CN118052753A

CN118052753A - Defect processing method, device, electronic equipment and storage medium

Info

Publication number: CN118052753A
Application number: CN202211407654.7A
Authority: CN
Inventors: 姜克营; 曹李辉; 陈成锦
Original assignee: Jiangsu Longi Solar Technology Co Ltd
Current assignee: Jiangsu Longi Solar Technology Co Ltd
Priority date: 2022-11-10
Filing date: 2022-11-10
Publication date: 2024-05-17

Abstract

The embodiment of the application provides a defect processing method, a defect processing device, electronic equipment and a storage medium. The defect processing method comprises the following steps: performing defect detection on a target object on the stringer to obtain target object defect information, wherein the target object comprises a belt or a battery string; acquiring defect processing information associated with target object defect information; generating early warning information containing defect information and defect processing information of the target object. According to the embodiment of the application, automatic defect detection can be realized on the belt or the battery string, so that the timeliness and the accuracy of defect detection are higher, and the defect information of the target object and the associated defect processing information can be automatically displayed to a maintainer, so that the maintainer can process the defect of the target object according to the defect processing information, the requirement on personal experience of the maintainer is reduced, and the defect processing is more standardized.

Description

Defect processing method, device, electronic equipment and storage medium

Technical Field

The present application relates to the field of semiconductor technologies, and in particular, to a defect processing method, a defect processing device, an electronic device, and a storage medium.

Background

In industrial production and manufacture, as the utilization rate of automatic equipment is increased, spare parts can be replaced regularly in long-term use of the equipment, so that the loss of the spare parts is reduced, and the technology is a technology to be broken through in the industrial production and manufacture industry.

In the photovoltaic module production industry, one type of equipment used is a stringer. The battery piece is conveyed by a mechanical transmission mechanism, and is welded on a heating bottom plate by high-temperature gas of a hot air pipe, so that a battery string is obtained.

After a period of production, the string welder may have a belt or battery string therein that may be defective. In the prior art, a belt or a battery string is usually subjected to defect detection based on personal experience by means of manual processing, and then the detected defect is processed. However, the manual processing mode has poor timeliness of defect detection and high requirement on personal experience of maintenance personnel.

Disclosure of Invention

In view of the above problems, an embodiment of the present application provides a defect processing method, a device, an electronic apparatus, and a storage medium, which are used for solving the technical problems of poor timeliness of defect detection and high requirement on personal experience of maintenance personnel in a manual processing manner.

According to an aspect of an embodiment of the present application, there is provided a defect processing method including: performing defect detection on a target object on a stringer to obtain target object defect information, wherein the target object comprises a belt or a battery string; acquiring defect processing information associated with the target object defect information; generating early warning information containing the defect information of the target object and the defect processing information.

Optionally, the defect handling information includes at least one of: associated object defect information associated with the target object defect information, series welding machine defect information associated with the target object defect information, defect maintenance information associated with the target object defect information.

Optionally, when the target object is a belt, the associated object is a battery string; when the target object is a battery string, the associated object is a belt.

Optionally, in the case that the target object is a belt, the defect processing information further includes: belt life information associated with the target object defect information.

Optionally, the acquiring defect processing information associated with the target object defect information includes: retrieving from a pre-established target object knowledge base based on the target object defect information to obtain defect processing information; and the target object knowledge base stores the association relation between the defect information and the defect processing information of each target object.

Optionally, the defect detection on the target object on the stringer includes: acquiring an image to be detected of the target object; inputting the image to be detected into a pre-trained defect detection model to obtain the output of the defect detection model, wherein the output represents the defect information of the target object.

Optionally, the defect detection model is trained by: acquiring a sample image and a sample label of the target object, wherein the sample label represents actual target object defect information corresponding to the sample image; taking the sample image as input of a model to be trained, taking the sample label as an output target of the model to be trained, and training the model to be trained; and taking the trained model as the defect detection model.

According to another aspect of an embodiment of the present application, there is provided a defect processing apparatus including: the detection module is used for carrying out defect detection on a target object on the series welding machine to obtain target object defect information, wherein the target object comprises a belt or a battery string; an acquisition module for acquiring defect processing information associated with the target object defect information; and the generation module is used for generating early warning information containing the defect information of the target object and the defect processing information.

Optionally, the acquiring module is specifically configured to retrieve, based on the target object defect information, from a pre-created target object knowledge base, to obtain the defect processing information; and the target object knowledge base stores the association relation between the defect information and the defect processing information of each target object.

