Fitting method for optimal position and attitude of major aircraft component

Abstract

The present invention relates to the technical field of digital aircraft assembly. Disclosed is a fitting method for an optimal position and attitude of a major aircraft component. In practice, some feature points may consistently fall outside allowable tolerance ranges, thus leading to an actual attitude adjustment result failing to meet requirements. Therefore, the tolerance ranges are generally relaxed to ensure that all feature points of a major aircraft component fall within the allowable tolerance ranges. In this situation, not only is the precision of certain core and key feature points sacrificed, but also the quality of position and attitude adjustment of the major aircraft component is not high due to the impact of other feature points with poor precision, and thus the overall quality of aircraft assembly may be degraded. In the present invention, when the above situation is encountered, grade assignment and rational trade-offs are performed on the feature points of the major aircraft component, thereby ensuring that the core and key feature points can fall within the allowable tolerance ranges, and also enabling the position and attitude of the major aircraft component to achieve the optimum in practical engineering terms.

Description

An optimal position and posture fitting method for an aircraft large component TECHNICAL FIELD

[0001] The present application relates to the technical field of digital assembly of an aircraft, and particularly to an optimal position and posture fitting method for an aircraft large component. BACKGROUND

[0002] In the process of adjusting the position and posture of an aircraft large component, a position and posture fitting algorithm is required to solve the position and posture transformation parameters of the aircraft large component from the current position and posture to the target position and posture. Characteristic points are arranged on the aircraft large component for position and posture fitting. However, due to manufacturing errors, a range of permissible overage is set for each characteristic point. The purpose of the position and posture fitting algorithm is to adjust each characteristic point to the range of permissible overage. In the algorithm solving process, the aircraft large component is regarded as an ideal rigid body.

[0003] However, in the actual application scenario, after adjusting the position and posture of the aircraft large component, it is found that the algorithm solution cannot necessarily make each characteristic point adjusted to the range of permissible overage, that is, there is no position and posture that can make each characteristic point on the aircraft large component satisfy the range of permissible overage, because this is caused by the larger manufacturing error of some characteristic points.

[0004] Therefore, in the actual situation, there may be a situation that some characteristic points always do not satisfy the range of permissible overage, which further leads to the actual result of posture adjustment not meeting the requirements. Therefore, the range of permissible overage is usually set wider to ensure that all characteristic points of the aircraft large component can be within the range of permissible overage. However, this situation not only sacrifices the accuracy of some core key characteristic points, but also is affected by other characteristic points with poor accuracy, so that the overall position and posture of the aircraft large component is not optimal in the actual engineering sense, resulting in low quality of the position and posture adjustment of the aircraft large component, and thus possibly reducing the overall assembly level of the aircraft. SUMMARY

[0005] The present application aims to solve the problem that in the process of adjusting the position and posture of an aircraft large component, some characteristic points always do not satisfy the range of permissible overage, which further leads to the actual result of posture adjustment not meeting the requirements. This situation not only sacrifices the accuracy of some core key characteristic points, but also is affected by other characteristic points with poor accuracy, so that the overall position and posture of the aircraft large component is not optimal in the actual engineering sense, resulting in low quality of the position and posture adjustment of the aircraft large component, and thus possibly reducing the overall assembly level of the aircraft. The present application provides an optimal position and posture fitting method for an aircraft large component.

[0006] The technical scheme adopted by the present application is as follows in order to achieve the above object: A fitting method for optimal position and posture of an aircraft large component, characterized by comprising the following steps: Step s1: according to the related requirements of aircraft large component design and manufacture, the importance of the position and posture adjustment of the feature points of the aircraft large component is graded, and the feature points are sorted according to the grading; Step s2: the range of permitted tolerance Tol of the feature points is set, the range of permitted tolerance Tol is set in the three directions of the coordinate system O-xyz of each feature point, and the feature points are sorted according to the importance level; Step s3: the influence factor W of the feature points is set, the influence factor W is set in the three directions of the coordinate system O-xyz of each feature point, and the importance level of the feature points is sorted according to the influence factor W; Step s4: in the coordinate system O-xyz, the manufacturing and assembly errors existing in the actual situation are set as e, it is determined that the error e is directly related to the position and posture transformation parameter R, and the position and posture transformation parameter R is set as the main variable in the algorithm iteration process; Step s5: the error e and the position and posture transformation parameter R in step s4 are used to establish a mathematical model for solving the optimal position and posture fitting algorithm of the aircraft large component, combined with the range of permitted tolerance Tol of the feature points and the influence factor W of the feature points; Step s6: the importance level of all feature point influence factors W is set to be the same; Step s7: the mathematical model established in the above steps is solved to obtain the position and posture transformation parameter R; Step s8: it is judged whether the optimal solution of the position and posture transformation parameter R that all points satisfy the range of permitted tolerance Tol can be obtained through the algorithm, if yes, the solving is continued, and after the execution is completed, the step jumps to step s13; if not, it goes to step s9; Step s9: the feature point tolerance type is checked in the order of core, key, important and general, it is judged whether the feature point tolerance type is only one type, if yes, the step is continued, and after the execution is completed, the step jumps to step s13; if the tolerance feature points exceed one type, it goes to step s10; Step s10: it is judged whether the feature point tolerance type is only two types, if yes, the step is continued, and after the execution is completed, the step jumps to step s13; if not, it jumps to step s11; Step s11: it is judged whether the feature point tolerance type is only three types, if yes, the step is continued, and after the execution is completed, the step jumps to step s13; if not, it jumps to step s12; Step s12: four types of feature points are all out of tolerance, the step is executed, and after the execution is completed, the step jumps to step s13; Step s13: the solved position and posture transformation parameter R is provided to the aircraft large component posture adjustment equipment system, the equipment system decomposes the related motion of the position and posture transformation parameter R, and the coordinates of the feature points of the aircraft large component in the optimal position and posture are obtained The actual position and posture of the aircraft large component are adjusted.

[0007] The importance levels in the step s1 are classified as: core C P, key K P, important I P, general G P.

[0008] The feature points in the step s1 are sorted according to the classification as: C N, K N, I N, G N is the number of feature points of each type, C N+ K N+ K N+ G N=N, C represents core, K represents key, I represents important, and G represents general. C P1 represents the first feature point of the core level, represents the first C N feature points of the core level; K P1 represents the first feature point of the key level, represents the first K N feature points of the key level; I P1 represents the first feature point of the important level, represents the first I N feature points of the important level; G P1 represents the first feature point of the general level, represents the first G N feature points of the general level; C x1 represents the x-coordinate value of the first core feature point, C y1 represents the y-coordinate value of the first core feature point, C z1 represents the z-coordinate value of the first core feature point; represents the x-coordinate value of the C N core feature points, represents the y-coordinate value of the C N core feature points, represents the z-coordinate value of the C N core feature points, and the rest are similar.

[0009] The importance level of the feature points in the step s2 is sorted as: C Tol represents the set of permitted tolerance ranges of core feature points, K Tol represents the set of permitted tolerance ranges of key feature points, I Tol represents the set of permitted tolerance ranges of important feature points,G Tol represents the set of allowable tolerance ranges for general feature points; C Tol1 represents the set of allowable tolerance ranges for the 1st core feature point, represents the set of allowable tolerance ranges for the 1st core feature point, C N core feature points, and so on.

[0010] The important level ranking of the feature points in step s3 is: C W represents the set of core feature point influence factors, K W represents the set of key feature point influence factors, I W represents the set of important feature point influence factors, G W represents the set of general feature point influence factors; C W1 represents the 1st core feature point influence factor, represents the 1st core feature point influence factor, C N core feature point influence factors, and so on. represents the 1st core feature point influence factor in the x direction, represents the 1st core feature point influence factor in the x direction, C N core feature point influence factors in the x direction; represents the 1st core feature point influence factor in the y direction, represents the 1st core feature point influence factor in the y direction, C N core feature point influence factors in the y direction; represents the 1st core feature point influence factor in the z direction, represents the 1st core feature point influence factor in the z direction, C N core feature point influence factors in the z direction; represents the 1st key feature point influence factor in the x direction, represents the 1st key feature point influence factor in the x direction, K N key feature point influence factors in the x direction; represents the 1st key feature point influence factor in the y direction, represents the 1st key feature point influence factor in the y direction, K N key feature point influence factors in the y direction; represents the 1st key feature point influence factor in the z direction, represents the 1st key feature point influence factor in the z direction, K N key feature point influence factors in the z direction; represents the 1st important feature point influence factor in the x direction, represents the 1st important feature point influence factor in the x direction, I N important feature point influence factors in the x direction; represents the 1st important feature point influence factor in the y direction, represents the 1st important feature point influence factor in the y direction, I N important feature point influence factors in the y direction; This represents the influence factor of the first important feature point in the z-axis. Representing the I Influence factors of N important feature points in the z-direction; This represents the influence factor of the first general feature point in the x-axis. Representing the G The influence factors of N general feature points in the x-direction; This represents the influence factor of the first general feature point in the y-direction. Representing the G The influence factors of N general feature points in the y-direction; This represents the influence factor of the first general feature point in the z-axis. Representing the G The influence factors of N general feature points in the z-direction; and so on for the rest.

[0011] In step s4, the error e is set as: e = R m P c - n P t ; m P c ( m x t , m y t , m z t () represents the actual coordinates of the feature point in the current attitude, measured in coordinate system O-xyz. n P t ( n x t , n y t , n z t ) represents the coordinates in the theoretical target pose in the coordinate system O-xyz; R represents the position and attitude transformation parameters.

[0012] The error e in step s4 is sorted as follows: C e represents the set of errors for the core feature points. K e represents the set of errors for key feature points. I e represents the set of errors for important feature points. G e represents the set of errors for general feature points; C e1 represents the error of the first core feature point. For the first C The error is calculated for N core feature points, and so on for the rest; The error of the first core feature point in the x-direction. For the first CError of N core feature points in x direction; Error of the 1st core feature point in y direction, C Error of N core feature points in y direction; Error of the 1st core feature point in z direction, C Error of N core feature points in z direction; Error of the 1st key feature point in x direction, K Error of N key feature points in x direction; Error of the 1st key feature point in y direction, K Error of N key feature points in y direction; Error of the 1st key feature point in z direction, K Error of N key feature points in z direction; Error of the 1st important feature point in x direction, I Error of N important feature points in x direction; Error of the 1st important feature point in y direction, I Error of N important feature points in y direction; Error of the 1st important feature point in z direction, I Error of N important feature points in z direction.

[0013] The mathematical model solved by the optimal position and attitude fitting algorithm of the aircraft major component established in the step s5 is: f(R) is the objective function of the algorithm optimization, s.t is the symbol of the constraint condition, and e≤Tol is the constraint condition.

[0014] The influence factors W of all feature points in the step s6 are set to be the same and are set to be 1, and the sorting is: C W is a core feature point influence factor set, K W is a key feature point influence factor set, I W is an important feature point influence factor set, G W is a general feature point influence factor set; C W1 is the 1st core feature point influence factor, W1 is the 1st core feature point influence factor, C N core feature point influence factors, and the rest are similar.

