Online detection method and system for etching quality of laser perovskite battery

Abstract

The invention discloses an on-line detection method and system for etching quality of a laser perovskite cell, and the method comprises the steps: employing a double-camera alternate working mode, installing high-resolution CCD camera assemblies at two sides of a laser processing head in an X direction, eliminating the shielding of a motion direction, carrying out the scribing quality analysis through combining the submicron optical imaging of the CCD camera assemblies with an image processing algorithm, and carrying out the detection of the etching quality of the laser perovskite cell. According to the method, local adaptive threshold segmentation is put forward, an Otsu method is used for adaptively calculating a binarization threshold, a morphological opening operation is used for removing irrelevant information, an edge searching logic algorithm is used for searching two edges of a scribed line, finally, the two edges and a center line are fitted, and scribed line quality analysis is carried out through the three lines. And real-time power adjustment, position calibration and defect position marking are carried out by detecting the scribing quality, the calculation speed of the high-resolution optical detection system is high, detection can be carried out while machining is carried out, and machining-detection-correction closed-loop control is achieved.

Description

Technical Field

[0001] The present invention relates to the technical field of laser scribing, and particularly relates to an on-line detection method and system for the etching quality of a laser perovskite battery. Background Art

[0002] Perovskite solar cells are a new type of photovoltaic technology based on perovskite-structured materials. In recent years, they have become a research hotspot in the energy field due to their high efficiency, low-cost potential, and flexible application scenarios. In the manufacturing of perovskite solar cells, the laser scribing technology (P1, P2, P3) is a key process for the modular tandem structure. Among them, the P1 scribing divides the bottom transparent conductive oxide (TCO, such as ITO or FTO) layer to form independent sub-cell regions. The continuous TCO layer is separated into multiple units, laying the foundation for the subsequent tandem structure. The technical difficulty is to precisely control the laser energy to ensure complete cutting of the TCO layer while avoiding damage to the substrate material (such as glass).

[0003] Existing laser etching equipment generally adopts the multi-optical-path parallel high-speed scribing technology to improve processing efficiency. The existing methods for detecting the effect of P1 scribing have problems such as lag in defect detection and missed detection of micron-level defects. Traditional electron microscopy (SEM) or electrical probe detection requires destructive sampling and takes several hours, and cannot provide real-time feedback on etching residues (such as uncut electrode layers or perovskite layers), resulting in the risk of batch rework. The thickness of the functional layer of perovskite batteries is only a few hundred nanometers, and sub-micron-level residues generated by incomplete etching (such as <1μm metal debris) exceed the resolution limit of conventional optical detection, leading to potential internal short-circuit hazards in the battery.

[0004] The patent document with publication number CN217739435U discloses a device for automatically detecting the P1 scribing effect of a perovskite battery assembly. The test sequence of the detection probe is that two rows of detection probes move horizontally along the length direction of the fixed frame, and test the resistance of the areas on both sides of the even and odd PI scribing lines respectively. It is simple, convenient and effective, and can automatically detect the resistance of the areas on both sides of each P1 scribing line, and automatically determine whether the front electrode is cut according to the resistance value. It is suitable for detecting the P1 scribing situation of any size of perovskite battery assembly formed by small battery modules in series or in parallel, filling the gap in the detection of the P1 scribing situation of perovskite batteries. The device can not only move horizontally, but also the fixed frame is connected to the drive device for transmission, and can also move longitudinally, so as to determine the regional position of the uncut point on the assembly by moving longitudinally and recording the change in resistance value. Although the above-mentioned probe resistance method fills the gap in perovskite battery P1 line detection, it still has the following defects: 1. The probe needs to be in direct contact with the surface of the perovskite battery, and the transparent electrode layer (such as ITO) is highly brittle and thin. Mechanical contact may cause surface scratches or electrode layer peeling, reducing battery efficiency. 2. It needs to drive the mobile mechanism to detect resistance line by line, which is inefficient and cannot match high-speed laser etching production lines. 3. The resistance method can only determine whether the line is electrically connected, but cannot detect defects such as debris, edge burrs, and line width deviation.

