• Earthquakes and Structures
• /
• v.25 no.1
• /
• pp.69-78
• /
• 2023

Life-cycle performance analysis of a reinforced concrete box section bridge was generated. Moreover, Monte Carlo simulation with important sampling (IS) was used to simulate the bridge material and load uncertainties. The bridge deterioration model was generated with the basic probabilistic principles and updated according to the measurement data. A genetic algorithm (GA) with the response surface model (RSM) was used to determine the deterioration rate. The importance of health monitoring systems to sustain the bridge to give services economically and reliably and the advantages of fiber-optic sensors for SHM applications were discussed in detail. This study showed that the most effective loss of strength in reinforced concrete box section bridges is corrosion of the reinforcements. Due to reinforcement corrosion, the use of the bridge, which was examined, could not meet the desired strength performance in 25 years, and the need for reinforcement. In addition, it has been determined that long-term health monitoring systems are an essential approach for bridges to provide safe and economical service. Moreover the use of fiber optic sensors has many advantages because of the ability of the sensors to be resistant to environmental conditions and to make sensitive measurements.

• Structural Engineering and Mechanics
• /
• v.26 no.5
• /
• pp.499-516
• /
• 2007

An experimental method denoted as Impulse Method is proposed as a cost-effective non-destructive technique for the on-site evaluation of concrete elastic modulus in existing structures: on the basis of Hertz's quasi-static theory of elastic impact and with the aid of a simple portable testing equipment, it makes it possible to collect series of local measurements of the elastic modulus in an easy way and in a very short time. A Hypothesis Testing procedure is developed in order to provide a statistical tool for processing the data collected by means of the Impulse Method and assessing the possible occurrence of significant variations in the elastic modulus without exceeding some prescribed error probabilities. It is based on a particular formulation of the renowned sequential probability ratio test and reveals to be optimal with respect to the error probabilities and the required number of observations, thus further improving the time-effectiveness of the Impulse Method. The results of an experimental investigation on different types of plain concrete prove the validity of the Impulse Method in estimating the unknown value of the elastic modulus and attest the effectiveness of the proposed Hypothesis Testing procedure in identifying significant variations in the elastic modulus.

• Proceedings of the KIEE Conference
• /
• 2005.10b
• /
• pp.273-275
• /
• 2005

Active thermography is being used since several years for remote non-destructive testing. It provides thermal images for remote detection and imaging of damages. Also, it is based on propagation and reflection of thermal waves which are launched from the surface into the inspected component by absorption of modulated radiation. For energy deposition, it use external heat sources (e.g., halogen lamp or convective heating) or internal heat generation (e.g., microwaves, eddy current, or elastic wave). Among the external heat sources, the ultrasound is generally used for energy deposition because of defect selective heating up. The heat source generating a thermal wave is provided by the defect itself due to the attenuation of amplitude modulated ultrasound. A defect causes locally enhanced losses and consequently selective heating up. Therefore amplitude modulation of the injected ultrasonic wave turns a defect into a thermal wave transmitter whose signal is detected at the surface by thermal infrared camera. This way ultrasound thermography(UT) allows for selective defect detection which enhances the probability of defect detection in the presence of complicated intact structures. In this paper the applicability of UT for fast defect detection is described. Examples are presented showing the detection of defects in PCB material. Measurements were performed on various kinds of typical defects in PCB materials (both Cu metal and non-metal epoxy). The obtained thermal image reveals area of defect in row of thick epoxy material and PCB.

• Proceedings of the Korean Geotechical Society Conference
• /
• 2009.03a
• /
• pp.673-676
• /
• 2009

