A welding quality monitoring system for a sodium salt battery housing structural member

Abstract

The application discloses a welding quality monitoring system for a sodium salt battery shell structure member, relates to the technical field of welding quality monitoring, and comprises an acquisition module, a analysis module, and the like. The acquisition module is used for acquiring heat input data from an arc starting point to a current welding position in a tailing stage of shell sealing welding and synchronously recording a welding seam position corresponding to each heat input. The analysis module is used for performing waveform analysis on the heat input data, extracting a heat input change waveform of the tailing stage, comparing each heat input with a preset standard heat input, and obtaining a heat input deviation of each welding seam position. The application can establish a corresponding relationship between data and positions in the acquisition stage, avoids analysis deviation caused by independent data and positions in a traditional monitoring mode, and provides more reliable data basis for subsequent defect identification and positioning.

Description

Technical Field

[0001] This invention belongs to the field of welding quality monitoring technology, specifically a welding quality monitoring system for sodium salt battery casing structural components. Background Technology

[0002] Sodium salt battery casings are mostly made of metal, making them highly susceptible to defects such as sudden changes in heat input, uneven molten pool shrinkage, crater depressions, and internal microcracks during the final stages of casing sealing welding. Traditional welding quality monitoring relies heavily on current and voltage waveforms, visual inspection, or post-weld destructive testing. These methods struggle to quantify the correlation between heat input and weld location in real time during the final stages, and also fail to establish a stable correlation between heat input waveform morphology and stress concentration locations.

[0003] While some monitoring solutions can collect thermal input data, they only perform simple threshold judgments and do not conduct specialized waveform classification and defect prediction for the final stage. Furthermore, they cannot automatically determine the post-processing location and energy based on the waveform type. Since the sealing weld directly affects the casing's sealing performance and structural strength, if stress concentration areas are not post-processed in a timely and accurate manner, failure and leakage are highly likely to occur under high-temperature cycling conditions. Existing systems are insufficient to meet the high-reliability welding quality control requirements of sodium-ion battery casings. Summary of the Invention

[0004] The purpose of this invention is to provide a welding quality monitoring system for sodium salt battery casing structural components, in order to solve the problems mentioned in the background art.

[0005] A welding quality monitoring system for sodium salt battery casing structural components, comprising:

[0006] The acquisition module is used to acquire heat input data from the arc starting point to the current welding position during the final stage of shell sealing welding, and synchronously record the weld position corresponding to each heat input.

[0007] The analysis module is used to perform waveform analysis on the heat input data, extract the heat input change waveform in the final stage, and compare each heat input with the preset standard heat input to obtain the heat input deviation at each weld position.

[0008] The determination module is used to compare the heat input change waveform with a variety of preset waveform templates based on the correspondence between the waveform shape and the stress concentration location obtained by statistical analysis of the high-temperature failure location of welded test pieces with different waveform shapes, and to determine the heat input waveform type of the current finishing stage.

[0009] The position determination module is used to determine the number of weld positions that need to be post-processed based on the heat input waveform type, and to determine each weld position that needs to be post-processed based on the change of heat input deviation with weld position.

[0010] The post-processing module is used to generate post-processing energy according to the heat input waveform type and each weld location that requires post-processing, and to apply the post-processing energy to each weld location.

[0011] Using the above-mentioned scheme, fluctuations in welding heat input during the final stage of sealing the sodium-ion battery casing directly affect the stress distribution of the weld under high-temperature service conditions. However, existing detection methods struggle to predict such delayed failures during the welding process. This application addresses this issue by acquiring the heat input and corresponding weld location in real time during the final stage using an acquisition module. An analysis module performs waveform analysis and compares the waveform with a standard heat input to obtain the heat input deviation. A determination module identifies the current heat input waveform type based on the correspondence between pre-generated waveform shapes and stress concentration locations. A location determination module then determines the weld location requiring post-processing. Finally, a post-processing module generates post-processing energy and applies it to the corresponding location. This implementation shifts welding quality control from post-weld inspection to the welding process, intervening before stress concentration points arise due to abnormal heat input, thereby reducing the risk of casing leakage in sodium-ion batteries operating at high temperatures.

[0012] In some possible implementations, the correspondence between waveform shape and stress concentration location is pre-summarized through the following steps:

[0013] Multiple sodium salt battery casing test pieces from the same batch were selected, and a preset periodic oscillating current was applied to each of them at the end stage, so that a recognizable time mark was left in the waveform of heat input change.

[0014] For each test piece after leaving a time mark, the waveform of heat input change of the test piece is recorded during the welding process, and the weld position is matched with the heat input waveform by the time mark after welding is completed;

[0015] The test piece was placed in the working temperature environment of the sodium salt battery for high-temperature aging test, and the acoustic emission signal of the weld area was monitored at the same time. When the acoustic emission signal changed abruptly, it was determined that failure and leakage had occurred, and the time mark corresponding to the time of failure and leakage was recorded.

[0016] Based on the time stamp of the failure and leakage occurrence, the corresponding heat input waveform segment and weld location are determined, and the direct correspondence between the local features of the heat input waveform and the failure and leakage location is summarized.

[0017] This application applies a periodic oscillating current during the final stage of welding, leaving identifiable time markers on the thermal input waveform, thus mapping each point on the waveform to the physical location of the weld. Based on this, through high-temperature aging tests and acoustic emission signal monitoring, when a test piece experiences failure and leakage, the waveform segment corresponding to the failure location can be determined based on the time markers at that time, thereby summarizing the correspondence between local waveform features and the failure / leakage location. This implementation provides experimental data support for subsequent failure risk prediction, enabling a direct link between waveform analysis results and actual failure locations.

[0018] In some possible implementations, the direct correspondence between local features of the thermal input waveform and the location of the failure / leakage includes:

[0019] When the heat input waveform shows a monotonically increasing trend and the rate of increase gradually slows down in the final stage, the failure leakage location is located in front of the end point of the final stage, and the deviation distance of the failure leakage location is positively correlated with the area under the heat input waveform line.

