CN115423803A - Assembly detection method, device, equipment and storage medium - Google Patents
Assembly detection method, device, equipment and storage medium Download PDFInfo
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- CN115423803A CN115423803A CN202211276840.1A CN202211276840A CN115423803A CN 115423803 A CN115423803 A CN 115423803A CN 202211276840 A CN202211276840 A CN 202211276840A CN 115423803 A CN115423803 A CN 115423803A
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T7/00—Image analysis
- G06T7/0002—Inspection of images, e.g. flaw detection
- G06T7/0004—Industrial image inspection
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T7/00—Image analysis
- G06T7/70—Determining position or orientation of objects or cameras
- G06T7/73—Determining position or orientation of objects or cameras using feature-based methods
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- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2207/00—Indexing scheme for image analysis or image enhancement
- G06T2207/30—Subject of image; Context of image processing
- G06T2207/30108—Industrial image inspection
- G06T2207/30141—Printed circuit board [PCB]
Abstract
The invention belongs to the technical field of electronic assembly, and discloses an assembly detection method, an assembly detection device, assembly detection equipment and a storage medium. The method comprises the steps of collecting image information of the PCB in the chip mounting assembly process, selecting target image information corresponding to each chip mounting process flow from the image information, determining a detection strategy according to the chip mounting process flow corresponding to the target image information, and performing anomaly detection on the chip mounting assembly process according to the detection strategy. Compared with the conventional manual detection, the method can firstly obtain the detection strategies corresponding to different patch process flows, and then carry out the abnormal detection on the corresponding patch process flows according to the detection strategies, so that the whole patch assembly process can be automatically and accurately detected.
Description
Technical Field
The present invention relates to the field of electronic assembly technologies, and in particular, to an assembly detection method, an assembly detection apparatus, an assembly detection device, and a storage medium.
Background
At present, an SMT (Surface Mount Technology) process mainly includes solder paste printing, solder paste detection, device mounting, reflow soldering, post-soldering detection, and other processes, and manual detection is required in an assembly process to avoid problems in the assembly process. However, it is time and labor consuming to detect by human, and inaccurate detection by visual observation may also occur. Therefore, how to accurately detect the assembling process of the patch becomes a problem to be solved urgently.
The above is only for the purpose of assisting understanding of the technical aspects of the present invention, and does not represent an admission that the above is prior art.
Disclosure of Invention
The invention mainly aims to provide an assembly detection method, an assembly detection device, equipment and a storage medium, and aims to solve the technical problem of accurately detecting the assembly process of a patch.
In order to achieve the above object, the present invention provides an assembly detection method, including the steps of:
collecting image information of a PCB in a chip mounting assembly process, and selecting target image information corresponding to each chip mounting process flow from the image information;
determining a detection strategy according to a patch process flow corresponding to the target image information;
and carrying out anomaly detection on the assembling process of the patch according to the detection strategy.
Optionally, the step of collecting image information of the PCB during the process of mounting and assembling the chip and selecting target image information corresponding to each chip process from the image information specifically includes:
collecting image information of a PCB in a surface mounting assembly process;
acquiring initial image information corresponding to each paster process flow from historical image information;
and selecting target image information corresponding to each paster process flow from the image information according to the initial image information.
Optionally, the step of selecting target image information corresponding to each tile process flow from the image information according to the initial image information specifically includes:
determining PCB characteristic information corresponding to each paster process flow according to the initial image information;
matching the characteristic information of the PCB with the image information to obtain a matching result;
and selecting target image information corresponding to each paster process flow from the image information according to the matching result.
Optionally, the step of performing anomaly detection on the patch assembly process according to the detection strategy specifically includes:
when the detection strategy is a tin printing detection strategy, acquiring first image information corresponding to a tin printing process from the historical image information;
acquiring standard points and standard positions of solder paste printing points in the first image information;
acquiring second image information corresponding to a tin printing process from the target image information, and acquiring actual points and actual positions of tin paste printing points in the second image information;
comparing the standard points with the actual points to obtain a point comparison result;
comparing the standard position with the actual position to obtain a position comparison result;
and carrying out tin printing detection according to the point number comparison result and the position comparison result.
