Flexible circuit board feeding parameter real-time monitoring method and system

Abstract

The application provides a flexible circuit board feeding parameter real-time monitoring method and system, and belongs to the technical field of process control. The method determines whether there is error accumulation in the current feeding process by obtaining a feeding gap deviation value. If there is, the step frequency sequence is adjusted by using a feedforward compensation adaptive PID algorithm to correct the feeding gap deviation value when the error accumulation trend value continues to grow, realizing the dynamic adaptation of the step frequency and the physical displacement. At the same time, by obtaining the feeding parameter monitoring interval and the temperature fluctuation period, when the monitoring interval exceeds the temperature fluctuation period, the Fourier transform algorithm is used to optimize the monitoring interval, so that the monitoring frequency matches the environmental fluctuation characteristics in the processing process, avoiding the accumulation of feeding parameter deviation and improving the stability and feeding accuracy of the flexible circuit board feeding device.

Description

Technical Field

[0001] This application belongs to the field of process control technology, specifically a method and system for real-time monitoring of feeding parameters of flexible circuit boards. Background Technology

[0002] Currently, flexible circuit boards (PCBs) are an indispensable core component in modern electronic products. The feeding accuracy during their production process directly affects the quality and production efficiency of electronic products, especially in the fields of intelligent manufacturing and high-end electronic equipment, where the stability and precision of PCB feeding devices are crucial. However, existing PCB feeding monitoring methods often struggle to adapt to the complex and ever-changing working environment of continuous roll processing, particularly at high speeds. Their responsiveness to dynamic changes is insufficient, easily leading to the accumulation of feeding parameter deviations. This accumulated deviation not only affects the accuracy of the PCB slicing process but can also have a cascading impact on subsequent processes, wasting raw materials and reducing production efficiency.

[0003] The above information in the background section of the invention is only used to enhance the understanding of the background of this application, and therefore may include information that does not constitute prior art known to those skilled in the art. Summary of the Invention

[0004] To address the above problems, this application provides a method and system for real-time monitoring of flexible circuit board feeding parameters, which is used to solve the problem of error accumulation during the feeding process.

[0005] To achieve the above objectives, the technical solution adopted in this application is as follows: In a first aspect, embodiments of this application provide a method for real-time monitoring of flexible circuit board feeding parameters. The method includes: acquiring feeding parameters of a flexible circuit board feeding device, the feeding parameters including a step frequency sequence and a physical displacement sequence; acquiring a preset number of feeding attempts; if, within the preset number of feeding attempts, the feeding gap deviation between the physical displacement sequence and the ideal displacement value exceeds a preset deviation threshold, it is determined that error accumulation exists in the current feeding process, and the feeding gap deviation value of the first feeding attempt is used as an error accumulation benchmark value; determining an error accumulation trend value based on the error accumulation benchmark value and each feeding gap deviation value; if the error accumulation trend value continues to increase, a feedforward compensation adaptive PID algorithm is used to adjust the step frequency sequence to optimize the physical displacement sequence. The displacement sequence is processed, and the positions of each cutting point of the flexible circuit board feeding device in the optimized physical displacement sequence are extracted. A nonlinear interpolation algorithm is used to calibrate the positions of each cutting point. If the positional accuracy errors of each calibrated cutting point are all within a preset accuracy range, the current stepping frequency and physical displacement are determined to be matched. The monitoring interval and temperature fluctuation period of the current feeding parameters of the flexible circuit board feeding device are obtained respectively. If the monitoring interval exceeds the temperature fluctuation period, the monitoring interval is optimized using a Fourier transform algorithm. Based on the optimized monitoring interval, if the positional accuracy error is not within the preset accuracy range, the self-locking shutdown mechanism of the flexible circuit board feeding device is activated, and the current positional accuracy error is recorded.

[0006] Secondly, embodiments of this application provide a real-time monitoring system for flexible circuit board feeding parameters. This system includes: an acquisition module, a first determination module, a second determination module, an adjustment module, a third determination module, an optimization module, and a determination module. The acquisition module acquires feeding parameters of the flexible circuit board feeding device, including a step frequency sequence and a physical displacement sequence. The first determination module acquires a preset number of feeding attempts. If, within the preset number of feeding attempts, the feeding gap deviation between the physical displacement sequence and the ideal displacement value exceeds a preset deviation threshold, it is determined that there is error accumulation in the current feeding process, and the feeding gap deviation value of the first feeding attempt is used as the error accumulation benchmark value. The second determination module determines an error accumulation trend value based on the error accumulation benchmark value and each feeding gap deviation value. The adjustment module adjusts the step frequency sequence using a feedforward compensation adaptive PID algorithm to optimize the physical displacement sequence if the error accumulation trend value continues to increase, and extracts the optimized result. The system comprises the following modules: a first module for determining the position of each cutting point in the physical displacement sequence of the flexible circuit board feeding device; a second module for calibrating the position of each cutting point using a nonlinear interpolation algorithm; a third module for determining the matching between the current stepping frequency and the physical displacement if the position accuracy error of each calibrated cutting point is within a preset accuracy range, and an optimization module for optimizing the monitoring interval using a Fourier transform algorithm if the monitoring interval exceeds the temperature fluctuation period; and a start module for activating the self-locking shutdown mechanism of the flexible circuit board feeding device based on the optimized monitoring interval if the position accuracy error is not within the preset accuracy range, and recording the current position accuracy error.

[0007] This application provides a method and system for real-time monitoring of feeding parameters for flexible circuit boards. By determining that the feeding gap deviation exceeds a preset deviation threshold, it is determined that there is an accumulation of errors in the current feeding process. If the error accumulation trend continues to increase, a feedforward compensation adaptive PID algorithm is used to adjust the stepping frequency sequence to correct the feeding gap deviation, achieving dynamic adaptation between the stepping frequency and physical displacement. Simultaneously, by acquiring the feeding parameter monitoring interval and temperature fluctuation period, a Fourier transform algorithm is used to optimize the monitoring interval when it exceeds the temperature fluctuation period. This ensures that the monitoring frequency matches the environmental fluctuation characteristics during processing, avoiding the accumulation of feeding parameter deviations, reducing raw material waste, improving the stability and feeding accuracy of the flexible circuit board feeding device, and thus ensuring the accuracy and production efficiency of flexible circuit board production. Attached Figure Description

[0008] Figure 1This is a flowchart illustrating a real-time monitoring method for flexible circuit board feeding parameters provided in an exemplary embodiment of this application.

[0009] Figure 2 This is a flowchart illustrating a method for real-time monitoring of flexible circuit board feeding parameters provided in another exemplary embodiment of this application.

[0010] Figure 3 This is a flowchart illustrating a method for real-time monitoring of flexible circuit board feeding parameters provided in another exemplary embodiment of this application.

[0011] Figure 4 This is a flowchart illustrating a method for real-time monitoring of flexible circuit board feeding parameters provided in another exemplary embodiment of this application.

[0012] Figure 5 This is a flowchart illustrating a method for real-time monitoring of flexible circuit board feeding parameters provided in another exemplary embodiment of this application.

[0013] Figure 6 This is a flowchart illustrating a method for real-time monitoring of flexible circuit board feeding parameters provided in another exemplary embodiment of this application. Detailed Implementation

[0014] To enable those skilled in the art to better understand the technical solution, the present application will be described in detail below with reference to the embodiments. The description in this section is only exemplary and explanatory, and should not be used to limit the scope of protection of the present application in any way.

