• Journal of the Institute of Electronics Engineers of Korea SC
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• v.44 no.2 s.314
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• pp.10-17
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• 2007

The echo signal on ultrasonic transducer is a mixed signal from tissues, blood vessel walls, blood cells and noise. In this mixed-signal, the signal reflected from tissues and blood vessel walls is called clutter. It is necessary to extract pure blood signal from this mixed-signal, when measuring blood flow velocity with medical ultrasonic system The quality of measured blood flow velocity is highly dependent on sufficient attenuation of the clutter signals. In this paper, we suggest a clutter rejection method using ICA For simulation, the echo signals are generated by Field n ultrasonic simulation program In this echo signals, independent signals are separated by using ICA Then the blood signal is obtained from the separated signals. Blood flow velocity is measured by 2D autocorrelation method. We compare ICA clutter rejection method with PCA-based eigen filter method using both measured blood flow velocity profiles by 2D autocorrelation. In simulation results, ICA clutter rejection method can be better applied measuring blood flow velocity in noisy echo signals.

• Proceedings of the KSME Conference
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• 2003.11a
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• pp.998-1003
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• 2003

Ultrasonic flow metering(UFM) technology is being received much attention from a variety of industrial fields to exactly measure the flow rate. The UFM has much advantage over other conventional flow meter systems, since it has no moving parts, and offers good accuracy and reliability without giving any disturbances to measure the flow rate, thereby not causing pressure losses in the flow fields. In the present study, 3-dimensional, unsteady, compressible Navier-Stokes equations are solved by a finite volume scheme, based upon the second order upwind scheme for spatial derivatives and the multi-stage Runge-Kutta integral method for time derivatives. In order to simulate multi-path ultrasonic flow meter, an excited pressure signal is applied to three different locations upstream, and the pressure signals are received at three different locations downstream. The mean flow velocities are calculated by the time difference between upstream and downstream propagating pressure signals. The obtained results show that the present CFD method simulates successfully ultrasonic meter gas flow and the mean velocity measured along the chord near the wall is considerably influenced by the boundary layers.

• International Journal of Precision Engineering and Manufacturing
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• v.6 no.4
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• pp.67-72
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• 2005

In a park or street, we can see many people jogging or walking with their dogs that are chasing their masters. In this study, a pet robot that imitates dog's behavior is developed. The task of robot is to chase a person who is recognized as the master. The physical structure and the sensor system are designed for the task and environment. A three-wheel type locomotion system is designed as the robot's physical structure which can follow a person who is jogging in outdoor environment like a park. A sensor system, which can detect relative position of the master to the robot in highly dynamic and hazardous worlds, is developed. This sensor system consists of a signal transmitter which is held by the master and ultrasonic sensor array which are mounted on the robot. The transmitter emits RF (radio frequency) and ultrasonic signals simultaneously. The ultrasonic sensor array detects the signals and calculates direction and distance between the robot and the transmitter. The developed RF-ultrasonic sensor is evaluated through experiments. A purely reactive behavior-based control architecture is used for the robot. The behavior control performance of the robot is assessed in outdoor and indoor tests.

• Journal of the Korean Society for Nondestructive Testing
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• v.33 no.2
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• pp.205-211
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• 2013

This paper studies on mechanical properties, fractures, and ultrasonic characteristics of Pure Titanium welds using ultrasonic attenuation. Ti specimen was made by using AR purge gas. When the titanium weld specimen is fractured, Tensile tests were conducted in order to observe the ultrasonic signal changes. A scanning electron microscope(SEM) was used to observe changes in failure surface and an ultrasonic normal probe with the central frequency of 4 MHz was used to obtain ultrasonic signals. As a result, the value of the mechanical properties in the weld zone was lower than that in the base zone and heat affected zone(HAZ) from Ti. Also the grain size in the weld zone was bigger than that in the weld zone and HAZ from Ti. Ultrasonic signals using a RMS method presents correlation between envelope area and the tensile strength. Consequently, the ultrasonic method could be potential tool for integrity evaluation of the Ti weld zone.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.4
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• pp.515-522
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• 2021

In this paper, we present and analyze a method of applying a machine learning to ultrasonic test signals for constant monitoring of the welding faults in a tubular steel tower. For the machine learning, feature selection based on genetic algorithm and fault signal classification using a support vector machine have been used. In the feature selection, the peak value, histogram lower bound, and normal negative log-likelihood from 30 features are selected. Those features clearly indicate the difference of signals according to the depth of faults. In addition, as a result of applying the selected features to the support vector machine, it has been possible to perfectly distinguish between the regions with and without faults. Hence, it is expected that the results of this study will be useful in the development of an early detection system for fault growth based on ultrasonic signals and in the energy transmission related industries in the future.

