Weld defect repair welding control method and device, computer device and storage medium

Abstract

The application relates to a weld defect repair welding control method and device, computer equipment, a storage medium and a computer program product. The method comprises the following steps: acquiring weld defect information of a target millimeter section in a welding process, determining a deviation and a deviation change of the target millimeter section according to the weld defect information; performing fuzzy processing on the deviation and the deviation change, determining a deviation fuzzy value corresponding to the deviation and a deviation change fuzzy value corresponding to the deviation change; performing fuzzy reasoning on the deviation fuzzy value and the deviation change fuzzy value based on fuzzy rules corresponding to the deviation fuzzy value and the deviation change fuzzy value, and determining a welding control quantity fuzzy value matched with the deviation fuzzy value and the deviation change fuzzy value; performing numerical mapping on the welding control quantity fuzzy value to obtain a repair welding parameter of the target millimeter section; and controlling a repair welding gun to perform repair welding on the weld defect in the target millimeter section based on the repair welding parameter. The method can improve the repair welding control efficiency of the weld defect.

Description

Technical Field

[0001] This application relates to the field of weld seam tracking and control technology, and in particular to a method, apparatus, computer equipment, storage medium and computer program product for weld seam defect repair welding control. Background Technology

[0002] With the development of weld seam tracking and control technology, weld defect repair technology has emerged, which can detect and repair weld defects, ensuring the normal operation of the welding process.

[0003] In traditional techniques, X-rays are typically used to detect weld defects and repair them during downtime, which disrupts the normal operation of the welding process and results in low production efficiency. Summary of the Invention

[0004] Therefore, it is necessary to provide a method, apparatus, computer equipment, computer-readable storage medium, and computer program product that can improve production efficiency in controlling weld defect repair welding, addressing the aforementioned technical problems.

[0005] Firstly, this application provides a method for controlling weld defect repair welding. The method includes: acquiring weld defect information of a target meter segment during the welding process; determining the deviation and deviation change amount of the target meter segment based on the weld defect information; performing fuzzification processing on the deviation and deviation change amount to determine a fuzzy value corresponding to the deviation and a fuzzy value corresponding to the deviation change amount; performing fuzzy reasoning on the fuzzy values ​​of the deviation and deviation change amount based on fuzzy rules corresponding to the fuzzy values ​​of the deviation and deviation change amount to determine a fuzzy value of a welding control quantity matching the fuzzy values ​​of the deviation and deviation change amount; performing numerical mapping on the fuzzy value of the welding control quantity to obtain repair welding parameters for the target meter segment; and controlling a repair welding torch to repair weld defects in the target meter segment based on the repair welding parameters.

[0006] In one embodiment, acquiring weld defect information of a target meter segment during the welding process includes: during the welding process, emitting a pulsed laser beam toward the weld of the target meter segment and receiving the reflected signal of the pulsed laser beam; generating a weld image of the target meter segment based on the reflected signal, and determining weld defect information in the weld image.

[0007] In one embodiment, the weld defect repair welding control method further includes: acquiring a standard value for weld defects and a standard value for deviations; determining the deviation and the amount of deviation change of the target meter segment based on the weld defect information includes: comparing the weld defect information with the standard value for weld defects to determine the deviation of the target meter segment; and comparing the deviation with the standard value for deviations to determine the amount of deviation change of the target meter segment.

[0008] In one embodiment, obtaining weld defect standard values ​​and deviation standard values ​​includes: determining the defect type represented by the weld defect information; and obtaining weld defect standard values ​​and deviation standard values ​​that match the defect type from a standard value database.

[0009] In one embodiment, based on the fuzzy rules corresponding to the deviation fuzzy value and the deviation change fuzzy value, fuzzy inference is performed on the deviation fuzzy value and the deviation change fuzzy value to determine the welding control quantity fuzzy value that matches the deviation fuzzy value and the deviation change fuzzy value. This includes: obtaining the membership degree matrix corresponding to each of the deviation fuzzy value and the deviation change fuzzy value, and the fuzzy rule matrix corresponding to the deviation fuzzy value and the deviation change fuzzy value; performing a synthesis operation based on each of the membership degree matrix and the fuzzy rule matrix to obtain the membership degree matrix of the welding control quantity; and defuzzifying the membership degree matrix of the welding control quantity to determine the welding control quantity fuzzy value that matches the deviation fuzzy value and the deviation change fuzzy value.

[0010] In one embodiment, the weld defect repair welding control method further includes: acquiring weld defect update information after repair welding of the target meter section; if the weld defect update information meets a first condition, continuing to acquire weld defect information of the next meter section of the target meter section for repair welding operation; if the weld defect update information meets a second condition, issuing an alarm and continuing to acquire weld defect information of the next meter section of the target meter section for repair welding operation; and if the weld defect update information meets a third condition, issuing an alarm and stopping the repair welding.

[0011] In one embodiment, the weld defect repair welding control method further includes: uploading the weld defect update information and the identification information of the target meter segment to a weld defect information database; in response to a query event for weld defect information, obtaining the identification information of the meter segment to be queried; and based on the identification information of the meter segment to be queried, querying the weld defect update information of the meter segment to be queried from the weld defect information database.

[0012] Secondly, this application also provides a weld defect repair welding control device. The device includes:

[0013] The weld defect information acquisition module is used to acquire weld defect information of the target meter segment during the welding process, and to determine the deviation and deviation change of the target meter segment based on the weld defect information.

[0014] A fuzzification processing module is used to fuzzify the deviation and the change in deviation to determine the fuzzy value of the deviation and the fuzzy value of the change in deviation.

[0015] The fuzzy inference module is used to perform fuzzy inference on the fuzzy deviation value and the fuzzy deviation change value based on the fuzzy rules corresponding to the fuzzy deviation value and the fuzzy deviation change value, and determine the fuzzy welding control quantity value that matches the fuzzy deviation value and the fuzzy deviation change value.

