Calculation method for gasket adjustment amount in helicopter tail transmission shaft coaxiality adjustment process

Abstract

The invention relates to the technical field of aviation assembly, in particular to a method for calculating the gasket adjustment amount in the coaxiality adjustment process of a helicopter tail transmission shaft, and the method comprises the steps: constructing a target key point and a target virtual camera of the helicopter tail transmission shaft, so as to determine a first coaxiality error representation vector of the helicopter tail transmission shaft; obtaining target measurement data of the helicopter tail transmission shaft, and equivalently mapping the target measurement data to the first coaxiality error representation vector to obtain a second coaxiality error representation vector meeting a preset format; and inputting the second coaxiality error representation vector into a pre-calibrated mathematical solution model to output the adjustment amount of each gasket of the helicopter tail transmission shaft. Therefore, the problems that in the prior art, only two sets of single circular targets are measured, the coaxiality of the helicopter tail transmission shaft cannot be effectively observed, the adjustment amount of the installation gasket is estimated only according to manual experience, the labor cost is increased, and the accuracy of the adjustment amount of the gasket is reduced are solved.

Description

Technical Field

[0001] The present application relates to the field of aviation assembly technology, and in particular to a method for calculating a gasket adjustment amount during a coaxiality adjustment process of a helicopter tail transmission shaft. Background Art

[0002] In the field of aviation manufacturing, during the assembly of helicopter transmission systems, it is necessary to control the coaxiality between the transmission shafts at the tail of the helicopter to meet the process requirements. At present, the main means is to evaluate the coaxiality of the transmission shaft at the tail of the helicopter through a sensor (laser tracker, laser centering instrument, collimator, etc.), and then add or remove shims on multiple mounting brackets of the middle reducer to solve the coaxiality compensation problem of the input / output shafts of the main reducer-middle reducer-tail reducer.

[0003] In the helicopter manufacturing plant, the existing tail drive shaft coaxiality adjustment technology adopts a collimating telescope. According to the workers' experience analysis, the coaxiality inspection and compensation of each axis are completed. Figure 1 As shown in FIG. 1 , the main process is as follows: (1) Install a mid-reducing simulation tooling at the position of the intermediate reducer mounting seat, on which are installed two dedicated collimating telescopes, with the included angle of the axes of the two pairs of collimating telescopes being 145°±2'; (2) Install a Φ2.0 mm round target at the center of the output shaft flange of the tail shaft of the main reducer, and install a Φ2.0 mm round target at the center of the input shaft end flange of the tail reducer model; (3) Use the collimating telescope to check, and repeatedly adjust the thickness of the adjustment pad between the mid-reducing and the mid-reducing mounting bracket according to manual experience, so that the two Φ2.0 mm round targets appear at the center of the field of view of the two collimating telescopes at the same time.

[0004] However, there are several problems with the existing methods of manually measuring and adjusting the coaxiality of the tail drive shaft: (1) Measuring only two groups of single circular targets cannot effectively observe the coaxiality. For example, observing only one target on the main reducer can only characterize the center position of the starting point of the main reducer output shaft, and cannot characterize the coaxiality between the main reducer output shaft and the intermediate reducer input shaft; observing only one target on the tail reducer can only characterize the center position of the end point of the tail reducer output shaft, and cannot characterize the coaxiality between the tail reducer output shaft and the intermediate reducer input shaft. (2) It is impossible to obtain a quantitative mathematical relationship between the observed data and the adjustment amount of the installation gasket: the adjustment amount of the installation gasket is estimated only based on manual experience, so it may require repeated adjustments and repeated observations.

[0005] In response to the above problems, people hope to use digital measurement methods to assist in coaxiality measurement and gasket adjustment analysis. Some scholars have used laser trackers to detect the coaxiality of very large astronomical telescopes. They also used collimating telescopes and laser trackers to obtain the coaxiality measurement of two holes to be processed that are far apart on very large parts. These studies have inspired the measurement methods of the coaxiality of each axis of the tail beam. Coaxiality measurement methods are certainly important, but after obtaining the coaxiality between each axis, it is difficult to obtain the accurate adjustment amount of the gasket system.

[0006] Therefore, the related technology only measures two groups of single circular targets, which cannot effectively observe the coaxiality of the helicopter tail drive shaft, and only estimates the adjustment amount of the installed gasket based on manual experience, which increases labor costs. In addition, the accuracy of the estimated gasket adjustment amount is low, which reduces the accuracy and reliability of the gasket adjustment amount, which needs to be solved urgently. Summary of the invention

[0007] The present application provides a method for calculating the amount of shim adjustment during the coaxiality adjustment of a helicopter tail drive shaft, so as to solve the problems in the related art where only two groups of single circular targets are measured, the coaxiality of the helicopter tail drive shaft cannot be effectively observed, and the adjustment amount of the installed shim is estimated only based on manual experience, which increases labor costs, and the accuracy of the estimated shim adjustment amount is low, which reduces the accuracy and reliability of the shim adjustment amount.

[0008] The first aspect of the present application provides a method for calculating the amount of gasket adjustment during the coaxiality adjustment of a helicopter tail drive shaft, comprising the following steps: constructing target key points and a target virtual camera of the helicopter tail drive shaft, and using the target virtual camera and the target key points to determine a first coaxiality error characterization vector of the helicopter tail drive shaft; acquiring target measurement data of the helicopter tail drive shaft, and equivalently mapping the target measurement data to the first coaxiality error characterization vector to obtain a second coaxiality error characterization vector that meets a preset format; and inputting the second coaxiality error characterization vector into a pre-calibrated mathematical solution model to output the adjustment amount of each gasket of the helicopter tail drive shaft.

[0009] Optionally, in one embodiment of the present application, constructing the target key points and the target virtual camera of the helicopter tail drive shaft, and determining the first coaxiality error characterization vector of the helicopter tail drive shaft using the target virtual camera and the target key points, includes: respectively extracting the first key points, the second key points, the third key points and the fourth key points on the axes of the main reducer output shaft, the intermediate reducer input shaft, the intermediate reducer output shaft and the tail reducer input shaft, and respectively constructing a first virtual camera and a second virtual camera on the axes of the intermediate reducer input shaft and the intermediate reducer output shaft; based on the first virtual camera, the first key points and the second key points, determining the first coaxiality relationship between the main reducer output shaft and the intermediate reducer input shaft; based on the second virtual camera, the third key points and the fourth key points, determining the second coaxiality relationship between the tail reducer input shaft and the intermediate reducer output shaft; and determining the first coaxiality error characterization vector of the helicopter tail drive shaft according to the first coaxiality relationship and the second coaxiality relationship.

