• Proceedings of the KIEE Conference
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• 1999.07b
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• pp.969-971
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• 1999

Wavelet analysis is applying to many fields such as the time-frequency localization of a time series and a time varying data. In this paper, a statistical testing based Wavelet power spectrum analysis for the stationary Nino3 Sea Surface Temperature(SST) data was executed. Specially, the 95% confidence level for SST was effective in searching the periods of El-Nino using various wavelet basis functions.

• Journal of Mechanical Science and Technology
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• v.19 no.spc1
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• pp.429-436
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• 2005

This paper presents a precise and stable time integration method for dynamic analysis of vibration or multibody systems. A total system is divided into several subsystems and their responses are calculated separately, while the coupling effect is treated equivalently as constant force during time steps. By using iterative procedure to improve equivalent coupling forces, a precise and stable solution is obtained. Some examples such as a seismic response and multibody analyses were carried out to demonstrate its usefulness.

• KIPS Transactions on Computer and Communication Systems
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• v.3 no.10
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• pp.377-382
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• 2014

Analysis techniques of the data over time from the mobile environment and IoT, is mainly used for extracting patterns from the collected data, to find meaningful information. However, analytical methods existing, is based to be analyzed in a state where the data collection is complete, to reflect changes in time series data associated with the passage of time is difficult. In this paper, we introduce a method for analyzing multi-block streaming data(AM-MBSD: Analysis Method for Multi-Block Stream Data) for the analysis of the data stream with multiple properties, such as variability of pattern and large capacitive and continuity of data. The multi-block streaming data, define a plurality of blocks of data to be continuously generated, each block, by using the analysis method of the proposed method of analysis to extract meaningful patterns. The patterns that are extracted, generation time, frequency, were collected and consideration of such errors. Through analysis experiments using time series data.

• International Journal of Automotive Technology
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• v.5 no.4
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• pp.257-268
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• 2004

The wavelet analysis method is introduced in this paper to study the nonstationary vibration of vehicles. A new road model, a so-called time domain correlated four-wheel road roughness, which considers the coherence relationships between the four wheels of a vehicle, has been newly developed. Based on a vehicle model with eight degrees of freedom, the analysis of nonstationary random vibration responses was carried out in a time domain on a computer. Verification of the simulation results show that the proposed road model is more accurate than previous ones and that the simulated responses are credible enough when compared with some references. Furthermore, by taking wavelet analysis on simulated signals, some substantial rules of vehicle nonstationary vibration, such as the relationship between each vibration level, and how the vibration energy flows on a time-frequency map, beyond those from conventional spectral analysis, were revealed, and these will be of much benefit to vehicle design.

• Proceedings of the Korean Society For Composite Materials Conference
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• 2004.10a
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• pp.47-50
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• 2004

It is very important that the analysis of postbuckling characteristics for stiffened composite structure. Damage tolerance design concept has been imported in many aerospace structures design to increase the structural efficiency and material failure is an inevitable process in postbuckling behavior. These design concepts are very efficient but consume very much calculation time in analytical process. The proper analysis method for reducing calculation time was researched and the total analysis time was reduced. A selection of proper element, the large load increments in linear response region, and the termination of analysis for unnecessary region were imported in the analysis and about $70\%$ time reduction was achieved with keeping a high accuracy of results.

• Journal of Power System Engineering
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• v.3 no.1
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• pp.74-79
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• 1999

This paper describes formulation for algorithm of time historical response analysis of vibration for straight-line structure. This method is derived from a combination of the transfer stiffness coefficient method and the Newmark method. And this present method improves the computational accuracy of the transient vibration response analysis remarkably owing to several advantages of the transfer stiffness coefficient method. We regarded the structure as a lumped mass system here. The analysis algorithm for the time historical response was formulated for the straight-line structure containing crooked, tree type system. The validity of the present method compared with the transfer matrix method and the Finite Element Method for transient vibration analysis is demonstrated through the numerical computations.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.55 no.1
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• pp.13-17
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• 2006

In this paper, the RCF(Resistive Companion Form) analysis method which is used to analyze small signal stability problems of non-continuous systems including switching devices. The RCF analysis method is mathematically rigorous and computes eigenvalue of the system periodic transition matrix based on discrete system analysis method. As an effect of switching operations, the eigenvalues of the systems are changed and newly unstable oscillation modes may be occurred. As an illustrating example, the oscillation modes of the system with different switching time intervals are computed exactly by the RCF analysis method and the results show that ON/OFF time intervals of switching equipments are important factors to make the system stable or unstable. This result shows that the RCF analysis method is very powerful to analyze small signal stability problems of power systems including switching devices such as FACTS equipments.

• Journal of the Korean Society for Railway
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• v.12 no.6
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• pp.989-995
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• 2009

Short-time Fourier transforms (STFT) are useful for analyzing signals with harmonics that vary with time. If the variation of the harmonics with time is smooth, such as in kinematic vibrations in vehicles, then it is possible to improve the STFT using order spectra and correlation analysis. In this paper, it is shown how correlation analysis can be performed when the speed signal is noisy or unknown and then it is shown how order spectra become simple to compute after this analysis. The results are illustrated by an analysis of axle and car body vibrations in the prototype high-speed train, HSR-350x.

• Earthquakes and Structures
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• v.3 no.6
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• pp.839-852
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• 2012

Earthquake records are often analyzed in various earthquake engineering problems, making time-frequency analysis for such records of primary concern. The best tool for such analysis appears to be based on wavelet functions; selection of which is not an easy task and is commonly carried through trial and error process. Furthermore, often a particular wavelet is adopted for analysis of various earthquakes irrespective of record's prime characteristics, e.g. wave's magnitude. A wavelet constructed based on records' characteristics may yield a more accurate solution and more efficient solution procedure in time-frequency analysis. In this study, a low-pass reconstruction filter is obtained for each earthquake record based on multi-resolution decomposition technique; the filter is then assigned to be the normalized version of the last approximation component with respect to its magnitude. The scaling and wavelet functions are computed using two-scale relations. The calculated wavelets are highly efficient in decomposing the original records as compared to other commonly used wavelets such as Daubechies2 wavelet. The method is further advantageous since it enables one to decompose the original record in such a way that a clear time-frequency resolution is obtained.

• The Journal of Information Systems
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• v.22 no.3
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• pp.25-42
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• 2013

Recently various kinds of Information Technology services are created and the quantities of the data flow are increase rapidly. Not only that, but the data patterns that we deal with also slowly becoming diversity. As a result, the demand of discover the meaningful knowledge/information through the various mining analysis such as linkage analysis, sequencing analysis, classification and prediction, has been steadily increasing. However, solving the business problems using data mining analysis does not always concerning, one of the major causes of these limitations is there are some analyzed data can't accurately reflect the real world phenomenon. For example, although the time gap of purchasing the two products is very short, by using the traditional sequencing analysis, the precedence relationship of the two products is clearly reflected. But in the real world, with the very short time interval, the precedence relationship of the two purchases might not be defined. What was worse, the sequence of the purchase intention and the sequence of the purchase realization of the two products might be mutually be reversed. Therefore, in this study, an expanded sequencing analysis methodology has been proposed in order to reflect this situation. In this proposed methodology, the purchases that being made in a very short time interval among the purchase order which might not important will be notice, and the analysis which included the original sequence and reversed sequence will be used to extend the analysis of the data. Also, to some extent a very short time interval can be defined as the time interval, so an experiment were carried out to determine the varying based on the time interval for the actual data.