CN113607652B - Workpiece superficial layered imaging method based on photoacoustic spectrum - Google Patents

Abstract

The invention belongs to the technical field of photoacoustic spectrum non-destructive testing, in particular to a method for superficial layered imaging of workpieces based on photoacoustic spectrum. The invention utilizes the pulsed laser combined with the scanning galvanometer to excite the photoacoustic signal on the surface of the workpiece, and selects the peak spectrum in the photoacoustic signal collected by the acoustic sensor through the fast Fourier transform according to the thermal wave depth distribution characteristics represented by the photoacoustic signal of different frequencies. information, and use the pulse laser beam scanning position information controlled by the galvanometer controller as the pixel position information of the image to obtain accumulated layers of different depths. Image, provides a new imaging solution for workpiece surface/subsurface defect detection. The invention can not only be widely applied to the off-line surface subsurface defect detection of the workpiece, but also can be applied to the on-line monitoring of various laser processing processes including metal 3D printing, and has broad application prospects.

Description

A method for superficial layered imaging of workpieces based on photoacoustic spectroscopy

technical field

The invention belongs to the technical field of photoacoustic spectrum non-destructive testing, in particular to a method for superficial layered imaging of workpieces based on photoacoustic spectrum.

Background technique

The laser excitation acoustic technology combines the non-destructive propagation of laser space and the almost non-destructive characteristics of acoustic transmission in solid workpieces, which not only makes the acoustic excitation in the workpiece easy to adjust, but also can carry a variety of materials in the process of converting light energy into sound energy. The physical and structural properties of the material have resulted in more and more development and applications. However, due to the low energy conversion efficiency of photoacoustics, the detection of photoacoustic signals is difficult, which restricts the promotion of photoacoustic technology in industry. With the development of electronic information technology, especially digital technology, small signal detection has become more and more popular. Driven by electronic technology, photoacoustic technology is ushering in a golden period of development and application.

So far, photoacoustic spectroscopy technology has mainly focused on: 1 identification of biological tissues/features, including: skin elasticity, blood sugar, tissue imaging, etc.; 2 gas detection, mainly the improvement of the sensitivity of gas in transformer oil and gas photoacoustic cells; 3 Cross-application of artificial intelligence methods in the field of photoacoustic spectroscopy. At present, there is no related invention in the field of subsurface imaging of workpiece surface.

SUMMARY OF THE INVENTION

The purpose of the present invention is to overcome the deficiencies of the prior art, and to provide a superficial layered imaging technology of workpieces based on photoacoustic spectrum. Correlation, combined with differential image processing, enables layered imaging of sample surfaces/subsurfaces.

The technical scheme adopted in the present invention is:

A method for superficial layered imaging of workpiece based on photoacoustic spectrum, as shown in FIG. 1 , includes a pulsed photoacoustic excitation module 1 and a photoacoustic spectrum layered imaging module 2; the pulsed photoacoustic excitation module 1 includes a pulsed laser 11, The scanning galvanometer 12, the galvanometer controller 13, the acoustic sensor 14 and the acquisition card 15, wherein the pulsed laser 11 emits laser light by means of pulse emission; the scanning galvanometer 12 is used to scan and reflect the laser beam emitted by the pulsed laser 11 to realize Focusing on the workpiece surface, and performing imaging scanning; the galvanometer controller 13 is used to drive the scanning galvanometer 12, control the scanning work of the scanning galvanometer 12, and at the same time send the scanning position information to the photoacoustic spectrum layered imaging module 2; Acoustic sensor 14 is arranged on the other side of the workpiece relative to the surface of the receiving laser beam, detects the signal after the photoacoustic signal passes through the workpiece, and outputs the photoacoustic vibration signal as an analog photoacoustic signal in the form of an analog signal; the acquisition card 15 is used to collect The photoacoustic signal is simulated and converted into a digital signal to output a digital photoacoustic signal; the laser beam performs photoacoustic excitation on the superficial area of the workpiece, and the depth h of the superficial area is the maximum thermal wave input depth, h=2π(D /2f _min ) ^1/2 , where D is the thermal diffusivity of the material, and f _min is the lowest frequency peak of the excitation photoacoustic spectrum;

