Chip Fixture Debugging System Based on Digital Twin

Abstract

The present invention relates to the field of automated debugging technology, specifically a chip fixture debugging system based on digital twin. The system includes a state perception fusion module, a positioning correction judgment module, a contact adjustment execution module, a closed-loop feedback correction module, and a data linkage optimization module. In the present invention, through the time-axis synchronization and matching of multiple types of sensing data, the intersection characteristics of position offset and pressure mutation are extracted to enhance direction recognition and dynamic accuracy. The angular interval analysis realizes the quantification of angular trends, improves the continuity of spatial positioning, and the comparison of driving rate differences ensures the effective response of the adjustment window. The introduction of stretching and deformation data backtracking improves the path deviation correction ability. By combining node logs and delay identifiers, a virtual-real link is constructed to constrain the consistency between simulation and actual behaviors. The data linkage and timing control cooperate to optimize the overall debugging process, achieving higher response timeliness, attitude recognition accuracy, and data fusion stability.

Description

Technical Field

[0001] The present invention relates to the technical field of automated debugging, and particularly to a chip fixture debugging system based on digital twin. Background Art

[0002] The technical field of automated debugging includes technical methods and technical devices for debugging, detecting, and optimizing equipment, systems, or processes without manual intervention. The core content of this field involves the design, implementation, and application of automated tools and equipment, aiming to improve debugging efficiency, reduce human operation errors, and optimize system performance. Through intelligent control, precise detection, and adjustment, automated debugging technology can automatically complete tasks such as equipment setup, testing, and correction, and is widely used in multiple fields such as industrial production, product manufacturing, and system maintenance.

[0003] Among them, a chip fixture debugging system refers to an automated system used for debugging fixtures during the chip assembly and testing process. This system specifically solves the debugging problems of chip fixtures during actual use, ensuring the contact accuracy and reliability between the fixture and the chip. Through automated adjustment and testing methods, this system can monitor the cooperation between the fixture and the chip in real time, and automatically adjust the working parameters or positions of the fixture according to the detection results to adapt to different types of chips and testing requirements. Through the debugging process, this system can efficiently and accurately complete the debugging work of chip fixtures, avoid errors and inconsistencies in manual debugging, and improve production efficiency and quality.

[0004] The prior art mainly relies on single-dimensional data responses during the chip fixture debugging process. For example, adjustments are made only based on position or pressure, resulting in the inability to form an effective multi-dimensional dynamic judgment logic, and thus the problem of unstable fixture contact occurs. During the adjustment process, fixed logic or set thresholds are often used, lacking a trend judgment mechanism based on real-time perception data. It is easy to fail to intervene and correct in a timely manner when there is a slight deviation in the fixture posture, resulting in misjudgment or over-adjustment. Traditional closed-loop control mainly relies on the static error feedback of the final adjustment result, ignoring the association between the action sequence and dynamic deviation in the adjustment path, making it difficult to retrospectively analyze some abnormal adjustments and causing the error source to be difficult to locate. During the system mapping process, the time delay difference between the simulation model response and the actual fixture operation is ignored, resulting in a response lag and data asynchronization in the mapping relationship, affecting the coherence and accuracy of the overall debugging chain, and causing the debugging result to be limited by single-point data judgment and static action correction, unable to effectively support the synchronous debugging requirements of complex chip types and multi-condition contact accuracy. Summary of the Invention

[0005] In order to solve the problem that in the existing chip fixture debugging process, it mainly relies on the data response of a single dimension, such as adjustment only based on position or pressure, resulting in the inability to form an effective multi-dimensional dynamic judgment logic, and then the problem of unstable fixture contact occurs. During the adjustment process, fixed logic or set thresholds are often used, lacking a trend judgment mechanism based on real-time perception data, and it is easy to fail to intervene and correct in time when there is a slight deviation in the fixture attitude, resulting in misjudgment or over-adjustment phenomena. Traditional closed-loop control mainly relies on the static error feedback of the final adjustment result, ignoring the association between the action sequence and dynamic deviation in the adjustment path, making it difficult to retrospectively analyze some abnormal adjustments and difficult to locate the error source. During the system mapping process, the time delay difference between the simulation model response and the actual fixture operation is ignored, resulting in response lag and data asynchronization in the mapping relationship, affecting the coherence and accuracy of the overall debugging chain, and causing the debugging result to be limited by data single-point judgment and action static correction, unable to effectively support the technical problem of synchronous debugging requirements for complex chip types and multi-condition contact accuracy. The embodiments of the present invention provide a chip fixture debugging system based on digital twin. The technical solutions are as follows:

[0006] On the one hand, a chip fixture debugging system based on digital twin is provided, and the system includes:

[0007] The state perception fusion module synchronously matches three types of data streams based on the chip fixture data, including the signal values of the fixture contact surface position sensing unit, the clamping structure pressure detection unit, and the chip contact area thermal measurement unit, and identifies the intersection frequency of the position offset direction and the pressure response mutation point to obtain the fixture perception correlation feature set;

[0008] The positioning and correction judgment module judges the corresponding angle interval between the peak point position and the fixture guide rail limit surface based on the fixture perception correlation feature set, and screens the current offset direction according to the length of the angle interval to obtain the fixture offset angular trend;

[0009] The contact adjustment execution module selects the operating state of the adjustment mechanism and the chip assembly chassis synchronous drive interface according to the fixture offset angular trend, combines the alignment range of the fixture execution end, screens the response time window and triggers the adjustment action to obtain the fixture active adjustment trigger sequence;

[0010] The closed-loop feedback correction module calls the fixture active adjustment trigger sequence, collects the tensile data fed back by the chip contact surface deformation probe and the fixture, detects the different-direction interval of the data change direction, and retrospectively analyzes the action sequence with an excessive deviation amplitude to obtain the contact action retrospective node group.