[0015] Currently, flexible circuit boards (PCBs) are an indispensable core component in modern electronic products. The feeding accuracy during their production is a key indicator of process control, directly impacting product quality and production efficiency. This is especially true in intelligent manufacturing and high-end electronic equipment, where the stability and precision of PCB feeding devices are paramount. However, existing PCB feeding monitoring methods often struggle to adapt to the complex and ever-changing working environment of continuous roll processing, particularly at high speeds. Their responsiveness to dynamic changes is insufficient, leading to the accumulation of feeding parameter deviations. This accumulated deviation not only affects the accuracy of the PCB slicing process but can also have a cascading impact on subsequent processes, wasting raw materials and reducing production accuracy and efficiency.

[0016] Specifically, the stepping frequency, as a key indicator for controlling the feeding rhythm of flexible circuit boards in process control, will result in slight deviations in the gap between each feeding if it cannot be kept consistent with the physical displacement. These deviations will gradually accumulate during continuous processing, forming a larger error. This phenomenon of error accumulation is particularly evident in high-speed slicing processes. For example, when cutting flexible circuit board rolls, the initial tiny gap deviation may evolve into a shift of several millimeters after hundreds of cycles, directly causing misalignment of the cutting position and affecting the consistency of product dimensions.

[0017] Therefore, how to monitor the parameter interval between stepping frequency and physical displacement in real time during continuous roll material processing and effectively avoid the accumulation of errors has become a technical problem that needs to be solved to improve the production accuracy of flexible circuit boards.

[0018] This application provides a method for real-time monitoring of flexible circuit board feeding parameters, such as... Figure 1 The method for real-time monitoring of flexible circuit board feeding parameters is shown. This method may include the following steps: Step S110: Obtain the feeding parameters of the flexible circuit board feeding device, including the step frequency sequence and the physical displacement sequence; Step S120: Obtain the preset number of feedings. If the feeding gap deviation between the physical displacement sequence and the ideal displacement value exceeds the preset deviation threshold within the preset number of feedings, it is determined that there is error accumulation in the current feeding process, and the feeding gap deviation value of the first feeding is used as the error accumulation benchmark value. Step S130: Determine the cumulative error trend value based on the cumulative error benchmark value and the deviation values ​​of each feeding gap; Step S140: If the cumulative error trend value continues to increase, the feedforward compensation adaptive PID algorithm is used to adjust the step frequency sequence to optimize the physical displacement sequence, and the positions of each cutting point of the flexible circuit board feeding device in the optimized physical displacement sequence are extracted. Step S150: Use a nonlinear interpolation algorithm to calibrate the position of each cutting point. If the position accuracy error of each cutting point after calibration is within the preset accuracy range, then determine that the current step frequency sequence and the physical displacement sequence are matched, and obtain the monitoring interval and temperature fluctuation period of the current flexible circuit board feeding device feeding parameters respectively. Step S160: If the monitoring interval exceeds the temperature fluctuation period, the Fourier transform algorithm is used to optimize the monitoring interval; Step S170: Based on the optimized monitoring interval, if the position accuracy error is not within the preset accuracy range, the self-locking shutdown mechanism of the flexible circuit board feeding device is activated, and the current position accuracy error is recorded.

[0019] According to the real-time monitoring method for flexible circuit board feeding parameters provided in this application, this method can determine that there is an error accumulation in the current feeding process when the feeding gap deviation exceeds a preset deviation threshold. Furthermore, by judging that the error accumulation trend value continues to increase, a feedforward compensation adaptive PID algorithm is used to adjust the stepping frequency sequence to correct the feeding gap deviation value, achieving dynamic adaptation between the stepping frequency and physical displacement. Simultaneously, by acquiring the feeding parameter monitoring interval and temperature fluctuation period, when the monitoring interval exceeds the temperature fluctuation period, a Fourier transform algorithm is used to optimize the monitoring interval, making the monitoring frequency match the environmental fluctuation characteristics during processing. This avoids the accumulation of feeding parameter deviations, reduces raw material waste, improves the stability and feeding accuracy of the flexible circuit board feeding device, and thus ensures the accuracy and production efficiency of flexible circuit board production.

[0020] The following is a detailed description of each step in the real-time monitoring method for flexible circuit board feeding parameters provided in the embodiments of this application: In one embodiment of this application, step S110 involves obtaining the feeding parameters of the flexible circuit board feeding device. The feeding parameters include a step frequency sequence and a physical displacement sequence. The step also includes the following steps: Figure 2 As shown, the specific content is as follows: Step S210: Obtain the stepping frequency data and physical displacement data of the flexible circuit board feeding device; Step S220: Based on the step frequency data and physical displacement data, the Kalman filter algorithm is used to determine the step frequency sequence and physical displacement sequence; Step S230: If the time synchronization deviation between the step frequency sequence and the physical displacement sequence exceeds the preset synchronization deviation threshold, then time calibration is performed on the step frequency sequence and the physical displacement sequence.

[0021] Specifically, during the feeding and processing of continuous rolls of flexible circuit boards, a frequency meter can be installed at the motor drive end of the feeding mechanism to collect stepping frequency data; a laser displacement sensor can be installed at the core track of the roll conveyor to collect physical displacement data. Simultaneously, a unified sampling frequency can be set for both types of sensors to ensure data acquisition synchronization and enable real-time continuous data acquisition of the feeding device's operation.

[0022] Furthermore, the step frequency data and physical displacement data can be input into the Kalman filter algorithm for data optimization processing to eliminate random noise generated during the acquisition process due to factors such as equipment mechanical vibration, electromagnetic interference in the production environment, and fluctuations in the accuracy of the sensor itself. Then, the smooth and continuous step frequency data after noise filtering are arranged sequentially according to the time dimension of acquisition to form a step frequency sequence; and the filtered physical displacement data are arranged in order based on the same time dimension to form a physical displacement sequence.

[0023] Furthermore, the time synchronization deviation between the step frequency sequence and the physical displacement sequence can be calculated. This time synchronization deviation refers to the time dimension shift in the step frequency data and physical displacement data at the same time node caused by factors such as different sensor acquisition response speeds, data transmission link delays, and differences in device signal processing time. Next, the calculated actual time synchronization deviation value is compared with a preset synchronization deviation threshold. If the actual deviation value exceeds the preset threshold, a time calibration process is initiated, using methods such as timestamp alignment and linear interpolation to correct the time dimension shift, ensuring that the step frequency sequence and physical displacement sequence match at the time node and guaranteeing the accuracy of error analysis in process control. The preset synchronization deviation threshold is quantitatively set by combining the sampling period of the sensor acquisition. Simultaneously, it can be dynamically fine-tuned according to the sampling frequency of the feeding device (high-speed sampling / low-speed sampling) to adapt to different flexible circuit board production and processing scenarios. For example, it can be set to 5% of the sampling period to avoid analysis distortion caused by minor time misalignments.

