Simulation design method for conveying mechanism of assembling machine

Abstract

The invention relates to the technical field of mechanical simulation, in particular to a simulation design method for a conveying mechanism of an assembling machine. The method comprises the following steps: acquiring physical attribute data of a disposable infusion apparatus pipeline; establishing a pipeline flexible simulation model based on flexible characteristics according to the physical attribute data, and performing mechanical analysis of bending, twisting and mutual contact of the infusion apparatus pipeline based on a winding mode, so as to generate deformation simulation data of the flexible pipeline; performing pipeline flexibility simulation on the pipeline flexibility simulation model according to the deformation simulation data so as to obtain pipeline winding behavior simulation data; and acquiring material characteristic data of the plastic film in the hot melting sealing process, and carrying out heat-fluid-solid coupling analysis on the material characteristic data, so as to obtain phase change transfer coupling data. According to the method, the pipeline simulation model based on the flexibility characteristic is established, so that the complex winding behavior is accurately simulated.

Description

Technical Field

[0001] The invention relates to the technical field of mechanical simulation, and in particular to a simulation design method for a conveying mechanism of an assembly machine. Background Art

[0002] A disposable infusion set is a medical device used to inject liquid medicine or nutrients into the human body through a vein. It is usually used only once to avoid cross infection and maintain sterility. The infusion set consists of multiple parts, including: a bottle needle, which is used to pierce the rubber stopper of a medicine bottle or bottle to extract the medicine; a dropper, which controls the flow of the medicine, usually by observing the dripping speed to adjust the infusion speed; an infusion tube, which connects the medicine bottle and the needle to deliver the medicine; a filter, which filters out tiny particles or air bubbles in the medicine to prevent it from entering the human body; a regulator, which is used to adjust the liquid flow rate; a needle, which is connected to the infusion tube and inserted into the patient's vein to deliver the medicine. These infusion sets are usually made of medical grade PVC (polyvinyl chloride) or other non-toxic plastic materials and should be discarded after use to prevent infection. Blister packaging is a packaging method that heats the plastic material to soften it and then uses vacuum suction to fit it on a mold to form a specific shape. It is often used to protect products such as electronic products, food and medicines, and has good transparency and moisture resistance.

[0003] The current simulation design methods for the assembly machine conveying mechanism in the scenario of blister-packed disposable infusion sets often have the following problems: the infusion set tubing is soft and deformable, and it is very difficult to accurately simulate its behavior in simulation; hot-melt sealing involves phase change and flow of materials, which is a complex multi-physics problem. Summary of the invention

[0004] Based on this, it is necessary for the present invention to provide a simulation design method for a conveying mechanism of an assembly machine to solve at least one of the above-mentioned technical problems.

[0005] To achieve the above object, a simulation design method for a conveying mechanism of an assembly machine includes the following steps:

[0006] Step S1: obtaining physical property data of a disposable infusion set pipeline; establishing a pipeline flexibility simulation model based on flexibility characteristics according to the physical property data, and performing a mechanical analysis of bending, twisting and mutual contact of the infusion set pipeline based on a winding method, thereby generating deformation simulation data of the flexible pipeline; performing pipeline flexibility simulation on the pipeline flexibility simulation model according to the deformation simulation data, thereby obtaining simulation data of pipeline winding behavior;

[0007] Step S2: obtaining material property data of the plastic film during the hot melt sealing process, and performing a thermal-fluid-solid coupling analysis on the material property data, thereby obtaining phase change transfer coupling data; estimating the temperature field distribution, melting and solidification process of the plastic film during the infusion set packaging process according to the phase change transfer coupling data, performing a packaging pressure change analysis, and performing a plastic film flow and solidification simulation, thereby obtaining packaging effect simulation data;

[0008] Step S3: performing packaging simulation analysis on the wound infusion set tube according to the deformation simulation data and the packaging effect simulation data, and simulating the position adjustment of the infusion set tube in the blister packaging array in the simulation, so as to obtain packaging behavior simulation data;

[0009] Step S4: analyzing the effect of air exhaust inside the packaging bag based on the temperature distribution and pressure change according to the packaging effect simulation data, thereby obtaining air exhaust efficiency simulation data; using a vacuum pump to perform air extraction simulation according to the air exhaust efficiency simulation data to generate vacuum packaging effect simulation data;

[0010] Step S5: Perform a multi-physics field comprehensive analysis on the positioning, winding tightness and vacuum sealing effect of the infusion set tubing during the packaging process according to the packaging behavior simulation data and the vacuum packaging effect simulation data, so as to generate an optimal design scheme for the packaging system.

[0011] The present invention acquires the physical property data of the disposable infusion set pipeline, establishes a pipeline simulation model based on the flexibility characteristics, and can accurately simulate the deformation behavior of the infusion set pipeline during the winding process. This simulation analysis can not only predict the mechanical changes of the pipeline when it is bent, twisted and in contact with each other, but also effectively prevent damage caused by excessive stretching, twisting or mutual winding of the pipeline during the winding process. This step provides basic data for subsequent packaging behavior, ensures that the flexible simulation results of the pipeline can accurately reflect the state in actual production, and improves the consistency and quality of pipeline winding. By acquiring the material property data of the plastic film and performing thermal-fluid-solid coupling analysis, the temperature distribution, melting and solidification process of the plastic film during the packaging process can be accurately simulated. The analysis of the packaging pressure change further ensures the fluidity and solidification uniformity of the plastic film during the packaging process. This greatly improves the packaging quality of the infusion set, avoids the problems of loose packaging and plastic film leakage caused by improper temperature control, ensures the tightness and durability of the packaging, and improves the storage safety of the product. When performing packaging simulation, by combining deformation simulation data and packaging effect simulation data, the position adjustment of the infusion tube after winding in the blister packaging can be accurately simulated. This analysis avoids the problem of pipeline misalignment or overlap that is easy to occur during manual operation, so that the infusion tubes in each packaging array are evenly distributed and tightly wound, improving packaging efficiency and consistency. This not only improves the mechanization of packaging, but also reduces the problem of packaging damage or reduced production efficiency due to uneven distribution of pipelines. Through the simulation analysis of the air exhaust effect inside the packaging bag, the vacuum degree can be accurately controlled based on temperature distribution and pressure changes, and air extraction can be simulated by a vacuum pump. This step ensures that the air inside the packaging bag can be efficiently discharged, avoids air residue, and improves the vacuum packaging effect. Efficient air removal and vacuum sealing not only increase the shelf life of the product, but also avoid hygiene problems or product quality degradation caused by loose packaging. This step ensures the airtightness and stability of the infusion tube packaging. By conducting a multi-physics field comprehensive analysis of the positioning, winding tightness and vacuum sealing effect of the infusion tube during the packaging process, it can provide an accurate basis for the optimization design of the entire packaging system. This comprehensive simulation optimization solution ensures quality control of the infusion set throughout the production process. This step ultimately provides a comprehensive optimized design for the packaging system, improving the overall efficiency and reliability of the system and reducing uncertainty and failure risks on the production line. The optimized design of the packaging system not only improves production efficiency, but also provides flexibility and scalability for possible future product improvements. BRIEF DESCRIPTION OF THE DRAWINGS

[0012] Other features, objects and advantages of the present invention will become more apparent from the detailed description of non-limiting embodiments thereof made with reference to the following drawings:

[0013] Figure 1It is a schematic flow chart of the steps of the simulation design method of the conveying mechanism of the assembly machine of the present invention;

[0014] Figure 2 for Figure 1 Detailed step flow diagram of step S1;

[0015] Figure 3 for Figure 1 Detailed step flow chart of step S2 in FIG. DETAILED DESCRIPTION

[0016] The technical method of the present invention is described clearly and completely below in conjunction with the accompanying drawings. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by technicians in this field without creative work are within the scope of protection of the present invention.

[0017] In addition, the accompanying drawings are only schematic illustrations of the present invention and are not necessarily drawn to scale. The same reference numerals in the figures represent the same or similar parts, and their repeated description will be omitted. Some of the block diagrams shown in the accompanying drawings are functional entities and do not necessarily correspond to physically or logically independent entities. The functional entities can be implemented in software form, or implemented in one or more hardware modules or integrated circuits, or implemented in different networks and / or processor methods and / or microcontroller methods.

[0018] It should be understood that, although the terms "first", "second", etc. may be used herein to describe various units, these units should not be limited by these terms. These terms are used only to distinguish one unit from another unit. For example, without departing from the scope of the exemplary embodiments, the first unit may be referred to as the second unit, and similarly the second unit may be referred to as the first unit. The term "and / or" used herein includes any and all combinations of one or more of the listed associated items.

[0019] To achieve this, please refer to Figures 1 to 3 The present invention provides a simulation design method for a conveying mechanism of an assembly machine, the method comprising the following steps:

[0020] Step S1: obtaining physical property data of a disposable infusion set pipeline; establishing a pipeline flexibility simulation model based on flexibility characteristics according to the physical property data, and performing a mechanical analysis of bending, twisting and mutual contact of the infusion set pipeline based on a winding method, thereby generating deformation simulation data of the flexible pipeline; performing pipeline flexibility simulation on the pipeline flexibility simulation model according to the deformation simulation data, thereby obtaining simulation data of pipeline winding behavior;

[0021] Step S2: obtaining material property data of the plastic film during the hot melt sealing process, and performing a thermal-fluid-solid coupling analysis on the material property data, thereby obtaining phase change transfer coupling data; estimating the temperature field distribution, melting and solidification process of the plastic film during the infusion set packaging process according to the phase change transfer coupling data, performing packaging pressure change analysis, and performing plastic film flow and solidification simulation, thereby obtaining packaging effect simulation data;

[0022] Step S3: performing packaging simulation analysis on the wound infusion set tube according to the deformation simulation data and the packaging effect simulation data, and simulating the position adjustment of the infusion set tube in the blister packaging array in the simulation, so as to obtain packaging behavior simulation data;

[0023] Step S4: analyzing the effect of air exhaust inside the packaging bag based on the temperature distribution and pressure change according to the packaging effect simulation data, thereby obtaining air exhaust efficiency simulation data; using a vacuum pump to perform air extraction simulation according to the air exhaust efficiency simulation data to generate vacuum packaging effect simulation data;

[0024] Step S5: Perform a multi-physics field comprehensive analysis on the positioning, winding tightness and vacuum sealing effect of the infusion set tubing during the packaging process according to the packaging behavior simulation data and the vacuum packaging effect simulation data, so as to generate an optimal design scheme for the packaging system.

[0025] In the embodiment of the present invention, reference Figure 1 The above is a schematic flow chart of the steps of a simulation design method for a conveying mechanism of an assembly machine according to the present invention. In this example, the simulation design method for a conveying mechanism of an assembly machine includes the following steps:

[0026] Step S1: obtaining physical property data of a disposable infusion set pipeline; establishing a pipeline flexibility simulation model based on flexibility characteristics according to the physical property data, and performing a mechanical analysis of bending, twisting and mutual contact of the infusion set pipeline based on a winding method, thereby generating deformation simulation data of the flexible pipeline; performing pipeline flexibility simulation on the pipeline flexibility simulation model according to the deformation simulation data, thereby obtaining simulation data of pipeline winding behavior;

[0027] The embodiment of the present invention obtains the physical property data of the disposable infusion set pipeline. First, the geometric parameters of the pipeline, including length, inner and outer diameters, wall thickness, etc., are collected by measuring equipment, and its physical properties such as elastic modulus, Poisson's ratio and density are measured in combination with mechanical property testing equipment, and its mechanical property changes are tested under different temperature conditions. Based on these physical property data, a flexible property simulation model is established using finite element analysis (FEA) software such as ANSYS or ABAQUS. Mechanical analysis is performed by loading the model with torsion, bending stress and winding mode, and the mutual contact behavior between the pipelines is simulated. During the simulation process, the geometric parameters of the pipeline winding (such as winding radius 10mm, number of turns 5, pitch 2mm) are set to obtain simulation data of pipeline deformation. Finally, the deformation data is used to perform simulation analysis of the winding behavior, generate simulation data of the pipeline winding behavior, and display the stress distribution, distortion and contact point mechanical analysis results of the pipeline during the winding process.

