Multimodal intense continuous laser ablation diagnostic method

Abstract

The present invention belongs to the technical field of laser-matter interaction, and in particular relates to a multimodal intense continuous laser ablation diagnostic method. The method comprises: S1: utilizing an ablation diagnostic experimental platform to obtain in real time the laser spectrum incident on the target material to be diagnosed; S2: obtaining the continuous spectrum, pump peak, and laser scattering peak; S3: calculating in real time the weights of the normalized continuous spectrum, normalized pump peak, and normalized laser scattering peak; S4: plotting a normalized continuous spectrum weight curve, a normalized pump peak weight curve, and a normalized laser scattering peak curve in a weight change curve graph based on the normalized continuous spectrum weight, normalized pump peak weight, and normalized laser scattering peak weight calculated in real time in step S3; and S5: selecting an ablation diagnostic criterion based on the changing trends of each curve in the weight change curve graph to obtain an ablation diagnostic result for the target material to be diagnosed. The present invention can solve the problem of remote diagnosis of laser ablation targets.

Description

Technical Field

[0001] The present invention belongs to the technical field of laser-matter interaction, and in particular relates to a multi-modal intense continuous laser ablation diagnostic method. Background Art

[0002] Multi-spectral temperature measurement technology uses the thermal radiation spectrum of the target. By constructing an emissivity model containing a small number of unknown parameters (2-4), and taking advantage of the linear independence between the unknown parameters and the temperature parameters, the theoretical formula is derived and fitted based on the blackbody radiation theory formula.

[0003] In their 2009 paper, "Study of Multispectral Temperature Measurement Technique for Laser Damage," Qin Yalou et al. from the University of Electronic Science and Technology of China proposed an improved over-spectral temperature measurement method to study the state changes and temperature distribution in laser-damaged areas. This method, which inverts the radiation spectrum of the damaged area, can reduce temperature measurement errors by at least 24%. However, this method simply partitions the radiation spectrum intensity contribution at different temperatures and discusses the impact of different partition weights on temperature measurement accuracy.

[0004] On November 12, 2019, Li Kewu of North University of China published a patent in China with the patent number CN201910723646.5. He used a high-speed CCD camera to complete the explosion flame combustion field distribution test, used an ultra-high-speed spectrometer to realize the explosion radiation spectrum test, and then completed the explosion temperature test. That is, combining imaging and spectroscopy analysis to provide a multi-dimensional explosion flame combustion speed and temperature measurement device and method.

[0005] On December 27, 2022, Wang Zhentao and others from Harbin Institute of Technology published a Chinese patent, CN202110706440.9, which describes a multispectral thermal imager for measuring laser-damaged temperature fields. This method uses a five-channel, four-wavelength filter photometer, with the fifth channel used as a calibration channel, enabling the infrared thermal imager to accurately capture data from multiple spectral channels. Multispectral thermometry can be used to invert the temperature field corresponding to the spectral data, achieving a measurement error of less than 1.5% compared to temperature measurements using thermocouples.

[0006] On March 29, 2022, Wang Zhentao and others from Tianhe (Wuxi) Instrument Co., Ltd. published a patent in China with patent number CN202111645398.0, in which they used a blackbody furnace and an attenuation plate to simulate a high-temperature transient real target, and used a multi-wavelength pyrometer image and an attenuation plate to measure the real temperature of the blackbody furnace. Finally, by judging whether the spectral emissivity curve is consistent with the spectral transmittance curve of the attenuation plate, compensation for the emissivity model was achieved.

[0007] Existing literature on multispectral temperature measurement technology focuses on improving the model accuracy of multispectral temperature measurement spectral emissivity, improving the multispectral measurement accuracy under specific working conditions, and combining multiple temperature measurement methods (such as contact thermocouple method and non-contact infrared thermal imager, colorimetry, multispectral temperature measurement method) to comprehensively evaluate and calibrate them to obtain reasonable temperature measurement results.

[0008] Multispectral temperature measurement is susceptible to numerous factors, including the spatial distribution of temperature, stimulated emission characteristics, fluorescence, phosphorescence, and nonlinear optical processes, making temperature measurement accuracy difficult to guarantee. The laser ablation process exhibits nonlinear characteristics, particularly near the ablation temperature. Phase transitions, oxidation, and plasma generation in the target material are inherently associated with numerous nonlinear effects. Consequently, the measured target ablation temperature often deviates significantly from the actual temperature. Furthermore, contact-based measurement methods struggle to measure targets above 1500°C, making them unsuitable for calibration of radiation temperature measurement. Consequently, laser ablation diagnosis and detection present significant challenges. Existing technologies rely on multispectral temperature measurement to improve, expand, and calibrate emissivity models, thereby enhancing the accuracy of multispectral temperature measurement. Currently, there is a lack of a versatile, effective, and fast real-time method that leverages multiple temperature and radiation characterization techniques, centered around multispectral temperature measurement, to remotely diagnose target ablation using multiple indicators (particularly temperature and emissivity). Summary of the Invention

[0009] In view of this, the present invention aims to provide a multimodal intense continuous laser ablation diagnostic method to solve the problem of lack of effective methods to diagnose target damage characteristics in the industrial field of laser etching and laser damage targets.

[0010] To achieve the above object, the technical solution created by the present invention is implemented as follows:

[0011] A multi-modal intense continuous laser ablation diagnostic method specifically comprises the following steps:

[0012] S1: Build an ablation diagnosis experimental platform and use it to obtain the laser spectrum incident on the target material to be diagnosed in real time;

[0013] S2: Perform real-time spectral decoupling calculation on the laser spectrum to obtain the continuous spectrum, pump peak and laser scattering peak;

[0014] S3: Perform real-time normalization on the continuous spectrum, pump peak, and laser scattering peak, and calculate the weights of the normalized continuous spectrum, normalized pump peak, and normalized laser scattering peak in real time;

[0015] S4: based on the normalized continuous spectrum weight, normalized pump peak weight, and normalized laser scattering peak weight obtained by real-time calculation in step S3, drawing a normalized continuous spectrum weight curve, a normalized pump peak weight curve, and a normalized laser scattering peak curve in a weight change curve graph;

[0016] S5: selecting an ablation diagnosis criterion according to the temperature change trend and the change trend of each curve in the weight change curve diagram, and obtaining an ablation diagnosis result of the target material to be diagnosed.

[0017] Furthermore, the ablation diagnosis experimental platform includes a computer, a spectrometer, a shortwave visible band camera, a laser, an infrared thermal imager, a target material to be diagnosed, and an energy meter. The output end of the computer is connected to the input end of the spectrometer, the input end of the shortwave visible band camera, the input end of the laser, and the input end of the infrared thermal imager, respectively. The output end of the spectrometer, the output end of the shortwave visible band camera, and the output end of the infrared thermal imager are all aimed at the target material to be diagnosed. The output end of the target material to be diagnosed is connected to the input end of the energy meter, and the output end of the energy meter is connected to the input end of the computer.

[0018] A small hole is provided at the center of the target material to be diagnosed, and the laser emitted by the laser passes through the small hole in the target material to be diagnosed and is incident on the energy meter; the energy meter collects the laser energy passing through the small hole in the target material to be diagnosed in real time; the computer displays the data collected by the energy meter in real time; the spectrometer collects the laser spectrum incident on the target material to be diagnosed in real time; the shortwave visible band camera monitors the ablation state of the target material to be diagnosed in real time and obtains a visible light image in real time; the infrared thermal imager monitors the ablation state of the target material to be diagnosed in real time and obtains an infrared thermal image and the current temperature of the target material to be diagnosed in real time.

[0019] Furthermore, the number of lasers is not less than one, wherein,

[0020] The specific process of using a laser to ablate the target material to be diagnosed is as follows:

[0021] Align the output end of the laser toward the target material to be diagnosed, and allow the laser light emitted by the laser to pass through the small hole in the target material to be diagnosed;

[0022] The specific process of using two or more lasers to ablate the target material to be diagnosed is as follows:

[0023] Two or more lasers are combined to transmit the combined laser beams through the small holes in the target material to be diagnosed.

[0024] Furthermore, a first short-wave pass filter is provided between the spectrometer and the target material to be diagnosed, along the optical axis direction of the spectrometer;

[0025] Between the shortwave-pass visible band camera and the target material to be diagnosed, a second shortwave-pass filter, a third shortwave-pass filter and a fourth shortwave-pass filter are sequentially provided along the optical axis direction of the shortwave-pass visible band camera;

[0026] The first short-wave pass filter includes a 1000nm short-wave pass filter, the second short-wave pass filter includes a 700nm short-wave pass filter, the third short-wave pass filter includes a 515nm short-wave pass filter, and the fourth short-wave pass filter includes an 800nm ​​short-wave pass filter.

[0027] Furthermore, in step S3, calculating the weights of the normalized continuous spectrum, the normalized pump peak, and the normalized laser scattering peak specifically includes the following steps:

[0028] S31: fitting the normalized pump peak and the normalized laser scattering peak in sequence based on the Lorentz line shape or the Foucault line shape to obtain the line width parameters of the normalized pump peak and the normalized laser scattering peak;

[0029] S32: obtaining a peak position of the normalized pump peak and a peak position of the normalized laser scattering peak based on the line width parameter of the normalized pump peak and the line width parameter of the normalized laser scattering peak;

[0030] S33: according to the peak position of the normalized pump peak and the peak position of the normalized laser scattering peak, the data of the pump peak and the data of the laser scattering peak are mined, and the data values ​​corresponding to the positions of the mined data are reassigned by interpolation to obtain continuous spectrum data;

[0031] S34: splicing the continuous spectrum data, the normalized pump peak, and the normalized laser scattering peak to obtain a matrix M;

[0032] S35: Calculate the weights of the normalized continuous spectrum, normalized pump peak, and normalized laser scattering peak using the following formula:

[0033] ;

[0034] Wherein, w is the weight of the normalized continuous spectrum, normalized pump peak or normalized laser scattering peak, pinv is the pseudo-inverse matrix calculated for the matrix M, and S is the actual spectral data incident on the target material to be diagnosed after irradiance calibration.

