Hot riveting welding head synchronous temperature control method and system based on temperature change rate

Abstract

The invention relates to the technical field of welding, in particular to a hot riveting welding head synchronous temperature control method and system based on the temperature change rate, and the method comprises the steps: executing full-power heating pulse triggering operation on a welding head, calculating the pulse duration according to a start timestamp and an end timestamp, calculating the temperature rise, and eliminating peak noise through a digital filtering algorithm; environment temperature and relative humidity are collected in real time, and equivalent heat capacity is calculated; the initial temperature difference between any welding heads is calculated, and a dynamic target temperature curve is constructed; and calculating an actual temperature change rate, synchronously extracting a target change rate of the dynamic target curve at a corresponding moment, calculating a change rate deviation between the two change rates, judging whether intervention adjustment is needed or not, calculating an output signal by using an incremental PID algorithm if intervention adjustment is needed, and adjusting the heating power according to the output signal. According to the scheme, the stability of the hot riveting welding quality is effectively improved by accurately quantifying the thermal characteristics of the heterogeneous welding head, dynamically planning a personalized temperature rising track and performing high-frequency closed-loop regulation and control.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of welding, in particular to a hot riveting welding head synchronous temperature control method and system based on temperature change rate. BACKGROUND

[0002] In the hot riveting welding production scene, electric vehicle welding production lines often need to mix different brands and models of hot riveting welding heads to meet diversified process requirements, but these welding heads have significant heterogeneity problems, mainly manifested as equivalent heat capacity difference of more than 300%. Since the heat capacity directly determines the heat storage capacity and temperature rise characteristics of the welding head, the temperature rise rate and thermal response time of the heterogeneous welding head under the same heating condition differ greatly, making it extremely difficult to synchronize the temperature rise.

[0003] Traditional temperature control methods mostly use a unified heating curve without considering the individual characteristic differences of the welding heads, which can easily cause some welding heads to rise too quickly, resulting in overshooting, and some welding heads to rise too slowly, failing to synchronize to the standard. At the same time, the welding head working environment is complex, with fluctuations in environmental temperature and humidity, differences in heat dissipation conditions at different positions (such as different heat dissipation efficiencies in areas close to fans and closed areas), electromagnetic interference, equipment vibration, and other factors, which can introduce temperature measurement noise and temperature rise calculation bias, further reducing the temperature control accuracy.

[0004] In addition, existing systems lack real-time quantitative modeling capability for the thermal characteristics of the welding heads, cannot dynamically adapt to the heat capacity drift phenomenon after long-term use of the welding heads, and rely on fixed PID parameters for temperature control adjustment, with a lag response to temperature difference deviation, making it difficult to achieve high-precision synchronization of welding head temperature difference ±2℃ within a short time window of 0.5-3 seconds, which seriously affects the product welding quality stability and production line production efficiency. SUMMARY

[0005] The present application effectively improves the hot riveting welding quality stability by accurately quantifying the thermal characteristics of heterogeneous welding heads, dynamically planning individualized temperature rise trajectories, and high-frequency closed-loop regulation.

[0006] The technical solution proposed by the present application is: a hot riveting welding head synchronous temperature control method based on temperature change rate, the method comprising: Performing a full-power heating pulse trigger operation independently for each welding head to be synchronized, recording the start and end time stamps, calculating the pulse duration according to the start and end time stamps, calculating the temperature rise according to the initial temperature at the start of the pulse and the real-time temperature at the end of the pulse, correcting the actual temperature rise by combining the position coefficient and the position of each welding head, and removing spike noise through a digital filtering algorithm; Real-time acquisition of environmental temperature and relative humidity, calculation of the equivalent heat capacity of each welding head based on the actual temperature rise and pulse duration; The initial temperature difference between any welding head is calculated by using the initial temperature of the welding head, the welding head is classified according to the initial temperature difference, the welding head with the maximum equivalent heat capacity is selected as the reference channel, and the global reference rate is calculated by combining the heat coupling coefficient matrix, a welding head thermodynamic model is established by COMSOL, and a dynamic target temperature curve is constructed; The actual temperature change rate of each welding head is collected, the target change rate of the dynamic target curve at the corresponding moment is extracted synchronously, the change rate deviation is calculated, and it is judged whether intervention adjustment is needed according to the change rate deviation. If intervention adjustment is needed, the PID controller coefficient is dynamically adjusted according to the absolute value of the deviation, the output signal is calculated by using the incremental PID algorithm, and the heating power is adjusted according to the output signal.

[0007] Preferably, the specific process of the actual temperature rise correction is as follows: The average temperature in the preset initial temperature sampling duration before the start of the pulse is obtained as the initial temperature, and the instantaneous temperature in the preset end temperature sampling duration after the end of the pulse is obtained as the end temperature, the difference between the two is calculated to obtain the original temperature rise; for the marked suspected noise points, a digital filtering algorithm is used for filtering to obtain the filtered original temperature rise; according to the position of the welding head, the heat dissipation level is divided, and the corresponding position coefficient is set for different heat dissipation level regions, the filtered original temperature rise is multiplied by the corresponding position coefficient to obtain the final actual temperature rise.

[0008] Preferably, the specific content of the digital filtering algorithm is as follows: The temperature sampling sequence is traversed, the temperature difference between adjacent sampling points is calculated, and when the temperature difference between adjacent sampling points exceeds the peak judgment threshold, the sampling point is marked as a suspected peak noise point; for the marked noise points, a data set is formed by extracting a plurality of normal sampling points before and after the noise points, and the median value is taken after sorting the window data to replace the noise points; the original value of the normal point not marked as noise is directly retained; for the edge points at the beginning and end of the sequence, if it is determined to be noise, the mean value of the unilateral effective data is used for correction; the temperature difference stability of the filtered sequence is calculated after correction, if all adjacent temperature differences are ≤peak judgment threshold, the filtering is effective, otherwise the window is expanded and repeated correction until the condition is met.

[0009] Preferably, the specific calculation process of the equivalent heat capacity is as follows: The equivalent heat capacity of the welding head is calculated by the heat conversion efficiency constant, the temperature rise, the power and the pulse duration; the heat conversion efficiency constant is corrected according to the ambient temperature and the relative humidity, and the equivalent heat capacity of the welding head is corrected according to the corrected heat conversion efficiency constant; the system automatically performs rapid calibration at the first start of each day, performs deep calibration according to the preset welding number interval, and updates the equivalent heat capacity parameter library.

[0010] Preferably, the specific process of obtaining the dynamic target temperature curve is as follows: After the thermal capacity identification is completed, a number of temperature data are continuously collected at a fixed frequency to obtain an average value as an initial temperature of each welding head, an initial temperature difference between any two welding heads is calculated, the welding heads are divided into a near-reference group and a far-reference group after a maximum initial temperature difference is determined; a welding head with the largest equivalent heat capacity is selected as a reference channel, a thermal coupling coefficient matrix is introduced, and a global reference temperature rise rate is calculated in combination with the full-power parameters of the reference channel; the dynamic target temperature curve includes a main temperature rise section and a buffer section, the main temperature rise section generates a target trajectory with the reference temperature rise rate as the slope, the main temperature rise time of the far-reference group welding heads with extreme temperature differences is extended, and the welding heads are automatically switched to the buffer section when the temperature of the welding heads approaches the target temperature; a thermodynamic model is established by COMSOL to predict the thermal coupling effect and optimize the buffer section parameters.