[0015] ​​​​​​​​The process of solving the algorithm in step s7 is performed in an iterative manner, and the algorithm exits the iteration when the number of iterations reaches the set maximum number of iterations; the maximum number of iterations is a fixed positive integer set according to actual application conditions, which does not change during algorithm iteration.

[0016] In step s9, if only the general feature points are out of tolerance, the out-of-tolerance points are discarded, and the algorithm is used to continue solving to obtain the optimal solution of the position and pose transformation parameter R that makes all points satisfy the permitted tolerance range Tol.

[0017] In step s9, if only the important feature points are out of tolerance, the influence factor W of the feature points is modified, the influence factors of the core, key and important feature points are all set to a, and a>1 is ensured, and the sorting is: C W is a core feature point influence factor set, K W is a key feature point influence factor set, I W is an important feature point influence factor set, G W is a general feature point influence factor set; C W1 is the first core feature point influence factor, W1 is the first core feature point influence factor, C N core feature point influence factors, and the rest are similar; then the algorithm is used to solve, and the core, key and important feature points are emphasized. If the results show that the core, key and important feature points satisfy the permitted tolerance range Tol, the optimal solution of the position and pose transformation parameter R for the core, key and important feature points is further obtained, and the out-of-tolerance general feature points are discarded.

[0018] In step s9, if only the key feature points are out of tolerance, the influence factor W of the feature points is modified, the influence factors of the core and key feature points are all set to a, the influence factor of the important feature point is set to b, a>b>1 is ensured, and the sorting is: C W is a core feature point influence factor set, K W is a key feature point influence factor set, I W is an important feature point influence factor set, G W is a general feature point influence factor set; C W1 is the first core feature point influence factor, W1 is the first core feature point influence factor, CN core feature points influence factors, and so on; then the algorithm is used to solve, at this time, the general feature points are only observed, and the core, key and important feature points are mainly ensured, if the result shows that the core, key and important feature points meet the permitted range Tol of the tolerance, at this time, the optimal solution of the position and attitude transformation parameter R of the core, key and important feature points is further obtained, and the general feature points with the tolerance are discarded; if the result shows that only the core and key feature points meet the permitted range Tol of the tolerance, at this time, the optimal solution of the position and attitude transformation parameter R of the core and key feature points is further obtained, and the important and general feature points with the tolerance are discarded.

[0019] In the step s9, if only the core feature points have the tolerance, the influence factors W of the feature points are modified, the influence factors of the core feature points are all set as a, the influence factors of the key feature points are set as b, and the influence factors of the important feature points are set as c, and it is ensured that a>b>c>1, and the order is: C W is a core feature point influence factor set, K W is a key feature point influence factor set, I W is an important feature point influence factor set, G W is a general feature point influence factor set; C W1 is a first core feature point influence factor, W1 is a first core feature point influence factor, C N core feature points influence factors, and so on; then the algorithm is used to solve, if the result shows that only the core feature points meet the permitted range Tol of the tolerance, at this time, the optimal solution of the position and attitude transformation parameter R of the core feature points is further obtained, and the key, important and general feature points with the tolerance are discarded; if the result shows that only the core and key feature points meet the permitted range Tol of the tolerance, at this time, the optimal solution of the position and attitude transformation parameter R of the core and key feature points is further obtained, and the important and general feature points with the tolerance are discarded; if the result shows that the core, key and important feature points meet the permitted range Tol of the tolerance, at this time, the optimal solution of the position and attitude transformation parameter R of the core, key and important feature points is further obtained, and the general feature points with the tolerance are discarded.

[0020] In the step s10, if the tolerance feature points are general and important, the influence factors W of the feature points are modified, the core, key and important influence factors are all set as a, and it is ensured that a>1, and the order is: C W is a core feature point influence factor set, K W is a key feature point influence factor set, I W is an important feature point influence factor set, G W is a general feature point influence factor set; C W1 is a first core feature point influence factor, For the first C N core feature points influence factor, the rest of the same; Then use the algorithm to solve, at this time will be observed only the general feature points, focus on the core, key, important feature points, if the results show that the core, key and important feature points meet the permitted range of tolerance Tol, at this time further obtained for the core, key and important feature points of position and pose transformation parameter R optimal solution, the general feature points discarded; If the important feature points still have the tolerance points, discard.

[0021] The step s10 if the tolerance feature points are general and key, modify the influence factor W of the feature points, set the influence factor of the core and key feature points to a, and set the influence factor of the important feature points to b, ensure that a > b > 1, and the order is: C W is a core feature point influence factor set, K W is a key feature point influence factor set, I W is an important feature point influence factor set, G W is a general feature point influence factor set; C W1 is the first core feature point influence factor, For the first C N core feature points influence factor, the rest of the same; Then use the algorithm to solve, at this time will be observed only the general feature points, focus on the core, key feature points, if the results show that the core, key and important feature points meet the permitted range of tolerance Tol, at this time further obtained for the core, key and important feature points of position and pose transformation parameter R optimal solution, the general feature points discarded; If the results show that the core, key feature points meet the permitted range of tolerance Tol, at this time further obtained for the core, key feature points of position and pose transformation parameter R optimal solution, important and general feature points discarded.

[0022] The step s10 if the tolerance feature points are general and core, modify the influence factor W of the feature points, set the influence factor of the core feature points to a, set the influence factor of the key feature points to b, and set the influence factor of the important feature points to c, ensure that a > b > c > 1, and the order is: C W is a core feature point influence factor set, K W is a key feature point influence factor set, I W is an important feature point influence factor set, G W is a general feature point influence factor set; C W1 is the first core feature point influence factor, For the first CN core feature points influence factors, and the rest are similar; then use the algorithm to solve, if the result shows that only the core feature points meet the permitted range of tolerance Tol, at this time further obtain the optimal solution of the position and attitude transformation parameter R for the core feature points, discard the key, important and general feature points with the tolerance; if the result shows that only the core and key feature points meet the permitted range of tolerance Tol, at this time further obtain the optimal solution of the position and attitude transformation parameter R for the core and key feature points, discard the important and general feature points with the tolerance; if the result shows that the core, key and important feature points meet the permitted range of tolerance Tol, at this time further obtain the optimal solution of the position and attitude transformation parameter R for the core, key and important feature points, discard the general feature points with the tolerance.

[0023] In the step s10, if the feature points with the tolerance are important and key, modify the influence factor W of the feature points, set the influence factor of the core feature points as a, set the influence factor of the key feature points as b, and ensure that a>b>1, and the order is: C W is a core feature point influence factor set, K W is a key feature point influence factor set, I W is an important feature point influence factor set, G W is a general feature point influence factor set; C W1 is the first core feature point influence factor, W1 is the first core feature point influence factor, C N core feature points influence factors, and the rest are similar; then use the algorithm to solve, if the result shows that only the core feature points meet the permitted range of tolerance Tol, at this time further obtain the optimal solution of the position and attitude transformation parameter R for the core feature points, discard the key, important and general feature points with the tolerance; if the result shows that only the core and key feature points meet the permitted range of tolerance Tol, at this time further obtain the optimal solution of the position and attitude transformation parameter R for the core and key feature points, discard the important and general feature points with the tolerance; if the result shows that the core, key and important feature points meet the permitted range of tolerance Tol, at this time further obtain the optimal solution of the position and attitude transformation parameter R for the core, key and important feature points, discard the general feature points with the tolerance.

[0024] In the step s10, if the feature points with the tolerance are important and core, or key and core, modify the influence factor W of the feature points, set the influence factor of the core feature points as a, set the influence factor of the key feature points as b, and set the influence factor of the important feature points as c, and ensure that a>b>c>1, and the order is: C W is a core feature point influence factor set, K W is a key feature point influence factor set, IW is a set of general feature point influence factors, G W is a set of general feature point influence factors; C W1 is the first core feature point influence factor, is the C N core feature point influence factors, and the rest are used in the same way; then the algorithm is used to solve, and the core feature points are guaranteed not to exceed the tolerance. If the result shows that only the core feature points meet the permitted tolerance range Tol, the optimal solution for the position and attitude transformation parameter R of the core feature points is further obtained, and the key, important and general feature points that exceed the tolerance are discarded. If the result shows that only the core and key feature points meet the permitted tolerance range Tol, the optimal solution for the position and attitude transformation parameter R of the core and key feature points is further obtained, and the important and general feature points that exceed the tolerance are discarded. If the result shows that the core, key and important feature points meet the permitted tolerance range Tol, the optimal solution for the position and attitude transformation parameter R of the core, key and important feature points is further obtained, and the general feature points that exceed the tolerance are discarded.

[0025] The step s11 modifies the influence factor W of the feature points if the feature points that exceed the tolerance are general, important or key. The influence factor of the core feature points is set to a, the influence factor of the key and important feature points is set to b, and a > b > 1 is guaranteed. The order is: C W is a set of core feature point influence factors, K W is a set of key feature point influence factors, I W is a set of important feature point influence factors, G W is a set of general feature point influence factors; C W1 is the first core feature point influence factor, is the C N core feature point influence factors, and the rest are used in the same way; then the algorithm is used to solve, and the core feature points are guaranteed not to exceed the tolerance. If the result shows that only the core feature points meet the permitted tolerance range Tol, the optimal solution for the position and attitude transformation parameter R of the core feature points is further obtained, and the key, important and general feature points that exceed the tolerance are discarded. If the result shows that only the core and key feature points meet the permitted tolerance range Tol, the optimal solution for the position and attitude transformation parameter R of the core and key feature points is further obtained, and the important and general feature points that exceed the tolerance are discarded. If the result shows that the core, key and important feature points meet the permitted tolerance range Tol, the optimal solution for the position and attitude transformation parameter R of the core, key and important feature points is further obtained, and the general feature points that exceed the tolerance are discarded.

[0026] The step s11 modifies the influence factor W of the feature points if the out-of-tolerance feature points are general, important, core, or important, critical, core, or general, critical, core, sets the influence factor of the core feature points as a, the influence factor of the critical feature points as b, and the influence factor of the important feature points as c, and ensures that a>b>c>1, and the order is: C W is a core feature point influence factor set, K W is a critical feature point influence factor set, I W is an important feature point influence factor set, G W is a general feature point influence factor set; C W1 is the first core feature point influence factor, W1 is the first core feature point influence factor, C N core feature point influence factors, and the rest are similar; then solve by algorithm, and focus on ensuring that the core feature points are not out of tolerance; if the result shows that only the core feature points meet the permitted out-of-tolerance range Tol, further solve the optimal solution of the position and attitude transformation parameter R for the core feature points, and discard the out-of-tolerance critical, important, and general feature points; if the result shows that only the core and critical feature points meet the permitted out-of-tolerance range Tol, further solve the optimal solution of the position and attitude transformation parameter R for the core and critical feature points, and discard the out-of-tolerance important and general feature points; if the result shows that the core, critical, and important feature points meet the permitted out-of-tolerance range Tol, further solve the optimal solution of the position and attitude transformation parameter R for the core, critical, and important feature points, and discard the out-of-tolerance general feature points.