Optionally, the step of performing anomaly detection on the patch assembly process according to the detection strategy further includes:
when the detection strategy is a stokehole QC detection strategy, acquiring third image information corresponding to a stokehole QC flow from the target image information;
acquiring the number and positions of the components in the third image information;
and carrying out pre-furnace QC detection according to the positions of the components and the number of the components.
Optionally, the step of performing anomaly detection on the patch assembly process according to the detection strategy further includes:
when the detection strategy is a welding detection strategy, acquiring the welding temperature condition of the PCB;
acquiring fourth image information corresponding to a welding process from the target image information;
acquiring welding tightness information and solder flow information of the component in the fourth image information;
and performing welding detection according to the welding temperature condition, the welding tightness information and the solder flow information.
Optionally, the step of performing anomaly detection on the patch assembly process according to the detection strategy further includes:
when the detection strategy is a post-welding detection strategy, acquiring fifth image information corresponding to a post-welding process from the target image information;
determining red glue position information and red glue using amount information according to the color information in the fifth image information;
and carrying out post-welding detection according to the red glue position information and the red glue dosage information.
In addition, to achieve the above object, the present invention also provides an assembly detection apparatus including:
the image acquisition module is used for acquiring image information of the PCB in the process of assembling the patches and selecting target image information corresponding to each patch process flow from the image information;
the strategy determining module is used for determining a detection strategy according to the patch process flow corresponding to the target image information;
and the assembly detection module is used for carrying out abnormity detection on the patch assembly process according to the detection strategy.
In addition, in order to achieve the above object, the present invention also provides an assembly inspection apparatus, including: a memory, a processor and an assembly detection program stored on the memory and executable on the processor, the assembly detection program configured to implement the steps of the assembly detection method as described above.
Furthermore, to achieve the above object, the present invention further proposes a storage medium having stored thereon an assembly detection program, which when executed by a processor, implements the steps of the assembly detection method as described above.
The method comprises the steps of collecting image information of the PCB in the chip mounting assembly process, selecting target image information corresponding to each chip mounting process flow from the image information, determining a detection strategy according to the chip mounting process flow corresponding to the target image information, and performing anomaly detection on the chip mounting assembly process according to the detection strategy. The method comprises the steps of selecting target image information corresponding to each paster process flow from the image information, determining a detection strategy according to the paster process flow corresponding to the target image information, and performing abnormity detection on the paster assembly process according to the detection strategy.
Drawings
FIG. 1 is a schematic structural diagram of an assembly detection device of a hardware operating environment according to an embodiment of the present invention;
FIG. 2 is a schematic flow chart diagram illustrating a first embodiment of an assembly inspection method according to the present invention;
FIG. 3 is a flow chart illustrating a second embodiment of an assembly inspection method according to the present invention;
FIG. 4 is a flow chart illustrating a third embodiment of an assembly inspection method according to the present invention;
FIG. 5 is a block diagram of the assembly inspection apparatus according to the first embodiment of the present invention.
The implementation, functional features and advantages of the objects of the present invention will be further explained with reference to the accompanying drawings.
Detailed Description
It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.
Referring to fig. 1, fig. 1 is a schematic structural diagram of an assembly detection device of a hardware operating environment according to an embodiment of the present invention.
As shown in fig. 1, the assembly inspection apparatus may include: a processor 1001, such as a Central Processing Unit (CPU), a communication bus 1002, a user interface 1003, a network interface 1004, and a memory 1005. The communication bus 1002 is used to implement connection communication among these components. The user interface 1003 may include a Display screen (Display), an input unit such as a Keyboard (Keyboard), and the optional user interface 1003 may also include a standard wired interface, a wireless interface. The network interface 1004 may optionally include a standard wired interface, a Wireless interface (e.g., a Wireless-Fidelity (Wi-Fi) interface). The Memory 1005 may be a Random Access Memory (RAM) or a Non-Volatile Memory (NVM), such as a disk Memory. The memory 1005 may alternatively be a storage device separate from the processor 1001.
