Intelligent identification method and system for abnormal points in communication mold welding

Abstract

The present invention relates to the field of intelligent identification, and proposes an intelligent identification method and system for abnormal points under communication mold welding. The method includes: first obtaining welding temperature data, collecting hot spot distribution information and querying temperature sequence, extracting temperature peak points and detecting abnormal temperature areas, then fitting a curve of temperature change gradient in abnormal areas, identifying trends and calculating change rates, based on which heat transfer analysis is performed, temperature control ratings are determined and thermal equilibrium points are marked, then thermal control channels are determined and states are detected, channel heat capacity is calculated to optimize monitoring thresholds and calculate threshold deviation rates, and finally abnormal welding instructions are generated based on the deviation rates, welding parameters are queried and welding factors are identified, and abnormal monitoring details are generated. The present invention can improve the effect of abnormal point identification under communication mold welding.

Description

Technical Field

[0001] The present invention relates to the field of intelligent identification, and in particular to an abnormal point intelligent identification method and system applied to communication mold welding. Background Art

[0002] In the field of modern industrial production, the welding quality of communication molds plays a vital role in the performance and reliability of communication equipment. Especially in the context of large-scale production and complex processes, the need for accurate identification of welding abnormalities is becoming more and more urgent.

[0003] At present, the traditional communication mold welding abnormal point detection method mainly relies on manual observation and simple measuring tools (such as weld inspection ruler, micrometer, etc.). This method is not only extremely inefficient, but also greatly affected by human factors, and is prone to missed detection and misjudgment. The traditional detection method is fixed and single, and it is difficult to adapt to the diversity and complexity of welding conditions of communication molds of different types and specifications, which easily leads to poor detection results. Therefore, a communication mold welding abnormal point intelligent recognition method based on deep learning is needed to improve the effect of abnormal point recognition under communication mold welding. Summary of the invention

[0004] The present invention provides an abnormal point intelligent identification method and system applied to communication mold welding, the main purpose of which is to improve the effect of abnormal point identification in communication mold welding.

[0005] Acquire welding temperature data of the communication mold during the welding process, collect hot spot distribution information in the welding temperature data, query the temperature sequence corresponding to the hot spot distribution information, extract the temperature peak point in the temperature sequence, and detect the abnormal temperature area corresponding to the temperature peak point;

[0006] Performing curve fitting on the temperature change gradient in the abnormal temperature region to obtain a gradient change curve, identifying the temperature change trend in the gradient change curve, and calculating the temperature change rate corresponding to the temperature change trend;

[0007] Based on the temperature change rate, a heat transfer process analysis is performed on the communication mold to obtain heat transfer data, and the thermal stability corresponding to the heat transfer data is monitored. Based on the thermal stability, a temperature control rating corresponding to the communication mold is determined, and a rating point in the temperature control rating is queried, and a thermal balance point corresponding to the rating point is marked;

[0008] Based on the thermal equilibrium point, determine the thermal control channel corresponding to the welding of the communication mold, detect the channel state corresponding to the thermal control channel, calculate the channel heat capacity corresponding to the thermal control channel based on the channel state, optimize the monitoring threshold of the communication mold in the thermal monitoring process based on the channel heat capacity, and calculate the threshold deviation rate corresponding to the monitoring threshold;

[0009] Based on the threshold deviation rate, an abnormal welding instruction corresponding to the communication mold welding is generated, the welding parameters corresponding to the abnormal welding instruction are queried, the welding factors corresponding to the welding parameters are identified, and based on the welding factors, an abnormal monitoring list corresponding to the communication mold welding is generated.

[0010] Optionally, the collecting hotspot distribution information in the welding temperature data includes:

[0011] Performing data preprocessing on the welding temperature data to obtain preprocessed temperature data;

[0012] Based on the pretreatment temperature data, construct a temperature field corresponding to the welding temperature data;

[0013] Setting a temperature threshold corresponding to the temperature field;

[0014] Based on the temperature threshold, determining a hot spot area corresponding to the welding temperature data;

[0015] The hotspot distribution information in the hotspot area is collected.

[0016] Optionally, the detecting the abnormal temperature area corresponding to the temperature peak point includes:

[0017] Taking the temperature peak point as the center, determining the corresponding temperature measurement area;

[0018] Querying the area range corresponding to the temperature measurement area, and collecting detailed temperature data within the area range;

[0019] Smoothing the detailed temperature data to obtain smoothed temperature data;

[0020] Comparing the temperature difference between the smoothed temperature data and a preset temperature deviation threshold to obtain temperature deviation data;

[0021] Identify abnormal temperature points in the temperature deviation data; and query abnormal temperature areas corresponding to the abnormal temperature points.

[0022] Optionally, performing curve fitting on the temperature change gradient in the abnormal temperature region to obtain a gradient change curve includes:

[0023] Dividing the abnormal temperature area into a plurality of spatial grids;

[0024] Calculating the temperature difference between the spatial grids;

[0025] Arrange the temperature difference values ​​in order according to their numerical values ​​to obtain a temperature difference sequence;

[0026] Analyzing the temperature change gradient corresponding to the temperature difference sequence;

[0027] The temperature change gradient is subjected to curve fitting to obtain a gradient change curve.

[0028] Optionally, calculating the temperature change rate corresponding to the temperature change trend includes:

[0029] The temperature change rate corresponding to the temperature change trend is calculated using the following formula:

[0030]

[0031] in, represents the temperature change rate corresponding to the temperature change trend, represents the final temperature, represents the initial temperature, represents the time interval over which the temperature variation trend is measured, represents the correction factor, Indicates the ambient reference temperature, Indicates the average temperature of the temperature change trend within the time period.

[0032] Optionally, performing heat transfer process analysis on the communication mold based on the temperature change rate to obtain heat transfer data includes:

[0033] Query the change value corresponding to the temperature change rate;

[0034] Based on the changed value, determining the key measurement point corresponding to the communication mold;

[0035] Based on the key measurement points, construct a temperature change matrix corresponding to the communication mold;

[0036] Analyzing the heat flux corresponding to the temperature change matrix, and drawing a heat flow path corresponding to the heat flux;

[0037] Based on the heat flow path, a heat transfer process analysis is performed on the communication mold to obtain heat transfer data.

[0038] Optionally, determining the temperature control rating corresponding to the communication mold based on the thermal stability includes:

[0039] Determining a thermal stability index corresponding to the thermal stability, and collecting a thermal stability parameter corresponding to the thermal stability index;

[0040] Performing data classification on the thermal stability parameters to obtain thermal stability classification parameters;

[0041] Query the temperature control level range corresponding to the thermal stability classification parameter;

[0042] Based on the temperature control level range, a temperature control rating corresponding to the communication mold is determined.

[0043] Optionally, calculating the channel heat capacity corresponding to the thermal control channel based on the channel state includes:

[0044] The channel heat capacity corresponding to the thermal control channel is calculated using the following formula:

[0045]

[0046] in, represents the channel heat capacity corresponding to the thermal control channel, Indicates the average density of the fluid in the channel corresponding to the channel state, represents the effective volume corresponding to the thermal control channel, Indicates the average temperature change value in the channel corresponding to the channel state, represents the correction factor of the channel state to the heat capacity, represents the roughness coefficient of the inner wall of the thermal control channel, represents the amplitude coefficient related to the influence of the thermal control channel and the inner wall roughness on the heat capacity, Indicates the obstruction coefficient in the channel corresponding to the channel state, Indicates the influence coefficient related to the heat capacity effect.