The photoacoustic spectrum layered imaging module 2 includes a fast Fourier transformer and n image output channels, wherein the fast Fourier transformer receives the digital photoacoustic signal output by the acquisition card 15, and performs a fast Fourier transformation on the digital photoacoustic signal. Liye change, and then according to the set threshold, the frequency output by the fast Fourier transformer is divided into n frequency segments in order from high to low, and all frequency segments are sent in order from high to low. For each image input channel, the first image channel corresponds to the highest frequency segment, and the nth image channel corresponds to the lowest frequency segment; in each image channel, the average intensity of the output signal is taken as the gray scale, and the galvanometer controller 13 The scanning position information is the pixel coordinates of the image, and the grayscale image ∑MAP _i of the superficial layer of the workpiece at the depth _hi is obtained, hi =2π(D/2fi) ^1/2 , _{f i is} the _ith channel Output frequency, i=0,1,...,n, then subtract the grayscale image of the i-1th channel from the grayscale image of the ith channel to obtain the output picture MAP _i of each channel, and the picture MAP _i reflects The case where the depth range of the shallow area of the workpiece is [h _i-1 , h _i ] area is presented.

The beneficial effects of the present invention are:

The invention can obtain layers of different depths by decomposing frequency features on the basis of pump laser scanning imaging, and obtain layered imaging images through layer difference, so the invention can not only be widely applied to off-line surface subsurface defects of workpieces It can also be applied to online monitoring of various laser processing processes including metal 3D printing, with broad application prospects.

Description of drawings

Fig. 1 is the schematic diagram of superficial layered imaging of pulsed photoacoustic spectroscopy workpiece;

Figure 2 is a schematic diagram of the implementation of pulsed photoacoustic spectroscopy superficial 8-layer layered imaging of stainless steel.

Detailed ways

The technical solutions of the present invention will be described in detail below with reference to the accompanying drawings.

As shown in FIG. 2, a case of the specific embodiment of the present invention is to perform layered imaging on the subsurface of the stainless steel sample according to the mode of 8 layers, and the specific implementation method is as follows:

1. The pulsed photoacoustic excitation part 1 is composed of a semiconductor pulsed laser 11 , a scanning galvanometer 12 , a galvanometer controller 13 , a piezoelectric buzzer 14 , and a capture card 15 .

The semiconductor pulse laser 11 is used as an energy source for pulsed photoacoustic excitation, and its laser emission adopts the pulse emission method. The energy time characteristics of the emitted laser directly affect the general characteristics of the photoacoustic signal, so different pulsed lasers can excite different pulsed lasers. photoacoustic spectrum.

The scanning galvanometer 12 is used as a beam space scanning reflection device of the pulsed laser 11, which has the characteristic of focusing on the upper surface of the workpiece, and can complete imaging scanning within a certain range of the upper surface of the workpiece, including row scanning and column scanning.

The galvanometer controller 13 serves as the driving device of the scanning galvanometer 12, provides the driving signal for the scanning galvanometer 12, controls the scanning working state of the scanning galvanometer 12, and simultaneously provides its scanning position information to the photoacoustic spectrum layered imaging part 2, as imaged pixel position information.

The pulsed laser beam is emitted by the pulsed laser 11 and is reflected and controlled by the scanning galvanometer 12 to realize the photoacoustic excitation on the upper surface of the workpiece.

The superficial area of the workpiece is located on the surface and subsurface of the workpiece, and its depth h is the maximum thermal wave input depth, h=2π(D/2f _min ) ^1/2 , (where: D is the thermal diffusivity of the material, and f _min is the lowest frequency peak of the excitation photoacoustic spectrum).

