Array heat flux lateral heat flux diffusion suppression device and method based on feature iteration

Abstract

The application provides a feature iteration-based array heat flow transverse heat flow diffusion suppression device and method, belongs to the technical field of nondestructive testing, and solves the problem of transverse heat flow diffusion in current active infrared thermal wave imaging detection, wherein the suppression device comprises a computer, a USB data line, a data acquisition card, a first BNC data line, a laser power supply, a laser power supply line, a TEC refrigeration device power supply line, a laser, a TEC refrigeration device, a fiber bundle, a collimating mirror, a first polarizer, a sample, a clamping frame, a moving table, a movement driving line, a moving table controller, a movement control line, a filter, a first fixed support, a second polarizer, a second fixed support, a magnetic force seat, an infrared thermal imager, an Ethernet line, a second BNC data line, a third fixed support, a fourth fixed support, a third BNC data line, and a temperature control feedback system.

Description

Technical Field

[0001] The invention relates to an array heat flow lateral heat flow diffusion suppression device and method based on feature iteration, belonging to the technical field of non-destructive testing. Background Art

[0002] Composite materials, with their excellent mechanical properties, corrosion resistance, and high specific strength, have been widely used in the automotive industry, aerospace, medical devices, shipbuilding, power electronics, and other fields, becoming an important material choice in the manufacture of key components. However, during the manufacturing, processing, and actual use of composite materials, internal defects such as delamination, bubbles, and cracks are very easy to occur. These defects can significantly weaken the structural integrity and mechanical properties of the material, thus seriously affecting its service life and may even lead to system-level failures and safety hazards. Therefore, accurately identifying and quantifying potential defects in composite materials is crucial to ensuring their reliability in demanding applications.

[0003] Traditional non-destructive testing methods, such as ultrasonic testing and radiographic testing, have been widely used to detect internal defects in materials, but they still have significant limitations in the non-destructive testing of composite materials. Ultrasonic testing has a certain sensitivity in detecting delamination defects, but its ability to identify tiny bubbles and cracks is insufficient, and it is easily affected by the complexity of the material structure, resulting in reduced detection signal resolution; radiographic testing relies on high-energy rays to penetrate the material, but it often has difficulty achieving ideal imaging resolution when testing thicker or complex composite materials. In addition, radiographic testing has high requirements for the operating environment and poses radiation safety risks. Therefore, in the field of non-destructive testing of complex composite materials, the detection sensitivity and resolution of traditional methods are difficult to meet the current high-precision detection needs. There is an urgent need to explore new and more sensitive detection technologies to achieve accurate identification and reliable assessment of internal defects in composite materials.

[0004] As a cutting-edge nondestructive testing method, infrared thermal imaging technology, with its efficient, non-contact detection method, has become a powerful supplement to traditional ultrasonic and radiographic testing. Unlike these traditional detection methods, infrared thermal imaging technology captures the material's response to thermal stimulation, enabling rapid, non-invasive detection of internal defects. It offers the advantages of high sensitivity and superior resolution. Active infrared thermal imaging technology, in particular, applies external thermal stimulation to guide heat propagation within the material, effectively identifying thermal conductivity anomalies caused by internal defects. This principle makes it suitable for inspecting the internal structure of a variety of materials, particularly for defect assessment in complex structures or heterogeneous materials.

[0005] Under thermal stimulation, internal defects in materials, such as cracks, delamination, and bubbles, can disrupt the heat transfer process due to their different thermal conductivity from the surrounding materials, forming abnormal heat flow paths and temperature gradients. These defective areas can cause significant differences in the temperature distribution on the surface of an object. Infrared thermal imagers can capture and record these tiny temperature changes in real time, revealing defect information within the object being tested through temperature distribution image analysis and defect feature extraction. Compared to traditional methods, infrared thermal wave imaging detection technology can complete detection in a shorter time and maintain high detection accuracy for shallow surface defects, thus showing significant advantages in meeting the needs of precise detection and large-area inspection.

