Wind power mixed tower pipe piece three-dimensional laser combined detection method

Abstract

The present application relates to the technical field of wind power hybrid tower pipe piece quality detection and deformation measurement, and discloses a wind power hybrid tower pipe piece three-dimensional laser combined detection method.The method comprises the following steps: arranging a mark ball on a to-be-detected wind power hybrid tower pipe piece, obtaining a deviation cloud picture of the surface deformation of the pipe piece by using a phase three-dimensional laser scanner based on the mark ball, and obtaining the point coordinates of the mark ball by using a pulse laser tracker; converting the deviation cloud picture to a global coordinate, correcting the deviation cloud picture according to the point coordinates to obtain a corrected deviation cloud picture; obtaining the corrected deviation cloud pictures of all ring spliced to-be-detected wind power hybrid tower pipe pieces, and judging whether the quality of the to-be-detected wind power hybrid tower pipe piece is qualified.The method solves the problem that the existing single measurement method cannot effectively and accurately measure the quality of the wind power hybrid tower pipe piece.

Description

Technical Field

[0001] This invention relates to the field of wind power hybrid tower segment quality inspection and deformation measurement technology, and in particular to a method for accurate deformation detection of wind power hybrid tower segments at the factory stage based on a combination of pulse and phase three-dimensional laser scanning technology. Background Technology

[0002] Currently, during the manufacturing process of wind turbine hybrid tower segments, problems such as insufficient mold support rigidity often occur. During concrete pouring and solidification, the segments are prone to inward tilting or outward overturning, resulting in significant misalignment of the circumferential and vertical joints between the quarter segments after on-site ring hoisting, which affects installation accuracy and structural integrity.

[0003] Phase scanning generates high-density point clouds, which have the advantage of complete surface coverage and high point density. However, its coordinates are usually derived from the stitching of local coordinates from multiple stations, making it susceptible to the effects of station layout, surface reflectivity, ambient light, initial ICP values, and cumulative stitching errors. Pulse measurement generates a small number of high-precision target point coordinates, which have the advantage of accurate key point positioning and stable absolute scale, but cannot express the overall deformation of the continuous curved surface of the tunnel segment. Furthermore, the two types of data have different data densities, coordinate sources, error distributions, and applicable objects, and cannot be directly added or simply superimposed.

[0004] Wind turbine hybrid tower segments are large-sized, curved precast concrete components. Their surfaces lack stable natural features, and key areas such as vertical joints, circumferential joints, bolt holes, and edge points exhibit occlusion and curvature variations. If only conventional point cloud registration is used, inconsistencies easily arise between the overall cloud map and the positions of key joints. If only key point measurements are used, it is impossible to obtain six-region deviation cloud maps and local deformation distributions. Neither of the existing measurement methods can accurately detect deformation issues when applied to the quality inspection of wind turbine hybrid tower segments. Summary of the Invention

[0005] This invention provides a three-dimensional laser combined inspection method for wind turbine hybrid tower segments to solve the problem that existing single measurement methods cannot effectively and accurately measure the quality of wind turbine hybrid tower segments.

[0006] To achieve the above objectives, the present invention employs the following technical solution:

[0007] This invention provides a three-dimensional laser joint inspection method for wind turbine hybrid tower segments, comprising the following steps: For the wind power hybrid tower segments under test, marker balls are deployed. Based on the marker balls, phase-type three-dimensional laser scanning is used to obtain the deviation cloud map of the segment surface deformation, and pulse-type laser tracking is used to obtain the point coordinates of the marker balls. Convert the deviation cloud map to global coordinates, and correct the deviation cloud map based on the point coordinates to obtain the corrected deviation cloud map; Obtain the corrected deviation cloud map of all the wind turbine hybrid tower segments to be tested, and determine whether the quality of the wind turbine hybrid tower segments to be tested is qualified.

[0008] Based on the above design, addressing quality issues such as geometric deformation, circumferential joint misalignment, and vertical joint misalignment that are prone to occur during the production and hoisting of existing tunnel segments, a phase-type 3D laser scanning system and a pulsed laser tracking measurement system are proposed to respectively acquire surface point clouds and perform high-precision measurements of key points on the tunnel segments, achieving comprehensive and high-precision acquisition of segment geometric information. Compared with traditional manual point measurement or single scanning techniques, this approach achieves a balance between measurement efficiency and accuracy during tunnel segment inspection, providing fundamental data support for subsequent deformation analysis and quality control.

