Intelligent installation method of volute based on three-dimensional laser scanning

Abstract

The present application relates to the technical field of hydropower station construction, and discloses a spiral case intelligent installation method based on three-dimensional laser scanning, comprising the following steps: S1: establishing a three-dimensional coordinate measurement control network and establishing a plurality of adjustment piles; S2: placing a spiral case segment on a corresponding adjustment pile to obtain an initial installation posture; S3: acquiring pipe orifice point cloud data of the installed spiral case segment and initial coordinate sets of a plurality of adjustment pile support points; S4: obtaining spiral case segment point cloud data; S5: obtaining a first optimal transformation and target center target point coordinates of a to-be-installed spiral case segment; S6: taking the finally obtained target center target point coordinates of the to-be-installed spiral case segment as a first installation instruction; S7: obtaining a second optimal transformation; S8: obtaining a second installation instruction through the second optimal transformation and the initial coordinates of the adjustment pile support points; and S9: repeating S2-S8 to install the remaining to-be-installed spiral case segments and complete the spiral case installation. The present application can improve the installation efficiency and accuracy of the spiral case segments.

Description

Technical Field

[0001] This invention relates to the field of hydropower station construction technology, specifically to an intelligent installation method for spiral casing based on three-dimensional laser scanning. Background Technology

[0002] In the turbine piping system of a hydropower station, the spiral casing, as a key terminal component of the water intake system, functions to guide water flow evenly and smoothly into the turbine runner chamber. The spiral casing is typically assembled on-site from multiple sections of spirally rolled and welded steel plates. These spiral sections, also known as spiral casing segments, are welded together. The precision of this fitting directly determines the uniformity of the water flow, the efficiency of the unit's operation, and the level of structural vibration, making it a core element in ensuring the safe, stable, and efficient operation of the hydropower station.

[0003] However, the traditional on-site installation method for volute segments has significant drawbacks: First, the process relies heavily on the experience of the installers to make repeated adjustments in a "trial and error" manner, moving the volute segments up, down, left, right, back, and front to fit adjacent volute segments together, which is time-consuming and labor-intensive, resulting in low efficiency in single-segment placement.

[0004] Secondly, after the installation workers visually confirm the fit of adjacent volute segments, they weld the fitted segments together. Subsequent adjacent segments are then fitted and welded using the same method to complete the volute installation. However, volute segments range in diameter from several meters to over ten meters, and there are dimensional manufacturing errors in their production. Combined with the manual visual assessment of the fit between adjacent segments, this leads to the continuous transmission and accumulation of installation errors during the installation process (for example, the outer edge of the nozzle of one volute segment may be offset by a few centimeters from the outer edge of the nozzle of the next volute segment). There was a few centimeters of error at the joint of the adjacent volute segments. Compared with the design position, the installation position of the adjacent volute segment of the previous section was different from the design position. The subsequent volute segment continued to be installed in the wrong position of the previous section, which caused the tail section of the volute to deviate from the preset position. This forced a lot of on-site repair and welding adjustments, which not only greatly affected the construction progress, but also easily caused the internal flow channel to be rough and generate eddies, threatening the safety and economy of the unit's long-term operation. Summary of the Invention

[0005] In order to overcome the shortcomings of the existing technology, the purpose of this invention is to provide an intelligent installation method for volute casing based on three-dimensional laser scanning, which can improve the installation efficiency and accuracy of volute casing segments.

[0006] The technical solution adopted in this invention is as follows: an intelligent installation method for a volute based on three-dimensional laser scanning, comprising the following steps:

[0007] S1: Establish a three-dimensional coordinate measurement control network with the centerline of the width direction of the hydropower station unit as the X-axis, the centerline of the length direction of the hydropower station unit as the Y-axis, and the elevation benchmark point of the hydropower station unit as the Z-axis, and establish multiple adjustment piles with the measurement control network as the coordinate system;

[0008] S2: The initial elevation of the adjusting pile is given according to the design theoretical value. Then, the volute segment to be installed is placed on the corresponding adjusting pile to obtain the initial installation posture.

[0009] S3: The pipe opening and adjustment pile support points of the installed volute segment are scanned by a 3D laser scanner to obtain the actual manufacturing shape point cloud data of the pipe opening of the installed volute segment and the initial coordinate set of multiple adjustment pile support points.