[0047] Optionally, calculating the threshold deviation rate corresponding to the monitoring threshold includes:

[0048] The threshold deviation rate corresponding to the monitoring threshold is calculated using the following formula:

[0049]

[0050] in, represents the threshold deviation rate corresponding to the monitoring threshold, represents the index of the monitoring point corresponding to the monitoring threshold, Indicates the total number of monitoring points corresponding to the monitoring threshold, Indicates The set temperature of each monitoring point, Indicates The actual measured temperature of each monitoring point, Indicates The weight of each monitoring point, Indicates the highest temperature set among all monitoring points. Indicates the lowest temperature set among all monitoring points.

[0051] In order to solve the above problems, the present invention also provides an abnormal point intelligent identification system for communication mold welding, the system comprising:

[0052] An area detection module is used to obtain welding temperature data of the communication mold during the welding process, collect hot spot distribution information in the welding temperature data, query the temperature sequence corresponding to the hot spot distribution information, extract the temperature peak point in the temperature sequence, and detect the abnormal temperature area corresponding to the temperature peak point;

[0053] a change rate calculation module, used for performing curve fitting on the temperature change gradient in the abnormal temperature region to obtain a gradient change curve, identifying the temperature change trend in the gradient change curve, and calculating the temperature change rate corresponding to the temperature change trend;

[0054] A balance point marking module is used to analyze the heat transfer process of the communication mold based on the temperature change rate, obtain heat transfer data, monitor the thermal stability corresponding to the heat transfer data, determine the temperature control rating corresponding to the communication mold based on the thermal stability, query the rating points in the temperature control rating, and mark the thermal balance point corresponding to the rating point;

[0055] a deviation rate calculation module, used for determining the thermal control channel corresponding to the welding of the communication mold based on the thermal equilibrium point, detecting the channel state corresponding to the thermal control channel, calculating the channel heat capacity corresponding to the thermal control channel based on the channel state, optimizing the monitoring threshold of the communication mold in the thermal monitoring process based on the channel heat capacity, and calculating the threshold deviation rate corresponding to the monitoring threshold;

[0056] The detailed list generation module is used to generate an abnormal welding instruction corresponding to the communication mold welding based on the threshold deviation rate, query the welding parameters corresponding to the abnormal welding instructions, identify the welding factors corresponding to the welding parameters, and generate an abnormal monitoring detailed list corresponding to the communication mold welding based on the welding factors.

[0057] Firstly, by acquiring the welding temperature data of the communication mold during the welding process, the present invention can timely discover the area with abnormal temperature, give early warning of possible welding defects, effectively avoid subsequent quality problems, and achieve the best welding effect. At the same time, the present invention obtains a gradient change curve by curve fitting the temperature change gradient in the abnormal temperature area, which helps to accurately judge the nature and severity of the abnormality, such as whether the abnormality is caused by local heat accumulation or poor heat dissipation. Secondly, it provides a key basis for optimizing the welding process to improve temperature distribution and reduce the occurrence of abnormal situations. Based on the temperature change rate, the present invention analyzes the heat transfer process of the communication mold to obtain heat transfer data, which can help accurately evaluate the thermal performance of the mold during the working process. And by deeply understanding the heat transfer situation, it can be clear how the heat flows between the inside of the mold and the external environment, thereby providing a key basis for optimizing the structural design of the mold. The present invention determines the thermal control channel corresponding to the communication mold welding based on the thermal equilibrium point, and can clarify the key position of the heat distribution of the mold during the welding process, so as to design the thermal control channel in a targeted manner, so that the heat can be more effectively conducted and dissipated, and avoid welding defects caused by local overheating. Furthermore, the present invention generates abnormal welding instructions corresponding to the communication mold welding based on the threshold deviation rate, which can timely discover and handle situations where there are deviations from the expected threshold, and can effectively eliminate potential welding defects, ensuring that each welding point meets the quality standards and improving the overall reliability of the product. Therefore, the intelligent identification method and system for abnormal points applied to communication mold welding proposed by the present invention can improve the effect of abnormal point identification under communication mold welding. BRIEF DESCRIPTION OF THE DRAWINGS

[0058] Figure 1 A schematic diagram of a flow chart of an abnormal point intelligent identification method applied to communication mold welding provided by an embodiment of the present invention;

[0059] Figure 2 A schematic diagram of the structure of the exhaust slot in the abnormal point intelligent identification method applied to the communication mold welding provided by one embodiment of the present invention;

[0060] Figure 3 A schematic diagram of a module of an abnormal point intelligent identification system for communication mold welding provided by an embodiment of the present invention.

[0061] The realization of the purpose, functional features and advantages of the present invention will be further explained in conjunction with embodiments and with reference to the accompanying drawings. DETAILED DESCRIPTION

[0062] It should be understood that the specific embodiments described herein are only used to explain the present invention, and are not used to limit the present invention.

[0063] The embodiment of the present application provides an intelligent identification method for abnormal points applied to communication mold welding. The execution subject of the method for intelligent identification of abnormal points applied to communication mold welding includes but is not limited to at least one of the electronic devices such as a server and a terminal that can be configured to execute the method provided by the embodiment of the present application. In other words, the method for intelligent identification of abnormal points applied to communication mold welding can be executed by software or hardware installed on a terminal device or a server device, and the software can be a blockchain platform. The server includes but is not limited to: a single server, a server cluster, a cloud server or a cloud server cluster, etc. The server can be an independent server, or it can be a cloud server that provides basic cloud computing services such as cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communications, middleware services, domain name services, security services, content delivery networks (CDN), and big data and artificial intelligence platforms.

[0064] Reference Figure 1 FIG. 1 is a flow chart of an abnormal point intelligent identification method applied to communication mold welding provided by an embodiment of the present invention. In this embodiment, the abnormal point intelligent identification method applied to communication mold welding includes:

[0065] S1. Obtain welding temperature data of a communication mold during a welding process, collect hotspot distribution information in the welding temperature data, query a temperature sequence corresponding to the hotspot distribution information, extract a temperature peak point in the temperature sequence, and detect an abnormal temperature area corresponding to the temperature peak point.

[0066] By acquiring the welding temperature data of the communication mold during the welding process, the present invention can timely discover the area with abnormal temperature, warn in advance of possible welding defects, effectively avoid subsequent quality problems, and achieve the best welding effect.

[0067] Among them, the communication mold refers to a mold used to manufacture communication equipment parts, such as a molding mold for manufacturing mobile phone housings, base station components and other communication-related products; the welding temperature data refers to the temperature information of the welding area collected by specific temperature measuring equipment and technology during the welding process of the communication mold, including the temperature values ​​of the welding point, weld and its surrounding area at different time points, as well as temperature change trends and distribution data, for example, the temperature value recorded every second or every minute by a thermocouple or infrared thermometer, or the maximum, minimum and average temperature over a period of time and other statistical data. Optionally, the acquisition of the welding temperature data of the communication mold during the welding process can be achieved through temperature detection tools, such as: infrared temperature measuring guns, thermal imaging cameras, etc.