[0024] For example, the acquired step frequency data is 50.2Hz and the physical displacement data is 10.5mm. After continuous acquisition, a complete set of step frequency and physical displacement data is formed. These data are then input into a Kalman filter algorithm, with the process noise covariance preset to 0.01, the measurement noise covariance to 0.05, and the initial state estimation error to 0.1. Noise filtering is performed through iterative calculations of state prediction and measurement updates. The data are then arranged in chronological order of acquisition, resulting in the following step frequency sequence: [50.0Hz, 49.9Hz, 50.1Hz, 50.0Hz, 50.0Hz]; and the physical displacement sequence: [10.3mm, 10.2mm, 10.4mm, 10.3mm, 10.3mm]. Next, the time synchronization deviation between the two sequences is calculated using a time difference calculation algorithm. The preset synchronization deviation threshold is 0.02 seconds. Calculations show that due to data transmission link delays, the timestamp of the step frequency sequence lags behind the physical displacement sequence by 0.05 seconds, and the actual time synchronization deviation exceeds the threshold. Then, using the acquisition timestamp of the physical displacement sequence as a benchmark, the timestamp of the step frequency sequence is corrected using a timestamp alignment method. At the same time, missing frequency data within the 0.05-second delay interval are supplemented by linear interpolation combined with adjacent data. For example, at the 0.03-second time gap, a missing value of 50.0Hz is obtained by interpolation between 49.9Hz and 50.1Hz. After calibration, a time-dimension matched step frequency sequence and physical displacement sequence are regenerated.

[0025] In one embodiment of this application, in step S120, a preset number of feeds is obtained. If the feed gap deviation between the physical displacement sequence and the ideal displacement value exceeds a preset deviation threshold within the preset number of feeds, it is determined that there is error accumulation in the current feeding process, and the feed gap deviation value of the first feed is used as the error accumulation benchmark value. Specifically, the preset number of continuous feeds is set based on the error accumulation characteristics of high-speed processing of flexible circuit boards, and combined with the detectable cumulative error formed by small deviations in continuous roll processing through multiple feeding cycles. The preset deviation threshold is set based on the industry precision requirements for flexible circuit board feeding processing. For example, as a high-precision electronic component, the allowable deviation of the feed gap of a flexible circuit board needs to be controlled within 0.2mm, so the preset deviation threshold is set to 0.2mm. Furthermore, the preset number of continuous feeds and the preset deviation threshold can be dynamically fine-tuned according to the processing precision level and processing speed of the flexible circuit board to adapt to different production scenario requirements and meet the requirements of different process control precision.

[0026] Furthermore, based on the physical displacement sequence, the actual physical displacement value during each feeding process can be extracted. The difference between the actual physical displacement value and the ideal displacement value for flexible circuit board feeding processing is calculated to obtain the feeding gap deviation value corresponding to each feeding. This value is an indicator reflecting the degree of displacement deviation in a single feeding. The ideal displacement value is the theoretical standard physical displacement amount preset by the flexible circuit board feeding device within the feeding cycle, based on the product cutting specifications and feeding step distance process parameters. It is the target displacement reference value that the feeding device should output under ideal working conditions without mechanical transmission errors, environmental disturbances, flexible circuit board deflection, or sensor deviation. Subsequently, using a preset number of consecutive feedings as a judgment window, the feeding gap deviation value of each feeding within this window is checked to see if it exceeds a preset deviation threshold. If all feeding gap deviation values ​​within the window meet the condition of "exceeding the preset deviation threshold," it is determined that there is a real error accumulation in the current flexible circuit board feeding process, thus eliminating the interference of single random deviations. After determining that error accumulation exists, the feeding gap deviation value corresponding to the first feeding within the preset number of consecutive feedings is used as the error accumulation reference value.

[0027] For example, with a preset continuous feeding count of 10 times, a preset deviation threshold of 0.2 mm, and an ideal displacement value of 5.0 mm for a single feeding, the physical displacement sequence after noise filtering using a Kalman filter algorithm represents the actual physical displacement values ​​for 10 consecutive feedings. The feeding gap deviation value for each feeding is calculated. The actual physical displacement values ​​for 10 consecutive feedings are 5.3 mm, 5.25 mm, 5.32 mm, 5.28 mm, 5.35 mm, 5.29 mm, 5.31 mm, 5.27 mm, 5.33 mm, and 5.30 mm, respectively. The corresponding calculated feeding gap deviation values ​​for the 10 feedings are 0.3 mm, 0.25 mm, 0.32 mm, 0.28 mm, 0.35 mm, 0.29 mm, 0.31 mm, 0.27 mm, 0.33 mm, and 0.30 mm, respectively. Subsequently, the 10 feeding gap deviation values ​​within the preset continuous feeding number window were checked, and it was found that all values ​​exceeded the preset deviation threshold of 0.2mm. Therefore, it was determined that there was an error accumulation in the current flexible circuit board feeding process. Finally, the feeding gap deviation value of 0.3mm corresponding to the first feeding in the 10 feedings was extracted and used as the error accumulation benchmark value for this feeding process.

[0028] In one embodiment of this application, step S120, obtaining the preset feeding number, further includes the following steps: establishing a coupling deviation model based on the step frequency sequence and the physical displacement sequence; and determining the preset feeding number based on the coupling deviation model. Specifically, a Kalman filter algorithm can be used to reduce noise, and a time-matched step frequency sequence and physical displacement sequence can be obtained after time calibration. Using the feeding time sequence as a reference, the data in the two sets of sequences are matched one-to-one, and the instantaneous coupling deviation value of each set of data is calculated sequentially. The instantaneous coupling deviation value reflects the degree of matching deviation between the step frequency and the physical displacement during a single feeding process. Instantaneous coupling deviation value = |(current step frequency / reference step frequency) × ideal displacement value - current physical displacement value|. Subsequently, multiple sets of instantaneous coupling deviation values ​​were accumulated in order of the number of feedings. A coupling deviation model was constructed by linear fitting with the number of feedings as the independent variable and the cumulative value of coupling deviation as the dependent variable. The model adopts the linear fitting form y=kx+b, where x represents the number of feedings, y represents the cumulative value of coupling deviation, k represents the growth slope of coupling deviation, and b represents the initial value of coupling deviation. The coupling deviation model can quantify the correspondence between the number of feedings and the degree of cumulative coupling deviation, reflecting the cumulative law of the deviation between the step frequency sequence and the physical displacement sequence as the number of feedings increases.

[0029] Furthermore, a preset deviation threshold for flexible circuit board feeding processing is used as a coupling deviation warning value. This warning value is the critical value for determining whether the deviation has reached an abnormal standard. Subsequently, the coupling deviation warning value is substituted into the coupling deviation model to solve for the corresponding independent variable value in the model. This value is the preset feeding number. This enables adaptive adjustment of the feeding number and also identifies the minimum judgment window for true error accumulation. It can effectively filter out interference from single random deviations and ensure that error accumulation is only judged when a persistent deviation occurs during continuous feeding.