[0011] As a further solution of the present invention, the fixture sensing correlation feature set includes an offset direction distribution, a pressure mutation frequency point, and a thermal response feature. The fixture offset angular trend includes an included angle interval range, an angular change direction, and an angle offset amplitude. The fixture active adjustment trigger sequence includes an adjustment response time window, a drive rate difference value, and an execution alignment trigger bit. The contact action backtracking node group includes a deformation trend reverse point, an overlimit response amplitude, and an original backtracking trajectory point.

[0012] As a further solution of the present invention, the state sensing fusion module includes:

[0013] The contact feature extraction sub-module collects the fixture position signal and the chip thermal response data based on the chip fixture data, extracts the offset value and the temperature change difference value through time axis matching, identifies the ratio of the offset rate to the thermal change rate, and maps and classifies them to the fixture structure area to generate a displacement-thermal coupling mapping diagram;

[0014] The pressure response recognition sub-module calls the clamping structure pressure data according to the displacement-thermal coupling mapping diagram, screens the pressure mutation points and locates the mapping blocks, calculates the difference between the pressure amplitude and the thermal sensitivity slope within the blocks, and obtains a multi-segment pressure response coefficient group;

[0015] The debugging parameter fusion sub-module calls the coefficient distribution in the multi-segment pressure response coefficient group and the displacement-thermal coupling mapping diagram, identifies the coincidence area of the displacement direction and the pressure mutation frequency within the same segment, extracts the response sequence on the time axis, and obtains the fixture sensing correlation feature set.

[0016] As a further solution of the present invention, the positioning and correction judgment module includes:

[0017] The induction data synchronization sub-module extracts the multi-dimensional node coordinates of the fixture sensing model in the digital twin based on the fixture sensing correlation feature set, collects the corresponding displacement induction data, and generates a node displacement induction mapping table;

[0018] The included angle recognition sub-module calculates the included angle between the node peak point and the normal direction according to the aligned node coordinates and the displacement induction value sequence in the node displacement induction mapping table, extracts the angle value and divides the belonging interval to obtain a guide rail included angle interval set;

[0019] The offset trend determination sub-module calls the interval data in the guide rail included angle interval set, extracts the node indexes within the interval, screens the consistency of the included angle direction in order, and analyzes the distribution of the fixture offset attitude vector in the current frame to obtain the fixture offset angular trend.

[0020] As a further solution of the present invention, the included angle between the node peak point and the normal direction adopts the formula:

[0021] ;

[0022] Among them, represents the angle between the node peak point and the normal direction, and respectively represent the X and Y axis coordinate values of the th node, and respectively represent the X and Y axis coordinate values of the reference point, represents the number of nodes, is the inverse cosine function.

[0023] As a further solution of the present invention, the contact adjustment execution module includes:

[0024] The drive mapping recognition sub-module extracts the drive parameter of the control model according to the trend of the fixture offset angle, combines the angular offset trend of the fixture in the digital twin, synchronously collects the action sequence of the virtual channel, analyzes the mapping relationship between the offset trend and the interface state, and generates a drive state mapping set;

[0025] The speed difference determination sub-module calls the running frequency of the drive interface in the drive state mapping set, combines the attitude change rate value recorded in the virtual execution surface of the fixture, analyzes the speed difference amplitude of the interface, and performs difference screening based on the alignment threshold to obtain a list of speed difference channels;

[0026] The action time window extraction sub-module extracts the output time period of the driver according to the channel number in the speed difference channel list, screens the action segments within the adjustment threshold, and identifies the effective trigger time interval of the channel to obtain the active adjustment trigger sequence of the fixture.

[0027] As a further solution of the present invention, the closed-loop feedback correction module includes:

[0028] The contact feedback recognition sub-module calls the active adjustment trigger sequence of the fixture, combines the deformation probe and the fixture displacement data, identifies the direction difference value of the time alignment calculation, marks the continuous different-direction intervals and analyzes the contact feedback mapping to obtain the fixture response different-direction section group;

[0029] The action offset backtracking sub-module calls the action trigger sequence of the fixture, extracts the action offset value within the different-direction response section, identifies the over-limit points based on the critical value of the digital twin model, and reconstructs the time series action structure diagram to obtain the contact action backtracking node group.

[0030] As a further solution of the present invention, the direction difference value adopts the formula:

[0031] ;

[0032] Among them, represents the direction difference value, represents the The angular deviation of each data point, represents the weight of the th data point,

[0033] As a further solution of the present invention, the system further includes a data linkage optimization module:

[0034] Based on the contact action backtracking node group, the data linkage optimization module detects the node synchronization log records in the digital twin simulation mapping, screens out the mapping points with dynamic response lags, combines the response delay section identifiers before and after the mapping points, constructs the corresponding virtual-real response mapping chain, and obtains the virtual-real debugging mapping path of the chip fixture;

[0035] The virtual-real debugging mapping path of the chip fixture includes a synchronous response node chain, a delay section identifier, and a simulation mapping lag point.

[0036] As a further solution of the present invention, the data linkage optimization module includes:

[0037] The node log recognition sub-module detects the corresponding node synchronization logs in the simulation mapping based on the contact action backtracking node group, extracts the difference between the trigger time and the response record, screens out the record items exceeding the delay threshold, and generates a lag node index set;

[0038] The response delay section sub-module calls the response identifiers within the range before and after the nodes in the simulation mapping log according to the lag node index set, counts the difference between the start and end times of the response, and determines whether it exceeds the response tolerance section range to obtain a group of delay response time periods;

[0039] The mapping path construction sub-module extracts the real-time action chain structure data of the corresponding chip fixture and the simulation mapping path information according to the node sections marked by the group of delay response time periods, and rearranges the structure mapping in the order of the trigger time to obtain the virtual-real debugging mapping path of the chip fixture.