[0016] The welding parameter determination module is used to perform numerical mapping on the fuzzy value of the welding control quantity to obtain the welding parameters of the target meter segment;

[0017] The weld defect repair module is used to control the repair welding gun to repair weld defects in the target meter section based on the repair welding parameters.

[0018] Thirdly, this application also provides a computer device. The computer device includes a memory and a processor, the memory storing a computer program, and the processor executing the computer program to implement the steps of the method described above.

[0019] Fourthly, this application also provides a computer-readable storage medium. The computer-readable storage medium stores a computer program thereon, which, when executed by a processor, implements the steps of the method described above.

[0020] Fifthly, this application also provides a computer program product. The computer program product includes a computer program that, when executed by a processor, implements the steps of the method described above.

[0021] The aforementioned weld defect repair welding control method, device, computer equipment, storage medium, and computer program product, by acquiring weld defect information of the target meter section during the welding process, can determine whether the target meter section has weld defects and the specific details of the defects. Based on the weld defect information, it determines the deviation and change in deviation of the target meter section, and performs fuzzification processing on the deviation and change in deviation to determine the fuzzy value corresponding to the deviation and the fuzzy value corresponding to the change in deviation. This maps the deviation and change in deviation to a set numerical range, facilitating fuzzy reasoning operations. Subsequently, based on... The fuzzy rules corresponding to the deviation fuzzy value and the deviation change fuzzy value are used to perform fuzzy inference on the deviation fuzzy value and the deviation change fuzzy value to determine the welding control quantity fuzzy value that matches the deviation fuzzy value and the deviation change fuzzy value. The welding control quantity fuzzy value is numerically mapped to obtain the repair welding parameters for the target meter section. Based on the mapping relationship between the welding control quantity fuzzy value and the repair welding parameters, the specific data of the repair welding parameters can be determined. Finally, based on the repair welding parameters, the repair welding gun is controlled to repair the weld defects in the target meter section. The repair welding of the weld defect can be carried out while the welding process is ongoing, thereby improving the welding efficiency. Attached Figure Description

[0022] Figure 1 This is a diagram illustrating the application environment of a weld defect repair welding control method in one embodiment.

[0023] Figure 2 This is a flowchart illustrating a weld defect repair welding control method in one embodiment;

[0024] Figure 3 This is a diagram illustrating the specific implementation process of a weld defect repair welding control method in one embodiment.

[0025] Figure 4 This is a schematic diagram of the process for recording weld defect information in one embodiment.

[0026] Figure 5 This is a flowchart illustrating a weld defect repair welding control method in another embodiment;

[0027] Figure 6 This is a structural block diagram of a weld defect repair welding control device in one embodiment;

[0028] Figure 7 This is an internal structural diagram of a computer device in one embodiment. Detailed Implementation

[0029] To make the objectives, technical solutions, and advantages of this application clearer, the following detailed description is provided in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the scope of this application.

[0030] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, data stored, data displayed, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties.

[0031] The weld defect repair and control method provided in this application embodiment can be applied to, for example... Figure 1 In the application environment shown, terminal 102 communicates with welding torch 104 via a network. Terminal 102 can be, but is not limited to, various personal computers, laptops, smartphones, tablets, IoT devices, and portable wearable devices. IoT devices can include smart speakers, smart TVs, smart air conditioners, smart in-vehicle devices, etc. Portable wearable devices can include smartwatches, smart bracelets, head-mounted devices, etc. Specifically, during the process of controlling the welding torch 104 to repair weld defects, the terminal 102 first acquires the weld defect information of the target meter segment during the welding process, and determines the deviation and deviation change amount of the target meter segment based on the weld defect information; it then performs fuzzification processing on the deviation and deviation change amount to determine the fuzzy value of the deviation corresponding to the deviation and the fuzzy value of the deviation change amount corresponding to the deviation change amount; based on the fuzzy rules corresponding to the fuzzy values ​​of the deviation and deviation change amount, it performs fuzzy reasoning on the fuzzy values ​​of the deviation and deviation change amount to determine the fuzzy value of the welding control quantity that matches the fuzzy values ​​of the deviation and deviation change amount; it then performs numerical mapping on the fuzzy values ​​of the welding control quantity to obtain the repair welding parameters of the target meter segment; and finally, based on the repair welding parameters, it controls the welding torch 104 to repair the weld defects in the target meter segment.

[0032] In one embodiment, such as Figure 2 As shown, a method for controlling weld defect repair welding is provided, which is applied to... Figure 1 Taking the terminal in the example, the explanation includes the following steps:

[0033] Step S202: Obtain weld defect information of the target meter section during the welding process, and determine the deviation and deviation change of the target meter section based on the weld defect information.

[0034] In this context, the meter mark is used to indicate the cable length, similar to the graduations on a measuring tape, to measure the weld length of the cable's metal sheath. The target meter segment refers to the segment from which weld defect information is to be obtained. Weld defect information refers to relevant information about weld defects, such as their location, position, and size. The deviation and change in deviation of the target meter segment refer to the deviation and change in the weld defect information within that segment.

[0035] Specifically, during cable welding, weld defects are inevitable. Since the cable moves forward continuously, two welding torches can be sequentially positioned along the cable's path to repair these defects. The first torch is used for general welding (denoted as the welding torch), and the second torch is used for repair welding (denoted as the repair torch). A camera is positioned near each torch. As the cable passes the welding torch, the torch welds the cable's seam, and the camera captures the weld information, thus obtaining weld defect information for the target meter segment. Based on this defect information, the deviation and change in deviation of the target meter segment can then be determined.

[0036] In one specific embodiment, the standard value of weld defect and the standard value of deviation can be obtained from the database first. The weld defect information is compared with the standard value of weld defect to determine the deviation of the target meter segment. Then, the deviation is compared with the standard value of deviation to determine the amount of deviation change of the target meter segment.

