Welding monitoring method and automatic welding device

Abstract

The present invention relates to the field of welding monitoring and discloses a welding monitoring method and an automatic welding device, comprising the following steps: collecting welding process data and welding monitoring images of welding equipment, obtaining status information of the welding equipment based on the welding process data, and if the welding equipment status is abnormal, a control module generates a welding monitoring container, matches the welding equipment welding image based on the welding equipment information, and sends the result to the welding monitoring container; a monitoring plan generation module generates a monitoring plan based on parameter monitoring information and corresponding parameter monitoring weight information, and sends the result to a monitoring display module. The monitoring display module divides the display pages according to the monitoring plan and performs welding status monitoring and display. The present invention can comprehensively and accurately reflect the operating status of the welding equipment and the dynamic changes of the welding process, providing comprehensive data support for monitoring welding quality.

Description

Technical Field

[0001] The present invention relates to the field of welding monitoring, in particular to a welding monitoring method and an automatic welding device. Background Art

[0002] In modern industrial manufacturing, welding, as a crucial joining technology, is widely used in a variety of fields, including automotive, aerospace, construction, and bridges. The quality of the welding process directly impacts the structural strength, safety, and service life of the product. Therefore, real-time monitoring of the welding process and the timely detection and resolution of abnormalities during welding are crucial to ensuring product quality and production efficiency.

[0003] Traditional welding monitoring relies primarily on manual observation or simple instrumentation, an approach with numerous limitations. For one thing, manual monitoring is susceptible to factors like fatigue and distraction, making it difficult to consistently and accurately monitor subtle changes in the welding process. Furthermore, traditional instruments can only provide limited information on welding parameters, such as current and voltage, and fail to fully reflect the overall status of the welding equipment or dynamic changes during the welding process.

[0004] With the rapid development of computer technology, image processing technology, and the Internet of Things (IoT), intelligent welding monitoring systems have gradually become a research hotspot. While some existing intelligent welding monitoring systems can achieve real-time monitoring and data recording of welding parameters, they still lack comprehensive monitoring, intelligent monitoring capabilities, and flexibility in exception handling. For example, some systems can only monitor a single welding parameter and are unable to effectively distinguish and handle abnormalities in multiple parameters simultaneously. Other systems lack targeted monitoring solutions when an anomaly occurs, resulting in inefficient monitoring. Finally, some systems have a fixed monitoring interface that cannot dynamically adjust the display content based on the welding status, affecting the intuitiveness and effectiveness of monitoring.

[0005] Therefore, there is an urgent need for a welding monitoring system and method that can comprehensively and intelligently monitor the welding process, dynamically adjust the monitoring mode according to the welding status, and provide targeted monitoring solutions to improve welding quality, ensure production safety, and improve production efficiency. Summary of the Invention

[0006] The purpose of the present invention is to overcome the deficiencies of the prior art and provide a welding monitoring method, comprising the following steps:

[0007] Step 1: Collect welding process data and welding monitoring images of the welding equipment, and obtain status information of the welding equipment based on the welding process data. If the welding equipment status is abnormal, proceed to step 2;

[0008] In step 2, the control module generates a welding monitoring container, matches the welding equipment welding image based on the welding equipment information, and sends it to the welding monitoring container; the control module obtains the monitoring mode based on the welding status information. If it is a single parameter monitoring mode, it proceeds to step 3; if it is a multi-parameter monitoring mode, it proceeds to step 4;

[0009] Step 3: Send the welding status information to the welding monitoring container. The welding monitoring container obtains the welding image data corresponding to the abnormal parameters from the welding database based on the abnormal parameters in the welding image and the status information of the welding equipment, generates a monitoring plan, and sends it to the monitoring display module, and then proceeds to step 6;

[0010] In step 4, the control module generates monitoring containers corresponding to the abnormal parameters based on the multiple abnormal parameters in the welding status information, connects each monitoring container corresponding to the abnormal parameters to the welding monitoring container, and the welding monitoring container obtains welding image data corresponding to the parameter information from the welding database based on the welding image and the monitoring container corresponding to the abnormal parameters, generates parameter monitoring information, and sends it to the monitoring solution generation module, and then proceeds to step 5;

[0011] Step 5: The monitoring plan generation module generates a monitoring plan based on the parameter monitoring information and the corresponding parameter monitoring weight information, and sends it to the monitoring display module, and then proceeds to step 6;

[0012] Step 6: The monitoring display module divides the display pages according to the monitoring plan and performs welding status monitoring display.