Optionally, the detection module is specifically configured to obtain an image to be detected of the target object; inputting the image to be detected into a pre-trained defect detection model to obtain the output of the defect detection model, wherein the output represents the defect information of the target object.

Optionally, the defect detection model is trained by the following modules: the sample acquisition module is used for acquiring a sample image and a sample label of the target object, wherein the sample label represents the defect information of the actual target object corresponding to the sample image; the model training module is used for taking the sample image as input of a model to be trained, taking the sample label as an output target of the model to be trained, and training the model to be trained; and taking the trained model as the defect detection model.

According to another aspect of an embodiment of the present application, there is provided an electronic apparatus including: one or more processors; and one or more computer-readable storage media having instructions stored thereon; the instructions, when executed by the one or more processors, cause the processors to perform the defect handling method of any of the above claims.

According to another aspect of embodiments of the present application, there is provided a computer-readable storage medium having stored thereon a computer program which, when executed by a processor, causes the processor to perform the defect processing method as set forth in any one of the above.

In the embodiment of the application, the defect information of the target object is obtained by carrying out defect detection on the target object on the series welding machine, and the target object comprises the belt or the battery string, so that the belt or the battery string can be automatically detected, and the timeliness and the accuracy of the defect detection are higher; by acquiring the defect processing information related to the defect information of the target object and generating early warning information containing the defect information of the target object and the defect processing information, the defect information of the target object and the related defect processing information can be automatically displayed to maintenance personnel, so that the maintenance personnel can process the defects of the target object according to the defect processing information, the requirement on personal experience of the maintenance personnel is reduced, and the defect processing is more standardized.

Drawings

In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings that are needed in the description of the embodiments of the present application will be briefly described below, and it is obvious that the drawings in the following description are only some drawings of the present application, and other drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.

FIG. 1 is a flow chart showing the steps of a defect processing method according to an embodiment of the present application.

FIG. 2 is a schematic diagram of a defect handling process according to an embodiment of the present application.

FIG. 3 is a schematic diagram of another defect handling process according to an embodiment of the present application.

Fig. 4 is a block diagram of a defect processing apparatus according to an embodiment of the present application.

Fig. 5 is a schematic structural diagram of an electronic device according to an embodiment of the present application.

Detailed Description

The technical solutions of the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application, and it is apparent that the described embodiments are only some embodiments of the present application, not all embodiments of the present application. All other embodiments, which can be made by those skilled in the art based on the embodiments of the application without making any inventive effort, are intended to be within the scope of the application.

In the embodiment of the application, considering that certain defects detected based on the belt can directly reflect the defect information existing on the battery string, and certain defects detected based on the battery string can directly reflect the defect information existing on the belt, so that a relevant judgment model can be trained according to practical experience and used for detecting and processing relevant defects, the defects of the belt and the battery string can be detected, the defects of the battery string can be related to the defect information of the belt, the defects of the battery string can be related to the defect information of the battery string, and the like, and the information related to the detected defect information can be further obtained after the defect information is detected, thereby realizing timely processing of the defect information and the information related to the defect information.

Referring to fig. 1, a flowchart of steps of a defect processing method according to an embodiment of the present application is shown.

As shown in fig. 1, the defect processing method may include the steps of:

And step 101, performing defect detection on the target object on the stringer to obtain target object defect information.

In an embodiment of the present application, the target objects on the stringer may include, but are not limited to: belts, battery strings, etc.

In the embodiment of the application, the defect detection can be carried out on the target object on the series welding machine by adopting modes of comparison detection, model detection and the like, so as to obtain the defect information of the target object.

For example, in the comparison detection mode, a standard image of the target object may be preset, where the standard image of the target object refers to an image corresponding to the target object when the target object has no defect, and an image capturing device is installed at a suitable position on the stringer, where the image capturing device is used to acquire the image of the target object on the stringer in real time or at a fixed time.

In the process of carrying out defect detection on a target object on the series welding machine, the following operations are executed:

first, an image of a target object acquired by an image pickup apparatus is acquired, and the image is taken as an image to be detected of the target object.

And then comparing the image to be detected of the target object acquired by the image pickup equipment with a preset standard image of the target object, and determining whether the image to be detected of the target object is consistent with the standard image of the target object.