[0010] Optionally, in one embodiment of the present application, obtaining the target measurement data of the helicopter tail drive shaft includes: obtaining first measurement data of the helicopter tail drive shaft based on a laser tracker; obtaining second measurement data of the helicopter tail drive shaft based on a laser centering instrument; obtaining third measurement data of the helicopter tail drive shaft based on a collimating telescope; and composing the target measurement data based on the first measurement data, the second measurement data and the third measurement data.

[0011] Optionally, in one embodiment of the present application, before inputting the second coaxiality error characterization vector into a pre-calibrated mathematical solution model, it also includes: using the target measurement method to collect multiple sets of pre-calibrated data; performing equivalent processing on the multiple sets of pre-calibrated data to obtain equivalently processed data; and using the equivalently processed data to perform parameter calibration on a pre-constructed initial mathematical solution model to determine the pre-calibrated mathematical solution model.

[0012] Optionally, in one embodiment of the present application, the outputting of the adjustment amounts of each gasket of the helicopter tail drive shaft includes: constructing a target approximate linear Jacobian matrix relationship; calibrating each coefficient of the Jacobian matrix based on the target approximate linear Jacobian matrix relationship and at least one set of data in the target measurement data to obtain a calibrated Jacobian matrix; and using the calibrated Jacobian matrix to calculate the adjustment amounts of each gasket of the helicopter tail drive shaft.

[0013] A second aspect of the present application provides a device for calculating the amount of gasket adjustment during the coaxiality adjustment process of a helicopter tail drive shaft, comprising: a construction module for constructing target key points and a target virtual camera of the helicopter tail drive shaft, and using the target virtual camera and the target key points to determine a first coaxiality error characterization vector of the helicopter tail drive shaft; an acquisition module for acquiring target measurement data of the helicopter tail drive shaft, and equivalently mapping the target measurement data to the first coaxiality error characterization vector to obtain a second coaxiality error characterization vector that meets a preset format; and a calculation module for inputting the second coaxiality error characterization vector into a pre-calibrated mathematical solution model to output the adjustment amount of each gasket of the helicopter tail drive shaft.

[0014] Optionally, in one embodiment of the present application, the construction module includes: a first construction unit, used to respectively extract the first key point, the second key point, the third key point and the fourth key point on the axis of the main reducer output shaft, the middle reducer input shaft, the middle reducer output shaft and the tail reducer input shaft, and respectively construct a first virtual camera and a second virtual camera on the axis of the middle reducer input shaft and the middle reducer output shaft; a first determination unit, used to determine the first coaxiality relationship between the main reducer output shaft and the middle reducer input shaft based on the first virtual camera, the first key point and the second key point; a second determination unit, used to determine the second coaxiality relationship between the tail reducer input shaft and the middle reducer output shaft based on the second virtual camera, the third key point and the fourth key point; a third determination unit, used to determine the first coaxiality error characterization vector of the helicopter tail drive shaft according to the first coaxiality relationship and the second coaxiality relationship.

[0015] Optionally, in one embodiment of the present application, the acquisition module includes: a first acquisition unit, used to acquire first measurement data of the helicopter tail drive shaft based on a laser tracker; a second acquisition unit, used to acquire second measurement data of the helicopter tail drive shaft based on a laser centering instrument; a third acquisition unit, used to acquire third measurement data of the helicopter tail drive shaft based on a collimating telescope; and a fourth acquisition unit, used to compose the target measurement data based on the first measurement data, the second measurement data and the third measurement data.

[0016] Optionally, in one embodiment of the present application, the device of the embodiment of the present application also includes: an acquisition module, which is used to acquire multiple groups of pre-calibrated data using the target measurement method before inputting the second coaxiality error characterization vector into the pre-calibrated mathematical solution model; a determination module, which is used to perform equivalent processing on the multiple groups of pre-calibrated data before inputting the second coaxiality error characterization vector into the pre-calibrated mathematical solution model to obtain equivalently processed data; and a processing module, which is used to perform parameter calibration on a pre-constructed initial mathematical solution model using the equivalently processed data before inputting the second coaxiality error characterization vector into the pre-calibrated mathematical solution model to determine the pre-calibrated mathematical solution model.

[0017] Optionally, in one embodiment of the present application, the calculation module includes: a second construction unit, used to construct a target approximate linear Jacobian matrix relationship; a fifth acquisition unit, used to calibrate each coefficient of the Jacobian matrix based on the target approximate linear Jacobian matrix relationship and at least one set of data in the target measurement data to obtain a calibrated Jacobian matrix; and a calculation unit, used to calculate the adjustment amount of each gasket of the helicopter tail drive shaft using the calibrated Jacobian matrix.

[0018] A third aspect of the present application provides an electronic device, comprising: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the program to implement a method for calculating a gasket adjustment amount during coaxiality adjustment of a helicopter tail drive shaft as described in the above embodiment.

[0019] A fourth aspect of the present application provides a computer-readable storage medium, which stores a computer program. When the program is executed by a processor, it implements the method for calculating the gasket adjustment amount during the coaxiality adjustment of the helicopter tail drive shaft as described above.

[0020] A fifth aspect of the present application provides a computer program product, including a computer program, which, when executed, is used to implement the method for calculating the gasket adjustment amount during the coaxiality adjustment of the helicopter tail drive shaft as described above.

[0021] The embodiment of the present application can construct the target key points and target virtual camera of the helicopter tail drive shaft to determine the first coaxiality error characterization vector of the helicopter tail drive shaft, obtain the target measurement data of the helicopter tail drive shaft, and map it to the first coaxiality error characterization vector equivalently to obtain a second coaxiality error characterization vector that satisfies a certain format, and then input the second coaxiality error characterization vector into a pre-calibrated mathematical solution model to output the adjustment amount of each gasket of the helicopter tail drive shaft, effectively improving the accuracy and reliability of the gasket adjustment amount. Thus, the problem that only two groups of single circular targets are measured in the related art, the coaxiality of the helicopter tail drive shaft cannot be effectively observed, and the adjustment amount of the installed gasket is estimated only based on manual experience, which increases labor costs and reduces the accuracy and reliability of the gasket adjustment amount is solved.

