Circuit board surface defect detection device and method

Abstract

The embodiment of the invention provides a circuit board surface defect detection device and method. The circuit board surface defect detection device comprises a defect acquisition unit and a defect analysis unit, the defect acquisition unit comprises a precision displacement table, a line laser, an annular light source, an industrial lens, an optical splitter, an area-array camera I and an area-array camera II; the defect analysis unit comprises calculation analysis equipment and result display equipment; the detection method is realized based on the detection device. According to the device and the method, on the premise that two-dimensional defect detection and three-dimensional defect detection are realized at the same time, the process of registration of two-dimensional features and three-dimensional point cloud is simplified by adopting a common-caliber technology. In the feature extraction stage, the extraction result of the two-dimensional features is used as a priori condition of three-dimensional point cloud extraction, so that the computing power demand of detection equipment can be saved, and the detection efficiency is improved. In the defect identification process, the information contained in the two-dimensional features is combined with the three-dimensional point cloud, the defects are identified from multiple dimensions, and the detection of the surface defects of the circuit board can be accurately and quickly completed.

Description

Technical Field

[0001] The present application relates to the technical field of circuit board detection, and in particular to a circuit board surface defect detection device and method. Background Art

[0002] With the development of modern electronic technology, printed circuit boards (PCB) have been widely used in various common fields. At present, China has become the number one circuit board manufacturing country, and the export volume of circuit boards is also among the best in the world. In the production process, it is inevitable that defective circuit boards will be manufactured. Once these circuit boards flow into the market, they will bring great hidden dangers. Therefore, in order to prevent defective circuit boards from entering the market, screening them out during the inspection process has become an important part of production.

[0003] According to the characteristics of defects, the surface defects of circuit boards can be divided into two-dimensional defects and three-dimensional defects. Two-dimensional defects include short circuit, open circuit, less line, more line, line width, narrow line, pad missing, component offset, and wrong soldering and leakage; three-dimensional defects include bending deformation, cold soldering, solder bridging, etc. of the circuit board. At present, common circuit board surface defect detection methods include two-dimensional detection method, line laser scanning method and other three-dimensional detection methods. The two-dimensional detection method uses a camera to capture the image of the circuit board and identify various defects. The detection is fast and efficient, and can effectively obtain the color and texture of the target. However, the two-dimensional detection method cannot obtain the depth information of the circuit board, and it is difficult to identify three-dimensional defects such as solder cold soldering. The detection results are greatly affected by the shooting angle and lighting conditions. The line laser scanning method adopts structured light projection technology to obtain the three-dimensional morphology of the circuit board surface. The measurement results are less affected by external lighting conditions, but the color and texture of the circuit board cannot be obtained, and it is difficult to identify the silk screen of components and two-dimensional defects such as short circuit and open circuit. Summary of the invention

[0004] In view of the fact that two-dimensional detection methods are difficult to identify three-dimensional defects such as solder joint failure, and three-dimensional detection methods are difficult to identify two-dimensional defects such as silk screen printing and short circuits and open circuits of components, the present invention designs a circuit board surface defect detection device and method. The method adopts common aperture technology and multi-spectral technology to combine two-dimensional information and three-dimensional information to comprehensively judge whether there are defects from multiple dimensions. It can not only meet the detection requirements of two-dimensional defects and three-dimensional defects in circuit board detection, but also simplify the registration process of two-dimensional information and three-dimensional information. While enhancing the detection capability of circuit boards, it also improves the detection efficiency.

[0005] An embodiment of the present invention provides a circuit board surface defect detection device, comprising: a defect collection unit and a defect analysis unit;

[0006] The defect acquisition unit includes a precision translation stage, a line laser, a ring light source, an industrial lens, a beam splitter, a first area array camera and a second area array camera;

[0007] The industrial lens is vertically mounted on a mounting frame and is used to image defect information on the surface of the circuit board;

[0008] The line laser is installed at an angle, the optical axis of the line laser is coplanar with the optical axis of the industrial lens and forms an angle, the line laser can emit line laser, the spectrum range of the emitted laser is [λ1, λ2], and the three-dimensional information on the circuit board is encoded into a light strip signal;

