Method and device for quickly screening and generating standard resistance curve of resistance spot welding

Abstract

The invention provides a resistance spot welding standard resistance curve rapid screening generation method and device, and relates to the field of steel plate resistance spot welding, and the method comprises the following steps: obtaining a resistance data set in a resistance spot welding process, and constructing an original resistance curve set according to the resistance data set, performing effective resistance curve screening on the original resistance curve set to obtain an effective resistance curve set; performing Kendall coefficient calculation and screening on effective resistance curves in the effective resistance curve set to obtain a first candidate resistance curve set; performing Pearson coefficient calculation and screening on effective resistance curves in the first candidate resistance curve set to obtain a second candidate resistance curve set; and according to the effective resistance curve in the second candidate resistance curve set, constructing a standard resistance curve through a median statistical algorithm.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of steel sheet resistance spot welding, in particular to a method and device for quickly screening and generating a standard resistance curve of resistance spot welding. BACKGROUND

[0002] With the development of the automobile industry towards lightweight and high-strength, resistance spot welding, as an efficient and reliable connection technology, is widely used in the assembly process of high-strength steel, ultra-high-strength steel and other vehicle body structural components. In the field of resistance spot welding quality control, the dynamic resistance curve gradually becomes an important basis for evaluating the stability of the welding process and the quality of the welding spot because it can reflect the physical changes in the welding spot formation process in real time. How to generate a representative "standard resistance curve" from a large amount of welding data is of great significance for realizing online evaluation and intelligent control of welding quality.

[0003] The current common standard curve generation method in the industry mainly relies on manual or semi-automatic data acquisition and curve screening. For example, some methods select "high-quality curves" by a large number of welding experiments combined with destructive or non-destructive detection means, and then construct a standard curve by mathematical fitting. This method not only has high cost and long cycle for data acquisition, but also relies on professional equipment and manual experience, which is difficult to meet the needs of modern manufacturing for efficiency and real-time performance. At the same time, due to the limited number of initial samples, the standard curve obtained has obvious deficiencies in representativeness and adaptability.

[0004] On the other hand, traditional methods mostly use fixed point features (such as resistance extreme value, curve inflection point, etc.) to construct fitting models, which are prone to fitting distortion and weak noise resistance in the face of actual production with severe curve fluctuations and complex interference signals. In addition, the screening process of the standard curve often lacks systematic consistency evaluation of both trend and amplitude, resulting in deviation of the final generated standard resistance curve from the actual working condition and affecting the judgment effect of the welding monitoring system. SUMMARY

[0005] To solve the above problems, the present application provides a method for quickly screening and generating a standard resistance curve of resistance spot welding, comprising the steps of: obtaining a set of resistance data in the resistance spot welding process, constructing a set of original resistance curves from the set of resistance data, screening the set of original resistance curves for effective resistance curves, and obtaining a set of effective resistance curves; calculating and screening the effective resistance curves in the set of effective resistance curves for Kendall coefficients to obtain a first set of candidate resistance curves; calculating and screening the effective resistance curves in the first set of candidate resistance curves for Pearson coefficients to obtain a second set of candidate resistance curves; According to the effective resistance curves in the second candidate resistance curve set, a standard resistance curve is constructed by a median statistical algorithm.

[0006] Optionally, the constructing of the original resistance curve set according to the resistance data set, the screening of the effective resistance curves on the original resistance curve set, and the obtaining of the effective resistance curve set specifically include: S11: constructing multiple original resistance curves in the resistance data set according to time sequence, and obtaining the original resistance curve set by all the original resistance curves; S12: selecting the i-th original resistance curve in the original resistance curve set, dividing the original resistance curve into multiple sub-curves according to a preset time interval, and calculating the slope and the differential slope of each sub-curve; if the product of the slope and the differential slope of a sub-curve is greater than a preset value, the i-th original resistance curve is removed; otherwise, the i-th original resistance curve is reserved as an effective resistance curve; S13: repeating step S12 until all the original resistance curves are traversed, and obtaining the effective resistance curve set by the reserved effective resistance curves.

