There is a large number of line traces on the surface of the broken end which left in the cable cutting case crime scene of highspeed railway, they often present nonlinear morphological feature and has strong randomness. In order to make rapid trace analysis and infer the tools, a fast algorithm based on wavelet domain feature aiming at the nonlinear line traces is presented. The proposed algorithm applies wavelet decomposition to the 1D signal which picked up by single point laser displacement sensor to partially reduce noises. After that, the dynamic time warping is employed to realize the trace feature similarity matching. Finally, the linear regression machine learning algorithm based on gradient descent method is used to realize the constant iteration. The experiment results of cut traces sample data comparison demonstrate the accuracy and reliability of the proposed algorithm.