Molten pool temperature online monitoring method and system in laser additive manufacturing process

Abstract

The invention belongs to the technical field of additive manufacturing, and discloses a molten pool temperature online monitoring method and system in the laser additive manufacturing process. A spectroscope is used for dividing a molten pool optical signal into a first light beam and a second light beam with the same intensity; the first light beam passes through the first optical filter, reaches the first reflector, passes through the first optical filter again after being reflected by the first reflector, and is imaged by the detector; the second light beam passes through the second optical filter, reaches the second reflector, passes through the second optical filter again after being reflected by the second reflector, and is imaged by the detector; the central wavelengths of the first filter and the second filter are different, and the detector obtains a dual-wavelength molten pool image; and obtaining a molten pool temperature field based on the dual-wavelength molten pool image by using an image processing unit. The measurement precision of the molten pool temperature in the laser additive manufacturing process can be improved.

Description

Technical Field

[0001] The present invention belongs to the technical field of additive manufacturing, and more specifically, relates to a method and system for online monitoring of molten pool temperature during laser additive manufacturing. Background Art

[0002] Laser Powder Bed Fusion (LPBF), as the mainstream technology of metal additive manufacturing (AM), plays an important role in key fields such as aviation and aerospace. Among them, key variables such as the temperature field distribution of the molten pool during the AM process are directly related to the performance of the component. For example, many defects such as porosity, unfusion, microcracks, and contour deformation may occur in this process. Therefore, the lack of quality assurance and performance control seriously hinders the widespread application of LPBF technology. In order to improve the stability and repeatability of components, real-time monitoring of the molten pool temperature field has gradually attracted attention.

[0003] At present, the methods used to monitor the temperature field of the LPBF melt pool mainly include photodiodes, infrared thermal imagers, and dual-wavelength temperature measurement systems. However, the emissivity calibration of commercial equipment such as photodiodes and infrared thermal imagers is complex, the temperature range is small, it is difficult to meet the monitoring requirements, and the cost is high. In addition, the application of traditional infrared equipment is greatly limited due to the large system size and difficulty in integration in a limited space. Although the current dual-wavelength temperature measurement system based on a single camera or dual cameras can monitor higher melt pool temperatures without the need for emissivity calibration, the frame rate consistency error, large size, and high cost of the dual-camera system limit its application range. Although the current single-camera system reduces costs, the optical path is complex and difficult to integrate, and the impact of the coaxial imaging system on temperature measurement is not considered. Summary of the invention

[0004] The present invention solves the problem of low measurement accuracy of the molten pool temperature in the laser additive manufacturing process in the prior art by providing a method and system for online monitoring of the molten pool temperature in the laser additive manufacturing process.

[0005] In a first aspect, the present invention provides a method for online monitoring of molten pool temperature during laser additive manufacturing, comprising the following steps:

[0006] A spectroscope is used to split the molten pool optical signal into a first light beam and a second light beam of equal intensity; the first light beam passes through a first filter and reaches a first reflector, and then passes through the first filter again after being reflected by the first reflector, and is imaged by a detector; the second light beam passes through a second filter and reaches a second reflector, and then passes through the second filter again after being reflected by the second reflector, and is imaged by the detector; the first filter and the second filter have different central wavelengths, and the detector obtains a dual-wavelength molten pool image;

[0007] An image processing unit is used to obtain a molten pool temperature field based on the dual-wavelength molten pool image.

[0008] Preferably, the image processing unit is used to perform preliminary segmentation on the dual-wavelength molten pool image, and the first molten pool image and the second molten pool image obtained after the preliminary segmentation are matched and aligned; the first molten pool image corresponds to the first light beam, and the second molten pool image corresponds to the second light beam;

[0009] After matching and alignment, the image processing unit calculates the temperature of the molten pool using a dual-wavelength colorimetric temperature measurement formula.

[0010] Preferably, performing preliminary segmentation of the dual-wavelength molten pool image by using the image processing unit comprises the following sub-steps:

[0011] Binarization is performed on the dual-wavelength molten pool image using an adaptive threshold binarization method, and molten pool boundary position information is obtained based on a binary image corresponding to the dual-wavelength molten pool image;

[0012] According to the molten pool boundary position information and the prior size information of the molten pool, the first molten pool image and its binary image, and the second molten pool image and its binary image are obtained by region of interest extraction.

[0013] Preferably, matching and aligning the first molten pool image and the second molten pool image comprises the following sub-steps:

[0014] According to the molten pool boundary position information, the center position of the i-th iteration of the first molten pool image and the center position of the i-th iteration of the second molten pool image are calculated; wherein i=1, 2, ..., n; n is the set number of iterations;

[0015] According to the center position of the first molten pool image at the i-th iteration and the center position of the second molten pool image at the i-th iteration, a center offset value of the two images at the i-th iteration is calculated;

[0016] After completing n iterations, calculate the average of the n center offset values ​​to get the final offset value;

[0017] Correction is performed based on the final offset value to align the two images.

