Structure optimization method and system for vacuum sewage suction pipeline system

Abstract

The invention relates to the technical field of vacuum sewage suction trucks, and discloses a structure optimization method and system of a vacuum sewage suction pipeline system. The method comprises the following steps: determining a to-be-optimized part of the vacuum sewage suction pipeline system, and determining a to-be-optimized structure parameter X and a target evaluation parameter Y of the to-be-optimized part; analyzing internal fluid characteristics of the to-be-optimized part by adopting numerical simulation software, and determining a design range of X; designing a test table according to the design range of the X, calculating to obtain test sample data, and calculating to obtain a response relationship between the X and the Y according to the test data; and constructing an optimization objective function, and finding an optimal solution of the optimization objective function in the design range of the X by adopting an optimization algorithm. The system comprises an analysis module, a fitting module and an optimization module. The structure of the vacuum sewage suction pipeline system is optimized, the optimization efficiency is high, the optimization cost is low, and the reliability of the optimization result is good.

Description

Technical Field

[0001] The invention relates to the technical field of vacuum sewage suction vehicles, and in particular to a structure optimization method and system for a vacuum sewage suction pipeline system. Background Art

[0002] As an important tool for underground pipe network maintenance, vacuum sewage suction trucks play a key role in dredging and draining sewage. In the prior art, vacuum sewage suction trucks are important equipment for underground pipe network maintenance, which mainly cleans underground pipe networks through vacuum pumps and pipe systems. However, the design of its pipe system mostly relies on experience and lacks systematic optimization methods, resulting in low overall efficiency and rapid structural wear. These problems seriously affect the service life and work efficiency of the equipment. Summary of the invention

[0003] Based on the above, the purpose of the present invention is to provide a structural optimization method and system for a vacuum sewage suction pipeline system, so as to achieve structural optimization of the vacuum sewage suction pipeline system, with high optimization efficiency, low optimization cost and better reliability of optimization results.

[0004] To achieve the above object, the present invention adopts the following technical solutions:

[0005] A structural optimization method for a vacuum sewage suction pipeline system, comprising:

[0006] Determine the part to be optimized of the vacuum sewage suction pipeline system, and determine the structural parameter X to be optimized and the target evaluation parameter Y of the part to be optimized;

[0007] Numerical simulation software is used to analyze the internal fluid characteristics of the part to be optimized, and the design range of the structural parameter X to be optimized is determined;

[0008] Design a test table according to the design range of the structural parameter to be optimized, obtain test sample data by experimental calculation according to the test table, and calculate the response relationship between the structural parameter X to be optimized and the target evaluation parameter Y according to the test data;

[0009] An optimization objective function is constructed, and an optimization algorithm is used to find the optimal solution of the optimization objective function within the design range of the structural parameter X to be optimized, wherein the optimal solution is the structural parameter X′ of the optimized part corresponding to the structural parameter X to be optimized of the part to be optimized.

[0010] The present invention also provides a structure optimization system for a vacuum sewage suction pipeline system, comprising:

[0011] An analysis module, used to analyze the internal fluid characteristics of the part to be optimized and determine the design range of the structural parameter X to be optimized;

[0012] A fitting module is used to design a test table according to the design range of the structural parameter to be optimized, and obtain test sample data by experimental calculation according to the test table, and calculate the response relationship between the structural parameter X to be optimized and the target evaluation parameter Y according to the test data;

[0013] The optimization module is used to construct an optimization objective function and use an optimization algorithm to find the optimal solution of the optimization objective function within the design range of the structural parameter X to be optimized, wherein the optimal solution is the structural parameter X′ of the optimized part corresponding to the optimized structural parameter X of the part to be optimized.

[0014] The beneficial effects of the present invention are:

[0015] The present invention provides a structural optimization method for a vacuum sewage suction pipeline system. The design range of the structural parameters to be optimized is determined according to the internal fluid characteristics of the part to be optimized, so that the design range is reasonable and reliable, the subjectivity of artificially demarcated ranges is reduced, and the optimization efficiency is improved. A reliable and effective range is also provided for the establishment of subsequent test tables, so that the test sample data is more reasonable. By combining the response relationship between the structural parameters to be optimized and the target evaluation parameters and the optimization algorithm, the optimal structural parameters within the design range can be found quickly and reliably to achieve the optimization of the part to be optimized. The structural optimization method for the vacuum sewage suction pipeline system realizes the structural optimization of the vacuum sewage suction pipeline system to improve the working performance of the vacuum sewage suction pipeline system. The method has high optimization efficiency and low optimization cost.

[0016] The present invention also provides a structure optimization system for a vacuum sewage suction pipeline system, which realizes the structure optimization of the vacuum sewage suction pipeline system through an analysis module, a fitting module and an optimization module, has high optimization efficiency and a more reliable optimized structure. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following briefly introduces the drawings required for use in the description of the embodiments of the present invention. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on the contents of the embodiments of the present invention and these drawings without paying any creative work.

[0018] Figure 1 is a flow chart of a method for optimizing the structure of a vacuum sewage suction pipeline system provided by an embodiment of the present invention;

[0019] Figure 2 Schematic diagram of main structural parameters of a cyclone separator provided by an embodiment of the present invention;

[0020] Figure 3 is a mesh diagram of a fluid calculation domain after mesh division of a cyclone separator provided in an embodiment of the present invention;

[0021] Figure 4 is a static pressure cloud diagram of a cyclone separator before optimization provided by an embodiment of the present invention;

[0022] Figure 5 is a velocity vector diagram of a cyclone separator before optimization provided by an embodiment of the present invention;

[0023] Figure 6 It is a schematic diagram of main structural parameters of the sewage suction pipeline provided by an embodiment of the present invention;

[0024] Figure 7 is a grid diagram after grid division of the sewage suction pipe provided in an embodiment of the present invention;

[0025] Figure 8 yes Figure 7 Medium AA perspective image;

[0026] Fig. 9 is a maximum erosion rate curve diagram under different sewage flow rates provided by an embodiment of the present invention;

[0027] Fig.10 is a maximum erosion rate curve diagram under different particle mass flow rates provided by an embodiment of the present invention;

[0028] Fig.11 is a maximum erosion rate curve diagram under different particle sizes provided by an embodiment of the present invention;

[0029] Fig.12 is a maximum erosion rate curve diagram under different fluid viscosities provided by an embodiment of the present invention;

[0030] Fig.13 It is a static pressure cloud diagram of the sewage suction pipeline before optimization provided by an embodiment of the present invention;

[0031] Fig.14 is a velocity cloud diagram of the sewage suction pipeline before optimization provided by an embodiment of the present invention;

[0032] Fig.15 is a cloud diagram of the maximum erosion and wear rate of the sewage suction pipe before optimization provided by an embodiment of the present invention;

[0033] Fig.16 is a partial solid particle trace diagram of the sewage suction pipeline before optimization provided by an embodiment of the present invention;

[0034] Fig.17 is a curve diagram showing the effect of cylinder diameter on cyclone separator performance provided by an embodiment of the present invention;

[0035] Fig.18 is a curve diagram showing the effect of cylinder height on cyclone separator performance provided by an embodiment of the present invention;

[0036] Fig.19 is a curve diagram showing the effect of the exhaust pipe insertion depth on the cyclone separator performance provided by an embodiment of the present invention;

[0037] Fig. 20 is a curve diagram showing the effect of the elbow angle on the performance of the sewage suction pipe provided by an embodiment of the present invention;

[0038] Fig.21 is a curve diagram showing the effect of the transition metal pipeline length on the performance of the sewage suction pipeline provided by an embodiment of the present invention;

[0039] Fig. 22 is a curve diagram showing the effect of pipe diameter on the performance of a sewage suction pipe provided by an embodiment of the present invention;

[0040] Fig.23 is a static pressure cloud diagram of an optimized cyclone separator provided by an embodiment of the present invention;

[0041] Fig.24 is a velocity vector diagram of an optimized cyclone separator provided by an embodiment of the present invention;

[0042] Fig.25 is an internal particle trajectory diagram of an optimized cyclone separator provided by an embodiment of the present invention;

[0043] Fig.26 It is a static pressure cloud diagram of the optimized sewage suction pipeline provided by an embodiment of the present invention;

[0044] Fig. 27 is a velocity vector diagram of the optimized sewage suction pipeline provided by an embodiment of the present invention;

[0045] Fig.28 is an internal particle trajectory diagram of an optimized sewage suction pipeline provided by an embodiment of the present invention;

[0046] Fig.29 is a curve of system absolute pressure variation during a real vehicle test provided by an embodiment of the present invention;

[0047] Fig.30 This is a curve of suction speed variation during a real vehicle test provided by an embodiment of the present invention.

[0048] In the figure:

[0049] 1. Cyclone separator; 2. Sewage suction pipe. DETAILED DESCRIPTION

[0050] In the embodiments of the present application, words such as "exemplary" or "for example" are used to indicate examples, illustrations or descriptions. Any embodiment or design described as "exemplary" or "for example" in the embodiments of the present application should not be interpreted as being more preferred or more advantageous than other embodiments or designs. Specifically, the use of words such as "exemplary" or "for example" is intended to present related concepts in a specific way.

[0051] In the embodiments of the present application, the terms "first" and "second" are used for descriptive purposes only and are not to be understood as indicating or implying relative importance or implicitly indicating the number of the indicated technical features. Thus, a feature defined as "first" or "second" may explicitly or implicitly include one or more of the features. In the description of the present application, unless otherwise specified, "plurality" means two or more.