[0035] Furthermore, in step S33, the specific process of removing the pump peak data and the laser scattering peak data is as follows:

[0036] The pump peak is subtracted from the actual spectrum data incident on the target material to be diagnosed after irradiance calibration, and the data of the pump peak is removed;

[0037] The laser scattering peak is subtracted from the actual spectrum data incident on the target material to be diagnosed after irradiance calibration, and the data of the laser scattering peak is removed.

[0038] Furthermore, in step S4, a weight variation curve is plotted with the laser irradiation time of the target material to be diagnosed as the horizontal coordinate, and the normalized continuous spectrum weight, the normalized pump peak weight and the normalized laser scattering peak weight as the vertical coordinates.

[0039] Furthermore, step S5 specifically includes the following steps:

[0040] S51: Calculate the respective total average weight values ​​of the normalized pump peak and the normalized laser scattering peak during the laser irradiation time; if the difference between the average weight value of the normalized pump peak within 1 second before the current moment and the total average weight value of the normalized pump peak is greater than 15% of the total average weight value of the normalized pump peak, and the difference between the average weight value of the normalized laser scattering peak and the total average weight value of the normalized laser scattering peak is greater than 15% of the total average weight value of the normalized laser scattering peak, diagnose the target material to be diagnosed based on the ablation criterion of the characteristic spectral line intensity trend to obtain an ablation diagnosis result of the target material to be diagnosed; otherwise, execute step S52;

[0041] S52: diagnose the target material to be diagnosed based on the ablation criterion of the spatial weighted emissivity and the spectrum correlation, and obtain an ablation diagnosis result of the target material to be diagnosed.

[0042] Furthermore, in step S51, if the laser irradiation time is 1.2s, the target material to be diagnosed is diagnosed based on the shortwave-visible band camera imaging ablation criterion or the temperature measurement ablation criterion to obtain the ablation diagnosis result of the target material to be diagnosed.

[0043] Furthermore, the specific process of diagnosing the target material to be diagnosed based on the ablation criterion of the characteristic spectral line intensity trend in step S51 is as follows:

[0044] In the weight change curve diagram, the amplitudes of the normalized pump peak weight curve and the normalized laser scattering peak weight curve during the laser irradiation time are calculated respectively;

[0045] Calculate the unit amplitude of the normalized pump peak weight curve and the normalized laser scattering peak weight curve every 2 seconds during the laser irradiation time;

[0046] When the unit amplitudes of the normalized pump peak weight curve and the normalized laser scattering peak weight curve are respectively lower than 20% of the amplitudes of the normalized pump peak weight curve and the normalized laser scattering peak weight curve, the current laser irradiation moment is regarded as the plateau period;

[0047] When both the normalized pump peak weight curve and the normalized laser scattering peak weight curve leave the plateau period, the laser irradiation moment of the target material to be diagnosed is regarded as the ablation starting moment of the target material to be diagnosed.

[0048] Furthermore, the specific process of diagnosing the target material to be diagnosed based on the ablation criterion of spatial weighted emissivity and spectral correlation in step S52 is as follows:

[0049] Using multi-spectral temperature measurement technology to collect the surface temperature of the target material to be diagnosed in real time;

[0050] The spatial weighted emissivity of the target material to be diagnosed is calculated by the following formula:

[0051] ;

[0052] ;

[0053] in, is the function for calculating the spatially weighted emissivity, is the spatially weighted emissivity, is the wavelength, T is the temperature measured by multi-spectral temperature measurement technology, norm is the norm, is the actual spectral data incident on the target material to be diagnosed after irradiance calibration. is the ideal blackbody spectral radiation distribution, is the ideal blackbody spectral emissivity, =1.0, c1 is the first radiation constant, c 1=2π hc 2 =3.74×10 -16 W∙m 2 , h is Planck's constant, h =6.63×10 -34 J∙s, c is the speed of light, c=3×10 8 m / s, c2 is the second radiation constant, c2=hc / k B =1.43×10 -2 m∙K,k B is the Boltzmann constant, k B =1.38×10 -23 J / K;

[0054] Calculated by the following formula and Correlation coefficient :

[0055] ;

[0056] in, is the spatial weighted emissivity of the ith wavelength, is the average value of the spatially weighted emissivity of wavelength i, is the actual spectral data of the i-th wavelength incident on the target material to be diagnosed after irradiance calibration, is the average value of the actual spectral data of i wavelengths incident on the target material to be diagnosed after irradiance calibration, and n is the total number of spatially weighted emissivities;

[0057] In the temperature measurement confidence interval of the target material to be diagnosed, the laser irradiation moment of the target material to be diagnosed corresponding to the correlation coefficient greater than 0.99 is taken as the ablation starting moment of the target material to be diagnosed.

[0058] Further,

[0059] The maximum value of the temperature measurement confidence interval 2500℃;

[0060] The minimum value of the temperature measurement confidence interval is calculated by the following formula: :

[0061] ;

[0062] in, Take the maximum wavelength of the spectrometer, m is meter, K is Kelvin.

[0063] Furthermore, in step S51, the specific process of diagnosing the target material to be diagnosed based on the shortwave-visible band camera imaging ablation criterion is as follows:

[0064] Use a short-wave visible band camera to capture images of the target material to be diagnosed, and calculate the total grayscale value of the area near the spot;

[0065] The change curve of the total gray value is drawn with the laser irradiation time of the target material to be diagnosed as the horizontal axis and the total gray value of the area near the light spot as the vertical axis;

[0066] When the ablation spot of the target material to be diagnosed deviates from a perfect circle and the increase rate of the total gray value in the first 2 seconds before the current moment is greater than 15% of the average increase rate during the laser irradiation time, the current laser irradiation moment is regarded as the ablation start moment of the target material to be diagnosed;

[0067] The specific process of diagnosing the target material using the temperature measurement ablation criterion is as follows:

[0068] At the same time, the surface temperature of the target material to be diagnosed is collected using an infrared thermal imager, multi-spectral temperature measurement technology and weighted radiation spectrum inversion method;

[0069] In the temperature trend graph, the laser irradiation time is used as the horizontal axis, and the real-time temperature collected by the infrared thermal imager, multispectral temperature measurement technology, and weighted radiation spectrum inversion method is used as the vertical axis. The temperature change curves corresponding to the infrared thermal imager, multispectral temperature measurement technology, and weighted radiation spectrum inversion method are drawn respectively;

[0070] In the temperature trend graph, the two temperature change curves with the smallest cumulative sum of temperature differences at the same time during the laser irradiation time are selected, and the temperature values ​​of the two temperature change curves with the smallest cumulative sum of temperature differences at the same time are averaged to obtain the curve of the average temperature value changing with the laser irradiation time;

[0071] When the average surface temperature of the target material to be diagnosed is greater than 2000°C, and the difference between the average temperature rise rate of the target material to be diagnosed in the first 1s before the current moment and the total average temperature rise rate of the target material to be diagnosed during the laser irradiation time is greater than 15% of the total average temperature rise rate of the target material to be diagnosed during the laser irradiation time, the current laser irradiation moment is taken as the starting moment of ablation of the target material to be diagnosed.

[0072] Furthermore, the area of ​​the region near the light spot is the same as the area of ​​the target material to be diagnosed.

[0073] Furthermore, the specific process of the weighted radiation spectrum inversion method for real-time acquisition of the surface temperature of the target material to be diagnosed is as follows: setting the objective function The expression is:

[0074] ;

[0075] ;

[0076] in, is the ratio of the ith spectrum intensity to the ideal blackbody radiation curve, is the mean value of the ratio of the i-th spectral intensity to the ideal blackbody radiation curve, is the actual spectrum data incident on the target material to be diagnosed at the i-th wavelength after irradiance calibration, is the ideal blackbody spectral radiation distribution of the i-th wavelength;

[0077] The conjugate gradient method is used to optimize the objective function and obtain the surface temperature of the target material to be diagnosed.

