Silicon square bar detection equipment

Abstract

The present application discloses a silicon square bar detection device, which includes a frame, a size and appearance detection device, and a control module. The size and appearance detection device includes a plurality of first sensors. During the detection of the silicon square bar, each of the plurality of first sensors corresponds to an edge of the silicon square bar, and the plurality of first sensors can detect the edges of the silicon square bar along a preset direction to obtain point cloud data corresponding to each edge. The control module is connected to the size and appearance detection device, and the control module is used to judge whether there are size defects in the silicon square bar based on the point cloud data. Through the above settings, the perpendicularity of the silicon square bar can be detected, thereby improving the detection accuracy of the silicon square bar.

Description

Technical Field

[0001] This application relates to the technical field of silicon ingot processing, and in particular to a silicon ingot detection device. Background Art

[0002] As an important part of semiconductor materials, silicon ingots are widely used in the manufacture of electronic devices, and their quality directly affects the performance and reliability of the final products.

[0003] In the prior art, the size detection of square silicon ingots is measured by contact sensors. The surface of the square silicon ingot is detected by point contact through several contact sensors. The amount of data collected by the above size detection method is limited, resulting in inaccurate size detection results. Moreover, the perpendicularity of the square silicon ingot cannot be detected by the point contact detection method, resulting in inaccurate detection results.

[0004] Therefore, how to improve the detection accuracy of silicon ingots is a technical problem that needs to be solved urgently by those skilled in the art. Summary of the Invention

[0005] In order to solve the deficiencies of the prior art, the purpose of this application is to provide a silicon ingot detection device that can improve the detection accuracy.

[0006] To achieve the above purpose, this application adopts the following technical solutions:

[0007] A silicon ingot detection device, which includes a frame, a size and appearance detection device, and a control module. The frame has a guide rail extending along a preset direction. At least part of the size and appearance detection device is installed on the guide rail and can move relative to the frame along the preset direction. The size and appearance detection device includes several first sensors. During the detection of the silicon ingot, each of the several first sensors corresponds to an edge of the silicon ingot, and the several first sensors can detect the edges of the silicon ingot along the preset direction to obtain point cloud data corresponding to each edge. The control module is connected to the size and appearance detection device, and the control module is used to judge whether there are size defects in the silicon ingot based on the point cloud data.

[0008] Further, the steps for the control module to execute the judgment of whether there are size defects in the silicon ingot based on the point cloud data include: obtaining the first point cloud data corresponding to the first edge, the second point cloud data corresponding to the second edge, and the third point cloud data corresponding to the third edge; fitting a first side between the first edge and the second edge based on the first point cloud data and the second point cloud data; fitting a second side between the second edge and the third edge based on the second point cloud data and the third point cloud data; determining the perpendicularity of the silicon ingot according to the included angle between the first side and the second side, and judging whether there are size defects in the silicon ingot.

[0009] Further, the control module executes the step of determining whether there are dimensional defects in the silicon square bar based on the point cloud data, including: obtaining the first point cloud data corresponding to the first edge; determining two side edges adjacent to the first edge based on the first point cloud data; determining the perpendicularity of the silicon square bar according to the included angle between the two side edges, and judging whether there are dimensional defects in the silicon square bar.

[0010] Further, the control module executes the step of determining whether there are dimensional defects in the silicon square bar based on the point cloud data, including: obtaining the first point cloud data corresponding to the first edge; determining two side edges adjacent to the first edge based on the first point cloud data; determining the normal vectors of the two side edges respectively to obtain the included angle between the two normal vectors; determining the perpendicularity of the silicon square bar according to the included angle between the two normal vectors, and judging whether there are dimensional defects in the silicon square bar.

[0011] Further, the control module executes the step of determining whether there are dimensional defects in the silicon square bar based on the point cloud data, including: obtaining the first point cloud data corresponding to the first edge, the second point cloud data corresponding to the second edge, the third point cloud data corresponding to the third edge, and the fourth point cloud data corresponding to the fourth edge; fitting the first side edge between the first edge and the second edge based on the first point cloud data and the second point cloud data; fitting the third side edge between the third edge and the fourth edge based on the third point cloud data and the fourth point cloud data; judging whether there are dimensional defects in the silicon square bar according to the parallelism between the first side edge and the third side edge.

[0012] Further, the first sensor is also used to obtain the brightness image of the edge, and the control module is used to determine whether there are appearance defects on the edge based on the brightness image.

[0013] Further, the dimensional appearance detection device further includes a second sensor, and the second sensor detects a side surface of the silicon square bar to obtain the surface point cloud data corresponding to the surface; the control module determines the curvature of the surface based on the surface point cloud data, and if the curvature of the surface is outside the set threshold range, it is determined that there are dimensional defects in the silicon square bar.

[0014] Further, the dimensional appearance detection device further includes a plurality of surface detection cameras, and each surface detection camera in the plurality of surface detection cameras corresponds to a surface of the silicon square bar, and each surface detection camera is configured with two light sources, and the two light sources respectively face the surface of the silicon square bar at different irradiation angles.

[0015] Further, the control module is electrically connected to the surface detection camera and the two light sources respectively. During the detection of the silicon square bar, the control module can control the two light sources to illuminate the surface of the silicon square bar in sequence at a set interval, and the control module can control the surface detection camera to generate two images with different lighting angles at a set interval. If there are light spots in any of the two images, the control module determines that there are appearance defects on the side edge of the silicon square bar.

[0016] Further, the silicon ingot detection device further includes a crack detection device, which includes an infrared light source and an infrared camera. The infrared light source and the infrared camera are oppositely arranged, so that the infrared camera can obtain the light emitted from the infrared light source and passing through the silicon ingot to generate an infrared image. The control module is electrically connected to the infrared camera, and the control module can determine whether there is a crack inside the silicon ingot based on the gray value of the silicon ingot in the infrared image.

[0017] Further, the silicon ingot detection device further includes a lifting assembly and two clamping assemblies arranged along a preset direction. The lifting assembly is installed on the frame. The lifting assembly is used to support the silicon ingot and can move relative to the frame in the height direction. The lifting assembly is located between the two clamping assemblies, and the two clamping assemblies cooperate to clamp the silicon ingot arranged on the lifting assembly. The clamping assembly includes a fixing mechanism and a driving mechanism. The driving mechanism is installed on the frame, and the driving mechanism is used to drive the fixing mechanism to approach or move away from the silicon ingot along the preset direction. The fixing mechanism has a contact surface that abuts against the end of the silicon ingot, and the fixing mechanism is provided with a movable part. Define a longitudinal plane perpendicular to the preset direction, and adjust the angle between the contact surface and the longitudinal plane based on the movable part.

