Design method of tire mold

Abstract

The invention discloses a tire mold design method which comprises the following steps: acquiring a historical design log of a tire mold, determining a correlation degree between historical design parameters and preset performance indexes according to the historical design log, and obtaining feature design parameters of each preset performance index according to the correlation degree; calculating an application evaluation value of the feature design parameter of each preset performance index, and determining an optimal design parameter corresponding to the preset performance index according to the application evaluation value; generating a first design strategy by using the optimal design parameters of the plurality of preset performance indexes, carrying out analogue simulation on the first design strategy, and judging whether an adjustment instruction is generated or not according to an analogue simulation result; if the adjusting instruction is generated, the first design strategy is adjusted according to the adjusting instruction, the second design strategy is generated, if the adjusting instruction is not generated, the tire mold is machined according to the first design strategy, the quality and design efficiency of the tire mold are improved, and the production efficiency of the tire is further improved.

Description

Technical Field

[0001] The present application relates to the technical field of tire molds, and in particular to a design method for a tire mold. Background Art

[0002] Tires are ground-contacting and rolling annular elastic rubber products installed on various vehicles or machinery. They are usually installed on metal rims and can support the vehicle body, buffer external impacts, achieve contact with the road surface and ensure the vehicle's driving performance. With the development of the automobile industry, the design of tire molds has received more and more attention, and its design method directly determines the final quality and production efficiency of the tire.

[0003] In the prior art, tire molds are usually designed and adjusted based on the designer's personal experience or according to a common processing sequence. However, tire molds need to have multiple performances. Multiple performances are not fully considered, and the optimal design parameters corresponding to each performance cannot be determined, resulting in inaccurate and inefficient design results, which reduces the quality of the tire mold. Summary of the invention

[0004] In order to solve the above technical problems, the present application provides a tire mold design method, which determines the characteristic design parameters of each preset performance indicator and the corresponding application evaluation value, screens out the optimal design parameters, generates a first design strategy, simulates the first design strategy, and generates corresponding adjustment instructions based on whether the optimal design parameters in the simulation conflict or the simulation performance evaluation value of the first design strategy, thereby improving the quality and design efficiency of the tire mold and further improving the production efficiency of the tire.

[0005] In some embodiments of the present application, a tire mold design method is provided, comprising:

[0006] Obtain a historical design log of the tire mold, determine the degree of correlation between the historical design parameters and the preset performance indicators according to the historical design log, and obtain a characteristic design parameter of each preset performance indicator according to the degree of correlation;

[0007] Calculate the application evaluation value of the characteristic design parameter of each preset performance indicator, and determine the optimal design parameter corresponding to the preset performance indicator according to the application evaluation value;

[0008] generating a first design strategy from optimal design parameters of a plurality of preset performance indicators, simulating the first design strategy, and determining whether to generate an adjustment instruction according to the simulation result;

[0009] If an adjustment instruction is generated, the first design strategy is adjusted according to the adjustment instruction to generate a second design strategy; if no adjustment instruction is generated, the tire mold is processed according to the first design strategy.

[0010] In some embodiments of the present application, determining whether to generate an adjustment instruction according to a simulation result includes:

[0011] The simulation results include whether there is a conflict between the optimal design parameters;

[0012] If there are conflicts between the optimal design parameters, the conflicts are analyzed, and a first adjustment instruction is generated according to the analysis result;

[0013] If there is no conflict between the optimal design parameters, the simulation performance evaluation value of the first design strategy is calculated, and when the simulation performance evaluation value is less than the preset evaluation value threshold, a second adjustment instruction is generated, and when the simulation performance evaluation value is greater than the preset evaluation value threshold, no adjustment instruction is generated;

[0014] The adjustment instruction includes a first adjustment instruction and a second adjustment instruction.

[0015] In some embodiments of the present application, the characteristic design parameters of each preset performance indicator are obtained according to the correlation degree, including:

[0016] Determining a performance evaluation value of each preset performance indicator in the corresponding historical design log according to a preset performance indicator evaluation method, wherein the evaluation method includes a first evaluation method and a second evaluation method;

[0017] When the evaluation method is the first evaluation method, a plurality of real-time performance evaluation values ​​corresponding to the preset performance indicators in the historical design log are generated;

[0018] When the evaluation method is the second evaluation method, a final performance evaluation value corresponding to a preset performance indicator in the historical design log is generated;

[0019] Generate a standard processing time according to the historical processing time in multiple historical design logs of the tire mold, build a time reference line according to the standard processing time, and set a collection node of the time reference line according to a preset time interval;

[0020] When the evaluation method of the preset performance indicator is the first evaluation method, the historical design parameters and the real-time performance evaluation values ​​are collected according to the multiple collection nodes on the time reference, and the first similarity between the historical design parameters and the current preset performance indicator is generated according to the number of synchronous change time nodes of the historical design parameters and the real-time performance evaluation values ​​and the degree of synchronous change;

[0021] When the first similarity is greater than a preset first similarity threshold, the historical design parameter is set as a characteristic design parameter corresponding to the preset performance indicator;