[0078] Compared with the prior art, the present invention can achieve the following beneficial effects:

[0079] The present invention creates the multimodal intense continuous laser ablation diagnostic method described above, which is used to solve the problem of remote diagnosis of laser ablation targets. By combining a variety of remote detection technologies and data processing technologies, comprehensive analysis of multimodal indicators such as spatial weighted emissivity, characteristic spectral peaks, infrared thermal imaging, multi-dimensional temperature measurement, and visible band target imaging is carried out to achieve remote diagnosis of laser ablation. After investigation, no data that can be horizontally compared with the effect achieved by the present invention has been found in China. The present invention has the potential to provide a feasible basic technical solution and ideas for remote diagnosis of laser ablation in the industrial field, and at the same time provide theoretical guidance for understanding the ablation mechanism of common metals and alloys. BRIEF DESCRIPTION OF THE DRAWINGS

[0080] The accompanying drawings, which constitute part of the present invention, are intended to provide a further understanding of the present invention. The exemplary embodiments of the present invention and their descriptions are intended to explain the present invention and do not constitute an undue limitation of the present invention. In the accompanying drawings:

[0081] Figure 1 This is a schematic diagram of the structure of the ablation diagnostic experimental platform according to an embodiment of the present invention;

[0082] Figure 2 A schematic flow chart of a multi-modal intense continuous laser ablation diagnostic method according to an embodiment of the present invention;

[0083] Figure 3 A schematic diagram of the ablation spectrum component curve of stainless steel according to an embodiment of the present invention;

[0084] Figure 4 A schematic diagram of the ablation spectrum composition curve of the aluminum alloy according to an embodiment of the present invention;

[0085] FIG5 (a) is a schematic diagram of normalized weight curves of discrete spectrum and continuous spectrum components of a stainless steel target according to an embodiment of the present invention;

[0086] FIG5( b ) is a schematic diagram of a weight curve of discrete spectrum and continuous spectrum components of an aluminum alloy target according to an embodiment of the present invention;

[0087] Figure 6 A schematic diagram of a curve showing how the spatially weighted emissivity and spectral correlation coefficient of the stainless steel target material described in an embodiment of the present invention change with ablation time;

[0088] Figure 7 Schematic diagram of an image of the ablation area near the laser irradiation spot of the aluminum alloy target material and a corresponding grayscale value sum curve according to an embodiment of the present invention;

[0089] Figure 8A comparison chart of temperature measurement results of a stainless steel target using infrared thermal imaging, multispectral temperature measurement, and weighted radiation spectrum inversion as described in an embodiment of the present invention;

[0090] Figure 9 A comparison chart of the temperature measurement results of an aluminum alloy target using infrared thermal imaging, multispectral temperature measurement, and weighted radiation spectrum inversion as described in an embodiment of the present invention;

[0091] FIG10( a ) is a pinhole leakage power measurement curve obtained by ablating a stainless steel target for 3 s, 6 s, 9 s, and 12 s, respectively, according to an embodiment of the present invention;

[0092] FIG10( b ) is a pinhole leakage power measurement curve obtained by ablating an aluminum alloy target for 90 s, 120 s, 130 s, and 140 s, respectively, according to an embodiment of the present invention;

[0093] Figure 11 These are the ablation morphologies obtained by ablating a stainless steel target for 3s, 6s, 9s, and 12s, respectively, as described in the embodiments of the present invention;

[0094] Figure 12 These are the ablation morphologies obtained by ablating the aluminum alloy target for 90s, 120s, 130s, and 140s, respectively, as described in the embodiments of the present invention.

[0095] Description of reference numerals:

[0096] 1. Computer; 2. Spectrometer; 3. Shortwave-pass visible-band camera; 4. Laser; 5. Infrared thermal imager; 6. Energy meter; 7. Target material to be diagnosed; 8. First shortwave-pass filter; 9. Second shortwave-pass filter; 10. Third shortwave-pass filter; 11. Fourth shortwave-pass filter. DETAILED DESCRIPTION

[0097] In order to make the purpose, technical solutions and advantages of the present invention more clearly understood, the present invention is further described in detail below with reference to the accompanying drawings and specific embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and do not constitute a limitation of the present invention.

[0098] It should be noted that, in the absence of conflict, the embodiments of the present invention and the features in the embodiments can be combined with each other.

[0099] In the description of the present invention, it should be understood that the terms "center", "longitudinal", "lateral", "up", "down", "front", "back", "left", "right", "vertical", "horizontal", "top", "bottom", "inside", "outside" and the like indicate orientations or positional relationships based on the orientations or positional relationships shown in the accompanying drawings, and are only for the convenience of describing the present invention and simplifying the description, rather than indicating or implying that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and therefore cannot be understood as a limitation on the present invention. In addition, the terms "first", "second" and the like are only used for descriptive purposes and cannot be understood as indicating or implying relative importance or implicitly indicating the number of the indicated technical features. Thus, features defined as "first", "second" and the like may explicitly or implicitly include one or more of the features. In the description of the present invention, unless otherwise specified, "multiple" means two or more.

[0100] In the description of the present invention, it should be noted that, unless otherwise expressly specified or limited, the terms "installed," "connected," and "connected" should be understood in a broad sense. For example, they can refer to fixed connections, detachable connections, or integral connections; they can refer to mechanical connections or electrical connections; they can refer to direct connections or indirect connections through an intermediate medium; and they can refer to internal connections between two components. Those skilled in the art can understand the specific meanings of the above terms in the present invention based on specific circumstances.

[0101] The present invention will be described in detail below with reference to the accompanying drawings and in combination with embodiments.

[0102] Existing technologies all improve, expand, and calibrate the emissivity model based on multispectral temperature measurement technology, thereby enhancing the temperature measurement accuracy of multispectral temperature measurement technology. The present invention obtains temperature measurement results and the emissivity spectrum distribution affected by spatial distribution, namely the spatially weighted emissivity, through spectral decoupling and the use of a universal polynomial model. Utilizing the correlation coefficient between the spatially weighted emissivity and the spectrum itself, as well as the trend change in the characteristic spectral peak intensity, combined with various means such as temperature remote sensing and image monitoring, the surface temperature distribution characteristics of the target material 7 to be diagnosed are remotely analyzed and its ablation condition is diagnosed. In addition, in terms of temperature measurement, the present invention proposes a weighted radiation spectrum inversion ablation criterion by analyzing the spectrum. Combined with the infrared thermal imaging temperature measurement results and the measurement results of the central hole leakage power, the accuracy of temperature ablation diagnosis is ensured. Different from the existing technology, the present invention no longer focuses on improving temperature measurement accuracy, but instead focuses on combining multiple indicators to determine the occurrence of laser ablation, thereby solving the problem of the lack of effective methods to diagnose target damage characteristics in laser etching and laser damage targets in the industrial field. The present invention does not require detailed research and correction of the spectral emissivity model of the target material 7 to be diagnosed, and is applicable to complex real-world situations where there is no prior knowledge of the target. The present invention can effectively diagnose whether the target is damaged by laser.

[0103] The multi-modal intense continuous laser ablation diagnosis method proposed in this invention is implemented based on the ablation diagnosis experimental platform. Figure 1 As shown, the ablation diagnosis experimental platform includes a computer 1, a spectrometer 2, a shortwave visible band camera 3, a laser 4, an infrared thermal imager 5, a target material to be diagnosed 7 and an energy meter 6. The output end of the computer 1 is connected to the input end of the spectrometer 2, the input end of the shortwave visible band camera 3, the input end of the laser 4 and the input end of the infrared thermal imager 5 respectively. The output end of the spectrometer 2, the output end of the shortwave visible band camera 3 and the output end of the infrared thermal imager 5 are all aimed at the target material to be diagnosed 7. The output end of the target material to be diagnosed 7 is connected to the input end of the energy meter 6, and the output end of the energy meter 6 is connected to the input end of the computer 1.

[0104] The number of lasers 4 is not less than one, wherein:

[0105] The specific process of using a laser 4 to ablate the target material 7 to be diagnosed is as follows:

[0106] The output end of the laser 4 is aligned toward the target material 7 to be diagnosed, and the laser light emitted by the laser 4 is passed through the small hole of the target material 7 to be diagnosed; the wavelength of the laser 4 is typically 650nm, 720nm, 800nm, 880nm and 970nm.

[0107] The specific process of using two or more lasers 4 to ablate the target material 7 to be diagnosed is as follows:

[0108] Two or more lasers 4 are combined to perform a laser beam combining operation, and the combined laser beams are passed through the small holes of the target material 7 to be diagnosed.

[0109] If the two lasers 4 are combined into a laser beam, a dichroic mirror is used to combine the two perpendicular light beams into one beam.

[0110] A small hole with a diameter of 1 mm is opened in the center of the target material 7 to be diagnosed, so that a part of the laser light in the center of the spot is leaked out. When the coupling efficiency between the laser power and the target material 7 to be diagnosed changes (caused by effects such as the shape and position of the small hole, plasma shielding, recoil metal vapor or oxide absorption), the effectiveness of the ablation diagnosis is evaluated. The power passing through the small hole is monitored by the energy meter 6. When the reading of the energy meter 6 changes, the possible reason is that the small hole has been ablated, resulting in deformation of the small hole or plasma shielding effect, which affects the power passing through the small hole.

[0111] Between the spectrometer 2 and the target material 7 to be diagnosed, a first short-wave pass filter 8 is provided along the optical axis direction of the spectrometer 2 . The first short-wave pass filter 8 includes a 1000 nm short-wave pass filter.

[0112] To ensure good imaging quality when monitoring the ablation status of the target material 7 to be diagnosed using the shortwave-pass visible band camera 3, a cage cube is used in front of the lens of the shortwave-pass visible band camera 3. Two additional shortwave-pass filters with central wavelengths of 700 nm and 800 nm are added to the 515 nm shortwave-pass filter. This ensures that the attenuation factor of laser light in the wavelength range above 800 nm is greater than OD (optical density) 10, and the attenuation factor of laser light between 515 nm and 800 nm is greater than OD 4. Specifically, a second shortwave-pass filter 9, a third shortwave-pass filter 10, and a fourth shortwave-pass filter 11 are sequentially positioned between the shortwave-pass visible band camera 3 and the target material 7 along the optical axis of the shortwave-pass visible band camera 3. The second shortwave-pass filter 9 comprises a 700 nm shortwave-pass filter, the third shortwave-pass filter 10 comprises a 515 nm shortwave-pass filter, and the fourth shortwave-pass filter 11 comprises an 800 nm shortwave-pass filter.

[0113] The model of the laser 4 is SMATLas 4S-3000W, and the wavelength of the emitted continuous laser is 1070 nm.

