• Proceedings of the Korean Society for Emotion and Sensibility Conference
• /
• 2002.05a
• /
• pp.44-50
• /
• 2002

The fast Fourier transform (FFT) is a good method to estimate spectral density, but the frequency resolution is limited to the sampling window, and thus the precise characteristics of the spectral density for short signals are not clear. To solve the limitation, a multiple band-pass filter was introduced to estimate the precise time course of the spectral density for flash visual evoked potentials (VEPs). Signals were recorded during -200 and 600 ms using balanced noncephalic electrodes, and sampled at 1 K Hz in 12 bits. With 1 Hz and 10 ms resolutions, spectral density was estimated between 10 and 100 Hz. Background powers at the alpha-and beta-bands were high over the posterior scalp, and powers around 200ms were evoked at the same bands over the same region, corresponding to P110 and N165 of VEPs. normalized's spectral density showed evoked powers around 200 ms and suppressed powers following the evoked powers over the posterior scalp. The evoked powers above the 20Hz band were not statistically significant. However, the gamma band was significantly evoked intra-individually; details in the gamma bands were varied among the subjects. Details of spectral density were complicated even for a simple task such as watching flashes; both synchronization and desynchronization occurred with different distributions and different time courses.

• Transactions of the Korean Society of Automotive Engineers
• /
• v.19 no.3
• /
• pp.113-121
• /
• 2011

Rollover accident is one of the serious traffic accident and rollover accident takes high portion of all accident. The most common type of rollover is a tripped rollover which occupy 95% of all type of single-vehicle rollover. Tripped rollover occurs when a vehicle leaves normal road way and tripped by loose gravel, soil of fixed object such as guard rail, curbs and ditches. And the rest of the type of rollover is un-tripped rollover. An un-tripped rollovers that occurs during high-speed collision avoidance maneuvers. In this paper, presents the explanation of the un-tripped rollover test method and procedure, additionally this paper deals with various occurrence in the un-tripped test such as occurring excessive tire camber in the un-tripped test, tire side-wall contact with road surface and roll oscillation. And this paper analyzes the analysis of the roll rate amplitude in specific frequency through the FFT (Fast Fourier Transform) and the roll angle at the steering reverse timing which is the Fishhook test roll rate feedback time. Finally, this paper analyzes the relations between the estimated steady state roll gain and rollover stability.

• Smart Structures and Systems
• /
• v.30 no.4
• /
• pp.411-420
• /
• 2022

Monitoring large structures is a significant issue involving public health on which new studies are constantly carried out. Although the Global Navigation Satellite System (GNSS) is the most preferable method for measuring structural displacements, total stations, one of the classical geodetic instruments, are the first devices that come to mind in cases that require complementary usage and auxiliary measurement methods. In this study, the relative displacements of the structural movements of a tower were determined using robotic total stations (RTS) and GNSS. Two GNSS receivers and two RTS observations were carried out simultaneously for 10 hours under normal weather conditions. The spectral analysis of the GNSS data was performed using fast Fourier transform (FFT), and while the dominant modal frequencies were determined, the total station data were balanced with the least-squares technique, and the position and position errors were calculated for each measurement epoch. It has been observed that low-frequency structural movements can be determined by both methods. This result shows that total station measurements are a helpful alternative method for monitoring large structures in situations where measurements are not possible due to the basic handicaps of GNSS or where it is necessary to determine displacements with short observations.

• ETRI Journal
• /
• v.44 no.1
• /
• pp.85-93
• /
• 2022

We propose an efficient method for synthesizing mesh-based realistic computer-generated hologram (CGH). In a previous nonanalytic mesh-based CGH synthesis, the angular spectrum of the two-dimensional (2D) plane is calculated using the fast Fourier transform (FFT) with the same size as the resolution of the final hologram. Because FFT increases the computation time as the size of the input matrix increases, the previous method has a problem: The higher the resolution of the hologram, the greater the computational load, thereby delaying synthesis time. In this study, when calculating the angular spectrum of the 2D plane in mesh-based CGH synthesis, we propose a method to calculate the angular spectrum by defining the 2D plane with an arbitrary size smaller than the resolution of the final hologram. The resolution adjustment method reduces the computation time and can be applied to occlusion culling and texturing for the realistic effect of mesh-based CGH. We describe the principle, error analysis, application of realistic effect, and experimental results of the proposed method.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
• /
• 2008.04a
• /
• pp.742-746
• /
• 2008

With the trend of factory automation, nowadays, much industrial machinery tends to be put into 24-hours operation a day. However, these trends in industrial equipments also increase the possibility of various mechanical problems and bring about innumerable maintenance cost. There is a strong need of the condition monitoring and diagnosis for industrial equipment, especially rotating machinery, since they are connected not only to the reduction in the maintenance costs but also connected to the enhancement of production efficiency. Generally, to evaluate the operating conditions in the machinery in the industrial field, various physical properties are monitored. Among them, vibration and Noise signals are the mist important indicator and it is effectively used in many diagnosis systems for machinery. Much previous research is based in the FFT (Fast Fourier Transform) method. The spectral analysis is assumed that the signal is stationary. However, almost random signals are non-stationary. The wavelet transform has been recognized an efficient Method. Most interesting sounds have time-varying features. Signal processing techniques for the analysis of transient sound have been not clearly given yet.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
• /
• v.19 no.6
• /
• pp.36-45
• /
• 2005

