Measurement and digital twinning-based GCB disassembly and assembly process auxiliary decision-making method

Abstract

The invention, which relates to the technical field of power generation equipment management, discloses a measurement and digital twinning-based GCB disassembly and assembly process auxiliary decision-making method comprising the following steps: establishing a global complete and local fine GCB maintenance scene model; determining the specific position of the real laser tracker; in a GCB maintenance site, a laser tracker is used for real-time monitoring. The method provided by the invention can guide on-site maintainers to carry out a safe and efficient GCB disassembly and assembly process, and reduces safety risks and human errors in the GCB disassembly and assembly process, thereby improving the working efficiency and safety of the maintainers.

Description

Technical Field

[0001] The present invention relates to the technical field of power generation equipment management, and in particular to a GCB disassembly and assembly process auxiliary decision-making method based on measurement and digital twin. Background Art

[0002] GCB is one of the most important equipment in the power equipment of hydropower stations. During long-term operation, leakage and other faults may occur, so maintenance workers need to regularly inspect GCB. However, the maintenance process requires the disassembly and installation of the GCB arc extinguishing chamber by means of hoisting, etc. This process requires manual operation and requires close attention to the surrounding environment and equipment to prevent accidents such as collision, damage or personal injury. Therefore, a GCB disassembly and assembly process auxiliary decision-making method and system based on measurement and digital twin is needed to provide comprehensive decision support for the disassembly and assembly process. The system will use equipment such as total stations and laser trackers, combined with data analysis and digital twin technologies, to establish a digital twin model of the GCB maintenance process. By real-time collection of the posture data of the arc extinguishing chamber hoisting during the GCB disassembly and assembly process, accurate prediction and decision support are provided in the software system, thereby helping maintenance personnel to perform maintenance operations more safely and efficiently. Summary of the invention

[0003] In view of the above existing problems, the present invention is proposed.

[0004] Therefore, the present invention provides a GCB disassembly and assembly process auxiliary decision-making method based on measurement and digital twin, which can solve the problem that the traditional GCB disassembly and assembly process relies on manual experience and intuitive judgment, and there are operational risks and errors. At the same time, due to the complexity and particularity of GCB, attention should be paid to the surrounding environment and equipment during the disassembly and assembly process to avoid accidents such as collisions. Therefore, the present invention aims to provide a comprehensive GCB disassembly and assembly process auxiliary decision-making method and system by combining measurement with digital twin technology to solve the problems existing in traditional methods.

[0005] In order to solve the above technical problems, the present invention provides the following technical solutions: a GCB disassembly and assembly process auxiliary decision-making method based on measurement and digital twin, comprising: Establish a globally complete and locally detailed GCB maintenance scenario model; determine the specific location of the actual laser tracker; and use the laser tracker to conduct real-time monitoring at the GCB maintenance site.

[0006] As a preferred scheme of the GCB disassembly and assembly process auxiliary decision-making method based on measurement and digital twin described in the present invention, the establishment of a globally complete and locally detailed GCB maintenance scene model includes using a total station to perform preliminary measurements of the GCB maintenance scene to obtain global point cloud data, and at the same time using a high-precision handheld scanner to perform detailed measurements of equipment parts and auxiliary tooling inside the maintenance scene to obtain complete high-precision point cloud data for each device.

[0007] As a preferred solution of the GCB disassembly and assembly process auxiliary decision-making method based on measurement and digital twinning described in the present invention, wherein: the establishment of a globally complete and locally fine GCB maintenance scene model includes obtaining global point cloud data through a total station, and the expression is as follows: , in, is the global point cloud data, is the density function of the global point cloud data, is the measurement function of the total station, is the global measurement area, is the global measurement volume.

[0008] The local point cloud data is obtained by a high-precision handheld scanner, and the expression is as follows: , in, It is local point cloud data obtained by high-precision handheld scanner. is the density function of the local point cloud data, is the measurement function of the handheld scanner, is the local measurement area, The local measurement volume.

[0009] As a preferred solution of the GCB disassembly and assembly process auxiliary decision-making method based on measurement and digital twins described in the present invention, the establishment of a globally complete and locally refined GCB maintenance scene model includes filtering, denoising, and sampling the acquired point cloud data, and the formula is as follows: , in, is the processed local point cloud data, For the Neighborhood points, is the filter coefficient, is the number of neighborhood points.