[0005] The patent document with the publication number CN112599638A discloses a laser line positioning system and method. The light emitted by the light source passes through the battery cell and enters the photosensitive identification device to obtain the position of the P1 etching line on the photosensitive identification device, and then calculates the relative position relationship between the position of the P1 etching line on the photosensitive identification device and the zero point to achieve the positioning of the laser line. This invention can replace manual experience. When laser etching P2 and P3 lines, the position of the line is identified according to the P1 line. The present invention can effectively reduce the line spacing, reduce the dead zone, and can judge the etching effect, adjust the etching parameters in time, avoid the problem of over-engraving and under-engraving, and improve the yield rate. However, the above-mentioned transmission light detection method realizes line positioning and over-engraving / under-engraving judgment through transmission light intensity and spectral analysis. Although it is superior to the traditional manual experience method in positioning accuracy and process adjustment, and has achieved automation breakthroughs in line positioning and basic process control, its transmission dependence, insufficient sensitivity, speed bottleneck and other defects limit its application in high-end perovskite mass production. Summary of the invention

[0006] In order to solve the technical problems existing in the above-mentioned background technology, the present invention provides a method and system for online detection of laser perovskite cell etching quality, which realizes non-contact, real-time detection of submicron defects through high-resolution optical imaging and image processing technology, and cooperates with laser etching equipment to form a "processing-detection-correction" closed-loop control to improve etching accuracy and efficiency.

[0007] To achieve the above object, the present invention adopts the following technical solutions: In a first aspect of the present invention, an on-line detection method for the etching quality of a laser perovskite battery is provided. A first CCD camera assembly and a second CCD camera assembly are respectively installed on the left and right sides of a laser processing head. The first CCD camera assembly and the second CCD camera assembly are respectively aligned with the first beam and the last beam emitted by the laser processing head; Turn on the first CCD camera assembly and the second CCD camera assembly, perform internal parameter calibration on the CCD camera assembly, establish the mapping relationship between the pixel coordinate system and the world coordinate system, and calculate the pixel equivalent, denoted as Scalar ; Drive the laser processing head to move in the positive X-axis direction, and at the same time turn on the laser to perform scribing on the workpiece; While the laser processing head is moving forward, synchronously start the first CCD camera assembly to collect images, transmit the images to the upper computer for real-time image processing, and obtain the quality analysis result, where the image collection and image processing are parallel processes; The upper computer adjusts the real-time power of the laser, compensates the scribing position, and records the coordinate of the workpiece defect position according to the quality analysis result; When the laser processing head reaches the end of the X-axis stroke, turn off the laser, drive the laser processing head to step forward a specified distance in the positive Y-axis direction, then move in the negative X-axis direction and restart the laser, and switch the synchronous trigger signal source to the second CCD camera assembly; While the laser processing head is moving in the reverse direction, synchronously trigger the second CCD camera assembly to collect images and repeat the above image processing process and real-time adjustment process; During the scribing process, as the laser processing head moves back and forth in the forward and reverse directions, the first CCD camera assembly and the second CCD camera assembly alternate in operation, and the dual-camera alternate working mode eliminates the field of view occlusion caused by the movement direction.

[0008] Further, since the laser energy is Gaussian distributed, when scribing the perovskite battery, defects such as the overall offset of the upper and lower two edges, the line width being too thin or too wide due to inaccurate laser power, and burrs on the scribing edge may occur. Therefore, the specific process of image processing for the images collected by the first CCD camera assembly and the second CCD camera assembly is as follows: Perform ROI extraction on the original image; then adaptively calculate the binarization threshold for the intercepted ROI image using the Otsu method to generate a binary image; use morphological opening operation to remove irrelevant information in the binary image; then use the edge finding logic algorithm to find the two black-and-white boundary edges of the scribing, fit out two edge lines and a middle line, a total of three lines; perform scribing quality analysis through these three lines to obtain the scribing quality analysis result.

[0009] Further, the intercepted ROI image is divided into several sub-regions using the local threshold segmentation method. The Otsu method is independently applied within each sub-region to calculate the local threshold, and finally, the global binarization result is generated through interpolation.

[0010] Further, the edge-finding logic algorithm is used to find the two black-and-white boundary edges of the engraved line. The specific process of fitting the two edge lines and a midline is as follows: (1) Traverse the first column, find the first white region after the first black region from top to bottom, and record the first pixel of this region as the starting point of the white region ; (2) Continue to find the first black region after this white region, and record the last pixel of this white region as the end point of the white region ; (3) Calculate the midpoint of the white region in this column, that is: ; (4) Repeat the above steps to obtain the upper-edge point set of the engraved line and the lower-edge point set of the engraved line , and obtain the midpoint set of the engraved line ; (5) Use the least squares method to perform linear fitting on the upper-edge point set of the engraved line , the lower-edge point set of the engraved line , and the midpoint set of the engraved line respectively, and fit two edge lines and a midline.