[0018] Preferably, the molten pool optical signal comes from a coaxial test optical path system.

[0019] Preferably, the dual-wavelength colorimetric temperature measurement formula is as follows:

[0020]

[0021] k=R(λ 2 ) / R(λ1 )

[0022] Where, T co is the temperature of the molten pool under the coaxial test optical system, C 2 is the second radiation constant, λ 1 is the central wavelength of the first filter, λ 2 is the central wavelength of the second filter, w′ is the relationship coefficient between the grayscale values ​​under the dual-wavelength radiation after coaxial calibration, R(λ 1 ) is the detector's response to wavelength λ 1 The response, R(λ 2 ) is the detector's response to wavelength λ 2 response, and k is the coefficient obtained by non-coaxial calibration of the blackbody furnace.

[0023] Preferably, the relationship coefficient w′ between the grayscale values ​​under the dual-wavelength radiation after the coaxial calibration is obtained by the following formula:

[0024] w′=wAm′ / m

[0025]

[0026] Wherein, w is the relationship coefficient between the grayscale values ​​under dual-wavelength radiation before coaxial calibration, A is the calibration coefficient of the beam splitter in the non-coaxial test optical path system, m′ is the intensity ratio of the dual wavelengths under the non-coaxial test optical path system, m is the intensity ratio of the dual wavelengths under the coaxial test optical path system, and g′ is c (λ 1 ) is the wavelength λ of the non-coaxial test optical path system 1 The corresponding white image, g′ c (λ 2 ) is the wavelength λ of the non-coaxial test optical path system 2 The corresponding white image, g c (λ 1 ) is the wavelength λ of the coaxial test optical path system 1 The corresponding white image, g c (λ 2 ) is the wavelength λ of the coaxial test optical path system 2 The corresponding white image.

[0027] In a second aspect, the present invention provides an online monitoring system for molten pool temperature during laser additive manufacturing, comprising: a spectroscope, a first filter, a first reflector, a second filter, a second reflector, a detector, and an image processing unit;

[0028] The system for online monitoring of molten pool temperature during laser additive manufacturing is used to execute the steps of the above-mentioned method for online monitoring of molten pool temperature during laser additive manufacturing.

[0029] Preferably, the online monitoring system for the molten pool temperature during the laser additive manufacturing process further includes: a focusing lens group; before the two beams of light are incident on the detector, they are both focused by the focusing lens group.

[0030] In a third aspect, the present invention provides an electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein when the processor executes the program, the above-mentioned method for online monitoring of the molten pool temperature in the laser additive manufacturing process is implemented.

[0031] One or more technical solutions provided in the present invention have at least the following technical effects or advantages:

[0032] (1) The present invention first uses a spectroscope to divide the molten pool light signal into a first light beam and a second light beam of equal intensity. The first light beam passes through the first filter and reaches the first reflector, and then passes through the first filter again after being reflected by the first reflector, and is imaged by the detector; the second light beam passes through the second filter and reaches the second reflector, and then passes through the second filter again after being reflected by the second reflector, and is imaged by the detector; wherein the center wavelengths of the first filter and the second filter are different, and the detector obtains a dual-wavelength molten pool image; then an image processing unit is used to obtain the molten pool temperature field based on the dual-wavelength molten pool image. In the present invention, each beam of light after being split by the spectroscope is filtered twice by the corresponding filter, which can effectively remove the interference of stray wavelengths and improve the accuracy of molten pool temperature measurement.

[0033] (2) The present invention uses an image processing unit to perform preliminary segmentation on the dual-wavelength melt pool image (including using an adaptive threshold binarization method to binarize the dual-wavelength melt pool image, obtaining the melt pool boundary position information based on the binary image, and obtaining two melt pool images and corresponding binary images through region of interest extraction), and matches and aligns the first melt pool image and the second melt pool image obtained after the preliminary segmentation (including calculating the center position of the melt pool image for multiple iterations, calculating the center offset value and obtaining the final offset value, and correcting the two images according to the final offset value to match and align). That is, the present invention proposes a dynamic online matching method for the center position of the melt pool image with an adaptive threshold, which calculates the center deviation of the two images under dual wavelengths and corrects them to overlap, thereby achieving sub-pixel matching of the melt pool image. This high-precision matching technology can solve the problem of inaccurate matching of traditional methods when facing dynamic changes in the shape and position of the melt pool, and can achieve high-precision melt pool temperature field measurement under different laser scanning conditions.

