Rigid body rotation inertia product measurement system and method based on point cloud registration

Abstract

The invention provides a rigid body rotation inertia product measurement system and method based on point cloud registration, and relates to the field of inertia product measurement, and the system comprises a torsional pendulum measurement table, a structured light 3D model scanning device and a computer; the torsional pendulum measuring table is used for loading a measured object and performing torsional vibration motion on the measured object; the torsional pendulum measuring table is arranged in the scanning range of the structured light 3D model scanning device; the structured light 3D model scanning device is used for acquiring point cloud data and a CAD model of an object to be measured; the structured light 3D model scanning device is in communication connection with the computer, and transmits the obtained point cloud data of the to-be-measured object and the CAD model to the computer; and the computer is used for calculating the rotation inertia product of the to-be-measured object according to the point cloud data of the to-be-measured object and the CAD model. The rotational inertia and the rotational inertia product of the measured object can be accurately calculated.

Description

Technical Field

[0001] The present invention relates to the field of product of inertia measurement, and in particular to a system and method for measuring the product of inertia of a rigid body rotation based on point cloud registration. Background Art

[0002] The product of inertia is a physical quantity that describes the rotational inertia of a rigid body. It is used to analyze the rotational motion of a rigid body in three-dimensional space and is an important engineering parameter for studying, designing and controlling the motion laws of rotating objects. The product of inertia of an object is related to the shape of the object, the position of the axis of rotation and the mass distribution, and directly affects the initial disturbance, motion stability and motion trajectory characteristics of the object.

[0003] All equipment involving rotational behavior needs to be tested for rotational inertia, especially for intercontinental missiles, hypersonic vehicles, spacecraft, kinetic interceptors and other aerospace vehicles that require precise attitude and orbit control. The precise measurement of the rotational product of inertia is of great significance. The precise measurement of the rotational product of inertia provides design input for the motion analysis and attitude control system of such aerospace vehicles, and can also be used to verify the rationality of the load structure layout of the aerospace vehicle.

[0004] However, the traditional torsion pendulum method usually ignores the influence of damping when measuring the moment of inertia, causing the amplitude of the torsional vibration motion of the measured object to decay and changing the period of the motion, resulting in large measurement errors and being unable to fully display the physical process and characteristics of the entire torsional vibration motion. When performing multi-posture moment of inertia measurements, the traditional method requires repeated installation and positioning of the object, which increases the complexity and time consumption of the measurement, making it difficult to meet industrial needs and resulting in low accuracy of the measurement results. Summary of the invention

[0005] In order to solve the problem that the traditional torsion pendulum method usually ignores the influence of damping when measuring the moment of inertia, causing the amplitude of the torsional vibration motion of the measured object to decay, changing the period of the motion, resulting in large measurement errors, and failing to fully display the physical process and characteristics of the entire torsional vibration motion, the traditional method needs to repeatedly install and position the object when performing multi-posture moment of inertia measurement, which increases the complexity and time consumption of the measurement, makes it difficult to meet industrial needs, and leads to low accuracy of the measurement results. The present invention provides a rigid body rotational product of inertia measurement system and method based on point cloud registration.

[0006] The technical solution provided by the embodiment of the present invention is as follows:

[0007] First aspect:

[0008] An embodiment of the present invention provides a rigid body rotational product of inertia measurement system based on point cloud registration, the system comprising: a torsion pendulum measurement platform, a structured light 3D model scanning device and a computer;

[0009] The torsion pendulum measuring table is used to load the object to be measured and perform torsional vibration motion on the object to be measured;

[0010] The torsion pendulum measuring table is arranged within the scanning range of the structured light 3D model scanning device;

[0011] The structured light 3D model scanning device is used to obtain the point cloud data and CAD model of the object to be measured;

[0012] The structured light 3D model scanning device is connected to the computer for communication, and the acquired point cloud data and CAD model of the object to be measured are transmitted to the computer;

[0013] The computer is used to calculate the rotational inertia product of the object to be measured based on the point cloud data and the CAD model of the object to be measured.

[0014] Second aspect:

[0015] An embodiment of the present invention provides a method for measuring a rigid body rotational product of inertia based on point cloud registration, comprising:

[0016] S1: Obtain point cloud data of the object being measured;

[0017] S2: preprocessing point cloud data;

[0018] S3: Scan the object to be measured and generate a CAD model of the object to be measured;

[0019] S4: performing point cloud registration on the preprocessed point cloud data and the CAD model, obtaining the transformation matrix of the coordinate system of the object to be measured relative to the camera coordinate system, and calculating the information matrix of each coordinate axis of the coordinate system of the object to be measured in the camera coordinate system;

[0020] S5: Calculate geometric parameters of the stage based on the information matrix, wherein the geometric parameters include angles between each coordinate axis of the object to be measured and the central axis of the stage and a distance between the center of mass of the object to be measured and the central axis of the stage;

[0021] S6: Measure the moment of inertia of the object to be measured according to the geometric parameters;

[0022] S7: Change the load posture, repeat steps S1 to S6, measure the rotational inertia of the object to be measured under multiple load postures, and calculate the rotational inertia product of the object to be measured.

