CN106552998B - The method of estimation of laser index carving technological parameter and laser index carving method - Google Patents

Abstract

The invention relates to the field of laser marking, in particular to a method for estimating laser marking process parameters required for marking an aluminum ingot on the surface of an aluminum ingot by using a laser. In order to improve the marking effect and marking efficiency, the present invention proposes a method for estimating laser marking process parameters: conduct equal-level multi-factor orthogonal tests on aluminum ingots to be marked and record multiple sets of test data; establish marking images The calculation model equation of the image gray value G: b _i (i=0, 1, 2, 3), b ₄ , b ₅ ,..., b ₉ , b ₁₀ are fitting coefficients; according to the test data fitting of equal-level multi-factor orthogonal test Obtain the value of the fitting coefficient; estimate and obtain the laser marking process parameters according to the objective function G<150. Using the estimation method of laser marking process parameters, the laser marking process parameters can be estimated according to the gray value of the image required for marking, which can be directly used for laser marking, which improves the effect and efficiency of laser marking and the automatic recognition of marked images Rate.

Description

Estimation Method of Laser Marking Process Parameters and Laser Marking Method

technical field

The invention relates to the field of laser marking, in particular to a method for estimating laser marking process parameters required for marking an aluminum ingot on the surface of an aluminum ingot by using a laser and a method for marking an aluminum ingot on the surface of an aluminum ingot by using a laser.

Background technique

Before the aluminum ingot is finished and leaves the factory, the aluminum ingot logo needs to be marked on the aluminum ingot. The aluminum ingot logo usually uses text, barcode and/or two-dimensional code to record the production unit, production date, laboratory information, and melting furnace of the aluminum ingot. No., grade information and weight information and other relevant information.

At present, aluminum ingots are marked by pasting paper labels printed with aluminum ingots on the aluminum ingots or by using inkjet marking, pneumatic marking or laser marking to mark the aluminum ingots on the surface of the aluminum ingots. Among them, pasting the paper label printed with the aluminum ingot logo on the aluminum ingot is time-consuming, laborious, and costly, and the paper label is easily damaged during the transportation and storage of the aluminum ingot, which affects the identification. The automatic identification of aluminum ingot marks obtained by inkjet marking and pneumatic marking is poor and inconvenient. When using the laser marking method to mark the aluminum ingot on the surface of the aluminum ingot, it is necessary to select and adjust the laser marking process parameters according to the marking needs. However, due to the uneven surface of the aluminum ingot and the complex marking background image, the laser marking process The selection of parameters is difficult, the marking effect is poor, and the marking efficiency is low, which leads to a low automatic recognition rate of the marked aluminum ingot marking, especially the one-dimensional code and two-dimensional code in the aluminum ingot marking.

Contents of the invention

In order to improve marking effect and marking efficiency, the present invention proposes a method for estimating laser marking process parameters, which includes the following steps:

Step 1: Conduct an equal-level multi-factor orthogonal test on the aluminum ingot to be marked. During the test, adjust the laser marking process parameters to obtain different image gray values of the marked image, and record multiple sets of test data. The test data include laser marking process parameters focusing laser beam diameter d, laser machine Q frequency f, laser scanning speed v, laser power p, and filling line spacing s values, as well as the image gray value of the corresponding marking image;

Step 2: Establish the calculation model equation of the image gray value of the marked image:

in,

G represents the image gray value of the marked image,

b _i (i=0, 1, 2, 3), b ₄ , b ₅ ,..., b ₉ , b ₁₀ are fitting coefficients;

Step 3: According to the test data fitting of the equal-level multi-factor orthogonal test in the step 1, obtain the value of the fitting coefficient in the calculation model equation of the gray value of the image;

Step 4: According to the objective function G<150, estimate the laser marking process parameters laser spot overlapping times n, focused laser beam diameter d, laser machine Q frequency f, laser scanning speed v, laser single pulse energy e and laser power p value.

Using this estimation method of laser marking process parameters, the laser marking process parameters can be estimated according to the image gray value required for marking, and the gray value of the marking image obtained by marking with the estimated laser marking process parameters is The agreement between the actual gray value of the marked image and the estimated gray value of the marked image obtained by estimating the estimated laser marking process parameters is relatively high. That is to say, the gray value of the marking image obtained by direct laser marking using the estimated laser marking process parameters is relatively close to the expected gray value of the marking image. Therefore, the estimated laser marking The process parameters can be directly used for laser marking, which improves the laser marking effect and marking efficiency. In addition, when using the objective function to estimate the laser marking process parameters, the specific value of the objective function G can be set according to the needs of automatic identification, so that the automatic identification rate of the marked image can be improved.

