Design and control method of system for producing PET (Polyethylene Terephthalate) foam board by using bottle flakes

Abstract

The invention provides a design and control method of a system for producing a PET foam board by using bottle flakes, belongs to the field of PET foam board production, is used for solving the problem of high PET foam production cost in related technologies, and realizes the design of the system for producing the PET foam board by using the bottle flakes. The designed system can adapt to the bottle flake attribute parameters and the expected recovery probability of the bottle flakes to be recovered, and has a good overall production effect.

Description

Technical Field

[0001] This application relates to the field of PET foam board production, and particularly to a design and control method for a system for producing PET foam boards using bottle chips. Background Art

[0002] The existing production line for PET foam boards includes a raw material tank, a feeding pipeline, a fan, and a drying oven. Among them, the raw material is PET particles prepared from petroleum. The PET particles are added to the raw material tank, and the fan enables the feeding pipeline to extract the PET particles in the raw material tank. The PET particles are output after passing through the drying oven, and the output PET particles will enter the subsequent extruder, melt and finally form into PET foam boards.

[0003] The cost of PET particles prepared from petroleum is relatively high. The applicant found that there is a kind of recyclable bottle chips on the market that can replace PET particles as the raw material for preparing foam boards. When using the recycled bottle chips to prepare PET foam boards, the existing production line for preparing foam boards with PET particles cannot be directly used. The applicant needs to design a production line suitable for producing PET foam boards with bottle chips, and then realize the work of producing PET foam boards with bottle chips. Summary of the Invention

[0004] This application provides a design and control method for a system for producing PET foam boards with bottle chips, which can reasonably design the production line to support the realization of the work of producing PET foam boards with bottle chips.

[0005] In a first aspect, this application provides a design method for a system for producing PET foam boards with bottle chips. The method includes:

[0006] Obtaining the bottle chip attribute parameter group of the bottle chips to be recycled and the expected recycling probability of each bottle chip attribute parameter group;

[0007] Substituting each bottle chip attribute parameter group into a pre-constructed production process simulation model to obtain a production effect parameter group under each production system parameter group;

[0008] Combining the expected recycling probability of the bottle chip attribute parameter group and the production system parameter group corresponding to the optimal production effect parameter group of the bottle chip attribute parameter group to determine the comprehensive effect evaluation value of each bottle chip attribute parameter group;

[0009] Combining a specified number of higher comprehensive effect evaluation values and the preset parameter width range for each system parameter dimension of the relative production system parameter group to analyze and determine the optional system parameter group. The optional system parameter group takes the system parameter value of the corresponding system parameter dimension in one of the production system parameter groups corresponding to the specified number of higher comprehensive effect evaluation values as the center, and the parameter range width of each system parameter dimension is within the corresponding parameter width range;

[0010] Analyze the system design evaluation values of each optional system parameter group, and determine the recommended design scheme among the optional system parameter groups based on the system design evaluation values. The system design evaluation value is positively correlated with the production effect parameter values and the corresponding expected recovery probabilities of the production effect parameter groups that are optimal for each bottle chip attribute parameter group in the optional system parameter group, and is negatively correlated with the system parameter values and the parameter range widths of each system parameter dimension in the optional system parameter group, as well as the system parameter group gap value between the optional system parameter group and the pre-acquired system reference parameter group.

[0011] By adopting the above technical solution, the design of the system for producing PET foam boards from bottle chips is realized. The designed system can adapt to the bottle chip attribute parameters and the expected recovery probabilities of the bottle chips to be recycled, and has good overall production effects.

[0012] Further, the bottle chip parameter dimensions of the bottle chip attribute parameter group include bottle chip particle size, bottle chip density, and bottle chip humidity;

[0013] The system parameter dimensions of the production system parameter group include the feeding fan power, the inner diameter of the feeding pipeline, and the drying oven power;

[0014] The effect parameter dimensions of the production effect parameter group include the bottle chip conveying speed and the bottle chip drying effect.

