Quality detection method, device and equipment for welding seam of automobile exhaust pipeline

Abstract

The invention discloses a quality detection method, device and equipment for automobile exhaust pipeline weld joints, and relates to the field of weld joint detection. The method is applied to a welding seam quality analysis system, and comprises the following steps: heating a welding seam of an automobile exhaust pipeline, stopping heating when the welding seam reaches a specified temperature, and then monitoring a welding seam temperature change distribution diagram of the welding seam in a cooling process; the cooling process of a defect area is different from the cooling process of a normal welding seam. According to the method, the welding seam area is divided into the multiple welding seam units, then the similarity value of the temperature change curve of each welding seam unit and the temperature change curve of the normal welding seam is calculated one by one, and the welding seam defect type of the welding seam unit with the low similarity value is recognized, so that the defect type of the defective welding seam is determined. According to the method, deep defects of the weld defect area can be found, the accuracy of weld quality detection is improved, the method can be used for quality detection of the weld penetration depth, and the method has a wider application range.

Description

Technical Field

[0001] The present application relates to the technical field of weld detection, and in particular to a method, device and equipment for quality detection of welds of automobile exhaust pipes. Background Art

[0002] In order to adapt to the installation size of the vehicle, the shape of the automobile exhaust pipe is often irregular, which makes it difficult to form the automobile exhaust pipe in one go; currently, in order to process such an irregular pipe, generally multiple components of the pipe are produced first, and then the multiple components are welded to obtain a complete automobile exhaust pipe. In this context, the quality inspection of the weld is particularly important. At present, when inspecting the weld quality of automobile exhaust pipes, visual inspection technology is usually used. It takes pictures of the weld images, and then uses the weld inspection model to identify and classify the weld images, so as to obtain the defective parts of the welds.

[0003] However, visual inspection technology not only has high requirements for image clarity, but also has difficulty in detecting deep defects in welds, resulting in inaccurate quality inspection of automobile exhaust pipe welds. Summary of the invention

[0004] In order to solve the problem of inaccurate quality inspection of automobile exhaust pipe welds due to the difficulty of visual inspection technology in detecting deep weld defects, the present application provides a method, device and equipment for quality inspection of automobile exhaust pipe welds.

[0005] In a first aspect, the present application provides a quality detection method for a weld of an automobile exhaust pipe, which is applied to a weld quality analysis system, and the method comprises: Controlling the heating module to heat the weld to be detected, stopping heating when the weld to be detected reaches the target temperature, monitoring the temperature of the weld to be detected, and obtaining a weld temperature change distribution diagram of the weld to be detected; Extracting temperature variation curves of a plurality of weld seam units from the weld seam temperature variation distribution diagram; Calculating the similarity between the temperature variation curves of the plurality of weld seam units and the temperature variation curve of a preset weld seam unit; Calculating the similarity between the temperature variation curves of the first weld unit and the preset weld unit, and determining whether the first weld unit is an abnormal weld unit, the first weld unit being any one of the plurality of weld units; If the first weld unit is the abnormal weld unit, a characteristic analysis is performed on the temperature change curve of the abnormal weld unit to obtain the weld type of the abnormal weld unit, and the weld type includes weld nodule, weld penetration, porosity, undercut, poor forming and slag inclusion.

[0006] Optionally, the controlling and heating module heats the weld to be inspected, and before the heating is stopped after the weld to be inspected reaches a target temperature, further comprising: Obtaining the welding material type of the weld to be inspected; Matching the welding material type with a preset phase change temperature database to obtain the phase change temperature of the welding material; The phase change temperature is set as the target temperature.

[0007] Optionally, an initial thermal value distribution diagram of the weld temperature change distribution diagram is extracted, wherein the initial thermal value distribution diagram is composed of a plurality of thermal points, wherein one thermal point corresponds to one thermal value; Cluster analysis is performed on the thermal values ​​of the plurality of thermal points to determine the plurality of weld units.

[0008] Optionally, the cluster analysis of the thermal values ​​of the plurality of thermal points to determine the plurality of weld units specifically further includes: Based on the preset domain radius and the minimum number of points, traverse the thermal values ​​of multiple thermal points to obtain multiple core points; Calculating the associated distances between the plurality of core points, wherein the associated distances include numerical distances and size distances; If the association distance between the first core point and the second core point meets the preset association distance threshold, it is determined that the first core point and the second core point belong to the same weld unit, and the first core point and the second core point are any two different core points among the multiple core points.