[0010] S4: Place no fewer than three targets at intervals on the outer surface of the volute segment to be installed, and use a 3D laser scanner to perform multi-site scanning of the volute segment to be installed, thereby obtaining point cloud data of the volute segment containing the targets and the geometric information of the volute segment nozzle.

[0011] S5: Obtain the first optimal transformation and the coordinates of the target center of the volute segment to be installed by using the point cloud data of the installed volute segment inlet and the point cloud data of the volute segment inlet to be installed.

[0012] S6: Use the coordinates of the target center of the volute segment to be installed as the first installation command;

[0013] S7: The second optimal transformation is obtained by using the target center scan point set under the initial attitude of the volute segment to be installed and the target center target point set of the volute segment to be installed.

[0014] S8: The second installation command is obtained by adjusting the initial coordinates of the pile support point through the second optimal transformation. This command is used to guide the three-dimensional adjustment of the pile, and thus to guide the position adjustment of the volute segment to be installed.

[0015] S9: Repeat S2-S8 to install the remaining volute segments to complete the volute installation.

[0016] Compared with the prior art, the beneficial effects of the present invention are as follows:

[0017] This invention reverse reconstructs the actual manufacturing form of the volute segment through 3D laser scanning and performs optimal matching with the installed volute segment in digital space, fundamentally eliminating the transmission and accumulation of manufacturing errors. It solves the problems of cumulative error amplification and matching failure caused by the reliance on theoretical design benchmarks in traditional methods. This method generates precise and quantitative spatial pose adjustment commands based on actual interface matching, replacing trial-and-error adjustments based on human experience, and providing a clear goal for achieving high-precision installation. Integrating measurement feedback forms an intelligent closed-loop control of "perception-decision-execution", which improves the installation efficiency of a single segment by more than 50% and increases the pose control accuracy to ±2mm, effectively ensuring the smoothness of the internal flow channel of the volute and the long-term safe and stable operation of the unit.

[0018] Specifically, the present invention improves the installation accuracy of the volute segment through two optimal transformations. The first optimal transformation is obtained by using the pipe opening of the volute segment to be installed and the pipe opening of the installed volute segment. The pipe opening of the volute segment to be installed searches for the corresponding point on the pipe opening of the installed volute segment, ensuring that the pipe opening of the volute segment to be installed and the pipe opening of the installed volute segment are aligned, thereby obtaining the installation coordinates of the target under the target installation posture with the minimum misalignment.

[0019] The second optimal transformation is obtained by the relative relationship between the target center scanning point under the initial installation posture of the volute segment to be installed and the target center target point under the target posture of the volute segment to be installed (under the first installation command). Considering the unevenness of the outer surface of the volute segment to be installed caused by manufacturing, the second optimal transformation allows the adjusting pile to be finely adjusted again, improving the placement accuracy of the volute segment to be installed. Welding is then performed after the volute segment to be installed is completed, thereby improving the fit between adjacent volute segments and improving the installation accuracy of the volute segment to be installed. Attached Figure Description

[0020] Figure 1 This is a flowchart of the intelligent installation method for the volute based on three-dimensional laser scanning according to the present invention;

[0021] Figure 2 This is the point cloud of the installation volute segment obtained by a three-dimensional laser scanner in the intelligent installation method of the volute based on three-dimensional laser scanning of this invention. Detailed Implementation

[0022] Typical embodiments embodying the features and advantages of the present invention will be specifically described in the following description. It should be understood that the present invention can have various variations in different embodiments without departing from the scope of the present invention, and the descriptions and illustrations therein are for illustrative purposes only and not intended to limit the present invention.

[0023] The present invention will now be described in detail with reference to the accompanying drawings and embodiments.

[0024] This embodiment discloses an intelligent installation method for a volute based on three-dimensional laser scanning, such as... Figure 1 As shown, it includes the following steps:

[0025] S1: Establish an independent, high-precision three-dimensional coordinate measurement and control network with the centerline of the width direction of the hydropower station unit as the X-axis, the centerline of the length direction of the hydropower station unit as the Y-axis, and the elevation benchmark point of the hydropower station unit as the Z-axis. Then, establish multiple adjustment piles using the measurement and control network as the coordinate system.

