Operation Mode Recognition of Surface Microdischarge Based on Digital Image Processing Techniques

Surface microdischarge (SMD) has various application potential in biomedicine, agriculture and industry. An important issue for practical use is to develop an online monitoring method for operation mode recognition of SMD. In this paper, we proposed a operation mode recognition method for SMD based on digital image processing technique. The visible light digital images of SMD were shot and the RGB chromaticity index of the discharge images were extracted. It was found that the sum of all pixel values in the SMD discharge gray scale image and in the R, G, and B monochromatic images increased with the applied voltage monotonically, which can reflect the change of the discharge intensity. The difference between the proportions of the B component and the G component ( Δ (B-G)%) showed a trend of first increasing and then decreasing as the applied voltage increased. The Δ (B-G)% reached the maximum value of 46.93% at V p-p of 5kV and was corresponding to the mode transition point measured by Fourier transform infrared spectrometer (FTIR). Finally, a SMD operation mode recognition method, based on the Δ (B-G)% and the applied voltage was proposed.