A method and system for automatically identifying the deflection of a sleeve.

Abstract

This invention discloses an automated method and system for calculating the deflection of casing deformation, relating to the technical field of engineering applications. The method includes the following steps: acquiring initial point cloud data of the casing and preprocessing the initial point cloud data; constructing a casing deflection calculation model, which includes a three-dimensional spatial straight-line fitting module, a first rotation module, a second rotation module, a deflection parameter adjustment module, and a deflection calculation module; using the casing deflection calculation model to calculate the casing deflection of the preprocessed initial point cloud data and outputting the calculation results. Through the method and system of this invention, automated identification of the deformation endpoint and reference point can be achieved in engineering casing deflection calculation, improving the efficiency of casing deflection calculation, reducing the difficulty of point selection, and reducing the input of manpower and resources.

Description

Technical Field

[0001] This invention relates to the technical field of engineering applications, and in particular to an automated method and system for calculating the deflection of a sleeve to identify its deformation. Background Technology

[0002] Bushings are widely used in various engineering projects (such as power and civil engineering). Taking wall penetrations as an example, wall bushings are large in size and heavy in weight. In actual operation, relying solely on the middle section through the wall as the only gravity support point, both ends of the bushing (outdoor and indoor sides) will inevitably experience a certain degree of deflection due to their own weight. This can affect the connection of the current-carrying structure at the bushing end and cause malfunctions (such as bushing overheating). Currently, the only way to measure bushing deflection is to disassemble the bushing and measure it on the ground. This not only consumes a lot of manpower and resources, but also poses significant safety risks due to crane operations, and does not fully reflect actual operating conditions.

[0003] To address the above situation, existing methods typically combine laser point cloud scanning equipment to scan the through-wall bushing into point cloud data, and then calculate the deflection based on this data. However, since the coordinate data of the point cloud is generally in an independent coordinate system, lacking a reference system, and the methods for processing the point cloud mostly involve manually selecting the deformation endpoints and reference points, it is impossible to automatically identify and process these points. This results in low computational efficiency and difficulty in selecting points during the bushing deflection calculation based on reference points, baselines, and deformation endpoints, thus consuming significant human and material resources. Summary of the Invention

[0004] To overcome the problems of low efficiency and difficulty in point selection caused by the inability of existing casing deflection calculation technology to automatically identify and process the deformation endpoints and reference points during the calculation of casing deflection in engineering, the present invention aims to propose an automated casing deformation identification method and system for deflection calculation. This method and system can automatically identify and process the deformation endpoints and reference points, thereby improving the efficiency of casing deflection calculation, effectively reducing the difficulty in point selection, and reducing the investment of manpower and resources.

[0005] To achieve the objectives of this invention, the following technical solution is adopted:

[0006] A method for automatically identifying the deflection of a sleeve, the method comprising the following steps:

[0007] Acquire initial point cloud data of the casing and preprocess the initial point cloud data of the casing;

[0008] A casing deflection calculation model is constructed, which includes a three-dimensional space straight line fitting module, a first rotation module, a second rotation module, a deflection parameter adjustment module, and a deflection calculation module.

[0009] The casing deflection calculation model is used to calculate the casing deflection from the preprocessed initial point cloud data, and the calculation results are output.

[0010] In the above technical solution, data preprocessing of the acquired initial point cloud data of the casing can improve the practicality and reliability of the data and reduce data errors. By constructing a casing deflection calculation model that can effectively grasp the changes in the casing point cloud data, the deformation endpoint and the reference point can be automatically identified and processed to improve the casing deflection calculation efficiency, effectively reduce the difficulty of point selection, and reduce the investment of manpower and material resources.

[0011] Furthermore, the preprocessing of the initial point cloud data of the casing includes:

[0012] The acquired initial point cloud data of the casing is cropped and denoised.

[0013] In the above technical solution, noise reduction processing of the acquired initial point cloud data of the casing can improve the practicality and reliability of the data, reduce data errors, and improve computational efficiency.

