Stamping die service life analysis method and system

Abstract

The invention discloses a stamping die service life analysis method and system, and relates to the technical field of die analysis, and the method comprises the steps: obtaining initial deformation response data and initial connection state parameters; acquiring current deformation response data and current connection state parameters based on the set acquisition period; calculating a deviation degree parameter of the current deformation response data relative to the initial deformation response data based on the current deformation response data and the initial deformation response data; calculating a change trend parameter of the key connection component based on the current connection state parameter and the initial connection state parameter; and on the basis of the deviation degree parameter and the change trend parameter, whether the working molded surface on the stamping die is stressed abnormally or not is diagnosed. According to the embodiment of the invention, the problem of abnormal stress of the working molded surface caused by performance degradation of the assembly structure can be effectively identified and diagnosed, and the method has the advantages of comprehensiveness and accuracy of mold life analysis.

Description

Technical Field

[0001] This invention relates to the field of mold analysis technology, and specifically to a method and system for analyzing the life of stamping dies. Background Technology

[0002] Existing technologies typically use material wear models and fatigue damage accumulation theories to predict the lifespan of the main working surfaces of stamping dies. In actual production, even if die surface wear and fatigue cracks are not obvious, part forming defects may still occur, and the defect rate increases with the number of production runs. Furthermore, the internal assembly structure of the die, such as bolted connections, may experience performance degradation due to long-term exposure to cyclic alternating loads, manifesting as a decrease in preload or changes in clearance. This performance degradation of the assembly structure is not easily detected through conventional visual inspection, but it leads to a decline in the overall structural health of the die. This decline in structural health indirectly causes the die working surfaces to experience unexpected localized stress fluctuations or changes in contact states in specific areas, thereby triggering part forming defects or accelerating localized die damage. This failure mode, caused by the performance degradation of the stamping die's own assembly structure and exhibiting a cascading effect, is not rooted in insufficient performance of the surface material itself, but rather in the decline in the overall structural health of the die. Traditional life analysis methods primarily focus on the wear or fatigue evolution of surface materials under ideal contact conditions. However, they are insufficient in identifying and accurately quantifying failure modes caused by structural connection degradation that lead to abnormal stress on the working surfaces. This can result in an overestimation of the actual usable time of the mold, as the decline in part quality due to structural connection problems may force the mold to cease use prematurely before the working surface wear reaches its limit. Current technology lacks a method to effectively identify and quantify this phenomenon caused by assembly structure degradation, which acts on critical working surfaces and leads to unexpected stress, thereby accurately diagnosing these critical failure modes and their development trends related to the evolution of mold structural health. Summary of the Invention

[0003] The purpose of this application is to provide a method and system for analyzing the life of stamping dies, which can effectively identify and diagnose abnormal stress problems on the working surface caused by the performance degradation of the assembly structure. It overcomes the shortcomings of the prior art that only focuses on surface wear and fatigue, and improves the comprehensiveness and accuracy of die life analysis.

[0004] This application provides a method for analyzing the life of stamping dies, including: Acquire the initial deformation response data of the sensitive area of ​​assembly structure performance degradation on the stamping die, and acquire the initial connection state parameters of the key connecting components on the stamping die; In the subsequent production process of stamping dies, the current deformation response data of sensitive areas is acquired based on the set acquisition cycle, and the current connection status parameters of key connecting components are acquired based on the set acquisition cycle. Calculate the deviation parameter of the current deformation response data from the initial deformation response data based on the current deformation response data and the initial deformation response data; calculate the change trend parameter of the key connection components based on the current connection state parameter and the initial connection state parameter. Based on the deviation degree parameters and change trend parameters, the abnormal stress on the working surface of the stamping die can be diagnosed.

[0005] The above method can identify and diagnose abnormal stress on the working surface caused by the performance degradation of the assembly structure, overcoming the shortcomings of existing technologies that only focus on surface wear and fatigue.

[0006] Furthermore, the diagnosis of whether there is abnormal stress on the working surface of the stamping die based on the deviation degree parameter and the change trend parameter includes: Determine whether the deviation parameter exceeds the preset deviation threshold; If the deviation parameter exceeds the preset deviation threshold, then it is determined whether the trend of the change trend parameter is consistent with the degree of performance degradation of the key connecting components. If the trend of the changing parameters is consistent with the degree of performance degradation of the key connecting components, then an abnormal stress is diagnosed on the working surface of the stamping die.

[0007] The above methods provide specific diagnostic logic and improve diagnostic accuracy.

[0008] Furthermore, the step of diagnosing abnormal stress on the working surface of the stamping die includes: Obtain the quantitative impact relationship of the deformation response of each key connecting component in the sensitive area; Obtain the current actual performance degradation of each critical connection component; Based on the current actual performance degradation of the key connecting components and the corresponding quantitative impact relationship of the key connecting components, the expected impact of the deviation of the key connecting components on the deformation response data of the sensitive area is calculated. Based on the expected impact, identify the dominant key connecting components or dominant performance degradation factors that cause abnormal stress on the working surface.

[0009] The above methods can further identify the dominant factors causing abnormal stress, providing a basis for precise maintenance.

[0010] Furthermore, the step of obtaining the quantitative influence relationship of the deformation response of each key connecting component in the sensitive area includes: In the initial stage of stamping die, the initial quantitative influence relationship of each key connecting component on the deformation response of the sensitive area is obtained among multiple key connecting components; During the subsequent production process of stamping dies, at least one production status parameter related to the evolution of the physical properties of the stamping die is monitored. Determine whether at least one production status parameter meets the preset production threshold. When at least one production state parameter meets the preset production threshold, the initial quantitative influence relationship or the previously updated quantitative influence relationship is adjusted based on the current production state of the stamping die to obtain a quantitative influence relationship that is compatible with the current production state. The quantitative influence relationship is used for subsequent determination of the dominant failure factor based on the compatible quantitative influence relationship.

[0011] The above method takes into account the dynamic influence of the evolution of mold physical properties on the quantitative relationship, thus improving the adaptability and accuracy of the analysis.

[0012] Furthermore, the step of adjusting the initial quantified influence relationship or the previously updated quantified influence relationship based on the current stamping die production status includes: Identify production state parameters that change during the current production state of the stamping die; Based on the current actual changes in production status parameters and the pre-set adjustment rules of the physical influence mechanism corresponding to the production status parameters, the adjustment influence factor of the production status parameters on the initial quantitative influence relationship or the previously updated quantitative influence relationship is calculated. By aggregating all the adjustment factors and combining them with the strategies among the pre-determined physical influence mechanisms, the total adjustment value for the initial quantitative influence relationship or the previously updated quantitative influence relationship is calculated. The initial quantized influence relationship or the previously updated quantized influence relationship is adjusted based on the total adjustment value.

[0013] The above methods provide specific adjustment methods for quantifying the influence relationship, enabling the analysis model to better reflect the actual production status.

[0014] Furthermore, the step of adjusting the production state parameters based on the current actual changes in the production state parameters and the pre-set adjustment rules corresponding to the physical influence mechanisms of the production state parameters includes: Get the current adjustment rule, which may be the initial adjustment rule or the updated adjustment rule; During the production process of stamping dies, evaluation response data is acquired to assess the current adjustment rules; Based on the current adjustment rules and the current stamping die production status parameters, calculate the expected response data corresponding to the current adjustment rules; Based on the evaluation response data and the expected response data, determine the deviation parameters between the current adjustment rules and the current physical properties of the stamping die; Determine whether the deviation degree parameter meets the update conditions. If the deviation degree parameter meets the update conditions, update the current adjustment rule based on the deviation degree parameter.

[0015] The above method provides an adaptive update mechanism for adjusting rules, which further improves the accuracy and robustness of the model.

[0016] Furthermore, the step of updating the current adjustment rule based on the deviation degree parameter includes: Identify the elements in the current adjustment rules that characterize the physical influence mechanism. These elements are the rule parameters or rule structure of the adjustment rules. The updated adjustment rules are obtained by adjusting the elements characterizing the physical influence mechanism based on the deviation parameter.

[0017] The above method provides a specific approach to adjusting rule elements based on deviation parameters, making rule updates more targeted.