[0026] In this embodiment, the adjusting pile is a three-way jack, and each volute segment is theoretically equipped with no less than four adjusting piles below the installation position.

[0027] S2: The initial elevation of the adjusting pile is given according to the design theoretical value. Then, the volute segment to be installed is placed on the corresponding adjusting pile to obtain the initial installation posture.

[0028] S3: Using a 3D laser scanner, the pipe opening and adjustment pile support points of the installed volute segment are scanned to obtain the actual manufacturing morphology point cloud data of the pipe opening of the installed volute segment, such as... Figure 2 As shown, this is the set of initial coordinates for multiple adjustment pile support points;

[0029] In this embodiment, the 3D laser scanner can be placed anywhere as long as it can scan the opening of the pipe where the volute segment has been installed.

[0030] S4: Place no fewer than three targets at intervals on the outer surface of the volute segment to be installed, and use a 3D laser scanner to perform multi-site scanning of the volute segment to be installed, thereby obtaining point cloud data of the volute segment containing the targets and the geometric information of the volute segment nozzle.

[0031] In this embodiment, the target is distributed around the volute segment to ensure accuracy. The target is a black and white checkerboard pattern with high contrast and strong weather resistance to resist the interference of uneven lighting and oily background, so as to ensure that the target can be stably and clearly identified in the point cloud.

[0032] In this embodiment, the volute segment remains stationary, and the 3D laser scanner adjusts its position relative to the volute segment multiple times, with each position constituting a station, thus performing multi-station scanning. Geometric information refers to the length, width, and height—three-dimensional data.

[0033] S5: Obtain the first optimal transformation and the coordinates of the target center of the volute segment to be installed by using the point cloud data of the installed volute segment inlet and the point cloud data of the volute segment inlet to be installed.

[0034] Specifically, S5 also includes the following steps:

[0035] S51: Use the point cloud data of the installed volute segment pipe opening as the target reference benchmark for the ICP algorithm;

[0036] In S51, the point cloud data of the installed volute segment pipe opening is constructed into a structured point cloud set through data integration, spatial alignment, redundancy reduction and noise reduction, and attribute fusion, as shown in formulas (1) and (2), and the point cloud set of the installed volute segment pipe opening is used as the target reference benchmark of the ICP algorithm.

[0037] (1),

[0038] (2),

[0039] In formulas (1) and (2), The coordinates of the scanning point at the nozzle of the installed volute segment are given. The x-coordinate of the scanning point at the nozzle of the installed volute segment. The vertical coordinate of the scanning point at the nozzle of the installed volute segment is given. The vertical coordinates of the scanning points at the nozzles of the installed volute segment;

[0040] In this embodiment, the volute segment port scanning points refer to a large number of discrete points obtained after performing a three-dimensional laser scan on the port of the installed volute segment. The set of these points constitutes the three-dimensional shape of the port.

[0041] S52: Search for the point in the target reference datum that corresponds to the scanning point of the nozzle of the volute segment to be installed;

[0042] In S52, a point corresponding to the scanning point of the nozzle of the volute segment to be installed is searched in the target reference datum, as shown in formula (3).

[0043] (3),

[0044] In formula (3), To determine the corresponding coordinates of the scanning point of the volute segment to be installed in the target reference datum, The first section of the volute segment to be installed Coordinates of each scan point For the first section of pipe with installed volute segment Coordinates of each scan point;

[0045] In this embodiment, the point cloud data of the volute segment port to be installed includes coordinate information of multiple scan points.

[0046] S53: Construct a covariance matrix by using the corresponding coordinate points of the nozzle scanning points of the volute segment to be installed in the target reference datum and the nozzle scanning points of the volute segment to be installed, and perform singular value decomposition on the covariance matrix to obtain the rotation matrix and translation vector.

[0047] Specifically, S53 also includes the following steps:

[0048] S531: By using the corresponding coordinates of the scanning points of the volute segment to be installed in the target reference datum and the scanning points of the volute segment to be installed, the decentralized coordinates of the scanning points of the installed volute segment and the scanning points of the volute segment to be installed are obtained respectively, as shown in formulas (4) and (5).

