Process parameter determination method, apparatus, device, storage medium, and program product

Abstract

Embodiments of the present application provide a process parameter determination method, device, equipment, storage medium and program product, and belong to the technical field of composite material processing. The method comprises: obtaining a target product morphology parameter of a target pultrusion product to be generated; determining an initial process parameter corresponding to the target product morphology parameter based on a first mapping relationship constructed in advance and the target product morphology parameter; detecting an initial quality index of a pultrusion product sample produced based on the initial process parameter; determining deviation data between the initial quality index and a preset standard quality index; in a case where the deviation data is greater than a preset deviation threshold, determining an adjustment amount corresponding to a to-be-adjusted process parameter according to a second mapping relationship and the deviation data; and determining a target process parameter of the target pultrusion product based on the initial process parameter, the to-be-adjusted process parameter and the adjustment amount corresponding to the to-be-adjusted process parameter. According to the scheme of the embodiments of the present application, the process parameter accuracy can be improved, and the debugging period can be shortened.

Description

Technical Field

[0001] This application pertains to composite material processing technology, and particularly relates to a method, apparatus, equipment, storage medium, and program product for determining process parameters. Background Technology

[0002] With the development of composite material pultrusion technology, the requirements for the quality and production efficiency of pultruded products are becoming increasingly higher.

[0003] In the production of pultruded products, the setting and adjustment of process parameters are crucial. Pultrusion production requires matching different process parameters to different product forms, and involves multiple processes such as winding, pre-pressing, and cold pressing. However, existing process parameters cannot be quickly and accurately matched to the initial process parameters when product forms are updated or changed. Furthermore, quality deviations that occur during production are difficult to correct automatically, resulting in long debugging cycles, low first-piece yield, and high scrap rates, which affect the production stability and reliability of pultruded products.

[0004] Therefore, an efficient and intelligent scheme for determining pultrusion process parameters is needed. Summary of the Invention

[0005] This application provides a method, apparatus, equipment, storage medium, and program product for determining process parameters, which can improve the accuracy of process parameters, shorten the debugging cycle, reduce the scrap rate, and enhance the intelligence and stability of pultrusion production.

[0006] In a first aspect, embodiments of this application provide a method for determining process parameters, the method comprising: Obtain the target product form parameters of the target pultruded product to be generated; Based on the pre-constructed first mapping relationship between pultrusion morphology parameters and process parameters, and the target product morphology parameters, the initial process parameters corresponding to the target product morphology parameters are determined. The initial quality indicators of pultruded product samples produced based on the initial process parameters are tested. Determine the deviation data between the initial quality index and the preset standard quality index; If the deviation data is greater than a preset deviation threshold, the adjustment amount corresponding to the process parameter to be adjusted is determined according to the preset second mapping relationship between the deviation and the process parameter and the deviation data. Based on the initial process parameters, the process parameters to be adjusted, and the adjustment amounts corresponding to the process parameters to be adjusted, the target process parameters for the target pultruded product are determined.

[0007] In one feasible implementation, the first mapping relationship is obtained in the following way: Obtain historical product form parameters and corresponding historical process parameters from the mapping library; Generate a product form parameter to be matched that is different from the historical product form parameter; Based on the product form parameters to be matched, at least two similar candidate product form parameters are found from the historical product form parameters. Using a preset data interpolation algorithm, interpolation calculations are performed on the historical process parameters corresponding to the at least two candidate product form parameters to obtain the process parameters of the product to be matched corresponding to the product form parameters to be matched. Based on the product form parameters to be matched, the product process parameters to be matched, the historical product form parameters, and the historical process parameters, the first mapping relationship is constructed; The first mapping relationship is stored in the mapping library.

[0008] In one feasible implementation, the deviation data includes at least a deviation parameter type and a deviation amount; wherein, determining the process parameter to be adjusted and the corresponding adjustment amount based on a preset second mapping relationship between the deviation data and the process parameters, and the deviation data, includes: Based on the deviation parameter type and the second mapping relationship, determine the type of the process parameter to be adjusted corresponding to the process parameter to be adjusted; The adjustment amount is determined based on the deviation and the second mapping relationship.

[0009] In one feasible implementation, determining the adjustment amount based on the deviation and the second mapping relationship includes: Based on the second mapping relationship and each of the parameter types to be adjusted, the adjustment priority corresponding to each of the parameter types to be adjusted is determined; According to the adjustment priority, the second mapping relationship, the deviation amount, and each of the parameter types to be adjusted, the adjustment amount corresponding to each parameter type to be adjusted is determined in sequence.

[0010] In one feasible implementation, the process parameters to be adjusted include at least mold temperature, traction speed, traction tension, resin pump speed, and fiber tension.

[0011] In one feasible implementation, the target process parameters for the target pultruded product are determined based on the initial process parameters, the process parameters to be adjusted, and the adjustment amounts corresponding to the process parameters to be adjusted, including: From the initial process parameters, determine the first process parameter that does not belong to the process parameters to be adjusted; Based on the adjustment amount, the process parameters to be adjusted are corrected to obtain the second process parameters; The first process parameter and the second process parameter are combined to form the target process parameter.

