Statistical characteristics analysis of partial discharge in high voltage cable joint

Four typical physical models for the internal insulation defects of 110kV cable joint are designed, while the test platform for Partial Discharges (PD) research on cable joint is constructed. A large number of PD data under different models are obtained by inner broadband ring sensor. The statistical analysis on the PD pattern indicates that there are significant differences between four PD forms on the statistical characteristics such as the phase distribution, skewness, kurtosis and degree of asymmetry, which can be used as effective features to reflect different characteristics of PD. Surface discharge and conductive particles may cause more serious damage to the insulation performance of cable joint, so high precaution should be paid on site operation.     

Suppression of Periodic Narrowband Interferences in Cable Partial Discharge Detections

There are background noises and interferences in the signal acquired,due to partial discharge(PD) detection system covers a broad frequency band.To suppress periodic narrowband signal which is a quite serious interference in PD measurement,the existing suppression method is introduced,the new method of wavelet packet transform is mainly studied to de-noise the periodic narrowband in XLPE cable PD detection system,which is based on the db4 basic wavelet using soft threshold.The results of the experiment show that wavelet packet transform is effective in restraining the periodic narrowband interferences to extract the PD pulses in XLPE cable PD monitoring system.     

Partial Discharge in Oil-paper Insulation of Transformer

Based on the analysis of defect in oil-paper insulation of transformer, 5 corresponding PD models were made to simulate the actual defects existed in transformers. Aging experiment was carried out at different temperature and test voltage. The developing process of different types of PD was studied and the influence of temperature and voltage on PD in oil-paper insulation, were analyzed. Gray images show differences for different typrs of PD or one type of PD at different precedures. Gray images can be used to recognize PD patterns and discharge stage. The research resalts coutribute for further research on PD pattern recognition and insulation aging of transformer.     

A Practical Method of Eliminating the White Noise of Partial Discharge with Wavelet

The white noise of PD(partial discharge) signal brings great difficult to the PD signal's processing, so eliminating the white noise is a necessary section. There are many methods of eliminating white noise, but none of them are suitable to the PD signal processing. Because PD signal and white noise have different Lipschitz exponents and different wavelet transform features in time-scales, a new eliminating white noise method has been brought forward that has simple operation and meets the timing need of PD signal's processing. After the processing with this method, the PD signal is not distortion and the effect of eliminating white noise is very good. This method can be applied to the processing of PD signal gotten from the site.     

Simulation Propagation of Partial Discharge UHF Signals in Transformer

Many factors affect the propagation of ultra high frequency(UHF) signals caused by partial discharge(PD) on the waveforms and energy of signals in transformer.To investigate the relationshi Pof factors and UHF signals,simulation model of transformer for PD study are established.UHF signals in simulation model of transformer caused by PD are calculated using finite difference time domain method.By means of amplitude and cumulative energy plot of simulation signals,and combing the measured result,the following factors:distance between PD source and detection position,different metallic conductor position around detection position and iron core and winding are researched,which contribute to comprehend the propagation characteristic of UHF signals and detect UHF signals accurately.     

Partial discharge pattern recognition based on S transform and two-directional 2DPCA

A new feature extraction method is proposed to recognize different types of partial discharge (PD) signals. Firstly,four typical categories of PD artificial defect models are made and S transform (ST) is employed to obtain a time-frequency representation of the recorded UHF signals. Then,two-directional two-dimensional principal component analysis ((2D) 2PCA) is applied to compress the ST amplitude (STA) matrix to extract features. Finally,support vector machine (SVM) combined with particle swarm optimization (PSO) algorithm is introduced to accomplish the recognition of experimental samples. Classification results demonstrate that the average recognition rate of (10,5) combination is the highest while the one of (5,5) combination is the lowest among four kinds of feature dimension combinations. Moreover,PSO can obviously improve the classification performance of SVM. Specifically,all the average recognition rates of PSO-SVM are higher than 94.43%and the maximum value comes to 97.67%. Therefore,the feature sets extracted by ST and (2D) 2PCA can not only achieve dramatic dimension reduction,but also retain the major information of original data. It is proved that the proposed algorithm can obtain ideal results in PD pattern recognition.     

GIS Partial Discharge Signal and Its Internal Sensor Detection

Partial discharge electromagnetic waves in GIS propagate is not only in the transverse electric and magnetic(TEM)mode, but also in transverse electric(TE) and transverse magnetic(TM)mode. The paper deduces out the mathematic expressions transient field excited by PD in GIS anywhere by using dyadic Green function theory. The contributions of TEM mode and all high order modes in the detecting frequency scope should be taken into consideration when calculating the electric field excited by PD in GIS. In simulative GIS laboratory, the designed inner couplers are superior to other outer sensors in detection of partial discharge. Inner couplers for the GIS model are developed and their frequency responses are analyzed in antenna model. At last the PD pulses excited by man-made defect are detected by inner couplers using high parameters oscilloscope.     