[0049] (4),

[0050] (5),

[0051] In formulas (4) and (5), Decentralized coordinates for the scanning points at the nozzles of the installed volute segment. To determine the corresponding coordinates of the scanning point of the volute segment to be installed in the target reference datum, To find the centroid of the corresponding coordinate points of the scanning points at the nozzles of the volute segment to be installed in the target reference datum, Decentralize the coordinates of the scanning points at the nozzles of the volute segment to be installed. This is the set of coordinates for the scanning points of the nozzle of the volute segment to be installed. Centroid of the scanning point at the nozzle of the volute segment to be installed;

[0052] S532: Construct a covariance matrix using the decentralized coordinates of the scanning points at the nozzles of the installed volute segment and the scanning points of the nozzles of the volute segment to be installed, and then perform singular value decomposition on the covariance matrix to obtain the rotation matrix and translation vector, as shown in formulas (6), (7), (8), and (9).

[0053] (6),

[0054] (7),

[0055] (8),

[0056] (9),

[0057] In formulas (6), (7), (8), (9), Let covariance matrix be the variance matrix. Decentralized coordinates for the scanning points at the nozzles of the installed volute segment. Decentralize the coordinates of the scanning points at the nozzles of the volute segment to be installed. This is the transpose of the matrix. , These are the left and right singular vectors, respectively. It is a diagonal matrix. For rotation matrix, It is a translation vector.

[0058] S54: Update the pose of the point cloud of the volute segment to be installed and the target center point cloud by using rotation matrix and translation vector;

[0059] In S54, the pose of the nozzle and target center point cloud of the volute segment to be installed is updated by rotation matrix and translation vector, as shown in formulas (10) and (11).

[0060] (10)

[0061] (11),

[0062] In formulas (10) and (11), This represents the coordinates of the i-th scanning point at the inlet of the volute segment to be installed after coordinate transformation following the (k+1)-th iteration. It is a rotation matrix; The coordinates of the i-th scanning point of the volute segment nozzle to be installed are after the coordinate transformation following the k-th iteration. It is a translation vector;

[0063] This represents the coordinates of the i-th scanning point at the center of the target segment to be installed on after coordinate transformation following the (k+1)-th iteration. The coordinates of the i-th scanning point of the target center of the volute segment to be installed after coordinate transformation following the k-th iteration.

[0064] S55: Repeat S53-S54. If the average change of the difference between the scanning point coordinates of the volute segment nozzle after the current iteration and the scanning point coordinates of the volute segment nozzle after the next iteration is less than the preset threshold, or if the iteration reaches 100 iterations, the process will terminate. The first optimal transformation obtained will be taken as the final first optimal transformation.

[0065] In S55, the average change of the difference between the scanning point coordinates of the volute segment to be installed after the current iteration and the scanning point coordinates of the volute segment to be installed after the next iteration is less than the preset threshold, as shown in formula (12), or it will terminate after 100 iterations, and the first optimal transformation obtained will be used as the final first optimal transformation.

[0066] (12),

[0067] In formula (12), The average change The number of scan points, This represents the coordinates of the i-th scanning point at the inlet of the volute segment to be installed after coordinate transformation following the (k+1)-th iteration. The corresponding coordinates of the scanning points of the volute segment to be installed in the target reference datum are determined;

[0068] In this embodiment, the preset threshold is 0.1 mm. The first optimal transformation refers to the final rotation matrix and translation vector.

[0069] S6: Obtain the final coordinates of the target center point of the target segment to be installed. As the first installation instruction;

[0070] In this embodiment, initially, the adjustment piles have been given a preliminary elevation according to the design theoretical values. The first installation command is mainly used to guide the adjustment of the vertical plane position of the volute segment to be installed. The final target point of the target center of the volute segment to be installed is also the target center point of the target segment in the target attitude.

[0071] S7: The second optimal transformation is obtained by using the target center scan point set under the initial attitude of the volute segment to be installed and the target center target point set of the volute segment to be installed.

[0072] Specifically, S7 also includes the following steps:

[0073] In this embodiment, the second optimal transformation step in S7 is partially the same as the first optimal transformation step in S5.

[0074] S71: The target center point set under the target attitude of the volute segment to be installed is used as the target reference benchmark for the ICP algorithm, as shown in formulas (13) and (14).