[0012] Secondly, embodiments of this application provide a process parameter determination apparatus, the apparatus comprising: The acquisition module is used to acquire the target product form parameters of the target pultruded product to be generated; The initial process parameter determination module is used to determine the initial process parameters corresponding to the target product shape parameters based on the first mapping relationship between the pre-constructed pultrusion shape parameters and process parameters and the target product shape parameters. The detection module is used to detect the initial quality indicators of pultruded product samples produced based on the initial process parameters. The deviation data determination module is used to determine the deviation data between the initial quality index and the preset standard quality index; The adjustment amount determination module is used to determine the adjustment amount corresponding to the process parameter to be adjusted based on the second mapping relationship between the preset deviation and the process parameter and the deviation data when the deviation data is greater than the preset deviation threshold. The target process parameter determination module is used to determine the target process parameters of the target pultruded product based on the initial process parameters, the process parameters to be adjusted, and the adjustment amount corresponding to the process parameters to be adjusted.

[0013] Thirdly, embodiments of this application provide a process parameter determination device, the device comprising: A processor, and a memory storing computer program instructions; the processor reads and executes the computer program instructions to implement the method as described in the first aspect.

[0014] Fourthly, embodiments of this application provide a computer storage medium storing computer program instructions, which, when executed by a processor, implement the method described in the first aspect.

[0015] Fifthly, embodiments of this application provide a computer program product, including a computer program that, when executed by a processor, implements the method described in the first aspect.

[0016] The process parameter determination method, apparatus, equipment, storage medium, and program product of this application directly match initial process parameters based on a first mapping relationship, eliminating the need for repeated manual trial and error, significantly shortening the new product changeover and debugging time, and improving production efficiency. By real-time detection of product quality indicators and calculation of deviations, quality problems can be automatically identified, and adjustment amounts can be determined according to a second mapping relationship. Thus, through the determination of initial process parameters and automatic deviation correction, sample quality can quickly approach the standard range, effectively reducing defective products and improving production economy. Moreover, by constructing a complete closed loop of morphology input, initial matching, quality feedback, and parameter correction, intelligent control and automated management of the pultrusion process can be achieved. Attached Figure Description

[0017] To more clearly illustrate the technical solutions of the embodiments of this application, the accompanying drawings used in the embodiments of this application will be briefly introduced below. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0018] Figure 1 A flowchart illustrating a method for determining process parameters according to an embodiment of this application is shown. Figure 2 A flowchart illustrating a method for determining process parameters according to another embodiment of this application is shown; Figure 3 This paper shows a schematic diagram of a process parameter determination device provided in an embodiment of this application; Figure 4 A schematic diagram of the hardware structure of the process parameter determination device provided in an embodiment of this application is shown. Detailed Implementation

[0019] The features and exemplary embodiments of various aspects of this application will be described in detail below. To make the objectives, technical solutions, and advantages of this application clearer, the application will be further described in detail below with reference to the accompanying drawings and specific embodiments. It should be understood that the specific embodiments described herein are only intended to explain this application and not to limit it. For those skilled in the art, this application can be implemented without some of these specific details. The following description of the embodiments is merely to provide a better understanding of this application by illustrating examples.

[0020] It should be noted that, in this document, relational terms such as "first" and "second" are used merely to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitations, an element defined by the phrase "comprising..." does not exclude the presence of additional identical elements in the process, method, article, or apparatus that includes said element.

[0021] In traditional pultrusion processes, the determination of process parameters relies heavily on the accumulated experience of operators. When producing new pultruded products, the lack of a standardized parameter matching mechanism necessitates repeated trial and error to determine suitable process parameters. This not only leads to long product changeover cycles but also consumes significant amounts of raw materials and production time, severely impacting production efficiency. Human experience is subjective and limited; different operators set parameters that vary considerably, making it difficult to ensure optimal matching between initial process parameters and the target product form. This can result in large fluctuations in the quality of the first piece, increasing the difficulty of subsequent adjustments. When quality deviations occur during production, manual inspection and identification of the source of the deviation are required, followed by manual adjustment of process parameters based on experience. This method is not only slow to respond but also prone to misjudgment or over-adjustment, leading to new quality problems and hindering precise and rapid correction. The lack of an automated closed-loop control mechanism means that the consistency of process parameters depends entirely on manual operation. This makes parameters susceptible to fluctuations due to personnel changes, fatigue, and other factors, affecting product quality stability, increasing scrap rates and production costs. This fails to meet the requirements of modern intelligent manufacturing for efficient, stable, and traceable pultrusion production, limiting the large-scale and automated development of the pultrusion process.

[0022] To address the problems in the prior art, embodiments of this application provide a method, apparatus, equipment, storage medium, and program product for determining process parameters.