Those skilled in the art will appreciate that the configuration shown in FIG. 1 does not constitute a limitation of the assembly detection device and may include more or fewer components than those shown, or some components may be combined, or a different arrangement of components.
As shown in fig. 1, a memory 1005, which is a storage medium, may include therein an operating system, a network communication module, a user interface module, and an assembly detection program.
In the assembly inspection apparatus shown in fig. 1, the network interface 1004 is mainly used for data communication with a network server; the user interface 1003 is mainly used for data interaction with a user; the processor 1001 and the memory 1005 of the assembly inspection apparatus of the present invention may be provided in the assembly inspection apparatus, which calls the assembly inspection program stored in the memory 1005 through the processor 1001 and executes the assembly inspection method provided by the embodiment of the present invention.
Based on the assembly detection device, an assembly detection method is provided in an embodiment of the present invention, and referring to fig. 2, fig. 2 is a schematic flow chart of a first embodiment of the assembly detection method of the present invention.
In this embodiment, the assembly detection method includes the following steps:
step S10: collecting image information of a PCB in a chip mounting assembly process, and selecting target image information corresponding to each chip mounting process flow from the image information;
it should be noted that the execution subject of the embodiment may be a computing service device with data processing, network communication and program running functions, such as a mobile phone, a tablet computer, a personal computer, etc., or an electronic device or an assembly detection device capable of implementing the above functions. The present embodiment and the following embodiments will be described below by taking the assembly inspection apparatus as an example.
It can be understood that the patch assembly process in this embodiment is completed on the PCB, and the image information refers to an image collected in the whole patch assembly process, and may be specifically set to be collected at preset time intervals, for example: the image is acquired every 1 second or every 3 seconds, which is not limited in this embodiment.
It should be understood that the chip mounting process flow may include processes such as tin printing, QC before furnace, welding, and post welding, the target image information corresponding to each chip mounting process flow may be selected from the image information in this embodiment, specifically, the target image information corresponding to each chip mounting process flow may be obtained by comparing the standard image corresponding to each process flow with the image information, and may also be obtained by other methods, which is not limited in this embodiment.
Step S20: determining a detection strategy according to a patch process flow corresponding to the target image information;
it can be understood that after the target image information is obtained, the chip mounting process flow corresponding to the target image information can be determined, and the chip mounting process flow of the step of tin printing, oven front QC, welding and post welding to which the target image information belongs can be judged. In addition, in this embodiment, different patch process flows correspond to different detection strategies, and a mapping relationship may be specifically set between the patch process flow and the detection strategy in advance, so that the detection strategy may be determined according to the patch process flow.
Step S30: and carrying out anomaly detection on the patch assembling process according to the detection strategy.
In specific implementation, the embodiment can perform anomaly detection on each patch process flow according to different detection strategies, so that anomaly detection can be performed on the whole patch assembly process.
In the embodiment, the image information of the PCB in the chip mounting assembly process is acquired, the target image information corresponding to each chip mounting process flow is selected from the image information, then the detection strategy is determined according to the chip mounting process flow corresponding to the target image information, and then the abnormity detection is carried out on the chip mounting assembly process according to the detection strategy. In the embodiment, the target image information corresponding to each patch process flow is selected from the image information, the detection strategy is determined according to the patch process flow corresponding to the target image information, and then the anomaly detection is performed on the patch assembly process according to the detection strategy.
Referring to fig. 3, fig. 3 is a flow chart illustrating an assembly inspection method according to a second embodiment of the present invention.
Based on the first embodiment described above, in the present embodiment, the step S10 includes:
step S101: collecting image information of a PCB in a surface mounting assembly process;
it can be understood that the process of assembling the patch in this embodiment is completed on the PCB, and the image information refers to an image collected in the whole process of assembling the patch, and may be specifically set to be collected at preset time intervals, for example: the image is acquired every 1 second or every 3 seconds, which is not limited in this embodiment.
