A DC calibration method, system, computer-readable storage medium and electronic device

Abstract

The application relates to the technical field of board card calibration, and particularly discloses a DC calibration method, a DC calibration system, a computer readable storage medium and an electronic device. An accurate performance evaluation is provided for each digital board card by calculating a dynamic weight factor. Based on the evaluation, a tree-shaped calibration path is constructed to upgrade single-point calibration to large-scale parallel fission calibration. The system allocates different numbers of tasks to the calibration board cards according to the weight. This not only realizes optimal allocation of resources and improves calibration efficiency, but also effectively suppresses error transmission and reduces calibration error from the source. Finally, real-time monitoring and dynamic path adjustment constitute a closed-loop control, which can isolate abnormal board cards in time, thereby further consolidating the error suppression effect and finally ensuring that the whole calibration process has high efficiency and high precision.

Description

Technical Field

[0001] This invention relates to the field of circuit board calibration technology, and in particular to a DC calibration method, system, computer-readable storage medium, and electronic device. Background Technology

[0002] In automated test equipment (ATE) systems, the DC parameters of digital boards, such as the gain and bias of ADCs / DACs, are crucial for ensuring test accuracy and therefore require regular calibration. However, traditional calibration methods present numerous challenges.

[0003] First, inefficiency is one of its main problems. Each digital board must be connected to a high-precision multimeter for individual calibration, which is not only time-consuming but also causes the multimeter resources to be occupied for a long time, seriously affecting the overall throughput of the test system.

[0004] Secondly, traditional methods also have limitations in terms of scalability. Calibration time increases linearly with the number of boards, which becomes a significant bottleneck on large-scale production lines, making it difficult to meet the ever-increasing testing demands. Finally, some existing fission calibration schemes suffer from error accumulation. As the calibration transfer level increases, errors accumulate continuously, and there is a lack of effective control mechanisms to suppress these errors, ultimately affecting the accuracy of calibration and the reliability of testing. Summary of the Invention

[0005] The purpose of this invention is to provide a DC calibration method, system, computer-readable storage medium, and electronic device to improve the calibration rate and reduce calibration errors.

[0006] This invention discloses a DC calibration method, the method comprising:

[0007] Calculate the dynamic weighting factor for each digital board; wherein the dynamic weighting factor is determined based on the accuracy coefficient and temperature coefficient of the digital board.

[0008] A tree-like calibration path is constructed, which includes multiple calibration levels. Each calibration board in the calibration level is used to provide a calibration reference for the board to be calibrated in the next level.

[0009] When the calibration board is in normal working condition, a corresponding number of calibration boards are allocated to the calibration board based on the size of the dynamic weighting factor.

[0010] The digital board is monitored in real time, and the calibration path is adjusted when the calibration board is detected to be in an abnormal working state.

[0011] Furthermore, the formula for calculating the dynamic weighting factor is as follows:

[0012] W = α × S_acc + β × S_temp;

[0013] Where S_acc=1-(recent calibration error / 0.1%) is the accuracy coefficient; S_temp=1-(|temperature drift coefficient| / 5ppm / ℃) is the temperature coefficient; and α and β are adjustable coefficients.

[0014] Furthermore, when the dynamic weighting factor is greater than or equal to 0.8 and the temperature is less than 40°C, the corresponding digital board can be used as a calibration board.

[0015] When the dynamic weighting factor is less than 0.8 or the temperature is greater than or equal to 40°C, the corresponding digital board is only used as a board to be calibrated.

[0016] Furthermore, when the dynamic weighting factor is greater than or equal to 0.8 and less than 0.9, the corresponding calibration board can calibrate one of the boards to be calibrated.

[0017] When the dynamic weighting factor is greater than or equal to 0.9, the corresponding calibration board can calibrate multiple boards to be calibrated.

[0018] Furthermore, the number of levels in the tree-like calibration path is greater than or equal to 2 and less than or equal to 4.

[0019] Furthermore, calibration boards are assigned to be calibrated in descending order of their dynamic weighting factors.

[0020] The boards to be calibrated are calibrated in descending order of their dynamic weighting factors.

[0021] Furthermore, the digital board is monitored in real time, and when an abnormality is detected in the calibration board, the calibration path is adjusted, including:

[0022] When the temperature of the calibration board is greater than or equal to 40°C, or when the real-time error of the calibration board is greater than or equal to 0.1%, the calibration board is marked as being in an abnormal state, and the calibration work of the calibration board is suspended. The remaining calibration boards at the same level as the abnormal calibration board are then selected to calibrate the board to be calibrated.

