Rotor assembly coaxiality prediction method, device, equipment and storage medium

Abstract

The application provides a rotor assembly coaxiality prediction method, device, equipment and storage medium, relates to the technical field of engineering machinery, and the rotor assembly coaxiality prediction method comprises the following steps: obtaining first information and second information of rotor assembly; the first information comprises size error information of a first target rotor and a second target rotor; the second information comprises at least one of the following: surface topography information of a first surface of the first target rotor, surface topography information of a second surface of the second target rotor and non-contact deformation information between the first surface and the second surface; the first target rotor and the second target rotor are any two-stage rotors assembled; the first surface is a surface of the first target rotor assembled with the second target rotor, and the second surface is a surface of the second target rotor assembled with the first target rotor; and the assembly coaxiality of each stage rotor is obtained according to the first information and the second information. The assembly coaxiality of each stage rotor obtained by the scheme is more accurate.

Description

Technical Field

[0001] This invention relates to the field of engineering machinery technology, and in particular to a method, apparatus, equipment and storage medium for predicting the coaxiality of rotor assembly. Background Technology

[0002] Aero engines are the "heart" of aircraft, hailed as the crown jewel of industry. The rotor system is a core functional component of an aero engine, and its assembly performance directly affects various service performance indicators, thus determining the engine's reliability and stability. During assembly, manufacturing errors accumulate and amplify, eventually potentially leading to out-of-tolerance coaxiality of the entire system, thereby affecting the assembly accuracy of the rotor system and the overall performance of the aircraft.

[0003] Current methods for modeling the coaxiality error propagation of aero-engine rotors consider the position and orientation errors of each target rotor, and many scholars have proposed different rotor assembly optimization methods based on this. However, these error propagation models neglect the influence of rotor end face surface morphology and non-uniform contact deformation, and cannot fully reproduce and predict the actual rotor assembly situation. Therefore, existing rotor assembly coaxiality error prediction methods suffer from low prediction accuracy and poor reproduction accuracy. Summary of the Invention

[0004] This invention provides a method, apparatus, device, and storage medium for predicting rotor assembly coaxiality, which solves the problems of low prediction accuracy and poor accuracy in existing rotor assembly coaxiality error prediction methods.

[0005] To address the aforementioned technical problems, the embodiments of the present invention provide the following technical solutions:

[0006] This invention provides a method for predicting the coaxiality of rotor assembly, the method comprising:

[0007] Obtain first and second information about rotor assembly; the first information includes dimensional error information of the first target rotor and dimensional error information of the second target rotor; the second information includes at least one of the following: surface topography information of the first surface of the first target rotor, surface topography information of the second surface of the second target rotor, and non-contact deformation information between the first surface and the second surface; the first target rotor and the second target rotor are any two stages of assembled rotors, and the rotational speed of the first target rotor is higher than that of the second target rotor; the first surface is the surface on the first target rotor that is assembled with the second target rotor, and the second surface is the surface on the second target rotor that is assembled with the first target rotor;

[0008] Based on the first information and the second information, the assembly coaxiality of each stage of the rotor is obtained.

[0009] Optionally, second information about the rotor assembly is obtained, including:

[0010] The surface topography information of the first surface of the first target rotor and the surface topography information of the second surface of the second target rotor are established using the preset random midpoint displacement method (RMD).

[0011] Optionally, second information about the rotor assembly is obtained, including:

[0012] The non-contact deformation information between the first surface and the second surface is determined using a pre-defined conjugate gradient fast Fourier transform method (CG-FFT).

[0013] Optionally, based on the first information and the second information, the assembly coaxiality of each stage of the rotor is obtained, including:

[0014] Based on the first information and the second information, a homogeneous transformation matrix for rotor assembly error propagation is generated;

[0015] Based on the homogeneous transformation matrix of the rotor assembly error propagation, the assembly coaxiality of each stage of the rotor is obtained.

[0016] Optionally, based on the first information and the second information, a homogeneous transformation matrix for rotor assembly error propagation is generated, including:

[0017] The first homogeneous transformation matrix is ​​obtained based on the size error information of the first target rotor;

[0018] The second homogeneous transformation matrix is ​​obtained based on the size error information of the second target rotor;

[0019] The third homogeneous transformation matrix is ​​obtained based on the surface topography model information of the first surface of the first target rotor and the surface topography model information of the second surface of the second target rotor.