[0018] The silicon ingot detection device can obtain the point cloud data corresponding to each edge through the dimensional appearance detection device, and then the control module can judge whether there are defects in the size of the silicon ingot based on the point cloud data, which is beneficial to improving the detection accuracy of the silicon ingot. Description of the Drawings

[0019] Figure 1 Schematic diagram of the overall structure of the silicon ingot detection device provided by the present application;

[0020] Figure 2 Combined schematic diagram of the first sensor, the second sensor and the detection motion device of the silicon ingot detection device provided by the present application;

[0021] Figure 3 Schematic diagram of the structure of the silicon ingot provided by the present application;

[0022] Figure 4 Schematic diagram of the silicon ingot graph fitted by the control module of the silicon ingot detection device provided by the present application;

[0023] Figure 5 Schematic diagram of the process of detecting the perpendicularity of the silicon ingot by the silicon ingot detection device provided by the present application;

[0024] Figure 6 Second schematic diagram of the process of detecting the perpendicularity of the silicon ingot by the silicon ingot detection device provided by the present application;

[0025] Figure 7The third process schematic diagram for detecting the perpendicularity of the silicon ingot by the silicon ingot detection device provided by this application;

[0026] Figure 8 The schematic diagram of the control module of the silicon ingot detection device provided by this application fitting the first normal graph and the second normal graph;

[0027] Figure 9 The process schematic diagram for detecting the parallelism of the silicon ingot by the silicon ingot detection device provided by this application;

[0028] Figure 10 The process schematic diagram for detecting the surface curvature of the silicon ingot by the silicon ingot detection device provided by this application

[0029] Figure 11 The combined schematic diagram of the surface detection camera, light source, and detection motion device of the silicon ingot detection device provided by this application;

[0030] Figure 12 The combined schematic diagram of the first light source, second light source, surface detection camera, and silicon ingot of the silicon ingot detection device provided by this application;

[0031] Figure 13 The combined schematic diagram of the infrared light source, infrared camera, and silicon ingot of the silicon ingot detection device provided by this application;

[0032] Figure 14 The structural schematic diagram of the clamping component of the silicon ingot detection device provided by this application;

[0033] Figure 15 The structural schematic diagram of the fixing mechanism of the silicon ingot detection device provided by this application.

[0034] Among them, 100 is a silicon square bar detection device; 11 is a frame; 111 is a guide rail; 12 is a dimensional appearance detection device; 121 is a first sensor; 122 is a second sensor; 123 is a surface detection camera; 124 is a light source; 1241 is a first light source; 1242 is a second light source; 125 is an infrared light source; 126 is an infrared camera; 13 is a moving component; 14 is a detection motion device; 15 is a lifting component; 16 is a clamping component; 161 is a fixing mechanism; 1611 is a contact surface; 1612 is a movable part; 1613 is a fixed end; 162 is a driving mechanism; 101 is a longitudinal plane; 200 is a silicon square bar; 21 is a first edge; 22 is a second edge; 23 is a third edge; 24 is a fourth edge; 25 is a first surface; 251 is a first side; 2511 is a first normal; 26 is a second surface; 261 is a second side; 2611 is a second normal; 27 is a third surface; 271 is a third side; 28 is a fourth surface; 281 is a fourth side; α is a first angle; β is a second angle; γ is a third angle; δ is a fourth angle; ε is an angle. Detailed implementation manners

[0035] In order to enable those skilled in the art to better understand the solution of this application, the technical solutions in the specific implementation manners of this application will be clearly and completely described below in conjunction with the accompanying drawings in the implementation manners of this application.

[0036] It should be noted that the "first", "second" and similar terms used in the specification and claims of this application do not indicate any order, quantity or importance, but are only used to distinguish different components. Similarly, the similar terms such as "a" or "one" do not indicate a quantity limitation, but indicate that there is at least one. "Multiple" or "several" means at least two. Unless otherwise specified, the similar terms such as "front", "rear", "left", "right", "lower" and / or "upper" are only for convenience of description and are not limited to one position or a spatial orientation. The terms such as "comprising" or "including" mean that the elements or objects appearing before "comprising" or "including" cover the elements or objects listed after "comprising" or "including" and their equivalents, and do not exclude other elements or objects. The similar terms such as "connected" or "coupled" are not limited to physical or mechanical connections, and may include electrical connections, whether direct or indirect.

[0037] The singular forms of "a", "the" and "said" used in the specification and appended claims of this application are also intended to include the plural forms unless the context clearly dictates otherwise. It should also be understood that the term "and / or" as used herein refers to and encompasses any and all possible combinations of one or more of the associated listed items.

[0038] To clearly illustrate the technical solution of this application, the front, rear, upper, lower, left, and right directions as shown in Figure 1 are also defined.

[0039] As shown in Figure 1 and Figure 2 this application discloses a silicon square bar detection device 100, which is used to detect the appearance and dimensions of a square silicon square bar 200. Specifically, the silicon square bar detection device 100 includes a frame 11, a dimension and appearance detection device 12, and a control module (not shown in the figure). Among them, the frame 11 constitutes the basic framework of the silicon square bar detection device 100 and is used to support the dimension and appearance detection device 12. The dimension and appearance detection device 12 is used to detect the dimension and appearance data of the silicon square bar 200. The control module is connected to the dimension and appearance detection device 12, and the control module is used to judge whether there are dimension and appearance defects in the silicon square bar 200 based on the detection data of the dimension and appearance detection device 12. The control module can be a controller integrated on the silicon square bar detection device 100, or the control module can be a separately provided terminal, which is connected to the dimension and appearance detection device 12 through a data bus. With such a setting, the detection of dimension defects and appearance defects of the silicon square bar 200 can be realized by one silicon square bar detection device 100, which is beneficial to improving the quality detection efficiency of the silicon square bar 200. In addition, there is no need to arrange two devices in the site to detect the dimension defects and appearance defects of the silicon square bar 200 respectively, which is beneficial to reducing the space occupied by the silicon square bar detection device 100 and enabling more silicon square bar detection devices 100 to be arranged in a limited space to further improve the detection efficiency of the silicon square bar 200.

[0040] More specifically, the frame 11 has a guide rail 111 extending along a preset direction, and at least part of the dimension and appearance detection device 12 is installed on the guide rail 111 and can move relative to the frame 11 along the preset direction. In the embodiment of this application, the preset direction is the front-rear direction of this silicon square bar detection device 100. With such a setting, the guide rail 111 can play a guiding role in the movement of the dimension and appearance detection device 12 on the frame 11, thereby improving the movement stability of the dimension and appearance detection device 12 on the frame 11. Secondly, the silicon square bar 200 is supported by the frame 11, and the extending direction of the silicon square bar 200 is consistent with the preset direction, so that the dimension and appearance detection device 12 can detect the whole silicon square bar 200 during the movement along the preset direction.