[0006] However, traditional active infrared thermal imaging inspection technology currently relies primarily on surface-source heat flux excitation. The inevitable lateral heat flux diffusion phenomenon presents a bottleneck in the accurate detection of material defects using infrared thermal imaging. This lateral heat flux diffusion affects the clarity of the edge areas of defect features and blurs the identification of defect boundaries, thereby reducing image resolution and detection boundary accuracy, leading to a significant decrease in the measurement accuracy of defect morphology. The impact of lateral heat flux diffusion is particularly prominent in the inspection of large-scale, complex composite materials. Heat flux diffusion in complex material structures not only produces "artifacts" around the defect area, interfering with the accurate identification of defect boundaries, but also makes deeper defects difficult to distinguish from background areas. To achieve higher resolution and higher precision defect detection, it is urgent to develop new excitation and detection methods that can suppress lateral heat flux diffusion. This will ensure that infrared thermal imaging technology is suitable for nondestructive inspection of complex and large-scale composite materials, thereby improving the recognition and morphological identification of internal defects.

[0007] To address the problem of heat diffusion, the similarity optical flow method has been proposed as a novel heat diffusion suppression method. This method analyzes the gradient diffusion behavior of heat flow within a material to counteract the interference of lateral heat diffusion effects on detection results. However, the accuracy of similarity optical flow methods is easily affected by factors such as noise and the complexity of the material's internal structure, resulting in insufficient robustness in signal interpretation. Consequently, when detecting small or complex defects, these methods still have limited resolution accuracy and are unable to fully recover the true size and shape of the defects. With the widespread application of composite materials in aerospace, automotive, and high-end manufacturing, the requirements for detection technology are also increasing. The shortcomings of traditional active infrared thermal imaging technology in suppressing lateral heat diffusion have gradually become a technical obstacle to achieving high-precision detection. In high-end manufacturing, the increasing complexity and size diversity of material components require detection methods that not only have higher accuracy and reliability, but also adapt to the precise detection of various defect morphologies. Therefore, further development of new methods that can effectively suppress lateral heat diffusion is urgently needed to overcome the limitations of traditional infrared thermal imaging technology and meet the future demand for higher-precision and more complex defect morphology detection. Summary of the Invention

[0008] The present invention aims to solve the problem of lateral heat flow diffusion in current active infrared thermal wave imaging detection, and further proposes an array heat flow lateral heat flow diffusion suppression device and method based on feature iteration, wherein the diffusion suppression device includes:

[0009] Computer (1), USB data cable (2), data acquisition card (3), first BNC data cable (4), laser power supply (5), laser power cable (6), TEC cooler power cable (7), laser (8), TEC cooler (9), optical fiber bundle (10), collimator (11), first polarizer (12), sample (13), clamping frame (14), mobile stage (15), motion drive line (16), mobile stage controller (17), motion control line (18), filter (19), first fixed support (20), second polarizer (21), second fixed support (22), magnetic base (23), infrared thermal imager (24), Ethernet cable (25), second BNC data cable (26), third fixed support (27), fourth fixed support (28), third BNC data cable (29) and temperature control feedback system (30);

[0010] The computer (1) is provided with three signal output terminals, wherein the first signal output terminal of the computer is connected to the signal input terminal of the data acquisition card (3) via a USB data cable (2), the second signal output terminal of the computer is connected to the signal output terminal of the infrared thermal imager (24) via an Ethernet cable (25), and the third signal output terminal of the computer is connected to the signal input terminal of the mobile station controller (17) via a motion drive cable (16).

[0011] Preferably, the data acquisition card (3) is provided with two signal output terminals, the first signal output terminal of the data acquisition card being connected to the input terminal of the laser power supply (5) via a first BNC data line (4), and the second signal output terminal of the data acquisition card being connected to the signal input terminal of the infrared thermal imager (24) via a second BNC data line (26).

[0012] Preferably, the output end of the laser power supply (5) is connected to the laser (8) via a laser power line (6), the output end of the laser (8) is connected to the collimator (11) via an optical fiber bundle (10), the collimator (11) is fixed on a fourth fixed support (28), and the signal input end of the TEC cooler (9) is connected to the temperature control feedback system (30) via a third BNC data line (29).

[0013] Preferably, the first polarizer (12) is fixed on the third fixed support (27), the sample (13) is fixed on the clamping frame (14), the clamping frame (14) is placed on the moving platform (15), the moving platform (15) is connected to the moving platform controller (17) through the motion drive line (16), and the infrared thermal imager (24) is fixed on the magnetic base (23).

[0014] Preferably, the filter (19) is fixed on the first fixed support (20), and the second polarizer (21) is fixed on the second fixed support (22), and the infrared heat radiation signal radiated by the sample (13) is transmitted to the infrared thermal imager (24) through the filter (19) and the second polarizer (21).