Preferably, in the step 3, the value of the fitting coefficient in the calculation model equation of the gray value of the image is obtained by fitting the immune cloning algorithm. Further, when fitting, the affinity optimization objective function used is

in,

N is the group number of the test data collected when carrying out equal level multifactorial orthogonal test in described step 1,

G _mj is the estimated image gray value of the marked image obtained from the jth group of experiments in an affinity calculation,

G _cj is the image grayscale measurement value of the marked image obtained from the jth group of experiments in an affinity calculation.

In this way, the fitting speed and the accuracy of the fitting coefficients can be further improved, and thus the estimation accuracy of the laser marking process parameters can be improved.

The present invention also proposes a laser marking method, which includes the following steps:

S1. A light-color marking background area is ablated on the surface of the aluminum ingot to be marked, and the gray-scale value variance σ ² of the light-color marking background area is ≤50, and the image gray-scale average value M≥150;

S2. Using the method for estimating laser marking process parameters described in any one of claims 1-3 to estimate the laser marking process parameters for marking aluminum ingots in the light-colored marking background area;

S3. Using the laser marking process parameters estimated in step S2 to mark the aluminum ingot logo in the light-colored marking background area.

Preferably, in the step S1, the value range of the filling line spacing s in the laser ablation process parameters is 0.01-0.2 mm, the value range of the laser scanning speed v is 500-1000 mm/s, and the value range of the laser power p is The value range is 10-20W, and the value range of the Q frequency f of the laser machine is 50-100kHz.

Preferably, in the step S3, when the aluminum ingot logo is marked in the light-colored marking background area, the value range of the filling line spacing s in the laser marking process parameter is 0.01-0.1mm, and the laser The value range of the scanning speed v is 100-200mm/s, the value range of the laser power p is 12-20W, and the value range of the Q frequency f of the laser machine is 20-28kHz.

The laser marking method is used to mark the aluminum ingot logo on the surface of the aluminum ingot, and the estimated laser marking process parameters are directly used to mark the aluminum ingot logo in the light-colored marking background area, without having to adjust the laser marking process parameters. Repeated adjustments improved the marking efficiency of aluminum ingot markings; the objective function of estimating laser marking process parameters was set according to the needs of automatic identification, thereby improving the automatic recognition rate of aluminum ingot markings obtained by marking.

Description of drawings

Figure 1 is the laser marking image obtained from the laser marking test to verify the influence of laser spot overlapping times n, laser single pulse energy e and filling line spacing s on the laser marking effect;

Fig. 2 is the change curve of the image gray value of the marking image obtained by the single factor change test with the laser spot overlapping times n as the change factor;

Fig. 3 is the change curve of the image gray value of the marking image obtained by the single factor change test with the laser single pulse energy e as the change factor;

Fig. 4 is the change curve of the image gray value of the marked image obtained by the single factor change test with the filling line spacing s as the change factor;

Figure 5 is the marking effect diagram obtained by equal-level multi-factor orthogonal experiment;

Figure 6 is the marking effect diagram obtained by the verification test;

Fig. 7 is the comparison result of the gray scale estimation value of the marking image and the gray scale measurement value of the marking image obtained from the verification test.

Detailed ways

The estimation method of the laser marking process parameters of the present invention and the laser marking method of marking the aluminum ingot on the surface of the aluminum ingot using the estimated laser marking process parameters obtained by the estimation method will be described in detail below in conjunction with the accompanying drawings.

According to the principle of laser ablation, the energy obtained by the laser marking surface depends on the number of overlapping laser spots n and the single pulse energy e of the laser. Among them, the laser spot overlapping times n refers to the maximum accumulated ablation times of the inner area during the laser marking process when the laser pulse spot moves along the linear direction, and when the laser scanning speed v is slow and the Q frequency f is high, the laser spot The number of overlapping n is high, and vice versa, and can be expressed as Laser single pulse energy e refers to the energy contained in each laser pulse, and is positively correlated with laser power P and negatively correlated with Q frequency f, and can be expressed as It can be deduced from this that when laser marking is performed, when the number of overlapping laser spots n and laser single pulse energy e are the same, the energy input of laser marking to the material is the same, and the effect of the marking image obtained by marking is the same, that is, marking The grayscale values of the images are the same. In order to verify whether the above inference is correct, the inventor used a pulsed fiber laser to conduct a marking verification test on the surface of an aluminum block whose chemical composition is shown in Table 1. The focused laser beam diameter of the pulsed fiber laser is d ₀ , other marking process parameters are shown in Table 2.