[0075] (13)

[0076] (14)

[0077] In formulas (13) and (14), The coordinates of the target center point are given under the target attitude of the volute segment to be installed. These are the x, y, and vertices of the target center point in the target attitude of the volute segment to be installed;

[0078] S72: Search for the point in the target reference datum that corresponds to the target center scanning point in the initial installation state of the volute segment to be installed, as shown in formula (15).

[0079] (15)

[0080] In formula (15), To determine the coordinates of the target center scanning point in the target reference datum for the initial attitude of the searched volute segment to be installed, The coordinates of the target center scanning point under the initial attitude of the volute segment to be installed. The coordinates of the target center point are given under the target attitude of the volute segment to be installed;

[0081] S73: By using the coordinates of the target center scanning point in the target reference datum under the initial attitude of the searched volute segment to be installed and the target center scanning point in the initial installation state of the volute segment to be installed, the decentralized coordinates of the target center scanning point in the target reference datum under the initial attitude of the searched volute segment to be installed and the decentralized coordinates of the target center scanning point in the initial installation state of the volute segment to be installed are obtained, as shown in formulas (16) and (17).

[0082] (16)

[0083] (17)

[0084] In formulas (16) and (17), To decenter the coordinates of the target center scanning point in the target reference datum for the initial attitude of the searched volute segment to be installed, To determine the coordinates of the target center scanning point in the target reference datum for the initial attitude of the searched volute segment to be installed, To determine the centroid of the target center scanning point in the target reference datum at the initial attitude of the searched volute segment to be installed, The decentralized coordinates of the target center scanning point in the initial installation state of the volute segment to be installed. The target center scanning point is the initial installation state of the volute segment to be installed. The centroid of the target center scanning point is set in the initial installation state of the volute segment to be installed;

[0085] S74: Construct a covariance matrix by using the decentralized coordinates of the target center scanning point in the target reference datum under the initial attitude of the target segment to be installed and the decentralized coordinates of the target center scanning point under the initial installation state of the target segment. Then, perform singular value decomposition on the covariance matrix to obtain the rotation matrix and translation matrix, as shown in formulas (18), (19), (20), and (21).

[0086] (18)

[0087] (19)

[0088] (20)

[0089] (twenty one),

[0090] In formulas (18), (19), (20), (21), Let covariance matrix be the variance matrix. The decentralized coordinates of the target center scanning point in the initial installation state of the volute segment to be installed. To decenter the coordinates of the target center scanning point in the target reference datum for the initial attitude of the searched volute segment to be installed, This is the transpose of the matrix. , These are the left and right singular vectors, respectively. It is a diagonal matrix. For rotation matrix, It is a translation matrix.

[0091] S8: The second installation command is obtained by adjusting the initial coordinates of the pile support point through the second optimal transformation. This command is used to guide the three-dimensional adjustment of the pile, and thus to guide the position adjustment of the volute segment to be installed.

[0092] Specifically, S8 also includes the following steps:

[0093] S81: The target coordinates of the adjusted pile support point are calculated by adjusting the initial coordinates of the adjusted pile support point through the second optimal transformation, as shown in formulas (22), (23), (24), and (25).

[0094] (twenty two),

[0095] (twenty three),

[0096] (twenty four),

[0097] (25)

[0098] In formulas (22), (23), (24), (25), This is a set of coordinates for multiple adjustment pile support points. Initial coordinates for each adjustment pile support point, To adjust the target coordinates of the pile support points, Initial coordinates for each adjustment pile support point, For rotation matrix, It is a translation vector. These represent the initial x-coordinate, y-coordinate, and vertices of the adjustment pile support point. These are the x-coordinate, y-coordinate, and vertical coordinates of the target coordinates of the adjustment pile support point, respectively.

[0099] In this embodiment, the rotation matrix Translation vector These are the rotation matrix and translation vector in the second optimal transformation, respectively.

[0100] S82: The elevation adjustment amount of the adjusting pile is obtained by adjusting the target coordinates and the initial coordinates of the adjusting pile support point. The plane adjustment amount of the adjusting pile is obtained by adjusting the plane XY coordinates in the target coordinates and the plane XY coordinates in the initial coordinates of the adjusting pile support point, as shown in formulas (26) and (27).