[0015] Preferably, the lasers (8) are arranged in a 7×7 matrix, all laser beams are Gaussian light sources, and the lasers (8) are controlled by transmitting analog signals via the data acquisition card (3).

[0016] The method for suppressing lateral heat flow diffusion of array heat flow based on feature iteration includes:

[0017] Step 1: Fix the sample (13) on the clamping frame (14), turn on the computer (1), data acquisition card (3), laser power supply (5), TEC cooler (9) and temperature control feedback system (30), and set the operating temperature of the laser power supply (5) to 25°C;

[0018] Step 2: Turn on the infrared thermal imager (24), adjust the magnetic base (23), the first fixed support (20) and the second fixed support (22), and confirm that the imaging field of view of the infrared thermal imager (24) can completely cover the sample;

[0019] Step 3: emitting an analog signal through the data acquisition card (3) to turn on the array laser (8) to irradiate the sample (13), and adjusting the positions of the third fixed support (27) and the fourth fixed support (28) so that the spacing and size of the array light spots irradiated to the sample (13) meet the preset range;

[0020] Step 4: Use a dual-channel digital orthogonal demodulation algorithm based on feature iteration to extract the sample defect features and obtain the laser point excitation amplitude and phase after iteration;

[0021] Step 5: Repeat steps 3-4 according to the laser spot excitation amplitude and phase after iteration until a defect feature phase map based on feature iteration is obtained to achieve defect feature extraction;

[0022] Step 6: After the defect feature extraction is completed, turn off the computer (1), data acquisition card (3), laser power supply (5), TEC cooler (9), temperature control feedback system (30), infrared thermal imager (24), data acquisition card (3) and laser (8).

[0023] Preferably, the excitation intensity expression of a single laser beam of the laser (8) in step 3 is:

[0024]

[0025] In formula (1), I(i,j,t) is the laser intensity, i,j=1,2,…,7, I max is the peak light intensity, I max =1000W / m 2 , f is the excitation frequency, f = 0.05Hz.

[0026] Preferably, the expression of the two-way digital orthogonal demodulation algorithm based on feature iteration in step 4 is:

[0027]

[0028] Ph ex,k+1 =Ph ex,k -Ph meas,k

[0029]

[0030] In formula (2)-formula (6), F n (x, y) is the thermal wave signal image, N is the number of frames, Am is the characteristic amplitude, Ph is the characteristic phase, Am ex,k+1 is the laser point excitation amplitude after iteration, Ph ex,k+1 is the laser point excitation phase after iteration, Amp ex,k+1 is the laser point excitation amplitude before iteration, is the laser spot excitation phase before iteration, Ammeas,k is the characteristic amplitude of the central pixel of the laser point excitation in the amplitude characteristic map, Ph meas,k is the characteristic phase value of the central pixel excited by the laser point in the phase characteristic map.

[0031] The beneficial effects of the present invention are:

[0032] 1. Compared with traditional active infrared thermal wave imaging detection technology, this invention can effectively suppress lateral heat flow diffusion and improve the accuracy of material defect morphology feature extraction, especially for the precise and efficient detection of shallow surface defects (<5mm, diameter / depth ratio >1.5) in composite materials;

[0033] 2. The lateral heat flux diffusion suppression device designed in the present invention uses an array laser to actively excite the sample, and realizes excitation parameter regulation through the iteration of excitation phase characteristics, thereby suppressing the lateral heat flux diffusion, so that the defect morphology feature extraction deviation is controlled within 3%. BRIEF DESCRIPTION OF THE DRAWINGS

[0034] Figure 1 This is a schematic diagram of the structure of the array heat flow lateral heat flow diffusion suppression device based on feature iteration provided by the present invention. Figure 1 Among them, 1-computer, 2-USB data cable, 3-data acquisition card, 4-first BNC data cable, 5-laser power supply, 6-laser power cable, 7-TEC cooler power cable, 8-laser, 9-TEC cooler, 10-fiber bundle, 11-collimator, 12-first polarizer, 13-sample, 14-clamping frame, 15-moving stage, 16-motion drive cable, 17-moving stage controller, 18-motion control cable, 19-filter, 20-first fixed support, 21-second polarizer, 22-second fixed support, 23-magnetic base, 24-infrared thermal imager, 25-Ethernet cable, 26-second BNC data cable, 27-third fixed support, 28-fourth fixed support, 29-third BNC data cable, 30-temperature control feedback system.