[0114] Before starting the experiment, it is necessary to calibrate the blackbody radiation and wavelength of the spectrometer 2. Turn on all the instruments in the ablation diagnosis experimental platform. The laser emitted by the laser 4 passes through the small hole of the target material 7 to be diagnosed and is incident on the energy meter 6. The target spot diameter generated by the laser irradiating the target material 7 to be diagnosed is obtained by the knife-edge method test. The energy meter 6 collects the laser energy passing through the small hole of the target material 7 to be diagnosed in real time; the computer 1 displays the data collected by the energy meter 6 in real time; the spectrometer 2 collects the laser spectrum incident on the target material 7 to be diagnosed in real time; the shortwave visible band camera 3 monitors the ablation state of the target material 7 to be diagnosed in real time and obtains visible light images in real time; the infrared thermal imager 5 monitors the ablation state of the target material 7 to be diagnosed in real time and obtains infrared thermal images and the current temperature of the target material 7 to be diagnosed in real time.

[0115] The present invention uses multiple criteria such as spatial weighted emissivity, characteristic spectral peaks, infrared thermal imaging, and visible band target imaging for comprehensive analysis and judgment, and assigns specific weights to different criteria according to different sample characteristics, thereby realizing multimodal strong continuous laser ablation diagnosis.

[0116] like Figure 2 As shown, the multi-modal intense continuous laser ablation diagnostic method provided by the present invention specifically includes the following steps:

[0117] S1: Building an ablation diagnosis experimental platform, and using the ablation diagnosis experimental platform to obtain in real time the laser spectrum incident on the target material 7 to be diagnosed;

[0118] S2: Perform real-time spectral decoupling calculation on the laser spectrum to obtain the continuous spectrum, pump peak and laser scattering peak;

[0119] S3: Perform real-time normalization on the continuous spectrum, pump peak, and laser scattering peak, and calculate the weights of the normalized continuous spectrum, normalized pump peak, and normalized laser scattering peak in real time;

[0120] In step S3, calculating the weights of the normalized continuous spectrum, the normalized pump peak, and the normalized laser scattering peak specifically includes the following steps:

[0121] S31: fitting the normalized pump peak and the normalized laser scattering peak in sequence based on the Lorentz line shape or the Foucault line shape to obtain the line width parameters of the normalized pump peak and the normalized laser scattering peak;

[0122] S32: obtaining a peak position of the normalized pump peak and a peak position of the normalized laser scattering peak based on the line width parameter of the normalized pump peak and the line width parameter of the normalized laser scattering peak;

[0123] S33: according to the peak position of the normalized pump peak and the peak position of the normalized laser scattering peak, the data of the pump peak and the data of the laser scattering peak are mined, and the data values ​​corresponding to the positions of the mined data are reassigned by interpolation to obtain continuous spectrum data;

[0124] In step S33, the specific process of removing the pump peak data and the laser scattering peak data is as follows:

[0125] The pump peak is subtracted from the actual spectrum data incident on the target material to be diagnosed 7 after irradiance calibration, thereby eliminating the pump peak data;

[0126] The laser scattering peak is subtracted from the actual spectrum data incident on the target material to be diagnosed 7 after irradiance calibration, and the data of the laser scattering peak is removed.

[0127] S34: splicing the continuous spectrum data, the normalized pump peak, and the normalized laser scattering peak to obtain a matrix M;

[0128] S35: Calculate the weights of the normalized continuous spectrum, normalized pump peak, and normalized laser scattering peak using the following formula:

[0129] ;

[0130] Wherein, w is the weight of the normalized continuous spectrum, normalized pump peak or normalized laser scattering peak, pinv is the pseudo-inverse matrix calculated for the matrix M, and S is the actual spectral data incident on the target material 7 to be diagnosed after irradiance calibration.

[0131] S4: based on the normalized continuous spectrum weight, normalized pump peak weight, and normalized laser scattering peak weight obtained by real-time calculation in step S3, drawing a normalized continuous spectrum weight curve, a normalized pump peak weight curve, and a normalized laser scattering peak curve in a weight change curve graph;

[0132] In step S4 , a weight variation curve is plotted with the laser irradiation time on the target material 7 to be diagnosed as the horizontal axis, and the normalized continuous spectrum weight, the normalized pump peak weight and the normalized laser scattering peak weight as the vertical axes.

[0133] S5: selecting an ablation diagnosis criterion according to the change trend of each curve in the weight change curve diagram and the temperature change trend, and obtaining an ablation diagnosis result of the target material 7 to be diagnosed.

[0134] S51: Calculate the respective total average weight values ​​of the normalized pump peak and the normalized laser scattering peak during the laser irradiation time; if the difference between the average weight value of the normalized pump peak within 1 second before the current moment and the total average weight value of the normalized pump peak is greater than 15% of the total average weight value of the normalized pump peak, and the difference between the average weight value of the normalized laser scattering peak and the total average weight value of the normalized laser scattering peak is greater than 15% of the total average weight value of the normalized laser scattering peak, diagnose the target material 7 to be diagnosed based on the ablation criterion of the characteristic spectral line intensity trend to obtain an ablation diagnosis result of the target material 7 to be diagnosed; otherwise, execute step S52;

[0135] The specific process of diagnosing the target material 7 based on the ablation criterion of the characteristic spectral line intensity trend in step S51 is as follows:

[0136] In the weight change curve diagram, the amplitudes of the normalized pump peak weight curve and the normalized laser scattering peak weight curve during the laser irradiation time are calculated respectively;

[0137] Calculate the unit amplitude of the normalized pump peak weight curve and the normalized laser scattering peak weight curve every 2 seconds during the laser irradiation time;

[0138] When the unit amplitudes of the normalized pump peak weight curve and the normalized laser scattering peak weight curve are lower than 20% of the amplitudes of the normalized pump peak weight curve and the normalized laser scattering peak weight curve, the current laser irradiation moment is regarded as the plateau period.

[0139] When both the normalized pump peak weight curve and the normalized laser scattering peak weight curve leave the plateau period, the laser irradiation moment of the target material 7 to be diagnosed is regarded as the ablation start moment of the target material 7 to be diagnosed.

[0140] In step S51 , if the laser irradiation time (total laser irradiation time) is 1.2 s, the target material 7 to be diagnosed is diagnosed based on the shortwave-visible band camera imaging ablation criterion or the temperature measurement ablation criterion to obtain the ablation diagnosis result of the target material 7 to be diagnosed.

[0141] In step S51, the specific process of diagnosing the target material 7 based on the shortwave-visible band camera imaging ablation criterion is as follows:

[0142] The shortwave visible band camera 3 is used to capture an image of the target material 7 to be diagnosed, and the sum of the grayscale values ​​of the area near the light spot is calculated;

[0143] The change curve of the total gray value is plotted with the laser irradiation time of the target material 7 to be diagnosed as the horizontal axis and the total gray value of the area near the light spot as the vertical axis;

[0144] The area near the light spot and the target material 7 to be diagnosed are the same.

[0145] When the ablation spot of the target material 7 to be diagnosed deviates from a perfect circle, and the increase rate of the total gray value in the first 2 seconds before the current moment is greater than 15% of the average increase rate during the laser irradiation time, the current laser irradiation moment is taken as the ablation start moment of the target material 7 to be diagnosed;

[0146] The specific process of diagnosing the target material 7 using the temperature measurement ablation criterion is as follows:

[0147] At the same time, the temperature of the surface of the target material 7 to be diagnosed is collected using an infrared thermal imager 5, a multi-spectral temperature measurement technology and a weighted radiation spectrum inversion method;

[0148] In the temperature trend graph, the laser irradiation time is used as the horizontal axis, and the real-time temperature collected by the infrared thermal imager 5, the multi-spectral temperature measurement technology, and the weighted radiation spectrum inversion method are used as the vertical axis. The temperature change curves corresponding to the infrared thermal imager 5, the multi-spectral temperature measurement technology, and the weighted radiation spectrum inversion method are drawn respectively;

[0149] The specific process of real-time acquisition of the surface temperature of the target material 7 to be diagnosed by the weighted radiation spectrum inversion method is as follows:

[0150] Setting the objective function The expression is:

[0151] ;

[0152] ;

[0153] in, is the ratio of the ith spectrum intensity to the ideal blackbody radiation curve, is the mean value of the ratio of the i-th spectral intensity to the ideal blackbody radiation curve, is the actual spectrum data incident on the target material 7 to be diagnosed with respect to the i-th wavelength after irradiance calibration, is the ideal blackbody spectral radiation distribution of the i-th wavelength.

[0154] The objective function is optimized using the conjugate gradient method to obtain the surface temperature of the target material 7 to be diagnosed.

[0155] In the temperature trend graph, the two temperature change curves with the smallest cumulative sum of temperature differences at the same time during the laser irradiation time are selected, and the temperature values ​​of the two temperature change curves with the smallest cumulative sum of temperature differences at the same time are averaged to obtain the curve of the average temperature value changing with the laser irradiation time;

[0156] When the average temperature value of the surface of the target material to be diagnosed 7 is greater than 2000°C, and the difference between the average temperature rise rate of the target material to be diagnosed 7 in the first 1s of the current moment and the total average temperature rise rate of the target material to be diagnosed 7 during the laser irradiation time is greater than 15% of the total average temperature rise rate of the target material to be diagnosed 7 during the laser irradiation time, the current laser irradiation moment is taken as the starting moment of ablation of the target material to be diagnosed 7.

[0157] S52: Diagnose the target material 7 to be diagnosed based on the ablation criterion of spatial weighted emissivity and spectrum correlation to obtain an ablation diagnosis result of the target material 7 to be diagnosed.

[0158] The temperature of the surface of the target material 7 to be diagnosed is collected in real time using multi-spectral temperature measurement technology;

[0159] The multi-spectral temperature measurement technology is the same as the multi-spectral temperature measurement technology used in the paper "Research on Multi-spectral Temperature Measurement Technology in Laser Damage".

