• Steel and Composite Structures
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• v.21 no.6
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• pp.1183-1210
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• 2016

Viscoelastic sandwich structures (VSSs) are widely used in mechanical equipment, but in the service process, they always suffer from aging which affect the whole performance of equipment. Therefore, aging state recognition of VSSs is significant to monitor structural state and ensure the reliability of equipment. However, non-stationary vibration response signals and weak state change characteristics make this task challenging. This paper proposes a novel method for this task based on adaptive second generation wavelet packet transform (ASGWPT) and multiwavelet support vector machine (MWSVM). For obtaining sensitive feature parameters to different structural aging states, the ASGWPT, its wavelet function can adaptively match the frequency spectrum characteristics of inspected vibration response signal, is developed to process the vibration response signals for energy feature extraction. With the aim to improve the classification performance of SVM, based on the kernel method of SVM and multiwavelet theory, multiwavelet kernel functions are constructed, and then MWSVM is developed to classify the different aging states. In order to demonstrate the effectiveness of the proposed method, different aging states of a VSS are created through the hot oxygen accelerated aging of viscoelastic material. The application results show that the proposed method can accurately and automatically recognize the different structural aging states and act as a promising approach to aging state recognition of VSSs. Furthermore, the capability of ASGWPT in processing the vibration response signals for feature extraction is validated by the comparisons with conventional second generation wavelet packet transform, and the performance of MWSVM in classifying the structural aging states is validated by the comparisons with traditional wavelet support vector machine.

• The Transactions of the Korean Institute of Power Electronics
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• v.27 no.3
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• pp.206-213
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• 2022

This paper presents setting up a laboratory-scale testbed to estimate the aging of power MOSFET devices and integrated power modules by measuring its on-state voltage and current. Based on the aging mechanisms of the component inside the power module (e.g., bond-wire, solder layer, and semiconductor chip), a system to measure the on-state resistance of device-under-test (DUT) is designed and experimented: a full-bridge circuit applies current stress to DUT, and a temperature chamber controls the ambient temperature of DUT during the aging test. The on-state resistance of SiC MOSFET measured by the proposed testbed was increased by 2.5%-3% after 44-hour of the aging test.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2019.05a
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• pp.283-284
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• 2019

In the last decades patient's suffering with Parkinson's disease is increasing at a rapid rate and as per prediction it will grow more rapidly as old age population is increasing at a rapid rate through out the world. As the performance of wearable sensor based approach reached to a new height as well as powerful machine learning technique provides more accurate result these combination has been widely used for assessment of various neurological diseases. ON state is the state where the effect of medicine is present and OFF state the effect of medicine is reduced or not present at all. Classification of ON/OFF state for the Parkinson's disease is important because the patients could injure them self due to freezing of gait and gait related problems in the OFF state. in this paper wearable sensor based approach has been used to collect the data in ON and OFF state and machine learning techniques are used to automate the classification based on the gait pattern. Supervised machine learning techniques able to provide 97.6% accuracy while classifying the ON/OFF state.

• Corrosion Science and Technology
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• v.5 no.3
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• pp.99-105
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• 2006

This paper is to investigate feasibility on quantitative aging state of epoxy coating on concrete wall in containment structure under operation of nuclear power plants. For evaluating the physical characteristics of the epoxy coating, adhesion strengths of two kinds of degraded epoxy coating systems on both steel surfaces and concrete surfaces were measured via accelerated aging. Comparatively impedance data taken by ultrasonic test were also taken to relate with adhesion data. After aging, in case of concrete, from half of specimens, aging of epoxy coating was developed. As for steel, on $4^{th}$ inspection day, adhesion force was failed. To improve reliability on quality degradation of epoxy, relationship between adhesion and impedance was analyzed. By tracing to co-respond to these data, it was possible to Fig. out physical state of as-built epoxy coating. The possibility to develop new methodology of time - dependent aging state on epoxy coating was found and discussed.