[0013] Furthermore, the collection of welding process data and welding monitoring images of the welding equipment includes:

[0014] The welding process data includes welding current, voltage, welding speed, welding equipment posture and welding equipment infrared image; the welding monitoring image is a panoramic image.

[0015] Furthermore, obtaining welding status information according to welding process data includes:

[0016] The welding status information is obtained based on the welding process data. If all welding process data are normal, the welding status is normal; if there is a single welding process data abnormality, it is a single parameter abnormality, and the welding status is a single parameter status; if multiple parameters are abnormal, the welding status is a multi-parameter status.

[0017] Furthermore, the control module generates a welding monitoring container, matches the welding equipment welding image according to the welding equipment information, and sends the image to the welding monitoring container, including:

[0018] The control module obtains the device information of the abnormal state monitoring device, generates a welding monitoring container according to the device information, obtains the corresponding welding device welding image according to the device information, and sends it to the welding monitoring container.

[0019] Furthermore, the control module obtains a monitoring mode according to the welding status information, including:

[0020] If the welding status information indicates that a single parameter is abnormal, it is in single parameter monitoring mode; if the welding status information indicates that multiple parameters are abnormal, it is in multi-parameter monitoring mode.

[0021] Furthermore, the welding monitoring container obtains welding image data corresponding to abnormal parameters in the welding database according to abnormal parameters in the welding image and the status information of the welding equipment, generates a monitoring plan, and sends it to the monitoring display module, including:

[0022] According to the abnormal parameters in the status information, the welding image area information corresponding to the abnormal parameters is obtained in the welding database, and a monitoring plan is formed according to the welding image area information and the abnormal parameters.

[0023] Furthermore, the aforementioned connecting each monitoring container corresponding to the abnormal parameter to the welding monitoring container, the welding monitoring container respectively obtains welding image data corresponding to parameter information in the welding database according to the welding image and the monitoring container corresponding to the abnormal parameter, and respectively generates parameter monitoring information, including:

[0024] According to the abnormal parameters in the status information, the welding image area information corresponding to the abnormal parameters is obtained in the welding database. According to the welding image area information and the parameter monitoring information constituting the corresponding abnormal parameters, all the parameter monitoring information corresponding to the abnormal parameters constitute the parameter monitoring information.

[0025] Furthermore, the monitoring plan generation module generates a monitoring plan based on the parameter monitoring information and the corresponding parameter monitoring weight information, including:

[0026] According to the sum of the weights of each abnormal parameter in the parameter monitoring information and the weight of the abnormal parameter, the monitoring page ratio corresponding to the abnormal parameter is obtained. All the abnormal parameter monitoring information and the corresponding web page monitoring page ratio constitute a monitoring plan.

[0027] Furthermore, the monitoring display module divides the display pages according to the monitoring scheme to perform welding status monitoring display, including:

[0028] If a single parameter is abnormal, the full-size page will be displayed;

[0029] If there are multiple parameters abnormalities, the monitoring display module divides the monitoring page according to the proportion of each corresponding abnormal parameter monitoring page in the monitoring plan, and displays the corresponding parameter abnormality monitoring information on the divided corresponding monitoring web page.

[0030] An automatic welding device, applying the welding monitoring method, comprises a welding process data acquisition device, a data storage module, a welding database, a monitoring scheme generation module, a monitoring display module, a data processing module and a communication module.