Step S102: acquiring initial image information corresponding to each paster process flow from historical image information;
it should be understood that the historical image information refers to collecting an image of the PCB board in the process of assembling the chip on the PCB board that has completed the chip mounting process, and specifically, the model of the PCB board should be the same as that of the PCB board in this embodiment.
In a specific implementation, the initial image information corresponding to each of the tile process flows may be obtained from the historical image information, that is, the initial image information may include an image corresponding to each of the tile process flows.
Step S103: and selecting target image information corresponding to each paster process flow from the image information according to the initial image information.
Further, in order to accurately determine the target image information, in the present embodiment, the step S103 includes: determining PCB characteristic information corresponding to each chip mounting process flow according to the initial image information; matching the characteristic information of the PCB with the image information to obtain a matching result; and selecting target image information corresponding to each paster process flow from the image information according to the matching result.
It can be understood that, in this embodiment, the characteristic information of the PCB corresponding to each of the chip mounting process flows can be determined according to the initial image information, and in different chip mounting process flows, the corresponding characteristic information of the PCB is different, and the characteristic information of the PCB refers to the characteristic information corresponding to each of the chip mounting process flows of the PCB, and specifically may include: the feature information may be obtained specifically according to actual conditions, such as the dot number information of the printing dots, the position information of the component, and the like, which is not particularly limited in this embodiment.
It should be understood that the feature information corresponding to the image information of the PCB during the mounting process, that is, the feature information corresponding to each image, may be obtained, and then the feature information and the PCB feature information are sequentially matched, so as to obtain the image information successfully matched, and then the image information successfully matched is used as the target image information corresponding to each mounting process flow.
In the embodiment, the image information of the PCB in the process of assembling the patches is collected, the initial image information corresponding to each patch process flow is obtained from the historical image information, and the target image information corresponding to each patch process flow is selected from the image information according to the initial image information. In this embodiment, the initial image information corresponding to each of the tile process flows is obtained from the historical image information, and then the target image information corresponding to each of the tile process flows is selected from the image information according to the initial image information, so that the target image information corresponding to each of the tile process flows can be accurately obtained by combining the historical image information.
Referring to fig. 4, fig. 4 is a flowchart illustrating an assembly inspection method according to a third embodiment of the present invention.
Based on the foregoing embodiments, in this embodiment, the step S30 includes:
step S301: when the detection strategy is a tin printing detection strategy, acquiring first image information corresponding to a tin printing process from the historical image information;
it should be understood that, in the paster assembly process, the existing paster process is printing solder paste, namely the solder paste is printed on the PCB through a steel mesh screen, the solder paste needs to be printed on the PCB, and after the solder paste is printed, the solder paste needs to be printed for detection, and abnormality detection can be performed through a solder paste detection strategy.
It can be understood that the first image information corresponding to the tin printing process, that is, the first image information obtained after the tin printing process is completed, may include one image or multiple images, and this embodiment is not limited in particular.
Step S302: acquiring standard points and standard positions of solder paste printing points in the first image information;
it should be understood that after the first image information is subjected to image recognition, the standard point number and the standard position of the solder paste printing point can be obtained, the solder paste printing point refers to the center of gravity point of each solder paste printing area, and the specific manner of selecting the solder paste printing point can be to convert the first image information into a black-and-white picture, then set the gray level of the pixel point of which the gray level is smaller than the preset gray level threshold value in the black-and-white picture as 0, set the gray level of the pixel point of which the gray level is larger than the preset gray level threshold value in the black-and-white picture as 255, and then extract the area of which the gray level is 255 as the solder paste printing area, i.e., extract the center of gravity point of each solder paste printing area.
It is understood that the standard number of the solder paste printing points refers to the number of the solder paste printing points, and the standard position refers to the position of the solder paste printing points on the PCB, and may specifically include an abscissa and an ordinate.
