• Structural Engineering and Mechanics
• /
• v.80 no.5
• /
• pp.563-583
• /
• 2021

Composite materials, composed of multiple constituent materials with dissimilar properties, are actively adopted in a wide range of industrial sectors due to their remarkable strength-to-weight and stiffness-to-weight ratio. Nevertheless, the failure mechanism of composite materials is highly complicated due to their sophisticated microstructure, making it much harder to predict their residual material lives in real life applications. A promising solution for this safety issue is structural damage detection. In the present paper, damage detection of composite material via electrical resistance-based technique and infrared thermography is reviewed. The operating principles of the two damage detection methodologies are introduced, and some research advances of each techniques are covered. The advancement of IR thermography-based non-destructive technique (NDT) including optical thermography, laser thermography and eddy current thermography will be reported, as well as the electrical impedance tomography (EIT) which is a technology increasingly drawing attentions in the field of electrical resistance-based damage detection. A brief comparison of the two methodologies based on each of their strengths and limitations is carried out, and a recent research update regarding the coupling of the two techniques for improved damage detection in composite materials will be discussed.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.14 no.5
• /
• pp.2156-2170
• /
• 2020

This paper presents a fire detection algorithm with a minimal false detection rate, intended for a thermal imaging surveillance environment, whose properties vary depending on temporal conditions of day or night and environmental changes. This algorithm was designed to minimize the false detection alarm rate while ensuring a high detection rate, as required in fire detection applications. It was necessary to reduce false fire detections due to non-flame elements occurring when existing fixed threshold-based fire detection methods were applied. To this end, adaptive flame thresholds that varied depending on the characteristics of input images, as well as the center of gravity of the heat-source and hot-source regions, were analyzed in an attempt to minimize such non-flame elements in the phase of selecting flame candidate blocks. Also, to remove any false detection elements caused by camera shaking, one of the most frequently raised issues at outdoor sites, preliminary decision thresholds were adaptively set to the motion pixel ratio of input images to maximize the accuracy of the preliminary decision. Finally, in addition to the preliminary decision results, the texture correlation and intensity of the flame candidate blocks were averaged for a specific period of time and tested for their conformity with the fire decision conditions before making the final decision. To verify the fire detection performance of the proposed algorithm, a total of ten test videos were subjected to computer simulation. As a result, the fire detection accuracy of the proposed algorithm was determined to be 94.24%, with minimum false detection, demonstrating its improved performance and practicality compared to previous fixed threshold-based algorithms.

• Journal of the Institute of Electronics and Information Engineers
• /
• v.50 no.9
• /
• pp.194-200
• /
• 2013

In this paper, we propose a multi-scale crack detection method using scaling. It is based on morphology algorithm, crack features, and scaling. We use a morphology operator which extracts patterns of crack. It segments cracks and background using opening and closing operations. Morphology based segmentation is better than existing integration methods using subtraction in detecting a crack it has small width. However, morphology methods using only one structure element could detect only fixed width crack. Thus, we use a scaling method. We use bilinear interpolation for scaling. Our method calculates values of properties such as the number of pixels and the maximum length of the segmented region. We decide whether the segmented region belongs to cracks according to those data. Experimental results show that our proposed multi-scale crack detection method has better results than those of existing detection methods.

• Korean Journal of Materials Research
• /
• v.26 no.1
• /
• pp.47-53
• /
• 2016

Silicon nitride ($SiN_x:H$) films made by plasma enhanced chemical vapor deposition (PECVD) are generally used as antireflection layers and passivation layers on solar cells. In this study, we investigated the properties of silicon nitride ($SiN_x:H$) films made by PECVD. The passivation properties of $SiN_x:H$ are focused on by making the antireflection properties identical. To make equivalent optical properties of silicon nitride films, the refractive index and thickness of the films are fixed at 2.0 and 90 nm, respectively. This limit makes it easier to evaluate silicon nitride film as a passivation layer in realistic application situations. Next, the effects of the mixture ratio of the process gases with silane ($SiH_4$) and ammonia ($NH_3$) on the passivation qualities of silicon nitride film are evaluated. The absorption coefficient of each film was evaluated by spectrometric ellipsometry, the minority carrier lifetimes were evaluated by quasi-steady-state photo-conductance (QSSPC) measurement. The optical properties were obtained using a UV-visible spectrophotometer. The interface properties were determined by capacitance-voltage (C-V) measurement and the film components were identified by Fourier transform infrared spectroscopy (FT-IR) and Rutherford backscattering spectroscopy detection (RBS) - elastic recoil detection (ERD). In hydrogen passivation, gas ratios of 1:1 and 1:3 show the best surface passivation property among the samples.