[0030] For example, the feed device has a base stepping frequency of 50Hz, an ideal displacement of 10.0mm per feed, and a preset deviation threshold of 0.2mm. After Kalman filtering for noise reduction and time calibration, the resulting stepping frequency sequence is [50.0Hz, 49.9Hz, 50.1Hz, 50.0Hz, 50.0Hz, 49.8Hz, 50.2Hz, 50.0Hz, 49.9Hz, 50.1Hz], and the physical displacement sequence is [10.3mm, 10.2 ... [0.4mm, 10.3mm, 10.3mm, 10.1mm, 10.5mm, 10.3mm, 10.2mm, 10.4mm]; The instantaneous coupling deviation value is calculated successively and cumulatively fitted to construct the coupling deviation model as y=0.03x+0.27, where x is the number of feedings and y is the cumulative value of coupling deviation; The preset deviation threshold of 0.2mm is substituted into the model as the coupling deviation warning value, and x≈10 is obtained. Therefore, the preset number of feedings in this scenario is determined to be 10 times.

[0031] In the above method, using a preset number of consecutive feeding cycles as a window for verification effectively filters out interference signals caused by occasional fluctuations in operating conditions and momentary equipment vibrations. This accurately identifies the true and continuous error accumulation during the flexible circuit board feeding process, ensuring the accuracy and reliability of the error accumulation determination results. Furthermore, it can be directly embedded into monitoring and control and data acquisition systems to achieve automated deviation calculation, window verification, and status determination without manual intervention, significantly improving the efficiency and real-time performance of error monitoring during the flexible circuit board feeding process.

[0032] In one embodiment of this application, step S130, determining the error accumulation trend value based on the error accumulation benchmark value and each feeding gap deviation value, further includes the following step: adding the error accumulation benchmark value to each feeding gap deviation value respectively, and using the result of the addition operation as the error accumulation trend value. Specifically, the determined error accumulation benchmark value can be obtained from the feeding parameter monitoring system, and then the feeding gap deviation values ​​corresponding to each feeding within a preset number of consecutive feeding cycles (excluding the first feeding) can be obtained. These feeding gap deviation values ​​are arranged in order according to the feeding time sequence to ensure the timing and accuracy of subsequent accumulation operations, and to maintain consistency with the error superposition process of actual feeding. Subsequently, the error accumulation benchmark value is used as the initial value for the accumulation operation, and is added one by one to each of the sorted feeding gap deviation values. The result of each addition operation is the error accumulation trend value of the current feeding process after the corresponding number of feeding cycles is completed. This value can accurately quantify the actual cumulative scale of the feeding gap deviation based on the initial benchmark after each feeding cycle, and intuitively present the dynamic change trend of the error gradually increasing with the feeding cycle.

[0033] For example, the preset number of continuous feeds is 10, and the cumulative error benchmark is 0.3mm. The feed gap deviation values ​​obtained from the 10 feeds in chronological order are 0.3mm, 0.25mm, 0.32mm, 0.28mm, 0.35mm, 0.29mm, 0.31mm, 0.27mm, 0.33mm, and 0.30mm, respectively. By using a cumulative summation method, the cumulative error benchmark value is added to the feed gap deviation values ​​of each feed, resulting in a cumulative error trend value of 3.00mm after 10 feeds.

[0034] In the above method, the initial value is added to the cumulative error benchmark value. The calculation method, which involves sequentially adding the error to the deviation values ​​of each feeding interval arranged chronologically, conforms to the actual engineering law of error accumulation with each feeding cycle in the continuous roll processing of flexible circuit boards. This achieves the gradual quantification of the degree of error accumulation during the feeding process, and can intuitively and clearly present the complete trend characteristics of the gradual accumulation of errors. It can also be quickly embedded into monitoring and control and data acquisition systems to achieve automated real-time calculations, meeting the real-time parameter monitoring needs under high-speed operation of the feeding device.

[0035] In one embodiment of this application, in step S140, if the cumulative error trend value continues to increase, a feedforward compensation adaptive PID algorithm is used to adjust the step frequency sequence to optimize the physical displacement sequence. The step also includes the following steps: Figure 3 As shown, the specific content is as follows: Step S310: Based on the feeding gap deviation value, the adjustment range of the stepping frequency sequence is determined by using a feedforward compensation adaptive PID algorithm; Step S320: Adjust the step frequency sequence according to the adjustment range, and drive the flexible circuit board feeding device according to the adjusted step frequency sequence to optimize the physical displacement sequence.

[0036] Specifically, the system can acquire the feeding gap deviation value within a preset feeding cycle and the real-time feeding gap deviation value, while simultaneously collecting real-time temperature data and flexible circuit board roll tension data from the flexible circuit board feeding device as feedforward inputs. The feeding gap deviation value is used as feedback for PID closed-loop control. The proportional loop calculates the basic adjustment value based on the current feeding gap deviation value, the integral loop accumulates historical feeding gap deviation values ​​to eliminate system steady-state error, and the derivative loop predicts the deviation development trend based on the rate of change of the feeding gap deviation value. The feedforward compensation loop calculates the corresponding disturbance compensation value based on the fluctuation amplitude of real-time temperature and tension data relative to standard operating conditions. The PID closed-loop adjustment value is superimposed with the temperature and tension feedforward disturbance compensation values ​​to finally obtain the adjustment amplitude of the step frequency sequence. This adjustment amplitude can adaptively match the deviation state and operating condition disturbances, ensuring the accuracy and timeliness of the adjustment.

[0037] Furthermore, according to the feeding sequence of the flexible circuit board, each step frequency value in the step frequency sequence can be adjusted point by point based on the adjustment range. A positive adjustment range increases the step frequency value at the corresponding position, while a negative adjustment range decreases the step frequency value at the corresponding position, generating an adjusted step frequency sequence adapted to the current working conditions. Next, the adjusted step frequency sequence is transmitted to the drive control system of the flexible circuit board feeding device. The drive control system controls the operating rhythm of the feeding mechanism according to the adjusted step frequency sequence, adjusting the feeding speed and feeding interval in real time. Alternatively, a laser displacement sensor can be used to collect physical displacement data after the feeding mechanism has run in real time. This data is then arranged sequentially according to the collection time to form an optimized physical displacement sequence. The corresponding feeding gap deviation value will gradually decrease to within a preset deviation threshold, thus optimizing the physical displacement sequence.

[0038] In the above method, by employing feedforward compensated adaptive PID based on the feeding gap deviation value, it can quickly respond to the current feeding gap deviation, eliminate system steady-state error to avoid the continuous accumulation of small deviations, and predict the deviation development trend to achieve early adjustment, thereby reducing cumulative error. Furthermore, the parameter adjustment process can be directly embedded into the supervisory control and data acquisition system for automated execution without manual intervention, meeting the real-time monitoring and control requirements of the feeding device under high-speed operation. This achieves closed-loop process control of feeding parameters from deviation monitoring to frequency adjustment to displacement optimization, effectively avoiding the impact of error superposition on the processing accuracy of flexible circuit boards, and improving the operational stability of the feeding system and the accuracy of flexible circuit board feeding and processing.

[0039] In one embodiment of this application, step S140, which involves extracting the positions of each cutting point of the flexible circuit board feeding device from the optimized physical displacement sequence, further includes the following steps: Figure 4 As shown, the specific content is as follows: Step S410: Extract the displacement values ​​of each displacement point in the optimized physical displacement sequence; Step S420: If the rate of change of the displacement value exceeds the preset rate of change threshold, then the current displacement point is taken as the cutting point.