[0035] Figure 2 A flow chart of the method for suppressing lateral heat flow diffusion of array heat flow based on feature iteration provided by the present invention;

[0036] Figure 3 Schematic diagram of the experimental results of the array heat flow lateral heat flow diffusion suppression based on feature iteration provided by the present invention. DETAILED DESCRIPTION

[0037] Specific implementation method 1: Combination Figure 1 This embodiment is described as follows. Figure 1As shown, the structure of the array heat flow transverse heat flow diffusion suppression device based on feature iteration in the embodiment includes: 1-computer, 2-USB data line, 3-data acquisition card, 4-first BNC data line, 5-laser power supply, 6-laser power supply line, 7-TEC refrigeration power supply line, 8-laser, 9-TEC refrigeration, 10-fiber bundle, 11-collimating mirror, 12-first polarizer, 13-sample, 14-clamping frame, 15-moving table, 16-motion drive line, 17-moving table controller, 18-motion control line, 19-filter, 20-first fixed support, 21-second polarizer, 22-second fixed support, 23-magnetic base, 24-infrared thermal imager, 25-Ethernet cable, 26-second BNC data line, 27-third fixed support, 28-fourth fixed support, 29-third BNC data line, 30-temperature control feedback system, wherein the 8-laser is arranged in a 7x7 matrix, all laser beams are Gaussian light sources, and the 8-laser is controlled by the 3-data acquisition card to emit analog signals.

[0038] The transverse heat flow diffusion suppression device designed in the embodiment uses array laser to actively excite the sample, realizes excitation parameter regulation through excitation phase feature iteration, and further suppresses transverse heat flow diffusion, so that the defect topography feature extraction deviation is controlled within 3%.

[0039] 1-computer is provided with three signal output ends, the first signal output end of the computer is connected with the signal input end of the 3-data acquisition card through the 2-USB data line, the 3-data acquisition card is provided with two signal output ends, the first signal output end of the data acquisition card is connected with the input end of the 5-laser power supply through the 4-first BNC data line, the output end of the 5-laser power supply is connected with the 8-laser through the 6-laser power supply line, the output end of the 8-laser is connected with the 11-collimating mirror through the 10-fiber bundle, the 11-collimating mirror is fixed on the 28-fourth fixed support, the signal input end of the 9-TEC refrigeration is connected with the 30-temperature control feedback system through the 29-third BNC data line, and the second signal output end of the data acquisition card is connected with the signal input end of the 24-infrared thermal imager through the 26-second BNC data line.

[0040] The second signal output end of the computer is connected with the signal output end of the 24-infrared thermal imager through the 25-Ethernet cable, the 12-first polarizer is fixed on the 27-third fixed support, the 13-sample is fixed on the 14-clamping frame, the 14-clamping frame is placed on the 15-moving table, the 15-moving table is connected with the 17-moving table controller through the 16-motion drive line, and the 24-infrared thermal imager is fixed on the 23-magnetic base.

[0041] The third signal output terminal of the computer is connected to the signal input terminal of the mobile stage controller 17 through the motion drive line 16, the first polarizer 12 is fixed on the third fixed support 27, the sample 13 is fixed on the clamping frame 14, the clamping frame 14 is placed on the mobile stage 15, the mobile stage 15 is connected to the mobile stage controller 17 through the motion drive line 16, and the infrared thermal imager 24 is fixed on the magnetic base 23.

[0042] Specific implementation method 2: Combination Figure 2 and Figure 3 This embodiment is described as follows. Figure 2 As shown, the method for suppressing lateral heat flow diffusion of an array heat flow based on feature iteration in this embodiment includes the following steps:

[0043] S1: Fix the sample 13 on the clamping frame 14, turn on the computer 1, data acquisition card 3, laser power supply 5, TEC cooler 9 and temperature control feedback system 30, set the operating temperature of the laser power supply 5 to 25℃ to ensure the normal operation of the laser;

[0044] S2: Turn on the infrared thermal imager 24, adjust the magnetic base 23, the first fixed support 20 and the second fixed support 22, and confirm that the imaging field of view of the infrared thermal imager 24 can completely cover the sample;

