Fiber vibration sensing system two-order signal feature extraction and determining method

Abstract

The invention discloses a fiber vibration sensing system two-order signal feature extraction and determining method, and belongs to the technical field of fiber sensing signal determining, for solving the problems of incapability of accurately determining external vibration signal types under ambient noise interference and quite low efficiency of a conventional signal type discriminating method in the prior art. The method is characterized in that first of all, a short-time over-threshold rate of external vibration signals is extracted; secondary, an average algebraic sum of the extracted short-time over-threshold rate is calculated, and signal fragments comprising external vibration information are screened; thirdly, feature extraction is further performed on the short-time over-threshold rate of the signal fragments; and finally, a vibration type of each signal fragment is determined. The method provided by the invention, as a signal type determining algorithm, though signals come from a noisy background, various external vibration signal types can be accurately and efficiently determined, there are fewer false alarms, and false alarm rate is low.

Description

technical field [0001] The invention relates to a two-stage signal feature extraction and discrimination method of an optical fiber vibration sensing system, and belongs to the technical field of optical fiber sensing signal discrimination. Background technique [0002] The phase modulation fiber sensing technology characterizes the external measured physical quantity through the phase change of the light wave in the fiber. This sensing detection technology has high sensitivity, simple structure, low cost, and long operating distance of the sensing element, and is especially suitable for perimeter security. The fiber optic phase interferometers include Mach-Zehnder, Michelson and Sagnac types. The main difficulty of phase-modulated optical fiber sensing technology lies in signal localization and signal type discrimination. The existing signal type discrimination methods firstly carry out artificial feature design, that is, the vibration signal features are first extracted ...

AI Technical Summary

Problems solved by technology

The main problem of the method is that it is impossible to accurately determine the type of external vibration signals under the interference of environmental noise, and a large number of characteristic analyzes of vibration signals are required in the artificial feature design stage, resulting in low efficiency of the signal type identification method

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