[0023] On the other hand, the present invention also discloses a dynamic path fission DC calibration system based on weighting factors, the system comprising:

[0024] A calculation module is used to calculate the dynamic weighting factor of each digital board; wherein the dynamic weighting factor is determined based on the accuracy coefficient and the temperature coefficient of the digital board.

[0025] A tree-structured calibration module is used to construct tree-structured calibration paths, wherein each tree-structured calibration path includes multiple calibration levels, and the calibration board in each calibration level is used to provide a calibration reference for the board to be calibrated in the next level.

[0026] The board allocation module is used to allocate a corresponding number of calibration boards to the calibration board based on the size of the dynamic weighting factor when the calibration board is in normal working condition.

[0027] The adjustment module is used to monitor the digital board in real time and adjust the calibration path when the calibration board is detected to be in an abnormal working state.

[0028] On the other hand, the present invention also discloses a computer-readable storage medium storing a computer program that, when executed by a processor, implements the steps of the DC calibration method described above.

[0029] On the other hand, the present invention also discloses an electronic device, comprising: a processor; a memory; and a computer program stored in the memory and executable on the processor, wherein the computer program, when executed by the processor, implements the steps of the DC calibration method described above.

[0030] Compared with the prior art, the present invention has at least the following beneficial effects:

[0031] This invention provides accurate performance evaluation for each digital board by calculating dynamic weighting factors. Based on this evaluation, a tree-like calibration path is constructed, upgrading single-point calibration to large-scale parallel fission calibration. The system assigns different numbers of tasks to the calibration boards according to their weights. This not only optimizes resource allocation and improves calibration efficiency but also effectively suppresses error propagation at the source, reducing calibration errors. Finally, real-time monitoring and dynamic path adjustment constitute a closed-loop control system, which can immediately isolate abnormal boards, thereby further consolidating the error suppression effect and ultimately ensuring that the entire calibration process is both highly efficient and highly accurate. Attached Figure Description

[0032] Figure 1 This is a simplified flowchart of the DC calibration method in Embodiment 1 of the present invention;

[0033] Figure 2 This is a simplified flowchart of another method of the DC calibration method in Embodiment 1 of the present invention;

[0034] Figure 3 This is a simplified flowchart of another method of the DC calibration method in Embodiment 1 of the present invention;

[0035] Figure 4 This is a simplified flowchart of the process of allocating digital boards using the DC calibration method in Embodiment 1 of the present invention. Detailed Implementation

[0036] The DC calibration method, system, computer-readable storage medium, and electronic device of the present invention will now be described with reference to schematic diagrams, which illustrate preferred embodiments of the invention. It should be understood that those skilled in the art can modify the invention described herein while still achieving its advantageous effects. Therefore, the following description should be understood as being of general knowledge to those skilled in the art and is not intended to limit the invention.

[0037] The invention is described more specifically by way of example in the following paragraphs with reference to the accompanying drawings. The advantages and features of the invention will become clearer from the following description and claims. It should be noted that the drawings are in a very simplified form and use non-precise proportions, and are only used to facilitate and clarify the illustration of the embodiments of the invention.

[0038] Example 1

[0039] Please refer to Figures 1-4 This embodiment discloses a DC calibration method, the method comprising:

[0040] S1. Calculate the dynamic weighting factor for each digital board; wherein the dynamic weighting factor is determined based on the accuracy coefficient and temperature coefficient of the digital board;

[0041] S2. Construct a tree-like calibration path that includes multiple calibration levels, wherein the calibration board in each calibration level is used to provide a calibration reference for the board to be calibrated in the next level;

[0042] S3. When the calibration board is in normal working condition, allocate a corresponding number of calibration boards to the calibration board based on the magnitude of the dynamic weighting factor;

[0043] S4. Monitor the digital board in real time, and adjust the calibration path when the calibration board is detected to be in an abnormal working state.

[0044] In this embodiment, a precise performance evaluation is provided for each digital board by calculating a dynamic weighting factor. Based on this evaluation, a tree-like calibration path is constructed, upgrading single-point calibration to large-scale parallel fission calibration. The system assigns different numbers of tasks to the calibration boards according to their weights. This not only optimizes resource allocation and improves calibration efficiency but also effectively suppresses error propagation at the source, reducing calibration errors. Finally, real-time monitoring and dynamic path adjustment constitute a closed-loop control, which can immediately isolate abnormal boards, thereby further consolidating the error suppression effect and ultimately ensuring that the entire calibration process is both highly efficient and highly accurate.

