Tang Ju

Application of Complex Wavelet Transform to Suppress White Noise in GIS UHF PD Signals

During online partial discharge (PD), ultra-high-frequency (UHF) detection of gas-insulated switchgear (GIS), obtaining acceptable levels of sensitivity, still continues to remain a very challenging task, primarily due to strong electromagnetic interference (including white-noise, random, discrete spectral, and stochastic pulses). As white-noise interference stands in the breach existing in GIS PD UHF detection inevitably, the available suppression methods are unsatisfactory. According to the feature of white noise, the Daubechies complex wavelet is constructed. Through the simple information (SI) and combined information (CI) of the complex wavelet transform (CWT), the denoising method of simulation signals and field signals of PD UHF is studied by the authors. In view of the estimation parameters, the results manifest that white-noise in GIS PD UHF signals can be suppressed effectively by the SI and CI of the CWT.

GIS partial discharge quantitative measurements using UHF microstrip antenna sensors

In view of the structure characteristic and operation performance of the field gas insulation switchgear (GIS), an external ultra high frequency (UHF) sensor, a novel microstrip antenna, is designed to detect UHF partial discharge (PD) signals for the field GIS. The microstrip antenna, which receives the UHF electromagnetic wave leaked from the GIS spacer, is just mounted on the GIS spacer, and has some effect to suppress the surrounding space electromagnetic interference. The analysis and on-site measurements manifest that the microstrip antenna working frequency bandwidth is 340 MHz to 440 MHz, which voltage standing-wave ratio (VSWR) is less than 2, the center frequency is 390 MHz, the relative bandwidth is 25.6% up to the wide bandwidth range, and its gain of the maximum radiation and reception directivity is covered 5.38 dBi. Based on the laboratory GIS simulation device measurements, the investigation of the relationship between UHF PD amplitude and apparent discharge quantity based on 1EC60270 is presented as linear curve. Meanwhile, comparison to the field 220 kV level GIS, the quantitative charge evaluated to about 40 pC by the UHF method could give a preliminary diagnosis for GIS insulation conditions. And the UHF measurement system is suited for GIS field partial discharge UHF on line detection and diagnosis.

Pattern recognition of partial discharge with fractal analysis to characteristic spectrum

While partial discharge (PD) pattern recognition is widely considered as an important method to test insulation degradation, the major problem encountered is the extraction of PD pattern features. Using the analysis of the three-dimensional statistical spectrum, this paper adopts fractal theory to extract PD pattern features. From designed model tests and fraction calculation results, it is shown that the method is effective in extracting PD pattern features which are helpful in PD pattern recognition based on three-dimensional statistical spectrs.

Study on partial discharge of metallic outshoot insulation defect in GIS

Detection of partial discharge (PD) signals in gas-insulated substation (GIS) is a comprehensive research project. In this paper, physical model and corresponding mathematical model of metallic outshoot insulation defect oh enclosure are established and studied for PD in GIS using UHF method, which are based on the characteristics of metallic outshoot insulation defect and UHF inner-loop sensor. The parameters of the mathematical model are given according to data fitting method, and the validity of PD mathematical model in UHF is proved by fitting error, power spectrum and FFT analysis. In the end, applications of the PD mathematical model and complex wavelet transform for restraining white noise are illustrated.

Study on relationship between optical signals and charge quantity of partial discharge under four typical insulation defects

In order to solve the problem of the optical method for detecting partial discharge (PD) in the electric equipment in quantity, the integral value of the signals from the optical method has been analyzed to reflect naturally the energy of light released by PD from the principle of the optical method, then a linear relationship between the integral value and the charge quantity of PD has been deduced to give a guidance to detect charge quantity of PD in Gas Insulated Switchgear (GIS). Afterwards, as the result of PD experiments on four typical insulation defects in GIS based on optical method coupled with impulse current method, the relationship between the average integral value of signal of the optical and the average apparent charge quantity presented linear. However, the relation curve of different defects might be distinct as the PD properties under different defects were distinct. Besides, the distance between two electrodes would also influent the linear relation. The longer the two electrodes separate, the greater the slope of the relation curve would be. Therefore, PD charge quantity might be calculated through optical signal when the defect type could be assured. Results all above shows that the type and level of PD could be determined using the optical method, hence the PD online monitoring and fault diagnosis based on the optical method is feasible.