[0034] (3) When the molten pool optical signal comes from the coaxial test optical path system and the dual-wavelength colorimetric temperature measurement formula is used to calculate the temperature of the molten pool, the present invention also performs coaxial calibration on the relationship coefficient between the grayscale values ​​under dual-wavelength radiation. That is, the present invention aims at the influence of the coaxial system on the dual-wavelength temperature measurement, calibrates the dual-wavelength intensity of the coaxial test optical path system, and derives the calibration formula, thereby avoiding the use of additional hardware for calibration, reducing the complexity and cost of calibration, and further improving the accuracy of the coaxial measurement of the molten pool temperature.

[0035] (4) The online monitoring system for the molten pool temperature in the laser additive manufacturing process provided by the present invention mainly includes a beam splitter, a first filter, a first reflector, a second filter, a second reflector, a detector and an image processing unit, and only uses the five elements of the beam splitter, the first filter, the first reflector, the second filter and the second reflector to realize the beam splitting and filtering. The structure is compact, and the two reflectors can flexibly adjust the position of the dual-wavelength image to be suitable for a variety of processes such as a coaxial system and a paraxial system, and can be easily integrated into the LPBF equipment. BRIEF DESCRIPTION OF THE DRAWINGS

[0036] Figure 1 A schematic diagram of the positional relationship between an online monitoring system for molten pool temperature and a coaxial test optical path system in a laser additive manufacturing process provided by an embodiment of the present invention;

[0037] Figure 2 A schematic diagram of the structure of an online monitoring system for molten pool temperature in a laser additive manufacturing process provided by an embodiment of the present invention;

[0038] Figure 3 A schematic flow chart of dual-wavelength molten pool image correction in an online monitoring method of molten pool temperature in a laser additive manufacturing process provided by an embodiment of the present invention; wherein: Figure 3 (a) is a schematic diagram of the process of segmenting the dual-wavelength melt pool image using a priori adaptive threshold. Figure 3 (b) is a schematic diagram of the process of iterative matching and alignment of dual-wavelength melt pool images;

[0039] Figure 4 is a schematic diagram of the change in the center distance of the molten pool before and after matching in the dual-wavelength molten pool image; Figure 4 (a) is the distance between the centers of the two-wavelength melt pool images in the vertical and horizontal directions before matching. Figure 4 (b) in the figure is the melt pool center offset error of the dual-wavelength melt pool image after matching.

[0040] Figure 5 A schematic diagram of dual-wavelength intensity radiation calibration in an online monitoring method for molten pool temperature in a laser additive manufacturing process provided by an embodiment of the present invention;

[0041] Figure 6 This is a dual-wavelength image obtained by a blackbody furnace;

[0042] Figure 7 The molten pool temperature field result is obtained by using an online monitoring method for molten pool temperature in a laser additive manufacturing process provided by an embodiment of the present invention.

[0043] Among them, 100-online monitoring system of melt pool temperature during laser additive manufacturing;

[0044] 110 - spectroscope, 120 - first filter, 130 - first reflector, 140 - second filter, 150 - second reflector, 160 - focusing lens group, 170 - detector, 180 - image processing unit;

[0045] 201-processing laser, 202-beam expander, 203-long-wave dichroic mirror, 204-galvanometer, 205-field mirror, 206-substrate, 207-molten pool. DETAILED DESCRIPTION

[0046] In order to better understand the above technical solution, the above technical solution will be described in detail below in conjunction with the accompanying drawings and specific implementation methods.

[0047] Embodiment 1:

[0048] Example 1 provides a method for online monitoring of molten pool temperature during laser additive manufacturing. Figure 2 , including the following steps:

[0049] Step 1: Use a spectroscope 110 to split the molten pool optical signal (i.e., molten pool radiation light) into a first light beam and a second light beam of equal intensity; the first light beam passes through the first filter 120 and reaches the first reflector 130, and passes through the first filter 120 again after being reflected by the first reflector 130, and is imaged by the detector 170; the second light beam passes through the second filter 140 and reaches the second reflector 150, and passes through the second filter 140 again after being reflected by the second reflector 150, and is imaged by the detector 170; the central wavelengths of the first filter 120 and the second filter 140 are different, and the detector 170 obtains a dual-wavelength molten pool image.

[0050] Step 2: Utilize the image processing unit 180 to obtain the molten pool temperature field based on the dual-wavelength molten pool image.

[0051] Among them, the image processing unit 180 is used to perform preliminary segmentation on the dual-wavelength melt pool image, and the first melt pool image and the second melt pool image obtained after the preliminary segmentation are matched and aligned; the first melt pool image corresponds to the first light beam, and the second melt pool image corresponds to the second light beam; after matching and alignment, the image processing unit 180 uses the dual-wavelength colorimetric temperature measurement formula to calculate the temperature of the melt pool.