[0010] The processed local point cloud data is registered with the global point cloud data. The formula is as follows: , in, is the registration error function of global and local point cloud data, is the registration transformation function, and They represent the rotation angles used in the registration process.

[0011] As a preferred solution of the GCB disassembly and assembly process auxiliary decision-making method based on measurement and digital twins described in the present invention, wherein: the establishment of a globally complete and locally fine GCB maintenance scene model includes reverse modeling of the registered data, and the formula is as follows: , in, For the The reverse modeling element, is the weighting factor of the ith model element, is the geometry reconstruction function, is the reference point set, To reconstruct the point set, For time, For the The integration region for each model element, Represents the reverse modeling volume.

[0012] Combining all the reverse modeling elements, the final global model is constructed with the following formula: , in, In order to finally build a globally complete and locally detailed GCB maintenance scenario model, is the weight coefficient of the registration error, is the model transformation matrix function, is the transformation matrix, is the total number of reverse modeling elements, is the integration area.

[0013] As a preferred solution of the GCB disassembly and assembly process auxiliary decision-making method based on measurement and digital twin described in the present invention, the specific position of the actual laser tracker is determined, including selecting monitoring points according to the results and characteristics of the lifting equipment, and placing target balls at the points.

[0014] The coordinate system is established with the position of the on-site laser tracker as the coordinate origin.

[0015] The measurement error in the real environment is represented by a Gaussian random variable, and the dynamic change is represented by the covariance matrix control: , in, A Gaussian random variable representing the measurement error, Represents a multidimensional normal distribution.

[0016] In virtual and real environments, the scale of virtuality and reality It is dynamically adjusted based on the rate of change of measured data and the environmental impact function , specifically expressed as: , in, is the initial scale, is time t, is the rate of change of the actual target ball posture, It is the comprehensive influence function of environmental factors and the change rate of measurement data.

[0017] The actual position of the target ball is estimated by Bayesian reasoning, combining prior and measured data to obtain the optimal position that maximizes the posterior probability: , in, The estimated real-world target sphere pose represents the best estimate at time t; Represents the posterior probability Maximized realistic target ball pose ; Represents the posterior probability of the actual target ball position, given the measurement data back, probability.

[0018] Posterior probability According to Bayes' theorem, it can be expressed as: , in, is the likelihood function, which means that given a given posture Next, measurement data probability; is the prior probability.

[0019] As a preferred solution of the GCB disassembly and assembly process auxiliary decision-making method based on measurement and digital twinning described in the present invention, wherein: the specific position of the actual laser tracker is determined, the coordinate transformation matrix Map the real-world target ball pose to the virtual environment and combine it with the rotation matrix and the dynamic translation vector : , Rotation Matrix According to Kalman filter adjustment: , in, is the Kalman gain matrix; It is a dynamic translation vector, which is adjusted based on real-time measurement data; represents the initial rotation matrix; Represents the rate of change of the rotation matrix.

[0020] The final virtual target ball position The estimated value of the actual target ball position and measurement error , combined with the virtual and real scale and the coordinate transformation matrix To map, the expression is as follows: , In order to further ensure that the virtual and real target spheres match each other, real-time feedback correction is performed based on the feedback correction of the pose difference between the virtual and real target spheres. , through the correction function Adjust the virtual-real scale and the transformation matrix : , in, Indicates the coordinate position of the virtual target ball along the x-axis in the virtual environment. Indicates the coordinate position of the virtual target ball along the y-axis in the virtual environment. Indicates the coordinate position of the virtual target ball along the z-axis in the virtual environment. Respectively represent the estimated coordinate positions of the real target ball on the x, y, and z axes; The pose data of the virtual target ball in the virtual environment is the position vector of the virtual target ball in the digital twin system; The position data of the real target ball in the real environment is the target ball position vector measured by the laser tracker.

[0021] Recorded as Recorded as ; in, The position data of the real target ball in the real environment is the target ball position vector measured by the laser tracker; Indicates the coordinate position of the real target ball along the x-axis in the real environment. Indicates the coordinate position of the real target ball along the y-axis in the real environment. Indicates the coordinate position of the real target ball along the z-axis in the real environment.

[0022] Virtual-Real Scale and the coordinate transformation matrix It has been determined that the coordinates in the virtual environment are connected with the coordinates in the real world, and the virtual target ball is used as the reference for reverse deduction, and the mapping relationship is established as follows: , Assume that the initial position of the virtual laser tracker in the virtual environment is , the corresponding actual laser tracker pose is , the relative position of the real target ball to the real laser tracker is expressed as: , in, is the relative position vector of the target ball relative to the laser tracker.