[0007] Optionally, the calculating and screening of the Kendall coefficient on the effective resistance curves in the effective resistance curve set, and the obtaining of the first candidate resistance curve set specifically include: calculating the Kendall coefficient average between each effective resistance curve in the effective resistance curve set and the remaining effective resistance curves in turn, taking the effective resistance curve with the maximum Kendall coefficient average as a first trend reference curve, and setting a Kendall coefficient threshold according to the Kendall coefficient average of the first trend reference curve; calculating the Kendall coefficient between the first trend reference curve and the remaining effective resistance curves in turn, reserving the effective resistance curves with the Kendall coefficient greater than the Kendall coefficient threshold from the first trend reference curve, and obtaining the first candidate resistance curve set by the reserved effective resistance curves.

[0008] Optionally, the calculating and screening of the Pearson coefficient on the effective resistance curves in the first candidate resistance curve set, and the obtaining of the second candidate resistance curve set specifically include: calculating the Pearson coefficient average between each effective resistance curve in the first candidate resistance curve set and the remaining effective resistance curves in turn, taking the effective resistance curve with the maximum Pearson coefficient average as a second trend reference curve, and setting a Pearson coefficient threshold according to the Pearson coefficient average of the second trend reference curve; calculating the Pearson coefficient between the second trend reference curve and the remaining effective resistance curves in turn, reserving the effective resistance curves with the Pearson coefficient greater than the Pearson coefficient threshold from the second trend reference curve, and obtaining the second candidate resistance curve set by the reserved effective resistance curves.

[0009] Optionally, the standard resistance curve is constructed by a median statistical algorithm according to the effective resistance curves in the second candidate resistance curve set, and specifically comprises the following steps: S21: filtering each effective resistance curve in the second candidate resistance curve set by a filter to obtain each filtered effective resistance curve; S22: obtaining resistance data of each filtered effective resistance curve at the jth time point, calculating the resistance median at the jth time point according to each resistance data at the jth time point, and taking the resistance median at the jth time point as the resistance data of the standard resistance curve at the jth time point; S23: repeating step S22 until all time points are traversed, and constructing the standard resistance curve according to the resistance data of the standard resistance curve at all time points in chronological order.

[0010] Optionally: The standard resistance curve is repeatedly constructed multiple times through the resistance data set, the comprehensive score of each standard resistance curve is calculated, the Kendall coefficient threshold and the Pearson coefficient threshold of the standard resistance curve corresponding to the minimum comprehensive score are taken as the optimal Kendall coefficient threshold and the optimal Pearson coefficient threshold, and the final standard resistance curve is constructed through the resistance data set according to the optimal Kendall coefficient threshold and the optimal Pearson coefficient threshold.

[0011] Optionally, the calculation process of the comprehensive score specifically comprises: obtaining the current number N of the effective resistance curves in the second candidate resistance curve set corresponding to the standard resistance curve, setting a target number N0, and calculating a penalty function f(N) according to the current number N and the target number N0; calculating the fitting error average avg between the standard resistance curve and all effective resistance curves in the second candidate resistance curve set mse , and taking as the comprehensive score.

[0012] The application also provides a resistance spot welding standard resistance curve rapid screening and generating device for realizing the resistance spot welding standard resistance curve rapid screening and generating method. The effective resistance curve set acquisition module is configured to acquire a resistance data set in a resistance spot welding process, construct an original resistance curve set according to the resistance data set, and screen the original resistance curve set to obtain the effective resistance curve set. The first candidate resistance curve set acquisition module is configured to calculate and screen the Kendall coefficient of the effective resistance curves in the effective resistance curve set to obtain the first candidate resistance curve set. a second candidate resistance curve set acquisition module, configured to calculate and screen the effective resistance curves in the first candidate resistance curve set to obtain a second candidate resistance curve set; The standard resistance curve construction module is configured to construct a standard resistance curve by using a median statistical algorithm based on valid resistance curves in the second candidate resistance curve set.

