Explainable feature selection by SHAP for signal recognition of Ф-OTDR system

An explainable feature selection method based on Shapley additive explanation (SHAP) is proposed for the signal recognition of a phase-sensitive optical time-domain reflectometer system. The SHAP value is used to quantify the contribution of a feature. The original features of the signals to be identified are selected according their contributions. The support vector machine algorithm is employed as the classifier to verify the effectiveness and explanation of the proposed feature selection method in the signal recognition on an open dataset from Beijing Jiaotong University. The average recognition accuracy of six types of signals increases to 89.3% and the corresponding recognition time of each sample reduces to 0.097 s. The feature selection method provides a reliable guidance for feature selection and can improve the speed and accuracy of the signal recognition.