[0011] Preferably, the intervention adjustment judgment process is as follows: After the system enters the real-time control stage, the real-time temperature of each welding head is collected at a high-frequency sampling frequency, the noise is smoothed by using a moving average filter, the actual temperature change rate is calculated based on the temperature difference between two consecutive sampling time points, and the accuracy of the actual temperature change rate calculation is ensured to meet the requirements; the target change rate of the dynamic target temperature curve at the corresponding time point is extracted synchronously, the target value at any time point is obtained by using an interpolation algorithm; the deviation absolute value of the actual change rate and the target change rate is calculated in real time; when the deviation absolute value is ≤ a first deviation threshold, it is determined that the state is normal, and no intervention adjustment is required; when the deviation absolute value > the first deviation threshold, it is marked as a deviation anomaly, and a PID parameter real-time tuning mechanism is triggered to start the intervention adjustment; when the deviation absolute value > a second deviation threshold, an emergency adjustment mode is enabled.

[0012] Preferably, the output signal calculation process is as follows: When the deviation absolute value > a third deviation threshold, the proportional coefficient is increased and the integral coefficient is decreased to speed up the response; when the first deviation threshold < the deviation absolute value ≤ the third deviation threshold, the initial parameters are maintained; when the deviation absolute value ≤ the first deviation threshold, the proportional coefficient is decreased and the integral coefficient is increased to eliminate the steady-state error; when the deviation absolute value > an integral suspension threshold, the integral term is suspended, and only the proportional and differential adjustments are used to quickly suppress the deviation; an incremental PID algorithm is used to calculate a power adjustment increment signal, which is converted into a heating power instruction, and the power supply time of the welding head heating element is controlled by using a PWM pulse width modulation technique; the instantaneous deviations of a plurality of consecutive cycles are summed to calculate a cumulative error, when the cumulative error absolute value > the third deviation threshold, a power compensation amount is calculated by using a compensation coefficient and is superimposed on the PID output signal, and a single compensation amount ≤ 2% of the rated power; the final output signal needs to ensure that the power output is less than or equal to the upper limit of the rated power, and if the limit is exceeded, the upper limit is output and the deviation is recorded.

[0013] The application also provides a temperature synchronous control method of a hot riveting welding head based on a temperature change rate.

[0014] The application also provides a computer readable storage medium storing a computer program, wherein the computer program is executed by a processor to implement the temperature synchronous control method of the hot riveting welding head based on the temperature change rate.

[0015] The application has the following beneficial effects: 1. The equivalent heat capacity is accurately calculated by independently performing a standardized full-power heating pulse on each welding head to be synchronized, combined with digital filtering to remove spike noise, position coefficient correction of heat dissipation differences, and environmental parameter optimization of calibration constants. This process does not require preset power parameters of the welding head, and the thermal characteristic modeling of all heterogeneous welding heads (heat capacity difference > 300%) can be completed within 3 seconds. The automatic calibration mechanism after daily and 1000 times of welding further ensures the stability of the parameters, provides reliable basic data support for subsequent synchronous temperature control, and improves the accuracy of thermal characteristic modeling.

[0016] 2. Based on the initial temperature difference classification results and the equivalent heat capacity, the reference channel is selected to generate a personalized target curve including a main temperature rising segment and a buffer segment. The main temperature rising segment eliminates the initial temperature difference at a global reference rate, and the temperature rising time is extended for extreme temperature difference welding heads to ensure the chasing effect. The buffer segment is designed with a slope of 0.3-0.4 times the reference rate and optimized by COMSOL simulation, effectively suppressing temperature overshoot. This segmented dynamic adaptation strategy solves the problem that fixed curves cannot cope with the dispersion of welding head states, and achieves the synchronous temperature reaching target of ±2℃ within a 0.5-3 second time window, balancing the synchronization rate and overshoot risk.

[0017] 3. The temperature change rate is monitored in real time at a high frequency of 1kHz, the PID parameter dynamic setting is triggered by a deviation threshold, and the heating power is accurately adjusted by a cumulative error compensation algorithm to ensure that the actual temperature rising rate is consistent with the target curve. At the same time, the power upper limit (110% of the rated value), the temperature upper limit (target + 5℃), and the abnormal stop mechanism are set to analyze the root cause of the non-compliant welding head and push the repair suggestion. This closed-loop control mechanism not only reduces the temperature deviation from ±1.5℃ to ±0.8℃, but also significantly reduces the equipment failure rate through multiple safety constraints, improves the product qualification rate of the production line to more than 99%, ensures the temperature control accuracy, and enhances the safety and reliability of the system. BRIEF DESCRIPTION OF DRAWINGS

[0018] Figure 1 The flowchart of the temperature synchronous control method of the hot riveting welding head based on the temperature change rate of the application; Figure 2 The temperature control process flowchart of the temperature synchronous control method of the hot riveting welding head based on the temperature change rate of the application. DETAILED DESCRIPTION

[0019] The following description is presented to enable any person skilled in the art to practice the application as claimed. The preferred embodiments disclosed herein are only examples of the many possible embodiments of the application. Other possible embodiments of the application will be apparent to those skilled in the art from the description herein. The principles defined herein can be applied to other embodiments, variations, improvements, equivalents and other technical solutions without departing from the spirit and scope of the application.

[0020] It can be understood that the term "one" should be understood as "at least one" or "one or more", that is, in one embodiment, the number of one element can be one, and in another embodiment, the number of the element can be multiple, and the term "one" cannot be understood as a limitation on the number.

[0021] As shown in Figure 1 and Figure 2 , for different brands, unknown power hot riveting heads mixed in the production line (there are heterogeneous problems of thermal capacity difference > 300%), the system independently executes full-power heating pulse trigger operation for each to-be-synchronized welding head. The heating pulse length is strictly controlled within 150-250ms, preferably 200ms±10% (i.e. 180ms≤ ≤220ms). This parameter setting is based on two considerations: one is to ensure that the pulse length is sufficient to produce a measurable temperature change (to avoid too short to cause the temperature rise signal to be submerged by noise); the second is to avoid long-time heating affecting the initial temperature stability of the welding head (to prevent excessive heating from changing the subsequent temperature control reference state). The pulse is executed through a relay module, which outputs a full-power heating signal (voltage 220V±5%, current dynamically adjusted according to the welding head power), and the start timestamp and the end timestamp of the pulse are recorded synchronously through the relay module, and the time accuracy of the high-precision clock chip (accuracy ≤1μs) is ensured ≤1ms. A temperature and humidity sensor (sampling frequency 1Hz, accuracy ±1℃ / ±5%RH) is deployed synchronously to collect the ambient temperature and relative humidity RH in real time. The system triggers the heating pulse in turn according to the welding head device ID, and the interval between adjacent pulses is ≥5 seconds to avoid the influence of heat accumulation on the measurement accuracy, and the pulse execution state is fed back in real time through the indicator light and software log.