[0020] The fourth homogeneous transformation matrix is ​​obtained based on the non-contact deformation information between the first surface and the second surface;

[0021] The homogeneous transformation matrix for rotor assembly error propagation is obtained based on the first homogeneous transformation matrix, the second homogeneous transformation matrix, the third homogeneous transformation matrix, and the fourth homogeneous transformation matrix.

[0022] Optionally, based on the first information and the second information, the assembly coaxiality of each stage of the rotor is obtained, including:

[0023] When multiple rotor allocation schemes are obtained, the assembly coaxiality of each stage rotor assembled in each rotor allocation scheme is obtained based on the first information and the second information.

[0024] Optionally, the method further includes:

[0025] The total coaxiality error in each rotor allocation scheme is obtained based on the assembly coaxiality of each stage rotor assembled in each rotor allocation scheme.

[0026] The rotor assembly scheme with the smallest total coaxiality error among the multiple rotor assembly schemes is determined as the optimal assembly scheme.

[0027] Optionally, when multiple rotor allocation schemes are obtained, before determining the assembly coaxiality of each stage rotor assembled in each rotor allocation scheme based on the first information and the second information, the method further includes:

[0028] Based on the multiple rotors to be assembled, an initial rotor allocation scheme is generated;

[0029] The initial rotor allocation scheme is processed using a genetic algorithm to obtain the multiple rotor allocation schemes.

[0030] This invention also provides a rotor assembly coaxiality prediction device, the device comprising:

[0031] The acquisition module is used to acquire first information and second information of rotor assembly; the first information includes dimensional error information of a first target rotor and dimensional error information of a second target rotor; the second information includes at least one of the following: surface topography information of a first surface of the first target rotor, surface topography information of a second surface of the second target rotor, and non-contact deformation information between the first surface and the second surface; the first target rotor and the second target rotor are any two stages of assembled rotors, and the rotational speed of the first target rotor is higher than that of the second target rotor; the first surface is the surface on the first target rotor that is assembled with the second target rotor, and the second surface is the surface on the second target rotor that is assembled with the first target rotor;

[0032] The first processing module is used to obtain the assembly coaxiality of each stage of the rotor based on the first information and the second information.

[0033] This invention also provides a rotor assembly coaxiality prediction device, comprising: a processor, a memory, and a program stored in the memory and executable on the processor, wherein the program, when executed by the processor, implements the steps of the rotor assembly coaxiality prediction method as described above.

[0034] This invention also provides a readable storage medium storing a program that, when executed by a processor, implements the steps in the rotor assembly coaxiality prediction method as described above.

[0035] The beneficial effects of this invention are:

[0036] The rotor assembly coaxiality prediction method provided by this invention considers first information and second information when determining the assembly coaxiality of each stage of the rotor. The first information includes the dimensional error information of the first target rotor and the dimensional error information of the second target rotor. The second information includes at least one of the surface morphology information of the first surface of the first target rotor, the surface morphology information of the second surface of the second target rotor, and the non-contact deformation information between the first surface and the second surface. That is, this invention considers the surface morphology information and non-contact deformation information of the rotor. Therefore, the obtained assembly coaxiality of each stage of the rotor is more accurate, and the accuracy of the prediction is increased. Attached Figure Description

[0037] Figure 1 A flowchart illustrating the rotor assembly coaxiality prediction method provided in this embodiment of the invention;

[0038] Figure 2 This is one of the schematic diagrams illustrating a two-stage rotor assembly provided in an embodiment of the present invention;

[0039] Figure 3 This is a flowchart illustrating the construction of an assembly error propagation model provided in an embodiment of the present invention.

[0040] Figure 4 This is the second schematic diagram illustrating the two-stage rotor assembly provided in an embodiment of the present invention;

[0041] Figure 5 A schematic diagram illustrating the initial rotor allocation scheme and the optimal assembly scheme provided in the embodiments of the present invention;

[0042] Figure 6 This is a schematic diagram of the rotor assembly coaxiality prediction device provided in an embodiment of the present invention.

[0043] Figure 7 This is a schematic diagram of the rotor assembly coaxiality prediction device provided in an embodiment of the present invention. Detailed Implementation

[0044] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be described in detail below with reference to the accompanying drawings and specific embodiments.

[0045] To address the problems of low prediction accuracy and poor accuracy in existing rotor assembly coaxiality error prediction methods, this invention provides a rotor assembly coaxiality prediction method, apparatus, device, and storage medium.

