Antiseptic and insect prevention optimization control method and system for reconstituted bamboo production and processing

Abstract

This invention discloses an optimized control method and system for anti-corrosion and insect-proofing in the production and processing of reconstituted bamboo, relating to the field of reconstituted bamboo production and processing. The method includes: inputting model information into a reconstituted bamboo curing process database to obtain a range of curing process parameters; constructing a loss function and constraints based on the model information; combining the curing process parameter range with the pressure impregnation process parameter range for anti-corrosion and insect-proofing treatment of the target reconstituted bamboo to obtain an optimized process parameter range; obtaining the optimal process parameters within the optimized process parameter range based on the loss function and constraints, and controlling the production of curing and pressure impregnation anti-corrosion and insect-proofing treatment of the target reconstituted bamboo accordingly. This solves the technical problem of low accuracy in the production control of anti-corrosion and insect-proofing production of reconstituted bamboo in the prior art, leading to poor anti-corrosion and insect-proofing quality of reconstituted bamboo. It achieves technical effects such as improving the anti-corrosion and insect-proofing quality of reconstituted bamboo.

Description

Technical Field

[0001] This invention relates to the field of reconstituted bamboo production and processing, and more specifically, to an optimized control method and system for corrosion and insect prevention in the production and processing of reconstituted bamboo. Background Technology

[0002] Reconstituted bamboo is a bamboo product made from abundant bamboo resources with a short growth cycle, boasting high bamboo utilization and simple production processes. Similar to wood structures, reconstituted bamboo is a green building material. However, due to the high content of starch and sugars in reconstituted bamboo, it is susceptible to corrosion, mold, and insect infestation, significantly impacting its hardness, strength, and reliability. Preservative and insect-proofing treatments are a crucial aspect of reconstituted bamboo production. Current technologies suffer from low accuracy in controlling the preservative and insect-proofing process, resulting in poor quality reconstituted bamboo. Summary of the Invention

[0003] This application provides an optimized control method and system for the preservation and insect control of reconstituted bamboo production and processing. It solves the technical problem of low accuracy in the preservation and insect control production of reconstituted bamboo in existing technologies, which leads to poor preservation and insect control quality. It achieves the technical effect of improving the accuracy of preservation and insect control production of reconstituted bamboo, improving its preservation and insect control quality, and enhancing the overall quality of reconstituted bamboo production.

[0004] In view of the above problems, this application provides an optimized control method and system for corrosion and insect prevention in the production and processing of reconstituted bamboo.

[0005] In a first aspect, this application provides a method for optimizing the anti-corrosion and insect-proofing control of reconstituted bamboo production and processing. The method is applied to an optimization control system for the anti-corrosion and insect-proofing control of reconstituted bamboo production and processing. The method includes: acquiring model information of the target reconstituted bamboo to be optimized for anti-corrosion and insect-proofing, wherein the model information includes type, size, and moisture content; constructing a reconstituted bamboo curing process database, inputting the model information into the database to obtain a range of curing process parameters; constructing a loss function and constraints for optimizing the anti-corrosion and insect-proofing of the target reconstituted bamboo based on the model information; combining the range of curing process parameters with the range of pressure impregnation process parameters for anti-corrosion and insect-proofing treatment of the target reconstituted bamboo to obtain an optimized range of process parameters; optimizing the curing process parameters and pressure impregnation process parameters within the optimized range of process parameters based on the loss function and constraints to obtain optimal process parameters, wherein the process parameters are adjusted and optimized using multiple step sizes during the optimization process; and using the optimal process parameters for production control of curing and pressure impregnation anti-corrosion and insect-proofing treatment of the target reconstituted bamboo.

[0006] Secondly, this application also provides an anti-corrosion and insect-proof optimization control system for the production and processing of reconstituted bamboo. The system includes: a model information acquisition module, used to acquire model information of the target reconstituted bamboo to be optimized for anti-corrosion and insect-proofing, wherein the model information includes type, size, and moisture content; a process parameter range acquisition module, used to construct a reconstituted bamboo curing process database, inputting the model information into the database to obtain the curing process parameter range; and a function construction module, used to construct a loss function and constraint conditions for optimizing the anti-corrosion and insect-proofing of the target reconstituted bamboo based on the model information. The system includes: a parameter range combination module, which combines the curing process parameter range with the pressure impregnation process parameter range for preservative and insect-proofing treatment of the target reconstituted bamboo to obtain an optimized process parameter range; a parameter optimization module, which optimizes the curing process parameters and pressure impregnation process parameters within the optimized process parameter range based on the loss function and constraints to obtain the optimal process parameters, wherein the process parameters are adjusted and optimized through multiple step sizes during the optimization process; and a production control module, which controls the production of the target reconstituted bamboo for curing and pressure impregnation preservative and insect-proofing treatment using the optimal process parameters.

