Biblio

The core looseness fault is an important part of transformer fault. The state of the core can be obtained by analyzing the vibration signal. Vibration analysis method has been used in transformer condition monitoring and fault diagnosis for many years, while different methods produce different results. In order to select the correct method in engineering application, five kinds of joint time-frequency analysis methods, such as short-time Fourier transform, Wigner-Ville distribution, S transform, wavelet transform and empirical mode decomposition are compared, and the advantages and disadvantages of these methods for dealing with the vibration signal of transformer core are analyzed in this paper. It indicates that wavelet transform and empirical mode decomposition have more advantages in the diagnosis of core looseness fault. The conclusions have referential significance for the diagnosis of transformer faults in engineering.

IP geolocation technology is widely adopted in network security, privacy protection, online advertising, etc. However, existing IP geolocation methods are vulnerable to delay inflation, which reduces their reliability and applicability, especially in weakly connected networks. To solve this problem, a ranking nodes based IP geolocation method (RNBG) is proposed. RNBG leverages the scale-free nature of complex networks to find a few important and stable nodes in networks. And then these nodes are used in the geolocation of IPs in different regions. Experimental results in China and the US show that RNBG can achieve high accuracy even in weakly connected network. Compared with typical methods, the geolocation accuracy is increased by 2.60%-14.27%, up to 97.55%.