[0022] When the evaluation method of the preset performance indicator is the second evaluation method, the final performance evaluation value difference of the corresponding preset performance indicator of different historical design logs is calculated, and the historical design log group whose final performance evaluation value difference is greater than the preset difference threshold is screened out;

[0023] According to the collection nodes of the time reference line, the historical design parameters of multiple historical design log groups are collected, grouped and processed and analyzed to obtain the parameter difference of the same historical design parameter in the same historical design log group at each collection node, and the second similarity between the historical design parameter and the current preset performance indicator is generated according to the difference between the sum of the parameter difference in the multiple historical design log groups and the final performance evaluation value of the corresponding preset performance indicators of the multiple historical design log groups;

[0024] When the second similarity is greater than a preset second similarity threshold, the historical design parameter is set as a characteristic design parameter corresponding to the preset performance indicator.

[0025] In some embodiments of the present application, the calculation formula for the first similarity degree is:

[0026]

[0027] Among them, X1 is the first similarity degree, f is the similarity degree conversion coefficient, m is the number of synchronous change time nodes of historical design parameters and real-time performance evaluation values, n is the total number of acquisition nodes, △Pi-△Gi is the synchronous change degree at the i-th synchronous change time node, △Pi is the change amount of the historical design parameters at the i-th synchronous change time node, and △Gi is the change amount of the real-time performance evaluation value at the i-th synchronous change time node;

[0028] The calculation formula of the second similarity degree is:

[0029]

[0030] Among them, X2 is the second similarity degree, c is the number of historical design log groups whose final performance evaluation value difference is greater than the preset difference threshold, △Ks is the final performance evaluation value difference of the sth historical design log group, and △Ys is the sum of the parameter differences of the sth historical design log group.

[0031] In some embodiments of the present application, calculating the application evaluation value of the characteristic design parameter of each preset performance indicator, and determining the optimal design parameter corresponding to the preset performance indicator according to the application evaluation value includes:

[0032] When the evaluation method of the preset performance indicator is the first evaluation method, an application evaluation value of the corresponding characteristic design parameter is generated according to the evaluation value difference between the real-time performance evaluation value of the characteristic design parameter of the preset performance indicator in the corresponding historical design log and the preset standard performance evaluation value and the change trend of the real-time performance evaluation value;

[0033] When the evaluation method of the preset performance indicator is the second evaluation method, an application evaluation value of the corresponding feature design parameter is generated according to the evaluation value difference between the final performance evaluation value of the feature design parameter of the preset performance indicator in the corresponding historical design log and the preset performance evaluation value threshold, and the fluctuation degree of the feature design parameter;

[0034] Multiple application evaluation values ​​of the feature design parameters of each preset performance indicator are compared, and the feature design parameter corresponding to the application evaluation value ranked first is set as the optimal design parameter corresponding to the preset performance indicator.

[0035] In some embodiments of the present application, the first design strategy is simulated, including:

[0036] Obtain the structural information of the tire mold before processing, collect the surrounding environment information of the tire mold, and construct the static simulation scene information of the tire mold based on the surrounding environment information and structural information;

[0037] The dynamic simulation scenario information is obtained according to the optimal design parameters of each preset performance indicator;

[0038] Obtaining the processing relationship between each optimal design parameter and the tire mold in the dynamic simulation scene information, and establishing a dynamic relationship under the same dynamic node;

[0039] The dynamic relationship is linked to the static simulation scene information, a simulation of the first design strategy is performed, and a simulation result is obtained.

[0040] In some embodiments of the present application, if there is a conflict between the optimal design parameters, the conflict is analyzed, and a first adjustment instruction is generated according to the analysis result, including:

[0041] Analyze the optimal design parameters of the same dynamic node to obtain the position information of the optimal design parameters on the tire mold. When the position information is repeated and the repeated area is greater than the preset area threshold, it is determined that there is a conflict between the optimal design parameters.

[0042] According to the weight coefficient of the preset performance index corresponding to the optimal design parameter of the same dynamic node and the correlation degree between the optimal design parameter and other optimal design parameters, the processing priority of the optimal design parameter at the same dynamic node is set;

[0043] The optimal design parameters at the same dynamic node are sorted according to the processing priority, the optimal design parameters with a sorting value lower than the preset sorting value are offset, and the allowable normal offset area is determined;

[0044] The optimal design parameters with ranking values ​​lower than the preset ranking values ​​are adjusted to the area allowing normal deviation, and the impact degree after adjustment is calculated. If the impact degree is less than the preset impact degree, a corresponding first adjustment instruction is generated. If the impact degree is greater than the preset impact degree, it is determined whether there is a supplementary position in the idle area. If so, the area allowing normal deviation is expanded based on the supplementary position, the corresponding optimal design parameters are reasonably processed, and a corresponding first scheduling instruction is generated.