[0009] Optionally, obtaining the thermal point density of the initial thermal value distribution map; According to the density of the thermal points, the field radius and the minimum number of points of the plurality of thermal points are preset; Traversing multiple adjacent thermal points of a thermal point to be analyzed, wherein the thermal point to be analyzed is any one of the multiple thermal points; If the thermal values ​​of a plurality of adjacent thermal points exist within the range of the thermal point to be analyzed, and the number of adjacent thermal points is greater than or equal to the minimum number of points, the thermal point to be analyzed is determined to be a core point.

[0010] Optionally, performing cluster analysis on the thermal values ​​of the plurality of thermal points to determine the plurality of weld units specifically further includes: Dividing the plurality of thermal points into a plurality of weld regions of equal area; Calculating the variance within a plurality of said equal-area weld regions; If the variance in the first weld region is greater than or equal to a preset variance threshold, performing variance adjustment on the first weld region to obtain a plurality of abnormal thermal points, wherein the first weld region is any one of the plurality of weld regions of equal area; Eliminating the plurality of abnormal thermal points from the first weld region to obtain a second weld region; The second weld area is used as the weld unit.

[0011] Optionally, obtaining thermal properties of welding materials of the weld to be inspected; Based on the thermal properties of the welding material and the temperature change curve of the abnormal weld unit, constructing a section model of the abnormal weld unit; Feature recognition is performed on the section model to obtain the weld type of the abnormal weld unit.

[0012] In a second aspect, the present application provides a quality detection device for a weld of an automobile exhaust pipe, wherein the device is a weld quality analysis system, and the weld quality analysis system includes an input module, a processing module, and an output module, wherein: The input module is used to control the heating module to heat the weld to be detected, stop heating when the weld to be detected reaches the target temperature, monitor the temperature of the weld to be detected, and obtain a weld temperature change distribution diagram of the weld to be detected; The processing module is used to extract temperature change curves of multiple weld units from the weld temperature change distribution diagram; perform similarity calculation on the temperature change curves of the multiple weld units and the temperature change curve of a preset weld unit; calculate the similarity between the temperature change curves of a first weld unit and the preset weld unit, and determine whether the first weld unit is an abnormal weld unit, the first weld unit being any one of the multiple weld units; The output module is used to perform characteristic analysis on the temperature change curve of the abnormal weld unit if the first weld unit is the abnormal weld unit, so as to obtain the weld type of the abnormal weld unit, wherein the weld type includes weld nodule, weld penetration, porosity, undercut, poor forming and slag inclusion.

[0013] In a third aspect, the present application provides an electronic device comprising a processor, a memory, a user interface and a network interface, wherein the memory is used to store instructions, the user interface and the network interface are used to communicate with other devices, and the processor is used to execute the instructions stored in the memory so that the electronic device executes a method as described in any one of the first aspects.

[0014] In a fourth aspect, the present application provides a computer-readable storage medium, wherein the computer-readable storage medium stores instructions, and when the instructions are executed, the method as described in any one of the first aspects is executed.

[0015] In summary, one or more technical solutions provided in the embodiments of the present application have at least the following technical effects or advantages: 1. By heating the weld of the automobile exhaust pipe, stopping the heating when the weld reaches the specified temperature, and then monitoring the weld temperature change distribution diagram during the cooling process, it can be understood that for the defective area in the weld, since its shape is different from the shape of the normal weld, the cooling process of these defective areas is somewhat different from the cooling process of the normal weld. Based on this, the present application divides the weld area into multiple weld units, and then calculates the similarity value of the temperature change curve of each weld unit with the temperature change curve of the normal weld one by one. For the weld units with lower similarity values, the weld defect type is identified to determine the defect type of the defective weld. This process can not only discover the deep defects in the weld defect area and improve the accuracy of weld quality detection based on the temperature change of the defect area, but also can be used for quality detection of the weld penetration depth, and has a wider range of applicable scenarios.

[0016] 2. When dividing the weld units, in order to increase the proportion of the same welding structure in each weld unit, this application performs cluster analysis on the weld area, clusters the defective area in one weld unit, and clusters the non-defective area in one weld unit, thereby improving the subsequent recognition accuracy of weld defects. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] Figure 1 It is a flow chart of a quality inspection method for a weld of an automobile exhaust pipe provided in an embodiment of the present application.

[0018] Figure 2 A partial diagram of an initial thermal value distribution diagram provided in an embodiment of the present application.

[0019] Figure 3 It is a structural schematic diagram of a quality inspection device for an automobile exhaust pipe weld provided in an embodiment of the present application.

[0020] Figure 4 It is a structural schematic diagram of an electronic device provided in an embodiment of the present application.