[0046] like Figure 1As shown, an embodiment of the present invention provides a method for predicting the coaxiality of rotor assembly, the method comprising:

[0047] Step 101: Obtain first information and second information of rotor assembly; the first information includes dimensional error information of the first target rotor and dimensional error information of the second target rotor; the second information includes at least one of the following: surface topography information of the first surface of the first target rotor, surface topography information of the second surface of the second target rotor, and non-contact deformation information between the first surface and the second surface; the first target rotor and the second target rotor are any two stages of assembled rotors, and the rotational speed of the first target rotor is higher than the rotational speed of the second target rotor; the first surface is the surface on the first target rotor that is assembled with the second target rotor, and the second surface is the surface on the second target rotor that is assembled with the first target rotor.

[0048] The first target rotor and the second target rotor can be any two of a plurality of assembled rotors. Optionally, the first target rotor is a first-stage rotor and the second target rotor is a second-stage rotor.

[0049] Step 102: Based on the first information and the second information, obtain the assembly coaxiality of each stage of the rotor.

[0050] In this embodiment, when calculating the assembly coaxiality of each stage of the rotor, the rotor's dimensional error information, surface morphology, and non-uniform contact deformation information are comprehensively considered, making the calculated assembly coaxiality results of each stage of the rotor more accurate and effectively improving the assembly precision of the aero-engine rotor.

[0051] In an optional embodiment of the present invention, obtaining second information about the rotor assembly includes:

[0052] The surface morphology information of the first surface of the first target rotor and the surface morphology information of the second surface of the second target rotor are established by using a preset random midpoint displacement (RMD) method. That is, in this optional embodiment, a non-ideal surface model of the rotor is established by using the random midpoint displacement (RMD) method to obtain the surface morphology information of the rotor surface. This method has the advantages of fine description of microscopic information, small storage requirements and simple and easy-to-use algorithm.

[0053] In an optional embodiment of the present invention, obtaining second information about the rotor assembly includes:

[0054] The non-contact deformation information between the first surface and the second surface is determined using a pre-defined conjugate gradient fast Fourier transform (CG-FFT) method.

[0055] It should be noted that most current research on calculating non-uniform contact deformation is based on the finite element method. However, due to the complexity of the finite element modeling and solution process, its computational efficiency is low, making it unsuitable for calculating large amounts of contact deformation, such as contact deformation involving surface morphology. Therefore, in this optional embodiment, the non-uniform deformation of two non-ideal annular surfaces in contact is calculated using the conjugate gradient-fast Fourier transform (CG-FFT) method. The CG-FFT method has better convergence characteristics for calculating the contact behavior of rough surfaces, significantly improving the speed of calculating contact deformation of complex surfaces compared to the traditional finite element method.

[0056] In summary, this invention provides a method for predicting the coaxiality of rotor assembly. This method comprehensively considers the effects of dimensional errors, surface morphology, and non-uniform deformation, and provides a more efficient boundary element algorithm for calculating non-uniform deformation, making the assembly prediction results closer to reality. This lays the foundation for subsequent research on aero-engine rotor assembly modeling.

[0057] The rotor assembly coaxiality prediction method provided in this embodiment of the invention is achieved by constructing an assembly error propagation model. In order to accurately construct an assembly error propagation model that considers non-uniform contact deformation, this embodiment of the invention obtains the actual assembly pose by fitting the point cloud data of each rotor node after deformation of the mating surface using the least squares method.

[0058] In an optional embodiment of the present invention, the process of establishing the assembly error propagation model is as follows: based on the first information and the second information, the assembly coaxiality of each stage of the rotor is obtained, including:

[0059] Based on the first information and the second information, a homogeneous transformation matrix for rotor assembly error propagation is generated. Based on the homogeneous transformation matrix for rotor assembly error propagation, the assembly coaxiality of each stage of the rotor is obtained.

[0060] Furthermore, the process of establishing the assembly error propagation model is explained in detail, wherein,

[0061] Based on the first information and the second information, a homogeneous transformation matrix for rotor assembly error propagation is generated, including:

[0062] The first homogeneous transformation matrix is ​​obtained based on the dimensional error information of the first target rotor. This dimensional error information includes positioning error and orientation error. The first homogeneous transformation matrix is ​​obtained based on the positioning error and orientation error of the midpoint of the dimensional error information of the first target rotor. Taking the first target rotor as the first-stage rotor and the second target rotor as the second-stage rotor as an example, a schematic diagram of the two-stage rotor assembly is shown below. Figure 2 As shown, Figure 2 As shown, the upper end face (i.e., the first surface) of the first-stage rotor and the lower end face (i.e., the second surface) of the second-stage rotor coincide to form a mating surface. The lower end face of the first-stage rotor is the reference surface. C0 is the center of the lower end face of the first-stage rotor, C1 is the center of the upper end face of the first-stage rotor and the lower end face of the second-stage rotor, and C2 is the center of the upper end face of the second-stage rotor. The following is a modeling of the assembly error transmission of the multi-stage rotor.