[0040] Specifically, the optimized physical displacement sequence is structured displacement data arranged according to the feeding time axis and feeding cycle sequence. Each data node corresponds to a displacement point, that is, each displacement point corresponds to the actual physical position of the flexible circuit board feeding device at a certain moment. Next, the rate of change of displacement value of each displacement point relative to the previous displacement point is calculated according to the time sequence. The calculation method is: rate of change of displacement value = (current displacement value - previous displacement value) / time interval between adjacent displacement points. This value can reflect the displacement change rate between two adjacent displacement points. Then, the calculated rate of change of displacement value of each displacement point is compared with the preset rate of change threshold one by one. If the rate of change of displacement value of a certain displacement point exceeds the preset rate of change threshold, it indicates that the physical displacement of the feeding device at that displacement point has a step change, which is consistent with the displacement motion characteristics when the flexible circuit board cutting action is triggered. Therefore, this displacement point is determined as the cutting point. If the rate of change of displacement value does not exceed the preset rate of change threshold, it indicates that the displacement point is a smooth displacement change point in the normal feeding process and is excluded from the cutting point range. The preset rate of change threshold must follow the cutting process design principles of flexible circuit board feeding processing. When the cutting action is triggered, the physical displacement of the feeding device will undergo a step-like abrupt change, while the displacement changes smoothly and linearly during normal feeding. For example, in the scenario of high-precision flexible circuit board high-speed feeding and cutting, the preset change rate threshold can be set to 0.5mm / ms. The value of the preset change rate threshold can also be adjusted according to the processing accuracy level of the flexible circuit board and the cutting speed to adapt to different production and processing scenarios and ensure the scientific and accurate determination of the cutting point.

[0041] For example, the optimized physical displacement sequence collects displacement data at fixed time intervals of 0.1 ms, with a preset change rate threshold of 0.5 mm / ms. The displacement values ​​of displacement points 1-10 in the optimized physical displacement sequence are extracted according to the temporal sequence, forming a displacement point time sequence number-displacement dataset: Displacement value 1 is 5.0 mm, displacement value 2 is 5.02 mm, displacement value 3 is 5.03 mm, displacement value 4 is 8.0 mm, displacement value 5 is 8.01 mm, displacement value 6 is 8.02 mm, displacement value 7 is 11.0 mm, displacement value 8 is 11.03 mm, displacement value 9 is 11.04 mm, and displacement value 10 is 14.0 mm. The rate of change of displacement value at each displacement point relative to the previous displacement point was then calculated, with an interval of 0.1 ms between adjacent displacement points. The calculation results were as follows: displacement value change rate of 0.2 mm / ms for displacement value 2, 0.1 mm / ms for displacement value 3, 29.7 mm / ms for displacement value 4, 0.1 mm / ms for displacement value 5, 0.1 mm / ms for displacement value 6, 29.8 mm / ms for displacement value 7, 0.3 mm / ms for displacement value 8, 0.1 mm / ms for displacement value 9, and 29.6 mm / ms for displacement value 10. Comparing all the rates of change with a preset threshold of 0.5 mm / ms, it was found that the displacement value change rates of displacement points 4, 7, and 10 all exceeded the threshold. Therefore, these three displacement points were determined as the cutting points of the flexible circuit board feeding device, with corresponding cutting point position displacement values ​​of 8.0 mm, 11.0 mm, and 14.0 mm, respectively.

[0042] In one embodiment of this application, in step S150, a nonlinear interpolation algorithm is used to calibrate the position of each cutting point. If the positional accuracy error of each cutting point after calibration is within the preset accuracy range, it is determined that the current stepping frequency and physical displacement are matched, and the monitoring interval and temperature fluctuation cycle of the current flexible circuit board feeding device are obtained respectively.

[0043] Specifically, taking into account the flexible circuit board's physical characteristics of flexural deformation, a nonlinear interpolation algorithm adapted to the deformation law of the flexible circuit board can be used to calibrate the actual positions of all preset cutting points. The theoretical standard coordinates and actual on-site detection coordinates of all cutting points can be collected, and then a nonlinear interpolation calibration model can be constructed by combining the flexural deformation coefficients and tensile deformation laws of different regions of the flexible circuit board. Based on this model, the nonlinear positional offset of the cutting points caused by the flexible deformation of the circuit board is corrected point by point, thus completing the position calibration of all cutting points.

[0044] Furthermore, the absolute value of the difference between the calibrated position value and the ideal position value of each cutting point is calculated; this value represents the positional accuracy error of the cutting point. The positional accuracy errors of all cutting points are compared one by one with the preset accuracy range. If the positional accuracy errors of all cutting points fall within the preset accuracy range, it indicates that the stepping frequency adjusted by the PID control algorithm can accurately match the physical displacement, ensuring that the operating state of the feeding device meets the accuracy requirements of the cutting process. Therefore, it is determined that the current stepping frequency and physical displacement are well-matched. If the positional accuracy error of any cutting point exceeds the preset accuracy range, the stepping frequency sequence needs to be readjusted and the physical displacement sequence optimized until the positional accuracy of the cutting point meets the requirements. The preset accuracy range needs to be set according to the accuracy requirements of high-speed feeding and cutting of flexible circuit boards, and can also be adaptively adjusted according to the application scenario of the flexible circuit board (such as high-end precision electronics and conventional electronics) and the process requirements of the cutting process.

[0045] Furthermore, after determining the matching between the current stepping frequency and physical displacement, based on the actual operating status of the flexible circuit board feeding device, the monitoring interval of the current flexible circuit board feeding parameters is extracted. This parameter represents the interval between the actual acquisition times of feeding parameters such as the stepping frequency and physical displacement of the feeding device, reflecting the acquisition rhythm of the current monitoring system. Simultaneously, temperature data of the flexible circuit board production environment is collected. Commonly used engineering spectral analysis methods such as Fourier transform are employed to process the temperature data, extracting the main fluctuation characteristics and determining the temperature fluctuation period during the flexible circuit board processing. The temperature fluctuation period is the time interval between regular temperature fluctuations in the processing environment, and is an environmental parameter affecting the mechanical characteristics and feeding accuracy of the feeding device.

[0046] For example, in the batch cutting of a certain polyimide flexible circuit board, the board material is a typical flexible board structure with significant flexural and slight tensile deformation characteristics. The production process is set with 12 cutting points. Through testing, it was found that during the board feeding process, due to its own flexible deformation, the actual position of each cutting point is irregularly offset from the theoretical position. Conventional linear calibration cannot eliminate this kind of deviation. Subsequently, a nonlinear interpolation algorithm tailored to the flexural characteristics of the flexible circuit board was adopted. The theoretical coordinates, actual detection coordinates, and flexural deformation coefficients of each section of the board were input for 12 cutting points. A nonlinear position calibration model was built, and the position of each cutting point was interpolated and calibrated one by one. The preset accuracy range in this calibration scenario was ±0.02 mm. After calibration, the position accuracy error of each cutting point was calculated one by one. Finally, the error of each cutting point was controlled within the range of ±0.01 mm to ±0.02 mm, which met the preset accuracy requirements. It was thus determined that the stepping frequency of the current equipment and the physical displacement of the flexible circuit board feeding were accurately matched. The monitoring interval of the feeding parameters under the current working condition was accurately collected at 3 seconds. At the same time, the temperature fluctuation cycle of the processing environment and equipment was detected to be 18 minutes.