[0021] Explanation of the reference numerals: 1. Input module; 2. Processing module; 3. Output module; 400. Electronic device; 401. Processor; 402. Communication bus; 403. User interface; 404. Network interface; 405. Memory. DETAILED DESCRIPTION

[0022] In order to enable technicians in this field to better understand the technical solutions in this specification, the technical solutions in the embodiments of this specification will be clearly and completely described below in conjunction with the drawings in the embodiments of this specification. Obviously, the described embodiments are only part of the embodiments of this application, not all of the embodiments.

[0023] In the description of the embodiments of the present application, words such as "for example" or "for example" are used to indicate examples, illustrations or explanations. Any embodiment or design described as "for example" or "for example" in the embodiments of the present application should not be interpreted as being more preferred or more advantageous than other embodiments or designs. Specifically, the use of words such as "for example" or "for example" is intended to present related concepts in a specific way.

[0024] In the description of the embodiments of the present application, the meaning of the term "multiple" refers to two or more. For example, multiple systems refer to two or more systems, and multiple screen terminals refer to two or more screen terminals. In addition, the terms "first" and "second" are used for descriptive purposes only and cannot be understood as indicating or implying relative importance or implicitly indicating the indicated technical features. Thus, the features defined as "first" and "second" may explicitly or implicitly include one or more of the features. The terms "include", "comprise", "have" and their variations all mean "including but not limited to", unless otherwise specifically emphasized.

[0025] The production of automobile exhaust pipes generally includes mold forming and welding forming. For some irregular automobile exhaust pipes, the mold design is difficult and damaged, which greatly increases the cost. Therefore, most manufacturers use welding forming, and the quality inspection of the weld is particularly important during welding forming.

[0026] At present, the most commonly used method for weld inspection technology is to use visual inspection technology, which takes weld images, identifies the edge features of the welds from the weld images, and then inputs the edge features into the weld inspection model for identification and classification, thereby obtaining the weld defect type. However, visual inspection technology not only has high requirements for image clarity, but also has difficulty in detecting deep defects in welds, resulting in inaccurate quality inspection of automobile exhaust pipe welds.

[0027] In order to solve the above problems, the present application provides a method for detecting the quality of automobile exhaust pipe welds, which is applied to a weld quality analysis system, such as Figure 1 As shown, the method includes steps S101 to S105, which are as follows: S101, controlling the heating module to heat the weld to be detected, stopping the heating when the weld to be detected reaches the target temperature, monitoring the temperature of the weld, and obtaining a weld temperature change distribution diagram of the weld to be detected.

[0028] In the above steps, the weld quality analysis system controls the heating module to heat the weld to be tested until the weld temperature of the weld to be tested reaches the target temperature, and then stops heating. At this time, the temperature detection module starts to monitor the temperature of the weld area until the temperature of the weld to be tested drops to room temperature, and generates a weld temperature change distribution diagram.

[0029] In the process of heating the weld, in order to avoid damage to the weld, before heating, the phase change temperature of the weld to be tested should be queried from the preset phase change temperature database according to the type of welding material of the weld to be tested. The phase change temperature can be understood as the temperature at which the internal structure of the material changes during the heating or cooling process; then the phase change temperature of the weld to be tested is used as the target temperature to avoid structural damage to the weld to be tested. In addition, since the phase change temperature of some welding materials is higher than the phase change temperature of the welded parts (automobile exhaust pipes), in order to avoid the target temperature causing damage to the welded parts, the target temperature should also be lower than the phase change temperature of the welding material.

[0030] S102, extracting temperature variation curves of multiple weld units from the weld temperature variation distribution diagram.

[0031] In the above steps, the weld temperature change distribution diagram is a dynamic temperature change model, which characterizes the overall dynamic change of the temperature distribution of the weld to be tested over time. The defective area of ​​the weld is more obvious in the weld temperature change distribution diagram because its size structure is different from that of a normal weld. For example, a common welding defect: a weld nodule, its size structure is compared with that of a normal weld, and it appears as a nodule on the weld surface. When heated, the weld nodule will gather more heat, which will make the subsequent heat dissipation time longer than that of a normal weld. Based on this feature, the present application divides the weld temperature change distribution diagram into multiple weld units, and then extracts the temperature change curve of each weld unit to facilitate the subsequent analysis of the defect type of the weld.