[0022] Additional aspects and advantages of the present application will be given in part in the description below, and in part will become apparent from the description below, or will be learned through the practice of the present application. BRIEF DESCRIPTION OF THE DRAWINGS

[0023] The above and / or additional aspects and advantages of the present application will become apparent and easily understood from the following description of the embodiments in conjunction with the accompanying drawings, in which:

[0024] Figure 1 It is a schematic diagram of manual measurement of the coaxiality of the tail transmission shaft in the related art;

[0025] Figure 2 A flowchart of a method for calculating a gasket adjustment amount during a coaxiality adjustment process of a helicopter tail transmission shaft provided in accordance with an embodiment of the present application;

[0026] Figure 3 It is a schematic diagram of the key points of a specific embodiment of the present application and the arrangement of a virtual camera in a tail beam transmission shaft coaxiality adjustment system;

[0027] Figure 4 A schematic diagram of an equivalent mapping method of various sensor measurement data in an actual system to a coaxiality error characterization vector in a mathematical model in a specific embodiment of the present application;

[0028] Figure 5 A schematic diagram of the approximate linear influence of the shim adjustment on the reducer tooling posture and the pixel coordinates of key points in the image taken by the virtual camera in a specific embodiment of the present application;

[0029] Figure 6 A schematic diagram of a combined operation flow of a general method for calculating a gasket adjustment amount according to a specific embodiment of the present application;

[0030] Figure 7It is a structural schematic diagram of a device for calculating the gasket adjustment amount during the coaxiality adjustment of a helicopter tail transmission shaft provided in accordance with an embodiment of the present application;

[0031] Figure 8 It is a schematic diagram of the structure of an electronic device provided according to an embodiment of the present application. DETAILED DESCRIPTION

[0032] Embodiments of the present application are described in detail below, and examples of the embodiments are shown in the accompanying drawings, wherein the same or similar reference numerals throughout represent the same or similar elements or elements having the same or similar functions. The embodiments described below with reference to the accompanying drawings are exemplary and are intended to be used to explain the present application, and should not be construed as limiting the present application.

[0033] The following describes a method for calculating the amount of shim adjustment during the coaxiality adjustment of the helicopter tail drive shaft of an embodiment of the present application with reference to the accompanying drawings. In view of the problem that only two groups of single circular targets are measured in the related technology mentioned in the background technology center, the coaxiality of the helicopter tail drive shaft cannot be effectively observed, and the adjustment amount of the installed shim is estimated only based on manual experience, which increases labor costs and reduces the accuracy of the shim adjustment amount, the present application provides a method for calculating the amount of shim adjustment during the coaxiality adjustment of the helicopter tail drive shaft, in which a target key point and a target virtual camera of the helicopter tail drive shaft can be constructed to determine the first coaxiality error characterization vector of the helicopter tail drive shaft, obtain the target measurement data of the helicopter tail drive shaft, and map it equivalently to the first coaxiality error characterization vector to obtain a second coaxiality error characterization vector that meets a certain format, and then input the second coaxiality error characterization vector into a pre-calibrated mathematical solution model to output the adjustment amount of each shim of the helicopter tail drive shaft, effectively improving the accuracy and reliability of the shim adjustment amount. This solves the problem that in the related art, only two groups of single circular targets are measured, the coaxiality of the helicopter tail drive shaft cannot be effectively observed, and the adjustment amount of the installation gasket is estimated only based on manual experience, which increases labor costs and reduces the accuracy and reliability of the gasket adjustment amount.

[0034] Specifically, Figure 2 A flowchart of a method for calculating a gasket adjustment amount during coaxiality adjustment of a helicopter tail drive shaft provided in an embodiment of the present application.

[0035] like Figure 2 As shown, the method for calculating the gasket adjustment amount during the coaxiality adjustment of the helicopter tail transmission shaft includes the following steps:

[0036] In step S201, target key points and a target virtual camera of a helicopter tail drive shaft are constructed, and a first coaxiality error characterization vector of the helicopter tail drive shaft is determined using the target virtual camera and the target key points.

[0037] In the embodiment of the present application, the first coaxiality error characterization vector is a vector that abstractly characterizes the coaxiality error based on the constructed key points and the virtual camera.

[0038] It can be understood that the embodiment of the present application can construct the target key points and target virtual camera of the helicopter tail drive shaft. For example, first, in order to characterize the coaxiality relationship, the embodiment of the present application extracts key points on the axes of the main reducer output shaft, the middle reducer input shaft, the middle reducer output shaft and the tail reducer input shaft of the helicopter tail drive shaft to form two groups of spatial point groups to be aligned (each group contains two key points), which are respectively used to characterize the coaxiality relationship between the main reducer output shaft and the middle reducer input shaft, and the middle reducer output shaft and the tail reducer input shaft; in addition, two monocular cameras are virtually constructed on the middle reducer tooling. According to the perspective projection equation of the monocular camera, the coordinates of the aforementioned key points in the 2-D pixel coordinate system can be calculated, and then the image coordinate error vector in the following step, that is, the first coaxiality error characterization vector, can be constructed to realize the indirect observation and characterization of the coaxiality error, which effectively improves the feasibility of calculating the gasket adjustment amount in the process of coaxiality adjustment of the helicopter tail drive shaft.

[0039] Optionally, in one embodiment of the present application, target key points and a target virtual camera of a helicopter tail drive shaft are constructed, and the target virtual camera and the target key points are used to determine a first coaxiality error characterization vector of the helicopter tail drive shaft, including: extracting first key points, second key points, third key points and fourth key points on the axes of the main reducer output shaft, the intermediate reducer input shaft, the intermediate reducer output shaft and the tail reducer input shaft, respectively, and constructing a first virtual camera and a second virtual camera on the axes of the intermediate reducer input shaft and the intermediate reducer output shaft, respectively; based on the first virtual camera, the first key point and the second key point, determining a first coaxiality relationship between the main reducer output shaft and the intermediate reducer input shaft; based on the second virtual camera, the third key point and the fourth key point, determining a second coaxiality relationship between the tail reducer input shaft and the intermediate reducer output shaft; and determining the first coaxiality error characterization vector of the helicopter tail drive shaft according to the first coaxiality relationship and the second coaxiality relationship.

[0040] For example, when characterizing the relative position of two axes, at least the positional relationship of two different points on one axis relative to the other axis needs to be known; specifically in the tail beam assembly system, if the coaxiality of the main reducer output shaft and the intermediate reducer input shaft needs to be characterized, at least two spatial points on the intermediate reducer input shaft axis need to be observed by a fixed sensor on the main reducer output axis, or two spatial points on the main reducer output shaft axis need to be observed by a fixed sensor on the intermediate reducer input shaft. The same applies to the tail reducer input shaft and the intermediate reducer output shaft.

[0041] Next, considering that the reducers of the tail transmission shaft system are the main reducer, the middle reducer, and the tail reducer in order, the middle reducer is used as the reference, and two coordinate points on the axis of the main reducer output shaft and two coordinate points on the axis of the tail reducer input shaft are observed from the middle reducer to the front and rear sides, respectively, to obtain two groups of space points to be aligned, forming an indirect representation of the coaxiality of each axis. Figure 3 As shown, let P m,1 , P m,2 Represents the two spatial points on the output shaft axis of the main reducer to be aligned, P t,1 , P t,2 Represents the two spatial points on the axis of the tail reducer input shaft to be aligned, the main reducer coordinate system OX m Y m Z m , medium reducer coordinate system OX z Y z Z z , tail reducer coordinate system OX t Y t Z t They are respectively fixed on the main reducer simulation component, the middle reducer simulation component and the tail reducer simulation component.