[0041] As an optional implementation manner, the silicon square bar detection device 100 includes a moving component 13. The moving component 13 is installed on the frame 11, the moving component 13 is connected to the dimension and appearance detection device 12, and the moving component 13 is used to drive the dimension and appearance detection device 12 to move along the preset direction on the guide rail 111.

[0042] In this embodiment, the size and appearance detection device 12 includes a plurality of first sensors 121. The silicon square bar 200 has four edges extending along a preset direction, and the first sensors 121 are used to detect the edges of the silicon square bar 200. The number of the first sensors 121 is set to four, and each first sensor 121 corresponds to an edge of the silicon square bar 200.

[0043] During the detection process of the silicon square bar 200, each of the plurality of first sensors 121 corresponds to an edge of the silicon square bar 200, and the plurality of first sensors 121 can detect the edges of the silicon square bar 200 along the preset direction to obtain point cloud data corresponding to each edge. In the related art, when detecting the edges of the silicon square bar by means of point contact, there may be a situation where defective points are not detected during the edge detection. However, in the embodiment of the present application, by the above settings to obtain the point cloud data representing the edges of the silicon square bar 200, the situation of missing detection of the size defects of the edges can be avoided, which is beneficial to improving the detection accuracy of the edges of the silicon square bar 200.

[0044] The control module determines whether the silicon square bar 200 has size defects based on the point cloud data. Specifically, the control module can fit the corresponding silicon square bar 200 graph through the point cloud data corresponding to the edges, so as to be able to judge whether the size of the silicon square bar 200 has defects according to the fitted silicon square bar 200 graph, and further improve the detection accuracy of the silicon square bar 200.

[0045] It should be noted that the point cloud data refers to a set of vectors in a three-dimensional coordinate system. Therefore, the control module can fit the corresponding silicon square bar 200 graph based on the three-dimensional coordinates of the set of vectors, so that the control module can judge the size defects of the silicon square bar 200 according to the fitted graph of the silicon square bar 200. In addition, by fitting the corresponding silicon square bar 200 graph, the side length, chamfer size and length data of the silicon square bar 200 can be obtained. Therefore, the silicon square bar detection device 100 of the present application can also detect the size data of the silicon square bar 200 to improve the functionality of the silicon square bar detection device 100.

[0046] Exemplarily, four first sensors 121 are provided, and each first sensor 121 corresponds to an edge of the silicon square bar 200, so that the first sensor 121 can acquire the point cloud data of each edge of the silicon square bar 200. The control module can perform cropping ROI on the edge point cloud data acquired by the first sensor 121 according to the dimension data of the standard silicon square bar, and remove abnormal data such as imaging noise, so that the control module performs a rough screening on the edge point cloud data acquired by the first sensor 121. The control module sets the basic range of the three-dimensional coordinate threshold of the standard silicon square bar at any sampling moment according to the dimension of the standard silicon square bar. The control module performs a fine screening on the edge point cloud data after rough screening according to the basic range of the three-dimensional coordinate threshold, so as to remove the abnormal edge point cloud data that is too large or too small outside the basic range of the three-dimensional coordinate threshold, thereby obtaining the effective edge point cloud data. At any sampling moment, a relative coordinate system is constructed with the vector of the effective edge point cloud data acquired by one of the first sensors 121 as the coordinate origin. The control module fits the edge graph of the silicon square bar 200 at this sampling moment according to the effective edge point cloud data acquired by the four first sensors 121 in the relative coordinate system, and fits the side graph of the silicon square bar 200 at this sampling moment according to the fitted edge graph in the relative coordinate system, thereby obtaining the graph of the silicon square bar 200 fitted at this sampling moment. Furthermore, it is determined whether the silicon square bar 200 has a dimension defect by comparing the dimension data of the fitted silicon square bar 200 graph with the dimension data of the standard silicon square bar, such as the perpendicularity of the silicon square bar 200 and whether there are defects such as concavity in the silicon square bar 200.

[0047] It should be noted that cropping ROI refers to extracting a specific area containing important information from the original image in image processing or computer vision tasks. This area usually contains data useful for specific tasks, and cropping off other irrelevant parts can reduce the computational amount, improve the processing speed, or simplify the subsequent analysis process. Therefore, by performing cropping ROI on the first sensor 121, the point cloud data within the basic dimension range of the standard silicon square bar can be extracted.

[0048] Exemplarily, the fitted graph of the silicon square bar 200 can display the included angle size of the edges of the silicon square bar 200, so that the perpendicularity of the silicon square bar 200 can be judged according to the included angle of the edges of the silicon square bar 200, so as to realize the detection of the perpendicularity of the silicon square bar 200, and further facilitate improving the detection accuracy of the dimension of the silicon square bar 200.

[0049] It should be noted that in this application, the edges of the silicon square bar 200 have chamfers, and the first sensor 121 obtains the point cloud data of the points corresponding to the chamfers of each edge. Secondly, the first sensor 121 can also obtain the corresponding point cloud data of the edges of the silicon square bar 200 without chamfers. Therefore, this application does not limit whether the edges of the silicon square bar 200 are provided with chamfers. In addition, this application takes the edges of the silicon square bar 200 having chamfers as an example for illustration.

[0050] It should be noted that as Figure 3 and Figure 4 shown, the silicon square bar 200 in this application includes a first edge 21, a second edge 22, a third edge 23, and a fourth edge 24, as well as a first surface 25, a second surface 26, a third surface 27, and a fourth surface 28. Among them, the first surface 25 is arranged between the first edge 21 and the second edge 22, the second surface 26 is arranged between the second edge 22 and the third edge 23, the third surface 27 is arranged between the third edge 23 and the fourth edge 24, and the fourth surface 28 is arranged between the first edge 21 and the fourth edge 24. At any sampling moment, the area between the first edge 21 and the second edge 22 is defined as the first side 251, the area between the second edge 22 and the third edge 23 is defined as the second side 261, the area between the third edge 23 and the fourth edge 24 is defined as the third side 271, and the area between the first edge 21 and the fourth edge 24 is defined as the fourth side 281. And the included angle between the first side 251 and the second side 261 is the first included angle α, the included angle between the second side 261 and the third side 271 is the second included angle β, the included angle between the third side 271 and the fourth side 281 is the third included angle γ, and the included angle between the first side 251 and the fourth side 281 is the fourth included angle δ. The perpendicularity of the silicon square bar 200 is judged by detecting the angle sizes of the first included angle α, the second included angle β, the third included angle γ, and the fourth included angle δ.