[0023] The beneficial effects brought about by the technical solution provided by the embodiment of the present invention include at least:

[0024] In the present invention, the motion characteristics are accurately analyzed through point cloud registration, and the measurement errors caused by amplitude attenuation and period change due to ignoring the damping effect are avoided, thereby fully demonstrating the physical process and characteristics of torsional vibration motion, greatly improving the measurement accuracy, and realizing precise control of torsional vibration excitation through the torsion pendulum measuring table, ensuring the controllability and stability of torsional vibration motion, and providing a reliable basis for rotational inertia measurement. In the preprocessing of point cloud data, denoising, hole filling and model fitting are used to effectively improve the quality of point cloud data, reduce measurement errors, and ensure the stability of the final calculation results. Through the structured light 3D model scanning device and point cloud registration technology, the three-dimensional point cloud data and CAD model of the object to be measured can be accurately obtained, combined with high-precision coordinate system conversion and registration calculation, to ensure the accuracy of the rotational inertia measurement results, automatically adjust the load posture and perform multi-angle data acquisition and calculation, simplify the measurement process of multi-posture rotational inertia, reduce the operation complexity and time cost, and improve the measurement efficiency of rigid body rotational inertia. BRIEF DESCRIPTION OF THE DRAWINGS

[0025] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0026] Figure 1 A schematic structural diagram of a rigid body rotational product of inertia measurement system based on point cloud registration provided by an embodiment of the present invention;

[0027] Figure 2 A schematic flow chart of a method for measuring a rigid body rotational product of inertia based on point cloud registration provided in an embodiment of the present invention. DETAILED DESCRIPTION

[0028] The technical solution of the present invention is described below in conjunction with the accompanying drawings.

[0029] In the embodiments of the present invention, words such as "exemplarily" and "for example" are used to indicate examples, illustrations or explanations. Any embodiment or design described as "example" in the present invention should not be interpreted as being more preferred or more advantageous than other embodiments or designs. Specifically, the use of the word "example" is intended to present the concept in a specific way. In addition, in the embodiments of the present invention, the meaning expressed by "and / or" can be both, or it can be either of the two.

[0030] In the embodiments of the present invention, "image" and "picture" can sometimes be used interchangeably. It should be noted that when the difference between them is not emphasized, the meanings they intend to express are the same. "of", "corresponding, relevant" and "corresponding" can sometimes be used interchangeably. It should be noted that when the difference between them is not emphasized, the meanings they intend to express are the same.

[0031] In the embodiments of the present invention, sometimes a subscript such as W1 may be written as a non-subscript such as W1. When the difference is not emphasized, the meanings to be expressed are consistent.

[0032] In order to make the technical problems, technical solutions and advantages to be solved by the present invention more clear, a detailed description will be given below with reference to the accompanying drawings and specific embodiments.

[0033] Reference Manual Attached Figure 1 , showing a structural schematic diagram of a rigid body rotational product of inertia measurement system based on point cloud registration provided by an embodiment of the present invention.

[0034] The embodiment of the present invention provides a rigid body rotational product of inertia measurement system based on point cloud registration, the system comprising: a torsion pendulum measurement platform, a structured light 3D model scanning device and a computer;

[0035] The torsion pendulum measuring table is used to load the object to be measured and perform torsional vibration motion on the object to be measured;

[0036] The torsion pendulum measuring table is arranged within the scanning range of the structured light 3D model scanning device;

[0037] The structured light 3D model scanning device is used to obtain the point cloud data and CAD model of the object to be measured;

[0038] The structured light 3D model scanning device is connected to the computer for communication, and the acquired point cloud data and CAD model of the object to be measured are transmitted to the computer;

[0039] The computer is used to calculate the rotational inertia product of the object to be measured based on the point cloud data and the CAD model of the object to be measured.

[0040] Optionally, the oscillatory measurement platform includes a torsional vibration excitation device, a stage, an elastic element, a oscillatory measurement platform base and a oscillatory measurement platform housing; the oscillatory measurement platform base and the oscillatory measurement platform housing are connected, and a accommodating space is formed inside; one end of the elastic element is arranged inside the accommodating space, and the other end extends outside the accommodating space; the elastic element is connected to the stage; the object to be measured is loaded on the stage; the torsional vibration excitation device is connected to the stage; under the excitation of the torsional vibration excitation device, the stage drives the object to be measured to perform reciprocating torsional vibration motion around the central axis of the elastic element.

[0041] Optionally, the elastic element is connected to the stage via a bearing.

[0042] In the present invention, the elastic element is connected to the stage through a bearing, which can reduce mechanical friction and damping, improve measurement accuracy and equipment life, and ensure the stability and regularity of movement. It is an important measure to optimize the design of the torsion pendulum measurement platform.

[0043] Optionally, the elastic element is specifically: a torsion bar or a spiral spring.

[0044] Optionally, the torsional vibration excitation device includes an STM32 control board, a high-torque steering gear and a cam mechanism. The STM32 control board is connected to the high-torque steering gear; the high-torque steering gear is connected to the cam mechanism; and the cam structure is connected to the loading platform.

[0045] In the present invention, through the collaborative work of the STM32 control board, the high-torque steering gear and the cam mechanism, accurate control, efficient transmission and reliable output of the torsional vibration excitation process are achieved, providing a stable, adjustable and low-interference excitation source for the measuring platform, while having good adaptability and expansibility. This structure improves the measurement accuracy and system stability while also reducing the use and maintenance costs, and is an efficient and reliable design solution.

[0046] Optionally, the structured light 3D model scanning device includes a camera bracket, a binocular vision camera and a light projector. The binocular vision camera is arranged on the camera bracket; the light projector projects the structured light pattern onto the surface of the object to be measured, and the surface geometry of the object to be measured causes the light pattern to be deformed; the binocular vision camera captures the deformed light pattern from different angles, extracts the phase information of the object surface through the captured pattern, and obtains the point cloud data and CAD model of the object to be measured.

[0047] In the present invention, the structured light 3D model scanning device can efficiently and accurately obtain the three-dimensional geometric information of the object to be measured in a non-contact manner. The generation of point cloud data and CAD models provides key support for inertial measurement and other engineering analysis, while improving the automation, flexibility and applicability of the measurement process. This solution has significant advantages in accuracy, efficiency and economy.

[0048] Optionally, the structured light pattern is specifically: sinusoidal stripes or a grid.

