Method for reducing gram weight per meter of internal thread copper pipe for air conditioner based on full permutation and combination of parameters

Abstract

The invention relates to the technical field of copper pipe processing, in particular to a method for reducing gram weight per meter of an internal thread copper pipe for an air conditioner based on full permutation and combination of parameters, which comprises the following steps: determining parameter types and setting mass flow; endowing a size research range and the number of values in the size research range corresponding to each type of parameters; obtaining a parameter full permutation and combination total number; selecting a set number of combinations according to the total number, and obtaining parameter values of various types; under the set mass flow rate, the heat exchange value and the pressure drop value of the internal thread copper pipe are correspondingly calculated according to the parameter values of each combination; sorting the parameter values, the heat exchange values and the pressure drop values into a structured table; and determining an optimal parameter combination meeting a gram weight per meter reduction target. Through the technical path of parameter full permutation and combination construction, sampling and structural data analysis, global optimization and multi-target cooperation of the design of the internal threaded copper pipe of the air conditioner can be achieved, and the optimal parameter combination meeting the goal of gram weight per meter can be finally obtained to guide subsequent production.

Description

Technical Field

[0001] The present invention relates to the technical field of copper tube processing, and in particular to a method for reducing the meter-gram weight of an internally threaded copper tube for an air conditioner based on full parameter permutation and combination. Background Art

[0002] In air conditioning manufacturing, internally threaded copper tubes, core components of heat exchangers, have a performance that directly impacts the energy efficiency and cost of air conditioning systems. Meter weight is a key indicator for measuring copper tube material usage. Reducing meter weight not only reduces copper consumption and costs, but also enables lightweight design and enhances product competitiveness. However, existing technologies still face the following prominent issues when optimizing parameters for internally threaded copper tubes:

[0003] Traditional methods typically rely on empirical trial and error or single parameter adjustments, making it difficult to fully consider the coupled effects of multiple parameters such as the number of teeth, helix angle, tooth height, and outer diameter. This local optimization approach easily misses the global optimal solution, resulting in a reduction in weight while sacrificing heat transfer performance or increasing pressure drop, making it impossible to achieve multi-objective collaborative optimization. In addition, the correspondence between parameter combinations and performance indicators is usually stored in different files or systems, making historical data difficult to trace and the optimization process irreproducible. Multi-objective decision-making relies on manual compilation, which is inefficient and prone to errors. After the design constraints are changed, the original data needs to be reprocessed, resulting in a slow response. Summary of the Invention

[0004] The present invention provides a method for reducing the meter weight of internally threaded copper tubes for air conditioners based on full parameter permutation and combination, aiming to solve the problems in the background technology.

[0005] To achieve the above object, the technical solution of the present invention is as follows:

[0006] A method for reducing the meter weight of internally threaded copper tubes for air conditioners based on full parameter permutation and combination, including:

[0007] S1: Determine the parameter type for establishing the full parameter permutation combination and the set mass flow rate of the internally threaded copper pipe;

[0008] S2: Assign a size research range to each type of parameter, as well as the number of values within the size research range;

[0009] S3: Multiply the number of values corresponding to each type of parameter to obtain the total number of all parameter combinations;

[0010] S4: selecting a set number of combinations according to the total number, and obtaining parameter values of various types for the selected combinations;

[0011] S5: Under the set mass flow rate, the heat exchange value and the pressure drop value of the internally threaded copper tube are calculated according to the parameter values of each combination;

[0012] S6: Arranging the parameter values of each combination, as well as the corresponding heat exchange value and pressure drop value into a structured table;

[0013] S7: Perform a comprehensive comparison based on the structured table, and determine the optimal parameter combination that meets the goal of reducing meter weight within the size research range based on the comparison results.

[0014] Furthermore, the set number of said combinations are obtained by overall random sampling;

[0015] Alternatively, a set number of combinations are grouped, and random sampling and combination are performed in each group to obtain the combination.

