• Journal of Platform Technology
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• v.8 no.3
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• pp.10-21
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• 2020

Partial discharge occurs a lot in high-voltage power equipment such as switchgear, transformers, and switch gears. Partial discharge shortens the life of the insulator and causes insulation breakdown, resulting in large-scale damage such as a power outage. There are several types of partial discharge that occur inside the product and the surface. In this paper, we design a predictive model that can predict the pattern and probability of occurrence of partial discharge. In order to analyze the designed model, learning data for each type of partial discharge was collected through the UHF sensor by using a simulator that generates partial discharge. The predictive model designed in this paper was designed based on CNN during deep learning, and the model was verified through learning. To learn about the designed model, 5000 training data were created, and the form of training data was used as input data for the model by pre-processing the 3D raw data input from the UHF sensor as 2D data. As a result of the experiment, it was found that the accuracy of the model designed through learning has an accuracy of 0.9972. It was found that the accuracy of the proposed model was higher in the case of learning by making the data into a two-dimensional image and learning it in the form of a grayscale image.

• Journal of Sensor Science and Technology
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• v.10 no.1
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• pp.1-8
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• 2001

Conventional microgyroscopes of vibrating type require resonant frequency tuning of the driving and sensing modes to achieve high sensitivity. These tuning conditions depend on each fabricated microgyroscopes, even though the microgyroscopes are identically designed. A new micromachined resonator, which is applicable to microgyroscopes with self-toning characteristics, is presented. Since the laterally driven two degrees of freedom (2DOF) resonator was designed as a symmetric structure with identical stiffness in two orthogonal axes, the resonator is applicable to vibrating microgyroscopes, which do not need mode tuning. A dynamic model of the resonator was derived considering gyroscopic application. The dynamic model was evaluated by experimental comparison with fabricated resonators. The microgyroscopes were fabricated using a simple 2-mask-process of a single polysilicon layer deposited on an insulator layer. The feasibility of the resonator as a vibrating microgyroscopes with self-tuning capability is discussed. The fabricated resonators of a particular design have process-induced non-uniformities that cause different resonant frequencies. For several resonators, the standard deviations of the driving and sensing frequencies were as high as 1232Hz and 1214Hz, whereas the experimental average detuning frequency was 91.75Hz. The minimum detuned frequency was 68Hz with $0.034mVsec/^{\circ}$ sensitivity. The sensitivity of the microgyroscopes was low due to process-induced non-uniformity; the angular rate bandwidth, however, was wide. This resonator could be successfully applicable to a vibrating microgyroscopes with high sensitivity, if improvements in uniformity of the fabrication process are achieved. Further developments in improved integrated circuits are expected to lower the noise level even more.