[0009] The annular light source is installed in front of the industrial lens and keeps coaxial with the industrial lens, and the spectrum range of the emitted light is [λ3,λ4];

[0010] The beam splitter is installed behind the industrial lens, and splits the light beam entering the industrial lens according to the spectral range. The beam splitting ratio of the beam splitter is 50:50. The exit planes of the two light beams are coated with a filter film. The spectral band allowed to pass through the exit plane of one light beam is consistent with that of the line laser, which is [λ1,λ2], and the spectral band allowed to pass through the exit plane of the other light beam is consistent with that of the ring light source, which is [λ3,λ4].

[0011] The first area array camera and the second area array camera have the same parameters and are both installed on the imaging plane of the industrial lens, and receive the two light beams of the beam splitter respectively;

[0012] The precision displacement stage is installed below the industrial lens and ensures that the surface of the precision displacement stage is within the depth of field of the industrial lens. The precision displacement stage is used to drive the circuit board to move in a single axis.

[0013] The defect analysis unit includes a calculation and analysis device and a result display device;

[0014] The computing and analyzing device is responsible for extracting and identifying two-dimensional defects and three-dimensional defects of the circuit board from the multi-spectral information of the circuit board collected in the defect collection unit;

[0015] The result display device is used to display the multi-spectral information results and defect recognition results of the circuit board.

[0016] In some embodiments, the defect collection unit adopts multi-spectral encoding and decoding technology and co-aperture technology to encode the two-dimensional defects and three-dimensional defects on the surface of the circuit board into different spectral bands respectively, and collects information in the two spectral bands through the co-aperture area array camera 1 and the area array camera 2.

[0017] In some embodiments, the defect analysis unit uses the multi-spectral information of the circuit board collected by the defect collection unit to decode the line laser information in the [λ1, λ2] band to obtain the three-dimensional morphology of the circuit board surface, and each point in the three-dimensional point cloud is represented by coordinates (x, y, z). The image in the [λ3, λ4] band is processed to obtain two-dimensional defects on the circuit surface, and the color of each point on the image is represented by (R, G, B).

[0018] An embodiment of the present invention provides a circuit board surface defect detection method. Based on the circuit board surface defect detection device described in any of the above embodiments, the method includes:

[0019] Step 1: Install and fix the circuit board to be tested on the precision translation stage, and turn on the precision translation stage to drive the circuit board to move;

[0020] Step 2: Turn on the line laser and the ring light source. The line laser and the ring light source irradiate the light beam onto the circuit board. The light beam is reflected by the surface of the circuit board and enters the industrial lens for imaging.

[0021] Step 3: After the beam splitter splits the light beam entering the industrial lens according to the spectral range, it is collected by two area array cameras respectively to obtain two circuit board images with different spectral bands;

[0022] Step 4: extract the center of the light stripe from the online laser image using a line laser light stripe center extraction algorithm, extract the center of the light stripe and calculate the three-dimensional point cloud coordinates;

[0023] Step 5: According to the extracted center position of the light strip, the corresponding texture color information is indexed, that is, the extraction and registration of the two-dimensional information and the three-dimensional information are completed;

[0024] Step 6: Through image segmentation and recognition algorithms, components, solder joints and other features in the two-dimensional image are segmented and recognized. The segmentation results of the two-dimensional image are directly used for the pre-segmentation of the three-dimensional point cloud.

[0025] Step seven, using a circuit board defect recognition algorithm to identify the segmented two-dimensional texture image and three-dimensional point cloud, and displaying the defect recognition result through a display device.