Non-point pollutants, which mainly originate from high traffic roads and rural areas, contaminate the environment by flowing into various rivers and lakes and thus are of interest as an environmental issue. Accordingly, efforts have been made to design and maintain efficient filter systems for the control of the non-point pollutants. Meanwhile, clay-type materials are widely used for the absorption of chemicals included in pollutants and the absorption performances of various clays have been reported in the literature. Thus, the present study proposes a non-destructive monitoring method for the performance of a clay-type filter using electrical resistivity measurement. A series of experimental tests is performed on celite-based particulate filters with infiltrating non-point source pollutants having the same characteristics as pollutants on high traffic roads. Each test measures permeability, resistivity of the filter materials and resistivity of the filtrated water. As the particulate filter materials filtrate pollutants and absorb heavy chemicals (e.g., $Cr^{6+}$, lead, nickel, among others), ionic concentration increases resulting as the electrical resistivity decrease. When the filter systems approach the end of their lifetime, the electrical resistivity of the filter material converges to a very low value due to lowered filter absorption efficiency. Hence, the electrical resistivity of the filtrated water also converges to a low value due to high concentrations of heavy metals. The permeability converges to a very low value because of significantly reduced porosity due to clogging and absorption of pollutants on the filter material. The experimental results show that electrical resistivity monitoring of filter materials is a promising approach to estimation of filter performance and its life expectancy.

• Journal of Forest and Environmental Science
• /
• v.30 no.4
• /
• pp.351-361
• /
• 2014

Leaf area ($A_0$) and leaf biomass ($M_0$) estimation are significant prerequisites to studying tree physiological processes and modeling in the forest ecosystem. The objective of this study was to develop allometric models for estimating $A_0$ and $M_0$ of Swietenia mahagoni L. from different tree parameters such as DBH and tree height of mahogany plantations in the northeastern region of Bangladesh. A total of 850 healthy and well formed trees were selected randomly for sampling in the five study sites. Then, twenty two models were developed based on different statistical criteria that propose reliable and accurate models for estimating the $A_0$ and $M_0$ using non-destructive measurements. The results exposed that model iv and xv were selected on a single predictor of DBH and showed more statistically accuracy than other models. The selected models were also validated with an additional test data set on the basis of linear regression and t-test for mean difference between observed and predicted values. After that, a comparison between the best logarithmic and non-linear allometric model shows that the non-linear model produces systematic biases and underestimates $A_0$ and $M_0$ for larger trees. As a result, it showed that the bias-corrected logarithmic model iv and xv can be used to help quantify forest structure and functions, particularly valuable in future research for estimating $A_0$ and $M_0$ of S. mahagoni in this region.

• Journal of Animal Science and Technology
• /
• v.66 no.1
• /
• pp.31-56
• /
• 2024

Pig farming, a vital industry, necessitates proactive measures for early disease detection and crush symptom monitoring to ensure optimum pig health and safety. This review explores advanced thermal sensing technologies and computer vision-based thermal imaging techniques employed for pig disease and piglet crush symptom monitoring on pig farms. Infrared thermography (IRT) is a non-invasive and efficient technology for measuring pig body temperature, providing advantages such as non-destructive, long-distance, and high-sensitivity measurements. Unlike traditional methods, IRT offers a quick and labor-saving approach to acquiring physiological data impacted by environmental temperature, crucial for understanding pig body physiology and metabolism. IRT aids in early disease detection, respiratory health monitoring, and evaluating vaccination effectiveness. Challenges include body surface emissivity variations affecting measurement accuracy. Thermal imaging and deep learning algorithms are used for pig behavior recognition, with the dorsal plane effective for stress detection. Remote health monitoring through thermal imaging, deep learning, and wearable devices facilitates non-invasive assessment of pig health, minimizing medication use. Integration of advanced sensors, thermal imaging, and deep learning shows potential for disease detection and improvement in pig farming, but challenges and ethical considerations must be addressed for successful implementation. This review summarizes the state-of-the-art technologies used in the pig farming industry, including computer vision algorithms such as object detection, image segmentation, and deep learning techniques. It also discusses the benefits and limitations of IRT technology, providing an overview of the current research field. This study provides valuable insights for researchers and farmers regarding IRT application in pig production, highlighting notable approaches and the latest research findings in this field.

• Computers and Concrete
• /
• v.6 no.3
• /
• pp.225-234
• /
• 2009

Dredged silt from reservoirs in southern Taiwan was sintered to make lightweight aggregates (LWA), which were then used to produce lightweight aggregate concrete (LWAC).This study aimed to assess the compressive strength and homogeneity of LWAC using ultrasonic-echo sensing. Concrete specimens were prepared using aggregates of four different particle density, namely 800, 1100, 1300 and 2650 kg/$m^3$. The LWAC specimens were cylindrical and a square wall with core specimens drilled. Besides compressive strength test, ultrasonic-echo sensing was employed to examine the ultrasonic pulse velocity and homogeneity of the wall specimens and to explore the relationship between compressive strength and ultrasonic pulse velocity. Results show that LWA, due to its lower relative density, causes bloating, thus resulting in uneven distribution of aggregates and poor homogeneity. LWAC mixtures using LWA of particle density 1300 kg/$m^3$ show the most even distribution of aggregates and hence best homogeneity as well as highest compressive strength of 63.5 MPa. In addition, measurements obtained using ultrasonic-echo sensing and traditional ultrasonic method show little difference, supporting that ultrasonic-echo sensing can indeed perform non-destructive, fast and accurate assessment of LWAC homogeneity.