[0047] In one embodiment of this application, in step S160, if the monitoring interval exceeds the temperature fluctuation period, the monitoring interval is optimized using a Fourier transform algorithm, and the method further includes the following steps: Figure 5 As shown, the specific content is as follows: Step S510: Obtain the temperature time-domain data of the current flexible circuit board feeding device; Step S520: Based on the temperature time-domain data, the Fourier transform algorithm is used to determine the main fluctuation frequency; Step S530: Determine the main fluctuation period based on the main fluctuation frequency, and use the main fluctuation period as the optimized monitoring interval.

[0048] Specifically, high-precision temperature sensors can be installed in the drive mechanism, cutting station, and roll conveying area of ​​the flexible circuit board feeding device. Temperature data is continuously and in real-time collected according to the basic acquisition frequency of the monitoring, control, and data acquisition system. During the acquisition process, a unique timestamp is assigned to each set of temperature data, forming a structured temperature time-domain dataset with a one-to-one correspondence between timestamp and temperature value. It is important to note that the collected temperature data must completely cover at least one temperature fluctuation cycle, and invalid temperature data caused by sensor failure or sudden environmental interference must be removed to ensure that the temperature time-domain data accurately reflects the actual temperature fluctuation characteristics over time in the flexible circuit board production environment, without data loss or time sequence errors. Next, a Fast Fourier Transform (FFT) is performed on the temperature time-domain data to convert the continuous temperature change signal in the time dimension into a power spectral density distribution in the frequency dimension. The magnitude of the power spectral density represents the energy proportion of the temperature fluctuation at the corresponding frequency. Finally, the frequency value corresponding to the peak value in the power spectral density distribution is extracted, and this frequency value is determined as the main temperature fluctuation frequency. This frequency is the core frequency with the largest energy proportion and the most regularity in the temperature fluctuation of the production environment, accurately reflecting the main temperature fluctuation pattern.

[0049] Furthermore, the main fluctuation period can be calculated using the formula: main fluctuation period = 1 / main fluctuation frequency. During the calculation, the units must be consistent; if the main fluctuation frequency is in Hz (1 / second), then the main fluctuation period is in seconds. It can also be converted to units such as minutes or hours according to engineering usage habits. The calculated temperature main fluctuation period is then directly used as the optimized monitoring interval for the flexible circuit board feeding device, replacing the original monitoring interval that exceeds the temperature fluctuation period. This ensures that the acquisition rhythm of the feeding parameters is consistent with the temperature fluctuation rhythm, guaranteeing that the monitoring and control and data acquisition system can accurately and promptly capture the impact of temperature fluctuations on feeding parameters such as step frequency and physical displacement.

[0050] For example, the current flexible circuit board feeding device monitors feeding parameters at 5-minute intervals, while the collected temperature fluctuation period is 3 minutes. This shows that the monitoring interval exceeds the temperature fluctuation period. Therefore, one high-precision temperature sensor with an accuracy of ±0.1℃ is deployed at each of the feeding device's drive motor, cutting station, and roll conveying area. The basic acquisition frequency is set to 1 time / second, and temperature data is continuously collected for 600 seconds. After removing invalid data from two sets of sensor transient interference, a structured temperature time-domain dataset of 598 "timestamp-temperature value" sets is obtained. The data shows that the temperature exhibits regular periodic fluctuations over time within the range of 25℃-30℃. Next, this temperature time-domain dataset is preprocessed by detrending and zero-padding to 600 sets of data. Then, a fast Fourier transform is used to convert it into frequency domain data, and a power spectral density distribution map is plotted. The frequency corresponding to the peak power spectral density is found to be 0.00556Hz, which is determined as the main temperature fluctuation frequency. The main fluctuation period is approximately 1 / 0.00556Hz, which is 180 seconds, or 3 minutes. This 3-minute interval is used as the optimized monitoring interval for the flexible circuit board feeding device, replacing the original 5-minute monitoring interval.

[0051] In one embodiment of this application, after optimizing the monitoring interval using the Fourier transform algorithm in step S160, the following steps are also included: Figure 6 As shown, the specific content is as follows: Step S610: Obtain the adjusted step frequency sequence and the optimized physical displacement sequence; Step S620: Based on the adjusted step frequency sequence and the optimized physical displacement sequence, a linear matching model between the step frequency and the physical displacement is established using the least squares method; Step S630: Determine the error configuration scheme for flexible circuit board production based on the linear matching model.

[0052] Specifically, in the flexible circuit board feeding process, the stepping frequency of the feeding mechanism directly determines the feeding speed. Under the premise of normal equipment operation and no mechanical failures, the stepping frequency and physical displacement show a linear relationship, thus a linear matching model can be established. The linear matching model is y=ax+b, where y is the physical displacement value (dependent variable, unit: mm), x is the stepping frequency value (independent variable, unit: Hz), a is the slope of the linear matching model (representing the change in physical displacement corresponding to a unit change in stepping frequency), and b is the intercept of the linear matching model (representing the basic displacement compensation value of the feeding mechanism). Then, substituting the preprocessed x and y data, the values ​​of a and b are calculated using the least squares method. Next, based on the linear matching model, combined with the process requirements of flexible circuit board production, the operating characteristics of the feeding device, and the optimized monitoring interval, a standardized and implementable error configuration scheme for flexible circuit board production is formulated. The error configuration scheme is a document used for the automated control of the feeding system and the early avoidance of errors, including core quantitative indicators such as parameter matching rules, dynamic adjustment thresholds, deviation warning standards, and parameter calibration cycles.

[0053] For example, the adjusted step frequency sequence is [45.0, 45.2, 45.1, 45.3, 45.2, 45.4, 45.3, 45.2, 45.5, 45.4], and the optimized physical displacement sequence is [22.5, 22.6, 22.55, 22.65, 22.6, 22.7, 22.65, 22.6, 22.75, 22.7]. A linear matching model between the step frequency and physical displacement is established using the least squares method, with a slope a=0.5 and an intercept b=0. The linear matching model is further calculated to be y=0.5x. Finally, based on this linear matching model and a physical displacement accuracy range of ±0.5mm, the optimal step frequency ranges for various production conditions are obtained, such as a theoretical step frequency of 40.0Hz for a target displacement of 20mm, 50.0Hz for a target displacement of 25mm, and 60.0Hz for a target displacement of 30mm. Combining the mechanical response characteristics of the feeding device with the optimized monitoring interval of 3 minutes, the dynamic adjustment threshold of the stepping frequency is set to ±0.2Hz, and the real-time deviation warning value of the physical displacement is set to ±0.3mm. At the same time, based on the operating wear and tear of the feeding device, the model is periodically calibrated every 500 feeding cycles. When the temperature fluctuation of the production environment exceeds ±2℃, data is re-acquired and the linear model is fitted. All quantitative indicators and control rules are integrated to form a complete error configuration scheme for flexible circuit board production.

[0054] In one embodiment of this application, after optimizing the monitoring interval using the Fourier transform algorithm in step S160, the following steps are further included: obtaining the current board thickness and board toughness of the flexible circuit board; adjusting the preset deviation threshold according to the board thickness and board toughness. Specifically, the board thickness of the flexible circuit board refers to the actual physical thickness of the flexible circuit board substrate, which is a physical parameter that determines the ease of board deformation; the board toughness refers to the physical characteristics of the flexible circuit board in resisting flexural and tensile deformation, which directly affects the displacement stability of the board during the feeding process. The standard board thickness parameters and standard board toughness grade parameters of the current production batch can be retrieved from the flexible circuit board production process parameter library, or the actual board thickness and actual board toughness of the flexible circuit board in the current feeding process can be detected in real time using a dedicated board thickness sensor and toughness tester to ensure that the obtained parameters are completely matched with the currently processed flexible circuit board.

