Recognition of pipeline safety events is a key problem in the research of the optical fiber pre-warning system. In this paper a feature extraction method combined with wavelet energy spectrum (WES) and wavelet information entropy (WIE) is proposed. In order to avoid kernel function being dominated by trivial relevant or irrelevant features, a support vector machine (SVM) approach is also put forward based on the feature weighting, i.e. Feature Weighted SVM (FWSVM). The experiment shows that the method proposed in this paper is effective for recognition of the pipeline safety events and can be applied in optical fiber prewarning system.
Sun et al. REF proposed a feature extraction method combining with wavelet energy spectrum and wavelet information entropy, and proved its feasibility in experiments.