[0007] One or more technical solutions provided in this application have at least the following technical effects or advantages:

[0008] The model information of the target reconstituted bamboo to be optimized for anti-corrosion and insect-proofing is input into the reconstituted bamboo curing process database to obtain the curing process parameter range. This range is then combined with the pressure impregnation process parameter range for anti-corrosion and insect-proofing treatment of the target reconstituted bamboo to obtain the optimized process parameter range. Based on the loss function and constraints, the curing and pressure impregnation process parameters are optimized within the optimized range to obtain the optimal process parameters. These optimal process parameters are then used for production control of the curing and pressure impregnation anti-corrosion and insect-proofing treatment of the target reconstituted bamboo. This achieves the technical effect of improving the accuracy of anti-corrosion and insect-proofing production control of reconstituted bamboo, improving its anti-corrosion and insect-proofing quality, and enhancing the overall production quality of reconstituted bamboo.

[0009] The above description is only an overview of the technical solution of this application. In order to better understand the technical means of this application and to implement it in accordance with the contents of the specification, and to make the above and other objects, features and advantages of this application more obvious and understandable, the following are specific embodiments of this application. Attached Figure Description

[0010] To more clearly illustrate the technical solutions of the embodiments of this application, the accompanying drawings of the embodiments of this application will be briefly described below. Obviously, the drawings described below only relate to some embodiments of this application, and are not intended to limit this application.

[0011] Figure 1 This is a flowchart illustrating an optimized control method for corrosion and insect prevention in the production and processing of reconstituted bamboo, as described in this application.

[0012] Figure 2 This is a flowchart illustrating the process of obtaining the model information of the target reconstituted bamboo to be optimized for anti-corrosion and insect prevention in the anti-corrosion and insect prevention optimization control method for the production and processing of reconstituted bamboo according to this application.

[0013] Figure 3 This is a schematic diagram of the structure of an anti-corrosion and insect-proof optimized control system for the production and processing of reconstituted bamboo according to this application.

[0014] Explanation of reference numerals in the attached diagram: Model information acquisition module 11, process parameter range acquisition module 12, function construction module 13, parameter range combination module 14, parameter optimization module 15, production control module 16. Detailed Implementation

[0015] This application provides an optimized control method and system for the preservation and insect control of reconstituted bamboo production and processing. It solves the technical problem of low accuracy in the preservation and insect control production of reconstituted bamboo in existing technologies, which leads to poor preservation and insect control quality. It achieves the technical effect of improving the accuracy of preservation and insect control production of reconstituted bamboo, improving its preservation and insect control quality, and enhancing the overall quality of reconstituted bamboo production.

[0016] Example 1

[0017] Please see the appendix Figure 1 This application provides an optimized control method for corrosion and insect control in the production and processing of reconstituted bamboo. The method is applied to an optimized control system for corrosion and insect control in the production and processing of reconstituted bamboo, and specifically includes the following steps:

[0018] Step S100: Obtain the model information of the target reconstituted bamboo to be optimized for anti-corrosion and insect prevention, wherein the model information includes type, size and moisture content;

[0019] Further details are attached. Figure 2 As shown, step S100 of this application further includes:

[0020] Step S110: Collect information on bamboo species, size, and moisture content of the target reconstituted bamboo to be optimized for anti-corrosion and insect prevention;

[0021] Step S120: Integrate the bamboo type information, size information and moisture content information to form the model information.

[0022] Specifically, the system connects to the aforementioned anti-corrosion and insect-proof optimization control system for the production and processing of reconstituted bamboo. It collects information on the bamboo species, dimensions, and moisture content of the target reconstituted bamboo to be optimized for anti-corrosion and insect-proofing. This information is then integrated to obtain model information. The target reconstituted bamboo is any reconstituted bamboo subject to intelligent anti-corrosion and insect-proofing production control using the aforementioned system. The bamboo species information includes multiple bamboo species parameters corresponding to the target reconstituted bamboo to be optimized for anti-corrosion and insect-proofing. For example, these parameters may include moso bamboo, purple bamboo, and water bamboo. The dimensions include the length, width, and thickness corresponding to each bamboo species parameter. The moisture content information includes the moisture content parameter corresponding to each bamboo species parameter. The model information includes the species, dimensions, and moisture content.

[0023] For example, when integrating bamboo species, size, and moisture content information, the bamboo species, size, and moisture content information are standardized to obtain model information. Standardization refers to eliminating the dimensions of the bamboo species, size, and moisture content information, transforming them into dimensionless pure numerical values.

[0024] The technology achieved the goal of collecting model information of reconstituted bamboo for optimization of anti-corrosion and insect prevention, providing data support for subsequent production control of anti-corrosion and insect prevention of reconstituted bamboo.

[0025] Step S200: Construct a reconstituted bamboo curing process database, input the model information into the reconstituted bamboo curing process database, and obtain the curing process parameter range;

[0026] Furthermore, step S200 of this application also includes:

[0027] Step S210: Retrieve and extract data from various recombinant bamboos to obtain a sample type information set, wherein the sample type information set includes a sample type information set, a sample size information set, and a sample moisture content information set;

[0028] Step S220: Retrieve and extract data on the solidification process of reconstituted bamboo to obtain a set of sample solidification process parameter ranges. Each sample solidification process parameter range in the set of sample solidification process parameter ranges includes the sample drying moisture content range, the sample solidification temperature range, and the sample solidification time range.

