• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2006.11a
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• pp.41-47
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• 2006

In this study, the influences of environmentally friendly visual and auditory information on traffic noise perception were surveyed by the using electroencephalogram Green rural region image and CBD image in urban city were used as visual informations. And traffic noise, signal and environmental music were used to detect the impact on electroencephalogram variance. It was revealed that green rural region image caused a-wave ratio increase about 10% and environmental music increased $\alpha$-wave ratio approximately $40{\sim}50%$. The results of this study improved that environmentally friendly visual and auditory information had an effect on decreasing traffic noise loudness to some extents.

• Journal of the Korean Society for Precision Engineering
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• v.11 no.1
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• pp.108-113
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• 1994

Active noise control technique has superior performance in low frequency ranges(50 .approx. 400Hz) to the conventional passive noise control technique. For the feasibility of active noise control, it is required to develop a controller which can implement control algorithm on real-time. In this study, therefore, real-time controller is developed using TMS320c25, high speed digital processor. Unlike conventional DSP board of complete ADD ON type, it is possible for the developed controller to interface with the other computer system easily by series communication for the convenience of program development. Furthermore it is designes to be separated readily as a control device. Active noise control of duct system is implemented ti evaluate a performance of developed device. Active noise control of duct system is implemented to evaluate a performance of developed controller using filtered-x LMS algorithm.

• Journal of KSNVE
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• v.2 no.2
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• pp.107-116
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• 1992

An adaptive signal processing technique is implemented for the active noise cancellation of the plane acoustic wave propagating in a duct. To avoid the instability caused by the acoustic feedback from the control speaker to the detect microphone, an off-line modeling of the acoustic feedback plant is done using the FIR filter. Auxiliary path required for the filtered-x LMS algorithm is modeled as well. Before going into the experiments, a simulation is carried out under the same conditions with experiments. The simulation shows that the longer the length of the adaptive filter is, the better the results are achieved. Experiments have been carried out at lower audio frequency range (50 - 400Hz), and the results are in good agreements with those of simulation study. As a results of this adaptive noise control, around 50dB is reduced for a pure tone noise, and for a bandlimited noise with the bandwidth of 316Hz, a maximum of 30dB noise reduction is attained.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.17 no.2 s.119
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• pp.160-167
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• 2007

In this study, the influences of environmentally friendly visual and auditory information on traffic noise perception were surveyed by the using electroencephalogram. Green rural region image and CBD (central business district) image in urban city were used as visual informations. And traffic noise, signal and environmental music were used to detect the impact on electroencephalogram variance. It was revealed that green rural region image caused ${\alpha}-wave$ ratio increase about 10% and environmental music increased ${\alpha}-wave$ ratio approximately $40{\sim}50%$. The results of this study improved that environmentally friendly visual and auditory information had an effect on decreasing traffic noise loudness to some extents.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.14 no.9 s.90
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• pp.877-883
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• 2004

This paper addresses the way in which we can find where impulsive noise sources are. Specifically, we have an interest in the case that the signal is embedded in noise. We propose a signal processing method that can identify impulsive sources' location. The method is robust with respect to spatially distributed noise. This has been achieved by the modified beamforming method with regard to cepstrum domain is used. It is noteworthy that the cepstrum has the ability to detect periodic pulse signal in noise. Numerical simulation and experiments are performed to verify the method. Results show that the proposed technique is quite powerful for localizing the faults in noisy environments. The method also required less microphones than conventional beamforming method.

• Journal of the Institute of Electronics and Information Engineers
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• v.52 no.4
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• pp.207-212
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• 2015

We propose a noise estimation method using edge detection in moving pictures. Edge detection is to exclude structures and details which have an effect on the noise estimation. To detect edge, we use Sobel and morphological closing operators which are robust to details of images. The proposed noise estimation method is more efficiently applied to noise estimation in various types of moving images and has better results than those of existing noise estimation methods. Also, proposed algorithm can be efficiently applied to image and video applications.