[0063] Establish the homogeneous transformation matrix (i.e., the first homogeneous transformation matrix) for the first-stage rotor positioning and orientation error as follows:

[0064] The second homogeneous transformation matrix is ​​obtained based on the dimensional error information of the second target rotor. The specific process is basically the same as obtaining the second homogeneous transformation matrix based on the dimensional error information of the first target rotor; that is, the homogeneous transformation matrix of the second-stage rotor positioning and orientation error (i.e., the second homogeneous transformation matrix) is established as follows:

[0065] Without considering the influence of surface micromorphology on assembly accuracy, the homogeneous transformation matrix of the two-stage rotor assembly error propagation is shown in Equation 1.

[0066]

[0067] This represents the homogeneous transformation matrix that represents the propagation of assembly errors in the two-stage rotor.

[0068] in, The calculation formula is shown in Formula 2.

[0069]

[0070] The calculation formula is shown in Formula 3.

[0071]

[0072] In formulas two and three above, l1 and l2 represent the heights of the first and second stage rotors, respectively; These represent the positioning errors of the first-stage rotor in the x, y, and z directions, respectively. These represent the positioning errors of the second-stage rotor in the x, y, and z directions, respectively. and These represent the first-stage rotor rotation matrix and the second-stage rotor rotation matrix, respectively. These represent the deflection angles in the x and y directions between the upper end face of the first-stage rotor and the reference plane, respectively. These represent the deflection angles in the x and y directions between the upper end face of the second-stage rotor and the reference plane, respectively. Substituting Equations 2 and 3 into Equation 1, we obtain the homogeneous transformation matrix for the propagation of assembly errors between the two-stage rotors, as shown in Equation 4.

[0073]

[0074] Given the coordinates of the center C0 of the lower end face of the first-stage rotor, the coordinates of the center C2 of the upper end face of the second-stage rotor can be directly calculated using Formula 4. Extending the above assembly error propagation modeling process to an n-stage rotor, the homogeneous transformation matrix for assembly error propagation is shown in Formula 5.

[0075]

[0076] This allows for the accurate calculation of the center error of each stage of rotor assembly, taking into account positioning and orientation errors, and thus the calculation of the coaxiality of the rotor system.

[0077] Modeling of multi-stage rotor assembly error propagation considering rough surface topography and non-uniform contact deformation:

[0078] Traditional assembly error propagation models only consider positioning and orientation errors. When considering the effects of rough surface microstructure and non-uniform deformation, the mating surfaces of the engine rotor will change, thus affecting the modeling of multi-stage rotor assembly error propagation. Under the new assembly model, the homogeneous transformation matrix of the two-stage rotor assembly error propagation model is shown in Equation 6.

[0079]

[0080] in, The homogeneous transformation matrix represents the propagation of assembly errors in the two-stage rotor. The homogeneous transformation matrix represents the first-stage rotor positioning and orientation error. This represents the homogeneous transformation matrix of the second-stage rotor positioning and orientation error. This represents the homogeneous transformation matrix that considers the error propagation between the first and second stage rotors, taking into account the surface topography. This represents the homogeneous transformation matrix that considers the error propagation of the first and second stage rotors in the case of non-uniform contact deformation.

[0081] Specifically, a third homogeneous transformation matrix is ​​obtained based on the surface topography model information of the first surface of the first target rotor and the surface topography model information of the second surface of the second target rotor. This third homogeneous transformation matrix is ​​the homogeneous transformation matrix that considers the error propagation between the first and second stage rotors in terms of surface topography. The calculation method is shown in Formula 7.

[0082]

[0083] The fourth homogeneous transformation matrix is ​​obtained based on the non-contact deformation information between the first and second surfaces. This fourth homogeneous transformation matrix is ​​the homogeneous transformation matrix that considers the error propagation of the first and second stage rotors in the case of non-uniform contact deformation. The calculation method is shown in Formula 8.

[0084]

[0085] In formulas seven and eight above, These represent the angles in the x and y directions between the contact surface formed by the upper end face of the first-stage rotor and the lower end face of the second-stage rotor under rigid contact with the reference surface. 11’ This represents the translational variable indicating the spatial orientation of the lower surface of the second-stage rotor under rigid contact.