[0040] The beneficial effects brought by the technical solutions provided in the embodiments of the present invention at least include:

[0041] By achieving synchronous matching on the time axis of multi-type sensing data, it is possible to accurately extract the spatio-temporal intersection characteristics between the position offset and the sudden change in pressure response of the fixture during the chip contact process, ensuring that the sensed data has directional recognition and dynamic accuracy. Introducing the analysis of the included angle interval enables the offset trend to be not limited to the displacement value judgment, but can achieve the trend quantification in the attitude angle direction of the fixture, enhancing the continuity of spatial positioning. Combining the displacement response with the alignment judgment result of the fixture execution end for drive rate difference comparison ensures that the time window of the adjustment action is within the dynamic response range, thereby improving the dynamic adaptation ability of the fixture and the chip assembly. At the same time, introducing a two-way backtracking mechanism for tensile data and deformation trends can perform differential analysis on the deviation sequence of the adjustment action, ensuring that the adjustment path has the ability to correct direction and improving the correction accuracy of the contact action. Establishing a virtual-real link association by combining the node response log and the delay section identifier in the simulation mapping can constrain the time consistency between the virtual mapping and the actual fixture adjustment behavior, improving the response synchronization of the digital twin debugging chain. The combined improvement in key participation items such as data linkage, judgment strategy, timing control, and virtual-real mapping makes the overall debugging process have higher timeliness, spatial judgment accuracy, and multi-source data fusion stability. BRIEF DESCRIPTION OF THE DRAWINGS

[0042] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following will briefly introduce the drawings required for the description of the embodiments. Obviously, the following drawings are only some embodiments of the present invention. For those of ordinary skill in the art, without creative efforts, other drawings can be obtained based on these drawings.

[0043] Figure 1 is a schematic diagram of a chip fixture debugging system based on digital twin provided by an embodiment of the present invention;

[0044] Figure 2 is a schematic diagram of the system framework of the present invention;

[0045] Figure 3 is a flowchart of the state perception fusion module in the present invention;

[0046] Figure 4 is a flowchart of the positioning and correction judgment module in the present invention;

[0047] Figure 5 is a flowchart of the contact adjustment execution module in the present invention;

[0048] Figure 6 is a flowchart of the closed-loop feedback correction module in the present invention;

[0049] Figure 7 is a flowchart of the data linkage optimization module in the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0050] The technical solutions in the present invention will be described below in conjunction with the accompanying drawings.

[0051] In the embodiments of the present invention, words such as "exemplarily" and "for example" are used to represent examples, illustrations or explanations. Any embodiment or design solution described as an "example" in the present invention should not be construed as being more preferred or having more advantages than other embodiments or design solutions. Rather, the use of the word "example" is intended to present concepts in a specific manner. In addition, in the embodiments of the present invention, the meaning expressed by "and / or" can be both, or either one of the two.

[0052] In the embodiments of the present invention, "image" and "picture" can sometimes be used interchangeably. It should be noted that when the difference is not emphasized, the meanings they express are the same. "(of)", "corresponding", and "corresponding" can sometimes be used interchangeably. It should be noted that when the difference is not emphasized, the meanings they express are the same.

[0053] In the embodiments of the present invention, sometimes subscripts such as W1 may be written in a non-subscript form such as W1. When the difference is not emphasized, the meanings they express are the same.

[0054] To make the technical problems to be solved, technical solutions and advantages of the present invention clearer, the following will be described in detail in conjunction with the accompanying drawings and specific embodiments.

[0055] The embodiments of the present invention provide a chip fixture debugging system based on digital twin, as Figure 1-2 shown in the schematic diagram of the chip fixture debugging system based on digital twin. The system includes:

[0056] The state perception fusion module is based on chip fixture data, including the signal values of the fixture contact surface position sensing unit, the clamping structure pressure detection unit, and the chip contact area thermal measurement unit. According to the time axis, the three types of data streams are synchronously matched to identify the intersection frequency of the position offset direction and the pressure response mutation point, and a fixture perception correlation feature set is obtained;

[0057] The positioning correction judgment module is based on the fixture perception correlation feature set, extracts the displacement induction value of the electromagnetic offset detection, judges the corresponding angle interval between the peak point position and the fixture guide rail limit surface, and screens the current offset direction according to the length of the angle interval to obtain the fixture offset angle trend;

[0058] The contact adjustment execution module selects the operating state of the adjustment mechanism and the chip assembly chassis synchronous drive interface according to the trend of the fixture offset angle, identifies the drive rate difference, combines the alignment range of the fixture execution end, filters the response time window and triggers the adjustment action to obtain the fixture active adjustment trigger sequence;

[0059] The closed-loop feedback correction module calls the fixture active adjustment trigger sequence, collects the tensile data fed back by the chip contact surface deformation probe and the fixture, detects the different-direction interval of the change directions of the two groups of data, and performs retrospective analysis on the action sequence with the deviation amplitude exceeding the limit to obtain the contact action retrospective node group;

[0060] The data linkage optimization module, based on the contact action retrospective node group, detects the node synchronization log records in the digital twin simulation mapping, filters the mapping points with dynamic response lags, combines the response delay section identifiers before and after the mapping points, constructs the corresponding virtual-real response mapping chain, and obtains the chip fixture virtual-real debugging mapping path.

[0061] The fixture perception correlation feature set includes the offset direction distribution, the pressure mutation frequency point, and the thermal response feature. The fixture offset angle trend includes the included angle interval range, the angular change direction, and the angle offset amplitude. The fixture active adjustment trigger sequence includes the adjustment response time window, the drive rate difference value, and the execution alignment trigger bit. The contact action retrospective node group includes the deformation trend reverse point, the over-limit response amplitude, and the original retrospective trajectory point. The chip fixture virtual-real debugging mapping path includes the synchronous response node chain, the delay section identifier, and the simulation mapping lag point.