[0037] In another specific embodiment, the weld defect information and deviation of the previous meter segment of the target meter segment can be obtained first as the standard value of weld defect and standard value of deviation of the target meter segment. Then, the weld defect information is compared with the standard value of weld defect to determine the deviation of the target meter segment. The deviation is then compared with the standard value of deviation to determine the amount of deviation change of the target meter segment.

[0038] Step S204: Perform fuzzification processing on the deviation and the change in deviation to determine the fuzzy value of the deviation corresponding to the deviation and the fuzzy value of the change in deviation corresponding to the change in deviation.

[0039] Among them, the deviation fuzzy value refers to the deviation fuzzy value obtained by fuzzifying the precise value of the deviation, and the deviation change fuzzy value refers to the deviation change fuzzy value obtained by fuzzifying the precise value of the deviation change.

[0040] Specifically, since both the deviation and the change in deviation are precise values, to facilitate subsequent fuzzy inference operations, it is necessary to map the deviation and the change in deviation to a set domain. That is, the deviation and the change in deviation need to be fuzzified to determine the fuzzy value of the deviation corresponding to the deviation and the fuzzy value of the change in deviation corresponding to the change in deviation. For example, the deviation can be... and deviation change The two methods are fuzzified separately to obtain the deviation fuzzy value and the deviation change fuzzy value. .in, and Defined as the following fuzzy subset:

[0041] =NB, NM, NS, NO, PO, PS, PM, PB

[0042] =NB, NM, NS, O, PS, PM, PB

[0043] Wherein, NB, NM, NS, NO, O, PO, PS, PM, and PB represent negative large, negative small, negative medium, negative zero, zero, positive zero, positive small, positive medium, and positive large, respectively.

[0044] and The domain of discourse is defined by 13 levels, namely:

[0045] = -6, -5, -4, -3, -2, -1, 0, +1, +2, +3, +4, +5, +6

[0046] = -6, -5, -4, -3, -2, -1, 0, +1, +2, +3, +4, +5, +6

[0047] In a specific embodiment, mapping relationships between deviation and deviation fuzzy value, and between deviation change amount and deviation change amount fuzzy value can be established respectively. Based on the mapping relationship and the actual values ​​of deviation and deviation change amount, deviation fuzzy value and deviation change amount fuzzy value can be determined.

[0048] In another specific embodiment, the deviation, the change in deviation, and the proportional factor matching the deviation and the change in deviation can also be calculated and analyzed to determine the fuzzy value of the deviation and the fuzzy value of the change in deviation.

[0049] Step S206: Based on the fuzzy rules corresponding to the deviation fuzzy value and the deviation change amount fuzzy value, perform fuzzy reasoning on the deviation fuzzy value and the deviation change amount fuzzy value to determine the welding control amount fuzzy value that matches the deviation fuzzy value and the deviation change amount fuzzy value.

[0050] Fuzzy rules describe the relationship between input and output variables. For example, a fuzzy rule could be... The fuzzy value of welding control quantity refers to the fuzzy value of the control quantity for controlling the welding torch during repair welding, which is related to the above. and It shares the same properties, is also a fuzzy value, can be represented by a fuzzy subset, and also has multiple universe levels:

[0051] =NB, NM, NS, O, PS, PM, PB

[0052] = -6, -5, -4, -3, -2, -1, 0, +1, +2, +3, +4, +5, +6

[0053] Specifically, fuzzy rules corresponding to the deviation fuzzy value and the deviation change amount fuzzy value can be pre-established. After determining the deviation fuzzy value and the deviation change amount fuzzy value, fuzzy inference can be performed on the deviation fuzzy value and the deviation change amount fuzzy value based on the fuzzy rules to determine the welding control quantity fuzzy value that matches the deviation fuzzy value and the deviation change amount fuzzy value. In a specific embodiment, the membership degree matrix corresponding to the deviation fuzzy value and the deviation change amount fuzzy value, as well as the fuzzy rule matrix corresponding to the deviation fuzzy value and the deviation change amount fuzzy value, can be obtained. Based on the membership degree matrix and the fuzzy rule matrix, a synthesis operation is performed to obtain the membership degree matrix of the welding control quantity. Then, the membership degree matrix of the welding control quantity is defuzzified to determine the welding control quantity fuzzy value that matches the deviation fuzzy value and the deviation change amount fuzzy value. In another specific embodiment, a fuzzy rule can be established with the input variables being the deviation fuzzy value and the deviation change fuzzy value, and the output variable being the welding control quantity fuzzy value. After determining the deviation fuzzy value corresponding to the deviation and the deviation change fuzzy value corresponding to the deviation change, the deviation fuzzy value and the deviation change fuzzy value are substituted into the fuzzy rule to determine the welding control quantity fuzzy value that matches the deviation fuzzy value and the deviation change fuzzy value.

[0054] Step S208: Perform numerical mapping on the fuzzy values ​​of welding control quantities to obtain the welding parameters for the target meter section.

[0055] Among them, the welding parameters refer to the control parameters of the welding torch for welding repair, such as including but not limited to the angle adjustment value of the welding torch, the magnitude of the welding torch current, and the number of pulses for the welding torch movement.

[0056] Specifically, since the obtained fuzzy values ​​of welding control quantities are still domain values, it is necessary to perform numerical mapping on these fuzzy values ​​to obtain the corresponding rework welding parameters for the target meter segment. Furthermore, the method of numerical mapping is not unique; it can be based on pre-established numerical mapping relationships or feature matching based on the numerical characteristics of the fuzzy values ​​of welding control quantities to obtain the rework welding parameters for the target meter segment.

[0057] Step S210: Based on the repair welding parameters, control the repair welding gun to repair weld defects in the target meter section.

[0058] The welding torch refers to the part that performs the welding operation during the welding process. The welding torch can use the heat generated by the high current and high voltage of the welding machine to concentrate at the end of the welding torch, melt the welding wire, and the melted welding wire penetrates to the weld defect that needs to be welded, so that the weld defect can be repaired by welding.