[0018] Furthermore, the step of identifying the elements characterizing the physical influence mechanism in the current adjustment rule includes: Obtain the magnitude and pattern information of the deviation parameter, and determine the magnitude or pattern characteristics of the deviation parameter based on the magnitude and pattern information. When the magnitude characteristic of the deviation degree parameter meets the first type of magnitude condition or the pattern characteristic of the deviation degree meets the first type of pattern condition, the rule parameters in the element are adjusted according to the deviation degree parameter. When the magnitude characteristic of the deviation degree parameter meets the second type of magnitude condition or the pattern characteristic of the deviation degree parameter meets the second type of pattern condition, the rule structure in the element is adjusted according to the deviation degree parameter.

[0019] The above methods refine the adjustment conditions for rule parameters and rule structure, making rule updates more intelligent and precise.

[0020] Furthermore, a deformation monitoring device is installed in the sensitive area, which is used to collect initial deformation response data and current deformation response data.

[0021] The above-mentioned technologies provide a specific device for acquiring deformation response data, thereby enhancing the feasibility of the solution.

[0022] This application also proposes a stamping die life analysis system for performing the above-described stamping die life analysis method. The system includes: The initial data acquisition module is used to acquire the initial deformation response data of the sensitive area of ​​the assembly structure performance degradation on the stamping die, and to acquire the initial connection status parameters of the key connecting parts on the stamping die. The periodic data acquisition module is used to acquire the current deformation response data of sensitive areas and the current connection status parameters of key connecting components based on the set acquisition cycle during the subsequent production process of stamping dies. The deformation deviation calculation module is used to calculate the deviation parameter of the current deformation response data from the initial deformation response data based on the current deformation response data and the initial deformation response data; and to calculate the change trend parameter of the key connection components based on the current connection state parameter and the initial connection state parameter. The diagnostic module is used to diagnose whether there is any abnormal stress on the working surface of the stamping die based on the deviation degree parameter and the change trend parameter.

[0023] As can be seen from the above, the stamping die life analysis method and system provided in this application diagnoses whether there is abnormal stress on the working surface by monitoring the deformation response of sensitive areas of the die assembly structure performance degradation and the connection status of key connecting components, and calculating the degree of deviation and change trend based on these data. This effectively solves the problem that the existing technology is difficult to identify and quantify the abnormal stress on the working surface caused by the performance degradation of the assembly structure. It has the advantages of being able to effectively identify and diagnose the abnormal stress on the working surface caused by the performance degradation of the assembly structure, overcoming the shortcomings of the existing technology that only focuses on surface wear and fatigue, and improving the comprehensiveness and accuracy of die life analysis. Attached Figure Description

[0024] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0025] Figure 1 This is a flowchart of the stamping die life analysis method in an embodiment of the present invention; Figure 2 This is a flowchart of a method for diagnosing abnormal stress on the working surface of a stamping die according to an embodiment of the present invention; Figure 3 This is a schematic diagram of the stamping die life analysis system in an embodiment of the present invention. Detailed Implementation

[0026] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0027] This invention can be applied to a large stamping die used to produce automotive body panels. After hundreds of thousands of stamping cycles, although periodic inspections of the die's working surfaces did not reveal unexpected wear or significant fatigue cracks, the produced parts began to exhibit sporadic wrinkling or tearing in specific areas. Simultaneously, monitoring revealed that the preload of certain stress-concentrated connection points in the die structure, such as the bolt group securing the rear of the punch, had decreased compared to its initial state. Measurements showed that in the die area prone to defects, the clearance in the closed state was larger than the design value. This increased clearance was not directly caused by surface wear, but rather by the decrease in preload at the connection points, leading to reduced connection stiffness in that area. This resulted in additional elastic deformation or minute displacement during stamping, causing the contact pressure distribution between the sheet metal and the die surface in that area to deviate from the design state. This invention can assess the die's lifespan by monitoring wear or fatigue damage on the die's working surfaces, i.e., by monitoring the deformation response of specific areas of the die, as changes in structural condition are reflected in the deformation response. Simultaneously, monitoring the connection status of critical connecting components directly reflects the structural health. By comparing these monitoring data with the initial state and combining the two for analysis, it is possible to diagnose whether there are abnormal stresses on the working surface, thereby identifying problems caused by structural degradation.

[0028] Figure 1 A flowchart of a stamping die life analysis method according to an embodiment of the present invention is shown, including: S101. Obtain the initial deformation response data of the sensitive area of ​​assembly structure performance degradation on the stamping die, and obtain the initial connection state parameters of the key connecting parts on the stamping die. It should be noted that the sensitive area for assembly structure performance degradation refers to the area on the stamping die that is prone to abnormal stress on the working surface due to the degradation of the assembly structure performance. It can be determined by methods such as finite element analysis, historical experience, or experiments. The purpose is to focus the monitoring range and improve the efficiency and accuracy of analysis. The initial deformation response data refers to the deformation data of the sensitive area under specific working conditions when the stamping die is in a healthy state. It can be obtained by strain gauges, displacement sensors, or optical measurement equipment. The purpose is to establish a benchmark for subsequent deformation changes. The critical connection components refer to the connection parts that have a significant impact on the overall structural stiffness or local stress state of the stamping die and whose performance is prone to degradation with the increase of stamping cycles. Examples include high-strength bolt connections and guide post / sleeve mating parts. The purpose is to identify the main factors leading to structural performance degradation. The initial connection state parameters refer to the connection performance indicators of critical connection components when the stamping die is in a healthy state. Examples include bolt preload and fit clearance. They can be obtained by torque measurement, ultrasonic measurement, or feeler gauge measurement. The purpose is to establish an initial benchmark for the performance of critical connection components.

[0029] S102. During the subsequent production process of the stamping die, the current deformation response data of the sensitive area is obtained based on the set acquisition cycle, and the current connection status parameters of the key connecting components are obtained based on the set acquisition cycle. It should be noted that the acquisition period here refers to the time interval or stamping cycle interval for acquiring current deformation response data and current connection status parameters during the subsequent production process of the stamping die. It can be set according to factors such as the type of stamping die and production cycle, and its purpose is to periodically track changes in the state of the stamping die. The current deformation response data refers to the deformation data of the sensitive area under specific working conditions acquired according to the set acquisition period during the subsequent production process of the stamping die. Its acquisition method is similar to that of the initial deformation response data, and its purpose is to reflect the current deformation state of the stamping die. The current connection status parameters refer to the connection performance indicators of key connecting components acquired according to the set acquisition period during the subsequent production process of the stamping die. Its acquisition method is similar to that of the initial connection status parameters, and its purpose is to reflect the current performance state of the key connecting components.

[0030] S103. Calculate the deviation parameter of the current deformation response data from the initial deformation response data based on the current deformation response data and the initial deformation response data; calculate the change trend parameter of the key connection component based on the current connection state parameter and the initial connection state parameter. It should be noted that the deviation parameter here refers to the quantitative difference between the current deformation response data and the initial deformation response data. It can be characterized by calculating indicators such as root mean square error and maximum deviation. Its purpose is to quantify the degree of change in the deformation state of the sensitive area. The trend parameter refers to the change law of the current connection state parameter relative to the initial connection state parameter over time or the number of stampings. It can be characterized by calculating indicators such as the growth rate of the parameter and the cumulative change. Its purpose is to quantify the speed or degree of performance degradation of key connection components.

[0031] S104. Based on the deviation degree parameter and the change trend parameter, diagnose whether there is abnormal stress on the working surface of the stamping die.

[0032] It should be noted that diagnosing whether there is abnormal stress on the working surface here refers to a comprehensive analysis based on the deviation degree parameters and the change trend parameters to determine whether the working surface of the stamping die is subjected to local stress, strain or changes in contact state in sensitive areas that are not expected by the design. The purpose is to identify potential failure risks caused by structural performance degradation.

[0033] This invention provides a stamping die life analysis method that addresses the shortcomings of traditional life analysis methods in identifying and quantifying key failure modes caused by the degradation of the stamping die assembly structure. This method aims to more accurately assess the remaining usable time of the die, avoid overestimating die life by focusing solely on surface wear, and provide more precise guidance for maintenance. Specifically, this invention comprehensively analyzes the deformation response data of sensitive areas of the assembly structure degradation with the connection status parameters of key connecting components. This allows for the identification and diagnosis of abnormal stress on the working surface of the stamping die caused by the degradation of the assembly structure, achieving a more accurate assessment of the stamping die life and providing precise guidance for maintenance.