Wavelet Packet Decomposition Based on Entropy Threshold for White-noise Rejection in PD Signal

This paper analyzes the different characteristics of white-noise interference in the signals of partial discharge (PD) after wavelet transform. There is high value in lots of scales for PD and white-noise interference is to zero with increasing scale. The threshold is set for wavelet coefficient in all scales. If the coefficient of signal is higher than the threshold, it is PD signal. Otherwise it is noise interference. A threshold-based wavelet packet transform (WPT) algorithm is put forward to suppress white noise interference in PD signals. The results testifies that it has a favorable adaptability to extract PD signals using WPT.     

A floating threshold quantization algorithm to suppressmixing interferences in partial discharge

Due to the obvious difference of energy distribution frequencies from partial discharge (PD) signal and its mixing interferences (white noise and narrow brand), we uses the characteristic that node decomposition coefficients of wavelet packet transform can effectively show the energy change of signals to build up a floating threshold quantization algorithm (FTQA) varying with the noise energy of PD decomposition coefficients. It makes the node thresholds under the optimal base various with the noise strength in decomposition coefficients to self adaptively reality the choice of optimal threshold to finely partition PD decomposition coefficients. For simulated and real PD signals with mixing interferences, the conditional global threshold quantization algorithm (GTQA) and the proposed floating threshold quantization algorithm are employed to suppress the mixing interferences in PD signals and compared, and the results show that the proposed algorithm has the stronger suppression ability to mixing interference on PD signal and keeps perfect PD waveform via suppression.     

PD Pattern Recognition Using Complex Wavelet Transform Coefficient As The Feature

Complex wavelet transform can characterize the partial feature of the PD signal in time-domain and frequency-domain,and provides the unique phasic information.In this paper,the PD pulse waveforms which are created by 4 typical insulated defects are transformed by complex wavelet,and then the complex wavelet coefficient's real part,imaginary part and compound coefficient are clustered by the Fuzzy c-means,the energy of the cluster is the feature of pattern recognition.Discharge samples are got through large number of experiments,and BPNN can identify the PD created by 4 typical insulated defects effectively.The results show that the feature extracted from compound coefficient is better than the feature extracted form the real part and imaginary part of complex wavelet coefficient or wavelet coefficient.     

Application of the Weibull Distribution for the Recognition of Transformer PD Phenomena

The problem of identification of partial discharge phenomena occurring in a transformer insulating system is addressed. Under the assumption that different PD sources can produce pulse of different PD distributions, five typical artificial defects have been designed to compare the PD distributions coming from different sources, such as internal voids, surface and corona discharges. In this aim, Weibull distribution has been introduced to estimate the parameters and the least square methods (LSM) have been used to estimate the parameters. The goodness of fit to a Weibull distribution is checked by the Cramer-von-Mises (CVM) test. It is shown that the probability function fits well the partial discharge height distribution. By this way,different discharge sources can be distinguished. by Weibull parameter. In addition, the recognition of two or more PD phenomena simultaneously active is approached by means of an additive Weibull distribution. It allows quantities related to each of the two or more superimposed PD phenomena to be estimated, according to the Weibull parameters and the standard mean quantities.     

PD Online Measurement of Transformers with Wide Frequency Band System and the Noise Eliminating Method by Cascaded IIR Lattice Notch Digital Filter

The frequency band of conventional partial discharge (PD) measurement systems is selected just within several ten kilohertz. With the development of computer and digital signal processing techniques, wide frequency band (WFB) measurement systems have been used to detect PD in electrical equipment for its higher sensitivity. Nevertheless, the WFB measurement systems are easy suffered from the interference of strong field electromagnetism noises. A set of PD online monitoring system with frequency band from 50 kHz to 1 megahertz used for transformer is developed, in which pre-processing device and cascaded 2nd order IIR lattice notch digital filter are mainly used to suppress periodic narrow-band interference. With analysis of field monitored signal at a 220 kV substation, it is shown that the monitoring system not only can detect and extract the discharge pulse signal effectively, but also has the powerful capability of suppressing interference.     

Effective Coefficient Threshold for Complex Wavelet Transform

This paper constructs complex wavelet which used for suppressing white noise in PD,and then analyses some disadvantages of several existing wavelet threshold and presents a method of Effective Wavelet Coefficient(EWC) according to the characteristic of modulus maximum of PD signals.Then it is compared with maximin theory threshold selection and Stein unbiased risk estimate theory threshold selection.The findings suggest that the method of EWC is adaptive,and it can suppress noise completely with small distortion of PD signal.     