[0052] The term "at least one" in this application means one or more, and the term "multiple" in this application means two or more, for example, multiple second messages means two or more second messages. The terms "system" and "network" are often used interchangeably herein.

[0053] It should be understood that the terms used in the description of the various examples herein are only for describing specific examples and are not intended to be limiting. As used in the description of the various examples and the appended claims, the singular forms "a", "an", and "the" are intended to include the plural forms as well, unless the context clearly indicates otherwise.

[0054] It should also be understood that the term "and / or" used herein refers to and encompasses any and all possible combinations of one or more of the associated listed items. The term "and / or" is a description of the association relationship of associated objects, indicating that three relationships may exist. For example, A and / or B can represent: A exists alone, A and B exist at the same time, and B exists alone. In addition, the character " / " in this application generally indicates that the associated objects before and after are in an "or" relationship.

[0055] It should also be understood that in the various embodiments of the present application, the size of the serial number of each process does not mean the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of the present application.

[0056] It should be understood that determining B based on A does not mean determining B only based on A. B can also be determined based on A and / or other information.

[0057] It should also be understood that the term “comprise” (also known as “includes,” “including,” “comprises” and / or “comprising”) when used in this specification specifies the presence of stated features, integers, steps, operations, elements, and / or components, but does not preclude the presence or addition of one or more other features, integers, steps, operations, elements, components, and / or groups thereof.

[0058] It should also be understood that the term "if" may be interpreted to mean "when" or "upon" or "in response to determining" or "in response to detecting." Similarly, the phrase "if it is determined that ..." or "if [a stated condition or event] is detected" may be interpreted to mean "upon determining that ..." or "in response to determining that ..." or "upon detecting [a stated condition or event]" or "in response to detecting [a stated condition or event]," depending on the context.

[0059] It should be understood that the references to "one embodiment", "an embodiment", or "a possible implementation" throughout the specification mean that specific features, structures, or characteristics related to the embodiment or implementation are included in at least one embodiment of the present application. Therefore, the references to "in one embodiment" or "in an embodiment", or "a possible implementation" appearing throughout the specification do not necessarily refer to the same embodiment. In addition, these specific features, structures, or characteristics may be combined in any suitable manner in one or more embodiments.

[0060] like Figure 1 As shown, this embodiment provides a structure optimization method for a vacuum sewage suction pipeline system, and the structure optimization method for a vacuum sewage suction pipeline system includes the following steps:

[0061] S1: Determine the part to be optimized of the vacuum sewage suction pipeline system, and determine the structural parameter X to be optimized and the target evaluation parameter Y of the part to be optimized, including:

[0062] S11: The pipeline system of the vacuum sewage suction truck mainly includes two parts: the air suction pipeline and the sewage suction pipeline. Among them, the core of the air suction pipeline is the cyclone separator, and the corners of the sewage suction pipeline are severely worn. Therefore, the cyclone separator and the sewage suction pipeline in the air suction pipeline are determined to be the parts to be optimized.

[0063] S12: Establish physical models and mathematical models of the cyclone separator and the sewage suction pipe respectively, and use numerical simulation software to analyze the internal flow field characteristics of the cyclone separator and the sewage suction pipe, and then determine the structural parameters X to be optimized based on the characteristics, and the structural parameters X to be optimized include the cylinder height H and cylinder diameter D of the cyclone separator. 1 , the exhaust pipe insertion depth S, as well as the bend angle α and pipe diameter D of the sewage suction pipe 2, the length of the metal pipe in the transition zone L;

[0064] Step S12 specifically includes the following steps:

[0065] S121: Establishing the physical model of the cyclone separator and the sewage suction pipe, including determining the two-phase flow model, determining the turbulence model, determining the particle collision model and determining the erosion and wear model.

[0066] Among them, the volume proportion of solid particles in the sewage suction pipeline and the air exhaust pipeline is less than 10%, and the movement trajectory of the solid particles needs to be analyzed and simulated. In this embodiment, the DPM discrete phase model is used as the two-phase flow model. The discrete particle model takes the liquid phase as the continuous medium and is solved through the continuous model, while the particle phase is taken as the discrete phase and is solved by tracking the movement trajectory of the particles.

[0067] Among them, for the complex flow field distribution inside the cyclone separator, this embodiment uses the Reynolds stress model (RSM) as the basis for the numerical simulation analysis of the cyclone separator. When calculating the turbulent stress, the Reynolds stress model mainly solves the turbulent pulsation stress term in the Reynolds transport equation by directly establishing a differential equation, while taking into account the anisotropy of turbulence. The flow inside can be described by the Navier-Stokes equation:

[0068]

[0069]

[0070] Where v is the fluid velocity, p is the pressure, τ is the stress tensor, and f is the external force.

[0071] It is specifically expressed in the finite element software as follows:

[0072]

[0073] Where D i，j is the diffusion term,

[0074]

[0075] P i，j is the stress generating term,

[0076] G i，j is the buoyancy generating term,

[0077] Φ i，j is the pressure-strain redistribution term,

[0078] ε i，j is a discrete term,

[0079] F i，j Generate terms for the rotating system,

[0080] S user User-defined items.

[0081] Among them, for the solid-liquid two-phase flow in the sewage suction pipe, the "RNG" κ-ε model is used as the turbulence model for the sewage suction pipe fluid analysis in this embodiment to improve the analysis accuracy for the vortex flow. The expression is as follows:

[0082]

[0083]

[0084] Where: κ, ε——turbulent kinetic energy and its dissipation rate;

[0085] u i , μ eff ——the flow rate of sewage and its dynamic viscosity;

[0086] G κ , G b ——The turbulent kinetic energy term is generated by the velocity gradient and buoyancy;

[0087] C 1 , C 2 , C 3 , α ε , α κ ——constant term;

[0088] S κ , S ε ——User-defined;

[0089] σ κ , σ ε ——turbulent Prandtl number in the kappa equation and the epsilon equation;

[0090] Y M ——Contribution of wave expansion to the total dissipation rate in compressible flow.

[0091] In the process of fluid flow inside the sewage suction pipe, solid particles collide with the inner wall of the pipe continuously, causing the direction of movement of the particles to change before and after the collision. At the same time, the kinetic energy of the particles will also be lost during the collision, resulting in a change in the magnitude of their velocity. Therefore, in order to accurately obtain the velocity change of the particles during the entire collision process, a collision model is established and the collision elastic recovery coefficient is introduced. The changes in tangential and normal momentum before and after the collision are expressed as e n and e τ Represents. Its expression is as follows:

[0092]

[0093] In the formula, u p1 、u p2 、v p1 and v p2 They represent the tangential and normal components of the solid particle velocity at the beginning and end of the collision process, respectively.

[0094] In the process of fluid flow inside the sewage suction pipe, solid particles collide with the inner wall of the pipe continuously, so that the movement direction of the particles changes before and after the collision. At the same time, the kinetic energy of the particles is also lost during the collision, resulting in a change in the magnitude of their velocity. The mathematical model of the sewage suction pipe established in this embodiment also includes an erosion wear model, and the erosion rate formula is as follows:

[0095]

[0096] Where m is the particle mass flow rate; C(d p ) represents the particle size function; α is the impact angle between the particle trajectory and the pipe wall; f(α) is the impact angle function; n is the velocity index; V is the relative velocity between the solid particle and the inner wall of the pipe; A face It is the total inner wall area of ​​the sewage suction pipe.

[0097] This is reflected in the finite element software as:

[0098]

[0099] in, is the erosion wear rate, K is a constant, ρ p is the particle density, v p is the particle velocity, d p is the particle diameter, d h is the pipe diameter, and n is the experimental fitting coefficient.

[0100] S122: Establish mathematical model of cyclone separator and sewage suction pipe:

[0101] S1221: Establish a three-dimensional model of the cyclone separator, perform meshing and boundary condition setting, and use numerical simulation software to calculate and analyze the internal flow field characteristics of the cyclone separator to determine the structural parameters of the cyclone separator to be optimized;

[0102] In the process of structural design of the exhaust pipeline, factors such as the installation space on the sewage collection tank and the chassis, the internal flow field distribution, the particle separation efficiency and the energy loss need to be considered. When establishing the exhaust pipeline model, in order to simplify the calculation, the vacuum pump, anti-overflow device and other structures that have little effect on the internal flow field of the pipeline are ignored, and the pipeline part and the main structure such as the cyclone separator are retained. Figure 2 As shown, the simplified main structural parameters of the exhaust pipeline and the cyclone separator 1 include: the exhaust pipeline diameter D L , total length of the exhaust pipe, diameter of the cyclone separator inlet pipe d 1 , Exhaust pipe diameter d 2 , cylinder diameter D, straight cylinder height H 1 , cone height H 2 , the exhaust pipe insertion depth s and the dust collection port diameter t. Among them, the exhaust pipe diameter D L It directly affects the fluid flow rate and resistance loss in the pipeline. When the vacuum pump has a certain suction volume, the larger the diameter of the suction pipeline, the lower the air flow rate in the pipeline, and the pressure loss along the suction pipeline and the local pressure loss will decrease accordingly. At the same time, an increase in the total length of the suction pipeline will also lead to an increase in the pressure loss along the pipeline. During the design process, the selection of the suction pipeline diameter and the total length of the pipeline is limited by the installation space of the chassis and the tank body and the pipeline cost. Therefore, the main focus is on the analysis of the cyclone separator structural parameters. For example, in the cyclone separator under the initial structure, the diameter d of the cyclone separator inlet pipe is 1 Exhaust pipe diameter d 2 The diameter of the cylinder is 100 mm, the cylinder diameter D is 380 mm, and the height of the straight cylinder is H 1 The cone height is 450mm. 2 The exhaust pipe insertion depth s is 500mm and 150mm.