[0101] (26)

[0102] (27)

[0103] In formulas (26) and (27), The elevation adjustment required for the adjustment pile is as follows: This refers to the horizontal adjustment amount of the adjustment pile in the XY coordinate system.

[0104] S83: The elevation and horizontal adjustment of the adjusting piles are used as the second installation command to guide the three-dimensional adjustment of the adjusting piles, which in turn guides the position adjustment of the volute segment to be installed.

[0105] S9: Repeat S2-S8 to install the remaining volute segments to complete the volute installation.

[0106] The above embodiments are merely preferred embodiments of the present invention and should not be construed as limiting the scope of protection of the present invention. Any non-substantial changes and substitutions made by those skilled in the art based on the present invention shall fall within the scope of protection claimed by the present invention.

Claims

1. A method for intelligent installation of a volute based on three-dimensional laser scanning, characterized in that: Includes the following steps: S1: Establish a three-dimensional coordinate measurement control network with the centerline of the width direction of the hydropower station unit as the X-axis, the centerline of the length direction of the hydropower station unit as the Y-axis, and the elevation benchmark point of the hydropower station unit as the Z-axis, and establish multiple adjustment piles with the measurement control network as the coordinate system; S2: The initial elevation of the adjusting pile is given according to the design theoretical value. Then, the volute segment to be installed is placed on the corresponding adjusting pile to obtain the initial installation posture. S3: The pipe opening and adjustment pile support points of the installed volute segment are scanned by a 3D laser scanner to obtain the actual manufacturing shape point cloud data of the pipe opening of the installed volute segment and the initial coordinate set of multiple adjustment pile support points. S4: Place no fewer than three targets at intervals on the outer surface of the volute segment to be installed, and use a 3D laser scanner to perform multi-site scanning of the volute segment to be installed, thereby obtaining point cloud data of the volute segment containing the targets and the geometric information of the volute segment nozzle. S5: Obtain the first optimal transformation and the coordinates of the target center of the volute segment to be installed by using the point cloud data of the installed volute segment inlet and the point cloud data of the volute segment inlet to be installed. S6: Use the coordinates of the target center of the volute segment to be installed as the first installation command; S7: The second optimal transformation is obtained by using the target center scan point set under the initial attitude of the volute segment to be installed and the target center target point set of the volute segment to be installed. S8: The second installation command is obtained by adjusting the initial coordinates of the pile support point through the second optimal transformation. This command is used to guide the three-dimensional adjustment of the pile, and thus to guide the position adjustment of the volute segment to be installed. S9: Repeat S2-S8 to install the remaining volute segments to complete the volute installation.

2. The intelligent installation method for a volute based on three-dimensional laser scanning according to claim 1, characterized in that: S5 also includes the following steps: S51: Use the point cloud data of the installed volute segment pipe opening as the target reference benchmark for the ICP algorithm; S52: Search for the point in the target reference datum that corresponds to the scanning point of the nozzle of the volute segment to be installed; S53: Construct a covariance matrix by using the corresponding coordinate points of the nozzle scanning points of the volute segment to be installed in the target reference datum and the nozzle scanning points of the volute segment to be installed, and perform singular value decomposition on the covariance matrix to obtain the rotation matrix and translation vector. S54: Update the pose of the point cloud of the volute segment to be installed and the target center point cloud by using rotation matrix and translation vector; S55: Repeat S53-S54. If the average change of the difference between the scanning point coordinates of the volute segment nozzle after the current iteration and the scanning point coordinates of the volute segment nozzle after the next iteration is less than the preset threshold, or if the iteration reaches 100 iterations, the process will terminate. The first optimal transformation obtained will be taken as the final first optimal transformation.

3. The intelligent installation method for a volute based on three-dimensional laser scanning according to claim 2, characterized in that: In S51, the point cloud data of the installed volute segment pipe opening is constructed into a structured point cloud set through data integration, spatial alignment, redundancy reduction and noise reduction, and attribute fusion, as shown in formulas (1) and (2), and the point cloud set of the installed volute segment pipe opening is used as the target reference benchmark of the ICP algorithm. （1）， （2）， In formulas (1) and (2), The coordinates of the scanning point at the nozzle of the installed volute segment. The x-coordinate of the scanning point at the nozzle of the installed volute segment. The vertical coordinate of the scanning point at the nozzle of the installed volute segment is given. The vertical coordinates of the scanning points at the nozzles of the installed volute segment are given.