[0031] The welding process data acquisition device, data storage module, monitoring scheme generation module, monitoring display module and communication module are respectively connected to the data processing module; the welding database is in communication connection with the communication module;

[0032] The welding database is used to store welding related information, including the correspondence between equipment parameters, welding process parameters and welding monitoring image areas.

[0033] The beneficial effects of the present invention are: by real-time acquisition of various process data of welding equipment and 360° panoramic monitoring images, it can comprehensively and accurately reflect the operating status of the welding equipment and the dynamic changes of the welding process, providing comprehensive data support for monitoring the welding quality.

[0034] Through data analysis algorithms and intelligent judgment mechanisms, it can automatically identify the welding status, dynamically adjust the monitoring mode according to the welding status, and provide targeted monitoring solutions for abnormal conditions, greatly improving the intelligence level of welding monitoring.

[0035] The present invention supports both single-parameter and multi-parameter monitoring modes, which can be flexibly switched according to the actual situation during welding to meet the monitoring needs in different scenarios. At the same time, the monitoring display module can dynamically adjust the display page according to the monitoring plan, allowing operators to intuitively and quickly understand the welding status. BRIEF DESCRIPTION OF THE DRAWINGS

[0036] Figure 1 A schematic diagram of a welding monitoring method;

[0037] Figure 2 This is a schematic diagram of the principle of an automatic welding device. DETAILED DESCRIPTION

[0038] The technical solution of the present invention will be further described in detail below with reference to the accompanying drawings, but the protection scope of the present invention is not limited to the following.

[0039] The features and performance of the present invention are further described in detail below with reference to the embodiments.

[0040] like Figure 1As shown, a welding monitoring method includes the following steps:

[0041] Step 1: Collect welding process data and welding monitoring images of the welding equipment, and obtain status information of the welding equipment based on the welding process data. If the welding equipment status is abnormal, proceed to step 2;

[0042] In step 2, the control module generates a welding monitoring container, matches the welding equipment welding image based on the welding equipment information, and sends it to the welding monitoring container; the control module obtains the monitoring mode based on the welding status information. If it is a single parameter monitoring mode, it proceeds to step 3; if it is a multi-parameter monitoring mode, it proceeds to step 4;

[0043] Step 3: Send the welding status information to the welding monitoring container. The welding monitoring container obtains the welding image data corresponding to the abnormal parameters from the welding database based on the abnormal parameters in the welding image and the status information of the welding equipment, generates a monitoring plan, and sends it to the monitoring display module, and then proceeds to step 6;

[0044] In step 4, the control module generates monitoring containers corresponding to the abnormal parameters based on the multiple abnormal parameters in the welding status information, connects each monitoring container corresponding to the abnormal parameters to the welding monitoring container, and the welding monitoring container obtains welding image data corresponding to the parameter information from the welding database based on the welding image and the monitoring container corresponding to the abnormal parameters, generates parameter monitoring information, and sends it to the monitoring solution generation module, and then proceeds to step 5;

[0045] Step 5: The monitoring plan generation module generates a monitoring plan based on the parameter monitoring information and the corresponding parameter monitoring weight information, and sends it to the monitoring display module, and then proceeds to step 6;

[0046] Step 6: The monitoring display module divides the display pages according to the monitoring plan and performs welding status monitoring display.

[0047] The collection of welding process data and welding monitoring images of welding equipment includes:

[0048] The welding process data includes welding current, voltage, welding speed, welding equipment posture and welding equipment infrared image; the welding monitoring image is a panoramic image.

[0049] The method of obtaining welding status information according to welding process data includes:

[0050] The welding status information is obtained based on the welding process data. If all welding process data are normal, the welding status is normal; if there is a single welding process data abnormality, it is a single parameter abnormality, and the welding status is a single parameter status; if multiple parameters are abnormal, the welding status is a multi-parameter status.