[0086] These represent the angles in the x and y directions between the fitted mating surface formed by the upper end face of the first-stage rotor and the lower end face of the second-stage rotor under contact deformation, and the reference surface. 1’1” This represents the translational variable of the spatial orientation of the lower surface of the second-stage rotor under contact deformation.

[0087] Then, based on the first homogeneous transformation matrix, the second homogeneous transformation matrix, the third homogeneous transformation matrix, and the fourth homogeneous transformation matrix, the homogeneous transformation matrix for rotor assembly error propagation is obtained.

[0088] Specifically, the homogeneous transformation matrix for the propagation of assembly errors in a two-stage rotor, considering surface morphology and non-uniform deformation, is shown in Equation 9.

[0089]

[0090] Extending this to the nth stage, the homogeneous transformation matrix for rotor assembly error propagation is obtained as shown in Formula 10.

[0091] Formula 10:

[0092]

[0093] Based on the above formula derivation, the homogeneous transformation matrix corresponding to the i-th stage rotor can be obtained. The calculation result is shown in Formula 11. Where, Lxi L yi L zi These represent the x-axis, y-axis, and z-axis coordinates of the center of the upper end face of the i-th stage rotor, respectively.

[0094]

[0095] Therefore, the coaxiality C of the i-th stage rotor is calculated as shown in Formula XII.

[0096]

[0097] In Formulas 11 and 12 above, n represents the number of rotors assembled.

[0098] In an alternative embodiment, such as Figure 3 As shown, when constructing the assembly error propagation model, a model considering surface topography is built upon the traditional model. Then, based on this, a new model considering surface topography and non-uniform contact deformation is constructed. The schematic diagrams for the two-stage rotor assembly corresponding to the traditional model, the model considering surface topography, and the new model considering surface topography and non-uniform contact deformation are as follows: Figure 4 As shown.

[0099] It should be noted that the improved error propagation model can calculate the error propagation process considering the rotor end face surface topography under non-uniform loads. Compared with the traditional model, the new model, which considers surface topography and non-uniform contact deformation, improves the rotor assembly accuracy by approximately 10%.

[0100] In an optional embodiment of the present invention, the assembly coaxiality of each stage of the rotor is obtained based on the first information and the second information, including:

[0101] When multiple rotor allocation schemes are obtained, the assembly coaxiality of each stage of rotor assembled in each rotor allocation scheme is obtained according to the first information and the second information. That is, based on the new model that considers surface morphology and non-uniform contact deformation, the assembly coaxiality of each stage of rotor assembled in each rotor allocation scheme can be obtained in multiple rotor allocation schemes.

[0102] Furthermore, the method also includes:

[0103] Based on the assembly coaxiality of each stage of rotor assembled in each rotor allocation scheme, the total coaxiality error in each rotor allocation scheme is obtained by summing the values. The rotor assembly scheme with the smallest total coaxiality error among the multiple rotor assembly schemes is determined as the optimal assembly scheme. That is, based on the new model that considers surface morphology and non-uniform contact deformation, with the goal of minimizing the overall assembly coaxiality of the rotor system, the installation phase of each stage of rotor is optimized to obtain the rotor assembly scheme with the smallest total coaxiality error as the optimal assembly scheme.

[0104] Optionally, when multiple rotor allocation schemes are obtained, before determining the assembly coaxiality of each stage rotor assembled in each rotor allocation scheme based on the first information and the second information, the method further includes:

[0105] Based on the multiple rotors to be assembled, an initial rotor allocation scheme is generated, such as... Figure 5 As shown, taking four rotors to be assembled as an example, the four rotors to be assembled are randomly assembled to obtain an initial rotor allocation scheme. The initial rotor allocation scheme is then processed using a genetic algorithm to obtain multiple rotor allocation schemes. Specifically, the initial rotor allocation scheme is selected, crossovered, and mutated using a genetic algorithm to obtain a mutated rotor allocation scheme. The initial rotor allocation scheme and the mutated rotor allocation scheme are then used as the rotor allocation scheme.

[0106] Using the new model that considers surface morphology and non-uniform contact deformation, the total coaxiality error is calculated for each rotor allocation scheme. Based on the total coaxiality error, the assembly is optimized with the goal of reducing coaxiality, resulting in the optimal assembly scheme. Figure 5 As shown.