[0029] Step S230: Based on type, size and moisture content, construct three index attribute information; based on the sample type information set, sample size information set and sample moisture content information set, construct three index value sets.

[0030] Step S240: Using the set of sample curing process parameter ranges, construct multiple index elements;

[0031] Step S250: Construct the index relationship between the three sets of index values ​​and the multiple index elements to obtain the reconstituted bamboo solidification process database.

[0032] Specifically, the system connects to an optimized control system for the production and processing of reconstituted bamboo, collecting historical data on various types of reconstituted bamboo to obtain a sample model information set. The sample model information set includes a sample type information set, a sample size information set, and a sample moisture content information set. The sample type information set includes multiple historical bamboo species parameters corresponding to each historical reconstituted bamboo. The sample size information set includes the length, width, and thickness corresponding to each historical bamboo species parameter in the sample type information set. The sample moisture content information set includes the historical moisture content parameter corresponding to each historical bamboo species parameter in the sample type information set.

[0033] Furthermore, the system connects to the anti-corrosion and insect-proof optimization control system for the production and processing of reconstituted bamboo, collects historical curing processing data of multiple historical reconstituted bamboos corresponding to the sample model information set, and obtains a set of sample curing process parameter ranges. The set of sample curing process parameter ranges includes multiple sample curing process parameter ranges corresponding to multiple historical reconstituted bamboos in the sample model information set. Each sample curing process parameter range includes the sample drying moisture content range, sample curing temperature range, and sample curing time range of the historical reconstituted bamboo corresponding to the sample model information set. Then, type, size, and moisture content are set as three indexed attribute information. The sample type information set, sample size information set, and sample moisture content information set within the sample model information set are set as three sets of index values ​​corresponding to the three indexed attribute information. Multiple sample curing process parameter ranges within the set of sample curing process parameter ranges are set as multiple index elements. The correspondence between the sample model information set and the set of sample curing process parameter ranges is set as an index relationship.

[0034] Furthermore, according to the indexing relationship, the three sets of index values ​​corresponding to the three indexed attribute information, along with multiple index elements, are arranged to obtain a reconstituted bamboo curing process database. Model information is used as input information and entered into the reconstituted bamboo curing process database to obtain the curing process parameter range. The reconstituted bamboo curing process database includes the three sets of index values ​​corresponding to the three indexed attribute information arranged according to the indexing relationship, and multiple index elements. The curing process parameter range includes the drying moisture content range, curing temperature range, and curing time range corresponding to the model information. This achieves the technical effect of improving the comprehensiveness of production control for the anti-corrosion and insect-proofing of reconstituted bamboo by analyzing the curing process parameters of model information through the reconstituted bamboo curing process database and obtaining the curing process parameter range.

[0035] Step S300: Based on the model information, construct the loss function and constraints for optimizing the anti-corrosion and insect-proof properties of the target reconstituted bamboo;

[0036] Furthermore, step S300 of this application also includes:

[0037] Step S310: Based on the model information, construct a loss function for optimizing the anti-corrosion and insect-proof properties of the target reconstituted bamboo, as shown in the following formula:

[0038]

[0039] Where L represents the gradient of the process parameters, ω1 and ω2 are weights, and P represents the number of mold species involved in the corrosion of the target reconstituted bamboo. S represents the weight of the i-th mold species. i Let be the percentage of the target reconstituted bamboo area contaminated by corrosion under the mold test of the i-th mold species. Let be the mass loss rate of the target reconstituted bamboo due to corrosion and contamination under the test of the i-th type of mold, and Q be the number of pest species that corrode the target reconstituted bamboo. Let be the weight of the j-th pest species. Let C be the mass loss rate of the target recombinant bamboo due to corrosion and contamination under the pest test of the j-th pest species, and T be the time of the process parameters.

[0040] Step S320: With S i Not exceeding the contaminated area threshold, and The constraint condition is that the quality loss rate does not exceed the threshold.

[0041] Specifically, the loss function is:

[0042]

[0043] Where L is the gradient of the output process parameters, ω1 and ω2 are the weights pre-set and determined by the anti-corrosion and insect-proof optimization control system for the production and processing of reconstituted bamboo, and P is the number of mold species that corrode the target reconstituted bamboo. S represents the weight of the i-th type of mold, pre-set and determined by the anti-corrosion and insect-proof optimization control system for the production and processing of reconstituted bamboo. i Let be the percentage of the target reconstituted bamboo area contaminated by corrosion under the mold test of the i-th mold species. Let be the mass loss rate of the target reconstituted bamboo due to corrosion and contamination under the test of the i-th type of mold, and Q be the number of pest species that corrode the target reconstituted bamboo. The weight of the j-th pest species is pre-set and determined by the anti-corrosion and insect-proof optimization control system for the production and processing of reconstituted bamboo. Let C be the mass loss rate of the target reconstituted bamboo due to corrosion and contamination under the pest test of the j-th pest species, and T be the time of the process parameters.