[0020] When the heat input waveform suddenly changes during the final stage and the change amplitude exceeds the preset threshold, the failure leak location is located behind the change point, and the deviation distance of the failure leak location is positively correlated with the change amplitude and negatively correlated with the duration of the change.

[0021] When the heat input waveform fluctuates repeatedly at high and low levels during the final stage and the fluctuation amplitude exceeds the preset threshold, the failure leakage location is located at the low point of the fluctuation, and the shape of the leakage channel is negatively correlated with the fluctuation speed.

[0022] This embodiment of the invention transforms the morphological characteristics of the thermal input waveform into quantifiable criteria for determining the failure location, providing specific positioning rules for subsequent targeted post-processing.

[0023] In some possible implementations, the correspondence between the deviation distance of the failure leakage location and the area size, jump amplitude, jump duration, and fluctuation speed under the heat input waveform line is obtained through statistical analysis of existing data and corrected based on newly emerging failure leakage data.

[0024] Whenever new failure and leakage data is verified through a secondary high-temperature aging simulation test, the new failure and leakage data is used to correct the corresponding pattern.

[0025] Specifically, the effect of post-processing energy application is influenced by various factors, and simply relying on the initial rules for post-processing may not achieve the expected improvement. This application obtains actual quantitative data on the post-processing effect, including effectiveness and lifespan extension values, by setting a control group and conducting a second high-temperature aging simulation test. When these indicators are lower than preset thresholds, it indicates that there is a deviation in the current post-processing strategy or the corresponding rules it is based on. The system then adjusts the correspondence between waveform morphology and stress concentration location accordingly. This implementation method enables the system to self-correct based on the actual effect of post-processing, avoiding continuous inefficient repair due to rule deviations.

[0026] In some possible implementations, the post-processing module is also used for:

[0027] A control weld without post-treatment energy was selected from the same batch and subjected to a second high-temperature aging simulation test together with the weld after post-treatment energy was applied.

[0028] Record the failure and leakage location and failure and leakage time of the control weld, compare them with the failure and leakage location and failure and leakage time of the weld after applying post-treatment energy, and calculate the effectiveness and life extension value of the post-treatment energy.

[0029] When the efficiency is lower than a preset threshold or the lifespan extension is lower than a preset threshold, the correspondence between the waveform shape and the stress concentration location is adjusted.

[0030] In some possible implementations, the secondary high-temperature aging simulation test uses accelerated test conditions lower than the actual operating temperature of the sodium salt battery, reducing the test time to less than one-twentieth of the aging test time at the actual operating temperature.

[0031] The accelerated test conditions are determined based on the characteristics of the sodium salt battery casing material and the magnitude of the residual stress in the weld. The degree of acceleration is positively correlated with the magnitude of the residual stress.

[0032] This application employs accelerated testing conditions, conducting tests at temperatures below the actual operating temperature. The acceleration level is determined based on the shell material properties and the magnitude of residual stress in the welds, allowing welds with higher residual stress to receive a higher acceleration rate. This implementation significantly shortens the testing cycle while ensuring that the test results reflect actual failure trends, enabling feedback on post-processing effects and correction of patterns to be completed within a reasonable timeframe.

[0033] In some possible implementations, when the determining module compares the heat input change waveform with a variety of preset waveform templates, it adopts a multi-timescale comparison method, comparing the waveform at the original timescale, the compressed timescale, and the stretched timescale respectively.

[0034] The comparison results at the three scales are combined to obtain the overall matching degree. When the overall matching degree exceeds the preset threshold, the comparison is considered successful.

[0035] The scaling ratio of the compression time scale and the stretching time scale is determined based on the ratio of the actual welding speed to the standard welding speed during shell welding.

[0036] This application determines the scaling ratio of the compression and stretching time scales based on the ratio of the actual welding speed to the standard welding speed. The waveform under test is compared with the template waveform on the original scale, the compression scale, and the stretching scale, respectively, and the matching results of the three scales are combined for judgment. This implementation method can accommodate waveform distortion caused by welding speed fluctuations and improves the accuracy of waveform type identification.

[0037] In some possible implementations, the way the post-processing module applies the post-processing energy is selected based on the type of the thermal input waveform:

[0038] When the heat input waveform is monotonically increasing and the rate of increase gradually slows down, a continuous scanning method is adopted. The scanning path is to perform a reciprocating scan from the end point of the final stage to the first preset distance range in front. The scanning speed is negatively correlated with the size of the area under the heat input waveform line.

[0039] When the heat input waveform suddenly changes, a fixed-point pulse method is used, with the pulse application point located at the point of maximum heat input deviation, and the number of pulses is positively correlated with the change amplitude.

[0040] When the heat input waveform fluctuates repeatedly between high and low, a jump-point scanning method is adopted to apply the heat to each low point in sequence. The time interval between adjacent application points is positively correlated with the weld distance between adjacent low points.

[0041] This application selects differentiated post-processing energy application methods based on waveform type. For monotonically increasing waveforms, a continuous scanning method is used to release stress in wide-area stress zones; for waveforms with sudden jumps, a fixed-point pulse method is used to apply energy to concentrated stress points; and for waveforms with high and low fluctuations, multiple weak points are processed sequentially using a jump-point scanning method. Simultaneously, the processing parameters are correlated with the waveform's quantization characteristics, ensuring that the applied post-processing energy matches the severity of the failure risk.

[0042] In some possible implementations, when the thermal input waveform suddenly changes, the determining module also acquires the thermal input waveform shape within a first preset length after the change point;

[0043] If the heat input waveform after the jump point shows a downward trend, the failure leak location is located at the first distance after the jump point.

[0044] If the heat input waveform after the jump point shows a flat trend, the failure leakage location is located at the second distance after the jump point, and the second distance is greater than the first distance.