[0045] In some embodiments of the present application, if there is no conflict between the optimal design parameters, calculating the simulation performance evaluation value of the first design strategy includes:

[0046] Presetting a performance evaluation value threshold for each preset performance indicator;

[0047] Generate a predicted performance evaluation value for each preset performance indicator of the first design strategy according to the simulation results and the test simulation results;

[0048] The predicted performance evaluation value of each preset performance indicator is compared with the corresponding preset performance evaluation value threshold, a predicted performance evaluation value difference is generated according to the comparison result, and a simulation performance evaluation value of the first design strategy is generated according to multiple predicted performance evaluation value differences and corresponding weight coefficients.

[0049] In some embodiments of the present application, when the simulation performance evaluation value is less than a preset evaluation value threshold, generating a second adjustment instruction includes:

[0050] When the simulation performance evaluation value is less than the preset evaluation value threshold, the predicted performance evaluation value difference less than the predicted performance evaluation value difference threshold and the corresponding preset performance index are screened out;

[0051] If the predicted performance evaluation value difference is within the predicted second performance evaluation value difference threshold and the predicted performance evaluation value difference threshold, fine-tune the selected optimal design parameters of the preset performance indicators, and generate a second adjustment instruction according to the fine-tuning result;

[0052] If the predicted performance evaluation value difference is less than the predicted second performance evaluation value difference threshold, the optimal design parameters of the screened preset performance indicators are re-determined, and a second adjustment instruction is generated according to the re-determined optimal design parameters.

[0053] In some embodiments of the present application, the method further comprises:

[0054] Compare the actual processing parameters in the processing process with the optimal design parameters in the simulation process, and generate a similarity degree based on the comparison results;

[0055] If the similarity is less than a preset similarity threshold, the difference between the similarity and the preset similarity threshold is calculated, and a correction coefficient of the optimal design parameter of the next processing flow is generated according to the difference;

[0056] The corresponding optimal design parameters are corrected according to the correction coefficients to obtain the corrected design parameters, and the tire template of the next processing flow is processed according to the corrected design parameters.

[0057] Compared with the prior art, the tire mold design method of the embodiment of the present application has the following beneficial effects:

[0058] By determining the characteristic design parameters of each preset performance indicator and the corresponding application evaluation value, the optimal design parameters are screened out, a first design strategy is generated, and the first design strategy is simulated. According to whether the optimal design parameters in the simulation conflict or the simulation performance evaluation value of the first design strategy, corresponding adjustment instructions are generated to improve the quality and design efficiency of the tire mold and further improve the production efficiency of the tire. BRIEF DESCRIPTION OF THE DRAWINGS

[0059] Figure 1 It is a flow chart of a tire mold design method in a preferred embodiment of the present application. DETAILED DESCRIPTION

[0060] The specific implementation methods of the present application are further described in detail below in conjunction with the accompanying drawings and examples. The following examples are used to illustrate the present application but are not intended to limit the scope of the present application.

[0061] In the description of the present application, it should be understood that the terms "center", "up", "down", "front", "back", "left", "right", "vertical", "horizontal", "top", "bottom", "inside", "outside", etc., indicating orientations or positional relationships, are based on the orientations or positional relationships shown in the accompanying drawings, and are only for the convenience of describing the present application and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and therefore should not be understood as a limitation on the present application.

[0062] The terms "first" and "second" are used for descriptive purposes only and should not be understood as indicating or implying relative importance or implicitly indicating the number of the indicated technical features. Thus, a feature defined as "first" or "second" may explicitly or implicitly include one or more of the features. In the description of this application, unless otherwise specified, "plurality" means two or more.

[0063] In the description of this application, it should be noted that, unless otherwise clearly specified and limited, the terms "installed", "connected", and "connected" should be understood in a broad sense, for example, it can be a fixed connection, a detachable connection, or an integral connection; it can be a mechanical connection or an electrical connection; it can be a direct connection, or it can be indirectly connected through an intermediate medium, or it can be the internal communication of two components. For ordinary technicians in this field, the specific meanings of the above terms in this application can be understood according to specific circumstances.

[0064] like Figure 1 As shown, a tire mold according to a preferred embodiment of the present application includes:

[0065] Step S101: obtaining a historical design log of a tire mold, determining the correlation between historical design parameters and preset performance indicators according to the historical design log, and obtaining characteristic design parameters of each preset performance indicator according to the correlation;

[0066] Step S102: Calculate the application evaluation value of the characteristic design parameter of each preset performance indicator, and determine the optimal design parameter corresponding to the preset performance indicator according to the application evaluation value;

[0067] Step S103: generating a first design strategy from optimal design parameters of a plurality of preset performance indicators, simulating the first design strategy, and determining whether to generate an adjustment instruction according to the simulation result;

[0068] Step S104: if an adjustment instruction is generated, the first design strategy is adjusted according to the adjustment instruction to generate a second design strategy; if no adjustment instruction is generated, the tire mold is processed according to the first design strategy.

[0069] In this embodiment, the historical design log includes the design stage, the processing stage, and the testing stage of the tire mold.

