• Transactions of the Korean Society of Machine Tool Engineers
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• v.14 no.3
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• pp.38-46
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• 2005

The destructive method is reliable and widely used for the estimation of material degradation but it have time-consuming and a great difficulty in preparing specimens from in-service industrial facilities. Therefore, the estimation of degraded structural materials used at high temperature by nondestructive evaluation such as electric resistance method, replica method, Barkhausen noise method, electro-chemical method and ultrasonic method are strongly desired. In this study, various nondestructive evaluation(NDE) parameters of the Barkhausen noise method, such as MPA(Maximum Peak Amplitude), RMS, IABNS(Internal Area of Barkhausen Noise on Signal) and average amplitude of frequency spectrum are investigated and correlated with thermal damage level of 2.25cr-1.0Mo steel using wavelet analysis. Those parameters tend to increase while thermal degradation proceeds. It also turns out that the wavelet technique can help to reduce experimental false call in data analysis.

• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
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• 2004.07b
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• pp.1183-1186
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• 2004

Degradation and insulation failure of traction motor depend on the continuous stress imposed on it. And knowing on insulation condition is important thing for safety operation of EMU(electric multiple unit). In this paper, PD(partial discharge) characteristics for degradation analysis of stator coil is studied. For PD data acquisition, two models are made; one is normal condition coil, the other is aged condition coil. And PD data for discrimination were acquired from PD detector. And these data making use of a computer-aided discharge analyser, statistical and other discharge parameters is calculated to discrimination between different discharge sources. And also these parameter is applied to classify PD sources by neural networks. Neural Networks has good recognition rate for degradation of stator coil.

• The Transactions of the Korean Institute of Electrical Engineers C
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• v.50 no.2
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• pp.60-64
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• 2001

The degradation process of silicone rubber was investigated by leakage current monitoring in Inclined-Plane method. DAS (Data Acquisition System) with 12-bit, 8-channel A/D converter was prepared. Average current, cumulative charge, current waveform and the number of peak pulses were measured on-line. And, FFT (Fast Fourier Transform) analysis was performed with stored current waveform. Besides, maximum erosion depth was measured in order to use as the indicator of the degradation process. So, the results of leakage current components and maximum erosion depth measurements were compared to find one or more components which have trends of changing similarly to that of erosion process. The result suggests that the ratio of peak current to r.m.s. current, harmonic contents and the number of peak pulses are well corresponding with the degradation process.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.37 no.4
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• pp.372-382
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• 2009

A GNSS software for processing the SBAS correction data is developed, and Japan MSAS correction data is analyzed. MSAS orbit correction data is analyzed and compared with WAAS data. MSAS ionosphere correction data is analyzed and the effect of the equatorial anomaly on the correction accuracy is discussed. Degradation due to receive delay of correction information and effect of the degradation on protection level analyzed using partial remove of MSAS correction information. Integrity and availability for precision approch using the MSAS system analyzed.

• 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.

• Analytical Science and Technology
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• v.37 no.5
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• pp.280-294
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• 2024

This study introduces a novel analytical method for the assessment of pralsetinib impurities and degradation products (DPs), addressing critical gaps in existing methodologies. This research aims to develop a robust HPLC method for impurity analysis, characterize degradation products using LC-MS, and evaluate the environmental impact of the method. The study began by optimizing HPLC conditions with various columns and buffers, ultimately achieving successful separation using an XBridge^® RP-C18 column with ethanol as solvent A and 50 mM formic acid at pH 2.9. This setup provided excellent peak resolution and symmetry, essential for reliable stability studies. The developed HPLC method was then adapted for HPLC-MS/MS, enhancing sensitivity and detection efficiency of DPs. Stress degradation studies of pralsetinib under different conditions (acidic, basic, oxidative, thermal, and photolytic) revealed significant degradation under acidic (29.3 %) and basic (21.5 %) conditions, with several DPs identified. Oxidative stress resulted in 19.8 % degradation, while thermal and photolytic conditions caused minimal degradation. HPLC-MS/MS analysis identified structures of five degradation products, providing detailed insights into pralsetinib's stability and degradation pathways. Method validation followed ICH guidelines Q2(R1), confirming method's specificity, selectivity, sensitivity, linearity, accuracy, precision, and robustness. The method exhibited strong linearity with a coefficient of determination (r²) greater than 0.999 for pralsetinib and its impurities. This method advances impurity detection and DPs characterization, ensuring the quality and safety of pralsetinib. Additionally, method's environmental impact was assessed, aligning with sustainable analytical practices. These findings provide essential data on pralsetinib's stability, guiding storage conditions and ensuring its efficacy and safety in pharmaceutical applications.