• Journal of KIISE:Software and Applications
• /
• v.36 no.3
• /
• pp.236-243
• /
• 2009

With advances in topic detection and tracking(TDT), automatic trend analysis from a collection of time-stamped documents, like patents, news papers, and blog pages, is a challenging research problem. Past research in this area has mainly focused on showing a trend line over time of a given concept by measuring the strength of trend-associated term frequency information. for detection of emerging trends, either a simple criterion such as frequency change was used, or an overall comparison was made against a training data. We note that in order to show most salient trends detected among many possibilities, it is critical to devise a ranking function. To this end, we define four properties(change, persistency, stability and volume) of trend lines drawn from frequency information, to quantify various aspects of trends, and propose a method by which trend lines can be ranked. The properties are examined individually and in combination in a series of experiments for their validity using the ranking algorithm. The results show that a judicious combination of the four properties is a better indicator for salient trends than any single criterion used in the past for ranking or detecting emerging trends.

• Journal of Sensor Science and Technology
• /
• v.23 no.4
• /
• pp.217-223
• /
• 2014

Nerve agents are major chemical warfare agents with the "G series" and "V series" being the most widely known because of their lethal effect. Although not conspicuously used in major wars, the potential detrimental impact on modern society had been revealed from the sarin terror attack on Tokyo subway, which affected thousands of people. In this mini-review, major nerve agents of the "G series" and "V series" have been described along with various types of their detection methods. The physical properties and hydrolysis mechanisms of the major nerve agents are discussed since these are important factors to be considered in choosing detection methods, and specifying the procedures for sample preparations in order to enhance detection precision. Various types of extraction methods, including liquid-phase, solid-phase, gas-phase and solid-phase microextraction (SPME), are described. Recent development in the use of gas sensors for detecting nerve agents is also summarized.

• Proceedings of the KSRS Conference
• /
• 2002.10a
• /
• pp.696-701
• /
• 2002

This paper describes some results of change detection in Tokyo metropolitan area, Japan , using the Landsat TM data, and methods to quantify the ground cover classes. The changes are analyzed using the measures of not only conventional spectral classes but also a set of landscape indices to describe spatial properties of ground cove types using fractal dimension of objects, entropy in the specific windows defining the neighbors of focusing locations. In order eliminate the seasonal radiometric effects on TM data, an automated class labeling method is also attempted. Urban areas are also delineated automatically by defining the boundaries of the urban area. These procedures for urban change detection were implemented by the unified image computing methods proposed by the author, they can be automated in coherent and systematic ways, and it is anticipated to automate the whole procedures. The results of this analysis suggest that Tokyo metropolitan area was extended to the suburban areas along the new transportation networks and the high density area of Tokyo were also very much extended during the period between 1985 and 1995.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
• /
• 2014.04a
• /
• pp.81-82
• /
• 2014

Recently it is often reported about toxic nanomaterials to organisms. In other words, it is called nanotoxicity, toxic nanomaterials have extremely toxic properties. Zinc oxide is widely used as a promising nanomaterials, but some researchers are warning that nanotype zinc oxide has nanotoxicity. One of typical zinc oxide materials is a zinc oxide nanowire, especially, there is no technique which is detecting a zinc oxide nanowire because of its geometric. In here, we use reduced graphene oxide in order to detect zinc oxide nanowire and use DNA immobilized cantilever sensor, we detect graphene wrapped zinc oxide nanowire. Detection of a zinc oxide nanowire is measured by shifting of cantilever's resonance frequency based on vibration theory. It is proved that cantilever sensor is valid for nanomaterial detection. We showed that detection of a zinc oxide nanowire is successful.

• Proceedings of the IEEK Conference
• /
• 1999.06a
• /
• pp.615-618
• /
• 1999

In this paper, a object detection and tracking algorithm is presented which exhibits robust properties for image sequences with complex background. The proposed algorithm is composed of three parts: moving object detection, object tracking, and motion analysis. The moving object detection algorithm is implemented using a temporal median background method which is suitable for real-time applications. In the motion analysis, we propose a new technique for removing a temporal clutter, such as a swaying plant or a light reflection of a background object. In addition, we design a multiple vehicle tracking system based on Kalman filtering. Computer simulation of the proposed scheme shows its robustness for MPEG-7 test image sequences.

• 제어로봇시스템학회:학술대회논문집
• /
• 1987.10b
• /
• pp.709-712
• /
• 1987

In this paper, a mathematical model for the purpose of QRS detection is considered in the case of the occurrence of nonoverlapping pulse-shaped waveforms corrupted with white noise. The number of waveforms, the arrival times, amplitudes, and widths of QRS complexes are regarded as random variables. The joint MAP estimation of all the unknown quantities consists of linear filtering followed by an optimization procedure. Because of time-consuming, the optimization procedure is modified so that a threshold test is obtained. The model formulation with nonoverlapping waveforms leads to a standard procedure covering a segment before as well as after an accepted event. Adaptivity of the detector is gained by utilizing past signal properties in determining threshold for QRS detection.