CN116298340A - Product defect detection method and system based on task scheduling - Google Patents
Product defect detection method and system based on task scheduling Download PDFInfo
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Abstract
The invention provides a product defect detection method and system based on task scheduling, comprising the following steps: the detection preparation step comprises the following steps: transporting the product to a detection station and scheduling a detection task; and a defect detection step: and detecting the defects of the products on the detection stations by using a quality inspection machine according to the scheduled detection tasks. According to the invention, the purpose of inserting batch data into the XXL-JOB component is realized through the interface access mode, batch start-stop and deletion of the data can be realized, the time for manually creating the task is greatly shortened, and further the product detection time is shortened. When the product is subjected to multiple defect detection, the defects of the product are detected in a dispatching mode of the detection tasks of the multiple defects, so that the multifunctional detection is realized, the operation control is simple, and the product detection time is saved.
Description
Technical Field
The invention relates to the technical field of product defect detection, in particular to a product defect detection method and system based on task scheduling, which are applied to task scheduling of an intelligent manufacturing production line.
Background
Defect detection generally refers to detection of surface defects of an article, wherein the surface defects are detected by adopting advanced machine vision detection technology, such as spots, pits, scratches, color differences, defects and the like on the surface of a workpiece.
The Chinese patent document with publication number CN115187593A discloses a screen defect detection method and device, wherein the method comprises the following steps: acquiring a plurality of screen images, wherein the plurality of screen images are sequentially shot on screens with defects at different focusing distances in the up-down direction; determining a defect area of each screen image; calculating the brightness of a defect area of the defect area; and determining an image with the darkest brightness of the defect area as a target defect image, and determining the layer number of the image corresponding to the target defect image as the layer where the defect is located.
Aiming at the related technology, the inventor considers that the traditional defect detection method has single function, can only detect single defects such as spots, pits or scratches on products, and has poor adaptability.
Disclosure of Invention
Aiming at the defects in the prior art, the invention aims to provide a product defect detection method and system based on task scheduling.
The invention provides a product defect detection method based on task scheduling, which comprises the following steps:
the detection preparation step comprises the following steps: transporting the product to a detection station and scheduling a detection task;
and a defect detection step: and detecting the defects of the products on the detection stations by using a quality inspection machine according to the scheduled detection tasks.
Preferably, the detection preparation step includes the steps of:
an interface creation step: creating a task interface;
the operation steps are as follows: performing operations of adding data, modifying data, updating data or deleting data according to the task interface, and generating log information in operation;
calling a Websocket step: calling a Websocket component to send log information to the front end of the Websocket;
and a display step: the Websocket front end displays log information.
Preferably, the interface creation step includes the steps of:
the Java method is established as follows: calling annotation @ PostMapping to create a Java method;
creating a task interface: based on the created Java method, obtaining XXL-JOB and creating a task interface;
defining a type: defining a task interface parameter request type;
global token setting: acquiring a task interface token and setting the task interface token as a global token;
interface field declaration step: declaring a task interface field and setting to enable input of parameters;
judging the legality of the field: judging the legality of the input parameters of the task interface field according to the defined task interface parameter request type, and enabling the task interface to be filled with word segments to set a value which is not equal to a null value;
a field checking step: try catch examines the task interface field.
Preferably, in the operation step, log.info statistics log information;
or in the operations of adding data, modifying data, updating data or deleting data, naming the data to obtain the data id, acquiring the data id, printing the data to generate the number of data, and printing the number of data to the log information file.
Preferably, the step of calling Websocket includes the steps of:
front-end writing: writing HTML at the front end of the websocket to obtain an interface for displaying log information;
websocket component referencing step: a websocket component is referenced;
binding Web service: binding web services based on websocket components, and successfully calling a method by connection establishment;
the log method creation step: creating a log method based on a websocket component;
log path acquisition: acquiring a log path;
and a log sending step: the method comprises the steps that log information is sent to the front end of a websocket through a successful calling method, a log method and a log path;
connection closing creation step: and (3) creating a connection closing method, disconnecting a successful calling method, stopping reading log information, and stopping sending the log information to the websocket front end.