[0049] It should be noted that the excitation device of the torsion pendulum measuring table can ensure that the object under test performs stable torsional vibration motion. The industrial imaging device can collect high-resolution continuous motion images, and the structured light 3D model scanning device can be used to obtain the point cloud data and CAD model of the object under test, and accurately restore the geometric characteristics and vibration behavior of the object. The system uses point cloud registration technology to eliminate installation errors and improve measurement accuracy. At the same time, it can achieve flexible adaptation to objects with complex shapes and asymmetric structures, and effectively improve the accuracy and efficiency of multi-posture moment of inertia measurement.

[0050] Reference Manual Attached Figure 2 , shows a schematic flow chart of a method for measuring a rigid body rotational product of inertia based on point cloud registration provided in an embodiment of the present invention.

[0051] The embodiment of the present invention provides a method for measuring the rotational product of inertia of a rigid body based on point cloud registration, comprising:

[0052] S1: Obtain the point cloud data of the object being measured.

[0053] Among them, point cloud data is a collection of a large number of three-dimensional coordinate points, which is used to represent the spatial structure of the surface of an object and is usually collected through 3D scanning technology (such as laser scanning or structured light scanning).

[0054] In a possible implementation, S1 specifically includes:

[0055] S101: Acquire sinusoidal stripe structured light of known pattern:

[0056] I(x,y)=I0+I1 cos(P2πx+φ′)

[0057] Wherein, I(x, y) represents the sinusoidal stripe structured light of known pattern, I0 represents the average intensity of the sinusoidal stripe structured light, I1 represents the stripe amplitude of the sinusoidal stripe structured light, P represents the stripe period of the sinusoidal stripe structured light, and φ′ represents the initial phase of the sinusoidal stripe structured light.

[0058] S102: Projecting the sinusoidal stripe structured light onto the object to be measured using a light projector.

[0059] Among them, sinusoidal stripe structured light is a technology that projects light with periodic stripes onto the surface of an object through a projector. Sinusoidal stripes are usually used to capture the shape deformation of the object's surface.

[0060] It should be noted that by using a light projector to project sinusoidal fringe structured light onto the surface of the object to be measured, the three-dimensional shape of the object surface can be accurately obtained through fringe deformation analysis, providing high-resolution and high-precision surface data, avoiding surface damage or contact errors that may be caused by traditional measurement methods.

[0061] S103: Use a binocular vision camera to capture the projected sinusoidal stripe structured light to obtain a projection pattern:

[0062] I'(x,y)=R(x,y)[A(x,y)+B(x,y)cosφ(x,y)]

[0063] Where I′(x,y) represents the projection pattern, R(x,y) represents the reflectivity of the surface of the object to be measured at point (x,y), φ((x,y)) represents the phase value of the projection pattern at point (x,y), A(x,y) represents the background light intensity of the projection pattern, and B(x,y) represents the modulated light intensity.

[0064] S104: Calculate the phase difference of the projection pattern by using the N-step phase shift method:

[0065]

[0066] Δφ(x,y)=φ(x,y)-φ0(x,y)

[0067] Where Δφ(x,y) represents the phase difference of the projection pattern, φ(x,y) represents the phase value of the projection pattern at point (x,y), and N represents the total number of frames of the projection pattern phase shift. represents the light intensity value of the k-th frame projection pattern at point (x, y), and φ0(x, y) represents the reference phase.

[0068] S105: Determine the surface height of the object to be measured based on the phase difference:

[0069]

[0070] Wherein, h represents the surface height of the object to be measured, L0 represents the distance between the light projector and the binocular vision camera, T represents the fringe period of the projection pattern, and d represents the optical axis distance between the light projector and the binocular vision camera.

[0071] S106: Extract features from the projected avatar using a feature point detection algorithm to obtain feature points.

[0072] Among them, the feature point detection algorithm is a computer vision technology used to identify and extract key points or features with uniqueness and stability from images. These feature points are usually corners, edges or protruding parts of texture in the image, which can help identify objects or accurately match and analyze images.

[0073] It should be noted that extracting feature points in the projected avatar through the feature point detection algorithm can effectively capture important information in the image, provide stable recognition results under complex backgrounds or changing surface conditions, and improve the accuracy of subsequent three-dimensional reconstruction.

[0074] S107: According to the surface height and feature points of the object to be measured, multiple three-dimensional coordinates of the surface of the object to be measured are determined through coordinate transformation and triangulation:

[0075]

[0076] Among them, (x, y, z) represents the three-dimensional coordinates of the surface of the object to be measured, represents the pixel coordinates of the feature point in the projection pattern, K represents the intrinsic parameter matrix of the binocular vision camera, R and Q represent the extrinsic parameter matrix of the binocular vision camera, Represents the normalized coordinates of the feature point in the binocular vision camera coordinate system, A c Indicates the baseline length between the binocular vision cameras.

[0077] S108: Reconstruct the three-dimensional coordinates to form point cloud data.

[0078] It should be noted that obtaining point cloud data can accurately capture the three-dimensional shape of an object and is suitable for complex and irregular geometric objects. It can obtain high-precision object surface information, provide a reliable basis for subsequent point cloud registration and model reconstruction, avoid errors that may be introduced by traditional methods, and can greatly reduce the difficulty of measuring objects with complex geometric shapes.

[0079] S2: Preprocess the point cloud data.

[0080] In a possible implementation manner, S2 is specifically:

[0081] The point cloud data is preprocessed including denoising, hole filling and model fitting.

[0082] Among them, denoising refers to removing noise points in point cloud data. These noises are usually caused by sensor errors or environmental interference, which may affect the accuracy of subsequent processing. Hole filling refers to filling the missing data areas in the point cloud due to scanning angles, occlusions or other reasons. Model fitting refers to using mathematical methods (such as least squares method, surface fitting, etc.) to match point cloud data with specific geometric models (such as planes, surfaces or other shapes) to obtain a more accurate object shape.