[0160] The spatial weighted emissivity of the target material 7 to be diagnosed is calculated by the following formula:

[0161] ;

[0162] ;

[0163] in, is the function for calculating the spatially weighted emissivity, is the spatially weighted emissivity, is the wavelength, T is the temperature measured by multi-spectral temperature measurement technology, norm is the norm, is the actual spectrum data incident on the target material 7 to be diagnosed after irradiance calibration, is the ideal blackbody spectral radiation distribution, is the ideal blackbody spectral emissivity, =1.0, c1 is the first radiation constant, c 1=2π hc 2 =3.74×10 -16 W∙m 2 , h is Planck's constant, h =6.63×10 -34 J∙s, c is the speed of light, c=3×10 8 m / s, c2 is the second radiation constant, c2=hc / k B =1.43×10 -2 m∙K,k B is the Boltzmann constant, k B =1.38×10 -23 J / K;

[0164] Calculated by the following formula and Correlation coefficient :

[0165] ;

[0166] in, is the spatial weighted emissivity of the ith wavelength, is the average value of the spatially weighted emissivity of wavelength i, is the actual spectrum data of the i-th wavelength incident on the target material 7 to be diagnosed after irradiance calibration, is the average value of the actual spectrum data of i wavelengths incident on the target material to be diagnosed 7 after irradiance calibration, and n is the total number of spatially weighted emissivities;

[0167] After the spectrometer 2 collects the target material 7 to be diagnosed, the spectrum data of the target material 7 to be diagnosed with i pixels is obtained, and each pixel corresponds to a different i wavelengths.

[0168] exist and In the example, the number without i represents the entire array, and the number with i refers to the i-th number in the array.

[0169] In the temperature measurement confidence interval of the target material 7 to be diagnosed, the laser irradiation moment of the target material 7 to be diagnosed corresponding to the first time the correlation coefficient is greater than 0.99 is taken as the ablation start moment of the target material 7 to be diagnosed.

[0170] The maximum value of the temperature measurement confidence interval 2500℃;

[0171] The minimum value of the temperature measurement confidence interval is calculated by the following formula: :

[0172] ;

[0173] in, Take the maximum wavelength of spectrometer 2, where m is meter and K is Kelvin.

[0174] Example 1

[0175] Taking the target material 7 to be diagnosed as aluminum alloy or stainless steel as an example, the method proposed in the present invention is described in detail.

[0176] S1: Building an ablation diagnosis experimental platform and using the ablation diagnosis experimental platform to obtain a laser spectrum incident on the target material 7 to be diagnosed;

[0177] S2: Perform spectral decoupling calculation on the laser spectrum to obtain the continuous spectrum, pump peak and laser scattering peak;

[0178] The laser spectrum obtained in step S1 is calibrated by standard steps such as background removal, wavelength calibration and blackbody radiation calibration. Then the laser spectrum is decomposed based on the Grubbs method or simulation software. If the target material 7 to be diagnosed is stainless steel, the following is obtained: Figure 3 The spectral components shown include the initial spectrum, the reconstructed spectrum, the continuous spectrum, the pump peak and the laser scattering peak. If the target material 7 to be diagnosed is an aluminum alloy, the following is obtained: Figure 4 The spectral components shown include the initial spectrum, reconstructed spectrum, continuous spectrum, pump peak, and laser scattering peak.

[0179] S3: normalize the continuous spectrum, pump peak, and laser scattering peak, and calculate the weights of the normalized continuous spectrum, normalized pump peak, and normalized laser scattering peak;

[0180] Calculating the weights of the normalized continuous spectrum, the normalized pump peak, and the normalized laser scattering peak specifically includes the following steps:

[0181] S31: fitting the normalized pump peak and the normalized laser scattering peak in sequence based on the Lorentz line shape or the Voigt line shape to obtain the line width parameters of the normalized pump peak and the normalized laser scattering peak;

[0182] S32: obtaining a peak position of the normalized pump peak and a peak position of the normalized laser scattering peak based on the line width parameter of the normalized pump peak and the line width parameter of the normalized laser scattering peak;

[0183] S33: according to the peak position of the normalized pump peak and the peak position of the normalized laser scattering peak, removing the data affected by the pump peak and the laser scattering peak, and reassigning the data values ​​corresponding to the positions of the removed data by using an interpolation method to obtain continuous spectrum data;

[0184] In step S33, the specific process of removing the pump peak data and the laser scattering peak data is as follows:

[0185] The pump peak is subtracted from the actual spectrum data incident on the target material to be diagnosed 7 after irradiance calibration, thereby eliminating the pump peak data;

[0186] The laser scattering peak is subtracted from the actual spectrum data incident on the target material to be diagnosed 7 after irradiance calibration, and the data of the laser scattering peak is removed.

[0187] S34: splicing the continuous spectrum data, the normalized pump peak, and the normalized laser scattering peak to obtain a matrix M;

[0188] S35: Calculate the weights of the normalized continuous spectrum, normalized pump peak, and normalized laser scattering peak using the following formula:

[0189] ;

[0190] Wherein, w is the weight, pinv is the pseudo-inverse matrix calculated for the matrix M, and S is the actual spectral data incident on the target material to be diagnosed 7 after irradiance calibration.

[0191] S4: According to the normalized continuous spectrum weight, normalized pump peak weight and normalized laser scattering peak weight obtained by real-time calculation in step S3, the normalized continuous spectrum weight curve, the normalized pump peak weight curve and the normalized laser scattering peak curve are drawn in the weight change curve diagram; the laser irradiation time of the target material 7 to be diagnosed is used as the horizontal axis, and the normalized continuous spectrum weight, the normalized pump peak weight and the normalized laser scattering peak weight are used as the vertical axis to draw the weight change curve diagram.

[0192] Among them, the weight change curve of the stainless steel target is shown in Figure 5 (a), and the weight change curve of the aluminum alloy target is shown in Figure 5 (b). By comparing Figure 5 (a) and Figure 5 (b), it can be seen that the parameter change rules of stainless steel and aluminum alloy during ablation are inconsistent. In 5 (a), the change trends of the normalized pump peak weight curve and the normalized laser scattering peak weight curve are basically the same, while the normalized pump peak weight curve of 5 (b) oscillates more violently at 80s, indicating that the normalized weight curves of the discrete spectra (pump peak and laser scattering peak) of the aluminum alloy change significantly.

[0193] S5: selecting an ablation diagnosis criterion according to the change trend of each curve in the weight change curve diagram and the temperature change trend, and obtaining an ablation diagnosis result of the target material 7 to be diagnosed.

[0194] S51: Calculate the respective total average weight values ​​of the normalized pump peak and the normalized laser scattering peak during the laser irradiation time; if the difference between the average weight value of the normalized pump peak within 1 second before the current moment and the total average weight value of the normalized pump peak is greater than 15% of the total average weight value of the normalized pump peak, and the difference between the average weight value of the normalized laser scattering peak and the total average weight value of the normalized laser scattering peak is greater than 15% of the total average weight value of the normalized laser scattering peak, diagnose the target material 7 to be diagnosed based on the ablation criterion of the characteristic spectral line intensity trend to obtain an ablation diagnosis result of the target material 7 to be diagnosed; otherwise, execute step S52;

[0195] The specific process of diagnosing the target material 7 based on the ablation criterion of the characteristic spectral line intensity trend in step S51 is as follows:

[0196] In the weight change curve diagram, the area where the normalized pump peak weight curve and the normalized laser scattering peak weight curve are both in a relatively stable state is regarded as a plateau period, and when both the normalized pump peak weight curve and the normalized laser scattering peak weight curve leave the plateau period, the moment when the laser irradiates the target material 7 to be diagnosed is regarded as the starting moment of ablation of the target material 7 to be diagnosed.

[0197] Because the normalized weight curves of the discrete spectra (pump peak and laser scattering peak) of aluminum alloy targets change significantly, the ablation criterion based on the intensity trend of the characteristic spectral line is suitable for judging the ablation of aluminum alloy targets. For aluminum alloy targets, the peak intensity changes of the discrete spectra (pump peak and laser scattering peak) can intuitively reflect the occurrence of ablation. As shown in Figure 5(b), an analysis of the trend of the normalized pump peak weight curve during the ablation of the aluminum alloy target shows that after about 80 seconds of irradiation, the peak of the discrete spectrum is no longer stable, that is, it leaves the so-called "plateau period". This is due to changes in the surface shape and reflectivity of the aluminum alloy.

[0198] The principle is that after some of the aluminum metal melts within the irradiated area of ​​the aluminum alloy, this local area will deform due to gravity. Although the aluminum alloy will not undergo significant morphological changes temporarily due to the outer high-melting-point oxide film, the phase of the sample-reflected light is extremely sensitive to changes in the surface shape of the aluminum alloy. Therefore, given that the phase of the sample-reflected light is extremely sensitive to changes in the surface shape of the aluminum alloy, even slight local surface deformation will significantly change the intensity of the corresponding characteristic spectral peaks (pump peak and laser scattering peak). This is particularly true for targets 7 to be diagnosed, which have dense oxide films, such as aluminum alloys. Therefore, the end of the plateau period of the characteristic spectral line intensity is used as one of the criteria for ablation diagnosis.

[0199] Since it is difficult to determine the specific moment of ablation from the intensity trend of the characteristic spectral lines of the stainless steel target, the ablation state of the stainless steel can be diagnosed using the ablation criterion based on the correlation between the spatially weighted emissivity and the spectrum.

[0200] S52: Diagnose the target material 7 to be diagnosed based on the ablation criterion of spatial weighted emissivity and spectrum correlation to obtain an ablation diagnosis result of the target material 7 to be diagnosed.