[0023] The method for determining process parameters provided in the embodiments of this application will be introduced first below.

[0024] Figure 1 A flowchart illustrating a method for determining process parameters according to an embodiment of this application is shown. Figure 1 As shown, the method may include the following steps: S110 to S160.

[0025] S110. Obtain the target product form parameters of the target pultruded product to be generated.

[0026] In this embodiment, the target pultruded product to be generated refers to a pultruded product that has not yet been actually produced and is in the process planning or parameter debugging stage. The target product morphology parameters refer to the key parameters used to describe the product morphology of the target pultruded product to be generated, including but not limited to the cross-sectional dimensions, cross-sectional shape and structural features of the target pultruded product to be generated.

[0027] S120. Based on the pre-constructed first mapping relationship between pultrusion morphology parameters and process parameters, and the target product morphology parameters, determine the initial process parameters corresponding to the target product morphology parameters.

[0028] In this embodiment, pultrusion morphology parameters refer to parameters used to describe the geometry or structure of pultruded products, while process parameters refer to key process variables that need to be controlled during pultrusion production. Process parameters include, but are not limited to, mold temperature, traction speed, resin injection pressure or flow rate, curing time, and tension control parameters. The first mapping relationship refers to the pre-constructed mapping relationship between pultrusion morphology parameters and process parameters. The first mapping relationship can be a mapping rule, function, or database.

[0029] In this embodiment, initial process parameters corresponding to the target product's shape parameters are determined based on the first mapping relationship. Initial process parameters refer to process parameters initially determined based on the product's shape parameters and used for trial production. The initial process parameters corresponding to the target product's shape parameters can be obtained by performing table lookup matching or function operations within the first mapping relationship based on the target product's shape parameters.

[0030] S130. Inspect the initial quality indicators of pultruded product samples produced based on initial process parameters.

[0031] In this embodiment, the pultruded product sample refers to a pultruded product generated using initial process parameters. This sample is not a product destined for mass production; it is a test sample created using the initial process parameters. By testing the pultruded product sample, its initial quality indicators can be obtained. Initial quality indicators are key parameters or metrics used to measure the quality grade or quality of the pultruded product sample. For example, initial quality indicators may include dimensional accuracy, hardness, tensile strength, flexural strength, and water absorption. It should be noted that only a small number of pultruded product samples are produced to further reduce trial-and-error losses related to process parameters.

[0032] S140. Determine the deviation data between the initial quality indicators and the preset standard quality indicators.

[0033] In this embodiment, the preset standard quality index is a pre-set qualification standard or design requirement. For example, the preset standard quality index may include bending standard strength, standard thickness, etc. Deviation data refers to the difference or disparity between the initial quality index and the preset standard quality index. The deviation data can be obtained by subtracting the initial quality index from the preset standard quality index, or vice versa.

[0034] S150. When the deviation data is greater than the preset deviation threshold, the adjustment amount corresponding to the process parameter to be adjusted is determined according to the preset second mapping relationship between the deviation and the process parameter and the deviation data.

[0035] In this embodiment, the preset deviation threshold refers to a pre-set allowable error range. Different preset standard quality indicators correspond to different preset deviation thresholds. If the deviation data is greater than the preset deviation threshold, it means that the sample or product is unqualified. For example, the preset deviation threshold for thickness can be a thickness error allowance of ±0.1mm; if it exceeds this, it is unqualified.

[0036] In this embodiment, the preset second mapping relationship between deviation and process parameters refers to a pre-established and stored correspondence or function rule used to characterize the relationship between quality deviation and the adjustment direction and magnitude of the corresponding process parameters. The process parameters to be adjusted refer to one or more process parameters among the current initial process parameters that are determined to need correction or adjustment. The adjustment amount corresponding to the process parameters to be adjusted refers to the specific value that needs to be modified in order to bring the quality deviation or deviation data back to the acceptable range; it typically includes two parts: adjustment direction and adjustment magnitude.

[0037] In this embodiment, the deviation data can be used as input based on the deviation data and the second mapping relationship. Matching or calculation can be performed in the second mapping relationship to determine the process parameter to be adjusted corresponding to the deviation data, and the adjustment direction and adjustment value required for the process parameter to be adjusted can be obtained, that is, the adjustment amount corresponding to the process parameter to be adjusted can be obtained.

[0038] S160. Based on the initial process parameters, the process parameters to be adjusted, and the adjustment amounts corresponding to the process parameters to be adjusted, determine the target process parameters for the target pultruded product.

[0039] In this embodiment, the target process parameters refer to the final, complete process parameters that can be directly used for the formal mass production of the target pultruded product. Specifically, based on the initial process parameters, parameters that do not need to be adjusted are retained unchanged, and only the process parameters that need to be adjusted are modified according to the adjustment amount. Finally, a set of final process parameters suitable for formal mass production and meeting quality standards are formed, namely, the target process parameters.