[0070] In this embodiment, the preset performance indicators include adaptation performance, quality performance, handling performance, comfort performance, aesthetic performance, life performance, etc. The similarity between the preset performance indicators and the historical design parameters is determined based on the synchronous change relationship between multiple performance evaluation values ​​of the preset performance indicators and the historical design parameters or the relationship between the final performance evaluation values ​​of the preset performance indicators in multiple historical design logs and the parameter difference between the historical design parameters in the corresponding historical design logs. The characteristic design parameters of the preset performance indicators are determined based on the similarity, laying a data foundation for the subsequent determination of the optimal design parameters of each preset performance indicator.

[0071] In some embodiments of the present application, determining whether to generate an adjustment instruction according to a simulation result includes:

[0072] The simulation results include whether there is a conflict between the optimal design parameters;

[0073] If there are conflicts between the optimal design parameters, the conflicts are analyzed, and a first adjustment instruction is generated according to the analysis result;

[0074] If there is no conflict between the optimal design parameters, the simulation performance evaluation value of the first design strategy is calculated, and when the simulation performance evaluation value is less than the preset evaluation value threshold, a second adjustment instruction is generated, and when the simulation performance evaluation value is greater than the preset evaluation value threshold, no adjustment instruction is generated;

[0075] The adjustment instruction includes a first adjustment instruction and a second adjustment instruction.

[0076] In some embodiments of the present application, the characteristic design parameters of each preset performance indicator are obtained according to the correlation degree, including:

[0077] Determining a performance evaluation value of each preset performance indicator in the corresponding historical design log according to a preset performance indicator evaluation method, wherein the evaluation method includes a first evaluation method and a second evaluation method;

[0078] When the evaluation method is the first evaluation method, a plurality of real-time performance evaluation values ​​corresponding to the preset performance indicators in the historical design log are generated;

[0079] When the evaluation method is the second evaluation method, a final performance evaluation value corresponding to a preset performance indicator in the historical design log is generated;

[0080] Generate a standard processing time according to the historical processing time in multiple historical design logs of the tire mold, build a time reference line according to the standard processing time, and set a collection node of the time reference line according to a preset time interval;

[0081] When the evaluation method of the preset performance indicator is the first evaluation method, the historical design parameters and the real-time performance evaluation values ​​are collected according to the multiple collection nodes on the time reference, and the first similarity between the historical design parameters and the current preset performance indicator is generated according to the number of synchronous change time nodes of the historical design parameters and the real-time performance evaluation values ​​and the degree of synchronous change;

[0082] When the first similarity is greater than a preset first similarity threshold, the historical design parameter is set as a characteristic design parameter corresponding to the preset performance indicator;

[0083] When the evaluation method of the preset performance indicator is the second evaluation method, the final performance evaluation value difference of the corresponding preset performance indicator of different historical design logs is calculated, and the historical design log group whose final performance evaluation value difference is greater than the preset difference threshold is screened out;

[0084] According to the collection nodes of the time reference line, the historical design parameters of multiple historical design log groups are collected, grouped and processed and analyzed to obtain the parameter difference of the same historical design parameter in the same historical design log group at each collection node, and the second similarity between the historical design parameter and the current preset performance indicator is generated according to the difference between the sum of the parameter difference in the multiple historical design log groups and the final performance evaluation value of the corresponding preset performance indicators of the multiple historical design log groups;

[0085] When the second similarity is greater than a preset second similarity threshold, the historical design parameter is set as a characteristic design parameter corresponding to the preset performance indicator.

[0086] In this embodiment, the first evaluation method refers to real-time evaluation, that is, when processing is carried out according to the design strategy, the tire mold in processing is subjected to performance tests of corresponding preset performance indicators to obtain multiple real-time performance evaluation values, and the second evaluation method refers to final evaluation, that is, when processing is carried out according to the design strategy, the tire mold after the design is completed is subjected to performance tests to obtain final performance evaluation values, and the corresponding performance evaluation values ​​are determined according to the preset performance evaluation evaluable methods.

[0087] In this embodiment, the number of synchronous change time nodes refers to the nodes in the collection node where the historical design parameters and the real-time performance evaluation values ​​change simultaneously, and the degree of synchronous change refers to the difference between the change amount of the historical design parameters and the change amount of the real-time performance evaluation value at the simultaneous change node. The smaller the difference in the change amount, the greater the degree of synchronous change. The historical design log group includes two historical design logs, and the difference in the final performance evaluation values ​​of the preset performance indicators of the two historical design logs is greater than the preset difference threshold.

[0088] In this embodiment, the calculation method of the similarity between the historical design parameters and the corresponding preset performance indicators is determined according to the evaluation method of the preset performance indicators, so as to screen out the characteristic design parameters of each preset performance indicator, lay a data foundation for the subsequent determination of the optimal performance parameters of each preset performance indicator, and improve the performance and design efficiency of the tire mold.