[0059] Specifically, after obtaining the repair welding parameters, when the cable of the target meter section is moved to the repair welding gun, the terminal can control the repair welding gun to repair the weld defects of the target meter section according to the repair welding parameters. It can be understood that while the repair welding gun is repairing the target meter section, it can simultaneously weld the next meter section of the target meter section without affecting the welding operation. That is, the repair welding operation and the welding operation can be performed synchronously.

[0060] In the aforementioned weld defect repair welding control method, by acquiring weld defect information of the target meter section during the welding process, it is possible to determine whether the target meter section has weld defects and the specific details of the weld defects. Based on the weld defect information, the deviation and deviation change of the target meter section are determined, and the deviation and deviation change are fuzzified to determine the fuzzy value of the deviation and the fuzzy value of the deviation change. The deviation and deviation change can be mapped to a set numerical range, facilitating fuzzy inference. Then, based on the fuzzy rules corresponding to the fuzzy values ​​of the deviation and deviation change, fuzzy inference is performed on the fuzzy values ​​of the deviation and deviation change to determine the fuzzy value of the welding control quantity that matches the fuzzy values ​​of the deviation and deviation change. The fuzzy value of the welding control quantity is numerically mapped to obtain the repair welding parameters of the target meter section. Based on the mapping relationship between the fuzzy value of the welding control quantity and the repair welding parameters, the specific data of the repair welding parameters can be determined. Finally, based on the repair welding parameters, the repair welding torch is controlled to repair the weld defects in the target meter section. Repair welding of the weld defect can be performed while the welding process is ongoing, thereby improving welding efficiency.

[0061] In one embodiment, acquiring weld defect information of a target meter segment during the welding process includes: during the welding process, emitting a pulsed laser beam toward the weld of the target meter segment and receiving the reflected signal of the pulsed laser beam; generating a weld image of the target meter segment based on the reflected signal, and determining weld defect information in the weld image.

[0062] A pulsed laser beam refers to a single light pulse emitted by a laser operating in pulsed mode. Simply put, it's like the operation of a flashlight: keeping the button on continuously activates the light, while turning it off immediately emits a single "light pulse." The pulsed laser beam is emitted by a pulsed laser unit in a camera. This beam is focused into a narrow beam by a lens, and when it strikes a weld defect, it reflects back, generating a reflected signal. A weld image is an image containing three-dimensional information about the object, such as the location, size, and location of the weld defect.

[0063] Specifically, in order to obtain weld defect information of the target meter segment, during the welding process, the terminal can control a pulsed laser to emit a pulsed laser beam towards the weld of the target meter segment. Based on the speed of the beam formed by the convergence of the pulsed laser beam and the time interval from emission to reception, the distance between the weld defect location and the camera, i.e., the weld depth value, is determined. Then, the weld defect is periodically scanned by the laser beam to determine the size and texture information of the weld defect. The weld depth value is combined with the weld defect size and location information to generate a weld image. The image contains information such as the weld defect location, weld position, and weld defect size.

[0064] In this embodiment, by emitting a pulsed laser beam toward the weld location to obtain a weld image containing weld defect information, the efficiency of obtaining weld defect information can be improved, thereby improving the efficiency of repairing weld defects.

[0065] In one embodiment, the weld defect repair welding control method further includes: obtaining standard values ​​and deviation standard values ​​for weld defects; determining the deviation and deviation change of a target meter segment based on the weld defect information, including: comparing the weld defect information with the standard values ​​for weld defects to determine the deviation of the target meter segment; and comparing the deviation with the standard values ​​for deviation to determine the deviation change of the target meter segment.

[0066] Among them, the standard values ​​for weld defects and the standard values ​​for deviations are pre-set values ​​stored in the standard value database. They are the weld defect values ​​and deviation values ​​under ideal conditions.

[0067] Specifically, the deviation of the target meter segment refers to the discrepancy between the weld defect information and the standard value of the weld defect, while the change in deviation refers to the change between the deviation and the standard value of the deviation. To determine the deviation and the change in deviation of the target meter segment, it is necessary to first obtain the standard value of the weld defect and the standard value of the deviation. By comparing the weld defect information with the standard value of the weld defect, the deviation of the target meter segment can be determined. By comparing the deviation with the standard value of the deviation, the change in deviation of the target meter segment can be determined.

[0068] In one specific embodiment, the locations of weld defects are respectively... Weld position and the size of weld defects By subtracting the corresponding standard value from the weld's value, the location of the weld defect can be determined. Weld position and the size of weld defects Their respective deviation values , , The location of weld defects Weld position and the size of weld defects Their respective deviation values , , By subtracting the values ​​from their respective standard deviations, the location of weld defects can be determined. Weld position and the size of weld defects The change in deviation corresponding to each deviation value , , .

[0069] Each weld repair corresponds to a meter segment, and the previous weld repair corresponds to the previous meter segment. This weld repair is based on the weld seam and the defect weld seam is detected. The premise is that the computer has established a common weld seam defect image feature parameter library in advance through the information characteristics of the defects. In the subsequent weld seam defect detection, the deviation value between the detected weld seam defect information features and the common weld seam defect image feature parameter library established in the computer can be used as the standard deviation value. Only when the deviation value is greater than 1 can the defect weld seam be completely covered in the second weld repair.

[0070] In this embodiment, by comparing the standard value with the obtained weld defect information and deviation, the deviation and the amount of deviation change can be determined, thus ensuring the accuracy of the obtained deviation and deviation change values.

[0071] In one embodiment, obtaining weld defect standard values ​​and deviation standard values ​​includes: determining the defect type represented by the weld defect information; and obtaining weld defect standard values ​​and deviation standard values ​​that match the defect type from a standard value database.

