Distributed Acoustic Sensor Signal Denoising Method Based On CEEMDAN-MPE

To solve the problem that the unknown noise of distributed acoustic sensor (DAS) signal interferes with railway safety detecting and monitoring, a novel denoising method based on complete ensemble empirical mode decomposition with adaptive noise (CEEMDAN) and multiscale permutation entropy (MPE) is proposed. The CEEMDAN algorithm is used to decompose the raw signal into several intrinsic mode functions (IMFs), and then calculate the MPE value of each IMF. The IMFs with MPE greater than 0.6 are denoised through the interval thresholding, and then reconstruct all IMFs. The application example of knocking signal shows the validity and reliability of the approach.