[0040] Through steps S110 to S160, initial process parameters are automatically determined based on product form, eliminating reliance on manual trial and error. This significantly improves the efficiency and consistency of parameter setting. By analyzing sample quality and calculating deviations, combined with preset mapping relationships, parameter adjustment amounts are automatically determined, achieving closed-loop control from quality deviations to process corrections. Initial parameters are closer to optimal values, and further optimization through deviation correction improves the matching degree between process parameters and product quality requirements, reduces the number of repeated manual adjustments, accelerates the launch of new products, reduces raw material waste and production costs, and standardizes and automates the process parameter determination process, reducing the impact of human factors, making batch production quality more stable, and improving product qualification rates.

[0041] Figure 2 A flowchart illustrating a method for determining process parameters according to another embodiment of this application is shown. As shown, the first mapping relationship can be obtained through the following steps: S210 to S260.

[0042] S210. Obtain historical product form parameters and corresponding historical process parameters from the mapping library.

[0043] In this embodiment, the mapping library refers to a pre-established database or set of relationships used to store the correspondence between product forms and process parameters, serving as a carrier of historical production data. The mapping library also includes historical product form parameters and their corresponding historical process parameters. Historical product form parameters refer to the form parameters of previously produced pultruded products, including geometric features such as shape, size, and structure. The corresponding historical process parameters are the process parameters actually used and verified to be effective during the production of these historical pultruded products. Historical product form parameters and their corresponding historical process parameters can be obtained from the mapping library.

[0044] S220. Generate product form parameters that are different from the historical product form parameters.

[0045] In this embodiment, S220 can refer to obtaining a new set of product form data through methods such as manual setting, simulation construction, automatic system generation, or external input. This new set of product form data is different from historical product form parameters and can be referred to as the product form parameters to be matched. In other words, the product form parameters to be matched are product form parameters that are different from historical product form parameters and do not exist in the mapping library.

[0046] S230. Based on the product form parameters to be matched, find at least two similar candidate product form parameters from the historical product form parameters.

[0047] In this embodiment, based on the shape parameters of the product to be matched, a search and comparison is performed on all historical product shape data retrieved from the mapping library. At least one historical product shape parameter similar to the shape parameters of the product to be matched is found from the historical product shape parameters. The candidate product shape parameter refers to the historical product shape parameter similar to the shape parameters of the product to be matched. Here, similarity means that the specific shape parameters such as structural type, cross-sectional features, and size range are relatively close or belong to the same type of product shape. That is, the candidate product shape parameter refers to the historical product shape parameter similar to at least one sub-shape parameter of the shape parameters of the product to be matched.

[0048] In some embodiments, S230 may include: comparing the form parameter of the product to be matched with each historical product form parameter item by item, calculating the absolute value of the difference between each first sub-form parameter in the form parameter of the product to be matched and each second sub-form parameter in the historical product form parameters; and determining the current historical product form parameter as a candidate product form parameter similar to the form parameter of the product to be matched when the number of feature parameters whose absolute value of the difference is less than a preset similarity threshold reaches a preset number threshold.

[0049] S240. Using a preset data interpolation algorithm, interpolate the historical process parameters corresponding to at least two candidate product form parameters to obtain the process parameters of the product to be matched corresponding to the product form parameters to be matched.

[0050] In this embodiment, the preset data interpolation algorithm refers to a pre-defined calculation method used to deduce intermediate values ​​based on known data, such as linear interpolation or weighted interpolation. Its purpose is to deduce reasonable process parameters corresponding to the new shape based on existing historical data. By using the preset data interpolation algorithm to perform interpolation calculations on the historical process parameters corresponding to at least two candidate product shape parameters, process parameters that may be applicable to the new product shape can be obtained, i.e., the process parameters of the product to be matched.

[0051] S250. Based on the form parameters of the product to be matched, the process parameters of the product to be matched, the form parameters of historical products, and the process parameters of historical products, construct the first mapping relationship.

[0052] In this embodiment, the product form parameters to be matched, the product process parameters to be matched, and the historical product form parameters and historical process parameters can be integrated. That is, the product form parameters to be matched and the historical product form parameters are merged, and the product process parameters to be matched and the historical process parameters are merged. The merged data is then used for data fitting to construct the first mapping relationship.

[0053] S260. Store the first mapping relationship in the mapping library.

[0054] In this embodiment, the latest first mapping relationship that has been constructed can be written and saved to the mapping library so that it can be directly called when S120 is executed later, and also to provide a data foundation for the subsequent construction of updated mapping relationships.

[0055] Through S210 to S260, based on historical data, the correspondence between new product forms and process parameters can be generated by interpolation, continuously enriching the mapping library. Without the need for manual rule establishment, the mapping relationship between product forms and process parameters can be intelligently generated and updated. By continuously supplementing new data, the initial process parameters of subsequent S120 can be more accurate and more in line with actual production.