4. The intelligent installation method for a volute based on three-dimensional laser scanning according to claim 2, characterized in that: In S52, a point corresponding to the scanning point of the nozzle of the volute segment to be installed is searched in the target reference datum, as shown in formula (3). （3）， In formula (3), To determine the corresponding coordinates of the scanning point of the volute segment to be installed in the target reference datum, The first section of the volute segment to be installed Coordinates of each scan point For the first section of pipe with installed volute segment Coordinates of each scan point.

5. The intelligent installation method for a volute based on three-dimensional laser scanning according to claim 1, characterized in that: S53 also includes the following steps: S531: By using the corresponding coordinates of the searched volute segment inlet scanning point in the target reference datum and the volute segment inlet scanning point in the target reference datum, respectively, the decentralized coordinates of the searched volute segment inlet scanning point and the volute segment inlet scanning point in the target reference datum are obtained, as shown in formulas (4) and (5). （4）， （5）， In formulas (4) and (5), To decenter the coordinates of the corresponding coordinate points of the searched volute segment inlet in the target reference datum, The coordinates of the scanning point of the volute segment to be installed are located in the corresponding coordinate point of the target reference datum. To find the centroid of the corresponding coordinate points of the scanning points at the nozzles of the volute segment to be installed in the target reference datum, Decentralize the coordinates of the scanning points at the nozzles of the volute segment to be installed. This is the set of coordinates for the scanning points of the nozzle of the volute segment to be installed. Centroid of the scanning point at the nozzle of the volute segment to be installed; S532: Construct a covariance matrix using the decentralized coordinates of the scanning points at the nozzles of the installed volute segment and the scanning points of the nozzles of the volute segment to be installed, and then perform singular value decomposition on the covariance matrix to obtain the rotation matrix and translation vector, as shown in formulas (6), (7), (8), and (9). （6）， （7）， （8）， （9）， In formulas (6), (7), (8), (9), Let covariance matrix be the variance matrix. To decenter the coordinates of the corresponding coordinate points of the searched volute segment inlet in the target reference datum, Decentralize the coordinates of the scanning points at the nozzles of the volute segment to be installed. This is the transpose of the matrix. , These are the left and right singular vectors, respectively. It is a diagonal matrix. For rotation matrix, It is a translation vector.

6. The intelligent installation method for a volute based on three-dimensional laser scanning according to claim 2, characterized in that: In S54, the pose of the nozzle and target center point cloud of the volute segment to be installed is updated by rotation matrix and translation vector, as shown in formulas (10) and (11). （10）， （11）, In formulas (10) and (11), This represents the coordinates of the i-th scanning point at the inlet of the volute segment to be installed after coordinate transformation following the (k+1)-th iteration. It is a rotation matrix; The coordinates of the i-th scanning point of the volute segment nozzle to be installed are after the coordinate transformation following the k-th iteration. It is a translation vector; This represents the coordinates of the i-th scanning point at the center of the target segment to be installed on the volute after coordinate transformation following the (k+1)-th iteration. The coordinates of the i-th scanning point of the target center of the volute segment to be installed are obtained after the coordinate transformation following the k-th iteration.

7. The intelligent installation method for a volute based on three-dimensional laser scanning according to claim 2, characterized in that: In S55, the average change of the difference between the scanning point coordinates of the volute segment to be installed after the current iteration and the scanning point coordinates of the volute segment to be installed after the next iteration is less than the preset threshold, as shown in formula (12), or it will terminate after 100 iterations, and the first optimal transformation obtained will be used as the final first optimal transformation. （12）， In formula (12), The average change The number of scan points. This represents the coordinates of the i-th scanning point at the inlet of the volute segment to be installed after coordinate transformation following the (k+1)-th iteration. The corresponding coordinates of the scanning point of the volute segment to be installed are located in the target reference datum.