[0016] Furthermore, the parameter types include at least the number of teeth, helix angle, tooth top angle, tooth height and outer diameter.

[0017] Furthermore, the comprehensive comparison performed according to the structured table includes a preliminary comparison and a secondary comparison. The preliminary comparison is to narrow down the range of combinations according to the secondary comparison. The preliminary comparison includes:

[0018] determining an acceptable range of heat exchange values and pressure drop values based on the structured table;

[0019] The combinations whose heat transfer value and pressure drop value are both within the acceptable range are retained as updated comparison samples, and the remaining combinations are eliminated.

[0020] Furthermore, the secondary comparison includes:

[0021] A combination that can meet the meter weight reduction target is determined in the updated comparison sample, and the meter weight reduction target is reflected by the dimensional limit range of the number of teeth, helix angle, tooth top angle, tooth height and outer diameter.

[0022] Furthermore, the set mass flow rate is selected to be 180-220 kg / (m 2 s);

[0023] The types of parameters mentioned only include the number of teeth, helix angle, tooth top angle, tooth height and outer diameter, and the corresponding size research ranges are 15~50, 10~30°, 10~20°, 0.05~0.15mm and 3.5~5.0mm respectively.

[0024] Furthermore, the size limit ranges corresponding to the number of teeth, helix angle, tooth top angle, tooth height and outer diameter are 33-40, 13-20°, 13-17°, 0.1-0.14 mm, and 3.4-4.0 mm, respectively.

[0025] Furthermore, in the secondary comparison, the optimal parameter combination is determined by the tube blank microstructure uniformity index, the internal thread forming equipment parameter adaptability index and the wall thickness uniformity index.

[0026] Furthermore, performing comprehensive comparison based on the structured table includes standardizing the data in the structured table, setting an objective function and constraints, and using a multi-objective optimization algorithm to screen the pre-processed data;

[0027] The standardization process includes:

[0028] B1: Calculate the sensitivity coefficient according to the sensitivity of each parameter to the change of the objective function, and divide it into high-sensitivity layer parameters and low-sensitivity layer parameters according to the calculation results;

[0029] B2: applying quantile normalization to the parameters of the high-sensitivity layer, and applying linear normalization to the parameters of the low-sensitivity layer;

[0030] B3: assigning the corresponding sensitivity coefficient to each normalized parameter value to complete weighting, and using the weighted value as input data for the multi-objective optimization algorithm.

[0031] Furthermore, performing a comprehensive comparison based on the structured table includes:

[0032] C1: Set several objective functions;

[0033] C2: Calculating a fitness score for each parameter combination in the structured table based on the deviation of each objective function;

[0034] C3: assigning weights to the objectives according to the suitability scores;

[0035] C4: recalculating the deviation of each objective function according to the adjusted weight;

[0036] Steps C2 to C4 are executed in a loop.

[0037] The technical solution of the present invention can achieve the following technical effects:

[0038] The present invention realizes global optimization and multi-objective coordination of the design of internal threaded copper tubes for air conditioners through the technical path of full parameter permutation and combination construction, sampling, and structured data analysis, and can ultimately obtain the optimal parameter combination that meets the goal of reducing meter weight to guide subsequent production. BRIEF DESCRIPTION OF THE DRAWINGS

[0039] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are only some embodiments recorded in the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0040] Figure 1 This is a flow chart of a method for reducing the meter weight of internally threaded copper tubes for air conditioners based on full permutation and combination of parameters;

[0041] Figure 2 A partially structured table showing the groups when the outer diameter is 3.9 mm.

[0042] Figure 3 This is the partial structural data with 35 teeth and 4mm outer diameter;

[0043] Figure 4 A flowchart for comprehensive comparison based on a structured table;

[0044] Figure 5 Flowchart for standardized processing;

[0045] Figure 6 Flowchart for comprehensive comparison of structured tables. DETAILED DESCRIPTION

[0046] The technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, rather than all the embodiments.