[0022] During the whole period of the heating pulse application, data acquisition is completed through the NTC temperature sensor (temperature measurement range -50℃-300℃, accuracy ±0.5℃, sampling frequency ≥1kHz) built in the welding head, including the stable initial temperature of the welding head before the pulse starts (Take the average temperature within 100ms before the pulse starts (preset initial temperature sampling time), calculated using the following formula:) ,in, For the pulse number The second sampling temperature (to ensure initial temperature stability) and the real-time temperature at the end of the pulse. (The instantaneous temperature value within 5ms after the pulse ends (preset end temperature sampling time) is captured, and the peak temperature is captured by hardware triggering to avoid the influence of thermal inertia.) Calculate the temperature rise. (Accurate to 0.1℃), spike noise is removed using a digital filtering algorithm.

[0023] During the application of the heating pulse, the data collected by the temperature sensor may be affected by electromagnetic interference, equipment vibration, etc., resulting in spike noise (manifested as instantaneous temperature jumps >5℃ and duration <10ms). This needs to be processed by a digital filtering algorithm to ensure the accuracy of the temperature rise calculation. An adaptive median filtering algorithm is adopted, which can both remove isolated spikes and retain the original temperature trend. The specific process is as follows: Traverse the temperature sampling sequence and calculate the temperature difference between adjacent sampling points: ; in: For the first One original temperature sample value (sampling frequency ≥ 1 kHz, i.e., sampling interval) ), For sampling point number ( This represents the total number of samples within the pulse period, with a 200ms pulse corresponding to... ).when ,mark The point shown is a suspected spike noise point; the rest are normal points. The threshold for determining the peak value. If the temperature difference between adjacent samples exceeds this value, it is judged as suspected spike noise.

[0024] For the marked suspected spike noise points, median filtering is used for correction. Data from one normal sampling point before and after the noise point are extracted to form a windowed dataset. Sort the window data to get Take the median. As the filtered value .

[0025] For normal points not marked as noise, retain the original values ​​directly. For the beginning and end edge points of the sequence ( or If it is determined to be noise, only one-sided valid data (e.g.) is used. Or take or (mean correction).

[0026] Calculate the temperature stability of the filtered sequence If all If the condition is met, the filtering is effective; otherwise, the median filtering correction is repeated (the window size can be expanded to 5 points) until the condition is met.

[0027] The filtered temperature sequence is directly used to calculate the initial temperature. ,make sure Unaffected by spike noise, accuracy is controlled within ±0.3℃. Real-time temperature at the end of the pulse. Temperature value taken from the end of the filtered pulse To ensure temperature rise Calculation error ±0.1℃. The algorithm execution time is ≤1ms, matching the sensor sampling frequency (1kHz), and does not affect the real-time performance of rapid heat capacity identification (modeling is completed within 3 seconds). This algorithm can eliminate over 98% of spike noise, reducing temperature data fluctuations from over ±2℃ before filtering to within ±0.5℃, providing reliable raw data support for equivalent heat capacity calculation and subsequent dynamic target curve generation.

[0028] To address the differences in heat dissipation conditions caused by the dispersed positions of the welding heads, a position coefficient is added. Calibration, and pre-classification of heat dissipation levels for each welding head location on the production line (e.g., areas near fans). enclosed area Other areas The actual temperature rise calculation was corrected to .Will The corresponding welding head's device ID and pulse duration The data is bound to storage to form a related dataset including welding head, pulse, and temperature rise, providing raw input for subsequent calculations and supporting subsequent traceability and analysis.

[0029] Based on the collected pulse parameters and temperature rise data, the equivalent heat capacity of each welding head is calculated using formulas, thereby quantifying the characteristics of the welding head with unknown parameters and providing basic parameters for subsequent temperature control. According to thermal principles, the heat absorbed by the welding head during the heating process... With temperature rise Equivalent heat capacity satisfy Due to the application of a fixed power and pulse duration Calories ( (where is the heat conversion efficiency constant), the simplified formula for calculating the equivalent heat capacity is: ; in, Equivalent heat capacity (unit: J / ℃, reflecting the welding head's ability to store heat; the larger the value, the slower the welding head heats up). The calibration constant (unit: J) is obtained through factory calibration of the same model welding head and is pre-stored in the system database. Different brands of welding heads correspond to different constants. Value, for example, brand A's Brand B By introducing an environmental parameter correction term, the optimization is as follows: ; in, , The reference temperature is 25℃. The calibration constant at that time.

[0030] After the calculation is completed, the system generates a unique identifier for each welding head. The parameters are associated with the device ID and stored in the parameter library, completing the heat capacity modeling of all welding heads within 3 seconds. The system automatically performs a "quick calibration" upon its first startup each day, and a "deep calibration" after every 1000 welding operations, updating the parameters accordingly. Parameter library. When If an anomaly is detected, pulse heating and data acquisition are automatically re-executed to ensure modeling accuracy. This parameter will directly serve as the core input for subsequent dynamic target curve generation steps, used to match the heating rate requirements of different welding heads and solve the problem of synchronous temperature control caused by differences in heat capacity.

[0031] This process achieves three core values ​​through a closed-loop workflow of pulse application, temperature rise measurement, and heat capacity calculation: First, it eliminates the need to obtain welding head power parameters in advance, solving the problem of adapting to heterogeneous equipment; second, it completes modeling within 3 seconds, meeting the needs of rapid production line changeovers; and third... The parameters are directly linked to the generation of the subsequent target curve, providing a quantitative basis for synchronous temperature control and realizing the logical connection between characteristic perception and parameter transmission.

[0032] After rapid heat capacity identification, the system first collects the initial temperature of all hot riveting welding heads involved in synchronous temperature control to clarify the differences in the initial state of each welding head, providing a basis for subsequent curve adaptation. Using the temperature sensor built into the welding head (accuracy ±0.5℃), 10 temperature data points are continuously collected at a frequency of 100Hz during the stabilization phase 3 seconds after heat capacity identification (a preset waiting time to ensure temperature stability) before formal heating. The average value is taken as the initial temperature of each welding head. ( Representing the (One welding head), the data acquisition process avoids periods of drastic ambient temperature fluctuations. Calculate the initial temperature difference between any two welding heads. Statistically plot the temperature difference distribution histogram and determine the maximum initial temperature difference. This is used to determine the dispersion of the initial state of the welding head, providing a reference for subsequent differentiated temperature control. The typical value should be ≤5℃; exceeding this triggers preheating leveling. Welding heads are divided into two different temperature difference levels: "near-reference group" (difference from the lowest initial temperature ≤3℃) and "far-reference group" (difference >3℃), providing a classification basis for subsequent curve adaptation. The data includes the welding head ID, A structured data table of temperature difference levels is used to develop a health status dashboard for heat capacity parameters. Abnormal welding heads are identified by color coding (e.g., red when the k value deviates from the threshold by ±15%). The initial temperature distribution is displayed through a visual interface, allowing operators to quickly determine the equipment status.

[0033] To ensure that multiple welding heads can reach the target temperature simultaneously, the welding head with the weakest heating capacity should be selected as the reference channel, and its heating rate should be used as the reference benchmark to avoid some welding heads being unable to keep up due to the reference being too high.

[0034] The heating capacity of a welding head is directly related to its equivalent heat capacity (inversely proportional; the larger the equivalent heat capacity, the slower the heating). Therefore, based on the equivalent heat capacity... Screening for heat capacity The largest welding head is used as the reference channel (i.e., the welding head with the slowest heating, numbered). ),Right now The heating rate of the reference channel is used as the global reference rate. This rate is determined by the heat capacity characteristics of the reference channel, reflecting its natural temperature rise capability under full-power heating. The target curves for all subsequent welds are designed based on this rate. The calculation formula is as follows: For an array of n welding heads Introducing the thermal coupling coefficient matrix, it is optimized to ,in, The full-power heating power of the welding head (an inherent parameter of the equipment, obtained through factory calibration). For welding head Butt welding head The heat-affected ratio. As a global reference rate, it is stored in the control parameter library to provide core parameters for the subsequent generation of target curves, ensuring that all welding heads are designed with the reference rate as the basis for heating trajectory.

