• 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 Ocean Engineering and Technology
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• v.17 no.3 s.52
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• pp.46-51
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• 2003

Acoustic emission (AE) signals, emanated during local failure of aluminum alloys, have been the subject of numerous investigations. It is well known that the characteristics of AE are strongly influenced by the previous thermal and mechanical treatment of the sample. Possible sources of AE during deformation have been suggested as the avalanche motion of dislocations, fracture of brittle particles, and debonding of these particles from the alloy matrix. The goal of the present study is to determine if AE occurring as the result of fatigue crack propagation could be evaluated by the joint time-frequency analysis method, short time Fourier transform (STFT), and Wigner-Ville distribution (WVD). The time-frequency analysis methods can be used to analyze non-stationary AE more effectively than conventional techniques. STFT is more effective than WVD in analyzing AE signals. Noise and frequency characteristics of crack openings and closures could be separated using STFT. The influence of various fatigue parameters on the frequency characteristics of AE signals was investigated.

• Journal of the Korean Society for Nondestructive Testing
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• v.19 no.4
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• pp.270-276
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• 1999

Fourier transform has been one of the most commonly used tools in study of frequency characteristics of signal. However, based on the Fourier transform. it is hard to tell whether a signal's frequency contents evolve in time or not. Recently, to overcome Fourier transform fault. not to represent non-stationary signal, time-frequency analysis methods are developed and those can represent informations of signal's time and frequency at the same time. In this study we analysed ultrasonic signal for degraded SUS 316 with time-frequency analysis method. In particular the methods such as short time Fourier(STFT) and Wigner-Ville distribution(WVD) were used to extract frequency contents and characteristics from ultrasonic signals.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.11
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• pp.5527-5545
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• 2019

Through-wall ultra-wide band (UWB) radar has been considered as one of the preferred and non-contact technologies for the targets detection owing to the better time resolution and stronger penetration. The high time resolution is a result of a larger of bandwidth of the employed UWB pulses from the radar system, which is a useful tool to separate multiple targets in complex environment. The article emphasised on human subject localization and detection. Human subject usually can be detected via extracting the weak respiratory signals of human subjects remotely. Meanwhile, the range between the detection object and radar is also acquired from the 2D range-frequency matrix. However, it is a challenging task to extract human respiratory signals owing to the low signal to clutter ratio. To improve the feasibility of human respiratory signals detection, a new method is developed via analysing the standard deviation based kurtosis of the collected pulses, which are modulated by human respiratory movements in slow time. The range between radar and the detection target is estimated using joint time-frequency analysis (JTFA) of the analysed characteristics, which provides a novel preliminary signature for life detection. The breathing rates are obtained using the proposed accumulation method in time and frequency domain, respectively. The proposed method is validated and proved numerically and experimentally.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.23 no.9
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• pp.1100-1106
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• 2012

This paper has presented the analysis of the micro-Doppler signatures scattered from the blades of the rotating propeller using the modified HHT method, one of the joint time-frequency analysis methods. The field scattered from the blade edge of the propeller was calculated using equivalent current method(ECM). After the acquisition of the scattered field data in the time domain, the modified HHT method was applied to analyze the micro-Doppler signature. The analysis results showed not only a good agreement with the realistic dynamic characteristic of the blade but also sinusoidally varing characteristics of the micro-Doppler signatures generated from rotating objects. It could be concluded that the joint time-frequency analysis via the modified HHT provided the discriminative characteristics for recognizing a small aircraft target with small RCS value.

• Proceedings of the Korean Fiber Society Conference
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• 1999.04a
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• pp.120-123
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• 1999

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.8 no.2
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• pp.73-79
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• 1999

Most of mechanical structures are combined of substructures such as beams and/or plates. There are few systems with unibody structures but are many systems with united body structures. Generally the dynamic a nalysis of whole structures is performed under alternation load. In the structure design, the analysis of each bolted joint is more important than others for zero severity. This paper presents the analysis method of contact stress distribution factor in the bolted joint with variable fastening torque on joints in the structure. At first, a static vibration test was performed to find out a nominal stress of bolt jointed plates from the relationship between natural frequency and nominal stress. Then a contact stress was computed at contact point between bolt and plate in the structure. It is believed that the proposed method has promisiong implications for safer design with index of contact stress distribution factor and has merits for cost-down and saving time at the beginning of vehicle development.

• Journal of Ocean Engineering and Technology
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• v.13 no.2 s.32
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• pp.90-98
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• 1999

Boiler high-temperature pipelines such as main steam pipe, header and steam drum in fossil power plants are degraded by creep damage due to severe operationg conditions like high temperature and high pressure for an extended period time. Such material degradation lead to various component faliures causing serious accidents at the plant. Conventional measurement techniques such as replica method, electric resistance method, and hardness test method have such disadvantages as complex preparation and measurement procedures, too many control parameters, and therefore, low practicality and they were applied only to component surfaces with good accessibility. In this study, both artificial creep degradation test using life prediction formula and frequency analysis by ultrasonic tests for their preparing creep degraded specimens have been carried out for the purpose of nondestructive evaluation for creep damage which can occur in high-temperature pipelline of fossil power plant. As a result of ultrasonic tests for crept specimens, we confirmed that the high frequency side spectra decrease and central frequency components shift to low frequency bans, and bandwiths decrease as increasing creep damage in backwall echoes.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.12
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• pp.5860-5876
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• 2018

A single snapshot data can only provide limited amount of information so that the rank of covariance matrix is not full, which is not adopted to complete the parameter estimation directly using the traditional super-resolution method. Aiming at solving the problem, a joint time delay and angle estimation using matrix pencil method based on information reconstruction vector for orthogonal frequency division multiplexing (OFDM) signal is proposed. Firstly, according to the channel frequency response vector of each array element, the algorithm reconstructs the vector data with delay and angle parameter information from both frequency and space dimensions. Then the enhanced data matrix for the extended array element is constructed, and the parameter vector of time delay and angle is estimated by the two-dimensional matrix pencil (2D MP) algorithm. Finally, the joint estimation of two-dimensional parameters is accomplished by the parameter pairing. The algorithm does not need a pseudo-spectral peak search, and the location of the target can be determined only by a single receiver, which can reduce the overhead of the positioning system. The theoretical analysis and simulation results show that the estimation accuracy of the proposed method in a single snapshot and low signal-to-noise ratio environment is much higher than that of Root Multiple Signal Classification algorithm (Root-MUSIC), and this method also achieves the higher estimation performance and efficiency with lower complexity cost compared to the one-dimensional matrix pencil algorithm.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.57 no.4
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• pp.729-734
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• 2008

Vibroarthrographic(VAG) signals, emitted by human knee joints, are non-stationary and multi-component in nature and time-frequency distributions(TFD) provide powerful means to analyze such signals. The objective of this paper is to classify VAG signals, generated during joint movement, into two groups(normal and patient group) using the characteristic parameters extracted by time-frequency transform, and to evaluate the classification accuracy. Noise within TFD was reduced by singular value decomposition and back-propagation neural network(BPNN) was used for classifying VAG signals. The characteristic parameters consist of the energy parameter, energy spread parameter, frequency parameter, frequency spread parameter by Wigner-Ville distribution and the amplitude of frequency distribution, the mean and the median frequency by fast Fourier transform. Totally 1408 segments(normal 1031, patient 377) were used for training and evaluating BPNN. As a result, the average value of the classification accuracy was 92.3(standard deviation ${\pm}0.9$)%. The proposed method was independent of clinical information, and showed good potential for non-invasive diagnosis and monitoring of joint disorders such as osteoarthritis and chondromalacia patella.