A calculational method of transient electric field excited by partial discharge in gas insulated substation using dyadic Green function

In this paper, Gaussian current pulse is used to simulate the PD current pulse in gas insulated substation (GIS). The expressions of transient electric field excited by PD in GIS are deduced by using dyadic Green function theory, which is important to study the principle of detecting PD in GIS using ultra-high frequency (UHF) method. The calculation results of electric field show that the TEM mode and high order modes excited by PD make different contributions to the electric field. So the contributions of TEM mode and all the high order modes in the detection frequency scope should be taken into consideration when calculating the electric field excited by PD in GIS.

Application of Iterative Curve-Fitting Method in Separating Overlapped Peaks of SF 6 Decomposed Products

The SF6 decomposed products are very alike, so the peaks of the SF6 decomposed products are overlapped. It make us hard to quantitative calculate. This paper introduced a method to seperate the overlapped chromatogram peaks with iterative curve-fitting and Gauss function, and deduced the formula of the iterative curve-fitting; provided a method to calculate the initial value of the peaks intensity and width by iterative formula, and confirm the final peaks intensity and width to seperate the overlapped signals. By the analysis of the real chromatogragh data, it proved the validity of this method on the main components used in distinguishing the GIS internal defects. This method overcomes the influence of SF6 peak to the other thin concentration peaks, so it can use on the study of the quantitative analysis of the decomposed products on different failures and different voltages.

Simulation study of large power transformer advanced winding model in high frequency

According to the propagation characteristic of high frequency signal in large power transformer winding, an advanced winding model is presented in this paper. Utilizing the complex equation and mesh calculation method, the transfer function is deduced theoretically. Frequency characteristic is studied through the small-signal tool in Saber simulation software, meanwhile the characteristic parameters in winding model are discussed to prove how to influence frequency characteristic. According to the variation of the frequency characteristic, it could improve measurement accuracy of partial discharge (PD) on-line monitoring and winding deformation for large power transformer.

The sensitive characteristics analysis on adsorbent-doped carbon nanotube sensors for detecting H 2 S

Although Gas Insulated Switchgear (hereinafter referred to as GIS) equipment has the very high operation reliability, the internal inevitable defects of GIS could cause partial discharge (short for PD). SF6 gas decomposition occurs because of the energy which PD produced. The analysis of SF6 gas components in GIS is of great significance in the diagnosis and assessment of the operating status of GIS. As an important characteristic gas, the variation detection in the concentration of H2S is significant to judge the insulation level of SF6 gas. There are a number of gas sensors using carbon nanotubes. Unfortunately, their applications are greatly limited by their low intrinsic sensitivity. In this paper, we propose an adsorbent-doped carbon nanotubes gas sensor to make an improvement in detecting the concentration of H2S. The preparation and test method of the developed sensor was introduced. Meanwhile, the sensor response was conducted using the gas test device. We perform experiments and the results show that, compared to intrinsic carbon nanotubes gas sensor, the gas sensor featuring adsorbent-doped carbon nanotubes has a great deal higher sensitivity and responsiveness to H2S. In other words, the developed sensor has a capability of detecting the low concentration H2S. Therefore, it indicates that the doped sensor can improve the minimum detectable concentration of H2S and has great potential in H2S detection. Resistance change rate of H2S increased to 23.69% from 12.9%. Meanwhile, the sensor has good repeatability and stability.

Influence of trace water and oxygen on characteristic decomposed components of SF 6 under partial discharge

Monitoring the contents of decomposed components of SF₆ in order to identify the internal insulation faults of electrical equipment with SF₆ dielectric is a common practice. Partial discharges (PDs) can lead to the decomposition of the SF₆ dielectric. The new reactions also cause the final decomposed components to differ due to the different concentrations of H₂O and O₂ even under the same strength of PD. Thus, the accuracy of assessing inner insulation faults is affected when using the concentration and corresponding change of decomposed components. In this work, two main characteristic components SO₂F₂ and SOF₂ was researched. The purpose is to perform influence analysis of trace H₂O and O₂ on the characteristic components. Research findings indicated that the amount of SOF₂ strongly correlates to the amount of trace H₂O, whereas the amount of SO₂F₂ is weakly related to trace H₂O. Furthermore, the dilution effect of trace O₂ on SOF₂ obviously exceeds that on SO₂F₂.