[0045] Furthermore, the formula for calculating the dynamic weighting factor is as follows:

[0046] W = α × S_acc + β × S_temp.

[0047] Where S_acc=1-(recent calibration error / 0.1%) is the accuracy coefficient; S_temp=1-(|temperature drift coefficient| / 5ppm / ℃) is the temperature coefficient; and α and β are adjustable coefficients.

[0048] Specifically, the accuracy coefficient S_acc is a parameter calculated by the ratio of the most recent calibration error to a preset error threshold. It can be normalized by the ratio of the calibration error measurement value to 0.1%, and is used to characterize the calibration accuracy status of the digital board.

[0049] The temperature coefficient S_temp is a parameter calculated by the ratio of the absolute value of the temperature drift coefficient to a preset temperature stability threshold. Specifically, it can be normalized by the ratio of the absolute value of the temperature drift coefficient to 5ppm / ℃, and is used to characterize the temperature stability of the digital board.

[0050] Adjustable coefficients α and β are parameters used to adjust the weight ratio of the accuracy coefficient and the temperature coefficient in the dynamic weighting factor. Specifically, they can be dynamically adjusted using preset empirical values ​​or adaptive algorithms to balance the impact of calibration accuracy and temperature stability on the weighting. In a specific embodiment, α and β are 0.7 and 0.3, respectively.

[0051] Those skilled in the art can flexibly adjust the weight ratio of accuracy and temperature according to actual needs. For example, in a high-temperature environment, the β value can be increased to enhance the influence of temperature stability, thereby improving the robustness of the calibration path.

[0052] In this embodiment, by using a dynamic weighting factor to linearly weight the accuracy coefficient and the temperature coefficient, the calibration accuracy and temperature stability of the digital board can be comprehensively reflected.

[0053] In one specific embodiment, the dynamic weighting factor is calculated by linearly weighting the accuracy coefficient and the temperature coefficient, thus comprehensively reflecting the calibration accuracy and temperature stability of the digital board. For example, when the most recent calibration error of a digital board is 0.05%, its accuracy coefficient S_acc can be calculated as 1 - (0.05% / 0.1%) = 0.5; if the temperature drift coefficient of the board is 3 ppm / ℃, then the temperature coefficient S_temp can be calculated as 1 - (3 / 5) = 0.4. Assuming α = 0.7 and β = 0.3, then the dynamic weighting factor W = 0.47. This calculation method allows for the priority selection of boards with high accuracy and strong temperature stability as calibration benchmarks when constructing calibration paths, thereby suppressing error propagation.

[0054] In this embodiment, when the dynamic weighting factor is greater than or equal to 0.8 and the temperature is less than 40°C, the corresponding digital board can be used as a calibration board; when the dynamic weighting factor is less than 0.8 or the temperature is greater than or equal to 40°C, the corresponding digital board is only a calibration board.

[0055] In one specific embodiment, the system first selects boards with a dynamic weighting factor of 0.8 and an operating temperature below 40°C as candidate calibration sources. For example, if a board's most recent calibration error is 0.05% and its temperature drift coefficient is 3ppm / °C, its calculated dynamic weighting factor is 0.8. If the measured temperature is 35°C, the board is deemed qualified for calibration. Conversely, if a board has a dynamic weighting factor of 0.85 but its temperature reaches 42°C, the system will automatically disqualify it from calibration. This dual-condition determination mechanism ensures that the calibration board simultaneously meets the requirements for accuracy stability and thermal stability.

[0056] Furthermore, when the dynamic weighting factor is greater than or equal to 0.8 and less than 0.9, the corresponding digital board can calibrate one of the boards to be calibrated; when the dynamic weighting factor is greater than or equal to 0.9, the corresponding digital board can calibrate multiple boards to be calibrated.

[0057] In the specific judgment process, a dynamic weighting factor is first calculated by collecting real-time temperature data and historical calibration error data from the board. When the factor value reaches 0.8 but does not exceed 0.9, it indicates that the board is in a moderately reliable state. In this case, only a single board to be calibrated is allowed to be calibrated to control the risk of error propagation. When the factor value exceeds 0.9, it indicates that the board is in a highly stable state. At this time, its multi-target calibration capability can be activated, such as simultaneously calibrating 1, 2, 3, or 4 boards to be calibrated.