[0015] Further, determining the comprehensive effect evaluation value of each bottle chip attribute parameter group by combining the expected recovery probability of the bottle chip attribute parameter group and the production system parameter group corresponding to the production effect parameter group that is optimal for the bottle chip attribute parameter group includes:

[0016] Analyze and determine a production effect parameter value for each production effect parameter group of each bottle chip attribute parameter group. The production effect parameter value is positively correlated with the effect parameter values of each effect parameter dimension in the production effect parameter group;

[0017] Determine the highest production effect parameter value of each bottle chip attribute parameter, and calculate the highest production effect parameter value multiplied by the corresponding expected recovery probability as the comprehensive effect evaluation value.

[0018] Further, the analyzing and determining a production effect parameter value for each production effect parameter group of each bottle chip attribute parameter group, where the production effect parameter value is positively correlated with the effect parameter values of each effect parameter dimension in the production effect parameter group includes:

[0019] Normalize the effect parameter values of all effect parameter dimensions in the production effect parameter group;

[0020] Suppose the production effect parameter group contains effect parameter dimensions, and the effect parameter value of the i-th effect parameter dimension is , if the production effect parameter value is z, then , where is a preset constant, .

[0021] Further, the analysis and determination of the optional system parameter groups by combining a specified number of higher comprehensive effect evaluation values and the preset parameter width ranges for each system parameter dimension of the relative production system parameter group include:

[0022] Sort the comprehensive effect evaluation values from large to small, and select the production system parameter groups corresponding to the top specified number of comprehensive effect evaluation values as the reference system parameter groups;

[0023] Combine the reference system parameter groups and the preset parameter width ranges for each system parameter dimension of the pre-acquired production system parameter groups to determine all optional system parameter groups.

[0024] Further, the analysis of the system design evaluation value of each optional system parameter group includes: for each optional system parameter group,

[0025] Determine the highest production effect parameter value for each bottle sheet attribute parameter group within the optional system parameter group, calculate the product of the production effect parameter value and the expected recovery probability of the corresponding bottle sheet attribute parameter group as the comprehensive effect evaluation value, and analyze and determine the positive evaluation value of the optional system parameter group by combining the comprehensive effect evaluation values of each bottle sheet attribute parameter group;

[0026] Analyze and determine the negative evaluation value of the optional system parameter group by combining the system parameter values and the parameter range widths of each system parameter dimension of the optional system parameter group and the system parameter group gap value between the optional system parameter group and the pre-acquired system reference parameter group;

[0027] Analyze and determine the system design evaluation value of the optional system parameter group by combining the positive evaluation value and the negative evaluation value.

[0028] Further, the analysis of the system design evaluation value of each optional system parameter group includes:

[0029] Suppose there are bottle sheet attribute parameter groups, and the expected recovery probability of the i-th bottle sheet attribute parameter group is , and the highest production effect parameter value determined by the optional system parameter group for the i-th bottle sheet attribute parameter group is , and the positive evaluation value is , then ;

[0030] Suppose the optional system parameter group has system parameter dimensions, and the system parameter value of the i-th system parameter dimension is , is the parameter range width, and the system parameter value of the i-th system parameter dimension of the system reference parameter group is , the negative phase evaluation value is ,but , where 、 、 All are preset constants greater than zero;

[0031] Assume that the system design evaluation value is y, then .

[0032] Furthermore, determining a recommended design solution in the optional system parameter group based on the system design evaluation value includes:

[0033] The optional system parameter group with the highest system design evaluation value is selected as the recommended design scheme.

[0034] Furthermore, determining a recommended design solution in the optional system parameter group based on the system design evaluation value includes:

[0035] Constructing a recommended design solution list, wherein the recommended design solution list can accommodate a preset number of recommended design solutions;

[0036] Constructing a set of optional design solutions, wherein the set of optional design solutions includes all optional system parameter groups;

[0037] The scheme recommendation method is executed cyclically until the recommended design scheme list is full or the set of optional design schemes is empty;

[0038] The scheme recommendation method includes: selecting an optional system parameter group with the highest system design evaluation value from a set of optional design schemes, adding it to the first accommodation position in a recommended design scheme list, and removing the selected optional system parameter group and the optional system parameter group whose difference in system design evaluation value with the selected optional system parameter group is less than a preset evaluation difference threshold from the set of optional design schemes.