[0027] The step s12 modifies the influence factor W of the feature points if all four types of feature points are out of tolerance, sets the influence factor of the core feature points as a, the influence factor of the critical feature points as b, and the influence factor of the important feature points as c, and ensures that a>b>c>1, and the order is: C W is a core feature point influence factor set, K W is a critical feature point influence factor set, I W is an important feature point influence factor set, G W is a general feature point influence factor set; C W1 is the first core feature point influence factor, W1 is the first core feature point influence factor, CN core feature points influence factors, the rest in this way; Then use the algorithm to solve, ensure that the core feature points do not exceed the error, if the results show that only the core feature points meet the permitted error range Tol, the optimal solution of the position and attitude transformation parameter R for the core feature points is obtained, and the key, important and general feature points are discarded; If the results show that only the core and key feature points meet the permitted error range Tol, the optimal solution of the position and attitude transformation parameter R for the core and key feature points is obtained, and the important and general feature points are discarded; If the results show that the core, key and important feature points meet the permitted error range Tol, the optimal solution of the position and attitude transformation parameter R for the core, key and important feature points is further obtained, and the general feature points are discarded.

[0028] The step s13 is calculated to obtain the coordinates of the feature points of the aircraft major component in the optimal position and attitude For m P c Is the actual coordinate of the feature point in the current attitude.

[0029] The advantages of the present application are that: 1. The method of the present application classifies the feature points of the aircraft major component according to importance levels, and the more important the feature point is, the higher the requirement for accuracy is, which provides direction and basis for the setting of the influence factor in the subsequent algorithm solving process.

[0030] 2. The present application includes the influence factor of the feature point and the error in the corresponding mathematical model of the optimal position and attitude fitting of the aircraft major component, so that the continuous change of the influence factor and the error directly determines the optimization direction of the algorithm, and the optimization target is towards the desired direction.

[0031] 3. The present application proposes a method for updating the feature point influence factor according to the corresponding rule in the algorithm solving process of the optimal position and attitude fitting of the aircraft major component, and reasonably selects according to the importance level and the error of the feature point, so that the optimization and solving target of the algorithm is more clear, the efficiency is higher, and the attitude adjustment accuracy of the aircraft major component is easier to meet.

[0032] 4. After the algorithm is preliminarily solved, if it is judged that there is an error, the influence factor of the feature point of different importance level is modified according to different error conditions, instead of blindly relaxing the permitted error range, and instead of setting an adaptive influence factor, which solves the problem that the position and attitude of the aircraft major component may be the optimal in mathematical sense, but not in actual engineering sense.

[0033] 5. The method provided by the application focuses on ensuring the accuracy of the core key feature points of the aircraft major component, allows the accuracy of other non-core key feature points to be sacrificed, if the accuracy of other feature points can meet the requirements, the feature points are included in the pose adjustment process, if the accuracy cannot meet the requirements, the feature points are discarded, and the optimal position and attitude of the aircraft major component are ensured.

[0034] 6. In the method of the application, it is proposed that in the iteration process of the position and attitude fitting algorithm of the aircraft major component, not only the influence factor can be updated, but also the unwanted feature points can be removed in real time (the number of feature points will change), instead of the feature points being fixed, so that the position and attitude of the aircraft major component can meet the related requirements, and the overall assembly accuracy of the aircraft can be better improved.

[0035] 7. The method provided by the application provides a position and attitude adjustment idea and strategy for the actual assembly site of the aircraft major component, and has corresponding solutions when different situations are encountered. BRIEF DESCRIPTION OF DRAWINGS

[0036] Fig. 1 is a flow chart of the method of the application. DETAILED DESCRIPTION

[0037] Embodiment 1: A fitting method for optimal position and attitude of an aircraft major component, comprising the following steps: Step s1: According to the relevant requirements of the design and manufacture of the aircraft major component, the importance of the feature points of the aircraft major component in the position and attitude adjustment process is graded, and the feature points are sorted according to the grading; Step s2: Set the permitted range of tolerance Tol for the feature points, set the permitted range of tolerance Tol in the three directions of the coordinate system O-xyz of each feature point, and sort the feature points according to the importance level; Step s3: Set the influence factor W of the feature points, set the influence factor W in the three directions of the coordinate system O-xyz of each feature point, and sort the feature points according to the influence factor W; Step s4: In the coordinate system O-xyz, set the manufacturing and assembly error e existing in the actual situation, determine that the error e is directly related to the position and attitude transformation parameter R, and set the position and attitude transformation parameter R as the main variable in the algorithm iteration process; Step s5: Use the error e and the position and attitude transformation parameter R in step s4, combine the permitted range of tolerance Tol of the feature points and the influence factor W of the feature points to establish a mathematical model for solving the optimal position and attitude fitting algorithm of the aircraft major component; Step s6: Set the importance level of all feature point influence factors W to be the same; Step s7: Solve the position and attitude transformation parameter R of the mathematical model established in the above steps; Step s8: Determine whether the optimal solution of the position and attitude transformation parameter R that satisfies the permitted range of tolerance Tol of all points can be obtained through the algorithm, if yes, continue to solve, and after execution is completed, jump from this step to step s13; if not, go to step s9; Step s9: Check the feature point tolerance type in the order of core, key, important and general, determine whether the feature point tolerance type is only one type, if yes, continue to execute this step, and after execution is completed, jump from this step to step s13; if the tolerance feature points exceed one type, go to step s10; Step s10: Determine whether the feature point tolerance type is only two types, if yes, continue to execute this step, and after execution is completed, jump from this step to step s13; if not, jump to step s11; Step s11: Determine whether the feature point tolerance type is only three types, if yes, continue to execute this step, and after execution is completed, jump from this step to step s13; if not, jump to step s12; Step s12: Four types of feature points are all out of tolerance, execute this step, and after execution is completed, jump from this step to step s13; Step s13: Provide the solved position and attitude transformation parameter R to the aircraft major component attitude adjustment equipment system, and the equipment system decomposes the related motion of the position and attitude transformation parameter R to obtain the coordinates of the feature points of the aircraft major component in the optimal position and attitude The actual position and attitude of the aircraft major component are adjusted.

[0038] The important levels in the step s1 are classified as: core C P, key K P, important I P, general G P.

[0039] The feature points in the step s1 are sorted according to the classification as: C N, K N, I N, G N is the number of feature points corresponding to each type, C N+ K N+ K N+ G N=N, C represents core, K represents key, I represents important, and G represents general. C P1 represents the first feature point of the core level, represents the first C N feature points of the core level; K P1 represents the first feature point of the key level, represents the first K N feature points of the key level; I P1 represents the first feature point of the important level, represents the first I N feature points of the important level; G P1 represents the first feature point of the general level, represents the first G N feature points of the general level; C x1 represents the x-coordinate value of the first core feature point, C y1 represents the y-coordinate value of the first core feature point, C z1 represents the z-coordinate value of the first core feature point; represents the x-coordinate value of the first C N core feature points, represents the y-coordinate value of the first C N core feature points, represents the z-coordinate value of the first C N core feature points, and the rest are similar.

[0040] The important level sorting of the feature points in the step s2 is: C Tol represents the range set of permissible tolerances of core feature points, K Tol represents the range set of permissible tolerances of key feature points, I Tol represents the range set of permissible tolerances of important feature points, GTol represents the set of allowable tolerance range of general feature points; C Tol1 represents the set of allowable tolerance range of the 1st core feature point, represents the set of allowable tolerance range of the C Nth core feature point, and the rest in the same manner.

[0041] The important level ranking of the feature points in the step s3 is: C W represents the set of core feature point influence factors, K W represents the set of key feature point influence factors, I W represents the set of important feature point influence factors, G W represents the set of general feature point influence factors; C W1 represents the 1st core feature point influence factor, represents the 1st core feature point influence factor, C Nth core feature point influence factor, and the rest in the same manner. represents the 1st core feature point influence factor in x direction, represents the 1st core feature point influence factor, C Nth core feature point influence factor in x direction. represents the 1st core feature point influence factor in y direction, represents the 1st core feature point influence factor, C Nth core feature point influence factor in y direction. represents the 1st core feature point influence factor in z direction, represents the 1st core feature point influence factor, C Nth core feature point influence factor in z direction. represents the 1st key feature point influence factor in x direction, represents the 1st key feature point influence factor, K Nth key feature point influence factor in x direction. represents the 1st key feature point influence factor in y direction, represents the 1st key feature point influence factor, K Nth key feature point influence factor in y direction. represents the 1st key feature point influence factor in z direction, represents the 1st key feature point influence factor, K Nth key feature point influence factor in z direction. represents the 1st important feature point influence factor in x direction, represents the 1st important feature point influence factor, I Nth important feature point influence factor in x direction. represents the 1st important feature point influence factor in y direction, represents the 1st important feature point influence factor, I Nth important feature point influence factor in y direction. an influence factor of the first important feature point in the z direction, an influence factor of the first I important feature point in the z direction; an influence factor of the first general feature point in the x direction, an influence factor of the GNth general feature point in the x direction; an influence factor of the first general feature point in the y direction, an influence factor of the GNth general feature point in the y direction; an influence factor of the first general feature point in the z direction, an influence factor of the GNth general feature point in the z direction; and the rest in the same manner.

[0042] The error e in the step s4 is set as: e = R m P c - n P t ; m P c ( m x t , m y t , m z t ) is the actual coordinate of the feature point in the current pose measured in the coordinate system O-xyz; n P t ( n x t , n y t , n z t ) is the coordinate in the theoretical target pose in the coordinate system O-xyz; and R is the position and pose transformation parameter.

[0043] The error e in the step s4 is sorted as: C e is a core feature point error set, K e is a key feature point error set, I e is an important feature point error set, G e is a general feature point error set; C e1 is the error of the first core feature point, eN is the error of the Nth core feature point, and the rest in the same manner; C e1x is the error of the first core feature point in the x direction, eNx is the error of the Nth core feature point in the x direction; C e1y is the error of the first core feature point in the y direction, eNy is the error of the Nth core feature point in the y direction; C e1z is the error of the first core feature point in the z direction, the error of the first core feature point in the x direction, C the error of the Nth core feature point in the y direction; the error of the first core feature point in the z direction, the error of the first core feature point in the x direction, C the error of the Nth core feature point in the z direction; the error of the first key feature point in the x direction, the error of the first key feature point in the x direction, K the error of the Nth key feature point in the x direction; the error of the first key feature point in the y direction, the error of the first key feature point in the y direction, K the error of the Nth key feature point in the y direction; the error of the first key feature point in the z direction, the error of the first key feature point in the z direction, K the error of the Nth key feature point in the z direction; the error of the first important feature point in the x direction, the error of the first important feature point in the x direction, I the error of the Nth important feature point in the x direction; the error of the first important feature point in the y direction, the error of the first important feature point in the y direction, I the error of the Nth important feature point in the y direction; the error of the first important feature point in the z direction, the error of the first important feature point in the z direction, I the error of the Nth important feature point in the z direction.