[0047] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by those skilled in the art to which this invention pertains. The terms used in this specification are for the purpose of describing specific embodiments only and are not intended to limit the invention. The term "and / or" as used herein includes any and all combinations of one or more of the associated listed items.

[0048] Example 1

[0049] like Figure 1 As shown, the method for reducing the meter weight of internally threaded copper tubes for air conditioners based on full parameter permutation and combination includes:

[0050] S1: Determine the parameter type for establishing the full parameter permutation and combination and the set mass flow rate in the internally threaded copper tube. When selecting the parameter type, parameters sensitive to meter weight can be selected based on historical data or simulation verification. The selection of the set mass flow rate can refer to the actual operating conditions of the air conditioning system.

[0051] S2: Assign a size research range and the number of values within the size research range to each type of parameter. By properly selecting the parameter type and assigning the size research range, multiple possibilities in the parameter space can be covered after all permutations and combinations are established, avoiding missing potential optimal solutions. The number of values can be obtained by taking values at equal intervals.

[0052] S3: Multiply the number of values corresponding to each type of parameter to obtain the total number of all parameter combinations. After the total number is calculated, a preliminary estimate of the calculation amount can be made.

[0053] S4: Selecting a set number of combinations based on the total number, and obtaining parameter values of various types for the selected combinations; in existing sampling methods, selection can be made based on actual needs. After the selection is completed, the parameter values of each parameter in the combination can be clearly known. As a specific implementation method, the set number can be determined manually. Regardless of the basis for determination, it is within the scope of protection of the present invention;

[0054] S5: Under the set mass flow rate, the heat transfer value and pressure drop value of the internally threaded copper tube are calculated according to the parameter values of each combination;

[0055] S6: Arrange the parameter values of each combination, as well as the corresponding heat transfer value and pressure drop value into a structured table;

[0056] S7: Perform a comprehensive comparison based on the structured table, and determine the optimal parameter combination that meets the meter weight reduction target within the size research range based on the comparison results.

[0057] In the present invention, key data such as parameter values, heat transfer values, pressure drop values, etc. of all permutations and combinations are centrally managed in the form of structured tables, which can ensure that the input and output of each parameter combination correspond one-to-one, avoid data dispersion or loss, and facilitate retrospective verification and comparison with historical solutions. During implementation, through table tools such as conditional screening, sorting, and formula calculation, staged screening can be directly achieved, and multi-objective weighted scoring or Pareto front analysis can be supported, which can significantly improve decision-making efficiency. When there is a design constraint adjustment, it is only necessary to expand the table column or update the screening conditions to regenerate the optimization solution set, without the need to reconstruct the entire process, to adapt to dynamic engineering needs.

[0058] The present invention realizes global optimization and multi-objective coordination of the design of internal threaded copper tubes for air conditioners through the technical path of full parameter permutation and combination construction, sampling, and structured data analysis, and can ultimately obtain the optimal parameter combination that meets the goal of reducing meter weight to guide subsequent production.

[0059] As a preferred embodiment of the above, the set number of combinations is obtained by random sampling as a whole; or by grouping the set number of combinations and randomly sampling and combining them in each group. In this embodiment, the parameter types include at least the number of teeth, helix angle, tooth addendum angle, tooth height, and outer diameter.

[0060] In the above optimization scheme, grouping can be performed based on the above single parameter, for example, grouping based on the difference in outer diameter, or grouping based on the difference in the number of teeth; Figure 2 As shown, a partial structured table is shown when the outer diameter is 3.9 mm when grouped by the difference in outer diameter. The figure also shows the relevant data of heat exchange improvement and pressure drop improvement. This extended display method is also within the scope of protection of the present invention.

[0061] As a preferred embodiment of the above, Figure 4 As shown, the comprehensive comparison based on the structured table includes preliminary comparison and secondary comparison. The preliminary comparison is to narrow the combination range of the secondary comparison. The preliminary comparison includes:

[0062] A1: Determine the acceptable range of heat transfer values and pressure drop values based on a structured table;

[0063] A2: Keep the combinations with heat transfer and pressure drop values within the acceptable range as updated comparison samples, and eliminate the remaining combinations.