[0051] In addition, the detection steps for the first included angle α, the second included angle β, the third included angle γ, and the fourth included angle δ in this application are the same. Therefore, this application takes the detection step for the first included angle α as an example for illustration, and the detection steps for the second included angle β, the third included angle γ, and the fourth included angle δ will not be elaborated.

[0052] As Figure 5 shown, as an implementation manner, the control module executes the step of judging whether the silicon square bar 200 has dimensional defects based on the point cloud data, and this step includes:

[0053] S101: Obtain the first point cloud data corresponding to the first edge 21, the second point cloud data corresponding to the second edge 22, and the third point cloud data corresponding to the third edge 23.

[0054] During the process of the dimensional appearance detection device 12 moving along a preset direction, the detection direction of the first sensor 121 faces the first edge 21. The first sensor 121 obtains in real time the first point cloud data representing the appearance dimensions of the first edge 21 during the movement of the dimensional appearance detection device 12. According to the above content, the first point cloud data contains the vectors of a sampling point of the first edge 21 corresponding to each sampling moment in the three-dimensional coordinate system. At the same time, the first sensor 121 corresponding to the second edge 22 can obtain the second point cloud data. The first sensor 121 corresponding to the third edge 23 can obtain the third point cloud data.

[0055] S102: Fit the first side 251 between the first edge 21 and the second edge 22 based on the first point cloud data and the second point cloud data.

[0056] For example, the first point cloud data includes a first vector corresponding to the first sampling moment, and the second point cloud data includes a second vector corresponding to the first sampling moment. Based on the first vector and the second vector, it can be determined that at the first sampling moment, the first side 251 between the first edge 21 and the second edge 22.

[0057] S103: Fit the second side 261 between the second edge 22 and the third edge 23 based on the second point cloud data and the third point cloud data;

[0058] S104: Determine the perpendicularity of the silicon square bar 200 according to the included angle between the first side 251 and the second side 261, and judge whether the silicon square bar 200 has dimensional defects.

[0059] The control module can obtain the angle size of the first included angle α in the sampling moment of step S102 according to the first side 251 graph in step S102 and the second side 261 graph in step S103, so as to judge whether the first side 251 and the second side 261 of the silicon square bar 200 are perpendicular according to the angle of the first included angle α, and further judge whether the corresponding first surface 25 and the second surface 26 are perpendicular at the sampling moment, so as to achieve the purpose of detecting the dimensional defects of the silicon square bar 200, and further help to improve the detection accuracy of the silicon square bar 200.

[0060] As Figure 6 shown, as another implementation manner, the control module executes the step of judging whether the silicon square bar 200 has dimensional defects based on the point cloud data, and this step includes:

[0061] S201: Obtain the first point cloud data corresponding to the first edge 21.

[0062] S202: Determine two adjacent sides to the first edge 21 based on the first point cloud data.

[0063] During the process of the first sensor 121 detecting the first edge 21, the first sensor 121 can irradiate partial areas on both sides adjacent to the first edge 21, enabling the control module to fit the shapes of the first side 251 and the second side 261 based on the data of the obtained partial areas.

[0064] S203: Determine the perpendicularity of the silicon square bar 200 based on the included angle between the two sides, and judge whether there are dimensional defects in the silicon square bar 200.

[0065] In step S203, the control module can obtain the angle magnitude of the first included angle α at the sampling moment in step S201 based on the shapes of the first side 251 and the second side 261 in step S202, so as to judge whether the first side 251 and the second side 261 of the silicon square bar 200 are perpendicular according to the angle of the first included angle α, and further judge whether the corresponding first surface 25 and the second surface 26 are perpendicular at the sampling moment, so as to achieve the purpose of detecting dimensional defects of the silicon square bar 200.

[0066] It should be noted that in this embodiment, when the first sensor 121 corresponding to the first edge 21 obtains the point cloud data of the first edge 21 at any sampling moment, the first sensor 121 can simultaneously detect the point cloud data of the first surface 25 and the second surface 26 of the silicon square bar 200 adjacent to the first edge 21, so that the control module can fit the shape of the first side 251 corresponding to the first surface 25 at the sampling moment according to the three-dimensional coordinate vectors of the point cloud data of the first surface 25, and fit the shape of the second side 261 corresponding to the second surface 26 at the sampling moment according to the three-dimensional coordinate vectors of the point cloud data of the second surface 26, and further enable the control module to detect the angle magnitude of the first included angle α through the shapes of the first side 251 and the second side 261. To judge whether the corresponding first surface 25 and the second surface 26 are perpendicular at the sampling moment, and then achieve the purpose of detecting dimensional defects of the silicon square bar 200.

[0067] As Figure 7 and Figure 8 shown, as another embodiment, the control module executes the step of judging whether there are dimensional defects in the silicon square bar 200 based on the point cloud data, and this step includes:

[0068] S301: Obtain the first point cloud data corresponding to the first edge 21.

[0069] S302: Determine two sides adjacent to the first edge 21 based on the first point cloud data.

[0070] At any sampling moment, after receiving the first point cloud data, the control module can fit the shapes of the first side 251 and the second side 261.

[0071] S303: Determine the normal lines of the two side edges respectively to obtain the angle between the two normal lines.

[0072] The control module can fit the first normal line 2511 corresponding to the first side edge 251 according to the shape of the first side edge 251, fit the second normal line 2611 corresponding to the second side edge 261 according to the shape of the second side edge 261, and obtain the size of the first angle α at this sampling moment according to the size of the angle ε between the first normal line 2511 and the second normal line 2611. Thus, it can be determined whether the first side edge 251 and the second side edge 261 are perpendicular according to the angle of the first angle α, and further determine whether the first surface 25 and the second surface 26 of the silicon square bar 200 at this sampling moment are perpendicular, so as to achieve the purpose of detecting the size defects of the silicon square bar 200.

[0073] S304: Determine the perpendicularity of the silicon square bar 200 according to the angle between the two normal lines, and judge whether there are size defects in the silicon square bar 200.

[0074] As Figure 9 shown, as an optional implementation manner, the silicon square bar detection device 100 of the present application can also detect the parallelism of two opposite surfaces on the silicon square bar 200. Taking the detection of the parallelism of the first surface 25 and the third surface 27 as an example for description, the parallelism of the second surface 26 and the fourth surface 28 will not be elaborated.