[0026] In some embodiments, the step 4, extracting the center of the light stripe from the online laser image by using a line laser light stripe center extraction algorithm, extracting the center of the light stripe and calculating the three-dimensional point cloud coordinates, includes:

[0027] The line laser stripe center extraction algorithm is used to extract the center of the light stripe from the online laser image, and a set of n light stripe center coordinates {(X 1 ,Y 1 ),……,(X n ,Y n)}, calculate the three-dimensional point cloud coordinates (x, y, z) according to the formula;

[0028] The centroid method can be used to extract the center of the laser light strip, and the calculation formula is as follows:

[0029]

[0030] Among them, I(X,Y) is the gray value of the pixel on the line laser image, X is the horizontal coordinate of the pixel on the image, and Y is the vertical coordinate of the pixel on the image. 1 Y is the horizontal coordinate of the center of the laser light strip extracted by the centroid method, 1 is the ordinate of the center of the laser light strip extracted by the centroid method;

[0031] Since the center coordinates of the light strip calculated by the centroid method are in the image coordinate system and the unit is the number of pixels, it is necessary to convert the center coordinates of the light strip to the world coordinate system and convert the units to common units such as mm. The conversion formula is as follows:

[0032]

[0033] Among them, x', y', z' are the center coordinates of the light bar in the world coordinate system, s is the pixel size of the camera, and X 0 and Y 0 are the coordinates of the image center, respectively, and f is the focal length of the industrial lens;

[0034] Combine the coordinate calculation result in formula 2 with the light plane equation Ax+By+Cz+D=0 to obtain the three-dimensional point cloud coordinates (x, y, z).

[0035] The beneficial effects of the above embodiments include:

[0036] The device and method use the common aperture technology to simplify the process of aligning two-dimensional features with three-dimensional point clouds while realizing two-dimensional defect detection and three-dimensional defect detection at the same time. In the feature extraction stage, the extraction results of the two-dimensional features are used as the prior conditions for the extraction of the three-dimensional point cloud, which can save the computing power requirements of the detection equipment and improve the detection efficiency. In the defect identification process, the information contained in the two-dimensional features is combined with the three-dimensional point cloud to identify defects from multiple dimensions, which can accurately and quickly complete the detection of circuit board surface defects. BRIEF DESCRIPTION OF THE DRAWINGS

[0037] The drawings illustrate generally, by way of example and not limitation, various embodiments discussed herein.

[0038] Figure 1 It is a schematic diagram of the composition of a circuit board surface defect detection device;

[0039] Figure 2 The present invention is a flow chart of a method for detecting an inclination rotation error using the present device.

[0040] Explanation of symbols:

[0041] 1-precision translation stage; 2-line laser; 3-ring light source; 4-industrial lens; 5-area array camera 1; 6-beam splitter; 7-area array camera 2; 8-result display device; 9-computing and analysis equipment. DETAILED DESCRIPTION

[0042] In order to enable a more detailed understanding of the features and technical contents of the embodiments of the present application, the implementation of the embodiments of the present application is described in detail below in conjunction with the accompanying drawings. The attached drawings are for reference only and are not used to limit the embodiments of the present application.

[0043] In the embodiments of the present application, it should be noted that, unless otherwise specified and limited, the term "connection" should be understood in a broad sense. For example, it can be an electrical connection or a connection between two components. It can be a direct connection or an indirect connection through an intermediate medium. For ordinary technicians in this field, the specific meanings of the above terms can be understood according to the specific circumstances.

[0044] It should be noted that the terms "first\second\third" involved in the embodiments of the present application are only used to distinguish similar objects, and do not represent a specific order for the objects. It is understandable that the specific order or sequence of "first\second\third" can be interchanged where permitted. It should be understood that the objects distinguished by "first\second\third" can be interchanged where appropriate, so that the embodiments of the present application described herein can be implemented in an order other than those illustrated or described herein.

[0045] The present invention proposes a circuit board surface defect detection device, which is divided into a defect collection unit and a defect analysis unit. Figure 1 The defect acquisition unit includes a precision displacement stage 1, a line laser 2, a ring light source 3, an industrial lens 4, a surface array camera 1 5, a beam splitter 6 and a surface array camera 2 7. The defect analysis unit includes a calculation and analysis device 9 and a result display device 8.

