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Given the enormous capital value of power transformers and their integral role in the electricity network, increasing attention has been given to diagnostic and monitoring tools as a safety precaution measure to evaluate the internal condition of transformers. This study overcomes the fault diagnosis problem of power transformers using an ultra high frequency drain valve sensor. A convolutional neural network (CNN) is proposed to classify six types of discharge defects in power transformers. The proposed model utilizes the phase-amplitude response from a phase-resolved partial discharge (PRPD) signal to reduce the input size. The performance of the proposed method is verified through PRPD experiments using artificial cells. The experimental results indicate that the classification performance of the proposed method is significantly better than those of conventional algorithms, such as linear and nonlinear support vector machines and feedforward neural networks, at 18.78%, 10.95%, and 8.76%, respectively. In addition, a comparison with the different representations of the data leads to the observation that the proposed CNN using a PA response provides a higher accuracy than that using sequence data at 1.46%.

In this paper, the amount of SF6 decomposition gases due to the partial discharge (PD) was studied in the SF6 gas-insulated transformer. The long-term PD degradation experiment was performed while controlling the discharge magnitude using the surface discharge, and the gas generation amount was measured by using gas chromatography for SO2F2, SOF2, SO2, CO, and CF4. In addition, to investigate the relationship between the partial discharge energy and the decomposed gas generation amount, partial discharge energy was calculated by a data processing program and converted to the unit of joule per mole. With the finite element method (FEM), the electric field distribution and SF6 gas decomposition mechanism were explained for the partial discharge energy effect on the gas generation. This study helps understand the relationship between the partial discharge energy and the decomposed gas generation ratio with the experimental results and can be used for the diagnosis of PD and maintenance process for the gas-insulated transformers.

In this paper, we propose a new method for detecting bearing faults using vibration signals. The proposed method is based on support vector machines (SVMs), which treat the harmonics of fault-related frequencies from vibration signals as fault indices. Using SVMs, the cross-validations are used for a training process, and a two-stage classification process is used for detecting bearing faults and their status. The proposed approach is applied to outer-race bearing fault detection in threephase squirrel-cage induction motors. The experimental results show that the proposed method can effectively identify the bearing faults and their status, hence improving the accuracy of fault diagnosis.

A time-domain transmission measurement technique for extracting the complex propagation constant of a cross-linked polyethylene cable is proposed. For this extraction, a pulse transmitted through the cable is measured in the time domain and analyzed in the frequency domain. The proposed technique does not use an open termination for reflection, and therefore increases the upper frequency of the bandwidth for extraction; by reducing the pulse width, it decreases the measurement error as compared with an existing time-domain reflectometry method.

This paper proposes a new diagnosis algorithm to detect broken rotor bars (BRBs) faults in induction motors. The proposed algorithm is composed of a frequency signal dimension order (FSDO) estimator and a fault decision module. The FSDO estimator finds a number of fault-related frequencies in the stator current signature. In the fault decision module, the fault diagnostic index from the FSDO estimator is used depending on the load conditions of the induction motors. Experimental results obtained in a 75 kW three-phase squirrel-cage induction motor show that the proposed diagnosis algorithm is capable of detecting BRB faults with an accuracy that is superior to a zoom multiple signal classification (ZMUSIC) and a zoom estimation of signal parameters via rotational invariance techniques (ZESPRIT).

This paper presents a two-port time-domain reflectometry(TDR) measurement technique for extracting the complex propagation constant of a cross-linked polyethylene(XLPE) cable. For the extraction, a short pulse transmitted through the cable is measured in the time domain and analyzed in the frequency domain. The propagation constant of a 22.9 kV XLPE cable with a conductor area of 325 is extracted up to a frequency of approximately 2.14 GHz. The measured using a network analyzer and the two-port TDR technique are compared for verification. As a result compared with previous TDR method, the upper possible frequency limit for extracting the propagation constant increases and the measurement error decreases.