[0009] Furthermore, the number of marker balls is not less than four, and at least three marker balls are not collinear.

[0010] Furthermore, the marker balls are placed on the left edge, right edge, top, bottom, joint, and bolt holes of the wind turbine hybrid tower segment to be tested.

[0011] By setting constraints on the position and number of marker balls through the above design, the acquired data and subsequent global coordinate transformation and correction are more accurate, thereby improving the accuracy of wind power hybrid tower segment quality inspection.

[0012] Furthermore, two or more reflective spheres are placed on the measuring base of the phase scanner or the testing frame of the wind turbine tower segment to be tested.

[0013] The above design addresses the issues of inconsistent spatial coordinate systems and accumulated registration errors among different measuring devices. A shared global coordinate framework is constructed by placing distinctive reflective markers on the tunnel segment surface and the station base. The phase-based system determines the point cloud positional relationships using an angle encoder and phase difference calculation, while the pulse-based system obtains the absolute coordinates of key control points using marker spheres. Both systems are spatially registered under the constraint of unified markers. By minimizing the residuals between the two sets of data at the markers, high-precision alignment and unification of the point clouds in space are achieved. This avoids the positioning deviations caused by traditional manual registration, ensuring that the two scanning data have a consistent geometric reference within the same coordinate system, guaranteeing high spatial accuracy and good morphological continuity in the fused point cloud model.

[0014] Furthermore, the phase-type three-dimensional laser scanning includes the following steps: scanning the wind power hybrid tower segment to be tested multiple times to obtain multiple point cloud data; stitching the multiple point cloud data together based on the coordinates of the marker ball in the multiple point cloud data to obtain overall point cloud data; and calculating the deviation cloud map based on the overall point cloud data and the design model of the wind power hybrid tower segment to be tested.

[0015] Through the above design, the error caused by a single measurement is eliminated by taking multiple measurements. The marker ball placed on the wind turbine tower segment under test is used as a positioning point to eliminate the error generated during the stitching of multiple point cloud data, which effectively improves the accuracy of the final overall point cloud data.

[0016] Furthermore, after acquiring the overall point cloud data, the ICP iterative nearest point algorithm is used to eliminate the error in the overall point cloud data. The overall point cloud data after eliminating the error is then preprocessed and the deviation cloud map is calculated with the design model of the wind power hybrid tower segment to be tested.

[0017] Through the above design, the ICP iterative nearest point algorithm is used to eliminate the errors generated in the scanning and stitching process, further optimizing the accuracy of the overall point cloud data.

[0018] Furthermore, the preprocessing includes removing outliers, removing noise, filtering out background environmental points, and homogenizing points.

[0019] Through the above design, higher quality and higher density overall point cloud data were obtained, noise effects were eliminated, and the error rate of final quality inspection was reduced.

[0020] Furthermore, the pulsed laser tracking includes the following constraints: The marker ball is measured at least three times, and the standard deviation of the coordinates of the points measured each time is less than 0.05 mm; The measured echo intensity reaches the preset effective value of the measuring equipment; The registration residual of the reflective spheres deployed on the measuring base or testing frame is less than 0.2 mm.

[0021] The above design eliminates potential errors during pulsed laser tracking and effectively removes abnormal points from the coordinate system.

[0022] Furthermore, the global coordinates are constructed based on the design model or testing jig of the wind turbine hybrid tower segment to be tested; Using the center of the design model or testing frame as the origin of the coordinate system, the tower axis of the wind power hybrid tower segment under test as the Z-axis, the reference direction of the mid-baseline or midpoint of the wind power hybrid tower segment under test as the X-axis, and the circumferential tangent direction of the wind power hybrid tower segment under test as the Y-axis.

[0023] Furthermore, the step of converting the deviation cloud map to global coordinates includes: establishing an objective function about the point coordinates and the corresponding reflection sphere in the deviation cloud map by minimizing the sum of squared residuals, and converting the deviation cloud map to global coordinates under the constraint of point coordinates based on the objective function; The objective function is expressed by the following formula: ; in, Indicates weight; Represents the rotation matrix; The point represents the translation vector of the corresponding reflection sphere in the deviation cloud diagram, along with its coordinates. Indicates the coordinates of the point; This indicates the corresponding deviation contour map. The coordinates.

