• The Journal of Korean Institute of Communications and Information Sciences
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• v.32 no.3C
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• pp.189-194
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• 2007

This paper derives and computes the detection probability of timing synchronization in an orthogonal frequency division multiplexing (OFDM) system encountered with a multipath Rayleigh fading channel and imperfect noise estimation. The timing synchronization scheme using a simple repeated constant amplitude zero auto-correlation (CAZAC) training symbol and correlation techniques is adopted. With this provision, we focus on the numerical analysis for OFDM timing synchronization scheme employing a preadvancement technique to reduce the inter-symbol interference (ISI). For measuring system performance, the detection performance derived in the considered system is presented in a multipath Rayleigh fading channel.

• Proceedings of the IEEK Conference
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• 2002.07b
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• pp.1268-1271
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• 2002

The major threat of geometric manipulations is that they change the positions of watermarks, therefore the detection process fails to extract watermark properly. Since they cause the same effects on the host image as watermarks simultaneously, evaluating the distorted host image can be helpful to measure the nature of distortions. In this paper, we propose a geometrical distortion-resilient watermarking algorithm based on this property. Firstly we evaluate the orientation of a host image by filtering it with directional Gabor kernels, then we insert embedding pattern aligned to the estimated orientation. In its detection step, we evaluate the orientation again by Gabor filtering, then simply project and average the projected value to obtain a 1-D projection average pattern. Finally, auto-correlation function of the 1-D projection average pattern identifies periodic peaks. Analysed are experimental results against geometrical attacks including aspect ratio changes.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.8 no.3
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• pp.42-51
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• 1999

An experimental modeling of cutting and structural dynamics and the on-line detection of malfunction process is substantial not only for the investigation of the static and dynamic characteristics of cutting process but also for the analytic realization of diagnostic systems. In this regard, We have discussed on the comparative assessment of two recursive time series modeling algorithms that can represent the machining process and detect the abnormal machining behaviors in precision round shape machining such as turning, drilling and boring in mold and die making. In this study, simulation and experimental work were performed to show the malfunctioned behaviors. For this purpose, two new recursive approach (REIVM, RLSM) were adopted fur the on-line system identification and monitoring of a machining process, we can apply these new algorithm in real process for the detection of abnormal machining behaviors such as chipping, chatter, wear and round shape lobe waviness.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.22 no.2
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• pp.179-184
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• 2013

In this article, we introduce the study case of technology that can automatically compensate the errors of these factors of a machine during processing on the machine tool's CNC(Computerized Numerical Controller) in real time. The biggest factors that lower the machining accuracy are thermal deformation and chatter vibration. This study is related to the detection and compensation of thermal deformation and chatter vibration that can compensate for faster and produce processed goods with more precision by autonomous compensation. In addition, this study is related to the active control of vibration during machining, monitoring of cutting force and auto recognition of machining axes origin. Thus, we attempt to introduce the related contents of the development we have made in this article.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2000.06a
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• pp.1127-1132
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• 2000

Impulsive acoustic and vibration signals within rotating machinery are often induced by irregular impacting. The detection of these impulses can be useful for fault diagnosis purposes. Recently there has been an increasing trend towards the use of higher order statistics for fault detection within mechanical systems based on the observation that impulsive signals tend to increase the kurtosis values. This paper considers the use of the third and fourth order Wigner moment spectra, called the Wigner bi- and tri- spectra receptively, for analysing such signals. Expressions for the auto-and cross-terms in these distributions are presented and discussed. It is shown that the Wigner trispectrum is a more suitable analysis tool and it performance is compared to its second order counterpart for detecting impulsive signals. These methods are also applied to measured data sets from an industrial gearbox.

• Journal of the Korean Society for Precision Engineering
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• v.14 no.8
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• pp.115-121
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• 1997

The in-process detection of the tool wear is one of the most important technologies in completely auto- matic operation of machine tool. In this research, using the tools having flank wear, the dynamic compo- nent of cutting forces is considered to be available for identifying the cutting process. In order to investi- gate this relation in detail, the cutting forces in turning of workpiece made of aluminum were measured by dynamometer of piezoelectric type, and the dynamic components of cutting force were analyzed. The fre- quency analysis, probability density analysis and RMS analysis of the dynamic components were carried out independently. Through the experiments, the characteristics of the tool system have a large effect on the dynamic component of cutting forces. As a result, it is shown that the dynamic cutting force was able to detect flank wear accurately.

• Journal of Biomedical Engineering Research
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• v.17 no.2
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• pp.241-246
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• 1996

This paper describes a new system that detects radial pulse wave and allows the diagnosis of malfunctions of cardiovascular system by analyzing the waveforms with the newly proposed algorithm. The system consists of a sensor part and a data processing part within which a new detection algorithm is incorporated In acquiring radial pulse signal noninvasively, the sensor used in this system is a new combinational fiber-optic sensor which has a detecting Part and a transmitting Part. Also, In order to analyze the characteristics of pulsation quantitatively, the algorithm proposed in this paper is a method that runs in parallel with both the data of ECG and differential pulse simultaneously. these concepts are based upon the idea that thfee Q points of ECG give obious discrimination of one entire period of pulse in any abnormal cases, and newly defined feature lines at the differential counterpart can be used to recogrlize sDme significant points in one period of pulses.

• Journal of Aerospace System Engineering
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• v.1 no.4
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• pp.7-12
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• 2007

From the beginning of aviation history, in-flight smoke/fire events have been a serious issue. As aircraft are getting larger and are becoming more auto-piloted and aircraft systems are getting more complex, it is an increasing risk of in-flight smoke/fire accidents accompanied with fire events. Therefore, we review the statistics of fire/smoke accidents in order to enhance an understanding for risk of in-flight smoke events, and present the certification requirements for smoke per KAS Part 25. In addition, we provide acceptable methods of complying with related requirements, such as smoke detection test, smoke penetration test and smoke evacuation test.

• The Transactions of the Korean Institute of Electrical Engineers P
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• v.56 no.1
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• pp.28-36
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• 2007

Sensor networks are usually composed of tens or thousands of tiny devices with limited resources. Because of their limited resources, many researchers have studied on the energy management in the WSNs(Wireless Sensor Networks), especially taking into account communications efficiency. For effective data transmission and sensor fault detection in sensor network environment, a new remote monitoring system based on PCA(Principle Component Analysis) and AANN(Auto Associative Neural Network) is proposed. PCA and AANN have emerged as a useful tool for data compression and identification of abnormal data. Proposed system can be effectively applied to sensor network working in LEA2C(Low Energy Adaptive Connectionist Clustering) routing algorithms. To verify its applicability, some simulation studies on the data obtained from real WSNs are executed.

• Proceedings of the KIEE Conference
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• 2003.07d
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• pp.2289-2291
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• 2003

NLPCA(Nonlinear Principal Component Analysis is a novel technique for multivariate data analysis, similar to the well-known method of principal component analysis. NLPCA can be implemented by a feedforward neural network called AANN (AutoAssociative Neural Network) which performs the identity mapping. In this work, a sensor fault detection system based on NLPCA and Maximum Likelihood Estimation scheme is presented. To verify its applicability, simulation study on the data supplied from Saemangeum measurement stations is executed.