[0034] As a specific implementation method, for large stamping dies for automotive body panels, the connection area between the punch and the die holder, which is susceptible to the decay of bolt preload, can be selected as a sensitive area for the degradation of assembly structure performance. Displacement sensors are installed in this area to collect initial deformation response data in the closed state of the stamping die and current deformation response data during subsequent production. Simultaneously, key bolt groups securing the punch are identified as critical connection components, and their initial connection parameters (such as preload) and current connection parameters during subsequent production are measured using a torque wrench or ultrasonic sensors. During production, for example, at regular stamping cycles or during routine maintenance, current deformation response data and connection parameters are collected. The displacement deviation of the current deformation response data relative to the initial data is calculated as a deviation degree parameter, and the decrease or rate of decrease of the current bolt preload relative to the initial preload is calculated as a trend parameter. When the displacement deviation exceeds a preset threshold, and the decreasing trend of the bolt preload matches this displacement deviation, an abnormal stress is diagnosed on the working surface corresponding to the sensitive area.

[0035] It should be noted that the steps for diagnosing whether there is abnormal stress on the working surface of the stamping die based on the deviation degree parameter and the change trend parameter include: determining whether the deviation degree parameter exceeds the preset deviation degree threshold; if the deviation degree parameter exceeds the preset deviation degree threshold, determining whether the change trend of the change trend parameter is consistent with the performance degradation degree of the key connecting parts; if the change trend of the change trend parameter is consistent with the performance degradation degree of the key connecting parts, then it is diagnosed that there is abnormal stress on the working surface of the stamping die.

[0036] Among them, the preset deviation threshold refers to the pre-set numerical limit used to define whether the deviation parameter has reached the level that needs attention. It can be determined based on mold design specifications, historical experience data, simulation analysis results or expert knowledge. Its purpose is to provide a preliminary screening standard to avoid misjudging deformation fluctuations within a small or normal range. The performance degradation degree of key connecting components refers to the degree of decline in the actual performance of key connecting components relative to their initial or design performance. It can be quantified by methods such as bolt preload reduction, connection stiffness reduction, increase in fit clearance or fatigue damage accumulation. Its purpose is to characterize the root cause of the decline in the overall health of the mold structure.

[0037] This invention, through the introduction of a preset deviation threshold and the degree of performance degradation of key connecting components as diagnostic criteria, makes the diagnostic process more refined and accurate. First, it determines whether the deviation parameter exceeds the preset deviation threshold, providing an initial screening standard. Only when the deviation in the deformation response reaches a certain level is further judgment made, avoiding oversensitivity to minor deviations and improving diagnostic efficiency. Based on the deviation parameter obtained from prior solutions, this judgment step can quickly identify potential anomalies. Second, if the deviation parameter exceeds the preset deviation threshold, it determines whether the trend of the change trend parameter is consistent with the degree of performance degradation of the key connecting components. This step links the deviation in the deformation response with the actual degradation of the key connecting components. Based on the change trend parameter obtained from prior solutions, by comparing its trend with the degree of performance degradation of the key connecting components, it avoids misjudging deformation caused by other factors as abnormal stress, further improving diagnostic accuracy. Only when the deviation in the deformation response exceeds the threshold, and this deviation is consistent with the performance degradation trend of the key connecting components, is an abnormal stress on the working surface ultimately diagnosed. The above steps enable a more accurate identification of abnormal stress on the working surface caused by the degradation of the mold assembly structure, thus providing a more reliable basis for subsequent mold maintenance and life assessment. This diagnostic method, which combines deformation response deviation and structural component performance degradation trends, effectively complements and improves upon previous solutions that relied solely on parameter-based preliminary diagnosis, significantly enhancing the accuracy and reliability of the diagnosis.

[0038] In some preferred embodiments, a preset deviation threshold can be set. For example, when the deformation response of a sensitive area deviates from its initial value by more than a certain percentage, the deviation parameter is considered to have exceeded the threshold. Simultaneously, the preload decay of key connecting components (e.g., bolted connections) is monitored and quantified as the degree of performance degradation of the key connecting components. The calculated trend parameter reflects the rate of increase in deformation response over time. During diagnosis, the deviation of the deformation response is first checked to see if it exceeds the set threshold. If it does, the trend of the deformation response (e.g., whether it shows a continuous increase) is further checked to see if it is consistent with the preload decay trend of the key connecting components (e.g., a continuous decrease in preload). If both trends are consistent, an abnormal stress on the working surface can be diagnosed, indicating that this abnormal deformation is likely caused by the performance degradation of the key connecting components.

[0039] By using the above technical solutions, and by setting clear deviation thresholds and introducing the performance degradation of key connecting components as the basis for judgment, the diagnostic process for abnormal stress on the working surface of stamping dies has clear standards. This avoids the subjectivity and uncertainty of the diagnostic results, improves the accuracy of the diagnosis, and can effectively identify specific failure modes caused by the decline in the health of the die structure. This provides reliable technical support for the precise maintenance and life management of dies.

[0040] Specifically, Figure 2 A flowchart illustrating a method for diagnosing abnormal stress on the working surface of a stamping die according to an embodiment of the present invention is shown below: S201. Obtain the quantitative impact relationship of the deformation response of each key connecting component in the sensitive area; S202. Obtain the current actual performance degradation of each critical connection component; S203. Based on the current actual performance degradation of the key connecting components and the quantitative impact relationship corresponding to the key connecting components, calculate the expected impact of the deviation of the key connecting components on the deformation response data of the sensitive area. S204. Based on the expected impact, determine the dominant key connecting components or dominant performance degradation factors that cause abnormal stress on the working surface.

[0041] Among these, obtaining the quantitative impact relationship of the deformation response of each key connecting component in the sensitive area refers to establishing a quantitative correlation model between the performance state changes of each key connecting component and the deformation response changes in the sensitive area. This can be achieved through physical modeling, finite element simulation, experimental testing, or data-driven analysis, aiming to provide basic data for subsequent quantitative assessment of the impact of different key connecting components on the deformation deviation in the sensitive area. Obtaining the current actual performance degradation of each key connecting component refers to obtaining the degree of performance decline of each key connecting component relative to its initial state through monitoring or evaluation methods. Specifically, this can be achieved by measuring parameters such as bolt preload, connection gap, and guiding accuracy and converting them into quantitative indicators, aiming to reflect the current actual health status of the key connecting components. Based on the current actual performance degradation of the key connecting components and the key connecting components... The corresponding quantitative impact relationship, calculating the expected impact of the deviation of the deformation response data of the sensitive area by the key connecting component, refers to using the established quantitative impact relationship model, combined with the current actual performance degradation of the key connecting component, to predict or calculate how much deviation the degradation of the key connecting component will theoretically cause in the deformation response data of the sensitive area. Its purpose is to quantify the contribution of the performance degradation of a single key connecting component to the overall deformation anomaly. Based on the expected impact, determining the dominant key connecting component or dominant performance degradation factor causing the abnormal stress on the working surface refers to identifying the key connecting component or its corresponding performance degradation mode that contributes the most to the deviation of the deformation response in the sensitive area by comparing the expected impact of different key connecting components. Specifically, this can be achieved by setting thresholds, sorting, or cluster analysis, etc., with the aim of accurately locating the main root cause of the abnormal stress on the working surface.

[0042] This invention first establishes a quantitative correlation between the performance degradation of key connecting components and the deformation response of sensitive areas, and then acquires the actual degradation state of the key connecting components in real time. Based on this correlation and the actual state, it can quantitatively calculate the theoretical contribution of the degradation of each key connecting component to the deformation deviation of the sensitive area. Because the influence of each potential factor can be quantified, the most significant cause of abnormal stress on the working surface—the dominant key connecting component or the dominant performance degradation factor—can be accurately identified by comparing these quantified influence values. This logical progression from qualitative anomaly assessment to quantitative cause analysis effectively solves the problem of merely identifying a problem without pinpointing its root cause. In this way, this application provides precise guidance for mold maintenance, avoids ineffective intervention in non-dominant factors, improves maintenance efficiency and effectiveness, and ultimately extends the effective service life of the mold and ensures product quality.

