CN115060705A

CN115060705A - LIBS data flow table-based real-time evaluation method for laser paint removal effect

Info

Publication number: CN115060705A
Application number: CN202210568775.3A
Authority: CN
Inventors: 杨文锋; 林德惠; 李绍龙; 李果; 钱自然; 王迪升
Original assignee: Civil Aviation Flight University of China
Current assignee: Civil Aviation Flight University of China
Priority date: 2022-05-24
Filing date: 2022-05-24
Publication date: 2022-09-16

Abstract

The invention provides a real-time evaluation method for laser paint removal effect based on a LIBS data flow table, which comprises the following steps: classifying the effect of the removal degree of the paint layer; measuring the original LIBS spectrums of all paint layers and a matrix on the surface of the paint to be removed, determining characteristic peaks of all the paint layers and the matrix, selecting characteristic elements according to the characteristic peaks, and recording the intensities of the characteristic elements as standard intensities; collecting and calculating the relative intensity of each characteristic element in the real-time spectrum in real time; dividing intervals of the relative strength of each characteristic element, and determining a judgment rule of the paint removal effect; taking the relative strength of each characteristic element as a data unit, forming a data set by n continuous data units, and forming a data stream disk by n continuous data sets; and judging each data set according to the judgment rule and giving a conclusion of the real-time paint removal effect to the data flow disk. The method carries out trend judgment by using a real-time flowing data set, overcomes the instability and uncertainty of single spectrum data, and forms a more reliable effect evaluation rule.

Description

LIBS data flow table-based real-time evaluation method for laser paint removal effect

Technical Field

The invention relates to the technical field of spectrum and data processing, in particular to a real-time evaluation method for laser paint removal effect based on an LIBS data flow table.

Background

In recent years, with the exploration and development of laser paint removal technology, pulsed laser paint removal technology has gained general acceptance. The essence of the method is that the physical and chemical removal of the paint layer material is realized by utilizing the interaction of the laser pulse and the paint layer material, and compared with the traditional paint removal mode, the method has the advantages of high efficiency, environmental protection and controllable quality.

Laser-induced Breakdown Spectroscopy (LIBS) is a multi-element analysis technique developed in the late 20 th century. The technology uses high-energy laser pulses to ablate the surface of a sample and generate high-temperature plasma, the high-temperature plasma emits a linear spectrum representing atomic characteristics, and the wavelength position and the intensity of the spectral line respectively represent the type and the content of a measured element and are used as the fundamental basis for qualitative analysis and quantitative analysis. Therefore, substances and contents removed in the laser paint removing process can be reflected through real-time spectral data collected in the laser paint removing process, and the laser paint removing effect is evaluated.

Although there are many off-line based characterization methods that can be used as the basis and method for paint removal. However, most of these methods do not have real-time performance or have poor real-time performance, and real-time monitoring of paint removal effect is often required in industrial paint removal, so the LIBS technology with good real-time performance is more suitable for evaluating paint removal effect. However, it was experimentally found that the spectrum of a single spectral line based on LIBS technique has the following uncertainties and unreliability: due to micro-area nonuniformity, thickness nonuniformity, spectral data instability, plasma acquisition hysteresis, environmental and noise interference and the like, spectral data of one or a single position cannot be used as a basis for paint removal monitoring, so that the necessity of providing a novel real-time evaluation basis and method for paint removal effect is realized.

Disclosure of Invention

In order to solve the problems, the invention provides a laser paint removal effect real-time evaluation method based on an LIBS data flow table, which carries out trend judgment by using a real-time flow data set, overcomes the instability and uncertainty of single-strip spectral data, and forms a more reliable effect evaluation rule.

The invention provides the following technical scheme.

A laser paint removal effect real-time evaluation method based on an LIBS data flow table comprises the following steps:

classifying the effect of the removal degree of the paint layer;

measuring the original LIBS spectrum of each paint layer and matrix on the surface of the paint to be removed; determining characteristic peaks of each paint layer and matrix according to the original LIBS spectrum; selecting characteristic elements according to the characteristic peaks, and recording the intensities of the characteristic elements as standard intensities;

collecting an LIBS spectrum in the laser paint removal process in real time, and extracting the real-time intensity of each characteristic element in the LIBS spectrum; obtaining the relative intensity of each characteristic element by dividing the real-time intensity by the standard intensity;

dividing intervals of relative strength of each characteristic element according to the type of the paint layer removal degree effect, and determining a judgment rule of the paint removal effect;

taking the relative strength of each characteristic element as a data unit, forming a data set by n continuous data units, and forming a data stream disk by n continuous data sets;

and judging each data set in the data flow disc according to a judgment rule, and giving a real-time paint removal effect evaluation conclusion.