[0023] In order to ensure that the pose of the virtual laser tracker is consistent with the real laser tracker, it is necessary to infer the pose of the virtual laser tracker. , so that the mapping relationship between the virtual target ball and the real target ball is consistent, and the position and posture of the mapped virtual target ball are expressed as: , in, is the relative position vector of the virtual target ball relative to the virtual laser tracker. Combining the virtual-real scale and coordinate conversion relationship: , Will Replace with : , Obtain the transformation relationship between the virtual target ball and the real target ball: , in, and They are the inverse operations of the coordinate transformation matrix and scale, respectively.

[0024] After solving the pose of the virtual laser tracker, the pose is applied to the virtual environment, and the actual pose of the virtual target ball is compared with the expected pose. If the consistency between the two meets the preset standard, the derivation is correct; otherwise, the input parameters need to be adjusted and recalculated.

[0025] If there is a difference between the pose of the virtual laser tracker and the real laser tracker, the digital twin system will start the feedback adjustment mechanism to adjust the coordinate transformation matrix. and virtual-real scale Fine-tuning is performed and the feedback mechanism recalculates the pose.

[0026] As a preferred solution of the GCB disassembly and assembly process auxiliary decision-making method based on measurement and digital twin described in the present invention, the real-time monitoring using a laser tracker includes pre-planning the GCB disassembly and assembly route, and placing the laser target ball on the point that needs to be monitored during the GCB disassembly and assembly process, using the laser tracker to obtain the data of the monitoring point during the GCB disassembly and assembly process, and at the same time, according to the standard transmission protocol of the laser tracker, the data of the monitoring point is transmitted to the digital twin system to monitor the GCB disassembly and assembly process in real time.

[0027] A computer device includes a memory and a processor, wherein the memory stores a computer program, and is characterized in that when the processor executes the computer program, the steps of a GCB disassembly and assembly process auxiliary decision-making method based on measurement and digital twin are implemented.

[0028] A computer-readable storage medium having a computer program stored thereon, characterized in that when the computer program is executed by a processor, the steps of a GCB disassembly and assembly process auxiliary decision-making method based on measurement and digital twin are implemented.

[0029] Beneficial effects of the present invention: The method proposed in the present invention can guide on-site maintenance personnel to perform a safe and efficient GCB disassembly and assembly process, reduce safety risks and human errors in the GCB disassembly and assembly process, and thus improve the work efficiency and safety of maintenance personnel. BRIEF DESCRIPTION OF THE DRAWINGS

[0030] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings required for use in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other accompanying drawings can be obtained based on these accompanying drawings without paying creative work.

[0031] Figure 1 A flow chart of a GCB disassembly and assembly process decision-making assistance method based on measurement and digital twins is provided for one embodiment of the present invention. DETAILED DESCRIPTION

[0032] In order to make the above-mentioned purposes, features and advantages of the present invention more obvious and easy to understand, the specific implementation methods of the present invention are described in detail below in conjunction with the drawings of the specification. Obviously, the described embodiments are part of the embodiments of the present invention, but not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary persons in the art without creative work should fall within the scope of protection of the present invention.

[0033] In the following description, many specific details are set forth to facilitate a full understanding of the present invention, but the present invention may also be implemented in other ways different from those described herein, and those skilled in the art may make similar generalizations without violating the connotation of the present invention. Therefore, the present invention is not limited to the specific embodiments disclosed below.

[0034] Secondly, the term "one embodiment" or "embodiment" as used herein refers to a specific feature, structure, or characteristic that may be included in at least one implementation of the present invention. The term "in one embodiment" that appears in different places in this specification does not necessarily refer to the same embodiment, nor does it refer to a separate or selective embodiment that is mutually exclusive with other embodiments.

[0035] The present invention is described in detail with reference to schematic diagrams. When describing the embodiments of the present invention, for the sake of convenience, the cross-sectional diagrams showing the device structure will not be partially enlarged according to the general scale, and the schematic diagrams are only examples, which should not limit the scope of protection of the present invention. In addition, in actual production, the three-dimensional dimensions of length, width and depth should be included.