[0103] After the three-dimensional model of the cyclone separator is established, the structured meshing of the cyclone separator fluid domain model is performed to control the number of meshes while avoiding large errors in the calculation results caused by unstructured meshes. Figure 3 Shown is the grid diagram of the cyclone separator fluid calculation domain after division.

[0104] The flow process of the dust-laden airflow in the cyclone separator is simulated by numerical simulation software such as fluent software, and the discrete phase model is used as the two-phase flow model and the Reynolds stress model is used as the turbulence model.

[0105] Set the cyclone separator inlet as velocity inlet, and the flow rate calculation formula is:

[0106]

[0107] Where: v – cyclone separator inlet velocity, m / s;

[0108] Q——Vacuum pump suction volume, m 3 / s;

[0109] A——cyclone separator inlet cross-sectional area, m 2 .

[0110] For example, the vacuum pump has a suction capacity of 660 m 3 / h, the inlet diameter of the cyclone separator is 100mm, and the calculated inlet flow velocity v of the cyclone separator is 23m / s.

[0111] The outlet of the cyclone separator is set as a pressure outlet (Pressure-outlet). For example, the outlet pressure of the cyclone separator is measured by a vacuum pressure gauge when it is working stably, and is approximately -75500Pa.

[0112] That is, the boundary conditions are set as: velocity inlet, 23 "m / s"; pressure outlet, -75500 "Pa"; no slip wall. For example, the discrete phase parameters are set as shown in Table 1 below:

[0113] Table 1 Discrete phase particle parameters

[0114]

[0115] Wherein, the particle size of solid particles refers to the following Table 2:

[0116] Table 2 Solid particle size distribution

[0117]

[0118] Computational analysis is performed through Fluent, such as Figure 4 As shown in the figure, it can be seen that the static pressure distribution of the cyclone separator has good symmetry, and the pressure gradually decreases from the separator wall to the center. The center presents a low-pressure belt extending to the exhaust pipe, and a certain "tail swing" phenomenon occurs near the dust collection port. At the exhaust pipe inlet, due to the sudden change in structure, a large local pressure loss occurs here. Figure 5It can be seen from the velocity vector diagram of the Z=0 section of the cyclone separator that the velocity field inside the cyclone separator also basically presents a symmetrical distribution and is divided into two layers of flow, inner and outer. Among them, the direction of the outer layer velocity at the separator wall is opposite to the direction of the inner layer velocity in the central area. The dust-laden airflow moves along the wall to the bottom, and the solid particles are captured by the dust collecting port; the airflow in the central area moves toward the exhaust pipe, forming an upward air column, and there is an obvious vortex phenomenon in this area. The airflow velocity at the inlet of the exhaust pipe increases sharply due to the structural mutation. This area will cause the solid particles in the dust-laden airflow to be captured as soon as they enter the cyclone separator and be directly discharged through the exhaust pipe, causing "short-circuit flow". It can be seen from this that the cyclone separator under the initial structure has a sudden pressure change at the exhaust pipe, the local pressure loss is large, and there is an obvious vortex phenomenon in the flow field inside the separator. Taking the cylinder height H and cylinder diameter D of the cyclone separator as examples, 1 , the exhaust pipe insertion depth S is taken as the structural parameter of the cyclone separator to be optimized.

[0119] S1222: Establishing a three-dimensional model of the sewage suction pipe, performing mesh division and boundary condition setting, and using numerical simulation software to calculate and analyze the internal flow field characteristics of the sewage suction pipe, and determining the structural parameters of the sewage suction pipe to be optimized;

[0120] The sewage suction pipe is an important component of the vacuum sewage suction truck pipeline system for transporting sewage mixture to the sewage collection tank. Its structural parameters will directly affect the sewage suction efficiency of the system. In the structural design process of the sewage suction pipe, factors such as its height in the tank body, internal flow field distribution, erosion and wear, and energy loss need to be considered. When establishing the sewage suction pipe model, structures such as valves and pipe fixing brackets that have little effect on the internal flow field of the sewage suction pipe are ignored to simplify the calculation. To simplify the calculation, only the main sewage suction pipe part is retained. Figure 6 As shown, the main structural parameters of the pipeline include: the length of the straight pipe section inside the tank L 1 , bend angle α, transition zone metal pipe length L 2 , the diameter of the metal pipe and the suction hose d. For example, in the suction pipe under the initial structure, the bend angle α is 135°, the length of the transition metal pipe L 2 The diameter of the sewage suction pipe is 300mm, the diameter of the sewage suction pipe is 100mm, and the sewage suction depth is 4m; the pressure loss of the sewage suction pipe under the initial structure is 10749.46Pa.

[0121] The hexahedral structured mesh is used to divide the fluid domain model of the sewage suction pipe, and 10 layers of boundary layer mesh are added to the pipe wall through the FirstLayerThick-ness division method. Figure 7 and Figure 8 shown.

[0122] The flow process of sewage in the pipe is simulated by numerical simulation software such as Fluent software, and the discrete phase model is used as the two-phase flow model and the RNGκ-ε model is used as the turbulence model.

[0123] The boundary conditions of the sewage suction pipeline flow field simulation are velocity inlet and pressure outlet. For example, the tank pressure of the sewage suction truck (the outlet pressure of the sewage suction pipeline) is -74000Pa as measured by a vacuum pressure gauge.

[0124] The Bernoulli equation describes the law of energy transfer in the process of ideal fluid movement. However, during the flow of fluid, there will be friction resistance between the micro-elements inside the viscous fluid, between the fluid layers, and between the fluid and the wall of the flow pipe, so energy loss is inevitable. Considering the resistance loss term on the basis of the Bernoulli equation, the following formula is obtained:

[0125]

[0126] Where: For example, the suction depth is z = 4m; the pressures at the inlet and outlet of the suction pipe are p 1 =1.01×10 5 Pa, p 2 =0.27×10 5 Pa; sewage flow rate is v, m / s; sewage density is ρ = 1015 kg / m 3 , g is the acceleration due to gravity, take 9.8m / s 2 ;h w is the pipeline loss, Pa; h f is the resistance loss along the way, Pa; h j is the local resistance loss, Pa; pipeline diameter d = 100mm; pipeline length l = 4.8m; λ is the resistance coefficient along the way; ζ is the local resistance coefficient.

[0127] Substituting the relevant parameters into the formula, we get the suction flow rate of about 5m / s. According to the critical flow rate formula:

[0128]

[0129] In the formula, S F —Particle shape coefficient, spherical particles take 1; d pmax —Maximum particle size, m; d pm —Average particle size, m; ρ s —Solid phase particle density, take 2650kg / m 3 ρ l —Liquid density, kg / m 3 ; C d =0.44; CV —Particle volume fraction, volume fraction of solid particles in sewage C V It is about 1%. Please refer to Table 2 below for the particle size distribution of solid particles.

[0130] Table 2 Solid particle size distribution

[0131]

[0132] Obtain the critical velocity v of the fluid that satisfies the solid particle lifting condition c The velocity is 0.19 m / s, which is less than the suction velocity. Therefore, the model boundary conditions are set as: velocity inlet, 5 m / s; pressure outlet, -74000 Pa; no-slip wall.

[0133] Based on the above analysis, for example, the discrete phase parameters are set as shown in Table 3 below:

[0134] Table 3 Discrete phase particle parameters

[0135]

[0136]

[0137] In order to obtain a reasonable and reliable range of optimized structural parameters of the sewage suction pipe, it is also necessary to determine the factors affecting the erosion and wear of the sewage suction pipe, that is, to determine the optimal physical parameters of the sewage in the sewage suction pipe to maximize the efficiency of the sewage suction system. Under the condition that other conditions remain unchanged, based on the DPM discrete phase model, by changing the discrete phase and continuous phase parameters, the influence of different fluid parameters on the maximum erosion rate of the sewage suction pipe is analyzed to determine the optimal operating parameters, that is, first determine the fluid velocity, mass flow rate, particle size and fluid viscosity, which specifically includes the following steps:

[0138] Determination of fluid velocity: Set the particle mass flow rate to 1kg / s, the particle size to 0.2mm, and the fluid viscosity to 0.001Pa.s. Change the fluid velocity to obtain the maximum erosion wear rate of the sewage suction pipe. Fig. 9 As shown. Fig. 9 It can be seen that the maximum erosion rate changes approximately exponentially with the increase of inlet flow rate. When the fluid flow rate is low, its ability to carry particles is limited, so the maximum erosion wear rate is small; and as the fluid flow rate continues to increase, its ability to carry particles also increases, and the solid particles gain more kinetic energy, resulting in a more intense collision process between the particles and the sewage suction pipe, and a greater impact on the wall, which leads to a continuous increase in the growth rate of the maximum erosion wear rate.

[0139] Determination of mass flow rate: Set the fluid velocity to 5m / s, the particle size to 0.2mm, and the fluid viscosity to 0.001Pa.s. Change the particle mass flow rate to obtain the maximum erosion wear rate of the sewage suction pipe. Fig.10 As shown. Fig.10 It can be seen that the maximum erosion wear rate increases with the increase of mass flow rate. As the particle mass flow rate gradually increases, the total number of particles entering the sewage suction pipe per unit time also increases, that is, the total number of particles colliding with the inner wall of the pipe increases, and the collision impact on the inner wall of the pipe becomes more frequent and severe, which in turn causes the maximum erosion wear rate to continue to rise.