[0051] The control module generates a welding monitoring container, matches the welding equipment welding image according to the welding equipment information, and sends the image to the welding monitoring container, including:

[0052] The control module obtains the device information of the abnormal state monitoring device, generates a welding monitoring container according to the device information, obtains the corresponding welding device welding image according to the device information, and sends it to the welding monitoring container.

[0053] The control module obtains a monitoring mode according to the welding status information, including:

[0054] If the welding status information indicates that a single parameter is abnormal, it is in single parameter monitoring mode; if the welding status information indicates that multiple parameters are abnormal, it is in multi-parameter monitoring mode.

[0055] The welding monitoring container obtains welding image data corresponding to abnormal parameters in the welding database according to abnormal parameters in the welding image and the status information of the welding equipment, generates a monitoring plan, and sends it to the monitoring display module, including:

[0056] According to the abnormal parameters in the status information, the welding image area information corresponding to the abnormal parameters is obtained in the welding database, and a monitoring plan is formed according to the welding image area information and the abnormal parameters.

[0057] The aforementioned method of connecting each monitoring container corresponding to the abnormal parameter to the welding monitoring container, wherein the welding monitoring container obtains welding image data corresponding to the parameter information from the welding database according to the welding image and the monitoring container corresponding to the abnormal parameter, and generates parameter monitoring information respectively, including:

[0058] According to the abnormal parameters in the status information, the welding image area information corresponding to the abnormal parameters is obtained in the welding database. According to the welding image area information and the parameter monitoring information constituting the corresponding abnormal parameters, all the parameter monitoring information corresponding to the abnormal parameters constitute the parameter monitoring information.

[0059] The monitoring plan generation module generates a monitoring plan based on the parameter monitoring information and the corresponding parameter monitoring weight information, including:

[0060] According to the sum of the weights of each abnormal parameter in the parameter monitoring information and the weight of the abnormal parameter, the monitoring page ratio corresponding to the abnormal parameter is obtained. All the abnormal parameter monitoring information and the corresponding web page monitoring page ratio constitute a monitoring plan.

[0061] The monitoring display module divides the display page according to the monitoring scheme and performs welding status monitoring display, including:

[0062] If a single parameter is abnormal, the full-size page will be displayed;

[0063] If there are multiple parameters abnormalities, the monitoring display module divides the monitoring page according to the proportion of each corresponding abnormal parameter monitoring page in the monitoring plan, and displays the corresponding parameter abnormality monitoring information on the divided corresponding monitoring web page.

[0064] like Figure 2 As shown, an automatic welding device, applying the welding monitoring method, includes a welding process data acquisition device, a data storage module, a welding database, a monitoring plan generation module, a monitoring display module, a data processing module and a communication module.

[0065] The welding process data acquisition device, data storage module, monitoring scheme generation module, monitoring display module and communication module are respectively connected to the data processing module; the welding database is in communication connection with the communication module;

[0066] The welding database is used to store welding related information, including the correspondence between equipment parameters, welding process parameters and welding monitoring image areas.

[0067] Specifically, the present invention adopts the following technical solutions:

[0068] A welding monitoring method comprises the following steps:

[0069] Step 1: Collect welding process data and welding monitoring images from the welding equipment. This welding process data includes, but is not limited to, welding current, voltage, welding speed, welding equipment posture (such as tilt angle and rotation angle), and infrared images of the welding equipment. This data is collected in real time using appropriate sensors and detection equipment, comprehensively reflecting the operating status of the welding equipment and the physical characteristics of the welding process.

[0070] The welding monitoring image is a 360° panoramic image, which is obtained through a panoramic camera and can fully display the environment of the welding site and the status of the welding parts, providing intuitive visual information for subsequent abnormality analysis and monitoring plan formulation.