Preferably, the step of calling Websocket further comprises the steps of:
creating a monitoring event callback step: creating a file monitoring event callback according to the websocket component;
and a data processing step: and acquiring log information through a log method and a log path, and processing the queried data from the log information according to the file monitoring event callback.
Preferably, in the log method creating step, if all log information is obtained, a load is created to send all log methods;
or,
if the log information is acquired according to the requirement, a method for receiving the call of the client information is created.
Preferably, the method further comprises the steps of:
log monitoring: creating slf4j monitoring log information;
abnormal data throwing step: the OnError annotation method throws out the abnormal data in the log information, sets the abnormal data to be marked red, and aligns with the front-end field.
Preferably, the method further comprises the steps of:
and a port self-defining step: the server opens a customized port of the websocket component;
and data pushing: and calling an interface access service to push data, and acquiring the log through accessing the custom port and the custom address to update and push in real time.
The invention provides a product defect detection system based on task scheduling, which comprises the following modules:
the detection preparation step comprises the following steps: transporting the product to a detection station and scheduling a detection task;
and a defect detection module: and detecting the defects of the products on the detection stations by using a quality inspection machine according to the scheduled detection tasks.
Compared with the prior art, the invention has the following beneficial effects:
1. when multiple defects of the product are detected, the defects of the product are detected in a dispatching mode of detecting tasks of the multiple defects, so that the multifunctional detection is realized, the operation control is simple, and the product detection time is saved;
2. according to the invention, the purpose of inserting batch data into the XXL-JOB component is realized through an interface access mode, batch start-stop and deletion of the data can be realized, the time for manually creating tasks is greatly shortened, and further the product detection time is shortened;
3. the invention can reduce the time for manually creating the task, monitor the error information of the task and process the error task in time.
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Other features, objects and advantages of the present invention will become more apparent upon reading of the detailed description of non-limiting embodiments, given with reference to the accompanying drawings in which:
FIG. 1 is a flow chart of the present invention.
Detailed Description
The present invention will be described in detail with reference to specific examples. The following examples will assist those skilled in the art in further understanding the present invention, but are not intended to limit the invention in any way. It should be noted that variations and modifications could be made by those skilled in the art without departing from the inventive concept. These are all within the scope of the present invention.
The embodiment of the invention discloses a product defect detection method based on task scheduling, which is shown in fig. 1 and comprises the following steps:
the detection preparation step comprises the following steps: the product is transported to a detection station. The products are for example a charging connector of a mobile phone, a keyboard, a mouse and the like. And scheduling the detection task. The detection preparation step includes the steps of:
interface creation step (step 1): a task interface is created.
The interface creation step includes the steps of:
the Java method is established as follows: invoking annotation @ PostMapping to create a Java method. Postmapping is used to process HTTP POST requests, and mapping the requests to a specific processing method maps a POST request to process the POST request.
Creating a task interface: based on the created Java method, XXL-JOB is obtained, and a task interface is created. And calling a newly built task interface externally provided by the XXL-JOB component.
Defining a type: a task interface parameter request type is defined. Defining interface parameter request type; defining the type of interface parameters of the XXL-JOB, which are needed for subsequent insertion of data into this interface.
Global token setting: the task interface token is acquired and set to a global token. Invoking an http request, acquiring an interface token and setting the interface token as a global token; english of HTTP is named Hyper Text Transfer Protocol, chinese translation is hypertext transfer protocol; token represents a token, a token. The XXL-JOB interface requires a token to be checked, acquired and set globally available, and other interfaces may be used later.
Interface field declaration step: the task interface field is asserted and set to enable entry of parameters. I.e. declare the interface field and set to an inputtable parameter. The interface field is stated as String type, and parameters can be flexibly input to carry out data addition, modification, update or deletion when the interface is called.