Step S303: acquiring second image information corresponding to a tin printing process from the target image information, and acquiring actual points and actual positions of tin paste printing points in the second image information;
it can be understood that the second image information corresponding to the tin printing process, that is, the second image information obtained after the tin printing process is completed, may include one image or multiple images, and this embodiment is not limited in particular.
In a specific implementation, after the second image information is obtained, the actual number and the actual position of the solder paste printing dots in the second image information may also be obtained in the above manner, where the actual number corresponds to the standard number, and the actual position corresponds to the standard position.
Step S304: comparing the standard points with the actual points to obtain a point comparison result;
it should be understood that the standard point number and the actual point number are compared, and the specific comparison mode can be that when the difference value between the standard point number and the actual point number is smaller than a preset threshold value, the point number is not problematic; when the difference between the standard point number and the actual point number is greater than or equal to the preset threshold value, it is described that the point number has no problem, and the value of the preset threshold value can be set according to the actual situation, for example: 3. 5, and the like.
Step S305: comparing the standard position with the actual position to obtain a position comparison result;
it can be understood that the standard position is compared with the actual position, and the specific comparison mode can be that the distance between the standard position and the actual position is obtained, and when the distance between the standard position and the actual position is smaller than the preset distance, the position is not in problem; and when the distance between the standard position and the actual position is larger than or equal to the preset distance, the position is proved to have a problem. The value of the specific preset distance may be set according to actual conditions, and this embodiment does not specifically limit this.
Step S306: and carrying out tin printing detection according to the point number comparison result and the position comparison result.
In specific implementation, the tin printing detection can be performed according to the point number comparison result and the position comparison result, the tin printing detection is described to be abnormal under the condition that the point number is in a problem or the position is in a problem or the point number and the position are in a problem, the patch assembling work can be immediately stopped at the moment, and a worker is reminded to process the tin printing detection.
In the embodiment, when the detection strategy is the tin printing detection strategy, first image information corresponding to a tin printing process is obtained from historical image information, then standard points and standard positions of tin paste printing points in the first image information are obtained, then second image information corresponding to the tin printing process is obtained from target image information, actual points and actual positions of the tin paste printing points in the second image information are obtained, the standard points and the actual points are compared, a point comparison result is obtained, the standard positions and the actual positions are compared, a position comparison result is obtained, and tin printing detection is performed according to the point comparison result and the position comparison result. This embodiment is through standard point and the standard position who obtains in the first image information to obtain the actual point and the actual position in the second image information, then compare respectively, carry out the seal tin according to the contrast result again and detect, thereby can carry out anomaly detection to the seal tin automatically, and can make the testing result more accurate.
Further, in order to implement the pre-oven QC detection, in this embodiment, the step S30 further includes: when the detection strategy is a stokehole QC detection strategy, acquiring third image information corresponding to a stokehole QC flow from the target image information; acquiring the number and positions of the components in the third image information; and carrying out pre-furnace QC detection according to the positions of the components and the number of the components.
It will be appreciated that, during the patch assembly process, a pre-oven QC detection is required, at which time an anomaly detection may be performed via a pre-oven QC detection strategy.
It can be understood that the third image information corresponding to the stokehold QC procedure can be obtained from the target image information, and the second image information may include one image or a plurality of images, which is not limited in this embodiment.
In specific implementation, the number, types and positions of the components in the second image information can be acquired, and then the pre-furnace QC detection is performed according to the number, types and positions of the components. The specific detection mode can refer to the tin printing detection mode, namely image information corresponding to the stokehole QC flow in the historical image information is obtained, then the number, types and positions of components in the image information are compared respectively, and the stokehole QC detection is carried out according to the comparison result.
Further, in order to realize the welding detection, in this embodiment, the step S30 further includes: when the detection strategy is a welding detection strategy, acquiring the welding temperature condition of the PCB; acquiring fourth image information corresponding to a welding process from the target image information; acquiring welding tightness information and solder flow information of the component in the fourth image information; and performing welding detection according to the welding temperature condition, the welding tightness information and the solder flow information.