[0071] The welding equipment status information is obtained based on the welding process data. Data analysis algorithms are used to process the collected welding process data in real time to determine whether each parameter is within the normal range. If all welding process data are normal, the welding status is normal. If a single welding process data anomaly indicates a single parameter anomaly, the welding status is considered single-parameter. If multiple parameters are abnormal, the welding status is considered multi-parameter. If the welding equipment status is abnormal, proceed to step two.

[0072] In step 2, the control module generates a welding monitoring container and, based on the welding equipment information, matches the welding equipment's welding image to the welding monitoring container. The control module obtains device information for the abnormal status monitoring equipment, such as the model and serial number, and generates a virtual welding monitoring container based on this information to store and manage monitoring data and information related to the equipment. Simultaneously, the control module retrieves the corresponding welding equipment's welding image from the data storage module or welding database based on the equipment information and sends it to the welding monitoring container, providing visual information about the equipment during monitoring.

[0073] The control module determines the monitoring mode based on the welding status information. If the welding status information indicates a single parameter abnormality, the control module enters the single-parameter monitoring mode, focusing on monitoring and analyzing the abnormal parameter. If the welding status information indicates multiple parameters abnormality, the control module enters the multi-parameter monitoring mode, requiring simultaneous monitoring and processing of multiple abnormal parameters. If the control mode is single-parameter monitoring mode, the control module proceeds to step 3; if the control mode is multi-parameter monitoring mode, the control module proceeds to step 4.

[0074] Step 3: Send the welding status information to the welding monitoring container.

[0075] The welding monitoring container receives and stores welding status information, including the specific values of abnormal parameters and the time when the abnormality occurred. Based on the abnormal parameters in the welding image and the status information of the welding equipment, the welding monitoring container obtains the welding image data corresponding to the abnormal parameters from the welding database, generates a monitoring plan, and sends it to the monitoring display module.

[0076] Based on the abnormal parameters in the status information, the welding monitoring container searches the welding database for information related to the weld image region, such as the weld location and defect type corresponding to the abnormal parameter. Combining this information with the abnormal parameters, the welding monitoring container generates a monitoring plan that includes the abnormal location labeling and abnormal parameter descriptions, and sends it to the monitoring display module for display. Proceed to step 6.

[0077] In step 4, the control module generates monitoring containers corresponding to the multiple abnormal parameters in the welding status information. For multiple-parameter abnormalities, the control module generates a monitoring container for each abnormal parameter to independently store and manage monitoring data and information related to that parameter. Each monitoring container corresponding to the abnormal parameter is connected to the welding monitoring container. Each abnormal parameter monitoring container is connected to the main welding monitoring container, forming a multi-level monitoring structure that facilitates simultaneous monitoring and processing of multiple abnormal parameters. Based on the welding image and the monitoring container corresponding to the abnormal parameter, the welding monitoring container retrieves welding image data corresponding to the parameter information from the welding database, generates parameter monitoring information, and sends it to the monitoring solution generation module. Based on the information in the monitoring container for each abnormal parameter, the welding monitoring container queries the welding database and retrieves the welding image data related to that parameter. Combining the welding image data and abnormal parameter information, the welding monitoring container generates comprehensive monitoring data containing monitoring information for multiple abnormal parameters and sends it to the monitoring solution generation module. Proceed to step 5.

[0078] In step 5, the monitoring plan generation module generates a monitoring plan based on the parameter monitoring information and the corresponding parameter monitoring weight information. The monitoring plan generation module receives the parameter monitoring information from the welding monitoring container and assigns weights to each abnormal parameter based on preset parameter monitoring weight information (such as the degree of impact of each parameter on welding quality and the frequency of abnormalities). Based on the sum of the weights of each abnormal parameter in the parameter monitoring information and the abnormal parameter weight, the monitoring page ratio corresponding to the abnormal parameter is calculated, that is, the proportion of each abnormal parameter in the monitoring display page. All abnormal parameter monitoring information and the corresponding web monitoring page ratios constitute a complete monitoring plan. This plan is then sent to the monitoring display module, and the process proceeds to step 6.