[0046] The defect acquisition unit adopts multi-spectral encoding and decoding technology and co-aperture technology to encode the two-dimensional defects and three-dimensional defects on the surface of the circuit board into different spectral bands respectively, and collects the information in the two spectral bands through the co-aperture area array camera. Under the premise of simplifying the registration steps of two-dimensional information and three-dimensional information, the two-dimensional defects and three-dimensional defects on the surface of the circuit board are effectively collected. Among them, the industrial lens 4 is vertically installed on the mounting frame to image the defect information on the surface of the circuit board. The line laser 2 is installed at an angle, and the optical axis of the line laser 2 is coplanar with the optical axis of the industrial lens 4 and forms a certain angle. The line laser 2 can emit a line laser, and the spectral range of the emitted laser is [λ 1 ,λ2 ], the three-dimensional information on the circuit board is encoded into a light bar signal. The ring light source 3 is installed in front of the industrial lens 4 and is coaxial with the lens. The spectral range of its emitted light is [λ 3 ,λ 4 ]. The beam splitter 6 is installed behind the industrial lens 4 to split the light beam entering the lens according to the spectral range. The splitting ratio of the beam splitter 6 is 50:50. The exit planes of the two beams are coated with filter films. The spectral band allowed to pass through the exit plane of one beam is consistent with that of the line laser 2, which is [λ 1 ,λ 2 ]; the spectral band allowed to pass through the exit plane of the other beam is consistent with the annular light source 3, which is [λ 3 ,λ 4 ] The two area array cameras, area array camera 1 5 and area array camera 2 7, have the same parameters and are both installed on the imaging plane of the industrial lens 4, respectively receiving the two beams of the beam splitter 6. The precision translation stage 1 is installed below the industrial lens 4 and ensures that the surface of the precision translation stage 1 is within the depth of field of the industrial lens 4. The precision translation stage 1 is used to drive the circuit board to move in a single axis.

[0047] The defect analysis unit uses the multi-spectral information of the circuit board collected by the defect collection unit to analyze [λ 1 ,λ 2 ] band line laser information is decoded to obtain the three-dimensional morphology of the circuit board surface. Each point in the three-dimensional point cloud is represented by coordinates (x, y, z). 3 ,λ 4 ] band images are processed to obtain two-dimensional defects on the circuit surface, and the color of each point on the image is represented by (R, G, B). In addition, for two-dimensional information such as color texture, image segmentation and image recognition technology are used to segment and identify features such as components and solder joints on the circuit board. Since the two array cameras have the same aperture, the two-dimensional information and the three-dimensional information have been aligned, and the results of segmentation and recognition can be directly used for the extraction and identification of three-dimensional defects, which can effectively reduce the computing power requirements for three-dimensional defect identification and improve the recognition rate. The computing and analysis device 9 is responsible for extracting and identifying the two-dimensional defects and three-dimensional defects of the circuit board from the multi-spectral information of the circuit board collected in the defect acquisition unit. The result display device 8 is used to display the multi-spectral information results of the circuit board and the defect recognition results.

[0048] The circuit board surface defect detection device is used to detect the circuit board surface defects, and the steps are as follows:

[0049] Step 1: Install and fix the circuit board to be tested on the precision translation stage, and turn on the precision translation stage to drive the circuit board to move at a constant speed.

[0050] Step 2: Turn on the line laser and the ring light source. The line laser and the ring light source irradiate the light beam onto the circuit board. The light beam is reflected by the surface of the circuit board and enters the industrial lens for imaging.

[0051] Step three: After the beam splitter splits the light beam entering the industrial lens according to the spectral range, it is collected separately by two area array cameras to obtain two circuit board images in different spectral bands.

[0052] Step 4: extract the center of the light stripe from the online laser image using the line laser light stripe center extraction algorithm, extract the center of the light stripe and calculate the three-dimensional point cloud coordinates.

[0053] Specifically, the line laser light stripe center extraction algorithm is used to extract the light stripe center from the online laser image, and a set of n light stripe center coordinates {(X 1 ,Y 1 ),……,(X n ,Y n )}, and calculate the 3D point cloud coordinates (x, y, z) according to the formula.

[0054] The centroid method can be used to extract the center of the laser light strip, and the calculation formula is as follows:

[0055]

[0056] Where I(X,Y) is the grayscale value of the pixel on the line laser image, X is the horizontal coordinate of the pixel on the image, and Y is the vertical coordinate of the pixel on the image. 1 Y is the horizontal coordinate of the center of the laser light strip extracted by the centroid method, 1 It is the ordinate of the center of the laser light strip extracted by the centroid method.