[0044] The mathematical model solved by the optimal position and attitude fitting algorithm of the aircraft major component established in the step s5 is: f(R) is the objective function of the algorithm optimization, s.t is the symbol of the constraint condition, and e≤Tol is the constraint condition.

[0045] The influence factors W of all the feature points in the step s6 are set to be the same and are set to be 1, and the sorting is: C W is a core feature point influence factor set, K W is a key feature point influence factor set, I W is an important feature point influence factor set, G W is a general feature point influence factor set; C W1 is the first core feature point influence factor, the first core feature point influence factor, C N core feature point influence factors, and the rest are similar.

[0046] The process of solving the algorithm in step s7 is performed in an iterative manner, and the algorithm exits the iteration when the number of iterations reaches the set maximum number of iterations; the maximum number of iterations is a fixed positive integer set according to actual application conditions, which does not change during algorithm iteration.

[0047] In step s9, if only the general feature points are out of tolerance, the out-of-tolerance points are discarded, and the algorithm is used to continue solving to obtain the optimal solution of the position and pose transformation parameter R that makes all points satisfy the permitted tolerance range Tol.

[0048] In step s9, if only the important feature points are out of tolerance, the influence factor W of the feature points is modified, the influence factors of the core, key and important feature points are all set to a, and a>1 is ensured, and the sorting is as follows: C W is a core feature point influence factor set, K W is a key feature point influence factor set, I W is an important feature point influence factor set, G W is a general feature point influence factor set; C W1 is the first core feature point influence factor, W1 is the first core feature point influence factor, C N core feature point influence factors, and the rest are similar; then the algorithm is used to solve, and the core, key and important feature points are emphasized. If the results show that the core, key and important feature points satisfy the permitted tolerance range Tol, the optimal solution of the position and pose transformation parameter R for the core, key and important feature points is further obtained, and the out-of-tolerance general feature points are discarded.

[0049] In step s9, if only the key feature points are out of tolerance, the influence factor W of the feature points is modified, the influence factors of the core and key feature points are all set to a, the influence factor of the important feature point is set to b, a>b>1 is ensured, and the sorting is as follows: C W is a core feature point influence factor set, K W is a key feature point influence factor set, I W is an important feature point influence factor set, G W is a general feature point influence factor set; C W1 is the first core feature point influence factor, W1 is the first core feature point influence factor, CN core feature points influence factors, and so on; then the algorithm is used to solve, at this time, the general feature points are only observed, and the core, key and important feature points are mainly ensured, if the result shows that the core, key and important feature points meet the permitted range Tol of the tolerance, at this time, the optimal solution of the position and attitude transformation parameter R of the core, key and important feature points is further obtained, and the general feature points with the tolerance are discarded; if the result shows that only the core and key feature points meet the permitted range Tol of the tolerance, at this time, the optimal solution of the position and attitude transformation parameter R of the core and key feature points is further obtained, and the important and general feature points with the tolerance are discarded.

[0050] In the step s9, if only the core feature points have the tolerance, the influence factors W of the feature points are modified, the influence factors of the core feature points are all set as a, the influence factors of the key feature points are set as b, and the influence factors of the important feature points are set as c, and it is ensured that a>b>c>1, and the order is: C W is a core feature point influence factor set, K W is a key feature point influence factor set, I W is an important feature point influence factor set, G W is a general feature point influence factor set; C W1 is a first core feature point influence factor, W1 is a first core feature point influence factor, C N core feature points influence factors, and so on; then the algorithm is used to solve, if the result shows that only the core feature points meet the permitted range Tol of the tolerance, at this time, the optimal solution of the position and attitude transformation parameter R of the core feature points is further obtained, and the key, important and general feature points with the tolerance are discarded; if the result shows that only the core and key feature points meet the permitted range Tol of the tolerance, at this time, the optimal solution of the position and attitude transformation parameter R of the core and key feature points is further obtained, and the important and general feature points with the tolerance are discarded; if the result shows that the core, key and important feature points meet the permitted range Tol of the tolerance, at this time, the optimal solution of the position and attitude transformation parameter R of the core, key and important feature points is further obtained, and the general feature points with the tolerance are discarded.

[0051] In the step s10, if the tolerance feature points are general and important, the influence factors W of the feature points are modified, the core, key and important influence factors are all set as a, and it is ensured that a>1, and the order is: C W is a core feature point influence factor set, K W is a key feature point influence factor set, I W is an important feature point influence factor set, G W is a general feature point influence factor set; C W1 is a first core feature point influence factor, For the first C The N core feature points have influence factors, and the rest follow the same logic. The algorithm is then used to solve the problem. At this point, general feature points are only observed, and the focus is on ensuring the core, key, and important feature points. If the results show that the core, key, and important feature points meet the allowable deviation range Tol, the optimal solution for the position and attitude transformation parameters R for the core, key, and important feature points is then obtained. General feature points that exceed the tolerance are discarded. If important feature points still have points that exceed the tolerance, they are also discarded.

[0052] In step s10, if the out-of-range feature points are general or critical, modify the influence factor W of the feature points. Set the influence factor of core and critical feature points to a, and the influence factor of important feature points to b, ensuring a > b > 1. The order is as follows: C W represents the set of influencing factors for core feature points. K W represents the set of key feature point influencing factors. I W represents the set of influencing factors for important feature points. G W is the set of influence factors for general feature points; C W1 is the first core feature point influence factor. For the first C The algorithm then calculates the influence factors for N core feature points, and so on for the rest. It then uses an algorithm to solve the problem, observing only general feature points and focusing on core and critical feature points. If the results show that the core, critical, and important feature points meet the allowable deviation range Tol, it further calculates the optimal solution for the position and attitude transformation parameters R for the core, critical, and important feature points, discarding general feature points that exceed the tolerance.

[0053] In step s10, if the out-of-tolerance feature points are general or core, modify the influence factor W of the feature points. Set the influence factor of core feature points to a, the influence factor of key feature points to b, and the influence factor of important feature points to c, ensuring a > b > c > 1. The order is as follows: C W represents the set of influencing factors for core feature points. K W represents the set of key feature point influencing factors. I W represents the set of influencing factors for important feature points. G W is the set of influence factors for general feature points; C W1 is the first core feature point influence factor. For the first CN core feature points influence factors, and the rest are similar; then use the algorithm to solve, if the result shows that only the core feature points meet the permitted range of tolerance Tol, at this time further obtain the optimal solution of the position and attitude transformation parameter R for the core feature points, discard the key, important and general feature points with tolerance; if the result shows that only the core and key feature points meet the permitted range of tolerance Tol, at this time further obtain the optimal solution of the position and attitude transformation parameter R for the core and key feature points, discard the important and general feature points with tolerance; if the result shows that the core, key and important feature points meet the permitted range of tolerance Tol, at this time further obtain the optimal solution of the position and attitude transformation parameter R for the core, key and important feature points, discard the general feature points with tolerance.

[0054] In the step s10, if the feature points with tolerance are important and key, modify the influence factor W of the feature points, set the influence factor of the core feature points as a, set the influence factor of the key feature points as b, and ensure that a>b>1, and the order is: C W is a core feature point influence factor set, K W is a key feature point influence factor set, I W is an important feature point influence factor set, G W is a general feature point influence factor set; C W1 is a first core feature point influence factor, W1 is a first core feature point influence factor, C N core feature points influence factors, and the rest are similar; then use the algorithm to solve, if the result shows that only the core feature points meet the permitted range of tolerance Tol, at this time further obtain the optimal solution of the position and attitude transformation parameter R for the core feature points, discard the key, important and general feature points with tolerance; if the result shows that only the core and key feature points meet the permitted range of tolerance Tol, at this time further obtain the optimal solution of the position and attitude transformation parameter R for the core and key feature points, discard the important and general feature points with tolerance; if the result shows that the core, key and important feature points meet the permitted range of tolerance Tol, at this time further obtain the optimal solution of the position and attitude transformation parameter R for the core, key and important feature points, discard the general feature points with tolerance.

[0055] In the step s10, if the feature points with tolerance are important and key, modify the influence factor W of the feature points, set the influence factor of the core feature points as a, set the influence factor of the key feature points as b, and ensure that a>b>1, and the order is: C W is a core feature point influence factor set, K W is a key feature point influence factor set, IW is a set of general feature point influence factors, G W is a set of general feature point influence factors; C W1 is the first core feature point influence factor, is the first C N core feature point influence factors, and the rest are used in this way. Then, the algorithm is used to solve the problem, and the core feature points are guaranteed not to exceed the tolerance. If the result shows that only the core feature points meet the permitted tolerance range Tol, the optimal solution for the position and attitude transformation parameter R of the core feature points is further obtained, and the key, important, and general feature points that exceed the tolerance are discarded. If the result shows that only the core and key feature points meet the permitted tolerance range Tol, the optimal solution for the position and attitude transformation parameter R of the core and key feature points is further obtained, and the important and general feature points that exceed the tolerance are discarded. If the result shows that the core, key, and important feature points meet the permitted tolerance range Tol, the optimal solution for the position and attitude transformation parameter R of the core, key, and important feature points is further obtained, and the general feature points that exceed the tolerance are discarded.

[0056] The step s11 modifies the influence factor W of the feature points if the feature points that exceed the tolerance are general, important, or key. The influence factor of the core feature points is set to a, the influence factor of the key and important feature points is set to b, and a > b > 1 is guaranteed. The order is: C W is a set of core feature point influence factors, K W is a set of key feature point influence factors, I W is a set of important feature point influence factors, G W is a set of general feature point influence factors; C W1 is the first core feature point influence factor, is the first C N core feature point influence factors, and the rest are used in this way. Then, the algorithm is used to solve the problem, and the core feature points are guaranteed not to exceed the tolerance. If the result shows that only the core feature points meet the permitted tolerance range Tol, the optimal solution for the position and attitude transformation parameter R of the core feature points is further obtained, and the key, important, and general feature points that exceed the tolerance are discarded. If the result shows that only the core and key feature points meet the permitted tolerance range Tol, the optimal solution for the position and attitude transformation parameter R of the core and key feature points is further obtained, and the important and general feature points that exceed the tolerance are discarded. If the result shows that the core, key, and important feature points meet the permitted tolerance range Tol, the optimal solution for the position and attitude transformation parameter R of the core, key, and important feature points is further obtained, and the general feature points that exceed the tolerance are discarded.