[0079] Step 6: The monitoring display module divides the display pages according to the monitoring plan and performs welding status monitoring display.

[0080] If a single parameter is abnormal, the monitoring display module uses a full-size page to display the monitoring information of the abnormal parameter, including an image of the abnormal part, the abnormal parameter value, and processing suggestions.

[0081] If there are multiple parameters abnormalities, the monitoring display module divides the monitoring page according to the proportion of each corresponding abnormal parameter monitoring page in the monitoring plan, and displays the corresponding parameter abnormal monitoring information in the divided corresponding monitoring web page area to ensure that each abnormal parameter can receive sufficient attention and display.

[0082] The automatic welding device includes a welding process data acquisition device, a data storage module, a welding database, a monitoring program generation module, a monitoring display module, a data processing module and a communication module.

[0083] The welding process data acquisition device is responsible for collecting the welding process data and welding monitoring images of the welding equipment in real time, and sending the data to the data processing module through the communication module.

[0084] The data storage module is used to store the collected welding process data and monitoring images, as well as other data generated during the system operation.

[0085] The welding database is the system's core data warehouse, used to store welding-related information, including equipment parameters, the correspondence between welding process parameters and welding monitoring image areas, and suggestions for handling abnormal parameters. This information provides basic data support for the system's intelligent analysis and monitoring plan formulation.

[0086] The monitoring plan generation module generates a personalized monitoring plan based on the received parameter monitoring information and parameter monitoring weight information, and sends it to the monitoring display module.

[0087] The monitoring display module is responsible for displaying the monitoring plan in an intuitive and easy-to-understand manner for operators to view and process.

[0088] The data processing module is the core of the system, responsible for receiving, processing and analyzing data from the welding process data acquisition device, as well as data interaction with the data storage module, welding database, monitoring plan generation module and monitoring display module.

[0089] The communication module is responsible for the communication connection between the modules within the system, as well as the communication with external devices (such as welding equipment, sensors, etc.).

[0090] The welding process data acquisition device, data storage module, monitoring scheme generation module, monitoring display module and communication module are respectively connected to the data processing module; the welding database is communicatively connected to the communication module.

[0091] The welding database is used to store welding related information, including the correspondence between equipment parameters, welding process parameters and welding monitoring image areas.

[0092] Example 1: Single parameter abnormality monitoring

[0093] In an automated welding production line of a certain manufacturing plant, an automatic welding device based on the above-mentioned welding monitoring method is used to monitor various parameters in the welding process in real time to ensure welding quality.

[0094] Specific implementation steps:

[0095] Step 1: Data collection and status judgment

[0096] The welding process data acquisition device uses sensors installed on the welding equipment to collect real-time data such as welding current, voltage, welding speed, and the welding equipment's posture (such as tilt angle). At the same time, a panoramic camera captures 360-degree welding monitoring images.

[0097] After receiving this data, the data processing module uses a data analysis algorithm to perform real-time processing. It finds that the welding current exceeds the preset normal range, while other parameters are normal. The system determines that a single parameter (welding current) is abnormal.

[0098] Step 2: Generate monitoring container and matching image

[0099] Based on the abnormal state (abnormal welding current), the control module generates a virtual welding monitoring container for the welding equipment. The control module retrieves welding monitoring images of the equipment from the data storage module, specifically images of areas potentially associated with abnormal welding current, such as the contact area between the welding torch and the workpiece, and sends them to the welding monitoring container.

[0100] Step 3: Send status information to the monitoring container and generate a monitoring plan

[0101] The welding monitoring container receives and stores information such as the specific value of the abnormal welding current and the time the abnormality occurred. Based on the welding image and the abnormal parameter (welding current), the welding monitoring container searches the welding database for information about the relevant welding image area, such as the possible defect type (such as a weld that is too wide or too narrow), and generates a monitoring plan that includes the abnormal area annotation and abnormal parameter description.