[0089] In some embodiments of the present application, the calculation formula for the first similarity degree is:

[0090]

[0091] Among them, X1 is the first similarity degree, f is the similarity degree conversion coefficient, m is the number of synchronous change time nodes of historical design parameters and real-time performance evaluation values, n is the total number of acquisition nodes, △Pi-△Gi is the synchronous change degree at the i-th synchronous change time node, △Pi is the change amount of the historical design parameters at the i-th synchronous change time node, and △Gi is the change amount of the real-time performance evaluation value at the i-th synchronous change time node;

[0092] The calculation formula of the second similarity degree is:

[0093]

[0094] Among them, X2 is the second similarity degree, c is the number of historical design log groups whose final performance evaluation value difference is greater than the preset difference threshold, △Ks is the final performance evaluation value difference of the sth historical design log group, and △Ys is the sum of the parameter differences of the sth historical design log group.

[0095] In some embodiments of the present application, calculating the application evaluation value of the characteristic design parameter of each preset performance indicator, and determining the optimal design parameter corresponding to the preset performance indicator according to the application evaluation value includes:

[0096] When the evaluation method of the preset performance indicator is the first evaluation method, an application evaluation value of the corresponding characteristic design parameter is generated according to the evaluation value difference between the real-time performance evaluation value of the characteristic design parameter of the preset performance indicator in the corresponding historical design log and the preset standard performance evaluation value and the change trend of the real-time performance evaluation value;

[0097] When the evaluation method of the preset performance indicator is the second evaluation method, an application evaluation value of the corresponding feature design parameter is generated according to the evaluation value difference between the final performance evaluation value of the feature design parameter of the preset performance indicator in the corresponding historical design log and the preset performance evaluation value threshold, and the fluctuation degree of the feature design parameter;

[0098] Multiple application evaluation values ​​of the feature design parameters of each preset performance indicator are compared, and the feature design parameter corresponding to the application evaluation value ranked first is set as the optimal design parameter corresponding to the preset performance indicator.

[0099] In this embodiment, the application evaluation value refers to the application effect of the characteristic design parameters in each group of historical design logs of the preset performance index, and does not specifically refer to a fixed design parameter, but a group of variable design parameters.

[0100] In this embodiment, the preset standard performance evaluation value refers to a performance evaluation value that meets the minimum requirements of the tire mold, and the preset performance evaluation value threshold refers to the maximum performance evaluation value of the corresponding preset performance index. When the evaluation method of the preset performance index is the first evaluation method, it is judged whether the minimum requirements are met and the rigidity, precision, etc. of the tire mold are not damaged according to the comparison result of the real-time performance evaluation value of the test result in the historical design log and the preset standard performance evaluation value, and whether the change trend of the real-time performance evaluation value is an upward trend. When the evaluation value difference between the real-time performance evaluation value and the preset standard performance evaluation value is getting bigger and bigger and is in a continuous upward trend, the larger the application evaluation value of the feature design parameter is, the better the application effect of the feature design parameter corresponding to the preset performance index is. When the evaluation method of the preset performance index is the first evaluation method, it is judged whether the maximum performance evaluation value is reached according to the evaluation value difference between the final performance evaluation value and the preset performance evaluation value threshold, and the fluctuation degree is generated according to the variance of the feature design parameter. When the evaluation value difference between the final performance evaluation value and the preset performance evaluation value threshold is smaller and the fluctuation degree is smaller, the application evaluation value of the feature design parameter is larger.

[0101] In this embodiment, the optimal design parameters of each preset performance indicator are determined according to the application evaluation value of the calculated characteristic design parameters, and the design strategy of the tire mold is generated according to the optimal design parameters to improve the performance and design efficiency of the tire mold.

[0102] In some embodiments of the present application, the first design strategy is simulated, including:

[0103] Obtain the structural information of the tire mold before processing, collect the surrounding environment information of the tire mold, and construct the static simulation scene information of the tire mold based on the surrounding environment information and structural information;

[0104] The dynamic simulation scenario information is obtained according to the optimal design parameters of each preset performance indicator;

[0105] Obtaining the processing relationship between each optimal design parameter and the tire mold in the dynamic simulation scene information, and establishing a dynamic relationship under the same dynamic node;

[0106] The dynamic relationship is linked to the static simulation scene information, a simulation of the first design strategy is performed, and a simulation result is obtained.

[0107] In this embodiment, the static simulation scene information refers to the scenes, environments, etc. involved in the tire mold before it is designed and processed, and the dynamic simulation scene information refers to the dynamic relationship between the optimal design parameters of each preset performance indicator and the tire mold during processing.

[0108] In this embodiment, a simulation model of the tire mold under the first design strategy is built through static simulation scene information and dynamic simulation scene information, so as to simulate the first design strategy to process the tire mold, obtain and analyze the simulation results of the optimal design parameters under the same dynamic node, which is conducive to discovering whether there are conflicts in the optimal design parameters of different preset performance indicators and the shortcomings of the optimal design parameters, thereby improving the performance and design efficiency of the tire mold and ensuring the quality of the tire mold and the production efficiency of the tire.

[0109] In some embodiments of the present application, if there is a conflict between the optimal design parameters, the conflict is analyzed, and a first adjustment instruction is generated according to the analysis result, including:

[0110] Analyze the optimal design parameters of the same dynamic node to obtain the position information of the optimal design parameters on the tire mold. When the position information is repeated and the repeated area is greater than the preset area threshold, it is determined that there is a conflict between the optimal design parameters.