[0057] Since the center coordinates of the light strip calculated by the centroid method are in the image coordinate system and the unit is the number of pixels, it is necessary to convert the center coordinates of the light strip to the world coordinate system (generally the camera coordinate system is set to the world coordinate system) and convert the units to common units such as mm. The conversion formula is as follows:

[0058]

[0059] Among them, x', y', z' are the center coordinates of the light bar in the world coordinate system, s is the pixel size of the camera, and X 0 and Y 0 are the coordinates of the image center, and f is the focal length of the industrial lens.

[0060] Combine the coordinate calculation result in formula 2 with the light plane equation Ax+By+Cz+D=0 to obtain the three-dimensional point cloud coordinates (x, y, z).

[0061] Step 5: According to the extracted light bar center position {(X 1 ,Y1 ),……,(X n ,Y n )}, index to the corresponding texture color information {(R 1 ,G 1 ,B 1 ),……,(R n ,G n ,B n )}, that is, the extraction and registration of two-dimensional information and three-dimensional information are completed, and the registered point cloud can be expressed as (x, y, z, R, G, B).

[0062] Step six: Through image segmentation, recognition and other algorithms, the features such as components and solder joints in the two-dimensional image are segmented and recognized. The segmentation results of the two-dimensional image are directly used for the pre-segmentation of the three-dimensional point cloud.

[0063] Step seven, using a circuit board defect recognition algorithm to identify the segmented two-dimensional texture image and three-dimensional point cloud, and displaying the defect recognition result through a display device.

[0064] The device and method use the common aperture technology to simplify the process of aligning two-dimensional features with three-dimensional point clouds while realizing two-dimensional defect detection and three-dimensional defect detection at the same time. In the feature extraction stage, the extraction results of the two-dimensional features are used as the prior conditions for the extraction of the three-dimensional point cloud, which can save the computing power requirements of the detection equipment and improve the detection efficiency. In the defect identification process, the information contained in the two-dimensional features is combined with the three-dimensional point cloud to identify defects from multiple dimensions, which can accurately and quickly complete the detection of circuit board surface defects.

[0065] The technical solutions described in the embodiments of the present application can be combined arbitrarily without conflict.

[0066] The above is only a specific implementation of the present application, but the protection scope of the present application is not limited thereto. Any person skilled in the art who is familiar with the present technical field can easily think of changes or substitutions within the technical scope disclosed in the present application, which should be included in the protection scope of the present application. Therefore, the protection scope of the present application should be based on the protection scope of the claims.

Claims

1. A circuit board surface defect detection device, characterized in that: include: Defect collection unit and defect analysis unit; The defect acquisition unit includes a precision translation stage, a line laser, a ring light source, an industrial lens, a beam splitter, a first area array camera and a second area array camera; The industrial lens is vertically mounted on a mounting frame and is used to image defect information on the surface of the circuit board; The line laser is installed at an angle, the optical axis of the line laser is coplanar with the optical axis of the industrial lens and forms an angle, the line laser can emit line laser, the spectrum range of the emitted laser is [λ1, λ2], and the three-dimensional information on the circuit board is encoded into a light strip signal; The annular light source is installed in front of the industrial lens and keeps coaxial with the industrial lens, and the spectrum range of the emitted light is [λ3,λ4]; The beam splitter is installed behind the industrial lens, and splits the light beam entering the industrial lens according to the spectral range. The beam splitting ratio of the beam splitter is 50:

50. The exit planes of the two light beams are coated with a filter film. The spectral band allowed to pass through the exit plane of one light beam is consistent with that of the line laser, which is [λ1,λ2], and the spectral band allowed to pass through the exit plane of the other light beam is consistent with that of the ring light source, which is [λ3,λ4]. The first area array camera and the second area array camera have the same parameters and are both installed on the imaging plane of the industrial lens, and receive the two light beams of the beam splitter respectively; The precision displacement stage is installed below the industrial lens and ensures that the surface of the precision displacement stage is within the depth of field of the industrial lens. The precision displacement stage is used to drive the circuit board to move in a single axis. The defect analysis unit includes a calculation and analysis device and a result display device; The computing and analyzing device is responsible for extracting and identifying two-dimensional defects and three-dimensional defects of the circuit board from the multi-spectral information of the circuit board collected in the defect collection unit; The result display device is used to display the multi-spectral information results and defect recognition results of the circuit board.