[0102] Step 6: Monitor the display

[0103] After receiving the monitoring plan, the monitoring display module uses a full-size page to display the monitoring information of the welding current abnormality, because it is a single parameter abnormality, including an image of the abnormal part, abnormal current value, and processing suggestions (such as adjusting the welding current setting), so that the operator can take quick measures.

[0104] Example 2: Multi-parameter abnormality monitoring

[0105] During the precision welding process of a certain component, an automatic welding device using the above-mentioned welding monitoring method was used to ensure the high stability and accuracy of the welding process.

[0106] Specific implementation steps:

[0107] Step 1: Data collection and status judgment

[0108] The welding process data acquisition device collects real-time data such as welding current, voltage, welding speed, and infrared images of the welding equipment. A panoramic camera provides a 360-degree image of the welding environment. The data processing module analyzes and finds that both the welding current and voltage are outside the normal range, while the welding speed is normal. The system identifies a multi-parameter abnormality.

[0109] Step 2: Generate monitoring container and matching image

[0110] The control module generates a main welding monitoring container for multi-parameter abnormalities and two sub-monitoring containers for welding current and voltage abnormalities, respectively. The control module retrieves welding monitoring images related to these two abnormal parameters from the welding database, such as the welding gun head thermal distribution image (correlated infrared image) and weld formation image, and sends them to the corresponding monitoring containers.

[0111] Step 4: Generate parameter monitoring information

[0112] Based on the welding image and information from the two sub-monitoring containers, the main welding monitoring container queries the welding database to retrieve welding image data related to welding current and voltage anomalies. Combining this data, the main welding monitoring container generates comprehensive monitoring data containing welding current and voltage anomaly monitoring information.

[0113] Step 5: Generate a monitoring plan

[0114] The monitoring plan generation module receives comprehensive monitoring data and assigns a weight to each abnormal parameter based on preset parameter monitoring weights (taking into account the impact of current and voltage on welding quality). Based on this weight, the module determines the proportion of abnormal welding current and voltage on the monitoring display page and generates a monitoring plan that includes monitoring information for both abnormal parameters.

[0115] Step 6: Monitor the display

[0116] Based on the monitoring plan, the monitoring display module divides the monitoring page into two sections, corresponding to monitoring information for welding current and voltage anomalies. Each section displays an image of the abnormal area, the abnormal parameter value, and treatment suggestions (such as adjusting welding current and voltage settings simultaneously), ensuring that operators can fully understand and handle multi-parameter abnormalities.

Claims

1. A welding monitoring method, characterized in that: The steps include: Step 1: Collect welding process data and welding monitoring images of the welding equipment, and obtain status information of the welding equipment based on the welding process data. If the welding equipment status is abnormal, proceed to step 2; In step 2, the control module generates a welding monitoring container, matches the welding equipment welding image based on the welding equipment information, and sends it to the welding monitoring container; the control module obtains the monitoring mode based on the welding status information. If it is a single parameter monitoring mode, it proceeds to step 3; if it is a multi-parameter monitoring mode, it proceeds to step 4; Step 3: Send the welding status information to the welding monitoring container. The welding monitoring container searches the welding database for welding image area information related to the abnormal parameters based on the abnormal parameters in the welding image and the welding equipment status information, including the welding location and defect type corresponding to the abnormal parameters, and generates a monitoring plan. The plan is sent to the monitoring display module, and then the process proceeds to step 6. In step 4, the control module generates monitoring containers corresponding to the abnormal parameters based on the multiple abnormal parameters in the welding status information, connects each monitoring container corresponding to the abnormal parameters to the welding monitoring container, and the welding monitoring container obtains welding image area information related to the abnormal parameters from the welding database based on the welding image and the monitoring container corresponding to the abnormal parameters, including the welding location and defect type corresponding to the abnormal parameters, generates parameter monitoring information, and sends it to the monitoring plan generation module, and then proceeds to step 5; Step 5: The monitoring plan generation module generates a monitoring plan based on the parameter monitoring information and the corresponding parameter monitoring weight information, and sends it to the monitoring display module, and then proceeds to step 6; Step 6: The monitoring display module divides the display page according to the monitoring plan and performs welding status monitoring display; The control module obtains a monitoring mode according to the welding status information, including: If the welding status information indicates a single parameter abnormality, the system will be in single parameter monitoring mode; if the welding status information indicates multiple parameters abnormality, the system will be in multi-parameter monitoring mode. The monitoring plan generation module generates a monitoring plan based on the parameter monitoring information and the corresponding parameter monitoring weight information, including: According to the sum of the weights of each abnormal parameter in the parameter monitoring information and the weight of the abnormal parameter, the proportion of monitoring pages corresponding to the abnormal parameter is obtained. All abnormal parameter monitoring information and the corresponding web page monitoring page proportion constitute a monitoring plan; The monitoring display module divides the display page according to the monitoring scheme and performs welding status monitoring display, including: If a single parameter is abnormal, the full-size page will be displayed; If there are multiple parameters abnormalities, the monitoring display module divides the monitoring page according to the proportion of each corresponding abnormal parameter monitoring page in the monitoring plan, and displays the corresponding parameter abnormality monitoring information on the divided corresponding monitoring web page.