[0042] Then, if Figure 3 As shown, a virtual camera is generated on the input and output axes of the middle reducer, that is, a virtual monocular camera: it is connected to the coordinate system OX z Y z Z z The relative position and posture of the two virtual cameras always remain unchanged, and the optical axes of the two virtual cameras coincide with the input shaft / output shaft of the middle reducer respectively.

[0043] Furthermore, according to the perspective projection equation of the monocular camera, P can be obtained m,1 , P m,2 The coordinates of the virtual image 1 captured by the virtual camera 1 are p m,1 、p m,2 ;P t,1 , P t,2 The coordinates of the virtual image 2 captured by the virtual camera 2 are p t,1 、p t,2 In this way, the relative position and posture relationship of each axis is finally indirectly represented by two groups of four key points to be aligned.

[0044] Secondly, according to the four key points and two virtual cameras constructed, the coaxiality error can be abstractly characterized. The coaxiality relationship between the output shaft of the main reducer and the input shaft of the intermediate reducer will be represented by the p in the virtual image 1. m,1 、p m,2and the central coordinate error of virtual image 1; the coaxiality relationship between the tail reducer input shaft and the middle reducer output shaft will be represented by the p in virtual image 2 t,1 、p t,2 and the center coordinates of the virtual image 2, assuming that the image coordinates of the two groups of four spatial points to be aligned are: m,1 =(u m,1 ,v m,1 ), p m,2 =(u m,2 ,v m,2 ), p t,1 =(u t,1 ,v t,1 ), p t,2 =(u t,2 ,v t,2 ), and jointly construct the image coordinate vectors u and v as follows:

[0045] u=[u m,1 ,u m,2 ,u t,1 ,u t,2 ] T

[0046] v=[v m,1 ,v m,2 ,v t,1 ,v t,2 ] T

[0047] Among them, p m,1 、p m,2 P m,1 , P m,2 The coordinates of virtual image 1 captured by virtual camera 1, p t,1 、p t,2 P t,1 , P t,2 The coordinates of the virtual image 2 taken by the virtual camera 2; u and v are image coordinate vectors.

[0048] Assume that the center coordinates of virtual image 1 are (u m ,v m ), the center coordinates of virtual image 2 are (u t ,v t ), construct the image coordinate error vector e u 、e v :

[0049] e u =[u m,1 -u m ,u m,2 -u m ,u t,1 -ut ,u t,2 -u t ] T

[0050] e v =[v m,1 -v m ,v m,2 -v m ,v t,1 -v t ,v t,2 -v t ] T

[0051] Among them, e u 、e v is the image coordinate error vector.

[0052] Therefore, the embodiment of the present application abstracts two groups of key points to be aligned, the main reducer coordinate system, the middle reducer coordinate system, the tail reducer coordinate system and two virtual cameras, and accurately establishes their positions and postures; and designs a virtual image coordinate error vector in a unified format, so as to uniformly and indirectly characterize the coaxiality error.

[0053] In step S202, target measurement data of the helicopter tail drive shaft is acquired, and the target measurement data is equivalently mapped into a first coaxiality error characterization vector to obtain a second coaxiality error characterization vector that meets a preset format.

[0054] In an embodiment of the present application, the preset format is a coordinate format in a 2-D pixel coordinate system; the second coaxiality error characterization vector may include a coaxiality error characterization vector of a collimating telescope, a coaxiality error characterization vector of a laser centering instrument or a laser tracker.

[0055] It is understandable that the embodiment of the present application can obtain the target measurement data of the helicopter tail drive shaft. For example, it can obtain the original measurement data based on a variety of measurement methods such as a laser alignment instrument, a laser tracker or a collimating telescope, and uniformly equate the coordinates of each key point in the above steps in the 2-D pixel coordinate system. Specifically, the collimating telescope can directly capture the image, and then use the image processing algorithm to calculate the 2-D pixel coordinates of the key points; the laser alignment instrument and the laser tracker can measure the relative posture relationship of each reducer corresponding axis, calculate the three-dimensional coordinates of each key point, and then calculate the 2-D pixel coordinates of the key point according to the perspective projection equation of the monocular camera, so that the coaxiality error characterization vector of the collimating telescope and the coaxiality error characterization vector of the laser alignment instrument or the laser tracker can be obtained, which effectively improves the accuracy of the shim adjustment amount in the process of calculating the coaxiality adjustment of the helicopter tail drive shaft.

[0056] Optionally, in one embodiment of the present application, target measurement data of a helicopter tail drive shaft is obtained, including: based on a laser tracker, obtaining first measurement data of the helicopter tail drive shaft; based on a laser centering instrument, obtaining second measurement data of the helicopter tail drive shaft; based on a collimating telescope, obtaining third measurement data of the helicopter tail drive shaft; and composing target measurement data based on the first measurement data, the second measurement data, and the third measurement data.

[0057] In the embodiment of the present application, the digital equipment for measuring the axis of the helicopter tail transmission system mainly includes the following three types: laser tracker, laser centering instrument and collimating telescope. The specific measurement principles are divided into two categories:

[0058] (1) Through rotation scanning, the laser tracker and laser alignment instrument will give the relative position relationship between the axes of the intermediate reducer simulation tooling, the main reducer output shaft simulation component, and the tail reducer input shaft simulation component, which corresponds to the main reducer coordinate system OX defined above. m Y m Z m , medium reducer coordinate system OX z Y z Z z , tail reducer coordinate system OX t Y t Z t The homogeneous transformation matrix T between them;

[0059] (2) By designing the image target and using the image information captured by the collimating telescope, combined with the image processing algorithm, the center coordinates of the actual system observation target are directly given.

[0060] Therefore, it is necessary to uniformly map different types of actual sensor measurement data to the above-defined coaxiality indirect characterization parameters, namely, the image coordinate error vector e u 、e v , thereby assisting in the unified calculation of subsequent shim adjustment amounts.

[0061] For example, Figure 4 As shown, the embodiments of the present application respectively design data mapping methods for different types of measurement devices, as follows:

[0062] (1) Laser tracker or laser alignment instrument: Combined with the CAD digital model of the intermediate reducer simulation tooling, the main reducer output shaft simulation part, and the tail reducer input shaft simulation part, these two measurement methods can give the main reducer coordinate system OX m Y m Z m , medium reducer coordinate system OX z Y z Z z , tail reducer coordinate system OXt Y t Z t The homogeneous transformation matrix between them. Assume that the coordinate system OX z Y z Z z Relative to the virtual camera 1 coordinate system OX C1 Y C1 Z C1 The homogeneous transformation matrix is ​​T C1 Z , measured coordinate system OX m Y m Z m Relative to coordinate system OX z Y z Z z The homogeneous transformation matrix is ​​T z m , P m,1 , P m,2 In the coordinate system OX m Y m Z m The three-dimensional coordinates of and Then use the following formula to calculate P m,1 , P m,2 In the coordinate system OX C1 Y C1 Z C1 The coordinates below are and Using the perspective projection equation of a monocular camera, we can get p m,1 and p m,2 , among which, and It can be expressed as:

[0063]

[0064] in, and P m,1 , P m,2 In the coordinate system OX C1 Y C1 Z C1 The coordinates below; T C1 Z is the coordinate system OX z Y z Z z Relative to the virtual camera 1 coordinate system OX C1 Y C1 Z C1 The homogeneous transformation matrix of z m is the coordinate system OXm Y m Z m Relative to coordinate system OX z Y z Z z The homogeneous transformation matrix of and P m,1 , P m,2 In the coordinate system OX m Y m Z m The three-dimensional coordinates of .