[0072] The defect types include, but are not limited to, incomplete welds, cold welds, pinholes, and undercuts. The standard value database stores standard values ​​and deviation standard values ​​for weld defects corresponding to various defect types.

[0073] Specifically, before obtaining the standard values ​​and deviation standard values ​​of weld defects, it is necessary to first determine the defect type of the weld defect represented by the weld defect information. Since the standard value database stores standard values ​​and deviation standard values ​​of weld defects corresponding to various defect types, the standard values ​​and deviation standard values ​​of weld defects matching the defect type can be obtained based on the defect type. For example, if the defect type represented by the weld defect information is "weld leakage", the standard values ​​and deviation standard values ​​of weld defects matching "weld leakage" can be extracted from the standard value database.

[0074] In this embodiment, the weld defect standard value and deviation standard value matching the defect type are obtained from the standard value database according to the defect type of the weld defect information. This ensures that the weld defect standard value and deviation standard value are consistent with the weld defect type. In other words, it ensures that the obtained weld defect standard value and deviation standard value are accurate when applied to the scenario of the weld defect type, thereby improving the accuracy of weld defect repair welding.

[0075] In one embodiment, based on the fuzzy rules corresponding to the deviation fuzzy value and the deviation change fuzzy value, fuzzy reasoning is performed on the deviation fuzzy value and the deviation change fuzzy value to determine the welding control quantity fuzzy value that matches the deviation fuzzy value and the deviation change fuzzy value. This includes: obtaining the membership degree matrix corresponding to each deviation fuzzy value and the deviation change fuzzy value, as well as the fuzzy rule matrix corresponding to the deviation fuzzy value and the deviation change fuzzy value; performing a synthesis operation based on each membership degree matrix and the fuzzy rule matrix to obtain the membership degree matrix of the welding control quantity; and defuzzifying the membership degree matrix of the welding control quantity to determine the welding control quantity fuzzy value that matches the deviation fuzzy value and the deviation change fuzzy value.

[0076] The membership matrix represents the degree of belonging of each object. The fuzzy rule matrix is ​​obtained by taking the union of all pre-defined fuzzy rules. The composition operation combines two or more functions or relations to form a new function or relation.

[0077] Specifically, the terminal can substitute the obtained deviation fuzzy value and deviation change fuzzy value into their respective membership degree-universe matrix to obtain the membership degree matrix corresponding to the deviation fuzzy value and deviation change fuzzy value, respectively. It then performs a union operation on each preset fuzzy rule to obtain a fuzzy rule matrix. Based on the membership degree matrix and the fuzzy rule matrix, it performs a synthesis operation to obtain the membership degree matrix of the welding control quantity. Finally, it defuzzifies the membership degree matrix of the welding control quantity to determine the fuzzy value of the welding control quantity that matches the deviation fuzzy value and deviation change fuzzy value. Furthermore, the defuzzification method is not unique; for example, it can be the maximum membership degree method, the centroid method, and the weighted average method, etc. In a specific embodiment, the fuzzy control rule is represented by the following composite conditional statement:

[0078]

[0079] in,

[0080] Each statement corresponds to one relationship, that is...

[0081]

[0082] The overall relationship, namely

[0083] The symbol U represents a pair Find the union relationship. By performing a synthesis operation between the membership matrix and the matrix corresponding to the fuzzy rule, the membership relationship of the corresponding control quantity can be obtained.

[0084]

[0085] The final fuzzy values ​​of the welding control quantities are shown in Table 1.

[0086] Table 1 Fuzzy Values ​​of Welding Control Quantities

[0087]

[0088] In this embodiment, by pre-establishing reasonable fuzzy rules and a series of fuzzy inferences, the welding control quantity fuzzy value that matches the deviation fuzzy value and the deviation change amount fuzzy value can be determined, which can ensure the normal operation of the weld defect repair welding control process.

[0089] In one embodiment, the weld defect repair welding control method further includes: acquiring updated weld defect information after repair welding of the target meter section; if the updated weld defect information meets a first condition, continuing to acquire weld defect information of the next meter section of the target meter section for repair welding operation; if the updated weld defect information meets a second condition, issuing an alarm and continuing to acquire weld defect information of the next meter section of the target meter section for repair welding operation; and if the updated weld defect information meets a third condition, issuing an alarm and stopping the repair welding.

[0090] Among them, weld defect update information refers to the weld defect information obtained after repair welding of the weld defect, which can be used to confirm the repair welding status. The first condition is that the weld represented by the weld defect update information does not affect the use and is aesthetically pleasing; the second condition is that the weld represented by the weld defect update information does not affect the use; the third condition is that the weld represented by the weld defect update information affects the use.

[0091] Specifically, since the weld defect repair process is carried out while the cable is continuously moving forward, it is necessary to monitor the results of the weld defect repair. If the weld defect update information meets the first condition, that is, the weld represented by the weld defect update information does not affect use and is aesthetically pleasing, then the weld defect information of the next meter section of the target meter section can be obtained for repair operation. If the weld defect update information meets the second condition, that is, the weld represented by the weld defect update information does not affect use, then an alarm needs to be triggered and the weld defect information of the next meter section of the target meter section needs to be obtained for repair operation. If the weld defect update information meets the third condition, that is, the weld represented by the weld defect update information affects use, then an alarm needs to be triggered and the repair operation needs to be stopped.