[0013] The present invention also provides an electronic device comprising a memory, a processor and a computer program stored in the memory and runnable on the processor, wherein the processor implements the method for rapidly screening and generating standard resistance curves for resistance spot welding when executing the program.

[0014] The present invention also provides a non-transitory computer-readable storage medium having a computer program stored thereon. When the computer program is executed by a processor, the method for quickly screening and generating a standard resistance curve for resistance spot welding is implemented.

[0015] The present invention has the following beneficial effects: 1. The original resistance curve set constructed from the resistance data set was screened based on slope and differential slope to eliminate abnormal resistance curves with sudden slope changes and improve the stability of the effective resistance curve. A second screening was performed based on the Kendall coefficient of the effective resistance curve to ensure that the retained effective resistance curves maintained a high degree of consistency in their overall change trends. A third screening was performed based on the Pearson coefficient of the effective resistance curve to improve the linear correlation between the effective resistance curves. Based on the last retained effective resistance curve, a standard resistance curve was constructed using a median statistical algorithm. This process can automatically screen out high-precision standard resistance curves without manual screening. It has the advantages of efficiency, automation, and adaptability, and is suitable for the rapid construction of resistance spot welding standard curves for various vehicle models and materials. 2. Calculate the comprehensive scores of multiple sets of Kendall coefficient thresholds and Pearson coefficient thresholds, and use the Kendall coefficient threshold and Pearson coefficient threshold of the standard resistance curve corresponding to the minimum comprehensive score as the optimal Kendall coefficient threshold and optimal Pearson coefficient threshold. Based on the optimal Kendall coefficient threshold and optimal Pearson coefficient threshold, construct the final standard resistance curve through the resistance data set; through the comprehensive score, automatically optimize the multiple sets of Kendall coefficient thresholds and Pearson coefficient thresholds, eliminating the need for engineers to adjust parameters based on experience, thereby improving the accuracy of the standard resistance curve. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] Figure 1 This is a flow chart of a method according to an embodiment of the present invention; Figure 2 This is a structural diagram of an embodiment of the present invention; The purpose, features and advantages of the present invention will be further described with reference to the accompanying drawings and in conjunction with the embodiments. DETAILED DESCRIPTION

[0017] The following will be combined with the embodiments of this application to clearly and completely describe the technical solutions in the embodiments of this application. Obviously, the described embodiments are only part of the embodiments of this application, not all of the embodiments. Based on the embodiments of this application, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of this application.

[0018] Reference Figure 1 The present invention provides a method for quickly screening and generating a standard resistance curve for resistance spot welding, comprising the steps of: Obtaining a resistance data set during the resistance spot welding process, constructing an original resistance curve set based on the resistance data set, screening the original resistance curve set for effective resistance curves, and obtaining an effective resistance curve set; In some embodiments, constructing an original resistance curve set based on the resistance data set, screening the original resistance curve set for effective resistance curves, and obtaining an effective resistance curve set specifically includes: S11: constructing multiple original resistance curves from each resistance data in the resistance data set in chronological order, and forming an original resistance curve set from all the original resistance curves; In some embodiments, for example, if the power-on time is 240 ms and a resistance value is extracted every 1 ms, the length of the original resistance curve is 240 data points. S12: selecting the i-th original resistance curve in the original resistance curve set, dividing the original resistance curve into multiple sub-curves according to a preset time interval, and calculating the slope and differential slope of each sub-curve; if the product of the slope and the differential slope of any sub-curve is greater than a preset value, then discarding the i-th original resistance curve; otherwise, retaining the i-th original resistance curve as a valid resistance curve; In some embodiments, the original resistance curve is smoothed and four time points are selected to approximate the slope. Four points are selected because fewer time points cannot better reflect the changing trend of the slope and the data jitter has a greater impact. More time points will hide some detailed data. The slope is differentially calculated because the slope fluctuations of some feature points with smaller slope fluctuations are not significantly different from those of normal points. Therefore, the slope is calculated using the following formula.