[0201] The temperature of the surface of the target material 7 to be diagnosed is collected in real time using multi-spectral temperature measurement technology;

[0202] The multi-spectral temperature measurement technology is the same as the multi-spectral temperature measurement technology used in the paper "Research on Multi-spectral Temperature Measurement Technology in Laser Damage".

[0203] The spatial weighted emissivity of the target material 7 to be diagnosed is calculated by the following formula:

[0204] ;

[0205] ;

[0206] in, is the function for calculating the spatially weighted emissivity, is the spatially weighted emissivity, is the wavelength, T is the temperature measured by multi-spectral temperature measurement technology, norm is the norm, is the actual spectrum data incident on the target material 7 to be diagnosed after irradiance calibration, is the ideal blackbody spectral radiation distribution, is the ideal blackbody spectral emissivity, =1.0, c1 is the first radiation constant, c 1=2π hc 2 =3.74×10 -16 W∙m 2 , h is Planck's constant, h =6.63×10 -34 J∙s, c is the speed of light, c=3×10 8 m / s, c2 is the second radiation constant, c2=hc / k B =1.43×10 -2 m∙K,k B is the Boltzmann constant, k B =1.38×10 -23 J / K;

[0207] Calculated by the following formula and Correlation coefficient :

[0208] ;

[0209] in, is the spatial weighted emissivity of the ith wavelength, is the average value of the spatially weighted emissivity of wavelength i, is the actual spectrum data of the i-th wavelength incident on the target material 7 to be diagnosed after irradiance calibration, is the average value of the actual spectrum data of i wavelengths incident on the target material to be diagnosed 7 after irradiance calibration, and n is the total number of spatially weighted emissivities;

[0210] In the temperature measurement confidence interval of the target material 7 to be diagnosed, the laser irradiation moment of the target material 7 to be diagnosed corresponding to the first time the correlation coefficient is greater than 0.99 is taken as the ablation start moment of the target material 7 to be diagnosed.

[0211] The maximum value of the temperature measurement confidence interval 2500℃;

[0212] The minimum value of the temperature measurement confidence interval is calculated by the following formula: :

[0213] ;

[0214] in, Take the maximum wavelength of spectrometer 2, where m is meter and K is Kelvin.

[0215] Define spatially weighted emissivity for:

[0216] ;

[0217] For simplicity, the spatially weighted emissivity is referenced to the highest value in a specific spectral interval (unit 1) for S and M. b The ratio is normalized.

[0218] When the laser irradiation area and the detection interval within the incident aperture of spectrometer 2 have a wide temperature distribution, It will be affected by the temperature distribution of the sample heating area. For reference, assume that the temperature distribution of the radiation area with radial variation obeys:

[0219] ;

[0220] Where r is the radial distance from the center of the spot as the origin, T(r) is the temperature distribution function value that changes with the radial distance, and g is the maximum temperature value with the radial distance and the center of the spot. Varying temperature distribution function.

[0221] In the detection aperture r a Within the range of , the total spectral radiation distribution N of the radiation area (the superposition of all radiation within the detection aperture) can be expressed as

[0222] ;

[0223] in, is the emissivity.

[0224] The detection aperture refers to the radius of the sample imaging range that can be detected by the detection system objective lens and other collecting optical systems in the imaging plane.

[0225] When the temperature gradient in the above detection range is small (i.e. the temperature change is not large), The integrated function form will be consistent with the radiance distribution function form. Theoretically, Will degenerate into the following form:

[0226] ;

[0227] is the integration constant.

[0228] In calculation , or when using multi-spectral temperature measurement technology to measure temperature, the emissivity of the target material 7 to be diagnosed It is generally considered to have a relatively smooth form with wavelength variation; furthermore, since the emissivity is strictly bounded in the physical sense, and for metals, the emissivity fluctuation in the visible-near infrared band is not large. Therefore, the emissivity can be expressed in the form of a polynomial , and the higher-order terms are usually considered to be negligible, that is,

[0229] ;

[0230] in, is the i-th Taylor coefficient.

[0231] like It has a nearly linear form (1st order), and it is not difficult to find that from the actual spectral data Computed will with It has a good linear correlation; on the contrary, when the temperature gradient in the detection interval is large, the spatial distribution of temperature will greatly affect , which reduces its linear correlation with the blackbody radiation formula.

[0232] Summarizing the above reasoning process, we can see that when the spatial gradient of the temperature in the detection area decreases, and The correlation coefficient will increase. Generally, the decrease in temperature spatial gradient represents a sudden decrease in energy coupling efficiency in the area with strong irradiation, or a sudden increase in local specific heat capacity (i.e., affected by the latent heat of phase change). These two represent a strong nonlinear effect and the generation of phase change, respectively, and have strong spectral characteristics. Therefore, the spatial weighted emissivity is introduced in the multi-spectral temperature measurement technology. This helps to use time-resolved spectroscopy technology to remotely diagnose whether the effector has been ablated when the target material 7 to be diagnosed is irradiated by strong laser.

[0233] like Figure 6 As shown in the figure, the calculated correlation coefficient for multispectral temperature measurement of stainless steel gradually decreases and then rises rapidly. Within the temperature measurement confidence interval greater than 1000°C, it can be assumed that when the correlation coefficient is greater than 0.99, the temperature rise in the center of the spectral detection area has stopped, indicating that a significant phase transformation (i.e., ablation) is occurring.

[0234] However, in Figure 6The correlation coefficient is also very high at relatively low temperatures. This is because the stainless steel temperature at this point has not yet reached a level sufficient to generate a high signal-to-noise ratio thermal radiation signal within the operating wavelength range of spectrometer 2 (400nm-1100nm), but it still meets the requirement for a low temperature gradient. Only after the temperature rises to a certain level does the emissivity shift caused by the spatial temperature field distribution that can be extracted within the operating wavelength band gradually become apparent. Therefore, to enhance the reliability of ablation diagnosis, it is also necessary to roughly determine whether the central temperature of the target material 7 to be diagnosed has reached the damage temperature in conjunction with the temperature measurement results.

[0235] In step S51 , if the laser irradiation time (total laser irradiation time) is 1.2 s, the target material 7 to be diagnosed is diagnosed based on the shortwave-visible band camera imaging ablation criterion or the temperature measurement ablation criterion to obtain the ablation diagnosis result of the target material 7 to be diagnosed.

[0236] In step S51, the specific process of diagnosing the target material 7 based on the shortwave-visible band camera imaging ablation criterion is as follows:

[0237] The shortwave visible band camera 3 is used to capture an image of the target material 7 to be diagnosed, and the sum of the grayscale values ​​of the area near the light spot is calculated;

[0238] The change curve of the total gray value is plotted with the laser irradiation time of the target material 7 to be diagnosed as the horizontal axis and the total gray value of the area near the light spot as the vertical axis;

[0239] The area near the light spot and the target material 7 to be diagnosed are the same.

[0240] When the ablation spot of the target material 7 to be diagnosed deviates from a perfect circle, and the increase rate of the total grayscale value in the first 2 seconds of the current moment is greater than 15% of the average increase rate during the laser irradiation time, the current laser irradiation moment is taken as the starting moment of ablation of the target material 7 to be diagnosed.

[0241] When the target material 7 to be diagnosed is laser ablated, the short-wave pass visible band camera 3 can also be used to image the target material 7 to be diagnosed. The role of the cascaded short-wave pass filter (the second short-wave pass filter 9, the third short-wave pass filter 10 and the fourth short-wave pass filter 11) is to filter out radiation that may interfere with the imaging.

[0242] From a spectroscopic perspective, the impact on target image pattern recognition is primarily manifested in two aspects: first, the influence of laser 4, namely the scattering signal of the pump and output lasers in the long-wave visible light to short-wave near-infrared region; second, the irrelevant radiation generated by the sample itself, namely the possible metal combustion luminescence and stimulated emission signals. These signals can interfere with the imaging device and affect image recognition accuracy.

[0243] Thermal radiation, metallic flame reaction (i.e. stimulated emission spectrum of metal atoms), fluorescence upconversion of doped or coated semiconductors / dyed materials, and anti-Stokes / stimulated anti-Stokes scattering are all unlikely to appear in wavelengths shorter than 500nm. Therefore, using a cascade of short-wavelength pass filters can produce clearer images (e.g. Figure 7 shown).

[0244] Figure 7 The mid-grayscale sum curve shows a clear inflection point near 80 seconds of laser irradiation time. In the corresponding image captured at 86.75 seconds of laser irradiation time, a teardrop-shaped mark appears around the ablation spot, indicating the onset of ablation. Severe ablation occurs after 100 seconds of laser irradiation, even leading to sample collapse.

[0245] The specific process of diagnosing the target material 7 using the temperature measurement ablation criterion is as follows:

[0246] At the same time, the temperature of the surface of the target material 7 to be diagnosed is collected using an infrared thermal imager 5, a multi-spectral temperature measurement technology and a weighted radiation spectrum inversion method;

[0247] In the temperature trend graph, the laser irradiation time is used as the horizontal axis, and the real-time temperature collected by the infrared thermal imager 5, the multi-spectral temperature measurement technology, and the weighted radiation spectrum inversion method are used as the vertical axis. The temperature change curves corresponding to the infrared thermal imager 5, the multi-spectral temperature measurement technology, and the weighted radiation spectrum inversion method are drawn respectively;

[0248] The specific process of real-time acquisition of the surface temperature of the target material 7 to be diagnosed by the weighted radiation spectrum inversion method is as follows:

[0249] Setting the objective function The expression is:

[0250] ;

[0251] ;

[0252] in, is the ratio of the ith spectrum intensity to the ideal blackbody radiation curve, is the mean value of the ratio of the i-th spectral intensity to the ideal blackbody radiation curve, is the actual spectrum data incident on the target material 7 to be diagnosed with respect to the i-th wavelength after irradiance calibration, is the ideal blackbody spectral radiation distribution of the i-th wavelength.