[0065] Similarly, suppose the coordinate system OX in the system z Y z Z z Relative to the virtual camera 2 coordinate system OX C2 Y C2 Z C2 The homogeneous transformation matrix is ​​T C2 Z , measured coordinate system OX t Y t Z t Relative to coordinate system OX z Y z Z z The homogeneous transformation matrix is ​​T z t , P t,1 , P t,2 In the coordinate system OX t Y t Z t The three-dimensional coordinates of and Then use the following formula to calculate P t,1 , P t,2 In the coordinate system OX C2 Y C2 Z C2 The coordinates below are and Using the perspective projection equation of a monocular camera, we can get p t,1 and p t,2 ,in, and It can be expressed as:

[0066]

[0067] Among them, T C2 Z is the coordinate system OX z Y z Z z Relative to the virtual camera 2 coordinate system OX C2 YC2 Z C2 The homogeneous transformation matrix of z t is the coordinate system OX t Y t Z t Relative to coordinate system OX z Y z Z z The homogeneous transformation matrix of ; and P t,1 , P t,2 In the coordinate system OX t Y t Z t The three-dimensional coordinates of and P t,1 , P t,2 In the coordinate system OX C2 Y C2 Z C2 The coordinates below.

[0068] Therefore, the embodiment of the present application can equate the actual measurement data of the laser tracker or laser alignment instrument to e u 、e v .

[0069] (2) Collimating telescope: It needs to correspond to the P on the main reducer simulation of the actual system. m,1 , P m,2 Install the output shaft simulation with two targets at the position of the tail reducer simulation. t,1 , P t,2 An input shaft simulation with two targets is installed at the position of the middle reducer simulation, and a collimating telescope is installed at the position corresponding to the virtual cameras 1 and 2 of the middle reducer simulation. Two industrial 2-D cameras are installed at the ends of the two collimating telescopes respectively. The manual data collection method is replaced by a digital collection device, so that the coordinates p of the target on the simulation part are directly obtained from the digital collection image using the image processing algorithm. m,1 、p m,2 、p t,1 and p t,2 .

[0070] It should be noted that the core of this equivalent method is to accurately correspond the positions of the four observation targets in the actual system to the four key points in the constructed mathematical system. Therefore, it is necessary to measure the two axial distances L of the shaft simulation part in the actual system. m , L t In mathematical systems, when selecting key points, pay attention to making: dist(P m,1 , P m,2 )=Lm ;dist(P t,1 , P t,2 )=L t Secondly, it is necessary to make the internal and external parameters of the real camera of the actual system and the virtual camera of the mathematical system correspond to each other, including camera pixels, imaging plane size, focal length, camera position, etc. After completing the above two steps, the image of the actual system can be directly processed to obtain p m,1 、p m,2 、p t,1 and p t,2 Therefore, the embodiment of the present application can equate the actual measurement data of the collimating telescope to e u and e v .

[0071] It should be noted that the embodiments of the present application can equivalently map different types of actual sensor measurement data to the coaxiality error characterization vector in the aforementioned constructed mathematical model; and two equivalent methods are designed for the measurement data obtained by two different measurement principles, so that the multi-source sensor data collected by the actual system generates the same type of error characterization of the constructed mathematical model.

[0072] In step S203, the second coaxiality error characterization vector is input into a pre-calibrated mathematical solution model to output the adjustment amount of each gasket of the helicopter tail transmission shaft.

[0073] It can be understood that the embodiment of the present application can input the second coaxiality error characterization vector into a pre-calibrated mathematical solution model. For example, according to the image coordinate error vector equivalent to the measurement data of each sensor in the above steps, the adjustment amount of each gasket of the helicopter tail drive shaft is obtained. In other words, its essence is to obtain the optimal gasket adjustment amount by optimization method through a mathematical model based on the deviation condition, which effectively improves the accuracy and reliability of the gasket adjustment amount.

[0074] Optionally, in one embodiment of the present application, the adjustment amount of each gasket of the helicopter tail drive shaft is output, including: constructing a target approximate linear Jacobian matrix relationship; calibrating each coefficient of the Jacobian matrix based on the target approximate linear Jacobian matrix relationship and at least one set of data in the target measurement data to obtain a calibrated Jacobian matrix; and using the calibrated Jacobian matrix to calculate the adjustment amount of each gasket of the helicopter tail drive shaft.

[0075] In the embodiment of the present application, the adjustment of the thickness of the gasket can indirectly adjust the pitch and yaw angles of the reducer. The principle is as follows: Figure 5As shown in the figure, when the thickness of the two gaskets distributed along the axis direction is adjusted, the pitch angle of the middle reducer can be adjusted. Similarly, when the thickness of the two gaskets distributed in the vertical axis direction is changed, the yaw angle of the middle reducer will be generated. In addition, increasing or decreasing the thickness of all gaskets at the same time will also cause the overall movement of the middle reducer.

[0076] For example, when the z-axis of the virtual camera is far from the observation key point, the pitch, yaw, and translation of the medium will approximately cause the linear movement of the coordinates of the key point in the pixel coordinate system. When the shim adjustment is far from each mounting bracket, the shim adjustment will approximately linearly cause the pitch, yaw, and translation of the medium. Therefore, the two linear relationships are comprehensively transmitted, and the derived shim adjustment will approximately linearly affect the pixel coordinates of the key point to be aligned.

[0077] In which, suppose there are n sets of gaskets on the mounting support, and their adjustment amounts are x1, x2, ..., x n , forming the vector:

[0078] x=[x1,x2,...,x n ] T

[0079] Then the vectors satisfy the approximate linear image Jacobian matrix relationship:

[0080]

[0081] Next, we obtain the model Jacobian coefficient matrix J u , J v After that, the influence of the gasket adjustment on the virtual image coordinate values ​​can be characterized, and the model Jacobian coefficient matrix is ​​accurately obtained using the calibration method in the following steps.