[0043] For example, when abnormal deformation occurs in the sensitive area of ​​a stamping die, it is necessary to identify the dominant factors. First, the quantitative influence relationships of the deformation responses of multiple key connecting components in the die (e.g., bolt group A, bolt group B, guide post / sleeve C) in the sensitive area can be obtained. For instance, through prior finite element simulation analysis or experimental testing, it can be found that for every unit decrease in the preload of bolt group A, the deformation in the sensitive area increases by 0.05 units; for every unit decrease in the preload of bolt group B, the deformation increases by 0.03 units; and for every unit increase in the clearance of guide post / sleeve C, the deformation increases by 0.04 units. Next, the actual performance degradation of these key connecting components is obtained. For example, through online monitoring or periodic inspection, it is found that the preload of bolt group A has actually decreased by 1.5 units, the preload of bolt group B has actually decreased by 0.5 units, and the clearance of guide post / sleeve C has actually increased by 0.8 units. Then, based on these actual degradation amounts and quantitative influence relationships, the expected impact of each key connecting component on the deformation deviation in the sensitive area is calculated. For example, the expected impact of bolt group A is 1.5 * 0.05 = 0.075 units; the expected impact of bolt group B is 0.5 * 0.03 = 0.015 units; and the expected impact of guide post and guide sleeve C is 0.8 * 0.04 = 0.032 units. Finally, based on these expected impacts, the dominant key connecting components or dominant performance degradation factors causing abnormal stress on the working surface can be identified. By comparing the calculation results (0.075, 0.015, 0.032), it can be found that bolt group A has the largest expected impact; therefore, it can be determined that the preload decay of bolt group A is the dominant factor causing abnormal deformation in the sensitive area.

[0044] The step of obtaining the quantitative influence relationship of the deformation response of each key connecting component in the sensitive area in this embodiment of the invention includes: in the initial stage of the large stamping die for automotive body panels, obtaining the initial quantitative influence relationship of the deformation response of each key connecting component in the sensitive area; during the subsequent production process of the stamping die, monitoring at least one production state parameter related to the evolution of the physical properties of the stamping die; determining whether the at least one production state parameter meets the production preset threshold; when the at least one production state parameter meets the production preset threshold, adjusting the initial quantitative influence relationship or the previously updated quantitative influence relationship based on the current production state of the stamping die to obtain a quantitative influence relationship adapted to the current production state, and the quantitative influence relationship is used for subsequent determination of the dominant failure factor based on the adapted quantitative influence relationship.

[0045] It should be noted that production state parameters refer to indicators characterizing the current working environment or physical state of the stamping die. These parameters can be acquired using devices such as temperature sensors, pressure sensors, and lubrication status monitoring devices. Their purpose is to capture changes in external or internal conditions that may affect the deformation response of the die structure. Production preset thresholds refer to the conditional limits used to trigger adjustments to the quantitative influence relationship. These thresholds can be set based on die design specifications, empirical data, or historical production data. Their purpose is to ensure that adjustments to the quantitative influence relationship are only made when there are significant changes in the production state, avoiding unnecessary processing. Adjustment processing refers to the process of correcting existing quantitative influence relationships based on the current production state parameters. This can be achieved through rule-based adjustment, model-based prediction correction, or data-driven learning updates. The purpose is to enable the quantitative influence relationship to more accurately reflect the actual deformation response characteristics under the current die state.

[0046] This invention establishes an initial quantitative influence relationship between key connecting components and the deformation response of sensitive areas during the initial stage of mold making, serving as the basis for subsequent analysis. During continuous mold production, production state parameters related to the evolution of mold physical properties, such as mold temperature, stamping pressure, and lubricant viscosity, are systematically monitored. Changes in these parameters directly or indirectly reflect the current working environment and internal state of the mold, and these state changes affect the interaction between mold structural components and the overall stiffness distribution, thereby altering the degree to which the performance degradation of key connecting components affects the deformation response of sensitive areas. By setting a preset production threshold, the system can intelligently determine whether the changes in the current production state parameters have reached a level requiring a reassessment of the quantitative influence relationship. When the production state parameters meet the preset threshold, it indicates that the physical properties of the mold may have undergone a significant evolution sufficient to affect the deformation response relationship. At this point, the system adjusts the previously acquired initial quantitative influence relationship or the most recently updated quantitative influence relationship based on the current stamping mold production state. This adjustment process considers the specific values ​​or trends of current parameters such as temperature and pressure, correcting the original quantitative influence relationship to more accurately reflect the true correlation between the performance degradation of key connecting components and the deformation deviation of sensitive areas under the current mold state. Subsequently, when determining the dominant failure factors, static or outdated quantitative influence relationships are no longer used. Instead, dynamically adjusted quantitative influence relationships adapted to the current production status are adopted. This dynamic adaptability makes the determination of failure factors closer to the actual working state of the mold, significantly improving the accuracy of the judgment. Compared with methods that rely solely on static quantitative relationships, this solution can effectively address the uncertainties brought about by the evolution of physical properties of the mold during long-term production, ensuring that the dominant factors causing abnormal stress on the working surface can be accurately identified at different production stages, thus providing a reliable basis for precise mold maintenance and life management.

[0047] In this embodiment of the invention, after the initial installation and commissioning of the large stamping die for automotive body panels, a series of standard stamping strokes are performed. Using deformation sensors installed in sensitive areas and sensors monitoring the connection status of key connecting components (such as specific bolt groups), data is collected to establish an initial quantitative influence relationship model between the preload decay or clearance change of each key bolt group and the deformation response of the sensitive area. This model could be a linear or nonlinear regression model. After the die is put into mass production, production status parameters such as the temperature of the die body, the tonnage of the stamping press (reflecting the actual stamping pressure), and the operating status of the automatic lubrication system (indirectly reflecting lubrication) are continuously monitored. The system sets a preset production threshold of a temperature change exceeding 10°C or a stamping tonnage fluctuation exceeding 5% of the rated value. When the die temperature rises above this threshold, the system determines that the quantitative influence relationship needs adjustment. Based on the current die temperature value, the system calls a preset adjustment algorithm, which may be a correction factor designed according to the temperature-stiffness change curve, to correct the correlation coefficient in the initial quantitative influence relationship model, obtaining a quantitative influence relationship suitable for the current higher temperature condition. For example, high temperatures may slightly reduce the stiffness of the mold material, making the impact of bolt preload decay on deformation more significant. The adjusted quantification relationship will reflect this enhanced effect. When subsequently determining the dominant failure factor, this temperature-adjusted quantification relationship, combined with the current preload decay of the key bolt group, will be used to calculate its expected impact on deformation deviation in sensitive areas. This allows for a more accurate determination of which bolt group's performance degradation is the primary cause of abnormal deformation under the current temperature environment.

[0048] Based on the above technical solution, the embodiments of the present invention can dynamically adjust the quantitative influence relationship of key connecting components on the deformation response of sensitive areas, adapting it to the current production state of the stamping die. This overcomes the problem of static and unchanging quantitative relationships in traditional methods, which cannot adapt to the evolution of the physical properties of the die, and significantly improves the accuracy of judging the dominant failure factors based on quantitative influence relationships. Therefore, this solution can more reliably identify the root cause of abnormal stress on the working surface, providing more accurate guidance for predictive maintenance and life management of stamping dies.

[0049] The steps for adjusting the initial quantitative influence relationship or the previously updated quantitative influence relationship based on the current production state of the stamping die in this embodiment of the invention include: identifying the production state parameters that have changed under the current production state of the stamping die; calculating the adjustment influence factor of the production state parameters on the initial quantitative influence relationship or the previously updated quantitative influence relationship based on the current actual change of the production state parameters and the adjustment rules of the physical influence mechanism corresponding to the pre-set production state parameters; collecting all the adjustment influence factors and combining them with the strategies between the pre-determined physical influence mechanisms to calculate the total adjustment value of the initial quantitative influence relationship or the previously updated quantitative influence relationship; and adjusting the initial quantitative influence relationship or the previously updated quantitative influence relationship based on the total adjustment value.

