• Journal of Power Electronics
• /
• v.16 no.2
• /
• pp.685-694
• /
• 2016

This paper presents a reliability assessment model for the power semiconductors used in wind turbine power converters. In this study, the thermal loadings at different timescales of wind speed are considered. First, in order to address the influence of long-term thermal cycling caused by variations in wind speed, the power converter operation state is partitioned into different phases in terms of average wind speed and wind turbulence. Therefore, the contributions can be considered separately. Then, in regards to the reliability assessment caused by short-term thermal cycling, the wind profile is converted to a wind speed distribution, and the contribution of different wind speeds to the final failure rate is accumulated. Finally, the reliability of an actual power converter semiconductor for a 2.5 MW wind turbine is assessed, and the failure rates induced by different timescale thermal behavior patterns are compared. The effects of various parameters such as cut-in, rated, cut-out wind speed on the failure rate of power devices are also analyzed based on the proposed model.

• Journal of Sensor Science and Technology
• /
• v.32 no.5
• /
• pp.320-327
• /
• 2023

In this study, an FPGA-based sealer inspection system was developed to inspect the sealer applied to install vehicle glass on a car body. The sealer is a liquid or paste-like material that promotes adhesion such as sealing and waterproofing for mounting and assembling vehicle parts to a car body. The system installed in the existing vehicle design parts line does not detect the sealer in the glass rotation section and takes a long time to process. This study developed a line laser camera sensor and an FPGA vision signal processing module to solve this problem. The line laser camera sensor was developed such that the resolution and speed of the camera for data acquisition could be modified according to the irradiation angle of the laser. Furthermore, it was developed considering the mountability of the entire system to prevent interference with the sealer ejection machine. In addition, a vision signal processing module was developed using the Zynq-7020 FPGA chip to improve the processing speed of the algorithm that converted the profile to the sealer shape image acquired from a 2D camera and calculated the width and height of the sealer using the converted profile. The performance of the developed sealer application inspection system was verified by establishing an experimental environment identical to that of an actual automobile production line. The experimental results confirmed the performance of the sealer application inspection at a level that satisfied the requirements of automotive field standards.

• The Journal of the Acoustical Society of Korea
• /
• v.26 no.8
• /
• pp.381-389
• /
• 2007

In this paper, the measuring method of underwater acoustic communication channel characteristics in the shallow water using the autocorrelation characteristic of PN sequence and the undorwater communication channel analysis results from the received signal sample data are described. For measuring the underwater acoustic communication channel characteristics, two PN sequences are used as a transmitted data of I-channel and Q-channel of QPSK symbol and QPSK signal is transmitted with symbol rate of 5 kHz and carrier frequency of 25 kHz. In the receiver the received signal, which pass through 675 m and 1492 m, is sampled and then stored. Using the stored sample data, the scattering function, coherent time, delay power profile, spaced-tone autocorrelation function, delay spread, and coherent bandwidth of each propagation distance cases are analyzed. Based on the analysis results, several guidelines are suggested for the design and implementation of underwater transmission system.

• Asian Journal of Atmospheric Environment
• /
• v.8 no.3
• /
• pp.162-174
• /
• 2014

An abnormal decrease in ozonesonde sensor signal occurred during air-pollution study campaigns in November 2011 and March 2012 in Mexico City Metropolitan Area (MCMA). Sharp drops in sensor signal around 5 km above sea level and above were observed in November 2011, and a reduction of signal over a broad range of altitude was observed in the convective boundary layer in March 2012. Circumstantial evidence indicated that $SO_2$ gas interfered with the electrochemical concentration cell (ECC) ozone sensors in the ozonesonde and that this interference was the cause of the reduced sensor signal output. The sharp drops in November 2011 were attributed to the $SO_2$ plume from Popocat$\acute{e}$petl volcano southeast of MCMA. Experiments on the response of the ECC sensor to representative atmospheric trace gases showed that only $SO_2$ could cause the observed abrupt drops in sensor signal. The vertical profile of the plume reproduced by a Lagrangian particle diffusion simulation supported this finding. A near-ground reduction in the sensor signal in March 2012 was attributed to an $SO_2$ plume from the Tula industrial complex north-west of MCMA. Before and at the time of ozonesonde launch, intermittent high $SO_2$ concentrations were recorded at ground-level monitoring stations north of MCMA. The difference between the $O_3$ concentration measured by the ozonesonde and that recorded by a UV-based $O_3$ monitor was consistent with the $SO_2$ concentration recorded by a UV-based monitor on the ground. The vertical profiles of the plumes estimated by Lagrangian particle diffusion simulation agreed fairly well with the observed profile. Statistical analysis of the wind field in MCMA revealed that the effect Popocat$\acute{e}$petl was most likely to have occurred from June to October, whereas the effect of the industries north of MCMA, including the Tula complex, was predicted to occur throughout the year.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
• /
• v.30 no.3
• /
• pp.252-259
• /
• 2019

