An automatic identification method of near-surface defects based on ultrasonic resonance method

Abstract

The present invention discloses an automatic identification method for near-surface defects based on ultrasonic resonance method, which is used for ultrasonic detection of near-surface defects of workpieces and belongs to the technical field of ultrasonic non-destructive testing. The method comprises: 1. Calculating the defect resonance frequency range according to the thickness range of the near-surface delamination defect of the workpiece; 2. Using an ultrasonic probe to detect the workpiece and collecting the ultrasonic signal; 3. Fourier transforming a sample of a specified length intercepted by the ultrasonic signal to obtain a backscattered signal spectrum; 4. Bandpass filtering the backscattered signal spectrum to filter out the frequency components outside the resonance frequency range; 5. Calculating the power spectrum and its characteristic value. If the characteristic value exceeds the set defect threshold, it is determined that the workpiece has a defect, otherwise there is no defect. The present invention utilizes the principle of ultrasonic resonance, and by calculating the characteristic value of the power spectrum within the resonance frequency, it can effectively identify the subcutaneous tail delamination defect near the surface, without being limited by the surface blind area.

Description

Technical Field

[0001] The present invention is applied to the technical field of ultrasonic nondestructive testing, and in particular relates to a near-surface defect detection method based on an ultrasonic resonance method. Background Art

[0002] Extrusion technology is an important method for processing metal parts. Extruded copper bars are a common extruded bar material, which has important applications in high-speed rail motor rotors. Various defects will occur in the production process of copper bars. Among them, the main types of defects detected by ultrasonic detection technology include cracks, delamination, inclusions, looseness and extrusion tails. Extrusion tails are a special defect that appears at the tail of extruded products. They are generally easy to appear in extruded bars, profiles, and thick-walled pipes. In the later stage of extrusion production, when the remaining length of the billet in the extrusion barrel is reduced to the height equal to the stable flow plastic zone, the extrusion pressure begins to rise, the radial flow velocity of the metal increases, and the metal material in the deformation dead zone also participates in the deformation, resulting in the oxide scale on the surface of the billet, the lubricating oil in the extrusion equipment and other contaminants flowing into the finished product, resulting in stratification between the metals. According to the location of its distribution in the copper bars, the extrusion tail defect can be divided into central tail and subcutaneous tail. Among them, the defect that is more difficult to detect is the subcutaneous tail defect. The temperature difference between the extrusion barrel and the billet causes the metal in the dead zone to be cooled. Compared with the metal in the center area, its metal plasticity is reduced, and the interface with the plastic flow zone slips violently, causing the metal to shear and break. At the same time, dirt such as scale on the surface of the billet flows along the shear section and covers the near surface of the extruded product, resulting in subcutaneous shrinkage. Due to its defective position, the subcutaneous shrinkage seriously affects the subsequent cold processing of the extruded product, resulting in problems such as reduced strength of the copper conductor bar.

[0003] Ultrasonic waves can be used to identify and locate copper conductor bar defects in industrial testing. Ultrasonic testing is a commonly used nondestructive testing technology that uses the reflection, transmission and other properties of ultrasound to detect and locate defects using the time and amplitude of the echo. Ultrasonic nondestructive testing technology has become one of the important means of defect detection for extruded products because of its safe operation, accurate defect location, high sensitivity, low cost and high speed. The subcutaneous shrinkage tail produced in the extrusion production of copper conductor bars mostly appears on the surface and near the surface of the workpiece. In conventional pulse reflection ultrasonic testing technology, the surface echo has a certain width, and the defect echo near the surface is difficult to identify, resulting in a certain detection blind area in the near-surface area of ​​the tested piece, and it is impossible to identify whether there is a defect. Summary of the invention

[0004] The purpose of the present invention is to overcome the insufficiency of the detection capability of the traditional ultrasonic detection technology for the near-surface subcutaneous shrinkage defect, and to provide a near-surface defect automatic identification method based on the ultrasonic resonance method, which can realize the accurate identification of the near-surface delamination defect of the workpiece.