[0028] Step S2: obtaining material property data of the plastic film during the hot melt sealing process, and performing a thermal-fluid-solid coupling analysis on the material property data, thereby obtaining phase change transfer coupling data; estimating the temperature field distribution, melting and solidification process of the plastic film during the infusion set packaging process according to the phase change transfer coupling data, performing a packaging pressure change analysis, and performing a plastic film flow and solidification simulation, thereby obtaining packaging effect simulation data;

[0029] The embodiment of the present invention obtains the material property data of the plastic film during the hot melt sealing process, including the melting point, specific heat capacity, thermal conductivity, etc. of the material. The phase change characteristics of the plastic film are measured using a DSC (differential scanning calorimetry) device, and a thermal-fluid-solid coupling model of the material is constructed in combination with the experimental data. In software such as COMSOL Multiphysics, these material data are input to establish the coupling equations of heat conduction, fluid mechanics, and solid mechanics, and analyze the temperature field distribution and phase change transfer behavior of the plastic film during heating, melting, and solidification. According to the experimental data, the temperature of the plastic film when it melts is set to 160°C, and the pressure during packaging is 0.5MPa. The plastic flow and solidification behavior during the packaging process are simulated to generate packaging effect simulation data for evaluating the sealing strength and airtightness.

[0030] Step S3: performing packaging simulation analysis on the wound infusion set tube according to the deformation simulation data and the packaging effect simulation data, and simulating the position adjustment of the infusion set tube in the blister packaging array in the simulation, so as to obtain packaging behavior simulation data;

[0031] According to the pipeline deformation simulation data of step S1 and the packaging effect simulation data of step S2, the embodiment of the present invention uses 3DCAD software (such as SolidWorks or CATIA) to construct the initial geometric model of the infusion pump pipeline and blister packaging array after winding, and inputs the physical properties of the packaging material and the infusion pump. Perform a static interference check to ensure that the wound pipeline does not interfere with the packaging structure. The position of the pipeline in the package is adjusted by the optimization algorithm. The position parameters set during the adjustment process are as follows: the spacing of the packaging array is 50mm, and the diameter of the pipeline after winding is controlled within 15mm to ensure the stability of the pipeline. In the simulation software, the dynamic process of the pipeline being inserted into the package is simulated, the deformation and stress distribution are calculated, and finally the packaging behavior simulation data is generated.

[0032] Step S4: analyzing the effect of air exhaust inside the packaging bag based on the temperature distribution and pressure change according to the packaging effect simulation data, thereby obtaining air exhaust efficiency simulation data; using a vacuum pump to perform air extraction simulation according to the air exhaust efficiency simulation data to generate vacuum packaging effect simulation data;

[0033] The embodiment of the present invention utilizes packaging effect simulation data and fluid dynamics simulation software (such as Fluent) to simulate the air exhaust process inside the packaging bag. Input the geometric information and material properties of the packaging bag, including the thickness distribution and temperature gradient of the sealing area. Set the vacuum pump's exhaust speed to 5L / min and the target vacuum degree to 10Pa to simulate the process of air being discharged from the inside of the packaging bag, analyze the air exhaust efficiency, and generate air exhaust efficiency simulation data. Using the vacuum pump simulation data, further simulate the air extraction process to obtain the final vacuum packaging effect simulation data to evaluate the air tightness of the packaging bag.

[0034] Step S5: Perform a multi-physics field comprehensive analysis on the positioning, winding tightness and vacuum sealing effect of the infusion set tubing during the packaging process according to the packaging behavior simulation data and the vacuum packaging effect simulation data, so as to generate an optimal design scheme for the packaging system.

[0035] The embodiment of the present invention constructs a multi-physics field coupling model based on the packaging behavior simulation data and the vacuum packaging effect simulation data, and comprehensively analyzes the positioning accuracy, winding tightness and vacuum sealing effect of the infusion pump pipeline during the packaging process. Through the multi-objective optimization algorithm, the influence of different packaging parameters (such as heat sealing temperature of 160°C, pressure of 0.6MPa, and packaging time of 5 seconds) on the winding tightness and sealing effect of the pipeline is evaluated. Through simulation analysis of the positioning accuracy and winding tightness data, the optimal design scheme of the packaging system is finally generated to ensure that the position of the infusion pump pipeline is stable during the packaging process, the sealing effect is good, and the airtightness meets the requirements.

[0036] Preferably, step S1 comprises the following steps:

[0037] Step S11: collecting the length, inner and outer diameters, and wall thickness information of the disposable infusion set pipeline, thereby obtaining pipeline geometry data;

[0038] Step S12: Acquire the elastic modulus, Poisson's ratio and density data of the infusion set tubing material, thereby generating material physical property data;

[0039] Step S13: measuring the change of mechanical properties of the infusion set pipeline at different temperatures, thereby obtaining mechanical property data;

[0040] Step S14: merging pipeline geometry data, material physical property data and mechanical property data into physical property data;

[0041] Step S15: establishing a pipeline flexibility simulation model based on flexibility characteristics according to the physical property data, and performing a mechanical analysis of the bending, twisting and mutual contact of the infusion set pipeline based on the winding method, thereby generating deformation simulation data of the flexible pipeline;

[0042] Step S16: Perform a pipeline flexibility simulation model on the pipeline flexibility simulation model according to the deformation simulation data, so as to obtain pipeline winding behavior simulation data.

[0043] As an embodiment of the present invention, refer to Figure 2 As shown, Figure 1 Detailed step flow diagram of step S1 in the embodiment of the present invention, step S1 includes the following steps:

[0044] Step S11: collecting the length, inner and outer diameters, and wall thickness information of the disposable infusion set pipeline, thereby obtaining pipeline geometry data;

[0045] The embodiment of the present invention first uses a high-precision digital caliper to measure the length, inner and outer diameters, and wall thickness of the disposable infusion set tubing with an accuracy of 0.01mm. The measurement points are evenly distributed at multiple locations of the tubing, and the measurements are not less than 10 times, and the average value is taken as the final geometric data of the tubing. For example, the tubing length of a certain model of infusion set is 1500mm, the inner diameter is 2mm, the outer diameter is 3mm, and the wall thickness is 0.5mm. These geometric data will be used in subsequent simulations to determine the initial geometric model of the tubing and accurately simulate the deformation behavior of the tubing.

[0046] Step S12: Acquire the elastic modulus, Poisson's ratio and density data of the infusion set tubing material, thereby generating material physical property data;

[0047] The embodiment of the present invention uses material testing equipment (such as a universal material testing machine) to test the elastic modulus, Poisson's ratio and density of the infusion tube material. First, a tensile test is performed to record the stress-strain relationship of the material during the force process to obtain the elastic modulus. Use strain gauges to measure the transverse and longitudinal strains of the material, calculate the Poisson's ratio, and the density is calculated by weighing and combining the geometric volume. For example, the elastic modulus of a certain plastic material is 1.5 GPa, the Poisson's ratio is 0.35, and the density is 1.2 g / cm 3 Based on this data, accurate physical property input can be provided for the flexible simulation model.

[0048] Step S13: measuring the change of mechanical properties of the infusion set pipeline at different temperatures, thereby obtaining mechanical property data;

[0049] The embodiment of the present invention tests the mechanical properties of the infusion set tubing material at different temperatures. The tubing samples are placed at different temperatures such as ambient temperature, 30°C, and 50°C, and a universal material testing machine is used to test the tensile strength, torsional strength, and shear strength of the tubing. The test is repeated no less than 5 times under each temperature condition to ensure the stability and reliability of the data. For example, at room temperature, the tensile strength of the material is 60MPa, and the tensile strength drops to 45MPa at 50°C. Through these mechanical property data, we can understand the impact of temperature changes on the mechanical properties of the infusion set tubing during actual use.

[0050] Step S14: merging pipeline geometry data, material physical property data and mechanical property data into physical property data;

[0051] The embodiment of the present invention combines the pipeline geometry data obtained in step S11, the material physical property data obtained in step S12, and the mechanical property data in step S13. Using data processing tools such as MATLAB or Excel, these data are input into a unified database or parameter table as the basic input data for the subsequent flexible simulation model. The table of physical property data includes the length, inner and outer diameters, wall thickness, elastic modulus, Poisson's ratio, density of the pipeline and its mechanical property parameters at different temperatures. Through the integration of these data, a complete physical property data set of the infusion pump pipeline is formed, providing a basis for simulation modeling.

[0052] Step S15: establishing a pipeline flexibility simulation model based on flexibility characteristics according to the physical property data, and performing a mechanical analysis of the bending, twisting and mutual contact of the infusion set pipeline based on the winding method, thereby generating deformation simulation data of the flexible pipeline;

[0053] According to the physical property data, the embodiment of the present invention uses finite element analysis software (such as ABAQUS or ANSYS) to establish an infusion pump pipeline simulation model based on flexible characteristics. First, the geometric shape of the pipeline is input into the software, the boundary conditions are set, and the elastic modulus, Poisson's ratio, density and other properties of the material are assigned to the pipeline model. In the simulation software, the winding method of the pipeline is simulated, including the bending, torsion and mutual contact of the pipeline. Set the pipeline winding radius to 10mm and the number of winding turns to 5, perform bending and torsion mechanical analysis, and obtain the deformation simulation data of the pipeline. These data show how the pipeline deforms and the stress distribution changes during the winding process.

[0054] Step S16: Perform a pipeline flexibility simulation model on the pipeline flexibility simulation model according to the deformation simulation data, so as to obtain pipeline winding behavior simulation data.

[0055] The embodiment of the present invention uses deformation simulation data as input to perform a comprehensive winding behavior simulation on the pipeline flexibility simulation model. By applying multiple mechanical loads such as torsion, tension, and external pressure, the actual performance of the infusion pump pipeline under different winding conditions is simulated. For example, by setting different winding densities and external pressures, the behavior of the pipeline during packaging or use can be simulated. The winding behavior simulation data finally generated includes the deformation amount, torque distribution, stress-strain distribution, etc. of different parts of the pipeline during the winding process. These data can be used to optimize the winding process and design to ensure the reliability of the infusion pump pipeline in actual applications.

[0056] The present invention ensures that the geometric model used in the simulation process can accurately reflect the physical dimensions of the actual pipeline by accurately collecting the length, inner and outer diameters and wall thickness information of the disposable infusion set pipeline. This provides reliable basic data for subsequent mechanical analysis and simulation model establishment. Accurate geometric data collection avoids simulation errors caused by dimensional deviations, helps to achieve high-precision simulation analysis, and thus optimizes the pipeline design and winding method in the production process. By collecting the physical properties of the material such as elastic modulus, Poisson's ratio and density of the infusion set pipeline, the behavior of the pipeline material under different mechanical and environmental conditions can be accurately reflected. These attribute data are the key to subsequent flexible simulation analysis and directly affect the accuracy of the simulation results. Accurate acquisition of material properties helps to predict the strength, durability and deformation resistance of the pipeline during use, thereby ensuring that the performance of the product meets the standards and reducing the production of unqualified products. By measuring the changes in the mechanical properties of the infusion set pipeline at different temperatures, the actual performance of the pipeline under different environmental conditions can be simulated. This helps to identify the impact of temperature on the pipeline material, especially deformation, fracture or other failures that may occur in extreme environments. Through this step, it is ensured that the infusion set can maintain stable performance in various use environments, improving the reliability and service life of the product. Merging the geometric data, material physical property data and mechanical property data of the pipeline into complete physical property data can provide comprehensive input information for the subsequent simulation model. The process of merging data ensures that the parameters used in the simulation model are consistent and comprehensive, avoiding the deviation of simulation results caused by one-sided data. This comprehensive data processing method improves the accuracy of simulation and the adaptability of the model, which helps to achieve more accurate product optimization. According to the physical property data, a pipeline simulation model based on flexible characteristics is established, and mechanical analysis of bending, torsion and mutual contact during winding is performed. This step can fully simulate the behavior of the infusion pump pipeline in actual production and use, especially the dynamic deformation behavior of the flexible pipeline. Through mechanical analysis, potential structural weaknesses or design deficiencies can be identified, and adjustments and optimizations can be made in advance, thereby improving the structural stability and production efficiency of the product. According to the deformation simulation data, further simulation analysis of the pipeline flexibility simulation model can accurately predict the behavior of the pipeline during the winding process. This simulation process can optimize the winding method, reduce the risk of stress concentration or mutual winding of the pipeline during the winding process, thereby improving the accuracy of production automation. The winding behavior simulation data provides an important basis for subsequent packaging design, ensuring the tightness and consistency of winding, and effectively improving the efficiency and safety of packaging and transportation. Through the simulation and analysis of the above steps, the pipeline design and production process of the disposable infusion set have been optimized. These simulation results help identify various potential problems of the pipeline in actual use and ensure the stability of its structure and performance.In the production process, the use of these simulation data can reduce the number of experiments, reduce development costs, improve production efficiency, and ensure high-quality output of products.