• The Journal of the Acoustical Society of Korea
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• v.38 no.4
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• pp.433-441
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• 2019

In this paper, a method of estimating speech parameters for ultrasonic Doppler signals reflected from the articulatory muscles using LSTM (Long Short Term Memory) RNN (Recurrent Neural Networks) was introduced and compared with the method using MLP (Multi-Layer Perceptrons). LSTM RNN were used to estimate the Fourier transform coefficients of speech signals from the ultrasonic Doppler signals. The log energy value of the Mel frequency band and the Fourier transform coefficients, which were extracted respectively from the ultrasonic Doppler signal and the speech signal, were used as the input and reference for training LSTM RNN. The performance of LSTM RNN and MLP was evaluated and compared by experiments using test data, and the RMSE (Root Mean Squared Error) was used as a measure. The RMSE of each experiment was 0.5810 and 0.7380, respectively. The difference was about 0.1570, so that it confirmed that the performance of the method using the LSTM RNN was better.

• Proceedings of the Korea Committee for Ocean Resources and Engineering Conference
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• 2004.05a
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• pp.395-400
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• 2004

For the purpose of monitoring by ultrasonic test of the ball bearing conditions in rotating machinery, a system for their diagnosis was developed. ultrasonic technique is used to detect abnormal conditions in the bearing system. And various data such as frequency spectrum, energy and amplitude of ultrasonic signals, and ultrasonic parameters were acquired during experiments with the simulated ball bearing system. Based on the above results and practical application for power plant, algorithms and judgement criteria for diagnosis system was established. Bearing diagnosis system is composed of four parts as follows : sensing part for ultrasonic sensor and preamplifier, signal processing part for measuring frequency spectrum, energy and amplitude, interface part for connecting ultrasonic signal to PC using A/D converter, graphic display and software part for display of bearing condition and for managing of diagnosis program.

• Journal of Ocean Engineering and Technology
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• v.15 no.3
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• pp.87-92
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• 2001

In this studies, joint time-frequency analysis techniques were applied to analyze ultrasonic signals in the degraded austenitic 316 stainless steels, to study the evolution of damage in these materials. It was demonstrated that the nonstationary characteristics of ultrasonic signals could be analyzed effectively by these methods. The WVD was more effective for analyzing the attenuation and frequency characteristics of the degraded materials through ultrasonic. It is indicated that the joint time-frequency analysis, WVD method, should also be useful in evaluating various damages and defects in structural members.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.9 no.2
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• pp.45-51
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• 2000

This study proposes that analysis and evaluation method of time series ultrasonic signal using the chaotic feature extrac-tion for degradation extent. Features extracted from time series data using the chaotic time series signal analyze quantitatively material degradation extent. For this purpose analysis objective in this study if fractal dimension lyapunov exponent and strange attractor on hyperspace. The lyapunov exponent is a measure of the rate at which nearby trajectories in phase space diverge. Chaotic trajectories have at least one positive lyapunov exponent. The fractal dimension appears as a metric space such as the phase space trajectory of a dynamical syste, In experiment fractal(correlation) dimensions and lyapunov experiments showed values of mean 3.837-4.211 and 0.054-0.078 in case of degradation material The proposed chaotic feature extraction in this study can enhances ultrasonic pattern recognition results from degrada-tion signals.

• Journal of Welding and Joining
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• v.17 no.6
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• pp.100-107
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• 1999

In this paper, we deal with the speckle noise reduction and parameter estimation of ultrasonic NDT(non-destructive test) signals obtained during weld inspection of piping. The overall approach consists of three major steps, namely, speckle noise analysis, proposition of wavelet domain AR(autoregressive) model and flaw detection by proposed model parameter. The data are first processed whereby signals obtained using vertical and angle beam transducer. Correlation properties of speckle noise are then analyzed using multiresolution analysis in wavelet domain. The parameter estimation curve obtained using the proposed model is classified a flaw in weld region where is contaminated by severe speckle noise and also clear flaw signal is obtained through CA-CFAR threshold estimator that is a nonlinear post-processing method for removing the noise from reconstructed ultrasonic signal.