Finally, if the partial area in the image to be detected of the target object is inconsistent with the corresponding area in the standard image of the target object, indicating that the partial area in the image to be detected of the target object has defects, and thus obtaining target object defect information in the image to be detected of the target object.

For example, in the model detection mode, a defect detection model for detecting a defect of a target object may be trained in advance, and an image pickup apparatus for acquiring an image of the target object on the stringer in real time or at a fixed timing is installed at a suitable position on the stringer.

In the process of training the defect detection model, the following operations are performed:

first, a sample image and a sample tag of the target object are acquired.

The sample image of the target object may be an image of the target object when there is a defect during historical use of the stringer.

Each sample image corresponds to a sample label, and the sample label can represent the defect information of the actual target object corresponding to the sample image. The sample label can be obtained by manually labeling the sample image.

Illustratively, the target object defect information may include, but is not limited to, at least one of: defect type, defect area information, etc.

In the case where the target object is a belt, the defect types may include, but are not limited to, at least one of: deviation, dirt, spreading, breaking, curling, fuzzing, holes, crystallization, aging, etc. In the case where the target object is a battery string, the defect type may include, but is not limited to, at least one of: oxidation, dirt, fragments, abnormal cluster length, foreign matter, etc.

The defect area information may include, but is not limited to, at least one of: defect area location, defect area width, defect area height, defect area, etc. Wherein the defective area location may include, but is not limited to: center point coordinates, vertex coordinates, and the like.

And then taking the sample image as input of a model to be trained, taking the sample label as an output target of the model to be trained, and training the model to be trained.

And constructing a model to be trained, wherein the model to be trained refers to a defect detection model which is not trained yet, parameters in the model to be trained are initial parameters, and the parameters are subjected to iterative optimization in the model training process.

Illustratively, the model to be trained may be any neural network model with image classification functions, including but not limited to: VGG (Visual Geometry Group ) model, resNet (Residual Network) model, RCNN (Region Convolutional Neural Network, regional convolutional neural Network) series model, SSD (Single Shot MultiBox Detector, single multi-class detection) series model, YOLO (You Only Look Once, one-time browsing) series model, and the like.

And inputting the sample image into a model to be trained, and performing operations such as image feature extraction, image feature coding, image feature aggregation, image feature classification and the like on the sample image in the model to be trained, wherein the output of the model to be trained is prediction target object defect information corresponding to the sample image.

And taking the sample label as an output target of the model to be trained, and judging whether the model to be trained is trained according to the actual target object defect information in the sample label and the predicted target object defect information output by the model to be trained.

For example, based on the actual target object defect information in the sample label and the predicted target object defect information output by the model to be trained, a loss function of the model may be calculated, and in case the loss function satisfies a preset condition (e.g., is smaller than a certain threshold value), the training may be determined to be completed. Illustratively, the loss function may include, but is not limited to: cross entropy loss function, exponential loss function, absolute loss function, square loss function, and the like.

And finally, taking the trained model as the defect detection model.

In the process of carrying out defect detection on the target object on the series welding machine, the defect detection can be carried out on the image to be detected of the target object by utilizing the defect detection obtained by training, and the target object defect information corresponding to the image to be detected of the target object is obtained.

Specifically, first, an image of a target object acquired by an image pickup apparatus is acquired, and the image is taken as an image to be detected of the target object; then, inputting the image to be detected of the target object into a pre-trained defect detection model to obtain the output of the defect detection model, wherein the output represents the defect information of the target object. The specific content of the defect information of the target object is just described with reference to the above related description.

Step 102, obtaining defect processing information associated with the target object defect information.

In the embodiment of the application, the defect processing information related to the defect information of each target object can be preset for the defect information of each target object, and the defect information of the target object can be correspondingly processed according to the defect processing information, so that the requirement on personal experience of maintenance personnel is reduced, and the processing process is normalized and standardized.

For example, when a great number of defects of a target object (a belt or a battery string) on the stringer are routinely processed, relevant repair, maintenance, parameter standard and other experience defect processing information can be collected, summary and quantitative grading are conducted on different target object defect information and relevant defect processing information, so that a target object knowledge base is constructed, and the association relation between each target object defect information and the defect processing information is stored in the target object knowledge base.

Illustratively, the storage manner of the association relationship between the defect information of each target object and the defect processing information may include, but is not limited to: table storage, index storage, KV (key-value pair) storage, etc.

Accordingly, the process of acquiring defect processing information associated with the target object defect information may include: and searching from a pre-established target object knowledge base based on the target object defect information to obtain defect processing information related to the target object defect information.