• Journal of Applied Reliability
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• v.18 no.2
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• pp.114-121
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• 2018

Purpose: This study proposes a process for evaluating the preventive maintenance policy for a system with degradation characteristics and for calculating the appropriate preventive maintenance cycle using time- and condition-based maintenance. Methods: First, the collected data is divided into the maintenance history lifetime and degradation lifetime, and analysis datasets are extracted through preprocessing. Particle filter algorithm is used to estimate the degradation lifetime from analysis datasets and prior information is obtained using LSE. The suitability and cost of the existing preventive maintenance policy are each evaluated based on the degradation lifetime and by using a minimum repair block replacement model of time-based maintenance. Results: The process is applied to the degradation of the reverse osmosis (RO) membrane in a seawater reverse osmosis (SWRO) plant to evaluate the existing preventive maintenance policy. Conclusion: This method can be used for facilities or systems that undergo degradation, which can be evaluated in terms of cost and time. The method is expected to be used in decision-making for devising the optimal preventive maintenance policy.

• The Transactions of the Korean Institute of Electrical Engineers C
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• v.53 no.10
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• pp.515-522
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• 2004

In this study, we tried to investigate that the advantages of SOM(Self Organizing Map) algorithm such as data accumulation ability and the degradation trend trace ability would be adaptable to the analysis of partial discharge pattern recognition. For the purpose, we analyzed partial discharge data obtained from the typical artificial defects in GIS and XLPE power cable system through SOM algorithm. As a result, partial discharge pattern recognition could be well carried out with an acceptable error by use of Kohonen map in SOM algorithm. Also, it was clarified that the additional data could be accumulated during the operation of the algorithm. Especially, we found out that the data accumulation ability of Kohonen map could make it possible to suggest new patterns, which is impossible through the conventional BP(Back Propagation) algorithm. In addition, it is confirmed that the degradation trend could be easily traced in accordance with the degradation process. Therefore, it is expected to improve on-site applicability and to trace real-time degradation trends using SOM algorithm in the partial discharge pattern recognition

• Proceedings of the IEEK Conference
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• 1999.11a
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• pp.651-654
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• 1999

This paper investigates the varying characteristics of the performance degradation resulting from the different combination of wordlength in fixed-point implementation of recursive sinusoidal transform. The performance degradation is analytically derived in the form of noise-to-signal power ratio. The best wordlength combination is shown to be the equal length distribution of the given number of bits between the transform coefficients and the data. The analysis results are also verified through the computer simulations.

• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.817-819
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• 2003

Land degradation is a crucial issue in mountainous areas and is manifested in a variety of processes. For its assessment, application of existing models is not straightforward. In addition, data availability might be a problem. In this paper, a procedure for land degradation assessment is described, which follows a four-step approach: (1) detection, inventory and mapping of land degradation features, (2) assessing the magnitude of soil loss, (3) study of causal factors, and (4) hazard assessment by applying decision trees. This approach is applied to a case study in the Middle Mountain region of Nepal. The study shows that individual mass movement features such as debris slides and slumps can be easily mapped by photo interpretation techniques. Application of soil loss estimation models helps get insight on the magnitude of soil losses. In the study area soil losses are higher in rainfed crops on sloping terraces (highest soil loss is 32 tons/ha/yr) and minimal under dense forest and in irrigated rice fields (less than 1 ton/ha/yr). However there is high frequency of slope failures in the form of slumps in the rice fields. Debris slides are more common on south-facing slopes under rainfed agriculture or in degraded forest. Field evidences and analysis of causal factors for land degradation helps in building decision trees, the use of which for modelling land degradation has the advantage that attributes can be ranked and tested according to their importance. In addition, decision trees are simple to construct, easy to implement and very flexible in adaptations.