2. The circuit board surface defect detection device according to claim 1, characterized in that: The defect collection unit adopts multi-spectral encoding and decoding technology and common aperture technology to encode the two-dimensional defects and three-dimensional defects on the surface of the circuit board into different spectral bands respectively, and collects information in the two spectral bands through the area array camera 1 and the area array camera 2 of the common aperture.

3. The circuit board surface defect detection device according to claim 2, characterized in that: The defect analysis unit uses the multi-spectral information of the circuit board collected in the defect collection unit to decode the line laser information in the [λ1, λ2] band to obtain the three-dimensional morphology of the circuit board surface. Each point in the three-dimensional point cloud is represented by coordinates (x, y, z). The image in the [λ3, λ4] band is processed to obtain two-dimensional defects on the circuit surface. The color of each point on the image is represented by (R, G, B).

4. A circuit board surface defect detection method, based on the circuit board surface defect detection device according to any one of claims 1 to 3, characterized in that: The method comprises: Step 1: Install and fix the circuit board to be tested on the precision translation stage, and turn on the precision translation stage to drive the circuit board to move; Step 2: Turn on the line laser and the ring light source. The line laser and the ring light source irradiate the light beam onto the circuit board. The light beam is reflected by the surface of the circuit board and enters the industrial lens for imaging. Step 3: After the beam splitter splits the light beam entering the industrial lens according to the spectral range, it is collected by two area array cameras respectively to obtain two circuit board images with different spectral bands; Step 4: extract the center of the light stripe from the online laser image using a line laser light stripe center extraction algorithm, extract the center of the light stripe and calculate the three-dimensional point cloud coordinates; Step 5: According to the extracted center position of the light strip, the corresponding texture color information is indexed, that is, the extraction and registration of the two-dimensional information and the three-dimensional information are completed; Step 6: Use image segmentation and recognition algorithms to segment and identify features such as components and solder joints in the two-dimensional image. The segmentation results of the two-dimensional image are directly used for pre-segmentation of the three-dimensional point cloud. Step seven, using a circuit board defect recognition algorithm to identify the segmented two-dimensional texture image and three-dimensional point cloud, and displaying the defect recognition result through a display device.

5. The circuit board surface defect detection method according to claim 4, characterized in that: The fourth step, extracting the center of the light stripe from the online laser image by using the line laser light stripe center extraction algorithm, extracting the center of the light stripe and calculating the three-dimensional point cloud coordinates, includes: The line laser stripe center extraction algorithm is used to extract the stripe center from the online laser image, and a set of n stripe center coordinates {(X1, Y1), ..., (X n ,Y n )}, calculate the three-dimensional point cloud coordinates (x, y, z) according to the formula; The centroid method can be used to extract the center of the laser light strip, and the calculation formula is as follows: Where I(X,Y) is the grayscale value of the pixel on the line laser image, X is the horizontal coordinate of the pixel on the image, Y is the vertical coordinate of the pixel on the image, X1 is the horizontal coordinate of the center of the laser light strip extracted by the centroid method, and Y1 is the vertical coordinate of the center of the laser light strip extracted by the centroid method; Since the center coordinates of the light strip calculated by the centroid method are in the image coordinate system and the unit is the number of pixels, it is necessary to convert the center coordinates of the light strip to the world coordinate system and convert the units to common units such as mm. The conversion formula is as follows: Among them, x', y', z' are the coordinates of the center of the light bar in the world coordinate system, s is the pixel size of the camera, X0 and Y0 are the coordinates of the center of the image, and f is the focal length of the industrial lens; Combine the coordinate calculation result in formula 2 with the light plane equation Ax+By+Cz+D=0 to obtain the three-dimensional point cloud coordinates (x, y, z).

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