[0036] At the same time, in the description of the present invention, it should be noted that the directions or positional relationships indicated by the terms "upper, lower, inner and outer" are based on the directions or positional relationships shown in the drawings, and are only for the convenience of describing the present invention and simplifying the description, rather than indicating or implying that the device or element referred to must have a specific direction, be constructed and operated in a specific direction, and therefore cannot be understood as limiting the present invention. In addition, the terms "first, second or third" are only used for descriptive purposes and cannot be understood as indicating or implying relative importance.

[0037] In the present invention, unless otherwise clearly specified and limited, the terms "install, connect, connect" should be understood in a broad sense, for example: it can be a fixed connection, a detachable connection or an integral connection; it can also be a mechanical connection, an electrical connection or a direct connection, or it can be indirectly connected through an intermediate medium, or it can be the internal communication of two components. For ordinary technicians in this field, the specific meanings of the above terms in the present invention can be understood according to specific circumstances.

[0038] Example 1, reference Figure 1 , which is the first embodiment of the present invention, and provides a GCB disassembly and assembly process auxiliary decision method based on measurement and digital twin, including: S1: Establish a globally complete and locally detailed GCB maintenance scenario model.

[0039] S2: Determine the specific position of the real laser tracker.

[0040] S3: At the GCB maintenance site, real-time monitoring is performed using a laser tracker.

[0041] The establishment of a globally complete and locally detailed GCB maintenance scene model includes performing preliminary measurements of the GCB maintenance scene using a total station to obtain global point cloud data, and simultaneously performing detailed measurements of equipment parts and auxiliary tooling within the maintenance scene using a high-precision handheld scanner to obtain complete high-precision point cloud data for each device.

[0042] The establishment of a globally complete and locally fine GCB maintenance scene model includes obtaining global point cloud data through a total station, and the expression is as follows: , in, is the global point cloud data, is the density function of the global point cloud data, is the measurement function of the total station, is the global measurement area, is the global measurement volume.

[0043] The local point cloud data is obtained by a high-precision handheld scanner, and the expression is as follows: , in, It is local point cloud data obtained by high-precision handheld scanner. is the density function of the local point cloud data, is the measurement function of the handheld scanner, is the local measurement area, It is a local measurement volume.

[0044] The establishment of a globally complete and locally refined GCB maintenance scene model includes filtering, denoising, and sampling the acquired point cloud data. The formula is as follows: , in, is the processed local point cloud data, For the Neighborhood points, is the filter coefficient, is the number of neighborhood points.

[0045] The processed local point cloud data is registered with the global point cloud data. The formula is as follows: , in, is the registration error function of global and local point cloud data, is the registration transformation function, and They represent the rotation angles used in the registration process.

[0046] The establishment of a globally complete and locally refined GCB maintenance scenario model includes reverse modeling of the registered data, with the formula as follows: , where, is the th element of reverse modeling, is the weighting factor of the ith model element, is the geometric reconstruction function, is the reference point set, is the reconstruction point set, is the time, is the integration region of the ith model element,

[0047] Combining all reverse modeling elements to construct the final global model, with the formula as follows: , where, is the finally constructed globally complete and locally refined GCB maintenance scenario model, is the weight coefficient of the registration error, is the model transformation matrix function, is the transformation matrix, is the total number of reverse modeling elements, is the integration region.

[0048] The determination of the specific position of the actual laser tracker includes selecting monitoring points according to the results and characteristics of the hoisting equipment and placing target balls at the points.

[0049] Taking the position of the on-site laser tracker as the coordinate origin, a coordinate system is established.

[0050] The measurement error in the real environment is represented by a Gaussian random variable, and the dynamic change is controlled by the covariance matrix : , where, is the Gaussian random variable representing the measurement error, represents the multi-dimensional normal distribution.

[0051] In the virtual environment and the real environment, the virtual-real scale is dynamically adjusted based on the change rate of the measurement data and the environmental impact function , and the specific expression is: , where, is the initial scale, is time t, is the rate of change of the actual target ball posture, It is the comprehensive influence function of environmental factors and the change rate of measurement data.

[0052] The actual position of the target ball is estimated by Bayesian reasoning, combining prior and measured data to obtain the optimal position that maximizes the posterior probability: , in, The estimated real-world target sphere pose represents the best estimate at time t; Represents the posterior probability Maximized realistic target ball pose ; Represents the posterior probability of the actual target ball position, given the measurement data back, probability.

[0053] Posterior probability According to Bayes' theorem, it can be expressed as: , in, is the likelihood function, which means that given a given posture Next, measurement data The probability of is the prior probability.

