• Communications for Statistical Applications and Methods
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• v.21 no.1
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• pp.69-80
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• 2014

This paper considers the problem of monitoring the mean of a normally distributed process variable when the objective is to effectively detect both a sustained shift and a linear drift. The design and application of a generalized likelihood ratio (GLR) chart for simultaneously monitoring a sustained shift and a linear drift are evaluated. The GLR chart has the advantage that when we design this chart, we do not need to specify the size of the parameter change. The performance of the GLR chart is compared with that of other control charts, such as the standard cumulative sum (CUSUM) charts and the cumulative score (CUSCORE) charts. And we compare the proposed GLR chart with the GLR charts designed for monitoring only a sustained shift and for monitoring only a linear drift. Finally, we also compare the proposed GLR chart with the chart combinations. We show that the proposed GLR chart has better overall performance for a wide range of shift sizes and drift rates relative to other control charts, when a special cause produces a sustained shift and/or a linear drift in the process mean.

• Geosciences Journal
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• v.22 no.6
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• pp.1041-1052
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• 2018

A single-well push-drift-pull tracer test using two different tracers ($SF_6$ and salt) was performed at the Environmental Impact Test (EIT) site to determine suitable locations for monitoring wells and arrange them prior to artificial $CO_2$ injection and leak tests. Local-scale estimates of hydraulic properties (linear groundwater velocity and effective porosity) were obtained at the study site by the tracer test with two tracers. The mass recovery percentage of the volatile tracer ($SF_6$) was lower than that of the non-volatile tracer (salt) and increased drift time may make degassing of $SF_6$ intensified. The $CO_2$ leakage monitoring results for both unsaturated and saturated zones suggest that the $CO_2$ monitoring points should be located near points at which a high concentration gradient is expected. Based on the estimated hydraulic properties and tracer mass recovery rates, an optimal $CO_2$ monitoring network including boreholes for monitoring the unsaturated zone was constructed at the study site.

• Smart Structures and Systems
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• v.24 no.5
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• pp.649-657
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• 2019

Recently, an advanced video deflectometer based on the principle of off-axis digital image correlation was presented and advocated for remote and real-time deflection monitoring of large engineering structures. In engineering practice, measurement accuracy is one of the most important technical indicators of the video deflectometer. However, it has been observed in many outdoor experiments that data drift often presents in the measured deflection-time curves, which is caused by the instability of imaging system and the unavoidable influences of ambient interferences (e.g., ambient light changes, ambient temperature variations as well as ambient vibrations) in non-laboratory conditions. The non-ideal unstable imaging conditions seriously deteriorate the measurement accuracy of the video deflectometer. In this work, to perform high-accuracy deflection monitoring, potential sources for the drift error are analyzed, and a drift error model is established by considering these error sources. Based on this model, a simple, easy-to-implement yet effective reference point compensation method is proposed for real-time removal of the drift error in measured deflections. The practicality and effectiveness of the proposed method are demonstrated by in-situ deflection monitoring of railway and highway bridges.

• Structural Monitoring and Maintenance
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• v.5 no.1
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• pp.111-127
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• 2018

Horizontal displacement of high-rise building is an essential index for assessing the structural performance and safety. In this paper, a novel inclinometer-based method is proposed to address this issue and an algorithm based on three spline interpolation principle is presented to estimate the horizontal displacement of high-rise buildings. In this method, the whole structure is divided into different elements by different measured points. The story drift angle curve of each element is modeled as a three spline curve. The horizontal displacement can be estimated after integration of the story drift angle curve. A numerical example is designed to verify the proposed method and the result shows this method can effectively estimate the horizontal displacement with high accuracy. After that, this method is applied to a practical slender structure - Shanghai Tower. Nature frequencies identification and deformation monitoring are conducted from the signal of inclinometers. It is concluded that inclinometer-based technology can not only be used for spectrum analysis and modal identification, but also for monitoring deformation of the whole structure. This inclinometer-based technology provides a novel method for future structural health monitoring.

• Korean Journal of Fisheries and Aquatic Sciences
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• v.31 no.2
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• pp.202-209
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• 1998

A three-dimensional numerical method based on the Green's integral equation is developed to predict the motion response and drift force in waves for the ocean monitoring facilities. In this method, we use source and doublet distribution, and triangular and rectangular eliments. To eliminate the irregular frequency phenomenon, the method of improved integral equation is applied and the time-mean drift force is calculated by the method of direct pressure integration over the body surface. To conform the validity of the present numerical method, some calculations for the floating sphere are performed and it is shown that the present method provides sufficiently reliable results. As a calculation example for the real facilities, the motion response and the drift force of the vertical cylinder type ocean monitoring buoy with 2.6 m diameter and 3,77 m draft are calculated and discussed. The obtained results of motion response can be used to determine the shape and dimension of the buoy to reduce the motion response, and other data such as the effect of motion reduction due to a damper can be predictable through these motion calculations. Also, the calculation results of drift force can be used in the design procedure of mooring system to predict the maximum wave load acting on the mooring system. The present method has, in principle, no restriction in the application to the arbitrary shape facilities. So, this method can be a robust tool for the design, installation, and operation of various kinds of the floating-type ocean monitoring facilities.

