Welding joint penetration rate online detection method and system considering welding working condition

Abstract

The application discloses a kind of welding joint penetration rate on-line detection method and system considering welding working condition, mainly related to welding technical field. Including the following steps: install sensor on two electrodes to collect current signal and intrinsic process signal in real time;Establish the relationship diagram of signal change with time;According to current signal and intrinsic process signal, the relationship diagram is processed in sections, and signal characteristic quantity in the relationship diagram is extracted;According to welding working condition, different analytical model is selected to calculate nugget thickness and workpiece final thickness;Get the predicted value of penetration rate.The beneficial effects of the application are that it has the characteristics of low cost, strong timeliness and high measurement accuracy, and can be applied to welding production line.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of welding technology, in particular to a welding spot penetration rate online detection method and system considering welding working conditions. BACKGROUND

[0002] More than 90% of the welding work of the all-steel body is completed by the resistance spot welding process. The principle of resistance spot welding is to apply a large current of several hundred to several ten thousand amperes between two electrodes and the workpiece to be welded, and to make the workpiece interface melt and generate a welding spot through the combined action of pressure and Joule heat. Generally speaking, the penetration rate cannot be too small or too large. If the penetration rate is too small, the welding quality will not be sufficient to support the stable connection of the welded part, and if the penetration rate is too large, the material of the workpiece to be welded will become soft, and even spatter will occur during welding, affecting the quality of welding. The traditional penetration rate detection method mainly relies on manual sampling and metallographic experiments. This method is destructive and can only detect a part of the welding spots, so the detection structure is not comprehensive and reliable. In addition, this method needs to go through steps such as cutting, grinding, polishing and etching, which takes a long time and cannot achieve real-time detection. SUMMARY

[0003] The purpose of the present application is to provide a welding spot penetration rate online detection method and system considering welding working conditions, which has the characteristics of low cost, strong timeliness and high accuracy, and can be applied to the welding production line.

[0004] To achieve the above-mentioned purpose, the present application realizes the following technical solutions:

[0005] A welding spot penetration rate online detection method considering welding working conditions, comprising the following steps: installing sensors on two electrodes to collect current signals and intrinsic process signals in real time; establishing a relationship diagram of the current signals and the intrinsic process signals changing with time; segmenting the relationship diagram according to the current signals and the intrinsic process signals, and extracting signal characteristic quantities in the relationship diagram; selecting different analytical models according to the welding working conditions to calculate the nugget thickness and the final thickness of the workpiece; and calculating the penetration rate.

[0006] Preferably, the analytical model is a parameterized model constructed based on basic functions, including: a workpiece welding zone diameter analytical model, a nugget volume analytical model and an indentation depth analytical model.

[0007] Preferably, the workpiece welding zone diameter analytical model is:

[0008]

[0009] wherein: D S is the predicted value of the workpiece welding zone diameter, R B is the dynamic resistance signal value at the end of the welding current, d Eis the distance from the center of the welding nugget to the edge of the workpiece, H is the total thickness of the workpiece to be welded, and p is the resistivity of the workpiece to be welded.

[0010] The nugget volume analysis model is:

[0011]

[0012] wherein V N is the predicted value of the nugget volume, AS BC is the dynamic electrode displacement signal change value from the welding current end time to the dynamic electrode displacement signal inflection point occurrence time, l M is the initial gap size between the two plates of the workpiece under the gap working condition, H is the total thickness of the workpiece to be welded, a is the thermal expansion coefficient of the workpiece to be welded, and T m is the melting point of the workpiece to be welded.

[0013] The indentation depth analysis model is:

[0014] D I = AS AD / cosθ

[0015] wherein D I is the predicted value of the indentation depth, AS AD is the dynamic electrode displacement signal change value from the welding current conduction time to the electrode opening time, and θ is the included angle between the normal line of the workpiece to be welded and the electrode and the axis.

[0016] Preferably, the calculation formula of the nugget thickness is:

[0017] P N = V N / D S

[0018] wherein P N is the nugget thickness, V N is the nugget volume, and D S is the predicted value of the workpiece welding area diameter.