[0044] The constraints include: S i Not exceeding the contaminated area threshold, and The contamination area threshold shall not exceed the mass loss rate threshold. The contamination area threshold includes the percentage of the target reconstituted bamboo contaminated by corrosion under a mold test for the i-th type of mold, pre-set and determined by the anti-corrosion and insect-proof optimization control system for reconstituted bamboo production and processing. The mass loss rate threshold is also pre-set and determined by the anti-corrosion and insect-proof optimization control system for reconstituted bamboo production and processing. For example, the contamination area threshold is 10%, and the mass loss rate threshold is 5%. and The weighting can be determined based on the number of times the target reconstituted bamboo has been corroded by various types of mold and pests.

[0045] Step S400: Combine the curing process parameter range with the pressure impregnation process parameter range for preservative and insect-proof treatment of the target reconstituted bamboo to obtain an optimized process parameter range;

[0046] Step S500: Based on the loss function and constraints, optimize the curing process parameters and pressure impregnation process parameters within the optimized process parameter range to obtain the optimal process parameters. During the optimization process, the process parameters are adjusted and optimized using multiple step sizes.

[0047] Furthermore, step S500 of this application also includes:

[0048] Step S510: Within the range of optimized process parameters, first process parameters are randomly generated, and the first process parameters are tested. When the constraints are met, the first gradient is calculated based on the loss function.

[0049] Step S520: With a preset step size and a preset quantity K, randomly adjust and test any process parameter among the multiple curing process parameters and pressure impregnation process parameters in the first process parameters to obtain K second process parameters that satisfy the constraints, and calculate K second gradients based on the loss function, where K is an integer greater than 1;

[0050] Specifically, the system connects to the anti-corrosion and insect-proofing optimization control system for the production and processing of reconstituted bamboo, and collects the range of pressure impregnation process parameters. These parameters include historical ranges of anti-corrosion and insect-proofing agents, historical pressure times, historical impregnation pressures, historical drying temperatures, and historical drying times for multiple historical reconstituted bamboo treatments. The curing process parameter range and the pressure impregnation process parameter range are then set as the optimized process parameter range.

[0051] Furthermore, random values ​​are selected within the optimized process parameter range to obtain the first process parameter, which is then tested to obtain the first test result. When the first test result meets the constraints, it is input into the loss function to obtain the first gradient. The first process parameter includes multiple curing process parameters and pressure impregnation process parameters. The multiple curing process parameters include a random drying moisture content, a random curing temperature, and a random curing time within the optimized process parameter range. The pressure impregnation process parameters include a random concentration of preservative and insecticide, a random pressure time, a random impregnation pressure, a random drying temperature, and a random drying time within the optimized process parameter range. The first test result includes the area ratio and mass loss rate of the target reconstituted bamboo corroded and contaminated under different mold species tests, the mass loss rate of the target reconstituted bamboo corroded and contaminated under different pest species tests, as well as the test cost and test time.

[0052] Furthermore, based on a preset step size and a preset quantity K, any process parameter in the first process parameters is randomly adjusted and tested to obtain K second process parameters that satisfy the constraints, and K second gradients are calculated based on the loss function. The preset step size includes the proportion of the adjusted process parameters pre-set by the anti-corrosion and insect-proof optimization control system for reconstituted bamboo production and processing. For example, if the preset step size is 5%, then any process parameter in the first process parameters is reduced by 5% or increased by 5%, such as increasing the impregnation pressure from 1.0 MPa to 1.05 MPa. The preset quantity K is pre-set by the anti-corrosion and insect-proof optimization control system for reconstituted bamboo production and processing. Furthermore, K is an integer greater than 1, for example, any integer between 5 and 20.

[0053] Step S530: Adjust the preset step size and preset quantity according to the K second gradients and the first gradient to obtain K adjustment step sizes and K adjustment quantities;

[0054] Furthermore, step S530 of this application also includes:

[0055] Step S531: Calculate the mean of the K second gradients to obtain the mean of the second gradient, and calculate the mean of the second gradient and the mean of the first gradient to obtain the real-time gradient mean;

[0056] Step S532: Calculate the ratio of each second gradient to the real-time gradient mean, adjust the preset number K to obtain the K adjustment numbers, wherein the K adjustment numbers are greater than or equal to the minimum adjustment number and less than or equal to the maximum adjustment number;

[0057] Step S533: Calculate the reciprocal of the ratio of each second gradient to the mean of the real-time gradient, adjust the preset step size to obtain the K adjustment step sizes, wherein the K adjustment step sizes are greater than or equal to the minimum adjustment step size and less than or equal to the maximum adjustment step size.

[0058] Step S540: Based on the K adjustment step sizes and K adjustment quantities, randomly adjust and test any process parameter within the K second process parameters to obtain a set of K third process parameters that satisfy the constraints.

[0059] Step S550: Continue iterative optimization until the preset number of iterations is reached. Output the process parameter with the largest gradient during the optimization process to obtain the optimal process parameter.

[0060] Step S600: Production control of solidification and pressure impregnation for anti-corrosion and insect prevention treatment of the target reconstituted bamboo using the optimal process parameters.