[0068] By collecting the hot spot distribution information in the welding temperature data, the present invention can accurately locate the area with too high temperature during the welding process, so that the welding current, voltage, welding speed and other parameters can be adjusted in a targeted manner to make the heat distribution more uniform and improve the consistency and stability of welding.

[0069] The hotspot distribution information refers to detailed data and feature descriptions such as the location, range, temperature value of the hotspot area in space and the relationship between hotspots.

[0070] As an embodiment of the present invention, the collecting of hotspot distribution information in the welding temperature data includes: performing data preprocessing on the welding temperature data to obtain preprocessed temperature data; constructing a temperature field corresponding to the welding temperature data based on the preprocessed temperature data; setting a temperature threshold corresponding to the temperature field; determining a hotspot area corresponding to the welding temperature data based on the temperature threshold; and collecting hotspot distribution information in the hotspot area.

[0071] Among them, the pre-processed temperature data refers to the welding temperature data after data cleaning, screening, smoothing and other operations, the purpose of which is to remove interference factors such as noise and outliers, so that the data is more accurate, reliable, and more suitable for subsequent analysis and processing; the temperature field refers to the field formed by the temperature distribution of each position in the welding area during the welding process, which can intuitively display the spatial changes and distribution of temperature; the temperature threshold refers to a specific temperature value set when determining the hot spot area. When the temperature in the temperature field exceeds this value, the corresponding area is identified as a hot spot area; the hot spot area refers to a local area in the welding temperature field where the temperature exceeds the set threshold. These areas may have potential welding quality problems or thermal phenomena that require special attention.

[0072] Furthermore, the data preprocessing of the welding temperature data can be achieved through Python tools, such as: using Python's Pandas library to read the welding temperature data, removing duplicate data through the drop_duplicates function, using the fillna function to fill missing values, and then using the rolling_mean function to perform mean filtering to achieve data smoothing; the construction of the temperature field corresponding to the welding temperature data can be achieved through finite element analysis tools, such as: ANSYS, COMSOL and other tools; the setting of the temperature threshold corresponding to the temperature field can be achieved through a clustering algorithm, such as: K-Means algorithm, etc.; the determination of the hot spot area corresponding to the welding temperature data can be achieved through an image segmentation method, such as: segmenting the temperature field image into hot spot areas and non-hot spot areas according to a threshold; the collection of hot spot distribution information in the hot spot area can be achieved through the Scikit-image library in Python.

[0073] The present invention queries the temperature sequence corresponding to the hot spot distribution information and extracts the temperature peak points in the temperature sequence. The welding parameters, such as current, voltage, welding speed, etc., can be adjusted according to these peak points to achieve a more uniform and stable temperature distribution and improve the consistency of welding quality.

[0074] Among them, the temperature sequence refers to a series of temperature measurement values ​​arranged in chronological order, which records the temperature changes in a specific time period; the temperature peak point refers to the time point corresponding to the highest temperature value reached in the temperature sequence, representing the maximum value to which the temperature rises in the time period. Optionally, the query of the temperature sequence corresponding to the hotspot distribution information can be implemented through database management system tools, such as MySQL, Oracle and other tools; the extraction of the temperature peak point in the temperature sequence can be implemented through Python's NumPy library, such as: directly obtaining the maximum value in the temperature sequence as the temperature peak point through the np.max() function in the NumPy library.

[0075] Furthermore, by detecting the abnormal temperature area corresponding to the temperature peak point, the present invention can adjust the power, welding speed, shielding gas flow rate and other parameters of the welding equipment in a targeted manner according to the position, size and temperature deviation degree of the abnormal temperature area to achieve a more uniform and stable welding temperature distribution.

[0076] The abnormal temperature area refers to an area with a certain range composed of multiple adjacent abnormal temperature points.

[0077] As an embodiment of the present invention, the detecting of the abnormal temperature area corresponding to the temperature peak point includes: determining the temperature measurement area corresponding to the temperature peak point as the center; querying the area range corresponding to the temperature measurement area; collecting detailed temperature data within the area range; smoothing the detailed temperature data to obtain smoothed temperature data; comparing the temperature difference between the smoothed temperature data and a preset temperature deviation threshold to obtain temperature deviation data; identifying abnormal temperature points in the temperature deviation data; and querying the abnormal temperature area corresponding to the abnormal temperature points.

[0078] Among them, the temperature measurement area refers to a specific area with the temperature peak point as the core and covering a certain range of the surrounding area; the area range refers to the specific boundary and size description of the temperature measurement area in space; the detailed temperature data refers to the specific temperature values ​​collected at each location and each time point in the determined temperature measurement area; the smoothed temperature data refers to the data that is processed by a specific data processing method (such as moving average, median filtering, etc.) to reduce noise and fluctuations to obtain a smoother and more reflective data of the overall trend; the preset temperature deviation threshold refers to a standard value set in advance for judging whether the temperature is abnormal. If the value exceeds this value, it is considered that there may be a temperature anomaly; the temperature deviation data refers to the difference data between the smoothed temperature data and the preset standard temperature or average temperature; the abnormal temperature point refers to the specific position or measurement point corresponding to the preset temperature deviation threshold in the temperature deviation data.

[0079] Furthermore, the determination of the corresponding temperature measurement area can be achieved through GIS tools, such as: in the GIS tool, input the coordinates of the temperature peak point, and draw a circular area with a radius of 5 cm as the temperature measurement area; the query of the area range corresponding to the temperature measurement area can be achieved through regional measurement tools, such as: CAD and other tools; the collection of detailed temperature data within the area range can be achieved through data sampling algorithms, such as: simple random sampling, adaptive sampling and other algorithms; the smoothing of the detailed temperature data can be achieved through a moving average method, such as: SMA, WMA, etc.; the identification of abnormal temperature points in the temperature deviation data can be achieved through MATLAB, such as: in MATLAB, setting the temperature deviation threshold to 5°C, and points greater than this value are identified as abnormal temperature points; the query of the abnormal temperature area corresponding to the abnormal temperature point can be achieved through regional processing tools, such as: ImageJ and other tools.

[0080] S2. Perform curve fitting on the temperature change gradient in the abnormal temperature region to obtain a gradient change curve, identify the temperature change trend in the gradient change curve, and calculate the temperature change rate corresponding to the temperature change trend.

[0081] The present invention obtains a gradient change curve by curve fitting of the temperature change gradient in the abnormal temperature area, which helps to accurately judge the nature and severity of the abnormality, such as whether the abnormality is caused by local heat accumulation or poor heat dissipation. Secondly, it provides a key basis for optimizing the welding process to improve temperature distribution and reduce the occurrence of abnormal situations.

[0082] The gradient change curve refers to a graph obtained by curve fitting the temperature change gradient data, which can intuitively show the trend of the temperature change gradient changing with spatial position or time.

