• Journal of the Ergonomics Society of Korea
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• v.10 no.2
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• pp.51-55
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• 1991

Since slipping has been identified as a major hazard, it is important to understand the mechanism of a slip. Many researches, based on biomechanical studies, had been attempted to do that. Thowever, the correlation between the mechanism of a slip and psychophysical behaviors of people had rarely been verified. For example, the existence of small slips in a forward direction, which do not normally perceived by human subjects, has been established by several experimenters. However, the term "microslips are not perceived by the walkers[4]." has not been examined precisely by any experiments. The objective of this study is, using a Signal Detection Theory (SDT), to define a microslip and slip more quqntitatively with the biomechanical measurement of slip distance. The results showed that, the slip distance around the 3 centimeters, there was a obvious change in the accident detectability of the subject. The conclusion is that it is possible to identify the boundary of a microslip and slip around the 3 centermeters of slip distance.

• Proceedings of the Korean Nuclear Society Conference
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• 1995.10a
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• pp.197-202
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• 1995

When the process disturbance of nuclear power plant occurred, the operator should ensure plant safety, economy and identify the causes of disturbance. To accomplish these goals, operator should process a large amounts of information. Among these, alarms would be often in the operator's first indication of a plant state change or disturbance. To support limited information processing capability of operator, considerable works are under way to develop advanced alarm processing systems and to evaluate it. However, conventional evaluation method could provide just evaluation results but the design alternatives to enhance alarm system performance. To overcome problems associated with conventional evaluation methods of alarm system, signal detection theory(SDT) was introduced, and it was possible conclude that SDT could not only evaluate system but also suggest design alternatives for performance enhancement.

• ETRI Journal
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• v.41 no.3
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• pp.316-325
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• 2019

Accurate suppressive jamming is a prominent problem faced by radar equipment. It is difficult to solve signal detection problems for extremely low signal to noise ratios using traditional signal processing methods. In this study, a joint sensing dictionary based compressed sensing and adaptive iterative optimization algorithm is proposed to counter suppressive jamming in information domain. Prior information of the linear frequency modulation (LFM) and suppressive jamming signals are fully used by constructing a joint sensing dictionary. The jamming sensing dictionary is further adaptively optimized to perfectly match actual jamming signals. Finally, through the precise reconstruction of the jamming signal, high detection precision of the original LFM signal is realized. The construction of sensing dictionary adopts the Pei type fast fractional Fourier decomposition method, which serves as an efficient basis for the LFM signal. The proposed adaptive iterative optimization algorithm can solve grid mismatch problems brought on by undetermined signals and quickly achieve higher detection precision. The simulation results clearly show the effectiveness of the method.

• Journal of Power Electronics
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• v.13 no.5
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• pp.884-895
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• 2013

In this paper, the Fourier-based PLL (Phase-locked Loop) is introduced with a new structure, capable of selective harmonic detection in single and three-phase systems. The application of the FB-PLL to harmonic detection is discussed and a new model applicable to three-phase systems is introduced. An analysis of the convergence of the FB-PLL based on a linear model is presented. Simulation and experimental results are included for performance analysis and to support the theoretical development. The decomposition of an input signal in its harmonic components using the Fourier theory is based on previous knowledge of the signal fundamental frequency, which cannot be easily implemented with input signals with varying frequencies or subjected to phase-angle jumps. In this scenario, the main contribution of this paper is the association of a phase-locked loop system, with a harmonic decomposition and reconstruction method, based on the well-established Fourier theory, to allow for the tracking of the fundamental component and desired harmonics from distorted input signals with a varying frequency, amplitude and phase-angle. The application of the proposed technique in three-phase systems is supported by results obtained under unbalanced and voltage sag conditions.

• Journal of Power Electronics
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• v.14 no.6
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• pp.1303-1313
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• 2014

Dynamic behavior of the harmonic detection part of an active power filter (APF) has an essential role in filter compensation performances during transient conditions. Instantaneous power (p-q) theory is extensively used to design harmonic detectors for active filters. Large overshoot of p-q theory method deteriorates filter response at a large and rapid load change. In this study the harmonic estimation of an APF during transient conditions for balanced three-phase nonlinear loads is conducted. A novel fuzzy instantaneous power (FIP) theory is proposed to improve conventional p-q theory dynamic performances during transient conditions to adapt automatically to any random and rapid nonlinear load change. Adding fuzzy rules in p-q theory improves the decomposition of the alternating current components of active and reactive power signals and develops correct reference during rapid and random current variation. Modifying p-q theory internal high-pass filter performance using fuzzy rules without any drawback is a prospect. In the simulated system using MATLAB/SIMULINK, the shunt active filter is connected to a rapidly time-varying nonlinear load. The harmonic detection parts of the shunt active filter are developed for FIP theory-based and p-q theory-based algorithms. The harmonic detector hardware is also developed using the TMS320F28335 digital signal processor and connected to a laboratory nonlinear load. The software is developed for FIP theory-based and p-q theory-based algorithms. The simulation and experimental tests results verify the ability of the new technique in harmonic detection of rapid changing nonlinear loads.