[0062] Specifically, as Figure 2 、 3 shown, the state perception fusion module includes:

[0063] The contact feature extraction sub-module, based on the chip fixture data, collects the fixture position signal and the chip thermal response data, extracts the offset value and the temperature change difference value through time axis matching, identifies the ratio of the offset rate to the thermal change rate, and maps and classifies them to the fixture structure area to generate a displacement-thermal coupling mapping diagram;

[0064] First, obtain the fixture position signal and the thermal response data of the chip. The two data sources respectively record the changes in the fixture position and the thermal response generated by the chip during operation. Through time-axis matching, ensure that the two sets of data are aligned in time, so that the relationship between the fixture movement and the chip's thermal response can be more accurately extracted. After time synchronization, calculate the offset value and the temperature change difference. The offset value represents the change in the relative position of the fixture during movement, while the temperature change difference is a measure of the chip's response to temperature changes. Through the data, further identify the ratio of the offset rate to the thermal change rate, that is, the ratio of the fixture displacement change rate to the chip's thermal response change rate. This ratio reflects the strength of the association between the two. According to the ratio, map and classify the data into the fixture structure area, and separately process the thermal change and displacement characteristics of different areas for more accurate analysis. Through the above steps, finally generate a displacement-thermal coupling map, which shows the relationship between heat and displacement changes in different fixture structure areas. For example, in an automated assembly process, there is a high correlation between the displacement of the fixture and the temperature change of the chip. The generated map helps optimize the fixture adjustment and chip control to ensure precise operation.

[0065] Based on the displacement-thermal coupling map, the pressure response identification sub-module calls the clamping structure pressure data, filters out the pressure mutation points and locates the mapping block, calculates the difference between the pressure amplitude and the thermal sensitivity slope within the block, and obtains a multi-segment pressure response coefficient group;

[0066] Obtain real-time pressure data through a pressure sensor. The data records the pressure changes of the fixture under different operating conditions, and filters out the pressure mutation points, that is, those moments when the pressure value changes significantly. The change reflects the change in the contact state between the fixture and the workpiece. After finding the mutation points, locate the mapping block, that is, the time segment related to the pressure mutation. Within this block, calculate the difference between the pressure amplitude and the thermal sensitivity slope. The thermal sensitivity slope refers to the rate of change of temperature with respect to time, and the pressure amplitude refers to the change range of the pressure value. By calculating the difference between the two, a multi-segment pressure response coefficient group can be obtained. The coefficients describe the relationship between different pressure segments and the temperature change response. For example, in a precision assembly process, when the fixture applies pressure, the thermal response of the chip will affect the pressure application effect of the fixture. By calculating the coefficients, the pressure and temperature change responses of each segment can be accurately grasped, and the operation strategy can be further optimized.

[0067] The debugging parameter fusion sub-module calls the coefficient distribution in the multi-segment pressure response coefficient group and the displacement-thermal coupling map, identifies the overlapping area of the displacement direction and the pressure mutation frequency within the same segment, extracts the response sequence on the time axis, and obtains the fixture perception association feature set;

[0068] The coefficient group is combined with the displacement thermal coupling map to identify the overlapping area of the displacement direction and the pressure mutation frequency in the same section. The key to the process is to identify the relationship between the pressure mutation and the displacement direction of the fixture through multi-dimensional data analysis, so as to ensure that the displacement change of the fixture when the pressure mutation occurs can be accurately understood. An observation window is set around each pressure mutation point, and the window size is set according to actual needs. For example, the observation time window can be 50 milliseconds. By analyzing the displacement data and pressure change data in the window, it can be determined whether there is a significant overlap area, and the response sequence on the time axis in the overlap area can be extracted. The response sequence shows the relationship between the displacement change and the pressure response of the fixture in a specific time period. Through further processing of the sequence, a fixture perception association feature set can be generated, which contains the correlation characteristics between pressure change, displacement change and thermal response. For example, in a certain process, the relationship between the displacement of the fixture and the applied pressure shows a significant change within a certain period of time. By analyzing the response sequence, the adjustment parameters of the fixture can be further optimized to ensure the accuracy and stability of the operation process.

[0069] Specifically, if Figure 2 , 4 As shown, the positioning correction judgment module includes:

[0070] The sensing data synchronization submodule extracts the multi-dimensional node coordinates of the fixture sensing model in the digital twin based on the fixture sensing associated feature set, collects the corresponding displacement sensing data, and generates a node displacement sensing mapping table;

[0071] The multi-dimensional node coordinates in the digital twin are extracted through the perception model of the fixture. The process is achieved by collecting perception data of the fixture and analyzing its correlation characteristics with the physical environment. By collecting the displacement data of the fixture at different time nodes, multi-dimensional coordinate information is obtained, and then the coordinate information is mapped in the data processing and converted into node data with physical meaning. In order to ensure accurate coordinate data, it is necessary to calibrate the position of each node through multiple sensor sampling and algorithm optimization. Especially in complex environments, the influence of factors such as ambient temperature changes, sensor offset, and external vibration must be considered. In practical applications, for example, on an automated production line, the fixture will continue to move during operation, and the sensor will continue to collect displacement data, and finally output the node displacement sensing mapping table to ensure that the fixture is always within the predetermined position range during the entire operation process, record the displacement data of each node and its timestamp, and ensure that subsequent data processing can be carried out based on accurate information.