[0019] The calculation formula of the final thickness of the workpiece is:

[0020] h S = H-D I

[0021] wherein h S is the final thickness of the workpiece, H is the total thickness of the workpiece to be welded, and D I is the indentation depth.

[0022] The calculation formula of the welding penetration rate is:

[0023] λ = P N / hS

[0024] wherein: λ is the weld penetration rate.

[0025] Preferably, the intrinsic process signals are dynamic resistance signals and dynamic electrode displacement signals, the welding working conditions include: standard working condition, margin working condition, gap working condition and electrode tilt working condition, the signal characteristic quantities include: dynamic resistance signal value at the end of welding current, dynamic electrode displacement signal change value from the end of welding current to the occurrence of dynamic electrode displacement signal inflection point, dynamic electrode displacement signal change value from the turn-on of welding current to the opening of electrode.

[0026] Preferably, the dynamic electrode displacement signal inflection point is obtained by comparing the differential of the dynamic electrode displacement signal with a preset threshold value.

[0027] Preferably, the segmented processing is to divide the relationship diagram into multiple stages according to different time points based on the current signal and the dynamic electrode displacement signal.

[0028] Preferably, the different time points include: the turn-on of welding current, the end of welding current, the occurrence of dynamic electrode displacement inflection point and the opening of electrode, and the multiple stages include: pre-welding pre-pressing stage, power-on welding stage, pre-pressure early stage and post-pressure late stage.

[0029] Preferably, the pre-welding pre-pressing stage refers to the stage of closing and clamping the workpiece to be welded until the welding current signal is turned on, the power-on welding stage refers to the stage from the turn-on of welding current signal to the turn-off, the pre-pressure early stage refers to the stage from the turn-off of welding current signal to the occurrence of dynamic electrode displacement signal inflection point, and the post-pressure late stage refers to the stage from the occurrence of dynamic electrode displacement signal inflection point to the opening of electrode.

[0030] A weld penetration rate online detection system considering welding working conditions, comprising: a calculation and analysis module, a current signal acquisition module and an intrinsic process signal acquisition module, the current signal acquisition module is connected with a current sensor arranged at two electrodes and acquires current signals, two input ends of the intrinsic process signal acquisition module are respectively connected with displacement signal sensors arranged at two electrodes and acquire upper electrode displacement signals and lower electrode displacement signals in the welding process, the calculation and analysis module calculates two intrinsic process signals: dynamic resistance signals and dynamic electrode displacement signals according to the acquired signals, and calculates the value of the weld penetration rate according to the intrinsic process signals and the current signals.

[0031] Compared with the prior art, the present application has the following beneficial effects:

[0032] The method is based on a penetration rate calculation formula of an intrinsic process signal feature quantity of resistance spot welding, and can realize online quantitative evaluation and automatic detection of the spot welding nugget morphology, overcome the defects of traditional technologies relying on manual detection, has high detection precision, fast calculation speed, low requirement on a hardware system, and is suitable for various resistance spot welding application scenarios; by introducing various analytical models, influences of different welding conditions are considered, the method has strong applicability, when the welding condition deviates from a standard condition, the analytical model can be corrected by measuring the geometric state of the condition, so that the prediction accuracy of the penetration rate is ensured. BRIEF DESCRIPTION OF DRAWINGS

[0033] Figure 1 is a method flow of the present application.

[0034] Figure 2 is a system schematic diagram of the present application.

[0035] Figure 3 is a standard condition schematic diagram of the present application.

[0036] Figure 4 is a margin condition schematic diagram of the present application.

[0037] Figure 5 is a gap condition schematic diagram of the present application.

[0038] Figure 6 is an inclination condition schematic diagram of the present application.

[0039] Figure 7 is a local section schematic diagram of a welding spot.

[0040] Figure 8 is an evolution diagram of a spot welding process signal over time.

[0041] Figure 9 is a schematic diagram of a dynamic electrode displacement signal inflection point.

[0042] Figure 10 is a scatter diagram of a penetration rate prediction value and a penetration rate measured value under different welding conditions.