[0140] Determination of particle size: Set the fluid velocity to 5m / s, the particle mass flow rate to 1kg / s, and the fluid viscosity to 0.001Pa.s. Change the particle size to obtain the maximum erosion wear rate of the pipeline. Fig.15 As shown in the figure, when the particle size is less than 1.4 mm, the maximum erosion wear rate of the pipeline changes greatly with the increase of particle size; but when the particle size exceeds 1.4 mm, the maximum erosion wear rate is gradually reduced by the change of particle size. As the particle size increases, its mass also increases accordingly, which means that the particles have higher kinetic energy during the movement process. Therefore, when the particles hit the sewage suction pipe, the inner wall of the sewage suction pipe is more strongly impacted, resulting in a continuous increase in the maximum erosion wear rate. However, when the particle mass flow rate remains unchanged, the increase in particle size and weight will reduce the total amount of particles flowing through the sewage suction pipe per unit time, that is, the number of particles colliding with the inner wall of the sewage suction pipe will decrease. Therefore, although the maximum erosion wear rate is still rising, the amplitude of its increase will gradually decrease.

[0141] Determination of fluid viscosity: Set the fluid velocity to 5m / s, the particle size to 0.2mm, and the particle mass flow rate to 1kg / s. Change the fluid viscosity to obtain the maximum erosion wear rate of the pipeline. Fig.11 As shown. Fig.11 It can be seen that the maximum erosion wear rate decreases with the increase of fluid viscosity. As the fluid viscosity increases, the adhesion of solid particles increases, and they can better follow the flow of fluid, and the collision with the inner wall of the suction pipe when passing through the elbow area is reduced, thereby reducing the maximum erosion wear rate.

[0142] The physical parameters of the sewage in the sewage suction pipe are obtained through the above analysis, which provides the physical parameters of the sewage under the best working conditions for the subsequent fluent software calculation and analysis, so that the optimized structure of the sewage pipe is reliable.

[0143] The calculation and analysis were performed by Fluent software, such as Figures 12 to 16As shown in the figure, during the flow of sewage inside the pipeline, the static pressure distribution in the vertical pipe section at the entrance of the pipeline shows a uniform decreasing trend. The pressure loss in this section is mainly caused by the pressure loss along the flow of sewage. The velocity distribution of the vertical pipe section is relatively uniform and basically remains unchanged. It can be seen from the velocity vector cloud map of the sewage suction pipeline that when the sewage flows through the curved pipe section, due to the sudden change in the flow direction, the flow velocity at the concave wall decreases and the flow velocity at the convex wall increases. At this time, a strong secondary flow is generated inside the curved pipe, and both the pressure field and the velocity field are destroyed. The pressure distribution in the curved pipe section is opposite to the velocity distribution. Due to the low fluid velocity at the concave wall, the pressure at the concave wall increases significantly, while the pressure at the convex wall decreases significantly due to the high fluid velocity. After the sewage flows out of the metal curved pipe to the inclined straight pipe section, the pressure distribution and velocity distribution in the pipeline quickly return to uniform distribution, which is basically consistent with the distribution of the vertical pipe section. Through simulation analysis, the cloud map of the sewage suction pipe eroded by solid particles can be obtained, and the maximum erosion rate is 1.23×10 -5 kg / (m 2 ·s). In the straight pipe section at the entrance of the sewage suction pipe, the solid particles are evenly distributed in the fluid and move in a straight line; after the solid particles enter the curved pipe section with the sewage, they are affected by the continuous phase, and the direction of movement suddenly changes. Under the action of inertia, they impact the outer wall of the curved pipe, resulting in severe wear of the outer wall of the curved pipe, while the particles and the inner wall basically do not collide, so the inner wall of the curved pipe hardly suffers erosion and wear; after the solid particles flow out of the curved pipe section, a few particles collide with the inner wall of the pipe under the action of inertia, at this time the erosion and wear of the wall is small, and the remaining particles flow out of the pipe under the action of the continuous phase. It can be concluded that the curved pipe section of the sewage suction pipe is more susceptible to wear than the straight pipe section. In the curved pipe section, due to the influence of centrifugal force and local eddy current zone on the solid particles, the outer wall of the pipe is more severely impacted than the inner wall, so the erosion and wear position is mainly concentrated on the outer wall of the metal curved pipe section. After analyzing the flow field characteristics inside the sewage suction pipe, it can be found that the suction pipe under the initial structure has a sudden change in velocity at the bend, the local pressure loss is large, and the erosion and wear of the inner wall of the pipe by solid particles is serious. Therefore, the bend angle α, pipe diameter D2, and transition zone metal pipe length L of the sewage suction pipe are taken as the structural parameters to be optimized.

[0144] S13: Determine the target evaluation parameter Y according to the sewage suction efficiency and vacuuming efficiency of the vacuum sewage suction pipeline system. The target evaluation parameter Y includes the pressure loss ΔP of the cyclone separator. 1 , particle separation efficiency η, and pressure loss ΔP in the sewage suction pipe 2 , maximum erosion wear rate

[0145] Due to the limitations of the chassis and tank size of Class II vehicles, the structural design of the vacuum sewage suction truck pipeline system requires the use of elbows, hoses and other components to achieve the change of direction of the pipeline, which also leads to more corners and structural mutations in the pipeline system of the vacuum sewage suction truck. These structural changes are the main source of local resistance loss in the pipeline, which directly affects the sewage suction efficiency and vacuum efficiency of the vacuum sewage suction truck pipeline system. Therefore, when designing the structure of the vacuum sewage suction truck pipeline system, it is necessary to make reasonable optimization and improvement on the pressure loss of the fluid in the pipeline to minimize the pressure loss generated during the working process.

[0146] In order to prevent solid particles from entering the air extraction pipeline and being sucked into the vacuum pump, which would damage the vacuum pump, a cyclone separator is installed in the air extraction pipeline. During the operation of the sewage suction truck, the cyclone separator needs to separate and discharge the solid particles in the air flow to ensure the stable operation of the vacuum pump. Therefore, the particle separation efficiency needs to be used as an evaluation index for the working performance of the cyclone separator.

[0147] Vacuum sewage suction trucks are used to treat sewage containing a lot of sand particles. During operation, solid particles constantly collide with the inner wall of the sewage suction pipe, causing the metal pipe to gradually wear out or even perforate and break, making the equipment ineffective. In order to extend the service life of the structure, it is necessary to reduce the erosion wear rate of the pipe. Therefore, the erosion wear rate is used as a performance evaluation indicator for the sewage suction pipeline.

[0148] S2: Use numerical simulation software to analyze the internal fluid characteristics of the part to be optimized and determine the design range of the structural parameter X to be optimized;

[0149] S21: Specifically, the cylinder height H, cylinder diameter D 1 , the exhaust pipe insertion depth S is taken as a single variable, and the cylinder height H, cylinder diameter D are analyzed using numerical simulation software. 1 The effect of the exhaust pipe insertion depth S on the pressure loss ΔP of the cyclone separator 1 , the particle separation efficiency η, and the cylinder height H and cylinder diameter D 1 The effect of the exhaust pipe insertion depth S on the pressure loss ΔP of the cyclone separator 1 The first influence curve of the cylinder height H and cylinder diameter D are obtained 1 The second influence curves of the exhaust pipe insertion depth S on the particle separation efficiency η are obtained by taking the preset range value of the intersection of each first influence curve and each corresponding second influence curve, that is, the cylinder height H and cylinder diameter D are obtained respectively. 1 , design range of exhaust pipe insertion depth S.

[0150] S211: The cylinder diameter D 1 As a single variable, determine the design range of the barrel diameter;

[0151] For example, referring to step S2, in the initial structure, the cylinder diameter D 1 The diameter of the cylinder is 380mm, the height of the cylinder H is 450mm, and the insertion depth of the exhaust pipe is 150mm. Change the diameter of the cylinder, for example, the diameter of the cylinder is changed to 340mm, 360mm, 400mm, 420mm, 440mm, 460mm, 480mm, 500mm, 520mm in sequence, and calculate the corresponding pressure loss ΔP after each change of the cylinder diameter 1 and particle separation efficiency η, as Fig.17 As shown ( Fig.17 The pressure drop in the cyclone separator is the pressure loss ΔP 1 , separation efficiency is the particle separation efficiency), pressure loss ΔP 1 With cylinder diameter D 1 decreases with the increase of 1 <400mm, the particle separation efficiency increases with D 1 increases with the increase of 1 When the diameter is >400 mm, the particle separation efficiency increases with D 1 The particle separation efficiency changes slightly. 1 When it is smaller, the downflow area accounts for a smaller proportion, resulting in lower particle separation efficiency. 1 During the process of increasing, the maximum tangential velocity of the fluid inside the cyclone separator gradually decreases, which reduces the dynamic pressure loss and the pressure loss. At the same time, the incident particles are less affected by the rising airflow and can be fully settled under the action of the descending airflow; however, the tangential velocity of the airflow gradually decreases, resulting in a decrease in the centrifugal force on the particles, which gradually reduces the particle separation efficiency. Therefore, the cylinder diameter D 1 The reasonable design range is 400 ~ 440mm.

