• Proceedings of the KIEE Conference
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• 1999.07e
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• pp.2057-2059
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• 1999

This paper describes the phenomena of the refraction and reflection when the ultrasonic signals generated by PD(Partial Discharge) in a transformer propagate through the boundary between insulating oil and the tank of the transformer. In this paper, considering the characteristic of the ultrasonic signal and the velocity of the propagation in medium, propagation time from PD source to sensor for incidence angle was calculated. As a result, it was found that the shortest time at specific angle exists. Taking into account the velocity of the propagation in medium, the shortest time with a computer was simulated. It was shown that the simulation was same as experimental result at a real PD source in the transformer.

• Journal of the Korean Institute of Electrical and Electronic Material Engineers
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• v.16 no.9
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• pp.838-841
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• 2003

This paper shows results on the application of optical fiber sensors(OFS) for locations of ultrasonic signals in silicon insulating oil. The OFS system based on the principle of Sagnac interferometry has been designed and established for this work. The hollowed cylindrical mandrel wound by single mode optical fiber was used as a sensing component and ultrasonic signals which simulate the partial discharge In the oil have been generated by PZT actuator operated with function generator. The experimental results shows that the OFS has a excellent performance for the PD location with resolutions less than 1$^{\circ}C$ error range in the miniature insulating oil tank.

• Journal of Electrical Engineering and information Science
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• v.1 no.2
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• pp.45-51
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• 1996

This paper presents a neural network approach for on-line estimation of partial discharge(PD) location using advanced correlation technique in power transformer. Ultrasonic sensors detect ultrasonic signals generated by a PD and the proposed method calculates time difference between the ultrasonic signals at each sensor pair using the cross-correlation technique applied by moving average and the Hamming window. The neural network takes distance difference as inputs converted from time difference, and estimates the PD location. Case studies showed that the proposed method using advanced correlation technique and a neural network estimated the PD location better than conventional methods.

• Smart Structures and Systems
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• v.18 no.3
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• pp.471-484
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• 2016

Optical fiber sensors have been proven that they have the potential to detect high-frequency ultrasonic signals, in structural health monitoring field which generally refers to acoustic emission signals from active structural damages and guided waves excited by ultrasonic actuators and propagating in waveguide. In this work, the sensing properties of optical fiber sensors based on Mach-Zehnder interferometer were investigated in the metal plate. Analytical formulas were conducted first to explore the parameters affecting its sensing performances. Due to the simple and definable frequency component, the Lamb wave excited by the piezoelectric wafer was employed to study the sensitivity of the proposed optical fiber sensors with respect to the frequency, rather than the acoustic emission signals. In the experiments, according to above investigations, spiral shape optical fiber sensors with different size were selected to increase their sensitivity. Lamb waves were excited by a circular piezoelectric wafer, while another piezoelectric wafer was used to compare their voltage responses. Furthermore, by changing the excitation frequency, the tuning frequency characteristic of the proposed optical fiber sensor was also investigated experimentally.

• International Journal of Control, Automation, and Systems
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• v.6 no.5
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• pp.767-775
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• 2008

Methods used for exploring marine resources and spaces include positioning a probe under water and then recalling it after a specified time. Hydro-acoustic Releasers are commonly used for positioning and retrieving of such exploration equipment. The most important factor in this kind of system is the reliability for recalling the instruments. The frequently used ultrasonic signal detection method can detect ultrasonic signals using a fixed comparator, but because of increased rates of errors due to outside interferences, information is repetitively acquired. This study presents an effective ultrasonic signal detection algorithm using the characteristics of a resonance and adaptive comparator Combined with the FSK+ASK modulator. As a result, approximately 8.8% of ultrasonic wave communication errors caused by background noise and transmission losses were reduced for effectively detecting ultrasonic waves. Furthermore, the resonance circuit's quality factor was enhanced (Q = 120 to 160). As such, the bias voltage of the transistor (Vb= 3.3 to 6.8V) was increased thereby enhancing the frequency's selectivity.

• The Journal of the Acoustical Society of Korea
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• v.18 no.7
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• pp.45-55
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• 1999

In this paper, we used the WLMS(Wavelet domain Least Mean Square) adaptive filter based on the wavelet transform to cancel grain noise. Usually, grain noise occurs in changes of the crystalline structure of metals in high temperature environment. It makes the detection of flaw difficult. The WLMS adaptive filtering algorithm establishes the faster convergence rate by orthogonalizaing the input vector of adaptive filter as compared with that of LMS adaptive filtering algorithm in time domain. We implemented the WLMS adaptive filter by using the delayed version of the primary input vector as the reference input vector and then implemented the CA-CFAR(Cell Averaging- Constant False Alarm Rate) threshold estimator. CA-CFAR threshold estimator enables to detect the flaw and back echo signals automatically. Here, we used the output signals of adaptive filter as its input signal. To Cow the statistical characteristic of ultrasonic signals corrupted by grain noise, we performed run test. The results showed that ultrasonic signals are nonstationary signal, that is, signals whose statistical properties vary with time. The performance of each filter is appreciated by the signal-to-noise ratio. After LMS adaptive filtering in time domain, SNR improves to about 2-3㏈ but after WLMS adaptive filtering in wavelet domain, SNR improves to about 4-6㏈.