[0052] Specifically, using the image processing unit 180 to perform preliminary segmentation on the dual-wavelength melt pool image includes the following sub-steps: using an adaptive threshold binarization method to binarize the dual-wavelength melt pool image, and obtaining the melt pool boundary position information based on the binary image corresponding to the dual-wavelength melt pool image; according to the melt pool boundary position information and the prior size information of the melt pool, the first melt pool image and its binary image, as well as the second melt pool image and its binary image are obtained by extracting the region of interest.

[0053] Specifically, matching and aligning the first melt pool image and the second melt pool image includes the following sub-steps: according to the melt pool boundary position information, calculating the center position of the first melt pool image at the i-th iteration and the center position of the second melt pool image at the i-th iteration; wherein i=1, 2, ..., n; n is the set number of iterations; according to the center position of the first melt pool image at the i-th iteration and the center position of the second melt pool image at the i-th iteration, calculating the center offset value of the two images at the i-th iteration; after completing n iterations, calculating the average of the n center offset values ​​to obtain the final offset value; and performing correction according to the final offset value to match and align the two images.

[0054] The molten pool optical signal may come from a coaxial test optical path system. That is, the online monitoring method provided by the present invention can be used for coaxial online monitoring of the LPBF molten pool temperature field, and can obtain dual-wavelength information of the molten pool, thereby obtaining the molten pool temperature field.

[0055] The dual-wavelength colorimetric temperature measurement formula is as follows:

[0056]

[0057] k=R(λ 2 ) / R(λ 1 )

[0058] Where, T co is the temperature of the molten pool under the coaxial test optical system, C 2 is the second radiation constant, λ 1 is the central wavelength of the first filter, λ 2 is the central wavelength of the second filter, w′ is the relationship coefficient between the grayscale values ​​under the dual-wavelength radiation after coaxial calibration, R(λ 1) is the detector's response to wavelength λ 1 The response, R(λ 2 ) is the detector's response to wavelength λ 2 response, and k is the coefficient obtained by non-coaxial calibration of the blackbody furnace.

[0059] The relationship coefficient w′ between the grayscale values ​​under the dual-wavelength radiation after the coaxial calibration is obtained by the following formula:

[0060] w′=wAm′ / m

[0061]

[0062] Wherein, w is the relationship coefficient between the grayscale values ​​under dual-wavelength radiation before coaxial calibration, A is the calibration coefficient of the beam splitter in the non-coaxial test optical path system, m′ is the intensity ratio of the dual wavelengths under the non-coaxial test optical path system, m is the intensity ratio of the dual wavelengths under the coaxial test optical path system, and g′ is c (λ 1 ) is the wavelength λ of the non-coaxial test optical path system 1 The corresponding white image, g′ c (λ 2 ) is the wavelength λ of the non-coaxial test optical path system 2 The corresponding white image, g c (λ 1 ) is the wavelength λ of the coaxial test optical path system 1 The corresponding white image, g c (λ 2 ) is the wavelength λ of the coaxial test optical path system 2 The corresponding white image.

[0063] Embodiment 2:

[0064] Example 2 provides an online monitoring system for the temperature of the molten pool during laser additive manufacturing. Figure 2 , mainly comprising: a spectroscope 110, a first filter 120, a first reflector 130, a second filter 140, a second reflector 150, a detector 170 and an image processing unit 180. In addition, a focusing lens group 160 may also be included; before the two beams of light are incident on the detector 170, they are both focused by the focusing lens group 160.

[0065] The system for online monitoring of molten pool temperature during laser additive manufacturing provided in Example 2 is used to execute the steps in the method for online monitoring of molten pool temperature during laser additive manufacturing as described in Example 1.

[0066] Since the functions of the various components in the monitoring system provided in Example 2 correspond to the steps in the monitoring method provided in Example 1, they can be understood by referring to the description of Example 1 and will not be repeated here.

[0067] Embodiment 3:

[0068] Embodiment 3 provides an electronic device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein when the processor executes the program, the method for online monitoring of the molten pool temperature during the laser additive manufacturing process as described in Embodiment 1 is implemented.

[0069] Among them, the processor mainly executes the relevant content of obtaining the molten pool temperature field based on the dual-wavelength molten pool image using the image processing unit.

[0070] Several main parts of the present invention are further described below.

[0071] (1) Design of online monitoring system for molten pool temperature during laser additive manufacturing process.

[0072] See also Figure 1 The online monitoring system 100 for the temperature of the molten pool in the laser additive manufacturing process provided by the present invention is preferably used in conjunction with a coaxial test optical path system (such as an LPBF system) to capture dual-wavelength molten pool images in real time. The configuration of the coaxial imaging device ensures that when the laser scans the powder bed, the molten pool remains in the center of the image, thereby maintaining good spatial resolution of the molten pool in the entire monitoring area. Figure 1 The coaxial test optical system mainly includes a processing laser 201, a beam expander 202, a long-wave dichroic mirror 203, a galvanometer 204, and a field lens 205, and also involves a substrate 206 and a molten pool 207. The light emitted by the molten pool 207 passes through the field lens 205, the galvanometer 204, and the long-wave dichroic mirror 203, and finally reaches the molten pool temperature online monitoring system 100 designed by the present invention. The function of the long-wave dichroic mirror 203 is to allow light with the same wavelength as the laser to pass through, while light with a shorter wavelength, such as the light in the molten pool, is reflected to the filter to prevent the high-power laser from damaging the imaging device.