[0152] S212: Taking the cylinder height H as a single variable, determining the design range of the cylinder height H;

[0153] For example, referring to step S2, in the initial structure, the cylinder diameter D 1 is 380mm, the cylinder height H is 450mm, and the exhaust pipe insertion depth s is 150mm. Change the cylinder height, for example, the cylinder height is changed to 420mm, 440mm, 460mm, 480mm, 500mm, 520mm, 530mm, 540mm, 560mm, etc., and calculate the corresponding pressure loss ΔP after each change of the cylinder height 1 and particle separation efficiency η, as Fig.18 As shown ( Fig.18 The pressure drop in the cyclone separator is the pressure loss ΔP 1, the separation efficiency is the particle separation efficiency), the pressure loss gradually decreases with the increase of the cylinder height, but the change is small and the effect is not significant; when H<500mm, the particle separation efficiency increases continuously with the increase of H, and when H>500mm, the particle separation efficiency gradually decreases with the increase of H. When the cylinder height H is small, the solid particles enter the cone section before they can settle in the straight section and are discharged from the exhaust pipe with the rising airflow, resulting in low particle separation efficiency; as the straight cylinder height H increases, the solid particles can fully settle in the straight section, and the particle separation efficiency gradually increases; however, the airflow tangential velocity decreases with the increase of H, the centrifugal force on the particles decreases, and the particle separation efficiency drops sharply. Therefore, the reasonable design range of the straight cylinder height H is 490~510mm.

[0154] S213: Taking the exhaust pipe insertion depth s as a single variable, determining a design range of the exhaust pipe insertion depth s;

[0155] For example, referring to step S2, in the initial structure, the cylinder diameter D 1 The exhaust pipe insertion depth s is 380mm, the cylinder height H is 450mm, and the exhaust pipe insertion depth s is 150mm. Change the exhaust pipe insertion depth s, for example, the exhaust pipe insertion depth s is changed to 110mm, 120mm, 130mm, 140mm, 160mm, 170mm, 180mm, 190mm, 200mm, etc., and calculate the corresponding pressure loss ΔP after each change of the exhaust pipe insertion depth s. 1 and particle separation efficiency η, as Fig.19 As shown ( Fig.19 The pressure drop in the cyclone separator is the pressure loss ΔP 1 , the separation efficiency is the particle separation efficiency, the insertion depth is the exhaust pipe insertion depth s), and the pressure loss gradually increases with the increase of the exhaust pipe insertion depth s; when s<160mm, the particle separation efficiency increases with the increase of the insertion depth, and when s>160mm, the particle separation efficiency decreases with the increase of the insertion depth. When the exhaust pipe insertion depth s is small, some solid particles near the exhaust pipe are directly discharged with the rising airflow, resulting in a "short-circuit flow" phenomenon; with the increase of the exhaust pipe insertion depth s, the exhaust pipe plays a "stable vortex" role in the internal flow field, the maximum value of the fluid tangential velocity increases, and the symmetry is better, which increases the particle separation efficiency; however, with the continuous increase of the exhaust pipe insertion depth s, the velocity mutation at the exhaust pipe inlet is more obvious, the local pressure loss increases, and the solid particles are more easily affected by the airflow at the exhaust pipe inlet and discharged from the exhaust pipe, resulting in a decrease in particle separation efficiency. Therefore, the reasonable design range of the exhaust pipe insertion depth s is 140 to 160 mm.

[0156] S22: Specifically, by changing the bending angle α and the pipe diameter D of the sewage suction pipe 2, the length of the metal pipe in the transition zone L is taken as a single variable, and the numerical simulation software is used to analyze the bending angle α and the pipe diameter D of the sewage suction pipe. 2 The length of the metal pipe in the transition zone L affects the pressure loss of the sewage suction pipe ΔP 2 , maximum erosion wear rate The influence of the suction pipe bend angle α and pipe diameter D are obtained. 2 The length of the metal pipe in the transition zone L affects the pressure loss of the sewage suction pipe ΔP 2 The third influence curve, and the elbow angle α and pipe diameter D of the sewage suction pipe are obtained 2 The maximum erosion wear rate is The fourth influence curve of the third influence curve is obtained by taking the preset range value of the intersection of each third influence curve and each corresponding fourth influence curve, that is, the elbow angle α and the pipe diameter D of the sewage suction pipe are obtained respectively. 2 , design range of metal pipe length L in the transition zone.

[0157] S221: Taking the pipe bending angle α as a single variable, determining a design range of the pipe bending angle α;

[0158] For example, referring to step S2, in the initial structure, the bend angle α is 135°, the transition metal pipe length L is 300 mm, and the suction pipe diameter D is 2 The suction depth is 4m and the pressure loss of the suction pipe under the initial structure is 10749.46Pa. Change the elbow angle α, for example, the elbow angle α is changed to 100mm, 110mm, 120mm, 130mm, 140mm, 150mm in sequence, and calculate the corresponding pressure loss ΔP after each change of the elbow angle 2 and maximum erosion wear rate like Fig. 20 As shown ( Fig. 20 The pressure drop is the pressure loss of the sewage suction pipe ΔP 2 , the maximum erosion rate is the maximum erosion wear rate ), when the elbow angle is less than 130°, the pressure loss ΔP 2 The pressure loss is less affected by the change of the elbow angle. When the elbow angle is greater than 130°, the pressure loss ΔP 2 The maximum erosion wear rate increases significantly with the increase of the bending angle. As the elbow angle increases, it shows a trend of increasing first and then decreasing. When the elbow angle is small, the sewage flows through the elbow at a higher speed, resulting in a greater collision speed for the solid particles. At this time, the solid particles are more likely to accumulate at the elbow, and the maximum erosion rate is larger. As the elbow angle increases, the sewage velocity at the elbow slows down, and the maximum erosion rate decreases. Since the outlet of the suction pipe must be kept above the maximum liquid level, the length of the metal pipe inside the tank must increase with the increase of the elbow angle, resulting in a continuous increase in the pressure drop. Therefore, the reasonable design range of the elbow angle α is 130-140°.

[0159] S222: Taking the transition metal pipeline length L as a single variable, determining a design range of the transition metal pipeline length L;

[0160] For example, referring to step S2, in the initial structure, the bend angle α is 135°, the transition metal pipe length L is 300 mm, and the suction pipe diameter D is 2 The length of the transition metal pipeline L is changed, for example, the length of the transition metal pipeline L is changed to 280mm, 320mm, 340mm, 350mm, 380mm, 400mm, 450mm, and the corresponding pressure loss ΔP after each change of the length of the transition metal pipeline L is calculated. 2 and maximum erosion wear rate like Fig.21 As shown ( Fig.21 The pressure drop is the pressure loss of the sewage suction pipe ΔP 2 , the maximum erosion rate is the maximum erosion wear rate ), pressure loss along the sewage suction pipeline ΔP 2 The maximum erosion wear rate increases with the increase of the transition section length, and decreases with the increase of the transition section length. When the transition section length is greater than 340 "mm", the maximum erosion wear rate is less affected by the change of the transition section length. When the transition section length is small, the sewage flows from the sewage suction hose into the metal pipe after a change of direction and quickly changes direction for the second time in the elbow area. At this time, a strong "secondary flow" phenomenon occurs at the elbow, the movement of solid particles changes irregularly, a large number of particles collide with the inner wall of the elbow and accumulate at the elbow, resulting in a large maximum erosion wear rate; with the increase of the transition section length, the sewage is buffered in the transition section pipeline after flowing out of the sewage suction hose, and the solid particles are fully dispersed in this section, the accumulation at the elbow is alleviated, and the maximum erosion rate is significantly reduced; when the transition section length is greater than 400mm, the flow field distribution inside the sewage suction pipeline is less affected by the change of the transition section pipeline length. At this time, due to the continuous increase in the total length of the pipeline, the pressure loss ΔP along the sewage suction pipeline 2Therefore, the reasonable design range of the transition section metal pipe length L is 340-380 mm.

[0161] S223: Change the pipe diameter D 2 As a single variable, determine the pipe diameter D 2 Design scope;

[0162] For example, referring to step S2, in the initial structure, the bend angle α is 130°, the transition metal pipe length L is 300 mm, and the suction pipe diameter D is 2 The length of the transition metal pipe L is changed, for example, the length of the transition metal pipe L is changed to 80mm, 90mm, 110mm, 120mm, 130mm, and the pipe diameter D is calculated for each change. 2 The corresponding pressure loss ΔP 2 and maximum erosion wear rate like Fig. 22 As shown ( Fig. 22 The pressure drop is the pressure loss of the sewage suction pipe ΔP 2 , the maximum erosion rate is the maximum erosion wear rate ), pressure loss along the sewage suction pipeline ΔP 2 The maximum erosion wear rate and the pipe diameter D 2 It shows an approximate quadratic curve relationship, which increases with the pipe diameter D 2 As the pipe diameter D 2 As the diameter D increases, the velocity and distribution of the flow field inside the pipeline change little, the maximum pressure gradually decreases, and the local pressure loss at the bend and the pressure loss along the pipeline are significantly reduced; when the total amount of solid particles remains unchanged, the particle volume fraction increases with the pipe diameter D 2 The particle distribution is more dispersed and the particle impact area is increased. 2 When the diameter is larger than 110 mm, the maximum erosion wear rate increases with the diameter D 2 The increase is small, and at this time the pipe diameter D 2 The increase in pipe diameter D will affect the layout space of the vehicle. 2 The reasonable design range is 110 ~ 120mm.