[0083] As an embodiment of the present invention, curve fitting is performed on the temperature change gradient in the abnormal temperature area to obtain a gradient change curve, including: dividing the abnormal temperature area into multiple spatial grids; calculating the temperature difference between the spatial grids; arranging the temperature differences in order according to numerical values ​​to obtain a temperature difference sequence; analyzing the temperature change gradient corresponding to the temperature difference sequence; and curve fitting is performed on the temperature change gradient to obtain a gradient change curve.

[0084] Among them, the spatial grid refers to a number of small units into which the abnormal temperature area is divided in space, which is used to more accurately analyze the temperature distribution; the temperature difference refers to the difference in temperature measurement values ​​between adjacent spatial grids or specific locations; the temperature difference sequence refers to an ordered data sequence formed by arranging multiple calculated temperature differences in order from large to small or from small to large; the temperature change gradient refers to the rate of change of temperature in space or time, that is, the change in temperature per unit distance or unit time.

[0085] Furthermore, the division of the abnormal temperature area into multiple spatial grids can be achieved through finite element analysis tools, such as ANSYS and other tools; the calculation of the temperature difference between the spatial grids can be achieved through the following temperature difference calculation formula; the arrangement of the temperature differences in order according to numerical values ​​can be achieved through MATLAB tools, such as using the sort function in MATLAB to arrange the temperature difference array in ascending or descending order; the analysis of the temperature change gradient corresponding to the temperature difference sequence can be achieved through data analysis tools, such as Origin and other tools; the curve fitting of the temperature change gradient can be achieved through Excel tools, such as selecting the temperature change gradient data in Excel and adding a polynomial trend line for curve fitting.

[0086] As an embodiment of the present invention, the calculating the temperature difference between the spatial grids includes:

[0087] The temperature difference between the spatial grids is calculated using the following formula:

[0088]

[0089] in, represents the temperature difference between the spatial grids, represents the row index of the spatial grid in the two-dimensional plane, represents the column index of the spatial grid in the two-dimensional plane, The coordinates are ( )’s adjacent grid temperature value (right grid), The coordinates are ( )'s adjacent grid temperature value (left grid), The coordinates are ( )’s adjacent grid temperature value (the upper grid), The coordinates are ( )’s adjacent grid temperature (lower grid).

[0090] In detail, the two-dimensional plane refers to a plane with two dimensions (usually horizontal and vertical directions) used to describe the distribution of spatial grids. The upper grid refers to the grid located directly above the current grid (i, j) in the vertical direction, that is, the grid with coordinates (i, j+1); the lower grid refers to the grid located directly below the current grid (i, j) in the vertical direction, that is, the grid with coordinates (i, j-1); the left grid refers to the grid located directly to the left of the current grid (i, j) in the horizontal direction, that is, the grid with coordinates (i-1, j); the right grid refers to the grid located directly to the right of the current grid (i, j) in the horizontal direction, that is, the grid with coordinates (i+1, j).

[0091] Furthermore, by identifying the temperature change trend in the gradient change curve, the present invention can help to improve the design in a targeted manner, select more suitable materials or adjust the structure to enhance the performance and stability of the product under different temperature conditions.

[0092] Among them, the temperature change trend refers to the overall direction and characteristics of temperature rising, falling, remaining stable or fluctuating within a certain time or space range, which reflects the dynamic change pattern of temperature over time or at a specific spatial position, including the characteristics of the speed, amplitude, periodicity and continuity of the change. Optionally, the identification of the temperature change trend in the gradient change curve can be achieved through a temperature difference tool, such as: SPSS, Origin and other tools.

[0093] Furthermore, the present invention helps to predict the performance of materials under temperature changes by calculating the temperature change rate corresponding to the temperature change trend. Different materials respond differently to temperature changes. Understanding the temperature change rate can predict the thermal expansion, thermal stress, etc. of the material in advance, providing a scientific basis for the selection and application of materials and ensuring the safety and reliability of engineering structures.

[0094] The temperature change rate refers to the amount of temperature change per unit time, and is used to describe how fast the temperature changes.

[0095] As an embodiment of the present invention, the calculating the temperature change rate corresponding to the temperature change trend includes:

[0096] The temperature change rate corresponding to the temperature change trend is calculated using the following formula:

[0097]

[0098] in, represents the temperature change rate corresponding to the temperature change trend, represents the final temperature, represents the initial temperature, represents the time interval over which the temperature variation trend is measured, represents the correction factor, Indicates the ambient reference temperature, Indicates the average temperature of the temperature change trend within the time period.

[0099] In detail, the final temperature refers to the temperature value measured at the end of a specific time period; the initial temperature refers to the temperature value recorded at the beginning of the specific time period; the time interval refers to the time elapsed from the initial temperature measurement moment to the final temperature measurement moment; the correction coefficient refers to a numerical value used to adjust and correct the calculation results to take into account the influence of other relevant factors on the temperature change rate; the ambient reference temperature refers to the temperature of the surrounding environment used as a reference standard; the average temperature refers to the arithmetic mean of the initial temperature and the final temperature within a specific time period, which is used to reflect the overall temperature level during this period.

[0100] S3. Based on the temperature change rate, analyze the heat transfer process of the communication mold to obtain heat transfer data, monitor the thermal stability corresponding to the heat transfer data, determine the temperature control rating corresponding to the communication mold based on the thermal stability, query the rating points in the temperature control rating, and mark the thermal balance points corresponding to the rating points.

[0101] The present invention analyzes the heat transfer process of the communication mold based on the temperature change rate to obtain heat transfer data, which can help accurately evaluate the thermal performance of the mold during operation. By deeply understanding the heat transfer situation, it can be clarified how heat flows inside the mold and between the mold and the external environment, thereby providing a key basis for optimizing the structural design of the mold.

[0102] The heat transfer data refers to a series of heat transfer related information obtained by analyzing the heat transfer process of the communication mold, including but not limited to temperature distribution, heat flux size, heat flow path direction, thermal resistance, etc.

[0103] As an embodiment of the present invention, the heat transfer process analysis of the communication mold is performed based on the temperature change rate to obtain heat transfer data, including: querying the change value corresponding to the temperature change rate; determining the key measurement points corresponding to the communication mold based on the change value; constructing the temperature change matrix corresponding to the communication mold based on the key measurement points; analyzing the heat flux corresponding to the temperature change matrix; drawing the heat flow path corresponding to the heat flux; and performing the heat transfer process analysis of the communication mold based on the heat flow path to obtain heat transfer data.

[0104] Among them, the change value refers to the specific value of the temperature change rate, that is, the change in temperature per unit time; the key measurement point refers to a specific position in the communication mold that has an important influence on the heat transfer process and can reflect the thermal characteristics of the mold; the temperature change matrix refers to a two-dimensional data table that arranges the temperature change rates of different positions of the communication mold at different times; the heat flux refers to the heat passing through a unit area per unit time; the heat flow path refers to the specific route and direction of heat transfer inside the communication mold.