[0011] Further, the quality analysis of the engraved line is performed through these three lines. The specific process of obtaining the quality analysis result includes: calculating the difference between the actual width value between the two edge lines in the current real-time image and the set width value, and judging whether the real-time power of the laser is matched according to the size of the difference between the actual width value and the set width value.

[0012] Specifically, the calculation formula for the actual width value between the two edge lines is as follows: ; where and are the y coordinates of the upper edge and the lower edge of the engraved line in the i-th column respectively, Scalar is the pixel equivalent, N is the total number of columns in the current real-time image, and Width is the actual width value between the two edge lines in the current real-time image.

[0013] Further, for the line quality analysis using these three lines, the specific process of obtaining the quality analysis result further includes: calculating the Y-axis offset between the center line coordinates in the current real-time image and the reference center line coordinates, and determining whether to adjust the Y-axis position of the workpiece based on the Y-axis offset.

[0014] Specifically, the specific process of calculating the Y-axis offset between the center line coordinates in the current real-time image and the reference center line coordinates is as follows: Manually input or photograph the engraved line equation in the image coordinate system for calculating the reference theoretical path ; Real-time detect the center line coordinates of the engraved line ; Substitute the current coordinates into the engraved line equation , to obtain the theoretical image coordinates in the theoretical Y direction ; Calculate the Y-axis offset , and the formula is as follows: ; Where is the Y coordinate of the center point of the currently detected engraved line, is the theoretical image coordinate, Scalar is the pixel equivalent; When the Y-axis offset is greater than the set value, it indicates that the Y-axis position of the workpiece needs to compensate for the error.

[0015] Further, for the line quality analysis using these three lines, the specific process of obtaining the quality analysis result further includes: Calculate the slope difference between the two straight lines fitted by the two edge lines. If the slope difference is greater than the set threshold, it indicates that the engraved line is unqualified, and the actual workpiece defect position coordinates are calculated and recorded based on the image timestamp and the movement speed.

[0016] In the second aspect of the present invention, a laser perovskite battery etching quality on-line detection system for implementing the above on-line detection method is provided, including a laser processing head, a first CCD camera assembly, a second CCD camera assembly, a gantry, a workpiece, a machine tool, and a displacement platform; A displacement platform and a gantry are installed on the machine tool. A workpiece is placed on the displacement platform, and the displacement platform can drive the workpiece to move along the Y-axis direction. A laser processing head is installed on the gantry. An optical path formed by multiple optical devices is inside the laser processing head, and N light beams are emitted. The gantry can drive the laser processing head to move along the X-axis and Z-axis directions. First CCD camera components and second CCD camera components are respectively installed on both sides of the laser processing head along the X-axis direction. The first CCD camera component and the second CCD camera component are respectively aligned with the first light beam and the last light beam emitted by the laser processing head, so that the processed engraved lines can be photographed at all times when moving along the X-axis direction. And the CCD camera components are equipped with continuously variable magnification eyepieces and focusing objectives, so that the camera imaging can clearly photograph the width of a single laser etching line.

[0017] Compared with the prior art, the present invention has the following beneficial effects: (1) In the present invention, a dual-camera alternating working mode is adopted. High-resolution CCD camera components are installed on both sides of the laser processing head in the X direction to eliminate the occlusion in the moving direction. Cooperating with the motion mechanism, high-speed real-time online detection is realized, and the rhythm of the laser etching production line is matched.

[0018] (2) The sub-micron optical imaging of the CCD camera components is combined with image processing algorithms for engraving line quality analysis. Local adaptive threshold segmentation is proposed. The Otsu method is used to adaptively calculate the binarization threshold, and then morphological opening operation is used to remove irrelevant information. Then the edge finding logic algorithm is used to find the two edges of the engraved line, and finally two edges + a middle line are fitted. The quality of the engraved line is analyzed through these three lines, and real-time power adjustment (dynamically adjusting the laser power according to the engraved line width deviation), position calibration (adjusting the position of the Y-axis platform according to the offset of the middle line, and setting a dead zone to avoid interference from micro-vibrations), and marking the defect position (recording the coordinates of the defect area with a large slope difference for subsequent repair) are carried out by detecting the engraved line quality. The high-resolution optical detection system has a fast calculation speed and can perform detection while processing, realizing a closed-loop control of "processing - detection - correction". Description of the Drawings

[0019] The present invention will be further described in detail below with reference to the drawings and specific embodiments.