[0061] Specifically, the mean of K second gradients is set as the second gradient mean. The mean between the second gradient mean and the first gradient mean is set as the real-time gradient mean. Then, the ratio of each second gradient to the real-time gradient mean is calculated to obtain K second gradient mean ratios. Based on these K second gradient mean ratios, a preset quantity K is adjusted to obtain K adjustment quantities. The K second gradient mean ratios include the ratio between each second gradient and the real-time gradient mean. The K adjustment quantities include the product of each second gradient mean ratio and the preset quantity K. The K adjustment quantities are greater than or equal to the minimum adjustment quantity and less than or equal to the maximum adjustment quantity. The minimum adjustment quantity is 1. The maximum adjustment quantity includes all possible permutations and combinations when adjusting various curing process parameters and various pressure impregnation process parameters within the curing process parameter range. Then, the preset step size is adjusted based on the reciprocal of the ratio of each second gradient to the real-time gradient mean to obtain K adjustment step sizes. Each adjustment step size includes the product of the reciprocal of the ratio of each second gradient to the real-time gradient mean and the preset step size. The K adjustment step sizes are greater than or equal to the minimum adjustment step size and less than or equal to the maximum adjustment step size. The minimum and maximum adjustment step sizes are pre-set and determined by the aforementioned anti-corrosion and insect-proof optimization control system for the production and processing of reconstituted bamboo.

[0062] Furthermore, based on K adjustment step sizes and K adjustment quantities, any process parameter within the K second process parameters is randomly adjusted and tested to obtain a set of K third process parameters that satisfy the constraints. Iterative optimization continues based on the K third process parameter sets until a preset number of iterations is reached. The process parameter with the largest gradient during the optimization process is output as the optimal process parameter, and production control for curing and pressure impregnation for anti-corrosion and insect prevention treatment of the target reconstituted bamboo is performed based on the optimal process parameter. The preset number of iterations includes a threshold for the number of iterations determined in advance by the anti-corrosion and insect prevention optimization control system for reconstituted bamboo production and processing. The optimal process parameter includes the process parameter with the largest gradient during the optimization process when the preset number of iterations is reached. The iterative optimization based on the K third process parameter sets is performed in the same way as obtaining the K third process parameter sets, and will not be repeated here for the sake of brevity. This achieves the technical effect of improving the accuracy of anti-corrosion and insect prevention production control of reconstituted bamboo by using optimal process parameters for curing and pressure impregnation for anti-corrosion and insect prevention treatment.

[0063] Furthermore, step S540 of this application also includes:

[0064] Step S541: Obtain the minimum value among the K second gradients and add it to the tabu list without further optimization;

[0065] Step S542: Obtain the maximum value within the K second gradients, and use the minimum adjustment step size and the maximum adjustment quantity to adjust and optimize the second process parameters corresponding to the maximum value within the K second gradients.

[0066] Specifically, the minimum value among the K second gradients is added to a tabu list. Data in the tabu list is not further optimized. Then, the maximum value among the K second gradients is selected. The second process parameter corresponding to the maximum value among the K second gradients is adjusted and optimized using the minimum adjustment step size and the maximum adjustment quantity. The second process parameter corresponding to the maximum value among the K second gradients is the better process parameter among the K second process parameters.

[0067] There may be better process parameters nearby, so we reduce the step size and increase the number of adjustments to find the globally optimal process parameters more precisely, thus improving the optimization accuracy. The optimization of the second process parameters corresponding to the maximum values ​​within the K second gradients using the minimum adjustment step size and the maximum adjustment number is done in the same way as obtaining the set of K third process parameters, and will not be elaborated further here for the sake of brevity.

[0068] In summary, the anti-corrosion and insect-proofing optimization control method for the production and processing of reconstituted bamboo provided in this application has the following technical effects:

[0069] 1. Input the model information of the target reconstituted bamboo to be optimized for anti-corrosion and insect-proofing into the reconstituted bamboo curing process database to obtain the curing process parameter range; combine the curing process parameter range with the pressure impregnation process parameter range for anti-corrosion and insect-proofing treatment of the target reconstituted bamboo to obtain the optimized process parameter range; based on the loss function and constraints, optimize the curing process parameters and pressure impregnation process parameters within the optimized process parameter range to obtain the optimal process parameters, and use the optimal process parameters for production control of curing and pressure impregnation anti-corrosion and insect-proofing treatment of the target reconstituted bamboo. This achieves the technical effect of improving the accuracy of anti-corrosion and insect-proofing production control of reconstituted bamboo, improving the anti-corrosion and insect-proofing quality of reconstituted bamboo, and enhancing the production quality of reconstituted bamboo.

[0070] 2. By analyzing the curing process parameters of the reconstituted bamboo through the reconstituted bamboo curing process database, the range of curing process parameters can be obtained, thereby improving the comprehensiveness of the production control of reconstituted bamboo for anti-corrosion and insect prevention.