[0054] The determination of the specific position of the actual laser tracker includes: a coordinate transformation matrix Map the real-world target ball pose to the virtual environment and combine it with the rotation matrix and the dynamic translation vector : , Rotation Matrix According to Kalman filter adjustment: , in, is the Kalman gain matrix; It is a dynamic translation vector, which is adjusted based on real-time measurement data; represents the initial rotation matrix; Represents the rate of change of the rotation matrix.

[0055] The final virtual target ball position The estimated value of the actual target ball position and measurement error , combined with the virtual and real scale and the coordinate transformation matrix To map, the expression is as follows: , In order to further ensure that the virtual and real target spheres match each other, real-time feedback correction is performed based on the feedback correction of the pose difference between the virtual and real target spheres. , through the correction function Adjust the virtual-real scale and the transformation matrix : , in, Indicates the coordinate position of the virtual target ball along the x-axis in the virtual environment. Indicates the coordinate position of the virtual target ball along the y-axis in the virtual environment. Indicates the coordinate position of the virtual target ball along the z-axis in the virtual environment. Respectively represent the estimated coordinate positions of the real target ball on the x, y, and z axes; The pose data of the virtual target ball in the virtual environment is the position vector of the virtual target ball in the digital twin system; The position data of the real target ball in the real environment is the target ball position vector measured by the laser tracker.

[0056] Recorded as Recorded as ; in, The position data of the real target ball in the real environment is the target ball position vector measured by the laser tracker; Indicates the coordinate position of the real target ball along the x-axis in the real environment. Indicates the coordinate position of the real target ball along the y-axis in the real environment. Indicates the coordinate position of the real target ball along the z-axis in the real environment.

[0057] Virtual-Real Scale and the coordinate transformation matrix It has been determined that the coordinates in the virtual environment are connected with the coordinates in the real world, and the virtual target ball is used as the reference for reverse deduction, and the mapping relationship is established as follows: , Assume that the initial position of the virtual laser tracker in the virtual environment is , the corresponding actual laser tracker pose is , the relative position of the real target ball to the real laser tracker is expressed as: , in, is the relative position vector of the target ball relative to the laser tracker.

[0058] In order to ensure that the pose of the virtual laser tracker is consistent with the real laser tracker, it is necessary to infer the pose of the virtual laser tracker. , so that the mapping relationship between the virtual target ball and the real target ball is consistent, and the position and posture of the mapped virtual target ball are expressed as: , in, is the relative position vector of the virtual target ball relative to the virtual laser tracker. Combining the virtual-real scale and coordinate conversion relationship: , Will Replace with : , Obtain the transformation relationship between the virtual target ball and the real target ball: , in, and They are the inverse operations of the coordinate transformation matrix and scale, respectively.

[0059] After solving the pose of the virtual laser tracker, the pose is applied to the virtual environment, and the actual pose of the virtual target ball is compared with the expected pose. If the consistency between the two meets the preset standard, the derivation is correct; otherwise, the input parameters need to be adjusted and recalculated.

[0060] If there is a difference between the pose of the virtual laser tracker and the real laser tracker, the digital twin system will start the feedback adjustment mechanism to adjust the coordinate transformation matrix. and virtual-real scale Fine-tuning is performed and the feedback mechanism recalculates the pose.

[0061] The real-time monitoring using a laser tracker includes setting relevant parameters in the digital twin system to pre-plan the GCB disassembly and assembly route, placing the laser target ball at the point that needs to be monitored during the GCB disassembly and assembly process, using the laser tracker to obtain data on the monitoring points during the GCB disassembly and assembly process, and at the same time, according to the standard transmission protocol of the laser tracker, transmitting the data of the monitoring points to the digital twin system to monitor the GCB disassembly and assembly process in real time.

[0062] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical solutions of the present invention may be modified or replaced by equivalents without departing from the spirit and scope of the technical solutions of the present invention, which should all be included in the scope of the claims of the present invention.

[0063] Example 3 The third embodiment of the present invention is different from the first two embodiments in that: If the functions are implemented in the form of software functional units and sold or used as independent products, they 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, including several instructions to enable 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 described in various embodiments of the present invention. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), disk or optical disk, etc., which can store program codes.

