Ultrasound nondestructive detecting echo signal classificating method based on vague plane characteristic

Abstract

The invention relates to a classifying method for the echo signals in ultrasonic non-destructive inspection that is based on fuzzy plane, which comprises the following procedures: first the Hibert transformation of ultrasonic signal is worked out to get the analytic signal; then the fuzzy function of the analytic ultrasonic signal is worked out; finally in respect to the sample of training set, the fuzzy function of the ultrasonic signal is mapped on a characteristic space of low dimensions by K-L transformation. The invention uses a classification method of echo signal based on the non variability of the time shift and frequency shift of mode of fuzzy function, can solve any problem in the pre treating method at characteristic extracting, overcome the influence on characteristic extracting from the arrival times of echo signals of different defects and from the central frequency of probe at inspection. The invention is of good noise proofness, good classification effect, and is of a wide application prospect.

Description

(1) Technical field [0001] The invention belongs to the technical field of signal processing, and in particular relates to a method for classifying ultrasonic nondestructive testing signals. (2) Background technology [0002] When ultrasonic waves propagate in objects, they always carry various information that characterizes the physical properties of objects. Ultrasonic non-destructive testing is to analyze and evaluate the structural state inside the material by using various propagation characteristics of ultrasonic waves in the inspected workpiece, such as propagation, reflection, refraction, attenuation, and waveform conversion. Therefore, the identification and evaluation of ultrasonic echo signals key. The echo signal detected by an ordinary ultrasonic flaw detector can determine whether there is a defect in the inspected workpiece, but it is difficult to accurately estimate the shape and size of the defect, making it difficult to conduct qualitative and quantitative...

AI Technical Summary

Problems solved by technology

Time alignment is usually to make the position of the first minimum value of the defect echo the same through waveform shifting. Frequency conversion is usually to transfer signals of different center frequencies to a reference frequency through interpolation and decimation. This preprocessing method It is easily affected by noise, and there is a certain error between the actual operating frequency and the nominal frequency of the probe in practical applications. If the probe is replaced, this error will be more obvious, and it is difficult to achieve accurate transformation through interpolation and extraction.

In short, the existing ultrasonic nondestructive testing echo signal classification methods are affected by the arrival time of different defect echo signals and the center frequency of the probe during detection, and cannot perform feature extraction accurately.

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