[0024] The above design constrains the process of converting the deviation cloud map to global coordinates based on the point coordinates, providing a spatial basis for subsequent correction of the deviation cloud map using point coordinates, and avoiding erroneous corrections from affecting the final quality inspection.

[0025] Furthermore, the step of correcting the deviation cloud map based on the point coordinates includes: calculating the common target residual between the point coordinates in the global coordinates and the deviation cloud map; if the common target residual is greater than a preset value, the corresponding marker ball is removed, and the deviation cloud map is re-converted to the global coordinates based on the point coordinates; if it is less than the preset value, the coordinates of the corresponding marker ball meet the requirements.

[0026] Furthermore, the obtained corrected deviation cloud map is used to represent the deviation with different color distributions, and a deviation statistics table and feature point error curves are generated based on the corrected deviation cloud map.

[0027] Through the above design, the geometric deformation of the tunnel segments is presented intuitively during the data analysis phase. First, the fused 3D point cloud model is spatially aligned with the original design model in a unified coordinate system. Then, the distance deviation between each measurement point and the surface of the design model is calculated. Phase-based scanning data provides geometric deviation information for continuous surface regions, while pulse-based data provides precise deviation constraints for key points. After integrating the calculation results from both, the system generates a deviation cloud map in the form of a color distribution and outputs a deviation statistics table and feature point error curves, thus clearly identifying local deformation features such as inward tilting, outward bulging, and vertical seam misalignment of the tunnel segments. This technological innovation significantly improves the visualization and digital analysis capabilities of the inspection results, shifting quality inspection from traditional point measurement and experience-based judgment to full 3D quantitative analysis, providing an intuitive basis for quality assessment and on-site installation control of hybrid tower tunnel segments.

[0028] Furthermore, the process of determining whether the quality of the wind turbine hybrid tower segments under test is qualified includes the following steps: The correction deviation cloud map of all the wind power hybrid tower segments to be tested is divided into zones. The misalignment of each wind power hybrid tower segment to be tested is obtained in combination with the design model. The quality of the wind power hybrid tower segment to be tested is judged based on the misalignment.

[0029] Furthermore, the misalignment includes the misalignment on both sides and the misalignment at the top. The misalignment on both sides is calculated based on the coordinates of the splicing joint of the two wind turbine hybrid tower segments under test at the same height. The top misalignment is calculated based on the bottom coordinate deviation, top coordinate deviation, and assembly error of the wind turbine hybrid tower segment under test.

[0030] It is understandable that the misalignment amount is obtained based on the deviation amount of each zone, and the deviation amount can be obtained based on the corrected deviation cloud map and the design model of the wind power hybrid tower segment under test. When the deviation is positive, it indicates that the corrected deviation cloud map is outward or deviated from the design model. When the deviation is negative, it indicates that the corrected deviation cloud map is inward or deviated from the design model. If the deformation directions on both sides of the vertical seam are the same when two wind turbine hybrid tower segments are assembled, the deviation will be either positive or negative. The misalignment on both sides is the difference of the absolute values ​​of the corresponding deviations or the remaining amount after offsetting. If the deformations are opposite, the misalignment on both sides is the sum of the absolute values ​​of the corresponding deviations. The bottom misalignment is manually adjusted to 0 during installation and will be reflected in the top misalignment through posture compensation. Therefore, the top misalignment is the sum of the bottom coordinate deviation, the top coordinate deviation, and the assembly error.

[0031] Beneficial effects: This invention provides a three-dimensional laser joint inspection method for wind turbine hybrid tower segments. It introduces a combined phase-based and pulse-based three-dimensional laser scanning measurement system, resolving the technical contradiction between accuracy and range in traditional single-measurement methods. The phase-based scanning system boasts high resolution and high sampling density, enabling it to acquire full-coverage point cloud data of the segment's outer surface in a short time, reflecting the overall geometry and minor local deformations. The pulse-based system utilizes the laser time-of-flight ranging principle to perform high-precision spatial positioning of key control points on the segment (such as edge points, joint positions, and arc-shaped bolt holes). After registration using a unified coordinate system, the two types of data form a complementary "area + point" structure, achieving high accuracy and full coverage of the inspection results. This technical approach balances spatial breadth and precision depth, significantly improving the reliability and engineering adaptability of wind turbine hybrid tower segment factory inspection without increasing measurement time. Attached Figure Description