[0083] It should be noted that preprocessing of point cloud data such as denoising, hole filling and model fitting can significantly improve the quality of point cloud data, reduce errors caused by noise and missing points, help obtain a smoother and continuous three-dimensional model, and ensure the accuracy of subsequent calculations and analysis.

[0084] S3: Scan the object to be measured and generate a CAD model of the object to be measured.

[0085] In a possible implementation, S3 is specifically:

[0086] The object to be measured is scanned using a Gouguang 3D model scanning device to generate a CAD model of the object to be measured.

[0087] Among them, the CAD (Computer-Aided (Design) model is a three-dimensional model generated based on computer-aided design, which is used to accurately describe the geometric shape and structure of an object.

[0088] It should be noted that using a structured light 3D model scanning device to generate a CAD model can quickly and accurately restore the geometric shape of the object to be measured, facilitate subsequent analysis and calculation, and reduce errors caused by human intervention.

[0089] S4: performing point cloud registration on the preprocessed point cloud data and the CAD model, obtaining the transformation matrix of the coordinate system of the object to be measured relative to the camera coordinate system, and calculating the information matrix of each coordinate axis of the coordinate system of the object to be measured in the camera coordinate system.

[0090] Among them, point cloud registration is to align two sets of point cloud data (such as scanned point cloud and CAD model point cloud) and make the two coincide in space by calculating the optimal transformation relationship between them. The transformation matrix describes the geometric relationship between the two coordinate systems, including rotation and translation, and is used to map points of one coordinate system to another coordinate system. The information matrix is ​​a mathematical representation of the distribution characteristics of each axis of the coordinate system (such as position, direction, weight), which is used to quantify the spatial distribution information of the object. The camera coordinate system refers to the three-dimensional coordinate system defined in the camera system, usually with the camera optical axis as the Z axis, and the X and Y axes parallel to the camera imaging plane, which is used to describe the relative position of objects in the image.

[0091] In a possible implementation, S4 specifically includes:

[0092] S401: Calculate the covariance matrix of the preprocessed point cloud data:

[0093]

[0094] Among them, r i represents the i-th data point in the point cloud data, i=1, 2, ..., m, m represents the total number of data points in the point cloud data, J represents the covariance matrix of the point cloud data, and T represents the transpose.

[0095] S402: Perform PCA decomposition on the covariance matrix to obtain eigenvalues ​​and eigenvectors;

[0096]

[0097] Among them, N represents the covariance matrix after PCA decomposition, N1, N2 and N3 all represent eigenvectors, and N ijRepresents the element in the i-th row and j-th column of the covariance matrix after PCA decomposition, i=j=1,…,3.

[0098] S403: Construct the coordinate system of the object to be measured according to the eigenvalues ​​and eigenvectors:

[0099]

[0100] Where R represents the coordinate system of the object to be measured.

[0101] S404: Perform point cloud registration on the preprocessed point cloud data and the CAD model based on the coordinate system of the object to be measured, and obtain a transformation matrix of the coordinate system of the object to be measured relative to the camera coordinate system:

[0102]

[0103] Among them, t represents the translation matrix of the coordinate system of the object to be measured relative to the camera coordinate system, T represents the transformation matrix of the coordinate system of the object to be measured relative to the camera coordinate system, and p x 、p y and p z They respectively represent the translation of the center of mass of the coordinate system of the object to be measured in the camera coordinate system.

[0104] S405: According to the transformation matrix, the camera coordinate system is obtained and the information matrix of each coordinate axis of the object to be measured in the camera coordinate system is calculated:

[0105]

[0106] Among them, A C represents the information matrix, and A0 represents the unit vectors of the three coordinate axes of the coordinate system of the object to be measured.

[0107] In the present invention, phase unwrapping uses the dual-frequency heterodyne method in the multi-frequency phase shift method to synthesize the global phase with the difference of the normalized wrapped phase:

[0108]

[0109] in, is the normalized phase. For any point on the object, λ1n1=λ2n2 is satisfied, that is, the camera coordinate values ​​in different frequency graphs are the same. Φ1 and Φ2 represent the absolute phase.

[0110] For the same point, the integer fringe numbers measured by gratings of different periods need to meet the following conditions:

[0111]

[0112] It can be deduced that:

[0113]

[0114] After obtaining the absolute phase, the height h of the object surface can be calculated through the relationship between phase and height:

[0115]

[0116] It should be noted that by performing point cloud registration on the preprocessed point cloud data and the CAD model, the position and posture of the object coordinate system in the camera coordinate system can be accurately obtained, ensuring the consistency of the measurement data and the model, improving the accuracy of geometric parameter calculations, and providing high-precision input data for subsequent inertial parameter calculations, greatly improving measurement efficiency and reliability, which is especially suitable for dynamic measurement of complex objects.

[0117] S5: Calculate geometric parameters of the stage based on the information matrix, wherein the geometric parameters include angles between each coordinate axis of the object to be measured and the central axis of the stage and the distance between the center of mass of the object to be measured and the central axis of the stage.

[0118] Among them, the information matrix is ​​used to represent and calculate the distribution of objects in different coordinate axes in space, and can provide detailed information such as the direction, position and mass distribution of each axis of the object. The geometric parameters are mathematical quantities that describe the spatial relationship between the object and the stage, usually including the angle and distance between the object and the center axis of the stage, which are used to define the relative position and motion trajectory of the object. The center of mass refers to the center of mass of the object, which is the balance point of the mass distribution of each part of the object.

[0119] In a possible implementation, S5 specifically includes:

[0120] S501: Unifying the various coordinate axes of the coordinate system of the object to be measured and the central axis of the stage in the camera coordinate system through a cylindrical fitting algorithm.

