ABSTRACT
As the basis of accurate diagnosis, fault early-warning of gas insulation switchgear (GIS) focuses on the time-effectiveness and the applicability. It would be significant to research the method of unified early-warning for partial discharge (PD) and overheated faults in GIS. In the present paper, SO2 is proposed as the common and typical by-product. The unified monitoring could be achieved through ultraviolet spectroscopy (UV) detection of SO2. The derivative method and Savitzky-Golay filtering are employed for baseline correction and smoothing. The wavelength range of 290-310 nm is selected for quantitative detection of SO2. Through UV method, the spectral interference of SF6 and other complex by-products, e.g., SOF2 and SOF2, can be avoided and the features of trace SO2 in GIS can be extracted. The detection system is featured by compacted structure, low maintenance and satisfactory suitability in filed surveillance. By conducting SF6 decomposition experiments, including two types of PD faults and the overheated faults between 200-400 degrees C, the feasibility of proposed UV method has been verified. Fourier transform infrared spectroscopy and gas chromatography methods can be used for subsequent fault diagnosis. The different decomposition features in two kinds of faults are confirmed and the diagnosis strategy has been briefly analyzed. The main by-products under PD are SOF2 and SO2F2. The generated SO2 is significantly less than SOF2. More carbonous by-products will be generated when PD involves epoxy. By contrast, when the material of heater is stainless steel, SF6 decomposes at about 300 "C and the main by-products in overheated faults are SO2 and SO2F2. When heated over 350 degrees C, SO2 is generated much faster. SOz content stably increases when the GIS fault lasts. The faults types could be preliminarily identified based on the generation features of SO2.
ABSTRACT
By detecting the stable by-products of SF6 through ultraviolet spectroscopy, the present paper achieved the rapid detection of the GIS partial discharge fault. First derivative and the S-G filter were used for the spectral denoising and smoothing. The discharge experiment was used for validating feature selection. Principal component regression was used for the analysis of the concentration of SO2. The concentration of SO2 was used for fuzzy judge. By selecting the appropriate wavelength range (295~305 nm), ultraviolet spectrum can identify SO2 from the complex by-products of SF6. In this paper, firstly, the author reviewed the decomposition mechanism of SF6 under partial discharge, and then verified the rationality of detecting partial discharge by UV, and ultimately achieved the rapid detection of GIS partial discharge and fuzzy judgment of discharge time.
ABSTRACT
Infrared spectroscopy analysis of SF6 and its derivative is an important method for operating state assessment and fault diagnosis of the gas insulated switchgear (GIS). Traditional methods are complicated and inefficient, and the results can vary with different subjects. In the present work, the feature extraction methods in machine learning are recommended to solve such diagnosis problem, and a multiscale weighted principal component analysis method is proposed. The proposed method combines the advantage of standard principal component analysis and multiscale decomposition to maximize the feature information in different scales, and modifies the importance of the eigenvectors in classification. The classification performance of the proposed method was demonstrated to be 3 to 4 times better than that of the standard PCA for the infrared spectra of SF6 and its derivative provided by Guangxi Research Institute of Electric Power.
ABSTRACT
Pressured SF6 gas is widely used in GIS for electrical insulation as well as for are extinction. And a chemical way for detecting the SF6 and its byproducts is a powerful diagnosis method for GIS. The present paper analyzes the decomposition of insulated gas of GIS (mostly SF6) in three cases with infrared spectrometer. As a result, it was found that the content of S2F10 can be used to decide whether spark or arc discharge leads to the fall down of GIS; CF4 can be used for judging the insulation grade of GIS. Besides, the gas leakage of the GIS should be concerned in the long lifetime of GIS. Finally, it is supposed that a data base containing the history of results from the gas diagnostics for each piece of equipment should be created for future maintenance activities.