[0057] Preferably, step S15 comprises the following steps:

[0058] Step S151: performing material stress-strain curve analysis according to the physical property data of the infusion set pipeline, thereby obtaining stress-strain relationship data;

[0059] The embodiment of the present invention first selects a sample of pipeline material according to the physical property data of the infusion set pipeline, and uses a universal material testing machine to perform a stress-strain curve test. At different stretching rates, the force and deformation data of the pipeline material are recorded to obtain a stress-strain curve. During the test, the material sample is fixed at both ends of the testing machine, the tensile force is gradually increased, and the corresponding strain value is measured. The stress-strain relationship curve is drawn according to the collected data, and key parameters such as yield point, elastic zone, plastic zone, etc. are recorded. For example, in a specific model of plastic material, the elastic modulus is 1.4GPa and the yield stress is 45MPa. These data will be used for subsequent mechanical simulation analysis of pipeline materials.

[0060] Step S152: Establishing a constitutive model for the pipeline material according to the stress-strain relationship data, and analyzing the influence of temperature on the constitutive model according to the mechanical property data, thereby obtaining a pipeline material characteristic data set;

[0061] The embodiment of the present invention uses a material constitutive model (such as a linear elastic model, a nonlinear elastic model or a viscoelastic model) to establish a constitutive model of the material based on stress-strain relationship data. Select a suitable material model, such as the Neo-Hookean or Mooney-Rivlin model, to analyze the mechanical properties of the material at different temperatures. By comparing the changes in the stress-strain curves at different temperatures, the effect of temperature on the mechanical properties of the material is evaluated. For example, at 25°C, the elastic modulus of the material is 1.5GPa, which decreases to 1.2GPa at 50°C. According to these data, the material properties at different temperatures are integrated to form a pipeline material property data set for material property assignment during simulation analysis.

[0062] Step S153: establishing a three-dimensional geometric model of the pipeline according to the geometric information in the physical property data, and integrating the material properties of the three-dimensional geometric model according to the pipeline material property data set, thereby obtaining a material property integrated model;

[0063] The embodiment of the present invention uses CAD software (such as SolidWorks or AutoCAD) to establish a three-dimensional geometric model of the infusion pump pipeline according to the geometric information in the physical property data. First, the geometric parameters such as the inner and outer diameters, length, and bending radius of the pipeline are input to generate a three-dimensional geometric entity. Then, the pipeline material property data set is applied to the three-dimensional geometric model to give the geometric model different material properties, such as elastic modulus and Poisson's ratio in different regions. After the material properties are integrated, the three-dimensional geometric model not only contains the shape information, but also has material properties, forming a material property integrated model as the basic model for subsequent simulation.

[0064] Step S154: setting meshing parameters for the material property integrated model, and determining boundary conditions and loading methods, thereby obtaining a pipeline flexibility simulation model;

[0065] The embodiment of the present invention imports the material property integrated model into the finite element analysis software (such as ABAQUS or ANSYS) and performs meshing on it. When meshing, the size and details of the pipeline need to be considered, and a moderate mesh density is used. For example, for pipelines with a diameter less than 5 mm, a refined mesh with a unit size of 0.1 mm is selected. Then, the boundary conditions and loading methods are set, such as fixing both ends of the pipeline and applying winding torque, tensile force, etc. When setting, different loading modes need to be set according to the actual winding situation to ensure that the simulation model reflects the actual stress state of the pipeline during winding.

[0066] Step S155: performing mechanical analysis on the infusion set pipeline according to the preset infusion set pipeline winding model, thereby obtaining a pipeline stress state data set, wherein the mechanical analysis includes bending stress and strain distribution analysis, pipeline torsion analysis, and contact force distribution analysis;

[0067] The embodiment of the present invention performs a mechanical analysis of the pipeline in a finite element analysis software based on a preset infusion set pipeline winding model. First, the bending stress and strain distribution of the pipeline are analyzed to observe the changes in the internal stress of the pipeline at different winding radii. Next, a torsion analysis is performed on the pipeline to analyze the stress state of the pipeline when torque is applied, and the relationship between the torsion angle and the applied load is calculated. Finally, the contact force distribution when the pipelines contact each other during the winding process is analyzed to identify the local stress at the contact site. For example, under the conditions of a winding radius of 10 mm and a torque of 5 N·m, the maximum stress in the pipeline is 35 MPa, and the contact force is concentrated in the area with the tightest winding.

[0068] Step S156: applying the pipeline stress state data set to the pipeline flexibility simulation model to perform static nonlinear analysis based on deformation under winding state, thereby obtaining static deformation data, and simulating transient deformation behavior during winding, thereby obtaining dynamic deformation data;

[0069] The embodiment of the present invention applies the pipeline stress state data set to the pipeline flexibility simulation model to perform static and dynamic analysis. First, based on the static nonlinear analysis under the winding state, torque and tensile force are applied, and the deformation of the pipeline under constant loading is calculated to obtain static deformation data. Then, the transient deformation behavior during the winding process is simulated, the winding speed is simulated to be 5rad / s, and the dynamic deformation during the winding process is observed. The analysis results include instantaneous stress and displacement distribution, and dynamic deformation data is obtained. These data will be used to evaluate the dynamic performance and structural stability of the infusion pump pipeline during the winding process.

[0070] Step S157: Perform pipeline deformation simulation based on node displacement and stress distribution using static deformation data and dynamic deformation data, thereby generating deformation simulation data of the flexible pipeline.

[0071] The embodiment of the present invention performs a comprehensive analysis of static deformation data and dynamic deformation data, and uses node displacement and stress distribution to simulate the deformation of the pipeline. The deformation of the pipeline under different winding states is displayed in the simulation software to determine its bending and torsion limit states. By analyzing the displacement and stress changes of key nodes, deformation simulation data of the flexible pipeline is generated. For example, the maximum value of the node displacement is 2mm, and the stress concentration point is located at the minimum bending radius of the pipeline. With these data, the design and production process of the infusion pipeline can be further optimized to ensure its safety and durability in use.

[0072] The present invention can accurately understand the mechanical performance of the material under different loads by analyzing the stress-strain curve of the infusion tube material. This process ensures that the real deformation characteristics of the tube material can be reflected in the simulation. The stress-strain relationship data lays the foundation for the subsequent establishment of the constitutive model, which can make the simulation more accurate, improve the mechanical performance evaluation of the product, and avoid unnecessary material failure in actual production. By establishing a constitutive model of the tube material and combining the analysis of the influence of different temperatures on the mechanical properties of the material, it is ensured that the simulation model can not only reflect the material behavior at room temperature, but also accurately simulate the response of the material when the temperature changes. This multi-dimensional analysis helps to improve the adaptability of the infusion tube in different working environments, ensuring that it can still maintain good mechanical properties under extreme conditions such as high temperature and low temperature, thereby improving the reliability of the product. Establishing a three-dimensional geometric model based on physical property data and integrating material property data helps to perfectly combine the geometric properties and material properties of the tube to form a model with real physical properties. This step ensures that the simulation of geometric shape and material behavior is highly consistent during the simulation process, thereby improving the simulation accuracy. Through this comprehensive model, the deformation and mechanical performance of the tube in actual operation can be better predicted. By meshing the material property integrated model and setting boundary conditions, it is ensured that the local and overall stress and strain distribution can be accurately captured during the simulation process. Meshing is the core of simulation accuracy. By setting the mesh size reasonably, the simulation accuracy can be greatly improved. The reasonable setting of boundary conditions also helps to simulate the various external forces that the pipeline may be subjected to in actual applications, ensuring the reliability of the simulation results. By performing detailed mechanical analysis on the bending stress, strain distribution, torsion analysis, and contact force distribution of the infusion pipeline, the stress conditions of the pipeline in the winding state can be fully understood. This step provides key data support for the optimization design, and can identify stress concentration or other potential problems that may occur in the pipeline during the winding process, thereby reducing the risk of failure such as fracture or deformation. Through static nonlinear analysis and transient simulation of dynamic deformation behavior, the deformation of the infusion pipeline during the winding process can be fully understood. Static deformation data helps to evaluate the stress and strain distribution of the pipeline at a specific location, while dynamic deformation data can better predict the behavior of the pipeline during actual operation. This combined analysis method enables the simulation model to accurately reflect the stability under static conditions and simulate transient changes during dynamic winding. By performing deformation simulation on node displacement and stress distribution, the flexible deformation process of the tubing in the winding state can be accurately captured. The flexible tubing deformation simulation data generated in this step can help engineers optimize the design of the infusion tube, thereby reducing the risk of excessive deformation or material fatigue during the winding process. The acquisition of this data helps to improve the durability and reliability of the product and ensure that efficient and high-quality tubing winding operations can be maintained throughout the production process.Through detailed simulation analysis of the above steps, the flexible behavior of the infusion tube during winding and packaging has been fully simulated. These analysis results not only improve the structural design quality of the product, but also provide key data support for optimizing the production process. Through accurate simulation, the trial and error process in production is avoided, material waste and cost are reduced, and the durability, safety and production efficiency of the product are improved.

[0073] Preferably, step S155 includes the following steps:

[0074] Step S1551: determining the geometric configuration of the pipeline winding according to the preset infusion set pipeline winding model, thereby obtaining winding geometric parameter data, wherein the geometric configuration of the pipeline winding includes winding diameter, winding number and winding pitch;

[0075] The embodiment of the present invention first determines the geometric configuration of the winding according to the preset infusion tube winding model. The winding form of the pipeline is determined by inputting geometric parameters such as winding diameter, winding number and winding pitch. For example, if the winding diameter is 50mm, the winding number is 5, and the winding pitch is 10mm, the three-dimensional geometric modeling of the wound pipeline can be performed through geometric modeling software (such as SolidWorks) to obtain winding geometric parameter data. These geometric parameters are used for subsequent curvature and stress calculations.

[0076] Step S1552: Calculating the curvature distribution of the pipeline in the winding state according to the winding geometric parameter data, thereby obtaining the pipeline curvature distribution data;

[0077] The embodiment of the present invention calculates the curvature distribution of the pipeline in the winding state based on the winding geometric parameter data. The specific operation is to define the geometric curve of the pipeline in the finite element analysis software, calculate the curvature of each point by the differential equation of the geometric curve, and focus on the analysis of the area where the winding bend is most obvious. For example, when the curvature radius is 10mm, the maximum curvature of the winding may appear in the area where the winding is most dense. Through these calculations, the curvature distribution data of the entire winding pipeline is obtained.