[0163] S3: designing a test table according to the design range of the structural parameter to be optimized, obtaining test sample data according to the test table test calculation, and obtaining the response relationship between the structural parameter X to be optimized and the target evaluation parameter Y according to the test data calculation;

[0164] The specific steps include:

[0165] S31: The structural parameter X to be optimized is designed into a three-factor three-level Box-Behnken test table, the target evaluation parameter Y is used as the response variable, and the test sample data is calculated using numerical simulation software according to the Box-Behnken test table;

[0166] Exemplarily, a three-factor three-level Box-Behnken test is designed according to the design range of each structural parameter to be optimized obtained in step S2:

[0167] Table 4 Cyclone separator test factors and levels

[0168]

[0169] Table 5 Test factors and levels of sewage suction pipeline

[0170]

[0171] Taking the structural parameters to be optimized of the cyclone separator as design variables, and taking the pressure loss and particle separation efficiency as evaluation indicators, the Box-Behnken test design table is shown in Table 6 below:

[0172] Table 6 Cyclone separator structural parameter factor level table

[0173]

[0174]

[0175] Taking the structural parameters to be optimized of the sewage suction pipe as the design variables, and the pressure loss and the maximum erosion wear rate as the evaluation indicators, the Box-Behnken test design table is shown in Table 7 below:

[0176] Table 7 Sewage suction pipe structural parameter factor level table

[0177]

[0178]

[0179] S32: Using the least squares method to perform response surface function fitting on the test sample data, obtain ΔP 1 With H, D 1 , S fitting function, η and H, D 1 , the fitting function of S, ΔP 2 With α, D 2 , the fitting function of L, and With α, D 2 , the fitting function of L.

[0180] According to the test results in Table 6 above, the least squares method is used to fit the response surface function. The pressure loss ΔP of the cyclone separator is obtained. 1 , the response surface model between the particle separation efficiency η and each design parameter is as follows:

[0181] AP 1 =2191.4525+0.869D 1 -4.74875H-2.75125s-0.000375D 1 H+0.008625D 1 s+0.012Hs-0.00285D 1 2 +0.00285H 2 -0.02215s 2

[0182]

[0183] According to the test results in Table 7 above, the least squares method is used to fit the response surface function. The pressure loss ΔP of the sewage suction pipeline is obtained. 2 , maximum erosion wear rate The response surface model between the design parameters is as follows:

[0184] ΔP 2 =-51672.2475-12.3615α-2.40988L+1149.541D 2 +0.0214αL+0.0118αD 2 -0.0183LD 2

[0185] -0.0369α 2 +0.003394L 2 -5.1989D 2 2

[0186] η=27.98625-0.14527α+0.025832L-0.37118D 2 -0.000235αL+0.00034αD 2 -0.000325LD 2

[0187] +0.0006969α 2 +0.000063L 2 +0.00185D 2 2

[0188] Preferably, after fitting, variance analysis is performed based on the Box-Behnken test data to obtain its variance ratio F and significance value P, the fitting condition is judged by the P value of the lack-of-fit term, and the influence of the structural parameters to be optimized on the target evaluation parameters is judged by the F value.

[0189] For example, according to Table 6, ΔP 1 With H, D 1 The F value of the fitting model of , S is 109.7, P value <0.0001, and the P value of the lack of fit term is 0.2715 (>0.05), indicating that ΔP 1 With H, D 1 The fitting function of S has a good fitting degree and high accuracy; the diameter D of the cyclone separator cylinder 1 , cylinder height H, exhaust pipe insertion depth s, F value and P value can be obtained, the cyclone separator to be optimized structural parameters of the pressure loss ΔP 1 The order of influence is D 1 >H>s. According to Table 6, η, H, and D 1 The F value of the fitting model of H and S is 38.56, P value <0.0001, and the P value of the lack of fit term is 0.0868 (>0.05), indicating that η is related to H and D 1 The fitting function of S has a good fitting degree and high accuracy; the diameter D of the cyclone separator cylinder 1 From the F value and P value of the cylinder height H and the exhaust pipe insertion depth s, it can be concluded that the order of influence of the structural parameters to be optimized on the particle separation efficiency η of the cyclone separator is s>H>D 1 .

[0190] For example, according to Table 7, ΔP 2 With α, D 2 The F value of the fitting model of , L is 11537.78, P value <0.0001, and the P value of the lack-of-fit term is 0.6471 (>0.05), indicating that ΔP 2 With α, D 2 The fitting function of L has a good fitting degree and high accuracy; the bending angle α of the sewage suction pipe, the length L of the metal pipe in the transition zone, and the pipe diameter D 2 The F value and P value can be obtained, the effect of the optimized structural parameters of the sewage suction pipeline on the pressure loss ΔP 2 The order of influence is D 2 >α>L. According to Table 7, we can get η, α, and D 2 The F value of the fitting model of η and α was 36.71, the P value was <0.0001, and the P value of the lack-of-fit term was 0.1575 (>0.05), indicating that η and α, D 2 The fitting function of L has a good fitting degree and high accuracy; the bending angle α of the sewage suction pipe, the length L of the metal pipe in the transition zone, and the pipe diameter D2 The F value and P value can be concluded that the optimal structural parameters of the sewage suction pipeline have an effect on the maximum erosion wear rate. The order of influence is D 2 >L>α.

[0191] S4: construct an optimization objective function, and use an optimization algorithm to find the optimal solution of the optimization objective function within the design range of the structural parameter X to be optimized. The optimal solution is the structural parameter X′ of the optimized part corresponding to the optimized part after the structural parameter X to be optimized is optimized.

[0192] S41: In this embodiment, both the cyclone separator and the sewage suction pipe need to be structurally optimized. The optimization goal of the cyclone separator is to improve the particle separation efficiency while reducing the pressure loss. The structural parameters to be optimized include the cylinder diameter D 1 , cylinder height H and exhaust pipe insertion depth s; the optimization goal of the sewage suction elbow is to reduce the pressure loss while reducing the maximum erosion wear rate. The structural parameters to be optimized include the elbow angle α, the transition zone metal pipe length L, and the pipe diameter D 2 . Based on this, the following optimization objective function is constructed:

[0193]

[0194] Among them, a 1 、a 2 、b 1 、b 2 are the weights of each target evaluation parameter, a 1 To reduce the priority of cyclone separator pressure loss; a 2 Indicates the importance of improving the separation efficiency of cyclone separators; b 1 Indicates the priority of reducing the pressure loss of the sewage suction pipeline; b 2 Indicates the priority of reducing the maximum erosion wear rate of the sewage suction pipe.

[0195] Specifically, the hierarchical method is used to calculate the weights of each target evaluation parameter:

[0196] According to the relative importance of each target evaluation parameter, a pairwise comparison matrix A is constructed, using a 9-point scale method, and the importance levels are as follows:

[0197] 1: The two target evaluation parameters have equal importance

[0198] 3: One target evaluation parameter is slightly more important than another target evaluation parameter

[0199] 5: One target evaluation parameter is significantly more important than another target evaluation parameter

[0200] 7: One target evaluation parameter is strongly more important than another target evaluation parameter

[0201] 9: One target evaluation parameter is absolutely more important than another target evaluation parameter

[0202] In this embodiment, according to the requirements of the vacuum sewage suction pipeline system, the relative importance of the four optimization target evaluation parameters is determined as follows:

[0203] The particle separation efficiency of the cyclone separator is the most important, with an importance of 9; the pressure loss of the cyclone separator is second, with an importance of 5; the maximum erosion and wear rate of the sewage suction pipe is also relatively important, but slightly lower than the target evaluation parameter of the cyclone separator, with an importance of 3; the pressure loss of the sewage suction pipe is relatively low, with an importance of 1.

[0204] Based on this, a pairwise comparison matrix A is constructed:

[0205]

[0206] Divide each element in the above comparison matrix A by the sum of its column to obtain the normalized matrix A norm :

[0207]

[0208] Normalize the matrix A norm Sum the elements of each row of , and take the average value to obtain the weight coefficient of each target evaluation parameter;

[0209]

[0210] That is: a 1 =0.579; a 2 =0.236; b 1 =0.146; b 2 =0.039.

[0211] Therefore, the optimization objective function is as follows:

[0212]

[0213] That is, after the above fitting process and weight calculation, the response surface model between the target evaluation parameter and the structural parameter to be optimized is obtained, which is used to find the optimal solution of the structural parameter to be optimized in the response surface model through the optimization algorithm in the subsequent step, as follows:

[0214] S42: After constructing the optimization objective function, perform optimization calculation, which specifically includes:

[0215] S421: Initialize a population within the design range of the parameter to be optimized, and set the number of the population to n;

[0216] There are n individuals in the population, and each individual has six design variables, namely H, D 1 ,s,α,D 2 , L, randomly generate a set of initial solutions within the design range of each design variable, that is, the design variable combination, and define it as the population:

[0217] X i，j (0) = X min，j +rand(0,1)·(X max，j -X min，j )

[0218] Among them, X min，j and X max，j are the upper and lower limits of the j-th variable respectively, and rand(0,1) is a random number between 0 and 1.

[0219] S422: The White Shark algorithm is used to iterate the optimization, the position of each individual in the population is updated, and the fitness of the new individual is calculated according to the optimization objective function;

[0220] The White Shark Optimization Algorithm simulates the behavior of hunting prey to find the potential optimal solution in the vast search space, and the position of each individual (design variable combination) is updated as follows:

[0221] X i，j (t+1)=X i，j (t)+rand(0,1)·(X best，j -X i，j (t))

[0222] Among them, X i，j (t+1) represents the value of the jth design variable of the ith individual in the population at the t+1th iteration; X best，j is the jth design variable value of the current optimal solution.