[0019]

[0020] in, represents the slope at time t, The data with slope greater than or equal to 0 are set to 0; The product of the slope and the differential slope The expression is:

[0021] Wherein, is the differential slope, when the value of f(t) is greater than the preset value, it is determined that there is a sharp fluctuation or a splash feature of the abnormal resistance curve and is rejected; through this way, most of the original resistance curves with sudden slope change can be effectively removed, thereby improving the stability and representativeness of subsequent standard curve screening; S13: repeating step S12 until all original resistance curves are traversed, and the effective resistance curve set is composed of the retained effective resistance curves.

[0022] The Kendall coefficient of the effective resistance curves in the effective resistance curve set is calculated and screened to obtain a first candidate resistance curve set; In some embodiments, the Kendall coefficient of the effective resistance curves in the effective resistance curve set is calculated and screened to obtain a first candidate resistance curve set, specifically comprising: The Kendall coefficient average value between each effective resistance curve in the effective resistance curve set and the remaining effective resistance curves is calculated in sequence, the effective resistance curve with the largest Kendall coefficient average value is taken as the first trend reference curve, and the Kendall coefficient threshold is set according to the Kendall coefficient average value of the first trend reference curve; In some embodiments, the effective resistance curves in the effective resistance curve set are subjected to time alignment processing, the Kendall coefficient between each effective resistance curve and all the remaining effective resistance curves is calculated in sequence to quantify the consistency of each effective resistance curve in the rising and falling trend, and the Kendall coefficient average value between each effective resistance curve and the remaining effective resistance curves is calculated according to the calculated Kendall coefficient.

[0023] The Kendall coefficient is a non-parametric statistical index based on the ordering relationship of data, mainly used to measure the correlation between two ordered variables or the consistency between evaluators. Assuming that for curves x and y, x1=1, x2=2, y1=1, y2=2, the trend consistency of the curves is judged as consistent when both curves are rising at this stage, and the Kendall coefficient of the entire curve is calculated to reflect the consistency of the trend of the curve. The calculation formula of the Kendall coefficient is as follows:

[0024] Wherein, C represents (x i -x j ) and (y i -y j ​) same sign (same direction) logarithms, D represents the number of i < j when (x i -x j ) and (y i -y j ) different sign (opposite direction) logarithms, T x represents the number of x i =x j , T y represents the number of y i =y j ; Kendall coefficients between the first trend reference curve and the rest of the effective resistance curves are calculated in turn, and the effective resistance curves with Kendall coefficients greater than a Kendall coefficient threshold value are reserved, and a first candidate resistance curve set is formed by the reserved effective resistance curves.

[0025] In some embodiments, the Kendall coefficient average value of the first trend reference curve with two decimal places is taken as the Kendall coefficient threshold value, assuming that the Kendall coefficient average value of the first trend reference curve is 0.857, the Kendall coefficient threshold value is set to 0.85, and the effective resistance curves with Kendall coefficients greater than 0.85 are screened out, and a first candidate resistance curve set that maintains high consistency in the overall trend of change is constructed.

[0026] Pearson coefficients of the effective resistance curves in the first candidate resistance curve set are calculated and screened to obtain a second candidate resistance curve set. In some embodiments, the Pearson coefficients of the effective resistance curves in the first candidate resistance curve set are calculated and screened to obtain a second candidate resistance curve set, specifically including: Pearson coefficient average values between each effective resistance curve in the first candidate resistance curve set and the rest of the effective resistance curves are calculated in turn, and the effective resistance curve with the largest Pearson coefficient average value is taken as a second trend reference curve, and a Pearson coefficient threshold value is set according to the Pearson coefficient average value of the second trend reference curve. In some embodiments, the effective resistance curves in the first candidate resistance curve set are subjected to time alignment processing, Pearson coefficients between each effective resistance curve and all the rest of the effective resistance curves are calculated in turn to quantify the linear consistency in the resistance amplitude change process, and Pearson coefficient average values between each effective resistance curve and the rest of the effective resistance curves are calculated according to the calculated Pearson coefficients.