Illustratively, the defect handling information associated with the target object defect information may include, but is not limited to, at least one of: associated object defect information associated with the target object defect information, series welding machine defect information associated with the target object defect information, defect maintenance information associated with the target object defect information.

For the above-mentioned associated object defect information associated with the target object defect information, wherein the defect of the associated object is associated with the defect of the target object, therefore, the defect of the associated object can be estimated from the defect of the target object, and the defect of the target object can be estimated from the defect of the associated object. By setting the associated object defect information in the defect processing information, the corresponding associated object defect information can be obtained simultaneously after the target object defect information is detected, so that the defect of the associated object can be found out in time and processed in time.

In the embodiment of the application, considering that the defect of the belt generally causes the defect of the battery string, when the target object is the belt, the associated object is the battery string; when the target object is a battery string, the associated object is a belt.

Regarding the above-mentioned series welding machine defect information related to the defect information of the target object, considering that the defect of the target object may be caused by inaccurate parameters of the series welding machine and problems of certain mechanisms, the defect of the series welding machine can be estimated according to the defect of the target object. By setting the information of the defects of the stringer in the defect processing information, the information of the defects of the stringer can be obtained simultaneously after the information of the defects of the target object is detected, so that the defects of the stringer can be found out in time and adjusted in time.

For the above-described defect maintenance information associated with the target object defect information, the defect maintenance information may provide standardized maintenance means to be adopted for the target object defect information, and thus, by setting the defect maintenance information in the defect processing information, it is possible to provide an optimal experience method to a maintenance person after detecting the target object defect information, so that the defect existing in the target object can be maintained by using the optimal experience method.

Illustratively, in the case where the target object is a belt, the defect processing information may further include: belt life information associated with the target object defect information. Through setting up belt life information in defect processing information, can provide the current life of belt for maintenance personal to remind the maintenance personal to carry out the change of belt more accurately according to the life of belt.

Next, the association between the defect information of the target object and the defect processing information in the target object knowledge base will be described by way of the following examples.

Example 1: the target object is a belt, the belt defect information is a belt deviation, the battery string defect information related to the belt deviation comprises a battery string cold joint and the like, the string welding machine defect information related to the belt deviation comprises a string welding machine deviation correcting mechanism abnormality and the like, and the defect maintenance information related to the belt deviation comprises a string welding machine deviation correcting mechanism adjustment and the like.

Example 2: the target object is a belt, the belt defect information is belt dirt, the battery string defect information related to the belt dirt comprises a battery string cold weld, a white dew and the like, and the defect maintenance information related to the belt dirt comprises a maintenance belt, a cleaning belt and the like.

Example 3: the target object is a belt, the belt defect information is a belt adhesive opening protrusion, the battery string defect information related to the belt adhesive opening protrusion comprises a battery string rosin joint, a white dew and the like, the defect maintenance information related to the belt adhesive opening protrusion comprises a new belt replacement, the condition that the quality of the belt is abnormal is prompted, and a manufacturer needs to be fed back.

Example 4: the target object is a belt, the belt defect information is a belt fracture, the battery string defect information related to the belt fracture comprises a battery string cold joint, a white exposure and the like, the string welder defect information related to the belt fracture comprises an excessive air pressure of a string welder and the like, and the defect maintenance information related to the belt fracture comprises an adjustment of the air pressure of the string welder and the like.

Example 5: the target object is a belt, the belt defect information is a belt curled edge, the battery string defect information related to the belt curled edge comprises a battery string cold joint, a white exposure and the like, the string welding machine defect information related to the belt curled edge comprises a string welding machine limiting abnormality and the like, the defect maintenance information related to the belt curled edge comprises a string welding machine mounting belt, a string welding machine limiting mechanism adjusting and the like.

Example 6: the target object is a battery string, the battery string defect information is battery string oxidation, and the defect maintenance information related to battery string oxidation comprises checking whether the battery piece is abnormal or not and is required to be emptied for isolation treatment.

Example 7: the target object is a battery string, the battery string defect information is battery string dirt, the belt defect information related to the battery string dirt comprises belt dirt, scaling powder crystallization and the like, the string welder defect information related to the battery string dirt comprises a string welder sucker abnormality, a string welder scaling powder concentration abnormality and the like, and the defect maintenance information related to the battery string dirt comprises a device for checking whether the string welder sucker is damaged or not, whether the scaling powder concentration is too high or not and the like.