[0005] The technical solution of the present invention is as follows:

[0006] An automatic identification method for near-surface defects based on ultrasonic resonance method, characterized in that the method comprises the following steps:

[0007] Step 1, calculating the defect resonance frequency range according to the thickness range of the near-surface delamination defect of the workpiece;

[0008] Step 2: Use a specific ultrasonic probe to detect the workpiece and collect ultrasonic signals;

[0009] Step 3, performing Fourier transform on a sample of a specified length of the ultrasonic signal to obtain a backscattered signal spectrum;

[0010] Step 4: band-pass filter the backscattered signal spectrum to remove frequency components other than the resonance frequency;

[0011] Step 5: Calculate the power spectrum and its eigenvalues. If the eigenvalue exceeds the set defect threshold, it is determined that the workpiece has defects, otherwise, there are no defects.

[0012] Furthermore, the calculation formula of the defect resonance frequency is f=c / 2d, wherein f is the resonance frequency, c is the speed of the ultrasonic longitudinal wave in the material, and d is the thickness of the delamination defect.

[0013] The delamination defect thickness is determined based on the empirical thickness range of possible defects in a specific workpiece.

[0014] Furthermore, in step 2, the selected ultrasonic probe is a wide-band narrow-pulse ultrasonic probe, and the probe frequency band covers the resonance frequency range of delamination defects; the probe is detecting the surface of the workpiece where defects may exist.

[0015] Furthermore, the method of cutting samples is: removing the surface echo and the bottom echo, and leaving the backscattered signal.

[0016] Furthermore, in step 5, the eigenvalue of the power spectrum is calculated by integrating and then squaring the power spectrum.

[0017] Furthermore, the defect threshold is set according to the specific conditions of the workpiece and the probe to be tested. The specific method is: before testing, ultrasonic backscatter signals of sample workpieces without defects and with artificially simulated defects are collected. The sample workpieces have the same specifications as the workpiece to be tested, and at least 100 sample workpieces with and without defects are collected respectively, and the defect threshold is set according to the difference between the characteristic values ​​of the two.

[0018] By adopting the above technical solution, the beneficial effects of the present invention are:

[0019] The present invention adopts the resonance method for defect detection. The center frequency of the selected ultrasonic probe is close to the defect resonance frequency. Whether there is a defect is judged according to the size of the power spectrum characteristic value within the resonance frequency of the ultrasonic echo signal, and is not limited by the near-surface blind area. BRIEF DESCRIPTION OF THE DRAWINGS

[0020] Figure 1 It is a schematic flow chart of the method for automatic identification of near-surface defects based on ultrasonic resonance method of the present invention.

[0021] Figure 2 It is the ultrasonic backscattering signal when the copper conductor bar is free of defects in the embodiment.

[0022] Figure 3 : is the power spectrum of the defect-free backscattered signal of the copper conductor in the embodiment.

[0023] Figure 4 : is the ultrasonic backscattered signal when there is a near-surface defect in the copper conductor in the embodiment.

[0024] Figure 5 : is the power spectrum of the backscattered signal when there are near-surface defects in the copper conductor in the embodiment. DETAILED DESCRIPTION

[0025] In order to make the advantages of the invention more clear and understandable, the present invention is further described in detail below with reference to the accompanying drawings, taking the detection of subcutaneous shrinkage and delamination defects near the surface of copper conductors as an example. The specific implementation methods of the present invention are as follows:

[0026] An automatic identification method of near-surface defects based on ultrasonic resonance method, such as Figure 1 As shown, the method comprises the following steps:

[0027] Step 1: Calculate the resonant frequency of the delamination defect according to the sound velocity of the copper conductor and the depth of the subcutaneous shrinkage tail delamination defect, wherein the sound velocity in copper is c=4700m / s, and the subcutaneous shrinkage tail delamination defect d near the surface produced in the actual production of the copper conductor is about 0.2-0.4mm. According to the formula f=c / 2d, the resonant frequency f can be calculated to be between 5.9MHz and 11.8MHz;

[0028] Step 2: Use a wide-band narrow-pulse ultrasonic probe with a frequency band of 5 to 15 MHz to detect the workpiece and collect the ultrasonic echo signal of the copper conductor;

[0029] Step 3: Remove the surface echo and bottom wave from the collected ultrasonic signal to obtain Figure 4 The backscattered signal shown is subjected to fast Fourier transform to obtain the backscattered signal spectrum;

[0030] Step 4: Filter the Fourier transformed signal to remove low-frequency signals with a frequency lower than 5 MHz and leave signals with a frequency within the resonant frequency range;

[0031] Step 5: Calculate the power spectrum energy value of the filtered signal, such as Figure 5 As shown, the calculated eigenvalue is 30921, which exceeds the threshold value of 3500, and it can be determined that there is a defect at this position.