[0050] It should be noted that the adjustment rules of the physical influence mechanism here refer to the rules or models describing how changes in specific production state parameters affect the quantitative influence relationship of the deformation response of key connecting components in sensitive areas. Specifically, it can be a function, a lookup table, a calculation formula based on a physical model, or a machine learning model. Its purpose is to quantify the contribution of changes in a single production state parameter to the quantitative influence relationship. The adjustment influence factor refers to the quantitative influence of a specific production state parameter on the quantitative influence relationship, calculated based on the actual change in the specific production state parameter and its corresponding adjustment rules. Its purpose is to transform the influence of different production state parameters into a comprehensively calculable value. The strategy between physical influence mechanisms refers to the method used to comprehensively consider the influence of multiple production state parameters. Specifically, it can include simple superposition, weighted average, multiplicative combination, complex calculations based on interaction models, etc. Its purpose is to handle the possible interaction or coupling effects between different production state parameters. The total adjustment value refers to the overall correction amount required for the initial quantitative influence relationship or the previously updated quantitative influence relationship after comprehensively considering all changed production state parameters and their interactions. Its purpose is to provide a single value for adjusting the quantitative influence relationship.

[0051] In this embodiment of the invention, by identifying production state parameters that have changed under the current production state, the influencing factors that need to be considered are clarified. Based on the actual change in each changed production state parameter and according to pre-set adjustment rules reflecting the physical influence mechanism of that parameter, the specific adjustment factor of that parameter on the quantitative influence relationship is calculated. This process considers the differences in the way and degree of influence of different parameters on the quantitative influence relationship. Subsequently, all calculated adjustment factors are collected and combined with the interaction strategy between pre-determined physical influence mechanisms to calculate a total adjustment value. This total adjustment value comprehensively reflects the overall influence of all relevant parameters on the quantitative influence relationship under the current production state. Finally, based on this total adjustment value, the initial or previously updated quantitative influence relationship is corrected to obtain a quantitative influence relationship that is more consistent with the current actual production state. In this way, the scheme can more comprehensively and meticulously consider the transmission effect of complex and ever-changing production state parameters on the performance degradation of mold structure, making the adjustment of the quantitative influence relationship more accurate, thereby improving the accuracy of subsequent judgment of dominant failure factors and mold life analysis based on this relationship. Compared with methods that rely solely on fixed relationships or simple single-parameter adjustments, this approach is better able to adapt to the dynamic and changing environment faced by stamping dies during long-term production, providing a more reliable data foundation for predictive maintenance and life management of dies.

[0052] During a specific production cycle of a stamping die, the system monitors changes in production parameters such as increased die temperature, increased stamping speed, and decreased lubricant viscosity. First, the system identifies temperature, speed, and viscosity as the parameters currently changing. Next, for the temperature increase, it calculates the corresponding adjustment factor based on preset temperature-influence rules (e.g., for every degree Celsius increase in temperature, a coefficient in the quantified influence relationship needs to be increased by a specific value). Similarly, it calculates the adjustment factors corresponding to increased speed and decreased viscosity based on preset speed-influence and viscosity-influence rules, respectively. Then, these three adjustment factors are aggregated. Assuming the preset strategy between physical influence mechanisms is weighted summation, and considering the different weights of temperature, speed, and viscosity in the quantified influence relationship, the system will perform a weighted summation of the three adjustment factors to obtain a total adjustment value. Finally, this total adjustment value is superimposed on the current quantified influence relationship to obtain a new quantified influence relationship reflecting the current high-temperature, high-speed, and low-viscosity production state. This new quantified influence relationship will be used for subsequent die condition diagnosis and life analysis.

[0053] The above technical solution can comprehensively consider the complex influence of multiple production state parameters on the quantitative influence relationship, making the adjustment of the quantitative influence relationship closer to the actual production situation, thereby improving the accuracy of mold life analysis based on the quantitative influence relationship.

[0054] The steps of adjusting the production state parameters based on the current actual change in the production state parameters and the pre-set physical influence mechanism corresponding to the production state parameters in this embodiment of the invention include: obtaining the current adjustment rule, which is either an initial adjustment rule or an updated adjustment rule; during the production process of the stamping die, obtaining evaluation response data for evaluating the current adjustment rule; calculating the expected response data corresponding to the current adjustment rule based on the current adjustment rule and the current production state parameters of the stamping die; determining the deviation degree parameter between the current adjustment rule and the physical properties of the current stamping die based on the evaluation response data and the expected response data; determining whether the deviation degree parameter meets the update condition; and updating the current adjustment rule based on the deviation degree parameter when the deviation degree parameter meets the update condition.

[0055] It should be noted that the evaluation response data here refers to the actual monitoring data used to measure the effectiveness of the current adjustment rule. It can be collected from the physical state or output results of the stamping die during the production process, such as the deformation amount, temperature, or quality indicators of the stamped parts at specific locations of the die. The expected response data refers to the theoretical prediction data calculated based on the current adjustment rule and the current production state parameters of the stamping die. It can be calculated by inputting the current production state parameters into the mathematical model or algorithm represented by the current adjustment rule. The update condition refers to the judgment criteria that trigger the update of the adjustment rule. It can be set as the deviation parameter exceeding a preset threshold, the deviation parameter continuously showing a certain trend, or the deviation being significant based on statistical methods. The update process refers to the process of correcting the current adjustment rule according to the deviation parameter. It can include the parameter values ​​in the adjustment rule or changing the structure of the rule.

[0056] This invention addresses the problem of preset rules failing after mold state changes by establishing an adaptive mechanism for adjustment rules. First, the currently used adjustment rule, whether initially set or previously optimized, is acquired. During actual mold production, evaluation response data reflecting the mold's true state is collected synchronously. Using the current adjustment rule and the mold's production state parameters, the expected response data under the current rule is calculated. The actual collected evaluation response data is compared with the calculated expected response data, quantifying the difference to obtain a deviation parameter. This deviation parameter directly reflects the degree of agreement between the current adjustment rule and the actual evolution of the mold's physical properties. If the deviation parameter meets the update conditions, it indicates that the current rule can no longer accurately reflect the mold state; in this case, the current adjustment rule is corrected based on this deviation parameter. This process forms a closed-loop feedback, enabling the adjustment rule to dynamically optimize based on the mold's actual performance at different production stages. In this way, the adjustment influence factor calculated based on the adjustment rule more accurately reflects the actual impact of production state parameters on the quantified influence relationship, thereby improving the accuracy of subsequent judgments of dominant failure factors based on the quantified influence relationship and ultimately enhancing the reliability of the entire mold life analysis.

[0057] In practice, the current adjustment rule can be a simple linear function, for example, adjustment influence factor = a * (temperature change) + b, where a and b are rule parameters. During the stamping die production process, the actual deformation of sensitive areas of the die can be periodically acquired as evaluation response data. Simultaneously, the temperature change of key parts of the die is monitored as a production status parameter. Based on the current linear function rule and the temperature change, the expected deformation is calculated as the expected response data. Subtracting the expected deformation from the actual deformation yields the deviation parameter. When the absolute value of this deviation parameter exceeds a set threshold, such as 0.05 mm, the update condition is met. At this point, the values ​​of parameters a and b can be recalculated based on the deviation parameter, for example, using the least squares method or other optimization algorithms, thereby updating the adjustment rule.

[0058] The aforementioned technical solution enables the dynamic evaluation and updating of pre-set adjustment rules based on the changing state of the stamping die during actual production. This allows the adjustment influence factors of the production state parameters calculated according to the adjustment rules to more accurately reflect the current physical property evolution of the die. Therefore, the accuracy of the quantified influence relationship is improved, which in turn improves the accuracy of subsequent judgments on key connecting components or dominant performance degradation factors, ultimately enhancing the accuracy and reliability of stamping die life analysis and avoiding misjudgments or prediction deviations caused by rule failure.

[0059] The step of updating the current adjustment rule based on the deviation degree parameter in this embodiment of the invention includes: identifying the elements in the current adjustment rule that characterize the physical influence mechanism, wherein the elements are the rule parameters or rule structure of the adjustment rule; and adjusting the elements characterizing the physical influence mechanism according to the deviation degree parameter to obtain the updated adjustment rule.