The diagnosis of motor failures using an on-line method has been the aim of many researchers and studies. Several spectral analysis techniques have been developed and are used to facilitate on-line diagnosis methods in industry. This paper discusses the first application of a motor flux spectral analysis to the identification of broken rotor bar (BRB) faults in induction motors using a multiple signal classification (MUSIC) technique as an on-line diagnosis method. The proposed method measures the leakage flux in the radial direction using a radial flux sensor which is designed as a search coil and is installed between stator slots. The MUSIC technique, which requires fewer number of data samples and has a higher detection accuracy than the traditional fast Fourier transform (FFT) method, then calculates the motor load condition and extracts any abnormal signals related to motor failures in order to identify BRB faults. Experimental results clearly demonstrate that the proposed method is a promising candidate for an on-line diagnosis method to detect motor failures.

A non-toxic boron-containing material, carborane (C2B10H12), has been utilized to deposit amorphous hydrogenated carbon/boron (a-C/B:H) thin films in helium DC glow discharges. The helium plasma was produced at a target pressure of ∼5 mTorr in the pulsed mode at a duty cycle of 0.375 (3 s on/5 s off) or 0.23 (3 s on/10 s off) by using a filament discharge system connected with a carborane evaporation source. Deposited a-C/B:H thin films were characterized by using variable angle spectroscopic ellipsometry, scanning electron microscopy, Auger electron spectroscopy, and X-ray photoelectron spectroscopy. The a-C/B:H thin films have soft polymer-like characteristics with optical constants of n = 1.65 and k = 10−3 at 632 nm, and the B/C ratio inside the bulk was ∼2 for an ∼60% boron contents. The evaporation characteristics of carborane powder under vacuum were also investigated.

Internal pressure of vacuum interrupter (VI) is one of the most important parameters in VI operation and may increase due to the outgassing from the materials inside VI or gas permeation through metal flange or ceramic vessel. The increase of the pressure above a certain level leads to the failures of switching or insulation. Therefore, an effective pressure check of VI is essential and an analysis of partial discharge (PD) characteristics is an effective monitoring method to identify the degree of the internal pressure of VI. This paper introduces a research work on monitoring the internal pressure of VI by analyzing PDs which were measured using a capacitive PD coupler. The authors have developed cost effective capacitive coupler based on the ceramic material that has an excellent insulation properties and the main component of the capacitive coupler is made by SrTiO3. Detectable internal pressure range and distinguishability of the internal pressure of VI were investigated. From the PD tests results, the internal pressure range, from 10 -2 torr to 500 torr, can be monitored by PD measurements using the capacitive coupler and PD inception voltage (PDIV) follows the Paschen's law. In addition, rise time of PD pulse at 13.2kV decreases with the increase of the internal pressure of VI.

The present study describes the considerations on the long-term reliability of the on-line partial discharge (PD) ceramic sensor for thermal power generators. Voltage acceleration aging tests were carried out under continuous and impulsive thermal aging at more than 100℃, considering the practical service environment. Experimental results show that the sensors have a life that could last for more than 100 years, excellent dielectric characteristics, and insulation strength. In addition, the ceramic on-line PD sensors were installed in a thermal power generator in Korea for demonstration. The results of the PD calibration and test voltage application prove that the on-line ceramic sensors have satisfactory performances for on-line PD measurement.

In this paper, a method for detecting broken rotor bar and stator winding fault in a low voltage squirrel-case induction motor using an air-gap flux variation analysis is proposed to develop a simple and low cost diagnosis technique. To measure the leakage flux in radial direction, a radial flux sensor is designed as a search coil and installed between stator slots. The proposed method is able to identify two kinds of motor faults by calculating load condition of motors and monitoring abnormal signals those are related with motor faults. Experimental results obtained on 7.5kW three-phase squirrel-cage induction motors are discussed to verify the performance of the proposed method. Induction motors are widely used electrical machines, for their simplicity of construction and reliability. However, they are subject to failures those may be due to production processes or operating conditions. These unexpected failures cause severe damages in industrial processes. Motor reliability working group have announced that percentage failure in induction motors is typically: stator related (38%), rotor related (10%), bearing related (40%), and others (12%) (1). Recently, many researchers have studied diagnosis techniques to predict motor failures at their incipient stage and decide proper replacement time of induction motors. Most of them are focused on the failure prediction method using abnormal signals of failure patterns of motors from current and vibration signals (2)- (4). Although vibration and current analysis are the most powerful methods for diagnosing motor faults, their sensors are occasionally difficult to install where the environment of industrial field is in poor condition. In addition to this installation problem, there are many low priced low voltage induction motors in the field. Therefore, the diagnosis technique should be easy to install their sensors and low cost comparing to the price of motors. This paper proposes a method for detecting broken rotor bar and stator winding fault in a low voltage squirrel-cage induction motor using a radial flux sensor to develop a simple and low cost diagnosis technique. The sensor is designed as a search coil and installed between stator slots during motor production to measure the leakage flux in radial direction at the air-gap. The proposed method consists of a calculating load condition, finding abnormal signals and monitoring those signals related with motor faults to indentify two kinds of motor failures. To demonstrate the performance of the method, experimental results obtained on 7.5kW three-phase squirrel-cage induction motors are discussed.