[0107] It should also be noted that the research results show that assembling according to the optimized installation angle guide reduces coaxiality by about 60% compared to random assembly, and significantly improves the assembly accuracy of the rotor system.

[0108] The modeling method for the assembly error transmission model provided in this embodiment of the invention can be applied to the field of aircraft engine rotor assembly. This method comprehensively considers the influence of dimensional error, surface morphology and non-uniform contact deformation, and the calculation results are more accurate, effectively improving the assembly accuracy of aircraft engine rotors.

[0109] like Figure 6 As shown, this embodiment of the invention also provides a rotor assembly coaxiality prediction device, the device comprising:

[0110] The acquisition module 601 is used to acquire first information and second information of rotor assembly; the first information includes dimensional error information of a first target rotor and dimensional error information of a second target rotor; the second information includes at least one of the following: surface topography information of a first surface of the first target rotor, surface topography information of a second surface of the second target rotor, and non-contact deformation information between the first surface and the second surface; the first target rotor and the second target rotor are any two stages of assembled rotors, and the rotational speed of the first target rotor is higher than that of the second target rotor; the first surface is the surface on the first target rotor that is assembled with the second target rotor, and the second surface is the surface on the second target rotor that is assembled with the first target rotor;

[0111] The first processing module 602 is used to obtain the assembly coaxiality of each stage rotor based on the first information and the second information.

[0112] Optionally, module 601 includes:

[0113] The first processing unit is used to establish the surface morphology information of the first surface of the first target rotor and the surface morphology information of the second surface of the second target rotor using a preset random midpoint displacement method (RMD).

[0114] Optionally, module 601 includes:

[0115] The second processing unit is used to determine the non-contact deformation information between the first surface and the second surface using a preset conjugate gradient fast Fourier transform method (CG-FFT).

[0116] Optionally, the first processing module 602 includes:

[0117] The third processing unit is used to generate a homogeneous transformation matrix for rotor assembly error propagation based on the first information and the second information.

[0118] The fourth processing unit is used to obtain the assembly coaxiality of each stage of the rotor based on the homogeneous transformation matrix of the rotor assembly error transmission.

[0119] Optionally, the third processing unit is specifically used for:

[0120] The first homogeneous transformation matrix is ​​obtained based on the size error information of the first target rotor;

[0121] The second homogeneous transformation matrix is ​​obtained based on the size error information of the second target rotor;

[0122] The third homogeneous transformation matrix is ​​obtained based on the surface topography model information of the first surface of the first target rotor and the surface topography model information of the second surface of the second target rotor.

[0123] The fourth homogeneous transformation matrix is ​​obtained based on the non-contact deformation information between the first surface and the second surface;

[0124] The homogeneous transformation matrix for rotor assembly error propagation is obtained based on the first homogeneous transformation matrix, the second homogeneous transformation matrix, the third homogeneous transformation matrix, and the fourth homogeneous transformation matrix.

[0125] Optionally, module 601 includes:

[0126] The fifth processing unit is used to obtain the assembly coaxiality of each stage of rotor assembled in each rotor allocation scheme based on the first information and the second information, when multiple rotor allocation schemes are obtained.

[0127] Optionally, the acquisition module 601 further includes:

[0128] The sixth processing unit is used to obtain the total coaxiality error in each rotor allocation scheme based on the assembly coaxiality of each stage rotor assembled in each rotor allocation scheme.

[0129] The determining unit is used to determine the rotor assembly scheme with the smallest total coaxiality error among the multiple rotor assembly schemes as the optimal assembly scheme.

[0130] Optionally, the acquisition module 601 further includes:

[0131] The seventh processing unit is used to generate an initial rotor allocation scheme based on the multiple rotors to be assembled.

[0132] The eighth processing unit is used to process the initial rotor allocation scheme using a genetic algorithm to obtain the plurality of rotor allocation schemes.

[0133] It should be noted that the rotor assembly coaxiality prediction device provided in the embodiments of the present invention is a device capable of performing the above-described rotor assembly coaxiality prediction method. Therefore, all embodiments of the above-described rotor assembly coaxiality prediction method are applicable to this device and can achieve the same or similar technical effects.

[0134] like Figure 7 As shown, this embodiment of the invention also provides a rotor assembly coaxiality prediction device, including: a processor 701, a memory 702, and a program stored in the memory 702 and executable on the processor 701. When the program is executed by the processor 701, it implements the above-described rotor assembly coaxiality prediction method.