[0073] See also Figure 2 In the molten pool temperature online monitoring system provided by the present invention, the light emitted by the molten pool is divided into two beams of light at a ratio of 1:1 by the beam splitter 110, namely, the transmitted light and the reflected light. 1 The first filter 120 is passed through by the first reflector 130. After being reflected by the first reflector 130, the transmitted light passes through the first filter 120 again and is focused by the focusing lens group 160 to be imaged by the detector 170. 2The second optical filter 140 is then reflected by the second reflector 150, passes through the second filter 140 again, is focused by the same focusing lens group 160, and is finally imaged by the same detector 170. That is, the two beams of light split by the spectroscope 110 pass through two wavelength filters respectively and emit two beams of light with different intensities. The two beams of light then pass through the same focusing lens group and are transmitted to the detector 170 to obtain two molten pool images (i.e., a dual-wavelength molten pool image). Then, the image processing unit 180 is used to obtain the molten pool temperature field based on the dual-wavelength molten pool image, including calculating the center deviation of the two images through an adaptive threshold dynamic matching algorithm and correcting them to overlap, and obtaining the molten pool temperature field based on a dual-wavelength colorimetric temperature calculation method.

[0074] The melt pool temperature online monitoring system designed by the present invention is compact and easy to integrate. The reflector can flexibly adjust the angle to meet the melt pool temperature field monitoring requirements of different LPBF equipment. In the present invention, the melt pool radiation light is divided into two beams by the spectroscope 110, and both light beams are filtered twice. For example, one of the light beams is reflected by the first filter 120 and filtered once to obtain a wavelength λ 1 The wavelength of the optical signal is λ due to the error of the filter itself. 1 The optical signal is doped with a small amount of stray light of other wavelengths, which brings a large error to the temperature detection of the molten pool. 1 The molten pool optical signal is reflected by the first reflector 130 and then passes through the first filter 120 for secondary filtering, which can effectively filter out the interference of stray wavelengths. Similarly, the wavelength λ 2 Secondary filtering is performed to improve the accuracy of molten pool temperature detection.

[0075] (2) Dual-wavelength colorimetric temperature calculation method.

[0076] The dual-wavelength colorimetric temperature calculation method uses the Wien approximation formula to calculate Planck's law to determine the intensity of the object to be measured:

[0077]

[0078] Where L(λ,T) represents the brightness at wavelength λ and temperature T, h represents Planck's constant, c represents the speed of light, and k represents the speed of light. B represents the Boltzmann constant; ε represents the emissivity, which is used to describe the degree to which an object emits thermal radiation relative to an ideal black body, and its value is between 0 and 1.

[0079] Wavelength 1 and wavelength λ 2The emissivity is close to that of the detector. The grayscale value detected by the detector at wavelength λ and temperature T is G(λ,T), and it is assumed that G(λ,T)=R(λ)L(λ,T), where R(λ) represents the amplification constant that needs to be calibrated. The temperature can be solved by the grayscale ratio of the detector at two wavelengths:

[0080]

[0081] Among them, C 1 =2hc 2 , C 2 =1.44×10 -2 m.K.

[0082] Where R(λ) is the detector response to wavelength λ, w = G(λ 1 ,T) / G(λ 2 ,T), k=R(λ 2 ) / R(λ 1 ). w is defined as the relationship coefficient between gray values ​​under dual-wavelength radiation, and the coefficient k is a constant.

[0083] In summary, firstly, the matching alignment G(λ 1 ,T) and G(λ 2 ,T), and then the coefficient k is obtained through blackbody furnace calibration, and finally the distribution of the molten pool temperature field is obtained.

[0084] The calibration of the blackbody furnace is as follows: Set the blackbody furnace to T i (i=1,2,…n), record w at each temperature, and based on formula (3), convert multiple T i And k can be obtained by linear fitting.

[0085] (3) Sub-pixel adaptive threshold dynamic online matching algorithm.

[0086] The present invention designs a dynamic online matching method for the center position of a molten pool image with an adaptive threshold. The framework of the method is as follows: Figure 3 Shown. First, the two images are obtained by roughly segmenting the double-wavelength melt pool images in a single image, and then the adaptive threshold dynamic online matching algorithm is used to match the center positions of the two images after segmentation. The following details will be explained.