[0032] In one possible implementation, the weld unit represents a weld area, which includes both normal weld areas and defective weld areas. The present application considers the average distribution of the entire weld unit when extracting the temperature change curve of the weld unit. Therefore, if the normal weld area in the weld unit is much larger than the defective weld area, the defective weld area will be covered up, thereby reducing the accuracy of weld detection. In order to solve this problem, the present application uses cluster analysis when dividing the welding units to extract the initial thermal value distribution map of the weld temperature change distribution map. The initial thermal value distribution map includes the distribution of thermal points in the entire weld area, and each thermal point corresponds to a thermal value; then cluster analysis is performed on multiple thermal points in the initial thermal value distribution map to increase the proportion of principal components in each weld unit, thereby reducing the impact of secondary component data on the principal component data. Specifically: In one embodiment, firstly, based on the preset domain radius and the minimum number of points, the thermal values ​​of multiple thermal points are traversed to obtain multiple core points; specifically: first, the thermal point density of the initial thermal value distribution map is obtained; then, based on the thermal point density, the domain radius and the minimum number of points of multiple thermal points are preset. It should be noted that the thermal density is determined by the system analysis capability, and the specific setting standard is determined according to the actual situation, which is not limited in this application; finally, multiple adjacent thermal points corresponding to each of the multiple thermal points are traversed. If the thermal values ​​of multiple adjacent thermal points of a certain thermal point exist within the domain of the thermal point, and the number of adjacent thermal points is greater than or equal to the minimum number of points, then the thermal point is determined to be a core point. For example, if Figure 2 As shown, Figure 2 A local map of an initial thermal value distribution map provided in an embodiment of the present application, with a preset domain radius of 1 and a minimum number of points of 6. Area A represents a thermal point, and area B represents another thermal point. The thermal value of point A is 60, and the thermal value of point B is 62. At this time, the domain of point A is [59, 61], and the domain of point B is [61, 63]. It can be seen from the figure that among the 8 thermal points adjacent to point A, the domain radius that satisfies point A includes [60.5, 60.4, 60.5, 60.7, 61, 59.9, 60], and the domain radius that satisfies point B includes [61.4, 61.6, 61.5, 61]. Through statistics, it is obtained that the number of points at point A is 7, and the number of points at point B is 4. At this time, if the number of points at point A is greater than the minimum number of points 6, then point A is a core point, and if the number of points at point B is less than the minimum number of points 6, then point B is a non-core point.

[0033] After obtaining multiple core points, since the core points are relatively scattered, the present application integrates the multiple core points by calculating the associated distance between the multiple core points, so as to obtain a complete weld unit, wherein the associated distance includes a numerical distance and a size distance, the numerical distance is the distance between the thermal values ​​of the two core points, and the size distance is the distance between the two core points on the weld to be detected; at this time, by setting a preset associated distance threshold, it is determined whether different core points are suitable for being divided into the same weld unit, specifically, the associated distance is calculated using the following formula:

[0034] in, is the association distance, is the numerical distance, S2 is the size distance, is the association distance, is the numerical distance variance, is the size distance variance.

[0035] In the above formula, It can be regarded as a Gaussian distribution representation of the numerical distance. It can be regarded as a Gaussian distribution representation of the size distance. From the above formula, it can be seen that when the numerical distance remains unchanged and the size distance becomes smaller, the overall correlation degree becomes larger; similarly, when the numerical distance remains unchanged and the size distance becomes larger, the overall correlation degree becomes smaller; but when both are in a changing state, the degree of change of the two is amplified by an exponential function, which is very suitable for the calculation of the correlation distance of multiple thermal points with subtle changes in thermal values.

[0036] When the correlation distance between two thermal points is less than the correlation distance threshold, it is determined that the two thermal points are suitable for being divided into the same weld unit.

[0037] In another embodiment, if the number of core points in the initial thermal value distribution map is too scattered and small, the weld units constructed according to the correlation distances between the core points will be discretely distributed, resulting in the inability to effectively distinguish between normal weld areas and defective weld areas. In view of this situation, the present application proposes another clustering analysis method, specifically: Firstly, the initial thermal value distribution map is divided into a plurality of equal-area weld areas, and the thermal points in each equal-area weld area are connected to each other; then, the variance in the plurality of equal-area weld areas is calculated, that is, the discrete degree of the thermal values ​​of the plurality of thermal points in each equal-area weld area is calculated, and then a preset variance threshold is set, and the variance of each weld area is debugged to obtain a plurality of abnormal thermal points; it should be further explained that, in the process of variance debugging, when the variance of the equal-area weld area is greater than the preset variance threshold, the influence of each thermal point in the equal-area weld area on the variance is tested one by one, and when a thermal point After elimination, if the variance of the equal-area weld area is less than or equal to the preset variance threshold, it means that the eliminated thermal point is an abnormal thermal point. In reality, there is more than one abnormal thermal point in the equal-area weld area. Therefore, when performing variance debugging, the variance debugging of a single thermal point is gradually increased to the variance debugging of multiple thermal points. That is, when all thermal points in the equal-area weld area are debugged one by one, the variance of the equal-area weld area is still greater than the preset variance threshold, then the number of thermal points used for debugging is increased to two, three, four... until the variance of the equal-area weld area is less than or equal to the preset variance threshold. Finally, the weld area with multiple abnormal thermal points eliminated is taken as a weld unit. This process looks at the uniformity of the thermal value in each weld area as a whole, without considering the differences between each thermal point, but only needs to know the influence of each thermal point on the overall weld area, so that the divided weld unit can be better regarded as a whole.