[0064] As follows Figure 3 As shown in the figure, some structural data with a tooth number of 35 and an outer diameter of 4 mm are displayed. In the following table, the heat transfer calculation values of Group 1, Group 2 and Group 4 are relatively low, indicating that the heat transfer performance has deteriorated significantly, while in Group 5, the pressure drop change rate exceeds 30%. Based on the above situation, even if the pressure drop performance in Group 1, Group 2 and Group 4 is improved to a certain extent, and the heat transfer coefficient in Group 5 is improved, they all need to be eliminated because the heat transfer coefficient and pressure drop are not a relatively compromised result.

[0065] To achieve the goal of preliminary comparison, conditional deletion can be used in structured tables to directly set hard constraints and eliminate combinations that do not meet the requirements. This method can quickly narrow the candidate range.

[0066] After the initial comparison is completed, as a further preferred embodiment, the secondary comparison includes: determining a combination in the updated comparison sample that can meet the metre weight reduction target, where the metre weight reduction target is reflected by the size limit range of the number of teeth, helix angle, tooth top angle, tooth height and outer diameter.

[0067] In the set of feasible solutions retained in the preliminary comparison, the secondary comparison directly links the meter weight target through the parameter size restriction range to ensure that the final combination meets both performance requirements and lightweight requirements, avoiding the problem of separation of performance and cost targets. The size range of each parameter is restricted separately, rather than just restricted by a single meter weight. The implicit processing requirements can ensure the processing capacity and raw material requirements of the mold, etc., to avoid the situation where the laboratory optimization results are difficult to mass produce. This method of multi-parameter collaborative restriction essentially constructs a multi-dimensional optimization space that takes into account performance, cost, and manufacturability, thereby improving the conversion rate of laboratory results to mass production applications.

[0068] As a specific implementation method, based on the demand for reducing the weight of the internal thread copper tube for air conditioners, the mass flow rate is set to 180-220 kg / (m 2 s); the parameter types only include the number of teeth, helix angle, tooth top angle, tooth height, and outer diameter, and the corresponding size research ranges are 15-50, 10-30°, 10-20°, 0.05-0.15mm, and 3.5-5.0mm, respectively. Based on the above ranges, in this example, the size limit ranges corresponding to the number of teeth, helix angle, tooth top angle, tooth height, and outer diameter are further optimized to 33-40, 13-20°, 13-17°, 0.1-0.14mm, and 3.4-4.0mm, respectively.

[0069] Based on the aforementioned size limits, the optimal parameter combinations often include multiple combinations, such as 35 teeth, an 18° helix angle, a 15° tooth top angle, a 0.12mm tooth height, and a 3.6mm outer diameter; or 38 teeth, an 15° helix angle, a 15° tooth top angle, a 0.12mm tooth height, and a 3.6mm outer diameter. It should be noted that the outer diameter in these combinations is the average outer diameter. Ultimately, selecting production parameters from among the multiple optimal parameter combinations often requires manual effort, considering a more comprehensive production situation and drawing on expert advice.

[0070] In actual operation, to reduce the meter weight, the outer diameter is reduced within the size limit, which significantly increases the relative ratio of the thread teeth to the tube base, resulting in a size effect. The mold core head is then reduced, which poses challenges to the spinning process and greatly reduces the efficiency of the internal thread forming process. In addition, due to the reduction in tube size, the uniformity of the tube blank microstructure and wall thickness has a more significant impact on the forming process, making it easy to break the tube during processing, greatly reducing the yield of the tube. Based on the above situation, as a preferred embodiment of the above embodiment, the optimal parameter combination is also determined in the secondary comparison based on the tube blank microstructure uniformity index, the internal thread forming equipment parameter adaptability index, and the wall thickness uniformity index.