First boronization was performed in KSTAR tokamak during 2009 campaign in order to reduce oxygen impurities and to lower the power loss due to radiation. We report the results from the experiences on carborane during the first boronization in KSTAR. After the boronization, H2O and O2 level in the vacuum vessel are reduced significantly. The characteristics of the deposited thin films were analyzed by variable angle spectroscopic ellipsometry, XPS, and AES. ∼1.78 × 1016 cm−2 s−1 of carbon flux on the wall is estimated by using cavity technique.

First boronization in KSTAR is reported. KSTAR boronization system is based on a carborane (C2B10H12) injection system. The design, construction, and test of the system are accomplished and it is tested by using a small vacuum vessel before it is mounted to a KSTAR port. After the boronization in KSTAR, impurity levels are significantly reduced by factor of 3 (oxygen) and by 10 (carbon). Characteristics of a-C/B:H thin films deposited by carborane vapor are investigated. Re-condensation of carborane vapor during the test phase has been reported.

The partial discharge (PD) measurement is a very effective method to assess the winding insulation condition of high-voltage machines, since most of the insulation failure processes are directly or indirectly caused by PD. On-line PD measurements, which can detect insulation defects of winding in the early stages on rotating machines in operation, have been accepted as the most important technique. The epoxy mica capacitive coupler is currently and extensively used for on-line detection of PD pulses of high-voltage rotating machines. To evaluate the feasibility of developing a capacitive coupler that is easier to manufacture at a lower cost compared to epoxy mica couplers, a 100 ㎊ capacitive coupler made of ceramic material is designed, fabricated and tested for on-line PD measurements of 23 ㎸ electrical machines. A series of electrical tests and accelerated aging tests are performed on the ceramic coupler to evaluate the performance requirements, long-term reliability and thermal stability for in field application. The test results show that the newly developed ceramic coupler provides equal and improved performance at a lower cost compared to epoxy mica couplers, and estimated voltage life is anticipated to surpass 100 years.

In this paper, measurement of hydrogen gas using three kinds of gas sensors were studied for improving selectivity and quantification on hydrogen gas. Output characteristics for each sensors were analyzed to some concentrations of hydrogen gas. It was illustrated that the wide range of hydrogen gas concentrations upto 10,000[ppm] can be reliably measured from investigation of concentration ranges with high amplitudes and good resolutions. Also, the combinations of outputs from three kinds sensors were able to improve the selectivity of hydrogen gas.

Dissolved gas in oil analysis has been used for fault diagnosis of oil immersed insulation. In this paper to improve the reliability in deciding the degradation causes of the oil immersed insulation, we carried out electrical and thermal degradations for the insulations, and analyzed the characteristics of dissolved gases distribution on each situation. As a result more reliable faults discrimination is possible if we use the interrelation of factors like key gases and gas compositions of hydrocarbon gases and ratios of CO/.