Table 1 Al99.7 material chemical composition (mass fraction)

Al Fe Si Cu Ca Mg Zn 99.75% 0.17% 0.05% 0% 0.02% 0% 0.01%

Table 2 Laser marking process parameters

Among them, s is the filling line spacing, which means the spacing between scanning lines when the laser ablates the surface pattern. The laser marking image obtained by marking the surface of the Al99.7 aluminum block with the laser marking process parameters shown in Table 2 is shown in Figure 1. Corresponding to Table 2, it can be seen that the laser marking process parameters for the four sets of marking verification tests in each row in Figure 1 have the same laser spot overlapping times n, laser single pulse energy e, and filling line spacing s; the second row and the second row The laser marking process parameters used in the marking verification test in row 3 have the same laser spot overlap n and laser single pulse energy e, and different filling line spacing s; the marking verification test in row 4 and row 5 The laser marking process parameters used have the same laser spot overlapping times n and laser single pulse energy e, and different filling line spacing s; the laser marking process parameters used in the marking verification test in the second row and the fourth row have The same filling line spacing s, different laser spot overlapping times n and laser single pulse energy e; the laser marking process parameters used in the marking verification test in the third row and the fifth row have the same filling line spacing s, different The laser spot overlapping times n and laser single pulse energy e. It can be seen that, in addition to the laser spot overlapping times n and laser single pulse energy e, the value of the filling line spacing s will also affect the image gray value of the laser marking image obtained by marking.

In order to study the effects of laser spot overlapping times n, laser single pulse energy e, and filling line spacing s on the image gray value of the laser marking image obtained by laser marking, the inventors used a pulsed fiber laser with multiple specifications of 150mm× 150mm×10mm and the grades of aluminum blocks are all Al99.7 on the surface of the single-factor change laser marking test, and the focused laser beam diameter of the pulsed fiber laser used for the test is 0.05mm, the focal length is 20cm, the maximum output power is 20W, the wavelength It is 1064nm, and the pulse width is 100nm.

Firstly, three sets of single-factor changing laser marking experiments were carried out with the number of overlapping laser spots n as the changing factor, and the values of laser single pulse energy e in the three sets of single-factor changing laser marking tests were 0.5mJ, 0.7mJ and 0.9mJ, the value of the filling line spacing s is 0.1mm, the test marking size is a square figure of 8mm×8mm, and the image gray value of the marked image is obtained by using a scanner that can avoid the gray value being affected by the light. And the change curves of three image gray values obtained from three groups of single factor change laser marking experiments are shown in Fig. 2 . It can be seen from Figure 2 that at the initial positions of the three image gray value change curves, the distribution of image gray value is not equal, but as the value of the overlapping number of laser spots n increases, the three image gray value change curves show an overall decline trend, and the greater the energy e of the laser single pulse, the faster the decline rate. When the number of laser spot overlap n is between 5 and 15 times, the marked image takes the lowest image gray value; when the number of laser spot overlap n After reaching a certain number of times, the image gray value of the marked image gradually increases and tends to be consistent; when the laser spot overlap n exceeds 15 times, the image gray value of the marked image changes slowly and tends to be consistent.

Secondly, four sets of single-factor change experiments were carried out with the laser single pulse energy e as the change factor, and the values of the overlapping times n of laser spots in the four sets of single-factor change laser marking tests were 2, 6, 10 and 15 in sequence. The value of the line spacing s is 0.1mm, and the test marking specification is a square figure of 8mm×8mm, and the image gray value of the marked image is obtained by using a scanner that can avoid the influence of light on the gray value, and the four groups of single Factor Variation The variation curves of the gray values of the four images obtained from the laser marking test are shown in Figure 3. It can be seen from Figure 3 that the image gray value of the marking image obtained from the four groups of single-factor change laser marking experiments shows a downward trend with the increase of laser single pulse energy e, and under different laser spot overlapping times n, The image gray value declines at different speeds. When the number of laser spot overlaps is 2, the image gray value decreases slowly. As the number of laser spot overlap n increases, the image gray value decreases faster. For example, the number of laser spot overlaps When the number of overlapping laser spots n reaches a certain number, the gray value of the image tends to a certain value, such as when the number of overlapping laser spots is 15. In addition, when the laser single pulse energy e is less than 0.3, the laser marking marks are not obvious and the image is not clear because the energy is too small.