[0111] According to the weight coefficient of the preset performance index corresponding to the optimal design parameter of the same dynamic node and the correlation degree between the optimal design parameter and other optimal design parameters, the processing priority of the optimal design parameter at the same dynamic node is set;

[0112] The optimal design parameters at the same dynamic node are sorted according to the processing priority, the optimal design parameters with a sorting value lower than the preset sorting value are offset, and the allowable normal offset area is determined;

[0113] The optimal design parameters with ranking values ​​lower than the preset ranking values ​​are adjusted to the area allowing normal deviation, and the impact degree after adjustment is calculated. If the impact degree is less than the preset impact degree, a corresponding first adjustment instruction is generated. If the impact degree is greater than the preset impact degree, it is determined whether there is a supplementary position in the idle area. If so, the area allowing normal deviation is expanded based on the supplementary position, the corresponding optimal design parameters are reasonably processed, and a corresponding first scheduling instruction is generated.

[0114] In this embodiment, the same dynamic node refers to the same processing moment, the allowed normal offset area is the processable area according to the same historical design parameters in the historical design log, the degree of influence refers to the performance impact on the preset performance indicators and the impact on the processing process of other optimal design parameters after adjusting the corresponding optimal design parameters, and the preset degree of influence is the maximum degree of influence after adjustment.

[0115] In this embodiment, when a conflict occurs in the optimal design parameters, the processing priority of the optimal design parameters at the same dynamic node is calculated, and processing is performed according to the processing priority. To prevent the optimal design parameters of subsequent processing from affecting the performance of the optimal design parameters of previous processing, the optimal design parameters with a sorting value less than the preset sorting value are adjusted to the area allowing normal deviation and a first adjustment instruction is generated, thereby improving the completion of the performance indicators of the tire mold, thereby ensuring the quality of the tire mold and the production efficiency of the tire.

[0116] In some embodiments of the present application, if there is no conflict between the optimal design parameters, calculating the simulation performance evaluation value of the first design strategy includes:

[0117] Presetting a performance evaluation value threshold for each preset performance indicator;

[0118] Generate a predicted performance evaluation value for each preset performance indicator of the first design strategy according to the simulation results and the test simulation results;

[0119] The predicted performance evaluation value of each preset performance indicator is compared with the corresponding preset performance evaluation value threshold, a predicted performance evaluation value difference is generated according to the comparison result, and a simulation performance evaluation value of the first design strategy is generated according to multiple predicted performance evaluation value differences and corresponding weight coefficients.

[0120] In this embodiment, the test simulation result refers to a performance test simulation of the tire mold after the first design strategy, obtaining a predicted performance evaluation value of each preset performance indicator, and comparing it with the preset performance evaluation value threshold to obtain a predicted performance evaluation value difference, thereby determining the simulation performance evaluation value of the first design strategy, that is, evaluating multiple performance indicators in the first design strategy to determine whether the maximum performance requirements are met. If not, generating corresponding adjustment instructions, thereby improving the performance and design efficiency of the tire mold.

[0121] In some embodiments of the present application, when the simulation performance evaluation value is less than a preset evaluation value threshold, generating a second adjustment instruction includes:

[0122] When the simulation performance evaluation value is less than the preset evaluation value threshold, the predicted performance evaluation value difference less than the predicted performance evaluation value difference threshold and the corresponding preset performance index are screened out;

[0123] If the predicted performance evaluation value difference is within the predicted second performance evaluation value difference threshold and the predicted performance evaluation value difference threshold, fine-tune the selected optimal design parameters of the preset performance indicators, and generate a second adjustment instruction according to the fine-tuning result;

[0124] If the predicted performance evaluation value difference is less than the predicted second performance evaluation value difference threshold, the optimal design parameters of the screened preset performance indicators are re-determined, and a second adjustment instruction is generated according to the re-determined optimal design parameters.

[0125] In this embodiment, the predicted second performance evaluation value difference threshold is less than the predicted performance evaluation value difference threshold, and fine-tuning the optimal design parameters of the screened preset performance indicators refers to correcting the optimal design parameters according to a correction coefficient set in advance, and the correction coefficient is set based on the historical design log. Re-determining the optimal design parameters of the screened preset performance indicators includes reselecting the characteristic design parameters corresponding to the preset performance indicators.

[0126] In this embodiment, the corresponding optimal design parameters in the first design strategy are adjusted according to the second adjustment instruction, thereby improving the quality and design efficiency of the tire mold and further improving the production efficiency of the tire.

[0127] In some embodiments of the present application, the method further comprises:

[0128] Compare the actual processing parameters in the processing process with the optimal design parameters in the simulation process, and generate a similarity degree based on the comparison results;

[0129] If the similarity is less than a preset similarity threshold, the difference between the similarity and the preset similarity threshold is calculated, and a correction coefficient of the optimal design parameter of the next processing flow is generated according to the difference;

[0130] The corresponding optimal design parameters are corrected according to the correction coefficients to obtain the corrected design parameters, and the tire template of the next processing flow is processed according to the corrected design parameters.