[0014] The point cloud data is fitted in three dimensions using a three-dimensional spatial line fitting module to obtain the sleeve spatial line features of the sleeve point cloud data.

[0015] The sleeve is rotated once using a single rotation module based on the linear characteristics of the sleeve space, and the planar position characteristics of the sleeve base are extracted.

[0016] The secondary rotation module performs a secondary rotation on the sleeve based on the extracted plane position features of the sleeve base, and extracts the point cloud features of the sleeve edge;

[0017] The deflection parameter adjustment module selects points based on the extracted point cloud features of the casing edge to determine the casing deformation endpoints and the casing root points.

[0018] The deflection calculation module determines the casing baseline based on the planar position characteristics of the casing base, and performs deflection calculation on the casing based on the casing deformation endpoint, casing root point and casing baseline, and outputs the calculation results.

[0019] In the above technical solution, the constructed casing deflection calculation model is divided into modules according to different functions. The three-dimensional spatial straight line fitting module extracts the spatial straight line features of the casing from the point cloud data. The first rotation module extracts the planar position features of the casing base based on the spatial straight line features. The deflection parameter adjustment module determines the casing deformation endpoint and the casing root point based on the planar position features of the casing base. The deflection calculation module determines the casing baseline based on the planar position features of the casing base and performs deflection calculation on the casing based on the casing deformation endpoint, the casing root point, and the casing baseline. Through the cooperation of each module, the casing deflection calculation model can effectively grasp the changes in the casing point cloud data, thereby enabling the casing deflection calculation model to automatically identify and process the casing deformation endpoint and reference point, improve the efficiency of casing deflection calculation, and effectively reduce the difficulty of point selection.

[0020] Furthermore, the process of performing three-dimensional fitting on the casing point cloud data using the three-dimensional spatial line fitting module includes:

[0021] The casing point cloud data is subjected to 3D fitting using a decentralized approach and covariance matrix calculation to extract the straight-line features in the casing space. The expression is as follows:

[0022] ;

[0023] in, Let represent the coordinates of the fitted line, and respectively. These represent the centroids of the coordinate axes. These represent the direction vectors in the x, y, and z directions, respectively.

[0024] Furthermore, the process of performing 3D fitting of the casing point cloud data using the decentralization and covariance matrix calculation methods includes:

[0025] The centroid of the sleeve in the X, Y, and Z directions is calculated using the following expression:

[0026] ;

[0027] The centroids of the bushing in the X, Y, and Z directions are decentered, as expressed by:

[0028] ;

[0029] Calculate the covariance matrix of the casing and perform singular value decomposition. The expression is as follows:

[0030] ;

[0031] ;

[0032] in, Let N represent the centroid and the number of data points. Represents coordinates, The coordinate data is decentralized. This represents the processed casing coordinate data. Indicates matrix transpose. Represents the covariance matrix of the data. This indicates the singular value decomposition process. Represents a left singular vector. This represents a right singular vector.

[0033] In the above technical solution, the method of decentralization and covariance matrix calculation can effectively simplify the data processing flow and improve the efficiency of data calculation during the three-dimensional fitting of casing point cloud data.

[0034] Furthermore, the process of extracting the planar position features of the sleeve base includes:

[0035] Based on the linear characteristics of the casing space, the casing slope is calculated using a linear regression method. The expression is:

[0036] ;

[0037] Calculate the rotation angle of the casing based on the casing slope. The expression is:

[0038] ;

[0039] According to the rotation angle After rotating the sleeve once, the planar position features of the sleeve base are extracted, expressed as:

[0040] ;

[0041] in, Indicates the number of points. Represents coordinates, This represents the average value of the coordinates. This represents the rotation matrix about the Z-axis. Indicates matrix transpose. This represents the initial sleeve coordinate data.

[0042] Furthermore, the process of calculating the deflection of the casing based on the casing deformation endpoints, casing root points, and casing baseline includes:

[0043] The casing slope is obtained by fitting the planar position characteristics of the casing base to determine the baseline.