Finally, four sets of single-factor change experiments were carried out with the filling line spacing s as the change factor, and the values of the overlapping times n of laser spots in the four sets of single-factor change laser marking tests were 4, 20, 3, and 10 in sequence. The value of the single pulse energy e is 0.3mJ, 0.3mJ, 0.6mJ and 0.6mJ in turn, the test marking size is a square pattern of 8mm×8mm, and the scanner that can avoid the gray value affected by the light is selected to obtain the marking image The gray value of the image, and the change curves of the four image gray values obtained from the four sets of single factor change laser marking experiments are shown in Figure 4. It can be seen from Figure 4 that the image gray value of the marking image obtained from the four groups of single-factor change laser marking experiments gradually increases with the increase of the filling line spacing s. When the filling line spacing s changes between 0.01mm and 0.03mm , the image gray value increases significantly; when the filling line spacing s is greater than 0.03mm, the image gray value increases slightly and tends to be stable; when the filling line spacing s exceeds 0.1mm, the heat generated by the interaction between the laser and the aluminum block surface The surface of the aluminum block between the filling lines cannot be affected, the gray value of the surface of the aluminum block hardly changes, and a clear marking image cannot be obtained. In addition, since the smaller the spacing s of the filling lines, the lower the efficiency of laser marking, the value of the spacing s of the filling lines is generally greater than 0.5 mm during laser marking.

Through the analysis of the above three single factor change experiments, it can be obtained that the laser spot overlap n, the laser single pulse energy e and the filling line spacing s are used for laser marking on the surface of the Al99.7 aluminum block using a pulsed fiber laser range of values. However, when the laser spot overlapping times n, laser single pulse energy e, and filling line spacing s are respectively selected to different values, the image gray value of the marking image obtained by laser marking on the surface of the aluminum block with the pulsed fiber laser is different, that is, the marking The color depth of the engraved image is different. When the image gray value of the marked image is close to the gray value of the marked background area, it is easy to cause the automatic marking of the marked image, especially the barcode and/or two-dimensional code in the marked image. The recognition rate is reduced.

In order to improve the automatic recognition rate of the marking image obtained by laser marking on the surface of an aluminum ingot using a pulsed fiber laser, the inventor established a calculation model equation for the image gray value of the marking image based on the above test results, so that according to the marking image The calculation model of the gray value of the image can be used to obtain the laser marking process parameters laser machine Q frequency f, laser scanning speed v and laser power p values required for laser marking on the surface of aluminum ingots by pulsed fiber lasers.

First of all, according to the correspondence between the laser spot overlapping times n and the image gray value of the marking image shown in Figure 2, the image gray value _G of the marking image only affected by the laser spot overlapping n The computational model equation fit is:

G ₁ =a ₀ +a ₁ n+a ₂ n ² +a ₃ n ³ (1)

which is

Among them, a _i is the fitting coefficient, i=0, 1, 2, 3.

Secondly, according to the correspondence between the laser single pulse energy e and the image gray value of the marked image shown in Figure 3, the image gray value _G'2 of the marked image that is only affected by the laser single pulse energy e is The computational model equation for is fitted as:

Among them, a ₄₁ and a ₅ are fitting coefficients.

Then, according to the corresponding relationship between the filling line spacing s and the image gray value of the marked image shown in Figure 4, the image gray value _G'3 of the marking image that will only be affected by the filling line spacing s The computational model equation fit is:

Among them, a ₄₂ and a ₈ are fitting coefficients.