[0071] Take the following equipment parameters as an example: including spinning speed, pulling force and core head temperature, and satisfying: 12m / min≤spinning speed≤18m / min, 8kN≤pulling force≤12kN, 140℃≤core head temperature≤160℃. Of course, the above parameters are only exemplary and do not limit the scope of protection of the present invention. Specific selection needs to be made based on the actual equipment structure and control method.

[0072] Example 2

[0073] like Figure 1 As shown, the method for reducing the meter weight of internally threaded copper tubes for air conditioners based on full parameter permutation and combination includes:

[0074] S1: Determine the parameter type for establishing the full parameter permutation combination and the set mass flow rate in the internally threaded copper tube;

[0075] S2: Assign a size research range to each type of parameter, as well as the number of values within the size research range;

[0076] S3: Multiply the number of values corresponding to each type of parameter to obtain the total number of all parameter combinations;

[0077] S4: Select a set number of combinations according to the total number, and obtain parameter values of each type for the selected combinations;

[0078] S5: Under the set mass flow rate, the heat transfer value and pressure drop value of the internally threaded copper tube are calculated according to the parameter values of each combination;

[0079] S6: Arrange the parameter values of each combination, as well as the corresponding heat transfer value and pressure drop value into a structured table;

[0080] S7: Perform a comprehensive comparison based on the structured table, and determine the optimal parameter combination that meets the meter weight reduction target within the size research range based on the comparison results.

[0081] Based on the above content, this embodiment differs from the first embodiment in that a comprehensive comparison is performed based on a structured table. Unlike a hierarchical comparison method, this embodiment adopts an intelligent comprehensive comparison method.

[0082] Specifically, as a preferred embodiment of the present invention, performing comprehensive comparison based on the structured table includes standardizing the data in the structured table, setting an objective function and constraints, and using a multi-objective optimization algorithm to screen the pre-processed data to obtain an optimal parameter combination;

[0083] like Figure 5 As shown, the standardization process includes:

[0084] B1: Calculate the sensitivity coefficient based on the sensitivity of each parameter to the change of the objective function, and divide the parameters into high-sensitivity layer and low-sensitivity layer according to the calculation results. Sensitivity analysis can distinguish the degree of influence of different parameters on the objective function. For example, the number of teeth and outer diameter are often high-sensitivity layer parameters. The above distinction can be achieved through local perturbation method, regression analysis or gradient analysis. Specifically, the sensitivity coefficient threshold can be set. This part is existing technology and will not be repeated here.

[0085] B2: Quantile normalization is used for parameters in the high-sensitivity layer, and linear normalization is used for parameters in the low-sensitivity layer. This normalization makes the subsequent model more sensitive to the extreme value distribution of important parameters. For low-sensitivity parameters, all parameter values are mapped to the same interval [0, 1] to prevent numerical differences from interfering with the optimization effect. For the specific use case of internally threaded copper pipes for air conditioning, this method can maintain a reasonable distinction between parameter influences and prevent high-sensitivity parameters from being diluted by average.

[0086] B3: Each normalized parameter value is assigned a corresponding sensitivity coefficient to complete weighting, and the weighted value is used as the input data of the multi-objective optimization algorithm. By explicitly embedding the degree of influence of the parameters on actual performance changes into the optimization model input, the optimization algorithm is given structural perception capabilities. In particular, during the model operation, when the combined solution approaches the boundary of heat transfer performance or pressure drop constraints, the weight configuration can dynamically emphasize the parameter dimensions that are sensitive to the boundary, thereby obtaining the ability to adaptively adjust the boundary performance constraints.

[0087] For the multi-objective optimization algorithm, as a preferred embodiment of the above, the comprehensive comparison based on the structured table includes:

[0088] C1: Setting several objective functions; in this embodiment, corresponding to the first embodiment, the objectives may correspond to manufacturing process indicators such as weight per meter, heat transfer performance, pressure drop, tube microstructure uniformity, internal thread forming equipment adaptability, and wall thickness uniformity;

[0089] C2: Calculate the fitness score for each design parameter combination based on the deviation of each objective function. The fitness score is used to reflect the performance of each design parameter combination on multiple objectives.