Example 8: the target object is a battery string, the battery string defect information is a battery string broken piece, the belt defect information related to the battery string broken piece comprises belt foreign matters and the like, the string welding machine defect information related to battery string dirt comprises string welding machine sucker anomalies and the like, the defect maintenance information related to the battery string dirt comprises debugging of the string welding machine sucker, and whether the belt has foreign matters or not is checked.

Example 9: the target object is a battery string, the battery string defect information is a battery string length abnormality (such as that the battery string length exceeds a preset standard range, and the like), the string welder defect information related to the battery string length abnormality comprises a string welder servo motor parameter abnormality, a tractor parameter abnormality, and the like, and the defect maintenance information related to the battery string length abnormality comprises a string welder servo motor parameter adjustment, a tractor parameter adjustment, and the like, the battery string length is recalibrated, and after adjustment is completed, the operation is carried out again after the manual use of a tape measure confirmation.

Example 10: the target object is a battery string, the battery string defect information is a battery string foreign matter, the belt defect information related to the battery string foreign matter comprises belt foreign matter and the like, and the defect maintenance information related to the battery string foreign matter comprises processing surrounding environment of a belt, welding strips, battery piece fragments and the like.

And step 103, generating early warning information containing the defect information of the target object and the defect processing information.

The early warning information can be displayed in the user interface by generating the early warning information containing the defect information of the target object and the defect processing information, and maintenance personnel can timely process the defect of the target object according to the early warning information, so that the maintenance personnel can conveniently and quickly know the defect condition, acquire a solution and improve the processing efficiency.

In the following, a defect treatment process of the belt will be described by taking the belt as an example.

Referring to fig. 2, a schematic diagram of a defect handling process according to an embodiment of the present application is shown.

As shown in fig. 2, the defect handling process may include:

And carrying out defect detection on the belt by using the belt defect detection model to obtain belt defect information. Illustratively, a belt defect detection model may be utilized to extract relevant belt defect information for defects such as tearing, fuzzing, holes, crystallization, etc. of the belt.

And storing defect processing information corresponding to different belt defect information by using the belt knowledge base. Illustratively, the defect handling information includes battery string defect information, string welder defect information, defect maintenance information, belt life information, and the like.

And searching a belt knowledge base according to the belt defect information to obtain defect processing information corresponding to the belt defect information.

Referring to fig. 3, a schematic diagram of another defect handling process according to an embodiment of the present application is shown. Fig. 3 can be understood as a specific process of fig. 2.

As shown in fig. 3, the defect handling process may include:

① A belt image is input.

② FTP (FILE TRANSFER Protocol ) reading is performed.

③ And (5) preprocessing an image.

In the embodiment of the application, the problem that the existing mechanical arm can shield the belt and influence the belt image in the working and running process of the series welding machine belt is considered, so that the belt image can be screened, the shielded belt image is removed, and the belt image of the area needing to be identified is reserved to be completely presented. The noise of the belt image can be subjected to certain pretreatment operations such as inhibition and elimination, so that the quality of the belt image is improved.

④ And detecting belt defects.

And carrying out defect detection on the belt by using the belt defect detection model to obtain belt defect information, wherein the belt defect information is specifically described by referring to the related description of the embodiment.

⑤ And (5) information quantization coding.

And the detected belt defect information is quantitatively encoded to form defect information which is convenient for maintenance personnel to understand, so that the later-stage comparison and analysis problem is facilitated.

⑥ The belt knowledge base is retrieved.

And searching a belt knowledge base by utilizing the quantized and encoded defect information, and rapidly analyzing the reasons of the defects, coping measures and the like.

⑦ And generating early warning information.

Detailed early warning information containing belt defect information and defect processing information is generated, so that maintenance personnel can quickly know and solve the scheme, and the processing efficiency is improved.

In the embodiment of the application, aiming at daily abnormal problems of the photovoltaic industry stringer, experience of daily accumulated and accumulated abnormal handling experience, maintenance, experience methods for prolonging the service life of a belt and the like of maintenance personnel are summarized, a dedicated intelligent knowledge base of the photovoltaic industry stringer is established, when corresponding defects are detected by using a defect detection model, a method for displaying the optimal handling problem and experience can be provided, and the maintenance personnel can quickly position the problem according to the experience method provided by the system, so that the production line optimization is assisted, the yield of battery strings is improved, and meanwhile, the efficiency and the capability of the maintenance personnel for handling the problems are also improved.