Judging the legality of the field: judging the legality of the input parameters of the task interface field according to the defined task interface parameter request type, and enabling the task interface to be filled with word segments to set unequal null values.
Judging the legality of the interface parameters, and setting the character to be filled to be unequal to null; null indicates a null value. Judging the key parameter input range and field type (1-30 characters/non-inputtable English), wherein the data which is equal to the new null value is meaningless and does not accord with the new specification of XXL-JOB.
A field checking step: try catch examines the task interface field. Try catch check field and set exception: two pieces of code are set, and if the former piece of code is wrong, the other piece of code is executed. the try-catch statement, as a standard way to handle exceptions in JavaScript, if any code in the try block is in error, immediately exits the code execution process and then follows the catch block. At this point, the catch block receives an object containing error information.
Examples:
try{
code that may cause errors
}catch(error){
How to deal with when an error occurs
}。
Operating step (step 2): and performing operations of adding data, modifying data, updating data or deleting data according to the task interface, and generating log information in operation. Namely, the step 2 (adding, modifying, updating and deleting) operation can be realized by calling the interface of the tool in the step 1 (interface), and the step 2 can generate log information.
And printing log information of program operation, and storing the log information into a designated file. The log information (may be all log information or part of log information) is counted as needed. Or in the operations of adding data, modifying data, updating data or deleting data, naming the data to obtain the data id, acquiring the data id, printing the data to generate the number of data, and printing the number of data to the log information file. Acquiring a data id, printing the data to generate a number of data, and printing the number of data to a log file; and saving the log information to a specified file, wherein the log information comprises a log (comprising data corresponding to the data id) generated in the running process of the program.
Calling a Websocket step (step 3): the Websocket component is invoked to send log information to the Websocket front end. And 3, collecting the log information and the error information, and sending the generated log information to a front-end page (step 4) in real time and displaying the generated log information in real time by calling a component websocket.
The step of calling Websocket comprises the following steps:
front-end writing: writing websocket front-end HTML to obtain an interface for displaying log information. HTML english is known in full as Hyper Text Markup Language and chinese translations are hypertext markup languages. websocket is a protocol that performs full duplex communication over a single transmission control protocol connection. The front end of Websocket is the page used to expose the log.
websocket component referencing step: reference is made to the websocket component. The external component is referenced in the configuration file of the program.
Binding Web service: based on websocket components, web services are bound, and a connection establishment success calling method is realized.
The log method creation step: based on the websocket component, a log method is created. Creating a method for loading and sending all logs: if all log information is obtained, a method for loading and sending all logs is created, and the method is needed for displaying the Websocket front end; or, creating a method for receiving the call of the client information: if the log information is acquired according to the requirement, a method for receiving the call of the client information is created, and the method is required to be used for displaying the log at the front end of the Websocket.
Log path acquisition: a log path (shiqi/XXL-JOB/log. Txt) is obtained. And customizing the log path. The Websocket front-end exposes the path that needs to be used to this log. (shiqi/XXL-JOB/log. Txt) this path is the path of the log files in the server and the log file name.
And a log sending step: the method comprises the steps that log information is sent to the front end of a websocket through a successful calling method, a log method and a log path; the log path is read internally by the program and is not perceived by the user.
Connection closing creation step: and (3) creating a connection closing method, disconnecting a successful calling method, stopping reading log information, and stopping sending the log information to the websocket front end. This method is needed when Websocket does not read logs.
Creating a monitoring event callback step: creating a file monitoring event callback according to the websocket component; and creating a file monitoring event callback, and processing the queried data. The processed data can be stored in a server designated directory.
And a data processing step: and acquiring log information through a log method and a log path, and processing the queried data from the log information according to the file monitoring event callback. The processed data can be stored under a specified directory of a server, or the processed data is sent to the front end of the websocket through a successful calling method.
Display step (step 4): the Websocket front end displays log information.
And a port self-defining step: the server opens the websocket component custom port 8090.