[0090] C3: Assign weights to the corresponding objectives of each objective function based on the suitability score. For example, if controlling the meter weight is more important in the initial design phase, the weight of the meter weight will be higher. If heat transfer performance or pressure drop becomes a bottleneck during the optimization process, its weight may be dynamically increased.

[0091] C4: Recalculate the deviation of each objective function based on the adjusted weights to ensure that the weight changes can affect the evaluation criteria of the objective function and refocus the optimization algorithm on the new key goals;

[0092] Steps C2 to C4 are executed cyclically. Through the feedback of the adaptability score, the optimization algorithm can dynamically adjust the weight of each objective function to achieve a balance among multiple objectives.

[0093] In this embodiment, target-oriented dynamic focusing can be achieved under a large number of parameter combinations, solving the problem of uncertain goals in the design stage. The adaptability scoring mechanism effectively integrates performance and manufacturability evaluation to solve the problem of process feasibility. Specifically, process indicators such as molding equipment adaptability and wall thickness uniformity are introduced into the adaptability scoring, and these factors are taken into account in the weight adjustment, so that the final screened solution not only has excellent performance, but also has the realistic possibility of being put into practical manufacturing.

[0094] For the loop of steps C2 to C4, adapt to the dynamic trade-off process between multiple objectives and solve the compromise selection problem under "extreme compression". For example, in the following scenario:

[0095] (1) Parameter combination A has the lowest mk weight, but the pressure drop is slightly higher;

[0096] (2) Combination B has the best heat transfer, but the wall thickness is extremely difficult to process.

[0097] It is difficult for traditional methods to select the optimal solution in the above-mentioned compromise problem. However, through this optimization scheme, the adaptability between multiple objectives can be continuously re-evaluated, and the weights can be dynamically fine-tuned according to the deviation feedback to finally find the comprehensive optimal solution. Optimization screening is performed based on the dynamically adjusted objective function, and multi-objective optimization is performed using the weighted objective function to screen out the optimal design parameter combination while ensuring that it meets the actual needs of multiple performance objectives such as heat transfer, pressure drop, and meter weight.

[0098] Compared with the first embodiment, the advantages of this embodiment are that it is suitable for rapid processing of massive combinations, can accumulate data, and continuously optimize and iterate to form an intelligent system; while the method in the first embodiment is simple to implement, has clear logic, and is easy to trace and review, and can be selected according to needs during specific implementation.

[0099] The basic principles, main features, and advantages of the present invention are shown and described above. Those skilled in the art should understand that the present invention is not limited to the foregoing embodiments. The foregoing embodiments and descriptions are merely illustrative of the principles of the present invention. Various changes and modifications may be made to the present invention without departing from the spirit and scope of the present invention. Such changes and modifications are intended to fall within the scope of the present invention. The scope of protection claimed in the present invention is defined by the appended claims and their equivalents.

Claims

1. A method for reducing the meter weight of internally threaded copper tubes for air conditioners based on full parameter permutation and combination, characterized in that: include: S1: Determine the parameter type for establishing the full parameter permutation combination and the set mass flow rate of the internally threaded copper pipe; S2: Assign a size research range to each type of parameter, as well as the number of values within the size research range; S3: Multiply the number of values corresponding to each type of parameter to obtain the total number of all parameter combinations; S4: selecting a set number of combinations according to the total number, and obtaining parameter values of various types for the selected combinations; S5: Under the set mass flow rate, the heat exchange value and the pressure drop value of the internally threaded copper tube are calculated according to the parameter values of each combination; S6: Arranging the parameter values of each combination, as well as the corresponding heat exchange value and pressure drop value into a structured table; S7: Perform a comprehensive comparison based on the structured table, and determine the optimal parameter combination that meets the goal of reducing meter weight within the size research range based on the comparison results.