[0072] The angle recognition submodule calculates the angle between the node peak point and the normal direction according to the aligned node coordinates and displacement sensing value sequence in the node displacement sensing mapping table, extracts the interval to which the angle value belongs, and obtains the guide rail angle interval set;

[0073] The angle between the node peak point and the normal direction is calculated using the formula:

[0074] ;

[0075] where represents the angle between the node peak point and the normal direction, and respectively represent the X and Y axis coordinate values of the th node, and respectively represent the X and Y axis coordinate values of the reference point, represents the number of nodes, is the arccosine function;

[0076] The process of obtaining each parameter:

[0077] and respectively represent the coordinates of the th node on the plane. The coordinates are actual data directly obtained through a displacement induction mapping table or a measuring device. The data acquisition device locates the nodes in the target area according to the node positions to obtain the specific coordinates of each node;

[0078] and respectively represent the coordinates of the reference point. The reference point is the geometric center, initial position, or fixed reference position of the target area. The coordinates of this reference point can be obtained through a position sensor or previous calculation results;

[0079] represents the total number of nodes, which is determined by the node distribution of the system. For example, the number of nodes is 100, 200, etc. The data can be obtained through the calculation of the node distribution range or the system settings;

[0080] The first part of the formula: ;

[0081] This calculation is the sum of the products of the offsets between each node and the reference point. For each node , calculate the difference between its coordinate and the coordinate of the reference point, multiply it by the difference between its coordinate and the coordinate of the reference point, and sum up the results of all nodes to obtain the total of this item;

[0082] The second part: ;

[0083] This is for each node in The square root of the sum of the squares of the offsets in the axis direction represents the total offset degree of all nodes from the reference point in the

[0084] Third part: ;

[0085] Similarly, this is the square root of the sum of the squares of the offsets of each node in the direction, representing the total offset degree of all nodes from the reference point in the axis direction;

[0086] Substitute specific numbers for calculation: Suppose there are 4 nodes, , reference point coordinates and , and the coordinates of each node are as follows:

[0087] Node 1: ;

[0088] Node 2: ;

[0089] Node 3: ;

[0090] Node 4: ;

[0091] Calculation steps:

[0092] Calculate the first part:

[0093] ;

[0094] Calculate the second part:

[0095] ;

[0096] Calculate the third part:

[0097] ;

[0098] Substitute into the formula to calculate the included angle:

[0099] ;

[0100] It is obtained through calculation: ;

[0101] Convert radians to degrees: ;

[0102] and The acquisition depends on the data acquisition accuracy and resolution of the sensor. To ensure high precision, the error range of the sensor should be within 1 mm, and the coordinates of each node need to be obtained based on actual physical position measurements;

[0103] and The selection of the reference point can depend on the initial positioning of the device or the preset geometric center point. The coordinates of this reference point are obtained through known reference positions or previous measurement data;

[0104] Number of nodes For large structures or complex surfaces, it can be up to hundreds or even more, ensuring that the system can handle the computational requirements of large-scale data;

[0105] The result shows that the included angle is 14.1 degrees, representing the included angle between the node peak point and the normal. The result can be used to further calculate the angle interval set of the guide rail and make accurate mathematical derivations of the change trend of the nodes in subsequent analyses.

[0106] The offset trend determination sub-module calls the interval data in the guide rail included angle interval set, extracts the node indexes within the interval, screens the consistency of the included angle directions in order, analyzes the distribution of the fixture offset attitude vectors in the current frame, and obtains the fixture offset angular trend;

[0107] First, it is necessary to retrieve the data in the guide rail included angle interval set, extract the qualified node indexes, screen the angle data corresponding to the node indexes, and check whether they meet the standard of direction consistency. This step requires sorting and classifying the angle data to ensure that the directions of all selected nodes are consistent. The basis for screening is a standard of included angle consistency, and a threshold is set to define the allowable deviation range of the angle direction. For example, a tolerance of ±5° can be set. If the included angle change exceeds this range, it is considered that the direction is inconsistent. By analyzing the distribution of the fixture offset attitude vectors in the current frame, the actual offset trend of the fixture is further judged. The distribution of the offset attitude vectors is analyzed based on the change rate of the node displacement data. A larger change in the node position indicates a larger offset of the fixture. Suppose that in the previous frame, the position data of the fixture is (10, 20, 30), and in the current frame, the position data is (11, 21, 31). The offset trend of the fixture can be obtained by calculating the difference between the two frames. If the offset of the node continuously increases, the offset direction of the fixture can be judged and its future movement trend can be predicted, and the fixture offset angular trend can be output to help further perform offset compensation or adjustment operations to ensure that the fixture remains within a reasonable working attitude range.

[0108] Specifically, as Figure 2 、 5 shown, the contact adjustment execution module includes:

[0109] Based on the trend of the fixture offset angle, the drive mapping recognition sub-module combines the angular offset trend of the fixture in the digital twin, extracts the drive parameters of the control model, synchronously collects the action sequence of the virtual channel, analyzes the mapping relationship between the offset trend and the interface state, and generates a drive state mapping set;

[0110] Compare the data of the fixture's offset angle trend with the angular offset trend of the fixture in the digital twin to analyze the drive parameters required by the control model. In this process, the data of the fixture's offset angle trend is obtained by recording the offset angle of the fixture during actual operation. For example, the angle change of the fixture is monitored in real time by a sensor, and the actual monitored angle data is compared with the angle change trend in the digital twin model. The data in the model reflects the theoretically regular angle changes that the fixture should follow under various operating conditions. Through this comparison, the deviations that occur during the actual operation of the fixture can be identified, and the drive parameters can be extracted from the control model to ensure that the drive can respond appropriately to the changes of the fixture. Synchronously collect the action sequence of the virtual channel, and the sequence records each action of the fixture and its parameters during execution. By analyzing the action sequence, the response behavior of the fixture in various states can be further understood, and then through the mapping relationship between the offset trend and the interface state, the mutual influence of each link in the operation process of the fixture can be found, and finally a drive state mapping set is generated. For example, on an automated assembly production line, the fixture needs to adjust its angle according to the size and shape of the workpiece, and through feedback, ensure the accuracy and stability during the assembly process.