[0044] Using the intercept of the baseline at the casing root point, the deflection between the casing deformation endpoint and the baseline is calculated, expressed as:

[0045] ;

[0046] in, Indicates deflection. All represent the parameters of the baseline. These represent the X and Z coordinates of the deformation endpoints, respectively.

[0047] In the above technical solution, the casing slope is calculated using a linear regression method, based on the rotation angle. Rotating the casing once and extracting the planar position features of the casing base facilitates the subsequent identification of the casing head and tail and fitting, improving the accuracy of automated identification of the casing's deformation endpoints and reference points. Using the Adam optimizer to optimize the parameters of the casing deflection calculation model can improve the calculation efficiency and accuracy of the casing deflection calculation model, thereby effectively reducing the input of manpower and material resources.

[0048] An automated deflection calculation system for identifying sleeve deformation, the system comprising:

[0049] The data acquisition module is used to acquire the initial point cloud data of the casing;

[0050] The data processing module is used to preprocess the initial point cloud data of the casing;

[0051] The model building module is used to build a casing deflection calculation model, which includes a three-dimensional space straight line fitting module, a first rotation module, a second rotation module, a deflection parameter adjustment module, and a deflection calculation module.

[0052] The casing deflection calculation module is used to calculate the casing deflection from the preprocessed initial point cloud data of the casing using the casing deflection calculation model, and output the calculation results.

[0053] An electronic device includes a memory, a processor, and a computer program stored in the memory and running on the processor, wherein when the processor executes the computer program, it implements the steps of an automated method for calculating the deflection of a sleeve deformation.

[0054] Compared with the prior art, the beneficial effects of the present invention are as follows:

[0055] This invention proposes an automated method and system for calculating the deflection of casing deformation. By preprocessing the acquired initial point cloud data of the casing, the practicality and reliability of the data can be improved, and data errors can be reduced. By constructing a casing deflection calculation model that can effectively grasp the changes in the casing point cloud data, the deformation endpoint and reference point can be automatically identified and processed, thereby improving the efficiency of casing deflection calculation, effectively reducing the difficulty of point selection, and reducing the input of manpower and material resources. Attached Figure Description

[0056] Figure 1 A flowchart illustrating the steps of an automated deflection calculation method for identifying sleeve deformation, as provided in this application embodiment;

[0057] Figure 2 The initial image of the sleeve obtained for the embodiments of this application;

[0058] Figure 3 This is a preprocessed initial image of the sleeve provided in an embodiment of this application;

[0059] Figure 4 A casing spatial straight line feature map obtained by three-dimensional fitting of casing point cloud data provided in this application embodiment;

[0060] Figure 5 This application provides a comparison image of the sleeve before and after a single rotation, as shown in the embodiments of this application.

[0061] Figure 6 The result of rotating the sleeve according to the embodiments of this application is projected onto the XZ plane view;

[0062] Figure 7 This is a comparison image of the sleeve before and after a second rotation, provided in an embodiment of this application.

[0063] Figure 8 This is a schematic diagram of the slice after secondary rotation provided in an embodiment of this application;

[0064] Figure 9 This is a schematic diagram of the sleeve fitting region distribution provided in an embodiment of this application;

[0065] Figure 10 This is a schematic diagram of point cloud parameter adjustment provided in an embodiment of this application;

[0066] Figure 11 A schematic diagram of the distribution of deformation endpoints and root points provided in the embodiments of this application;

[0067] Figure 12 A schematic diagram of the output casing deflection calculation results provided for an embodiment of this application;

[0068] Figure 13This is a schematic diagram of the structure of an automated deflection calculation system for identifying sleeve deformation, provided in an embodiment of this application. Detailed Implementation

[0069] To facilitate understanding of the present invention, a more complete description will be given below with reference to the accompanying drawings. Preferred embodiments of the invention are shown in the drawings. However, the invention can be implemented in many different forms and is not limited to the embodiments described herein. Rather, these embodiments are provided to provide a thorough and complete understanding of the disclosure of the invention.