[0121] Among them, the cylinder fitting algorithm is a mathematical method that fits a set of data points to make it best fit the model of a cylindrical shape, and reduces the error between the data points and the model by optimizing model parameters (such as radius and center position). It is often used to process objects with symmetrical structures. The center axis of the stage refers to the center line or axis of the stage, which is usually the reference axis for the fixation and rotation of the object. All measurements and calculations are based on this axis.

[0122] In the present invention, through the cylindrical fitting algorithm, the coordinate axes of the coordinate system of the object to be measured and the central axis of the stage are unified in the camera coordinate system as follows:

[0123] In three-dimensional space, a cylinder is a collection of points whose distance from its central axis is a constant r:

[0124]

[0125] In the least squares algorithm fitting process, the fitting error of the definition point is the difference between the distance from the point to the center axis of the cylindrical stage and the radius of the wiggling stage:

[0126]

[0127] The fitting algorithm based on geometric analysis linearizes the error equation of the formula, discards the high-order terms, and then iterates according to the Gauss-Newton method to obtain the final estimated value of the oscillating stage axis in the camera coordinate system.

[0128] It should be noted that the cylindrical fitting algorithm is used to unify the various coordinate axes of the coordinate system of the object to be measured and the center axis of the stage into the camera coordinate system, which helps to accurately align the object and the measuring equipment, eliminate the errors caused by the object's posture or position deviation, and make subsequent measurements and analysis more accurate.

[0129] S502: In the camera coordinate system, obtain the information matrix, the centroid coordinates of the object to be measured and the stage information, the stage information including the reference point coordinates on the center axis of the stage and the vector of the center axis of the stage:

[0130]

[0131] p0(x0,y0,z0)

[0132] in, represents the vector of the center axis of the stage, p0(x0,y0,z0) represents the coordinates of the reference point on the center axis of the stage, and They respectively represent the coordinate axes of the coordinate system of the object to be measured in the camera coordinate system.

[0133] S503: Calculate the geometric parameters of the stage according to the information matrix, the centroid coordinates of the object to be measured and the stage information:

[0134]

[0135] Among them, α, β and γ represent the angles between the coordinate axes of the object to be measured and the central axis of the stage, d represents the distance between the center of mass of the object to be measured and the central axis of the stage, and t represents the scale factor of the projection of the center of mass of the object to be measured onto the central axis of the stage.

[0136] It should be noted that by calculating the geometric parameters based on the information matrix, the spatial relationship between the object to be measured and the stage can be accurately described, which provides the necessary geometric information for the calculation of the moment of inertia, can improve the accuracy of the measurement results, and ensure high-precision measurement of complex objects, especially in multi-posture or dynamic measurement processes.

[0137] S6: Measure the moment of inertia of the object to be measured based on the geometric parameters.

[0138] Among them, the moment of inertia is a measure of an object's inertial resistance to rotation when it rotates, which depends on the mass distribution of the object and the position of the rotation axis. The larger the object's moment of inertia, the more difficult it is to change its rotation state.

[0139] In a possible implementation manner, S6 specifically includes:

[0140] Use the torsion pendulum measuring table to measure the moment of inertia of the object to be measured:

[0141]

[0142] Wherein, J represents the moment of inertia of the object to be measured, k represents the stiffness coefficient of the stage, T represents the torsional vibration period of the object to be measured, J0 represents the no-load moment of inertia of the object to be measured, and π represents pi.

[0143] It should be noted that by measuring the moment of inertia of the object to be measured based on geometric parameters, the rotational characteristics of the object can be evaluated efficiently and accurately. By understanding the geometric relationship between the object coordinate system and the stage, errors caused by installation deviations or changes in measurement angles can be effectively avoided.

[0144] S7: Change the load posture, repeat steps S1 to S6, measure the rotational inertia of the object to be measured under multiple load postures, and calculate the rotational inertia product of the object to be measured.

[0145] Among them, load posture refers to the spatial position and direction of the object to be measured relative to the measuring equipment during the rotation process. The change of load posture means that the position of the object's rotation axis and center of mass relative to the measuring platform is constantly changing. The rotational inertia product refers to the sum of the products of the object's moment of inertia in all directions and the corresponding distance (the distance from the center of mass to the rotation axis). It is a comprehensive indicator of the object's moment of inertia and is usually used to describe the object's moment of inertia in multiple directions.

[0146] In a possible implementation manner, S7 specifically includes:

[0147] Measure the moment of inertia of the object to be tested under various load postures to obtain the rotational inertia product of the object to be tested:

[0148]

[0149] Among them, J1-md1 2 、J2-md2 2 、J3-md3 2 、J4-md4 2 、J5-md5 2 and J6-md6 2 Respectively represent the moment of inertia of the object to be tested under various load postures, J x, J y and J z represents the moment of inertia of the object to be measured around each coordinate axis of the coordinate system of the object to be measured, α1, α2, α3, α4, α5 and α6 represent the angles between the coordinate axis X of the object to be measured and the central axis of the stage under each load posture, β1, β2, β3, β4, β5 and β6 represent the angles between the coordinate axis Y of the object to be measured and the central axis of the stage under each load posture, γ1, γ2, γ3, γ4, γ5 and γ6 represent the angles between the coordinate axis Z of the object to be measured and the central axis of the stage under each load posture, J yz , J xz and J xy They represent the product of inertia of the object to be measured around the yz plane, xz plane and xy plane respectively.

[0150] It should be noted that by performing repeated measurements under multiple load postures, the moment of inertia of the object to be measured in different directions can be fully understood, and a more accurate product of inertia can be obtained. This can eliminate errors that may be caused by a single posture and improve the reliability and comprehensiveness of the measurement results. Repeated measurements can provide more data support and help obtain more stable and accurate moment of inertia values ​​through comprehensive analysis. For objects with complex geometric shapes, changing the load posture can more comprehensively capture the anisotropic characteristics of the object and further improve the accuracy and applicability of moment of inertia measurement.