[0253] The objective function is optimized using the conjugate gradient method to obtain the surface temperature of the target material 7 to be diagnosed.

[0254] In the temperature trend graph, the two temperature change curves with the smallest cumulative sum of temperature differences at the same time during the laser irradiation time are selected, and the temperature values ​​of the two temperature change curves with the smallest cumulative sum of temperature differences at the same time are averaged to obtain the curve of the average temperature value changing with the laser irradiation time;

[0255] When the average temperature value of the surface of the target material to be diagnosed 7 is greater than 2000°C, and the difference between the average temperature rise rate of the target material to be diagnosed 7 in the first 1s before the current moment and the total average temperature rise rate of the target material to be diagnosed 7 during the laser irradiation time is greater than 15% of the total average temperature rise rate of the target material to be diagnosed 7 during the laser irradiation time, the current laser irradiation moment is taken as the starting moment of ablation of the target material to be diagnosed 7.

[0256] The weighted radiation spectrum inversion method of the present invention differs from the principle of multispectral temperature measurement methods in that it assumes that the sample's spectral emissivity is approximately constant within the selected wavelength band and is unaffected by the spatial temperature distribution of the target surface 7 to be diagnosed. In other words, the average temperature of the sample imaging area is calculated. This is similar to the temperature measurement principle of infrared thermal imagers (calculating temperature by integrating the locally generated 3-8 μm radiation) when the resolution is low.

[0257] Under this assumption, there is

[0258] ;

[0259] Where C is a constant.

[0260] Because the general least squares method relies on the sum of squares of absolute errors in the data, the influence of wavelengths with stronger signals (longer wavelengths) on the final optimization results is overwhelmingly dominant. This makes the linear characteristics of the thermal radiation spectrum itself, that is, the nonlinear characteristic parameters exhibited by temperature changes, impossible to effectively capture using least squares-based optimization methods. In order to fully participate in the optimization process of weak signal data and obtain the best optimization results, it is necessary to design a new objective function instead of the Euclidean distance in the data space.

[0261] To meet the above requirements, two weight factors need to be adjusted: first, the objective function needs to shield the linear factor and use the variance of the relative error as the main indicator to highlight its nonlinear characteristics; second, in order not to overemphasize the contribution of weak signals (especially signals close to the signal-to-noise ratio limit), the signal strength needs to be used as the weight and linearly combined with the square of the relative error of the corresponding data.

[0262] Therefore, suppose

[0263] ;

[0264] in, is the ratio of the spectral intensity to the ideal blackbody radiation curve.

[0265] The objective function can be designed as

[0266]

[0267] in, is the mean value of R.

[0268] The average temperature can then be obtained by optimizing the objective function using conventional optimization algorithms such as the conjugate gradient method.

[0269] Multispectral temperature measurement technology uses multiple parameters to simultaneously fit and calculate temperature. The weighted radiation spectrum inversion method is different from multispectral temperature measurement technology in that it directly fits the temperature through spectral intensity. At the same time, it also integrates the comprehensive consideration of multiple wavelength data to avoid the interference of radiation from certain specific wavelengths in the temperature measurement results. The temperature measurement results obtained using infrared thermal imaging, multispectral temperature measurement method, and weighted radiation spectrum inversion method are compared. Figure 8 As shown in the figure, the heat conduction of stainless steel is slow, resulting in a very large local temperature gradient. The multi-spectral temperature measurement results deviate far from the infrared thermal imaging temperature measurement results when the temperature exceeds 1500℃; in contrast, the temperature calculation results of weighted radiation spectrum inversion are closer to the infrared thermal imaging temperature measurement results, but Figure 8 The maximum temperature measured by the infrared thermal imager 5 is 2100°C, so in the part exceeding the limit, the present invention uses spline interpolation to assist comparison. Figure 9 As shown in the figure, the temperature results obtained by multi-spectral temperature measurement and weighted radiation spectrum inversion for aluminum alloy target are poor. This is because the heat conduction speed of aluminum alloy target is relatively fast, which makes it impossible to concentrate energy locally, resulting in a weak thermal radiation spectrum. It is not until the aluminum alloy target sample collapses and leaks that the liquid aluminum releases strong thermal radiation when it encounters oxygen combustion. At this time, the temperature measurement results of infrared thermal imager 5, multi-spectral temperature measurement and weighted radiation spectrum inversion are close.

[0270] As shown in Figures 10(a) and 10(b), a decrease in the pinhole leakage power can be observed near the ablation moment. This is due to the shielding effect of local steam, flame, and plasma, or the deformation of the pinhole caused by metal liquefaction. The pinhole leakage power can be used to estimate the approximate time of ablation. Ultimately, the result is consistent with the ablation diagnosis result (gray dotted line). If the laser irradiation time is longer than the ablation time, a clear downward trend will be observed after the ablation moment.

[0271] like Figure 11 and Figure 12 It can be seen that steam and ablation pits appeared in stainless steel at 6 seconds; an annular area formed by the recondensation of internal metal liquid was observed in aluminum alloy at 90 seconds, indicating that ablation had occurred. These phenomena are consistent with the results of ablation diagnosis ( Figure 7-Figure 9The orange dashed line perpendicular to the time axis in FIG10 and the gray dashed line perpendicular to the time axis in FIG11 are consistent.

[0272] The present invention is not intended to measure temperature; temperature measurement results serve only as an auxiliary indicator to determine whether ablation is likely to occur. The present invention requires a comprehensive evaluation of multiple criteria, including spatially weighted emissivity, characteristic spectral peaks, infrared thermal imaging, and visible band target imaging, to achieve ablation diagnosis.

[0273] It should be understood that the various forms of the processes shown above can be used to reorder, add, or delete steps. For example, the steps described in the present disclosure can be performed in parallel, sequentially, or in a different order, as long as the desired results of the technical solutions disclosed in the present disclosure can be achieved. This is not limited herein.

[0274] The above specific embodiments do not limit the scope of protection of the present invention. Those skilled in the art will appreciate that various modifications, combinations, sub-combinations, and substitutions may be made based on design requirements and other factors. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of the present invention are intended to be included within the scope of protection of the present invention.

Claims

1. A multimodal intense continuous laser ablation diagnostic method, characterized by: The specific steps include: S1: Building an ablation diagnosis experimental platform, and using the ablation diagnosis experimental platform to obtain in real time the laser spectrum incident on the target material to be diagnosed; S2: performing real-time spectrum decoupling calculation on the laser spectrum to obtain a continuous spectrum, a pump peak, and a laser scattering peak; S3: performing real-time normalization processing on the continuous spectrum, the pump peak, and the laser scattering peak, and calculating the weights of the normalized continuous spectrum, the normalized pump peak, and the normalized laser scattering peak in real time; In step S3, calculating the weights of the normalized continuous spectrum, the normalized pump peak, and the normalized laser scattering peak specifically includes the following steps: S31: fitting the normalized pump peak and the normalized laser scattering peak in sequence based on the Lorentz line shape or the Foucault line shape to obtain the line width parameters of the normalized pump peak and the normalized laser scattering peak; S32: obtaining a peak position of the normalized pump peak and a peak position of the normalized laser scattering peak based on the line width parameter of the normalized pump peak and the line width parameter of the normalized laser scattering peak; S33: according to the peak position of the normalized pump peak and the peak position of the normalized laser scattering peak, the data of the pump peak and the data of the laser scattering peak are mined, and the data values ​​corresponding to the positions of the mined data are reassigned by interpolation to obtain continuous spectrum data; S34: splicing the continuous spectrum data, the normalized pump peak, and the normalized laser scattering peak to obtain a matrix M; S35: Calculate the weights of the normalized continuous spectrum, normalized pump peak, and normalized laser scattering peak using the following formula: ； Wherein, w is the weight of the normalized continuous spectrum, normalized pump peak or normalized laser scattering peak, pinv is the pseudo-inverse matrix calculated for the matrix M, and S is the actual spectral data incident on the target material to be diagnosed after irradiance calibration; S4: based on the normalized continuous spectrum weight, normalized pump peak weight, and normalized laser scattering peak weight obtained by real-time calculation in step S3, drawing a normalized continuous spectrum weight curve, a normalized pump peak weight curve, and a normalized laser scattering peak curve in a weight change curve graph; S5: selecting an ablation diagnosis criterion according to the temperature change trend and the change trend of each curve in the weight change curve diagram to obtain an ablation diagnosis result of the target material to be diagnosed; S51: Calculate the respective total average weight values ​​of the normalized pump peak and the normalized laser scattering peak during the laser irradiation time; if the difference between the average weight value of the normalized pump peak within 1 second before the current moment and the total average weight value of the normalized pump peak is greater than 15% of the total average weight value of the normalized pump peak, and the difference between the average weight value of the normalized laser scattering peak and the total average weight value of the normalized laser scattering peak is greater than 15% of the total average weight value of the normalized laser scattering peak, diagnose the target material to be diagnosed based on the ablation criterion of the characteristic spectral line intensity trend to obtain an ablation diagnosis result of the target material to be diagnosed; otherwise, execute step S52; S52: diagnose the target material to be diagnosed based on the ablation criterion of the spatial weighted emissivity and the spectrum correlation, and obtain an ablation diagnosis result of the target material to be diagnosed.