• International Journal of Fluid Machinery and Systems
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• v.8 no.4
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• pp.264-273
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• 2015

This presentation describes an experimental approach for the detection of cavitation in hydraulic machines by use of ultrasonic signal analysis. Instead of using the high frequency pulses (typically 1MHz) only for transit time measurement different other signal characteristics are extracted from the individual signals and its correlation function with reference signals in order to gain knowledge of the water conditions. As the pulse repetition rate is high (typically 100Hz), statistical parameters can be extracted of the signals. The idea is to find patterns in the parameters by a classifier that can distinguish between the different water states. This classification scheme has been applied to different cavitation sections: a sphere in a water flow in circular tube at the HSLU in Lucerne, a NACA profile in a cavitation tunnel and two Francis model test turbines all at LMH in Lausanne. From the signal raw data several statistical parameters in the time and frequency domain as well as from the correlation function with reference signals have been determined. As classifiers two methods were used: neural feed forward networks and decision trees. For both classification methods realizations with lowest complexity as possible are of special interest. It is shown that two to three signal characteristics, two from the signal itself and one from the correlation function are in many cases sufficient for the detection capability. The final goal is to combine these results with operating point, vibration, acoustic emission and dynamic pressure information such that a distinction between dangerous and not dangerous cavitation is possible.

• Journal of Biomedical Engineering Research
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• v.4 no.1
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• pp.29-36
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• 1983

In this paper, center frequency down slift of ultrasonic echo signals which for the measurements of frequency dependent attenuation in the biological tissue are estimated. Center frequency down shift of echo-signals are estimated after signal spectrum analysis of whole echo-signals. In case of signal spectrums are simple, estimation of down shift frequency is very simple and in case of complicate spectrum, estimation of down shift frequency is depend on spectral shape. In case of unable to estimate, frequency dependence of medium is nonlinear(n) 1), in which upper shift of spectrums are presented. In case of unable to estimate, spectrum analysis are performed at local position. At consquence, we know that spectral dispersions are caused complicately by biological tissue layer.

• The Journal of the Acoustical Society of Korea
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• v.35 no.2
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• pp.134-142
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• 2016

In this paper, a method synthesizing speech signal using the 40 kHz ultrasonic signals reflected from the articulatory muscles was introduced and performance was evaluated. When the ultrasound signals are radiated to articulating face, the Doppler effects caused by movements of lips, jaw, and chin observed. The signals that have different frequencies from that of the transmitted signals are found in the received signals. These ADS (Acoustic-Doppler Signals) were used for estimating of the speech parameters in this study. Prior to synthesizing speech signal, a quantitative correlation analysis between ADS and speech signals was carried out on each frequency bin. According to the results, the feasibility of the ADS-based speech synthesis was validated. ADS-to-speech transformation was achieved by the joint Gaussian mixture model-based conversion rules. The experimental results from the 5 subjects showed that filter bank energy and LPC (Linear Predictive Coefficient) cepstrum coefficients are the optimal features for ADS, and speech, respectively. In the subjective evaluation where synthesized speech signals were obtained using the excitation sources extracted from original speech signals, it was confirmed that the ADS-to-speech conversion method yielded 72.2 % average recognition rates.

• Journal of Institute of Control, Robotics and Systems
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• v.12 no.10
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• pp.955-961
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• 2006

The global ultrasonic system for the self-localization of a mobile robot consists of several ultrasonic transmitters fixed at some reference positions in the global coordinates of robot environment. By activating the ultrasonic transmitters, the mobile robot is able to get the distance to the ultrasonic transmitters and compute its own position in the global coordinate. Due to the limitation on the ultrasonic signal strength and beam width as well as the environmental obstacles however, the ultrasonic signals from some generator may not be transmitted to the robot. Thus, instead of activating the all ultrasonic transmitters, it is necessary to select some ultrasonic generators to activate based on the current robot position. In this paper, we propose a selective activation algorithm for self-localization with the global ultrasonic system. The selective activation algorithm gets the meaningful ultrasonic data at every sampling instants, which results in the faster and more accurate response of the self-localization than the conventional sequential activation. Through the self-localization and path following control, we verify the effectiveness of the proposed selective activation algorithm.