[0043] Reference signs shown in the drawings:

[0044] 1, calculation and analysis module; 2, intrinsic process signal acquisition module; 3, current signal acquisition module; 4, current sensor; 5, displacement signal sensor; 6, voltage signal sensor; 7, workpiece; 8, electrode; 9, welding spot nugget; 10, gasket. DETAILED DESCRIPTION

[0045] The present invention will be further illustrated below with reference to specific embodiments. It should be understood that these embodiments are for illustrative purposes only and are not intended to limit the scope of the invention. Furthermore, it should be understood that after reading the teachings of this invention, those skilled in the art can make various alterations or modifications to the invention, and these equivalent forms also fall within the scope defined in this application.

[0046] Example 1: An online detection method and system for weld penetration considering welding conditions

[0047] This example relates to an online measurement method for weld penetration considering welding conditions, such as... Figure 1 As shown, firstly, sensors are installed on the two electrodes to collect current signals and intrinsic process signals in real time; then, a relationship graph of the current signals and intrinsic process signals changing with time is established based on the collected current signals and intrinsic process signals; the relationship graph is segmented based on the current signals and intrinsic process signals to extract signal feature quantities from the relationship graph; next, different analytical models are selected according to different welding conditions to calculate the weld nugget thickness and the final thickness of the workpiece; finally, the penetration rate is calculated based on the weld nugget thickness and the final thickness under the working conditions.

[0048] like Figure 2 As shown, this embodiment illustrates an online weld penetration prediction system considering welding conditions. It mainly includes: a calculation and analysis module, an intrinsic process signal acquisition module, and a current signal acquisition module connected to these modules. The current signal acquisition module is connected to a current sensor mounted on the lower electrode and acquires the current signal I. Two input terminals of the intrinsic process signal acquisition module are connected to displacement signal sensors mounted on the two electrodes to acquire the upper electrode displacement signal S1 and the lower electrode displacement signal S2 during the welding process, respectively. The other two input terminals of the intrinsic process signal acquisition module are connected to voltage signal sensors mounted on the two electrodes to acquire the voltage signal U between the two electrodes. The calculation and analysis module calculates two intrinsic process signals based on the acquired current signal, voltage signal, and electrode displacement signal: a dynamic resistance signal and a dynamic electrode displacement signal. It then calculates the predicted weld penetration rate based on the intrinsic process signal and the current signal.

[0049] The upper electrode, the upper electrode displacement signal sensor, and the upper electrode voltage signal sensor are sequentially disposed on the upper surface of the workpiece, and the lower electrode, the lower electrode displacement signal sensor, and the lower electrode voltage signal sensor are sequentially disposed on the lower surface of the workpiece.

[0050] The current sensor is a Rogowski coil; both the upper electrode voltage signal sensor and the lower electrode voltage signal sensor are isolated probes; both the upper electrode displacement signal sensor and the lower electrode displacement signal sensor are grating ruler displacement sensors.

[0051] The workpiece is a two-piece metal plate stacked together, which can be made of steel, aluminum alloy, copper alloy, magnesium alloy, titanium alloy, and combinations thereof.

[0052] The computing and analyzing module comprises a microprocessor, an industrial computer, a PLC, a monitor, a welding controller, a desktop computer, a notebook computer, a server, or a workstation. In this embodiment, a monitor is used.

[0053] As shown in Figure 3 , the welding condition of this embodiment is a standard condition, and the welding nugget is located at the center of the workpiece. Both the upper electrode and the lower electrode are perpendicular to the workpiece.

[0054] As shown in Figure 7 , the welding point cross-section after welding is shown in the figure, in which the welding nugget is located between the two metal plates, and the welding penetration rate refers to the ratio of the thickness P N of the welding nugget to the final thickness h S of the workpiece, which reflects the penetration state of the welding point and is an important indicator for evaluating the quality of the welding point.