[0038] In a possible implementation, for each weld unit that eliminates multiple abnormal thermal points, if one of the abnormal thermal points is adjacent to another weld unit, the abnormal thermal point can be divided into the adjacent weld unit for variance debugging, thereby improving the data integrity of each weld unit.

[0039] S103, calculating the similarity between the temperature change curves of the plurality of weld seam units and the temperature change curve of a preset weld seam unit.

[0040] S104, calculating the similarity between the temperature change curves of the first weld unit and the preset weld unit, and determining whether the first weld unit is an abnormal weld unit, the first weld unit being any one of the plurality of weld units.

[0041] S105. If the first weld unit is an abnormal weld unit, characteristic analysis is performed on the temperature change curve of the abnormal weld unit to obtain the weld type of the abnormal weld unit, where the weld types include weld bead, weld penetration, porosity, undercut, poor forming and slag inclusion.

[0042] In the above steps S103 to S105, the preset weld unit is a weld unit of a normal weld, and its temperature change curve is obtained based on actual testing. By calculating the similarity between the temperature change curves of multiple weld units of the weld to be detected and the temperature change curve of the preset weld unit, the abnormal weld unit with weld defects among the multiple weld units of the weld to be detected can be determined.

[0043] When performing similarity calculation, it is considered that the temperature change curve of a normal weld unit is only an idealized characteristic curve, and the actual weld unit is affected by the process, material, welding method, etc. Even if the actual weld unit is a normal weld, its temperature change curve is quite different from the idealized characteristic curve. Therefore, when performing similarity calculation, the present application first sets the curve deviation interval of the preset weld unit according to the actual welding process, material, welding method, etc., and then extracts multiple characteristic curves of the actual weld unit according to the actual welding process, material, welding method, etc., and finally extracts the multiple characteristic curves of the weld unit. The degree of overlap between the characteristic curves and the preset weld unit is calculated. If the proportion of the multiple characteristic curves in the curve deviation interval of the preset weld unit is less than the preset proportion, the weld unit is determined to be an abnormal weld unit. It should be further explained that when setting the curve deviation interval of the preset weld unit, a large amount of historical welding data is analyzed and the control variable method is used to calculate the influence coefficient of each weld influencing factor on the weld. Then, according to the multiple influence coefficients, the ideal curve of the preset weld unit is adjusted to generate multiple influence curves. At this time, the closed area between the multiple influence curves is used as the curve deviation interval of the preset weld unit.

[0044] In order to further determine the defect type of the weld defect, the present application performs feature analysis on the temperature change curve of the abnormal weld unit, and converts the temperature change curve of the abnormal weld unit into the structural model of the abnormal weld unit according to the thermal properties of the welding material of the weld to be detected. The principle is that before the temperature of the welding material reaches the phase change temperature, its temperature change shows a linear change law. As its structure changes, the temperature change will also change. Therefore, its structural change can be inferred according to its temperature change. Finally, the structural model of the abnormal weld unit is cut into a section model, and then the section model is feature identified to obtain the defect type of the abnormal weld unit. The scheme of the present application is not only suitable for detecting deep defects of welds, but also for the penetration quality detection of welds. For example, due to the difference in structure between the welding material and the parent material, that is, the phase change temperature is different, when the weld is heated to different stages, the temperature change curve of the weld will show a more obvious change. By analyzing this change trend, the quality of the weld penetration can be detected. Therefore, the scheme of the present application can have good adaptability in the quality detection of most welding processes.

[0045] Reference Figure 3 The present application also provides a quality detection device for automobile exhaust pipe welds, the device is a weld quality analysis system, the weld quality analysis system includes an input module 1, a processing module 2 and an output module 3, wherein: Input module 1 is used to control the heating module to heat the weld to be detected, stop heating when the weld to be detected reaches the target temperature, monitor the temperature of the weld to be detected, and obtain a weld temperature change distribution diagram of the weld to be detected; Processing module 2 is used to extract temperature change curves of multiple weld units from the weld temperature change distribution diagram; perform similarity calculation on the temperature change curves of the multiple weld units and the temperature change curve of the preset weld unit; calculate the similarity between the temperature change curves of the first weld unit and the preset weld unit, and determine whether the first weld unit is an abnormal weld unit, the first weld unit is any one of the multiple weld units; Output module 3 is used to perform characteristic analysis on the temperature change curve of the abnormal weld unit if the first weld unit is an abnormal weld unit, and obtain the weld type of the abnormal weld unit. The weld types include weld nodules, weld penetrations, pores, undercuts, poor forming and slag inclusions.