[0223] When the individual is close to the optimal solution, the algorithm enters the local refined search. At this time, the individual position update formula is:

[0224] X i，j (t+1)=X i，j (t)+λ·(X best，j -X i，j (t))+δ·rand(0,1)

[0225] Among them, λ is the step size of local search, δ is the perturbation coefficient, which is set according to experience, and rand(0, 1) is a normally distributed random number used to simulate random fluctuations in local search.

[0226] S423: updating the test sample data according to the fitness of the new individual and the response surface model error, and re-fitting the response surface function according to the test sample data;

[0227] S4231: Global search based on prediction error: The prediction error of the response surface model is measured by cross-validation error or residual error (residual) to calculate the prediction accuracy of the response surface model. Taking the residual error as an example, the calculation formula is:

[0228] Error = |f actual (X)-f predicted (X)|

[0229] Among them, f atual (X) is the actual calculated value, f predicted (X) is the predicted value from the response surface model.

[0230] In the current population, find the area with the largest prediction error and add the points in this area as new sample points. It should be noted that if the area with high uncertainty is too scattered, you can set a threshold ∈ to only sample points with an error greater than ∈:

[0231] X new ={X i |Error(X i >∈)}

[0232] S4232: Local development based on fitness: In order to further explore the high potential area near the current optimal solution, it is necessary to sample around the area with better fitness. First, determine the area near the optimal solution and find the individual with the highest fitness in the current population (X best ), and generate candidate points around it:

[0233] X candidate =X best +Δ

[0234] Among them, Δ is a random perturbation vector, whose size can be dynamically adjusted according to the optimization process:

[0235] Δ=rand(-r,r)

[0236] Where r is the search radius, which is set to a larger value (such as 10% of the design variable range) in the initial stage and gradually reduced in the later stage.

[0237] Secondly, calculate the fitness of the new sample points, use the response surface model to predict the fitness of the selected points, and sort them according to the fitness value. Finally, select the high potential points as new sample points, and select several points with higher fitness from the candidate points as new sample points:

[0238] X new ={X i |fpredicted (X i ) is close to the optimal value}

[0239] S4233: Combine global exploration and local development dynamic sampling: In order to achieve a balance between global exploration and local development, the ratio of the two can be dynamically adjusted. In the initial exploration, the ratio of global exploration is increased, that is, β→1; in the later stage of optimization, the ratio of global exploration is gradually reduced, that is, β→. Combine the points of global exploration and local development according to the weight:

[0240] X new =β·X global +(1-β)·X local

[0241] Where: X global is the set of sample points selected in the global exploration; X local is the set of sample points selected in local development.

[0242] After the test sample data is updated, the updated test sample data is refitted using the least squares method to obtain a new fitting function for the next iteration.

[0243] S424: Use the White Shark algorithm to continue to iterate until the number of iterations reaches the preset number or the fitness condition converges, and the optimal solution is obtained. The optimal solution includes the optimized cylinder height H′ and cylinder diameter D 1 ', the exhaust pipe insertion depth S', the suction pipe elbow angle α', the pipe diameter D 2 ′, length of metal pipe in transition zone L′.

[0244] Repeat steps S422 and S423 until the convergence condition is reached, stop the optimization iteration, and finally output the optimal structural parameters of the cyclone separator and the optimal structural parameters of the sewage suction pipe.

[0245] Among them, in the process of updating the sample points, the number of iterations or the fitness convergence value is used as the basis for dynamic adjustment:

[0246]

[0247] Among them, k is the adjustment rate, t is the current iteration number, and T is the total iteration number.

[0248] For example, after the optimization algorithm and rounding design, the final cylinder diameter D is obtained. 1 ' is 423mm, the cylinder height H' is 500mm, the exhaust pipe insertion depth s is 146mm, the elbow angle α' of the sewage suction pipe is 135°, and the pipe diameter D 2′ is 120 mm, and the length of the metal pipe in the transition zone L′ is 355 mm. Under this structural parameter, the pressure loss of the cyclone separator is 845.18 Pa, the particle separation efficiency is 90.95%, the pressure loss of the sewage suction pipe is 9147.61 Pa, and the maximum erosion wear rate is 0.752×10 -5 kg / (m 2 ·s).

[0249] Furthermore, in order to verify whether the final optimized structural parameters are effective, after the optimized structural parameters of the cyclone separator and the sewage suction pipe are obtained by optimization calculation, the internal fluid characteristics of the optimized parts are analyzed by numerical simulation software, and the effectiveness of the structural parameters X′ is verified by real vehicle experiments, including:

[0250] S5: Use numerical simulation software to analyze the internal fluid characteristics of the optimized part;

[0251] Specifically referring to step S12, numerical simulation software such as fluent software is used to simulate and analyze the flow field of the cyclone separator under the optimized structural parameters to obtain the static pressure distribution cloud map, velocity vector map and particle trajectory inside the cyclone separator at the Z=0 section of the cyclone separator, such as Figure 23 to Figure 25 As shown in the figure, it can be seen that the air flow turbulence at the exhaust pipe inlet has been effectively improved, and the cyclone separator pressure loss ΔP 1 The pressure drop was 826.16Pa, which was 5.42% lower than the initial structure. Most solid particles can settle and be collected in the cyclone separator, and a few particles escape from the exhaust pipe. During the analysis, 892 particles were injected into the cyclone separator inlet, 806 were captured, and the particle separation efficiency was about 90.36%, which was 5.89% higher than the initial structure.

[0252] Specifically referring to step S12, numerical simulation software such as fluent software is used to simulate and analyze the flow field of the sewage suction pipe under the optimized structural parameters. The static pressure distribution cloud diagram and velocity vector diagram of the longitudinal section of the sewage suction pipe are as follows: Figure 26 to Figure 28 As shown in the figure, the pressure mutation and low-speed area at the bend of the sewage suction pipe are effectively improved. At this time, the pressure loss of the sewage suction pipe is 9076.85Pa, which is 15.56% lower than the initial structure. The accumulation of particles in the bend section is significantly reduced, and the maximum erosion rate of solid particles on the sewage suction pipe is 0.775×10 -5 kg / (m 2 ·s), which is 37.19% lower than that of the initial structure.

[0253] S6: Use real vehicle experiments to verify the validity of the structural parameter X′;

[0254] S61: Design and manufacture a cyclone separator and a sewage suction pipe according to the optimized structural parameter X′, and assemble the optimized cyclone separator and sewage suction pipe on a vacuum sewage suction truck; the rated speed of the vacuum pump of the vacuum sewage suction truck is 1000r / min, and the suction volume is 660m 3 / h.

[0255] S62: Measure and record the maximum suction speed, vacuum degree of the sewage collection tank and vacuum degree of the air extraction pipeline during the actual operation of the vacuum suction truck, and judge the effectiveness of the optimized structural parameter X' based on the recorded results

[0256] The maximum vacuum degree of the system is an important indicator reflecting the working performance of the vacuum system, which directly affects the effective suction range of the vacuum suction truck. Install the vacuum pressure gauge at the sewage collection tank and the outlet of the suction pipe respectively to measure the change of vacuum degree during the suction process. The maximum vacuum degree is usually expressed as absolute pressure. During the test, the suction valve needs to be closed, the value change of the vacuum pressure gauge needs to be recorded, and the duration of the pressure gauge value after reaching the maximum value is observed. The curve of the pressure change over time of the tank body and the outlet of the suction pipe is as follows Fig.29 As shown. At the beginning of the test, the internal pressure of the vacuum truck is the same as the external atmospheric pressure. When the truck starts working, the internal pressure drops rapidly. When the system reaches the maximum vacuum degree, the absolute pressure of the pressure change is atmospheric pressure. As the vacuum pump tends to be stable, there is a certain pressure difference between the tank and the exhaust pipe, that is, the pressure loss of the exhaust pipe is about 3000Pa. The maximum vacuum degree of the system is about 27000Pa, and the duration of the maximum vacuum degree is more than 2 minutes, which meets the standard requirements.

[0257] The suction speed is an important indicator of the suction performance of the vacuum sewage suction pipeline system. The higher the suction speed, the shorter the system suction time. Fig.30 As shown, a flow meter is used to measure and record the speed change during the suction process. During the test, the vacuum pump was maintained at the rated speed, and the curve of the suction speed changing with time is shown in the figure below. During the air extraction stage, the sewage suction valve is in a closed state, and the suction speed is 0 at this time; when the system vacuum degree meets the requirements, the sewage suction valve is opened, the suction speed gradually increases, and remains stable after reaching the maximum suction speed. The system suction time is 252s, which is less than the 300s specified in QC / T652-2000. And as can be seen from the figure, the maximum suction speed of the system during operation is 4.64m / s, and the error with the 5m / s obtained by the theoretical calculation of step S1222 is 7.76%, which is less than 10%, proving that the numerical simulation model provided in this embodiment has a high accuracy.

[0258] The present embodiment also provides a structure optimization system for a vacuum sewage suction pipeline system, which includes an analysis module, a fitting module and an optimization module. The analysis module is used to analyze the internal fluid characteristics of the part to be optimized and determine the design range of the structural parameter X to be optimized; the fitting module is used to design a test table according to the design range of the structural parameter to be optimized, and obtain the test sample data according to the test table test calculation, and calculate the response relationship between the structural parameter X to be optimized and the target evaluation parameter Y according to the test data; the optimization module is used to construct an optimization objective function, and use an optimization algorithm to find the optimal solution of the optimization objective function within the design range of the structural parameter X to be optimized, and the optimal solution is the structural parameter X′ of the optimized part corresponding to the optimized structural parameter X of the part to be optimized. The structural optimization of the vacuum sewage suction pipeline system is achieved by the analysis module, the fitting module and the optimization module, and the optimization efficiency is high and the optimized structure is more reliable.