This paper addresses the application of motor current spectral analysis for the detection of rolling-element bearing damage in induction machines. We set the experimental test bed. They is composed of the normal condition bearing system, the abnormal rolling-element bearing system of 2 type induction motors with shaft deflection system by external force and a hole drilled through the outer race of the shaft end bearing of the four pole test motor. We have developed the embedded distributed fault tolerant and fault diagnosis system for industrial motor. These mechanisms are based on two 32-bit DSPs and each TMS320F2407 DSP module is checking stator current The effects on the stator current spectrum are described and related frequencies are also determined. This is an important result in the formulation of a fault detection scheme that monitors the stator currents. We utilized the FFT(Fast Fourier Transform), Wavelet analysis and averaging signal pattern by inner product tool to analyze stator current components. Especially, the analyzed results by inner product clearly illustrate that the stator signature analysis can be used to identify the presence of a bearing fault.

• Journal of the Korea Society of Computer and Information
• /
• v.11 no.2 s.40
• /
• pp.35-42
• /
• 2006

In this paper we implement a new simulator for performance analysis of a parallel digital signal processing distributed shared memory multiprocessor systems. using Parsec The key idea of this simulator is suitable in simulation of system that uses DMA function of TMS320C6701 DSP chip and local memory which have fast access time. Also, because correction of performance parameter and reconfiguration for hardware components are easy, we can analyze performance of system in various execution environments. In the simulation, FET, 2D FET, Matrix Multiplication. and Fir Filter, which are widely used DSP algorithms. have been employed. Using our simulator, the result has been recorded according to different the number of processor, data sizes, and a change of hardware element. The performance of our simulator has been verified by comparing those recorded results.

• Journal of Multimedia Information System
• /
• v.8 no.1
• /
• pp.1-10
• /
• 2021

Heart Rate is a crucial physiological parameter that provides basic information about the state of the human body in the cardiovascular system, as well as in medical diagnostics and fitness assessments. At present day, it has been demonstrated that facial video-based photoplethysmographic signal captured using a low-cost RGB camera is possible to retrieve remote heart rate. Traditional heart rate measurement is mostly obtained by direct contact with the human body, therefore, it can result inconvenient for long-term measurement due to the discomfort that it causes to the subject. In this paper, we propose a non-contact-based remote heart rate measuring approach of the subject which depends on the color intensity variation of the subject's facial skin. The proposed method is applied in two regions of the subject's face, forehead and cheeks. For this, three different algorithms are used to measure the heart rate. i.e., Fast Fourier Transform (FFT), Independent Component Analysis (ICA) and Principal Component Analysis (PCA). The average accuracy for the three algorithms utilizing the proposed method was 89.25% in both regions. It is also noteworthy that the FastICA algorithm showed a higher average accuracy of more than 92% in both regions. The proposed method obtained 1.94% higher average accuracy than the traditional method based on average color value.

• KIPS Transactions on Computer and Communication Systems
• /
• v.6 no.11
• /
• pp.437-444
• /
• 2017

Electric Pole is a supporting beam used for power transmission/distribution which is sensitive to external force change of environmental factors. Therefore, power facilities have many difficulties in terms of maintenance/conservation from external environmental changes and natural disasters that cause a great economic impact. The aerial wire cause elasticity due to the influence of temperature, or factors such as wind speed and wind direction, that weakens the electric pole. The situation may lead to many safety risk in day-to-day life. But, the safety assessment of the pole is carried out at the design stage, and aftermath is not considered. For the safety and maintenance purposes, it is very important to analyze the influence of weather factors on external forces periodically. In this paper, we analyze the acceleration data of the sensor nodes installed in electric pole for maintenance/safety purpose and use Kalman filter as noise compensation method. Fast Fourier Transform (FFT) is performed to analyze the influence of each meteorological factor, along with the meteorological factors on frequency components. The result of the analysis shows that the temperature, humidity, solar radiation, hour of daylight, air pressure, wind direction and wind speed were influential factors. In this paper, the influences of meteorological factors on frequency components are different, and it is thought that it can be an important factor in achieving the purpose of safety and maintenance.

• International Journal of Fuzzy Logic and Intelligent Systems
• /
• v.6 no.1
• /
• pp.27-32
• /
• 2006

Verbal communication is the most commonly used mean of communication. A spoken word carries a lot of informations about speakers and their emotional states. In this paper we designed a model to recognize emotional states in a speech, a first phase of two phases in developing a toy machine that recognizes emotional states in a speech. We conducted an experiment to extract and analyse the emotional state of a speaker in relation with speech. To analyse the signal output we referred to three characteristics of sound as vector inputs and they are the followings: frequency, intensity, and period of tones. Also we made use of eight basic emotional parameters: surprise, anger, sadness, expectancy, acceptance, joy, hate, and fear which were portrayed by five selected students. In order to facilitate the differentiation of each spectrum features, we used the wavelet transform analysis. We applied ANFIS (Adaptive Neuro Fuzzy Inference System) in designing an emotion recognition model from a speech. In our findings, inference error was about 10%. The result of our experiment reveals that about 85% of the model applied is effective and reliable.