It should be noted that, in the process of assembling the patches, the process of the patches is welding, that is, overcurrent and reflow welding, after the welding is completed, welding detection is required, and abnormality detection can be performed through a welding detection strategy.
It can be understood that, in the process of the overcurrent reflow soldering, the soldering temperature curve may include four regions, namely, a preheating region, a holding region, a reflow region and a cooling region, where the soldering temperature region corresponding to each region is different, and the soldering temperature condition in this embodiment may include a temperature variation condition during the overcurrent reflow soldering.
It should be understood that the fourth image information corresponding to the welding process, that is, the fourth image information obtained after the welding process is completed, may be obtained from the target image information, and the fourth image information may include one image or multiple images, which is not limited in this embodiment. After the fourth image information is obtained, the solder close information of the component and the solder flow information in the fourth image information can be obtained, the solder close information refers to the solder close condition of the component and the PCB, and the solder flow information refers to the flow condition of the solder after melting, for example, the solder is in a solidification state in a cooling zone.
In a specific implementation, the present embodiment may perform welding detection according to a welding temperature condition, welding tightness information, and solder flow information, and specifically, may determine which temperature curve region is located according to the welding temperature condition, and then determine whether a state corresponding to the temperature curve region is satisfied at the current time according to the welding tightness information and the solder flow information, where if the state is satisfied, the welding is normal, and if the state is not satisfied, the welding is abnormal.
Further, in order to realize the post-welding detection, in this embodiment, the step S30 further includes: when the detection strategy is a post-welding detection strategy, acquiring fifth image information corresponding to a post-welding process from the target image information; determining red glue position information and red glue using amount information according to color information in the fifth image information; and carrying out post-welding detection according to the red glue position information and the red glue dosage information.
It should be understood that, fifth image information corresponding to a post-welding process may be obtained from the target image information, where the post-welding process refers to advanced wave soldering in a red glue process, that is, fifth image information obtained after the post-welding process is completed, and the fifth image information may include one image or multiple images, which is not limited in this embodiment.
It can be understood that the red glue is a red or yellow-white adhesive mixed with various materials such as a hardening agent, a pigment, a solvent and the like, so that the embodiment can acquire color information from the fifth image, and then can determine the position information of the red glue according to the color information, and can determine the usage information of the red glue according to the area range of the color information corresponding to the red glue.
In concrete implementation, can weld the detection after according to red gluey positional information and red gluey quantity information, concrete detection mode can be whether judge red gluey positional information is accurate, and red gluey under the general condition should be filled in the centre of two pads, then judges whether red gluey quantity information exceeds the volume of predetermineeing, and the volume of predetermineeing can set up according to actual conditions, and this embodiment does not do specific restriction to this.
In this embodiment, when the detection strategy is the post-welding detection strategy, fifth image information corresponding to the post-welding process is acquired from the target image information, then the red glue position information and the red glue usage information are determined according to color information in the fifth image information, and post-welding detection is performed according to the red glue position information and the red glue usage information. This embodiment is through confirming red gluey positional information and red gluey quantity information according to the colour information in the fifth image information, welds the detection after according to red gluey positional information and red gluey quantity information again to can weld after automatically and carry out anomaly detection, and can make the testing result more accurate.
Referring to fig. 5, fig. 5 is a block diagram illustrating a first embodiment of the assembly detection apparatus according to the present invention.
As shown in fig. 5, the assembly detection apparatus according to the embodiment of the present invention includes:
the image acquisition module 10 is used for acquiring image information of the PCB in the mounting assembly process and selecting target image information corresponding to each mounting process flow from the image information;
a policy determining module 20, configured to determine a detection policy according to a patch process flow corresponding to the target image information;
and the assembly detection module 30 is used for carrying out abnormity detection on the patch assembly process according to the detection strategy.
In the embodiment, the image information of the PCB in the chip mounting assembly process is collected, the target image information corresponding to each chip mounting process flow is selected from the image information, then the detection strategy is determined according to the chip mounting process flow corresponding to the target image information, and then the abnormity detection is carried out on the chip mounting assembly process according to the detection strategy. In the embodiment, the target image information corresponding to each patch process flow is selected from the image information, the detection strategy is determined according to the patch process flow corresponding to the target image information, and then the anomaly detection is performed on the patch assembly process according to the detection strategy.