[0078] Step S1553: Calculate the bending stress using the pipeline curvature distribution data and the pipeline material characteristic data set, thereby obtaining the pipeline bending stress distribution data;

[0079] The embodiment of the present invention uses curvature distribution data and pipeline material characteristic data sets (such as elastic modulus, Poisson's ratio, etc.) to calculate the bending stress of the pipeline during the winding process. The specific method is to select the curvature value of each section, combine the mechanical properties of the material, and apply the bending stress formula σ=E·κ·y, where E is the elastic modulus, κ is the curvature, and y is the distance from the neutral axis. By calculating point by point, the bending stress distribution data under the entire winding state is obtained. For example, when the winding radius is 10mm and the material elastic modulus is 1.4GPa, the maximum bending stress may be 45MPa.

[0080] Step S1554: Calculating the torsional stress based on the torsional angle of each section of the pipeline based on the winding geometric parameter data, thereby obtaining pipeline torsional stress data;

[0081] The embodiment of the present invention calculates the torsion angle of each section of the pipeline according to the winding geometric parameter data, and calculates the torsional stress based on these torsion angles. In finite element analysis, the torsional stress formula τ=T·r / J is used, where T is the torque, r is the section radius, and J is the polar moment of inertia. For each section, a different torsion angle is input, and the torsional stress of the pipeline is calculated one by one. For example, if the torque applied during the winding process is 2N·m and the torsion angle is 30 degrees, the maximum torsional stress may be generated at the section of the outermost circle. Finally, the torsional stress data of the pipeline is obtained.

[0082] Step S1555: identifying the contact points of the infusion set tubing winding model during the tubing winding process, and calculating the normal force and tangential force of the contact points, thereby obtaining contact force distribution data;

[0083] The embodiment of the present invention identifies the contact points of the pipeline during the winding process in the pipeline winding model, and calculates the normal force and tangential force of the contact points. In the simulation software, the contact force analysis module is used to set the friction coefficient between the contact surfaces of the pipelines, and the dynamic behavior of the pipelines contacting each other during the winding process is simulated to identify the contact parts. The normal force is calculated by the force in the orthogonal direction of the contact surface, and the tangential force is calculated according to the friction force calculation formula F t =μ·F n (μ is the friction coefficient, F n For example, if the friction coefficient is set to 0.3 and the normal force at the contact point is 10N, then the tangential force is 3N. The contact force distribution data is obtained through analysis.

[0084] Step S1556: Combine the pipeline bending stress distribution data, pipeline torsional stress data and contact force distribution data into pipeline strain distribution data, and perform axial tension and compression effect analysis to obtain a pipeline stress state data set.

[0085] The embodiment of the present invention integrates the pipeline bending stress distribution data, torsional stress data and contact force distribution data into the strain distribution data of the pipeline. In the simulation software, these stress data are uniformly applied to the finite element model of the pipeline, and the axial tension and compression effect analysis is performed. The axial tension and compression force are set, for example, the tension force is set to 50N and the compression force is set to 30N, to simulate the stress state of the infusion pump pipeline during the winding process, with special attention paid to the deformation behavior of the pipeline after winding. Through these calculations, the overall stress state data set of the pipeline is obtained for subsequent design optimization and winding process evaluation.

[0086] The present invention clarifies the geometric configuration parameters of winding by determining the winding diameter, number of turns and winding pitch of the pipeline. The determination of these geometric parameters provides accurate input for subsequent simulation, ensuring that each variable in the winding process can be accurately simulated under actual conditions. Accurate control of winding geometric parameters helps to avoid winding too tight or too loose, and prevents pipeline deformation or damage during storage and transportation. By calculating the curvature distribution of the pipeline in the winding state, the local bending of the pipeline during winding can be accurately understood. The change of pipeline curvature is directly related to the bending stress of the pipeline in actual operation. The curvature distribution data helps to analyze whether the pipeline will have excessive bending at certain points, thereby avoiding local excessive deformation or damage. These data provide an accurate basis for subsequent stress analysis and optimization design. The bending stress calculation based on the pipeline curvature distribution data and material property data can predict the specific stress conditions that the pipeline will bear during the winding process. The bending stress distribution data can help find the stress concentration area during the winding process, and avoid pipeline fracture or fatigue caused by excessive local stress. At the same time, this step can optimize the winding design, ensure that the stress control during the winding process is within a safe range, thereby extending the service life of the pipeline. By calculating the torsional stress of each section of the pipeline based on the geometric parameters, the torsional effect on the pipeline during the winding process can be evaluated. This is very important to ensure that the pipeline does not suffer from excessive distortion during winding, especially when the winding is dense, the torsional stress may cause material fatigue or failure of the pipeline. By controlling the torsional stress, the winding parameters can be adjusted during the design process to reduce stress concentration and prevent material damage. Identifying the contact points of the pipeline during the winding process and calculating the contact force distribution can analyze whether the pipeline will produce local deformation due to the normal force and tangential force of the contact point during winding. The reasonable distribution of contact point force helps to avoid permanent indentation or damage to the pipeline during winding. Through the analysis of contact force, the winding method of the pipeline can be optimized, and the negative impact of contact force on the pipeline can be reduced, thereby ensuring the overall integrity of the infusion set pipeline. Combining the bending stress, torsional stress and contact force data into the strain distribution data of the pipeline, and analyzing the axial tension and compression effects, the multi-dimensional mechanical effects on the pipeline during the winding process can be fully evaluated. This comprehensive analysis helps to identify whether the pipeline will suffer structural failure due to multiple stresses during the winding process. At the same time, these data provide a reliable basis for further optimizing the pipeline design, thereby reducing the risks in actual use during the design stage. Through the above steps, the distribution and changes of the bending, torsion and contact stresses that the pipeline is subjected to during the winding process can be fully simulated. These mechanical data help optimize the winding scheme of the infusion pump pipeline, avoid material fatigue, deformation and even fracture caused by stress concentration, and improve the reliability and durability of the infusion pump product. In addition, the analysis of comprehensive strain data can also effectively prevent the performance degradation caused by uneven force or excessive compression of the material, thereby extending the service life of the product and reducing the risks in production and transportation.

[0087] Preferably, step S16 comprises the following steps:

[0088] Step S161: geometrically updating the pipeline flexibility simulation model according to the node displacement information of the deformation simulation data, thereby obtaining an updated pipeline geometric model;

[0089] The embodiment of the present invention performs a geometric update on the pipeline flexibility simulation model based on the node displacement information in the deformation simulation data generated in the previous step. In the simulation software, the geometric model of the pipeline is updated using the node displacement, and the deformation data of each node is used as an input parameter to reconstruct the geometric shape of the pipeline after winding. For example, if a node is displaced by 0.5 mm during the winding process, the displacement is applied to the corresponding node position in the geometric model, and the updated pipeline geometric model is generated by recalculating the overall geometric structure of the pipeline.

[0090] Step S162: applying a preload based on the deformation prestress that may be generated during the winding process to the infusion set pipeline according to the pipeline geometric model, thereby generating preload data;

[0091] The embodiment of the present invention applies a preload to the pipeline based on the updated geometric model and taking into account the deformation prestress generated during the winding process. In the simulation environment, preload data is generated by setting the prestress of each section of the pipeline (for example, bending stress, torsional stress, etc.). In specific operations, the stress value can be calculated by mechanical formulas according to the bending radius and angle of the pipeline, and these stresses can be applied to key parts of the geometric model. For example, in a pipeline section with a winding diameter of 30 mm, the prestress may be 20 MPa. The preload data generated by calculation is used for subsequent boundary condition setting.

[0092] Step S163: using the preload data to set mechanical boundary conditions for pipeline winding, thereby determining winding boundary condition data, wherein the mechanical boundary conditions include boundary conditions of bending, torsion and contact stress;

[0093] The embodiment of the present invention uses the preload data in step S162 to set mechanical boundary conditions, including boundary conditions of bending, torsion and contact stress. In the simulation system, the preload data is combined with the actual boundary conditions, such as fixing the positions of the two ends of the winding, setting a certain torque, and the normal force and tangential force of the contact point. For example, the boundary conditions may include constraints of a bending stress of 30 MPa and a torsion angle of 45 degrees. These settings can reflect the actual stress conditions of the pipeline during the winding process and generate winding boundary condition data.

[0094] Step S164: performing mechanical analysis of the flexible pipeline during the winding process according to the winding boundary condition data, and calculating the deformation amplitude and force change of the pipeline at different winding positions, thereby obtaining stress data of the winding position;

[0095] The embodiment of the present invention performs a mechanical analysis of the flexible pipe during the winding process according to the set winding boundary conditions. In the finite element analysis, various boundary conditions are input, and the force and deformation analysis is performed point by point to calculate the stress change and deformation amplitude at different winding positions. For example, in the area with the tightest winding, the deformation of the pipe may be the largest, reaching 3mm, and the force may reach 50MPa, while in the looser winding area, the deformation may be only 1mm. The winding position stress data at different winding positions is obtained by calculation.

[0096] Step S165: performing local stress concentration area analysis based on the winding position stress data and the pipeline material characteristic data set, and optimizing the winding parameters of the infusion set pipeline winding model, thereby obtaining winding parameter optimization data;

[0097] The embodiment of the present invention analyzes the area of ​​local stress concentration based on the stress data of the winding position. The pipeline material characteristic data set is matched, the location where stress concentration may occur is identified, and the winding parameters are optimized and adjusted. For example, if the stress concentration is found to be too high in certain areas, which may cause material fatigue, the winding pitch or winding angle can be adjusted to reduce the stress in these areas. For example, if the stress reaches the limit value of 80MPa at a certain cross section, the stress at that location is reduced to 60MPa by adjusting the pitch from 10mm to 12mm. Finally, the optimized winding parameter data is obtained.

[0098] Step S166: Perform pipeline flexibility simulation using winding parameter optimization data and pipeline geometric model to obtain pipeline winding behavior simulation data.

[0099] The embodiment of the present invention uses winding parameter optimization data to re-simulate pipeline flexibility. In the simulation software, the updated winding parameters and geometric model are input to perform an overall simulation analysis of the winding behavior. For example, by gradually loading the optimized winding parameters, observing the deformation and stress changes during the winding process, and analyzing the overall effect of winding under the new parameters. The updated winding behavior data can be obtained through simulation to verify the rationality of the optimized design, and finally generate pipeline winding behavior simulation data. These data provide optimization guidance for the winding process in the subsequent actual production process.

[0100] The present invention can ensure that the shape and structure of the model in the simulation are consistent with the state after the actual winding by performing geometric updates on the pipeline flexibility simulation model based on the deformation simulation data. The introduction of node displacement information can correct the pipeline geometric model in real time, so that the simulation more accurately reflects the deformation that may occur during the winding process. This step provides a more accurate basis for subsequent mechanical analysis and optimization design, ensuring that the simulation results have a high degree of credibility. By applying a preload to the pipeline, the prestress generated by the initial stress state of the pipeline during the winding process can be simulated. The preload data helps to understand the stress state of the pipeline at the beginning of the winding and to estimate the force response of the material during the winding process in advance. This is important for avoiding deformation failure of the pipeline caused by winding too tight or too loose, thereby improving the stress resistance of the infusion pipeline and optimizing the winding process. The setting of mechanical boundary conditions ensures that the actual conditions of bending, torsion and contact stress can be accurately simulated during the simulation process. By setting the winding boundary conditions in detail, the simulation model can be closer to the mechanical environment in the actual winding process, ensuring the accuracy of the simulation results. This step helps to identify stress concentration areas that may occur during the winding process in advance and reduce damage or excessive deformation of the material due to unreasonable boundary conditions. By performing mechanical analysis on the stress and deformation of the pipeline at different positions during the winding process, the changing trend of the force during the winding process can be identified. The winding position stress data can help engineers analyze the stress distribution of the pipeline at different winding positions to ensure that there will be no excessive stress concentration or local deformation out of control during the winding process. Through this analysis, the winding parameters can be further optimized to improve the stability and safety of the overall design. Using the local stress concentration area analysis, the high stress areas that may be generated in the pipeline during the winding process can be identified. By optimizing these stress concentration areas, the material fatigue or rupture caused by local stress can be effectively reduced, and the service life of the infusion tube can be improved. The winding parameter optimization data provides a basis for further adjusting the winding geometry configuration, so that the stress during the winding process is more evenly distributed, reducing the risk of failure caused by uneven winding. By using the winding parameter optimization data and the updated pipeline geometry model, a more accurate flexible simulation can be performed, and the simulation data of the pipeline winding behavior that is closer to the actual situation can be obtained. This step not only provides a reliable basis for subsequent production and manufacturing, but also provides accurate data support for further optimization of the winding process. The accuracy of simulation data helps improve production efficiency, reduce rework and material waste during the winding process, and thus reduce manufacturing costs. Through these steps, comprehensive simulation and optimization of the winding behavior of the infusion tube can be achieved. Preload application, boundary condition setting and stress analysis can help identify and solve potential mechanical problems in the winding process, avoid stress concentration and material deformation failure. Local stress concentration area analysis and winding parameter optimization provide an effective optimization solution for winding process design, further improving the durability and performance of the infusion set.The winding behavior simulation data finally generated can greatly improve the accuracy of simulation design and provide strong support for the actual production and quality control of products.