When fitting the calculation model equations of G ₁ , G' ₂ and G' ₃ , it is preferable to use the immune cloning algorithm to fit and obtain the value of the fitting coefficient. In order to improve the goodness of fit of the immune cloning algorithm, G' ₂ and G' ₃ are transformed into G ₂ and G ₃ , where,

Because when a ₆ =a ₉ =0, a ₇ =a ₁₀ =1, G' ₂ =G ₂ , G' ₃ =G ₃ , so when using the immune cloning algorithm to find G' ₂ , G' ₃ , G ₂ and the optimal solution of _G3 , the optimal value of _G'2 is included in _G2 , and the optimal value of _G'3 is included in _G3 , so the calculation model of the image gray value G of the marked image can be obtained equation:

G＝G ₁ ×G ₂ ×G ₃ (7)

Among them, a ₄ =a ₄₁ +a ₄₂

which is,

Since the focused laser beam diameter d of the pulsed fiber laser is a non-adjustable process parameter, and Therefore,

in,

b _i = a _i d ⁱ , i = 0, 1, 2, 3,

b ₄ =a ₄ , b ₅ =a ₅ , b ₆ =a ₆ , b ₇ =a ₇ , b ₈ =a ₈ , b ₉ =a ₉ , b ₁₀ =a ₁₀ .

According to the value ranges of laser spot overlapping times n, laser single pulse energy e and filling line spacing s obtained by single factor experiment, combined with the physical meaning of laser spot overlapping times n and laser single pulse energy e, the adjustable pulsed fiber laser is set The laser marking process parameters and levels are shown in Table 3.

Table 3 Adjustable laser marking process parameters and levels

According to Table 3, an equal-level multi-factor orthogonal experiment was designed, and a total of 25 sets of laser marking process parameters were obtained. The 25 marking images obtained by using the 25 sets of laser marking process parameters for marking are shown in Figure 5. The scanner that can prevent the gray value from being affected by light can obtain the image gray value of the marked image, and the laser marking process parameters and the corresponding image gray value of the marked image are shown in Table 4.

Table 4 Experimental data of equal-level multi-factor orthogonal experiment

Group No s(mm) v(mm/s) P(w) f(kHz) e(mJ) no Image gray scale measurement 1 0.06 100 10 20 0.5 10 128 2 0.07 200 12 twenty two 0.55 5.5 154 3 0.08 300 14 twenty four 0.58 4 169 4 0.09 400 16 26 0.62 3.25 172 5 0.10 500 18 28 0.64 2.8 176 6 0.07 300 16 28 0.571 4.67 162 7 0.08 400 18 20 0.9 2.5 170 8 0.09 500 10 twenty two 0.45 2.2 198 9 0.10 100 12 twenty four 0.5 12 145 10 0.06 200 14 26 0.54 6.5 143 11 0.08 500 12 26 0.46 2.6 196 12 0.09 100 14 28 0.5 14 142 13 0.10 200 16 20 0.8 5 148 14 0.06 300 18 twenty two 0.82 3.67 150 15 0.07 400 10 twenty four 0.42 3 201 16 0.09 200 18 twenty four 0.75 6 139 17 0.10 300 10 26 0.38 4.33 186 18 0.06 400 12 28 0.43 3.5 186 19 0.07 500 14 20 0.7 2 184 20 0.08 100 16 twenty two 0.73 11 134 twenty one 0.10 400 14 twenty two 0.67 2.75 174 twenty two 0.06 500 16 twenty four 0.67 2.4 169 twenty three 0.07 100 18 26 0.69 13 137 twenty four 0.08 200 10 28 0.36 7 170 25 0.09 300 12 20 0.6 3.33 168

According to the experimental data of the above-mentioned equal-level multi-factor orthogonal experiment, there is no obvious regularity between the laser marking process parameters and the image gray value of the marked image, and the marked image in the neighborhood of the image gray value of the marked image The corresponding laser marking process parameters are not simply distributed in the neighborhood of the laser marking process parameters corresponding to the image gray value of the marking image, but distributed in the laser marking area corresponding to the image gray value of several marking images. In the neighborhood union of engraving process parameters, such as the first group, the 12th group, the 16th group, the 20th group and the 23rd group test, the laser marking process parameters used in the test are at a power P of 10 ~ 18W, The Q frequency f is 20-28kHz, the filling line spacing s is 0.06-0.09mm, and the scanning speed v is 100-200mm/s The combination of laser marking process parameters with different values selected in the value range, and calculated Different values of laser single pulse energy e and laser spot overlapping times n, and the laser marking process parameters with different values are combined to mark the marking image with similar gray value on the surface of the aluminum block. However, not any combination of laser marking process parameters selected within the above value range can mark images with similar gray values, and different combinations of laser marking process parameters may mark gray images. Marked images with large differences in degree values. According to the above analysis, it can be seen that the equal-level multi-factor orthogonal experiment reflects the corresponding relationship between different laser marking process parameter combinations and the image gray value of the marked image obtained by marking: multiple groups of different laser marking process parameters The combination can mark images with similar gray values; the combination of different laser marking process parameters can mark images with large differences in image gray values. Therefore, the above-mentioned equal-level multi-factor orthogonal test data is highly representative and can be used as reasonable data to fit the fitting coefficient in the calculation model equation of the image gray value G of the marked image.