[0151] The beneficial effects brought about by the technical solution provided by the embodiment of the present invention include at least:

[0152] In the present invention, the motion characteristics are accurately analyzed through point cloud registration, and the measurement errors caused by amplitude attenuation and period change due to ignoring the damping effect are avoided, thereby fully demonstrating the physical process and characteristics of torsional vibration motion, greatly improving the measurement accuracy, and realizing precise control of torsional vibration excitation through the torsion pendulum measuring table, ensuring the controllability and stability of torsional vibration motion, and providing a reliable basis for rotational inertia measurement. In the preprocessing of point cloud data, denoising, hole filling and model fitting are used to effectively improve the quality of point cloud data, reduce measurement errors, and ensure the stability of the final calculation results. Through the structured light 3D model scanning device and point cloud registration technology, the three-dimensional point cloud data and CAD model of the object to be measured can be accurately obtained, combined with high-precision coordinate system conversion and registration calculation, to ensure the accuracy of the rotational inertia measurement results, automatically adjust the load posture and perform multi-angle data acquisition and calculation, simplify the measurement process of multi-posture rotational inertia, reduce the operation complexity and time cost, and improve the measurement efficiency of rigid body rotational inertia.

[0153] It should be understood that the processor in the embodiment of the present invention may be a central processing unit (CPU), and the processor may also be other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), field-programmable gate arrays (FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. A general-purpose processor may be a microprocessor or the processor may also be any conventional processor, etc.

[0154] It should also be understood that the memory in the embodiments of the present invention may be a volatile memory or a non-volatile memory, or may include both volatile and non-volatile memories. Among them, the non-volatile memory may be a read-only memory (ROM), a programmable read-only memory (PROM), an erasable programmable read-only memory (EPROM), an electrically erasable programmable read-only memory (EPROM, EEPROM) or a flash memory. The volatile memory may be a random access memory (RAM), which is used as an external cache. By way of example but not limitation, many forms of random access memory (RAM) are described. M) is available, such as static random access memory (static (RAM, SRAM), dynamic random access memory (DRAM), synchronous dynamic random access memory (synchronous (DRAM, SDRAM), double data rate synchronous dynamic random access memory (double (data (rate (SDRAM, DDR (SDRAM), enhanced synchronous dynamic random access memory (enhanced (SDRAM, ESDRAM), synchronous link dynamic random access memory (synchlink (DRAM, SLDRAM) and direct memory bus random access memory (direct (rambus (RAM, DR (RAM).

[0155] The above embodiments can be implemented in whole or in part by software, hardware (such as circuits), firmware or any other combination. When implemented using software, the above embodiments can be implemented in whole or in part in the form of a computer program product. The computer program product includes one or more computer instructions or computer programs. When a computer instruction or computer program is loaded or executed on a computer, a process or function according to an embodiment of the present invention is generated in whole or in part. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. Computer instructions can be stored in a computer-readable storage medium, or transmitted from one computer-readable storage medium to another computer-readable storage medium. For example, computer instructions can be transmitted from one website, computer, server or data center to another website, computer, server or data center by wired (such as infrared, wireless, microwave, etc.). The computer-readable storage medium can be any available medium that can be accessed by a computer or a data storage device such as a server or data center that contains one or more available media sets. The available medium can be a magnetic medium (for example, a floppy disk, a hard disk, a tape), an optical medium (for example, a DVD), or a semiconductor medium. The semiconductor medium can be a solid-state hard disk.

[0156] It should be understood that the term "and / or" in this article is only a description of the association relationship of associated objects, indicating that there can be three relationships. For example, A and / or B can represent: A exists alone, A and B exist at the same time, and B exists alone. A and B can be singular or plural. In addition, the character " / " in this article generally indicates that the associated objects before and after are in an "or" relationship, but it may also indicate an "and / or" relationship. Please refer to the context for specific understanding.

[0157] In the present invention, "at least one" means one or more, and "plurality" means two or more. "At least one of the following" or similar expressions refers to any combination of these items, including any combination of single or plural items. For example, at least one of a, b, or c can be represented by: a, (b, (c, (ab, (ac, (bc, (or abc, where a, b, c can be single or plural.

[0158] It should be understood that in various embodiments of the present invention, the size of the serial numbers of the above-mentioned processes does not mean the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of the present invention.

[0159] Those skilled in the art will appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of the present invention.

[0160] Those skilled in the art can clearly understand that, for the convenience and brevity of description, the specific working processes of the above-described equipment, devices and units can refer to the corresponding processes in the aforementioned method embodiments and will not be repeated here.

[0161] In the several embodiments provided by the present invention, it should be understood that the disclosed devices, apparatuses and methods can be implemented in other ways. For example, the device embodiments described above are only schematic, for example, the division of units is only a logical function division, and there may be other division methods in actual implementation, such as multiple units or components can be combined or integrated into another device, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of devices or units, which can be electrical, mechanical or other forms.

[0162] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0163] In addition, each functional unit in each embodiment of the present invention may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit.

[0164] If the function is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, or the part that contributes to the prior art, or the part of the technical solution, can be embodied in the form of a software product. The computer software product is stored in a storage medium and includes a number of instructions for a computer device (which can be a personal computer, server, or network device, etc.) to perform all or part of the steps of the methods of each embodiment of the present invention. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM), random access memory (RAM), disk or optical disk, and other media that can store program codes.

[0165] An embodiment of the present invention provides a computer-readable storage medium having a computer program stored thereon. When the program is executed by a processor, a method for measuring a rigid body rotational product of inertia based on point cloud registration as described in a method embodiment is implemented.

[0166] A computer-readable storage medium provided by the present invention can implement the steps and effects of the rigid body rotational inertia product measurement method based on point cloud registration in the above method embodiment. To avoid repetition, the present invention will not go into details.