[0046] In a possible implementation manner, before controlling the heating module to heat the weld to be inspected and stopping the heating after the weld to be inspected reaches the target temperature, the method further includes: Obtain the welding material type of the weld to be inspected; Matching the welding material type with a preset phase change temperature database to obtain the phase change temperature of the welding material; Set the phase change temperature to the target temperature.

[0047] In a possible implementation, an initial thermal value distribution diagram of the weld temperature change distribution diagram is extracted, wherein the initial thermal value distribution diagram is composed of a plurality of thermal points, wherein one thermal point corresponds to one thermal value; Cluster analysis is performed on the thermal values ​​of multiple thermal points to determine multiple weld units.

[0048] In a possible implementation, cluster analysis is performed on the thermal values ​​of multiple thermal points to determine multiple weld units, which specifically includes: Based on the preset field radius and minimum number of points, traverse the thermal values ​​of multiple thermal points to obtain multiple core points; Calculate the correlation distance between multiple core points, the correlation distance includes numerical distance and size distance; If the association distance between the first core point and the second core point meets the preset association distance threshold, it is determined that the first core point and the second core point belong to the same weld unit, and the first core point and the second core point are any two different core points among the multiple core points.

[0049] In a possible implementation, the thermal point density of the initial thermal value distribution diagram is obtained; According to the density of heat points, preset the area radius and minimum number of points of multiple heat points; Traversing multiple adjacent thermal points of the thermal point to be analyzed, where the thermal point to be analyzed is any one of the multiple thermal points; If the thermal values ​​of multiple adjacent thermal points exist within the range of the thermal point to be analyzed, and the number of adjacent thermal points is greater than or equal to the minimum number of points, the thermal point to be analyzed is determined to be a core point.

[0050] In a possible implementation, cluster analysis is performed on the thermal values ​​of multiple thermal points to determine multiple weld units, which specifically includes: Divide multiple thermal points into multiple equal-area weld areas; Calculate the variance within multiple equal-area weld regions; If the variance in the first weld region is greater than or equal to a preset variance threshold, the first weld region is subjected to variance adjustment to obtain a plurality of abnormal thermal points, and the first weld region is any one of a plurality of equal-area weld regions; Eliminating a plurality of abnormal thermal points from the first weld region to obtain a second weld region; The second weld area is treated as a weld element.

[0051] In a possible implementation, thermal properties of welding materials of the weld to be inspected are obtained; Based on the thermal properties of welding materials and the temperature change curve of abnormal weld units, a cross-sectional model of abnormal weld units is constructed; The features of the section model are recognized to obtain the weld type of the abnormal weld unit.

[0052] It should be noted that: when the device provided in the above embodiment realizes its function, only the division of the above functional modules is used as an example. In actual application, the above functions can be assigned to different functional modules as needed, that is, the internal structure of the device is divided into different functional modules to complete all or part of the functions described above. In addition, the device and method embodiments provided in the above embodiment belong to the same concept, and the specific implementation process is detailed in the method embodiment, which will not be repeated here.

[0053] The present application also discloses an electronic device. Figure 4 , Figure 4 The electronic device 400 may include: at least one processor 401 , at least one network interface 404 , a user interface 403 , a memory 405 , and at least one communication bus 402 .

[0054] The communication bus 402 is used to realize the connection and communication between these components.

[0055] The user interface 403 may include a display screen (Display) and a camera (Camera). Optionally, the user interface 403 may also include a standard wired interface and a wireless interface.

[0056] The network interface 404 may optionally include a standard wired interface or a wireless interface (such as a WI-FI interface).

[0057] Among them, the processor 401 may include one or more processing cores. The processor 401 uses various interfaces and lines to connect various parts in the entire server, and executes various functions of the server and processes data by running or executing instructions, programs, code sets or instruction sets stored in the memory 405, and calling data stored in the memory 405. Optionally, the processor 401 can be implemented in at least one hardware form of digital signal processing (Digital Signal Processing, DSP), field programmable gate array (Field-Programmable Gate Array, FPGA), and programmable logic array (Programmable Logic Array, PLA). The processor 401 can integrate one or a combination of a central processing unit (Central Processing Unit, CPU), a graphics processing unit (Graphics Processing Unit, GPU) and a modem. Among them, the CPU mainly processes the operating system, user interface and application programs; the GPU is responsible for rendering and drawing the content to be displayed on the display screen; the modem is used to process wireless communications. It can be understood that the above-mentioned modem may not be integrated into the processor 401, and it can be implemented separately through a chip.