[0075] Specifically, the control module executes the step of judging whether there are size defects in the silicon square bar 200 based on the point cloud data, and this step includes:

[0076] S401: Obtain the first point cloud data corresponding to the first edge 21, the second point cloud data corresponding to the second edge 22, the third point cloud data corresponding to the third edge 23, and the fourth point cloud data corresponding to the fourth edge 24;

[0077] During the process of the size and appearance detection device 12 moving along the preset direction, the first sensor 121 corresponding to the first edge 21 can obtain the first point cloud data. The first sensor 121 corresponding to the second edge 22 can obtain the second point cloud data. The first sensor 121 corresponding to the third edge 23 can obtain the third point cloud data. The first sensor 121 corresponding to the fourth edge 24 can obtain the fourth point cloud data.

[0078] S402: Fit the first side edge 251 between the first edge 21 and the second edge 22 based on the first point cloud data and the second point cloud data;

[0079] S403: Fit the third side edge 271 between the third edge 23 and the fourth edge 24 based on the third point cloud data and the fourth point cloud data;

[0080] S404: Determine whether there are dimensional defects in the silicon square bar 200 based on the parallelism between the first side 251 and the third side 271.

[0081] The control module can obtain the parallelism between the first side 251 and the third side 271 at this sampling moment by detecting the parallelism between the pattern of the first side 251 and the pattern of the second side 261, and further obtain the parallelism at the first surface 25 and the third surface 27 corresponding to the sampling moment in step S402, so as to further judge the dimensional defects of the silicon square bar 200, thereby improving the detection accuracy of the silicon square bar 200.

[0082] As an optional implementation manner, in order to detect the appearance quality of the edges of the silicon square bar 200, the first sensor 121 is also used to obtain the brightness image of the edges, and the control module is used to determine whether there are appearance defects on the edges based on the brightness image. With such a setting, when the first sensor 121 detects the edges of the silicon square bar 200, the first sensor 121 will irradiate the edges of the silicon square bar 200 so that the first sensor 121 can obtain the brightness image of the edges of the silicon square bar 200. When there are defects on the edges, it will cause the light irradiated by the first sensor 121 to refract when passing through the defects, so that there are light spots with different brightness from the surrounding on the brightness image of the edges obtained by the first sensor 121. The control module judges whether there are defects on the edges by detecting whether there are light spots on the brightness image of the edges, so as to realize the detection of the appearance quality of the edges of the silicon square bar 200.

[0083] Exemplarily, taking the detection of whether there are appearance defects on the first edge 21 as an example for description. The first sensor 121 obtains the brightness image of the first edge 21. When there are defects such as protrusions or depressions on the first edge 21, the light source 124 will produce phenomena such as scattering, reflection or refraction when irradiating at the defect, so that the defect presents a light spot with different brightness from the surrounding on the brightness image. It can be understood that by detecting the brightness image obtained by the first sensor 121, it can be judged whether there are appearance defects on the first edge 21, thereby further improving the detection accuracy of the silicon square bar detection device 100 for the silicon square bar 200.

[0084] Such as Figure 2 and Figure 10As shown in the figure, in order to detect the surface dimension quality of the silicon square bar 200, the dimension appearance detection device 12 of the present application further includes a second sensor 122. The second sensor 122 corresponds to one side surface of the silicon square bar 200 for detection to obtain surface point cloud data corresponding to the surface. Specifically, the control module determines the curvature of the surface based on the surface point cloud data. If the curvature is outside the set threshold range, it is determined that the silicon square bar 200 has a dimension defect. Among them, the set threshold range is the surface curvature range of the silicon square bar 200 under the standard state. With such a setting, the curvature size of the corresponding surface of the silicon square bar 200 can be obtained through the second sensor 122 to determine whether the silicon square bar 200 has a defect.

[0085] Exemplarily, four second sensors 122 are provided, and each second sensor 122 corresponds to one surface of the silicon square bar 200, so that the second sensor 122 can detect the surface of the silicon square bar 200. Taking the second sensor 122 detecting the first surface 25 as an example for illustration. The steps of the control module determining the curvature of the surface based on the surface point cloud data and determining whether the silicon square bar 200 has a dimension defect include:

[0086] S501: Obtain surface point cloud data corresponding to the first surface 25.

[0087] During the process of the dimension appearance detection device 12 moving along the preset direction, the second sensor 122 acquires the surface point cloud data of the first surface 25.

[0088] S502: Fit out the first side 251 based on the surface point cloud data.

[0089] At any sampling moment, the control module fits out the first side 251 graph based on the three-dimensional coordinates of the vectors in the surface point cloud data. At this time, the control module detects the curvature size of the first side 251 graph.

[0090] S503: Determine whether the silicon square bar 200 has a dimension defect according to whether the curvature of the first side 251 conforms to the set threshold range.

[0091] The control module detects whether the curvature size of the first side 251 graph conforms to the set threshold range, so as to determine whether the curvature of the first surface 25 conforms to the set threshold range at the sampling moment of step S502, to determine whether the first surface 25 has a dimension defect, and further improve the detection accuracy of the silicon square bar 200.

[0092] Such as Figure 11 and Figure 12As shown, in order to detect the surface appearance quality of the silicon square bar 200, the size and appearance detection device 12 of the present application further includes a number of surface detection cameras 123, which are used to detect the surface appearance quality of the silicon square bar 200. Specifically, each of the number of surface detection cameras 123 corresponds to one surface of the silicon square bar 200, and each surface detection camera 123 is configured with two light sources 124. More specifically, the two light sources 124 are respectively oriented towards the surface of the silicon square bar 200 at different illumination angles. The two light sources 124 can illuminate the surface of the silicon square bar 200 so that the surface appearance detection camera can obtain the surface brightness image of the silicon square bar 200. When there are defects such as protrusions or depressions on the surface of the silicon square bar 200, the light rays of the two light sources 124 will be refracted when they hit the defect, resulting in light spots with different brightnesses on the surface brightness image, and then enabling the control module to determine whether there are light spots on the surface brightness image to judge whether there are defects on the surface of the silicon square bar 200, so as to further improve the detection accuracy of the silicon square bar 200.

[0093] Exemplarily, taking the surface detection camera 123 detecting the first surface 25 of the silicon square bar 200 as an example for illustration, the two light sources 124 are respectively defined as the first light source 1241 and the second light source 1242. When the first surface 25 is a smooth surface, the light rays of the first light source 1241 are refracted by the surface of the silicon square bar 200 and then shoot towards the viewing direction of the surface detection camera 123, and the light rays of the second light source 1242 are not refracted by the surface of the silicon square bar 200 and shoot towards the viewing direction of the surface detection camera 123, so that the surface detection camera 123 can obtain the surface brightness image of the silicon square bar 200. When there are defects such as protrusions or depressions on the first surface 25, the light rays of the first light source 1241 and the second light source 1242 will be refracted when passing through the defect, resulting in light spots with different brightness from the surrounding on the surface brightness image. Also, the surface detection camera 123 is connected to the control module, and the control module determines whether there are defects on the first surface 25 of the silicon square bar 200 according to whether there are light spots on the surface brightness image, so as to realize the appearance defect detection of the first surface 25 of the silicon square bar 200.