[0087] (3.1) The dual-wavelength image is segmented using the prior adaptive threshold method.

[0088] See also Figure 3As shown in (a) in the figure, the dual-wavelength image of the molten pool collected by the online monitoring system of the molten pool temperature shown in the left image of the first row is binarized according to the automatically calculated threshold value to obtain its binary image, and then the boundary position on the molten pool image is determined ( Figure 3 The left and right boundaries are shown in the middle, see the right image in the first row), and then the two images of the melt pool and their corresponding two binary images are extracted through the region of interest (ROI) according to the prior size of the melt pool (see the images in the second row).

[0089] (3.2) Iterative dual-wavelength melt pool image dynamic matching

[0090] See also Figure 3 As shown in (b), based on the preliminary segmented dual-wavelength image of the melt pool, the present invention designs an iterative method for dual-wavelength image matching and alignment, which is defined as follows:

[0091]

[0092] In formula (4), T li , B li , R li and L li represents the upper, lower, left, and right boundary positions of the left image of the i-th iteration, and T ri , B ri , R ri and L ri Indicates the upper, lower, left, and right boundary positions in the right image. ci and R ci represents the center position of the left and right images calculated in the i-th iteration, n represents the number of iterations, and Figure 3 Take the binary image shown on the right side of the second row of (a) as an example. In the first iteration, the upper, lower, left, and right boundaries of the left image of the melt pool are marked as T l1 , B l1 , L l1 , R l1 , the center position L of the first iteration is obtained by calculating the average value c1 Similarly, the center position R of the right image in the first iteration can be obtained c1 According to the center position of the left and right images of the melt pool, the offset T of the center of the dual-wavelength image of the first iteration is obtained. d1 However, the center offset calculated in a single pass is susceptible to image boundary noise and thus produces matching errors.

[0093] In order to solve the problem of large matching error in a single calculation, an iterative method is designed in the present invention. In order to highlight the boundary, it is assumed that the boundary of the dual-wavelength image is set to 1 and other areas are set to 0. The upper, lower, left and right boundary indexes marked in the first iteration are set to 0, and the calculation is repeated to obtain the center offset T of the molten pool dual-wavelength image of the second iteration. d2 By iterating n times continuously, n center offsets T can be obtained. dn , calculate the average of n center offsets to obtain the final offset T d , thereby achieving dual-wavelength image matching and alignment of the molten pool.

[0094] like Figure 4 As shown in (a), during the coaxial LPBF manufacturing process, when calculating the molten pool temperature based on the dual-wavelength colorimetry theory, the relative distance between the centers of the dual-wavelength images changes dynamically. Figure 4 (a) in the figure shows the center distance of the dual-wavelength image in the vertical and horizontal directions. It can be observed that the vertical distance variation (i.e., column error) of the center distance of the melt pool is relatively small, while the horizontal distance fluctuation (i.e., row error) is large, and the traditional static matching method will cause a large error.

[0095] In order to quantitatively prove the accuracy, the present invention measures the center offset error after the molten pool image is matched. Figure 4 (b) in the figure shows the offset error range. Specifically, Figure 4 The upper part of (b) shows the matched dual-wavelength melt pool profile image. Figure 4 The two bottom rows of (b) are matched molten pool dual-wavelength images and binary images, where the two images are superimposed pixel by pixel. By zooming in, it can be seen that the molten pool dual-wavelength image and the binary image in the present invention achieve sub-pixel matching.

[0096] In summary, the present invention has significant advantages in monitoring the molten pool temperature field. Unlike the traditional method that requires the dual-wavelength center position to be calibrated in advance and static matching, the static matching method is difficult to achieve stable and accurate molten pool image matching during a long processing process. Therefore, the present invention innovatively proposes an adaptive threshold dynamic online matching algorithm. The algorithm can dynamically adjust the matching threshold according to the real-time image data, realize sub-pixel-level precise online matching of the pixel position of the molten pool dual-wavelength image, and extract the dual-wavelength intensity information of each pixel point. This dynamic matching method effectively overcomes the limitations of static matching, significantly improves the accuracy and real-time performance of temperature field monitoring, and provides reliable support for subsequent high-precision temperature reconstruction.

[0097] (4) Calibration of dual-wavelength imaging of the molten pool temperature online monitoring system.

[0098] In coaxial systems such as LPBF, the field mirror and the galvanometer are coated with a special thin film layer to achieve efficient AM, but this may cause aberrations to the imaging system in the visible light range. If there is no field mirror and galvanometer in the system, that is, in the non-coaxial case, no aberration will occur, but when the two wavelength radiations maintain the same processing distance, for the system with a field mirror and a galvanometer, that is, in the coaxial case, the dual-wavelength radiation image may appear blurred to varying degrees. In addition, according to formula (3), k is usually obtained by non-coaxial calibration using a blackbody furnace, and when the molten pool temperature online monitoring system provided by the present invention is used in conjunction with a coaxial system, the beam splitting ratio of the coaxial system and the non-coaxial system cannot be kept consistent after calibration, resulting in the k obtained by the non-coaxial method cannot be directly used for coaxial measurement of the molten pool temperature.