2. A welding monitoring method according to claim 1, characterized in that: The collection of welding process data and welding monitoring images of welding equipment includes: The welding process data includes welding current, voltage, welding speed, welding equipment posture and welding equipment infrared image; the welding monitoring image is a 360-degree panoramic image.

3. A welding monitoring method according to claim 2, characterized in that: The method of obtaining welding status information according to welding process data includes: The welding status information is obtained based on the welding process data. If all welding process data are normal, the welding status is normal; if there is a single welding process data abnormality, it is a single parameter abnormality, and the welding status is a single parameter status; if multiple parameters are abnormal, the welding status is a multi-parameter status.

4. A welding monitoring method according to claim 3, characterized in that: The control module generates a welding monitoring container, matches the welding equipment welding image according to the welding equipment information, and sends the image to the welding monitoring container, including: The control module obtains the device information of the abnormal state monitoring device, generates a welding monitoring container according to the device information, obtains the corresponding welding device welding image according to the device information, and sends it to the welding monitoring container.

5. A welding monitoring method according to claim 4, characterized in that: The welding monitoring container obtains welding image data corresponding to abnormal parameters in the welding database according to abnormal parameters in the welding image and the status information of the welding equipment, generates a monitoring plan, and sends it to the monitoring display module, including: According to the abnormal parameters in the status information, the welding image area information corresponding to the abnormal parameters is obtained in the welding database, and a monitoring plan is formed according to the welding image area information and the abnormal parameters.

6. A welding monitoring method according to claim 5, characterized in that: The aforementioned method of connecting each monitoring container corresponding to the abnormal parameter to the welding monitoring container, wherein the welding monitoring container obtains welding image data corresponding to the parameter information from the welding database according to the welding image and the monitoring container corresponding to the abnormal parameter, and generates parameter monitoring information respectively, including: According to the abnormal parameters in the status information, the welding image area information corresponding to the abnormal parameters is obtained in the welding database. According to the welding image area information and the parameter monitoring information constituting the corresponding abnormal parameters, all the parameter monitoring information corresponding to the abnormal parameters constitute the parameter monitoring information.

7. An automatic welding monitoring device, characterized in that: A welding monitoring method according to any one of claims 1 to 6 is applied, comprising a welding process data acquisition device, a data storage module, a welding database, a monitoring scheme generation module, a monitoring display module, a data processing module, and a communication module; The welding process data acquisition device, data storage module, monitoring scheme generation module, monitoring display module and communication module are respectively connected to the data processing module; the welding database is in communication connection with the communication module; The welding database is used to store welding related information, including the correspondence between equipment parameters, welding process parameters and welding monitoring image areas.

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