[0056] In some embodiments, the deviation data includes at least the deviation parameter type and the deviation amount. The deviation parameter type refers to the specific quality indicator name or type in which the deviation occurs, and the deviation amount refers to the difference between the preset standard quality indicator and the actual detected quality indicator, including the deviation magnitude and the deviation direction.

[0057] In some embodiments, determining the adjustment amount corresponding to the process parameter to be adjusted based on the preset second mapping relationship between the deviation and the process parameter and the deviation data may include the following steps S310 to S320.

[0058] S310. Based on the deviation parameter type and the second mapping relationship, determine the type of parameter to be adjusted corresponding to the process parameter to be adjusted.

[0059] In this embodiment, the type of parameter to be adjusted refers to the type of process parameter corresponding to the process parameter to be adjusted. Since the second mapping relationship contains the correspondence between the deviation parameter type and the type of parameter to be adjusted, the deviation parameter type can be matched in the second mapping relationship to determine which type of process parameter needs to be adjusted to eliminate the deviation, thus obtaining the type of parameter to be adjusted.

[0060] S320. Determine the adjustment amount based on the deviation and the second mapping relationship.

[0061] In this embodiment, the second mapping relationship also includes the relationship between the deviation amount and the adjustment amount. Therefore, by taking the deviation amount as input and calculating or matching according to the second mapping relationship, the specific value and direction (how much to increase or how much to decrease) that the parameter type to be adjusted can be obtained, that is, the adjustment amount is determined.

[0062] Through S310 to S320, the type of process parameter that needs to be adjusted can be determined by the type of deviation, and then the specific adjustment value can be determined based on the magnitude of the deviation, so as to quickly and accurately obtain the specific adjustment method of the process parameter.

[0063] In some embodiments, determining the adjustment amount based on the deviation and the second mapping relationship may include the following steps: S321 to S322.

[0064] S321. Based on the second mapping relationship and the types of parameters to be adjusted, determine the adjustment priority corresponding to each type of parameter to be adjusted.

[0065] In this embodiment, the second mapping relationship pre-configures adjustment priorities corresponding to different process parameter types. These priorities indicate the order in which the parameter types to be adjusted should be performed. Based on the second mapping relationship, the adjustment priority for each parameter type to be adjusted is determined.

[0066] S322. Determine the adjustment amount corresponding to each type of parameter to be adjusted in sequence according to the adjustment priority, the second mapping relationship, the deviation amount and the type of each parameter to be adjusted.

[0067] In this embodiment, it is necessary to adjust the priority. Starting with the parameter type with the highest priority, the adjustment amount is calculated or matched one by one according to the second mapping relationship.

[0068] Through S321 to S322, when there are multiple process parameters to be adjusted, the adjustment priority can be set and the adjustment amount can be allocated in sequence to achieve orderly and stable parameter correction, avoid interference and fluctuations caused by simultaneous adjustment of multiple parameters, and improve the reliability of deviation correction.

[0069] In some embodiments, the process parameters to be adjusted include at least mold temperature, traction speed, traction tension, resin pump speed, and fiber tension. Mold temperature refers to the controlled temperature of the mold heating zone in the pultrusion process, used to fully cure the resin system, directly determining the degree of curing, internal defects, and mechanical properties of the product. Traction speed refers to the speed at which the traction device of the pultrusion equipment pulls the fiber-reinforced material continuously forward, determining the product's residence time in the mold and production efficiency, affecting product thickness, degree of curing, and surface quality. Traction tension refers to the overall tension applied by the traction device during the pulling of the profile, used to ensure smooth product movement and dimensional stability, avoiding bending, deformation, or dimensional deviations. Resin pump speed refers to the output speed or flow rate of the resin feed pump, controlling the supply of impregnating resin, affecting the product's resin content, wetting effect, and appearance defects. Fiber tension refers to the tension applied to each fiber bundle before entering the mold, used to ensure uniform and straight fiber arrangement, avoiding loose fibers and wrinkles, thereby improving the product's structural uniformity and strength stability.

[0070] In some embodiments, determining the target process parameters of the target pultruded product based on the initial process parameters, the process parameters to be adjusted, and the adjustment amount corresponding to the process parameters to be adjusted may include the following steps: S610 to S630.

[0071] S610. From the initial process parameters, determine the first process parameter that is not among the process parameters to be adjusted.

[0072] In this embodiment, the first process parameter refers to the parameter in the initial process parameters that does not need to be adjusted and whose original value remains unchanged. The first process parameter that is not a process parameter to be adjusted can be determined from the initial process parameters.

[0073] S620. Based on the adjustment amount, the process parameters to be adjusted are corrected to obtain the second process parameters.

[0074] In this embodiment, based on the adjustment amount, the original value corresponding to the process parameter to be adjusted is numerically corrected to obtain a new parameter value that has been adjusted and can be used for production, namely the second process parameter.

[0075] S630. Combine the first process parameter and the second process parameter into the target process parameter.