[0099] In order to solve the problem that the field mirror and galvanometer in the coaxial system such as LPBF will increase the error of the dual-wavelength intensity collected by the dual-wavelength temperature measurement system, resulting in an increase in the temperature measurement error, the present invention performs coaxial calibration and obtains a calibration formula. The present invention uses a halogen lamp to calibrate the dual-wavelength intensity of the coaxial system and derives a dual-wavelength temperature measurement calibration formula applicable to the coaxial system. For details, see Figure 5 , a broadband light source with a wavelength radiation range similar to that of the molten pool is used to calibrate the dual-wavelength radiation intensity of the non-coaxial (reference) optical path system and the coaxial test optical path system. In the embodiment, in the coaxial device, the present invention collects the λ reflected by the reflector at the same working distance. 1 and λ 2 The light signal is captured by the system to show white images of different brightness. Based on the white images, the ratio of the dual wavelengths of the non-coaxial and coaxial systems is obtained respectively. Let the dual wavelength white image of the coaxial system be g c (λ 1 ) and g c (λ 2 ), g for non-coaxial systems c '(λ 1 ) and g c '(λ 2 ). The dual-wavelength intensity ratio of the non-coaxial and coaxial systems can be obtained:

[0100]

[0101] Therefore, it can be defined that: w′=wAm′ / m, where A represents the calibration coefficient of the beam splitter. According to formula (3) and formula (5), in non-coaxial and coaxial systems, the dual-wavelength temperature measurement formula can be rewritten as formula (6) and formula (7) respectively.

[0102]

[0103] Among them, T a and T coThey represent the temperatures in the paraxial (i.e. non-coaxial) optical path test system and the coaxial test optical path system respectively.

[0104] For example, Figure 5 As shown, the present invention selects filters with central wavelengths of 550nm and 630nm to perform coaxial system calibration and molten pool temperature measurement.

[0105] In summary, the present invention proposes a dual-wavelength calibration method for a coaxial system, which can avoid the use of additional hardware for calibration, reduce the complexity and cost of calibration, and further improve the temperature measurement accuracy of the molten pool of the coaxial system.

[0106] Finally, a dual-wavelength image is obtained through a blackbody furnace, and the accuracy of the molten pool temperature online monitoring system provided by the present invention is verified by comparing the difference between the measured temperature field and the set temperature. r Analysis of the accuracy of the molten pool temperature online monitoring system:

[0107]

[0108] Among them, T m represents the temperature measured by the online monitoring system of the molten pool temperature, T t Indicates the actual temperature of the blackbody furnace.

[0109] Specifically, Figure 6 As shown, the present invention collects black body furnace images with wavelengths of 550nm and 630nm at a temperature of 3273.15K, and takes the maximum inscribed square area of ​​200pixels×200pixels from the image, totaling 40,000 pixels. In 40,000 pixels, the minimum relative error of the molten pool temperature online monitoring system is 0.17%, the average relative error is 1.26%, and the maximum relative error is 2.34%, and the coaxial online monitoring of the molten pool temperature field is realized on the LPBF equipment. The above data show that the molten pool temperature online monitoring system proposed by the present invention has good accuracy.

[0110] In addition, the present invention also uses high melting point alloy as an example to monitor the temperature field, and analyzes the molten pool temperature distribution and molten pool size changes to further verify the accuracy of the molten pool temperature online monitoring system proposed by the present invention.

[0111] Specifically, the molten pool temperature online monitoring system provided by the present invention is used to monitor the temperature of the high melting point alloy in the LPBF manufacturing process. Figure 7 From left to right in the figure are the molten pool temperature field distribution sequences with a molten pool interval of 30ms, where the horizontal axis represents the molten pool width and the vertical axis represents the molten pool length, both in μm. This result shows that the temperature is consistent with the laser scanning direction, indicating that the present invention can achieve high-precision online monitoring of the molten pool temperature field.

[0112] Finally, it should be noted that the above specific implementation methods are only used to illustrate the technical solution of the present invention rather than to limit it. Although the present invention has been described in detail with reference to examples, those skilled in the art should understand that the technical solution of the present invention can be modified or replaced by equivalents without departing from the spirit and scope of the technical solution of the present invention, which should be included in the scope of the claims of the present invention.