[0070] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention pertains. The terminology used herein in the description of the invention is for the purpose of describing particular embodiments only and is not intended to be limiting of the invention. The term "and / or" as used herein includes any and all combinations of one or more of the associated listed items.

[0071] Example 1:

[0072] This embodiment provides an automated method for calculating the deflection of sleeve deformation. See [link to relevant documentation]. Figure 1 The method includes the following steps:

[0073] Step S1: Obtain the initial point cloud data of the casing and preprocess the initial point cloud data of the casing;

[0074] Step S2: Construct a casing deflection calculation model, which includes a three-dimensional space straight line fitting module, a first rotation module, a second rotation module, a deflection parameter adjustment module, and a deflection calculation module;

[0075] Step S3: Calculate the casing deflection using the casing deflection calculation model on the preprocessed initial point cloud data of the casing, and output the calculation results.

[0076] In step S1, see Figure 2 and Figure 3 The preprocessing process for the initial point cloud data of the casing includes:

[0077] After cropping the acquired initial point cloud data of the casing, it is exported as a coordinate file in txt format and then subjected to noise reduction processing.

[0078] Understandably, denoising the acquired initial point cloud data of the casing can improve the usability and reliability of the data, reduce data errors, and improve computational efficiency.

[0079] Specifically, in step S2:

[0080] S21: Use the three-dimensional spatial line fitting module to perform three-dimensional fitting on the casing point cloud data to obtain the casing spatial line features of the casing point cloud data.

[0081] S22: Use a single rotation module to rotate the sleeve once based on the linear characteristics of the sleeve space, and extract the planar position features of the sleeve base;

[0082] S23: The secondary rotation module performs a secondary rotation on the sleeve based on the extracted plane position features of the sleeve base, and extracts the point cloud features of the sleeve edge;

[0083] S24: The deflection parameter adjustment module selects points based on the extracted point cloud features of the casing edge to determine the casing deformation endpoints and the casing root points;

[0084] S25: The deflection calculation module determines the casing baseline based on the plane position characteristics of the casing base, and performs deflection calculation on the casing based on the casing deformation endpoint, casing root point and casing baseline, and outputs the calculation results;

[0085] Understandably, the constructed casing deflection calculation model is divided into modules according to different functions. The three-dimensional spatial straight line fitting module extracts the casing spatial straight line features from the point cloud data. The first rotation module extracts the casing base plane position features based on the casing spatial straight line features. The deflection parameter adjustment module determines the casing deformation endpoint and casing root point based on the casing base plane position features. The deflection calculation module determines the casing baseline based on the casing base plane position features and performs casing deflection calculation based on the casing deformation endpoint, casing root point, and casing baseline. Through the cooperation of each module, the casing deflection calculation model can effectively grasp the changes in the casing point cloud data, thereby enabling the casing deflection calculation model to automatically identify and process the casing deformation endpoint and reference point, improve the casing deflection calculation efficiency, and effectively reduce the difficulty of point selection.

[0086] In step S21, see Figure 4 The process of performing three-dimensional fitting on the casing point cloud data using the three-dimensional spatial line fitting module includes:

[0087] The process of performing 3D fitting of casing point cloud data using a decentralized approach and covariance matrix calculation includes:

[0088] The centroid of the sleeve in the X, Y, and Z directions is calculated using the following expression:

[0089] ;

[0090] The centroids of the bushing in the X, Y, and Z directions are decentered, as expressed by:

[0091] ;

[0092] Calculate the covariance matrix of the casing and perform singular value decomposition. The expression is as follows:

[0093] ;

[0094] ;

[0095] in, Let N represent the centroid and the number of data points. Represents coordinates, The coordinate data is decentralized. This represents the processed casing coordinate data. Indicates matrix transpose. Represents the covariance matrix of the data. This indicates the singular value decomposition process. Represents a left singular vector. Denotes a right singular vector. The first column is the direction vector. .