[0020] Figure 1 It is a schematic structural diagram of the on-line detection system for laser perovskite battery etching quality in the present invention; Figure 2 It is a schematic structural diagram at the laser processing head in the present invention; Figure 3 It is a schematic diagram of the positions of the laser engraved line and the CCD camera components in the present invention; Figure 4 It is the original image collected by the CCD camera components in the present invention; Figure 5 The ROI image obtained by intercepting the original image in the present invention; Figure 6 The binary image obtained by binarizing the intercepted ROI image in the present invention; Figure 7 The image after morphological opening operation in the present invention; Figure 8 The calculation result diagram of the midpoint of the white engraved line in the present invention; Figure 9 The least squares linear fitting result diagram in the present invention; Among them, the specific reference numerals are: Laser processing head 1, first CCD camera assembly 2, second CCD camera assembly 3, gantry 4, workpiece 5, machine tool 6, displacement platform 7. Specific embodiments

[0021] Next, the technical solutions in the embodiments of the present invention will be clearly and completely described in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the protection scope of the present invention.

[0022] Embodiment 1 This embodiment discloses an on-line detection method for the etching quality of a laser perovskite battery. As Figures 1 to 3 shown, a first CCD camera assembly 2 and a second CCD camera assembly 3 are respectively installed on the left and right sides of the laser processing head 1, and the first CCD camera assembly 2 and the second CCD camera assembly 3 are respectively aligned with the first beam and the last beam emitted by the laser processing head 1; The entire on-line detection method process is as follows: (1) Turn on the first CCD camera assembly 2 and the second CCD camera assembly 3, use the Zhang-Zhengyou calibration method to calibrate the internal parameters of the CCD camera assembly, establish the mapping relationship between the pixel coordinate system and the world coordinate system, and calculate the pixel equivalent, denoted as Scalar (μm / pixel); (2) Drive the laser processing head 1 to move uniformly in the positive X-axis direction, and at the same time turn on the laser (pulse laser) to perform P1 engraving on the workpiece 5; (3) While the laser processing head 1 is moving forward, a synchronous trigger signal is generated by the motion platform encoder to start the first CCD camera assembly 2 to collect images, and the images are transmitted to the upper computer for real-time image processing to obtain the quality analysis result. Among them, the image collection and image processing are parallel processes, achieving the effect of "calculating while shooting"; (4)The host computer adjusts the real-time power of the laser, compensates the scribing position (motion platform position compensation), and records the coordinate positions of workpiece defects according to the quality analysis results; (5)When the laser processing head 1 reaches the end of the X-axis travel, turn off the laser, drive the laser processing head 1 to step forward a specified distance (generally the scribing pitch × N) in the positive Y-axis direction, then move in the negative X-axis direction and restart the laser, and switch the synchronous trigger signal source to the second CCD camera module 3; (6)While the laser processing head 1 moves in the reverse direction, the reverse motion encoder synchronously triggers the second CCD camera module 3 to collect images and repeats the above image processing process and real-time adjustment process; (7)During the scribing process, as the laser processing head 1 moves back and forth in the positive and negative directions, the first CCD camera module 2 and the second CCD camera module 3 alternate in operation, and the dual-camera alternating working mode eliminates the field of view occlusion caused by the motion direction.

[0023] Among them, the specific processes of image processing for the images collected by the first CCD camera module 2 and the second CCD camera module 3 in steps (3) and (6) are as follows: 1. As shown in the image collected by the CCD camera module, since the coaxial light source irradiates the surface of the target perovskite battery in a Gaussian distribution, it is necessary to perform ROI extraction on the original image to obtain a region with uniform illumination and good imaging quality, and obtain the ROI image as shown in Figure 4 ... Figure 5 ...