Claims

1. A method for online monitoring of molten pool temperature during laser additive manufacturing, characterized in that: The following steps are involved: A spectroscope is used to split the molten pool optical signal into a first light beam and a second light beam of equal intensity; the first light beam passes through a first filter and reaches a first reflector, and then passes through the first filter again after being reflected by the first reflector, and is imaged by a detector; the second light beam passes through a second filter and reaches a second reflector, and then passes through the second filter again after being reflected by the second reflector, and is imaged by the detector; the first filter and the second filter have different central wavelengths, and the detector obtains a dual-wavelength molten pool image; An image processing unit is used to obtain a molten pool temperature field based on the dual-wavelength molten pool image.

2. The method for online monitoring of molten pool temperature during laser additive manufacturing according to claim 1, characterized in that: The dual-wavelength molten pool image is preliminarily segmented by the image processing unit, and the first molten pool image and the second molten pool image obtained after the preliminarily segmented image are matched and aligned; the first molten pool image corresponds to the first light beam, and the second molten pool image corresponds to the second light beam; After matching and alignment, the image processing unit calculates the temperature of the molten pool using a dual-wavelength colorimetric temperature measurement formula.

3. The method for online monitoring of molten pool temperature during laser additive manufacturing according to claim 2, characterized in that: The preliminary segmentation of the dual-wavelength melt pool image by the image processing unit includes the following sub-steps: Binarization is performed on the dual-wavelength molten pool image using an adaptive threshold binarization method, and molten pool boundary position information is obtained based on a binary image corresponding to the dual-wavelength molten pool image; According to the molten pool boundary position information and the prior size information of the molten pool, the first molten pool image and its binary image, and the second molten pool image and its binary image are obtained by region of interest extraction.

4. The method for online monitoring of molten pool temperature during laser additive manufacturing according to claim 3, characterized in that: Matching and aligning the first molten pool image and the second molten pool image includes the following sub-steps: According to the molten pool boundary position information, the center position of the i-th iteration of the first molten pool image and the center position of the i-th iteration of the second molten pool image are calculated; wherein i=1, 2, ..., n; n is the set number of iterations; According to the center position of the first molten pool image at the i-th iteration and the center position of the second molten pool image at the i-th iteration, a center offset value of the two images at the i-th iteration is calculated; After completing n iterations, calculate the average of the n center offset values ​​to get the final offset value; Correction is performed based on the final offset value to align the two images.

5. The method for online monitoring of molten pool temperature during laser additive manufacturing according to claim 2, characterized in that: The molten pool optical signal comes from a coaxial test optical path system.

6. The method for online monitoring of molten pool temperature during laser additive manufacturing according to claim 5, characterized in that: The dual-wavelength colorimetric temperature measurement formula is as follows: k=R(λ2) / R(λ1) Where, T co is the temperature of the molten pool under the coaxial test optical path system, C2 is the second radiation constant, λ1 is the central wavelength of the first filter, λ2 is the central wavelength of the second filter, w′ is the relationship coefficient between the grayscale values ​​under dual-wavelength radiation after coaxial calibration, R(λ1) is the response of the detector to the wavelength λ1, R(λ2) is the response of the detector to the wavelength λ2, and k is the coefficient obtained by non-coaxial calibration of the blackbody furnace.

7. The method for online monitoring of molten pool temperature during laser additive manufacturing according to claim 6, characterized in that: The relationship coefficient w′ between the grayscale values ​​under the dual-wavelength radiation after the coaxial calibration is obtained by the following formula: w′=wAm′ / m Wherein, w is the relationship coefficient between the grayscale values ​​under dual-wavelength radiation before coaxial calibration, A is the calibration coefficient of the beam splitter in the non-coaxial test optical path system, m′ is the intensity ratio of the dual wavelengths under the non-coaxial test optical path system, m is the intensity ratio of the dual wavelengths under the coaxial test optical path system, and g′ is c (λ1) is the white image corresponding to wavelength λ1 in the non-coaxial test optical path system, g′ c (λ2) is the white image corresponding to wavelength λ2 in the non-coaxial test optical path system, g c (λ1) is the white image corresponding to wavelength λ1 under the coaxial test optical path system, g c (λ2) is the white image corresponding to wavelength λ2 in the coaxial test optical system.

8. An online monitoring system for molten pool temperature during laser additive manufacturing, characterized in that: include: A spectroscope, a first filter, a first reflector, a second filter, a second reflector, a detector, and an image processing unit; The system for online monitoring of molten pool temperature during laser additive manufacturing is used to perform the steps in the method for online monitoring of molten pool temperature during laser additive manufacturing as claimed in any one of claims 1 to 7.

9. The online monitoring system for molten pool temperature in laser additive manufacturing process according to claim 8, characterized in that: Also includes: Focusing lens group; Before the two beams of light are incident on the detector, they are both focused by the focusing lens group.

10. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein: When the processor executes the program, the method for online monitoring of molten pool temperature in a laser additive manufacturing process according to any one of claims 1 to 7 is implemented.

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