[0101] Preferably, step S2 comprises the following steps:

[0102] Step S21: obtaining material property data of the plastic film during the hot melt sealing process, including melting point, specific heat capacity, thermal conductivity, viscosity-temperature relationship and crystallization kinetic parameters;

[0103] Step S22: Establishing a multi-scale structural model of the plastic film material according to the material thermal property data, thereby obtaining a material microstructure model, wherein the multi-scale structure includes the structures of molecular chains, crystals, and amorphous regions;

[0104] Step S23: constructing a heat-fluid-solid coupling analysis model based on the coupling of heat conduction equations, fluid mechanics equations and solid mechanics equations according to the material microstructure model, thereby obtaining phase change transfer coupling data;

[0105] Step S24: estimating the temperature field distribution, melting and solidification process of the plastic film during the packaging of the infusion set according to the phase change transfer coupling data, analyzing the packaging pressure change, and simulating the flow and solidification of the plastic film, thereby generating temperature change and phase change simulation data of the solidification process;

[0106] Step S25: Simulate the packaging effect of the plastic film based on the temperature change and phase change simulation data, and analyze the packaging effect based on sealing, strength and airtightness, thereby obtaining packaging effect simulation data.

[0107] As an embodiment of the present invention, refer to Figure 3 As shown, Figure 1 Detailed step flow diagram of step S2 in the embodiment of the present invention, step S2 includes the following steps:

[0108] Step S21: obtaining material property data of the plastic film during the hot melt sealing process, including melting point, specific heat capacity, thermal conductivity, viscosity-temperature relationship and crystallization kinetic parameters;

[0109] In the hot melt sealing process of the embodiment of the present invention, it is first necessary to obtain the material property data of the plastic film, including melting point, specific heat capacity, thermal conductivity, viscosity-temperature relationship and crystallization kinetic parameters. The melting point and specific heat capacity of the plastic film are measured by a differential scanning calorimeter (DSC), the thermal conductivity is measured by a thermal conductivity meter, and the viscosity of the plastic film at different temperatures is measured by a rheometer to obtain a viscosity-temperature relationship curve. In addition, the crystallization kinetic parameters of the plastic film material are obtained in combination with the crystal growth kinetics theory. These data provide basic information for subsequent thermal-fluid-solid coupling analysis.

[0110] Step S22: Establishing a multi-scale structural model of the plastic film material according to the material thermal property data, thereby obtaining a material microstructure model, wherein the multi-scale structure includes the structures of molecular chains, crystals, and amorphous regions;

[0111] The embodiment of the present invention establishes a multi-scale structural model of the plastic film based on the obtained material thermophysical property data. First, the arrangement of the molecular chains of the plastic film is analyzed by molecular dynamics simulation to obtain the structural parameters of the molecular chains; then, the crystal region in the plastic film is analyzed by X-ray diffraction (XRD) technology to construct a crystal structure model; finally, the structural characteristics of the amorphous region in the plastic film are analyzed by combining scanning electron microscopy (SEM). The molecular chains, crystals and amorphous regions are combined to form a multi-scale material microstructure model for subsequent thermal-fluid-solid coupling analysis.

[0112] Step S23: constructing a heat-fluid-solid coupling analysis model based on the coupling of heat conduction equations, fluid mechanics equations and solid mechanics equations according to the material microstructure model, thereby obtaining phase change transfer coupling data;

[0113] The embodiment of the present invention is based on the material microstructure model of the plastic film, combined with the heat conduction equation, fluid mechanics equation and solid mechanics equation, to construct a heat-fluid-solid coupling analysis model. In specific operations, the heat conduction equation is used to describe the temperature field distribution of the plastic film during the melting and solidification process, the fluid mechanics equation is used to describe the flow behavior of the molten plastic film, and the solid mechanics equation is used to analyze the stress distribution of the material during the solidification process. Through finite element simulation software, these equations are coupled to generate phase change transfer coupling data of the plastic film during the hot melt sealing process.

[0114] Step S24: estimating the temperature field distribution, melting and solidification process of the plastic film during the packaging of the infusion set according to the phase change transfer coupling data, analyzing the packaging pressure change, and simulating the flow and solidification of the plastic film, thereby generating temperature change and phase change simulation data of the solidification process;

[0115] The embodiment of the present invention analyzes the temperature field distribution, melting and solidification process of the plastic film during the packaging process of the infusion pump based on the phase change transfer coupling data. By calculating the change of temperature over time, the entire process of the plastic film from heating to the melting point, melting and flowing to cover the surface of the infusion pump, and then cooling and solidifying is simulated. At the same time, the external force applied to the plastic film during the packaging process is analyzed by the change of the packaging pressure to determine its fluidity and solidification effect. For example, when the temperature reaches 180°C, the plastic film begins to melt, the packaging pressure is 1MPa, and the flow rate of the film is 5mm / s. Finally, the temperature change and phase change simulation data of the solidification process are obtained.

[0116] Step S25: Simulate the packaging effect of the plastic film based on the temperature change and phase change simulation data, and analyze the packaging effect based on sealing, strength and airtightness, thereby obtaining packaging effect simulation data.

[0117] The embodiment of the present invention uses temperature change and phase change simulation data to simulate the packaging effect of the plastic film. During the simulation process, key performance parameters such as sealing, strength and airtightness are considered to evaluate the effect of the plastic film after packaging. For example, through airtightness testing, the leakage of the plastic film in a vacuum environment of 0.1Pa is simulated, and through tensile simulation, whether the packaging strength meets the set standard (such as tensile strength of 20MPa) is tested. After comprehensive analysis, packaging effect simulation data is generated to provide a basis for further optimizing the packaging process.

[0118] The present invention ensures that the thermal response and mechanical properties of the material are fully understood during the hot melt sealing process by obtaining key material property data of the plastic film, such as melting point, specific heat capacity, thermal conductivity, viscosity-temperature relationship and crystallization kinetic parameters. These data provide reliable input parameters for subsequent thermal-fluid-solid coupling analysis, which can more accurately simulate the melting and solidification process of the plastic film, thereby improving the accuracy of the packaging simulation. Establishing a multi-scale structural model of the plastic film (molecular chain, crystal and amorphous region) helps to accurately simulate the influence of the microstructure characteristics of the plastic film on the macroscopic performance. Through a detailed description of the microstructure, it is possible to better understand how the material deforms and flows during the hot melt sealing process, especially to capture the changes in the microstructure during the melting and solidification process, thereby improving the accuracy of the simulation model and ensuring that the sealing effect reaches the expected result. By constructing a coupling model of heat conduction, fluid mechanics and solid mechanics equations, it is possible to accurately simulate how the plastic film conducts heat, flows and solidifies during the hot melt process. Phase change transfer coupling data provides phase change information of the plastic film in different states, such as the transition from melting to solidification, which is crucial to the packaging quality. The coupling model can not only reflect the changes in the temperature field, but also provide distribution information of pressure, stress and flow velocity, so as to comprehensively evaluate the sealing performance and structural integrity of the plastic film. Based on the phase change transfer coupling data, the temperature distribution, melting and solidification process of the plastic film during the packaging process can be accurately predicted. This process helps to ensure that the plastic film can be evenly heated and cooled during the packaging process, avoiding packaging defects caused by local overheating or uneven cooling. Through the analysis of pressure changes, the optimal pressure during the packaging process can be determined to ensure that the plastic film fits tightly to the infusion set pipeline, thereby enhancing the sealing and strength. Through the temperature change and phase change simulation data, detailed packaging effect simulation can be performed to ensure that the plastic film can maintain good sealing, airtightness and strength after packaging. The analysis of sealing and airtightness helps to verify whether the plastic film can effectively prevent the entry of air or other external substances after packaging, thereby ensuring the quality and safety of the infusion set. The packaging effect simulation data can provide support for process optimization and improve the reliability of the packaging process and the consistency of the product. Through the implementation of the above steps, the behavior of the plastic film in the hot melt sealing process can be fully and accurately simulated to ensure that it can be evenly heated, effectively flow and form a tight package during the packaging process. The establishment of multi-scale structural models and the application of thermal-fluid-solid coupling analysis improve the accuracy of simulation and provide a scientific basis for optimizing packaging parameters and improving product quality. The packaging effect simulation analyzes the sealing, strength and airtightness to ensure that the finished product has reliable performance in actual applications, thereby improving the packaging quality of disposable infusion sets.

[0119] Preferably, step S24 comprises the following steps:

[0120] Step S241: performing temperature field simulation of the plastic film during the hot melt sealing process according to the phase change transfer coupling data, thereby obtaining temperature distribution data;

[0121] In the hot melt sealing process of the plastic film, the embodiment of the present invention first establishes a temperature field simulation model of the plastic film in the heating stage based on the phase change transfer coupling data. By applying heating power to the plastic film (for example, setting the temperature to 200°C and the power to 500W), the finite element method is used to solve the heat conduction equation to simulate the temperature change of each point inside the plastic film over time. The simulation results show that the temperature of the center of the plastic film rises faster, while the temperature of the edge area rises slower due to heat dissipation. Based on these data, the temperature distribution data of the plastic film in the hot melt sealing process is generated to provide a basis for the subsequent melting behavior simulation.

[0122] Step S242: simulating the temperature distribution of the plastic film during the heating stage according to the temperature distribution data, and predicting the melting behavior, thereby generating melting simulation data;

[0123] After obtaining the temperature distribution data, the embodiment of the present invention simulates the temperature distribution in detail for the heating stage. The specific operation includes analyzing the temperature change rate of different areas of the plastic film during the heating process, and the critical point at which melting begins. Through the melting point parameters (for example, the melting point of the plastic film is 180°C), the time point and position at which each area of ​​the plastic film begins to melt are determined to predict its melting behavior. At the same time, by adjusting the heating rate and temperature control strategy, the melting speed and uniformity can be optimized, and finally the melting simulation data is generated. For example, when the heating rate is 10°C / s, the melting time of the plastic film is 15 seconds, and the melting range is a 30mm diameter area.

[0124] Step S243: Based on the melting simulation data, the flow behavior of the plastic film during the sealing process is simulated based on the flow path, thickness change and contact surface morphology of the melted plastic, thereby obtaining plastic flow simulation data;

[0125] The embodiment of the present invention simulates the flow behavior of the plastic film after melting based on the melting simulation data. During the simulation process, it is first necessary to set the flow path of the plastic film, and mainly calculate the flow trend of the molten plastic film through the influence of gravity, packaging pressure and surface tension. For example, when the packaging pressure is 1.5MPa, the molten plastic film flows to the surface of the infusion pump tubing at a speed of 3mm per second. Next, the thickness change is simulated to determine the thickness change of the plastic film at different positions; at the same time, the morphology of the contact surface between the plastic film and the infusion pump tubing is analyzed to evaluate the uniformity and integrity of its packaging. After multiple simulations, plastic flow simulation data is generated to show the film thickness change curve and contact surface quality during the flow process.