[0027] Pearson correlation coefficient is a core statistical measure of linear correlation between two continuous variables, when two curve trends are consistent, if the amplitude difference is large in a certain curve, for example, for curve x and y, x1=1, y1=1.1, x2=1, y2=2, the value of y at the first point is 1.1 times of x, but the value of y at the second point is twice of x, the linear consistency in the amplitude variation process will decrease, the value of Pearson correlation coefficient r will decrease, and by setting a suitable threshold, the effective resistance curve with poor linear correlation in the amplitude variation process can be removed, the calculation formula of Pearson correlation coefficient r is as follows:

[0028] Wherein, x i represents the i th value of curve x, y i represents the i th value of curve y, represents the average value of curve x, represents the average value of curve y; The Pearson correlation coefficient between the second trend reference curve and the remaining effective resistance curves is calculated in turn, and the effective resistance curves with the Pearson correlation coefficient greater than the Pearson correlation coefficient threshold are retained to form the second candidate resistance curve set.

[0029] In some embodiments, the average value of the Pearson correlation coefficient of the second trend reference curve with three decimal places is taken as the Pearson correlation coefficient threshold, assuming that the average value of the Pearson correlation coefficient of the second trend reference curve is 0.9903, the Pearson correlation coefficient threshold is set to 0.990, then the effective resistance curves with the Pearson correlation coefficient greater than 0.990 with the second trend reference curve are screened out, and the screened effective resistance curves form the second candidate resistance curve set.

[0030] According to the effective resistance curves in the second candidate resistance curve set, a standard resistance curve is constructed by median statistical algorithm.

[0031] In some embodiments, the standard resistance curve is constructed by median statistical algorithm according to the effective resistance curves in the second candidate resistance curve set, specifically including: S21: filtering each effective resistance curve in the second candidate resistance curve set by a filter to obtain each filtered effective resistance curve; In some embodiments, although the original resistance curve has been preliminarily smoothed to improve the accuracy of the slope and differential slope judgment, this processing is aimed at the feature extraction of a single curve and cannot directly replace the smoothness guarantee required by the global fitting for the generation of the standard resistance curve. Therefore, smoothing and filtering processing needs to be performed before the construction of the standard resistance curve, and through the smoothing and filtering of the effective resistance curve, the high-frequency disturbance during the fusion of the effective resistance curve can be effectively reduced, and the influence of the abnormal sharp point on the median operation process can be avoided.

[0032] The effective resistance curves in the second candidate resistance curve set are selected, and a first-order polynomial Savitzky-Golay filter with a window length of 5 and an order of 1 is used to realize signal smoothing and filtering, and high-frequency noise interference is eliminated. S22: Obtain the resistance data of each filtered effective resistance curve at the jth time point, calculate the resistance median at the jth time point according to the resistance data at the jth time point, and take the resistance median at the jth time point as the resistance data of the standard resistance curve at the jth time point. S23: Repeat step S22 until all time points are traversed, and construct the standard resistance curve according to the resistance data of the standard resistance curve at all time points in chronological order.

[0033] In some embodiments, the standard resistance curve is repeatedly constructed multiple times through the resistance data set, the comprehensive score of each standard resistance curve is calculated, the Kendall coefficient threshold and the Pearson coefficient threshold of the standard resistance curve corresponding to the minimum comprehensive score are taken as the optimal Kendall coefficient threshold and the optimal Pearson coefficient threshold, and the final standard resistance curve is constructed through the resistance data set according to the optimal Kendall coefficient threshold and the optimal Pearson coefficient threshold.

[0034] In some embodiments, a plurality of combinations of Kendall coefficient thresholds and Pearson coefficient thresholds are set, and the effective resistance curve screening, the standard resistance curve generation and the fitting error evaluation are respectively performed for each combination. Through the construction of a comprehensive score function combining the fitting error, the number of screened curves and the representative deviation, all combinations are evaluated and sorted, the threshold combination with the smallest score is selected, the smaller the score is, the better the Kendall coefficient threshold and the Pearson coefficient threshold are selected, and finally the complete process is re-executed with the threshold of the combination, and the final standard curve with high fitting accuracy and representativeness is output.