[0167] The beneficial effects brought about by the technical solution provided by the embodiment of the present invention include at least:

[0168] In the present invention, the motion characteristics are accurately analyzed through point cloud registration, and the measurement errors caused by amplitude attenuation and period change due to ignoring the damping effect are avoided, thereby fully demonstrating the physical process and characteristics of torsional vibration motion, greatly improving the measurement accuracy, and realizing precise control of torsional vibration excitation through the torsion pendulum measuring table, ensuring the controllability and stability of torsional vibration motion, and providing a reliable basis for rotational inertia measurement. In the preprocessing of point cloud data, denoising, hole filling and model fitting are used to effectively improve the quality of point cloud data, reduce measurement errors, and ensure the stability of the final calculation results. Through the structured light 3D model scanning device and point cloud registration technology, the three-dimensional point cloud data and CAD model of the object to be measured can be accurately obtained, combined with high-precision coordinate system conversion and registration calculation, to ensure the accuracy of the rotational inertia measurement results, automatically adjust the load posture and perform multi-angle data acquisition and calculation, simplify the measurement process of multi-posture rotational inertia, reduce the operation complexity and time cost, and improve the measurement efficiency of rigid body rotational inertia.

[0169] The above are only specific embodiments of the present invention, but the protection scope of the present invention is not limited thereto. Any person skilled in the art who is familiar with the technical field can easily think of changes or substitutions within the technical scope disclosed by the present invention, which should be included in the protection scope of the present invention. Therefore, the protection scope of the present invention should be based on the protection scope of the claims.

[0170] There are a few points to note:

[0171] (1) The drawings of the embodiments of the present invention only relate to the structures related to the embodiments of the present invention, and other structures may refer to the general design.

[0172] (2) For the sake of clarity, in the drawings used to describe the embodiments of the present invention, the thickness of the layers or regions is exaggerated or reduced, that is, these drawings are not drawn according to the actual scale. It is understood that when an element such as a layer, film, region or substrate is referred to as being "on" or "under" another element, the element may be "directly" "on" or "under" the other element or there may be intermediate elements.

[0173] (3) In the absence of conflict, the embodiments of the present invention and the features therein may be combined with each other to obtain new embodiments.

[0174] The above are only specific embodiments of the present invention, but the protection scope of the present invention is not limited thereto. The protection scope of the present invention shall be based on the protection scope of the claims.

Claims

1. A rigid body rotational product of inertia measurement system based on point cloud registration, characterized in that: The system includes: a torsion pendulum measuring table, a structured light 3D model scanning device and a computer; The torsion pendulum measuring platform is used to load the object to be measured and perform torsional vibration motion on the object to be measured; The torsion pendulum measuring platform is arranged within the scanning range of the structured light 3D model scanning device; The structured light 3D model scanning device is used to obtain point cloud data and a CAD model of the object to be measured; The structured light 3D model scanning device is communicatively connected to the computer, and transmits the acquired point cloud data and CAD model of the object to be measured to the computer; The computer is used to calculate the rotational inertia product of the object to be measured according to the point cloud data and the CAD model of the object to be measured.

2. A method for measuring the rigid body rotational product of inertia based on point cloud registration, applied to the rigid body rotational product of inertia measurement system based on point cloud registration according to claim 1, characterized in that: Methods include: S1: Acquire point cloud data of the object to be measured; S2: preprocessing the point cloud data; S3: Scanning the object to be measured to generate a CAD model of the object to be measured; S4: performing point cloud registration on the preprocessed point cloud data and the CAD model, obtaining a transformation matrix of the coordinate system of the object to be measured relative to the camera coordinate system, and calculating an information matrix of each coordinate axis of the coordinate system of the object to be measured in the camera coordinate system; S5: Calculating geometric parameters of the stage based on the information matrix, wherein the geometric parameters include angles between each coordinate axis of the object to be measured and the central axis of the stage and a distance between the center of mass of the object to be measured and the central axis of the stage; S6: measuring the moment of inertia of the object to be measured according to the geometric parameters; S7: changing the load posture, repeating steps S1 to S6, measuring the rotational inertia of the object to be measured under multiple load postures, and calculating the rotational inertia product of the object to be measured.

3. The method for measuring the rigid body rotational product of inertia based on point cloud registration according to claim 2, characterized in that: The S1 specifically includes: S101: Acquire sinusoidal stripe structured light of known pattern: I(x,y)=I0+I1cos(P2πx+φ′) Where I(x, y) represents the sinusoidal fringe structured light of known pattern, I0 represents the average intensity of the sinusoidal fringe structured light, I1 represents the fringe amplitude of the sinusoidal fringe structured light, P represents the fringe period of the sinusoidal fringe structured light, and φ′ represents the initial phase of the sinusoidal fringe structured light; S102: Projecting the sinusoidal fringe structured light onto the object to be measured using the light projector; S103: Using the binocular vision camera to capture the projected sinusoidal stripe structured light to obtain a projection pattern: I'(x,y)=R(x,y)[A(x,y)+B(x,y)cosφ(x,y)] Where I′(x,y) represents the projection pattern, R(x,y) represents the reflectivity of the surface of the object to be measured at point (x,y), φ((x,y)) represents the phase value of the projection pattern at point (x,y), A(x,y) represents the background light intensity of the projection pattern, and B(x,y) represents the modulated light intensity; S104: Calculate the phase difference of the projection pattern by an N-step phase shift method: Where Δφ(x,y) represents the phase difference of the projection pattern, φ(x,y) represents the phase value of the projection pattern at point (x,y), and N represents the total number of frames of the projection pattern phase shift. represents the light intensity value of the k-th frame projection pattern at point (x, y), φ0(x, y) represents the reference phase; S105: Determine the surface height of the object to be measured according to the phase difference: Wherein, h represents the surface height of the object to be measured, L0 represents the distance between the light projector and the binocular vision camera, T represents the fringe period of the projection pattern, and d represents the optical axis distance between the light projector and the binocular vision camera; S106: extracting features from the projected avatar using the feature point detection algorithm to obtain feature points; S107: Determine multiple three-dimensional coordinates of the surface of the object to be measured through coordinate conversion and triangulation according to the surface height of the object to be measured and the feature points: Among them, (x, y, z) represents the three-dimensional coordinates of the surface of the object to be measured, represents the pixel coordinates of the feature point in the projection pattern, K represents the intrinsic parameter matrix of the binocular vision camera, R and Q represent the extrinsic parameter matrix of the binocular vision camera, Represents the normalized coordinates of the feature point in the binocular vision camera coordinate system, A c Represents the baseline length between binocular vision cameras; S108: Reconstruct the three-dimensional coordinates to form point cloud data.