[0032] Figure 1 This is a flowchart of the three-dimensional laser joint inspection method for wind power hybrid tower segments in Example 1; Figure 2 This is a schematic diagram of the segment division in Example 1; Figure 3 This is a flowchart of a phase-based 3D laser scanner measurement method. Figure 4 The point cloud results show the deviation between the phase-type 3D laser scanner scanning the tube segment and the design model. Figure 5 This is a list of point cloud results showing the deviation between the phase-type 3D laser scanner scanning the tube segment and the design model. Figure 6 This is a flowchart of the measurement method for a pulsed laser tracker. Figure 7 The results show the key point deviations between the tube segment scanned by the pulsed laser tracker and the design model. Figure 8 This is a table showing the key point values ​​of the tube segment after scanning with a pulsed laser tracker and comparing them with the design model. Detailed Implementation

[0033] The technical solution of the present invention will be clearly and completely described below. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0034] Example 1 Embodiment 1 of this application provides a three-dimensional laser joint inspection method for wind turbine hybrid tower segments, including the following steps: Step 1: Place marker balls on the tunnel segments of the wind turbine tower under test. Based on the marker balls, use phase-type three-dimensional laser scanning to obtain the deviation cloud map of the surface deformation of the tunnel segments, and use pulse-type laser tracking to obtain the position coordinates of the marker balls. For the deployment of marker balls, there shall be no less than four, and at least three of the marker balls shall be non-collinear, and shall be deployed on the left edge, right edge, top, bottom, joint and bolt holes of the wind turbine hybrid tower segment to be tested. In order to improve the accuracy of subsequent global coordinate transformation, two or more reflective balls shall be deployed on the measuring base of the phase scanner or the testing jig of the wind turbine hybrid tower segment to be tested.

[0035] The process for obtaining the deviation cloud map includes the following steps: scanning the wind turbine hybrid tower segment under test multiple times to obtain multiple point cloud data; stitching the multiple point cloud data together based on the coordinates of the marker sphere in the multiple point cloud data to obtain the overall point cloud data; using the ICP iterative nearest point algorithm to eliminate the error of the overall point cloud data; preprocessing the overall point cloud data after eliminating the error; and then calculating the deviation cloud map with the design model of the wind turbine hybrid tower segment under test.

[0036] The preprocessing includes: removing outliers, removing noise, filtering out background points, and homogenizing points.

[0037] For pulsed laser tracking, the following constraints apply: The marker ball is measured at least three times, and the standard deviation of the coordinates of the points measured each time is less than 0.05 mm; The measured echo intensity reaches the preset effective value of the measuring equipment; The registration residual of the reflective spheres deployed on the measuring base or testing frame is less than 0.2 mm.

[0038] Step 2: Convert the deviation cloud map to global coordinates, and correct the deviation cloud map according to the point coordinates to obtain the corrected deviation cloud map; When converting the deviation cloud map to global coordinates, the global coordinates are constructed based on the design model or testing jig of the wind power hybrid tower segment to be tested. Specifically, the center of the design model or testing jig is used as the origin of the coordinates, the tower axis of the wind power hybrid tower segment to be tested is used as the Z-axis, the reference direction of the mid-baseline or midpoint line of the wind power hybrid tower segment to be tested is used as the X-axis, and the circumferential tangent direction of the wind power hybrid tower segment to be tested is used as the Y-axis.

[0039] For the specific conversion process, the objective function of minimizing the sum of squared residuals is established with respect to the point coordinates and the corresponding reflection sphere in the deviation cloud map. Based on the objective function, the deviation cloud map is converted to global coordinates under the point coordinate constraints. The objective function is expressed by the following formula: ; in, Indicates weight; Represents the rotation matrix; The point represents the translation vector of the corresponding reflection sphere in the deviation cloud diagram, along with its coordinates. Indicates the coordinates of the point; This indicates the corresponding deviation contour map. The coordinates.

[0040] After converting to global coordinates, the common target residual between the point coordinates and the deviation cloud map in global coordinates is calculated. If the common target residual is greater than the preset value, the corresponding marker ball is removed, and the conversion of the deviation cloud map to global coordinates based on the point coordinates is performed again. If it is less than the preset value, the coordinates of the corresponding marker ball meet the requirements, and the corrected deviation cloud map is finally obtained.

