BiLSTM-based composite characteristic optical fiber sensing disturbance signal mode identification method

Abstract

The invention relates to a BiLSTM-based composite characteristic optical fiber sensing disturbance signal mode identification method, which comprises the following steps that vibration signals including optical fiber sensing disturbance signals in different modes are collected, data is stored, and type labels are added; the time domain feature extraction unit is used for calculating short-time energy and a short-time over-level rate for the acquired vibration signals, setting thresholds of the short-time energy and the short-time over-level rate, and preliminarily judging intrusion disturbancesignals according to judgment conditions; the frequency domain feature extraction unit is used for carrying out four-layer wavelet packet decomposition on each vibration signal, solving 16 sub-band energy spectrum distribution, splicing short-time energy and short-time over-level rate to form a composite feature vector, carrying out normalization processing on the composite feature vector, and taking the normalized feature vector as an input feature vector; and a bidirectional LSTM network model is constrcuted, the normalized feature vector is taken as an input, the event label is taken as aclassification output result, and a classifier is trained by using the test sample to realize optical fiber sensing disturbance signal mode identification.

Description

technical field [0001] The invention relates to the field of optical fiber sensing signal identification, in particular to a method for classifying and identifying events of optical fiber sensing disturbance signals based on the BiLSTM algorithm. Background technique [0002] The distributed optical fiber sensing system has the advantages of high sensitivity, simple structure, long detection distance, less susceptible to interference, and no power supply. It has been widely used in peripheral security, oil and gas pipeline detection and other fields. In the field of perimeter security, the optical fiber sensing system uses optical fiber as the sensing element, which can be wound on the fence or buried in the ground. By collecting the sensing signal, the signal processing and analysis module is used to classify and identify the disturbance signal. The purpose of identifying the type of vibration intrusion signal is achieved. At present, the typical optical fiber perimeter pr...

AI Technical Summary

Problems solved by technology

The traditional methods of signal recognition mainly include short-term average zero-crossing rate ZC based on time-domain characteristics, differential short-term average zero-crossing DZC, short-term average energy E, differential short-term average energy DE, and disturbance duration. Analysis of time-amplitude information can characterize some local features of the signal, but cannot extract useful information such as waveform transformation; there is a wavelet packet decomposition method based on frequency domain feature analysis, which decomposes the signal into sub-frequency bands to extract energy features, extract features Vector can solve the problem of non-stationary signals; the method based on empirical mode decomposition EMD has insufficient theoretical basis and requires multiple iterative calculations, which is not efficient

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