[0035] In some embodiments, the comprehensive score calculation process specifically includes: The current number N of the effective resistance curves in the second candidate resistance curve set corresponding to the standard resistance curve is obtained, a target number N0 is set, and a penalty function f(N) is calculated according to the current number N and the target number N0; Calculate the average value avg of the fitting error between the standard resistance curve and all valid resistance curves in the second candidate resistance curve set mse , the as a comprehensive score.

[0036] In some embodiments, the comprehensive score is constructed based on a Bayesian optimization algorithm, and the expression of the comprehensive score Score is as follows:

[0037]

[0038] Wherein, f(N) is a penalty function of the number of deviations from the target curve, |N-N0| represents the deviation between the current number N and the target number N0, the greater the deviation, the greater f(N), indicating the heavier the penalty; Assuming that the target number N0 is 100 and the current number N is 40, the value of the penalty function f(N) is 1.6; When the target number N0 is 100 and the current number N is 160, the value of the penalty function f(N) is also 1.6, but the small sample is easy to appear local optimum of the standard resistance curve, which leads to distortion of the curve and insufficient representation; Therefore, the is added to prevent the occurrence of extreme small samples. When the sample size is less than 100, the small sample will be punished again, so that the comprehensive score can more comprehensively control the balance between representation and quality.

[0039] Reference Figure 2 The application also provides a resistance spot welding standard resistance curve rapid screening and generating device 20 for realizing the resistance spot welding standard resistance curve rapid screening and generating method. The device comprises: An effective resistance curve set acquisition module 21 is configured to acquire a resistance data set in a resistance spot welding process, construct an original resistance curve set according to the resistance data set, perform screening of effective resistance curves on the original resistance curve set, and obtain an effective resistance curve set. A first candidate resistance curve set acquisition module 22 is configured to calculate and screen Kendall coefficients of the effective resistance curves in the effective resistance curve set, and obtain a first candidate resistance curve set. A second candidate resistance curve set acquisition module 23 is configured to calculate and screen Pearson coefficients of the effective resistance curves in the first candidate resistance curve set, and obtain a second candidate resistance curve set. A standard resistance curve construction module 24 is configured to construct a standard resistance curve by a median statistical algorithm according to the effective resistance curves in the second candidate resistance curve set.

[0040] The embodiment of the present application provides an electronic device, including a processor and a memory; the memory has a computer program stored therein, wherein the computer program implements the resistance spot welding standard resistance curve fast screening generation method of any one of the above solutions when executed by the processor.

[0041] Specifically, the processor may, for example, include a general microprocessor, an instruction set processor and / or a related chipset and / or a special microprocessor (for example, an application specific integrated circuit (ASIC)), etc. The processor may also include on-board memory for cache use. The processor may be a single processing unit for performing different actions of the method flow according to the embodiment of the present application or a plurality of processing units.

[0042] The memory may, for example, be any medium capable of containing, storing, communicating, propagating or transmitting instructions. For example, the memory may include but is not limited to electrical, magnetic, optical, electromagnetic, infrared or semiconductor systems, devices, devices or propagation media. Specific examples of the memory include: magnetic storage devices such as magnetic tapes or hard disk drives (HDD); optical storage devices such as compact discs (CD-ROM); also random access memory (RAM) or flash memory; and / or wired / wireless communication links.

[0043] The present application also provides a computer readable medium having a computer program stored thereon, which, when executed by a processor, implements the resistance spot welding standard resistance curve fast screening generation method of any one of the above solutions. The computer readable medium may be included in the device / apparatus / system described in the above embodiments; or may exist separately and not be assembled into the device / apparatus / system. The above computer readable medium carries one or more programs, which, when executed, implement the method as in the embodiment of the present application.