[0096] The casing point cloud data is subjected to 3D fitting using a decentralized approach and covariance matrix calculation to extract the spatial straight line features of the casing. The expression is as follows:

[0097] ;

[0098] in, Let represent the coordinates of the fitted line, and respectively. These represent the centroids of the coordinate axes. These represent the direction vectors in the x, y, and z directions, respectively.

[0099] Understandably, adopting a decentralized approach and calculating the covariance matrix can effectively simplify the data processing flow and improve the efficiency of data computation during the 3D fitting of casing point cloud data.

[0100] In step S22, the process of extracting the planar position features of the sleeve base includes:

[0101] Based on the linear characteristics of the casing space, the casing slope is calculated using a linear regression method. The expression is:

[0102] ;

[0103] Calculate the rotation angle of the casing based on the casing slope. The expression is:

[0104] ;

[0105] According to the rotation angle After rotating the sleeve once, the planar position features of the sleeve base are extracted, expressed as:

[0106] ;

[0107] in, Indicates the number of points. Represents coordinates, This represents the average value of the coordinates. This represents the rotation matrix about the Z-axis. Indicates matrix transpose. This represents the initial sleeve coordinate data.

[0108] In some embodiments, based on a spatial straight line, the sleeve is rotated for the first time around the Z-axis and Y-axis, respectively.

[0109] Since the initial coordinates do not have a fixed reference coordinate system, the spatial straight line features obtained from step S22 are projected onto the XY plane, and the slope is calculated to obtain the rotation angle. This "aligns" the line roughly parallel to the X-axis, facilitating later identification of the head and tail and fitting. The rotation result is as follows: Figure 5 , Figure 6 As shown, the linear regression formula is as follows.

[0110]

[0111]

[0112] in, The slope The intercept is... For points, As coordinates, This is the average value of the coordinates. Then, the rotation angle is calculated. :

[0113]

[0114] Rotation matrix for rotation around the Z-axis for:

[0115]

[0116] Then the rotated sleeve for:

[0117]

[0118] Here For initial casing coordinate data, Indicates matrix transpose;

[0119] Similarly, project the three-dimensional coordinates onto the XZ plane and perform the same process to rotate the sleeve around the Y-axis.

[0120] For example, in step S23, the head (deformed end) and tail (reference end) are identified, and the XY plane is rotated twice. See [link / reference]. Figure 7 and Figure 8 ( Figure 8 The red line represents the cross-section of the slice, and the yellow dot represents the lowest point in the slice. Since there is no fixed standard for coordinate data, it is impossible to determine which end of the X-axis the base is located at. Therefore, the head and tail are identified. The identification method is as follows: take 10% of the maximum value and 10% of the minimum value of the X-axis (10% is the proportion that has achieved better results after testing), create an index to find their Y and Z coordinates, and thus filter out the coordinate data of the head and tail. Then find the maximum and minimum values ​​of the corresponding Y-axis of the two parts, and determine the end with the larger difference as the chassis part.

[0121] The casing is projected onto the xy plane, and random slices (i.e., cross-sections) are made within the casing section. The point with the smallest y-coordinate in each slice is selected, and linear regression is performed using these points. Finally, the entire casing is strictly rotated around the z-axis based on the slope of the fitted line.

[0122] Next, the sleeve is projected onto the xz plane, and random slices (i.e. cross sections) are made within the base area, with the slices parallel to the xy plane. The point with the smallest x-coordinate in each slice is selected, and linear regression fitting is performed using these points. Finally, the entire sleeve is strictly rotated around the y-axis based on the slope of the fitted line.

[0123] For example, in step S24, the deformation endpoint and the casing root point are determined. A portion of the chassis, casing head, and root are each cut off, and the point with the lowest elevation within a certain x-coordinate range is found to obtain the deformation endpoint and root point, thus avoiding the influence of individual noise points. Figure 9 and Figure 10 ( Figure 9 The deformation endpoints are obtained by fitting the dark gray area in the middle of the head, the root points are obtained by fitting the light gray area, and the gray area in the tail is left to be fitted and solved for the baseline in the next step. Figure 10 The center circle represents the deformation endpoint, and the square point represents the root point. (For example...) Figure 11 As shown, the fitting positions of the root point and the baseline can be adjusted according to requirements.