[0105] Furthermore, the query of the change value corresponding to the temperature change rate can be implemented through a data query tool, such as SQL and other tools; the determination of the key measurement points corresponding to the communication mold can be implemented through a cluster analysis algorithm, such as: (and examples of the methods, tools or algorithms that can be implemented therein are given); the construction of the temperature change matrix corresponding to the communication mold can be implemented through a spreadsheet, such as Excel and other tools; the analysis of the heat flux corresponding to the temperature change matrix can be implemented through a thermal analysis calculation tool, such as COMSOL Multiphysics, importing temperature change matrix data, setting material properties, and the software automatically calculates the heat flux; the drawing of the heat flow path corresponding to the heat flux can be implemented through a drawing tool, such as AutoCAD, Visio and other tools; the analysis of the heat transfer process of the communication mold can be implemented through a heat transfer simulation algorithm, such as the finite difference method and other algorithms.

[0106] The present invention helps to ensure that the molding effect of the mold on the product is consistent during each production process by monitoring the thermal stability corresponding to the heat transfer data. Furthermore, the monitoring of thermal stability provides a strong basis for optimizing the production process, and can accurately adjust production parameters such as heating time, cooling speed, etc. to achieve the best heat transfer effect and improve production efficiency.

[0107] Among them, the thermal stability refers to the ability of the communication mold to maintain its temperature distribution and heat transfer performance relatively stable during the heat transfer process. It reflects the characteristics of the mold to resist temperature fluctuations and maintain a stable working state when affected by changes in the external thermal environment or internal heat generation and dissipation. Optionally, the thermal stability corresponding to the monitoring of the heat transfer data can be achieved through thermal stability monitoring equipment, such as: high-precision thermal sensors and data acquisition systems.

[0108] Furthermore, the present invention determines the temperature control rating corresponding to the communication mold based on the thermal stability, so as to reasonably arrange the production plan, and use molds with good thermal stability and high ratings for high-precision production tasks with strict temperature requirements, while using molds with lower ratings for production links with relatively loose temperature requirements, thereby improving the overall production efficiency and resource utilization efficiency.

[0109] The temperature control rating refers to the grade assessment result indicating the thermal control level of the communication mold, which is ultimately determined based on the thermal stability of the mold.

[0110] As an embodiment of the present invention, determining the temperature control rating corresponding to the communication mold based on the thermal stability includes: determining a thermal stability index corresponding to the thermal stability; collecting thermal stability parameters corresponding to the thermal stability index; performing data classification on the thermal stability parameters to obtain thermal stability classification parameters; querying the temperature control level range corresponding to the thermal stability classification parameters; and determining the temperature control rating corresponding to the communication mold based on the temperature control level range.

[0111] Among them, the thermal stability index refers to the specific characteristics or aspects used to measure the thermal stability of the communication mold, such as temperature fluctuation amplitude, thermal equilibrium time, temperature difference in different parts, etc.; the thermal stability parameter refers to the numerical value obtained by measurement or calculation that can specifically reflect the thermal stability index; the thermal stability classification parameter refers to the different categories of parameters obtained after the collected thermal stability parameters are classified according to certain rules or standards; the temperature control level range refers to the pre-set interval range divided according to different thermal stability levels, and each interval corresponds to a specific temperature control level.

[0112] Furthermore, the determination of the thermal stability index corresponding to the thermal stability can be achieved through a thermal index analysis tool, such as Fluent and other tools; the collection of the thermal stability parameters corresponding to the thermal stability index can be achieved through a high-precision temperature sensor and a data acquisition device; the data classification of the thermal stability parameters can be achieved through a clustering algorithm, such as K-Means and other algorithms; the query of the temperature control level range corresponding to the thermal stability classification parameters can be achieved through a binary search algorithm; the determination of the temperature control rating corresponding to the communication mold can be achieved through a fuzzy reasoning algorithm, such as Mamdani, Sugeno and other algorithms.

[0113] The present invention helps to more accurately grasp the key characteristics of the communication mold in thermal control by querying the rating points in the temperature control rating and marking the thermal balance points corresponding to the rating points. By paying attention to the rating points and thermal balance points, potential thermal problems can be prevented in advance, mold deformation and damage caused by thermal stress can be reduced, and the service life of the mold can be extended.

[0114] Among them, the rating points refer to those important factors or characteristics that have a key influence and can significantly reflect the thermal stability and thermal control effect of the mold in determining the communication mold temperature control rating process; the thermal equilibrium point refers to the position or state where the heat generation and dissipation of various parts inside the mold reach a dynamic balance and the temperature no longer changes significantly during the heat transfer process of the communication mold. Optionally, the query of the rating points in the temperature control rating can be achieved through text analysis tools, such as RapidMiner and other tools; the marking of the thermal equilibrium point corresponding to the rating points can be achieved through hotspot detection equipment, such as thermal imagers and other equipment.

[0115] S4. Based on the thermal equilibrium point, determine the thermal control channel corresponding to the communication mold welding, detect the channel state corresponding to the thermal control channel, calculate the channel heat capacity corresponding to the thermal control channel based on the channel state, optimize the monitoring threshold of the communication mold during the thermal monitoring process based on the channel heat capacity, and calculate the threshold deviation rate corresponding to the monitoring threshold.

[0116] The present invention determines the thermal control channel corresponding to the communication mold welding based on the thermal equilibrium point, and can clarify the key position of heat distribution of the mold during the welding process, so as to design the thermal control channel in a targeted manner, so that heat can be more effectively conducted and dissipated, thereby avoiding welding defects caused by local overheating.

[0117] The heat control channel refers to a conduction path or channel specially designed to control heat transfer and distribution during the communication mold welding process. It can be a specific structure inside the mold, such as holes, grooves, pipes, exhaust grooves, etc., or a heat sink or thermal conductive coating added to the mold surface. Its function is to effectively guide the flow of heat to achieve the purpose of optimizing the temperature control during the welding process. For further information, please refer to Figure 2 As shown, it is a schematic diagram of the structure of the exhaust groove in this embodiment. Optionally, the determination of the thermal control channel corresponding to the welding of the communication mold can be achieved by thermal analysis calculation tools, such as: COMSOL and other tools.

[0118] Furthermore, by detecting the channel state corresponding to the thermal control channel, the present invention can promptly discover whether the channel has problems such as blockage, damage or deformation, ensuring that the thermal control channel always maintains a good working state, thereby ensuring the heat transfer efficiency and temperature control effect during the communication mold welding process.

[0119] Among them, the channel state refers to the performance of various performance and physical characteristics of the thermal control channel during the working process, including but not limited to the degree of channel smoothness, wear of the inner wall, presence of foreign matter obstruction, changes in heat transfer efficiency, uniformity of temperature distribution, and integrity of the channel structure. Optionally, the detection of the channel state corresponding to the thermal control channel can be achieved through the Fluent tool, such as: establishing a model of the thermal control channel in Fluent, setting boundary conditions and fluid properties, analyzing the flow field in the channel through the turbulence model algorithm, and judging whether there is abnormal flow, thereby inferring the channel state.