[0111] The speed difference determination sub-module calls the operating frequency of the drive interface in the drive state mapping set, combines the attitude change rate value recorded in the virtual execution surface of the fixture, analyzes the speed difference amplitude of the interface, and performs difference screening based on the alignment threshold to obtain a speed difference channel list;

[0112] First, extract the operating frequency of the drive interface from the drive state mapping set. This frequency refers to the number of times the drive system triggers the fixture action per unit time. The acquisition of the frequency depends on the system's accurate recording of the timestamps of each action and calculating the occurrence frequency of each action through the timestamps. It also needs to combine the attitude change rate recorded in the virtual execution surface of the fixture. The rate represents the amount of attitude change of the fixture in each time period. For example, when the fixture undergoes an angular change during operation, record the attitude data at each moment and calculate the change rate within a short period. By comparing the rate change of the fixture with the frequency of the drive interface, analyze the magnitude of the rate difference. To ensure the accuracy of the judgment, set a reference threshold as the screening criterion for the rate difference. For example, if the attitude change rate of the fixture exceeds a certain threshold (such as 0.1 degrees per second), it is considered that the rate is abnormal, and a list of relevant rate difference channels is screened out according to the difference. This screening process helps to identify that under specific conditions, the fixture's action exceeds the expected range and needs further processing. Finally, a list of rate difference channels is obtained, which lists all the channels with abnormal rate differences.

[0113] The action time window extraction sub-module extracts the driver output time period according to the channel numbers in the rate difference channel list, screens out the action segments within the adjustment threshold, and identifies the effective trigger time interval of the channel to obtain the fixture active adjustment trigger sequence;

[0114] Find the driver output time period related to the channel number according to the channel number. The time period records the specific execution time of the fixture in each action stage. By comparing the time period with the adjustment threshold, the action segments that meet the conditions can be screened out. The adjustment threshold is set according to the accuracy requirements of the fixture operation. For example, it can be set to a range where the offset does not exceed 0.5 mm. Whenever the action offset of the fixture is within this threshold, the action is considered valid and included in the action time window. By analyzing the screened action segments, the effective trigger time interval of the channel can be identified, that is, the operation actions successfully triggered by the fixture within a specific period. By integrating the effective time intervals, a fixture active adjustment trigger sequence is generated, providing a basis for subsequent automatic adjustment. In practical applications, assume that the fixture performs an action within a certain period, and its offset is 0.3 mm, which meets the adjustment threshold. Then this period will be included in the effective trigger time interval and finally used to guide the precise adjustment of the fixture.

[0115] Specifically, as Figure 2 、 6 shown, the closed-loop feedback correction module includes:

[0116] The contact feedback recognition sub-module calls the fixture active adjustment trigger sequence, combines the deformation probe and the fixture displacement data, identifies the time-aligned calculation direction difference value, marks the continuous opposite direction intervals and analyzes the contact feedback mapping to obtain the fixture response opposite direction section group;

[0117] Direction difference value, using the formula:

[0118] ;

[0119] Where, represents the direction difference value, represents the angular deviation of the th data point, represents the weight of the th data point, represents the total number of data points;

[0120] Obtaining the angular deviation value ( ): The angular deviation value of each data point is obtained by measuring the angle difference between the measuring fixture and the deformation probe, and a high-precision angle sensor is used for measurement to ensure the accuracy of the data. The measurement result is in degrees and ranges from to ;

[0121] Basis for setting the weight ( ): The weight reflects the importance of each data point in the overall calculation. The basis for setting the weight includes factors such as the confidence level of the measurement and the stability of the data point. For example, if a data point has a high measurement confidence level, a larger weight value is assigned. The weight value ranges from to , and the specific value is determined according to the actual measurement situation;

[0122] Process of unifying the dimension: All angular deviation values are in degrees to ensure the dimensional consistency in the calculation process. The weight is a dimensionless quantity and does not affect the calculation of the angle unit;

[0123] Suppose there are three data points, and their angular deviation values and corresponding weights are as follows:

[0124] , ;

[0125] , ;

[0126] , ;

[0127] Calculate the total weight: ;

[0128] Calculate the sum of the weighted angular deviations:

[0129] ;

[0130] Calculate the direction difference value : ;

[0131] The result shows that after weighted calculation, the average direction difference between the fixture and the deformed probe is , and this value is used to mark the continuous different-direction intervals and analyze the contact feedback mapping, and finally obtain the fixture response different-direction section group.

[0132] The action offset backtracking sub-module calls the fixture action trigger sequence, extracts the action offset values within the different-direction response sections, identifies the over-limit points based on the critical values of the digital twin model, and reconstructs the time-series action structure diagram to obtain the contact action backtracking node group;

[0133] Extract relevant data from the action trigger sequence. The data records the actions triggered by the fixture in different operation steps and the corresponding offsets. The core of the extraction process is to analyze the timestamps of the trigger sequence and the corresponding action offset values to ensure that the offset of each action is accurately matched with its corresponding time point, and identify the over-limit points based on the critical values in the digital twin model. The digital twin model simulates the behavior of the fixture under different operating conditions, and determines whether the current action exceeds the normal range by setting certain critical values (such as the maximum allowable offset, angle deviation, etc.). For example, if during the operation of the fixture, the offset value of a certain action exceeds the preset critical value (such as the offset exceeds 0.5 mm), it will be marked as an over-limit point. The identification of over-limit points is completed through real-time monitoring and data analysis. The system will automatically mark points according to the set rules for subsequent optimization and adjustment. According to the marked over-limit points, reconstruct the time-series action structure diagram, taking the over-limit points into consideration, so as to optimize the operation path of the fixture. Through reconstruction, the obtained contact action backtracking node group can clearly show the action offset situation of the fixture in each operation step, further supporting the offset correction operation. For example, in some precision assembly tasks, the fixture undergoes a small offset due to external forces, and the backtracking sub-module can analyze the small offset and adjust the operation process to improve the overall accuracy.