[0024] 2. Then, it is necessary to binarize the intercepted ROI image. Although the imaging quality of the intercepted ROI image is improved, the illumination is still uneven. The traditional global Otsu method may fail to segment due to its inability to adapt to local contrast changes. Therefore, in this embodiment, local threshold segmentation is used: the image is divided into several sub-regions, and the Otsu method is independently applied to each sub-region to calculate the local threshold, and finally the global binarization result is generated by interpolation.

[0025] The specific steps are as follows: (1)Divide the image into M×N sub-blocks, each block with a size of w × w ; (2)For each sub-block , calculate the Otsu threshold ; (3)To avoid threshold jumps between sub-blocks, use bilinear interpolation to generate a smooth threshold surface ; (4)Compare each pixel of the original image with pixel by pixel to generate a binarized image, that is: ; where is the output pixel, and the segmented binary image is as Figure 6 shown.

[0026] 3. Use morphological opening operation, whose mathematical definition is: ; where A is the input image, B is the structuring element, C is the output image, ⊖ represents erosion operation, and ⊕ represents dilation operation. The opening operation can effectively eliminate small noise and smooth the edges, obtaining Figure 7 as shown.

[0027] Here, the structuring element selected for the morphological opening operation is a rectangle. Rectangles are usually used to process noise in the horizontal or vertical directions, or to preserve features with right-angled edges. Since there is a lot of large-particle noise in the image, the size of the structuring element is selected as 15×15. The size selection needs to be adjusted according to the actual scenario. It can be Figure 7 concluded that the morphological opening operation can preserve the features of the main engraved lines.

[0028] 4. Use the edge-finding logic algorithm to find the two black-and-white intersection edges and fit the midline of the white area (i.e., the engraved line). The specific logic is as follows: (1) Traverse the first column, find the first white area after the first black area from top to bottom, and record the first pixel of this area as the starting point of the white area ; (2) Continue to find the first black area after this white area, and record the last pixel of this white area as the end point of the white area ; (3) Calculate the midpoint of the white area in this column, that is ; (4) Repeat the above steps to obtain the upper edge point set and the lower edge point set , and obtain the set of midpoints of the engraved lines , as Figure 8 , where the blue dots are the edge point sets of the engraved lines and , and the red dots are the set of midpoints of the engraved lines ; (5) Use the least squares method to perform linear fitting on the upper edge point set of the engraved line, the lower edge point set of the engraved line, and the set of midpoints of the engraved line respectively. After fitting, two edge lines and a midline are obtained, as Figure 9 shown.

[0029] Due to the Gaussian distribution of laser energy, when scribing perovskite cells, defects such as overall offset of the upper and lower edges, inaccurate laser power resulting in too thin or too wide line widths, and burrs on the scribed line edges may occur. Therefore, in step (3), the scribing quality is analyzed through these three lines, mainly including three aspects (the actual width value between the two edge lines, the Y-axis offset of the midline coordinate, and the slope difference between the two edge lines). In step (4), the host computer correspondingly adjusts the real-time power of the laser, compensates the scribing position (motion platform position compensation), and records the coordinate of the workpiece defect position according to the quality analysis result.

[0030] (1) Calculate the difference between the actual width value between the two edge lines in the current real-time image and the set width value, and judge whether the real-time power of the laser is matched according to the size of the difference between the actual width value and the set width value. If the actual width value is less than the set width value, increase the laser power; otherwise, decrease the laser power.

[0031] Specifically, the calculation method of the actual width value between the two edge lines is to multiply the Y-coordinate difference in the upper and lower edge point sets of the currently captured image by the pixel equivalent to obtain the displayed width. The calculation formula is as follows: ; where and are the y-coordinates of the upper edge and the lower edge of the i-th column scribed line respectively, Scalar is the pixel equivalent, N is the total number of columns in the current real-time image, and Width is the actual width value between the two edge lines in the current real-time image.

[0032] (2) Calculate the Y-axis offset between the midline coordinate in the current real-time image and the reference midline coordinate, and judge whether it is necessary to adjust the Y-axis position of the workpiece 5 according to the Y-axis offset. Note that a dead zone value needs to be set to ignore minor jitters (<±1μm).

[0033] The specific steps are as follows: 1. Manually input or capture the scribed line equation of the image coordinate system for calculating the reference theoretical path ; 2. Real-time detect the midline coordinate of the scribed line ; 3. Substitute the current coordinate into the scribed line equation , and obtain the theoretical image coordinate in the theoretical Y direction ; 4. Calculate the Y-axis offset , and the formula is as follows: ; where is the Y coordinate of the midpoint of the currently detected scribed line, is the theoretical image coordinate, Scalar is the pixel equivalent.