[0071] Example 2

[0072] Based on the aforementioned embodiment of the optimized control method for corrosion and insect prevention in the production and processing of reconstituted bamboo, and using the same inventive concept, this invention also provides an optimized control system for corrosion and insect prevention in the production and processing of reconstituted bamboo. Please refer to the appendix. Figure 3 The system includes:

[0073] Model information acquisition module 11, the model information acquisition module 11 is used to acquire the model information of the target reconstituted bamboo to be optimized for anti-corrosion and insect prevention, wherein the model information includes type, size and moisture content;

[0074] Process parameter range acquisition module 12 is used to construct a reconstituted bamboo curing process database, input the model information into the reconstituted bamboo curing process database, and obtain the curing process parameter range.

[0075] Function construction module 13 is used to construct a loss function and constraints for optimizing the anti-corrosion and anti-insect properties of the target recombinant bamboo based on the model information.

[0076] The parameter range combination module 14 is used to combine the curing process parameter range with the pressure impregnation process parameter range for preserving and preventing insects in the target reconstituted bamboo to obtain an optimized process parameter range.

[0077] The parameter optimization module 15 is used to optimize the curing process parameters and the pressure impregnation process parameters within the range of optimized process parameters according to the loss function and constraints, so as to obtain the optimal process parameters. In the optimization process, the process parameters are adjusted and optimized through multiple step sizes.

[0078] The production control module 16 is used to control the production of the target reconstituted bamboo by using the optimal process parameters for curing and pressure impregnation for anti-corrosion and anti-insect treatment.

[0079] Furthermore, the system also includes:

[0080] The information acquisition module is used to collect information on the bamboo species, size, and moisture content of the target reconstituted bamboo to be optimized for anti-corrosion and insect prevention.

[0081] An integration module is used to integrate the bamboo type information, size information, and moisture content information as the model information.

[0082] Furthermore, the system also includes:

[0083] The retrieval and extraction module is used to retrieve and extract data from various recombinant bamboos to obtain a sample type information set, wherein the sample type information set includes a sample type information set, a sample size information set, and a sample moisture content information set.

[0084] The sample curing process parameter range set acquisition module is used to retrieve and extract data on the curing process of reconstituted bamboo to obtain a sample curing process parameter range set. Each sample curing process parameter range in the sample curing process parameter range set includes the sample drying moisture content range, the sample curing temperature range, and the sample curing time range.

[0085] An index value set construction module is used to construct three index attribute information based on type, size, and moisture content, and to construct three index value sets based on the sample type information set, sample size information set, and sample moisture content information set.

[0086] An index element construction module is used to construct multiple index elements using the set of sample solidification process parameter ranges.

[0087] The first execution module is used to construct the index relationship between the three sets of index values ​​and the multiple index elements to obtain the reconstituted bamboo solidification process database.

[0088] Furthermore, the system also includes:

[0089] The loss function construction module is used to construct a loss function for optimizing the anti-corrosion and insect-proof properties of the target reconstituted bamboo based on the model information, as shown in the following formula:

[0090]

[0091] Where L represents the gradient of the process parameters, ω1 and ω2 are weights, and P represents the number of mold species involved in the corrosion of the target reconstituted bamboo. S represents the weight of the i-th mold species. i Let be the percentage of the target reconstituted bamboo area contaminated by corrosion under the mold test of the i-th mold species. Let be the mass loss rate of the target reconstituted bamboo due to corrosion and contamination under the test of the i-th type of mold, and Q be the number of pest species that corrode the target reconstituted bamboo. Let be the weight of the j-th pest species. Let C be the mass loss rate of the target recombinant bamboo due to corrosion and contamination under the pest test of the j-th pest species, and T be the time of the process parameters.

[0092] The constraint determination module is used to determine the constraint conditions using S. i Not exceeding the contaminated area threshold, and The constraint condition is that the quality loss rate does not exceed the threshold.

[0093] Furthermore, the system also includes:

[0094] The first gradient acquisition module is used to randomly generate first process parameters within the range of the optimized process parameters, test the first process parameters, and calculate and obtain the first gradient based on the loss function when the constraint conditions are met.

[0095] The second execution module is used to randomly adjust and test any process parameter among multiple curing process parameters and pressure impregnation process parameters in the first process parameters with a preset step size and a preset number K, to obtain K second process parameters that satisfy the constraints, and to calculate K second gradients based on the loss function, where K is an integer greater than 1.

[0096] The third execution module is used to adjust the preset step size and preset quantity according to the K second gradients and the first gradient to obtain K adjustment step sizes and K adjustment quantities;

[0097] The third process parameter set acquisition module is used to randomly adjust and test any process parameter within the K second process parameters based on the K adjustment step sizes and K adjustment quantities to obtain a set of K third process parameters that satisfy the constraints.

[0098] The optimal process parameter acquisition module is used to continue iterative optimization until a preset number of iterations is reached, and outputs the process parameter with the largest gradient during the optimization process to obtain the optimal process parameter.

[0099] Furthermore, the system also includes:

[0100] A real-time gradient mean acquisition module is used to calculate the mean of the K second gradients, obtain the second gradient mean, and calculate the mean of the second gradient and the mean of the first gradient to obtain the real-time gradient mean.