• The Journal of Korea Robotics Society
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• v.18 no.3
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• pp.271-280
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• 2023

FMCW (Frequency Modulated Continuous Wave) radar system is widely used in autonomous driving and navigation applications due to its high detection capabilities independent of weather conditions and environments. However, radar signals can be easily contaminated by various noises such as speckle noise, receiver saturation, and multipath reflection, which can worsen sensing performance. To handle this problem, we propose a learning-free noise removal technique for radar to enhance detection performance. The proposed method leverages adaptive thresholding to remove speckle noise and receiver saturation, and wavelet transform to detect multipath reflection. After noise removal, the radar image is reconstructed with the geometric structure of the surrounding environments. We verify that our method effectively eliminated noise and can be applied to autonomous driving by improving the accuracy of odometry and place recognition.

• Proceedings of the Acoustical Society of Korea Conference
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• spring
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• pp.225-230
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• 2004

Leak noise is a good source to identify the exact location of a leak point of underground water pipelines. Water leak generates broadband noise from a leak location and can be propagated to both directions of water pipes. However, the necessity of long-range detect ion of this leak location makes to identify low-frequency acoustic waves rather than high frequency ones. Acoustic wave propagation coupled with surrounding boundaries including cast iron pipes is theoretical analyzed and the wave velocity was confirmed with experiment The leak locations were identified both by the acoustic emission (AE) method and the cross-correlation method. In a short-range distance, both the AE method and cross-correlation method are effective to detect leak position. However, the detect ion for a long-range distance required a lower frequency range accelerometers only because higher frequency waves were attenuated very quickly with the increase of propagation paths. Two algorithms for the cross-correlation function were suggested and a long-range detection has been achieved at real underground water pipelines longer than 300m.

• Journal of Electrical Engineering and Technology
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• v.11 no.4
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• pp.1035-1041
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• 2016

Internal cracks in products are invisible and can lead to fatal crashes or damage. Since X-rays can penetrate materials and be attenuated according to the material’s thickness and density, they have rapidly become the accepted technology for non-destructive inspection of internal cracks. This paper presents a robust crack filter based on local gray level variation and multiscale analysis for automatic detection of cracks in X-ray images. The proposed filter takes advantage of the image gray level and its local variations to detect cracks in the X-ray image. To overcome the problems of image noise and the non-uniform intensity of the X-ray image, a new method of estimating the local gray level variation is proposed in this paper. In order to detect various sizes of crack, this paper proposes using different neighboring distances to construct an image pyramid for multiscale analysis. By use of local gray level variation and multiscale analysis, the proposed crack filter is able to detect cracks of various sizes in X-ray images while contending with the problems of noise and non-uniform intensity. Experimental results show that the proposed crack filter outperforms the Gaussian model based crack filter and the LBP model based method in terms of detection accuracy, false detection ratio and processing speed.

• Journal of the Korea Society of Computer and Information
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• v.25 no.5
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• pp.73-79
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• 2020

As the number of earthquakes gradually increases on the Korean Peninsula, much research has been actively conducted to detect earthquakes quickly and accurately. Because traditional seismic stations are expensive to install and operate, recent research is currently being conducted to detect earthquakes using low-cost MEMS sensors. In this article, we evaluate how a low-cost MEMS acceleration sensor installed in a smartphone can be used to detect earthquakes. To this end, we installed about 280 smartphones at various locations in Korea to collect acceleration data and then assessed the installed sensors' noise floor through PSD calculation. The noise floor computed from PSD determines the magnitude of the earthquake that the installed MEMS acceleration sensors can detect. For the last few months of real operation, we collected acceleration data from 200 smartphones among 280 installed smartphones and then computed their PSDs. Based on our experiments, the MEMS acceleration sensor installed in the smartphone is capable of observing and detecting earthquakes with a magnitude 3.5 or more occurring within 10km from an epic center. During the last several months of operation, the smartphone acceleration sensor recorded an earthquake of magnitude 3.5 in Miryang on December 30, 2019, and it was confirmed as an earthquake using STA/LTA which is a simple earthquake detection algorithm. The earthquake detection system using MEMS acceleration sensors is expected to be able to detect increasing earthquakes more quickly and accurately.