[0055] As shown in Figure 8 , the calculation of the intrinsic process signal is to divide the current signal I by the voltage signal U between the two electrodes to obtain the dynamic resistance signal R of the spot welding process; and subtract the upper electrode displacement signal S1 from the lower electrode displacement signal S2 to obtain the dynamic electrode displacement signal S of the spot welding process.

[0056] The relationship diagram segmentation processing refers to dividing the relationship diagram into four stages by using the current signal I and the dynamic electrode displacement signal S, which are: the pre-welding pre-pressing stage T1, the power-on welding stage T2, the pre-pressure stage T3, and the post-pressure stage T4. The pre-welding pre-pressing stage T1 refers to the stage of closing and clamping the workpiece by the electrodes until the welding current signal I is turned on. The power-on welding stage T2 refers to the stage from the turning on of the welding current signal I to the turning off. After the welding current signal I is turned off, the electrodes are opened to enter the pressure maintaining stage, which can be further divided into the pre-pressure stage T3 and the post-pressure stage T4. The pre-pressure stage T3 refers to the stage from the turning off of the welding current signal I to the inflection point S C of the dynamic electrode displacement signal S. The post-pressure stage T4 refers to the stage from the inflection point S C of the dynamic electrode displacement signal S to the opening of the electrodes.

[0057] As shown in Figure 9 , the inflection point S C of the dynamic electrode displacement signal S is obtained by comparing the differential of the dynamic electrode displacement signal S with a preset threshold value, which specifically includes: during the pressure maintaining stage, when the differential of the dynamic electrode displacement signal S with respect to time is equal to the preset threshold value A, that is, the threshold level line intersects with the point J sthen the inflection point is determined to start, and point J s The corresponding time is recorded as the start time t j ; after the start of the inflection point, when the differential of the dynamic electrode displacement signal S is equal to the threshold value A again, i.e., intersects the threshold horizontal line at point K S , then the inflection point is determined to end, and K S The corresponding time is recorded as the end time t k ; the arithmetic mean of t j and t k is taken as the inflection point occurrence time t C , i.e., t C = (t j +t k ) / 2, and the dynamic electrode displacement signal S at t C is recorded as the inflection point displacement S C . In this embodiment, the threshold value A is set to 2 μm.

[0058] The signal feature extraction refers to recording the welding current signal I conduction time as t A , recording the dynamic electrode displacement signal S at t A as the conduction displacement S A ; recording the welding current signal I turn-off time as t B , recording the dynamic electrode displacement signal S at t B as the turn-off displacement S B , recording the dynamic resistance signal R at t B as the turn-off resistance R B ; recording the electrode opening time as t D , recording the dynamic electrode displacement signal t D at t D as the opening displacement S D ; recording the difference between the turn-off displacement S B and the inflection point displacement S C as the nugget feature ΔS BC , i.e., ΔS BC =S B -S C ; recording the difference between the conduction displacement S A and the opening displacement S D as the plate thickness feature ΔS AD , i.e., ΔS AD =S A -S D .

[0059] The welding spot key appearance features include: workpiece welding area diameter D S , nugget volume V N , and indentation depth D I , and D I = ΔS AD Wherein: H is the total thickness of the workpiece to be welded, p is the resistivity of the workpiece to be welded, a is the thermal expansion coefficient of the workpiece to be welded, T m is the melting point of the workpiece to be welded; in this embodiment, H = 1.6 mm, p = 1.2 x 10-7Ωm, a = 1.1 x 10-5, T m = 1520℃. Under standard working conditions, the weld nugget thickness P N is P N = V N / D S , the final thickness of the workpiece h S is h S = H-D I , the weld penetration rate λ is λ = P N / h S .

[0060] As shown in Figure 10 (a), it is a scatter plot of the penetration rate prediction value and the penetration rate measured value in this embodiment, wherein the welding current is 4-9kA, the welding time is 150ms, and the pressure holding time is 550ms. As can be seen from the figure, under standard working conditions, the weld penetration rate prediction value and the penetration rate measured value have a good linear relationship, the determination coefficient is 0.988, the root mean square error is 0.172mm, the prediction accuracy is high; at the same time, the average calculation time of the predicted penetration rate is 0.05s, and the calculation speed is fast.