[0045] If the heat input waveform after the jump point shows an upward trend, the failure leak location is located at the third distance after the jump point, and the third distance is greater than the second distance.

[0046] In some possible implementations, the timing of applying continuous scanning, fixed-point pulses, or skip-point scanning is determined based on the temperature at the current weld location;

[0047] When the temperature at the weld location is higher than the first temperature threshold, the post-processing module applies post-processing energy;

[0048] When the temperature at the weld location is lower than the first temperature threshold, the post-processing module first preheats the weld location, and then applies post-processing energy after the temperature rises back above the first temperature threshold.

[0049] The preheating energy is less than the post-processing energy, and the preheating range is greater than the effective range of the post-processing energy.

[0050] Specifically, applying post-treatment energy directly when the weld temperature is low may cause localized overheating and generate new thermal stress, affecting the post-treatment effect. This application controls the timing of post-treatment energy application based on the temperature of the weld location. When the temperature is below a threshold, preheating is performed over a larger area with lower energy to allow the temperature of the area to be treated to rise gradually before applying the core post-treatment energy. This implementation uses temperature as a control parameter for the post-treatment process, ensuring that the post-treatment operation is performed under appropriate temperature conditions and avoiding the introduction of new problems due to improper temperature.

[0051] The technical solutions provided by the embodiments of this disclosure have at least the following beneficial effects:

[0052] This invention, by simultaneously acquiring thermal input data and weld location, can establish a correspondence between data and location during the acquisition stage, avoiding the analytical bias caused by the independence of data and location in traditional monitoring methods, and providing a more reliable data foundation for subsequent defect identification and location.

[0053] By employing a multi-timescale waveform comparison method, the waveform recognition process can be adapted to the speed changes that exist in the actual welding process, reducing the interference caused by the fluctuation of working conditions on the waveform recognition results, and making the waveform type judgment more consistent with the actual welding state.

[0054] This invention establishes corresponding failure location determination methods for different thermal input waveforms. In particular, for waveform abrupt changes, it comprehensively determines the failure location by combining the waveform change trend after the abrupt change point, making the defect location basis more complete and more in line with the actual failure generation process. Attached Figure Description

[0055] Figure 1 This is a schematic diagram of the system framework structure of the present invention. Detailed Implementation

[0056] The technical solution of the present invention will be clearly and completely described below with reference to the embodiments. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0057] Please see Figure 1 This application provides a welding quality monitoring system for sodium salt battery casing structural components, including an acquisition module, an analysis module, a determination module, a location determination module, and a post-processing module.

[0058] The acquisition module is used to acquire heat input data from the arc starting point to the current welding position during the final stage of shell sealing welding, and synchronously record the weld position corresponding to each heat input.

[0059] It should be noted that the final stage of the shell sealing weld is not a fixed range, but is defined according to the characteristics of the welding process. It is usually the last 10% to 15% of the total weld length, or the stage when the welding speed drops to less than 50% of the normal welding speed.

[0060] This interval was chosen because the stability of heat input during the final stage has the greatest impact on weld formation, and selecting the current interval can accurately cover the critical stages of molten pool shrinkage and crater formation.

[0061] In one implementation of this step, the heat input data is output in real time by the welding power source, in units of joules per millimeter, and the sampling frequency is set to no less than 100 Hz. This frequency can ensure that the minute fluctuations in heat input at the millisecond level are captured, avoiding the omission of key changes.

[0062] The weld position is obtained through a walking encoder or vision positioning device with a resolution of no less than 0.1 mm. This accuracy can achieve millimeter-level positioning of the weld position, meeting the targeting requirements of post-processing.

[0063] By adopting the above scheme, a one-to-one temporal position mapping relationship can be formed between each heat input data and the corresponding weld position, avoiding spatial misalignment that could lead to subsequent analysis deviations and ensuring that the data are synchronized in space and time.

[0064] The analysis module is used to perform waveform analysis on the heat input data, extract the heat input change waveform in the final stage, and compare each heat input with the preset standard heat input to obtain the heat input deviation at each weld position.

[0065] After the acquisition module completes data collection and synchronization, the analysis module needs to perform targeted processing on the raw data. The core purpose is to remove interference signals and highlight the trend of heat input changes, laying the foundation for subsequent waveform comparison and defect judgment.

[0066] Specifically, the waveform analysis process includes filtering and denoising, segmented normalization, and waveform smoothing.

[0067] In one implementation of this step, the median filtering algorithm is used for filtering and denoising, with the window size set to 5x5. This algorithm is chosen because it can effectively preserve the waveform trend while eliminating high-frequency noise caused by current fluctuations and mechanical jitter. Compared with mean filtering, it is more suitable for non-stationary hot input data.

[0068] Segmented normalization maps the heat input data in the final stage to the 0 to 1 interval. This process can eliminate the influence of the difference in heat input magnitude under different welding process parameters, which is convenient for subsequent unified comparison with standard waveform templates.

[0069] The preset standard heat input needs to be pre-calibrated based on the shell material thickness, welding wire type, and welding process parameters. For example, the standard heat input corresponding to a 1.5 mm thick aluminum alloy shell is 80 joules per millimeter. This is stored as a standard curve table for system use. The calibration process needs to be obtained through the statistical analysis of welding data from no less than 30 sets of qualified test pieces to ensure the representativeness of the standard value.

[0070] There are two ways to calculate the deviation of heat input: one is to calculate the absolute difference, that is, the deviation is equal to the measured heat input minus the standard heat input; the other is to calculate the relative percentage, that is, the relative deviation is equal to the measured heat input minus the standard heat input, divided by the standard heat input, and then multiplied by 100%. A positive deviation indicates that the heat input is too large, and a negative deviation indicates that the heat input is too small.

[0071] In this embodiment, relative percentage calculation is preferred, which can more intuitively reflect the degree of deviation. The preset relative deviation threshold is 15%, which is determined by statistically analyzing the deviation distribution of a large number of failed test pieces, and can effectively distinguish between normal fluctuations and abnormal deviations.