[0094] As an optional implementation manner, the control module is electrically connected to the surface detection camera 123 and the two light sources 124 respectively. Specifically, during the detection process of the silicon square bar 200, the control module can control the two light sources 124 to illuminate the surface of the silicon square bar 200 in sequence at a set interval, and the control module can control the surface detection camera 123 to generate two images with different lighting angles at a set interval. If there are light spots in any of the two images, the control module determines that there are appearance defects on the side of the silicon square bar 200.

[0095] In this embodiment, the irradiation angles of the two light sources 124 with respect to the surface of the silicon ingot 200 are different, so that the surface detection camera 123 can obtain images with different brightness levels, enabling the defects on the surface of the silicon ingot 200 to be presented simultaneously in the images with different brightness levels, thus avoiding the situation where the defects on the surface of the silicon ingot 200 are not obvious in a single brightness image and causing detection omissions, which is conducive to improving the accuracy of detecting the surface of the silicon ingot 200.

[0096] Exemplarily, taking the detection of the first surface 25 of the silicon ingot 200 by the surface detection camera 123 as an example, the two light sources 124 are defined as the first light source 1241 and the second light source 1242 respectively. When the first surface 25 is a smooth surface, the light rays of the first light source 1241 are refracted by the surface of the silicon ingot 200 and then shoot towards the viewing direction of the surface detection camera 123, so that the surface detection camera 123 can obtain a bright-field image with a higher brightness of the first surface 25 of the silicon ingot 200. The light rays of the second light source 1242 are refracted by the surface of the silicon ingot 200 and do not shoot towards the viewing direction of the surface detection camera 123, so that the surface detection camera 123 can obtain a dark-field image with a lower brightness of the first surface 25 of the silicon ingot 200. The control module can control the two light sources 124 to illuminate the surface of the silicon ingot 200 in sequence at a set interval, so that the defects such as protrusions, depressions or chipping edges on the first surface 25 can be simultaneously displayed in the bright-field image and the dark-field image, thus avoiding the situation where the defects such as protrusions, depressions or chipping edges are obvious in the bright-field image but not obvious in the dark-field image, or vice versa. It can be understood that through the above settings, the situation where the defects such as protrusions, depressions or chipping edges are not obvious in a single brightness image and causing detection omissions can be avoided, which is conducive to improving the detection accuracy of the silicon ingot detection device 100 for the silicon ingot 200.

[0097] It should be noted that since the detection method of the surface detection camera 123 for the second surface 26, the third surface 27 and the fourth surface 28 of the silicon ingot 200 is the same as that for the first surface 25 of the silicon ingot 200, the detection methods for the second surface 26, the third surface 27 and the fourth surface 28 of the silicon ingot 200 will not be elaborated here.

[0098] Such as Figure 13As shown, in order to detect whether there are defects inside the silicon square bar 200, the silicon square bar detection device of the present application further includes a hidden crack detection device, and the hidden crack detection device includes an infrared light source 125 and an infrared camera 126. Specifically, the infrared light source 125 and the infrared camera 126 are arranged opposite to each other, so that the infrared camera 126 can obtain the light emitted from the infrared light source 125 and passing through the silicon square bar 200 to generate an infrared image. With such an arrangement, the infrared light source 125 cooperates with the infrared camera 126 to display the internal structure of the silicon square bar 200 and generate an infrared image, so that it is possible to determine whether there are defects inside the silicon square bar 200 by observing the infrared image, so as to realize the detection of the internal defects of the silicon square bar 200.

[0099] More specifically, the control module is electrically connected to the infrared camera 126, and the control module can determine whether there are hidden cracks inside the silicon square bar 200 based on the gray value of the silicon square bar 200 in the infrared image. With such an arrangement, when there are defects inside the silicon square bar 200, it will cause the gray value at the defect location on the infrared image to be different from that of the surrounding area, thus forming a trace with uneven gray values on the infrared image. The control module can judge whether there are hidden crack defects inside the silicon square bar 200 according to whether there are traces with uneven gray values on the infrared image, and further improve the accuracy of the quality detection of the silicon square bar 200.

[0100] Exemplarily, the infrared light source 125 emits infrared light with a wavelength of 1300 - 1700 nm, and the infrared light is incident on the silicon square bar 200 perpendicular to the first surface 25 of the silicon square bar 200. After the infrared light is conducted through the inside of the silicon square bar 200, it exits from the third surface 27 and enters the infrared camera 126, so that the infrared camera 126 can present the internal image of the silicon square bar 200. When there are defects such as hidden cracks inside the silicon square bar 200, traces with different gray values from the surrounding area will appear on the infrared image. The control module judges whether there are defects such as hidden cracks inside the silicon square bar 200 by judging whether there are traces with different gray values on the infrared image, thereby realizing the detection of the internal defects of the silicon square bar 200.

[0101] Such as Figure 2 and Figure 11As shown, in order for the silicon square bar detection device 100 to detect silicon square bars 200 of different sizes, the silicon square bar detection device 100 of the present application further includes a detection motion device 14. The detection motion device 14 is connected to at least part of the size and appearance detection device 12, and the detection motion device 14 is used to drive the infrared light source 125, the infrared camera 126, the surface detection camera 123, the first sensor 121, and the second sensor 122 to move in a direction closer to or farther from the silicon bar. Exemplarily, the detection motion device 14 is a cylinder, and the cylinder can drive the infrared light source 125, the infrared camera 126, the surface detection camera 123, the first sensor 121, and the second sensor 122 to move closer to or farther from the silicon bar respectively, so that the above-mentioned components can adjust the distance from the silicon square bar 200 according to the size of the silicon square bar 200, so as to avoid the distance between the above-mentioned components and the silicon square bar 200 being too close and resulting in incomplete detection of the silicon square bar 200, and also avoid the distance between the above-mentioned components and the silicon square bar 200 being too far and resulting in a decrease in the imaging clarity of the above-mentioned components for detecting the silicon square bar 200, thereby facilitating the improvement of the detection accuracy of the silicon square bar detection device 100 for the silicon square bar 200.