[0061] Embodiment 2: A weld penetration rate online detection method and system considering welding working conditions

[0062] Compared with embodiment 1, the welding working condition of this embodiment is the edge distance working condition, as shown in Figure 4 , that is, the weld deviates from the center of the workpiece to be welded during the welding process. Under the edge distance working condition, the analytical prediction model of the workpiece welding area diameter is:

[0063]

[0064] Wherein: D S is the predicted value of the workpiece welding area diameter, R B is the dynamic resistance signal value at the end of the welding current, d E is the distance between the center of the weld nugget and the edge of the workpiece, d E = 3mm in this embodiment, H is the total thickness of the workpiece to be welded, p is the resistivity of the workpiece to be welded.

[0065] As shown in Figure 10(b) is a scatter plot of the penetration rate prediction value and the penetration rate measured value in this embodiment. As can be seen from the figure, under the edge margin working condition, the penetration rate prediction value and the penetration rate measured value have a very strong linear relationship, the determination coefficient is 0.985, the root mean square error is 0.174 mm, and the prediction accuracy is high.

[0066] Embodiment 3: A welding spot penetration rate online detection method and system considering welding working conditions

[0067] Compared with embodiment 1, the welding working condition of this embodiment is a gap working condition, as shown in Figure 5 , that is, there is an initial gap between the two metal plates of the workpiece to be welded during the welding process. Under the gap working condition, the analytical prediction model of the nugget volume is:

[0068]

[0069] Wherein: V N is the prediction value of the nugget volume, ΔS BC is the dynamic electrode displacement signal change value from the end of the welding current to the occurrence time of the dynamic electrode displacement signal inflection point, l M is the initial gap size between the two plates of the workpiece under the gap working condition, which can be obtained by measuring the thickness of the insulating pad, and l M = 1 mm in this embodiment, H is the total thickness of the workpiece to be welded, a is the thermal expansion coefficient of the workpiece to be welded, and T m is the melting point of the workpiece to be welded.

[0070] As shown in Figure 10 (c), it is a scatter plot of the penetration rate prediction value and the penetration rate measured value in this embodiment. As can be seen, under the gap working condition, the penetration rate prediction value and the penetration rate measured value have a very strong linear correlation, the determination coefficient is 0.988, the root mean square error is 0.167, and the prediction accuracy is high.

[0071] Embodiment 4: A welding spot penetration rate online detection method and system considering welding working conditions

[0072] Compared with embodiment 1, the welding working condition of this embodiment is an inclined working condition, as shown in Figure 6 , that is, the workpiece to be welded is not perpendicular to the electrode. Under the inclined working condition, the analytical prediction model of the indentation depth is:

[0073] D I = ΔS AD / cosθ

[0074] Wherein: D I is the prediction value of the indentation depth, ΔS ADis the dynamic electrode displacement signal change value from the welding current on time to the electrode opening time, θ is the included angle between the normal line of the workpiece to be welded and the electrode and the axis, and θ = 3° in the embodiment.

[0075] As shown in Figure 10 (d) is a scatter plot of the penetration rate prediction value and the penetration rate measured value in the embodiment. It can be seen that under the inclined welding condition, the penetration rate prediction value of the welding spot has a strong linear correlation with the penetration rate measured value, the determination coefficient is 0.983, the root mean square error is 0.145, and the prediction accuracy is high.