[0076] In this embodiment, the first process parameter that does not need to be modified and the second process parameter that has been corrected are combined to form a complete set of target process parameters that can be directly used for pultrusion production.

[0077] Through S610 to S630, based on the original production parameters, only the process parameters that need to be adjusted can be modified, while the parameters that do not need to be adjusted remain unchanged. Finally, a complete set of target process parameters that can be directly used for production is formed, achieving precise and efficient process optimization.

[0078] Figure 3 A schematic diagram of a process parameter determination device provided in an embodiment of this application is shown. As shown, the process parameter determination device 300 may include an acquisition module 310, an initial process parameter determination module 320, a detection module 330, a deviation data determination module 340, an adjustment amount determination module 350, and a target process parameter determination module 360.

[0079] The acquisition module 310 is used to acquire the target product shape parameters of the target pultruded product to be generated.

[0080] The initial process parameter determination module 320 is used to determine the initial process parameters corresponding to the target product morphology parameters based on the first mapping relationship between the pre-constructed pultrusion morphology parameters and process parameters and the target product morphology parameters.

[0081] The detection module 330 is used to detect the initial quality indicators of the pultruded product sample produced based on the initial process parameters.

[0082] The deviation data determination module 340 is used to determine the deviation data between the initial quality index and the preset standard quality index.

[0083] The adjustment amount determination module 350 is used to determine the adjustment amount corresponding to the process parameter to be adjusted based on the preset second mapping relationship between the deviation and the process parameter and the deviation data when the deviation data is greater than the preset deviation threshold.

[0084] The target process parameter determination module 360 ​​is used to determine the target process parameters of the target pultruded product based on the initial process parameters, the process parameters to be adjusted, and the adjustment amount corresponding to the process parameters to be adjusted.

[0085] In some embodiments, the process parameter determining device 300 may further include a first mapping relationship determining module, the first mapping relationship determining module being used for: Obtain historical product form parameters and corresponding historical process parameters from the mapping library; Generate a product form parameter to be matched that is different from the historical product form parameter; Based on the product form parameters to be matched, at least two similar candidate product form parameters are found from the historical product form parameters. Using a preset data interpolation algorithm, interpolation calculations are performed on the historical process parameters corresponding to the at least two candidate product form parameters to obtain the process parameters of the product to be matched corresponding to the product form parameters to be matched. Based on the product form parameters to be matched, the product process parameters to be matched, the historical product form parameters, and the historical process parameters, the first mapping relationship is constructed; The first mapping relationship is stored in the mapping library.

[0086] In some embodiments, the adjustment amount determination module 350 may further include an adjustment parameter type determination module and an adjustment amount determination module.

[0087] The parameter type determination module is used to determine the type of parameter to be adjusted corresponding to the process parameter to be adjusted based on the deviation parameter type and the second mapping relationship.

[0088] The adjustment amount determination module is used to determine the adjustment amount based on the deviation amount and the second mapping relationship.

[0089] In some embodiments, the adjustment amount determination module may include an adjustment priority determination module and an adjustment amount sequential determination module.

[0090] The priority determination module is used to determine the adjustment priority corresponding to each of the parameter types to be adjusted based on the second mapping relationship and each of the parameter types to be adjusted.

[0091] The adjustment amount determination module is used to determine the adjustment amount corresponding to each of the parameter types to be adjusted in sequence according to the adjustment priority, the second mapping relationship, the deviation amount and each of the parameter types to be adjusted.

[0092] In some embodiments, the process parameters to be adjusted include at least mold temperature, traction speed, traction tension, resin pump speed, and fiber tension.

[0093] In some embodiments, the target process parameter determination module 360 ​​may include a first process parameter determination module, a second process parameter determination module, and a combination module.

[0094] The first process parameter determination module is used to determine a first process parameter that does not belong to the process parameter to be adjusted from the initial process parameters.

[0095] The second process parameter determination module is used to correct the process parameter to be adjusted according to the adjustment amount to obtain the second process parameter.

[0096] The combination module is used to combine the first process parameter and the second process parameter into the target process parameter.

[0097] Figure 4 A schematic diagram of the hardware structure of the process parameter determination device provided in an embodiment of this application is shown.

[0098] The equipment for determining process parameters may include a processor 401 and a memory 402 storing computer program instructions.

[0099] Specifically, the processor 401 may include a central processing unit (CPU), an application specific integrated circuit (ASIC), or one or more integrated circuits that can be configured to implement the embodiments of this application.

[0100] Memory 402 may include mass storage for data or instructions. For example, and not limitingly, memory 402 may include a hard disk drive (HDD), floppy disk drive, flash memory, optical disk, magneto-optical disk, magnetic tape, or Universal Serial Bus (USB) drive, or a combination of two or more of these. In one instance, memory 402 may include removable or non-removable (or fixed) media, or memory 402 may be non-volatile solid-state memory. Memory 402 may be internal or external to the integrated gateway disaster recovery device.

