Sang-Hwa Yi

Development of diagnosis algorithm for induction motor using flux sensor

The development of the diagnosis algorithm is carried out for identifying health and faulted conditions in three-phase induction motors. The algorithm consists of feature calculation, feature extraction, and feature classification procedures in sequence. For that, the non-linear feature extraction method with kernel function is used and the classifier of k-nearest neighbors is introduced to decide motor conditions among normal motor, broken rotor bar, short-turn stator windings, and bearing faults. Signal for this algorithm is acquired flux sensor. It is to measure the change of magnetic flux at the air-gap. To get the effective features related with faults, the peak ratio of some frequencies related with line frequency is introduced. This work proposes the efficient diagnosis method for induction motors by developing the powerful algorithm. The calculated features show a good linearity according to faults severities. Moreover, the final results show a good classification rate on motor conditions.

Study on the Transfer Functions for Detecting Windings Displacement of Power Transformers with Impulse Method

The paper investigates three types of transfer function methods for detecting displacements of winding in a model transformer. To acquire these transfer functions, the measuring method of input voltage, current and its response is used in impulse method. The applied impulse voltages had three rising times, which were short rising time (less than 0.6 ㎲), medium rising time (about 0.8 ㎲) and long rising time (about 1 ㎲) in front waves. Every 10 measurements of voltage and current waves were averaged from 50 measurements of voltage and current waves. These transfer functions were tested in normal, 24mm elevated and 48mm elevated windings conditions and were analyzed with correlation coefficients and spectrum deviations. In the analysis, the results depend on the types of transfer functions and the rising times of input voltages.

MUSIC-based Diagnosis Algorithm for Identifying Broken Rotor Bar Faults in Induction Motors Using Flux Signal

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.

Development of Oil Immersed Transformer Management Technologies by Using Dissolved Gas Analysis

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

A Method to Monitor Vacuum Degree Using Capacitive Partial Discharge Coupler

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 Paschens law. In addition, rise time of PD pulse at 13.2kV decreases with the increase of the internal pressure of VI.

Study on the On-line PD Measurement Technology for Power Transformer

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

Setup of standard PD calibrator and its uncertainties

The present paper describes the setup of standard partial discharge calibrator for measuring partial discharge and estimating uncertainties. The standard PD calibrator was designed and set up, consisting of a digital pulse generator, capacitor modules, and a digital oscilloscope controlled by software developed in the laboratory. Using this software, averages of charges and rising times and their standard deviations in the measured pulses can also be calculated. The standard PD calibrator generates five types of pulses: single, double, random, oscillating, and long-rising. The coefficient sensitivities to estimate the uncertainties of pulses were extracted in the model circuit of the standard PD calibrator. The uncertainties of charges and rising times in pulses of the standard PD calibrator were estimated with single pulses. These values were 0.3%-1.4% in charges and 1.9%-7.0% in rising time; however, these values are lower than the limit values in IEC 60270.

Noise Evaluation Algorithm for Applying Complex Denoising Technique in On-line Partial Discharge Diagnosis System for Power Apparatus

This paper introduces an evaluation code, which can numerically express the noise possessing degree of signals. By using this code, the best kind and setting of noise suppressing techniques can be chosen automatically. This code is applied to three kinds of specific denoising techniques; those are simple noise removing method in the count versus phase distribution, fuzzy logic method based on noise type in magnitude versus phase plot, and lastly, the technique using grouping characteristics of PD pulses in 3D plot of magnitude versus phase versus cycle. The algorithm shows good performance in the various real PD signals measured from various high voltage apparatuses in Korea.

A novel complex algorithm for denoising partial discharge signals

This paper introduces an evaluation code, which can numerically express the noise possessing degree of signals. By using this code, the best kind and setting of noise suppressing techniques can be chosen automatically. This code is applied to three kinds of specific denoising techniques; those are simple noise removing method in the count versus phase distribution, fuzzy logic method based on noise type in magnitude versus phase plot, and lastly, the technique using grouping characteristics of PD pulses in 3D plot of magnitude versus phase versus cycle. The algorithm shows good performance in the various real PD signals measured from various high voltage apparatuses in Korea.

Improvement of Measurement and Selectivity of Hydrogen Gas Using Multi-gas Sensors

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.