[0041] The obtained corrected deviation cloud map represents the deviation with different color distributions, and a deviation statistics table and feature point error curves are generated based on the corrected deviation cloud map; Step 3: Obtain the corrected deviation cloud map of all the ring-mounted wind turbine hybrid tower segments to be tested, and determine whether the quality of the wind turbine hybrid tower segments to be tested is qualified.

[0042] Specifically, the correction deviation cloud map of all the wind power hybrid tower segments to be tested is divided into zones, and the misalignment of each wind power hybrid tower segment to be tested is obtained in combination with the design model. Based on the misalignment, it is determined whether the quality of the wind power hybrid tower segment to be tested is qualified. Please see Figure 2The partitioning refers to dividing the correction deviation cloud map into six regions: top left, top middle, top right, bottom left, bottom middle, and bottom right. In other embodiments, it can also be divided into other numbers of partitions based on the measurement accuracy. After partitioning, the maximum deviation of the partition can be directly obtained as the deviation of the partition.

[0043] The misalignment includes the misalignment on both sides and the misalignment at the top. The misalignment on both sides is calculated based on the coordinates of the splice joint of the two wind turbine hybrid tower segments under test at the same height. The top misalignment is calculated based on the bottom coordinate deviation, top coordinate deviation, and assembly error of the wind turbine hybrid tower segment under test.

[0044] Example 2 In Embodiment 2, the present invention provides a specific process for phase-based three-dimensional laser scanning. It is understood that Embodiment 2 only provides one method for obtaining a deviation cloud map, and in other embodiments, different devices can be used, as long as their methods and processes are substantially the same as those in Embodiment 2, to obtain the deviation cloud map.

[0045] Please see Figure 3 In Example 2, a phase-modulated three-dimensional laser scanning system is used to acquire high-density point clouds on the outer surface of the tube segment. This system consists of a phase-modulated scanner body, an angle encoder, a data acquisition and processing unit, a marker point positioning system, a tripod support device, and scanning control software. The scanner body integrates a phase-modulated laser transmitter and receiver, a signal amplification module, and primary data processing circuitry. Its working principle is to emit a continuous-wave modulated laser, which, after illuminating the surface of the tube segment being measured, is reflected back to the receiver. The distance to the measured point is calculated by comparing the phase difference between the emitted and received signals. A precision optical system is installed within the main body shell to ensure stable laser beam emission direction, small spot size, and low beam divergence angle, thereby improving measurement accuracy and spatial resolution.

[0046] An angle encoder is used to accurately measure the rotation angle of the scanning head in the horizontal and vertical directions. The encoder acquires the rotation angle information of the scanning head in real time through high-precision optical or magnetic grating elements, and the measurement accuracy can reach the arcsecond level. The horizontal and pitch angle information is acquired synchronously with the distance measurement value, and the spatial coordinates of the marker ball can be obtained after coordinate transformation.

[0047] The data acquisition and processing unit synchronously acquires, buffers, and performs preliminary calculations on laser ranging signals and angle information. Internally, it includes a high-frequency analog-to-digital converter, a signal synchronization module, an embedded processor, and a storage module. During acquisition, this unit filters, amplifies, and digitizes the raw signal, and calculates the 3D coordinates of points in real time according to the scanning angle sequence, generating preliminary point cloud data. After acquisition, the data is transmitted to an external computing terminal via wired or wireless means for further point cloud registration, coordinate transformation, and deviation analysis.

[0048] The marker positioning system is used to achieve spatial consistency and alignment between multi-station scans. Multiple marker spheres with high reflectivity and high recognizability are pre-deployed in the survey area. These marker spheres are collected during each station's scan and used to stitch together and unify the coordinates of the multi-station cloud data through spatial rigid body transformation or ICP algorithms. The positions of the marker points are precisely determined and serve as references for the global coordinate system, ensuring spatial consistency and overall accuracy of data across different scan locations.

[0049] Tripod support equipment provides a stable platform for phase scanners, featuring height and level adjustments as well as shock absorption, enabling the instrument to remain stable in complex construction sites. Understandably, to avoid angular errors and point cloud misalignment caused by minute instrument displacements, tripods are typically placed in areas with a wide field of view that cover the tunnel lining segments to obtain complete point cloud coverage.

