Signal feature extraction method used for distributed optical fiber vibration sensing system

Abstract

The invention discloses a signal feature extraction method used for a distributed optical fiber vibration sensing system. The method mainly comprises the steps of in an improved ensemble empirical mode decomposition (MEEMD) processing process, reading original data, and performing vibration signal locating and phase demodulation; introducing two groups of white noises with a mean value of zero toperform EMD; performing permutation entropy calculation for a first IMF component; comparing an entropy value with a set threshold, and if the entropy value is higher than the set threshold, repeatingthe steps until the entropy value is lower than the threshold; performing EMD on residual data to obtain residual IMF components of a vibration signal; and performing Hilbert analysis on the IMF components to obtain an eigenvector of vibration signal mode identification. By applying the method provided by the invention, the problems of mode mixing, false components and the like in a conventionaldecomposition method can be solved; the processing process is simplified; the reconstruction precision is improved; the data processing time is shortened; and the method is of important significance for improving the mode identification timeliness and accuracy of the distributed optical fiber vibration sensing system.

Description

technical field [0001] The invention belongs to the field of distributed optical fiber sensing, relates to a new feature extraction method in vibration signal pattern recognition, specifically refers to a vibration based on improved overall empirical mode decomposition (MEEMD) for distributed optical fiber vibration sensing system Signal feature extraction method. Background technique [0002] Vibration is a common phenomenon in real life, and it is widely used in engineering applications and scientific research, especially in infrastructure safety monitoring. Traditional vibration detection methods are mainly based on electronic detection technologies such as piezoelectricity, capacitance, and inductance. They are susceptible to external environmental interference such as electromagnetic radiation, have a short service life and high maintenance costs, and do not meet the actual needs of modern engineering measurement. With the continuous advancement of sensor technology, n...

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Problems solved by technology

However, there are problems such as modal aliasing in the decomposition process, which leads to errors in the obtained IMF components and reduces the accuracy of vibration information pattern recognition.

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