[0072] The determination module is used to compare the heat input waveform changes with multiple preset waveform templates based on the correspondence between waveform shapes and stress concentration locations obtained by statistical analysis of high-temperature failure locations of welded test pieces with different waveform shapes, and to determine the heat input waveform type for the current final stage.

[0073] It should be noted that the preset waveform templates include five categories: smooth descent template, stepped fluctuation template, abrupt peak template, abrupt depression template, and end-to-zero anomaly template. Each template is obtained through cluster analysis of waveforms from a large number of qualified and failed welds, and is stored in the system for comparison and matching.

[0074] After the analysis module obtains the waveform of heat input change and the deviation of heat input, it is necessary to further establish the correlation between waveform morphology and welding defect risk. This process is completed by the determination module.

[0075] It is understandable that the waveform shape is directly related to the stability of the welding process, which in turn affects the location of stress concentration. Therefore, it is necessary to establish the corresponding rules through a large number of experiments.

[0076] Based on the above requirements, the correspondence between waveform shape and stress concentration location is pre-summarized through the following experimental steps: Select multiple sodium salt battery casing test pieces from the same batch, with no less than 500 test pieces, and ensure that the material, thickness, and size of the test pieces are completely consistent with the actual mass-produced sodium salt battery casing. Apply a preset periodic oscillation current at the final stage, with the oscillation frequency set to 50 Hz, the current amplitude being 20% ​​of the welding reference current, and the oscillation duration being 0.5 seconds.

[0077] This parameter was chosen because it can form a clearly identifiable characteristic peak in the thermal input waveform, which can serve as a basis for time marker identification, without affecting normal welding formation.

[0078] For each test piece after leaving a time mark, welding is carried out using welding process parameters consistent with actual production. During the welding process, the heat input change waveform of the test piece is recorded in real time through the data acquisition interface of the welding power supply. The sampling frequency is kept consistent with the acquisition module at no less than 100 Hz to ensure data timing consistency.

[0079] After welding is completed, the position coordinates along the weld length direction and the time axis of the heat input waveform are established by using the characteristic peak positions marked by time. This achieves precise matching between the weld position and the heat input waveform, solving the problem of position and waveform disconnection in traditional methods.

[0080] The test piece was placed in the operating temperature environment of a sodium salt battery for high-temperature aging test. The operating temperature environment was set to 60 to 80 degrees Celsius, and the test duration was not less than 1000 hours. This environmental parameter simulates the actual working conditions of the battery to ensure the authenticity of the failure mode.

[0081] Simultaneously, an acoustic emission sensor is placed close to the weld area of ​​the test piece to monitor the acoustic emission signal in the weld area. The sampling frequency of the acoustic emission sensor is set to 1 MHz. When the amplitude of the acoustic emission signal exceeds the preset threshold of 100 dB and the duration exceeds 0.1 seconds, it is determined that a failure and leakage have occurred. This threshold is determined by comparing the difference in acoustic emission signals between leaking and non-leaking test pieces, and the false judgment rate is less than 5%.

[0082] By using the time synchronization function of the test system, the time marker corresponding to the time of failure and leakage is recorded. Based on the time marker of the time of failure and leakage, the established correspondence is queried in reverse to determine the heat input waveform segment corresponding to the time of failure and leakage, and at the same time, the physical location of the weld corresponding to the time marker is located.

[0083] By statistically analyzing the failure data of all test pieces, local features of the thermal input waveform corresponding to different failure locations are extracted, including parameters such as waveform slope, peak value, and fluctuation frequency. The direct correspondence between the local features of the thermal input waveform and the failure leakage location is summarized, forming a structured rule comparison table.

[0084] Furthermore, to achieve accurate quantitative prediction of defect locations, the direct correspondence between the aforementioned local features of the thermal input waveform and the failure / leakage location specifically includes:

[0085] When the heat input waveform shows a monotonically increasing trend and the rate of increase gradually slows down in the final stage, the failure leakage location is located within 5 to 15 millimeters in front of the end point of the final stage. The deviation distance between the failure leakage location and the end point is positively correlated with the area under the heat input waveform line. For every 10 joules increase in area, the deviation distance increases by 1 to 2 millimeters.

[0086] Specifically, the core basis of the pattern is that when the heat input increases monotonically and the rate of increase slows down, the uneven cooling rate of the molten pool is prone to stress concentration in front of the end. The larger the area, the more obvious the stress accumulation. Therefore, the deviation distance is positively correlated.

[0087] When the thermal input waveform suddenly changes, the determination module also obtains the thermal input waveform shape within a first preset length after the change point. If the thermal input waveform after the change point shows a downward trend, the failure leakage location is located at a first distance after the change point. If the thermal input waveform after the change point shows a flat trend, the failure leakage location is located at a second distance after the change point, and the second distance is greater than the first distance. If the thermal input waveform after the change point shows an upward trend, the failure leakage location is located at a third distance after the change point, and the third distance is greater than the second distance.

[0088] When the thermal input waveform suddenly changes during the final stage and the change amplitude exceeds 30% of the preset threshold, the failure location can be further subdivided by combining the waveform trend after the change point, which can further improve the positioning accuracy.

[0089] The deviation distance between the failure leak location and the jump point is positively correlated with the jump amplitude and negatively correlated with the jump duration. For every 10 percent increase in jump amplitude, the deviation distance increases by 0.8 to 1.2 mm, and for every 0.1 second increase in jump duration, the deviation distance decreases by 0.5 to 0.8 mm.

[0090] The reason for presenting this correspondence is to prevent sudden jumps from causing drastic changes in the local molten pool. This is because the larger the jump amplitude, the more severe the stress concentration, while the longer the jump duration, the easier it is for the molten pool to stabilize and the stress to be partially released. Therefore, the deviation distance and the duration are negatively correlated.