[0055] Furthermore, the thinner the board and the higher the board toughness, the more easily the flexible circuit board will bend and shift during the feeding process. Therefore, it is necessary to reduce the preset deviation threshold and improve the feeding accuracy judgment requirements. The thicker the board and the lower the board toughness, the stronger the structural stability of the flexible circuit board and the less likely it is to be deformed. Therefore, the preset deviation threshold can be increased to avoid over-judgment that leads to frequent equipment shutdowns.

[0056] In one embodiment of this application, in step S170, based on the optimized monitoring interval, if the positional accuracy error is not within the preset accuracy range, the self-locking shutdown mechanism of the flexible circuit board feeding device is activated, and the current positional accuracy error is recorded. Specifically, for example, in a high-precision cutting and processing scenario for flexible circuit boards, the monitoring interval for the feeding parameters optimized by the Fourier transform algorithm is 3 minutes, and the preset accuracy range for flexible circuit board cutting and processing is ±0.02 mm. The positional accuracy error of each cutting point is continuously collected according to the optimized monitoring interval of 3 minutes. During a certain monitoring period, the positional accuracy errors of three cutting points were collected, which were 0.03 mm, 0.025 mm, and 0.01 mm, respectively. The positional accuracy errors of the first two cutting points were not within the preset accuracy range of ±0.02 mm. The self-locking shutdown mechanism of the flexible circuit board feeding device was immediately activated, the power supply of the feeding device was cut off and the mechanical transmission structure was locked, and all feeding and cutting actions were stopped. At the same time, the positional accuracy error value at the current moment, the time of error occurrence, the optimized monitoring interval of 3 minutes, the stepping frequency of the feeding device, the ambient temperature and other complete traceability data were recorded and stored in the supervision and control and data acquisition system database. This provides a complete data source for subsequent fault diagnosis, parameter adjustment and error tracing.

[0057] This application also provides a real-time monitoring system for flexible circuit board feeding parameters. This system may include an acquisition module, a first determination module, a second determination module, an adjustment module, a third determination module, an optimization module, and a determination module. The acquisition module acquires the feeding parameters of the flexible circuit board feeding device, including a step frequency sequence and a physical displacement sequence. The first determination module acquires a preset number of feeding attempts. If, within the preset number of feeding attempts, the feeding gap deviation between the physical displacement sequence and the ideal displacement value exceeds a preset deviation threshold, it is determined that there is error accumulation in the current feeding process, and the feeding gap deviation value of the first feeding attempt is used as the error accumulation benchmark value. The second determination module determines the error accumulation trend value based on the error accumulation benchmark value and each feeding gap deviation value. The adjustment module adjusts the step frequency sequence using a feedforward compensation adaptive PID algorithm to optimize the physical displacement sequence if the error accumulation trend value continues to increase, and extracts the optimized value. The physical displacement sequence includes the positions of each cutting point of the flexible circuit board feeding device; a third determination module, which uses a nonlinear interpolation algorithm to calibrate the positions of each cutting point. If the positional accuracy errors of each calibrated cutting point are within a preset accuracy range, the current stepping frequency and physical displacement are determined to be matched, and the monitoring interval and temperature fluctuation period of the current flexible circuit board feeding device are obtained respectively; an optimization module, which uses a Fourier transform algorithm to optimize the monitoring interval if the monitoring interval exceeds the temperature fluctuation period; and a start module, which, based on the optimized monitoring interval, starts the self-locking shutdown mechanism of the flexible circuit board feeding device if the positional accuracy error is not within a preset accuracy range, and records the current positional accuracy error.

[0058] It should be noted that the embodiments of the flexible circuit board feeding parameter real-time monitoring system provided in this application can be used to execute the processing flow of the embodiments of the flexible circuit board feeding parameter real-time monitoring method in the above embodiments. Its functions will not be repeated here, but can be referred to the detailed description of the above method embodiments.

[0059] This application also provides an electronic device, which includes one or more processors and memory resources represented by a memory for storing instructions executable by the processor, such as application programs. The application programs stored in the memory may include one or more modules, each corresponding to a set of instructions. Furthermore, the processor is configured to execute instructions to perform the aforementioned real-time monitoring method for flexible circuit board feeding parameters.

[0060] The electronic device may also include a power supply component configured to perform power management of the electronic device, a wired or wireless network interface configured to connect the electronic device to a network, and an input / output (I / O) interface. The electronic device can be operated based on operating devices stored in memory, such as Windows Server™, Mac OS X™, Unix™, Linux™, FreeBSD™, or similar.

[0061] In one embodiment, a computer device, which may be a server, is also provided. The computer device includes a processor, memory, input / output interfaces (I / O), and a communication interface. The processor, memory, and I / O interfaces are connected via a system bus, and the communication interface is connected to the system bus via the I / O interfaces. The processor of the computer device provides computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and internal memory. The non-volatile storage medium stores an operating system, computer programs, and a database. The internal memory provides an environment for the operation of the operating system and computer programs in the non-volatile storage medium. The database of the computer device stores data. The I / O interfaces of the computer device are used for exchanging information between the processor and external devices. The communication interface of the computer device is used for communicating with external terminals via a network connection. When the computer program is executed by the processor, it implements a method for real-time monitoring of flexible circuit board feeding parameters.

[0062] In one embodiment, a computer device is provided, which may be a terminal. The computer device includes a processor, memory, an input / output interface, a communication interface, a display unit, and an input device. The processor, memory, and input / output interface are connected via a system bus, and the communication interface, display unit, and input device are also connected to the system bus via the input / output interface. The processor of the computer device provides computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and internal memory. The non-volatile storage medium stores an operating system and computer programs. The internal memory provides an environment for the operation of the operating system and computer programs in the non-volatile storage medium. The input / output interface of the computer device is used for exchanging information between the processor and external devices. The communication interface of the computer device is used for wired or wireless communication with external terminals; wireless communication can be achieved through Wi-Fi, mobile cellular networks, NFC (Near Field Communication), or other technologies. When the computer program is executed by the processor, it implements a method for real-time monitoring of flexible circuit board feeding parameters. The display unit of the computer device is used to form a visually visible image and may be a display screen, a projection device, or a virtual reality imaging device. The display screen can be an LCD screen or an e-ink screen. The input device of the computer device can be a touch layer covering the display screen, or buttons, trackballs, or touchpads set on the casing of the computer device, or external keyboards, touchpads, or mice, etc.

[0063] This application also provides a non-transitory computer-readable storage medium, which, when the instructions in the storage medium are executed by the processor of the aforementioned electronic device, enables the electronic device to perform a real-time monitoring method for flexible circuit board feeding parameters.

[0064] This application may take the form of a computer program product implemented on one or more storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing program code. Computer-readable storage media include permanent and non-permanent, removable and non-removable media, and information storage can be implemented by any method or technology. Information may be computer-readable instructions, data structures, program modules, or other data. Examples of computer storage media include, but are not limited to: phase-change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technologies, CD-ROM, digital versatile optical disc (DVD) or other optical storage, magnetic tape, magnetic disk storage or other magnetic storage devices, or any other non-transfer medium that can be used to store information accessible by a computing device.