[0060] It should be noted that the current adjustment rule refers to the rule used to calculate the adjustment impact factor based on the current actual change in production state parameters. It can be an initially set rule or a previously updated rule. The element characterizing the physical impact mechanism refers to the part of the current adjustment rule that directly reflects the physical impact mechanism. It can be the rule parameters of the adjustment rule or the rule structure of the adjustment rule. The rule parameters refer to the numerical part of the adjustment rule used to quantify the physical impact mechanism. It can be coefficients, weights, thresholds, etc. The rule structure refers to the logical form or mathematical model of the adjustment rule. It can be a linear function, a nonlinear function, a piecewise function, a lookup table, etc. The deviation parameter refers to the parameter used to evaluate the deviation between the current adjustment rule and the current physical properties of the stamping die. It can be determined based on the evaluation response data and the expected response data.

[0061] In this embodiment of the invention, the elements characterizing the physical influence mechanism in the current adjustment rule are identified, and these elements are adjusted according to the deviation degree parameter to update the current adjustment rule. Specifically, by acquiring the evaluation response data and expected response data, the deviation degree parameter between the current adjustment rule and the physical properties of the current stamping die is calculated. This parameter quantifies the applicability deviation of the current adjustment rule. This solution uses this deviation degree parameter to specifically adjust the rule parameters or rule structure in the adjustment rule. For example, if the deviation degree parameter indicates a systematic deviation in the rule parameters, the rule parameters are corrected; if the deviation degree parameter indicates that the logical structure of the rule is no longer applicable, the rule structure is adjusted. This feedback adjustment mechanism based on the actual deviation degree allows the adjustment rule to evolve dynamically and adaptively, better reflecting the constantly changing physical influence mechanism of the stamping die during the production process. In this way, the adjustment rule used to adjust the quantified influence relationship can always maintain high accuracy and timeliness, thereby making the adjustment influence factor calculated based on the adjustment rule more accurate, and thus improving the accuracy of the quantified influence relationship adjustment. The improved accuracy of quantifying the impact relationship directly affects the accuracy of subsequent calculations of expected impact quantities based on the quantified impact relationship and the identification of dominant key connecting components or dominant performance degradation factors, ultimately improving the reliability of the entire stamping die life analysis method.

[0062] In practical implementation, we can assume the current adjustment rule is a linear model, where the adjustment impact factor equals k multiplied by the change in production state parameters plus b, where k and b are rule parameters. The calculated deviation parameter, for example, can be a mean squared error value. If this mean squared error value exceeds a preset threshold, it indicates that the current rule parameters k and b are no longer applicable. In this case, based on the magnitude and direction of the deviation parameter, gradient descent or other optimization algorithms can be used to fine-tune the rule parameters k and b to reduce the deviation. For example, if the deviation parameter indicates that the current rule underestimates the actual impact, k or b can be appropriately increased. As another example, suppose the current adjustment rule is a piecewise function or lookup table, its rule structure consisting of multiple segment points or lookup table entries. If the pattern characteristics of the deviation parameter indicate that the current rule has a particularly large deviation within a specific range of changes in production state parameters, this may mean that the current rule structure is not applicable in that region. In this case, the rule structure can be adjusted based on the pattern information of the deviation parameter. For example, a segment point can be added in the region with the large deviation, or the value of the corresponding entry in the lookup table can be modified, thereby allowing the adjustment rule to better fit the actual physical impact mechanism. In this way, rule parameters or rule structure can be flexibly adjusted according to the specific performance of the deviation parameter, so as to achieve adaptive updating of the adjustment rules.

[0063] In this embodiment of the invention, updating the current adjustment rules based on the deviation degree parameter allows the adjustment rules to dynamically adapt to the constantly changing physical properties of the stamping die during production. By identifying the rule parameters or rule structures that characterize the physical influence mechanism in the adjustment rules and making targeted adjustments based on the deviation degree parameter, the accuracy and timeliness of the adjustment rules can be effectively improved. This ensures that the adjustment influence factors calculated based on the adjustment rules are more accurate, thereby making the adjustment of the quantitative influence relationship more accurate and ultimately improving the reliability of stamping die life analysis.

[0064] The steps for identifying elements characterizing physical influence mechanisms in the current adjustment rules in this embodiment of the invention include: obtaining magnitude and pattern information of the deviation degree parameter; determining the magnitude or pattern characteristics of the deviation degree parameter based on the obtained magnitude and pattern information; adjusting the rule parameters in the elements based on the deviation degree parameter when the magnitude characteristics of the deviation degree parameter meet a first type of magnitude condition or the pattern characteristics of the deviation degree meet a first type of pattern condition; and adjusting the rule structure in the elements based on the deviation degree parameter when the magnitude characteristics of the deviation degree parameter meet a second type of magnitude condition or the pattern characteristics of the deviation degree parameter meet a second type of pattern condition.

[0065] It should be noted that the magnitude information of the deviation degree parameter here refers to the numerical size or range of the deviation degree parameter, which can be expressed in the form of absolute value, relative value, percentage, etc., and its purpose is to quantify the degree of deviation; the pattern information of the deviation degree parameter refers to the trend or form of the deviation degree parameter changing with variables such as time or production frequency, which can be expressed in the form of rate of change, fluctuation frequency, mutation point, etc., and its purpose is to describe the dynamic characteristics of the deviation; the magnitude characteristic refers to the performance of the deviation degree parameter in terms of numerical size, which can be judged by comparing the magnitude information with the preset threshold, and its purpose is to distinguish different degrees of deviation; the pattern characteristic refers to the performance of the deviation degree parameter in terms of the trend of change, which can be judged by matching the pattern information with the preset pattern, and its purpose is to distinguish different types of deviation; the first type of magnitude condition refers to the magnitude of the deviation degree parameter meeting a certain preset condition, such as a small magnitude, and its purpose is to identify situations where fine parameter adjustment is required; the first type Pattern conditions refer to the deviation pattern meeting certain preset conditions, such as gradual change, with the aim of identifying situations requiring fine-tuning of parameters; second-class magnitude conditions refer to the deviation parameter meeting another preset condition, such as a large magnitude, with the aim of identifying situations requiring structural adjustment; second-class pattern conditions refer to the deviation parameter meeting another preset condition, such as drastic change, with the aim of identifying situations requiring structural adjustment; rule parameters refer to variables or coefficients in the adjustment rules that can be numerically adjusted, which can take the form of coefficients of linear models, parameters of nonlinear functions, etc., with the aim of fine-tuning the rule output through numerical changes; rule structure refers to the mathematical form, algorithm model, or logical judgment process of the adjustment rules, which can take the form of switching different mathematical formulas, changing the number or type of model, adjusting judgment branches, etc., with the aim of adapting to fundamental changes in the physical properties of the mold by changing the internal logic of the rules.

[0066] In this embodiment of the invention, by acquiring the magnitude and pattern information of the deviation degree parameter, and judging the magnitude or pattern characteristics of the deviation degree parameter based on this information, a more comprehensive understanding of the specific situation of the evolution of the mold's physical properties reflected by the deviation degree parameter can be achieved. It is precisely because the magnitude and pattern of the deviation degree parameter are distinguished and judged that subsequent adjustment processing can be more targeted. When the magnitude of the deviation degree parameter is small or the change is gradual, it indicates that the evolution of the mold's physical properties is gradual and predictable. At this time, by adjusting the rule parameters, such as fine-tuning the linear coefficient or threshold, the adjustment rules can be effectively corrected to better fit the current actual situation. However, when the magnitude of the deviation degree parameter is large or the change is drastic, it indicates that the mold's physical properties may have undergone more fundamental changes, such as significant loosening or damage to the connection structure. In this case, simply adjusting the rule parameters may not be sufficient to accurately reflect this change; the rule structure needs to be adjusted, such as switching to a different mathematical model or introducing new influencing factors, to more accurately describe the evolution of the mold's state. This strategy of selecting adjustment rule parameters or rule structures based on the magnitude and pattern of deviation parameters, combined with the previous steps of acquiring evaluation response data, calculating expected response data, determining deviation parameters, and judging whether update conditions are met, forms a closed loop capable of adaptively and finely updating adjustment rules. In this way, the adjustment rules can more accurately reflect the actual evolution of the mold's physical properties, thereby improving the accuracy of determining dominant failure factors and analyzing mold life based on quantitative influence relationships.