[0091] When the heat input waveform fluctuates repeatedly at high and low levels during the final stage and the fluctuation amplitude exceeds 20% of the preset threshold, the failure leakage location is located at the low point of the fluctuation, and the leakage channel width is negatively correlated with the fluctuation speed. For every 1 Hz increase in fluctuation frequency, the leakage channel width decreases by 0.1 to 0.2 mm. When the number of fluctuations exceeds 5, the leakage channel shows a continuous distribution state.

[0092] This is because insufficient heat input at the low point of fluctuation easily leads to weak areas with incomplete penetration or coarse grains. The slower the fluctuation, the more difficult it is for heat to spread evenly, and the larger the range of weak areas. Therefore, the width of the leakage channel is negatively correlated with the speed of fluctuation.

[0093] To ensure the long-term effectiveness and adaptability of the corresponding patterns, the aforementioned corresponding patterns are not fixed but are obtained through statistical analysis of existing failure data and need to be continuously corrected and optimized based on newly emerging failure and leakage data.

[0094] The secondary high-temperature aging simulation test adopts accelerated test conditions lower than the actual operating temperature of sodium salt batteries, which shortens the test time to less than one-twentieth of the aging test time at the actual operating temperature. The accelerated test conditions are determined together based on the characteristics of the sodium salt battery shell material and the magnitude of the residual stress in the weld. The degree of acceleration is positively correlated with the magnitude of the residual stress.

[0095] It should be noted that the temperature for the secondary high-temperature aging simulation test was set at 130 degrees Celsius, and the test duration was no less than 800 hours. The test environment adopted an adiabatic air environment similar to the actual working environment of sodium salt batteries. The acceleration rate was determined based on the thermal conductivity of the shell material and the residual stress amplitude of the weld. The greater the residual stress, the higher the acceleration rate, which can shorten the conventional test time to less than one-twentieth.

[0096] Specifically, whenever new failure leakage data is generated, a secondary high-temperature aging simulation test must be performed to verify the data. The temperature of the secondary test is set to 130 degrees Celsius, and the duration is no less than 800 hours. This parameter is chosen to balance verification efficiency and reliability. It is shorter than the initial 1,000-hour accelerated test, but longer than the aging time corresponding to the actual working life. This ensures that the data can reflect the failure characteristics after long-term use and guarantees the validity and reliability of the new data.

[0097] After the secondary high-temperature aging simulation test is passed, the new failure leakage data will be included in the statistical sample library, and the correlation coefficient and parameter range in the corresponding pattern will be recalculated. The original positive and negative correlations and numerical ranges will be dynamically corrected so that the corresponding pattern can be adapted to more welding conditions and failure scenarios. After correction, it needs to pass the comparative test of no less than 50 sets of test pieces to ensure that the error of the pattern is controlled within a reasonable range.

[0098] In one implementation of this step, based on the corresponding rules summarized and continuously revised above, the test piece is further subjected to a high-temperature accelerated aging test. The temperature is set to the sum of the upper limit of the sodium salt battery operating temperature and 50 degrees Celsius, i.e., 130 degrees Celsius, and the duration is not less than 1000 hours to verify the reliability of the corresponding rules.

[0099] Subsequently, the failed test pieces were dissected and analyzed. The stress concentration area of ​​the weld section was observed using a metallographic microscope. The stress concentration location and the corresponding heat input waveform of the welding process were statistically analyzed. When the probability of failure of the same waveform at the same weld location exceeds 80%, the correspondence between the two is established and stored in the system database. This probability threshold can ensure the stability and reliability of the correspondence.

[0100] When the module compares the heat input change waveform with multiple preset waveform templates, it adopts a multi-time scale comparison method, comparing the waveform at the original time scale, the compressed time scale, and the stretched time scale respectively. The comparison results at the three scales are combined to obtain the comprehensive matching degree. When the comprehensive matching degree exceeds the preset threshold, it is determined that the comparison is successful. The scaling ratio of the compressed time scale and the stretched time scale is determined according to the ratio of the actual welding speed during shell welding to the standard welding speed.

[0101] In one implementation, when the determination module performs multi-timescale comparison, it resamples the heat input change waveform using the original acquired waveform time axis, the time axis compressed according to the ratio of the actual welding speed to the standard welding speed, and the time axis stretched according to the same ratio. The waveforms at each of the three scales are then compared with a preset waveform template to calculate correlation coefficients. A weighted average of the three correlation coefficients is taken to obtain the overall matching degree. When the overall matching degree is greater than a preset threshold, the current waveform is determined to have successfully matched the template.

[0102] Specifically, the execution logic of multi-timescale comparison is as follows: First, the actual welding speed during shell welding is obtained and fed back in real time by the walking encoder. The ratio of this speed to the standard welding speed is calculated. Based on this ratio, the scaling ratio of compression and stretching is determined so that the waveform comparison can adapt to welding speed fluctuations.

[0103] At each time scale, the correlation coefficient method is used to calculate the matching degree between the current waveform and the template. The matching degrees of the original scale, the compressed scale, and the stretched scale are weighted and fused to obtain the comprehensive matching degree.

[0104] A preset comprehensive matching degree threshold is set. When the comprehensive matching degree exceeds this threshold, the waveform type is considered to have been successfully identified.

[0105] By adopting the above scheme, waveform time-domain distortion caused by changes in welding speed can be eliminated, thereby improving the accuracy and robustness of waveform recognition.

[0106] If no matching template is found, the system will trigger an alarm and record the waveform data for manual review to avoid missing defects due to unidentified waveforms.

[0107] The position determination module is used to determine the number of weld positions that need to be post-processed based on the type of heat input waveform, and to determine each weld position that needs to be post-processed based on the change of heat input deviation with weld position.

[0108] Once the module identifies the current thermal input waveform type, it can determine the range and specific location of post-processing. The design concept is to combine the risk level of the waveform type and the severity of the deviation to achieve precise selection of the post-processing location.