[0126] Step S244: performing phase change analysis on the solidification behavior of the plastic film after cooling according to the plastic flow simulation data, thereby generating temperature change and phase change simulation data of the solidification process.

[0127] The embodiment of the present invention performs phase change analysis on the solidification behavior of the plastic film during the cooling process based on the plastic flow simulation data. During the simulation process, cooling conditions are applied (for example, the cooling temperature is 25°C), and the temperature drop of the plastic film over time is analyzed according to the temperature change model. Through the dynamic analysis of the temperature field, the phase change process of the plastic film from liquid to solid is captured, and its solidification rate and solidification time are determined. At the same time, the solidification strength of the plastic film at different positions is evaluated to determine whether stress concentration areas will be generated during the solidification process. Finally, through these phase change analyses, the temperature change and phase change simulation data of the solidification process are generated. For example, in an environment of 25°C, it takes 30 seconds for the plastic film to completely solidify, and the solidification strength on the contact surface reaches 10MPa, ensuring the airtightness and strength of the package.

[0128] The present invention can obtain the temperature distribution data of the plastic film at different positions and time points by simulating the temperature field of the plastic film during the hot melt sealing process according to the phase change transfer coupling data. This process ensures the accurate evaluation of the heating uniformity and heat conduction efficiency of the plastic film, helps to predict the performance of the plastic film during the melting process, and then provides basic data for the optimization of the entire packaging process. Understanding the temperature distribution can also help identify possible hot spots and reduce the risk of packaging defects. By simulating the temperature distribution of the plastic film during the heating stage through the temperature distribution data, the melting behavior can be predicted in more detail. This prediction of melting behavior not only helps to understand the temperature change of the plastic film during the heating process, but also determines the optimal heating time and temperature, thereby ensuring that the plastic film can reach the optimal melting state. This process can reduce unnecessary energy consumption, improve production efficiency, and ensure that the plastic can effectively flow and fit the infusion set during packaging. Based on the melting simulation data, the flow behavior of the plastic film during the sealing process is simulated, and the flow path, thickness change and contact surface morphology of the melted plastic can be deeply analyzed. This step is crucial because the flow behavior directly affects the integrity and sealing effect of the package. Understanding the flow characteristics of plastics helps optimize mold design and processing parameters to ensure that the plastic can fully fill all gaps during the packaging process, thereby improving sealing performance and avoiding air leakage or weak sealing problems. Phase change analysis of the solidification behavior of the plastic film after cooling based on the plastic flow simulation data can generate temperature change and phase change simulation data of the solidification process. This analysis can help understand the solidification of the plastic film during the cooling process to ensure the strength and airtightness of the final product. By predicting the temperature change during the solidification process, the cooling time and conditions can be optimized to ensure that the plastic film can maintain its structure and performance after solidification. This is crucial to improving packaging quality and consistency, especially in demanding medical device applications. Through the implementation of these steps, a comprehensive understanding and precise control of the hot melt sealing process can be achieved to ensure that the plastic film can be evenly heated, effectively flow and finally form a stable solidification state throughout the packaging process. This detailed simulation and analysis can not only improve packaging efficiency and reduce material waste in the production process, but also ensure the safety and reliability of the final product, thereby enhancing the market competitiveness of the product.

[0129] Preferably, step S3 comprises the following steps:

[0130] Step S31: constructing a three-dimensional geometric model of the infusion set pipeline after winding according to the deformation simulation data and the packaging effect simulation data, obtaining the geometric dimensions and material property data of the blister packaging array, and establishing an initial assembly model of the infusion set pipeline and the blister packaging, thereby obtaining initial assembly data;

[0131] According to the deformation simulation data and packaging effect simulation data generated in the early stage, the embodiment of the present invention first establishes a three-dimensional geometric model of the infusion set pipeline after winding. The model is constructed by inputting the geometric information of the pipeline, such as length, diameter, winding diameter and number of turns, combined with the material properties of the pipeline (such as elastic modulus, Poisson's ratio), and three-dimensional modeling is performed using finite element software. Next, the geometric dimensions of the blister packaging array (for example, a single package is 50mm long, 30mm wide, and 20mm high) and material properties (such as elastic modulus and tensile strength of thermoplastics) are obtained. Based on these data, an initial assembly model of the infusion set pipeline and the blister packaging is established, and the initial assembly data is obtained by defining the assembly relationship.

[0132] Step S32: Performing a static interference check on the initial assembly data, identifying the collision point between the pipeline and the package, and optimizing and adjusting the position of the infusion set pipeline in the blister packaging array, thereby obtaining position adjustment data;

[0133] After obtaining the initial assembly data, the embodiment of the present invention uses the interference detection function in the CAD software to perform a static interference check on the model. This operation will identify the collision points and potential interference areas between the infusion tube and the blister package. Assuming that three collision points are found between the edge of the tube and the package in the model, the position of the tube needs to be optimized according to the actual assembly situation. By adjusting the rotation angle and insertion depth of the tube, the number of collision points is gradually reduced. After several rounds of position adjustment, the collision points are completely eliminated, and position adjustment data is generated to ensure that the tube can be smoothly assembled in the blister package array.

[0134] Step S33: using the position adjustment data to perform dynamic insertion simulation on the initial assembly model, and simulating the deformation and stress distribution of the pipeline during the insertion into the package, evaluating the stability and fixation effect of the pipeline in the package, thereby obtaining fixation effect data;

[0135] The embodiment of the present invention utilizes the generated position information and uses a simulation tool to simulate the dynamic insertion process of the pipeline. The specific operation steps include: setting the insertion speed (such as 5mm / s), the friction coefficient of the package (such as 0.3), and the material characteristic parameters of the pipeline. The deformation and stress distribution of the pipeline during the insertion process of the package are calculated by simulation, especially the distribution of bending deformation and contact pressure. The simulation results show that the position of the maximum deformation of the pipeline during the insertion process is located at the winding part, the deformation is 2mm, and the maximum stress occurs near the edge of the package, which is 50MPa. When evaluating the stability, focus on analyzing the fixing effect of the pipeline in the package to ensure that the pipeline will not produce obvious displacement in the packaging array, and finally generate the fixing effect data.

[0136] Step S34: performing pipeline displacement and deformation analysis during the packaging process according to the fixed effect data, and performing local optimization on the packaging design, thereby obtaining optimized design data;

[0137] The embodiment of the present invention further analyzes the displacement and deformation of the pipeline during the packaging process based on the fixing effect data, and identifies the displacement deviation and deformation that may occur during the insertion of the pipeline. The local structure is optimized by adjusting the clamping force and boundary conditions of the package. For example, if it is found that a certain section of the pipeline has a displacement of 5mm during insertion, the displacement is reduced to less than 1mm by increasing the fixing groove depth of the blister packaging in this area and optimizing the clamping force. Based on these optimization measures, the optimized design data is generated to improve the assembly stability and deformation control of the pipeline.

[0138] Step S35: Dynamically simulate the position in the blister packaging array according to the optimized design data and the initial assembly data, so as to obtain packaging behavior simulation data.

[0139] The embodiment of the present invention performs dynamic simulation in the blister packaging array based on the optimized design data and the initial assembly data. Through the dynamic simulation of the packaging behavior, the deformation, displacement and force changes of the pipeline during the assembly process are observed. The simulation results show that after optimization, the maximum displacement of the pipeline in the package is reduced to 0.5mm, and the stress concentration area is significantly reduced. Based on these simulation results, the packaging behavior simulation data is generated to guide the subsequent actual packaging design optimization.

[0140] The embodiment of the present invention constructs a three-dimensional geometric model of the infusion set pipeline after winding according to the deformation simulation data and the packaging effect simulation data, and obtains the geometric dimensions and material property data of the blister packaging array, which can ensure that the relationship between the pipeline and the packaging is fully understood in the early stage of design. The establishment of this preliminary assembly model provides basic data for subsequent interference inspection and optimization, so that the design team can more accurately identify potential problems and reduce the complexity and cost of subsequent modifications. Static interference inspection of the initial assembly data can effectively identify the collision point between the pipeline and the packaging. This process ensures that design defects can be discovered and solved before product assembly, reducing assembly problems in actual production. By optimizing the position of the infusion set pipeline in the blister packaging array, the overall assembly efficiency can be improved, the stability of the pipeline in the final product can be ensured, and the risk of material loss and rework can be reduced. Using the position adjustment data to perform dynamic insertion simulation on the initial assembly model, the deformation and stress distribution of the pipeline during the insertion of the packaging can be simulated in detail. This dynamic analysis can help designers evaluate the stability and fixation effect of the pipeline during the packaging process, and ensure that the pipeline will not be accidentally displaced or damaged during the entire packaging process. By understanding the stress distribution, the packaging design can be further optimized to ensure the fixation and protection of the pipeline. According to the fixation effect data, the displacement and deformation analysis of the pipeline during the packaging process can identify potential problems that may occur in the actual packaging. By optimizing the packaging design locally, the adaptability of the packaging and the protection of the pipeline can be improved to ensure that the pipeline is not damaged during transportation and storage. This optimization not only improves the product quality, but also reduces the after-sales cost caused by product damage. According to the optimized design data and the initial assembly data, the dynamic simulation in the blister packaging array can simulate the behavior in the actual packaging process and obtain the packaging behavior simulation data. This step can provide a deep understanding of the packaging effect and ensure that the performance and quality of the final product can be evaluated in the design stage. Through the simulation and analysis of the packaging behavior, potential packaging problems can be identified and solved before production, thereby improving the market competitiveness of the product. Overall, through the implementation of these steps, the packaging design quality and production efficiency of the disposable infusion set can be effectively improved. Through accurate modeling, interference checking and dynamic simulation, not only can rework and material loss in production be reduced, but also the safety and reliability of the final product can be ensured. These optimization measures will ultimately make the products more competitive in the market and meet increasingly stringent user demands.

[0141] Preferably, step S4 comprises the following steps:

[0142] Step S41: extracting the geometric shape, material properties, sealing area structure and thickness distribution information of the packaging bag according to the packaging effect simulation data, thereby generating three-dimensional geometric model data;

[0143] According to the packaging effect simulation data, the embodiment of the present invention first extracts the geometric shape and material properties of the packaging bag, including the outer dimensions of the packaging bag (such as 300 mm in length, 200 mm in width, and 0.2 mm in thickness) and the structural characteristics and thickness distribution of the sealing area (for example, the thickness of the sealing area is 0.3 mm, which is thicker than other areas). Using these data, a three-dimensional geometric model of the packaging bag is created in the three-dimensional modeling software. The material properties include the elastic modulus, density, and thermal conductivity of the plastic material, which are also input into the model to generate three-dimensional geometric model data, ready for subsequent heat conduction and air exhaust simulation.

[0144] Step S42: using the three-dimensional geometric model data to set the temperature field distribution of the packaging material, and simulating the thermal conduction behavior of the material during the sealing process, thereby obtaining thermal conduction data of the sealing area, wherein the temperature field distribution includes the temperature gradient of the sealing area and the material softening area;

[0145] The embodiment of the present invention uses the generated three-dimensional geometric model data to set the temperature field distribution of the packaging material. The specific steps include: first, setting different temperature gradients for the sealing area, such as setting the sealing temperature to 180°C, the temperature near the seal to 150°C, and other areas to room temperature. Then, based on the thermal conductivity and specific heat capacity of the material, the finite element simulation software is used to simulate the thermal conduction behavior of the sealing area, focusing on analyzing the changes in the temperature gradient during the sealing process and the size of the material softening area. Through heat conduction simulation, the thermal conduction data of the sealing area is generated, and the heating width and softening depth of the sealing area are determined.