8. The intelligent installation method for a volute based on three-dimensional laser scanning according to claim 1, characterized in that: S7 also includes the following steps: S71: The target center point set under the target attitude of the volute segment to be installed is used as the target reference benchmark for the ICP algorithm, as shown in formulas (13) and (14). （13）， （14）， In formulas (13) and (14), The coordinates of the target center point are given under the target attitude of the volute segment to be installed. These are the x, y, and vertices of the target center point in the target attitude of the volute segment to be installed; S72: Search for the point in the target reference datum that corresponds to the target center scanning point in the initial installation state of the volute segment to be installed, as shown in formula (15). （15）， In formula (15), To determine the coordinates of the target center scanning point in the target reference datum for the initial attitude of the searched volute segment to be installed, The coordinates of the target center scanning point under the initial attitude of the volute segment to be installed. The coordinates of the target center point are given under the target attitude of the volute segment to be installed; S73: By using the coordinates of the target center scanning point in the target reference datum under the initial attitude of the searched volute segment to be installed and the target center scanning point in the initial installation state of the volute segment to be installed, the decentralized coordinates of the target center scanning point in the target reference datum under the initial attitude of the searched volute segment to be installed and the decentralized coordinates of the target center scanning point in the initial installation state of the volute segment to be installed are obtained, as shown in formulas (16) and (17). （16）， （17）， In formulas (16) and (17), To decenter the coordinates of the target center scanning point in the target reference datum for the initial attitude of the searched volute segment to be installed, To determine the coordinates of the target center scanning point in the target reference datum for the initial attitude of the searched volute segment to be installed, To determine the centroid of the target center scanning point in the target reference datum at the initial attitude of the searched volute segment to be installed, The decentralized coordinates of the target center scanning point in the initial installation state of the volute segment to be installed. The target center scanning point is the initial installation state of the volute segment to be installed. The centroid of the target center scanning point is set in the initial installation state of the volute segment to be installed; S74: Construct a covariance matrix by using the decentralized coordinates of the target center scanning point in the target reference datum under the initial attitude of the target segment to be installed and the decentralized coordinates of the target center scanning point under the initial installation state of the target segment. Then, perform singular value decomposition on the covariance matrix to obtain the rotation matrix and translation matrix, as shown in formulas (18), (19), (20), and (21). （18）， （19）， （20）， （21）， In formulas (18), (19), (20), (21), Let covariance matrix be the variance matrix. The decentralized coordinates of the target center scanning point in the initial installation state of the volute segment to be installed. To decenter the coordinates of the target center scanning point in the target reference datum for the initial attitude of the searched volute segment to be installed, This is the transpose of the matrix. , These are the left and right singular vectors, respectively. It is a diagonal matrix. For rotation matrix, It is a translation matrix.

9. The intelligent installation method for a volute based on three-dimensional laser scanning according to claim 1, characterized in that: S8 also includes the following steps: S81: The target coordinates of the adjusted pile support point are calculated by adjusting the initial coordinates of the adjusted pile support point through the second optimal transformation, as shown in formulas (22), (23), (24), and (25). （22）， （23）， （24）， （25）， In formulas (22), (23), (24), (25), This is a set of coordinates for multiple adjustment pile support points. Initial coordinates for each adjustment pile support point, To adjust the target coordinates of the pile support points, Initial coordinates for each adjustment pile support point, For rotation matrix, It is a translation vector. These represent the initial x-coordinate, y-coordinate, and y-coordinate of the adjustment pile support point. These are the x-coordinate, y-coordinate, and vertical coordinates of the target coordinates of the adjustment pile support point, respectively. S82: The elevation adjustment amount of the adjusting pile is obtained by adjusting the target coordinates and the initial coordinates of the adjusting pile support point. The plane adjustment amount of the adjusting pile is obtained by adjusting the plane XY coordinates in the target coordinates and the plane XY coordinates in the initial coordinates of the adjusting pile support point, as shown in formulas (26) and (27). （26）， （27）， In formulas (26) and (27), The elevation adjustment required for the adjustment pile is as follows: This refers to the planar adjustment amount of the adjustment pile in the XY coordinate system; S83: The elevation and horizontal adjustment of the adjusting piles are used as the second installation command to guide the three-dimensional adjustment of the adjusting piles, which in turn guides the position adjustment of the volute segment to be installed.

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