Preferably, the types of the effect of the degree of removal of the paint layer include: the finish paint is not completely removed; the finish paint 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; and (4) damaging the substrate.

Preferably, the determination of the characteristic elements and their standard intensities comprises the following steps:

removing paint on the surface to be subjected to paint removal by adopting a laser, and collecting spectral data of each paint layer sample and the surface of the matrix sample as a standard spectrum;

and comparing a plurality of elements with the maximum spectrum intensity difference in the spectrum of each sample, taking the elements as characteristic elements, and extracting the intensity of the characteristic elements of the corresponding sample from the spectrum data to be used as standard intensity.

Preferably, the characteristic elements are selected to distinguish the paint layers from the substrate according to the difference of the components among the materials and the collected spectrum.

Preferably, the characteristic element has a distinct characteristic peak in the spectrogram.

The invention has the beneficial effects that:

the method carries out trend judgment by using the real-time flowing data set, overcomes the instability and uncertainty of single spectrum data, and forms a more reliable effect evaluation rule.

Drawings

FIG. 1 is a flow chart of a laser paint removal effect real-time evaluation method based on a LIBS data flow table according to an embodiment of the invention;

FIG. 2 is a schematic diagram of an LIBS data acquisition and processing device in a laser delamination paint removal process according to an embodiment of the invention;

FIG. 3 is a standard spectra of a topcoat, primer, aluminum alloy sample of an example of the present invention (a) topcoat (b) primer (c) aluminum alloy;

FIG. 4 shows any one of the spectra collected during the laser paint removal process of the aluminum alloy skin sample according to the embodiment of the invention.

Detailed Description

In order to make the objects, technical solutions and advantages of the present invention more apparent, the present invention is described in further detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.

Example 1

The invention discloses a laser paint removal effect real-time evaluation method based on an LIBS data flow table. FIG. 2 is a schematic diagram of the LIBS data acquisition and processing device of the present invention, which mainly comprises a 1-laser device, a 2-lens, a 3-objective table, a 4-fiber probe, a 5-spectrometer and a 6-main control computer. Laser irradiated by laser equipment is focused on the surface of the paint layer through a lens, and plasma generated on the surface of the paint layer is collected by an optical fiber probe and then is transmitted to a spectrometer to continuously form a large amount of spectral data, and the spectral data is transmitted to a computer. The computer processes the spectral data according to the flow chart of fig. 1 and gives the evaluation result of the laser paint removal effect.

In this embodiment, an aluminum alloy skin sample with a surface sprayed with a primer and a finish is taken as an example. The method specifically comprises the following steps:

s1: determining the type of paint removal effect, comprising: the finish paint is not completely removed; the finish paint 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; and (4) damaging the substrate.

S2: and measuring the original LIBS spectra of each paint layer and the matrix on the surface of the paint to be removed, and determining the characteristic elements and the standard strength of each paint layer and the matrix.

The standard spectrogram of the finish paint, the primer and the aluminum alloy matrix is shown in fig. 3, and the characteristic peaks and the standard intensities of the paint layer and the matrix are determined according to the component information of the paint layer and the matrix and by combining the collected original spectrums of the paint layer and the matrix. The selected characteristic elements and their intensities are shown in table 1.

TABLE 1 selected characteristic elements and their intensity table

Characteristic element	Fe III	Mg III	Ca I	Al I	Zn II
						Wavelength/nm	396	498	616	393	490
Strength in finish/a.u.	641	592	0	0	0
						Mid-primer strength/a.u.	0	0	288	0	0
Strength/a.u in aluminum alloy matrix.	Micro-scale	Micro-scale	0	1050	400

Marking the determined characteristic elements as follows:

the finishing paint comprises the following characteristic elements: fe III and MgIII (denoted as a and b);

primer characteristic elements: ca I (noted as c);

aluminum alloy matrix characteristic elements: al I and Zn II (noted as d and e).

After the characteristic elements are determined, the standard strength of each characteristic element can be determined, and the standard strength of each paint layer and the matrix characteristic elements in the aluminum alloy skin can be obtained from table 1. The finishing is shown in Table 2.