[0146] Step S43: Preliminarily calculating the air volume in the packaging bag according to the heat conduction data of the sealing area and the three-dimensional geometric model data, and simulating the exhaust of air inside the packaging bag to generate preliminary air exhaust effect data;

[0147] The embodiment of the present invention calculates the initial air volume in the packaging bag based on the heat conduction data of the sealing area and the three-dimensional geometric model data. First, the effective volume in the packaging bag (for example, 600 cubic centimeters) is determined by the geometric model, and then the process of air being discharged is simulated by setting the degree of material deformation and the sealing effect during sealing. Using CFD simulation tools, the flow path, flow rate and discharge volume of the air during the packaging process are preliminarily simulated to generate preliminary air discharge effect data. The results show that during the sealing process, about 90% of the air can be discharged naturally.

[0148] Step S44: performing air extraction dynamic simulation based on vacuum pump simulation according to the preliminary air exhaust effect data, analyzing the residual air volume inside the packaging bag based on air flow and vacuum degree changes, thereby generating residual air distribution data;

[0149] Based on the preliminary air exhaust effect data, the embodiment of the present invention uses a dynamic simulation model of a vacuum pump to simulate the further extraction process of air. First, the working parameters of the vacuum pump are set, such as the vacuum degree is -0.09MPa and the extraction rate is 5L / min. The residual air volume inside the packaging bag is calculated by the air flow and pressure change equations. In the simulation, as the vacuum degree increases, the air exhaust rate gradually decreases, and the final residual air volume is 10 cubic centimeters. The generated residual air distribution data describes the air distribution at different positions, such as in the corners of the packaging bag, where air is more difficult to exhaust.

[0150] Step S45: analyzing the air exhaust efficiency at different positions in the packaging bag according to the residual air distribution data, and generating air exhaust efficiency simulation data;

[0151] The embodiment of the present invention uses residual air distribution data to analyze the air exhaust efficiency at different positions inside the packaging bag. By comparing the air flow rate at each position, it is found that the air exhaust efficiency at the sealing area and the edge of the bag is higher, while the exhaust efficiency at the corner position is lower, only 70%. Based on this analysis, the vacuum pump extraction method and bag structure during the packaging process are adjusted to optimize the air exhaust path and generate air exhaust efficiency simulation data.

[0152] Step S46: using a vacuum pump to perform air extraction simulation according to the air exhaust efficiency simulation data to generate vacuum packaging effect simulation data.

[0153] The embodiment of the present invention further optimizes the extraction process of the vacuum pump based on the air exhaust efficiency simulation data. The working cycle and extraction time of the vacuum pump are set to simulate the final air exhaust effect. By increasing the vacuum degree and extending the extraction time, the air exhaust efficiency is increased to 95%, and the residual air volume is reduced to 5 cubic centimeters. Finally, the vacuum packaging effect simulation data is generated to provide a reference for the optimization of the vacuum packaging process.

[0154] The present invention can generate accurate three-dimensional geometric model data by extracting the geometric shape, material properties, sealing area structure and thickness distribution information of the packaging bag according to the packaging effect simulation data. This process ensures a comprehensive understanding of the packaging bag design, so that the subsequent heat conduction and air exhaust analysis can be performed based on an accurate model. This accuracy will reduce errors in the design process, thereby reducing the cost of later modifications. By setting the temperature field distribution of the packaging material using the three-dimensional geometric model data and simulating the material heat conduction behavior during the sealing process, the heat conduction data of the sealing area can be obtained, including the temperature gradient and the material softening area. This analysis is crucial for optimizing the sealing process, and can ensure uniform heating of the material during hot melt sealing, avoid poor sealing problems caused by uneven heat distribution, and thus improve the sealing and safety of the product. According to the heat conduction data of the sealing area and the three-dimensional geometric model data, the air volume in the packaging bag is preliminarily calculated, and the air exhaust simulation inside the packaging bag is performed, and preliminary air exhaust effect data can be generated. This step provides a preliminary understanding of the air exhaust process, so that subsequent vacuum extraction and efficiency analysis can be optimized based on this data. This preliminary evaluation helps to discover potential problems and improve the design. Based on the preliminary air exhaust effect data, the dynamic simulation of air extraction based on vacuum pump simulation can analyze the residual air volume inside the packaging bag. This process simulates the relationship between air flow and vacuum degree change, helping the design team understand the efficiency and effect of air extraction under different operating conditions. This in-depth analysis ensures that the expected vacuum effect can be achieved in actual applications and optimizes the vacuum packaging process. The air exhaust efficiency analysis at different positions in the packaging bag based on the residual air distribution data can generate air exhaust efficiency simulation data. This analysis helps identify the air extraction effect in different areas, ensuring that the air exhaust scheme can be optimized in a targeted manner during the design stage. This targeted adjustment can greatly improve the sealing performance of the final packaging and reduce product quality problems caused by residual air during transportation and storage. The vacuum pump is used to perform air extraction simulation based on the air exhaust efficiency simulation data to generate vacuum packaging effect simulation data. This final step provides a detailed prediction and analysis of the performance of the packaging bag in actual applications, which helps optimize the production process and ensure the competitiveness of the product in the market. By obtaining real packaging effect simulation data, product quality control can be enhanced and data support can be provided for the improvement of production processes. Overall, the implementation of these steps can effectively improve the design quality and production efficiency of packaging bags. Through accurate modeling, heat conduction simulation and dynamic air exhaust analysis, not only can the vacuum packaging effect be optimized, but also the production cost and product loss caused by design defects can be reduced. These optimization measures will ultimately enhance the market competitiveness of products and meet the growing consumer demand.

[0155] Preferably, step S5 comprises the following steps:

[0156] Step S51: establishing a multi-physics field coupling model according to packaging behavior simulation data and vacuum packaging effect simulation data;

[0157] According to the previously obtained packaging behavior simulation data and vacuum packaging effect simulation data, the embodiment of the present invention first constructs a multi-physics field coupling model in the multi-physics field simulation software. The model combines the basic equations of heat conduction, fluid dynamics, and solid mechanics to comprehensively analyze the interaction of various physical fields in the packaging process. Specifically, the temperature field of the heat sealing area, the velocity field of the air flow, and the stress field of the material are defined, and the overall system response is obtained by coupling these physical fields. The parameter settings include a heat sealing temperature of 180°C, a pressure of 0.5MPa, and a time of 3 seconds to ensure that the model can accurately reflect the physical phenomena in actual operation.

[0158] Step S52: Analyze the positioning accuracy of the infusion tube during the packaging process using a multi-physics field coupling model, thereby obtaining the evaluation data of the tube positioning accuracy;

[0159] The embodiment of the present invention uses the established multi-physics field coupling model to analyze the positioning accuracy of the infusion pipeline. By setting different positioning errors (such as ±1mm, ±2mm), the influence of these errors on the position of the pipeline during the packaging process is simulated. By tracking the dynamic changes of the pipeline in the packaging, the influence data of the positioning error on the final position is collected. Furthermore, the deviation between the actual position and the ideal position of the pipeline is calculated and analyzed to generate pipeline positioning accuracy evaluation data. It is expected that the positioning accuracy can reach more than 95%, ensuring the packaging quality.

[0160] Step S53: evaluating the winding tightness of the infusion set tubing based on the multi-physics field coupling model, and performing a vacuum sealing process to evaluate the influence of different packaging parameters on the sealing effect, thereby obtaining winding tightness data and vacuum sealing effect evaluation data, wherein the packaging parameters include heat sealing temperature, pressure and time;

[0161] The embodiment of the present invention evaluates the winding tightness of the infusion pump tubing based on the multi-physics field coupling model. First, different packaging parameters are set, such as heat sealing temperature (170°C, 180°C, 190°C), packaging pressure (0.4MPa, 0.5MPa, 0.6MPa) and packaging time (2 seconds, 3 seconds, 4 seconds), and multiple groups of experimental simulations are performed. By observing the strain and deformation of the pipeline in the winding state, the relationship between the winding tightness and the vacuum sealing effect is evaluated. Finally, the winding tightness data and the vacuum sealing effect evaluation data are collected, and it is found that the optimal combination of winding tightness and packaging parameters can achieve the highest sealing effect. The sealing test results show that the gas leakage rate is less than 1%.

[0162] Step S54: Perform multi-objective optimization analysis based on the pipeline positioning accuracy evaluation data, the winding tightness data, and the vacuum sealing effect evaluation data, so as to obtain an optimized design solution for the packaging system.

[0163] The embodiment of the present invention performs multi-objective optimization analysis based on pipeline positioning accuracy evaluation data, winding tightness data, and vacuum sealing effect evaluation data. Specific steps include setting optimization goals, such as minimizing packaging costs, maximizing sealing effects, and optimizing pipeline positioning accuracy. Use optimization algorithms (such as genetic algorithms or particle swarm optimization) to search for the optimal solution in different packaging parameter combinations (such as temperature, pressure, and time). After multiple iterations and evaluations, the optimal design scheme for the packaging system is finally obtained, in which the recommended heat sealing temperature is set to 185°C, the pressure is 0.55MPa, and the time is 3 seconds. These parameters can achieve the highest overall packaging performance.

[0164] The present invention establishes a multi-physics coupling model based on packaging behavior simulation data and vacuum packaging effect simulation data, and can comprehensively consider the interaction of multiple physical fields such as heat, fluid and solid mechanics. This multi-physics model can provide a more realistic and comprehensive system behavior analysis, reveal the influence of each physical field on the packaging process, and provide a scientific basis for subsequent accuracy evaluation and optimization. Through a more comprehensive model, the design team can better understand the performance of the packaging system under different conditions, and then make more effective design adjustments. The positioning accuracy of the infusion pipeline during the packaging process is analyzed using a multi-physics coupling model, and pipeline positioning accuracy evaluation data can be generated. This analysis helps to identify the position deviation that may occur in the pipeline during the packaging process and ensure the accurate positioning of the pipeline in the final product. High positioning accuracy can ensure the functionality and safety of the product and reduce the use risk caused by inaccurate positioning. In addition, through precise positioning, production efficiency will also be improved, reducing unnecessary adjustments and rework. Based on the multi-physics coupling model, the winding tightness of the infusion pipeline is evaluated, and the influence of different packaging parameters (such as heat sealing temperature, pressure and time) on the sealing effect is analyzed, and winding tightness data and vacuum sealing effect evaluation data can be generated. The optimization of winding tightness directly affects the sealing performance and stability of the package, ensuring the safety of the product during transportation and storage. By evaluating the impact of different packaging parameters, the design team can find the best packaging conditions to improve the overall quality and reliability of the package and prevent leakage or contamination during use. Based on the pipeline positioning accuracy evaluation data, winding tightness data, and vacuum sealing effect evaluation data, a multi-objective optimization analysis can be performed to obtain the optimal design scheme of the packaging system. This process takes different design goals into consideration to ensure that the use of resources and production costs are optimized while meeting all performance requirements. Through multi-objective optimization, the efficiency and economy of the design can be achieved, and ultimately the market competitiveness and user satisfaction of the product can be improved. Overall, through the implementation of these steps, the design quality and production efficiency of the packaging system can be effectively improved. The establishment of a multi-physics field coupling model enables a deeper understanding of the behavior of complex systems, thereby ensuring the stability and safety of the product under different physical conditions. At the same time, accurate positioning and winding evaluation help improve the packaging quality of the product and prevent potential quality problems. In addition, through multi-objective optimization analysis, the design team can develop a more forward-looking design scheme, promote the effective use of resources and reduce production costs, and further enhance the market competitiveness and brand image of the enterprise.

[0165] Therefore, the embodiments should be regarded as illustrative and non-restrictive from all points, and the scope of the present invention is limited by the appended claims rather than the above description, and it is therefore intended that all changes falling within the meaning and range of equivalent elements of the application documents are included in the present invention.

[0166] The above description is only a specific embodiment of the present invention, so that those skilled in the art can understand or implement the present invention. Various modifications to these embodiments will be apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the present invention. Therefore, the present invention will not be limited to the embodiments shown herein, but should conform to the widest scope consistent with the principles and novel features invented herein.

