A real-time evaluation method for laser paint removal effect based on LIBS data flow disk

Abstract

The present invention provides a real-time evaluation method for the laser paint removal effect based on a LIBS data flow disk, including: classifying the degree of paint layer removal effect; measuring the original LIBS spectra of each paint layer and the substrate on the surface to be painted, determining the characteristic peaks of each paint layer and the substrate, selecting characteristic elements according to the characteristic peaks, and recording the intensity of the characteristic elements as the standard intensity; collecting and calculating the relative intensity of each characteristic element in the real-time spectrum in real time; dividing the interval of the relative intensity of each characteristic element to determine the judgment rule for the paint removal effect; taking the relative intensity of each characteristic element as a data unit, forming a data set with continuous n data units, and forming a data flow disk with continuous n data sets; judging each data set according to the judgment rule for the data flow disk and giving a conclusion on the real-time paint removal effect. This method makes a trend judgment based on a real-time flowing data set, overcomes the instability and uncertainty of single-spectrum data, and forms a more reliable effect evaluation rule.

Description

Technical Field

[0001] The present invention relates to the technical field of spectroscopy and data processing, and particularly relates to a real-time evaluation method for laser paint removal effect based on a LIBS data stream disk. Background Art

[0002] In recent years, with the exploration and development of laser paint removal technology, pulsed laser paint removal technology has been widely recognized. Its essence is to utilize the interaction between laser pulses and paint layer materials to achieve the physical and chemical removal of paint layer materials. Compared with traditional paint removal methods, it has the advantages of high efficiency, environmental protection, and quality controllability.

[0003] Laser-induced Breakdown Spectroscopy (LIBS) is a multi-element analysis technology developed in the late 20th century. This technology uses high-energy laser pulses to ablate the surface of a sample and generate a high-temperature plasma. The high-temperature plasma emits line spectra representing atomic characteristics. The wavelength position and intensity of its spectral lines respectively represent the types and contents of the measured elements, serving as the fundamental basis for qualitative and quantitative analysis. Therefore, the real-time spectral data collected during the laser paint removal process can be used to reflect the substances and contents removed during the laser paint removal process, thereby evaluating the laser paint removal effect.

[0004] Although there are currently many offline characterization methods that can be used as the basis and method for paint removal effect, most of these methods do not have real-time performance or have poor real-time performance. In industrial paint removal, real-time monitoring of the paint removal effect is often required. Therefore, the LIBS technology with good real-time performance is more suitable for evaluating the paint removal effect. However, experiments have found that the spectra of single spectral lines obtained based on the LIBS technology have the following uncertainties and unreliabilities: micro-region non-uniformity, thickness non-uniformity, spectral data instability, plasma collection lag, environmental and noise interference, etc., resulting in the spectral data of one or a single position not being able to be used as the basis for paint removal monitoring. Thus, it is necessary to propose a new real-time evaluation basis and method for paint removal effect. Summary of the Invention

[0005] To solve the above problems, the present invention provides a real-time evaluation method for laser paint removal effect based on a LIBS data stream disk. This method makes a trend judgment based on a real-time flow data set, overcomes the instability and uncertainty of single spectral data, and forms a more reliable effect evaluation rule.

[0006] The present invention provides the following technical solutions.

[0007] A real-time evaluation method for laser paint removal effect based on a LIBS data stream disk includes the following steps:

[0008] Classify the removal degree effect of the paint layer;

[0009] Measure the original LIBS spectra of each paint layer and the substrate on the surface to be de-painted; According to the original LIBS spectra, determine the characteristic peaks of each paint layer and the substrate; Select characteristic elements based on the characteristic peaks, and record the intensity of the characteristic elements as the standard intensity;

[0010] Collect the LIBS spectra during the laser paint removal process in real time, and extract the real-time intensity of each characteristic element in the LIBS spectra; Divide the real-time intensity by the standard intensity to obtain the relative intensity of each characteristic element;

[0011] According to the type of the removal degree effect of the paint layer, divide the interval of the relative intensity of each characteristic element, and determine the judgment rule for the paint removal effect;

[0012] Take the relative intensity of each characteristic element as a data unit, form a data set with consecutive n data units, and form a data flow disk with consecutive n data sets;

[0013] Judge each data set in the data flow disk according to the judgment rule, and give the evaluation conclusion of the real-time paint removal effect.

[0014] Preferably, the types of the removal degree effect of the paint layer include: the topcoat is not completely removed; the topcoat is completely removed and the primer is not damaged; the primer is not completely removed; the primer is completely removed and the substrate is not damaged; the substrate is damaged.