[0039] In a second aspect, the present application provides a control method for a system for producing PET foam boards using bottle flakes. The method comprises:

[0040] Obtaining the bottle flake attribute parameter group and bottle flake attribute ratio for each type of bottle flake used in production;

[0041] determining all adjustable production system parameter groups in a pre-acquired production system parameter plan;

[0042] Analyze the production effect parameter values of each production system parameter group for each type of bottle flake attribute parameter;

[0043] Determine the expected production effect value of all bottle flakes used in production based on the proportion of bottle flake attributes;

[0044] Adjust the system to the production system parameter group with the highest expected production effect value.

[0045] In summary, the present application at least includes the following beneficial effects:

[0046] 1. A design and control method for a PET foam board production system using bottle chips is provided, which can realize the design of a PET foam board production system using bottle chips to adapt to the condition of recycled bottle chips and improve the expected production effect;

[0047] 2. The algorithm for specifically determining the production effect parameter value has high compatibility and will not affect the calculation when adding or deleting the effect parameter dimension;

[0048] 3. The algorithm for specifically determining the system design evaluation value has better rationality, which is beneficial to accurately evaluate the optional system parameter group, so as to design a better PET foam board production system using bottle chips.

[0049] It should be understood that the content described in the summary of the invention section is not intended to limit the key or important features of the embodiments of the present application, nor to limit the scope of the present application. Other features of the present application will become easily understood through the following description. BRIEF DESCRIPTION OF THE DRAWINGS

[0050] In combination with the drawings and with reference to the following detailed description, the above and other features, advantages and aspects of the embodiments of the present application will become more obvious. In the drawings, the same or similar reference numerals represent the same or similar elements, where:

[0051] Figure 1 Shows the schematic diagram of the PET foam board production system using bottle chips in the embodiments of the present application;

[0052] Figure 2 Shows the flowchart of a design method for a PET foam board production system using bottle chips in the embodiments of the present application;

[0053] Figure 3 Shows the flowchart of a control method for a PET foam board production system using bottle chips in the embodiments of the present application. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0054] To make the objectives, technical solutions and advantages of the embodiments of the present application clearer, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application. Obviously, the described embodiments are some, but not all, of the embodiments of the present application. All other embodiments obtained by those of ordinary skill in the art without creative efforts based on the embodiments in the present application belong to the scope of protection of the present application.

[0055] In addition, the term "and / or" in this text is merely a description of the association relationship of associated objects, indicating that there can be three relationships. For example, A and / or B can represent three situations: A exists alone, A and B exist simultaneously, and B exists alone. In addition, the character " / " in this text generally indicates that the associated objects before and after are in an "or" relationship.

[0056] The present application provides a design and control method for a PET foam board production system using bottle chips, which can be adapted to the scenario of producing PET foam boards with recycled bottle chips and make the production process meet the production requirements.

[0057] Figure 1 The schematic diagram of the PET foam board production system using bottle chips in the embodiment of the present application is shown.

[0058] Referring to FIG. 1, the PET foam board production system using bottle chips includes a raw material tank, a feeding pipeline, a fan, and a drying oven. The raw material tank is used to hold recycled bottle chips. Under the action of the fan, the bottle chips in the raw material tank are transported through the feeding pipeline and dried in the drying oven, and then transported to subsequent steps such as melting, compaction, and foam board preparation.

[0059] In the embodiment of the present application, the subsequent improvements are mainly aimed at the improvements from the raw material tank to the post-drying process, and do not involve the improvements of other steps. Of course, if the design of other steps is required, the methods disclosed in the present application can be analogized. The steps of realizing the PET production system using bottle chips in the present application are specifically introduced based on the following methods.

[0060] In the first aspect, the embodiment of the present application discloses a design method for a PET foam board production system using bottle chips.

[0061] Figure 2 The flowchart of a design method for a PET foam board production system using bottle chips in the embodiment of the present application is shown.

[0062] Referring to Figure 2 , the design method specifically includes the following steps:

[0063] S210: Obtain the bottle chip attribute parameter group of the bottle chips to be recycled and the expected recycling probability of each bottle chip attribute parameter group.