2. The multimodal intense continuous laser ablation diagnostic method according to claim 1, characterized in that: The ablation diagnosis experimental platform includes a computer, a spectrometer, a shortwave visible band camera, a laser, an infrared thermal imager, a target material to be diagnosed, and an energy meter. The output end of the computer is respectively connected to the input end of the spectrometer, the input end of the shortwave visible band camera, the input end of the laser, and the input end of the infrared thermal imager. The output ends of the spectrometer, the output ends of the shortwave visible band camera, and the output ends of the infrared thermal imager are all aimed at the target material to be diagnosed. The output end of the target material to be diagnosed is connected to the input end of the energy meter, and the output end of the energy meter is connected to the input end of the computer. A small hole is provided at the center of the target material to be diagnosed, and the laser emitted by the laser passes through the small hole of the target material to be diagnosed and is incident on the energy meter; the energy meter collects the laser energy passing through the small hole of the target material to be diagnosed in real time; the computer displays the data collected by the energy meter in real time; the spectrometer collects the laser spectrum incident on the target material to be diagnosed in real time; the shortwave visible band camera monitors the ablation state of the target material to be diagnosed in real time, and obtains a visible light image in real time; the infrared thermal imager monitors the ablation state of the target material to be diagnosed in real time, and obtains an infrared thermal image and the current temperature of the target material to be diagnosed in real time.

3. The multimodal intense continuous laser ablation diagnostic method according to claim 2, characterized in that: The number of the lasers is not less than one, wherein, The specific process of using a laser to ablate the target material to be diagnosed is as follows: Aligning the output end of the laser toward the target material to be diagnosed, and allowing the laser light emitted by the laser to pass through the small hole in the target material to be diagnosed; The specific process of using two or more lasers to ablate the target material to be diagnosed is as follows: Two or more lasers are combined to transmit the combined laser beams through the small holes in the target material to be diagnosed.

4. The multimodal intense continuous laser ablation diagnostic method according to claim 2, characterized in that: A first short-wave pass filter is provided between the spectrometer and the target material to be diagnosed, along the optical axis direction of the spectrometer; Between the short-wave-pass visible band camera and the target material to be diagnosed, a second short-wave-pass filter, a third short-wave-pass filter and a fourth short-wave-pass filter are sequentially provided along the optical axis direction of the short-wave-pass visible band camera; The first short-wave pass filter includes a 1000nm short-wave pass filter, the second short-wave pass filter includes a 700nm short-wave pass filter, the third short-wave pass filter includes a 515nm short-wave pass filter, and the fourth short-wave pass filter includes an 800nm ​​short-wave pass filter.

5. The multimodal intense continuous laser ablation diagnostic method according to claim 1, characterized in that: In step S33, the specific process of removing the pump peak data and the laser scattering peak data is as follows: The pump peak is subtracted from the actual spectrum data incident on the target material to be diagnosed after irradiance calibration, and the data of the pump peak is removed; The laser scattering peak is subtracted from the actual spectrum data incident on the target material to be diagnosed after irradiance calibration, and the data of the laser scattering peak is removed.

6. The multimodal intense continuous laser ablation diagnostic method according to claim 2, characterized in that: In step S4, a weight variation curve is drawn with the laser irradiation time on the target material to be diagnosed as the horizontal coordinate, and the normalized continuous spectrum weight, the normalized pump peak weight and the normalized laser scattering peak weight as the vertical coordinates.

7. The multimodal intense continuous laser ablation diagnostic method according to claim 1, characterized in that: In step S51, if the laser irradiation time is 1.2s, the target material to be diagnosed is diagnosed based on the shortwave-visible band camera imaging ablation criterion or the temperature measurement ablation criterion to obtain the ablation diagnosis result of the target material to be diagnosed.

8. The multimodal intense continuous laser ablation diagnostic method according to claim 1, characterized in that: The specific process of diagnosing the target material to be diagnosed based on the ablation criterion of the characteristic spectral line intensity trend in step S51 is as follows: In the weight change curve diagram, the amplitudes of the normalized pump peak weight curve and the normalized laser scattering peak weight curve during the laser irradiation time are calculated respectively; Calculate the unit amplitude of the normalized pump peak weight curve and the normalized laser scattering peak weight curve every 2 seconds during the laser irradiation time; When the unit amplitudes of the normalized pump peak weight curve and the normalized laser scattering peak weight curve are respectively lower than 20% of the amplitudes of the normalized pump peak weight curve and the normalized laser scattering peak weight curve, the current laser irradiation moment is regarded as the plateau period; When both the normalized pump peak weight curve and the normalized laser scattering peak weight curve leave the plateau phase, the irradiation moment of the laser on the target material to be diagnosed is taken as the ablation starting moment of the target material to be diagnosed.

9. The multimodal intense continuous laser ablation diagnostic method according to claim 1, characterized in that: The specific process of diagnosing the target material to be diagnosed based on the ablation criterion of spatial weighted emissivity and spectral correlation in step S52 is as follows: Using multi-spectral temperature measurement technology to collect the surface temperature of the target material to be diagnosed in real time; The spatial weighted emissivity of the target material to be diagnosed is calculated by the following formula: ； ； in, is the function for calculating the spatially weighted emissivity, is the spatially weighted emissivity, is the wavelength, T is the temperature measured by multi-spectral temperature measurement technology, norm is the norm, is the actual spectral data incident on the target material to be diagnosed after irradiance calibration. is the ideal blackbody spectral radiation distribution, is the ideal blackbody spectral emissivity, =1.0, c1 is the first radiation constant, c 1=2π hc 2 =3.74×10 -16 W∙m 2 , h is Planck's constant, h =6.63×10 -34 J∙s, c is the speed of light, c=3×10 8 m / s, c2 is the second radiation constant, c2=hc / k B =1.43×10 -2 m∙K,k B is the Boltzmann constant, k B =1.38×10 -23 J / K; Calculated by the following formula and Correlation coefficient : ； in, is the spatial weighted emissivity of the ith wavelength, is the average value of the spatially weighted emissivity of wavelength i, is the actual spectral data of the i-th wavelength incident on the target material to be diagnosed after irradiance calibration, is the average value of the actual spectral data of i wavelengths incident on the target material to be diagnosed after irradiance calibration, and n is the total number of spatially weighted emissivities; In the temperature measurement confidence interval of the target material to be diagnosed, the irradiation moment of the laser on the target material to be diagnosed corresponding to the correlation coefficient greater than 0.99 is used as the ablation starting moment of the target material to be diagnosed.

10. The multi-modal intense continuous laser ablation diagnostic method according to claim 9, characterized in that: The maximum value of the temperature measurement confidence interval 2500℃; The minimum value of the temperature measurement confidence interval is calculated by the following formula: : ； in, Take the maximum wavelength of the spectrometer, m is meter, K is Kelvin.

11. The multimodal intense continuous laser ablation diagnostic method according to claim 7, characterized in that: In step S51, the specific process of diagnosing the target material to be diagnosed based on the shortwave-visible band camera imaging ablation criterion is as follows: Using the shortwave visible band camera to capture an image of the target material to be diagnosed, and calculating the sum of the grayscale values ​​of the area near the light spot; With the laser irradiation time of the target material to be diagnosed being used as the horizontal axis and the gray value sum of the area near the light spot being used as the vertical axis, a gray value sum change curve is drawn; When the ablation spot of the target material to be diagnosed deviates from a perfect circle and the increase rate of the total gray value in the first 2 seconds before the current moment is greater than 15% of the average increase rate during the laser irradiation time, the current laser irradiation moment is taken as the ablation start moment of the target material to be diagnosed; The specific process of diagnosing the target material to be diagnosed using the temperature measurement and ablation criterion is as follows: At the same time, the surface temperature of the target material to be diagnosed is collected using an infrared thermal imager, multi-spectral temperature measurement technology and a weighted radiation spectrum inversion method; In the temperature trend graph, the laser irradiation time is used as the horizontal axis, and the real-time temperature collected by the infrared thermal imager, multispectral temperature measurement technology, and weighted radiation spectrum inversion method is used as the vertical axis. The temperature change curves corresponding to the infrared thermal imager, multispectral temperature measurement technology, and weighted radiation spectrum inversion method are drawn respectively; In the temperature trend graph, two temperature change curves with the smallest cumulative sum of temperature differences at the same time during the laser irradiation time are selected, and the temperature values ​​of the two temperature change curves with the smallest cumulative sum of temperature differences at the same time are averaged to obtain a curve of average temperature value changing with laser irradiation time; When the average temperature value of the surface of the target material to be diagnosed is greater than 2000°C, and the difference between the average heating rate of the target material to be diagnosed in the first 1s of the current moment and the total average heating rate of the target material to be diagnosed during the laser irradiation time is greater than 15% of the total average heating rate of the target material to be diagnosed during the laser irradiation time, the current laser irradiation moment is taken as the starting moment of ablation of the target material to be diagnosed.

12. The multimodal intense continuous laser ablation diagnostic method according to claim 11, characterized in that: The area of ​​the region near the light spot is the same as the area of ​​the target material to be diagnosed.

13. The multimodal intense continuous laser ablation diagnostic method according to claim 11, characterized in that: The specific process of using the weighted radiation spectrum inversion method to collect the surface temperature of the target material to be diagnosed in real time is as follows: Setting the objective function The expression is: ； ； in, is the ratio of the ith spectrum intensity to the ideal blackbody radiation curve, is the mean value of the ratio of the i-th spectral intensity to the ideal blackbody radiation curve, is the actual spectrum data incident on the target material to be diagnosed at the i-th wavelength after irradiance calibration, is the ideal blackbody spectral radiation distribution of the i-th wavelength; The objective function is optimized using the conjugate gradient method to obtain the surface temperature of the target material to be diagnosed.

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