[0092] In a specific embodiment, the first condition is: the weld of the metal sheath (60) is concave by 0-1.5mm, the height difference is ≤1.5mm, the inner edge penetration is uniform, the width difference after welding the same weld is ≤3.5mm, the weld formation is excellent, the weld is uniform and flat, the transition is smooth, there is no arc crater at the end of the arc, and the weld bead is free from black spots, missed welds, false welds, uneven welds, pinholes, undercuts, etc. The second condition is: the weld of the metal sheath (60) is concave by 1.5-2.5mm, the height difference is ≤2.0mm, the inner edge penetration is uniform, the width difference after welding the same weld is ≤4mm, the weld formation is excellent, the weld is uniform and flat, the transition is smooth, there is no arc crater at the end of the arc, the weld black spots are ≤1.5mm and no more than 2 within one meter, and the weld bead is free from missed welds, false welds, uneven welds, pinholes, undercuts, etc. The third condition is: the weld of the metal sheath (60) is concave by 2.5-3.5mm, the height difference is ≥2mm, the treatment of the penetration defect of the inner edge is basically uniform, the width difference of the same weld after welding is ≥4.5mm, the weld formation is poor, the transition is not smooth, the arc crater appears at the end of the arc and is ≥2.5mm, the size of the weld leakage, false welding, pinhole, black spot is ≥2.8mm, and the weld bead weld unevenness, undercut and other phenomena appear continuously within one meter.

[0093] In this embodiment, different operations are taken according to the different situations of the updated weld defect information after the repair welding of the target meter section. The repair welding can be stopped in time if the repair welding situation is not ideal, and the repair welding can continue if the repair welding situation is ideal, thereby ensuring the normal operation of the repair welding process.

[0094] In one embodiment, the weld defect repair welding control method further includes: uploading weld defect update information and the identification information of the target meter segment to a weld defect information database; in response to a query event for weld defect information, obtaining the identification information of the meter segment to be queried; and based on the identification information of the meter segment to be queried, querying the weld defect update information of the meter segment to be queried from the weld defect information database.

[0095] The identification information refers to the marking and identification information of the target meter segment, which can be used for locating, monitoring, and searching the target meter segment.

[0096] Specifically, after the weld defects in the target meter section are repaired, the updated weld defect information and the identification information of the target meter section need to be uploaded to the weld defect information database. Then, during subsequent quality tracking and tracing, upon receiving a query event for weld defect information, a response can be initiated to obtain the identification information of the queried meter section. Based on this identification information, the updated weld defect information for the queried meter section is retrieved from the weld defect information database, and quality tracking and tracing are performed based on this updated information. Furthermore, the updated weld defect information and identification information after each meter section's repair welding operation are uploaded to the weld defect information database.

[0097] In this embodiment, the updated information on weld defects and the identification information of the target meter segment are uploaded to the weld defect information database. This facilitates a series of operations such as querying weld defect information, quality tracking, and tracing, thereby ensuring the quality of weld defect repair welding.

[0098] In one specific embodiment, the flowchart for weld defect repair control is as follows: Figure 3 As shown, firstly, the deviation is obtained by subtracting the standard values ​​of the weld defect location, weld position, and weld defect size from their respective standard values. Then, the deviation value is subtracted from the standard deviation value to obtain the deviation change. Next, the deviation and deviation change are fuzzified to obtain the fuzzy deviation value corresponding to the deviation and the fuzzy deviation change value corresponding to the deviation change. Then, fuzzy inference is performed on the fuzzy deviation value and the fuzzy deviation change value to obtain the fuzzy welding control value. The fuzzy welding control value is numerically mapped according to the set numerical mapping relationship to obtain the repair welding parameters, including parameters such as current value and pulse number. The repair welding gun is controlled to repair the weld defect according to the repair welding parameters.

[0099] In a specific embodiment, such as Figure 4 As shown, weld defects can be entered into the weld defect information feature database and then uploaded to the expert system, where the expert system will evaluate the weld defect information.

[0100] In a specific embodiment, such as Figure 5 As shown, the methods for controlling weld defect repair welding include:

[0101] Step S501: During the welding process, a pulsed laser beam is emitted towards the weld of the target meter segment, and the reflected signal of the pulsed laser beam is received. Based on the reflected signal, a weld image of the target meter segment is generated, and weld defect information in the weld image is determined.

[0102] Step S502: Determine the defect type represented by the weld defect information, and obtain the weld defect standard value and deviation standard value that match the defect type from the standard value database;

[0103] Step S503: Compare the weld defect information with the weld defect standard value to determine the deviation of the target meter segment, and compare the deviation with the deviation standard value to determine the change in deviation of the target meter segment.

[0104] Step S504: Perform fuzzification processing on the deviation and the change in deviation to determine the fuzzy value of the deviation corresponding to the deviation and the fuzzy value of the change in deviation corresponding to the change in deviation.

[0105] Step S505: Obtain the membership matrix corresponding to the deviation fuzzy value and the deviation change fuzzy value, as well as the fuzzy rule matrix corresponding to the deviation fuzzy value and the deviation change fuzzy value.

[0106] Step S506: Perform a synthesis operation based on each membership matrix and fuzzy rule matrix to obtain the membership matrix of the welding control quantity. Defuzzify the membership matrix of the welding control quantity to determine the fuzzy value of the welding control quantity that matches the fuzzy value of the deviation and the fuzzy value of the deviation change.

[0107] Step S507: Perform numerical mapping on the fuzzy value of the welding control quantity to obtain the welding repair parameters of the target meter section. Based on the welding repair parameters, control the welding gun to repair the weld defects in the target meter section and obtain the updated information of the weld defects after the welding repair of the target meter section.

[0108] Step S508: If the weld defect update information meets the first condition, continue to obtain the weld defect information of the next meter section of the target meter section and perform repair welding operation.

[0109] Step S509: If the weld defect update information meets the second condition, an alarm is triggered and the weld defect information of the next meter section of the target meter section is acquired for repair welding.

[0110] Step S510: If the weld defect update information meets the third condition, an alarm is triggered and the repair welding is stopped.

[0111] Step S511: Upload the weld defect update information and the identification information of the target meter section to the weld defect information database;

[0112] Step S512: In response to a query event for weld defect information, obtain the identification information of the meter segment to be queried;

[0113] Step S513: Based on the identification information of the meter segment to be queried, query the weld defect update information of the meter segment to be queried from the weld defect information database.

