Surface intrusion event identification for subway tunnels using ultra-weak FBG array based fiber sensing

A scheme is proposed for the identification of surface intrusion events, from signals detected by an ultra-weak fiber Bragg grating array in a subway tunnel. The spectral subtraction and the root mean square of the power spectral density are combined to extract event signals. The local characteristics-scale decomposition and the multi-scale permutation entropy are employed subsequently for feature extraction, which can improve the event recognition rate from the perspective of multi-scale analysis. Experimental demonstration verifies that the proposed scheme can identify four common events. Among the events, the discrete pulse construction and the continuous pulse construction on the ground surface are intrusion events, the subway train traveling in the tunnel and the lorry passing on the ground surface are non-intrusion events. The average recognition rate of 96.57% is achieved, which can satisfy actual application requirements.