And data pushing: and calling an interface access service to push data, and acquiring the log through accessing the custom port and the custom address to update and push in real time. Namely, the interface access service is called to realize data pushing and log real-time update pushing can be obtained through access (ip+8090/log).
Log monitoring: and creating slf4j monitoring log information. English for slf4j is called simple logging facade for Java, translating into a simple log look for Java.
Abnormal data throwing step: the OnError annotation method throws out the abnormal data in the log information, sets the abnormal data to be marked red, and aligns with the front-end field. The Websocket built-in annotation method is used for intercepting abnormal data, and the abnormal data is marked with red and requires the processing of a Websocket front field.
And a defect detection step: and controlling a quality inspection machine or quality inspection software through the scheduled detection task, and detecting defects of products on the detection station.
The invention also provides a defect detection system based on task scheduling, which can be realized by executing the flow steps of the defect detection method based on task scheduling, namely, a person skilled in the art can understand the defect detection method based on task scheduling as a preferred implementation mode of the defect detection system based on task scheduling.
The system comprises the following modules:
the detection preparation module: and transporting the product to a detection station and scheduling detection tasks.
And a defect detection module: and controlling a quality inspection machine or quality inspection software through the scheduled detection task, and detecting defects of products on the detection station.
The method is to control tasks in batches, reduce the cost of manual maintenance, monitor abnormal information generated in the batch operation process, exchange or transmit network management information on the Internet, manage generated faults, events, alarms or notices based on a web service protocol and log display on pages, and can be applied to task management scheduling platforms in servers and intelligent manufacturing production lines.
XXL-JOB is a lightweight distributed task scheduling platform. The core design goal is to develop quickly, learn simply, lightweight and expand easily. XXL-JOB schedules multiple executors to execute tasks through a central scheduling platform. The XXL-JOB is ready to use after unpacking, is easy to operate, is fast to operate, has very good integration with SpringBoot, and a monitoring interface is integrated in a dispatching center, so that the interface is concise, the maintenance cost of enterprises is low, and failed mail alarms and the like are realized. This allows many enterprises to choose XXL-JOB as the dispatch platform. According to the invention, java is used as a basic development language, a Spingboot lightweight framework is integrated, an XXL-JOB component is invoked to add, delete, start and modify interfaces, batch processing requests are carried out on interface data, batch pushing and modifying functions of the data are realized, a websocket log forwarding component is integrated, the log is redirected to a dynamic page, server data resources are received in real time, and the efficiency is improved for data pushing and log analysis. According to the invention, the printed log can be pushed to the page in real time, log information of data and key marks of abnormal data can be checked in real time without a server, and convenience is provided for later debugging.
The defect detection software needs a large number of programs and scheduling tasks to cooperatively operate, the XXL_JOB can perform scheduling operation on the processes and the tasks, and the manual starting and closing of the scheduling tasks are complicated.
Those skilled in the art will appreciate that the invention provides a system and its individual devices, modules, units, etc. that can be implemented entirely by logic programming of method steps, in addition to being implemented as pure computer readable program code, in the form of logic gates, switches, application specific integrated circuits, programmable logic controllers, embedded microcontrollers, etc. Therefore, the system and various devices, modules and units thereof provided by the invention can be regarded as a hardware component, and the devices, modules and units for realizing various functions included in the system can also be regarded as structures in the hardware component; means, modules, and units for implementing the various functions may also be considered as either software modules for implementing the methods or structures within hardware components.
The foregoing describes specific embodiments of the present invention. It is to be understood that the invention is not limited to the particular embodiments described above, and that various changes or modifications may be made by those skilled in the art within the scope of the appended claims without affecting the spirit of the invention. The embodiments of the present application and features in the embodiments may be combined with each other arbitrarily without conflict.
Claims (10)
1. The product defect detection method based on task scheduling is characterized by comprising the following steps:
the detection preparation step comprises the following steps: transporting the product to a detection station and scheduling a detection task;
and a defect detection step: and detecting the defects of the products on the detection stations by using a quality inspection machine according to the scheduled detection tasks.