[0120] The present invention calculates the channel heat capacity corresponding to the thermal control channel based on the channel state, and can reasonably control the energy input into the thermal control system. Furthermore, it can timely discover the impact of channel state changes on the heat capacity, and take measures in advance for maintenance or improvement to ensure that the thermal control channel always maintains good thermal performance and ensures the stability and consistency of welding quality.

[0121] The channel heat capacity refers to the ability of the thermal control channel to absorb or release heat within a certain temperature range.

[0122] As an embodiment of the present invention, the calculating the channel heat capacity corresponding to the thermal control channel based on the channel state includes:

[0123] The channel heat capacity corresponding to the thermal control channel is calculated using the following formula:

[0124]

[0125] in, represents the channel heat capacity corresponding to the thermal control channel, Indicates the average density of the fluid in the channel corresponding to the channel state, represents the effective volume corresponding to the thermal control channel, Indicates the average temperature change value in the channel corresponding to the channel state, represents the correction factor of the channel state to the heat capacity, represents the roughness coefficient of the inner wall of the thermal control channel, represents the amplitude coefficient related to the influence of the thermal control channel and the inner wall roughness on the heat capacity, Indicates the obstruction coefficient in the channel corresponding to the channel state, Indicates the influence coefficient related to the heat capacity effect.

[0126] In detail, the average density refers to the average value of the ratio of the mass to the volume of the fluid in the channel; the effective volume refers to the space occupied by the fluid actually participating in the heat transfer in the thermal control channel; the average temperature change value refers to the average value of the temperature change of the fluid in the channel during the operation of the thermal control channel; the correction coefficient refers to the parameter used to adjust and correct the basic calculation results, for example, the correction coefficient of temperature change to heat capacity It is used to consider the additional effect of temperature change on heat capacity, so that the calculation result is more in line with the actual situation; the roughness coefficient refers to the parameter used to describe the roughness of the inner wall surface of the channel. A higher roughness coefficient means that the inner wall is rougher, which will produce greater resistance to heat transfer and fluid flow; the amplitude coefficient refers to a coefficient related to other influencing factors, which indicates the degree of influence on the main parameters, for example, As an amplitude coefficient related to the effect of inner wall roughness on heat capacity, it indicates the strength of the effect of roughness on heat capacity; the obstruction coefficient refers to a parameter that reflects the magnitude of the obstruction of a certain factor on heat transfer or other processes, for example, the fouling coefficient It indicates the degree of obstruction of heat transfer caused by dirt accumulation in the channel. The larger the value, the stronger the obstruction. The influence coefficient refers to a parameter that reflects the influence of a specific factor on the overall result. For example, As a coefficient related to the effect of fouling on heat capacity, it indicates the specific degree of influence of fouling accumulation on heat capacity.

[0127] Furthermore, the present invention optimizes the monitoring threshold of the communication mold during the thermal monitoring process based on the channel heat capacity, which helps to improve welding identification efficiency and product quality, enables timely adjustments and interventions during the thermal monitoring process, reduces welding interruptions and product defects caused by thermal problems, and thus ensures the continuity of the welding process and the consistency of the product.

[0128] The monitoring threshold refers to a critical value or boundary value set during the thermal monitoring process for determining whether the thermal state of the communication mold is normal. Optionally, the optimization of the monitoring threshold of the communication mold during the thermal monitoring process can be implemented through the Scikit-learn library of Python, such as: using the Scikit-learn library in Python, taking relevant factors such as channel heat capacity as input features, and the monitoring threshold as the output target, establishing a model through a linear or nonlinear regression algorithm, and predicting the optimized threshold.

[0129] Furthermore, by calculating the threshold deviation rate corresponding to the monitoring threshold, the present invention can clearly understand the degree of difference between the actual monitoring results and the set threshold, provide a strong basis for adjusting and optimizing the monitoring threshold, and correct and improve the monitoring threshold to make it better adapt to the thermal change characteristics of the communication mold and improve the reliability and effectiveness of thermal monitoring.

[0130] The threshold deviation rate refers to the degree of deviation between the actual measured temperature and the set temperature in the monitoring system, and is usually expressed in percentage.

[0131] As an embodiment of the present invention, the calculating the threshold deviation rate corresponding to the monitoring threshold includes:

[0132] The threshold deviation rate corresponding to the monitoring threshold is calculated using the following formula:

[0133]

[0134] in, represents the threshold deviation rate corresponding to the monitoring threshold, represents the index of the monitoring point corresponding to the monitoring threshold, Indicates the total number of monitoring points corresponding to the monitoring threshold, Indicates The set temperature of each monitoring point, Indicates The actual measured temperature of each monitoring point, Indicates The weight of each monitoring point, Indicates the highest temperature set among all monitoring points. Indicates the lowest temperature set among all monitoring points.

[0135] In detail, the monitoring point refers to a specific location or area set in the thermal control system for real-time monitoring of temperature changes; the set temperature refers to the target temperature value pre-set for each monitoring point in the monitoring system; the actual measured temperature refers to the temperature value measured in real time by the monitoring system at each monitoring point.

[0136] S5. Based on the threshold deviation rate, an abnormal welding instruction corresponding to the communication mold welding is generated, welding parameters corresponding to the abnormal welding instruction are queried, welding factors corresponding to the welding parameters are identified, and based on the welding factors, an abnormal monitoring list corresponding to the communication mold welding is generated.

[0137] The present invention generates abnormal welding instructions corresponding to the communication mold welding based on the threshold deviation rate, can timely discover and handle situations where deviations from the expected threshold exist, and can effectively eliminate potential welding defects, ensuring that each welding point meets quality standards and improving the overall reliability of the product.

[0138] Among them, the abnormal welding instruction refers to an instruction generated during the communication mold welding process due to the monitoring threshold deviation rate exceeding the normal range, which is used to instruct specific actions such as adjusting, correcting or pausing the welding operation. Optionally, the generation of the abnormal welding instruction corresponding to the communication mold welding can be implemented through Python's TensorFlow framework. For example, by using the TensorFlow framework, the threshold deviation rate and related welding parameters are used as input features, and different types of abnormal welding instructions are used as classification labels. By training a support vector machine or a decision tree model, the corresponding abnormal welding instructions are automatically generated according to the new input data.

[0139] Furthermore, the present invention queries the welding parameters corresponding to the abnormal welding instructions and identifies the welding factors corresponding to the welding parameters, so as to accurately locate which one or several factors such as current, voltage, welding speed, etc. are abnormal, thereby providing a clear direction for subsequent problem solving.

[0140] Wherein, the welding parameters refer to specific values ​​or settings used to describe the characteristics and conditions of the welding operation during the communication mold welding process, such as welding current, voltage, welding speed, welding time, wire diameter, shielding gas flow rate, etc.; the welding factors refer to key factors that have a significant impact on welding quality, effect and performance. These factors may originate from changes in welding parameters, characteristics of welding materials, welding environmental conditions, etc., such as the influence factor of current size on weld penetration, the influence factor of voltage on weld width, etc. Optionally, the query of the welding parameters corresponding to the abnormal welding instruction can be implemented by a MySQL tool, such as: establishing a welding parameter database in MySQL, storing the associated data of abnormal welding instructions and corresponding welding parameters, and using SQL query statements, such as "SELECT welding parameters FROM table name WHERE abnormal welding instructions = 'specific instructions'", to obtain the welding parameters corresponding to the specific abnormal welding instructions; the identification of the welding factors corresponding to the welding parameters can be implemented by an R language tool, such as: in the R language, taking the welding parameters as independent variables, the welding quality or performance indicators as dependent variables, and using regression algorithm analysis to determine the degree of influence of each welding parameter on the welding quality, thereby identifying the welding factors.