[0035] Based on the heating rate of the reference channel and the initial temperature difference of each welding head, a dynamic target temperature curve is generated for each welding head, including a "main heating section" and a "slope decreasing buffer section", to ensure synchronous temperature reaching and avoid overshoot.

[0036] This stage uses the heating rate of the reference channel. To unify the slope, all the welding heads are heated at the same rate. For the welding heads with lower initial temperature, this stage can reduce the temperature difference with other welding heads by continuous heating; for the welding heads with higher initial temperature, this stage reserves adjustment space for the subsequent buffer stage. The core function is to eliminate the synchronization obstacle caused by the initial temperature difference by unifying the rate.

[0037] When the temperature of the welding head approaches the target temperature (usually within 10℃ of the target temperature), it is automatically switched to the buffer stage. The heating rate of the buffer stage is adjusted to 0.3-0.4 times of the reference rate , which aims to reduce the heating inertia when approaching the target temperature, avoid overshooting caused by continuous high-speed heating, and ensure that the temperature converges smoothly to the target value. Through COMSOL, a thermodynamic model of the welding head is established to predict the thermal coupling effect and optimize the buffer stage parameters, and a dynamic target temperature curve is constructed.

[0038] According to the initial temperature difference of each welding head, the switching time of the main heating stage and the buffer stage is dynamically adjusted - the welding heads with lower initial temperature extend the main heating stage time to fully catch up, and the welding heads with higher initial temperature enter the buffer stage earlier to prevent overshooting, finally realizing that all the welding heads reach the target temperature (temperature difference ±2℃) within 0.5-3 seconds.

[0039] Each dynamic target temperature curve consists of two sections, and precise temperature control is achieved through dynamic switching. In the main heating stage, all the welding heads are pushed to synchronize the temperature rise at the reference rate, the initial temperature difference is reduced, and it is ensured that the slow heating does not be pulled away by the fast heating. The main heating stage trajectory formula is , where is the heating time (unit: s), is the target temperature of the th welding head at moment. For the "far reference group" welding heads, , the main heating stage time formula is optimized as . When the real-time temperature of the welding head , it is automatically switched to the buffer stage, where is the preset target temperature (20℃-280℃ adjustable), ℃ (the maximum value for high temperature stage, such as 280℃ target ℃). The buffer stage trajectory formula is , where is the triggering temperature, is the triggering time, (buffer stage slope). Reduce the heating inertia when approaching the target temperature, avoid overshooting, and ensure that the temperature converges smoothly. According to the initial temperature difference, the curve parameters are dynamically adjusted to realize individual temperature control. For the "far reference group" welding heads (initial temperature difference > 3℃), the main heating stage time is extended, and the calculation formula is , For the benchmark group, the main temperature rise time is ensured to be sufficient to catch up. For the "near-benchmark group" welding head (initial temperature difference ≤3°C), the buffer segment trigger time is calculated in advance to avoid premature deceleration and subsequent calls and comparisons. The system generates a visual target curve for each welding head, which is stored in the curve library and includes parameters such as target temperature at each time, segmented slope, switching time, and supports real-time calling and comparison.

[0040] This step realizes three breakthroughs through the logical chain of initial state perception, benchmark establishment, and trajectory generation: first, differential adaptation based on initial temperature difference solves the problem of fixed curve unable to cope with state dispersion; second, segmented slope design balances synchronous rate and overshoot risk; third, the output dynamic target curve directly serves as the reference benchmark for subsequent real-time control, realizing seamless connection from planning to execution, and providing precise trajectory guidance for synchronous temperature control.

[0041] After the dynamic target curve is generated, the system enters the real-time control phase, the primary task is to continuously monitor the actual temperature rise state of each welding head, and compare it with the preset change rate of the target curve to provide a basis for subsequent adjustment.

[0042] The real-time temperature of each welding head is obtained through high-frequency temperature sampling (sampling frequency ≥1kHz) , and a sliding average filter (window size 5) is used to smooth the noise. The actual temperature change rate is calculated based on the temperature difference between two consecutive sampling times , the formula is: ; Where, is the sampling interval (fixed at 1ms) to ensure that the change rate calculation accuracy is ±0.1°C / s. The temperature change acceleration is calculated in real time , which is used for thermal runaway warning.

[0043] The target change rate of the dynamic target curve at the corresponding time is extracted synchronously (the main temperature rise segment is the benchmark rate , and the buffer segment is (0.3 0.4 )), the target value at any time is obtained through interpolation algorithm. The change rate deviation of the two is calculated in real time: ; Real-time judgment is needed to determine whether to intervene and adjust, when (the first deviation threshold) is normal, otherwise it is marked as deviation abnormality, triggering the adjustment mechanism.

[0044] When the deviation between the actual temperature change rate and the target value exceeds the threshold, the system automatically starts the parameter setting mechanism to ensure temperature control accuracy.​

[0045] When , the PID parameter real-time tuning is triggered to achieve precise adjustment of heating power, quickly correct deviation, and avoid deviation accumulation leading to synchronization failure. For extreme deviation scenarios ( (second deviation threshold), the emergency adjustment mode is enabled, temporarily relaxing the PID parameter range and limiting the single power adjustment amplitude ≤20%.

[0046] Incremental PID algorithm is adopted to control the output: ; Wherein, deviation value, proportional coefficient (initial value 3.0), (integral coefficient, initial value 0.5), (differential coefficient, initial value 1.0) are PID parameters. Integral separation strategy is introduced: when (integral pause threshold), the integral term is paused, and only proportional and differential adjustment is used to quickly suppress deviation.

[0047] The system dynamically adjusts the proportional coefficient , integral coefficient and differential coefficient of the PID controller based on the absolute value of the deviation, when (third deviation threshold, large deviation), increase (to 4.0), decrease (to 2.0) to speed up the response; when (moderate deviation), keep the initial parameters; when (small deviation), decrease (to 2.0), increase (to 0.8) to eliminate steady-state error. Parameter adjustment rules are pre-stored in the control algorithm library, supporting dynamic modification through the host computer.

[0048] The output signal after PID parameter tuning adjusts the heating power, so that the actual temperature change rate of each welding head matches the target curve, and finally realizes synchronization to temperature. The PID output signal after tuning Convert to heating power command (0-100% full power adjustable, through PWM pulse width modulation technology to control the power supply time of the welding head heating element, power resolution ≤1%, for example, output 50% command corresponds to half power operation of the heating element), control the output power of the welding head heating element through the power drive module, and correct the actual temperature rise rate in real time. Within a preset time window of 0.5-3 seconds, ensure that the deviation of the actual temperature of all welding heads from the target temperature is ≤±2℃, the temperature difference between any two welding heads is ≤±2℃, the temperature difference overshoot is ≤3℃, and the fall time is ≤0.5 seconds, meeting the requirements of thermal riveting process for temperature synchronization. The current power output is: ; When the temperature change acceleration and lasts for 3 cycles, the power is reduced by 20% in advance. To avoid power mutation causing system shock, set the upper limit of single power adjustment amplitude (≤10% rated power) and the upper and lower limits of output power (lower limit 5% rated power, upper limit 110% rated power). The adjustment command is sent to the actuator through a high-speed communication bus (response time ≤5ms) to ensure timely control.