[0082] The embodiment of the present application does not require the acquisition and calculation of detailed parameters of each component, which reduces the difficulty of system application. Applying the above-mentioned model Jacobian coefficient matrix, the image coordinate error vector e equivalently obtained according to the measurement data of each sensor mentioned above u 、e v , the gasket adjustment amount is obtained according to the following formula, which is essentially to obtain the best gasket adjustment amount by optimization method through mathematical model according to the deviation condition:

[0083]

[0084] The calibration method of the key parameters in the Jacobian coefficient matrix of the above model is as follows: first, install the main reducer, middle reducer, tail reducer and other components in the actual system without adding gaskets, record the sensor measurement data (relative position and posture measured by the laser centering instrument or laser tracker or the image measured by the collimating telescope), and then make the sensor measurement data equivalent, and record a set of data u1 and v1; add multiple sets of standard gaskets with known thickness in turn, and make the sensor measurement data equivalent, and record multiple sets of data u1 and v1. i 、v i , thus obtaining m groups of coaxiality characterization quantities, that is, the corresponding relationship between the actual system gasket adjustment quantity states:

[0085]

[0086] Among them, m is the number of samples of calibration data. Then, the model Jacobian coefficient matrix is ​​obtained according to the best fitting method:

[0087] J u =UX T (X T X) -1 , J v =VX T (X T X) -1

[0088] Where X=[x1 x2...x m ],U=[u1 u2...u m ],V=[v1 v2...v m ].

[0089] In other words, the embodiment of the present application can construct an approximate linear Jacobian matrix relationship between the gasket adjustment amount and the 2-D pixel coordinates, and calculate the coefficients of the Jacobian matrix through model parameter calibration means; finally, the gasket adjustment amount is solved by the inverse matrix of the Jacobian matrix, which effectively improves the accuracy and reliability of the gasket adjustment amount.

[0090] Optionally, in one embodiment of the present application, before inputting the second coaxiality error characterization vector into a pre-calibrated mathematical solution model, it also includes: collecting multiple sets of pre-calibrated data using a target measurement method; performing equivalent processing on the multiple sets of pre-calibrated data to obtain equivalently processed data; and performing parameter calibrating on a pre-constructed initial mathematical solution model using the equivalently processed data to determine the pre-calibrated mathematical solution model.

[0091] As a possible way to achieve this, Figure 6As shown in the figure, when constructing the model, it is necessary to consider the type of sensor used in the actual system, and use the corresponding data equivalence method to equate the actual system measurement data to the coaxiality indirect representation in the mathematical model. When calibrating the model, it is necessary to collect m groups of data combinations in the actual system, which are equivalent to the unified error data format defined in the mathematical model, and calibrate the model parameters to obtain a pre-calibrated mathematical solution model. When calculating the model, only one group of actual system measurement data needs to be collected, which is equivalent to the coaxiality indirect representation in the mathematical model, and the pre-calibrated mathematical solution model is used to solve the gasket adjustment required for the actual system, so that the coaxiality error approaches 0, which effectively improves the uniformity, versatility and efficiency of calculating the gasket adjustment amount.

[0092] According to the method for calculating the amount of shim adjustment during the coaxiality adjustment of the helicopter tail drive shaft proposed in the embodiment of the present application, the target key points and target virtual camera of the helicopter tail drive shaft can be constructed to determine the first coaxiality error characterization vector of the helicopter tail drive shaft, obtain the target measurement data of the helicopter tail drive shaft, and equivalently map it to the first coaxiality error characterization vector to obtain a second coaxiality error characterization vector that satisfies a certain format, and then input the second coaxiality error characterization vector into a pre-calibrated mathematical solution model to output the adjustment amount of each shim of the helicopter tail drive shaft, thereby effectively improving the accuracy and reliability of the shim adjustment amount. Thus, the problem that only two groups of single circular targets are measured in the related art, the coaxiality of the helicopter tail drive shaft cannot be effectively observed, and the adjustment amount of the installed shims is estimated only based on manual experience, which increases labor costs and reduces the accuracy and reliability of the shim adjustment amount is solved.

[0093] Next, a device for calculating the gasket adjustment amount during the coaxiality adjustment of the helicopter tail drive shaft according to an embodiment of the present application will be described with reference to the accompanying drawings.

[0094] Figure 7 It is a block diagram of a device for calculating the gasket adjustment amount during the coaxiality adjustment of the helicopter tail drive shaft in an embodiment of the present application.

[0095] like Figure 7 As shown, the device 10 for calculating the gasket adjustment amount during the coaxiality adjustment of the helicopter tail transmission shaft includes: a construction module 100, an acquisition module 200 and a calculation module 300.

[0096] Specifically, the construction module 100 is used to construct target key points and a target virtual camera of the helicopter tail drive shaft, and determine a first coaxiality error characterization vector of the helicopter tail drive shaft using the target virtual camera and the target key points.

[0097] The acquisition module 200 is used to acquire target measurement data of the helicopter tail transmission shaft, and equivalently map the target measurement data to a first coaxiality error characterization vector to obtain a second coaxiality error characterization vector that meets a preset format.

[0098] The calculation module 300 is used to input the second coaxiality error characterization vector into a pre-calibrated mathematical solution model to output the adjustment amount of each gasket of the helicopter tail transmission shaft.

[0099] Optionally, in one embodiment of the present application, the construction module 100 includes: a first construction unit, a first determination unit, a second determination unit and a third determination unit.

[0100] The first construction unit is used to extract the first key point, the second key point, the third key point and the fourth key point on the axis of the main reducer output shaft, the middle reducer input shaft, the middle reducer output shaft and the tail reducer input shaft, respectively, and construct the first virtual camera and the second virtual camera on the axis of the middle reducer input shaft and the middle reducer output shaft respectively;

[0101] The first determining unit is used to determine a first coaxiality relationship between the main reducer output shaft and the intermediate reducer input shaft based on the first virtual camera, the first key point and the second key point.

[0102] The second determining unit is used to determine the second coaxiality relationship between the tail reducer input shaft and the middle reducer output shaft based on the second virtual camera, the third key point and the fourth key point.

[0103] The third determining unit is used to determine a first coaxiality error characterization vector of the helicopter tail drive shaft according to the first coaxiality relationship and the second coaxiality relationship.

[0104] Optionally, in one embodiment of the present application, the acquisition module 200 includes: a first acquisition unit, a second acquisition unit, a third acquisition unit and a fourth acquisition unit.

[0105] The first acquisition unit is used to acquire first measurement data of the helicopter tail drive shaft based on a laser tracker.

[0106] The second acquisition unit is used to acquire second measurement data of the helicopter tail drive shaft based on the laser centering instrument.

[0107] The third acquisition unit is used to acquire third measurement data of the helicopter tail drive shaft based on the collimating telescope.

[0108] The fourth acquisition unit is used to compose target measurement data based on the first measurement data, the second measurement data and the third measurement data.

[0109] Optionally, in one embodiment of the present application, the device 10 of the embodiment of the present application further includes: a collection module, a determination module and a processing module.