Laser Thomson Scattering (LTS) is the non-invasive method for measuring the electron temperature and its density, which can be used for the calibrations of electric probes within collisional and magnetized plasmas. For LTS diagnostics in the low-temperature plasmas, one need to special optics for detection of the scattered light with restricting the Rayleigh and Stray lights. For this, one uses the Triple Grating Spectrometer (TGS), which is composed of Rayleigh block (notch filter for Rayleigh light) and double grating filter (DGF). All focusing lenses are used with achromatic doublet configuration for reducing the non-linear optical effects such as spherical aberration, coma, etc. The specifications of the grating and achromatic doublet lens are 1800 gr/mm with the dimensions of 84 mm × 84 mm and 400 mm of focal length with the diameter of 100 mm, respectively. In this configurations, the linear dispersion is given as 1.006 nm/mm. Considering the dimension of Charged Coupled Device (CCD) with the linear dispersion, the LTS system can be measure the electron temperatures of less than 10 eV (in most laboratory plasmas). The initial measurement of LTS measurement and comparative study with single probe are done in Divertor Plasma Simulator (DiPS) with the following plasma parameters; plasma density of 1011–1013 cm−3, electron temperature of 1–4 eV, and the magnetic field of 0.2–1 kG, respectively.

A newly developed diagnosis system using DGA (dissolved gas analysis) was studied for the effective management of oil-immersed transformers. It consists of the measurement system of dissolved hydrogen gas in oil and DGA software based on dissolved gases such as acetylene (C2H2), hydrogen (H2), ethylene (C2H4), methane (CH4), ethane (C2H6), carbon monoxide (CO) and carbon dioxide (CO2). The system for hydrogen gas measurement was designed using semiconductor gas sensor and polymer membrane. Artificial neural network and rule based DGA possibility in the software were used for recognition of fault causes and decision of fault

Since partial discharges weaken the insulation performance of power transformers, the detection of PD is very important for prevention of fatal incidents. This study describes the use of electromagnetic coupler for the partial discharge measurement of transformers. Folded dipole antennas were used as sensors and installed in test chamber for experiments. The spectrum and oscillogram measured in various defect cells are analyzed and showed. And these partial discharges signals are measured at the same time by two types UHF amplifiers with different bandwidth and a conventional PD detector. From these results, decision of defect type is available

This paper describes the development of an on-line partial discharge detector for high voltage apparatus. This detector consists of acoustic and high frequency current sensors, an amplitude part, an AID part, a data communication part and a computer. The authors study the characteristics of digital signal processing for reducing noise in partial discharge detection. We seek methods for good digital signal processing for detection of partial discharges. We apply the adaptive filtering and predictive filtering methods to the electric signal and cross correlation to the acoustic signal. This paper shows the characteristics of these filtering methods and cross correlation in partial discharge detection.

The initial phase wall conditioning in KSTAR is depicted. The KSTAR wall conditioning procedure consists of vessel baking, glow discharge cleaning (GDC), ICRH wall conditioning (ICWC) and boronization (Bz). Vessel baking is performed for the initial vacuum conditioning in order to remove various kinds of impurities including H2O, carbon and oxygen and for the plasma operation. The total outgassing rates after vessel baking in three successive KSTAR campaigns are compared. GDC is regularly performed as a standard wall cleaning procedure. Another cleaning technique is ICWC, which is useful for inter-shot wall conditioning under a strong magnetic field. In order to optimize the operation time and removal efficiency of ICWC, a parameter scan is performed. Bz is a standard technique to remove oxygen impurity from a vacuum vessel. KSTAR has used carborane powder which is a non-toxic boron-containing material. The KSTAR Bz has been successfully performed through two campaigns: water and oxygen levels in the vacuum vessel are reduced significantly. As a result, KSTAR has achieved its first L–H mode transition, although the input power was marginal for the L–H transition threshold. The characteristics of boron-containing thin films deposited for boronization are investigated.

A new method for detecting eccentricity and broken rotor bar conditions in a squirrel-cage induction motor is proposed. Air-gap flux variation analysis is done using search coils, which are inserted at stator slots. Using this method, the leakage flux in radial direction can be directly detected. Using finite element method, the air-gap flux variation is accurately modeled and analyzed. From the results of the simulation, a motor under normal condition shows maximum magnetic flux density of 1.3T. On the other hand, the eccentric air-gap condition displays about 1.1T at 60° and 1.6T at 240°. A difference of flux density is 0.5T in the abnormal condition, whereas no difference is detected in the normal motor. In the broken rotor bar conditions, the flux densities at 65° and 155° are about 0.4 T and 0.8T, respectively. These simulation results are coincided with those of experiment. Consequently, the measurement of the magnetic flux at air gap is one of effective ways to discriminate the faulted conditions o...