[0102] As an implementation manner, the silicon square bar detection device 100 further includes a lifting component 15 and a clamping component 16. The lifting component 15 is installed on the frame 11, and the lifting component 15 is used to support the silicon square bar 200, and the lifting component 15 can move relative to the frame 11 in the height direction. Wherein, the height direction is the up and down direction of the silicon square bar detection device 100, and the lifting component 15 can drive the silicon square bar 200 to move in the up and down direction of the silicon square bar detection device 100, so as to realize the loading and unloading of the silicon square bar 200. There are two clamping components 16, and the two clamping components 16 are arranged along a preset direction, so that the two clamping components 16 can clamp both ends of the silicon square bar 200 along the preset direction.

[0103] More specifically, the lifting component 15 is located between the two clamping components 16, and the two clamping components 16 cooperate to clamp the silicon square bar 200 arranged on the lifting component 15. With such a setting, interference between the lifting component 15 and the two clamping components 16 can be avoided, which is beneficial for the lifting component 15 to drive the silicon square bar 200 to lift, and is also beneficial for the two clamping components 16 to clamp the silicon square bar 200.

[0104] Such as Figure 14 and Figure 15As shown, in this embodiment, the clamping assembly 16 includes a fixing mechanism 161 and a driving mechanism 162. Specifically, the driving mechanism 162 is installed on the frame 11, and the driving mechanism 162 is used to drive the fixing mechanism 161 to approach or move away from the silicon ingot 200 along a preset direction. Exemplarily, the driving mechanism 162 is a linear cylinder, and the linear cylinder can be used to drive the fixing mechanism 161 to approach or move away from the silicon ingot 200 along a preset direction. When the driving mechanism 162 drives the fixing mechanism 161 to approach the silicon ingot 200, the fixing mechanism 161 can clamp the silicon ingot 200, which is beneficial for the appearance inspection device to inspect the silicon ingot 200; when the driving mechanism 162 drives the fixing mechanism 161 to move away from the silicon ingot 200, the fixing mechanism 161 can release the silicon ingot 200, which is beneficial for the loading and unloading of the silicon ingot 200.

[0105] More specifically, the fixing mechanism 161 has a contact surface 1611 that abuts against the end of the silicon ingot 200, and the fixing mechanism 161 is provided with a movable member 1612. Define a longitudinal plane 101 perpendicular to the preset direction, and adjust the angle between the contact surface 1611 and the longitudinal plane 101 based on the movable member 1612. With such a setting, the inclination angle between the contact surface 1611 and the longitudinal plane 101 can be adjusted, so that the contact surface 1611 can adapt to the silicon ingot 200 with an inclined end, which is beneficial to increasing the contact area between the contact surface 1611 and the end of the silicon ingot 200 along the preset direction, and further beneficial to improving the clamping stability of the fixing mechanism 161 on the silicon ingot 200.

[0106] Exemplarily, the fixing mechanism 161 includes a fixed end 1613, and the fixed end 1613 is connected to the driving mechanism 162 so that the driving mechanism 162 can drive the fixing mechanism 161 to move along a preset direction, thereby realizing the clamping and releasing of the silicon ingot 200. The movable member 1612 is set as a spherical shaft, one end of the spherical shaft away from the ball head is fixedly connected to the contact surface 1611, and the ball head of the spherical shaft is rotatably connected to the fixed end 1613. With such a setting, through the setting of the spherical shaft, the contact surface 1611 can rotate relative to the fixed end 1613, so that the contact surface 1611 can adjust the inclination angle relative to the longitudinal plane 101, and further the contact surface 1611 can adapt to the silicon ingot 200 with an inclined end, so as to improve the clamping stability of the clamping assembly 16 on the silicon ingot 200.

[0107] It should be noted that during the cutting process of the silicon ingot 200, due to cutting errors or the inclination of the silicon ingot 200 during the cutting process, there may be a situation where the opposite two end faces of the silicon ingot 200 are inclined planes, so that the contact surface 1611 capable of adjusting the inclination angle can adapt to the silicon ingot 200 with an inclined end face.

[0108] In this application, the detection process of the silicon ingot detection device 100 for the silicon ingot 200 is as follows:

[0109] First, place the silicon ingot 200 to be detected on the lifting component 15. The lifting component 15 drives the silicon ingot 200 to move to the same horizontal height as the clamping component, and then clamps the silicon ingot 200 through the clamping component. At this time, the lifting component 15 moves downward to avoid interference with the detection of the silicon ingot 200 by the lifting component 15.

[0110] Then, the moving component 13 drives the dimension and appearance detection device 12 to move forward on the guide rail 111, so that the silicon ingot detection device 100 performs dimension and appearance detection on the silicon ingot 200. At this time, the perpendicularity of the silicon ingot 200 and the parallelism of the opposite surfaces of the silicon ingot 200 are detected by the first sensor 121, and whether the curvature of the surface of the silicon ingot 200 meets the set threshold is detected by the second sensor 122. At the same time, the surface detection camera 123 detects the surface appearance quality of the silicon ingot 200. The infrared camera 126 and the infrared light source 125 detect the internal quality of the silicon ingot 200. Through the above components, the dimensions and appearance of the silicon ingot 200 can be detected, thereby improving the detection accuracy of the dimensions and appearance of the silicon ingot 200.

[0111] After the detection device is completed, the dimension and appearance detection device 12 resets, and the lifting component 15 moves upward so that the lifting component 15 bears the silicon ingot 200. Then, the clamping component releases the silicon ingot 200, and the lifting component 15 drives the silicon ingot 200 to move downward to realize the unloading of the silicon ingot 200, thereby completing the appearance and quality detection of the silicon ingot 200.

[0112] It should be understood that for those of ordinary skill in the art, improvements or transformations can be made according to the above description, and all such improvements and transformations should fall within the protection scope of the appended claims of this application.

Claims

1. A silicon square bar detection device, characterized in that The silicon square bar detection device includes: A frame (11), the frame (11) having a guide rail (111) extending along a preset direction; A size and appearance detection device (12), at least part of the size and appearance detection device (12) being mounted on the guide rail (111) and capable of moving relative to the frame (11) along the preset direction. The size and appearance detection device (12) includes a number of first sensors (121). During the detection of the silicon square bar, each of the number of first sensors (121) corresponds to an edge of the silicon square bar, and the number of first sensors (121) can detect the edges of the silicon square bar along the preset direction to obtain point cloud data corresponding to each edge; A control module, the control module being connected to the size and appearance detection device (12). The control module can acquire first point cloud data corresponding to a first edge (21), second point cloud data corresponding to a second edge (22), and third point cloud data corresponding to a third edge (23), and fit a first side (251) between the first edge (21) and the second edge (22) based on the first point cloud data and the second point cloud data, and fit a second side (261) between the second edge (22) and the third edge (23) based on the second point cloud data and the third point cloud data. The control module is used to determine the perpendicularity of the silicon square bar according to the included angle between the first side (251) and the second side (261) and judge whether the silicon square bar has size defects.