[0064] In the method of this step, the bottle chip parameter dimensions of the bottle chip attribute parameter group include bottle chip particle size, bottle chip density, and bottle chip humidity. Of course, the evaluation attribute parameter group can also include more bottle chip attribute dimensions, as long as it can reflect the attributes of the recycled bottle chips. In the present application, only the above dimensions are introduced.

[0065] The expected recovery probability can be determined based on data experience and / or expert experience, which reflects the probability of each type of bottle chip being recycled. For example, what proportion of this type of bottle chip exists in the market, so what is the recovery probability of this type of bottle chip during recycling. Of course, the specific method of determining the expected recovery probability of recycled bottle chips is not the specific content discussed in this application, so it will not be elaborated here.

[0066] S220: Substitute each of the bottle chip attribute parameter groups into the pre-constructed production process simulation model to obtain a production effect parameter group under each production system parameter group.

[0067] In the method of this step, the system parameter dimension of the production system parameter group includes the power of the feeding fan, the inner diameter of the feeding pipeline, and the power of the drying box; the effect parameter dimension of the production effect parameter group includes the bottle chip conveying speed and the bottle chip drying effect.

[0068] Under the constraints of production requirements, that is, under the constraints of the feeding fan, the inner diameter of the feeding pipeline, and the air drying power, a production system model can be constructed, and the parameters of the production system model are adjustable. When different bottle chips enter the production system model, the movement law of the bottle chips in the production system model can be simulated based on models such as mechanics and fluid dynamics, and then the conveying efficiency and drying effect can be determined.

[0069] That is, based on the production process simulation model, the production process simulation model can be constructed based on known principle models. Under the production process simulation model, the production effect parameter group can be determined based on the bottle chip attribute parameter group and the production system parameter group.

[0070] S230: Combine the expected recovery probability of the bottle chip attribute parameter group and the production system parameter group corresponding to the optimal production effect parameter group of the bottle chip attribute parameter group to determine the comprehensive effect evaluation value of each bottle chip attribute parameter group.

[0071] The method of this step specifically includes: analyzing and determining a production effect parameter value for each production effect parameter group of each bottle chip attribute parameter group. The production effect parameter value is positively correlated with the effect parameter values of each effect parameter dimension of the production effect parameter group; determining the highest production effect parameter value of each bottle chip attribute parameter, and calculating the highest production effect parameter value multiplied by the corresponding expected recovery probability as the comprehensive effect evaluation value.

[0072] The production effect parameter value can be determined by combining the production effect parameter dimension values of all production effect parameter dimensions of the production effect parameter group, such as by weighted summation or other methods.

[0073] In a specific example, the method of this step specifically includes: normalizing the effect parameter values of all effect parameter dimensions in the production effect parameter group; assuming that the production effect parameter group contains The number of effect parameter dimensions, and the effect parameter value of the i-th effect parameter dimension is , and the production effect parameter value is z, then , where is a preset constant, .

[0074] S240: Analyze and determine the optional system parameter groups by combining a specified number of higher comprehensive effect evaluation values and the preset parameter width ranges for each system parameter dimension of the relative production system parameter groups.

[0075] The optional system parameter groups are centered on the system parameter values of the corresponding system parameter dimensions in one of the production system parameter groups corresponding to a specified number of higher comprehensive effect evaluation values, and the parameter range width of each system parameter dimension is within the corresponding parameter width range.

[0076] In the method of this step, the analysis and determination of the optional system parameter groups by combining a specified number of higher comprehensive effect evaluation values and the preset parameter width ranges for each system parameter dimension of the relative production system parameter groups includes: sorting the comprehensive effect evaluation values from large to small, and selecting the production system parameter groups corresponding to the first specified number of comprehensive effect evaluation values as the reference system parameter groups; determining all optional system parameter groups by combining the reference system parameter groups and the preset parameter width ranges for each system parameter dimension of the pre-acquired production system parameter groups.

[0077] S250: Analyze the system design evaluation values of each optional system parameter group, and determine the recommended design scheme among the optional system parameter groups based on the system design evaluation values.