[0034] When the Y-axis offset is greater than the set value, for example, > ±1μm, it means that the Y-axis position of the workpiece 5 needs to be adjusted to compensate for the error.

[0035] (3) Calculate the slope difference of the straight line fitted by the two edge lines. If the slope difference is greater than the set threshold, it indicates that the engraved line is unqualified, and the actual workpiece defect position coordinates are calculated and recorded according to the image timestamp and the movement speed.

[0036] Embodiment 2 This embodiment discloses an on-line detection system for the laser etching quality of perovskite solar cells for implementing the above on-line detection method, as Figures 1 to 3 , including a laser processing head 1, a first CCD camera assembly 2, a second CCD camera assembly 3, a gantry 4, a workpiece 5, a machine tool 6 and a displacement platform 7; The displacement platform 7 and the gantry 4 are installed on the machine tool 6. The workpiece 5 is placed on the displacement platform 7, and the displacement platform 7 can drive the workpiece 5 to move along the Y-axis direction. The laser processing head 1 is installed on the gantry 4. The optical path formed by multiple optical devices inside the laser processing head 1 emits N beams of light. The gantry 4 can drive the laser processing head 1 to move along the X-axis and Z-axis directions. The first CCD camera assembly 2 and the second CCD camera assembly 3 are respectively installed on both sides of the laser processing head 1 along the X-axis direction. The first CCD camera assembly 2 and the second CCD camera assembly 3 are respectively aligned with the first beam of light and the last beam of light emitted by the laser processing head 1, so that the engraved line after processing can be photographed at all times when it moves along the X-axis direction. And the CCD camera assembly is equipped with a continuously variable magnification eyepiece and a focusing objective lens, so that the camera imaging can clearly photograph the single laser etching line width. In this solution, the CCD camera assembly uses a focusing objective lens with a 20-fold magnification and a 2-fold eyepiece, and is equipped with an industrial camera with 2.8 million pixels and a maximum frame rate of 132fps.

[0037] Although the embodiments of the present invention have been shown and described, those of ordinary skill in the art can understand that various changes, modifications, substitutions and variations can be made to these embodiments without departing from the principles and spirit of the present invention. The scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. A laser perovskite cell etching quality online detection method, characterized in that: A first CCD camera assembly and a second CCD camera assembly are respectively installed on the left and right sides of the laser processing head, and the first CCD camera assembly and the second CCD camera assembly are respectively aligned with the first light beam and the last light beam emitted by the laser processing head; Turn on the first CCD camera component and the second CCD camera component, perform internal calibration on the CCD camera component, establish the mapping relationship between the pixel coordinate system and the world coordinate system, and calculate the pixel equivalent, which is recorded as Scalar ; Drive the laser processing head to move along the positive direction of the X-axis, and turn on the laser to perform line processing on the workpiece; While the laser processing head is moving forward, the first CCD camera component is synchronously started to collect images, and the images are transmitted to the host computer for real-time image processing to obtain quality analysis results, wherein image collection and image processing are parallel processing; The host computer adjusts the laser power in real time, compensates for the marking position, and records the coordinates of the workpiece defect position based on the quality analysis results; When the laser processing head reaches the end of the X-axis travel, the laser is turned off, the laser processing head is driven to move a specified distance in the positive direction of the Y-axis, and then moves in the negative direction of the X-axis and restarts the laser, and the synchronous trigger signal source is switched to the second CCD camera assembly; While the laser processing head moves in the reverse direction, the second CCD camera assembly is synchronously triggered to collect images and repeat the above image processing and real-time adjustment processes; During the engraving process, as the laser processing head moves back and forth in the forward and reverse directions, the first CCD camera assembly and the second CCD camera assembly operate alternately.

2. The method for online detection of laser perovskite cell etching quality according to claim 1, characterized in that: The specific process of performing image processing on the images collected by the first CCD camera assembly and the second CCD camera assembly is as follows: The original image is intercepted by ROI; the binarization threshold is adaptively calculated by Otsu method for the intercepted ROI image to generate a binary image; the irrelevant information in the binary image is removed by morphological opening operation; the edge-finding logic algorithm is used to find the two black and white boundary edges of the engraved line, and two edge lines and one center line are fitted, a total of three lines; the engraved line quality analysis is performed through these three lines to obtain the engraved line quality analysis results.