[0131] In this embodiment, according to the similarity between the actual processing parameters and the optimal design parameters, the deviation of the optimal design parameters between the actual processing process and the simulation process is obtained, and the correction coefficient of the optimal design parameters of the next processing flow is obtained according to the deviation and the predicted processing results, thereby ensuring the performance and design effect of the tire mold.

[0132] The above is only a preferred implementation of the present application. It should be pointed out that for ordinary technicians in this technical field, several improvements and substitutions can be made without departing from the technical principles of the present application. These improvements and substitutions should also be regarded as the scope of protection of the present application.

Claims

1. A tire mold design method, characterized in that: include: Obtain a historical design log of the tire mold, determine the degree of correlation between the historical design parameters and the preset performance indicators according to the historical design log, and obtain a characteristic design parameter of each preset performance indicator according to the degree of correlation; Calculate the application evaluation value of the characteristic design parameter of each preset performance indicator, and determine the optimal design parameter corresponding to the preset performance indicator according to the application evaluation value; generating a first design strategy from optimal design parameters of a plurality of preset performance indicators, simulating the first design strategy, and determining whether to generate an adjustment instruction according to the simulation result; If an adjustment instruction is generated, the first design strategy is adjusted according to the adjustment instruction to generate a second design strategy; if no adjustment instruction is generated, the tire mold is processed according to the first design strategy.

2. The tire mold design method according to claim 1, characterized in that: Determine whether to generate an adjustment instruction based on the simulation results, including: The simulation results include whether there is a conflict between the optimal design parameters; If there are conflicts between the optimal design parameters, the conflicts are analyzed, and a first adjustment instruction is generated according to the analysis result; If there is no conflict between the optimal design parameters, the simulation performance evaluation value of the first design strategy is calculated, and when the simulation performance evaluation value is less than the preset evaluation value threshold, a second adjustment instruction is generated, and when the simulation performance evaluation value is greater than the preset evaluation value threshold, no adjustment instruction is generated; The adjustment instruction includes a first adjustment instruction and a second adjustment instruction.

3. The tire mold design method according to claim 2, characterized in that: According to the correlation degree, characteristic design parameters of each preset performance indicator are obtained, including: Determining a performance evaluation value of each preset performance indicator in the corresponding historical design log according to a preset performance indicator evaluation method, wherein the evaluation method includes a first evaluation method and a second evaluation method; When the evaluation method is the first evaluation method, a plurality of real-time performance evaluation values ​​corresponding to the preset performance indicators in the historical design log are generated; When the evaluation method is the second evaluation method, a final performance evaluation value corresponding to a preset performance indicator in the historical design log is generated; Generate a standard processing time according to the historical processing time in multiple historical design logs of the tire mold, build a time reference line according to the standard processing time, and set a collection node of the time reference line according to a preset time interval; When the evaluation method of the preset performance indicator is the first evaluation method, the historical design parameters and the real-time performance evaluation values ​​are collected according to the multiple collection nodes on the time reference, and the first similarity between the historical design parameters and the current preset performance indicator is generated according to the number of synchronous change time nodes of the historical design parameters and the real-time performance evaluation values ​​and the degree of synchronous change; When the first similarity is greater than a preset first similarity threshold, the historical design parameter is set as a characteristic design parameter corresponding to the preset performance indicator; When the evaluation method of the preset performance indicator is the second evaluation method, the final performance evaluation value difference of the corresponding preset performance indicator of different historical design logs is calculated, and the historical design log group whose final performance evaluation value difference is greater than the preset difference threshold is screened out; According to the collection nodes of the time reference line, the historical design parameters of multiple historical design log groups are collected, grouped and processed and analyzed to obtain the parameter difference of the same historical design parameter in the same historical design log group at each collection node, and the second similarity between the historical design parameter and the current preset performance indicator is generated according to the difference between the sum of the parameter difference in the multiple historical design log groups and the final performance evaluation value of the corresponding preset performance indicators of the multiple historical design log groups; When the second similarity is greater than a preset second similarity threshold, the historical design parameter is set as a characteristic design parameter corresponding to the preset performance indicator.

4. The tire mold design method according to claim 3, characterized in that: The calculation formula of the first similarity degree is: Among them, X1 is the first similarity degree, f is the similarity degree conversion coefficient, m is the number of synchronous change time nodes of historical design parameters and real-time performance evaluation values, n is the total number of acquisition nodes, △Pi-△Gi is the synchronous change degree at the i-th synchronous change time node, △Pi is the change amount of the historical design parameters at the i-th synchronous change time node, and △Gi is the change amount of the real-time performance evaluation value at the i-th synchronous change time node; The calculation formula of the second similarity degree is: Among them, X2 is the second similarity degree, c is the number of historical design log groups whose final performance evaluation value difference is greater than the preset difference threshold, △Ks is the final performance evaluation value difference of the sth historical design log group, and △Ys is the sum of the parameter differences of the sth historical design log group.