[0032] In step 2, a probe with a frequency band of 5 to 15 MHz is used. The high-frequency component can excite the more tightly compacted near-surface subcutaneous delamination defects to generate resonance signals; the surface of the workpiece that may have defects is detected.

[0033] The characteristic value calculation method in step 5 is to integrate the power spectrum of the backscattered signal and then square it. The defect threshold can be freely set according to the workpiece and probe during specific detection. In this embodiment, the threshold is set to 3500.

[0034] In this embodiment, the following operation is used to determine the threshold: before detection, a large number of ultrasonic backscatter signals of copper bars without defects and with artificially simulated defects are collected to set the defect threshold. The characteristic values ​​of the defect-free copper bars collected in this embodiment are between 400 and 2000, while the characteristic values ​​of the defective copper bars are all above 4000, so 3500 is defined as the defect threshold.

[0035] The backscattered signal of the defect-free copper conductor is collected as follows: Figure 2 As shown, it is Figure 4 The signal amplitudes of the defective copper conductors shown are not much different, and they are calculated separately. Figure 3 , Figure 5 The power spectrum is shown, and the power spectrum is integrated to obtain its eigenvalue, where the eigenvalue of the defect-free copper conductor is 544, and the eigenvalue of the defective copper conductor is 30920, which is much larger than the eigenvalue of the defect-free signal. It can be seen that compared with the traditional time domain signal detection, the method of calculating the eigenvalue of the power spectrum in the present invention can more easily detect the near-surface subcutaneous shrinkage tail defect.

[0036] The above-described embodiments are merely descriptions of preferred embodiments of the present invention and are not intended to limit the scope of the present invention. Without departing from the spirit of the present invention, various modifications and improvements made to the technical solutions of the present invention by ordinary technicians in this field should all fall within the scope of protection determined by the claims of the present invention.

Claims

1. A method for automatic identification of near-surface defects based on ultrasonic resonance method, characterized in that: The method includes: Step 1, calculating the defect resonance frequency range according to the thickness range of the near-surface delamination defect of the workpiece; Step 2: Use an ultrasonic probe to detect the workpiece and collect ultrasonic signals; Step 3, performing Fourier transform on a sample of a specified length of the ultrasonic signal to obtain a backscattered signal spectrum; Step 4, performing bandpass filtering on the backscattered signal spectrum to filter out frequency components outside the resonance frequency range; Step 5: Calculate the power spectrum and its eigenvalues. If the eigenvalue exceeds the set defect threshold, it is determined that the workpiece has defects, otherwise, there are no defects. In step 2, the selected ultrasonic probe is a wide-band narrow-pulse ultrasonic probe, and the probe frequency band covers the resonance frequency range of the delamination defect; In step 3, the method of cutting samples is: removing the surface echo and the bottom echo, leaving the backscattered signal; In step 5, the eigenvalue of the power spectrum is calculated by integrating and squaring it; The method for setting the defect threshold is as follows: before detection, ultrasonic backscatter signals of sample workpieces without defects and with artificially simulated defects are collected, the sample workpieces have the same specifications as the workpiece to be tested, at least 100 sample workpieces with and without defects are collected respectively, and the defect threshold is set according to the difference between the characteristic values ​​of the sample workpieces with and without defects.

2. The method for automatic identification of near-surface defects based on ultrasonic resonance method according to claim 1, characterized in that: The calculation formula of the defect resonance frequency is f=c / 2d, wherein f is the resonance frequency, c is the speed of the ultrasonic longitudinal wave in the material, and d is the thickness of the delamination defect.

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