Claims

1. A simulation design method for a conveying mechanism of an assembly machine, characterized in that: The following steps are involved: Step S1: obtaining physical property data of a disposable infusion set pipeline; establishing a pipeline flexibility simulation model based on flexibility characteristics according to the physical property data, and performing a mechanical analysis of bending, twisting and mutual contact of the infusion set pipeline based on a winding method, thereby generating deformation simulation data of the flexible pipeline; performing pipeline flexibility simulation on the pipeline flexibility simulation model according to the deformation simulation data, thereby obtaining simulation data of pipeline winding behavior; Step S2: obtaining material property data of the plastic film during the hot melt sealing process, and performing a thermal-fluid-solid coupling analysis on the material property data, thereby obtaining phase change transfer coupling data; According to the phase change transfer coupling data, the temperature field distribution, melting and solidification process of the plastic film during the infusion set packaging process are estimated, and the packaging pressure change analysis is performed, and the plastic film flow and solidification simulation is performed to obtain the packaging effect simulation data; Step S3: performing packaging simulation analysis on the wound infusion set tube according to the deformation simulation data and the packaging effect simulation data, and simulating the position adjustment of the infusion set tube in the blister packaging array in the simulation, so as to obtain packaging behavior simulation data; Step S4: analyzing the effect of air exhaust inside the packaging bag based on the temperature distribution and pressure change according to the packaging effect simulation data, thereby obtaining air exhaust efficiency simulation data; Using a vacuum pump to simulate air extraction based on air exhaust efficiency simulation data to generate vacuum packaging effect simulation data; Step S5: Perform a multi-physics field comprehensive analysis on the positioning, winding tightness and vacuum sealing effect of the infusion set tubing during the packaging process according to the packaging behavior simulation data and the vacuum packaging effect simulation data, so as to generate an optimal design scheme for the packaging system.

2. The simulation design method of the conveying mechanism of the assembly machine according to claim 1, characterized in that: Step S1 includes the following steps: Step S11: collecting the length, inner and outer diameters, and wall thickness information of the disposable infusion set pipeline, thereby obtaining pipeline geometry data; Step S12: Acquire the elastic modulus, Poisson's ratio and density data of the infusion set tubing material, thereby generating material physical property data; Step S13: measuring the change of mechanical properties of the infusion set pipeline at different temperatures, thereby obtaining mechanical property data; Step S14: merging pipeline geometry data, material physical property data and mechanical property data into physical property data; Step S15: establishing a pipeline flexibility simulation model based on flexibility characteristics according to the physical property data, and performing a mechanical analysis of the bending, twisting and mutual contact of the infusion set pipeline based on the winding method, thereby generating deformation simulation data of the flexible pipeline; Step S16: Perform a pipeline flexibility simulation model on the pipeline flexibility simulation model according to the deformation simulation data, so as to obtain pipeline winding behavior simulation data.

3. The simulation design method of the conveying mechanism of the assembly machine according to claim 2 is characterized in that: Step S15 includes the following steps: Step S151: performing material stress-strain curve analysis according to the physical property data of the infusion set pipeline, thereby obtaining stress-strain relationship data; Step S152: Establishing a constitutive model for the pipeline material according to the stress-strain relationship data, and analyzing the influence of temperature on the constitutive model according to the mechanical property data, thereby obtaining a pipeline material characteristic data set; Step S153: establishing a three-dimensional geometric model of the pipeline according to the geometric information in the physical property data, and integrating the material properties of the three-dimensional geometric model according to the pipeline material property data set, thereby obtaining a material property integrated model; Step S154: setting meshing parameters for the material property integrated model, and determining boundary conditions and loading methods, thereby obtaining a pipeline flexibility simulation model; Step S155: performing mechanical analysis on the infusion set pipeline according to the preset infusion set pipeline winding model, thereby obtaining a pipeline stress state data set, wherein the mechanical analysis includes bending stress and strain distribution analysis, pipeline torsion analysis, and contact force distribution analysis; Step S156: applying the pipeline stress state data set to the pipeline flexibility simulation model to perform static nonlinear analysis based on deformation under winding state, thereby obtaining static deformation data, and simulating transient deformation behavior during winding, thereby obtaining dynamic deformation data; Step S157: Perform pipeline deformation simulation based on node displacement and stress distribution using static deformation data and dynamic deformation data, thereby generating deformation simulation data of the flexible pipeline.

4. The simulation design method for the conveying mechanism of the assembly machine according to claim 3 is characterized in that: Step S155 includes the following steps: Step S1551: determining the geometric configuration of the pipeline winding according to the preset infusion set pipeline winding model, thereby obtaining winding geometric parameter data, wherein the geometric configuration of the pipeline winding includes winding diameter, winding number and winding pitch; Step S1552: Calculating the curvature distribution of the pipeline in the winding state according to the winding geometric parameter data, thereby obtaining the pipeline curvature distribution data; Step S1553: Calculate the bending stress using the pipeline curvature distribution data and the pipeline material characteristic data set, thereby obtaining the pipeline bending stress distribution data; Step S1554: Calculating the torsional stress based on the torsional angle of each section of the pipeline based on the winding geometric parameter data, thereby obtaining pipeline torsional stress data; Step S1555: identifying the contact points of the infusion set tubing winding model during the tubing winding process, and calculating the normal force and tangential force of the contact points, thereby obtaining contact force distribution data; Step S1556: Combine the pipeline bending stress distribution data, pipeline torsional stress data and contact force distribution data into pipeline strain distribution data, and perform axial tension and compression effect analysis to obtain a pipeline stress state data set.

5. The simulation design method for the conveying mechanism of the assembly machine according to claim 4, characterized in that: Step S16 includes the following steps: Step S161: geometrically updating the pipeline flexibility simulation model according to the node displacement information of the deformation simulation data, thereby obtaining an updated pipeline geometric model; Step S162: applying a preload based on the deformation prestress that may be generated during the winding process to the infusion set pipeline according to the pipeline geometric model, thereby generating preload data; Step S163: using the preload data to set mechanical boundary conditions for pipeline winding, thereby determining winding boundary condition data, wherein the mechanical boundary conditions include boundary conditions of bending, torsion and contact stress; Step S164: performing mechanical analysis of the flexible pipeline during the winding process according to the winding boundary condition data, and calculating the deformation amplitude and force change of the pipeline at different winding positions, thereby obtaining stress data of the winding position; Step S165: performing local stress concentration area analysis based on the winding position stress data and the pipeline material characteristic data set, and optimizing the winding parameters of the infusion set pipeline winding model, thereby obtaining winding parameter optimization data; Step S166: Perform pipeline flexibility simulation using winding parameter optimization data and pipeline geometric model to obtain pipeline winding behavior simulation data.

6. The simulation design method for the conveying mechanism of the assembly machine according to claim 5, characterized in that: Step S2 includes the following steps: Step S21: obtaining material property data of the plastic film during the hot melt sealing process, including melting point, specific heat capacity, thermal conductivity, viscosity-temperature relationship and crystallization kinetic parameters; Step S22: Establishing a multi-scale structural model of the plastic film material according to the material thermal property data, thereby obtaining a material microstructure model, wherein the multi-scale structure includes the structures of molecular chains, crystals, and amorphous regions; Step S23: constructing a heat-fluid-solid coupling analysis model based on the coupling of heat conduction equations, fluid mechanics equations and solid mechanics equations according to the material microstructure model, thereby obtaining phase change transfer coupling data; Step S24: estimating the temperature field distribution, melting and solidification process of the plastic film during the packaging of the infusion set according to the phase change transfer coupling data, analyzing the packaging pressure change, and simulating the flow and solidification of the plastic film, thereby generating temperature change and phase change simulation data of the solidification process; Step S25: Simulate the packaging effect of the plastic film based on the temperature change and phase change simulation data, and analyze the packaging effect based on sealing, strength and airtightness, thereby obtaining packaging effect simulation data.

7. The simulation design method for the conveying mechanism of the assembly machine according to claim 6, characterized in that: Step S24 includes the following steps: Step S241: performing temperature field simulation of the plastic film during the hot melt sealing process according to the phase change transfer coupling data, thereby obtaining temperature distribution data; Step S242: simulating the temperature distribution of the plastic film during the heating stage according to the temperature distribution data, and predicting the melting behavior, thereby generating melting simulation data; Step S243: Based on the melting simulation data, the flow behavior of the plastic film during the sealing process is simulated based on the flow path, thickness change and contact surface morphology of the melted plastic, thereby obtaining plastic flow simulation data; Step S244: performing phase change analysis on the solidification behavior of the plastic film after cooling according to the plastic flow simulation data, thereby generating temperature change and phase change simulation data of the solidification process.

8. The simulation design method for the conveying mechanism of the assembly machine according to claim 7, characterized in that: Step S3 includes the following steps: Step S31: constructing a three-dimensional geometric model of the infusion set pipeline after winding according to the deformation simulation data and the packaging effect simulation data, obtaining the geometric dimensions and material property data of the blister packaging array, and establishing an initial assembly model of the infusion set pipeline and the blister packaging, thereby obtaining initial assembly data; Step S32: Performing a static interference check on the initial assembly data, identifying the collision point between the pipeline and the package, and optimizing and adjusting the position of the infusion set pipeline in the blister packaging array, thereby obtaining position adjustment data; Step S33: using the position adjustment data to perform dynamic insertion simulation on the initial assembly model, and simulating the deformation and stress distribution of the pipeline during the insertion into the package, evaluating the stability and fixation effect of the pipeline in the package, thereby obtaining fixation effect data; Step S34: performing pipeline displacement and deformation analysis during the packaging process according to the fixed effect data, and performing local optimization on the packaging design, thereby obtaining optimized design data; Step S35: Dynamically simulate the position in the blister packaging array according to the optimized design data and the initial assembly data, so as to obtain packaging behavior simulation data.

9. The simulation design method for the conveying mechanism of the assembly machine according to claim 8, characterized in that: Step S4 includes the following steps: Step S41: extracting the geometric shape, material properties, sealing area structure and thickness distribution information of the packaging bag according to the packaging effect simulation data, thereby generating three-dimensional geometric model data; Step S42: using the three-dimensional geometric model data to set the temperature field distribution of the packaging material, and simulating the thermal conduction behavior of the material during the sealing process, thereby obtaining thermal conduction data of the sealing area, wherein the temperature field distribution includes the temperature gradient of the sealing area and the material softening area; Step S43: Preliminarily calculating the air volume in the packaging bag according to the heat conduction data of the sealing area and the three-dimensional geometric model data, and simulating the exhaust of air inside the packaging bag to generate preliminary air exhaust effect data; Step S44: performing air extraction dynamic simulation based on vacuum pump simulation according to the preliminary air exhaust effect data, analyzing the residual air volume inside the packaging bag based on air flow and vacuum degree changes, thereby generating residual air distribution data; Step S45: analyzing the air exhaust efficiency at different positions in the packaging bag according to the residual air distribution data, and generating air exhaust efficiency simulation data; Step S46: using a vacuum pump to perform air extraction simulation according to the air exhaust efficiency simulation data to generate vacuum packaging effect simulation data.

10. The simulation design method for the conveying mechanism of the assembly machine according to claim 9, characterized in that: Step S5 includes the following steps: Step S51: establishing a multi-physics field coupling model according to packaging behavior simulation data and vacuum packaging effect simulation data; Step S52: Analyze the positioning accuracy of the infusion tube during the packaging process using a multi-physics field coupling model, thereby obtaining the evaluation data of the tube positioning accuracy; Step S53: evaluating the winding tightness of the infusion set tubing based on the multi-physics field coupling model, and performing a vacuum sealing process to evaluate the influence of different packaging parameters on the sealing effect, thereby obtaining winding tightness data and vacuum sealing effect evaluation data, wherein the packaging parameters include heat sealing temperature, pressure and time; Step S54: Perform multi-objective optimization analysis based on the pipeline positioning accuracy evaluation data, the winding tightness data, and the vacuum sealing effect evaluation data, so as to obtain an optimized design solution for the packaging system.

Images