[0124] In step S25, the process of calculating the deflection of the casing based on the casing deformation endpoint, the casing root point, and the casing baseline includes:

[0125] The casing slope is obtained by fitting the planar position characteristics of the casing base to determine the baseline.

[0126] Using the intercept of the baseline at the casing root point, the deflection between the casing deformation endpoint and the baseline is calculated, expressed as:

[0127] ;

[0128] in, Indicates deflection. All represent the parameters of the baseline. These represent the X and Z coordinates of the deformation endpoints, respectively.

[0129] like Figure 12 The diagram shows the results of the casing deflection calculation. The gray line in the diagram is the baseline, and the black dots represent the distance from the deformation point to the baseline, which is the calculated deflection value.

[0130] In the embodiments of this application, the optimizer Adam is used to optimize the parameters of the casing deflection calculation model.

[0131] The methods described in the embodiments of this application can be executed in Cloud Compare software.

[0132] Understandably, the casing slope is calculated using linear regression, based on the rotation angle. Rotating the casing once and extracting the planar position features of the casing base facilitates the subsequent identification of the casing head and tail and fitting, improving the accuracy of automated identification of the casing's deformation endpoints and reference points. The Adam optimizer is used to optimize the parameters of the casing deflection calculation model, improving the calculation efficiency and accuracy of the casing deflection calculation model, thereby effectively reducing the input of manpower and material resources.

[0133] In this embodiment, data preprocessing of the acquired initial point cloud data of the casing can improve the practicality and reliability of the data and reduce data errors. By constructing a casing deflection calculation model and using the preprocessed data to perform deflection calculation on the constructed casing deflection calculation model, the deformation endpoint and reference point can be automatically identified and processed, thereby improving the efficiency of casing deflection calculation, effectively reducing the difficulty of point selection, and reducing the investment of manpower and material resources.

[0134] Example 2:

[0135] This embodiment provides an automated deflection calculation system for identifying sleeve deformation. See [link to documentation]. Figure 13 The system includes:

[0136] The data acquisition module is used to acquire the initial point cloud data of the casing;

[0137] The data processing module is used to preprocess the initial point cloud data of the casing;

[0138] The model building module is used to build a casing deflection calculation model, which includes a three-dimensional space straight line fitting module, a first rotation module, a second rotation module, a deflection parameter adjustment module, and a deflection calculation module.

[0139] The casing deflection calculation module is used to calculate the casing deflection from the preprocessed initial point cloud data of the casing using the casing deflection calculation model, and output the calculation results.

[0140] Example 3:

[0141] This embodiment provides an electronic device, including a memory, a processor, and a computer program stored in the memory and running on the processor. When the processor executes the computer program, it implements the steps of an automated method for calculating the deflection of a sleeve deformation.

[0142] The above description is merely an embodiment of the present invention and does not limit the patent scope of the present invention. Any equivalent structural or procedural transformations made based on the content of the present invention's specification and drawings, or direct or indirect applications in other related technical fields, are similarly included within the patent protection scope of the present invention.

Claims

1. A method for automatically identifying the deflection of a sleeve, characterized in that, The method includes the following steps: Acquire initial point cloud data of the casing and preprocess the initial point cloud data of the casing; A casing deflection calculation model is constructed, which includes a three-dimensional space straight line fitting module, a first rotation module, a second rotation module, a deflection parameter adjustment module, and a deflection calculation module. The casing deflection is calculated using a casing deflection calculation model on the preprocessed initial point cloud data of the casing, and the calculation results are output. The point cloud data is fitted in three dimensions using a three-dimensional spatial line fitting module to obtain the sleeve spatial line features of the sleeve point cloud data. The sleeve is rotated once using a single rotation module based on the linear characteristics of the sleeve space, and the planar position characteristics of the sleeve base are extracted. The secondary rotation module performs a secondary rotation on the sleeve based on the extracted plane position features of the sleeve base, and extracts the point cloud features of the sleeve edge; The deflection parameter adjustment module selects points based on the extracted point cloud features of the casing edge to determine the casing deformation endpoints and the casing root points. The deflection calculation module determines the casing baseline based on the planar position characteristics of the casing base, and performs deflection calculation on the casing based on the casing deformation endpoint, casing root point and casing baseline, and outputs the calculation results.