[0101] The adjustment quantity acquisition module is used to calculate the ratio of each second gradient to the real-time gradient mean, perform adjustment calculations on the preset quantity K, and obtain the K adjustment quantities, wherein the K adjustment quantities are greater than or equal to the minimum adjustment quantity and less than or equal to the maximum adjustment quantity;

[0102] The adjustment step size acquisition module is used to calculate the reciprocal of the ratio of each second gradient to the mean of the real-time gradient, and to adjust the preset step size to obtain the K adjustment step sizes, wherein the K adjustment step sizes are greater than or equal to the minimum adjustment step size and less than or equal to the maximum adjustment step size.

[0103] Furthermore, the system also includes:

[0104] The fourth execution module is used to obtain the minimum value among the K second gradients and add it to the tabu list without performing subsequent optimization.

[0105] The adjustment and optimization module is used to obtain the maximum value within the K second gradients, and to adjust and optimize the second process parameters corresponding to the maximum value within the K second gradients using the minimum adjustment step size and the maximum adjustment quantity.

[0106] The anti-corrosion and insect-proof optimization control system for the production and processing of reconstituted bamboo provided in this embodiment of the invention can execute the anti-corrosion and insect-proof optimization control method for the production and processing of reconstituted bamboo provided in any embodiment of the invention, and has the corresponding functional modules and beneficial effects of the execution method.

[0107] The modules included are divided according to functional logic, but are not limited to the above division, as long as they can achieve the corresponding functions; in addition, the specific names of each functional module are only for easy distinction between each other and are not used to limit the scope of protection of this invention.

[0108] This application provides a method for optimizing the anti-corrosion and insect-proofing control in the production and processing of reconstituted bamboo. The method is applied to an optimized control system for the production and processing of reconstituted bamboo. The method includes: inputting the model information of the target reconstituted bamboo to be optimized for anti-corrosion and insect-proofing into a reconstituted bamboo curing process database to obtain a range of curing process parameters; combining the range of curing process parameters with the range of pressure impregnation process parameters for anti-corrosion and insect-proofing treatment of the target reconstituted bamboo to obtain an optimized range of process parameters; optimizing the curing process parameters and pressure impregnation process parameters within the optimized range of process parameters according to a loss function and constraints to obtain optimal process parameters; and using the optimal process parameters to control the production of curing and pressure impregnation anti-corrosion and insect-proofing treatment of the target reconstituted bamboo. This solves the technical problem of low accuracy in the anti-corrosion and insect-proofing production control of reconstituted bamboo in the prior art, leading to poor anti-corrosion and insect-proofing quality of reconstituted bamboo. It achieves the technical effect of improving the accuracy of anti-corrosion and insect-proofing production control of reconstituted bamboo, improving the anti-corrosion and insect-proofing quality of reconstituted bamboo, and enhancing the overall production quality of reconstituted bamboo.

[0109] Note that the above description is merely a preferred embodiment of the present invention and the technical principles employed. Those skilled in the art will understand that the present invention is not limited to the specific embodiments described herein, and various obvious changes, readjustments, and substitutions can be made without departing from the scope of protection of the present invention. Therefore, although the present invention has been described in detail through the above embodiments, the present invention is not limited to the above embodiments, and may include many other equivalent embodiments without departing from the concept of the present invention, the scope of which is determined by the scope of the appended claims.

Claims

1. A method for optimized control of corrosion and insect prevention in the production and processing of reconstituted bamboo, characterized in that, The method includes: Obtain the model information of the target reconstituted bamboo to be optimized for anti-corrosion and insect prevention, wherein the model information includes type, size and moisture content; A database of reconstituted bamboo curing processes is constructed, and the model information is input into the database of reconstituted bamboo curing processes to obtain the range of curing process parameters; Based on the model information, construct the loss function and constraints for optimizing the anti-corrosion and insect-proof properties of the target recombinant bamboo; The range of curing process parameters is combined with the range of pressure impregnation process parameters for preserving and preventing insects in the target reconstituted bamboo to obtain an optimized range of process parameters. Based on the loss function and constraints, the curing process parameters and pressure impregnation process parameters are optimized within the range of optimized process parameters to obtain the optimal process parameters. During the optimization process, the process parameters are adjusted and optimized through multiple step sizes. The production control of the target reconstituted bamboo for curing and pressure impregnation for anti-corrosion and insect prevention is carried out using the aforementioned optimal process parameters; Based on the model information, a loss function and constraints are constructed to optimize the anti-corrosion and insect-resistant properties of the target reconstituted bamboo, including: Based on the model information, a loss function for optimizing the anti-corrosion and insect-resistant properties of the target reconstituted bamboo is constructed, as follows: ; in, For the gradient of process parameters, and Let P be the number of mold species involved in the corrosion of the target reconstituted bamboo, and let P be the weight. Let i be the weight of the i-th mold species. Let be the percentage of the target reconstituted bamboo area contaminated by corrosion under the mold test of the i-th mold species. Let be the mass loss rate of the target reconstituted bamboo due to corrosion and contamination under the test of the i-th type of mold, and Q be the number of pest species that corrode the target reconstituted bamboo. Let be the weight of the j-th pest species. The mass loss rate of the target reconstituted bamboo due to corrosion and contamination under the pest test of the j-th pest species. Let T be the cost of the process parameters, and T be the time required for the process parameters. by Not exceeding the pollution area threshold, and The constraint condition is that the quality loss rate does not exceed the threshold.