[0050] The scanning control software is used to control parameter settings, process monitoring, and data management throughout the scanning process. The software interface provides functions such as station settings, scanning range, angular resolution, measurement mode, marker point identification, and registration. After the operator selects the appropriate resolution and scanning range in the software interface, the system controls the scanning head to perform point-by-point measurements according to the set angular steps, and displays the scanning progress and point cloud preview in real time. After scanning is completed, the software also performs preliminary registration, noise reduction, and formatting of the point cloud data from each station, providing a high-quality data foundation for subsequent deviation calculations.

[0051] The measurement principle of a phase-based 3D laser scanner is described below, assuming the phase difference is... The modulation wavelength is ,distance The calculation formula is: ; The instrument simultaneously acquires the horizontal angle with vertical angle By converting between spherical and rectangular coordinates, the three-dimensional coordinates of a point can be obtained: ; in, This represents the instrument's position in the global coordinate system. In actual operation, the scanner is deployed at multiple locations around the segment, covering the entire outer surface of the segment. After setting the scanning range and resolution via software, high-speed scanning is performed automatically. Phase scanning can acquire a large amount of high-density point cloud data in a short time, enabling rapid acquisition of geometric information of the segment's outer surface and providing a complete geometric data foundation for subsequent deviation analysis.

[0052] Combining the instrument's position and orientation in the global coordinate system, and using the rigid body transformation matrix... Transform the point cloud to the global coordinate system: ; Through multi-station scanning and marker registration, a high-density point cloud dataset covering the entire outer surface of the pipe segment is formed.

[0053] The deviation calculation for phase scanning is based on the closest distance between the point cloud and the surface of the design model. For any point in the point cloud... On the surface of the design model Find the nearest point Deviation value Defined as: ; The direction of deviation is determined by the relationship between point cloud points and the normal to the model surface; a positive deviation indicates the point is biased towards the outside of the model, while a negative deviation indicates inward concavity. Calculations are performed for all points. Furthermore, a deviation cloud map is generated using a color mapping method based on the deviation value range, thereby providing an intuitive presentation of the overall deformation distribution on the surface of the pipe segment.

[0054] The testing process includes station setup, instrument installation and calibration, scanning parameter settings, data acquisition, multi-station stitching, and point cloud preprocessing. First, based on the spatial location and geometric dimensions of the tested pipe segment, several station locations with open fields of view covering the entire outer surface of the segment are selected around it. Several high-reflectivity marker spheres are then placed on the site as registration reference points. The positions of these marker points should ensure that they can be identified by the scanner within the field of view of multiple stations, facilitating unified coordinate registration of multi-station data. Next, the phase scanner is mounted on a tripod, and the height and level of the tripod are adjusted to ensure the scanner is stable and free from external vibration interference. After instrument installation, initial calibration is performed using the scanning control software. The calibration process includes instrument self-check, horizontal reference adjustment, and angle encoder zero-point correction to ensure that distance and angle measurement accuracy meets requirements. After calibration, measurement parameters are set in the scanning software, including scanning range, horizontal and vertical resolution, measurement mode, and laser power. For deformation detection of tunnel segments, a high angular resolution is required to obtain sufficiently dense point cloud data. Simultaneously, the laser power is adjusted based on ambient lighting and surface reflection to ensure signal reception quality. During data acquisition, the scanner automatically rotates its scanning head according to a set angular stepping pattern, emitting a modulated laser beam and receiving reflected signals. The spatial coordinates of each sampling point are calculated in real time by measuring the phase difference and angle information. The scanning software simultaneously displays the scanning progress and point cloud preview during acquisition, facilitating operator monitoring of the acquisition effect. If necessary, parameters can be paused or adjusted to optimize data quality. After scanning one station, the instrument is moved to the next station, and the installation, calibration, and acquisition steps are repeated until the entire tunnel segment surface is covered. After scanning all stations, a marker point positioning system is used to spatially register the point cloud data from multiple stations. The software automatically identifies marker points in each station's point cloud and calculates the rigid body transformation matrix, unifying all station point clouds into the same global coordinate system. For cases with slight errors, the stitching accuracy can be further optimized using the ICP (Iterative Closest Point) algorithm. After registration, the point cloud is preprocessed, including removing outliers and noise, filtering background points, and homogenizing point density to generate high-quality, high-density 3D point cloud data covering the entire outer surface of the tunnel segment. Finally, by aligning the point cloud with the design model in space, the deviation between the point cloud and the model surface is calculated to obtain the numerical distribution and deviation cloud map of the tunnel segment surface deformation.