[0064] The present application is described with reference to the flowcharts and / or block diagrams of the methods, devices (systems), and computer program products according to the embodiments of the present application. It should be understood that each process and / or box in the flowchart and / or block diagram, as well as the combination of the processes and / or boxes in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to generate a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0065] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0066] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0067] Although the preferred embodiments of the present application have been described, those skilled in the art may make other changes and modifications to these embodiments once they have learned the basic creative concept. Therefore, the appended claims are intended to be interpreted as including the preferred embodiments and all changes and modifications falling within the scope of the present application.

[0068] Obviously, those skilled in the art can make various changes and modifications to the present application without departing from the spirit and scope of the present application. Thus, if these modifications and variations of the present application fall within the scope of the claims of the present application and their equivalents, the present application is also intended to include these modifications and variations.

Claims

1. A GCB disassembly and assembly process auxiliary decision-making method based on measurement and digital twin, characterized by: include, Establish a globally complete and locally detailed GCB maintenance scenario model; Determine the exact location of the real laser tracker; At the GCB maintenance site, a laser tracker is used for real-time monitoring.

2. The GCB disassembly and assembly process auxiliary decision-making method based on measurement and digital twinning according to claim 1, characterized in that: The establishment of a globally complete and locally detailed GCB maintenance scene model includes performing preliminary measurements of the GCB maintenance scene using a total station to obtain global point cloud data, and simultaneously performing detailed measurements of equipment parts and auxiliary tooling within the maintenance scene using a high-precision handheld scanner to obtain complete high-precision point cloud data for each device.

3. The GCB disassembly and assembly process auxiliary decision-making method based on measurement and digital twin as claimed in claim 2 is characterized by: The establishment of a globally complete and locally fine GCB maintenance scene model includes obtaining global point cloud data through a total station, and the expression is as follows: ， in, is the global point cloud data, is the density function of the global point cloud data, is the measurement function of the total station, is the global measurement area, is the global measurement volume; The local point cloud data is obtained by a high-precision handheld scanner, and the expression is as follows: ， in, It is local point cloud data obtained by high-precision handheld scanner. is the density function of the local point cloud data, is the measurement function of the handheld scanner, is the local measurement area, The local measurement volume.

4. The GCB disassembly and assembly process auxiliary decision-making method based on measurement and digital twin as claimed in claim 3 is characterized by: The establishment of a globally complete and locally refined GCB maintenance scene model includes filtering, denoising, and sampling the acquired point cloud data. The formula is as follows: ， in, is the processed local point cloud data, For the Neighborhood points, is the filter coefficient, is the number of neighborhood points; The processed local point cloud data is registered with the global point cloud data. The formula is as follows: ， in, is the registration error function of global and local point cloud data, is the registration transformation function, and They represent the rotation angles used in the registration process.

5. The GCB disassembly and assembly process auxiliary decision-making method based on measurement and digital twin as claimed in claim 4 is characterized by: The establishment of a globally complete and locally refined GCB maintenance scene model includes reverse modeling of the registered data, and the formula is as follows: ， in, For the The reverse modeling element, is the weighting factor of the ith model element, is the geometry reconstruction function, is the reference point set, To reconstruct the point set, For time, For the The integration region for each model element, represents the reverse modeling volume; Combining all the reverse modeling elements, the final global model is constructed with the following formula: ， in, In order to finally build a globally complete and locally detailed GCB maintenance scenario model, is the weight coefficient of the registration error, is the model transformation matrix function, is the transformation matrix, is the total number of reverse modeling elements, is the integration area.

6. The GCB disassembly and assembly process auxiliary decision-making method based on measurement and digital twinning as claimed in claim 5, characterized in that: Determining the specific position of the actual laser tracker includes selecting a monitoring point according to the results and characteristics of the hoisting equipment and placing a target ball at the point; Establish a coordinate system with the position of the on-site laser tracker as the coordinate origin; The measurement error in the real environment is represented by a Gaussian random variable, and the dynamic change is represented by the covariance matrix control: ， in, A Gaussian random variable representing the measurement error, Represents a multidimensional normal distribution; In virtual and real environments, the scale of virtuality and reality It is dynamically adjusted based on the rate of change of measured data and the environmental impact function , specifically expressed as: ， in, is the initial scale, is time t, is the rate of change of the actual target ball posture, is the comprehensive influence function of environmental factors and the change rate of measurement data; The actual position of the target ball is estimated by Bayesian reasoning, combining prior and measured data to obtain the optimal position that maximizes the posterior probability: ， in, The estimated real-world target sphere pose represents the best estimate at time t; Represents the posterior probability Maximized realistic target ball pose ; Represents the posterior probability of the actual target ball position, given the measurement data back, The probability of Posterior probability According to Bayes' theorem, it can be expressed as: ， in, is the likelihood function, which means that given a given posture Next, measurement data The probability of is the prior probability.