[0135] Specifically, the processor 701 executes the following process:

[0136] Obtain first and second information about rotor assembly; the first information includes dimensional error information of the first target rotor and dimensional error information of the second target rotor; the second information includes at least one of the following: surface topography information of the first surface of the first target rotor, surface topography information of the second surface of the second target rotor, and non-contact deformation information between the first surface and the second surface; the first target rotor and the second target rotor are any two stages of assembled rotors, and the rotational speed of the first target rotor is higher than that of the second target rotor; the first surface is the surface on the first target rotor that is assembled with the second target rotor, and the second surface is the surface on the second target rotor that is assembled with the first target rotor;

[0137] Based on the first information and the second information, the assembly coaxiality of each stage of the rotor is obtained.

[0138] Optionally, the processor 701 is configured to:

[0139] The surface topography information of the first surface of the first target rotor and the surface topography information of the second surface of the second target rotor are established using the preset random midpoint displacement method (RMD).

[0140] Optionally, the processor 701 is configured to:

[0141] The non-contact deformation information between the first surface and the second surface is determined using a pre-defined conjugate gradient fast Fourier transform method (CG-FFT).

[0142] Optionally, the processor 701 is configured to:

[0143] Based on the first information and the second information, a homogeneous transformation matrix for rotor assembly error propagation is generated;

[0144] Based on the homogeneous transformation matrix of the rotor assembly error propagation, the assembly coaxiality of each stage of the rotor is obtained.

[0145] Optionally, the processor 701 is specifically used for:

[0146] The first homogeneous transformation matrix is ​​obtained based on the size error information of the first target rotor;

[0147] The second homogeneous transformation matrix is ​​obtained based on the size error information of the second target rotor;

[0148] The third homogeneous transformation matrix is ​​obtained based on the surface topography model information of the first surface of the first target rotor and the surface topography model information of the second surface of the second target rotor.

[0149] The fourth homogeneous transformation matrix is ​​obtained based on the non-contact deformation information between the first surface and the second surface;

[0150] The homogeneous transformation matrix for rotor assembly error propagation is obtained based on the first homogeneous transformation matrix, the second homogeneous transformation matrix, the third homogeneous transformation matrix, and the fourth homogeneous transformation matrix.

[0151] Optionally, the processor 701 is configured to:

[0152] When multiple rotor allocation schemes are obtained, the assembly coaxiality of each stage rotor assembled in each rotor allocation scheme is obtained based on the first information and the second information.

[0153] Optionally, the processor 701 is further configured to:

[0154] The total coaxiality error in each rotor allocation scheme is obtained based on the assembly coaxiality of each stage rotor assembled in each rotor allocation scheme.

[0155] The rotor assembly scheme with the smallest total coaxiality error among the multiple rotor assembly schemes is determined as the optimal assembly scheme.

[0156] Optionally, the processor 701 is further configured to:

[0157] Based on the multiple rotors to be assembled, an initial rotor allocation scheme is generated;

[0158] The initial rotor allocation scheme is processed using a genetic algorithm to obtain the multiple rotor allocation schemes.

[0159] Among them, Figure 7 In this context, the bus architecture may include any number of interconnected buses and bridges, specifically linking various circuits together, represented by one or more processors (processor 701) and memory (memory 702). The bus architecture may also link together various other circuits such as peripheral devices, voltage regulators, and power management circuits, which are well known in the art and therefore will not be described further herein. A bus interface provides a user interface 704. A transceiver 703 may be multiple elements, including transmitters and receivers, providing a unit for communicating with various other devices over a transmission medium. Processor 701 is responsible for managing the bus architecture and general processing, and memory 702 may store data used by processor 701 during operation.

[0160] In addition, a specific embodiment of the present invention also provides a readable storage medium storing a program, which, when executed by a processor, implements the steps in any of the rotor assembly coaxiality prediction methods described above.

[0161] The above describes the preferred embodiments of the present invention. It should be noted that those skilled in the art can make various improvements and modifications without departing from the principles of the present invention, and these improvements and modifications are also within the scope of protection of the present invention.