• Journal of Communications and Networks
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• v.14 no.5
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• pp.566-577
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• 2012

In randomly deployed networks, such as sensor networks, an important problem for each node is to discover its neighbor nodes so that the connectivity amongst nodes can be established. In this paper, we consider this problem by incorporating the physical layer parameters in contrast to the most of the previous work which assumed a collision channel. Specifically, the pilot signals that nodes transmit are successfully decoded if the strength of the received signal relative to the interference is sufficiently high. Thus, each node must extract signal parameter information from the superposition of an unknown number of received signals. This problem falls naturally in the purview of random set theory (RST) which generalizes standard probability theory by assigning sets, rather than values, to random outcomes. The contributions in the paper are twofold: First, we introduce the realistic effect of physical layer considerations in the evaluation of the performance of logical discovery algorithms; such an introduction is necessary for the accurate assessment of how an algorithm performs. Secondly, given the double uncertainty of the environment (that is, the lack of knowledge of the number of neighbors along with the lack of knowledge of the individual signal parameters), we adopt the viewpoint of RST and demonstrate its advantage relative to classical matched filter detection method.

• Journal of Sensor Science and Technology
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• v.6 no.6
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• pp.458-465
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• 1997

In this paper, a theory of the geological magnetic filter for the improvements of the signal to noise ratio of the magnetic detection system has been developed. The geological magnetic filter takes two sequences of magnetic fields measured from the reference sensor and the detector sensor and calculate the correlations between them in the frequency domain. Using the filter, we can remove the coherent noises in the time domain and improve the signal to noise ratio of the magnetic detection system. With the recent developments of the DSP hardware technology the geological magnetic filter can be easily implemented using the digital signal processor. We show the ability of the geological magnetic filter under various circumstances through computer simulations. Numerical simulation results show that geological magnetic filter can excellently remove the sensor misalignment effects and the regular short range local noise as well as it delete the coherent noises.

• Proceedings of the KIEE Conference
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• 1999.07g
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• pp.3221-3223
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• 1999

OAEs are low-level sounds produced by cochlea as part of the normal hearing process. OAEs can be measured with a microphone placed in the outer ear-cannel. We can diagnose cochlea's condition by using OAEs. To diagonose it's condition, however, is difficult by reason of OAEs' tiny. Thus, It need to a method using latency which essential diagnosing a time-element of OAEs. This study proposes a latency detection algorithm using 7-QMF for more effective detection of latency, 7-QMF designed by wavelet theory can process signal without a losses of information. The latency-detector based on 7-QMF is superior to former method.

• Journal of Electrical Engineering and Technology
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• v.10 no.4
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• pp.1540-1551
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• 2015

The detection of position and speed in BLDC motors without using position sensors has meant many efforts for the last decades. The aim of this paper is to develop a sensorless technique for detecting the position and speed of BLDC motors, and to overcome the drawbacks of position sensor-based methods by improving the performance of traditional approaches oriented to motor phase voltage sensing. The position and speed information is obtained by computing the derivative of the terminal phase voltages regarding to a virtual neutral point. For starting-up the motor and implementing the algorithms of the detection technique, a FPGA board with a real-time processor is used. Also, a versatile hardware has been developed for driving BLDC motors through pulse width modulation (PWM) signals. Delta and wye winding motors have been considered for evaluating the performance of the designed hardware and software, and tests with and without load are performed. Experimental results for validating the detection technique were attained in the range 5-1500 rpm and 5-150 rpm under no-load and full-load conditions, respectively. Specifically, speed and position square errors lower than 3 rpm and between 10º-30º were obtained without load. In addition, the speed and position errors after full-load tests were around 1 rpm and between 10º-15º, respectively. These results provide the evidence that the developed technique allows to detect the position and speed of BLDC motors with low accuracy errors at starting-up and over a wide speed range, and reduce the influence of noise in position sensing, which suggest that it can be satisfactorily used as a reliable alternative to position sensors in precision applications.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.23 no.10
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• pp.1195-1200
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• 2019

This paper proposes a detection algorithm for group testing. Group testing is a problem of finding a very small number of defect samples out of a large number of samples, which is similar to the problem of Compressed Sensing. In this paper, we define a noiseless group testing and propose a probabilistic algorithm for detection of defective samples. The proposed algorithm is constructed such that the extrinsic probabilities between the input and output signals exchange with each other so that the posterior probability of the output signal is maximized. Then, defective samples are found in the group testing problem through a simulation on the detection algorithm. The simulation results for this study are compared with the lower bound in the information theory to see how much difference in failure probability over the input and output signal sizes.