Study on Evaluation Method of Insulator Surface Contamination Level Based on LIBS Technology and PCA Algorithm

As one of the most important external insulation equipment in power system, insulators play an important role in transmission and distribution network. In this paper, qualitatively and quantitatively analysis of the contaminated elements on the surface of artificial contaminated insulators and natural contaminated insulators were carried out by Laser-Induced Breakdown Spectroscopy (LIBS). For artificial contaminated insulators, Na and Al elements can be used to characterize the equivalent salt deposit density (ESDD) and non-soluble deposit density (NSDD) levels respectively. For natural contaminated insulators, there are differences in spectral intensity of contaminated elements with different contamination years. And with the increase of the contamination years, the spectral intensity of the Si, Fe, Ca, Al, K and Na elements also have an increasing trend. Insulator samples under 4 contamination levels were classified based on the principal component analysis (PCA) algorithm. Dimension reduction analysis was conducted by extracting 6 excitation spectra (Si, Fe, Ca, Al, K, Na) which can represent contamination information. The 2 principal components with the largest contribution rate were obtained and the principal component scores of each spectrum were calculated. The research results showed that the spectral sample points have obvious convergence phenomenon according to the contamination level of the insulators. Compared with the commonly used methods for judging contamination level, LIBS technology has the advantages of easy operation, no sample processing and high sensitivity. Therefore, the combination of LIBS technology and PCA algorithm can save time and cost and improve the detection efficiency in the field of insulator contamination monitoring.