Vibration Signature Extraction of High-Voltage Circuit Breaker by Frequency and Chaotic Analysis

This paper aims at presenting a novel approach for the analysis of vibration signals detected from circuit breaker (CB) opening or closing operations and to mechanical fault identification. An adaptive signal decomposition approach and chaotic nonlinear dynamic technique are used for extracting fault sensitive features of CB. The fault sensitive frequency band is derived using variational mode decomposition (VMD) combining with Hilbert marginal spectrum (HMS). The obtained sensitive frequency band(s) are employed for the reconstruction of the dynamical attractor (chaotic dynamics viewed from a phase space perspective, namely, the attractor-based perspective) following the Taken's embedding theorem. The invariant measures and ergodic quantities such as the largest Lyapunov exponent, correlation dimension, and Kolmogorov entropy which can be estimated on the reconstructed attractor are presented as the fault sensitive features. The CB fault is estimated in a chaotic space using these sensitive features. The effectiveness of the developed method is evaluated by using data sets recorded from several vacuum CBs with the same type.