[0078] The system design evaluation value is positively correlated with the production effect parameter value and the corresponding expected recovery probability of the production effect parameter group that is optimal for each bottle attribute parameter group in the optional system parameter group, and negatively correlated with the system parameter values and parameter range widths of each system parameter dimension of the optional system parameter group and the system parameter group gap value between the optional system parameter group and the pre-acquired system reference parameter group.

[0079] In the method of this step, the system design evaluation value for analyzing each optional system parameter group includes: for each optional system parameter group, determining the highest production effect parameter value for each bottle sheet attribute parameter group within the optional system parameter group, calculating the product of the production effect parameter value and the expected recovery probability of the corresponding bottle sheet attribute parameter group as the comprehensive effect evaluation value, and analyzing and determining the positive evaluation value of the optional system parameter group by combining the comprehensive effect evaluation values of each bottle sheet attribute parameter group; analyzing and determining the negative evaluation value of the optional system parameter group by combining the system parameter values and parameter range widths of each system parameter dimension of the optional system parameter group and the system parameter group gap value between the optional system parameter group and the pre-obtained system reference parameter group; analyzing and determining the system design evaluation value of the optional system parameter group by combining the positive evaluation value and the negative evaluation value.

[0080] In a specific example, the system design evaluation value for analyzing each optional system parameter group includes: assuming there are bottle sheet attribute parameter groups, the expected recovery probability of the i-th bottle sheet attribute parameter group is , the highest production effect parameter value determined by the optional system parameter group for the i-th bottle sheet attribute parameter group is , and the positive evaluation value is , then ; assuming the optional system parameter group has system parameter dimensions, the system parameter value of the i-th system parameter dimension is , is the parameter range width, the system parameter value of the i-th system parameter dimension of the system reference parameter group is , and the negative evaluation value is , then , where , , are all preset constants greater than zero; assuming the system design evaluation value is y, then .

[0081] In an example of the method of this step, determining the recommended design scheme from the optional system parameter groups based on the system design evaluation value includes: selecting the optional system parameter group with the highest system design evaluation value as the recommended design scheme.

[0082] In another example of the method of this step, determining the recommended design scheme from the optional system parameter groups based on the system design evaluation value includes: constructing a recommended design scheme list that can accommodate a preset number of recommended design schemes; constructing a set of optional design schemes that contains all optional system parameter groups; repeatedly executing the scheme recommendation method until the recommended design scheme list is full or the set of optional design schemes is empty;

[0083] The described solution recommendation method includes: selecting, from the set of alternative design solutions, the alternative system parameter group with the highest system design evaluation value, adding it to the earliest accommodating position in the recommended design solution list, and removing from the set of alternative design solutions the selected alternative system parameter group and the alternative system parameter groups whose difference from the system design evaluation value of the selected alternative system parameter group is less than a preset evaluation difference threshold.

[0084] Combining the above content, it is possible to determine how to design the production system parameter solution based on the data experience of recycled bottle chips and the effect constraints expected to be recycled for production, and to ensure that the determined production system solution is reasonable and available, which is beneficial to better production effects.

[0085] It should be noted that for the foregoing method embodiments, for the sake of simple description, they are all expressed as a series of action combinations. However, those skilled in the art should know that this application is not limited by the described action sequence, because according to the embodiments of this application, certain steps can be performed in other sequences or simultaneously. Secondly, those skilled in the art should also know that the embodiments described in the specification are all optional embodiments, and the actions and modules involved are not necessarily essential to this application.

[0086] In a second aspect, an embodiment of this application discloses a control method for a system for producing PET foam boards using bottle chips.

[0087] Figure 3 The flowchart of a control method for a system for producing PET foam boards using bottle chips in an embodiment of this application is shown.

[0088] Referring to Figure 3 , the method includes:

[0089] S310: Obtain the bottle chip attribute parameter group and bottle chip attribute ratio of each type of bottle chip used for production; determine all adjustable production system parameter groups in the pre-obtained production system parameter solutions;

[0090] S320: Analyze the production effect parameter values of each production system parameter group for the bottle chip attribute parameters of each type of bottle chip;

[0091] S330: Determine the expected production effect values of all bottle chips used for production in combination with the bottle chip attribute ratio; adjust the system to the production system parameter group with the highest expected production effect value.

