Feature extracting method of sound transmitting signal of fiber tensile fracture

Abstract

The invention discloses a feature extracting method of a sound transmitting signal of fiber tensile fracture, and aims at searching a more effective scheme on studying the implementation on yarns by fibers in the yarn tensile fracturing process. The method comprises the steps that normalization processing is conducted on a preset signal; a covariance matrix of the preset signal after normalizationis conducted is computed; each row of the covariance matrix is taken as a transverse vector, and the variance of each transverse vector is computed; whether or not the variance is greater than a preset threshold value is judged, and if yes, the average value of the transverse vectors is computed; the frequencies of the transverse vectors on which average computation is conducted and the average value in original transverse vectors are obtained, and a feature matrix of the fiber tensile fracture sound transmission signal is obtained based on the obtained transverse vectors and the frequencies.The method has the advantages that the feature matrix of the fiber tensile fracture sound transmission signal is extracted from the preset signal through a main component analysis method, the computation complicity is reduced, and engineering analysis is convenient to a certain extent.

Description

technical field [0001] The invention relates to the field of signal processing, and in particular, the invention relates to a feature extraction method of acoustic emission signals of fiber tensile fracture. Background technique [0002] With the development of the country, high-performance and multi-functional fibers emerge one after another. The application range of fibers can not only meet people's daily needs, but also penetrate into more and more industries. Generally, a large part of the common yarns are blended yarns of various fibers. Different fiber compositions have different properties of the yarns. The traditional method of evaluating yarn performance mainly focuses on mechanics. Such indicators are relatively macroscopic and vague, and cannot accurately determine the influence of different fibers on yarn performance. Therefore, a new method is urgently needed to study the influence of fiber on yarn during the process of yarn tensile fracture. Contents of the ...

AI Technical Summary

Problems solved by technology

The traditional method of evaluating yarn performance mainly focuses on the mechanical aspect. Such indicators are relatively macroscopic and vague, and cannot accurately determine the influence of different fibers on yarn performance.

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