Obtain the regression of the image gray value G of the marking image according to the equal-level multi-factor orthogonal test data fitting in table 4 and calculate the fitting coefficient b _i (i=0,1,2,3) in the model equation , b ₄ , b ₅ , b ₆ , b ₇ , b ₈ , b ₉ and b ₁₀ . The value of the error sum between is the smallest.

In order to improve the fitting speed and fitting accuracy, the immune cloning algorithm is preferably used as the fitting algorithm for fitting. In the fitting process, the affinity optimization objective function adopted is:

in,

N is the group number of the experimental data collected when horizontal multifactorial orthogonal experiment, in table 4, N=25,

G _mj is the estimated image gray value of the marked image obtained from the jth group of experiments in an affinity calculation,

G _cj is the image grayscale measurement value of the marked image obtained from the jth group of experiments in an affinity calculation.

The fitting coefficients b ₀ , b ₁ , b ₂ , b ₃ , b in the calculation model equation of the image gray value G of the marked image are obtained by fitting the test data of the equal-level multi-factor orthogonal test in Table 4 ₄ , b ₅ , b ₆ , b ₇ , b ₈ , b ₉ and b ₁₀ , the calculation model equation of the image gray value G of the marked image obtained is:

In order to avoid the unreliable fitting coefficient obtained by fitting, the following uses the complex determination coefficient ^R2 and the variance analysis F value to measure the goodness of fit of the calculation model equation of the image gray value G of the marked image to the measured data set and the calculation The credibility of the model equation, the results are as follows:

in,

rss is the residual sum of squares between the image grayscale measurement value of the marked image and the image grayscale estimated value,

tss is the sum of squares of the total deviation between the measured image grayscale value of the marked image and the image grayscale estimated value;

in,

ess is the regression sum of squares,

h is the degree of freedom of the regression sum of squares,

w-h-1 is the degree of freedom of the residual sum of squares.

According to the above results, since R ² =0.97, which is close to 1, the goodness of fit is good; looking up the F table, it can be seen that F=51.45》F0.05(10,15)=2.54, the image gray value of the marked image G The reliability of the calculation model equation is high.

In order to deepen the color depth of the marked image and improve the automatic recognition rate of the marked image, the inventors set the image gray value G<150 of the marked image marked by laser marking. That is to say, the objective function when the laser marking process parameters are estimated by using the calculation model equation of the image gray value G of the marking image is G<150. Of course, in the actual marking process, the user can select the specific value of the objective function G according to the needs of automatic identification.

In order to verify the effectiveness of the method for estimating the laser marking process parameters of the present invention, 25 groups of laser marking process parameters shown in Table 5 were used to carry out a laser marking verification test on the surface of an aluminum block with a grade of Al99.7. The marking image is as follows As shown in FIG. 6 , the image grayscale measurement values of the marked images obtained by marking with different laser marking process parameters are shown in Table 5.

Table 5 Test data of laser marking verification test

At the same time, using the formula (11), the image gray value of the marking image obtained by laser marking on the surface of the Al99.7 aluminum block using the 25 sets of laser marking process parameters shown in Table 5 can be calculated in turn , and the comparison result of the image grayscale estimated value and the image grayscale measured value of the marked image obtained from the laser marking verification test is shown in FIG. 7 . It can be seen from Fig. 7 that the estimated image grayscale value of the marked image estimated by the method for estimating the laser marking process parameters of the present invention has a high degree of agreement with the measured image grayscale value of the marked image obtained from the laser marking verification test. .