[0015] Preferably, the determination of the characteristic elements and their standard intensities includes the following steps:

[0016] Use a laser to remove the paint on the surface to be de-painted, and collect the spectral data on the surfaces of each paint layer sample and the substrate sample as the standard spectrum;

[0017] Compare several elements with the largest spectral intensity difference in the spectra of each sample, take them as characteristic elements, and extract the intensity of the characteristic elements of the corresponding samples from the above spectral data as the standard intensity.

[0018] Preferably, the characteristic elements are selected according to the difference in composition between materials and combined with the collected spectra to distinguish each paint layer and the substrate.

[0019] Preferably, the characteristic elements have obvious characteristic peaks in the spectrogram.

[0020] Advantages of the present invention:

[0021] The present invention makes a trend judgment based on the real-time flowing data set, overcomes the instability and uncertainty of single spectral data, and forms a more reliable effect evaluation rule. Description of the Drawings

[0022] Figure 1 It is the flowchart of the real-time evaluation method for laser paint removal effect based on the LIBS data stream disk in the embodiment of the present invention;

[0023] Figure 2 It is the schematic diagram of the LIBS data acquisition and processing device for the laser layer-by-layer paint removal process in the embodiment of the present invention;

[0024] Figure 3 It is the standard spectrogram of the topcoat, primer, and aluminum alloy sample in the embodiment of the present invention, (a) topcoat (b) primer (c) aluminum alloy;

[0025] Figure 4 It is any one of the spectra collected during the laser paint removal process of the aluminum alloy skin sample in the embodiment of the present invention. Specific embodiments

[0026] In order to make the objectives, technical solutions, and advantages of the present invention clearer, the present invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not used to limit the present invention.

[0027] Embodiment 1

[0028] A real-time evaluation method for laser paint removal effect based on the LIBS data stream disk of the present invention. Figure 2 It is the schematic diagram of the LIBS data acquisition and processing device of the present invention, mainly composed of 1 - laser device, 2 - lens, 3 - stage, 4 - optical fiber probe, 5 - spectrometer, and 6 - main control computer. The laser irradiated by the laser device is focused on the paint layer surface through the lens, and the plasma generated on the paint layer surface is collected by the optical fiber probe and then transmitted to the spectrometer to continuously form a large amount of spectral data, and then transmitted to the computer. The computer processes the spectral data according to Figure 1 the flowchart and gives the evaluation result of the laser paint removal effect.

[0029] In this embodiment, an aluminum alloy skin sample with a topcoat and a primer sprayed on the surface is taken as an example. Specifically, it includes:

[0030] S1: Determine the type of paint removal effect, including: the topcoat is not completely removed; the topcoat is completely removed and the primer is not damaged; the primer is not completely removed; the primer is completely removed and the substrate is not damaged; the substrate is damaged.

[0031] S2: Measure the original LIBS spectra of each paint layer and the substrate on the surface to be painted, and determine the characteristic elements and their standard intensities of each paint layer and the substrate.

[0032] The standard spectrograms of the topcoat, primer, and aluminum alloy substrate are as shown in Figure 3As shown, based on the compositional information of the paint layer and the substrate, combined with the original spectra of the paint layer and the substrate collected, the characteristic peaks and their standard intensities of the paint layer and the substrate are determined. The selected characteristic elements and their intensities are shown in Table 1.

[0033] Table 1 Selected Characteristic Elements and Their Intensities

[0034] Characteristic element Fe III Mg III Ca I Al I Zn II Wavelength / nm 396 498 616 393 490 Intensity in topcoat / a.u. 641 592 0 0 0 Intensity in primer / a.u. 0 0 288 0 0 Intensity in aluminum alloy substrate / a.u. Trace Trace 0 1050 400

[0035] The determined characteristic elements are marked in the following way:

[0036] Characteristic elements of the topcoat: Fe III and MgIII (denoted as a and b);

[0037] Characteristic elements of the primer: Ca I (denoted as c);

[0038] Characteristic elements of the aluminum alloy substrate: Al I and Zn II (denoted as d and e).

[0039] After determining the characteristic elements, the standard intensities of each characteristic element can be determined. The standard intensities of the characteristic elements of each paint layer and the substrate in the aluminum alloy skin can be obtained from Table 1. The arrangement is shown in Table 2.

[0040] Table 2 Characteristic Elements and Their Corresponding Standard Intensities

[0041] Characteristic element a(Fe III) b(Mg III) c(Ca I) d(Al I) e(Zn II) Standard intensity 641 592 288 1050 400

[0042] S3: Real-time collect the LIBS spectrum during the laser paint removal process, extract the real-time intensities of each characteristic element in the spectrum, and divide by the standard intensity to obtain the relative intensity of each characteristic element.

[0043] Relative intensity = Real-time intensity / Standard intensity. Extract the intensity at the characteristic peak position of the selected characteristic element and divide by the corresponding standard intensity in Table 2 to calculate the relative intensity of the characteristic element.