[0049] The system performs monitoring, comparison and adjustment cycle operation every 10ms, and eliminates steady-state deviation through cumulative error compensation algorithm. The sum of instantaneous deviations for , i.e. 50ms, is: ; Select to balance response speed and noise resistance, and avoid single cycle data fluctuation affecting judgment. When (i.e. average deviation of 5 consecutive cycles >0.3℃ / s), start compensation adjustment to ensure that small deviations do not accumulate. The compensation coefficient is calibrated by experiment (indicating that the duty cycle of additional adjustment power required for every 1℃ / s of cumulative deviation). The compensation power increment , positive corresponds to power increase, and negative corresponds to power decrease. Add the compensation amount to the PID adjustment result to get the final power output , where is the power output calculated by the current cycle PID algorithm (range 0-100% rated power). The upper limit of single compensation amount is rated power, to avoid power mutation causing temperature shock. When the welding head temperature reaches the target temperature ±2℃ range, automatically reset =0, stop compensation to prevent over-regulation. The total power after compensation ​No more than 110% of the rated power, if over limit, output according to the upper limit and record the deviation. Through cumulative error compensation, the temperature deviation at the end of the target time window is reduced from ±1.5°C to ±0.8°C, ensuring that the synchronization requirements of “the deviation of each welding head from the target temperature is ≤±2°C and the temperature difference between welding heads is ≤±2°C” are met.

[0050] For example, if a welding head has a positive deviation of 0.3°C / s (actual rate of change is lower than the target value) for 5 consecutive control periods, the system will superimpose a power compensation of 0.5% on the basis of PID parameter tuning, gradually reducing the deviation to within the threshold range.

[0051] To avoid equipment damage caused by abnormal heating power, multiple protection mechanisms are set. The heating power of a single welding head is not more than 110% of its rated power (the rated power value is obtained through the device parameter library); when the welding head temperature exceeds the target temperature +5°C, the heating power is forcibly cut off and an alarm is triggered; if the maximum power output still cannot meet the target rate of change for 10 consecutive periods (100ms), it is determined that the device is abnormal, the welding head is suspended and maintenance is prompted. For non-compliant welding heads, root cause analysis dimensions are added: distinguishing between “environmental interference”, “thermal capacity drift”, “thermal coupling” and other fault types, and pushing targeted maintenance recommendations.

[0052] At the end of the preset time window (0.5-3 seconds), the system automatically checks the temperature of each welding head. If all welding head temperatures meet the requirements of “deviation from the target temperature ≤±2°C and temperature difference between welding heads ≤±2°C”, it is marked as “synchronization compliance”. If there are non-compliant welding heads, record the deviation value and analyze the reasons (such as excessive initial temperature difference, thermal capacity modeling error, etc.), providing data support for subsequent process optimization.

[0053] This link realizes three core values through the closed-loop process of real-time monitoring, deviation adjustment, and power control: first, 1kHz high-frequency sampling and 10ms fast adjustment ensure real-time response to temperature changes, solving the problem of traditional control lag; second, dynamic tuning of PID parameters based on rate of change deviation improves temperature control accuracy under complex conditions; third, multiple safety constraints and synchronization verification mechanisms ensure equipment operation safety and product quality stability, ultimately achieving high-precision synchronous temperature control of multiple heterogeneous welding heads.

[0054] Example 1: An automobile parts hot riveting production line is equipped with 4 different brand hot riveting welding heads (numbered H1-H4), with large thermal capacity difference (actual difference up to 320%) and significant initial temperature difference. Based on the technical steps of the scheme, this embodiment verifies the effect of synchronous temperature control through specific data, with a target temperature of 180°C, requiring synchronization within 3 seconds (temperature difference ≤±2°C).

[0055] Selecting the heating pulse length , (i.e. 0.2s), output 220V full power signal through relay module, record pulse start timestamp , end timestamp , time precision 0.5ms. Collect ambient temperature , relative humidity RH=60. Trigger pulse according to H1-H2-H3-H4, interval 5 seconds.

[0056] Take H1 as an example: Initial temperature sampling 100ms before pulse - Average value is 30.2℃, temperature 5ms after pulse explanation .

[0057] Calculate adjacent temperature difference , find (jump 5.3℃), determine as noise. Window data , after sorting , after median replacement . After filtering , , . H1 is close to the fan, position coefficient , .

[0058] H1 is brand A, . Environment correction k value . Substitute into equivalent heat capacity formula .

[0059] Similarly, calculate the heat capacity of welding head H2 , H2 is in other area , , brand B, , . The heat capacity of welding head H3 , H2 is close to the fan , , brand A, , . The heat capacity of welding head H4 , H4 is in a closed area , , brand B, , .

[0060] After 3 seconds of heat capacity identification, collect initial temperature of each welding head , , , . Calculate temperature difference . Grouping, H4 is "far reference group" (with the lowest temperature difference ), the rest are "near-reference group".

[0061] H4's , selected as the reference channel .8-head array simulation gets , , . H4 rated power , then .

[0062] Main heating section formula . H4 (far reference group) main heating duration ( , take 1). Trigger temperature difference ℃ (target 180℃), trigger temperature . . Buffer section trajectory .

[0063] H4 at , real-time temperature , . Actual change rate , after moving average correction . Main heating section , instantaneous deviation .

[0064] Cumulative error (M=5 periods) , no compensation needed.

[0065] H2 at Extreme deviation processing. , , . Trigger PID adjustment, from 3.0 to 4.0, to 2.0. Power output correction , power reduced by 4.5%.

[0066] 3 seconds, the measured temperature is H1=179.2℃, H2=180.5℃, H1=178.9℃, H1=180.1℃. The maximum temperature difference from the target temperature is 1.1℃, and the maximum temperature difference between the welding heads is 1.6℃, which meets the requirement of ±2℃.

[0067] Example 2: A new energy vehicle power battery pack production line needs to realize the IP67 level annular sealing welding of the upper cover (glass fiber reinforced PP composite material, thickness 3mm) and the box (6061 aluminum alloy, thickness 5mm), the welding seam circumference is 1200mm, the tensile strength after welding is required to be ≥25MPa, 6 different brand hot riveting welding heads (H1-H6) are configured, among which H1, H3 and H5 are installed on the left side of the production line (close to the cooling fan, wind speed 1.2m / s), H2, H4 and H6 are installed on the right side (closed area, the ambient temperature is 3-5℃ higher than that on the left side), the full power of all welding heads is 30W, the equivalent heat capacity is actually measured with a difference of 315% (H4 is 7.0J / ℃, H3 is 2.2J / ℃), and it needs to be synchronized to 185℃ within 3 seconds and the temperature difference of any two welding heads is ≤±2℃.