Referring to fig. 4, a block diagram of a defect processing apparatus according to an embodiment of the present application is shown.

As shown in fig. 4, the defect processing apparatus may include the following modules:

The detection module 401 is configured to detect a defect of a target object on the series welding machine, so as to obtain defect information of the target object, where the target object includes a belt or a battery string;

an acquisition module 402, configured to acquire defect processing information associated with the target object defect information;

A generating module 403, configured to generate early warning information including the defect information of the target object and the defect processing information.

Optionally, the obtaining module 402 is specifically configured to retrieve, based on the target object defect information, from a pre-created target object knowledge base, to obtain the defect processing information; and the target object knowledge base stores the association relation between the defect information and the defect processing information of each target object.

Optionally, the detection module 401 is specifically configured to obtain an image to be detected of the target object; inputting the image to be detected into a pre-trained defect detection model to obtain the output of the defect detection model, wherein the output represents the defect information of the target object.

For the device embodiments, since they are substantially similar to the method embodiments, the description is relatively simple, and reference is made to the description of the method embodiments for relevant points.

In an embodiment of the application, an electronic device is also provided. The electronic device may include one or more processors and one or more computer-readable storage media having instructions stored thereon, such as an application program. The instructions, when executed by the one or more processors, cause the processors to perform the defect handling method of any of the embodiments described above.

Referring to fig. 5, a schematic diagram of an electronic device structure according to an embodiment of the present application is shown. As shown in fig. 5, the electronic device comprises a processor 501, a communication interface 502, a memory 503, and a communication bus 504. The processor 501, the communication interface 502 and the memory 503 perform communication with each other through the communication bus 504.

A memory 503 for storing a computer program.

The processor 501 is configured to implement the defect processing method according to any of the above embodiments when executing the program stored in the memory 503.

The communication interface 502 is used for communication between the electronic device and other devices described above.

The communication bus 504 mentioned above may be a peripheral component interconnect standard (PERIPHERAL COMPONENT INTERCONNECT, PCI) bus or an extended industry standard architecture (Extended Industry Standard Architecture, EISA) bus, or the like. The communication bus may be classified as an address bus, a data bus, a control bus, or the like. For ease of illustration, the figures are shown with only one bold line, but not with only one bus or one type of bus.

The above-mentioned processor 501 may include, but is not limited to: central Processing units (Central Processing Unit, CPU), network processors (Network Processor, NP), digital signal processors (DIGITAL SIGNAL Processing, DSP), application SPECIFIC INTEGRATED Circuits (ASIC), field-Programmable GATE ARRAY, or other Programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, and so forth.

The above mentioned memory 503 may include, but is not limited to: read Only Memory (ROM), random access Memory (Random Access Memory RAM), compact disk Read Only Memory (Compact Disc Read Only Memory CD-ROM), electrically erasable programmable Read Only Memory (Electronic Erasable Programmable Read Only Memory EEPROM), hard disk, floppy disk, flash Memory, and the like.

In an embodiment of the present application, there is also provided a computer-readable storage medium having stored thereon a computer program executable by a processor of an electronic device, the computer program, when executed by the processor, causing the processor to perform the defect processing method as described in any of the embodiments above.

In this specification, various embodiments are interrelated, and each embodiment is described in a progressive manner, and each embodiment is mainly described in a different manner from other embodiments, so that identical and similar parts between the various embodiments are referred to each other.

It is noted that relational terms such as first and second, and the like are used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions. Moreover, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or terminal 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 terminal. Without further limitation, an element defined by the phrase "comprising one … …" does not exclude the presence of other like elements in a process, method, article, or terminal device that comprises the element.

From the above description of the embodiments, it will be clear to those skilled in the art that the above-described embodiment method may be implemented by means of software plus a necessary general hardware platform, but of course may also be implemented by means of hardware, but in many cases the former is a preferred embodiment. Based on such understanding, the technical solution of the present application may be embodied essentially or in a part contributing to the prior art in the form of a software product stored in a storage medium (such as ROM, RAM, magnetic disk, optical disk) and including several instructions for causing a terminal (which may be a mobile phone, a computer, a server, an air conditioner, or a network device, etc.) to perform the method according to the embodiments of the present application.

The embodiments of the present application have been described above with reference to the accompanying drawings, but the present application is not limited to the above-described embodiments, which are merely illustrative and not restrictive, and many forms may be made by those having ordinary skill in the art without departing from the spirit of the present application and the scope of the claims, which are to be protected by the present application.