[0057] The step s11 modifies the influence factor W of the feature points if the out-of-tolerance feature points are general, important, core, or important, critical, core, or general, critical, core, sets the influence factor of the core feature points as a, the influence factor of the critical feature points as b, and the influence factor of the important feature points as c, and ensures that a>b>c>1, and the order is: C W is a core feature point influence factor set, K W is a critical feature point influence factor set, I W is an important feature point influence factor set, G W is a general feature point influence factor set; C W1 is the first core feature point influence factor, W1 is the first core feature point influence factor, C N core feature point influence factors, and the rest are similar; then solve by algorithm, and focus on ensuring that the core feature points are not out of tolerance. If the result shows that only the core feature points meet the permitted out-of-tolerance range Tol, the optimal solution for the position and attitude transformation parameter R of the core feature points is further obtained, and the out-of-tolerance critical, important, and general feature points are discarded. If the result shows that only the core and critical feature points meet the permitted out-of-tolerance range Tol, the optimal solution for the position and attitude transformation parameter R of the core and critical feature points is further obtained, and the out-of-tolerance important and general feature points are discarded. If the result shows that the core, critical, and important feature points meet the permitted out-of-tolerance range Tol, the optimal solution for the position and attitude transformation parameter R of the core, critical, and important feature points is further obtained, and the out-of-tolerance general feature points are discarded.

[0058] The step s12 modifies the influence factor W of the feature points if all four types of feature points are out of tolerance, sets the influence factor of the core feature points as a, the influence factor of the critical feature points as b, and the influence factor of the important feature points as c, and ensures that a>b>c>1, and the order is: C W is a core feature point influence factor set, K W is a critical feature point influence factor set, I W is an important feature point influence factor set, G W is a general feature point influence factor set; C W1 is the first core feature point influence factor, W1 is the first core feature point influence factor, CN core feature points influence factor, the rest in this way; Then use algorithm to solve, ensure that the core feature points do not exceed the error, if the results show that only the core feature points meet the permitted error range Tol, get the optimal solution of the position and attitude transformation parameter R for the core feature points, discard the key, important and general feature points; If the results show that only the core and key feature points meet the permitted error range Tol, get the optimal solution of the position and attitude transformation parameter R for the core and key feature points, discard the important and general feature points; If the results show that the core, key and important feature points meet the permitted error range Tol, at this time further get the optimal solution of the position and attitude transformation parameter R for the core, key and important feature points, discard the general feature points.

[0059] The step s13 is to calculate the coordinates of the feature points of the aircraft major component in the optimal position and attitude For m P c For the actual coordinates of the feature points in the current attitude.

[0060] In order to make the purpose, technical solutions and advantages of the present application clearer and more apparent, the present application is further described in detail below in combination with specific examples and with reference to the accompanying drawings.

[0061] Step s1: A total of N feature points P are arranged on the aircraft major component, according to the related requirements of the design and manufacture of the aircraft major component, the related important levels of the feature points of the aircraft major component in the position and attitude adjustment process are divided into: C P, the key is K P, the important is I P, the general is G P, the number of each level is defined according to the actual situation of the aircraft major component, and the number of each type of feature point is defined according to the actual situation of the aircraft major component and is respectively set to C N, K N, I N, G N, and the points are sorted according to the levels.

[0062] Wherein, C N+ K N+ K N+ G N=N, C represents core, K represents key, I represents important, and G represents general. C P1 represents the first feature point of the core level, represents the first feature point of the core level, C N feature points; K P1 represents the first feature point of the key level, the first feature point of the key level K N feature points I P1 represents the first feature point of the important level, the first feature point of the important level I N feature points G P1 represents the first feature point of the general level, the first feature point of the general level G N feature points C x1 represents the x coordinate value of the first core feature point, C y1 represents the y coordinate value of the first core feature point, C z1 represents the z coordinate value of the first core feature point; the x coordinate value of the first C N core feature points, the y coordinate value of the first C N core feature points, the z coordinate value of the first C N core feature points. The rest is the same.

[0063] Step s2: Since manufacturing and assembly errors are inevitable, the range of permitted tolerance of the feature points needs to be set as Tol. Since the precision requirements of the aircraft major parts are more reasonable, the range of permitted tolerance in the O-xyz three directions may be different, so each feature point is provided with a corresponding range of permitted tolerance in the O-xyz three directions Tol, and the feature points are sorted according to the important level of the feature points.

[0064] wherein, C Tol represents the set of permitted tolerance ranges of core feature points, K Tol represents the set of permitted tolerance ranges of key feature points, I Tol represents the set of permitted tolerance ranges of important feature points, G Tol represents the set of permitted tolerance ranges of general feature points; C Tol1 represents the permitted tolerance range of the first core feature point, the permitted tolerance range of the first C N core feature points, and the rest is the same; wherein, the lower limit of the permitted tolerance range of the first core feature point in the x direction, the upper limit of the permitted tolerance range of the first core feature point in the x direction, and the rest is the same. wherein, Tol1 represents the set of permitted tolerance ranges of the first core feature point in the x, y and z directions, respectively; This represents the lower limit of the permissible out-of-tolerance range for the first core feature point in the x-direction. This represents the upper limit of the allowable deviation range of the first core feature point in the x-direction; This represents the lower limit of the permissible out-of-tolerance range for the first core feature point in the y-direction. This represents the upper limit of the allowable deviation range of the first core feature point in the y-direction; This represents the lower limit of the permissible out-of-tolerance range for the first core feature point in the z-direction. This represents the upper limit of the permissible deviation range of the first core feature point in the z-direction; Representing the C The set of allowable out-of-tolerance ranges for N core feature points in the x, y, and z directions, respectively; Representing the C The lower limit of the allowable out-of-tolerance range for N core feature points in the x-direction. Representing the C The upper limit of the allowable out-of-tolerance range for N core feature points in the x-direction; Representing the C The lower limit of the allowable out-of-tolerance range for N core feature points in the y-direction. Representing the C The upper limit of the allowable out-of-tolerance range for N core feature points in the y-direction; Representing the C The lower limit of the allowable out-of-tolerance range for N core feature points in the z-direction. Representing the C The upper limit of the allowable out-of-tolerance range for N core feature points in the z-direction; the rest are calculated similarly.

[0065] Step s3: Set the influence factor of the feature point to W. Since the importance of each feature point may differ in the three directions of O-xyz, an influence factor is set for each feature point in the three directions of O-xyz, and they are sorted according to the importance level of the feature point. in, C W represents the set of influencing factors for core feature points. K W represents the set of key feature point influencing factors. I W represents the set of influencing factors for important feature points. G W is the set of influence factors for general feature points; C W1 is the first core feature point influence factor. For the first C The N core feature points have influence factors, and the rest follow the same pattern; This represents the influence factor of the first core feature point in the x-axis. Representing the C The influence factors of N core feature points in the x-direction; an influence factor of the first key feature point in the x direction, an influence factor of the C Nth key feature point in the x direction; an influence factor of the first key feature point in the z direction, an influence factor of the C Nth key feature point in the z direction; an influence factor of the first key feature point in the x direction, an influence factor of the K Nth key feature point in the x direction; an influence factor of the first key feature point in the y direction, an influence factor of the K Nth key feature point in the y direction; an influence factor of the first key feature point in the z direction, an influence factor of the K Nth key feature point in the z direction; an influence factor of the first key feature point in the x direction, an influence factor of the I Nth key feature point in the x direction; an influence factor of the first key feature point in the y direction, an influence factor of the I Nth key feature point in the y direction; an influence factor of the first key feature point in the z direction, an influence factor of the I Nth key feature point in the z direction; an influence factor of the first key feature point in the x direction, an influence factor of the G Nth key feature point in the x direction; an influence factor of the first key feature point in the y direction, an influence factor of the G Nth key feature point in the y direction; an influence factor of the first key feature point in the z direction, an influence factor of the G Nth key feature point in the z direction; and the rest in the same manner.

[0066] Step s4: the actual coordinates of the feature points in the current pose are measured in the coordinate system O-xyz as m P t ( m x t , m yt , m z t The coordinates of the feature points in the theoretical target pose are: n P t ( n x t , n y t , n z t Ideally, by adjusting the position and attitude of large aircraft components in their current pose, these components will coincide with those in the theoretical target pose. m P t ( m x t , m y t , m z t After calculation with position and attitude transformation parameters, and with n P t ( n x t , n y t , n z t They are equal, that is: n P t =R m P c However, in reality, due to manufacturing and assembly errors, there will inevitably be errors. Let's define the error as e, i.e., e = R. m P c - n P t .

[0067] For all feature points, the error e has in, C e represents the set of errors for the core feature points. K e represents the set of errors for key feature points. I e represents the set of errors for important feature points. G e represents the set of errors for general feature points; C e1 represents the error of the first core feature point. For the first C The error is calculated for N core feature points, and so on for the rest; The error of the first core feature point in the x-direction. For the first C The error of N core feature points in the x-direction; The error of the first core feature point in the y-direction. For the first CError of the Nth core feature point in the x direction; Error of the 1st core feature point in the z direction, Error of the CNth core feature point in the z direction; Error of the 1st key feature point in the x direction, Error of the K Error of the Nth key feature point in the x direction; Error of the 1st key feature point in the y direction, Error of the K Error of the Nth key feature point in the y direction; Error of the 1st key feature point in the z direction, Error of the K Error of the Nth key feature point in the z direction; Error of the 1st important feature point in the x direction, Error of the I Error of the Nth important feature point in the x direction; Error of the 1st important feature point in the y direction, Error of the I Error of the Nth important feature point in the y direction; Error of the 1st important feature point in the z direction, Error of the Nth important feature point in the z direction; and the rest is similar.

[0068] As can be seen from the above, the error e is directly related to the position and attitude transformation parameter R, and the process of algorithm solving is actually the process of solving the position and attitude transformation parameter R, so the position and attitude transformation parameter R is set as the main variable in the iteration process of the algorithm.

[0069] Step s5: and according to the above two kinds of data, combining the permitted range of the feature point Tol, the influence factor W of the feature point, and the error e, a mathematical model for solving the optimal position and attitude fitting algorithm of the aircraft major component is established.

[0070] Wherein, f(R) is the objective function of the algorithm optimization, s.t. is the symbol of the constraint condition, e≤Tol is the constraint condition, the change of the influence factor W of the feature point and the error e will directly affect the size of f(R), and then determine the direction of the algorithm optimization.

[0071] Step s6: set the initial influence factor W of all feature points to 1, that is C W is a core feature point influence factor set, K W is a key feature point influence factor set, I W is an important feature point influence factor set, GW is a set of general feature point influence factors; C W1 is the first core feature point influence factor, is the C N core feature point influence factors, and the rest are similar.

[0072] The purpose of setting all initial influence factors W of the feature points to 1 is to make the influence factors of all levels of feature points equal to 1, i.e., the importance levels of all points are the same, at the beginning of solving.

[0073] Step s7: The mathematical model established in the above steps is solved by using a related optimization algorithm. The algorithm solving process is performed in an iterative manner. The algorithm exits the iteration when the number of iterations reaches the set maximum number of iterations. The maximum number of iterations is a fixed positive integer set according to actual application conditions and does not change during algorithm iteration.