3. The method for online detection of laser perovskite cell etching quality according to claim 2, characterized in that: The local threshold segmentation method is used to divide the captured ROI image into several sub-regions. The Otsu method is applied independently in each sub-region to calculate the local threshold, and finally the global binarization result is generated by interpolation.

4. The method for online detection of laser perovskite cell etching quality according to claim 3, characterized in that: The specific process of using the edge-finding logic algorithm to find the two black and white intersection edges of the engraved line and fitting two edge lines and a center line is as follows: (1) Traverse the first column and search from top to bottom for the first white area after the first black area. Record the first pixel of this area as the starting point of the white area. ; (2) Continue to search for the first black area after this white area, and record the last pixel of this white area as the end point of the white area. ; (3) Calculate the midpoint of the white area in this column, that is: ； (4) Repeat the above steps to obtain the upper edge point set of the engraved line. The point set with the lower edge of the score line , and get the set of midpoints of the engraved lines ; (5) Use the least squares method to calculate the upper and lower edge point sets of the engraved lines. , the lower edge point set of the scale line , Grating Line Midpoint Collection Straight line fitting is performed separately to obtain two edge lines and a center line.

5. The method for online detection of laser perovskite cell etching quality according to claim 2, characterized in that: The three lines are used to analyze the quality of the engraving lines. The specific process of obtaining the quality analysis results includes: calculating the difference between the actual width value and the set width value between the two edge lines in the current real-time image, and judging whether the real-time power of the laser matches according to the difference between the actual width value and the set width value.

6. The method for online detection of laser perovskite cell etching quality according to claim 5, characterized in that: The actual width between two edge lines is calculated as follows: ； in and are the y coordinates of the upper and lower edges of the i-th column scale line, respectively. Scalar is the pixel equivalent, N is the total number of columns in the current real-time image, and Width is the actual width value between two edge lines in the current real-time image.

7. The method for online detection of laser perovskite cell etching quality according to claim 5 or 6, characterized in that: The three lines are used to perform engraving quality analysis, and the specific process of obtaining the quality analysis results also includes: calculating the Y-axis offset between the centerline coordinates in the current real-time image and the reference centerline coordinates, and judging whether the Y-axis position of the workpiece needs to be adjusted according to the Y-axis offset.

8. The method for online detection of laser perovskite cell etching quality according to claim 7, characterized in that: The specific process of calculating the Y-axis offset between the centerline coordinates in the current real-time image and the reference centerline coordinates is as follows: Manual input or shooting of the image coordinate system equation for calculating the reference theoretical path ; Real-time detection of centerline coordinates ; The current coordinates Substitute the line equation , get the theoretical image coordinates in the theoretical Y direction ; Calculate the Y-axis offset , the formula is as follows: ； in is the Y coordinate of the midpoint of the currently detected scale line, is the theoretical image coordinate, Scalar is the pixel equivalent; When the Y axis offset If it is greater than the set value, it means that the Y-axis position error of the workpiece needs to be compensated.

9. The method for online detection of laser perovskite cell etching quality according to claim 8, characterized in that: The three lines are used to analyze the quality of the engraving line, and the specific process of obtaining the quality analysis results also includes: The slope difference of the straight lines fitted by the two edge lines is calculated. If the slope difference is greater than the set threshold, it means that the engraving line is unqualified. The actual workpiece defect position coordinates are calculated and recorded based on the image timestamp and movement speed.

10. An online detection system for laser perovskite cell etching quality for realizing the online detection method according to any one of claims 1 to 9, characterized in that: It includes a laser processing head, a first CCD camera assembly, a second CCD camera assembly, a gantry, a workpiece, a machine tool and a displacement platform; A displacement platform and a gantry are installed on the machine tool, a workpiece is placed on the displacement platform, and the displacement platform can drive the workpiece to move along the Y-axis direction, a laser processing head is installed on the gantry, and the gantry can drive the laser processing head to move along the X-axis and Z-axis directions, and a first CCD camera assembly and a second CCD camera assembly are respectively installed on the left and right sides of the laser processing head, and the first CCD camera assembly and the second CCD camera assembly are respectively aligned with the first light beam and the last light beam emitted by the laser processing head.

Images