[0092] Among them, the production system parameter solution represents a specific range of production system parameter groups. Each production system parameter group determines a set of definite production system parameter groups. Each definite production system parameter group can determine the expected production effect of each bottle chip attribute parameter group, and then, in combination with all its production effects and the composition probability of the bottle chips, determine the preferred production system parameter group for regulation and determination.

[0093] Those skilled in the art can clearly understand that for the convenience and brevity of description, the specific working process of the described device can refer to the corresponding process in the foregoing method embodiments and will not be elaborated herein.

[0094] In summary, the present application at least includes the following beneficial effects:

[0095] 1. A design and control method for a PET foam board production system using bottle chips is provided, which can realize the design of a PET foam board production system using bottle chips to adapt to the conditions of recycled bottle chips and improve the expected production effect;

[0096] 2. The algorithm for specifically determining the production effect parameter values has high compatibility and will not affect the calculation when adding or deleting the effect parameter dimensions;

[0097] 3. The algorithm for specifically determining the system design evaluation value has better rationality, which is beneficial to accurately evaluate the optional system parameter groups, so as to design a better PET foam board production system using bottle chips.

[0098] The above description is only a preferred embodiment of the present application and an explanation of the applied technical principles. Those skilled in the art should understand that the scope of disclosure involved in the present application is not limited to the technical solutions formed by the specific combination of the above technical features, and should also cover other technical solutions formed by any combination of the above technical features or their equivalent features without departing from the foregoing disclosure concept. For example, the technical solutions formed by mutually replacing the above features with (but not limited to) the technical features having similar functions disclosed in the present application.

Claims

1. A design method for a system for producing PET foam boards from bottle chips, characterized in that, Including: Obtaining a set of bottle chip attribute parameters of the bottle chips to be recycled and the expected recycling probability of each set of bottle chip attribute parameters; Substituting each set of the bottle chip attribute parameters into a pre-constructed production process simulation model to obtain a set of production effect parameters under each set of production system parameters; Determining the comprehensive effect evaluation value of each set of bottle chip attribute parameters by combining the expected recycling probability of the set of bottle chip attribute parameters and the set of production system parameters corresponding to the optimal production effect parameters of the set of bottle chip attribute parameters; Analyzing and determining an optional set of system parameters by combining a specified number of higher comprehensive effect evaluation values and the preset parameter width range for each system parameter dimension of the set of production system parameters. The optional set of system parameters is centered on the system parameter value of the corresponding system parameter dimension in one of the sets of production system parameters corresponding to the specified number of higher comprehensive effect evaluation values, and the parameter range width of each system parameter dimension is within the corresponding parameter width range; Analyzing the system design evaluation value of each optional set of system parameters and determining a recommended design solution among the optional sets of system parameters. The system design evaluation value is positively correlated with the production effect parameter value of the optimal production effect parameter set for each set of bottle chip attribute parameters in the optional set of system parameters and the corresponding expected recycling probability, and is negatively correlated with the system parameter value and the parameter range width of each system parameter dimension of the optional set of system parameters and the system parameter set gap value between the optional set of system parameters and the pre-obtained set of system reference parameters; 2. The method according to claim 1, characterized in that, The bottle chip parameter dimensions of the set of bottle chip attribute parameters include bottle chip particle size, bottle chip density, and bottle chip humidity; The system parameter dimensions of the set of production system parameters include the feeding fan power, the inner diameter of the feeding pipeline, and the drying oven power; The effect parameter dimensions of the set of production effect parameters include the bottle chip conveying speed and the bottle chip drying effect; 3. The method according to claim 1, wherein The determining the comprehensive effect evaluation value of each set of bottle chip attribute parameters by combining the expected recycling probability of the set of bottle chip attribute parameters and the set of production system parameters corresponding to the optimal production effect parameters of the set of bottle chip attribute parameters includes: Analyzing and determining a production effect parameter value for each production effect parameter set of each set of bottle chip attribute parameters. The production effect parameter value is positively correlated with the effect parameter values of each effect parameter dimension of the production effect parameter set; Determining the highest production effect parameter value of each set of bottle chip attributes and calculating the highest production effect parameter value multiplied by the corresponding expected recycling probability as the comprehensive effect evaluation value; 4. The method according to claim 3, characterized in that, The analyzing and determining a production effect parameter value for each production effect parameter set of each set of bottle chip attribute parameters, where the production effect parameter value is positively correlated with the effect parameter values of each effect parameter dimension of the production effect parameter set includes: Normalizing the effect parameter values of all effect parameter dimensions in the production effect parameter set; Suppose the production effect parameter group contains effect parameter dimensions, and the effect parameter value of the i-th effect parameter dimension is . If the production effect parameter value is z, then , where is a preset constant, .

