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As one of the most important mesoscopic properties of networks, the community structure plays an important role in cascading failures on isolated networks. However, the study for understanding the influences of the community structure on the cascading failures on interdependent scale-free networks remains missing. In this paper, we investigate cascading failures on interdependent modular scale-free networks under inner attacks and hub attacks from the global and local perspective. We mainly analyse the inter-community connections and coupling preferences, i.e. random coupling in communities (RCIC), assortative coupling in communities (ACIC) and assortative coupling with communities (ACWC). We find that increasing inter-community connections can enhance the robustness of interdependent modular scale-free networks for both inner attacks and hub attacks. Furthermore, we also find that the ACIC is more beneficial to resisting cascading failures compared with RCIC or ACWC. For ACIC, the cascading failures propagate mainly in a local community where the initial failure occurs. It is meaningful to control the cascading failures on interdependent modular scale-free networks by constructing ACIC.

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Surveillance of SF6 decomposition products is significant for detection of partial discharge (PD) in gas insulation switchgear (GIS). As a basis in on-site detection and diagnosis, PD early-warning aims to quickly find the abnormalities using a simple and cheap device. In this paper, SO2 is chosen as a feature product and detected through ultraviolet spectroscopy. The derivative method is employed for baseline correction and spectral enhancement. The standard gases of the main decomposition products are qualitatively and quantitatively detected. Then decomposition experiments with different defects are designed to further verify the feasibility. As a stable decomposition product under PD, SO2 is proved to be applicable for PD early-warning in the field. By selecting the appropriate wavelength range, namely 290–310 nm, ultraviolet derivative spectroscopy is sensitive enough to the trace SO2 in the decomposed gas and the interference of other products can be avoided. Fast Fourier transform could be used for feature extraction in qualitative detection. Concentrations of SO2 and other by-products increase with increasing discharge time and could be affected by the discharge energy and PD type. Ultraviolet detection based on SO2 is effective for PD early-warning but the threshold should still be carefully selected in practice.