[0045] S3: emitting an analog signal through the data acquisition card 3 to start the array 8-laser to irradiate the sample 13, and adjusting the positions of the third fixed support 27 and the fourth fixed support 28 so that the array spot spacing and size irradiated to the sample 13 are within the preset range;

[0046] The excitation intensity expression of a single laser beam of a laser is:

[0047]

[0048] In formula (1), I(i,j,t) is the laser intensity, i,j=1,2,…,7, I max is the peak light intensity, I max =1000W / m 2 , f is the excitation frequency, f = 0.05 Hz;

[0049] S4: A dual-channel digital quadrature demodulation algorithm based on feature iteration is used to extract the defect features of the sample and obtain the laser point excitation amplitude and phase after iteration;

[0050] The expression of the dual-path digital orthogonal demodulation algorithm based on feature iteration is:

[0051]

[0052] Phex,k+1 =Ph ex,k -Ph meas,k

[0053]

[0054] In formula (2)-formula (6), F n (x, y) is the thermal wave signal image, N is the number of frames, Am is the characteristic amplitude, Ph is the characteristic phase, Am ex,k+1 is the laser point excitation amplitude after iteration, Ph ex,k+1 is the laser point excitation phase after iteration, Amp ex,k+1 is the laser point excitation amplitude before iteration, is the laser spot excitation phase before iteration, Am meas,k is the characteristic amplitude of the central pixel of the laser point excitation in the amplitude characteristic map, Ph meas,k is the characteristic phase value of the central pixel excited by the laser point in the phase characteristic map;

[0055] S5: Repeat S3-S4 according to the laser point excitation amplitude and phase after iteration until the following is obtained: Figure 3 The defect feature phase diagram based on feature iteration is shown to realize defect feature extraction;

[0056] S7: After the defect feature extraction is completed, turn off 1-computer, 3-data acquisition card, 5-laser power supply, 9-TEC cooler, 30-temperature control feedback system, 24-infrared thermal imager, 3-data acquisition card and 8-laser.

[0057] In summary, compared with traditional active infrared thermal wave imaging detection technology, the present invention can effectively suppress the lateral diffusion of heat flow and improve the accuracy of extracting material defect morphology features, especially for the accurate and efficient detection of shallow surface defects of composite materials (<5mm, diameter / depth ratio>1.5).

[0058] The above description is merely a preferred embodiment of the present invention and does not constitute any form of limitation to the present invention. Although the present invention has been disclosed as a preferred embodiment as above, it is not intended to limit the present invention. Any technician familiar with the present profession can make some changes or modifications to equivalent embodiments of equivalent changes using the technical content disclosed above without departing from the scope of the technical solution of the present invention. However, any simple modification, equivalent replacement and improvement of the above embodiments made according to the technical essence of the present invention, within the spirit and principles of the present invention, without departing from the content of the technical solution of the present invention, shall still fall within the scope of protection of the technical solution of the present invention.

Claims

1. A method for suppressing lateral heat flow diffusion in array heat flow based on feature iteration, characterized in that: The device for applying the array heat flow lateral heat flow diffusion suppression method based on feature iteration includes: Computer (1), USB data cable (2), data acquisition card (3), first BNC data cable (4), laser power supply (5), laser power cable (6), TEC cooler power cable (7), array laser (8), TEC cooler (9), optical fiber bundle (10), collimator (11), first polarizer (12), sample (13), clamping frame (14), mobile stage (15), motion drive line (16), mobile stage controller (17), motion control line (18), filter (19), first fixed support (20), second polarizer (21), second fixed support (22), magnetic base (23), infrared thermal imager (24), Ethernet cable (25), second BNC data cable (26), third fixed support (27), fourth fixed support (28), third BNC data cable (29) and temperature control feedback system (30); The computer (1) is provided with three signal output terminals, wherein the first signal output terminal of the computer is connected to the signal input terminal of the data acquisition card (3) via a USB data cable (2), the second signal output terminal of the computer is connected to the signal output terminal of the infrared thermal imager (24) via an Ethernet cable (25), and the third signal output terminal of the computer is connected to the signal input terminal of the mobile station controller (17) via a motion drive cable (16); The method for suppressing lateral heat flow diffusion of an array heat flow based on feature iteration includes: Step 1: Fix the sample (13) on the clamping frame (14), turn on the computer (1), data acquisition card (3), laser power supply (5), TEC cooler (9) and temperature control feedback system (30), and set the operating temperature of the laser power supply (5) to 25°C; Step 2: Turn on the infrared thermal imager (24), adjust the magnetic base (23), the first fixed support (20) and the second fixed support (22), and confirm that the imaging field of view of the infrared thermal imager (24) can completely cover the sample; Step 3: emitting an analog signal through the data acquisition card (3) to turn on the array laser (8) to irradiate the sample (13), and adjusting the positions of the third fixed support (27) and the fourth fixed support (28) so that the spacing and size of the array light spots irradiated to the sample (13) meet the preset range; Step 4: Use a dual-channel digital orthogonal demodulation algorithm based on feature iteration to extract the sample defect features and obtain the laser point excitation amplitude and phase after iteration; Step 5: Repeat steps 3-4 according to the laser point excitation amplitude and phase after the iteration until a defect feature phase map based on feature iteration is obtained to achieve defect feature extraction; Step 6: After the defect feature extraction is completed, turn off the computer (1), data acquisition card (3), laser power supply (5), TEC cooler (9), temperature control feedback system (30), infrared thermal imager (24), data acquisition card (3) and array laser (8).