[0109] It should be noted that different heat input waveforms correspond to different heat flow distribution characteristics, which in turn lead to different stress concentration distribution patterns in the weld area. This is the physical basis for determining the number of post-processing locations in this invention. Specifically:

[0110] When the heat input waveform is monotonically increasing and the rate of increase gradually slows down, the heat flow continues to accumulate in the final stage, forming a continuous heat-affected zone along the weld direction. The corresponding stress concentration has a segmented distribution characteristic, so it is necessary to apply post-processing to the entire continuous area.

[0111] When the heat input waveform suddenly changes, the heat flow changes drastically at the point of change, forming a local thermal shock effect. The corresponding stress concentration has a point-like distribution characteristic. Therefore, it is only necessary to perform fixed-point post-processing near the point of change.

[0112] When the heat input waveform fluctuates repeatedly, the heat flow is insufficient at multiple low points, forming multiple discrete weak areas of thermal influence. The corresponding stress concentration has a multi-point distribution characteristic, so it is necessary to perform post-processing on multiple low point locations separately.

[0113] Based on the aforementioned physical laws, this invention adopts the following logical sequence: First, the distribution pattern of stress concentration is determined according to the waveform type, thereby predicting the number of areas requiring post-treatment; then, combined with the specific distribution of heat input deviation, the actual weld location requiring post-treatment is precisely located within the predicted area. This processing sequence conforms to the basic principles of welding thermodynamics, ensuring that the post-treatment strategy matches the physical nature of the defects.

[0114] Furthermore, different waveform types correspond to different stress concentration risks and defect distributions, therefore the number of post-processing locations needs to be set differently.

[0115] The steady-descent welding process is stable with low stress concentration risk, corresponding to 0 to 1 post-processing positions. The stepped fluctuation type has staged stress concentration, corresponding to 2 to 3 post-processing positions. The abrupt peak type and abrupt depression type are prone to local defects, corresponding to 3 to 5 post-processing positions. The end-to-zero abnormal type has high finishing quality risk, corresponding to 2 to 4 consecutive post-processing positions at the end. This number setting is based on the failure probability statistics of different waveform types, which can cover the risk area while avoiding over-processing.

[0116] The selection of post-processing locations needs to be combined with the thermal input deviation. The core rule is that for locations where the absolute value of the thermal input deviation exceeds the preset deviation threshold, the deviation interval of more than 3 consecutive points should be selected first. A single isolated deviation point is not included in the post-processing location because it is likely a measurement error. This rule can effectively eliminate accidental interference and improve the accuracy of selection.

[0117] The system first sorts the thermal input deviation of all weld positions from largest to smallest by absolute value, and then selects the top few positions as candidate post-processing positions according to the upper limit of the number corresponding to the current waveform type.

[0118] In another implementation, a secondary screening can be performed by combining the duration of the deviation. When the duration of the deviation exceeding the threshold is greater than 2 mm, the entire interval is included in the post-processing range to ensure complete coverage of the defect risk area and avoid risk omission due to segmented screening.

[0119] The post-processing module generates post-processing energy based on the heat input waveform type and each weld location requiring post-processing, and applies the post-processing energy to each weld location.

[0120] The post-processing module applies post-processing energy according to the type of heat input waveform. When the heat input waveform is monotonically increasing and the rate of increase gradually slows down, a continuous scanning method is used. The scanning path is a reciprocating scan from the end point of the final stage to the first preset distance range in front. The scanning speed is negatively correlated with the area under the heat input waveform line. When the heat input waveform suddenly jumps, a fixed-point pulse method is used. The pulse application point is located at the point of maximum heat input deviation. The number of pulses is positively correlated with the jump amplitude. When the heat input waveform fluctuates repeatedly, a jump-point scanning method is used, which applies energy to each low point in sequence. The interval between adjacent application points is positively correlated with the weld distance between adjacent low points.

[0121] The timing of continuous scanning, fixed-point pulse, or jump-point scanning is determined based on the temperature of the current weld position. When the temperature of the weld position is higher than the first temperature threshold, the post-processing module applies post-processing energy. When the temperature of the weld position is lower than the first temperature threshold, the post-processing module first preheats the weld position. After the temperature rises back above the first temperature threshold, the post-processing energy is applied. The preheating energy is less than the post-processing energy, and the preheating range is greater than the effective range of the post-processing energy.

[0122] It should be noted that the first temperature threshold is set based on the process characteristics of the shell material. The preheating energy is one-third to one-half of the post-treatment energy, and the preheating range is two to three times the effective range of the post-treatment energy. When the weld temperature is lower than the first temperature threshold, a large-scale, low-energy preheating is first used to allow the temperature to rise to a suitable range before performing the post-treatment.

[0123] After the location determination module locks the post-processing location, the post-processing module is needed to achieve accurate defect repair. The key lies in the reasonable matching and efficient application of post-processing energy.

[0124] It should be understood that precise matching of post-processing energy is the key to ensuring the effectiveness of defect repair, and the severity of the defect corresponding to the waveform type and the magnitude of the deviation must be taken into account.

[0125] Post-processing methods can include laser heating, high-frequency induction heating, or pulsed arc heating. In this embodiment, laser heating is used, with the laser wavelength set to 1064 nanometers. This wavelength of laser has a high absorption rate in metal materials and excellent heating efficiency. The spot diameter can be adjusted between 0.3 and 1.0 millimeters, which can adapt to defect areas of different sizes.

[0126] The system has a built-in energy mapping table that clearly defines the post-processing energy range corresponding to different waveform types and different deviation ranges. Small deviations in a steady decline type correspond to lower energy levels, while large deviations in abrupt depression type correspond to higher energy levels. The energy adjustment step size is set within a reasonable range to ensure the accuracy of energy fine-tuning. This mapping table has been verified through the post-processing effects of a large number of test pieces and can guarantee the stability of defect repair.