5. The tire mold design method according to claim 4, characterized in that: Calculate the application evaluation value of the characteristic design parameter of each preset performance indicator, and determine the optimal design parameter corresponding to the preset performance indicator according to the application evaluation value, including: When the evaluation method of the preset performance indicator is the first evaluation method, an application evaluation value of the corresponding characteristic design parameter is generated according to the evaluation value difference between the real-time performance evaluation value of the characteristic design parameter of the preset performance indicator in the corresponding historical design log and the preset standard performance evaluation value and the change trend of the real-time performance evaluation value; When the evaluation method of the preset performance indicator is the second evaluation method, an application evaluation value of the corresponding feature design parameter is generated according to the evaluation value difference between the final performance evaluation value of the feature design parameter of the preset performance indicator in the corresponding historical design log and the preset performance evaluation value threshold, and the fluctuation degree of the feature design parameter; Multiple application evaluation values ​​of the feature design parameters of each preset performance indicator are compared, and the feature design parameter corresponding to the application evaluation value ranked first is set as the optimal design parameter corresponding to the preset performance indicator.

6. The tire mold design method according to claim 5, characterized in that: The first design strategy is simulated, including: Obtain the structural information of the tire mold before processing, collect the surrounding environment information of the tire mold, and construct the static simulation scene information of the tire mold based on the surrounding environment information and structural information; The dynamic simulation scenario information is obtained according to the optimal design parameters of each preset performance indicator; Obtaining the processing relationship between each optimal design parameter and the tire mold in the dynamic simulation scene information, and establishing a dynamic relationship under the same dynamic node; The dynamic relationship is linked to the static simulation scene information, a simulation of the first design strategy is performed, and a simulation result is obtained.

7. The tire mold design method according to claim 6, characterized in that: If there is a conflict between the optimal design parameters, the conflict is analyzed, and a first adjustment instruction is generated according to the analysis result, including: Analyze the optimal design parameters of the same dynamic node to obtain the position information of the optimal design parameters on the tire mold. When the position information is repeated and the repeated area is greater than the preset area threshold, it is determined that there is a conflict between the optimal design parameters. According to the weight coefficient of the preset performance index corresponding to the optimal design parameter of the same dynamic node and the correlation degree between the optimal design parameter and other optimal design parameters, the processing priority of the optimal design parameter at the same dynamic node is set; The optimal design parameters at the same dynamic node are sorted according to the processing priority, the optimal design parameters with a sorting value lower than the preset sorting value are offset, and the allowable normal offset area is determined; The optimal design parameters with ranking values ​​lower than the preset ranking values ​​are adjusted to the area allowing normal deviation, and the impact degree after adjustment is calculated. If the impact degree is less than the preset impact degree, a corresponding first adjustment instruction is generated. If the impact degree is greater than the preset impact degree, it is determined whether there is a supplementary position in the idle area. If so, the area allowing normal deviation is expanded based on the supplementary position, the corresponding optimal design parameters are reasonably processed, and a corresponding first scheduling instruction is generated.

8. The tire mold design method according to claim 7, characterized in that: If there is no conflict between the optimal design parameters, the simulation performance evaluation value of the first design strategy is calculated, including: Presetting a performance evaluation value threshold for each preset performance indicator; Generate a predicted performance evaluation value for each preset performance indicator of the first design strategy according to the simulation results and the test simulation results; The predicted performance evaluation value of each preset performance indicator is compared with the corresponding preset performance evaluation value threshold, a predicted performance evaluation value difference is generated according to the comparison result, and a simulation performance evaluation value of the first design strategy is generated according to multiple predicted performance evaluation value differences and corresponding weight coefficients.

9. The tire mold design method according to claim 8, characterized in that: When the simulation performance evaluation value is less than the preset evaluation value threshold, generating a second adjustment instruction includes: When the simulation performance evaluation value is less than the preset evaluation value threshold, the predicted performance evaluation value difference less than the predicted performance evaluation value difference threshold and the corresponding preset performance index are screened out; If the predicted performance evaluation value difference is within the predicted second performance evaluation value difference threshold and the predicted performance evaluation value difference threshold, fine-tune the selected optimal design parameters of the preset performance indicators, and generate a second adjustment instruction according to the fine-tuning result; If the predicted performance evaluation value difference is less than the predicted second performance evaluation value difference threshold, the optimal design parameters of the screened preset performance indicators are re-determined, and a second adjustment instruction is generated according to the re-determined optimal design parameters.

10. The tire mold design method according to claim 9, characterized in that: Also includes: Compare the actual processing parameters in the processing process with the optimal design parameters in the simulation process, and generate a similarity degree based on the comparison results; If the similarity is less than a preset similarity threshold, the difference between the similarity and the preset similarity threshold is calculated, and a correction coefficient of the optimal design parameter of the next processing flow is generated according to the difference; The corresponding optimal design parameters are corrected according to the correction coefficients to obtain the corrected design parameters, and the tire template of the next processing flow is processed according to the corrected design parameters.

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