[0110] The acquisition module is used to acquire multiple sets of pre-calibrated data by using a target measurement method before inputting the second coaxiality error characterization vector into a pre-calibrated mathematical solution model.

[0111] The determination module is used to perform equivalent processing on multiple groups of pre-calibrated data before inputting the second coaxiality error characterization vector into the pre-calibrated mathematical solution model to obtain equivalently processed data.

[0112] The processing module is used to calibrate the parameters of the pre-constructed initial mathematical solution model using equivalently processed data before inputting the second coaxiality error characterization vector into the pre-calibrated mathematical solution model to determine the pre-calibrated mathematical solution model.

[0113] Optionally, in one embodiment of the present application, the calculation module 300 includes: a second construction unit, a fifth acquisition unit and a calculation unit.

[0114] The second construction unit is used to construct a target approximate linear Jacobian matrix relationship.

[0115] The fifth acquisition unit is used to calibrate each coefficient of the Jacobian matrix based on the target approximate linear Jacobian matrix relationship and at least one set of data in the target measurement data to obtain a calibrated Jacobian matrix.

[0116] The calculation unit is used to calculate the adjustment amount of each gasket of the helicopter tail transmission shaft by using the calibrated Jacobian matrix.

[0117] It should be noted that the above explanation of the embodiment of the method for calculating the shim adjustment amount during the coaxiality adjustment of the helicopter tail drive shaft is also applicable to the device for calculating the shim adjustment amount during the coaxiality adjustment of the helicopter tail drive shaft of this embodiment, and will not be repeated here.

[0118] According to the device for calculating the amount of shim adjustment during the coaxiality adjustment of the helicopter tail drive shaft proposed in the embodiment of the present application, the target key points and target virtual camera of the helicopter tail drive shaft can be constructed to determine the first coaxiality error characterization vector of the helicopter tail drive shaft, obtain the target measurement data of the helicopter tail drive shaft, and equivalently map it to the first coaxiality error characterization vector to obtain a second coaxiality error characterization vector that satisfies a certain format, and then input the second coaxiality error characterization vector into a pre-calibrated mathematical solution model to output the adjustment amount of each shim of the helicopter tail drive shaft, thereby effectively improving the accuracy and reliability of the shim adjustment amount. Thus, the problem that only two groups of single circular targets are measured in the related art, the coaxiality of the helicopter tail drive shaft cannot be effectively observed, and the adjustment amount of the installed shims is estimated only based on manual experience, which increases labor costs and reduces the accuracy and reliability of the shim adjustment amount is solved.

[0119] Figure 8 A schematic diagram of the structure of an electronic device provided in an embodiment of the present application. The electronic device may include:

[0120] A memory 801 , a processor 802 , and a computer program stored in the memory 801 and executable on the processor 802 .

[0121] When the processor 802 executes the program, the method for calculating the shim adjustment amount during the coaxiality adjustment of the helicopter tail drive shaft provided in the above embodiment is implemented.

[0122] Furthermore, the electronic device further comprises:

[0123] The communication interface 803 is used for communication between the memory 801 and the processor 802 .

[0124] The memory 801 is used to store computer programs that can be executed on the processor 802 .

[0125] The memory 801 may include a high-speed RAM memory, and may also include a non-volatile memory (non-volatile memory), such as at least one disk memory.

[0126] If the memory 801, the processor 802 and the communication interface 803 are implemented independently, the communication interface 803, the memory 801 and the processor 802 can be connected to each other through a bus and communicate with each other. The bus can be an Industry Standard Architecture (ISA) bus, a Peripheral Component Interconnect (PCI) bus or an Extended Industry Standard Architecture (EISA) bus. The bus can be divided into an address bus, a data bus, a control bus, etc. For ease of representation, Figure 8 Only one thick line is used in the diagram, but this does not mean that there is only one bus or only one type of bus.

[0127] Optionally, in a specific implementation, if the memory 801, the processor 802 and the communication interface 803 are integrated on a chip, the memory 801, the processor 802 and the communication interface 803 can communicate with each other through an internal interface.

[0128] The processor 802 may be a central processing unit (CPU), or an application specific integrated circuit (ASIC), or one or more integrated circuits configured to implement the embodiments of the present application.

[0129] This embodiment also provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the above-mentioned method for calculating the shim adjustment amount during the coaxiality adjustment of the helicopter tail drive shaft.

[0130] This embodiment also provides a computer program product, including a computer program. When the computer program is executed, it is used to implement the above-mentioned method for calculating the gasket adjustment amount during the coaxiality adjustment process of the helicopter tail transmission shaft.

[0131] In the description of this specification, the description with reference to the terms "one embodiment", "some embodiments", "example", "specific example", or "some examples" etc. means that the specific features, structures, materials or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present application. In this specification, the schematic representations of the above terms do not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described may be combined in any one or N embodiments or examples in a suitable manner. In addition, those skilled in the art may combine and combine the different embodiments or examples described in this specification and the features of the different embodiments or examples, without contradiction.

[0132] In addition, the terms "first" and "second" are used for descriptive purposes only and should not be understood as indicating or implying relative importance or implicitly indicating the number of technical features indicated. Therefore, a feature defined as "first" or "second" may explicitly or implicitly include at least one of the features. In the description of this application, "N" means at least two, such as two, three, etc., unless otherwise clearly and specifically defined.

[0133] Any process or method description in a flowchart or otherwise described herein may be understood to represent a module, fragment or portion of code comprising one or N executable instructions for implementing the steps of a custom logical function or process, and the scope of the preferred embodiments of the present application includes alternative implementations in which functions may not be performed in the order shown or discussed, including performing functions in a substantially simultaneous manner or in reverse order depending on the functions involved, which should be understood by technicians in the technical field to which the embodiments of the present application belong.

[0134] The logic and / or steps represented in the flowchart or otherwise described herein, for example, can be considered as an ordered list of executable instructions for implementing logical functions, and can be embodied in any computer-readable medium for use by an instruction execution system, device or apparatus (such as a computer-based system, a system including a processor, or other system that can fetch instructions from an instruction execution system, device or apparatus and execute instructions), or in combination with these instruction execution systems, devices or apparatuses. For the purposes of this specification, a "computer-readable medium" can be any device that can contain, store, communicate, propagate or transmit a program for use by an instruction execution system, device or apparatus, or in combination with these instruction execution systems, devices or apparatuses. More specific examples of computer-readable media (a non-exhaustive list) include the following: an electrical connection with one or N wirings (electronic devices), a portable computer disk box (magnetic device), a random access memory (RAM), a read-only memory (ROM), an erasable and programmable read-only memory (EPROM or flash memory), a fiber optic device, and a portable compact disk read-only memory (CDROM). In addition, the computer-readable medium may even be paper or other suitable medium on which the program is printed, since the program may be obtained electronically by optically scanning the paper or other medium and then editing, interpreting or processing in other suitable ways as necessary and then storing it in a computer memory.