[0127] In this embodiment, if the current waveform type is a sudden spike, and the relative deviation of the heat input at a certain post-processing position is in a high range, the corresponding post-processing energy can be determined by querying the energy mapping table. This energy value can eliminate the stress concentration corresponding to this type of defect.

[0128] During the post-processing execution, the post-processing execution mechanism obtains the target weld position coordinates through a positioning device that is the same as the acquisition module. After moving to the corresponding position, it applies post-processing according to the set energy to ensure positioning consistency.

[0129] The weld temperature is monitored in real time during the application process. When the temperature exceeds the preset upper limit, the energy output is automatically reduced. This upper limit is determined based on the thermal stability of the shell material to avoid secondary damage caused by overheating.

[0130] After completing the post-processing of one location, the system records the processing parameters and feedback data, and then processes the remaining locations in sequence, ensuring that the entire post-processing process is traceable and controllable, which facilitates subsequent quality traceability and process optimization.

[0131] The post-processing module is also used to verify the post-processing effect through comparative experiments and dynamically adjust the corresponding rules according to the verification results. Specifically, it includes selecting control welds without post-processing energy from the same batch, with no less than 30 control welds, and their welding process parameters and weld position characteristics are completely consistent with those of the welds with post-processing energy applied, to ensure the fairness and effectiveness of the comparison.

[0132] Both were placed together in the corresponding environment for a second high-temperature aging simulation test. The test duration was consistent with the first accelerated aging test to ensure the comparability of failure data.

[0133] During the secondary high-temperature aging simulation test, the failure leakage location and failure leakage time of the control weld and the treated weld were monitored and recorded in real time using acoustic emission sensors. The failure judgment criteria were consistent with those mentioned above.

[0134] After the test, the failure data of the control weld and the treated weld were compared, and the efficiency and life extension value of the post-treatment energy were calculated. The efficiency is equal to the number of failures of the control weld minus the number of failures of the treated weld, then divided by the number of failures of the control weld, and multiplied by 100%. The life extension value is equal to the average failure time of the treated weld minus the average failure time of the control weld.

[0135] The system presets an efficiency threshold and a lifespan extension threshold. When the calculated efficiency or lifespan extension value is lower than the preset threshold, it determines that the current post-processing effect has not met expectations. At this time, the system automatically triggers the corresponding adjustment process, re-calls the data in the statistical sample library, and corrects the correspondence parameters between waveform morphology and stress concentration location, including the number of post-processing locations corresponding to various waveforms, deviation threshold, energy matching range, etc. After adjustment, it needs to be verified by a corresponding number of test pieces to ensure that the efficiency and lifespan extension values ​​meet the preset requirements.

[0136] This system synchronously collects thermal input data and weld location data, enabling the establishment of a correspondence between data and location during the data collection phase. This avoids the analytical bias caused by the independence of data and location in traditional monitoring methods, providing a more reliable data foundation for subsequent defect identification and location.

[0137] By employing a multi-timescale waveform comparison method, the waveform recognition process can be adapted to the speed changes that exist in the actual welding process, reducing the interference caused by the fluctuation of working conditions on the waveform recognition results, and making the waveform type judgment more consistent with the actual welding state.

[0138] This system establishes corresponding failure location judgment methods for different thermal input waveforms. In particular, for waveform abrupt changes, it comprehensively determines the failure location by combining the waveform change trend after the abrupt change point, making the defect location basis more complete and more in line with the actual failure generation process.

[0139] By adopting accelerated testing conditions that match the material properties and residual stress, the system can summarize and verify the rules while ensuring the consistency of the failure mechanism. At the same time, it can dynamically correct the judgment rules by combining new failure data, so that the system can adapt to the welding process under different working conditions and improve the overall applicability of the solution.

[0140] During post-processing, selecting the appropriate energy application method based on the heat input waveform type ensures that the post-processing action matches the defect characteristics, enhancing the targeted nature of stress relief and defect repair. Furthermore, rationally determining the timing of post-processing based on weld temperature and preheating when temperature conditions are unsuitable reduces the adverse effects of temperature on the post-processing effect, ensuring stable implementation of the post-processing process.

[0141] This system forms a complete closed loop from defect identification, location, post-processing to effect feedback by setting up comparison verification and feedback adjustment links. It can continuously optimize internal judgment rules and processing parameters based on actual processing results, so that the system can maintain a stable and reliable working state.

[0142] Through the coordinated efforts of each stage, this system can identify, locate, and repair defects during the final stage of sealing and welding, reducing the possibility of leakage at the casing weld during actual use and improving the sealing performance and reliability of the sodium salt battery casing weld structure.

[0143] The above description is merely a specific embodiment of this application, but the scope of protection of this application is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in this application should be included within the scope of protection of this application. Therefore, the scope of protection of this application should be determined by the scope of the claims.

Claims

1. A welding quality monitoring system for structural components of sodium salt battery casings, characterized in that, include: The acquisition module is used to acquire heat input data from the arc starting point to the current welding position during the final stage of shell sealing welding, and synchronously record the weld position corresponding to each heat input. The analysis module is used to perform waveform analysis on the heat input data, extract the heat input change waveform in the final stage, and compare each heat input with the preset standard heat input to obtain the heat input deviation at each weld position. The determination module is used to compare the heat input change waveform with a variety of preset waveform templates based on the correspondence between the waveform shape and the stress concentration location obtained by statistical analysis of the high-temperature failure location of welded test pieces with different waveform shapes, and to determine the heat input waveform type of the current finishing stage. The correspondence between waveform shape and stress concentration location is pre-summarized through the following steps: Multiple sodium salt battery casing test pieces from the same batch were selected, and a preset periodic oscillating current was applied at the end stage to leave a recognizable time mark in the heat input change waveform. For each test piece after leaving a time mark, the waveform of heat input change of the test piece is recorded during the welding process, and the weld position is matched with the heat input waveform by the time mark after welding is completed; The test piece was placed in the working temperature environment of the sodium salt battery for high-temperature aging test, and the acoustic emission signal of the weld area was monitored at the same time. When the acoustic emission signal changed abruptly, it was determined that failure and leakage had occurred, and the time mark corresponding to the time of failure and leakage was recorded. Based on the time stamp of the time when the failure and leakage occurred, the heat input waveform segment and weld location corresponding to the time when the failure and leakage occurred were determined, and the direct correspondence between the local features of the heat input waveform and the location of the failure and leakage was summarized. The position determination module is used to determine the number of weld positions that need to be post-processed based on the heat input waveform type, and to determine each weld position that needs to be post-processed based on the change of heat input deviation with weld position. The post-processing module is used to generate post-processing energy according to the heat input waveform type and each weld location that requires post-processing, and to apply the post-processing energy to each weld location.