[0044] According to embodiments of the present application, the computer readable medium can be a computer readable signal medium or a computer readable storage medium or any combination thereof. The computer readable storage medium can be, for example but not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any suitable combination of the foregoing. More specific examples of the computer readable storage medium can include, but are not limited to, an electrical connection having one or more wires, a portable computer diskette, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or Flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing. In the present application, the computer readable storage medium can be any tangible medium that can contain or store a program for use by or in connection with an instruction execution system, apparatus, or device. In the present application, the computer readable signal medium can include a computer readable program code that can be transmitted or propagated over a computer readable medium, in baseband or as part of a carrier wave. Such a computer readable program code can take many forms, including but not limited to, an electromagnetic signal, an optical signal, or any suitable combination of the foregoing. The computer readable signal medium can also be any computer readable medium that can be transitory, propagating, or transmitting a program for use by or in connection with an instruction execution system, apparatus, or device. The program code contained on the computer readable medium can be transmitted or propagated using any suitable medium, including but not limited to wireless, wired, optical fiber cable, RF, and the like, or any suitable combination of the foregoing.

[0045] It is to be understood that the features recited in the various embodiments and / or claims of the present application can be combined and / or integrated in any number of ways, and that such combinations and / or integrations are specifically contemplated as falling within the scope of the present application. In particular, it will be apparent to those skilled in the art that the features recited in the various embodiments and / or claims of the present application can be combined and / or integrated in a number of ways, and that such combinations and / or integrations are specifically contemplated as falling within the scope of the present application. All such combinations and / or integrations are specifically contemplated as falling within the scope of the present application. The scope of the present application should therefore not be determined solely by reference to the above description but should also be determined with reference to the appended claims, along with the full scope of equivalents to which such claims are entitled. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application shall fall within the scope of the present application.

Claims

1. A method for quickly screening and generating a standard resistance curve for resistance spot welding, characterized in that: Including steps: Obtaining a resistance data set during the resistance spot welding process, constructing an original resistance curve set based on the resistance data set, screening the original resistance curve set for effective resistance curves, and obtaining an effective resistance curve set; Calculating and screening the Kendall coefficients of the effective resistance curves in the effective resistance curve set to obtain a first candidate resistance curve set; Calculating and screening the effective resistance curves in the first candidate resistance curve set by Pearson coefficients to obtain a second candidate resistance curve set; A standard resistance curve is constructed based on the valid resistance curves in the second candidate resistance curve set using a median statistical algorithm.

2. The method for rapidly screening and generating a standard resistance curve for resistance spot welding according to claim 1, wherein: The step of constructing an original resistance curve set according to the resistance data set and screening the original resistance curve set for effective resistance curves to obtain an effective resistance curve set specifically includes: S11: constructing multiple original resistance curves from each resistance data in the resistance data set in chronological order, and forming an original resistance curve set from all the original resistance curves; S12: selecting the i-th original resistance curve in the original resistance curve set, dividing the original resistance curve into multiple sub-curves according to a preset time interval, and calculating the slope and differential slope of each sub-curve; if the product of the slope and the differential slope of any sub-curve is greater than a preset value, then discarding the i-th original resistance curve; otherwise, retaining the i-th original resistance curve as a valid resistance curve; S13: Repeat step S12 until all original resistance curves are traversed, and the retained effective resistance curves form an effective resistance curve set.

3. The method for rapidly screening and generating a standard resistance curve for resistance spot welding according to claim 1, wherein: The calculating and screening of Kendall coefficients for the effective resistance curves in the effective resistance curve set to obtain a first candidate resistance curve set specifically includes: The average Kendall coefficient between each effective resistance curve and the remaining effective resistance curves in the effective resistance curve set is calculated in sequence, the effective resistance curve with the largest average Kendall coefficient is used as the first trend reference curve, and the Kendall coefficient threshold is set according to the average Kendall coefficient of the first trend reference curve; The Kendall coefficients between the first trend reference curve and the remaining effective resistance curves are calculated in sequence, and effective resistance curves whose Kendall coefficients with the first trend reference curve are greater than a Kendall coefficient threshold are retained. The retained effective resistance curves constitute a first candidate resistance curve set.