Below, the laser marking method for marking the aluminum ingot logo on the aluminum ingot to be marked will be described in detail in combination with the estimation method of the above laser marking process parameters. The laser marking method includes the following steps:

S1. Use a pulsed fiber laser to ablate a light-colored marking background area on the surface of the aluminum ingot to be marked, and the gray-scale value variance of the light-colored marking background area σ ² ≤50, and the image gray-scale average value M≥ 150. Preferably, when the light-colored marking background area is ablated on the surface of the aluminum ingot to be marked, the value range of the filling line spacing s in the laser ablation process parameters is 0.01-0.2 mm, and the value range of the laser scanning speed v is 500-1000mm/s, the value range of laser power p is 10-20W, and the value range of laser machine Q frequency f is 50-100kHz.

S2. Estimate the laser marking process parameters required for marking the aluminum ingots in the light-colored marking background area by using the estimation method of the above-mentioned laser marking process parameters;

S3. Use the pulsed fiber laser to mark the aluminum ingot logo in the light-colored marking background area, and the laser marking process parameters used for marking are the laser marking process parameters estimated in step S2. Preferably, when marking the aluminum ingot logo in the light-colored marking background area, the value range of the filling line spacing s in the laser marking process parameters is 0.01-0.1mm, and the value range of the laser scanning speed v is 100-200mm /s, the value range of laser power p is 12-20W, and the value range of laser machine Q frequency f is 20-28kHz.

Claims (6)

1. an estimation method of laser marking process parameter, is characterized in that, this estimation method comprises the steps: Step 1: Conduct an equal-level multi-factor orthogonal test on the aluminum ingot to be marked. During the test, adjust the laser marking process parameters to obtain different image gray values of the marked image, and record multiple sets of test data. The test data include laser marking process parameters focusing laser beam diameter d, laser machine Q frequency f, laser scanning speed v, laser power p, and filling line spacing s values, as well as the image gray value of the corresponding marking image; Step 2: Establish the calculation model equation of the image gray value of the marked image: in, G represents the image gray value of the marked image, b _i (i=0, 1, 2, 3), b ₄ , b ₅ ,..., b ₉ , b ₁₀ are fitting coefficients; Step 3: According to the test data fitting of the equal-level multi-factor orthogonal test recorded in the step 1, obtain the value of the fitting coefficient in the calculation model equation of the gray value of the image; Step 4: According to the objective function G<150, estimate and obtain the laser marking process parameters focusing laser beam diameter d, laser machine Q frequency f, laser scanning speed v and laser power p. 2. The estimation method of laser marking process parameter according to claim 1, is characterized in that, in described step 3, adopts immune cloning algorithm fitting to obtain the simulation model equation in the calculation model equation of described image gray value Combined coefficient value. 3. the estimation method of laser marking process parameter according to claim 2 is characterized in that, when fitting, the affinity optimization objective function that adopts is in, N is the group number of the test data collected when carrying out equal level multi-factor orthogonal test in the said step 1, _{and G} is the estimated image grayscale value of the marked image obtained by the j group test in the calculation of the affinity, G _cj is the image grayscale measurement value of the marked image obtained from the jth group of experiments in an affinity calculation. 4. A laser marking method, characterized in that the laser marking method comprises the steps: S1. A light-colored marking background area is ablated on the surface of the aluminum ingot to be marked, and the gray value variance σ ² of the light-colored marking background area is ≤50, and the image gray-scale average M≥150; S2. Using the method for estimating laser marking process parameters described in any one of claims 1-3 to estimate the laser marking process parameters for marking aluminum ingots in the light-colored marking background area; S3. Using the laser marking process parameters estimated in step S2 to mark the aluminum ingot logo in the light-colored marking background area. 5. The laser marking method according to claim 4, characterized in that, in the step S1, the value range of the filling line spacing s in the laser ablation process parameters is 0.01-0.2mm, and the laser scanning speed v The value range is 500-1000mm/s, the value range of laser power p is 10-20W, and the value range of laser machine Q frequency f is 50-100kHz. 6. The laser marking method according to claim 4, characterized in that, in the step S3, when marking the aluminum ingot logo in the light-colored marking background area, among the laser marking process parameters The value range of the filling line spacing s is 0.01-0.1mm, the value range of the laser scanning speed v is 100-200mm/s, the value range of the laser power p is 12-20W, and the value range of the Q frequency f of the laser machine 20-28kHz.