Distributed optical fiber vibration signal feature extraction and identification method

Abstract

The invention discloses a distributed optical fiber vibration signal feature extraction and identification method, which belongs to the field of optical fiber sensing signal processing, and comprisesthe following steps of: firstly, acquiring a space-time matrix signal of a vibration source, extracting a space column signal, dividing a short-time signal unit, and constructing an optical cable vibration event data set; constructing, training and optimizing an improved mCNN model, and performing feature evaluation on features extracted by the model during optimization until model iteration is optimal; secondly, extracting time structure feature vectors under multiple scales in parallel by utilizing an optimal mCNN model, recombining the time structure feature vectors into a short-time feature sequence according to a time sequence, and constructing a time structure feature sequence set; finally, constructing and training an HMM model, and constructing an offline vibration event HMM modellibrary to serve as a classifier for vibration source recognition. The problems that in the prior art, local structure features and time sequence features of distributed optical fiber vibration signals cannot be extracted at the same time, and the vibration source recognition accuracy and the generalization ability of the model are low are solved.

Description

technical field [0001] The invention belongs to the field of optical fiber sensing signal processing and relates to a method for feature extraction and recognition of distributed optical fiber vibration signals. Background technique [0002] The distributed optical fiber vibration sensing system based on phase-sensitive optical time domain reflectometry technology, using optical fiber as the sensing and transmission medium, can realize continuous monitoring of long-distance and wide-range vibration signals, with long monitoring distance, high sensitivity and environmental tolerance It is widely used in perimeter security, oil and gas pipeline safety, structural health monitoring and other civil and defense facilities safety monitoring fields. [0003] In the practical application of long-distance monitoring, the environment is complex and changeable, multiple vibration sources are mixed, and the real-time requirements are high. It is difficult to identify the vibration sourc...

AI Technical Summary

Problems solved by technology

[0006] The purpose of the present invention is to provide a method for feature extraction and identification of distributed optical fiber vibration signals, which solves the problems of the prior art that cannot simultaneously extract the local structural features and timing features of distributed optical fiber vibration signals, the accuracy of vibration source identification and the model. The problem of low generalization ability

Images