[0134] Specifically, as Figure 2 , 7 shown, the data linkage optimization module includes:

[0135] The node log identification sub-module, based on the contact action backtracking node group, detects the corresponding node synchronization logs in the simulation mapping, extracts the difference between the trigger moment and the response record, filters out the record items that exceed the delay threshold, and generates a lag node index set;

[0136] Detect the synchronization logs of the corresponding nodes in the simulation mapping. The process is achieved by comparing the contact actions in the actual operation to trace back the nodes with the log records in the simulation model, ensuring that the actions and responses of each operation are synchronized and avoiding analysis errors caused by different time sequences. Extract the difference between the trigger moment and the response record, and calculate the time difference between each action occurrence and the corresponding response. Through the difference value, it is possible to accurately identify which actions have delay phenomena and filter out the record items that exceed the set delay threshold. For example, if the preset delay threshold is 200 milliseconds, if the difference between the trigger moment and the response record exceeds this threshold, it is considered that there is a lag behavior for this node. By continuously comparing the trigger and response time differences of each node, a lag node index set is finally generated, listing all the nodes with significant lag phenomena. The lag nodes need to be further analyzed and corrected to ensure the accuracy of the operation. In practical applications, assume that during the automated testing process of a production line, if the time difference between the trigger action and the response of a fixture exceeds the set threshold, the node will be marked, and the action sequence of the fixture will be optimized and adjusted according to its lag situation.

[0137] The response delay section sub-module, according to the lag node index set, calls the response identifiers within the range before and after the node in the simulation mapping log, counts the difference in the start and end times of the response, and determines whether it exceeds the response tolerance section range to obtain a group of delayed response time periods;

[0138] Call the response identifier information within the range before and after the node in the simulation mapping log to determine the operation status before and after the lag node, and count the difference in the start and end times of the response of the node in terms of time, that is, the time required from the trigger action to the actual response completion. To determine whether there is a delayed response, a response tolerance section range needs to be set. For example, set the tolerance section range to 300 milliseconds. If the response time difference exceeds this range, it is considered that this response belongs to a delayed response. By judging whether the response time of each node exceeds this tolerance section, a group of delayed response time periods is filtered out. The time periods will show the delayed behavior of the fixture under specific operations, helping engineers locate the reasons for inaccurate operations. For example, if the response time of a certain node is 350 milliseconds, exceeding the preset tolerance range, this node will be included in the group of delayed response time periods, and subsequent operations will be optimized and corrected for this phenomenon.

[0139] The mapping path construction sub-module extracts the real-time action chain structure data of the corresponding chip fixture and the simulation mapping path information according to the node section marked by the group of delayed response time periods, and rearranges them according to the trigger time sequence structure mapping to obtain the virtual-real debugging mapping path of the chip fixture;

[0140] Extract the real-time action chain structure data of the chip fixture within the section. This action chain structure data is obtained by recording in real time the interaction process between the fixture and the chip, including the coordination of each adjustment of the fixture with the chip actions. Extract the simulation path data corresponding to the node section from the simulation mapping path information for comparison with the actual operation path. By comparing these two, rearrange the action chain and path information according to the sequential structure of the trigger time to form a new mapping path structure. The rearrangement process is based on the trigger time sequence, which ensures that all operation steps and adjustment actions are executed in the order of the time axis without conflicts or disorders, obtaining the virtual-real debugging mapping path of the chip fixture, which can more accurately reflect the actual performance of the fixture in the simulation environment and provide a clear operation path for subsequent debugging and optimization. In practical applications, assume that on a high-precision assembly line, the fixture needs to adjust its action path according to the simulation model. The virtual-real debugging mapping path after rearrangement can effectively improve the accuracy and efficiency of fixture adjustment and ensure the accuracy of assembly.

[0141] The above is only the specific implementation manner of the present invention, but the protection scope of the present invention is not limited thereto. Any person skilled in the art within the technical scope disclosed by the present invention can easily think of changes or substitutions, which should all be covered within the protection scope of the present invention. Therefore, the protection scope of the present invention should be subject to the protection scope of the claims.

Claims

1. A chip fixture debugging system based on digital twin, characterized in that, The system includes: Based on the chip fixture data, including the signal values of the fixture contact surface position sensing unit, the clamping structure pressure detection unit, and the chip contact area thermal measurement unit, the state perception fusion module synchronously matches the three types of data streams, identifies the intersection frequency of the position offset direction and the pressure response mutation point, and obtains the fixture perception correlation feature set; Based on the fixture perception correlation feature set, the positioning correction judgment module judges the corresponding included angle interval between the peak point and the limit surface of the fixture guide rail, and filters the current offset direction according to the length of the included angle interval to obtain the fixture offset angle trend; According to the fixture offset angle trend, the contact adjustment execution module selects the operating state of the adjustment mechanism and the synchronous drive interface of the chip assembly chassis, combines the alignment range of the fixture execution end, filters the response time window and triggers the adjustment action to obtain the fixture active adjustment trigger sequence; The closed-loop feedback correction module calls the fixture active adjustment trigger sequence, collects the tensile data fed back by the chip contact surface deformation probe and the fixture, detects the different-direction interval of the data change direction, and performs retrospective analysis on the action sequence with the deviation amplitude exceeding the limit to obtain the contact action retrospective node group.