2. A silicon square bar detection device, characterized in that, The silicon square bar detection device includes: A frame (11), the frame (11) having a guide rail (111) extending along a preset direction; A size and appearance detection device (12), at least part of the size and appearance detection device (12) being mounted on the guide rail (111) and capable of moving relative to the frame (11) along the preset direction. The size and appearance detection device (12) includes a number of first sensors (121). During the detection of the silicon square bar, each of the number of first sensors (121) corresponds to an edge of the silicon square bar, and the number of first sensors (121) can detect the edges of the silicon square bar along the preset direction to obtain point cloud data corresponding to each edge; A control module, the control module being connected to the size and appearance detection device (12). The control module can acquire first point cloud data corresponding to a first edge (21) and determine two adjacent sides of the first edge (21) based on the first point cloud data. The control module is used to determine the perpendicularity of the silicon square bar according to the included angle between the two sides and judge whether the silicon square bar has size defects.

3. A silicon square bar detection device, characterized in that, The silicon square bar detection device includes: A frame (11), the frame (11) having a guide rail (111) extending along a preset direction; A dimensional and appearance detection device (12), at least part of the dimensional and appearance detection device (12) is installed on the guide rail (111), and can move relative to the frame (11) along the preset direction. The dimensional and appearance detection device (12) includes a plurality of first sensors (121). During the detection of the silicon square bar, each of the plurality of first sensors (121) corresponds to an edge of the silicon square bar. The plurality of first sensors (121) can detect the edges of the silicon square bar along the preset direction to obtain point cloud data corresponding to each edge; A control module, the control module is connected to the dimensional and appearance detection device (12). The control module can obtain the first point cloud data corresponding to the first edge (21), determine the two side edges adjacent to the first edge (21) based on the first point cloud data, and determine the normal lines of the two side edges respectively to obtain the included angle between the two normal lines. The control module is used to determine the perpendicularity of the silicon square bar according to the included angle between the two normal lines and judge whether the silicon square bar has dimensional defects.

4. A silicon square bar detection device, characterized in that, The silicon square bar detection device includes: A frame (11), the frame (11) has a guide rail (111) extending along a preset direction; A dimensional and appearance detection device (12), at least part of the dimensional and appearance detection device (12) is installed on the guide rail (111), and can move relative to the frame (11) along the preset direction. The dimensional and appearance detection device (12) includes a plurality of first sensors (121). During the detection of the silicon square bar, each of the plurality of first sensors (121) corresponds to an edge of the silicon square bar. The plurality of first sensors (121) can detect the edges of the silicon square bar along the preset direction to obtain point cloud data corresponding to each edge; A control module, the control module is connected to the dimensional and appearance detection device (12). The control module can obtain the first point cloud data corresponding to the first edge (21), the second point cloud data corresponding to the second edge (22), the third point cloud data corresponding to the third edge (23), and the fourth point cloud data corresponding to the fourth edge (24). Based on the first point cloud data and the second point cloud data, the first side edge (251) between the first edge (21) and the second edge (22) is fitted, and based on the third point cloud data and the fourth point cloud data, the third side edge (271) between the third edge (23) and the fourth edge (24) is fitted. The control module is used to judge whether the silicon square bar has dimensional defects according to the parallelism between the first side edge (251) and the third side edge (271).

5. The silicon square bar detection device according to any one of claims 1-4, characterized in that The first sensor (121) is further configured to acquire a brightness image of the edge, and the control module is configured to determine whether there is an appearance defect on the edge based on the brightness image.

6. The silicon square bar detection device according to any one of claims 1-4, wherein the size and appearance detection device (12) further includes a second sensor (122), the second sensor (122) is configured to detect a side surface of the silicon square bar to obtain surface point cloud data corresponding to the surface; the control module determines the curvature of the surface based on the surface point cloud data, and if the curvature of the surface is outside the set threshold range, it is determined that the silicon square bar has a size defect.

7. The silicon square bar detection device according to any one of claims 1-4, wherein the size and appearance detection device (12) further includes a plurality of surface detection cameras (123), each of the plurality of surface detection cameras (123) corresponds to a surface of the silicon square bar, and each surface detection camera (123) is configured with two light sources (124), and the two light sources (124) are respectively oriented towards the surface of the silicon square bar at different illumination angles.

8. The silicon square bar detection device according to claim 7, wherein the control module is electrically connected to the surface detection camera (123) and the two light sources (124) respectively. During the detection of the silicon square bar, the control module can control the two light sources (124) to illuminate the surface of the silicon square bar in sequence at a set interval, and the control module can control the surface detection camera (123) to generate two images with different lighting angles at the set interval. If there is a light spot in any one of the two images, the control module determines that there is an appearance defect on the side of the silicon square bar.

9. The silicon square bar detection device according to any one of claims 1-4, wherein the silicon square bar detection device further includes a crack detection device, the crack detection device includes an infrared light source (125) and an infrared camera (126), the infrared light source (125) and the infrared camera (126) are arranged opposite to each other, so that the infrared camera (126) can obtain the light emitted from the infrared light source (125) and passing through the silicon square bar to generate an infrared image; the control module is electrically connected to the infrared camera (126), and the control module can determine whether there is a crack inside the silicon square bar based on the gray value of the silicon square bar in the infrared image.

10. The silicon square bar detection device according to any one of claims 1-4, wherein the silicon square bar detection device further includes: a lifting assembly (15), the lifting assembly (15) is installed on the frame (11), and the lifting assembly (15) is configured to support the silicon square bar and can move relative to the frame (11) in the height direction; Two clamping assemblies (16) arranged along the preset direction, the lifting assembly (15) is located between the two clamping assemblies (16), and the two clamping assemblies (16) cooperate to clamp the silicon square bar arranged on the lifting assembly (15); The clamping assembly (16) includes a fixing mechanism (161) and a driving mechanism (162). The driving mechanism (162) is installed on the frame (11), and the driving mechanism (162) is used to drive the fixing mechanism (161) to approach or move away from the silicon square bar along the preset direction; the fixing mechanism (161) has a contact surface (1611) that abuts against the end of the silicon square bar, and the fixing mechanism (161) is provided with a movable member (1612). Define a longitudinal plane (101) perpendicular to the preset direction, and adjust the angle between the contact surface (1611) and the longitudinal plane (101) based on the movable member (1612).

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