2. The method for reducing the meter weight of an internally threaded copper tube for air conditioning based on full parameter permutation and combination according to claim 1, characterized in that: A set number of said combinations are obtained by overall random sampling; Alternatively, a set number of combinations are grouped, and random sampling and combination are performed in each group to obtain the combination.

3. The method for reducing the meter weight of internally threaded copper tubes for air conditioners based on full parameter permutation and combination according to claim 1, characterized in that: The parameter types include at least the number of teeth, helix angle, tooth top angle, tooth height and outer diameter.

4. The method for reducing the meter weight of an internally threaded copper tube for air conditioning based on full parameter permutation and combination according to claim 1, characterized in that: The comprehensive comparison performed according to the structured table includes a preliminary comparison and a secondary comparison. The preliminary comparison is to narrow down the combination range of the secondary comparison. The preliminary comparison includes: determining an acceptable range of heat exchange values and pressure drop values based on the structured table; The combinations whose heat transfer value and pressure drop value are both within the acceptable range are retained as updated comparison samples, and the remaining combinations are eliminated.

5. The method for reducing the meter weight of internally threaded copper tubes for air conditioners based on full parameter permutation and combination according to claim 4, characterized in that: The secondary comparison includes: A combination that can meet the meter weight reduction target is determined in the updated comparison sample, and the meter weight reduction target is reflected by the dimensional limit range of the number of teeth, helix angle, tooth top angle, tooth height and outer diameter.

6. The method for reducing the meter weight of internally threaded copper tubes for air conditioners based on full parameter permutation and combination according to claim 5, characterized in that: The set mass flow rate is selected to be 180-220 kg / (m 2 s); The types of parameters mentioned only include the number of teeth, helix angle, tooth top angle, tooth height and outer diameter, and the corresponding size research ranges are 15~50, 10~30°, 10~20°, 0.05~0.15mm and 3.5~5.0mm respectively.

7. The method for reducing the meter weight of internally threaded copper tubes for air conditioners based on full parameter permutation and combination according to claim 6, characterized in that: The size limit ranges corresponding to the number of teeth, helix angle, tooth top angle, tooth height and outer diameter are 33-40, 13-20°, 13-17°, 0.1-0.14 mm and 3.4-4.0 mm respectively.

8. The method for reducing the meter weight of internally threaded copper tubes for air conditioners based on full parameter permutation and combination according to claim 5, characterized in that: In the secondary comparison, the optimal parameter combination is also determined through the tube blank structure uniformity index, the internal thread forming equipment parameter adaptability index and the wall thickness uniformity index.

9. The method for reducing the meter weight of an internally threaded copper tube for air conditioners based on full parameter permutation and combination according to any one of claims 1 to 3, characterized in that: Performing a comprehensive comparison based on the structured table includes standardizing the data in the structured table, setting an objective function and constraints, and using a multi-objective optimization algorithm to screen the pre-processed data; The standardization process includes: B1: Calculate the sensitivity coefficient according to the sensitivity of each parameter to the change of the objective function, and divide it into high-sensitivity layer parameters and low-sensitivity layer parameters according to the calculation results; B2: applying quantile normalization to the parameters of the high-sensitivity layer, and applying linear normalization to the parameters of the low-sensitivity layer; B3: assigning the corresponding sensitivity coefficient to each normalized parameter value to complete weighting, and using the weighted value as input data for the multi-objective optimization algorithm.

10. The method for reducing the meter weight of internally threaded copper tubes for air conditioners based on full parameter permutation and combination according to any one of claims 1 to 3, characterized in that: The comprehensive comparison according to the structured table includes: C1: Set several objective functions; C2: Calculating a fitness score for each parameter combination in the structured table based on the deviation of each objective function; C3: assigning weights to the objectives according to the suitability scores; C4: recalculating the deviation of each objective function according to the adjusted weight; Steps C2 to C4 are executed in a loop.

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