2. The method for suppressing lateral heat flow diffusion of array heat flow based on feature iteration according to claim 1, characterized in that: The data acquisition card (3) is provided with two signal output terminals, wherein the first signal output terminal of the data acquisition card is connected to the input terminal of the laser power supply (5) via a first BNC data line (4), and the second signal output terminal of the data acquisition card is connected to the signal input terminal of the infrared thermal imager (24) via a second BNC data line (26).

3. The method for suppressing lateral heat flow diffusion of an array heat flow based on feature iteration according to claim 1, characterized in that: The output end of the laser power supply (5) is connected to the array laser (8) via a laser power line (6), the output end of the array laser (8) is connected to the collimator (11) via an optical fiber bundle (10), the collimator (11) is fixed on a fourth fixed support (28), and the signal input end of the TEC cooler (9) is connected to the temperature control feedback system (30) via a third BNC data line (29).

4. The method for suppressing lateral heat flow diffusion of an array based on feature iteration according to claim 1, characterized in that: The first polarizer (12) is fixed on the third fixed support (27), the sample (13) is fixed on the clamping frame (14), the clamping frame (14) is placed on the moving table (15), the moving table (15) is connected to the moving table controller (17) through the motion drive line (16), and the infrared thermal imager (24) is fixed on the magnetic base (23).

5. The method for suppressing lateral heat flow diffusion of array heat flow based on feature iteration according to claim 1, characterized in that: The filter (19) is fixed on the first fixed support (20), and the second polarizer (21) is fixed on the second fixed support (22). The infrared heat radiation signal radiated by the sample (13) is transmitted to the infrared thermal imager (24) through the filter (19) and the second polarizer (21).

6. The method for suppressing lateral heat flow diffusion of an array based on feature iteration according to claim 1, characterized in that: The array laser (8) is arranged in a 7×7 matrix, and all laser beams are Gaussian light sources. The array laser (8) is controlled by transmitting analog signals through the data acquisition card (3).

7. The method for suppressing lateral heat flow diffusion of an array heat flow based on feature iteration according to claim 1, characterized in that: The excitation intensity expression of a single laser beam of the array laser (8) in step 3 is: （1）； In formula (1), I ( i , j , t ) is the laser intensity, i , j =1,2,…,7, I max is the peak light intensity, I max =1000W / m 2 , f is the excitation frequency, f =0.05Hz.

8. The method for suppressing lateral heat flow diffusion of an array based on feature iteration according to claim 1, characterized in that: The expression of the two-way digital orthogonal demodulation algorithm based on feature iteration in step 4 is: （2）； （3）； （4）； （5）； （6）； Formula (2)-Formula (6), F n ( x,y ) is the heat wave signal image, N is the number of frames, Am is the characteristic amplitude, Ph is the characteristic phase, Am ex,k+1 is the laser point excitation amplitude after iteration, Ph ex,k+1 is the laser point excitation phase after iteration, Amp ex,k+1 is the laser point excitation amplitude before iteration, φ ex,k+1 is the laser point excitation phase before iteration, Am meas,k is the characteristic amplitude of the central pixel of the laser point excitation in the amplitude characteristic map, Ph meas,k is the characteristic phase value of the central pixel excited by the laser point in the phase characteristic map.

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