[0141] Furthermore, the present invention generates an abnormal monitoring list corresponding to the communication mold welding based on the welding factor, which can provide comprehensive and detailed abnormal information and serve as an important basis to trace the root cause of the problem and related responsible links to strengthen quality control. In addition, the analysis and summary of the abnormal monitoring list can provide a reference for similar welding projects in the future, avoid the recurrence of the same problems, and improve the stability and reliability of production.

[0142] Among them, the abnormal monitoring details list refers to a list of detailed records of abnormal welding conditions generated during the communication mold welding process based on the analysis and evaluation of welding factors. This list usually contains rich and comprehensive information such as the time when the abnormality occurred, the abnormal value or state of the specific welding factor, the consequences that may be caused, the corresponding abnormal welding instructions, and the recommended treatment measures. Optionally, the generation of the abnormal monitoring details list corresponding to the communication mold welding can be achieved through the FineReport tool, such as: connecting to the database in FineReport to obtain welding factor data, setting the report format and data processing rules, and using its built-in algorithm to summarize and classify the data to generate an abnormal monitoring details list.

[0143] Firstly, by acquiring the welding temperature data of the communication mold during the welding process, the present invention can timely discover the area with abnormal temperature, give early warning of possible welding defects, effectively avoid subsequent quality problems, and achieve the best welding effect. At the same time, the present invention obtains a gradient change curve by curve fitting the temperature change gradient in the abnormal temperature area, which helps to accurately judge the nature and severity of the abnormality, such as whether the abnormality is caused by local heat accumulation or poor heat dissipation. Secondly, it provides a key basis for optimizing the welding process to improve temperature distribution and reduce the occurrence of abnormal situations. Based on the temperature change rate, the present invention analyzes the heat transfer process of the communication mold to obtain heat transfer data, which can help accurately evaluate the thermal performance of the mold during the working process. And by deeply understanding the heat transfer situation, it can be clear how the heat flows between the inside of the mold and the external environment, thereby providing a key basis for optimizing the structural design of the mold. The present invention determines the thermal control channel corresponding to the communication mold welding based on the thermal equilibrium point, and can clarify the key position of the heat distribution of the mold during the welding process, so as to design the thermal control channel in a targeted manner, so that the heat can be more effectively conducted and dissipated, and avoid welding defects caused by local overheating. Furthermore, the present invention generates abnormal welding instructions corresponding to the communication mold welding based on the threshold deviation rate, which can timely discover and handle situations where there are deviations from the expected threshold, and can effectively eliminate potential welding defects, ensuring that each welding point meets the quality standards and improving the overall reliability of the product. Therefore, the intelligent identification method and system for abnormal points applied to communication mold welding proposed by the present invention can improve the effect of abnormal point identification under communication mold welding.

[0144] like Figure 3 , which is a functional module diagram of an abnormal point intelligent identification system applied to communication mold welding provided by an embodiment of the present invention.

[0145] The abnormal point intelligent identification system 200 applied to communication mold welding of the present invention can be installed in an electronic device. According to the functions implemented, the abnormal point intelligent identification system 200 applied to communication mold welding may include an area detection module 201, a change rate calculation module 202, a balance point marking module 203, a deviation rate calculation module 2044 and a detailed list generation module 205. The module of the present invention can also be called a unit, which refers to a series of computer program segments that can be executed by an electronic device processor and can complete fixed functions, which are stored in the memory of the electronic device.

[0146] In this embodiment, the functions of each module / unit are as follows:

[0147] The area detection module 201 is used to obtain the welding temperature data of the communication mold during the welding process, collect the hot spot distribution information in the welding temperature data, query the temperature sequence corresponding to the hot spot distribution information, extract the temperature peak point in the temperature sequence, and detect the abnormal temperature area corresponding to the temperature peak point;

[0148] A change rate calculation module 202 is used to perform curve fitting on the temperature change gradient in the abnormal temperature region to obtain a gradient change curve, identify the temperature change trend in the gradient change curve, and calculate the temperature change rate corresponding to the temperature change trend;

[0149] The balance point marking module 203 is used to analyze the heat transfer process of the communication mold based on the temperature change rate, obtain heat transfer data, monitor the thermal stability corresponding to the heat transfer data, determine the temperature control rating corresponding to the communication mold based on the thermal stability, query the rating points in the temperature control rating, and mark the thermal balance point corresponding to the rating point;

[0150] The deviation rate calculation module 204 is used to determine the thermal control channel corresponding to the welding of the communication mold based on the thermal equilibrium point, detect the channel state corresponding to the thermal control channel, calculate the channel heat capacity corresponding to the thermal control channel based on the channel state, optimize the monitoring threshold of the communication mold in the thermal monitoring process based on the channel heat capacity, and calculate the threshold deviation rate corresponding to the monitoring threshold;

[0151] The detailed list generation module 205 is used to generate an abnormal welding instruction corresponding to the communication mold welding based on the threshold deviation rate, query the welding parameters corresponding to the abnormal welding instructions, identify the welding factors corresponding to the welding parameters, and generate an abnormal monitoring detailed list corresponding to the communication mold welding based on the welding factors.

[0152] In detail, the modules described in the abnormal point intelligent identification system 200 applied to communication mold welding described in the embodiment of the present invention adopt the same technical means as the abnormal point intelligent identification method applied to communication mold welding described in the accompanying drawings when in use, and can produce the same technical effects, which will not be repeated here.

[0153] The above description is only a specific embodiment of the present invention, so that those skilled in the art can understand or implement the present invention. Various modifications to these embodiments will be apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the present invention. Therefore, the present invention will not be limited to the embodiments shown herein, but should conform to the widest scope consistent with the principles and novel features invented herein.

Claims

1. The method for intelligently identifying abnormal points in communication mold welding is characterized by: The method comprises: Acquire welding temperature data of the communication mold during the welding process, collect hot spot distribution information in the welding temperature data, query the temperature sequence corresponding to the hot spot distribution information, extract the temperature peak point in the temperature sequence, and detect the abnormal temperature area corresponding to the temperature peak point; Performing curve fitting on the temperature change gradient in the abnormal temperature region to obtain a gradient change curve, identifying the temperature change trend in the gradient change curve, and calculating the temperature change rate corresponding to the temperature change trend; Based on the temperature change rate, a heat transfer process analysis is performed on the communication mold to obtain heat transfer data, and the thermal stability corresponding to the heat transfer data is monitored. Based on the thermal stability, a temperature control rating corresponding to the communication mold is determined, and a rating point in the temperature control rating is queried, and a thermal balance point corresponding to the rating point is marked; Based on the thermal equilibrium point, determine the thermal control channel corresponding to the welding of the communication mold, detect the channel state corresponding to the thermal control channel, calculate the channel heat capacity corresponding to the thermal control channel based on the channel state, optimize the monitoring threshold of the communication mold in the thermal monitoring process based on the channel heat capacity, and calculate the threshold deviation rate corresponding to the monitoring threshold; Based on the threshold deviation rate, an abnormal welding instruction corresponding to the communication mold welding is generated, the welding parameters corresponding to the abnormal welding instruction are queried, the welding factors corresponding to the welding parameters are identified, and based on the welding factors, an abnormal monitoring list corresponding to the communication mold welding is generated.