2. The chip fixture debugging system based on digital twin according to claim 1, wherein: The fixture perception correlation feature set includes the offset direction distribution, the pressure mutation frequency point, and the thermal response feature. The fixture offset angle trend includes the included angle interval range, the angle change direction, and the angle offset amplitude. The fixture active adjustment trigger sequence includes the adjustment response time window, the drive rate difference value, and the execution alignment trigger bit. The contact action retrospective node group includes the deformation trend reverse point, the over-limit response amplitude value, and the original retrospective trajectory point.

3. The chip fixture debugging system based on digital twin according to claim 1, wherein: The state perception fusion module includes: Based on the chip fixture data, the contact feature extraction sub-module collects the fixture position signal and the chip thermal response data, extracts the offset value and the temperature change difference value through time axis matching, identifies the ratio of the offset rate to the thermal change rate, and maps and classifies them to the fixture structure area to generate a displacement-thermal coupling mapping diagram; According to the displacement-thermal coupling mapping diagram, the pressure response recognition sub-module calls the clamping structure pressure data, filters the pressure mutation points and locates the mapping blocks, calculates the difference between the pressure amplitude and the thermal slope in the blocks, and obtains the multi-segment pressure response coefficient group; The debugging parameter fusion sub-module calls the coefficient distribution in the multi-segment pressure response coefficient group and the displacement-thermal coupling mapping diagram, identifies the overlapping area of the displacement direction and the pressure mutation frequency in the same segment, extracts the response sequence on the time axis, and obtains the fixture perception correlation feature set.

4. The chip fixture debugging system based on digital twin according to claim 3, wherein: The positioning correction judgment module includes: Based on the fixture perception correlation feature set, the induction data synchronization sub-module extracts the multi-dimensional node coordinates of the fixture perception model in the digital twin, collects the corresponding displacement induction data, and generates a node displacement induction mapping table; According to the aligned node coordinates and the displacement induction value sequence in the node displacement induction mapping table, the included angle recognition sub-module calculates the included angle between the node peak point and the normal direction, extracts the angle value and divides the belonging interval to obtain the guide rail included angle interval set; The offset trend determination sub-module calls the interval data in the concentrated guide rail angle intervals, extracts the node indexes within the intervals, screens the consistency of the angle directions in sequence, analyzes the distribution of the fixture offset attitude vectors in the current frame, and obtains the fixture offset angular trend.

5. The chip fixture debugging system based on digital twin according to claim 4, characterized in that: The angle between the node peak point and the normal direction is calculated using the formula: ； Among them, represents the angle between the node peak point and the normal direction, and represent the X and Y axis coordinate values of the th node respectively, and represent the X and Y axis coordinate values of the reference point respectively, represents the number of nodes, is the arccosine function.

6. The chip fixture debugging system based on digital twin according to claim 4, wherein: The contact adjustment execution module includes: The drive mapping recognition sub-module extracts the drive parameter of the control model according to the fixture offset angular trend, combines with the fixture angular offset trend in the digital twin, synchronously collects the action sequences of the virtual channels, analyzes the mapping relationship between the offset trend and the interface state, and generates a drive state mapping set. The speed difference determination sub-module calls the operating frequencies of the drive interfaces in the drive state mapping set, combines with the attitude change rate values recorded in the fixture virtual execution surface, analyzes the amplitude of the speed difference of the interfaces, and performs difference screening based on the alignment threshold to obtain a speed difference channel list. The action time window extraction sub-module extracts the output time period of the driver according to the channel numbers in the speed difference channel list, screens the action segments within the adjustment threshold, identifies the effective trigger time interval of the channels, and obtains the fixture active adjustment trigger sequence.

7. The chip fixture debugging system based on digital twin according to claim 6, wherein: The closed-loop feedback correction module includes: The contact feedback recognition sub-module calls the fixture active adjustment trigger sequence, combines with the deformation probe and the fixture displacement data, identifies the difference value of the time alignment calculation direction, marks the continuous different-direction intervals and analyzes the contact feedback mapping, and obtains the fixture response different-direction section group. The action offset backtracking sub-module calls the fixture action trigger sequence, extracts the action offset values within the different-direction response sections, identifies the over-limit points based on the critical values of the digital twin model, and reconstructs the time series action structure diagram to obtain the contact action backtracking node group.

8. The chip fixture debugging system based on digital twin according to claim 7, wherein: The difference value of the direction is calculated using the formula: ； Among them, represents the direction difference value, represents the angle deviation of the th data point, represents the weight of the th data point, and represents the total number of data points.

9. The chip fixture debugging system based on digital twin according to claim 1, wherein: The system further includes a data linkage optimization module: Based on the contact action backtracking node group, the data linkage optimization module detects the node synchronization log records in the digital twin simulation mapping, screens the mapping points with dynamic response lags, combines the response delay section identifiers before and after the mapping points, constructs the corresponding virtual-real response mapping chain, and obtains the virtual-real debugging mapping path of the chip fixture. The virtual-real debugging mapping path of the chip fixture includes a synchronous response node chain, a delay section identifier, and a simulation mapping lag point.

10. The chip fixture debugging system based on digital twin according to claim 9, characterized in that: The data linkage optimization module includes: The node log recognition sub-module detects the corresponding node synchronization logs in the simulation mapping based on the contact action backtracking node group, extracts the difference between the trigger moment and the response record, screens the record items exceeding the delay threshold, and generates a lag node index set. The response delay section sub-module calls the response identifiers within the range before and after the nodes in the simulation mapping log according to the lag node index set, calculates the difference between the start and end times of the response, and determines whether it exceeds the response tolerance section range to obtain a group of delay response time periods. The mapping path construction sub-module extracts the real-time action chain structure data and simulation mapping path information of the corresponding chip fixture according to the node sections marked by the group of delay response time periods, and rearranges them according to the trigger time sequence structure mapping to obtain the virtual-real debugging mapping path of the chip fixture.

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