[0074] Step s8: Determine whether the algorithm can obtain a solution (i.e., position and pose transformation parameter R) that satisfies the permitted tolerance range Tol (i.e., the constraint condition) for all points. If yes, continue to solve using the algorithm to obtain the optimal solution of the position and pose transformation parameter R that satisfies the permitted tolerance range Tol for all points, and jump to step s13 from this step. If no, go to the next step.

[0075] Step s9: Check which type of feature points are out of tolerance in the order of core, key, important, and general. If only one type of feature points is out of tolerance, continue to jump to this step. If more than one type of feature points is out of tolerance, go to the next step.

[0076] ① If only general feature points are out of tolerance, discard the out-of-tolerance points and continue to solve using the algorithm to obtain the optimal solution of the position and pose transformation parameter R that satisfies the permitted tolerance range Tol for all points; ② If only important feature points are out of tolerance, modify the influence factor W of the feature points, set the influence factors of core, key, and important feature points to a, and ensure that a>1, i.e. C W is a set of core feature point influence factors, K W is a set of key feature point influence factors, I W is a set of important feature point influence factors, G W is a set of general feature point influence factors; C W1 is the first core feature point influence factor, is the CN core feature points influence factor, the rest of the same; Then use the algorithm to solve, focus on the core, key, important feature points, if the results show that the core, key and important feature points meet the permitted range of tolerance Tol, at this time further get the optimal solution for the core, key and important feature points of position and attitude transformation parameter R, the general feature points of the difference are discarded.

[0077] ③ If only the key feature points are out of tolerance, modify the influence factor W of the feature points, set the influence factor of the core and key feature points to a, and the influence factor of the important feature points to b, ensure that a > b > 1, that is C W is a core feature point influence factor set, K W is a key feature point influence factor set, I W is an important feature point influence factor set, G W is a general feature point influence factor set; C W1 is the first core feature point influence factor, W2 is the second core feature point influence factor, C N core feature points influence factor, the rest of the same; Then use the algorithm to solve, focus on the core, key, important feature points, if the results show that the core, key and important feature points meet the permitted range of tolerance Tol, at this time further get the optimal solution for the core, key and important feature points of position and attitude transformation parameter R, the general feature points of the difference are discarded; If the results show that only the core and key feature points meet the permitted range of tolerance Tol, at this time further get the optimal solution for the core and key feature points of position and attitude transformation parameter R, the important and general feature points of the difference are discarded.

[0078] ④ If only the core feature points are out of tolerance, modify the influence factor W of the feature points, set the influence factor of the core feature points to a, the influence factor of the key feature points to b, and the influence factor of the important feature points to c, ensure that a > b > c > 1, that is C W is a core feature point influence factor set, K W is a key feature point influence factor set, I W is an important feature point influence factor set, G W is a general feature point influence factor set; C W1 is the first core feature point influence factor, W2 is the second core feature point influence factor, CN core feature point influence factors, and the rest are similar; then the algorithm is solved, if the result shows that only the core feature points meet the permitted tolerance range Tol, at this time the optimal solution of the position and attitude transformation parameter R for the core feature points is further obtained, and the key, important and general feature points with tolerance are discarded; if the result shows that only the core and key feature points meet the permitted tolerance range Tol, at this time the optimal solution of the position and attitude transformation parameter R for the core and key feature points is further obtained, and the important and general feature points with tolerance are discarded; if the result shows that the core, key and important feature points meet the permitted tolerance range Tol, at this time the optimal solution of the position and attitude transformation parameter R for the core, key and important feature points is further obtained, and the general feature points with tolerance are discarded.

[0079] Jump from the present step to step s13.

[0080] Step s10: judge whether the tolerance type is only two types, if yes, continue to jump to the present step, otherwise jump to the next step.

[0081] ① If the tolerance feature points are general and important, modify the influence factor W of the feature points, set the core, key and important influence factors as a, and ensure that a>1, that is, C W is a core feature point influence factor set, K W is a key feature point influence factor set, I W is an important feature point influence factor set, G W is a general feature point influence factor set; C W1 is the first core feature point influence factor, is the Nth core feature point influence factor, C N core feature point influence factors, and the rest are similar; then the algorithm is solved, if the result shows that only the core feature points meet the permitted tolerance range Tol, at this time the optimal solution of the position and attitude transformation parameter R for the core feature points is further obtained, and the key, important and general feature points with tolerance are discarded; if the result shows that only the core and key feature points meet the permitted tolerance range Tol, at this time the optimal solution of the position and attitude transformation parameter R for the core and key feature points is further obtained, and the important and general feature points with tolerance are discarded; if the result shows that the core, key and important feature points meet the permitted tolerance range Tol, at this time the optimal solution of the position and attitude transformation parameter R for the core, key and important feature points is further obtained, and the general feature points with tolerance are discarded.

[0082] ② If the tolerance feature points are general and key, modify the influence factor W of the feature points, set the core and key influence factors as a, and set the important influence factor as b, ensure that a>b>1, that is, C W is a core feature point influence factor set, K W is a key feature point influence factor set, I W is an important feature point influence factor set, G W is a general feature point influence factor set; CW1 is the first core feature point influence factor, W1 is the first core feature point influence factor, C N core feature point influence factors, and the rest are similar; then use the algorithm to solve, at this time, only observe the general feature points, and focus on ensuring the core, key and important feature points. If the results show that the core, key and important feature points meet the permitted range of tolerance Tol, at this time, further solve the optimal solution of the position and attitude transformation parameter R of the core, key and important feature points, and discard the general feature points with tolerance. If the results show that the core and key feature points meet the permitted range of tolerance Tol, at this time, further solve the optimal solution of the position and attitude transformation parameter R of the core and key feature points, and discard the important and general feature points with tolerance.

[0083] ③If the feature points with tolerance are general and core, modify the influence factor W of the feature points, set the influence factor of the core feature points as a, the influence factor of the key feature points as b, and the influence factor of the important feature points as c, and ensure that a > b > c > 1, that is, C W is a core feature point influence factor set, K W is a key feature point influence factor set, I W is an important feature point influence factor set, G W is a general feature point influence factor set; C W1 is the first core feature point influence factor, W1 is the first core feature point influence factor, C N core feature point influence factors, and the rest are similar; then use the algorithm to solve, if the results show that only the core feature points meet the permitted range of tolerance Tol, at this time, further solve the optimal solution of the position and attitude transformation parameter R of the core feature points, and discard the key, important and general feature points with tolerance; if the results show that only the core and key feature points meet the permitted range of tolerance Tol, at this time, further solve the optimal solution of the position and attitude transformation parameter R of the core and key feature points, and discard the important and general feature points with tolerance; if the results show that the core, key and important feature points meet the permitted range of tolerance Tol, at this time, further solve the optimal solution of the position and attitude transformation parameter R of the core, key and important feature points, and discard the general feature points with tolerance.

[0084] ④If the feature points with tolerance are important and key, modify the influence factor W of the feature points, set the influence factor of the core feature points as a, and the influence factor of the key and important feature points as b, and ensure that a > b > 1, that is, C W is a core feature point influence factor set, K W is a key feature point influence factor set, I W is an important feature point influence factor set, GW is a set of general feature point influence factors; C W1 is the first core feature point influence factor, is the C N core feature point influence factors, and the rest are similar; Then use the algorithm to solve, if the results show that only the core feature points meet the permitted tolerance range Tol, at this time the optimal solution for the position and attitude transformation parameter R of the core feature points is further obtained, and the key, important and general feature points with tolerance are discarded; If the results show that only the core and key feature points meet the permitted tolerance range Tol, at this time the optimal solution for the position and attitude transformation parameter R of the core and key feature points is further obtained, and the important and general feature points with tolerance are discarded; If the results show that the core, key and important feature points meet the permitted tolerance range Tol, at this time the optimal solution for the position and attitude transformation parameter R of the core, key and important feature points is further obtained, and the general feature points with tolerance are discarded.

[0085] ⑤If the feature points with tolerance are important and core, or key and core, modify the influence factor W of the feature points, set the influence factor of the core feature points as a, the influence factor of the key feature points as b, and the influence factor of the important feature points as c, ensure that a>b>c>1, that is C W is a set of core feature point influence factors, K W is a set of key feature point influence factors, I W is a set of important feature point influence factors, G W is a set of general feature point influence factors; C W1 is the first core feature point influence factor, is the C N core feature point influence factors, and the rest are similar; Then use the algorithm to solve, if the results show that only the core feature points meet the permitted tolerance range Tol, at this time the optimal solution for the position and attitude transformation parameter R of the core feature points is further obtained, and the key, important and general feature points with tolerance are discarded; If the results show that only the core and key feature points meet the permitted tolerance range Tol, at this time the optimal solution for the position and attitude transformation parameter R of the core and key feature points is further obtained, and the important and general feature points with tolerance are discarded; If the results show that the core, key and important feature points meet the permitted tolerance range Tol, at this time the optimal solution for the position and attitude transformation parameter R of the core, key and important feature points is further obtained, and the general feature points with tolerance are discarded.

[0086] Jump from this step to step s13.

[0087] Step s11: judge whether the type of feature points with tolerance is only three categories, if yes, continue to jump to this step, otherwise jump to the next step.

[0088] ① If the out-of-tolerance feature points are general, important, and key, modify the influence factor W of the feature points, set the influence factor of the core feature points as a, set the influence factor of the key and important feature points as b, and ensure that a > b > 1, that is, C W is a core feature point influence factor set, K W is a key feature point influence factor set, I W is an important feature point influence factor set, G W is a general feature point influence factor set; C W1 is the first core feature point influence factor, W1 is the first core feature point influence factor, C N core feature point influence factors, and the rest are similar; then use the algorithm to solve, if the result shows that only the core feature points meet the permitted out-of-tolerance range Tol, at this time the optimal solution of the position and attitude transformation parameter R for the core feature points is further obtained, and the out-of-tolerance key, important and general feature points are discarded; if the result shows that only the core and key feature points meet the permitted out-of-tolerance range Tol, at this time the optimal solution of the position and attitude transformation parameter R for the core and key feature points is further obtained, and the out-of-tolerance important and general feature points are discarded; if the result shows that the core, key and important feature points meet the permitted out-of-tolerance range Tol, at this time the optimal solution of the position and attitude transformation parameter R for the core, key and important feature points is further obtained, and the out-of-tolerance general feature points are discarded.

[0089] ② If the out-of-tolerance feature points are general, important, core, or important, key, core, or general, key, core, modify the influence factor W of the feature points, set the influence factor of the core feature points as a, set the influence factor of the key feature points as b, and set the influence factor of the important feature points as c, and ensure that a > b > c > 1, that is, C W is a core feature point influence factor set, K W is a key feature point influence factor set, I W is an important feature point influence factor set, G W is a general feature point influence factor set; C W1 is the first core feature point influence factor, W1 is the first core feature point influence factor, CN core feature point influence factors, and the rest are similar; then solve the algorithm, focus on ensuring that the core feature points do not exceed the error, if the result shows that only the core feature points meet the permitted error range Tol, at this time the optimal solution of the position and attitude transformation parameter R for the core feature points is further obtained, and the key, important and general feature points that exceed the error are discarded; if the result shows that only the core and key feature points meet the permitted error range Tol, at this time the optimal solution of the position and attitude transformation parameter R for the core and key feature points is further obtained, and the important and general feature points that exceed the error are discarded; if the result shows that the core, key and important feature points meet the permitted error range Tol, at this time the optimal solution of the position and attitude transformation parameter R for the core, key and important feature points is further obtained, and the general feature points that exceed the error are discarded.