[0067] The magnitude information of the deviation parameter can be obtained by calculating the mean absolute error or root mean square error of the numerical sequence. Pattern information of the deviation parameter can be obtained by performing time series analysis on the numerical sequence, such as calculating its first difference, performing trend analysis, or detecting abrupt changes. Based on the obtained magnitude and pattern information, the magnitude or pattern characteristics of the deviation parameter are determined. For example, when the mean absolute error is less than a preset threshold L1, the magnitude characteristic is determined to meet the first type of magnitude condition; when the mean absolute error is greater than or equal to the preset threshold L1, the magnitude characteristic is determined to meet the second type of magnitude condition. When the mean of the first difference of the numerical sequence is less than a preset threshold M1 and no abrupt changes are detected, the pattern characteristic is determined to meet the first type of pattern condition; when the mean of the first difference of the numerical sequence is greater than or equal to the preset threshold M1 or abrupt changes are detected, the pattern characteristic is determined to meet the second type of pattern condition. The current adjustment rule can be a linear regression model, where the rule parameters are the model coefficients. The rule structure can be the linear regression model itself or a nonlinear model (e.g., a multinomial regression model). When the magnitude of the deviation parameter meets the first type of magnitude condition or the pattern characteristic meets the first type of pattern condition, the coefficients of the linear regression model are fine-tuned based on the deviation parameter (e.g., based on the magnitude of the mean absolute error). When the magnitude of the deviation parameter meets the second type of magnitude condition or the pattern characteristic meets the second type of pattern condition, the adjustment rule is switched from the linear regression model to the multinomial regression model, or the order of the multinomial is increased, based on the deviation parameter (e.g., based on whether there is a mutation point).

[0068] Based on the above technical solution, the rule parameters or rule structure in the adjustment rules can be adjusted in a targeted manner according to the magnitude and pattern characteristics of the deviation parameters. This refined adjustment strategy enables the adjustment rules to more accurately reflect the actual evolution of the mold's physical properties, thereby improving the accuracy of mold life analysis.

[0069] It should be noted that, in this embodiment of the invention, a deformation monitoring device is installed in the sensitive area. This device is used to collect initial deformation response data and current deformation response data. The deformation monitoring device is a device used to measure and record changes in the shape or size of an object under stress or environmental changes. It can be implemented using strain gauges, displacement sensors, optical measurement systems, or image processing-based visual monitoring systems. Its purpose is to achieve automatic and accurate collection of deformation response data in the sensitive area. Initial deformation response data refers to the deformation data of the sensitive area collected when the stamping die is initially put into use or in good condition, serving as a benchmark for subsequent deformation changes. Current deformation response data refers to the deformation data of the sensitive area collected during the subsequent production process of the stamping die, based on a set collection cycle, reflecting the deformation status of the die in its current state.

[0070] This application's solution automates and refines the acquisition of initial and current deformation response data for a stamping die by installing a deformation monitoring device in the sensitive area. The ability of the deformation monitoring device to continuously or periodically acquire deformation data from the sensitive area with high precision makes it possible to subsequently calculate deformation deviation parameters based on this data. This automatically acquired data stream provides a stable and reliable input for stamping die life analysis methods, overcoming the limitations of traditional manual measurement in terms of efficiency and accuracy. By combining the precise deformation data acquired by the deformation monitoring device with the changes in the state parameters of key connecting components, this application's method can more accurately diagnose whether there are abnormal stresses on the working surface, thereby effectively identifying potential failure modes caused by the degradation of assembly structure performance. This analytical approach, combining structural health monitoring and connection status assessment, can more comprehensively reflect the actual working state and life evolution of the die, providing data support for die maintenance and management.

[0071] High-precision resistance strain gauges can be attached to sensitive areas of the stamping die, such as the die body surface near critical bolt connections, as deformation monitoring devices. These strain gauges can be arranged in multiple directions to capture the strain state of the area. The strain gauges are connected to a data acquisition system via wires, which can automatically trigger data acquisition at the end of each stamping cycle or at preset time intervals. Before the die is put into production, the acquisition system records a set of strain data as initial deformation response data. During subsequent production, the system periodically acquires the current strain data as current deformation response data. This acquired data is then transmitted to a processing unit to calculate the deviation of the current strain from the initial strain. As another specific implementation, non-contact displacement sensors, such as laser displacement sensors, can be installed in sensitive areas prone to clearance changes, such as the corresponding surfaces of the punch and die, when the die is closed, to measure clearance changes in this area. The electrical signals output by the sensors are received and recorded by the data acquisition system as deformation response data.

[0072] Figure 3 A schematic diagram of a stamping die life analysis system according to an embodiment of the present invention is shown. This system can be used to perform a stamping die life analysis method. The system includes: The initial data acquisition module is used to acquire the initial deformation response data of the sensitive area of ​​the assembly structure performance degradation on the stamping die, and to acquire the initial connection status parameters of the key connecting parts on the stamping die. The periodic data acquisition module is used to acquire the current deformation response data of sensitive areas and the current connection status parameters of key connecting components based on the set acquisition cycle during the subsequent production process of stamping dies. The deformation deviation calculation module is used to calculate the deviation parameter of the current deformation response data from the initial deformation response data based on the current deformation response data and the initial deformation response data; and to calculate the change trend parameter of the key connection components based on the current connection state parameter and the initial connection state parameter. The diagnostic module is used to diagnose whether there is any abnormal stress on the working surface of the stamping die based on the deviation degree parameter and the change trend parameter.

[0073] The initial data acquisition module refers to the unit used to collect key data reflecting the original state of the stamping die before it is put into use or in the initial stage. It can be implemented by hardware circuits or software programs connected to sensors, data storage devices or manual input interfaces.

[0074] Among them, the periodic data acquisition module refers to the unit used to automatically or semi-automatically acquire the current status data of the mold during the mold production process according to the preset time interval or stamping number interval. It can be implemented by a timed triggering data acquisition program, an interface circuit for communication with an automated sensor network, or a data acquisition card.

[0075] The deformation deviation calculation module refers to the unit used to receive initial and current state data and perform mathematical operations to quantify the degree of difference between the current state and the initial state. It can be implemented by a processor with built-in computing functions, a software module that runs specific algorithms, or a dedicated computing chip.

[0076] The diagnostic judgment module refers to the unit used to receive deviation degree parameters and change trend parameters, and output the judgment result on the stress state of the working surface of the mold according to preset rules, models or thresholds. It can be implemented by rule-based inference engine, machine learning model or simple logic judgment circuit.

[0077] This application's solution integrates stamping die life analysis methods into a single system, automating and collaboratively executing the method steps. The initial data acquisition module establishes a baseline when the die is put into use, while the periodic data acquisition module continuously acquires real-time status information of the die, providing a data stream for subsequent analysis. The deformation deviation calculation module compares and analyzes the acquired real-time data with the initial baseline data, quantifying the degree of change in the die's state and converting physical changes into calculable parameters. The diagnostic judgment module utilizes these quantified parameters to perform logical judgments or model reasoning, thereby identifying whether there are abnormal stresses on the die's working surface. The entire system, as a whole, transforms discrete method steps into a continuous and efficient monitoring and diagnostic process through data transfer and functional collaboration between modules. This systematic approach automates methods that previously required manual intervention or step-by-step execution, improving the frequency and accuracy of data acquisition, reducing human error, and providing diagnostic results in real-time or near real-time. The system executes the method, and the method guides the system design; the two support each other, jointly solving the problem of inefficient and accurate analysis relying solely on the method, achieving effective monitoring and life prediction of the die's state.