[0068] In implementation, first, H1-H6 is independently executed full power heating pulse trigger operation, according to the scheme, the heating pulse length is strictly controlled in the range of 150-250ms, preferably 200ms±10%, the actual setting is 200ms, a 220V±5% voltage signal is output through the relay module (the actual measured voltage of H1 is 218V, and the actual measured voltage of H4 is 222V). The STM32H743 clock chip with an accuracy of ≤1 is synchronously used to record the start time stamp and the end time stamp of the pulse, the start time stamp of H1 is 0.000000s, and the end time stamp is 0.200001s, the pulse length calculation accuracy is ≤1ms; in order to avoid heat accumulation, the pulse interval of adjacent welding heads is set to 5.2 seconds (when the interval is actually measured as 5 seconds, the initial temperature of H2 is increased by 0.8℃ due to the influence of H1, and after adjusting to 5.2 seconds, there is no temperature interference). At the same time, SHT30 temperature and humidity sensor (sampling frequency 1Hz, accuracy ±1℃ / ±5%RH) is deployed to collect the environment temperature 25.8℃ and the relative humidity 52% in real time, and the pulse execution state is fed back in real time through the red indicator light (not executed) and the green indicator light (executed) and the software log.

[0069] During the whole time of the heating pulse, the temperature data was collected by the NTC temperature sensor (temperature measurement range -50-300℃, accuracy ±0.5℃, sampling frequency 1 kHz, shielded cable data transmission) built in the welding head: for H1, the average value of 100 sampling values within 100 ms before the start of the pulse was taken as the initial temperature, and the calculation was 30.2℃ (sampling value range 29.9-30.5℃); the instantaneous temperature within 5 ms after the end of the pulse was taken as the end temperature, and the actual measurement was 37.5℃ (sampling value 37.4-37.6℃), and the calculation of the original temperature rise was 7.3℃. For H4, the initial temperature was 34.5℃ (sampling value 34.3-34.7℃), the end temperature was 39.2℃ (sampling value 39.1-39.3℃), and the original temperature rise was 4.7℃. During the collection process, H2 appeared a sharp noise due to line electromagnetic interference, and the temperature of the 142th sampling point jumped from 36.9℃ to 42.2℃, with an adjacent temperature difference of 5.3℃. According to the adaptive median filtering algorithm in the scheme, one normal sampling point (36.9℃, 37.1℃) was extracted before and after the noise point, forming a 3-point window data set {36.9℃, 42.2℃, 37.1℃}, and the median value 37.0℃ was taken after sorting to replace the noise point, and after correction, the maximum adjacent temperature difference of H2 was 4.8℃≤5℃ (scheme spike judgment threshold ), ensuring the effectiveness of filtering.

[0070] According to the position heat dissipation difference of the welding head, the position coefficient was preset according to the scheme: the position coefficient of H1, H3 and H5 on the left side close to the fan =1.1, and the position coefficient of H2, H4 and H6 in the closed area on the right side =0.9, the actual temperature rise was obtained by multiplying the filtered original temperature rise and the position coefficient: H1=7.3×1.1=8.03℃, H4=4.7×0.9=4.23℃. Then, the equivalent heat capacity was calculated based on the collected pulse parameters and temperature rise data. According to the scheme formula, the heat conversion efficiency constant was first corrected: H1, H3 and H5 were brand A, the reference =120J, and the environmental parameters were substituted to obtain =120×[1+0.002×(25.8-25)+0.001×(52-50)]=120.432J; H2, H4 and H6 were brand B, the reference =150J, and after correction =150×[1+0.002×0.8+0.001×2]=150.54J. Then, the equivalent heat capacity formula in the scheme was used ​​) Calculation: H1=120.43x0.2 / 8.03=3.00J / ℃, H4=150.54x0.2 / 4.23=7.11J / ℃. Since the system is started for the first time every day, the automatic execution scheme "fast calibration" is performed, and the H1 pulse test is repeated 3 times, and the equivalent heat capacity is 3.02J / ℃, and the error is less than 1%; H4 has been welded 1023 times (more than 1000 times) after the last calibration, and the "deep calibration" is executed, and compared with the same type of new welding head (known heat capacity 7.0J / ℃), it is corrected to 7.08J / ℃, and updated to the equivalent heat capacity parameter library.

[0071] After the heat capacity identification is completed, wait for 3.1 seconds (the actual measurement is 3 seconds, and the H4 temperature still fluctuates 0.3℃, and the 0.1 second is extended to ensure that the temperature is stable), and collect 10 temperature data of each welding head at a frequency of 100Hz, and take the average value as the initial temperature: H1=30.5℃ (30.3-30.7℃), H4=34.8℃ (34.6-35.0℃), calculate the initial temperature difference of any two welding heads, H3 (29.9℃) and H4 (34.8℃) The maximum difference is 4.9℃, according to the scheme rules, the welding heads are divided into "near reference group" (H1, H3, H5, and the difference with the lowest initial temperature is less than or equal to 3℃) and "far reference group" (H2, H4, H6, and the difference with the lowest initial temperature is greater than 3℃). Select H4 with the largest equivalent heat capacity as the reference channel, and establish a 6-welding head thermodynamic model (grid division accuracy 0.1mm) through COMSOL to obtain the thermal coupling coefficient matrix: =0.05, =0.06, =0.04, =0.05, =0.07, combined with H4 full power 30W, according to the scheme formula, the global reference temperature rise rate is calculated: =30 / [7.08x(1+0.05+0.06+0.04+0.05+0.07)]=30 / (7.08x1.27)=3.33℃ / s.

[0072] Then build a dynamic target temperature curve, the main temperature rise segment trajectory is generated according to the scheme formula: H1 is T=30.5+3.33t, H4 is T=34.8+3.33t; for H4 of the far reference group, according to the scheme, the main temperature rise time is extended, the calculation formula is =1.2+4.9 / 3.33=2.68s; when the welding head temperature approaches the target temperature 185℃, according to the scheme, the buffer segment trigger temperature difference is set to 10℃ (i.e. the temperature reaches 175℃), and the buffer segment rate is 0.35 times the reference rate, i.e. 1.16℃ / s, through COMSOL simulation prediction, the temperature of H4 at the end of the buffer segment is 184.9℃, and the overshoot is less than or equal to 0.1℃, and the curve parameters are effective.

[0073] After the system enters the real-time control phase, the real-time temperature of each welding head is collected at a high sampling frequency of 1 kHz. A sliding average filter with a window size of 5 is used to smooth the noise. The actual temperature change rate is calculated based on the temperature difference between two consecutive sampling times (1 ms apart), with an accuracy of ±0.1°C / s. H3 had an abnormal actual change rate (300°C / s) due to loose sensor, which was restored to 3.3°C / s after re-fixing. Under normal working conditions, H6 had a poor heat dissipation in the closed area, with an actual change rate of 3.9°C / s at t=2.2 seconds, a target change rate of 3.32°C / s, and a deviation of 0.58°C / s>0.5°C / s (first deviation threshold in the scheme). The PID parameter real-time tuning was triggered according to the scheme: the proportional coefficient was adjusted from 3.0 to 3.8, the integral coefficient was adjusted from 0.5 to 0.3, and the differential coefficient remained unchanged at 1.0. The incremental PID algorithm was used to calculate the power adjustment increment signal: =3.8×(0.58-0.45)+0.3×0.58+1.0×(0.58-2×0.45+0.32)=0.668%, i.e. the power adjustment increment is 0.668%, which is further reduced by 0.668% through PWM pulse width modulation technology, and the actual adjusted power =29.5W-(29.5W×0.668%)≈29.30W, with a single adjustment amplitude ≤10% of the rated power (30W×10%=3W), meeting the scheme "single power adjustment amplitude upper limit" requirement.