2. The task scheduling-based product defect detection method according to claim 1, wherein the detection preparation step includes the steps of:
an interface creation step: creating a task interface;
the operation steps are as follows: performing operations of adding data, modifying data, updating data or deleting data according to the task interface, and generating log information in operation;
calling a Websocket step: calling a Websocket component to send log information to the front end of the Websocket;
and a display step: the Websocket front end displays log information.
3. The task scheduling-based product defect detection method of claim 2, wherein the interface creation step includes the steps of:
the Java method is established as follows: calling annotation @ PostMapping to create a Java method;
creating a task interface: based on the created Java method, obtaining XXL-JOB and creating a task interface;
defining a type: defining a task interface parameter request type;
global token setting: acquiring a task interface token and setting the task interface token as a global token;
interface field declaration step: declaring a task interface field and setting to enable input of parameters;
judging the legality of the field: judging the legality of the input parameters of the task interface field according to the defined task interface parameter request type, and enabling the task interface to be filled with word segments to set a value which is not equal to a null value;
a field checking step: try catch examines the task interface field.
4. The task scheduling-based product defect detection method according to claim 2, wherein in the operation step, log.info statistical log information;
or in the operations of adding data, modifying data, updating data or deleting data, naming the data to obtain the data id, acquiring the data id, printing the data to generate the number of data, and printing the number of data to the log information file.
5. The task scheduling-based product defect detection method of claim 2, wherein the step of calling Websocket comprises the steps of:
front-end writing: writing HTML at the front end of the websocket to obtain an interface for displaying log information;
websocket component referencing step: a websocket component is referenced;
binding Web service: binding web services based on websocket components, and successfully calling a method by connection establishment;
the log method creation step: creating a log method based on a websocket component;
log path acquisition: acquiring a log path;
and a log sending step: the method comprises the steps that log information is sent to the front end of a websocket through a successful calling method, a log method and a log path;
connection closing creation step: and (3) creating a connection closing method, disconnecting a successful calling method, stopping reading log information, and stopping sending the log information to the websocket front end.
6. The task scheduling-based product defect detection method of claim 5, wherein the step of calling Websocket further comprises the steps of:
creating a monitoring event callback step: creating a file monitoring event callback according to the websocket component;
and a data processing step: and acquiring log information through a log method and a log path, and processing the queried data from the log information according to the file monitoring event callback.
7. The task scheduling-based product defect detection method according to claim 5, wherein in the log method creation step, if all log information is obtained, a load-transmitting all log method is created;
or,
if the log information is acquired according to the requirement, a method for receiving the call of the client information is created.
8. The task scheduling-based product defect detection method of claim 2, further comprising the steps of:
log monitoring: creating slf4j monitoring log information;
abnormal data throwing step: the OnError annotation method throws out the abnormal data in the log information, sets the abnormal data to be marked red, and aligns with the front-end field.
9. The task scheduling-based product defect detection method of claim 5, further comprising the steps of:
and a port self-defining step: the server opens a customized port of the websocket component;
and data pushing: and calling an interface access service to push data, and acquiring the log through accessing the custom port and the custom address to update and push in real time.
10. A product defect detection system based on task scheduling, which is characterized by comprising the following modules:
the detection preparation module: transporting the product to a detection station and scheduling a detection task;
and a defect detection module: and detecting the defects of the products on the detection stations by using a quality inspection machine according to the scheduled detection tasks.
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| CN116503412A (en) * | 2023-06-29 | 2023-07-28 | 宁德时代新能源科技股份有限公司 | Appearance defect detection method, apparatus, computer device and storage medium |
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| CN116503412A (en) * | 2023-06-29 | 2023-07-28 | 宁德时代新能源科技股份有限公司 | Appearance defect detection method, apparatus, computer device and storage medium |
| CN116503412B (en) * | 2023-06-29 | 2023-12-08 | 宁德时代新能源科技股份有限公司 | Appearance defect detection method, apparatus, computer device and storage medium |
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