4. The method for rapidly screening and generating a standard resistance curve for resistance spot welding according to claim 1, wherein: The calculating and screening of the Pearson coefficients of the effective resistance curves in the first candidate resistance curve set to obtain the second candidate resistance curve set specifically includes: sequentially calculating an average Pearson coefficient between each effective resistance curve and the remaining effective resistance curves in the first candidate resistance curve set, taking the effective resistance curve with the largest average Pearson coefficient as the second trend reference curve, and setting a Pearson coefficient threshold according to the average Pearson coefficient of the second trend reference curve; The Pearson coefficients between the second trend reference curve and the remaining effective resistance curves are calculated in sequence, and effective resistance curves whose Pearson coefficients with the second trend reference curve are greater than a Pearson coefficient threshold are retained. The retained effective resistance curves constitute a second candidate resistance curve set.

5. The method for rapidly screening and generating a standard resistance curve for resistance spot welding according to claim 1, wherein: The step of constructing a standard resistance curve using a median statistical algorithm based on valid resistance curves in the second candidate resistance curve set specifically includes: S21: filtering each effective resistance curve in the second candidate resistance curve set through a filter to obtain each filtered effective resistance curve; S22: Obtain resistance data of each filtered effective resistance curve at the jth time point, calculate the median resistance at the jth time point based on each resistance data at the jth time point, and use the median resistance at the jth time point as the resistance data of the standard resistance curve at the jth time point; S23: Repeat step S22 until all time points are traversed, and construct a standard resistance curve in chronological order based on the resistance data of the standard resistance curve at all time points.

6. The method for rapidly screening and generating a standard resistance curve for resistance spot welding according to claim 1, wherein: The standard resistance curves are repeatedly constructed multiple times through the resistance data set, and the comprehensive scores of each standard resistance curve are calculated. The Kendall coefficient threshold and the Pearson coefficient threshold of the standard resistance curve corresponding to the minimum comprehensive score are used as the optimal Kendall coefficient threshold and the optimal Pearson coefficient threshold; according to the optimal Kendall coefficient threshold and the optimal Pearson coefficient threshold, the final standard resistance curve is constructed through the resistance data set.

7. The method for rapidly screening and generating a standard resistance curve for resistance spot welding according to claim 6, wherein: The calculation process of the comprehensive score specifically includes: Obtain the current number N of valid resistance curves in the second candidate resistance curve set corresponding to the standard resistance curve, set a target number N0, and calculate a penalty function f(N) based on the current number N and the target number N0; Calculate the average fitting error avg between the standard resistance curve and all valid resistance curves in the second candidate resistance curve set mse ,Will As a comprehensive rating.

8. A device for quickly screening and generating a standard resistance curve for resistance spot welding, used to implement the method for quickly screening and generating a standard resistance curve for resistance spot welding according to any one of claims 1 to 7, characterized in that: The device comprises: An effective resistance curve set acquisition module is used to acquire a resistance data set during the resistance spot welding process, construct an original resistance curve set based on the resistance data set, and screen the original resistance curve set for effective resistance curves to obtain an effective resistance curve set; a first candidate resistance curve set acquisition module, configured to calculate and screen the Kendall coefficients of the effective resistance curves in the effective resistance curve set to obtain the first candidate resistance curve set; a second candidate resistance curve set acquisition module, configured to calculate and screen the effective resistance curves in the first candidate resistance curve set to obtain a second candidate resistance curve set; The standard resistance curve construction module is configured to construct a standard resistance curve by using a median statistical algorithm based on valid resistance curves in the second candidate resistance curve set.

9. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein: When the processor executes the program, the method for quickly screening and generating a standard resistance curve for resistance spot welding according to any one of claims 1 to 7 is implemented.

10. A non-transitory computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the method for quickly screening and generating a standard resistance curve for resistance spot welding according to any one of claims 1 to 7 is implemented.

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