Those of ordinary skill in the art will appreciate that the various illustrative elements and algorithm steps described in connection with the embodiments disclosed herein may be implemented as electronic hardware, or combinations of computer software and electronic hardware. Whether such functionality is implemented as hardware or software depends upon the particular application and design constraints imposed on the solution. Skilled artisans may implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the present application.

It will be clear to those skilled in the art that, for convenience and brevity of description, specific working procedures of the above-described systems, apparatuses and units may refer to corresponding procedures in the foregoing method embodiments, and are not repeated herein.

In the embodiments provided in the present application, it should be understood that the disclosed apparatus and method may be implemented in other manners. For example, the apparatus embodiments described above are merely illustrative, e.g., the division of the units is merely a logical function division, and there may be additional divisions when actually implemented, e.g., multiple units or components may be combined or integrated into another system, or some features may be omitted or not performed. Alternatively, the coupling or direct coupling or communication connection shown or discussed with each other may be an indirect coupling or communication connection via some interfaces, devices or units, which may be in electrical, mechanical or other form.

The units described as separate units may or may not be physically separate, and units shown as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

In addition, each functional unit in the embodiments of the present application may be integrated in one processing unit, or each unit may exist alone physically, or two or more units may be integrated in one unit.

The functions, if implemented in the form of software functional units and sold or used as a stand-alone product, may be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present application may be embodied essentially or in a part contributing to the prior art or in a part of the technical solution, in the form of a software product stored in a storage medium, comprising several instructions for causing a computer device (which may be a personal computer, a server, a network device, etc.) to perform all or part of the steps of the method according to the embodiments of the present application. And the aforementioned storage medium includes: a usb disk, a removable hard disk, a ROM, a RAM, a magnetic disk, or an optical disk, etc.

The foregoing is merely illustrative of the present application, and the present application is not limited thereto, and any person skilled in the art will readily recognize that variations or substitutions are within the scope of the present application. In view of the foregoing, this description should not be construed as limiting the application.

Claims

1. A method of defect handling, the method comprising:

performing defect detection on a target object on a stringer to obtain target object defect information, wherein the target object comprises a belt or a battery string;

acquiring defect processing information associated with the target object defect information;

generating early warning information containing the defect information of the target object and the defect processing information.

2. The method of claim 1, wherein the defect handling information comprises at least one of:

Associated object defect information associated with the target object defect information, series welding machine defect information associated with the target object defect information, defect maintenance information associated with the target object defect information.

3. The method of claim 2, wherein the step of determining the position of the substrate comprises,

When the target object is a belt, the associated object is a battery string;

When the target object is a battery string, the associated object is a belt.

4. The method according to claim 2, wherein in the case where the target object is a belt, the defect processing information further includes: belt life information associated with the target object defect information.

5. The method of claim 1, wherein the acquiring defect handling information associated with the target object defect information comprises:

retrieving from a pre-established target object knowledge base based on the target object defect information to obtain defect processing information;

And the target object knowledge base stores the association relation between the defect information and the defect processing information of each target object.

6. The method of claim 1, wherein the defect detection of the target object on the stringer comprises:

Acquiring an image to be detected of the target object;

inputting the image to be detected into a pre-trained defect detection model to obtain the output of the defect detection model, wherein the output represents the defect information of the target object.

7. The method of claim 6, wherein the defect detection model is trained by:

Acquiring a sample image and a sample label of the target object, wherein the sample label represents actual target object defect information corresponding to the sample image;

Taking the sample image as input of a model to be trained, taking the sample label as an output target of the model to be trained, and training the model to be trained;

And taking the trained model as the defect detection model.

8. A defect handling device, the device comprising:

the detection module is used for carrying out defect detection on a target object on the series welding machine to obtain target object defect information, wherein the target object comprises a belt or a battery string;

an acquisition module for acquiring defect processing information associated with the target object defect information;

and the generation module is used for generating early warning information containing the defect information of the target object and the defect processing information.

9. An electronic device, comprising:

one or more processors; and

One or more computer-readable storage media having instructions stored thereon;

The instructions, when executed by the one or more processors, cause the processor to perform the defect handling method of any of claims 1 to 7.

10. A computer-readable storage medium, having stored thereon a computer program which, when executed by a processor, causes the processor to perform the defect processing method of any of claims 1 to 7.