[0135] It should be understood that the various parts of the present application can be implemented by hardware, software, firmware or a combination thereof. In the above embodiment, the N steps or methods can be implemented by software or firmware stored in a memory and executed by a suitable instruction execution system. For example, if implemented by hardware, as in another embodiment, it can be implemented by any one or a combination of the following technologies known in the art: a discrete logic circuit having a logic gate circuit for implementing a logic function for a data signal, a dedicated integrated circuit having a suitable combination of logic gate circuits, a programmable gate array (PGA), a field programmable gate array (FPGA), etc.

[0136] A person skilled in the art may understand that all or part of the steps in the method for implementing the above-mentioned embodiment may be completed by instructing related hardware through a program, and the program may be stored in a computer-readable storage medium, which, when executed, includes one or a combination of the steps of the method embodiment.

[0137] In addition, each functional unit in each embodiment of the present application may be integrated into a processing module, or each unit may exist physically separately, or two or more units may be integrated into one module. The above-mentioned integrated module may be implemented in the form of hardware or in the form of a software functional module. If the integrated module is implemented in the form of a software functional module and sold or used as an independent product, it may also be stored in a computer-readable storage medium.

[0138] The storage medium mentioned above may be a read-only memory, a magnetic disk or an optical disk, etc. Although the embodiments of the present application have been shown and described above, it can be understood that the above embodiments are exemplary and cannot be understood as limiting the present application. A person of ordinary skill in the art may change, modify, replace and modify the above embodiments within the scope of the present application.

Claims

1. A method for calculating the gasket adjustment amount during the coaxiality adjustment of a helicopter tail transmission shaft, characterized in that: The following steps are involved: Constructing target key points and a target virtual camera of a helicopter tail drive shaft, and determining a first coaxiality error characterization vector of the helicopter tail drive shaft using the target virtual camera and the target key points; Acquire target measurement data of the helicopter tail drive shaft, and equivalently map the target measurement data to the first coaxiality error characterization vector to obtain a second coaxiality error characterization vector that satisfies a preset format; The second coaxiality error characterization vector is input into a pre-calibrated mathematical solution model to output the adjustment amount of each gasket of the helicopter tail transmission shaft.

2. The method according to claim 1, characterized in that The method of constructing a target key point and a target virtual camera of a helicopter tail drive shaft, and determining a first coaxiality error characterization vector of the helicopter tail drive shaft by using the target virtual camera and the target key point, comprises: Respectively extract the first key point, the second key point, the third key point and the fourth key point on the axis of the main reducer output shaft, the middle reducer input shaft, the middle reducer output shaft and the tail reducer input shaft, and respectively construct a first virtual camera and a second virtual camera on the axis of the middle reducer input shaft and the middle reducer output shaft; Determine a first coaxiality relationship between the main reducer output shaft and the intermediate reducer input shaft based on the first virtual camera, the first key point, and the second key point; Determine a second coaxiality relationship between the input shaft of the tail reducer and the output shaft of the middle reducer based on the second virtual camera, the third key point and the fourth key point; The first coaxiality error characterization vector of the helicopter tail drive shaft is determined according to the first coaxiality relationship and the second coaxiality relationship.

3. The method according to claim 1, characterized in that The step of obtaining target measurement data of the helicopter tail drive shaft comprises: Based on the laser tracker, obtaining first measurement data of the tail drive shaft of the helicopter; Based on the laser centering instrument, obtaining second measurement data of the tail drive shaft of the helicopter; Based on the collimating telescope, obtaining third measurement data of the tail drive shaft of the helicopter; The target measurement data is composed based on the first measurement data, the second measurement data, and the third measurement data.

4. The method according to claim 1, characterized in that: Before inputting the second coaxiality error characterization vector into a pre-calibrated mathematical solution model, the method further includes: Collecting multiple sets of pre-calibrated data using the target measurement method; Performing equivalent processing on the plurality of groups of pre-calibrated data to obtain equivalently processed data; The pre-constructed initial mathematical solution model is calibrated with parameters using the equivalently processed data to determine the pre-calibrated mathematical solution model.

5. The method according to claim 1, characterized in that The adjustment amount of each gasket of the output helicopter tail transmission shaft includes: Construct the target approximate linear Jacobian matrix relationship; Based on the target approximate linear Jacobian matrix relationship and at least one set of data in the target measurement data, calibrate each coefficient of the Jacobian matrix to obtain a calibrated Jacobian matrix; The calibrated Jacobian matrix is ​​used to calculate the adjustment amount of each gasket of the helicopter tail transmission shaft.

6. A device for calculating the amount of gasket adjustment during the coaxiality adjustment of a helicopter tail transmission shaft, characterized in that: include: A construction module is used to construct a target key point and a target virtual camera of a helicopter tail drive shaft, and determine a first coaxiality error characterization vector of the helicopter tail drive shaft by using the target virtual camera and the target key point; An acquisition module, used for acquiring target measurement data of the helicopter tail transmission shaft, and equivalently mapping the target measurement data to the first coaxiality error characterization vector to obtain a second coaxiality error characterization vector that meets a preset format; The calculation module is used to input the second coaxiality error characterization vector into a pre-calibrated mathematical solution model to output the adjustment amount of each gasket of the helicopter tail transmission shaft.

7. The device according to claim 6, characterized in that The building blocks include: A construction unit, used to extract the first key point, the second key point, the third key point and the fourth key point on the axis of the main reducer output shaft, the middle reducer input shaft, the middle reducer output shaft and the tail reducer input shaft, respectively, and construct a first virtual camera and a second virtual camera on the axis of the middle reducer input shaft and the middle reducer output shaft, respectively; A first determining unit, configured to determine a first coaxiality relationship between the main reducer output shaft and the intermediate reducer input shaft based on the first virtual camera, the first key point, and the second key point; A second determining unit is used to determine a second coaxiality relationship between the input shaft of the tail reducer and the output shaft of the middle reducer based on the second virtual camera, the third key point and the fourth key point; The third determining unit is used to determine the first coaxiality error characterization vector of the helicopter tail drive shaft according to the first coaxiality relationship and the second coaxiality relationship.

8. An electronic device, characterized in that: include: A memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the program to implement the method for calculating the amount of shim adjustment during the coaxiality adjustment of a helicopter tail drive shaft as described in any one of claims 1 to 5.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that: The program is executed by a processor to implement the method for calculating the shim adjustment amount during the coaxiality adjustment of the helicopter tail transmission shaft as described in any one of claims 1 to 5.

10. A computer program product, comprising a computer program, characterized in that The computer program is executed by a processor to implement the method for calculating the shim adjustment amount during the coaxiality adjustment of the helicopter tail transmission shaft as described in any one of claims 1 to 5.

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