Analysis of UHF Method Used in Partial Discharge Detection in GIS

The possibility of UHF (ultra high frequency) method used in partial discharge detection in GIS is analyzed, and the UHF sensor, simulating passive filter, detecting the method of wide-band and narrow-band are studied, in order to avoid interferes of low-frequency. The authors develop an inner loop sensor in GIS model and investigate UHF method detecting partial discharge in GIS. The results indicate that the UHF system of detecting PD can effectively detect partial discharge and avoid outer corona interfere and Periodic pulse interfere. At the same time, narrow-frequency PD detection is an effective detection method to restrain UHF interferes.     

Pd Pattern Recognition Based on Linear Discriminant Analysis in GIS

According to the character of PD in GIS, the authors design four kinds of GIS defection models. The GIS gray intensity images are constructed based on mass specimens gathered by the ultra - high frequency and high speeds systems, Aiming at the PD characteristics and its defections, A PCA-FDA method is put forward based on PD images. The principal component analysis is employed to condense the dimension of PD images, then the optimal sets of statistically uncorrelated discriminant vectors are extracted, and the minimum distance classifier is constructed as classifier. The identified results show that this method can effectively elevated the discrimination of the four kinds of defects in GIS PD.     

Capacitive Coupler Used for Detecting Partial Discharge in GIS

The coaxial configuration of gas-insulated substations is of great advantages transmitting the electromagnetic wave excitated by partial discharge and of great advantages of partial discharge detection. Based the characteristics of configuration of GIS and PD signals inside, the authors design a disc coupler and a loop coupler for continuous monitoring of partial discharge in GIS, and analyze the sensor's characteristics theoretically. The frequency response (FR) characteristics of the disc coupler and the loop coupler are analyzed by the simulation and measurement realistically of square wave response. In addition, the measured results of partial discharge by the sensors designed in GIS are given, and it is shown that the sensors designed are available for the measurement of partial discharge in GIS.     

Comparision of Theoritical Solutions and Ultimate Span-Length between FRP Cables and Steel Cables

As the self weight of cable affects mechanical behavior obviously with the inerease of span length.FRP (fiber reinforced polymer) cable that has the lighter weight than the conventional cables has advantage for long span structures.The analysis of single cable is the fundamental theory for the design of cable structures.Based on different considerations of gravity loads.the solutions of the single cable on gravity loads have three sets of solutions: parabola solution.catenary solution and elastic catenary solution.And the equations for the three sets of solutions are derived by taking the end tension force of cable as the control parameter.The comparison between FRP cables and steel cables is conducted by elastic catenary solution.and the results show that the lager span structure can be realized by FRP cables.The precision for the parabola solution and catenary solution is compared for stay cables and horizontal cables.and the proper ranges of both approximate methods are proposed.Based on the above methods.the ultimate span length of FRP cable and steel cable are analyzed.It is concluded that the ultimate span of FRP cable is 4.4 times larger than that of steel cable.     

Study on the New Technology of Extracting PD in Strong Noise Environment With Complex Wavelet

Based on existing research, this paper analyzes and compares the phase information characters between partial discharge signal (PD) and its disturbance, and also extracts the feature of Partial Discharge with complex wavelets in noise environment. The research demonstrates that complex wavelets are more superior to original real wavelets in identifying Partial Discharge signal, and those simulated applications and the datum from laboratory can guarantee the effectiveness of the extraction of the feature of Partial Discharge and the restraint of the strong electromagnetic disturbance.     

Application of Wavelet Denoising in Partial Discharge Online Monitoring of Transformer

Because of the strong interferences, such as discrete spectrum interferences (DSI), white noise and pulse-shaped interferences, it is still a difficult work to extract the partial discharge (PD) signal for transformer online monitoring techniques. Through deeply study on the automatic selection of threshold value and mother wavelet, the wavelet-based de-noising method for partial discharge signals is proposed. The analyzing results on simulation signal and field-measured signal indicate that the proposed method is fit for de-noising white noise but for DSI the comparably worse de-noising results is acquired. Hence it is predicted that good de-noising results will be achieved with the wavelet-based de-noising method combined with digital filtering method fitting for de-noising DSI.     

棉花生育的积温模型

通过对麦棉套作移栽、春棉直播和夏播棉三类棉田棉株生长的观测，利用生理时间建立了中等水肥条件下棉株的株高、果枝、现蕾、开花、吐絮、脱落等参数的预测模型。利用该模型系统可根据有效积温预测不同种植方式下棉株的生育动态，有助于指导棉花栽培和害虫治理。