In this example, stainless steel is used as the sample to be tested, and its material includes various samples to be tested, such as metals, non-metals, and semiconductors.

The piezoelectric buzzer 14 is a detector for photoacoustic signals, which is closely attached to the back of the workpiece to realize signal detection after the photoacoustic signal passes through the sample, and outputs the photoacoustic vibration signal as an analog photoacoustic signal in the form of an analog signal. .

The analog photoacoustic signal is an analog signal output after the photoacoustic signal is detected by the acoustic sensor.

The acquisition card 15 is matched with the acoustic sensor, and after the analog photoacoustic signal is collected, it is converted into a digital signal conforming to the digital signal specification, that is, the digital photoacoustic signal is output.

The digital photoacoustic signal is the output signal of the acquisition card, which meets the specifications of the digital signal.

2. The layered imaging part 2 of the photoacoustic spectrum consists of a fast Fourier transformer 21, the highest frequency peak channel of the photoacoustic spectrum 22, the second highest frequency peak channel of the photoacoustic spectrum 23, the lowest frequency peak channel of the photoacoustic spectrum 24, and the shallowest accumulation. Layer 25, second shallow accumulation layer 26, deepest accumulation layer 27, shallowest layer 28, second shallow layer 29, deepest layer 210, etc.

The fast Fourier transformer 21 performs fast Fourier transformation on the digital photoacoustic signal, and outputs signals corresponding to different frequencies in different channels.

The highest frequency peak channel 22 of the photoacoustic spectrum is the output spectrum peak of the fast Fourier transformer 21, and under the condition that the signal strength is not lower than a certain threshold, it is divided into 8 frequency segments according to the frequency, and the segment with the highest frequency The signal channel corresponding to the frequency is the highest frequency channel 22 of the photoacoustic spectrum, which is essentially a bandpass filter that can only pass the highest frequency band, and its average frequency is f ₁ .

The second highest frequency peak channel 23 of the photoacoustic spectrum is the spectral peak output of the fast Fourier transformer 21, and under the condition that the signal strength is not lower than a certain threshold, it is divided into 8 frequency segments according to the frequency level, of which the frequency is the second highest. The signal channel corresponding to the frequency of the photoacoustic spectrum is the second highest frequency peak channel 23 of the photoacoustic spectrum, which is essentially a bandpass filter that can only pass the second high frequency band, and its average frequency is f ₂ .

The lowest frequency peak channel 24 of the photoacoustic spectrum is the spectral peak output of the fast Fourier transformer 21, and under the condition that the signal strength is not lower than a certain threshold, it is divided into 8 frequency segments according to the frequency, and the segment with the lowest frequency The signal channel corresponding to the frequency is the lowest frequency peak channel 24 of the photoacoustic spectrum, which is essentially a bandpass filter that can only pass through the lowest frequency band, and its average frequency is f ₈ .

The shallowest accumulation layer 25 takes the average intensity of the photoacoustic signal output by the highest frequency peak channel of the photoacoustic spectrum as the gray scale, and takes the scanning position information of the galvanometer controller as the pixel coordinates of the image, forming a gray scale image ∑MAP ₁ , because its corresponding photoacoustic spectrum frequency segment is the highest, the obtained image is the shallowest workpiece surface area, and its image depth is [o, h ₁ ], h ₁ =2π(D/2f ₁ ) ^{1 /2} .

The second shallow accumulation layer 26 takes the average intensity of the photoacoustic signal output by the highest frequency peak channel of the photoacoustic spectrum as the gray scale, and takes (1-3) the scanning position information of the galvanometer controller as the pixel coordinates of the image, forming a picture. The gray-scale image ∑MAP ₂ , because its corresponding photoacoustic spectrum frequency segment is the second highest, the obtained image is of sub-shallow depth (the image of the superficial area of the workpiece has an image depth of [o, h ₂ ], and its image depth is h ₂ =2π(D/2f ₂ ) ^1/2 .