Claims

1. A method for predicting the coaxiality of rotor assembly, characterized in that, The method includes: Obtain first and second information about rotor assembly; the first information includes dimensional error information of the first target rotor and dimensional error information of the second target rotor; the second information includes at least one of the following: surface topography information of the first surface of the first target rotor, surface topography information of the second surface of the second target rotor, and non-contact deformation information between the first surface and the second surface; the first target rotor and the second target rotor are any two stages of assembled rotors, and the rotational speed of the first target rotor is higher than that of the second target rotor; the first surface is the surface on the first target rotor that is assembled with the second target rotor, and the second surface is the surface on the second target rotor that is assembled with the first target rotor; Based on the first information and the second information, the assembly coaxiality of each stage rotor is obtained. The second information obtained from the rotor assembly includes: The surface topography information of the first surface of the first target rotor and the surface topography information of the second surface of the second target rotor are established using the preset random midpoint displacement method (RMD). The non-contact deformation information between the first surface and the second surface is determined using a pre-defined conjugate gradient fast Fourier transform method (CG-FFT). The assembly coaxiality of each stage of the rotor is obtained based on the first information and the second information, including: Based on the first information and the second information, a homogeneous transformation matrix for rotor assembly error propagation is generated; Based on the homogeneous transformation matrix of the rotor assembly error propagation, the assembly coaxiality of each stage of the rotor is obtained.

2. The method according to claim 1, characterized in that, Based on the first information and the second information, a homogeneous transformation matrix for rotor assembly error propagation is generated, including: The first homogeneous transformation matrix is ​​obtained based on the size error information of the first target rotor; The second homogeneous transformation matrix is ​​obtained based on the size error information of the second target rotor; The third homogeneous transformation matrix is ​​obtained based on the surface topography model information of the first surface of the first target rotor and the surface topography model information of the second surface of the second target rotor. The fourth homogeneous transformation matrix is ​​obtained based on the non-contact deformation information between the first surface and the second surface; The homogeneous transformation matrix for rotor assembly error propagation is obtained based on the first homogeneous transformation matrix, the second homogeneous transformation matrix, the third homogeneous transformation matrix, and the fourth homogeneous transformation matrix.

3. The method according to claim 1, characterized in that, Based on the first information and the second information, the assembly coaxiality of each stage of the rotor is obtained, including: When multiple rotor allocation schemes are obtained, the assembly coaxiality of each stage rotor assembled in each rotor allocation scheme is obtained based on the first information and the second information.

4. The method according to claim 3, characterized in that, The method further includes: The total coaxiality error in each rotor allocation scheme is obtained based on the assembly coaxiality of each stage rotor assembled in each rotor allocation scheme. The rotor assembly scheme with the smallest total coaxiality error among the multiple rotor assembly schemes is determined as the optimal assembly scheme.

5. The method according to claim 4, characterized in that, In the case of obtaining multiple rotor allocation schemes, before determining the assembly coaxiality of each stage rotor assembled in each rotor allocation scheme based on the first information and the second information, the method further includes: Based on the multiple rotors to be assembled, an initial rotor allocation scheme is generated; The initial rotor allocation scheme is processed using a genetic algorithm to obtain the multiple rotor allocation schemes.

6. A rotor assembly coaxiality prediction device, characterized in that, The device includes: An acquisition module is used to acquire first information and second information of rotor assembly; the first information includes dimensional error information of a first target rotor and dimensional error information of a second target rotor; the second information includes at least one of the following: surface topography information of a first surface of the first target rotor, surface topography information of a second surface of the second target rotor, and non-contact deformation information between the first surface and the second surface; the first target rotor and the second target rotor are any two stages of assembled rotors, and the rotational speed of the first target rotor is higher than that of the second target rotor; the first surface is the surface on the first target rotor that is assembled with the second target rotor, and the second surface is the surface on the second target rotor that is assembled with the first target rotor; The first processing module is used to obtain the assembly coaxiality of each stage of the rotor based on the first information and the second information. The acquisition module includes: The first processing unit is used to establish the surface topography information of the first surface of the first target rotor and the surface topography information of the second surface of the second target rotor using a preset random midpoint displacement method (RMD). The second processing unit is used to determine the non-contact deformation information between the first surface and the second surface using a preset conjugate gradient fast Fourier transform method (CG-FFT). The first processing module includes: The third processing unit is used to generate a homogeneous transformation matrix for rotor assembly error propagation based on the first information and the second information. The fourth processing unit is used to obtain the assembly coaxiality of each stage of the rotor based on the homogeneous transformation matrix of the rotor assembly error transmission.

7. A rotor assembly coaxiality prediction device, characterized in that, include: A processor, a memory, and a program stored in the memory and executable on the processor, wherein the program, when executed by the processor, implements the steps of the rotor assembly coaxiality prediction method as described in any one of claims 1 to 5.

8. A readable storage medium, characterized in that, The readable storage medium stores a program that, when executed by a processor, implements the steps in the rotor assembly coaxiality prediction method as described in any one of claims 1 to 5.

Images