5. The method according to claim 1, wherein The analyzing and determining an optional set of system parameters by combining a specified number of higher comprehensive effect evaluation values and the preset parameter width range for each system parameter dimension of the set of production system parameters includes: Sorting the comprehensive effect evaluation values from largest to smallest, and selecting the sets of production system parameters corresponding to the first specified number of comprehensive effect evaluation values as the reference sets of system parameters; Determine all optional system parameter groups by combining the reference system parameter group and the pre-acquired production system parameter group according to the preset parameter width range of each system parameter dimension.

6. The method according to claim 1, wherein The system design evaluation value for analyzing each optional system parameter group includes: for each optional system parameter group, Determine the highest production effect parameter value for each bottle property parameter group within the optional system parameter group, calculate the product of the production effect parameter value and the expected recovery probability of the corresponding bottle property parameter group as the comprehensive effect evaluation value, and analyze and determine the positive evaluation value of the optional system parameter group by combining the comprehensive effect evaluation values of each bottle property parameter group; Analyze and determine the negative evaluation value of the optional system parameter group by combining the system parameter value and the parameter range width of each system parameter dimension of the optional system parameter group and the system parameter group gap value between the optional system parameter group and the pre-acquired system reference parameter group; Analyze and determine the system design evaluation value of the optional system parameter group by combining the positive evaluation value and the negative evaluation value.

7. The method according to claim 6, characterized in that, The system design evaluation value for analyzing each optional system parameter group includes: Suppose there are sets of bottle chip attribute parameters, and the expected recycling probability of the i-th set of bottle chip attribute parameters is . The highest production effect parameter value determined by the optional system parameter set for the i-th set of bottle chip attribute parameters is , and the positive evaluation value is . Then ; Suppose the optional system parameter group has system parameter dimensions, and the system parameter value of the i-th system parameter dimension is , is the parameter range width, and the system parameter value of the i-th system parameter dimension of the system reference parameter group is , the negative evaluation value is , then , where , , are all preset constants greater than zero; Let the system design evaluation value be y, then .

8. The method according to claim 1, wherein The method for determining the recommended design scheme based on the system design evaluation value in the optional system parameter group includes: Select the optional system parameter group with the highest system design evaluation value as the recommended design scheme.

9. The method according to claim 1, characterized in that, The method for determining the recommended design scheme based on the system design evaluation value in the optional system parameter group includes: Construct a recommended design scheme list, and the recommended design scheme list can accommodate a preset number of recommended design schemes; Construct an optional design scheme set, and the optional design scheme set contains all optional system parameter groups; Loop and execute the scheme recommendation method until the recommended design scheme list is full or the optional design scheme set is empty; The scheme recommendation method includes: select the optional system parameter group with the highest system design evaluation value in the optional design scheme set, add it to the earliest accommodation position in the recommended design scheme list, and remove the selected optional system parameter group and the optional system parameter groups whose difference from the system design evaluation value of the selected optional system parameter group is less than the preset evaluation difference threshold in the optional design scheme set.

10. A control method for a system for producing PET foam boards from bottle flakes, characterized in that, Include: Obtain the bottle property parameter group and the bottle property ratio of each type of bottle used for production; Determine all adjustable production system parameter groups in the pre-acquired production system parameter scheme; Analyze the production effect parameter value of each production system parameter group for the bottle property parameter of each type of bottle; Determine the expected production effect value of all bottles used for production by combining the bottle property ratio; Adjust the system to the production system parameter group with the highest expected production effect value.

Images