[0090] Jump from the present step to step s13.

[0091] Step s12: In this step, the influence factors W of the feature points are modified, the influence factors of the core feature points are all set to a, the influence factors of the key feature points are set to b, and the influence factors of the important feature points are set to c, so as to ensure that a>b>c>1, that is, C W is a core feature point influence factor set, K W is a key feature point influence factor set, I W is an important feature point influence factor set, G W is a general feature point influence factor set; C W1 is the first core feature point influence factor, W1 is the first core feature point influence factor, C N core feature point influence factors, and the rest are similar; then solve the algorithm, focus on ensuring that the core feature points do not exceed the error, if the result shows that only the core feature points meet the permitted error range Tol, at this time the optimal solution of the position and attitude transformation parameter R for the core feature points is further obtained, and the key, important and general feature points that exceed the error are discarded; if the result shows that only the core and key feature points meet the permitted error range Tol, at this time the optimal solution of the position and attitude transformation parameter R for the core and key feature points is further obtained, and the important and general feature points that exceed the error are discarded; if the result shows that the core, key and important feature points meet the permitted error range Tol, at this time the optimal solution of the position and attitude transformation parameter R for the core, key and important feature points is further obtained, and the general feature points that exceed the error are discarded.

[0092] Step s13: The optimal solution of the position and attitude transformation parameter R obtained is used as the position and attitude transformation parameter of the optimal position and attitude fitting of the aircraft major component, and the coordinates of the feature points of the aircraft major component in the optimal position and attitude are obtained by calculation W is a core feature point influence factor set, wherein,m P c is the actual coordinate of the feature point under the current pose.

[0093] Finally, the optimal solution of the position and pose transformation parameter R obtained by solving is provided to the aircraft major component pose adjustment equipment system, and the equipment system decomposes the related motion of the position and pose transformation parameter R to realize the adjustment of the actual position and pose of the aircraft major component.

Claims

1. A method for fitting optimal position and attitude of aircraft major components, characterized in that: The method comprises the following steps: Step s1: according to the relevant requirements of the design and manufacture of the aircraft major component, the importance of the feature points of the aircraft major component in the position and attitude adjustment process is classified, and the feature points are sorted according to the classification; Step s2: set the permitted range of the feature point to be Tol, set the permitted range of the feature point to be Tol in the three directions of the coordinate system O-xyz of each feature point, and sort the feature points according to the importance level; Step s3: set the influence factor of the feature point to be W, set the influence factor W in the three directions of the coordinate system O-xyz of each feature point, and sort the feature points according to the influence factor W; Step s4: in the coordinate system O-xyz, set the manufacturing and assembly error existing in the actual situation to be e, determine that the error e is directly related to the position and attitude transformation parameter R, and set the position and attitude transformation parameter R as the main variable in the algorithm iteration process; Step s5: using the error e and the position and attitude transformation parameter R in step s4, combining the permitted range of the feature point to be Tol and the influence factor of the feature point to be W, a mathematical model for solving the optimal position and attitude fitting algorithm of the aircraft major component is established; Step s6: set the importance level of all feature point influence factors W to be the same; Step s7: solve the position and attitude transformation parameter R of the mathematical model established in the above steps; Step s8: determine whether the optimal solution of the position and attitude transformation parameter R that satisfies the permitted range Tol of all points can be obtained through the algorithm; if yes, continue to solve, and jump from this step to step s13 after execution is completed; if not, go to step s9; Step s9: view the feature point error type in the order of core, key, important and general, and determine whether the feature point error type is only one type; if yes, continue to execute this step, and jump from this step to step s13 after execution is completed; if the error feature points exceed one type, go to step s10; Step s10: determine whether the feature point error type is only two types; if yes, continue to execute this step, and jump from this step to step s13 after execution is completed; if not, go to step s11; Step s11: determine whether the feature point error type is only three types; if yes, continue to execute this step, and jump from this step to step s13 after execution is completed; if not, go to step s12; Step s12: all four types of feature points are out of tolerance, execute this step, and jump from this step to step s13 after execution is completed; Step s13: providing the solved position and attitude transformation parameter R to the aircraft major component attitude adjustment equipment system, and the equipment system decomposes the relevant motion of the position and attitude transformation parameter R to obtain the coordinates of the feature points of the aircraft major component at the optimal position and attitude The actual position and attitude of the aircraft major component are adjusted.

2. The method of claim 1, wherein: The relevant importance levels in step s1 are classified as: core C P, key K P, important I P, general G P.

3. The method of claim 2, wherein: The feature points in the step s1 are sorted according to the hierarchy as: C N、 K N、 I N、 G N is the number of corresponding feature points of various types, C N+ K N+ K N+ G N = N, C represents core, K represents key, I represents important, and G represents general; C P1 represents the first feature point of the core level, the first feature point of the representative core level C N feature points; K P1 represents the first feature point of the key level, the first feature point representing the key level K N feature points; I P1 represents the first feature point of the important level, P1 represents a first feature point of a general level, I N feature points; G P1 represents a first feature point of a general level, the first G N feature points C x1 represents an x coordinate value of the first core feature point, C y1 represents a y coordinate value of the first core feature point, C z1 represents a z coordinate value of the first core feature point; represents the first C x-coordinate values of the N core feature points, represents the first C y-coordinate values of the N core feature points, representing the first C z-coordinate values of the N core feature points, and so on.

4. The method of claim 1, wherein: The important level sorting of the feature points in the step s2 is: C Tol represents a set of allowable ranges of tolerance for core feature points, K Tol represents a set of allowable ranges of tolerance for key feature points, I Tol represents a set of allowable ranges of tolerance for important feature points, G Tol represents a set of allowable ranges of tolerance for general feature points; C Tol1 represents a set of allowable ranges of tolerance for the 1st core feature point, representing the first C N core feature points are permitted to exceed the range, and the rest follow suit.

5. The method of claim 1, wherein: The important level sorting of the feature points in the step s3 is: C W is a set of core feature point influence factors, K W is a set of key feature point influence factors, I W is a set of important feature point influence factors, G W is a set of general feature point influence factors; C W1 is a first core feature point influence factor, For the first C N core feature points influence factors, the rest follows; an influence factor of a representative first core feature point in the x direction, representative of the first C N core feature points in the x direction influence factor; an influence factor of a representative first core feature point in a y direction, representative of the first C N core feature points in the y direction influence factor; an influence factor of the representative first core feature point in the z direction, representative of the C N core feature points in the z direction of the impact factor; an influence factor of a representative first key feature point in the x direction, representative of the first K N key feature points in the x direction of the impact factor; an influence factor of a representative first key feature point in the y direction, representative of the first K influence factor of N key feature points in the y direction; an influence factor of the representative first key feature point in the z direction, representative of the first K N key feature points in the z direction of the impact factor; an influence factor of a representative first important feature point in the x direction, representative of the first I N important feature points in the x direction of the impact factor; an influence factor representing the first important feature point in the y direction, representative of the I N important feature points in the y direction; an impact factor in the z direction representing the 1st important feature point, representative of the I N important feature points in the z-direction impact factor; an influence factor of the representative first general feature point in the x direction, representative of the G N number of general feature points in the x direction; an influence factor of the representative 1st general feature point in the y direction, representative of the G N number of general feature points in the y direction; an influence factor in the z direction representing the 1st general feature point, representing the first G N general feature points in the z direction; the rest follows suit.

6. The method of claim 1, wherein: The error e is set in step s4 as: e = R m P c - n P t ; m P c ( m x t , m y t , m z t ( ) represents the actual coordinates of the feature point in the current attitude, measured in the O-xyz coordinate system; n P t ( n x t , n y t , n z t ) represents the coordinates in the theoretical target pose in the coordinate system O-xyz; R represents the position and attitude transformation parameters.

7. The method of claim 6, wherein: The errors e in said step s4 are ranked as: C e is a set of core feature point errors, K e is a set of key feature point errors, I e is a set of important feature point errors, G e is a set of general feature point errors; C e1 is an error of a first core feature point, For the first C N core feature points of error, the rest of the analogy; Error in x direction for 1st core feature point, For the first C Error of N core feature points in x direction; Error in x direction for 1st core feature point, For the first C Error of N core feature points in y direction; Error in z direction for the 1st core feature point, For the first C Error of N core feature points in z direction; Error in x direction for 1st key feature point, For the first K Error of N key feature points in x direction; Error in x direction for 1st key feature point, For the first K Error of N key feature points in y direction; Error in z direction for the 1st key feature point, For the first K Error in z-direction for N key feature points; Error in x direction for 1st important feature point, For the first I Error in x-direction for N important feature points; Error in y direction for 1st important feature point, For the first I Error in the y direction for N important feature points; Error in z-direction for the 1st important feature point, For the first I Error in z-direction of N important feature points.

8. The method of claim 1, wherein: The mathematical model solved by the aircraft major component optimal position and attitude fitting algorithm established in the step s5 is as follows: f(R) is the objective function of the algorithm optimization, s.t is the symbol of the constraint condition, and e≤Tol is the constraint condition.

9. The method of claim 1, wherein: The impact factor W of all feature points in the step s6 is set to be the same and is set to 1, and the sorting is: C W is a set of core feature point influence factors, K W is a set of key feature point influence factors, I W is a set of important feature point influence factors, G W is a set of general feature point influence factors; C W1 is a first core feature point influence factor, For the first C N core feature points influence factors, the rest follows suit.

10. The method of claim 1, wherein: The algorithm solving process in step s7 is carried out in an iterative manner, and the algorithm jumps out of iteration when the number of iterations reaches the set maximum number of iterations; the maximum number of iterations is a fixed positive integer set according to the actual application, which does not change during the algorithm iteration.

11. The method of claim 1, wherein: If only the general feature points are out of tolerance in step s9, the out-of-tolerance points are discarded, and the algorithm is used to continue to solve, to obtain the optimal solution of the position and pose transformation parameter R that makes all points satisfy the range Tol of the permitted tolerance.

12. The method of claim 11, wherein: If only the important feature points are out of tolerance in the step s9, the influence factor W of the feature points is modified, the influence factors of the core, key and important feature points are all set as a, and a>1 is ensured, and the sorting is: C W is a set of core feature point influence factors, K W is a set of key feature point influence factors, I W is a set of important feature point influence factors, G W is a set of general feature point influence factors; C W1 is a first core feature point influence factor, For the first C N core feature points influence factor, the rest follows suit; The algorithm is used to solve again, and the core, key and important feature points are mainly ensured. If the results show that the core, key and important feature points satisfy the range Tol of the permitted tolerance, the optimal solution of the position and pose transformation parameter R for the core, key and important feature points is further obtained, and the out-of-tolerance general feature points are discarded.