[0058] This embodiment divides the load range into multiple levels by dynamic weighting factors, realizing flexible allocation of calibration resources and significantly improving calibration efficiency while ensuring calibration accuracy.

[0059] Furthermore, the number of levels in the tree-like calibration path is greater than or equal to 2 and less than or equal to 4.

[0060] During the calibration system's operation, setting the lower limit of the number of levels to 2 ensures at least two levels of calibration reference transfer, avoiding excessive resource concentration caused by single-point calibration. The upper limit of the number of levels is set to 4, calculated based on the error propagation model. When the number of levels exceeds 4, the cumulative error of the end-point boards will exceed the allowable threshold. In actual operation, the system controller automatically constructs the hierarchical structure based on dynamically calculated weighting factors in real time. For example, when a sufficient number of high-weighting factor boards are detected, a 3-layer structure is prioritized, expanding to a 4-layer structure when board resources are scarce.

[0061] This embodiment significantly optimizes ATE system DC parameter calibration by dynamically constructing a tree-like calibration path with 2 to 4 layers. A lower layer limit of 2 ensures effective transfer of calibration benchmarks, avoiding excessive concentration of resources at a single point. An upper layer limit of 4 precisely controls accumulated errors based on an error model, improving the accuracy of the final board. The system controller flexibly constructs a 3- or 4-layer structure based on real-time dynamic weighting factors: when high-weight boards are plentiful, a 3-layer structure is prioritized to improve efficiency; when resources are scarce, a 4-layer structure is expanded to maintain accuracy and task allocation. This intelligent strategy comprehensively improves calibration efficiency, scalability, and accuracy control capabilities.

[0062] In one specific embodiment, suppose there are 100 boards, of which a sufficient number (e.g., 10-15) have very high weighting factors (e.g., above 0.95), making them highly reliable calibration source boards. In this case, the system controller can construct a three-layer calibration structure to ensure both accuracy and efficiency.

[0063] First layer (reference source): Select 2-3 of the most weighted boards from these 10-15 high-weight boards as the core calibration reference source (first layer), as they have the highest accuracy.

[0064] The second layer (intermediate calibration benchmarks): These core calibration sources (first layer) will calibrate and establish the next batch of approximately 15-20 high-weight boards (e.g., weights between 0.85 and 0.95) as "intermediate calibration benchmarks" (second layer). After these second-layer boards are calibrated, they also possess high accuracy and can undertake calibration tasks.

[0065] The third layer (boards to be calibrated): The remaining approximately 70-80 boards (whose accuracy may vary) are calibrated by these 15-20 intermediate calibration benchmarks (second layer). In this way, each second-layer board may only need to calibrate 3-5 third-layer boards.

[0066] Furthermore, calibration boards are assigned to be calibrated in descending order of their dynamic weight factors; and the calibration boards are calibrated in descending order of their dynamic weight factors.

[0067] Specifically, during the calibration path construction process, calibration boards are allocated according to a descending order of their dynamic weighting factors. For example, a calibration board with a dynamic weighting factor of 0.95 is allocated up to three calibration boards, while a calibration board with a dynamic weighting factor of 0.85 is allocated only one. Simultaneously, the calibration boards are arranged in descending order of their own dynamic weighting factors to form a calibration queue, with boards having a dynamic weighting factor of 0.93 being calibrated first, and boards with a dynamic weighting factor of 0.78 being processed later. This dual-sorting mechanism ensures that high-precision and stable calibration boards take on more calibration tasks, while boards with urgent calibration needs receive priority resource allocation.

[0068] Through the above technical solution, this application effectively resolves the conflict between error accumulation control and resource allocation efficiency during large-scale digital board calibration. Optimizing the allocation order of calibration boards reduces the frequency of using low-reliability calibration sources, while the ordered calibration of boards reduces the impact of high-error boards on subsequent levels, thereby improving calibration efficiency while maintaining the overall system accuracy.

[0069] Furthermore, the digital board is monitored in real time, and when an abnormality is detected in the calibration board, the calibration path is adjusted, including:

[0070] When the temperature of the calibration board is greater than or equal to 40°C, or when the real-time error of the calibration board is greater than or equal to 0.1%, the calibration board is determined to be in an abnormal state.