• Journal of Electrical Engineering and Technology
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• v.13 no.3
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• pp.1355-1362
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• 2018

In order to obtain a better understanding of the ageing process of the field composite insulators, it is necessary to explore a quantitative-valuation method for the aging state evaluation. And the linear relationship between volume resistivity and temperature is proposed. In this paper, the composite insulators with different lengths of operating lives from two manufacturers were tested. The relationship between trap characteristics and volume resistivity-temperature characteristics were analyzed based on Thermal Stimulated Current (TSC), volume resistivity-temperature test, Scanning Electron Microscope (SEM) and Fourier Transform Infrared Spectroscopy (FTIR). Furthermore, the application of trap characteristics in the quantitative evaluation of aging state of composite insulators was discussed. The results showed that there was a general negative correlation between the relative variation ratio of trap charges and the volume resistivity-temperature characteristics. Meanwhile, the physicochemical properties would change with the aging time, which would result in the increasing of electron traps. Combined with the TSC and volume resistivity test results, the trap characteristic thresholds which indicated the serious age of the composite insulators had been proposed.

• Journal of Electrical Engineering and Technology
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• v.13 no.6
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• pp.2412-2420
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• 2018

The thermal degradation of low density polyethylene (LDPE) will accelerate the production of carbonyl groups (C=O), which can act as the induced dipoles under high voltage. In this paper, we researched the dielectric properties and space charge behavior of LDPE after thermal aging, which can help us to understand the correlation between carbonyl groups (C=O) and electrical properties of LDPE. The spectra results show that LDPE exhibit obvious thermooxidative reactions when the aging time is 35 days and the productions mainly contain carboxylic acid, carboxylic eater and carboxylic anhydride, whose amount increase with the increasing of aging time. The dielectric properties show that the real permittivity of LDPE is inversely proportional to temperature before aging and subsequently become proportional to temperature after thermal aging. Furthermore, both the real and imaginary permittivity increase sharply with the increasing of aging time. The fitting results of imaginary permittivity show that DC conductivity become more sensitive about temperature after thermal aging. On this basis, the active energies of materials calculated from DC conductivity increase first and then decrease with the increasing of aging time. In addition, the space charge results show that the heterocharges accumulated near electrodes in LDPE change to the homocharges after thermal aging and the mean volume charge density increase with the increasing of aging time. It is considered that the overlaps caused by electrical potential area is the main reason for the increase of DC conductivity.

• Bulletin of the Korean Chemical Society
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• v.35 no.3
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• pp.811-814
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• 2014

Bio-oil instability, or aging, is a significant problem for the long-term storage of fast pyrolysis oils. We investigated bio-oil aging at the molecular level using Fourier-transform ion cyclotron resonance mass spectrometry. Petroleomic analysis suggests that bio-oil aging is resulted from the oligomerization of phenolic lignin products whereas 'sugaric' cellulose/hemicellulose products have negligible effect.

• Journal of IKEEE
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• v.18 no.3
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• pp.298-304
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• 2014

Proper operation of the battery powered systems depends on the accuracy of the battery SOC(State of Charge) estimation, therefore it is critical for those systems that SOC is accurately determined. The SOC of the battery is related to the battery aging and the SOC estimation methods without considering the aging of the battery are not accurate. In this paper, a new method that accurately estimate the SOC of the battery is proposed considering the aging of the battery. A mathematical model for the Battery SOC-OCV(Open Circuit Voltage) relationship is presented using Boltzmann equation and aging indicator is defined, and then the SOC is estimated combining the mathematical model and aging indicator. The proposed method takes the aging of the battery into consideration, which leads to an accurate estimation of the SOC. The simulations and experiments show the effectiveness of the proposed method for improving the accuracy of the SOC estimation.

• Journal of the Korean Institute of Electrical and Electronic Material Engineers
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• v.14 no.1
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• pp.84-92
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• 2001

In this papers, we proposed the new method in order to diagnosis aging state of transformers. For wavelet transform, Daubechies filter is used, we can obtain wavelet coefficients which is used to extract feature of statistical parameters (maximum value, average value, dispersion skewness, kurtosis) about each acoustic emission signal. Also, these coefficients are used to identify normal and fault signal of internal partial discharge in transformer. As improved method for classification use neural network. Extracted statistical parameters are input into an back-propagation neural network. The number of neurons of hidden layer are obtained through Result of Cross-Validation. The network, after training, can decide whether the test signal is early aging state, alst aging state or normal state. In quantity analysis, capability of proposed method is superior to compared that of classical method.

• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
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• 2000.07a
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• pp.645-650
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• 2000

The discrete wavelet transform is utilized as processing of neural network(NN) to identifying aging state of internal partial discharge in transformer. The discrete wavelet transform is used to produce wavelet coefficients which are used for classification. The mean values of the wavelet coefficients are input into an back-propagation neural network. The networks, after training, can decide if the test signals is aging early state or aging last state, or normal state.