[0074] The instantaneous deviation cumulative value of the next 5 cycles (50ms) was then calculated: the H6 cycle deviations were 0.58°C / s, 0.52°C / s, 0.48°C / s, 0.45°C / s, and 0.42°C / s, respectively, and the cumulative error =0.58+0.52+0.48+0.45+0.42=2.45°C / s>1.5°C / s (cumulative error threshold in the scheme). The compensation coefficient =0.005 was calculated, and the compensation amount =0.005×2.45=0.01225 (i.e. 1.225%) was calculated. After adding to the PID adjustment result, the final power of H6 =29.30W+(29.30W×1.225%)≈29.66W, with a single compensation amount ≈0.36W≤2% of the rated power (30W×2%=0.6W), meeting the scheme "single compensation amount upper limit" constraint.

[0075] During production, H2 suddenly failed due to the heat dissipation fan, and the temperature instantaneously rose to 187°C (over 185+5°C). The multiple protection mechanism immediately triggered: the heating power was cut off within 10 ms and an audible and visual alarm was given. After replacing the fan, production was resumed. After 3 seconds of synchronization time window, the actual measured temperature of each welding head was: H1=184.8°C, H2=184.9°C, H3=184.5°C, H4=185.1°C, H5=184.7°C, H6=184.9°C, the maximum temperature difference was 0.6°C≤±2°C, and it was determined that the synchronization was up to standard. After welding, sampling detection was performed: 10 products were tested for IP67 (immersed in water 1 m for 30 minutes), and there was no leakage, the average tensile strength was 27.3 MPa, which met the production requirements, and all steps of the scheme were necessary and there was no redundant link.

[0076] Example 3: A Tier1 supplier VCU shell production line needs to connect the ADC12 die-cast aluminum shell (150x100x50mm) and the PA66+GF30 end cover (thickness 2mm), which requires air tightness ≤0.5kPa / 5min, vibration test (10-2000Hz, 10g) without loosening, 4 welding heads (H7-H10) are configured, H7 and H9 are close to the heat dissipation hole (22±1°C), H8 and H10 are located inside the shell (25±1°C), the full power is 28W, the equivalent heat capacity difference is 290%, and it needs to be synchronized to 170°C within 2.5 seconds and the temperature difference is ≤±2°C.

[0077] During implementation, first perform a 200ms full power pulse on H7-H10 (H7 voltage 219V, H10 voltage 221V), interval 5.1 seconds, temperature and humidity sensor collects 23°C, 58%RH. NTC sensor collects: H7 initial 29.3°C, end 36.1°C, original temperature rise 6.8°C; H10 initial 32.5°C, end 37.3°C, original temperature rise 4.8°C. H8 appears 5.2°C noise, after correction by median filter, calculate actual temperature rise according to position coefficient (H7, H9 position coefficient =1.1, H8, H10 position coefficient =0.9): H7=7.48°C, H10=4.32°C.

[0078] Correct the heat conversion efficiency constant: H7, H9 (brand D, =125J) k=125.5J; H8, H10 (brand E, =145J) k=145.58J. Calculate the equivalent heat capacity according to the scheme formula: H7=125.5x0.2 / 7.48≈3.36J / °C, H10=145.58x0.2 / 4.32≈6.74J / °C, H7 is calibrated to 3.42J / °C due to welding over 1000 times.

[0079] After 3 seconds of heat capacity identification, the initial temperature H7=29.6℃, H10=32.8℃, the temperature difference is 3.2℃, and H10 is divided into a far reference group. Select H10 as the reference channel, and COMSOL gets the heat coupling coefficient =0.04、 =0.05、 =0.03, calculate =28 / [6.74×(1+0.04+0.05+0.03)]≈3.71℃ / s. Construct a dynamic curve: H10 main temperature rise 2.6 seconds, 160℃ switch buffer segment (rate 1.29℃ / s).

[0080] In the real-time control stage, after 1kHz sampling and filtering, the change rate is calculated: H9 deviates e(t)=0.6℃ / s at t=1.8 seconds, triggering PID tuning ( =3.5, =0.4, =1.0), incremental PID calculation ( =0.5℃ / s, =0.4℃ / s): =3.5×(0.6-0.5)+0.4×0.6+1.0×(0.6-2×0.5+0.4)=0.35+0.24+0.0=0.59%, H9 power from 28W to 28-28×0.59%≈27.8348W. H10 accumulates error 1.6℃ / s for 5 cycles, compensation=0.005×1.6=0.8%, superimposed power≈28+28×0.8%≈28.224W. After 2.5 seconds, the temperature is: H7=169.7℃, H10=170.1℃, the temperature difference is 0.4℃. The air tightness after welding is 99.8%, and the vibration test is fault-free.

[0081] The processes described above with reference to the flowcharts can be implemented as computer software programs in accordance with embodiments of the present disclosure. Embodiments of the present disclosure include a computer program product comprising a computer program carried on a computer readable medium, the computer program comprising program code for performing the methods illustrated by the flowcharts. In such embodiments, the computer program can be downloaded and installed from a network via a communication section, and / or installed from a detachable medium. When the computer program is executed by a central processing unit (CPU), the above-described functions defined in the methods of the present application are performed. It should be noted that the computer readable medium of the present application can be a computer readable signal medium or a computer readable storage medium or any combination of the two. The computer readable storage medium may, for example, but not limited to, be an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus or device, or any suitable combination of the above. More specific examples of the computer readable storage medium can include, but are not limited to, an electrical connection having one or more wires, a portable computer diskette, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the above. In the present application, the computer readable storage medium can be any tangible medium that contains or stores a program that can be used by or in connection with an instruction execution system, apparatus or device. In the present application, the computer readable signal medium can include a data signal carried in a baseband or as part of a carrier wave, in which the computer readable program code is carried. Such a propagated data signal can take many forms, including but not limited to, an electromagnetic signal, an optical signal, or any suitable combination of the above. The computer readable signal medium can also be any computer readable medium that can send, propagate or transfer the program for use by or in connection with an instruction execution system, apparatus or device. The program code contained on the computer readable medium can be transmitted by any suitable medium, including but not limited to, wireless, wire, optical cable, RF, or any suitable combination of the above.

[0082] The flowcharts and block diagrams in the accompanying drawings illustrate the architecture, functionality, and operation of possible implementations of systems, methods, and computer program products according to various embodiments of the present invention. In this regard, each block in a flowchart or block diagram may represent a module, segment, or portion of code containing one or more executable instructions for implementing a specified logical function. It should also be noted that in some alternative implementations, the functions indicated in the blocks may occur in a different order than those indicated in the drawings. For example, two consecutively indicated blocks may actually be executed substantially in parallel, and they may sometimes be executed in reverse order, depending on the functions involved. It should also be noted that each block in the block diagrams and / or flowcharts, and combinations of blocks in the block diagrams and / or flowcharts, can be implemented using a dedicated hardware-based system that performs the specified function or operation, or using a combination of dedicated hardware and computer instructions.

[0083] Those skilled in the art should understand that the embodiments of the present invention described above and shown in the accompanying drawings are merely examples and do not limit the present invention. The purpose of the present invention has been fully and effectively achieved. The functions and structural principles of the present invention have been shown and explained in the embodiments. Without departing from the stated principles, the implementation of the present invention may have any variations or modifications.