[0071] During the calibration process, the temperature sensor collects the board's operating temperature at a fixed frequency, and the error detection unit simultaneously calculates the current calibration error value. When the temperature data reaches 40℃ or the error value exceeds 0.1%, the system automatically marks the board as an unusable node. At this time, the path reconstruction module is immediately activated. By traversing the dynamic weight factors of the remaining available boards, it selects the second-best node to replace the abnormal board and recalculates the hierarchical allocation relationship. For example, when the main calibration board at a certain level experiences an abnormal temperature rise, the system can automatically activate the backup board ranked second in dynamic weight factor at that level as the new reference source, while simultaneously reassigning the boards to be calibrated under the original calibration path to the new reference node.

[0072] The following specific embodiments describe how to efficiently and accurately calibrate the DC parameters of digital boards in an ATE test system containing 100 digital boards through dynamic weighting factors and hierarchical fission mechanisms.

[0073] S1. Initial Calibration

[0074] At the start of the calibration process, the system first performs DC parameter calibration on the three core digital boards manually or semi-automatically by connecting a high-precision multimeter. For example, it performs initial calibration on digital boards A, B, and C, and sets their initial dynamic weighting factors (W) to high values ​​based on the calibration results, such as W=0.95 for all of them. These three boards serve as the initial calibration reference sources, forming the "calibration source digital board queue". Simultaneously, the system adds the remaining 97 digital boards (digital boards 4 to 100) to the "digital board queue to be calibrated".

[0075] S2. The first round of dynamic allocation and calibration cycle system begins to traverse the boards in the "calibration source digital board queue" to carry out the first round of calibration task allocation and execution.

[0076] S21. Traverse the source boards: Retrieve digital board A (W=0.95): The system checks its weight to be 0.95 and, according to the rule (source board weight ≥ 0.9), assigns it 3 boards to be calibrated. Assume that digital board D, digital board E, and digital board F are retrieved from the "digital board queue to be calibrated" as target boards.

[0077] S22. Perform calibration and weight update: Calibrate digital board D: The DAC output of digital board A is set to a standard voltage. The ADC of digital board D measures and calculates the calibration error. Simultaneously, considering environmental factors such as temperature, the new dynamic weighting factor W_new of digital board D is calculated. Assume the calculated W_new of digital board D is 0.85.

[0078] S23. Qualification judgment: Since W_new (0.85) ≥ 0.8 for digital board D, digital board D is judged to be qualified and added to the "calibration source digital board queue" so that it can also be used as a calibration source to calibrate other boards in subsequent rounds.

[0079] S24. Calibrate digital board E: Calibration is also performed by digital board A. Assume that W_new = 0.75 for digital board E.

[0080] S25. Qualification Judgment: Since W_new (0.75) < 0.8 for digital board E, digital board E is marked as a "leaf node". This means that it has been calibrated, but due to insufficient accuracy, it will no longer be allowed to calibrate other boards, thereby reducing the propagation and contamination of errors.

[0081] S26. Calibrate digital board F: Assuming that digital board F has W_new = 0.90, it is also added to the "calibration source digital board queue".

[0082] S27. Take out digital board B (W=0.93): Similarly, digital board B has a weight of 0.93 (≥0.9), it is assigned 3 boards to be calibrated (e.g., digital boards G, H, I) and calibration is performed, with eligibility judgment and queue update based on W_new.

[0083] S28. Take out digital board C (W=0.94): As above, digital board C is also assigned 3 boards to be calibrated (e.g., digital boards J, K, L) and calibration and judgment are performed.

[0084] Once the initial digital boards A, B, and C in the "calibration source digital board queue" have finished processing their assigned target boards, the first round of dynamic allocation and calibration cycle ends. At this point, the number of boards in the "digital board queue to be calibrated" decreases, while new, eligible calibration source boards may be added to the "calibration source digital board queue".

[0085] The entire system will continuously perform multiple rounds of such dynamic allocation and calibration cycles, with new qualified calibration sources being added continuously until all 97 boards to be calibrated have been processed (either becoming new calibration boards or becoming boards to be calibrated).

[0086] Example 2

[0087] Based on the same inventive concept, this embodiment discloses a DC calibration system, the system comprising:

[0088] A calculation module is used to calculate the dynamic weighting factor of each digital board; wherein the dynamic weighting factor is determined based on the accuracy coefficient and the temperature coefficient of the digital board.

[0089] A tree-structured calibration module is used to construct tree-structured calibration paths, wherein each tree-structured calibration path includes multiple calibration levels, and the calibration board in each calibration level is used to provide a calibration reference for the board to be calibrated in the next level.

[0090] The board allocation module is used to allocate a corresponding number of calibration boards to the calibration board based on the size of the dynamic weighting factor when the calibration board is in normal working condition.