The deepest accumulation layer 27 takes the average intensity of the photoacoustic signal output by the highest frequency peak channel of the photoacoustic spectrum as the gray scale, and takes the scanning position information of the galvanometer controller as the pixel coordinates of the image, forming a gray scale image ∑MAP ₈ , because its corresponding photoacoustic spectrum frequency segment is the lowest, the image obtained is the deepest workpiece superficial area, its image depth is [o, h ₈ ], and its image depth is h ₈ =2π(D/2f ₈ ) ^1/2 .

The shallowest layer 28 is consistent with the picture corresponding to the shallowest accumulation layer 25, and reflects the most surface condition of the superficial area of the workpiece. Its picture is MAP ₁ , and its imaging depth range is [o, h ₁ ].

The sub-shallow layer 29 is a picture MAP ₂ obtained by subtracting the shallowest accumulation layer from the sub-shallow accumulation layer 26 , and reflects the situation of the area where the depth range of the superficial area of the workpiece is [h ₁ , h ₂ ].

The deepest layer 210 is a picture MAP ₈ obtained by subtracting the second-deepest accumulation layer from the deepest accumulation layer 27 , and reflects the situation of the area with the depth range of [h ₇ , h ₈ ] in the superficial area of the workpiece.

Claims (1)

1. A workpiece superficial layering imaging method based on photoacoustic spectrometry is characterized by comprisingThe device comprises a pulse photoacoustic excitation module (1) and a photoacoustic spectrum layered imaging module (2); the pulse photoacoustic excitation module (1) comprises a pulse laser (11), a scanning galvanometer (12), a galvanometer controller (13), an acoustic sensor (14) and a collection card (15), wherein the pulse laser (11) emits laser in a pulse emission mode; the scanning galvanometer (12) is used for scanning and reflecting laser beams emitted by the pulse laser (11), so that focusing on the surface of a workpiece is realized, and imaging scanning is performed; the galvanometer controller (13) is used for driving the scanning galvanometer (12), controlling the scanning work of the scanning galvanometer (12) and simultaneously sending scanning position information to the photoacoustic spectrum layered imaging module (2); the acoustic sensor (14) is arranged on the other surface of the workpiece opposite to the surface for receiving the laser beam, detects a signal of the photoacoustic signal after passing through the workpiece, and outputs the photoacoustic vibration signal as an analog photoacoustic signal in an analog signal mode; the acquisition card (15) is used for acquiring the analog photoacoustic signal, converting the analog photoacoustic signal into a digital signal and outputting the digital photoacoustic signal; the laser beam performs photoacoustic excitation on a superficial region of the workpiece, the depth h of the superficial region is the maximum heat wave input depth, and h is 2 pi (D/2 f)_min)^1/2Where D is the thermal diffusivity of the material, f_minIs the lowest frequency peak of the excitation photoacoustic spectrum;

the photoacoustic spectrum layered imaging module (2) comprises a fast Fourier transformer and n image output channels, wherein the fast Fourier transformer receives digital photoacoustic signals output by an acquisition card (15), the digital photoacoustic signals are subjected to fast Fourier change, then the frequency output by the fast Fourier transformer is sequentially divided into n frequency sections from high to low according to a set threshold value, all the frequency sections are sequentially sent to each image output channel from high to low, and the 1 st image channel corresponds to the highest frequency section and the nth image channel corresponds to the lowest frequency section; in each image channel, the average intensity of the output signal is used as a gray scale, the scanning position information of the galvanometer controller (13) is used as the pixel coordinate of the image, and the depth h is obtained_iThe gray scale image sigma MAP of the shallow surface of the workpiece_i，h_i＝2π(D/2f_i)^1/2，f_iIs the output frequency of the ith channel, i is 1,2, …, n, and then the ith channelSubtracting the gray scale image of the (i-1) th channel from the gray scale image of the i channels to obtain an output picture MAP of each channel_iMAP, picture_iReflects the depth range of the workpiece superficial region as h_i-1,h_i]The case of a region.

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