Claims

1. A temperature change rate-based hot riveting horn synchronous temperature control method, characterized by, The method comprises: Independently performing full-power heating pulse trigger operation on each welding head to be synchronized, recording pulse start timestamp and end timestamp, calculating pulse duration according to the start timestamp and the end timestamp, calculating temperature rise according to the initial temperature at the beginning of the pulse and the real-time temperature at the end of the pulse, combining the position coefficient and the position of each welding head to correct the actual temperature rise, and removing the peak noise through a digital filtering algorithm; Real-time acquisition of ambient temperature and relative humidity, combined with actual temperature rise and pulse duration to calculate the equivalent heat capacity of each welding head; Using the initial temperature of the welding head to calculate the initial temperature difference between any two welding heads, classifying the welding heads according to the initial temperature difference, selecting the welding head with the largest equivalent heat capacity as the reference channel and calculating the global reference rate combined with the thermal coupling coefficient matrix, establishing a welding head thermodynamic model through COMSOL, and constructing a dynamic target temperature curve; Acquiring the real-time temperature of each welding head to calculate the actual temperature change rate, synchronously extracting the target change rate of the dynamic target curve at the corresponding time to calculate the change rate deviation, and judging whether intervention adjustment is needed according to the change rate deviation, if needed, dynamically adjusting the PID controller coefficient according to the absolute value of the deviation, calculating the output signal using the incremental PID algorithm, and adjusting the heating power according to the output signal.

2. The temperature rate of change based hot rivet horn synchronized temperature control method of claim 1, wherein, The specific process of the actual temperature rise correction is as follows: Sampling the average temperature in a preset initial temperature sampling duration before the beginning of the pulse as the initial temperature and the instantaneous temperature in a preset end temperature sampling duration after the end of the pulse as the end temperature, calculating the difference between the two to obtain the original temperature rise; For the marked suspected noise points, filtering is performed through a digital filtering algorithm to obtain the filtered original temperature rise; according to the position of the welding head, the heat dissipation level is divided, and the corresponding position coefficient is set for different heat dissipation level regions; the filtered original temperature rise is multiplied by the corresponding position coefficient to obtain the final actual temperature rise.

3. The temperature rate of change based hot rivet horn synchronized temperature control method of claim 2, wherein, The specific content of the digital filtering algorithm is as follows: Traverse the temperature sampling sequence, calculate the temperature difference between adjacent sampling points, and mark the sampling point as a suspected peak noise point when the adjacent sampling temperature difference exceeds the peak judgment threshold; For the marked noise points, a data set is formed by extracting a plurality of normal sampling points before and after the noise points, and the median value is taken after sorting the window data to replace the noise points; The original value of the normal points not marked as noise is directly retained; for the edge points at the beginning and end of the sequence, if they are determined to be noise, the mean value of the effective data on one side is modified; After modification, the temperature difference stability of the filtered sequence is calculated, and if all adjacent temperature differences are ≤ the peak judgment threshold, the filtering is effective, otherwise the window is expanded and repeated modification is performed until the condition is met.

4. The temperature change rate-based hot riveting horn synchronous temperature control method according to claim 3, characterized in that, The specific calculation process of the equivalent heat capacity is as follows: The equivalent heat capacity of the welding head is calculated through the thermal conversion efficiency constant, temperature rise, power and pulse duration; the thermal conversion efficiency constant is corrected according to the ambient temperature and relative humidity, and the equivalent heat capacity of the welding head is corrected according to the corrected thermal conversion efficiency constant; The system automatically performs rapid calibration at the first start of each day, performs deep calibration according to the preset welding number interval, and updates the equivalent heat capacity parameter library.

5. The temperature rate of change based hot rivet horn synchronous temperature control method of claim 4, wherein, The specific process of obtaining the dynamic target temperature curve is as follows: After the thermal capacity identification is completed, a number of temperature data are continuously collected at a fixed frequency, and the average value is taken as the initial temperature of each welding head. The initial temperature difference between any two welding heads is calculated, and the welding heads are divided into a near-reference group and a far-reference group after the maximum initial temperature difference is determined; The welding head with the largest equivalent heat capacity is selected as the reference channel, and a thermal coupling coefficient matrix is introduced. The global reference temperature rise rate is calculated based on the full-power parameters of the reference channel; The dynamic target temperature curve includes a main heating section and a buffer section. The main heating section generates a target trajectory with the reference temperature rise rate as the slope. For the far-reference group of welding heads with extreme temperature differences, the main heating time is extended. When the welding head temperature approaches the target temperature, it automatically switches to the buffer section. A thermodynamic model is established by COMSOL to predict the thermal coupling effect and optimize the buffer section parameters.

6. The temperature rate of change based hot rivet horn synchronous temperature control method of claim 5, wherein, The intervention adjustment judgment process is as follows: After the system enters the real-time control phase, the real-time temperature of each welding head is collected at a high sampling frequency. After smoothing the noise with a moving average filter, the actual temperature change rate is calculated based on the temperature difference between two consecutive sampling times to ensure that the actual temperature change rate calculation accuracy meets the requirements; The target change rate at the corresponding time of the dynamic target temperature curve is extracted synchronously, and the target value at any time is obtained through an interpolation algorithm; The absolute value of the deviation between the actual change rate and the target change rate is calculated in real time. When the absolute value of the deviation is ≤ the first deviation threshold, it is determined to be in a normal state and no intervention adjustment is required; When the absolute value of the deviation is > the first deviation threshold, it is marked as a deviation anomaly, triggering the PID parameter real-time tuning mechanism and starting the intervention adjustment. When the absolute value of the deviation is > the second deviation threshold, the emergency adjustment mode is enabled.

7. The temperature rate of change based hot rivet horn synchronous temperature control method of claim 6, wherein, The output signal calculation process is as follows: When the absolute value of the deviation is > the third deviation threshold, increase the proportional coefficient and decrease the integral coefficient to speed up the response. When the first deviation threshold < the absolute value of the deviation ≤ the third deviation threshold, maintain the initial parameters. When the absolute value of the deviation ≤ the first deviation threshold, decrease the proportional coefficient and increase the integral coefficient to eliminate steady-state error. When the absolute value of the deviation > the integral pause threshold, pause the integral term, and only use proportional and differential adjustment to quickly suppress the deviation; An incremental PID algorithm is used to calculate the power adjustment increment signal, which is converted into a heating power command. The PWM pulse width modulation technique is used to control the power supply time of the welding head heating element; The cumulative error is calculated by summing the instantaneous deviations of consecutive cycles. When the absolute value of the cumulative error is > the third deviation threshold, the power compensation amount is calculated through a compensation coefficient and added to the PID output signal. The single compensation amount is ≤ 2% of the rated power; The final output signal must ensure that the power output is less than or equal to the upper limit of the rated power. If the limit is exceeded, the upper limit is output and the deviation is recorded.

8. A temperature change rate-based hot riveting horn synchronous temperature control system, characterized in that, The system is used to perform the synchronous temperature control method of the hot riveting welding head based on temperature change rate according to any one of claims 1-7.

9. A computer-readable storage medium, characterized in that, The computer readable storage medium stores a computer program, and the computer program is executed by the processor to implement the synchronous temperature control method of the hot riveting welding head based on temperature change rate according to any one of claims 1-7.

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