[0091] The adjustment module is used to monitor the digital board in real time and adjust the calibration path when the calibration board is detected to be in an abnormal working state.

[0092] It is understood that the technical effect that the dynamic path fission DC calibration system based on weight factors disclosed in this embodiment can achieve is the same as the technical effect that the DC calibration method in Embodiment 1 can achieve, and will not be repeated here.

[0093] Obviously, those skilled in the art can make various modifications and variations to this invention without departing from its spirit and scope. Therefore, if these modifications and variations fall within the scope of the claims of this invention and their equivalents, this invention also intends to include these modifications and variations.

Claims

1. A DC calibration method, characterized in that, The method includes: Calculate the dynamic weighting factor for each digital board; wherein the dynamic weighting factor is determined based on the accuracy coefficient and temperature coefficient of the digital board. A tree-structured calibration path is constructed, comprising multiple calibration levels, wherein each calibration board in the calibration level provides a calibration reference for the board to be calibrated in the next level. When the calibration board is in normal working condition, a corresponding number of calibration boards are allocated to the calibration board based on the magnitude of the dynamic weighting factor. The dynamic weighting factor is W = α × S_acc + β × S_temp; where S_acc = 1 - (recent calibration error / 0.1%), which is the accuracy coefficient; S_temp = 1 - (|temperature drift coefficient| / 5ppm / ℃), which is the temperature coefficient; and α and β are adjustable coefficients. The digital board is monitored in real time, and the calibration path is adjusted when the calibration board is detected to be in an abnormal working state.

2. The DC calibration method as described in claim 1, characterized in that, When the dynamic weighting factor is greater than or equal to 0.8 and the temperature is less than 40°C, the corresponding digital board can be used as a calibration board. When the dynamic weighting factor is less than 0.8 or the temperature is greater than or equal to 40°C, the corresponding digital board is only a board to be calibrated.

3. The DC calibration method as described in claim 2, characterized in that, When the dynamic weighting factor is greater than or equal to 0.8 and less than 0.9, the corresponding calibration board can calibrate one of the boards to be calibrated. When the dynamic weighting factor is greater than or equal to 0.9, the corresponding calibration board can calibrate multiple boards to be calibrated.

4. The DC calibration method as described in claim 3, characterized in that, The number of levels in the tree-structured calibration path is greater than or equal to 2 and less than or equal to 4.

5. The DC calibration method as described in claim 4, characterized in that, The calibration boards are assigned to be calibrated in descending order of their dynamic weighting factors. The boards to be calibrated are calibrated in descending order of their dynamic weighting factors.

6. The DC calibration method as described in claim 1, characterized in that, Real-time monitoring of the digital board; when an abnormality is detected in the calibration board, adjusting the calibration path includes: When the temperature of the calibration board is greater than or equal to 40°C, or when the real-time error of the calibration board is greater than or equal to 0.1%, the calibration board is marked as being in an abnormal state, and the calibration work of the calibration board is suspended. The remaining calibration boards at the same level as the abnormal calibration board are then selected to calibrate the board to be calibrated.

7. A DC calibration system, characterized in that, The system includes: A calculation module is used to calculate the dynamic weighting factor of each digital board; wherein the dynamic weighting factor is determined based on the accuracy coefficient and the temperature coefficient of the digital board. A tree-structured calibration module is used to construct tree-structured calibration paths, wherein each tree-structured calibration path includes multiple calibration levels, and the calibration board in each calibration level is used to provide a calibration reference for the board to be calibrated in the next level. The board allocation module is used to allocate a corresponding number of calibration boards to the calibration board based on the magnitude of the dynamic weighting factor when the calibration board is in normal working condition. The dynamic weighting factor is W = α × S_acc + β × S_temp; where S_acc = 1 - (recent calibration error / 0.1%), which is the accuracy coefficient; S_temp = 1 - (|temperature drift coefficient| / 5ppm / ℃), which is the temperature coefficient; and α and β are adjustable coefficients. The adjustment module is used to monitor the digital board in real time and adjust the calibration path when the calibration board is detected to be in an abnormal working state.

8. A computer-readable storage medium, characterized in that, The storage medium stores a computer program that, when executed by a processor, implements the steps of the DC calibration method as described in any one of claims 1-6.

9. An electronic device, characterized in that, include: processor; Memory; A computer program stored in the memory and executable on the processor, wherein the computer program, when executed by the processor, implements the steps of the DC calibration method as described in any one of claims 1-6.

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