[0114] It should be understood that although the steps in the flowcharts of the embodiments described above are shown sequentially according to the arrows, these steps are not necessarily executed in the order indicated by the arrows. Unless explicitly stated herein, there is no strict order restriction on the execution of these steps, and they can be executed in other orders. Moreover, at least some steps in the flowcharts of the embodiments described above may include multiple steps or multiple stages. These steps or stages are not necessarily completed at the same time, but can be executed at different times. The execution order of these steps or stages is not necessarily sequential, but can be performed alternately or in turn with other steps or at least some of the steps or stages of other steps.

[0115] Based on the same inventive concept, this application also provides a weld defect repair welding control device for implementing the weld defect repair welding control method described above. The solution provided by this device is similar to the solution described in the above method; therefore, the specific limitations of one or more weld defect repair welding control device embodiments provided below can be found in the limitations of the weld defect repair welding control method described above, and will not be repeated here.

[0116] In one embodiment, such as Figure 6 As shown, a weld defect repair welding control device 600 is provided, including: a weld defect information acquisition module, a fuzzification processing module, a fuzzy inference module, a repair welding parameter determination module, and a weld defect repair welding module, wherein:

[0117] The weld defect information acquisition module 602 is used to acquire weld defect information of the target meter section during the welding process, and to determine the deviation and the amount of deviation change of the target meter section based on the weld defect information.

[0118] The fuzzification processing module 604 is used to perform fuzzification processing on the deviation and the change in deviation to determine the fuzzy value of the deviation corresponding to the deviation and the fuzzy value of the change in deviation corresponding to the change in deviation.

[0119] The fuzzy inference module 606 is used to perform fuzzy inference on the fuzzy values ​​of deviation and change of deviation based on the fuzzy rules corresponding to the fuzzy values ​​of deviation and change of deviation, and to determine the fuzzy values ​​of welding control quantities that match the fuzzy values ​​of deviation and change of deviation.

[0120] The welding parameter determination module 608 is used to perform numerical mapping on the fuzzy values ​​of welding control quantities to obtain the welding parameters for the target meter section;

[0121] The weld defect repair module 610 is used to control the repair welding gun to repair weld defects in the target meter section based on the repair welding parameters.

[0122] In one embodiment, the weld defect information acquisition module is used to: during the welding process, emit a pulsed laser beam toward the weld of the target meter segment and receive the reflected signal of the pulsed laser beam; generate a weld image of the target meter segment based on the reflected signal, and determine the weld defect information in the weld image.

[0123] In one embodiment, the weld defect repair control device further includes a standard value acquisition module for acquiring standard values ​​of weld defects and standard values ​​of deviations. In this embodiment, the weld defect information acquisition module is also used to: compare the weld defect information with the standard values ​​of weld defects to determine the deviation of the target meter segment; and compare the deviation with the standard value of deviation to determine the amount of deviation change of the target meter segment.

[0124] In one embodiment, the standard value acquisition module is specifically used to: determine the defect type represented by the weld defect information; and acquire weld defect standard values ​​and deviation standard values ​​that match the defect type from the standard value database.

[0125] In one embodiment, the fuzzy inference module is specifically used to: obtain the membership degree matrix corresponding to the deviation fuzzy value and the deviation change amount fuzzy value, as well as the fuzzy rule matrix corresponding to the deviation fuzzy value and the deviation change amount fuzzy value; perform a synthesis operation based on each membership degree matrix and the fuzzy rule matrix to obtain the membership degree matrix of the welding control quantity; and defuzzify the membership degree matrix of the welding control quantity to determine the welding control quantity fuzzy value that matches the deviation fuzzy value and the deviation change amount fuzzy value.

[0126] In one embodiment, the weld defect repair welding control device further includes a weld defect update information condition judgment module, specifically used for: acquiring weld defect update information after repair welding of the target meter section; if the weld defect update information meets a first condition, continuing to acquire weld defect information of the next meter section of the target meter section for repair welding operation; if the weld defect update information meets a second condition, issuing an alarm and continuing to acquire weld defect information of the next meter section of the target meter section for repair welding operation; and if the weld defect update information meets a third condition, issuing an alarm and stopping the repair welding.

[0127] In one embodiment, the weld defect repair control device further includes a data upload module, specifically used for: uploading weld defect update information and the identification information of the target meter segment to the weld defect information database; in response to a query event for weld defect information, obtaining the identification information of the meter segment to be queried; and based on the identification information of the meter segment to be queried, querying the weld defect update information of the meter segment to be queried from the weld defect information database.

[0128] Each module in the aforementioned weld defect repair control device can be implemented entirely or partially through software, hardware, or a combination thereof. These modules can be embedded in or independent of the processor in a computer device, or stored in the computer device's memory as software, so that the processor can call and execute the corresponding operations of each module.

[0129] In one embodiment, a computer device is provided, which may be a terminal, and its internal structure diagram may be as follows: Figure 7 As shown, the computer device includes a processor, memory, communication interface, display screen, and input devices connected via a system bus. The processor provides computing and control capabilities. The memory includes non-volatile storage media and internal memory. The non-volatile storage media stores the operating system and computer programs. The internal memory provides an environment for the operation of the operating system and computer programs in the non-volatile storage media. The communication interface is used for wired or wireless communication with external terminals; wireless communication can be achieved through Wi-Fi, mobile cellular networks, NFC (Near Field Communication), or other technologies. When the computer program is executed by the processor, it implements a method for controlling weld defect repair welding. The display screen can be an LCD screen or an e-ink screen. The input devices can be a touch layer covering the display screen, buttons, a trackball, or a touchpad on the computer device casing, or an external keyboard, touchpad, or mouse.

[0130] Those skilled in the art will understand that Figure 7 The structure shown is merely a block diagram of a portion of the structure related to the present application and does not constitute a limitation on the computer device to which the present application is applied. Specific computer devices may include more or fewer components than those shown in the figure, or combine certain components, or have different component arrangements.