[0101] In one instance, memory 402 may be read-only memory (ROM). In one instance, the ROM may be a mask-programmed ROM, a programmable ROM (PROM), an erasable PROM (EPROM), an electrically erasable PROM (EEPROM), an electrically rewritable ROM (EAROM), or flash memory, or a combination of two or more of these.

[0102] Memory 402 may include read-only memory (ROM), random access memory (RAM), disk storage media device, optical storage media device, flash memory device, electrical, optical, or other physical / tangible memory storage device. Thus, generally, memory includes one or more tangible (non-transitory) computer-readable storage media (e.g., memory devices) encoded with software including computer-executable instructions, and when the software is executed (e.g., by one or more processors), it is operable to perform the operations described with reference to the method according to one aspect of this disclosure.

[0103] The processor 401 reads and executes computer program instructions stored in the memory 402 to achieve... Figure 1 The method for determining process parameters in the illustrated embodiment.

[0104] In one example, the process parameter determination device may also include a communication interface 403 and a bus 404. As shown in the figure, the processor 401, memory 402, and communication interface 403 are connected via bus 404 and communicate with each other.

[0105] The communication interface 403 is mainly used to realize communication between various modules, devices, units and / or equipment in the embodiments of this application.

[0106] Bus 404 includes hardware, software, or both, that couples components of an online data traffic metering device together. For example, and not as a limitation, the bus may include an Accelerated Graphics Port (AGP) or other graphics bus, an Extended Industry Standard Architecture (EISA) bus, a Front Side Bus (FSB), a Hyper Transport (HT) interconnect, an Industry Standard Architecture (ISA) bus, an Infinite Bandwidth Interconnect, a Low Pin Count (LPC) bus, a memory bus, a Microchannel Architecture (MCA) bus, a Peripheral Component Interconnect (PCI) bus, a PCI-Express (PCI-X) bus, a Serial Advanced Technology Attachment (SATA) bus, a Video Electronics Standards Association Local (VLB) bus, or other suitable buses, or combinations of two or more of these. Where appropriate, bus 404 may include one or more buses. Although specific buses are described and illustrated in embodiments of this application, this application contemplates any suitable bus or interconnect.

[0107] The process parameters determine that the equipment can execute the online data traffic billing method in this application embodiment based on currently blocked spam SMS messages and SMS messages reported by users, thereby achieving a combination of... Figure 1 The method for determining the process parameters is described.

[0108] Furthermore, in conjunction with the process parameter determination methods in the above embodiments, this application embodiment can provide a computer storage medium for implementation. This computer storage medium stores computer program instructions; when these computer program instructions are executed by a processor, they implement any of the process parameter determination methods in the above embodiments.

[0109] This application also provides a computer program product, including a computer program that, when executed by a processor, implements any of the process parameter determination methods described in the above embodiments.

[0110] It should be clarified that this application is not limited to the specific configurations and processes described above and shown in the figures. For the sake of brevity, detailed descriptions of known methods are omitted here. In the above embodiments, several specific steps are described and shown as examples. However, the method process of this application is not limited to the specific steps described and shown. Those skilled in the art can make various changes, modifications, and additions, or change the order of steps, after understanding the spirit of this application.

[0111] The functional blocks shown in the above-described block diagram can be implemented as hardware, software, firmware, or a combination thereof. When implemented in hardware, they can be, for example, electronic circuits, application-specific integrated circuits (ASICs), appropriate firmware, plug-ins, function cards, etc. When implemented in software, the elements of this application are programs or code segments used to perform the required tasks. Programs or code segments can be stored on a machine-readable medium or transmitted over a transmission medium or communication link via data signals carried on a carrier wave. "Machine-readable medium" can include any medium capable of storing or transmitting information. Examples of machine-readable media include electronic circuits, semiconductor memory devices, read-only memory (ROM), flash memory, erasable read-only memory (EROM), floppy disks, compact disc read-only memory (CD-ROM), optical disks, hard disks, fiber optic media, radio frequency (RF) links, etc. Code segments can be downloaded via computer networks such as the Internet, intranets, etc.

[0112] It should also be noted that the exemplary embodiments mentioned in this application describe methods or systems based on a series of steps or apparatus. However, this application is not limited to the order of the above steps; that is, the steps can be performed in the order mentioned in the embodiments, or in a different order, or several steps can be performed simultaneously.

[0113] The aspects of this disclosure have been described above with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of this disclosure. It should be understood that each block in the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable data processing apparatus to produce a machine such that these instructions, executable via the processor of the computer or other programmable data processing apparatus, enable the implementation of the functions / actions specified in one or more blocks of the flowchart illustrations and / or block diagrams. Such a processor can be, but is not limited to, a general-purpose processor, a special-purpose processor, a special application processor, or a field-programmable logic circuit. It is also understood that each block in the block diagrams and / or flowcharts, and combinations of blocks in the block diagrams and / or flowcharts, can also be implemented by special-purpose hardware performing the specified functions or actions, or can be implemented by a combination of special-purpose hardware and computer instructions.