4. The method for measuring the rigid body rotational product of inertia based on point cloud registration according to claim 2, characterized in that: The S2 is specifically: The point cloud data is preprocessed including denoising, hole filling and model fitting.

5. The method for measuring the rigid body rotational product of inertia based on point cloud registration according to claim 2, characterized in that: The S3 is specifically: The object to be measured is scanned by the light-forming 3D model scanning device to generate a CAD model of the object to be measured.

6. The method for measuring the rigid body rotational product of inertia based on point cloud registration according to claim 2, characterized in that: The S4 specifically includes: S401: Calculate the covariance matrix of the preprocessed point cloud data: Among them, r i represents the i-th data point in the point cloud data, i = 1, 2, ..., m, m represents the total number of data points in the point cloud data, J represents the covariance matrix of the point cloud data, and T represents the transpose; S402: Perform PCA decomposition on the covariance matrix to obtain eigenvalues ​​and eigenvectors; Among them, N represents the covariance matrix after PCA decomposition, N1, N2 and N3 all represent eigenvectors, and N ij represents the element in the i-th row and j-th column of the covariance matrix after PCA decomposition, i=j=1,…,3; S403: Constructing a coordinate system of the object to be measured according to the eigenvalue and the eigenvector: Where R represents the coordinate system of the object to be measured; S404: performing point cloud registration on the preprocessed point cloud data and the CAD model based on the coordinate system of the object to be measured, and obtaining a transformation matrix of the coordinate system of the object to be measured relative to the camera coordinate system: Where t represents the translation matrix of the coordinate system of the object to be measured relative to the camera coordinate system, T represents the transformation matrix of the coordinate system of the object to be measured relative to the camera coordinate system, and p x 、p y and p z They respectively represent the translation of the center of mass of the coordinate system of the object to be measured in the camera coordinate system; S405: According to the transformation matrix, a camera coordinate system is obtained and an information matrix of each coordinate axis of the object to be measured in the camera coordinate system is calculated: Among them, A C represents the information matrix, and A0 represents the unit vectors of the three coordinate axes of the coordinate system of the object to be measured.

7. The method for measuring the rigid body rotational product of inertia based on point cloud registration according to claim 2, characterized in that: The S5 specifically includes: S501: unifying the coordinate axes of the coordinate system of the object to be measured and the central axis of the stage in the camera coordinate system through a cylindrical fitting algorithm; S502: In the camera coordinate system, the information matrix, the centroid coordinates of the object to be measured and the stage information are obtained, wherein the stage information includes the reference point coordinates on the center axis of the stage and the vector of the center axis of the stage: p0(x0,y0,z0) in, represents the vector of the center axis of the stage, p0(x0,y0,z0) represents the coordinates of the reference point on the center axis of the stage, and Respectively represent the coordinate axes of the coordinate system of the object to be measured in the camera coordinate system; S503: Calculate the geometric parameters of the stage according to the information matrix, the centroid coordinates of the object to be measured and the stage information: Among them, α, β and γ represent the angles between the coordinate axes of the object to be measured and the central axis of the stage, d represents the distance between the center of mass of the object to be measured and the central axis of the stage, and t represents the scale factor of the projection of the center of mass of the object to be measured onto the central axis of the stage.

8. The method for measuring the rigid body rotational product of inertia based on point cloud registration according to claim 2, characterized in that: The S6 is specifically: The moment of inertia of the object to be measured is measured using the torsion pendulum measuring platform: Wherein, J represents the moment of inertia of the object to be measured, k represents the stiffness coefficient of the stage, T represents the torsional vibration period of the object to be measured, J0 represents the no-load moment of inertia of the object to be measured, and π represents pi.

9. The method for measuring the rigid body rotational product of inertia based on point cloud registration according to claim 2, characterized in that: The S7 is specifically: The moment of inertia of the object to be measured under various load postures is measured to obtain the rotational product of inertia of the object to be measured: Among them, J1-md1 2 、J2-md2 2 、J3-md3 2 、J4-md4 2 、J5-md5 2 and J6-md6 2 Respectively represent the moment of inertia of the object to be tested under various load postures, J x , J y and J z represents the moment of inertia of the object to be measured around each coordinate axis of the coordinate system of the object to be measured, α1, α2, α3, α4, α5 and α6 represent the angles between the coordinate axis X of the object to be measured and the central axis of the stage under each load posture, β1, β2, β3, β4, β5 and β6 represent the angles between the coordinate axis Y of the object to be measured and the central axis of the stage under each load posture, γ1, γ2, γ3, γ4, γ5 and γ6 represent the angles between the coordinate axis Z of the object to be measured and the central axis of the stage under each load posture, J yz , J xz and J xy They represent the product of inertia of the object to be measured around the yz plane, xz plane and xy plane respectively.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the program is executed by a processor, the method for measuring the rigid body rotational product of inertia based on point cloud registration as described in any one of claims 2 to 9 is implemented.

Images