[0044] S4: Determine the judgment rules for the paint removal effect according to the intervals of the relative intensities of each characteristic element, as shown in Tables 3 and 4.

[0045] Table 3 Judgment Rules for Data Units

[0046]

[0047] Table 4 Judgment Rules for Data Sets

[0048]

[0049] S5: Take the relative intensities of each characteristic element as a data unit, form a data set with consecutive n data units, and form a data flow disk with consecutive n data sets.

[0050] Take the calculated relative intensity as a data unit, Figure 4 For any one of the spectra collected during the laser paint removal process of the above aluminum alloy skin sample, taking this spectrum as an example, the data units extracted from it are shown in Table 5.

[0051] Table 5 Data units

[0052]

[0053] Thus, data unit A1 is obtained: (0.36, 0.60, 0.02, 0.27, 0.25)

[0054] Each consecutive n spectral lines can extract n data units, and their collection is called a data set.

[0055] Taking the data collected during the laser paint removal process of the above aluminum alloy skin as an example: For 20 consecutive spectra collected within a certain period at the beginning of laser paint removal, the data units of each spectrum are extracted, as shown in Table 6. Taking n = 10 as an example, the data units of every consecutive 10 spectral lines constitute a data set, that is:

[0056] Data units 1 - 10 are the 1st data set;

[0057] Data units 2 - 11 are the 2nd data set;

[0058] Data units 3 - 12 are the 3rd data set;

[0059] ……

[0060] Data units 11 - 20 are the 11th data set.

[0061] Table 6 Data units generated by the test

[0062]

[0063]

[0064] S6: Analyze the data set in the form of a data flow disk, and judge each data set according to the judgment rules and give a conclusion on the real-time paint removal effect. As shown in Table 7.

[0065] Table 7 Judgment results

[0066]

[0067]

[0068] Except for data unit 4, the remaining data units are all determined to be topcoats, that is, the probability of the topcoat is 90%. Therefore, it is applicable to the determination rule P1. Thus, the determination result of the first data set is: topcoat. According to this determination rule, the second data set, the third data set... the nth data set can be judged in turn.

[0069] Note: Although the specific values listed in this method are proposed with the paint layer material based on aluminum alloy as the experimental object, this thinking method and criterion are universal, and other materials can be modified according to different requirements.

[0070] The above are only the preferred embodiments of the present invention and are not intended to limit the present invention. Any modifications, equivalent replacements, and improvements made within the spirit and principle of the present invention shall be included in the protection scope of the present invention.

Claims

1. A real-time evaluation method for the laser paint removal effect based on a LIBS data flow disk, characterized in that, Including: Classify the effect of the degree of paint layer removal; Measure the original LIBS spectra of each paint layer and the substrate on the surface to be de-painted; Determine the characteristic peaks of each paint layer and the substrate according to the original LIBS spectra; Select characteristic elements based on the characteristic peaks and record the intensities of the characteristic elements as standard intensities; Collect the LIBS spectra during the laser paint removal process in real time, extract the real-time intensities of each characteristic element in the LIBS spectra; divide the real-time intensities by the standard intensities to obtain the relative intensities of each characteristic element; According to the type of the effect of the degree of paint layer removal, divide the intervals of the relative intensities of each characteristic element, and determine the judgment rules for the paint removal effect; Take the relative intensities of each characteristic element as a data unit, form a data set with consecutive n data units, and form a data flow disk with consecutive n data sets; Judge each data set in the data flow disk according to the judgment rules and give a real-time evaluation conclusion of the paint removal effect; The determination of the characteristic elements and their standard intensities includes the following steps: Use a laser to remove the paint on the surface to be de-painted and collect the spectral data on the surfaces of each paint layer sample and the substrate sample as standard spectra; Compare several elements with the largest spectral intensity differences in the spectra of each sample, take them as characteristic elements, and extract the intensities of the characteristic elements of the corresponding samples from the above spectral data as standard intensities.

2. The real-time evaluation method for laser paint removal effect based on the LIBS data stream disk according to claim 1, characterized in that The types of the effect of the degree of paint layer removal include: the topcoat is not completely removed; the topcoat is completely removed and the primer is not damaged; the primer is not completely removed; the primer is completely removed and the substrate is not damaged; the substrate is damaged.

3. The real-time evaluation method for laser paint removal effect based on the LIBS data flow disk according to claim 1, wherein, The characteristic elements are selected based on the compositional differences between materials and specific elements are selected from the collected spectra to distinguish each paint layer and the substrate.

4. The real-time evaluation method for laser paint removal effect based on the LIBS data flow disk according to claim 1, characterized in that, The characteristic elements have obvious characteristic peaks in the spectrogram.

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