[0078] In some preferred embodiments, the stamping die life analysis system may consist of an industrial control unit, multiple strain sensors connected to sensitive areas of the die, and wireless torque sensors connected to key connecting components. The industrial control unit runs software that integrates the functions of an initial data acquisition module, a periodic data acquisition module, a deformation deviation calculation module, and a diagnostic judgment module. After the die is initially installed and debugged, the initial data acquisition module reads data from the strain and torque sensors and stores it in a local database as an initial baseline. During subsequent production, the periodic data acquisition module is configured to automatically trigger a data acquisition task every 1,000 stamping cycles or every eight hours, acquiring current strain and torque data from the sensor network. The deformation deviation calculation module receives this data, calculates the root mean square error of the current strain data relative to the initial strain data as a deviation parameter, and calculates the linear regression slope of the torque of key bolts with the number of stamping cycles as a trend parameter. The diagnostic judgment module, based on preset threshold rules, for example, if the deviation parameter exceeds a certain threshold and the trend parameter shows a continuous decrease in torque, determines that there is an abnormal stress on the working surface and triggers an alarm signal.

[0079] Through the above technical solution, the stamping die life analysis system can automatically and periodically collect status data of key areas of the die, and perform quantitative analysis and diagnosis, overcoming the inefficiencies and inaccuracies caused by manual or decentralized methods. It achieves real-time monitoring and anomaly diagnosis of the stamping die status, improving the efficiency and reliability of die life analysis, helping to promptly identify potential problems, and avoiding part defects and premature die failure caused by a decline in die structural health.

[0080] Furthermore, the above provides a detailed description of the stamping die life analysis method and system provided by the embodiments of the present invention. Specific examples have been used to illustrate the principles and implementation methods of the present invention. The description of the above embodiments is only for the purpose of helping to understand the method and core ideas of the present invention. At the same time, for those skilled in the art, there will be changes in the specific implementation methods and application scope based on the ideas of the present invention. Therefore, the content of this specification should not be construed as a limitation of the present invention.

Claims

1. A method for analyzing the life of stamping dies, characterized in that, include: Acquire the initial deformation response data of the sensitive area of ​​assembly structure performance degradation on the stamping die, and acquire the initial connection state parameters of the key connecting components on the stamping die; During the subsequent production process of the stamping die, the current deformation response data of the sensitive area is acquired based on the set acquisition cycle, and the current connection status parameters of the key connecting components are acquired based on the set acquisition cycle. Calculate the deviation parameter of the current deformation response data relative to the initial deformation response data based on the current deformation response data and the initial deformation response data; Calculate the change trend parameters of the key connection components based on the current connection status parameters and the initial connection status parameters; Based on the deviation parameter and the trend parameter, it is determined whether there is any abnormal stress on the working surface of the stamping die.

2. The method for analyzing the life of a stamping die according to claim 1, characterized in that, The method of diagnosing whether there is an abnormal stress on the working surface of the stamping die based on the deviation parameter and the trend parameter includes: Determine whether the deviation parameter exceeds a preset deviation threshold; If it is determined that the deviation degree parameter exceeds the preset deviation degree threshold, then it is determined whether the change trend of the change trend parameter is consistent with the performance degradation degree of the key connection component; If the trend of the change trend parameter is consistent with the degree of performance degradation of the key connecting component, then an abnormal stress is diagnosed on the working surface of the stamping die.

3. The method for analyzing the life of a stamping die according to claim 2, characterized in that, The steps for diagnosing abnormal stress on the working surface of the stamping die include: Obtain the quantitative impact relationship of the deformation response of each key connecting component in the sensitive area; Obtain the current actual performance degradation of each critical connection component; Based on the current actual performance degradation of the key connecting component and the quantified impact relationship corresponding to the key connecting component, calculate the expected impact of the deviation of the key connecting component on the deformation response data of the sensitive area; Based on the expected impact, identify the dominant key connecting components or dominant performance degradation factors that cause abnormal stress on the working surface.

4. The method for analyzing the life of a stamping die according to claim 3, characterized in that, The step of obtaining the quantitative impact relationship of the deformation response of each key connecting component in the sensitive area includes: In the initial stage of the stamping die, the initial quantitative influence relationship of each of the multiple key connecting components on the deformation response of the sensitive area is obtained; During the subsequent production process of the stamping die, at least one production status parameter related to the evolution of the physical properties of the stamping die is monitored; Determine whether the at least one production status parameter meets the preset production threshold; When at least one production state parameter meets the preset production threshold, the initial quantitative influence relationship or the previously updated quantitative influence relationship is adjusted based on the current production state of the stamping die to obtain a quantitative influence relationship that is adapted to the current production state. The quantitative influence relationship is used for subsequent determination of the dominant failure factor based on the adapted quantitative influence relationship.

5. The method for analyzing the life of a stamping die according to claim 4, characterized in that, The step of adjusting the initial quantitative influence relationship or the previously updated quantitative influence relationship based on the current production status of the stamping die includes: Identify production state parameters that have changed under the current production state of the stamping die; Based on the current actual change of the production status parameters and the adjustment rules of the physical influence mechanism corresponding to the pre-set production status parameters, the adjustment influence factor of the production status parameters on the initial quantitative influence relationship or the previously updated quantitative influence relationship is calculated. By aggregating all the aforementioned adjustment factors and combining them with a strategy among predetermined physical influence mechanisms, the total adjustment value for the initial quantitative influence relationship or the previously updated quantitative influence relationship is calculated. The initial quantized influence relationship or the previously updated quantized influence relationship is adjusted based on the total adjustment value.

6. The method for analyzing the life of a stamping die according to claim 5, characterized in that, The steps of adjusting the production state parameters based on their current actual changes and the pre-set physical influence mechanisms corresponding to those parameters include: Obtain the current adjustment rule, which is either the initial adjustment rule or the updated adjustment rule; During the production process of the stamping die, evaluation response data is acquired to assess the current adjustment rule; Based on the current adjustment rule and the current stamping die production status parameters, calculate the expected response data corresponding to the current adjustment rule; Based on the evaluation response data and the expected response data, a parameter is determined to indicate the degree of deviation between the current adjustment rule and the current physical properties of the stamping die. Determine whether the deviation degree parameter meets the update condition. If the deviation degree parameter meets the update condition, update the current adjustment rule based on the deviation degree parameter.

7. The method for analyzing the life of a stamping die according to claim 6, characterized in that, The step of updating the current adjustment rule based on the deviation parameter includes: Identify the elements in the current adjustment rule that characterize the physical influence mechanism, wherein the elements are rule parameters or rule structure of the adjustment rule; The updated adjustment rules are obtained by adjusting the elements characterizing the physical influence mechanism based on the deviation parameter.

8. The method for analyzing the life of a stamping die according to claim 7, characterized in that, The step of identifying the elements characterizing the physical influence mechanism in the current adjustment rule includes: Obtain the magnitude and pattern information of the deviation parameter, and determine the magnitude or pattern characteristics of the deviation parameter based on the magnitude and pattern information. When the magnitude characteristic of the deviation degree parameter meets the first type of magnitude condition or the pattern characteristic of the deviation degree meets the first type of pattern condition, the rule parameters in the element are adjusted according to the deviation degree parameter. When the magnitude characteristic of the deviation degree parameter meets the second type of magnitude condition or the pattern characteristic of the deviation degree parameter meets the second type of pattern condition, the rule structure in the element is adjusted according to the deviation degree parameter.

9. The method for analyzing the life of a stamping die according to claim 1, characterized in that, A deformation monitoring device is installed in the sensitive area, which is used to collect initial deformation response data and current deformation response data.

10. A stamping die life analysis system, used to execute the stamping die life analysis method according to any one of claims 1-9, characterized in that, The system includes: The initial data acquisition module is used to acquire the initial deformation response data of the sensitive area of ​​the assembly structure performance degradation on the stamping die, and to acquire the initial connection status parameters of the key connecting components on the stamping die. The periodic data acquisition module is used to acquire the current deformation response data of the sensitive area based on the set acquisition period during the subsequent production process of the stamping die, and to acquire the current connection status parameters of the key connecting components based on the set acquisition period. The deformation deviation calculation module is used to calculate the deviation parameter of the current deformation response data relative to the initial deformation response data based on the current deformation response data and the initial deformation response data; and to calculate the change trend parameter of the key connection component based on the current connection state parameter and the initial connection state parameter. The diagnostic judgment module is used to diagnose whether there is any abnormal stress on the working surface of the stamping die based on the deviation degree parameter and the change trend parameter.

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