[0259] Note that the above are only preferred embodiments of the present invention and the technical principles used. Those skilled in the art will understand that the present invention is not limited to the specific embodiments described herein, and that various obvious changes, readjustments and substitutions can be made by those skilled in the art without departing from the scope of protection of the present invention. Therefore, although the present invention has been described in more detail through the above embodiments, the present invention is not limited to the above embodiments, and may include more other equivalent embodiments without departing from the concept of the present invention, and the scope of the present invention is determined by the scope of the appended claims.

Claims

1. A method for optimizing the structure of a vacuum sewage suction pipeline system, characterized in that: include: Determine the part to be optimized of the vacuum sewage suction pipeline system, and determine the structural parameter X to be optimized and the target evaluation parameter Y of the part to be optimized; Numerical simulation software is used to analyze the internal fluid characteristics of the part to be optimized, and the design range of the structural parameter X to be optimized is determined; Design a test table according to the design range of the structural parameter to be optimized, obtain test sample data by experimental calculation according to the test table, and calculate the response relationship between the structural parameter X to be optimized and the target evaluation parameter Y according to the test data; An optimization objective function is constructed, and an optimization algorithm is used to find the optimal solution of the optimization objective function within the design range of the structural parameter X to be optimized, wherein the optimal solution is the structural parameter X′ of the optimized part corresponding to the structural parameter X to be optimized of the part to be optimized.

2. The structural optimization method of the vacuum sewage suction pipeline system according to claim 1 is characterized in that: Determine the part to be optimized, and determine the structural parameter X to be optimized and the target evaluation parameter Y of the part to be optimized including: Determine the cyclone separator in the air extraction pipeline and the sewage suction pipeline as the parts to be optimized; The physical model and mathematical model of the cyclone separator and the sewage suction pipe are respectively established, and the internal flow field characteristics of the cyclone separator and the sewage suction pipe are analyzed by numerical simulation software, and then the structural parameters X to be optimized are determined accordingly, and the structural parameters X to be optimized include the cylinder height H, cylinder diameter D1, exhaust pipe insertion depth S of the cyclone separator, and the bend angle α, pipe diameter D2, and transition zone metal pipe length L of the sewage suction pipe; The target evaluation parameter Y is determined according to the suction efficiency and vacuum efficiency of the vacuum suction pipeline system. The target evaluation parameter Y includes the pressure loss ΔP1 of the cyclone separator, the particle separation efficiency η, the pressure loss ΔP2 of the suction pipeline, the maximum erosion wear rate 3. The structural optimization method of the vacuum sewage suction pipeline system according to claim 2 is characterized in that: The internal fluid characteristics of the part to be optimized are analyzed using numerical simulation software to determine the design range of the structural parameter X to be optimized, including: The cylinder height H, cylinder diameter D1, and exhaust pipe insertion depth S are taken as single variables in turn, and numerical simulation software is used to analyze the influence of the cylinder height H, cylinder diameter D1, and exhaust pipe insertion depth S on the pressure loss ΔP1 and particle separation efficiency η of the cyclone separator, respectively, to obtain the first influence curve of the cylinder height H, cylinder diameter D1, and exhaust pipe insertion depth S on the pressure loss ΔP1 of the cyclone separator, and the second influence curve of the cylinder height H, cylinder diameter D1, and exhaust pipe insertion depth S on the particle separation efficiency η, and take the preset range value of the intersection of each first influence curve and each corresponding second influence curve, that is, to obtain the design range of the cylinder height H, cylinder diameter D1, and exhaust pipe insertion depth s respectively; The elbow angle α, pipe diameter D2, and metal pipe length L in the transition zone of the sewage suction pipe are taken as single variables in turn, and numerical simulation software is used to analyze the effects of the elbow angle α, pipe diameter D2, and metal pipe length L in the transition zone on the pressure loss ΔP2, the maximum erosion wear rate, and the pressure drop of the sewage suction pipe. The third influence curve of the suction pipe elbow angle α, pipe diameter D2, and transition zone metal pipe length L on the pressure loss ΔP2 of the suction pipe is obtained, and the influence of the suction pipe elbow angle α, pipe diameter D2, and transition zone metal pipe length L on the maximum erosion wear rate is obtained. The fourth influence curve is obtained by taking the preset range value of the intersection of each third influence curve and each corresponding fourth influence curve, that is, the design range of the elbow angle α, the pipe diameter D2, and the metal pipe length L in the transition zone of the sewage suction pipe are obtained respectively.

4. The structural optimization method of the vacuum sewage suction pipeline system according to claim 2 is characterized in that: Designing a test table according to the design range of the structural parameter to be optimized, obtaining test sample data by experimental calculation according to the test table, and calculating the response relationship between the structural parameter X to be optimized and the target evaluation parameter Y according to the test sample data include: The structural parameter X to be optimized is designed into a three-factor three-level Box-Behnken test table, the target evaluation parameter Y is used as the response variable, and the test sample data is calculated according to the Box-Behnken test table using numerical simulation software; The least squares method is used to fit the test sample data to the response surface function to obtain the fitting function of ΔP1 with H, D1, S, the fitting function of η with H, D1, S, the fitting function of ΔP2 with α, D2, L, and Fitting function with α, D2, and L.

5. The structural optimization method of the vacuum sewage suction pipeline system according to claim 4 is characterized in that: Construct the optimization objective function: Among them, a1, a2, b1, and b2 are the weights of each target evaluation parameter, respectively. a1 is the priority of reducing the pressure loss of the cyclone separator; a2 represents the importance of improving the separation efficiency of the cyclone separator; b1 represents the priority of reducing the pressure loss of the sewage suction pipe; and b2 represents the priority of reducing the maximum erosion wear rate of the sewage suction pipe. The hierarchical method is used to calculate the weight of each target evaluation parameter, that is, the response surface model between the target evaluation parameters and the structural parameters to be optimized is obtained.

6. The structural optimization method of the vacuum sewage suction pipeline system according to claim 5, characterized in that: Using the White Shark optimization algorithm to find the optimal solution of the optimization objective function within the design range of the structural parameter X to be optimized includes: Initialize a population within the design range of the parameter to be optimized, and set the number of the population to n; The White Shark algorithm is used for optimization iteration, the position of each individual in the population is updated, and the fitness of the new individual is calculated according to the optimization objective function; updating the test sample data according to the fitness of the new individual and the response surface model error, and re-fitting the response surface function according to the test sample data; The White Shark algorithm is used to continue to iterate until the number of iterations reaches the preset number or the fitness condition converges to obtain the optimal solution, which includes the optimized cylinder height H′, cylinder diameter D1′, exhaust pipe insertion depth S′, sewage suction pipe elbow angle α′, pipe diameter D2′, and transition zone metal pipe length L′.

7. The structural optimization method of the vacuum sewage suction pipeline system according to claim 2, characterized in that: The internal fluid characteristics of the parts to be optimized are analyzed using numerical simulation software, including: Establishing physical models of the cyclone separator and the sewage suction pipe respectively, including determining a discrete phase model and a turbulence model of the cyclone separator, and determining a discrete phase model, a turbulence model, a collision model and an erosion and wear model of the sewage suction pipe; Establishing mathematical models of the cyclone separator and the sewage suction pipe respectively, including establishing a simplified three-dimensional model of the cyclone separator, meshing and setting boundary conditions, and establishing a simplified three-dimensional model of the sewage suction pipe, meshing and setting boundary conditions; According to the established physical model and mathematical model of the cyclone separator and the sewage suction pipe, the flow process of the dust-laden airflow in the cyclone separator is simulated by numerical simulation software, and the flow process of the sewage in the sewage suction pipe is simulated.

8. The structural optimization method of the vacuum sewage suction pipeline system according to claim 1, characterized in that: Also includes; Numerical simulation software is used to analyze the internal fluid characteristics of the optimized part, and actual vehicle experiments are used to verify the effectiveness of the structural parameter X′.

9. The structural optimization method of the vacuum sewage suction pipeline system according to claim 8, characterized in that: The effectiveness of the structural parameter X′ is verified by real vehicle experiments including: Design and manufacture a cyclone separator and a sewage suction pipe according to the optimized structural parameter X′, and assemble the optimized cyclone separator and sewage suction pipe on a vacuum sewage suction truck; The maximum suction speed, vacuum degree of the sewage collection tank and vacuum degree of the exhaust pipe during the actual operation of the vacuum sewage suction truck were measured and recorded, and the effectiveness of the optimized structural parameter X′ was judged based on the recorded results.

10. A structural optimization system for a vacuum sewage suction pipeline system, characterized in that: include: An analysis module, used to analyze the internal fluid characteristics of the part to be optimized and determine the design range of the structural parameter X to be optimized; A fitting module is used to design a test table according to the design range of the structural parameter to be optimized, and obtain test sample data by experimental calculation according to the test table, and calculate the response relationship between the structural parameter X to be optimized and the target evaluation parameter Y according to the test data; The optimization module is used to construct an optimization objective function and use an optimization algorithm to find the optimal solution of the optimization objective function within the design range of the structural parameter X to be optimized, wherein the optimal solution is the structural parameter X′ of the optimized part corresponding to the optimized structural parameter X of the part to be optimized.

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