2. The welding quality monitoring system for sodium salt battery casing structural components according to claim 1, characterized in that, The direct correspondence between local characteristics of thermal input waveforms and failure / leakage locations includes: When the heat input waveform shows a monotonically increasing trend and the rate of increase gradually slows down in the final stage, the failure leakage location is located in front of the end point of the final stage, and the deviation distance of the failure leakage location is positively correlated with the area under the heat input waveform line. When the heat input waveform suddenly changes during the final stage and the change amplitude exceeds the preset threshold, the failure leak location is located behind the change point, and the deviation distance of the failure leak location is positively correlated with the change amplitude and negatively correlated with the duration of the change. When the heat input waveform fluctuates repeatedly at high and low levels during the final stage and the fluctuation amplitude exceeds the preset threshold, the failure leakage location is located at the low point of the fluctuation, and the shape of the leakage channel is negatively correlated with the fluctuation speed.

3. The welding quality monitoring system for sodium salt battery casing structural components according to claim 2, characterized in that, The correspondence between the deviation distance of the failure and leakage location and the area under the heat input waveform line, the jump amplitude, the jump duration, and the fluctuation speed is obtained through statistical analysis of existing data and corrected based on newly emerging failure and leakage data. Whenever new failure and leakage data is verified through a secondary high-temperature aging simulation test, the new failure and leakage data is used to correct the corresponding pattern.

4. The welding quality monitoring system for sodium salt battery casing structural components according to claim 1, characterized in that, The post-processing module is also used for: A control weld without post-treatment energy was selected from the same batch and subjected to a second high-temperature aging simulation test together with the weld after post-treatment energy was applied. Record the failure and leakage location and failure and leakage time of the control weld, compare them with the failure and leakage location and failure and leakage time of the weld after applying post-treatment energy, and calculate the effectiveness and life extension value of the post-treatment energy. When the efficiency is lower than a preset threshold or the lifespan extension is lower than a preset threshold, the correspondence between the waveform shape and the stress concentration location is adjusted.

5. A welding quality monitoring system for sodium salt battery casing structural components according to claim 4, characterized in that, The secondary high-temperature aging simulation test adopts accelerated test conditions lower than the actual operating temperature of sodium salt batteries, which shortens the test time to less than one-twentieth of the aging test time at the actual operating temperature. The accelerated test conditions are determined based on the characteristics of the sodium salt battery casing material and the magnitude of the residual stress in the weld. The degree of acceleration is positively correlated with the magnitude of the residual stress.

6. The welding quality monitoring system for sodium salt battery casing structural components according to claim 1, characterized in that, When the determination module compares the heat input change waveform with multiple preset waveform templates, it adopts a multi-time scale comparison method, comparing the waveform at the original time scale, the compression time scale, and the stretching time scale respectively. The comparison results at the three scales are combined to obtain the overall matching degree. When the overall matching degree exceeds the preset threshold, the comparison is considered successful. The scaling ratio of the compression time scale and the stretching time scale is determined based on the ratio of the actual welding speed to the standard welding speed during shell welding.

7. The welding quality monitoring system for sodium salt battery casing structural components according to claim 1, characterized in that, The method by which the post-processing module applies post-processing energy is selected based on the type of the thermal input waveform: When the heat input waveform is monotonically increasing and the rate of increase gradually slows down, a continuous scanning method is adopted. The scanning path is to perform a reciprocating scan from the end point of the final stage to the first preset distance range in front. The scanning speed is negatively correlated with the size of the area under the heat input waveform line. When the heat input waveform suddenly changes, a fixed-point pulse method is used, with the pulse application point located at the point of maximum heat input deviation, and the number of pulses is positively correlated with the change amplitude. When the heat input waveform fluctuates repeatedly between high and low, a jump-point scanning method is adopted to apply the heat to each low point in sequence. The time interval between adjacent application points is positively correlated with the weld distance between adjacent low points.

8. A welding quality monitoring system for sodium salt battery casing structural components according to claim 2, characterized in that, When the thermal input waveform suddenly changes, the determination module also obtains the thermal input waveform shape within the first preset length after the change point; If the heat input waveform after the jump point shows a downward trend, the failure leak location is located at the first distance after the jump point. If the heat input waveform after the jump point shows a flat trend, the failure leakage location is located at the second distance after the jump point, and the second distance is greater than the first distance. If the heat input waveform after the jump point shows an upward trend, the failure leak location is located at the third distance after the jump point, and the third distance is greater than the second distance.

9. A welding quality monitoring system for sodium salt battery casing structural components according to claim 7, characterized in that, The timing for applying continuous scanning, fixed-point pulse, or skip-point scanning is determined based on the temperature of the current weld location; When the temperature at the weld location is higher than the first temperature threshold, the post-processing module applies post-processing energy; When the temperature at the weld location is lower than the first temperature threshold, the post-processing module first preheats the weld location, and then applies post-processing energy after the temperature rises back above the first temperature threshold. The preheating energy is less than the post-processing energy, and the preheating range is greater than the effective range of the post-processing energy.

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