13. The method of claim 11, wherein: If only the key feature points are out of tolerance in the step s9, the influence factor W of the feature points is modified, the influence factor of the core and key feature points is set as a, the influence factor of the important feature points is set as b, and a > b > 1 is ensured, and the sequence is: C W is a set of core feature point influence factors, K W is a set of key feature point influence factors, I W is a set of important feature point influence factors, G W is a set of general feature point influence factors; C W1 is a first core feature point influence factor, For the first C N core feature points influence factor, the rest follows suit; The algorithm is used to solve again, and the core, key and important feature points are mainly ensured. If the results show that the core, key and important feature points satisfy the range Tol of the permitted tolerance, the optimal solution of the position and pose transformation parameter R for the core, key and important feature points is further obtained, and the out-of-tolerance general feature points are discarded.

14. The method of claim 11, wherein: If only the core feature points are out of tolerance in the step s9, the influence factor W of the feature points is modified, the influence factor of the core feature points is set as a, the influence factor of the key feature points is set as b, and the influence factor of the important feature points is set as c, and a > b > c > 1 is ensured, and the order is: C W is a set of core feature point influence factors, K W is a set of key feature point influence factors, I W is a set of important feature point influence factors, G W is a set of general feature point influence factors; C W1 is a first core feature point influence factor, For the first C N core feature points influence factor, the rest follows suit; The algorithm is used to solve again, and the core, key and important feature points are mainly ensured. If the results show that the core, key and important feature points satisfy the range Tol of the permitted tolerance, the optimal solution of the position and pose transformation parameter R for the core, key and important feature points is further obtained, and the out-of-tolerance general feature points are discarded.

15. The method of claim 1, wherein: If the out-of-tolerance feature point is general and important in the step s10, the influence factor W of the feature point is modified, the core, key and important influence factors are all set as a, and a>1 is ensured, and the sorting is: C W is a set of core feature point influence factors, K W is a set of key feature point influence factors, I W is a set of important feature point influence factors, G W is a set of general feature point influence factors; C W1 is a first core feature point influence factor, For the first C N core feature points influence factor, the rest follows suit; The algorithm is used to solve again, and the core, key and important feature points are mainly ensured. If the results show that the core, key and important feature points satisfy the range Tol of the permitted tolerance, the optimal solution of the position and pose transformation parameter R for the core, key and important feature points is further obtained, and the out-of-tolerance general feature points are discarded.

16. The method of claim 1, wherein: If the out-of-tolerance feature points are general and key in the step s10, the influence factor W of the feature points is modified, the influence factor of the core and key feature points is set as a, the influence factor of the important feature points is set as b, a > b > 1 is ensured, and the order is: C W is a set of core feature point influence factors, K W is a set of key feature point influence factors, I W is a set of important feature point influence factors, G W is a set of general feature point influence factors; C W1 is a first core feature point influence factor, For the first C N core feature points influence factor, the rest follows suit; The algorithm is used to solve again, and the core, key and important feature points are mainly ensured. If the results show that the core, key and important feature points satisfy the range Tol of the permitted tolerance, the optimal solution of the position and pose transformation parameter R for the core, key and important feature points is further obtained, and the out-of-tolerance general feature points are discarded. The algorithm is used to solve again, and the core, key and important feature points are mainly ensured. If the results show that the core, key and important feature points satisfy the range Tol of the permitted tolerance, the optimal solution of the position and pose transformation parameter R for the core, key and important feature points is further obtained, and the out-of-tolerance general feature points are discarded.

17. The method of claim 1, wherein: In step s10, if the out-of-tolerance feature points are general and core, the influence factor W of the feature points is modified, the influence factor of the core feature points is set as a, the influence factor of the key feature points is set as b, and the influence factor of the important feature points is set as c, to ensure that a > b > c > 1, and the order is: C W is a set of core feature point influence factors, K W is a set of key feature point influence factors, I W is a set of important feature point influence factors, G W is a set of general feature point influence factors; C W1 is a first core feature point influence factor, For the first C N core feature points influence factor, the rest follows suit; Solve again by using the algorithm, if the result shows that only the core feature point meets the permitted range of tolerance Tol, at this time the optimal solution of the position and attitude transformation parameter R for the core feature point is further obtained, and the key, important and general feature points of the tolerance are discarded; if the result shows that only the core and key feature points meet the permitted range of tolerance Tol, at this time the optimal solution of the position and attitude transformation parameter R for the core and key feature points is further obtained, and the important and general feature points of the tolerance are discarded; if the result shows that the core, key and important feature points meet the permitted range of tolerance Tol, at this time the optimal solution of the position and attitude transformation parameter R for the core, key and important feature points is further obtained, and the general feature points of the tolerance are discarded.

18. The method of claim 1, wherein: If the out-of-tolerance feature point is important and key in the step s10, the influence factor W of the feature point is modified, the influence factor of the core feature point is set as a, the influence factor of the key and important feature point is set as b, and a > b > 1 is ensured, and the sequence is: C W is a set of core feature point influence factors, K W is a set of key feature point influence factors, I W is a set of important feature point influence factors, G W is a set of general feature point influence factors; C W1 is a first core feature point influence factor, For the first C N core feature points influence factor, the rest follows suit; Solve again by using the algorithm, if the result shows that only the core feature point meets the permitted range of tolerance Tol, at this time the optimal solution of the position and attitude transformation parameter R for the core feature point is further obtained, and the key, important and general feature points of the tolerance are discarded; if the result shows that only the core and key feature points meet the permitted range of tolerance Tol, at this time the optimal solution of the position and attitude transformation parameter R for the core and key feature points is further obtained, and the important and general feature points of the tolerance are discarded; if the result shows that the core, key and important feature points meet the permitted range of tolerance Tol, at this time the optimal solution of the position and attitude transformation parameter R for the core, key and important feature points is further obtained, and the general feature points of the tolerance are discarded.

19. The method of claim 1, wherein: If the out-of-tolerance feature point is important and core, or key and core in the step s10, the influence factor W of the feature point is modified, the influence factor of the core feature point is set as a, the influence factor of the key feature point is set as b, and the influence factor of the important feature point is set as c, so as to ensure that a > b > c > 1, and the order is: C W is a set of core feature point influence factors, K W is a set of key feature point influence factors, I W is a set of important feature point influence factors, G W is a set of general feature point influence factors; C W1 is a first core feature point influence factor, For the first C N core feature points influence factor, the rest follows suit; Solve again by using the algorithm, if the result shows that only the core feature point meets the permitted range of tolerance Tol, at this time the optimal solution of the position and attitude transformation parameter R for the core feature point is further obtained, and the key, important and general feature points of the tolerance are discarded; if the result shows that only the core and key feature points meet the permitted range of tolerance Tol, at this time the optimal solution of the position and attitude transformation parameter R for the core and key feature points is further obtained, and the important and general feature points of the tolerance are discarded; if the result shows that the core, key and important feature points meet the permitted range of tolerance Tol, at this time the optimal solution of the position and attitude transformation parameter R for the core, key and important feature points is further obtained, and the general feature points of the tolerance are discarded.

20. The method of claim 1, wherein: The step s11 modifies the influence factor W of the feature point if the out-of-tolerance feature point is general, important or critical, sets the influence factor of the core feature point as a, sets the influence factor of the important and critical feature point as b, ensures that a > b > 1, and sorts as: C W is a set of core feature point influence factors, K W is a set of key feature point influence factors, I W is a set of important feature point influence factors, G W is a set of general feature point influence factors; C W1 is a first core feature point influence factor, For the first C N core feature points influence factor, the rest follows suit; Solve again by using the algorithm, if the result shows that only the core feature point meets the permitted range of tolerance Tol, at this time the optimal solution of the position and attitude transformation parameter R for the core feature point is further obtained, and the key, important and general feature points of the tolerance are discarded; if the result shows that only the core and key feature points meet the permitted range of tolerance Tol, at this time the optimal solution of the position and attitude transformation parameter R for the core and key feature points is further obtained, and the important and general feature points of the tolerance are discarded; if the result shows that the core, key and important feature points meet the permitted range of tolerance Tol, at this time the optimal solution of the position and attitude transformation parameter R for the core, key and important feature points is further obtained, and the general feature points of the tolerance are discarded.

21. The method of claim 1, wherein: The step s11 modifies the influence factor W of the feature point if the out-of-tolerance feature point is general, important, core, or important, critical, core, or general, critical, core, sets the influence factor of the core feature point as a, the influence factor of the critical feature point as b, and the influence factor of the important feature point as c, and ensures that a > b > c > 1, and the order is: C W is a set of core feature point influence factors, K W is a set of key feature point influence factors, I W is a set of important feature point influence factors, G W is a set of general feature point influence factors; C W1 is a first core feature point influence factor, For the first C N core feature points influence factor, the rest follows suit; Then the algorithm is used to solve, focus on ensuring that the core feature points do not exceed the error, if the results show that only the core feature points meet the permitted range Tol error, at this time further obtained for the core feature points of position and attitude transformation parameters R optimal solution, the key, important and general feature points discarded; if the results show that only the core and key feature points meet the permitted range Tol error, at this time further obtained for the core and key feature points of position and attitude transformation parameters R optimal solution, the important and general feature points discarded; if the results show that the core, key and important feature points meet the permitted range Tol error, at this time further obtained for the core, key and important feature points of position and attitude transformation parameters R optimal solution, the general feature points discarded.

22. The method of claim 1, wherein: The four types of feature points in the step s12 are all out of tolerance, the influence factor W of the feature points is modified, the influence factor of the core feature points is set as a, the influence factor of the key feature points is set as b, the influence factor of the important feature points is set as c, and a > b > c > 1 is ensured, and the order is: C W is a set of core feature point influence factors, K W is a set of key feature point influence factors, I W is a set of important feature point influence factors, G W is a set of general feature point influence factors; C W1 is a first core feature point influence factor, For the first C N core feature points influence factor, the rest follows suit; Then the algorithm is used to solve, focus on ensuring that the core feature points do not exceed the error, if the results show that only the core feature points meet the permitted range Tol error, at this time further obtained for the core feature points of position and attitude transformation parameters R optimal solution, the key, important and general feature points discarded; if the results show that only the core and key feature points meet the permitted range Tol error, at this time further obtained for the core and key feature points of position and attitude transformation parameters R optimal solution, the important and general feature points discarded; If the results show that the core, key and important feature points meet the permitted range Tol error, at this time further obtained for the core, key and important feature points of position and attitude transformation parameters R optimal solution, the general feature points discarded.

23. The method of claim 1, wherein: the coordinates of the feature points of the aircraft major component in the optimal position and attitude are calculated in the step s13 for m P c is the actual coordinate of the feature point under the current pose.

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