[0065] It should be noted that, in this document, the terms "comprising," "including," and any other variations are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Specific examples have been used in this document to illustrate the principles and implementation methods of the technical solutions of this application. The above examples are only for the purpose of helping to understand the methods and core ideas of this application. The above descriptions are merely preferred embodiments of this application. It should be pointed out that, due to the limitations of written expression and the objective existence of infinite specific structures, those skilled in the art can make several improvements, modifications, or changes without departing from the principles of this application, and can also combine the above technical features in an appropriate manner; these improvements, modifications, changes, or combinations, or the direct application of the concept and technical solutions of this application to other situations without modification, should all be considered within the scope of protection of this application.

Claims

1. A method for real-time monitoring of feeding parameters for flexible circuit boards, characterized in that, include: The feeding parameters of the flexible circuit board feeding device are obtained, including the step frequency sequence and the physical displacement sequence. A preset number of feedings is obtained. If the feeding gap deviation between the physical displacement sequence and the ideal displacement value exceeds a preset deviation threshold within the preset number of feedings, it is determined that there is an error accumulation in the current feeding process, and the feeding gap deviation value of the first feeding is used as the error accumulation benchmark value. The error accumulation trend value is determined based on the error accumulation benchmark value and each of the feeding gap deviation values; If the cumulative error trend value continues to increase, a feedforward compensation adaptive PID algorithm is used to adjust the step frequency sequence to optimize the physical displacement sequence, and the positions of each cutting point of the flexible circuit board feeding device in the optimized physical displacement sequence are extracted. A nonlinear interpolation algorithm is used to calibrate the position of each cutting point. If the positional accuracy error of each cutting point after calibration is within the preset accuracy range, it is determined that the current stepping frequency and physical displacement are matched, and the monitoring interval and temperature fluctuation cycle of the current flexible circuit board feeding device are obtained respectively. If the monitoring interval exceeds the temperature fluctuation period, the monitoring interval is optimized using a Fourier transform algorithm. Based on the optimized monitoring interval, if the position accuracy error is not within the preset accuracy range, the self-locking shutdown mechanism of the flexible circuit board feeding device is activated, and the current position accuracy error is recorded.

2. The method for real-time monitoring of flexible circuit board feeding parameters according to claim 1, characterized in that, The process of obtaining the preset number of feeds includes: A coupling deviation model is established based on the step frequency sequence and the physical displacement sequence; The preset number of feedings is determined based on the coupling deviation model.

3. The method for real-time monitoring of flexible circuit board feeding parameters according to claim 1, characterized in that, The process of obtaining the feeding parameters of the flexible circuit board feeding device includes: Acquire stepping frequency data and physical displacement data of the flexible circuit board feeding device; Based on the step frequency data and the physical displacement data, the Kalman filter algorithm is used to determine the step frequency sequence and the physical displacement sequence. If the time synchronization deviation between the step frequency sequence and the physical displacement sequence exceeds a preset synchronization deviation threshold, then the step frequency sequence and the physical displacement sequence are time-calibrated.

4. The method for real-time monitoring of flexible circuit board feeding parameters according to claim 1, characterized in that, The step of determining the cumulative error trend value based on the cumulative error benchmark value and each of the feeding gap deviation values ​​includes: The cumulative error benchmark value is added to each of the feeding gap deviation values, and the result of the addition is used as the cumulative error trend value.

5. The method for real-time monitoring of flexible circuit board feeding parameters according to claim 1, characterized in that, The step frequency sequence is adjusted using a PID control algorithm to optimize the physical displacement sequence, including: Based on the feeding gap deviation value, a PID control algorithm is used to determine the adjustment range of the stepping frequency sequence; The stepping frequency sequence is adjusted according to the adjustment range, and the flexible circuit board feeding device is driven according to the adjusted stepping frequency sequence to optimize the physical displacement sequence.

6. The method for real-time monitoring of flexible circuit board feeding parameters according to claim 1, characterized in that, The extracted and optimized physical displacement sequence includes the positions of each cutting point of the flexible circuit board feeding device, including: Extract the displacement values ​​of each displacement point from the optimized physical displacement sequence; If the rate of change of the displacement value exceeds a preset rate of change threshold, then the current displacement point is taken as the cutting point.

7. The method for real-time monitoring of flexible circuit board feeding parameters according to claim 1, characterized in that, The optimization of the monitoring interval using the Fourier transform algorithm includes: Obtain the current time-domain temperature data of the flexible circuit board feeding device; Based on the temperature time-domain data, the Fourier transform algorithm is used to determine the main fluctuation frequency; The main fluctuation period is determined based on the main fluctuation frequency, and the main fluctuation period is used as the optimized monitoring interval.

8. The method for real-time monitoring of flexible circuit board feeding parameters according to claim 1, characterized in that, After optimizing the monitoring interval using the Fourier transform algorithm, the method further includes: Obtain the adjusted step frequency sequence and the optimized physical displacement sequence; Based on the adjusted step frequency sequence and the optimized physical displacement sequence, a linear matching model between the step frequency and the physical displacement is established using the least squares method. The error configuration scheme for flexible circuit board production is determined based on the linear matching model.

9. The method for real-time monitoring of flexible circuit board feeding parameters according to claim 1, characterized in that, After optimizing the monitoring interval using the Fourier transform algorithm, the method further includes: Obtain the current board thickness and board toughness of the flexible circuit board; The preset deviation threshold is adjusted based on the thickness and toughness of the plate.

10. A real-time monitoring system for feeding parameters of flexible circuit boards, characterized in that, include: The acquisition module is used to acquire the feeding parameters of the flexible circuit board feeding device, the feeding parameters including the step frequency sequence and the physical displacement sequence; The first determining module is used to obtain a preset number of feedings. If the feeding gap deviation between the physical displacement sequence and the ideal displacement value exceeds a preset deviation threshold within the preset number of feedings, it is determined that there is error accumulation in the current feeding process, and the feeding gap deviation value of the first feeding is used as the error accumulation benchmark value. The second determining module is used to determine the error accumulation trend value based on the error accumulation benchmark value and each of the feeding gap deviation values; An adjustment module is used to adjust the step frequency sequence to optimize the physical displacement sequence by using a feedforward compensation adaptive PID algorithm if the cumulative error trend value continues to increase, and to extract the positions of each cutting point of the flexible circuit board feeding device in the optimized physical displacement sequence. The third determining module is used to calibrate the position of each cutting point using a nonlinear interpolation algorithm. If the position accuracy error of each cutting point after calibration is within the preset accuracy range, it is determined that the current stepping frequency and physical displacement are matched, and the monitoring interval and temperature fluctuation cycle of the current feeding parameters of the flexible circuit board feeding device are obtained respectively. An optimization module is used to optimize the monitoring interval using a Fourier transform algorithm if the monitoring interval exceeds the temperature fluctuation period. The startup module is used to activate the self-locking shutdown mechanism of the flexible circuit board feeding device and record the current position accuracy error if the position accuracy error is not within the preset accuracy range based on the optimized monitoring interval.

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