Claims

1. A method for on-line detection of weld penetration rate considering welding conditions, characterized in that, It comprises the following steps: Real-time collection of current signals and intrinsic process signals on two electrodes; Establishment of a relationship diagram of current signals and intrinsic process signals over time; Segmented processing of the relationship diagram according to current signals and intrinsic process signals, and extraction of signal characteristic quantities in the relationship diagram; Calculation of workpiece welding zone diameter, nugget volume and indentation depth according to welding conditions using an analytical model; and calculation of nugget thickness and final thickness of the workpiece according to the workpiece welding zone diameter, nugget volume and indentation depth; Calculation of weld penetration rate; The analytical model is a parameterized model constructed on the basis of basic functions, comprising a workpiece welding zone diameter analytical model, a nugget volume analytical model and an indentation depth analytical model; The workpiece welding zone diameter analytical model is: ； wherein, is a predicted value of the diameter of the welding zone of the workpiece, is a dynamic resistance signal value at the end of the welding current, is the distance of the center of the weld nugget from the edge of the workpiece, is the total thickness of the workpiece being welded, is the resistivity of the workpiece to be welded; The nugget volume analytical model is: ； wherein, is a predicted value of the nugget volume, is a dynamic electrode displacement signal change value from the welding current ending time to the dynamic electrode displacement signal inflection point occurring time, is an initial gap size between the two plates of the workpiece under the gap working condition, is the total thickness of the workpiece to be welded, is the thermal expansion coefficient of the workpiece to be welded, is the melting point of the workpiece to be welded, The indentation depth analytical model is: ； wherein, is a predicted value of the indentation depth, is a dynamic electrode displacement signal change value from the welding current on time to the electrode opening time, is an included angle between the normal line of the workpiece to be welded and the electrode and the axis.

2. The method according to claim 1, wherein The calculation formula of the nugget thickness is: ； wherein, is the nugget thickness, is the nugget volume, is the predicted value of the workpiece weld zone diameter; The calculation formula of the final thickness of the workpiece is: ； wherein: is the final thickness of the workpiece, is the total thickness of the workpiece to be welded, is the indentation depth; The calculation formula of the weld penetration rate is: ； wherein: is the weld penetration rate.

3. The online detection method for weld penetration considering welding conditions according to claim 1, characterized in that, The intrinsic process signals are dynamic resistance signals and dynamic electrode displacement signals, the welding conditions comprise standard conditions, edge distance conditions, gap conditions and electrode inclination conditions, and the signal characteristic quantities comprise dynamic resistance signal values at the end of welding current, dynamic electrode displacement signal change values from the end of welding current to the occurrence of dynamic electrode displacement signal inflection points, and dynamic electrode displacement signal change values from the conduction of welding current to electrode opening.

4. The method according to claim 3, wherein the welding conditions are considered. The dynamic electrode displacement signal inflection point is obtained by comparing the differential of the dynamic electrode displacement signal with a preset threshold value.

5. The method according to claim 4, wherein the welding conditions are considered. The segmented processing is to divide the relationship diagram into multiple stages according to different time points of current signals and dynamic electrode displacement signals.

6. The method according to claim 5, wherein the welding conditions are considered. The different time points comprise the conduction of welding current, the end of welding current, the occurrence of dynamic electrode displacement inflection points and electrode opening, and the multiple stages comprise a pre-welding pre-pressing stage, an electrically welded stage, a pre-pressure stage and a post-pressure stage.

7. The method according to claim 6, wherein the welding conditions are considered. The pre-welding pre-pressing stage refers to the stage of closing and clamping the workpiece to be welded by the electrode until the conduction of the welding current signal, the electrically welded stage refers to the stage from the conduction to the shutdown of the welding current signal, the pre-pressure stage refers to the stage from the shutdown of the welding current signal to the occurrence of the dynamic electrode displacement signal inflection point, and the post-pressure stage refers to the stage from the occurrence of the dynamic electrode displacement signal inflection point to the opening of the electrode.

8. A system for on-line detection of weld penetration considering welding conditions for realizing a method for on-line detection of weld penetration considering welding conditions according to claim 1, characterized in that, It comprises: A calculation and analysis module, a current signal acquisition module and an intrinsic process signal acquisition module, the current signal acquisition module is connected with a current sensor arranged at two electrodes and acquires current signals, two input ends of the intrinsic process signal acquisition module are respectively connected with displacement signal sensors arranged at two electrodes and acquire upper electrode displacement signals and lower electrode displacement signals in the welding process, and the calculation and analysis module calculates two intrinsic process signals, dynamic resistance signals and dynamic electrode displacement signals according to the acquired signals, and calculates the value of the weld penetration rate according to the intrinsic process signals and the current signals.

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