TABLE 2 characteristic elements and their corresponding standard strengths

Characteristic element	a(Fe III)	b(Mg III)	c(Ca I)	d(Al I)	e(Zn II)
						Standard strength of	641	592	288	1050	400

S3: and collecting an LIBS spectrum in the laser paint removal process in real time, extracting the real-time intensity of each characteristic element in the spectrum, and dividing the real-time intensity by the standard intensity to obtain the relative intensity of each characteristic element.

The relative intensity is the real-time intensity/standard intensity, the intensity of the characteristic peak position of the selected characteristic element is extracted, and the relative intensity of the characteristic element can be calculated by dividing the intensity by the corresponding standard intensity in table 2.

S4: the judgment rule of the paint removal effect is determined according to the interval of the relative strength of each characteristic element, and is shown in tables 3 and 4.

TABLE 3 decision rules for data units

TABLE 4 decision rules for data sets

S5: and taking the relative strength of each characteristic element as a data unit, forming a data set by n continuous data units, and forming a data stream disk by n continuous data sets.

Taking the calculated relative intensity as a data unit, fig. 4 shows any one of the spectra collected during the laser paint removal process of the aluminum alloy skin sample, taking the spectrum as an example, and the extracted data unit is shown in table 5.

TABLE 5 data Unit

Resulting in data element a 1: (0.36, 0.60, 0.02, 0.27, 0.25)

N data units can be extracted from each successive n spectral lines, and the collection is called a data set.

Taking the data collected in the laser paint removal process of the aluminum alloy skin as an example: for 20 consecutive spectra collected over a period of time from the start of laser paint removal, a data unit for each spectrum was extracted, as shown in table 6. Taking n as an example 10, each consecutive data unit of 10 spectral lines constitutes a data set, that is:

the data units 1-10 are the 1 st data set;

the data units 2-11 are 2 nd data sets;

the data units 3-12 are the 3 rd data set;

……

the data units 11-20 are 11 th data sets.

TABLE 6 test of the resulting data units

S6: and analyzing the data sets in a data flow disk form, judging each data set according to a judgment rule and giving a conclusion of the real-time paint removal effect. As shown in table 7.

Table 7 judgment results

Except data cell 4, the remaining data cells are judged to be finish paint, i.e. the probability of finish paint is 90%, so that the method is applicable to the judgment rule P1, and the judgment result of the 1 st data set is as follows: and (5) finishing. The determination may be made for the nth data set of the 2 nd data set and the 3 rd data set … … in turn according to the determination rule.

Note: although the specific values listed in the method are provided by taking a paint layer material taking an aluminum alloy as a substrate as an experimental object, the thought method and the criterion have universality, and other materials can be modified according to different requirements.

The present invention is not limited to the above preferred embodiments, and any modifications, equivalent substitutions and improvements made within the spirit and principle of the present invention should be included in the protection scope of the present invention.

Claims

1. A real-time evaluation method for laser paint removal effect based on LIBS data flow table is characterized by comprising the following steps:

classifying the effect of the removal degree of the paint layer;

measuring the original LIBS spectrums of all paint layers and matrixes on the surface of the paint to be removed; determining characteristic peaks of each paint layer and each matrix according to the original LIBS spectrum; selecting characteristic elements according to the characteristic peaks, and recording the intensities of the characteristic elements as standard intensities;

collecting an LIBS spectrum in the laser paint removal process in real time, and extracting the real-time intensity of each characteristic element in the LIBS spectrum; dividing the real-time intensity by the standard intensity to obtain the relative intensity of each characteristic element;

2. The LIBS dataflow graph-based real-time evaluation method for laser paint removal effect according to claim 1, wherein the types of the paint layer removal degree effect include: the finish paint is not completely removed; the finish paint 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; and (4) damaging the substrate.

3. The LIBS data flow table-based real-time evaluation method for laser paint removal effect as claimed in claim 1, wherein the determination of the characteristic elements and their standard intensities comprises the following steps:

4. The method as claimed in claim 1, wherein the characteristic elements are selected according to the difference of the components between the materials, and the collected spectrum is combined to select specific elements to distinguish the paint layers from the substrate.

5. The LIBS data flow table-based real-time evaluation method for laser paint removal effect according to claim 1, wherein the characteristic elements have obvious characteristic peaks in a spectrogram.