Jet engine modulation(JEM) signals are widely used in the field of target recognition along with high-range resolution profile and inverse synthetic aperture radar because they provide specific information of the jet engine. To obtain the number of blades of the jet engine, the chopping frequency proportional to the number of blades must be extracted. In the conventional chopping frequency extraction method, an initial threshold value is defined and a method of detecting the chopping peak is used. However, this detection method takes time depending on the signal due to repetitive detection. Thus, in this study, we proposed to extract the chopping frequency using MUltiple SIgnal Classification(MUSIC) algorithm. We applied the MUSIC algorithm to a given JEM signal to find the chopping frequency and determine the blade number candidates. We also applied the MUSIC algorithm to other chopping frequency extractions to determine the score of the candidate groups. Unlike the conventional detection algorithm, which requires repetitive frequency detection, MUSIC algorithm quickly detects the accurate chopping frequency and reduces the calculation time.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.32 no.8C
• /
• pp.681-688
• /
• 2007

Applying an appropriate received signal processing algorithm based on the channel characteristics is important to improve the receiver performance. Wireless channels in general exhibit various time-delay characteristics depending on their power delay profile. When the estimated channel power summation is used to determine the amount of time delay, a channel adaptive receiver structure can be implemented. In this paper, we derive a closed-form expression for the error probability of the channel classification when the estimated channel power summation is used to classify channel groups having different time delay characteristics, and present the performance gain utilizing multiple estimation results.

• Transactions of the Korean Society of Machine Tool Engineers
• /
• v.17 no.3
• /
• pp.40-46
• /
• 2008

This paper presents the optimal motion control for 3-axis SCARA robot by using $LabVIEW^{(R)}$. Specifically, for optimal motion control of 3-axis SCARA robot, we study velocity profile based on finite jerk(the first derivative of acceleration) and optimal gain tunig based on frequency response method by using $LabVIEW^{(R)}$. The velocity optimization with finite jerk aims at generating the smooth velocity profile of robot. Velocity profile based on finite jerk is acquired and applied to 3-axis SCARA robot by using $LabVIEW^{(R)}$. DSA(Dynamic Signal Analyzer) for frequency response method is programed by using $LabVIEW^{(R)}$. We obtain the bode plot of transfer function about 3-axis SCARA robot by using DSA, and perform the gain tuning considering dynamic characteristic based on the bode plot. These experiments have shown that the proposed motion control can reduce vibration displacement and response error rate each 33.7% and 51.7% of 3-axis SCARA robot.

• Journal of information and communication convergence engineering
• /
• v.21 no.2
• /
• pp.103-109
• /
• 2023

We investigated the antipodal-symmetric dispersion maps of a dispersion-managed link with a midway optical phase conjugator to compensate for the distorted 960 Gb/s wavelength division multiplexed (WDM) signal caused by these effects. The proposed antipodal-symmetric dispersion map has various shapes depending on the detailed design scheme. We confirmed that the dispersion-managed link designed with the dispersion map of the antipodal-symmetric structure is more advantageous than the conventional uniform dispersion map for compensating WDM channels. It was also confirmed that among the antipodal-symmetric structures, the dispersion map configured with the S-1-profile, in which S is inverted up and down, was more effective for distortion compensation than the dispersion map configured with the S-profile. In particular, we confirmed that the S-1-profile can broaden the optical pulse width intensively at a short transmission distance, more effectively compensating for the distorted WDM channel. Because this structure makes the intensity of the optical pulse relatively weak, it can decrease the nonlinear Kerr effect.

• The Journal of the Acoustical Society of Korea
• /
• v.28 no.4
• /
• pp.383-391
• /
• 2009

In speech signal processing, speech signal corrupted by noise should be enhanced to improve quality. Usually noise estimation methods need flexibility for variable environment. Noise profile is renewed on silence region to avoid effects of speech properties. So we have to preprocess finding voice region before noise estimation. However, if received signal does not have silence region, we cannot apply that method. In this paper, we proposed SNR estimation method for continuous speech signal. The waveform which is stationary region of voiced speech is very correlated by pitch period. So we can estimate the SNR by correlation of near waveform after dividing a frame for each pitch. For unvoiced speech signal, vocal track characteristic is reflected by noise, so we can estimate SNR by using spectral distance between spectrum of received signal and estimated vocal track. Lastly, energy of speech signal is mostly distributed on voiced region, so we can estimate SNR by the ratio of voiced region energy to unvoiced.

• The Journal of the Acoustical Society of Korea
• /
• v.29 no.2
• /
• pp.148-153
• /
• 2010

In speech signal processing, speech signal corrupted by noise should be enhanced to improve quality. Usually noise estimation methods need flexibility for variable environment. Noise profile is renewed on silence region to avoid effects of speech properties. So we have to preprocess finding voice region before noise estimation. However, if received signal does not have silence region, we cannot apply that method. In this paper, we proposed SNR estimation method for continuous speech signal. A Speech signal consists of Voice and Unvoiced Band in The MBE excitation model. And the energy of speech signal is mostly distributed on voiced region, so we can estimate SNR by the ratio of voiced region energy to unvoiced. We use the IMBE vocoder for the Voice or Unvoice band of segmented speech signal. Continuously we calculate the segmented SNR using that information and the energy of each band. And we estimate the SNR of continuous speech signal.