[0114] The above description is merely a specific implementation of this application. Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the specific working processes of the systems, modules, and units described above can be referred to the corresponding processes in the foregoing method embodiments, and will not be repeated here. It should be understood that the protection scope of this application is not limited thereto. Any person skilled in the art can easily conceive of various equivalent modifications or substitutions within the technical scope disclosed in this application, and these modifications or substitutions should all be covered within the protection scope of this application.

Claims

1. A method for determining process parameters, characterized in that, include: Obtain the target product form parameters of the target pultruded product to be generated; Based on the pre-constructed first mapping relationship between pultrusion morphology parameters and process parameters, and the target product morphology parameters, the initial process parameters corresponding to the target product morphology parameters are determined. The initial quality indicators of pultruded product samples produced based on the initial process parameters are tested. Determine the deviation data between the initial quality index and the preset standard quality index; If the deviation data is greater than a preset deviation threshold, the adjustment amount corresponding to the process parameter to be adjusted is determined according to the preset second mapping relationship between the deviation and the process parameter and the deviation data. Based on the initial process parameters, the process parameters to be adjusted, and the adjustment amounts corresponding to the process parameters to be adjusted, the target process parameters for the target pultruded product are determined.

2. The method according to claim 1, characterized in that, The first mapping relationship was obtained in the following way: Obtain historical product form parameters and corresponding historical process parameters from the mapping library; Generate a product form parameter to be matched that is different from the historical product form parameter; Based on the product form parameters to be matched, at least two similar candidate product form parameters are found from the historical product form parameters. Using a preset data interpolation algorithm, interpolation calculations are performed on the historical process parameters corresponding to the at least two candidate product form parameters to obtain the process parameters of the product to be matched corresponding to the product form parameters to be matched. Based on the product form parameters to be matched, the product process parameters to be matched, the historical product form parameters, and the historical process parameters, the first mapping relationship is constructed; The first mapping relationship is stored in the mapping library.

3. The method according to claim 1, characterized in that, The deviation data includes at least the deviation parameter type and the deviation amount; wherein, determining the process parameter to be adjusted and the corresponding adjustment amount based on the preset second mapping relationship between the deviation data and the process parameter, and the deviation data, includes: Based on the deviation parameter type and the second mapping relationship, determine the type of the process parameter to be adjusted corresponding to the process parameter to be adjusted; The adjustment amount is determined based on the deviation and the second mapping relationship.

4. The method according to claim 3, characterized in that, Determining the adjustment amount based on the deviation and the second mapping relationship includes: Based on the second mapping relationship and each of the parameter types to be adjusted, the adjustment priority corresponding to each of the parameter types to be adjusted is determined; According to the adjustment priority, the second mapping relationship, the deviation amount, and each of the parameter types to be adjusted, the adjustment amount corresponding to each parameter type to be adjusted is determined in sequence.

5. The method according to claim 3, characterized in that, The process parameters to be adjusted include at least mold temperature, traction speed, traction tension, resin pump speed, and fiber tension.

6. The method according to claim 1, characterized in that, Based on the initial process parameters, the process parameters to be adjusted, and the corresponding adjustment amounts for the process parameters to be adjusted, the target process parameters for the target pultruded product are determined, including: From the initial process parameters, determine the first process parameter that does not belong to the process parameters to be adjusted; Based on the adjustment amount, the process parameters to be adjusted are corrected to obtain the second process parameters; The first process parameter and the second process parameter are combined to form the target process parameter.

7. A process parameter determining device, characterized in that, The device includes: The acquisition module is used to acquire the target product form parameters of the target pultruded product to be generated; The initial process parameter determination module is used to determine the initial process parameters corresponding to the target product shape parameters based on the first mapping relationship between the pre-constructed pultrusion shape parameters and process parameters and the target product shape parameters. The detection module is used to detect the initial quality indicators of pultruded product samples produced based on the initial process parameters. The deviation data determination module is used to determine the deviation data between the initial quality index and the preset standard quality index; The adjustment amount determination module is used to determine the adjustment amount corresponding to the process parameter to be adjusted based on the second mapping relationship between the preset deviation and the process parameter and the deviation data when the deviation data is greater than the preset deviation threshold. The target process parameter determination module is used to determine the target process parameters of the target pultruded product based on the initial process parameters, the process parameters to be adjusted, and the adjustment amount corresponding to the process parameters to be adjusted.

8. A process parameter determination device, characterized in that, The device includes: a processor and a memory storing computer program instructions; the processor reads and executes the computer program instructions to implement the method as described in any one of claims 1-6.

9. A computer storage medium, characterized in that, The computer storage medium stores computer program instructions, which, when executed by a processor, implement the method as described in any one of claims 1-6.

10. A computer program product, characterized in that, Includes a computer program that, when executed by a processor, implements the method as described in any one of claims 1-6.

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