[0131] In one embodiment, a computer device is provided, including a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to implement the steps of the method described above.

[0132] In one embodiment, a computer-readable storage medium is provided having a computer program stored thereon, which, when executed by a processor, implements the steps of the above-described method.

[0133] In one embodiment, a computer program product is provided, including a computer program that, when executed by a processor, implements the steps of the method described above.

[0134] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, data stored, data displayed, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties.

[0135] Those skilled in the art will understand that all or part of the processes in the above embodiments can be implemented by a computer program instructing related hardware. The computer program can be stored in a non-volatile computer-readable storage medium. When executed, the computer program can include the processes of the embodiments described above. Any references to memory, databases, or other media used in the embodiments provided in this application can include at least one of non-volatile and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetic random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. By way of illustration and not limitation, RAM can take many forms, such as Static Random Access Memory (SRAM) or Dynamic Random Access Memory (DRAM). The databases involved in the embodiments provided in this application may include at least one type of relational database and non-relational database. Non-relational databases may include, but are not limited to, blockchain-based distributed databases. The processors involved in the embodiments provided in this application may be general-purpose processors, central processing units, graphics processing units, digital signal processors, programmable logic devices, quantum computing-based data processing logic devices, etc., and are not limited to these.

[0136] The technical features of the above embodiments can be combined in any way. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0137] The embodiments described above are merely illustrative of several implementation methods of this application, and while the descriptions are specific and detailed, they should not be construed as limiting the scope of this patent application. It should be noted that those skilled in the art can make various modifications and improvements without departing from the concept of this application, and these all fall within the protection scope of this application. Therefore, the protection scope of this application should be determined by the appended claims.

Claims

1. A method for controlling weld defect repair welding, characterized in that, The method includes: During the welding process, weld defect information of the target meter segment is acquired, and the defect type represented by the weld defect information is determined; the target meter segment refers to the meter segment for which the weld defect information needs to be acquired. From the standard value database, obtain the weld defect standard value and deviation standard value that match the defect type; The weld defect information is compared with the standard value of the weld defect to determine the deviation of the target meter segment; the deviation of the target meter segment refers to the deviation of the weld defect information in the target meter segment. The deviation is compared with the standard deviation value to determine the change in deviation of the target meter segment; the change in deviation of the target meter segment refers to the change in deviation of the weld defect information in the target meter segment. The deviation and the change in deviation are fuzzified to determine the fuzzy value of the deviation and the fuzzy value of the change in deviation. The fuzzy value of the deviation refers to the fuzzy value of the deviation obtained by fuzzifying the precise value of the deviation. The fuzzy value of the change in deviation refers to the fuzzy value of the change in deviation obtained by fuzzifying the precise value of the change in deviation. Based on the fuzzy rules corresponding to the deviation fuzzy value and the deviation change amount fuzzy value, fuzzy reasoning is performed on the deviation fuzzy value and the deviation change amount fuzzy value to determine the welding control amount fuzzy value that matches the deviation fuzzy value and the deviation change amount fuzzy value; the welding control amount fuzzy value refers to the control amount fuzzy value for controlling the welding gun to perform welding. Numerical mapping is performed on the fuzzy values ​​of the welding control quantities to obtain the repair welding parameters for the target meter segment; Based on the aforementioned welding parameters, the welding torch is controlled to repair weld defects in the target meter section.

2. The method according to claim 1, characterized in that, During the welding process, information on weld defects in the target meter section is obtained, including: During the welding process, a pulsed laser beam is emitted toward the weld seam of the target meter section, and the reflected signal of the pulsed laser beam is received. Based on the reflected signal, a weld image of the target meter segment is generated, and weld defect information in the weld image is determined.

3. The method according to claim 1, characterized in that, The step of performing fuzzy inference on the fuzzy values ​​of the deviation and the deviation change based on the fuzzy rules corresponding to the deviation fuzzy value and the deviation change fuzzy value, and determining the welding control quantity fuzzy value that matches the deviation fuzzy value and the deviation change fuzzy value, includes: Obtain the membership degree matrix corresponding to the deviation fuzzy value and the deviation change amount fuzzy value, and the fuzzy rule matrix corresponding to the deviation fuzzy value and the deviation change amount fuzzy value; Based on the membership degree matrix and the fuzzy rule matrix, a synthesis operation is performed to obtain the membership degree matrix of the welding control quantity; The membership matrix of the welding control quantity is defuzzified to determine the fuzzy value of the welding control quantity that matches the fuzzy value of the deviation and the fuzzy value of the deviation change.

4. The method according to any one of claims 1 to 3, characterized in that, The method further includes: Obtain updated weld defect information after repair welding of the target meter section; the updated weld defect information refers to the weld defect information obtained after repair welding of the weld defect; If the weld defect update information meets the first condition, the weld defect information of the next meter segment of the target meter segment is obtained for repair welding operation; the first condition means that the weld represented by the weld defect update information does not affect use and is aesthetically pleasing. If the weld defect update information meets the second condition, an alarm is triggered and the weld defect information of the next meter segment of the target meter segment is acquired for repair welding; the second condition means that the weld represented by the weld defect update information does not affect its use; If the weld defect update information meets the third condition, an alarm will be triggered and repair welding will be stopped; the third condition refers to the impact of the weld on the use represented by the weld defect update information.

5. The method according to claim 4, characterized in that, The method further includes: The weld defect update information and the identification information of the target meter segment are uploaded to the weld defect information database; In response to a query event for weld defect information, obtain the identification information of the meter segment to be queried; Based on the identification information of the meter segment to be queried, the weld defect update information of the meter segment to be queried is retrieved from the weld defect information database.

6. A computer device comprising a memory and a processor, wherein the memory stores a computer program, characterized in that, When the processor executes the computer program, it implements the steps of the method according to any one of claims 1 to 5.

7. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by a processor, it implements the steps of the method according to any one of claims 1 to 5.

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