It should be noted that the above-mentioned work flows are only illustrative and do not limit the scope of the present invention, and in practical applications, those skilled in the art may select some or all of them according to actual needs to implement the purpose of the solution of the present embodiment, and the present invention is not limited herein.
In addition, the technical details that are not described in detail in this embodiment can be referred to the assembly detection method provided in any embodiment of the present invention, and are not described herein again.
Based on the first embodiment of the assembly inspection apparatus of the present invention, a second embodiment of the assembly inspection apparatus of the present invention is provided.
In this embodiment, the image obtaining module 10 is further configured to collect image information of the PCB during a mounting process; acquiring initial image information corresponding to each paster process flow from historical image information; and selecting target image information corresponding to each paster process flow from the image information according to the initial image information.
Further, the image obtaining module 10 is further configured to determine, according to the initial image information, PCB characteristic information corresponding to each chip mounting process flow; matching the characteristic information of the PCB with the image information to obtain a matching result; and selecting target image information corresponding to each paster process flow from the image information according to the matching result.
Further, the assembly detection module 30 is further configured to, when the detection policy is a tin printing detection policy, obtain first image information corresponding to a tin printing process from the historical image information; acquiring the standard points and the standard positions of the solder paste printing points in the first image information; acquiring second image information corresponding to a tin printing process from the target image information, and acquiring actual points and actual positions of tin paste printing points in the second image information; comparing the standard points with the actual points to obtain a point comparison result; comparing the standard position with the actual position to obtain a position comparison result; and carrying out tin printing detection according to the point number comparison result and the position comparison result.
Further, the assembly detection module 30 is further configured to, when the detection policy is a stokehole QC detection policy, obtain third image information corresponding to a stokehole QC procedure from the target image information; acquiring the number and positions of the components in the third image information; and carrying out pre-furnace QC detection according to the positions of the components and the number of the components.
Further, the assembly detection module 30 is further configured to obtain a welding temperature condition of the PCB when the detection strategy is a welding detection strategy; acquiring fourth image information corresponding to a welding process from the target image information; acquiring welding tightness information and solder flow information of the component in the fourth image information; and carrying out welding detection according to the welding temperature condition, the welding tightness information and the solder flow information.
Further, the assembly detection module 30 is further configured to, when the detection strategy is a post-welding detection strategy, obtain fifth image information corresponding to a post-welding process from the target image information; determining red glue position information and red glue using amount information according to the color information in the fifth image information; and carrying out post-welding detection according to the red glue position information and the red glue dosage information.
Other embodiments or specific implementations of the assembly detection apparatus of the present invention may refer to the above method embodiments, and are not described herein again.
In addition, an embodiment of the present invention further provides a storage medium, where the storage medium stores an assembly detection program, and the assembly detection program, when executed by a processor, implements the steps of the assembly detection method as described above.
It should be noted that, in this document, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or system that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or system. Without further limitation, an element defined by the phrases "comprising a," "8230," "8230," or "comprising" does not exclude the presence of other like elements in a process, method, article, or system comprising the element.
The above-mentioned serial numbers of the embodiments of the present invention are only for description, and do not represent the advantages and disadvantages of the embodiments.
Through the above description of the embodiments, those skilled in the art will clearly understand that the method of the above embodiments can be implemented by software plus a necessary general hardware platform, and certainly can also be implemented by hardware, but in many cases, the former is a better implementation manner. Based on such understanding, the technical solutions of the present invention or portions thereof contributing to the prior art may be embodied in the form of a software product, where the computer software product is stored in a storage medium (such as a rom/ram, a magnetic disk, and an optical disk), and includes several instructions for enabling a terminal device (such as a mobile phone, a computer, a server, an air conditioner, or a network device) to execute the methods according to the embodiments of the present invention.