2. The method for automatically identifying sleeve deformation and calculating deflection according to claim 1, characterized in that, The preprocessing process for the initial point cloud data of the casing includes: The acquired initial point cloud data of the casing is cropped and denoised.

3. The method for automatically identifying sleeve deformation and calculating deflection according to claim 1, characterized in that, The process of performing three-dimensional fitting on the casing point cloud data using the three-dimensional spatial line fitting module includes: The casing point cloud data is subjected to 3D fitting using a decentralized approach and covariance matrix calculation to extract the straight-line features in the casing space. The expression is as follows: ； in, These represent the coordinates of the fitted line. These represent the centroids of the coordinate axes. These represent the direction vectors in the x, y, and z directions, respectively.

4. The deflection calculation method for automatically identifying sleeve deformation according to claim 3, characterized in that, The process of performing 3D fitting of casing point cloud data using a decentralized approach and covariance matrix calculation includes: The centroid of the sleeve in the X, Y, and Z directions is calculated using the following expression: ； The centroids of the bushing in the X, Y, and Z directions are decentered, as expressed by: ； Calculate the covariance matrix of the casing and perform singular value decomposition. The expression is as follows: ； ； in, Let N represent the centroid and the number of data points. Represents coordinates, The coordinate data is decentralized. This represents the processed casing coordinate data. Indicates matrix transpose. Represents the covariance matrix of the data. This indicates the singular value decomposition process. Represents a left singular vector. This represents a right singular vector.

5. The method for automatically identifying sleeve deformation and calculating deflection according to claim 3, characterized in that, The process of extracting the planar position features of the sleeve base includes: Based on the linear characteristics of the casing space, the casing slope is calculated using a linear regression method. The expression is: ； Calculate the rotation angle of the casing based on the casing slope. The expression is: ； According to the rotation angle After rotating the sleeve once, the planar position features of the sleeve base are extracted, expressed as: ； in, Indicates the number of points. Represents coordinates, This represents the average value of the coordinates. This represents the rotation matrix about the Z-axis. Indicates matrix transpose. This represents the initial sleeve coordinate data.

6. The method for automatically identifying sleeve deformation and calculating deflection according to claim 5, characterized in that, The process of calculating the deflection of the casing based on the casing deformation endpoint, the casing root point, and the casing baseline includes: The casing slope is obtained by fitting the planar position characteristics of the casing base to determine the baseline. Using the intercept of the baseline at the casing root point, the deflection between the casing deformation endpoint and the baseline is calculated, expressed as: ； in, Indicates deflection. All represent the parameters of the baseline. These represent the X and Z coordinates of the deformation endpoints, respectively.

7. The method for automatically identifying the deflection of a sleeve according to claim 1, characterized in that, The Adam optimizer was used to optimize the parameters of the casing deflection calculation model.

8. An automated deflection calculation system for identifying sleeve deformation, the system being based on the method described in claims 1-7, characterized in that, The system includes: The data acquisition module is used to acquire the initial point cloud data of the casing; The data processing module is used to preprocess the initial point cloud data of the casing; The model building module is used to build a casing deflection calculation model, which includes a three-dimensional space straight line fitting module, a first rotation module, a second rotation module, a deflection parameter adjustment module, and a deflection calculation module. The casing deflection calculation module is used to calculate the casing deflection from the preprocessed initial point cloud data of the casing using the casing deflection calculation model, and output the calculation results.

9. An electronic device, characterized in that, The method includes a memory, a processor, and a computer program stored in the memory and running on the processor, wherein when the processor executes the computer program, it implements the steps of the method as described in any one of claims 1 to 7.

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