[0058] Among them, the memory 405 may include a random access memory (Random Access Memory, RAM) and may also include a read-only memory (Read-Only Memory). Optionally, the memory 405 includes a non-transitory computer-readable storage medium. The memory 405 can be used to store instructions, programs, codes, code sets or instruction sets. The memory 405 may include a program storage area and a data storage area, wherein the program storage area may store instructions for implementing an operating system, instructions for at least one function (such as a touch function, a sound playback function, an image playback function, etc.), instructions for implementing the above-mentioned various method embodiments, etc.; the data storage area may store data involved in the above-mentioned various method embodiments, etc. The memory 405 may optionally also be at least one storage device located away from the aforementioned processor 401. Refer to Figure 4 The memory 405 as a computer storage medium may include an operating system, a network communication module, a user interface module and an application program of a quality detection method for a weld of an automobile exhaust pipe.

[0059] exist Figure 4 In the electronic device 400 shown, the user interface 403 is mainly used to provide an input interface for the user and obtain the data input by the user; and the processor 401 can be used to call the application program stored in the memory 405 for a quality detection method of the automobile exhaust pipe weld. When executed by one or more processors 501, the electronic device 400 executes one or more of the methods described in the above embodiments. It should be noted that for the aforementioned method embodiments, for the sake of simple description, they are all expressed as a series of action combinations, but those skilled in the art should be aware that the present application is not limited by the described order of actions, because according to the present application, certain steps can be performed in other orders or simultaneously. Secondly, those skilled in the art should also be aware that the embodiments described in the specification are all preferred embodiments, and the actions and modules involved are not necessarily required for the present application.

[0060] In the above embodiments, the description of each embodiment has its own emphasis. For parts that are not described in detail in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

[0061] In the several embodiments provided in this application, it should be understood that the disclosed devices can be implemented in other ways. For example, the device embodiments described above are only schematic, such as the division of units, which is only a logical function division. There may be other division methods in actual implementation, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some service interfaces, and the indirect coupling or communication connection of devices or units can be electrical or other forms.

[0062] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0063] In addition, each functional unit in each embodiment of the present application may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit. The above-mentioned integrated unit may be implemented in the form of hardware or in the form of software functional units.

[0064] If the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable memory. Based on this understanding, the technical solution of the present application, or the part that contributes to the prior art, or all or part of the technical solution can be embodied in the form of a software product, which is stored in a memory and includes several instructions for a computer device (which can be a personal computer, server or network device, etc.) to execute all or part of the steps of the various embodiments of the present application. The aforementioned memory includes: various media that can store program codes, such as USB flash drives, mobile hard drives, magnetic disks or optical disks.

[0065] The above is only an exemplary embodiment of the present disclosure and cannot be used to limit the scope of the present disclosure. That is, any equivalent changes and modifications made according to the teachings of the present disclosure are still within the scope of the present disclosure. After considering the disclosure of the specification and the truth of practice, those skilled in the art will easily think of other embodiments of the present disclosure.

[0066] This application is intended to cover any variation, use or adaptation of the present disclosure, which follows the general principles of the present disclosure and includes common knowledge or customary technical means in the art not described in the present disclosure. The description and examples are to be regarded as exemplary only, and the scope and spirit of the present disclosure are defined by the claims.

Claims

1. A quality inspection method for automobile exhaust pipe welds, characterized in that: Applied to a weld quality analysis system, the method comprises: Controlling the heating module to heat the weld to be detected, stopping heating when the weld to be detected reaches the target temperature, monitoring the temperature of the weld to be detected, and obtaining a weld temperature change distribution diagram of the weld to be detected; Extracting temperature variation curves of a plurality of weld seam units from the weld seam temperature variation distribution diagram; Calculating the similarity between the temperature variation curves of the plurality of weld seam units and the temperature variation curve of a preset weld seam unit; Calculating the similarity between the temperature variation curves of the first weld unit and the preset weld unit, and determining whether the first weld unit is an abnormal weld unit, the first weld unit being any one of the plurality of weld units; If the first weld unit is the abnormal weld unit, a characteristic analysis is performed on the temperature change curve of the abnormal weld unit to obtain the weld type of the abnormal weld unit, and the weld type includes weld nodule, weld penetration, porosity, undercut, poor forming and slag inclusion.