• Journal of Korean Society for Atmospheric Environment
• /
• v.5 no.2
• /
• pp.21-29
• /
• 1989

The metals present in atmospheric particulate come from various sources; natural or anthropogenic. Among various metals Fe, Zn, Pb, Cu, and Mn are of particular concern in as much as they are not only present in large quantity, but toxic to human body. A simple, fast, and non-destructive analytical method for these metals in atmospheric particulate was developed and the analytical details were described herein. The method involves the measurements of X-ray fluorescence of sample contained in filters and comparing it with those for standards. The standard filters were prepared by applicating premeasured standard solution to the filters and then drying. The accuracy of the method was tested by analyzing standard reference materials and by independently analyzing samples using a different, previously accuracy-proven method, inductively coupled plasma atomic emission spectrometry, and comparing the results obtained. Analytical sensitivities and detection limits of the present method were 62.9, 178.2, 82.9, 146.1, 37.2, 120.3 cps/$\mug/cm^2$ and 39.0 35.6, 137.5, 125.9, 182.6, 72.8 $ng/cm^2$ for Fe, Zn, Pb, Cu, Mn, and Ni respectively. The method was applied to Seoul atmospheric particulate and some results were reported.

• Structural Engineering and Mechanics
• /
• v.54 no.2
• /
• pp.199-219
• /
• 2015

This paper presents the non-destructive evaluation of a high-speed railway bridge using train-induced strain responses. Based on the train-track-bridge interaction analysis, the strain responses of a high-speed railway bridge under moving trains with different operation status could be calculated. The train induced strain responses could be divided into two parts: the force vibration stage and the free vibration stage. The strain-displacement relationship is analysed and used for deriving critical displacements from theoretical stain measurements at a forced vibration stage. The derived displacements would be suitable for the condition assessment of the bridge through design specifications defined indexes and would show certain limits to the practical application. Thus, the damage identification of high-speed railways, such as the stiffness degradation location, needs to be done by comparing the measured strain response under moving trains in different states because the vehicle types of high-speed railway are relatively clear and definite. The monitored strain responses at the free vibration stage, after trains pass through the bridge, would be used for identifying the strain modes. The relationship between and the degradation degree and the strain mode shapes shows certain rules for the widely used simply supported beam bridges. The numerical simulation proves simple and effective for the proposed method to locate and quantify the stiffness degradation.

• Journal of the Optical Society of Korea
• /
• v.13 no.2
• /
• pp.245-250
• /
• 2009

We propose a digital holographic interference analysis method based on a 2-frame phase-shifting technique for measuring an optical mirror surface. The technique using 2-frame phase-shifting digital interferometry is more efficient than multi-frame phase-shifting techniques because the 2-frame method has the advantage of a reduced number of interferograms, and then takes less time to acquire the wanted topography information from interferograms. In this measurement system, 2-frame phase-shifting digital interferograms are acquired by moving the reference flat mirror surface, which is attached to a piezoelectric transducer, with phase step of 0 or $\pi$/2 in the reference beam path. The measurements are recorded on a CCD detector. The optical interferometry is designed on the basis of polarization characteristics of a polarizing beam splitter. Therefore the noise from outside turbulence can be decreased. The proposed 2-frame algorithm uses the relative phase difference of the neighbor pixels. The experiment has been carried out on an optical mirror which flatness is less than $\lambda$/4. The measurement of the optical mirror surface topography using 2-frame phase-shifting interferometry shows that the peak-to-peak value is calculated to be about $0.1779{\mu}m$, the root-mean-square value is about $0.034{\mu}m$. Thus, the proposed method is expected to be used in nondestructive testing of optical components.