• Biomedical Engineering Letters
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• v.8 no.4
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• pp.365-371
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• 2018

Uninterrupted monitoring of multiple subjects is required for mass causality events, in hospital environment or for sports by medical technicians or physicians. Movement of subjects under monitoring requires such system to be wireless, sometimes demands multiple transmitters and a receiver as a base station and monitored parameter must not be corrupted by any noise before further diagnosis. A Bluetooth Piconet network is visualized, where each subject carries a Bluetooth transmitter module that acquires vital sign continuously and relays to Bluetooth enabled device where, further signal processing is done. In this paper, a wireless network is realized to capture ECG of two subjects performing different activities like cycling, jogging, staircase climbing at 100 Hz frequency using prototyped Bluetooth module. The paper demonstrates removal of baseline drift using Fast Fourier Transform and Inverse Fast Fourier Transform and removal of high frequency noise using moving average and S-Golay algorithm. Experimental results highlight the efficacy of the proposed work to monitor any vital sign parameters of multiple subjects simultaneously. The importance of removing baseline drift before high frequency noise removal is shown using experimental results. It is possible to use Bluetooth Piconet frame work to capture ECG simultaneously for more than two subjects. For the applications where there will be larger body movement, baseline drift removal is a major concern and hence along with wireless transmission issues, baseline drift removal before high frequency noise removal is necessary for further feature extraction.

• Smart Structures and Systems
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• v.15 no.3
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• pp.881-896
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• 2015

The authors' research group has developed a noncontact type of sensors which directly measure the inter-story drift displacements of a building during a seismic event. Soon after that event, such seismically-induced drift displacement data would provide structural engineers with useful information to judge how the stories have been damaged. This paper presents a scheme of estimating the story cumulative plastic deformation ratios based on such measured drift displacement information toward the building safety monitoring. The presented scheme requires the data of story drift displacements and the ground motion acceleration. The involved calculations are rather simple without any detailed information on structural elements required: the story hysteresis loops are first estimated and then the cumulative plastic deformation ratio of each story is evaluated from the estimated hysteresis. The effectiveness of the scheme is demonstrated by utilizing the data of full-scale building model experiment performed at E-defense and conducting numerical simulations.

• Journal of the Korean Society for Marine Environment & Energy
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• v.1 no.1
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• pp.102-111
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• 1998

Ocean monitoring facilities are divided into two types, fixed type and floating type. This paper deals with wane load calculation and mooring system for a floating monitoring facility. Wave load and drift forces are calculated for an example case of floating monitoring buoy To enlarge holding power of anchor, circular pile model test was performed. A program for horizontal force of circular pile in sand was made and the calculated result showed fairy good agreement with the result of model test. It is expected that this method will provide good estimation for the holding power of the prototype of circular pile anchor which is relied upon SCUBA activity for installation.

• Journal of Magnetics
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• v.19 no.2
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• pp.151-154
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• 2014

Recent years have seen an increasing range of planar Hall resistive (PHR) sensor applications in the field of magnetic sensing. This study describes a new application of the PHR sensor to monitor a current. Initially, thermal drift experiments of the PHR sensor are performed, to determine the accuracy of the PHR signal output. The results of the thermal drift experiments show that there is no considerable drift in the signals attained from 0.1, 0.5, 1 and 2 mA current. Consequently, the PHR sensor provides adequate accuracy of the signal output, to perform the current monitoring experiments. The performances of the PHR sensor with bilayer and trilayer structures are then tested. The minimum detectable currents of the PHR sensor using bilayer and trilayer structures are $0.51{\mu}A$ and 54 nA, respectively. Therefore, the PHR sensor having trilayer structure is the better choice to detect ultra low current of few tens nanoampere.

• International conference on construction engineering and project management
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• 2022.06a
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• pp.814-822
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• 2022

The deployment of sensors for Structural Health Monitoring requires a complicated network arrangement, ground truthing, and calibration for validating sensor performance periodically. Any conventional sensor on a structural element is also subjected to static and dynamic vertical loadings in conjunction with other environmental factors, such as brightness, noise, temperature, and humidity. A structural model with strain gauges was built and tested to get realistic sensory information. This paper investigates different deep learning architectures and algorithms, including unsupervised, autoencoder, and supervised methods, to benchmark blind drift calibration methods using deep learning. It involves a fully connected neural network (FCNN), a long short-term memory (LSTM), and a gated recurrent unit (GRU) to address the blind drift calibration problem (i.e., performing calibrations of installed sensors when ground truth is not available). The results show that the supervised methods perform much better than unsupervised methods, such as an autoencoder, when ground truths are available. Furthermore, taking advantage of time-series information, the GRU model generates the most precise predictions to remove the drift overall.