2. The method according to claim 1, characterized in that, Obtain the model information of the target reconstituted bamboo for which anti-corrosion and insect-proofing optimization is to be performed, including: Collect information on bamboo species, size, and moisture content of the target recombinant bamboo to be optimized for anti-corrosion and insect-proofing. The information on bamboo species, size, and moisture content is integrated to form the model information.

3. The method according to claim 1, characterized in that, Construct a database of reconstituted bamboo curing processes, including: Data from various recombinant bamboos are retrieved and extracted to obtain a sample type information set, which includes a sample type information set, a sample size information set, and a sample moisture content information set. Data on the solidification process of reconstituted bamboo is retrieved and extracted to obtain a set of sample solidification process parameter ranges. Each sample solidification process parameter range in the set of sample solidification process parameter ranges includes the sample drying moisture content range, the sample solidification temperature range, and the sample solidification time range. Based on type, size, and moisture content, three index attribute information is constructed, and based on the sample type information set, sample size information set, and sample moisture content information set, three index value sets are constructed. Multiple index elements are constructed using the set of sample curing process parameter ranges; Construct the index relationships between the three sets of index values ​​and the multiple index elements to obtain the reconstituted bamboo curing process database.

4. The method according to claim 1, characterized in that, Based on the loss function and constraints, within the optimized process parameter range, the curing process parameters and pressure impregnation process parameters are optimized to obtain the optimal process parameters, including: Within the range of optimized process parameters, first process parameters are randomly generated, and the first process parameters are tested. When the constraints are met, the first gradient is calculated based on the loss function. With a preset step size and a preset quantity K, any process parameter among the multiple curing process parameters and pressure impregnation process parameters in the first process parameters is randomly adjusted and tested to obtain K second process parameters that satisfy the constraints. Based on the loss function, K second gradients are calculated, where K is an integer greater than 1. Based on the K second gradients and the first gradient, the preset step size and preset quantity are adjusted to obtain K adjustment step sizes and K adjustment quantities; Based on the K adjustment step sizes and K adjustment quantities, any process parameter within the K second process parameters is randomly adjusted and tested to obtain a set of K third process parameters that satisfy the constraints. Continue iterative optimization until the preset number of iterations is reached. Output the process parameter with the largest gradient during the optimization process to obtain the optimal process parameter.

5. The method according to claim 4, characterized in that, Based on the K second gradients and the first gradient, the preset step size and preset quantity are adjusted to obtain K adjustment step sizes and K adjustment quantities, including: Calculate the mean of the K second gradients to obtain the mean of the second gradient, and calculate the mean of the second gradient and the mean of the first gradient to obtain the real-time mean of the gradient; Calculate the ratio of each second gradient to the mean of the real-time gradient, and adjust the preset number K to obtain the K adjustment numbers, wherein the K adjustment numbers are greater than or equal to the minimum adjustment number and less than or equal to the maximum adjustment number; Calculate the reciprocal of the ratio of each second gradient to the mean of the real-time gradient, adjust the preset step size to obtain the K adjustment step sizes, wherein the K adjustment step sizes are greater than or equal to the minimum adjustment step size and less than or equal to the maximum adjustment step size.

6. The method according to claim 4, characterized in that, The method further includes: Obtain the minimum value among the K second gradients and add it to the tabu list without further optimization; The maximum value within the K second gradients is obtained, and the second process parameter corresponding to the maximum value within the K second gradients is adjusted and optimized using the minimum adjustment step size and the maximum adjustment quantity.

7. An optimized control system for corrosion and insect prevention in the production and processing of reconstituted bamboo, characterized in that, The system is used to perform the method according to any one of claims 1 to 6, the system comprising: The model information acquisition module is used to acquire the model information of the target reconstituted bamboo to be optimized for anti-corrosion and insect prevention, wherein the model information includes type, size and moisture content; A process parameter range acquisition module is used to construct a reconstituted bamboo curing process database, input the model information into the reconstituted bamboo curing process database, and obtain the curing process parameter range. A function construction module is used to construct a loss function and constraints for optimizing the anti-corrosion and anti-insect properties of the target reconstituted bamboo based on the model information. A parameter range combination module is used to combine the curing process parameter range with the pressure impregnation process parameter range for preserving and preventing insects in the target reconstituted bamboo to obtain an optimized process parameter range. The parameter optimization module is used to optimize the curing process parameters and pressure impregnation process parameters within the optimization process parameter range according to the loss function and constraints, so as to obtain the optimal process parameters. During the optimization process, the process parameters are adjusted and optimized through multiple step sizes. The production control module is used to control the production of the target reconstituted bamboo by using the optimal process parameters for curing and pressure impregnation for anti-corrosion and insect prevention.

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