian shape, the mean and standard deviation dropping in the ranges -1.1~$6.7^{\circ}$ and 13.3~$43.6^{\circ}$, respectively. Estimation errors are caused by SMR degradation due to propagation loss between the source and receiver, daily fluctuating geo-magnetic fields, and non-stationary background noises. If multiple DIFAR systems are employed, in addition to bearing, range information could be estimated and finally localization or tracking of a target is possible.

• Structural Engineering and Mechanics
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• v.38 no.1
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• pp.39-63
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• 2011

Referring to the formulation of physical stochastic optimal control of structures and the scheme of optimal polynomial control, a nonlinear stochastic optimal control strategy is developed for a class of structural systems with hysteretic behaviors in the present paper. This control strategy provides an amenable approach to the classical stochastic optimal control strategies, bypasses the dilemma involved in It$\hat{o}$-type stochastic differential equations and is applicable to the dynamical systems driven by practical non-stationary and non-white random excitations, such as earthquake ground motions, strong winds and sea waves. The newly developed generalized optimal control policy is integrated in the nonlinear stochastic optimal control scheme so as to logically distribute the controllers and design their parameters associated with control gains. For illustrative purposes, the stochastic optimal controls of two base-excited multi-degree-of-freedom structural systems with hysteretic behavior in Clough bilinear model and Bouc-Wen differential model, respectively, are investigated. Numerical results reveal that a linear control with the 1st-order controller suffices even for the hysteretic structural systems when a control criterion in exceedance probability performance function for designing the weighting matrices is employed. This is practically meaningful due to the nonlinear controllers which may be associated with dynamical instabilities being saved. It is also noted that using the generalized optimal control policy, the maximum control effectiveness with the few number of control devices can be achieved, allowing for a desirable structural performance. It is remarked, meanwhile, that the response process and energy-dissipation behavior of the hysteretic structures are controlled to a certain extent.

• Smart Structures and Systems
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• v.16 no.4
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• pp.579-591
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• 2015

This paper investigates a magnetoelectric (ME) vibration energy harvester that can scavenge energy in arbitrary directions in a plane as well as wide working bandwidth. In this harvester, a circular cross-section cantilever rod is adopted to extract the external vibration energy due to the capability of it's free end oscillating in arbitrary in-plane directions. And permanent magnets are fixed to the free end of the cantilever rod, causing it to experience a non-linear force as it moves with respect to stationary ME transducers and magnets. The magnetically coupled cantilever rod exhibits a nonlinear and two-mode motion, and responds to vibration over a much broader frequency range than a standard cantilever. The effects of the magnetic field distribution and the magnetic force on the harvester's voltage response are investigated with the aim to obtain the optimal vibration energy harvesting performances. A prototype harvester was fabricated and experimentally tested, and the experimental results verified that the harvester can extract energy from arbitrary in-plane directions, and had maximum bandwidth of 5.5 Hz, and output power of 0.13 mW at an acceleration of 0.6 g (with $g=9.8ms^{-2}$).

• Journal of Korean Society of Coastal and Ocean Engineers
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• v.31 no.2
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• pp.73-87
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• 2019

Ocean waves are the driving force for the sediment transport and the beach process. However, wave actions are nonlinear and non-stationary, and the response of the beach is inconsistent in terms of reaction rate and magnitude. Therefore, the beach process is difficult to predict accurately. The purpose of this study is to identify the correlations between the shoreline change and ocean waves observed in the east coast of Korea. The relation of the beach width obtained from video monitoring at five sandy beaches and the wave data obtained from nearby wave monitoring at three points was analyzed. Although the correlations estimated over the whole data sets was not significant, the correlations estimated based on the seasonal period or wave conditions provided more noteworthy information. When the non-exceedance probability of the wave height was greater than 0.99, the wave period and beach width showed strong negative correlations. In case the non-exceedance probability of the wave period was greater than 0.99, the wave height and beach width showed strong negative correlations as well. Furthermore, the erosion rate of the beach width increased when the primary wave direction was close to normal to the coastline. Little significant seasonal or monthly change was found between the beach width and the wave, but it was greatly affected by intensive events such as typhoons. Thus, it is necessary to analyze in detail the wave height or period level explaining the change of beach width for more relevant and practical information.

• Journal of Veterinary Clinics
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• v.36 no.1
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• pp.7-14
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• 2019

In South Korea, six large outbreaks of highly pathogenic avian influenza (HPAI) have occurred since the first confirmation in 2003 from chickens. For the past 15 years, HPAI outbreaks have become an annual phenomenon throughout the country and has extended to wider regions, across rural and urban environments. An understanding of the spatial epidemiology of HPAI occurrence is essential in assessing and managing the risk of the infection; however, local spatial variations of relationship between HPAI incidences in Korea and related risk factors have rarely been derived. This study examined whether spatial heterogeneity exists in this relationship, using a geographically weighted Poisson regression (GWPR) model. The outcome variable was the number of HPAI-positive farms at 252 Si-Gun-Gu (administrative boundaries in Korea) level notified to government authority during the period from January 2014 to April 2016. This response variable was regressed to a set of sociodemographic and topographic predictors, including the number of wild birds infected with HPAI virus, the number of wintering birds and their species migrated into Korea, the movement frequency of vehicles carrying animals, the volume of manure treated per day, the number of livestock farms, and mean elevation. Both global and local modeling techniques were employed to fit the model. From 2014 to 2016, a total of 403 HPAI-positive farms were reported with high incidence especially in western coastal regions, ranging from 0 to 74. The results of this study show that local model (adjusted R-square = 0.801, AIC = 954.5) has great advantages over corresponding global model (adjusted R-square = 0.408, AIC = 2323.1) in terms of model fitting and performance. The relationship between HPAI incidence in Korea and seven predictors under consideration were significantly spatially non-stationary, contrary to assumptions in the global model. The comparison between global Poisson and GWPR results indicated that a place-specific spatial analysis not only fit the data better, but also provided insights into understanding the non-stationarity of the associations between the HPAI and associated determinants. We demonstrated that an empirically derived GWPR model has the potential to serve as a useful tool for assessing spatially varying characteristics of HPAI incidences for a given local area and predicting the risk area of HPAI occurrence. Considering the prominent burden of HPAI this study provides more insights into spatial targeting of enhanced surveillance and control strategies in high-risk regions against HPAI outbreaks.

• Journal of Korea Water Resources Association
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• v.54 no.12
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• pp.1317-1328
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• 2021

This study aims to provide a predictive model based on climate models for simulating continuous daily rainfall sequences by combining bias-correction and spatio-temporal downscaling approaches. For these purposes, this study proposes a combined modeling system by applying conditional Copula and Multisite Non-stationary Hidden Markov Model (MNHMM). The GloSea5 system releases the monthly rainfall prediction on the same day every week, however, there are noticeable differences in the updated prediction. It was confirmed that the monthly rainfall forecasts are effectively updated with the use of the Copula-based bias-correction approach. More specifically, the proposed bias-correction approach was validated for the period from 1991 to 2010 under the LOOCV scheme. Several rainfall statistics, such as rainfall amounts, consecutive rainfall frequency, consecutive zero rainfall frequency, and wet days, are well reproduced, which is expected to be highly effective as input data of the hydrological model. The difference in spatial coherence between the observed and simulated rainfall sequences over the entire weather stations was estimated in the range of -0.02~0.10, and the interdependence between rainfall stations in the watershed was effectively reproduced. Therefore, it is expected that the hydrological response of the watershed will be more realistically simulated when used as input data for the hydrological model.