2. The method for intelligently identifying abnormal points in communication mold welding according to claim 1, characterized in that: The collecting of hotspot distribution information in the welding temperature data includes: Performing data preprocessing on the welding temperature data to obtain preprocessed temperature data; Based on the pretreatment temperature data, construct a temperature field corresponding to the welding temperature data; Setting a temperature threshold corresponding to the temperature field; Based on the temperature threshold, determining a hot spot area corresponding to the welding temperature data; The hotspot distribution information in the hotspot area is collected.

3. The method for intelligently identifying abnormal points in communication mold welding according to claim 1, characterized in that: The detecting the abnormal temperature area corresponding to the temperature peak point includes: Taking the temperature peak point as the center, determining the corresponding temperature measurement area; Querying the area range corresponding to the temperature measurement area, and collecting detailed temperature data within the area range; Smoothing the detailed temperature data to obtain smoothed temperature data; Comparing the temperature difference between the smoothed temperature data and a preset temperature deviation threshold to obtain temperature deviation data; Identify abnormal temperature points in the temperature deviation data; and query abnormal temperature areas corresponding to the abnormal temperature points.

4. The method for intelligently identifying abnormal points in communication mold welding according to claim 1, characterized in that: The performing curve fitting on the temperature change gradient in the abnormal temperature region to obtain a gradient change curve comprises: Dividing the abnormal temperature area into a plurality of spatial grids; Calculating the temperature difference between the spatial grids; Arrange the temperature difference values ​​in order according to their numerical values ​​to obtain a temperature difference sequence; Analyzing the temperature change gradient corresponding to the temperature difference sequence; The temperature change gradient is subjected to curve fitting to obtain a gradient change curve.

5. The method for intelligently identifying abnormal points in communication mold welding according to claim 1, characterized in that: The calculating the temperature change rate corresponding to the temperature change trend includes: The temperature change rate corresponding to the temperature change trend is calculated using the following formula: in, represents the temperature change rate corresponding to the temperature change trend, represents the final temperature, represents the initial temperature, represents the time interval over which the temperature variation trend is measured, represents the correction factor, Indicates the ambient reference temperature, Indicates the average temperature of the temperature change trend within the time period.

6. The method for intelligently identifying abnormal points in communication mold welding according to claim 1, characterized in that: The heat transfer process analysis of the communication mold based on the temperature change rate to obtain heat transfer data includes: Query the change value corresponding to the temperature change rate; Based on the changed value, determining the key measurement point corresponding to the communication mold; Based on the key measurement points, construct a temperature change matrix corresponding to the communication mold; Analyzing the heat flux corresponding to the temperature change matrix, and drawing a heat flow path corresponding to the heat flux; Based on the heat flow path, a heat transfer process analysis is performed on the communication mold to obtain heat transfer data.

7. The method for intelligently identifying abnormal points in communication mold welding according to claim 1, characterized in that: Determining the temperature control rating corresponding to the communication mold based on the thermal stability includes: Determining a thermal stability index corresponding to the thermal stability, and collecting a thermal stability parameter corresponding to the thermal stability index; Performing data classification on the thermal stability parameters to obtain thermal stability classification parameters; Query the temperature control level range corresponding to the thermal stability classification parameter; Based on the temperature control level range, a temperature control rating corresponding to the communication mold is determined.

8. The method for intelligently identifying abnormal points in communication mold welding according to claim 1, characterized in that: The calculating, based on the channel state, the channel heat capacity corresponding to the thermal control channel comprises: The channel heat capacity corresponding to the thermal control channel is calculated using the following formula: in, represents the channel heat capacity corresponding to the thermal control channel, Indicates the average density of the fluid in the channel corresponding to the channel state, represents the effective volume corresponding to the thermal control channel, Indicates the average temperature change value in the channel corresponding to the channel state, represents the correction factor of the channel state to the heat capacity, represents the roughness coefficient of the inner wall of the thermal control channel, represents the amplitude coefficient related to the influence of the thermal control channel and the inner wall roughness on the heat capacity, Indicates the obstruction coefficient in the channel corresponding to the channel state, Indicates the influence coefficient related to the heat capacity effect.

9. The method for intelligently identifying abnormal points in communication mold welding according to claim 1, characterized in that: The calculating the threshold deviation rate corresponding to the monitoring threshold includes: The threshold deviation rate corresponding to the monitoring threshold is calculated using the following formula: in, represents the threshold deviation rate corresponding to the monitoring threshold, represents the index of the monitoring point corresponding to the monitoring threshold, Indicates the total number of monitoring points corresponding to the monitoring threshold, Indicates The set temperature of each monitoring point, Indicates The actual measured temperature of each monitoring point, Indicates The weight of each monitoring point, Indicates the highest temperature set among all monitoring points. Indicates the lowest temperature set among all monitoring points.

10. The abnormal point intelligent identification system applied to communication mold welding is characterized by: The system is used to execute the method for intelligently identifying abnormal points in communication mold welding according to any one of claims 1 to 9, and the system comprises: An area detection module is used to obtain welding temperature data of the communication mold during the welding process, collect hot spot distribution information in the welding temperature data, query the temperature sequence corresponding to the hot spot distribution information, extract the temperature peak point in the temperature sequence, and detect the abnormal temperature area corresponding to the temperature peak point; a change rate calculation module, used for performing curve fitting on the temperature change gradient in the abnormal temperature region to obtain a gradient change curve, identifying the temperature change trend in the gradient change curve, and calculating the temperature change rate corresponding to the temperature change trend; A balance point marking module is used to analyze the heat transfer process of the communication mold based on the temperature change rate, obtain heat transfer data, monitor the thermal stability corresponding to the heat transfer data, determine the temperature control rating corresponding to the communication mold based on the thermal stability, query the rating points in the temperature control rating, and mark the thermal balance point corresponding to the rating point; a deviation rate calculation module, used for determining the thermal control channel corresponding to the welding of the communication mold based on the thermal equilibrium point, detecting the channel state corresponding to the thermal control channel, calculating the channel heat capacity corresponding to the thermal control channel based on the channel state, optimizing the monitoring threshold of the communication mold in the thermal monitoring process based on the channel heat capacity, and calculating the threshold deviation rate corresponding to the monitoring threshold; The detailed list generation module is used to generate an abnormal welding instruction corresponding to the communication mold welding based on the threshold deviation rate, query the welding parameters corresponding to the abnormal welding instructions, identify the welding factors corresponding to the welding parameters, and generate an abnormal monitoring detailed list corresponding to the communication mold welding based on the welding factors.

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