The above description is only a preferred embodiment of the present invention, and not intended to limit the scope of the present invention, and all modifications of equivalent structures and equivalent processes, which are made by using the contents of the present specification and the accompanying drawings, or directly or indirectly applied to other related technical fields, are included in the scope of the present invention.
Claims (10)
1. An assembly detection method, characterized in that it comprises the following steps:
collecting image information of a PCB in a chip mounting assembly process, and selecting target image information corresponding to each chip mounting process flow from the image information;
determining a detection strategy according to a patch process flow corresponding to the target image information;
and carrying out anomaly detection on the patch assembling process according to the detection strategy.
2. The assembly detection method according to claim 1, wherein the step of collecting image information of the PCB during the process of mounting the chip and selecting target image information corresponding to each process flow of the chip from the image information specifically comprises:
collecting image information of a PCB in a surface mounting assembly process;
acquiring initial image information corresponding to each paster process flow from historical image information;
and selecting target image information corresponding to each paster process flow from the image information according to the initial image information.
3. The assembly detection method according to claim 2, wherein the step of selecting the target image information corresponding to each tile process flow from the image information according to the initial image information specifically comprises:
determining PCB characteristic information corresponding to each paster process flow according to the initial image information;
matching the characteristic information of the PCB with the image information to obtain a matching result;
and selecting target image information corresponding to each paster process flow from the image information according to the matching result.
4. The assembly detection method according to claim 3, wherein the step of performing anomaly detection on the patch assembly process according to the detection strategy specifically includes:
when the detection strategy is a tin printing detection strategy, acquiring first image information corresponding to a tin printing process from the historical image information;
acquiring the standard points and the standard positions of the solder paste printing points in the first image information;
acquiring second image information corresponding to a tin printing process from the target image information, and acquiring actual points and actual positions of tin paste printing points in the second image information;
comparing the standard points with the actual points to obtain a point comparison result;
comparing the standard position with the actual position to obtain a position comparison result;
and carrying out tin printing detection according to the point number comparison result and the position comparison result.
5. The assembly detection method of claim 4, wherein the step of detecting an anomaly in the patch assembly process based on the detection strategy further comprises:
when the detection strategy is a stokehole QC detection strategy, acquiring third image information corresponding to a stokehole QC flow from the target image information;
acquiring the number and positions of the components in the third image information;
and carrying out pre-furnace QC detection according to the positions of the components and the number of the components.
6. The assembly inspection method of claim 5, wherein the step of detecting anomalies in the patch assembly process based on the inspection strategy further comprises:
when the detection strategy is a welding detection strategy, acquiring the welding temperature condition of the PCB;
acquiring fourth image information corresponding to a welding process from the target image information;
acquiring welding tightness information and solder flow information of the component in the fourth image information;
and performing welding detection according to the welding temperature condition, the welding tightness information and the solder flow information.
7. The assembly detection method of claim 6, wherein the step of detecting an anomaly in the patch assembly process based on the detection strategy further comprises:
when the detection strategy is a post-welding detection strategy, acquiring fifth image information corresponding to a post-welding process from the target image information;
determining red glue position information and red glue using amount information according to the color information in the fifth image information;
and carrying out post-welding detection according to the red glue position information and the red glue dosage information.
8. An assembly detection device, characterized in that the assembly detection device comprises:
the image acquisition module is used for acquiring image information of the PCB in the process of assembling the patches and selecting target image information corresponding to each patch process flow from the image information;
the strategy determining module is used for determining a detection strategy according to the patch process flow corresponding to the target image information;
and the assembly detection module is used for carrying out abnormity detection on the patch assembly process according to the detection strategy.
9. An assembly detection apparatus, characterized in that the apparatus comprises: a memory, a processor, and an assembly detection program stored on the memory and executable on the processor, the assembly detection program configured to implement the steps of the assembly detection method of any one of claims 1 to 7.
10. A storage medium having an assembly detection program stored thereon, the assembly detection program, when executed by a processor, implementing the steps of the assembly detection method according to any one of claims 1 to 7.
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