2. The method according to claim 1, characterized in that When the control heating module heats the weld to be inspected, and before the heating is stopped after the weld to be inspected reaches the target temperature, the method further comprises: Obtaining the welding material type of the weld to be inspected; Matching the welding material type with a preset phase change temperature database to obtain the phase change temperature of the welding material; The phase change temperature is set as the target temperature.

3. The method according to claim 1, characterized in that Extracting temperature variation curves of multiple weld seam units from the weld seam temperature variation distribution diagram specifically includes: Extracting an initial thermal value distribution diagram of the weld temperature change distribution diagram, wherein the initial thermal value distribution diagram is composed of a plurality of thermal points, wherein one thermal point corresponds to one thermal value; Cluster analysis is performed on the thermal values ​​of the plurality of thermal points to determine the plurality of weld units.

4. The method according to claim 3, characterized in that The cluster analysis of the thermal values ​​of the plurality of thermal points to determine the plurality of weld units specifically includes: Based on the preset domain radius and the minimum number of points, traverse the thermal values ​​of multiple thermal points to obtain multiple core points; Calculating the associated distances between the plurality of core points, wherein the associated distances include numerical distances and size distances; If the association distance between the first core point and the second core point meets the preset association distance threshold, it is determined that the first core point and the second core point belong to the same weld unit, and the first core point and the second core point are any two different core points among the multiple core points.

5. The method according to claim 4, characterized in that Based on the preset domain radius and the minimum number of points, the thermal values ​​of multiple thermal points are traversed to obtain multiple core points, specifically: Obtaining the thermal point density of the initial thermal value distribution diagram; According to the density of the thermal points, the field radius and the minimum number of points of the plurality of thermal points are preset; Traversing multiple adjacent thermal points of a thermal point to be analyzed, wherein the thermal point to be analyzed is any one of the multiple thermal points; If the thermal values ​​of a plurality of adjacent thermal points exist within the range of the thermal point to be analyzed, and the number of adjacent thermal points is greater than or equal to the minimum number of points, the thermal point to be analyzed is determined to be a core point.

6. The method according to claim 3, characterized in that The cluster analysis of the thermal values ​​of the plurality of thermal points to determine the plurality of weld units specifically includes: Dividing the plurality of thermal points into a plurality of weld regions of equal area; Calculating the variance within a plurality of the equal-area weld regions; If the variance in the first weld region is greater than or equal to a preset variance threshold, performing variance adjustment on the first weld region to obtain a plurality of abnormal thermal points, wherein the first weld region is any one of the plurality of weld regions of equal area; Eliminating the plurality of abnormal thermal points from the first weld region to obtain a second weld region; The second weld area is used as the weld unit.

7. The method according to claim 1, characterized in that The characteristic analysis of the temperature variation curve of the abnormal weld unit to obtain the weld type of the abnormal weld unit specifically includes: Obtaining thermal properties of the welding material of the weld to be inspected; Based on the thermal properties of the welding material and the temperature change curve of the abnormal weld unit, constructing a section model of the abnormal weld unit; Feature recognition is performed on the section model to obtain the weld type of the abnormal weld unit.

8. A quality inspection device for automobile exhaust pipe welds, characterized in that: The device is a weld quality analysis system, comprising an input module (1), a processing module (2) and an output module (3), wherein: The input module (1) is used to control the heating module to heat the weld to be detected, stop heating when the weld to be detected reaches the target temperature, monitor the temperature of the weld to be detected, and obtain a weld temperature change distribution diagram of the weld to be detected; The processing module (2) is used to extract temperature change curves of multiple weld units from the weld temperature change distribution diagram; perform similarity calculation on the temperature change curves of the multiple weld units and the temperature change curve of a preset weld unit; calculate the similarity between the temperature change curves of a first weld unit and the preset weld unit, and determine whether the first weld unit is an abnormal weld unit, the first weld unit being any one of the multiple weld units; The output module (3) is used to perform characteristic analysis on the temperature change curve of the abnormal weld unit if the first weld unit is the abnormal weld unit, so as to obtain the weld type of the abnormal weld unit, wherein the weld type includes weld nodule, weld penetration, pore, undercut, poor forming and slag inclusion.

9. An electronic device, characterized in that: The electronic device (400) comprises a processor (401), a memory (405), a user interface (403) and a network interface (404), wherein the memory (405) is used to store instructions, the user interface (403) and the network interface (404) are used to communicate with other devices, and the processor (401) is used to execute the instructions stored in the memory (405) so that the electronic device (400) executes the method according to any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores instructions, and when the instructions are executed, the method according to any one of claims 1 to 7 is performed.

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