7. The GCB disassembly and assembly process auxiliary decision-making method based on measurement and digital twinning as claimed in claim 6 is characterized by: The determination of the specific position of the actual laser tracker includes: a coordinate transformation matrix Map the real-world target ball pose to the virtual environment and combine it with the rotation matrix and the dynamic translation vector : ， Rotation Matrix According to Kalman filter adjustment: ， in, is the Kalman gain matrix; It is a dynamic translation vector, which is adjusted based on real-time measurement data; represents the initial rotation matrix; Represents the rate of change of the rotation matrix; The final virtual target ball position The estimated value of the actual target ball position and measurement error , combined with the virtual and real scale and the coordinate transformation matrix To map, the expression is as follows: ， In order to further ensure that the virtual and real target spheres match each other, real-time feedback correction is performed based on the feedback correction of the pose difference between the virtual and real target spheres. , through the correction function Adjust the virtual-real scale and the transformation matrix : ， in, Indicates the coordinate position of the virtual target ball along the x-axis in the virtual environment. Indicates the coordinate position of the virtual target ball along the y-axis in the virtual environment. Indicates the coordinate position of the virtual target ball along the z-axis in the virtual environment. Respectively represent the estimated coordinate positions of the real target ball on the x, y, and z axes; The pose data of the virtual target ball in the virtual environment is the position vector of the virtual target ball in the digital twin system; The position data of the real target ball in the real environment is the target ball position vector measured by the laser tracker; Recorded as Recorded as ; in, The position data of the real target ball in the real environment is the target ball position vector measured by the laser tracker; Indicates the coordinate position of the real target ball along the x-axis in the real environment. Indicates the coordinate position of the real target ball along the y-axis in the real environment. Indicates the coordinate position of the real target ball along the z-axis in the real environment; Virtual-Real Scale and the coordinate transformation matrix It has been determined that the coordinates in the virtual environment are connected with the coordinates in the real world, and the virtual target ball is used as the reference for reverse deduction, and the mapping relationship is established as follows: ， Assume that the initial position of the virtual laser tracker in the virtual environment is , the corresponding actual laser tracker pose is , the relative position of the real target ball to the real laser tracker is expressed as: ， in, is the relative position vector of the target ball relative to the laser tracker; In order to ensure that the pose of the virtual laser tracker is consistent with the real laser tracker, it is necessary to infer the pose of the virtual laser tracker. , so that the mapping relationship between the virtual target ball and the real target ball is consistent, and the position and posture of the mapped virtual target ball are expressed as: ， in, is the relative position vector of the virtual target ball relative to the virtual laser tracker; combined with the virtual-real scale and coordinate conversion relationship: ， Will Replace with : ， Obtain the transformation relationship between the virtual target ball and the real target ball: ， in, and They are the inverse operations of the coordinate transformation matrix and the scale respectively; After solving the pose of the virtual laser tracker, apply the pose to the virtual environment and compare the actual pose of the virtual target ball with the expected pose. If the consistency between the two meets the preset standard, the derivation is correct; otherwise, the input parameters need to be adjusted and recalculated. If there is a difference between the pose of the virtual laser tracker and the real laser tracker, the digital twin system will start the feedback adjustment mechanism to adjust the coordinate transformation matrix. and virtual-real scale Fine-tuning is performed and the feedback mechanism recalculates the pose.

8. The GCB disassembly and assembly process auxiliary decision-making method based on measurement and digital twinning as claimed in claim 7 is characterized by: The real-time monitoring using a laser tracker includes pre-planning the GCB disassembly and assembly route, placing a laser target ball at a point that needs to be monitored during the GCB disassembly and assembly process, using a laser tracker to obtain data on the monitoring points during the GCB disassembly and assembly process, and at the same time, according to the standard transmission protocol of the laser tracker, transmitting the data of the monitoring points to the digital twin system to monitor the GCB disassembly and assembly process in real time.

9. A computer device comprising a memory and a processor, wherein the memory stores a computer program, wherein: When the processor executes the computer program, the steps of the method according to any one of claims 1 to 8 are implemented.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 8 are implemented.

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