[0055] The concave or bulging regions are distinguished based on the sign of the deviation and its relationship with the normal, and a deviation cloud map is generated through color mapping, such as... Figure 4 As shown, the deviation contour map clearly displays the geometric deformation distribution of the tunnel segment, including features such as inclination, outward bulging, and misalignment. Based on this, the deviation amount at any point in the scanned area on the contour map can be identified and exported in list form, such as... Figure 5 As shown, this method achieves full-coverage, high-resolution detection of the segment geometry, providing fundamental data support for subsequent quality control and installation posture adjustment.

[0056] Example 3 In Example 3, the present invention provides a specific process for pulsed laser tracking and the correction and fusion of point coordinates and deviation cloud map data. It is understood that Example 3 only provides one method for obtaining the point coordinates of the marker ball and the correction and fusion of the point coordinates and deviation cloud map data. In other examples, different devices can be used, as long as their methods and processes are substantially the same as those in Example 2, to obtain the point coordinates of the marker ball.

[0057] Please see Figure 6 In Example 2, a pulsed laser tracker is used to acquire the coordinates of the marker sphere, enabling high-precision measurement of key control points of the tunnel segments (such as edge points, joints, and arc bolt holes). The pulsed system consists of a laser transmitting and receiving unit, an angle measurement module, a marker sphere, data acquisition software, and a stable base. These components work together to achieve high-precision spatial coordinate measurement of key control points of the wind turbine hybrid tower tunnel segments.

[0058] The laser transmitting and receiving unit is the core of the pulsed measurement system, integrating a high-frequency pulsed laser, a collimating optical system, a receiving lens, and a high-precision time measurement circuit. During operation, this unit emits a short-pulse laser beam to illuminate a marker sphere; the laser beam returns to the receiver after total internal reflection from the marker sphere. The system calculates the distance between the marker sphere and the instrument by measuring the time difference of the laser's round-trip propagation and combining this with the speed of light. During measurement, the transmitting and receiving unit needs to perform initial laser alignment, accurately aligning the emitted beam with the marker sphere under test to ensure the echo signal intensity reaches a preset threshold, thereby ensuring the stability and accuracy of the time measurement. The unit continuously monitors the echo signal quality during testing and automatically adjusts the gain to adapt to measurement requirements under different distances and surface reflection conditions.

[0059] The marker sphere is the target reflector for pulsed laser measurement. It is typically composed of a high-precision metal sphere coated with a total reflection coating or a pyramidal reflective structure, capable of accurately reflecting the incident laser back to the instrument's direction. In actual operation, the marker sphere is installed at key control points on the tunnel segment using magnetic mounts or brackets, such as the upper and lower ends of vertical seams, the edges of circumferential seams, or positioning reference holes. Operators position the marker sphere according to design requirements, ensuring its stable position and unobstructed reflective surface. During measurement, the laser tracker automatically searches, captures, and locks onto the marker sphere's reflected signal, enabling rapid and accurate distance and angle measurements.

[0060] The data acquisition and processing software controls the entire pulse measurement process, including instrument initialization, self-test, measurement parameter setting, real-time acquisition, and coordinate calculation. Operators set the measurement mode, sampling frequency, and marker ball indicators through the software interface. During the measurement process, the system displays the marker ball capture status, echo signal strength, and three-dimensional coordinate calculation results in real time. The software also provides automatic storage and export functions for measurement data, allowing for real-time or post-processing comparison of measured control point coordinates with design model coordinates, calculating deviations, and generating reports.

[0061] The stable base supports the entire laser tracking system and features height and level adjustments as well as shock absorption. During installation, operators must place the base on a firm, level surface and ensure its stability by adjusting the leveling screws and bubble level. Base stability directly impacts the accuracy of pulse measurements, especially during long-distance measurements and high-precision control point detection. The base effectively reduces measurement errors caused by environmental vibrations, ground subsidence, and other factors.

[0062] The measurement principle of a pulsed laser tracker is based on the time difference between laser emission and reflection. The formula for calculating distance is as follows: ; in, The speed of light. Combined with the azimuth angle measured in Example 2. With pitch angle Using the same coordinate transformation formula, the spatial position of the marker sphere in the global coordinate system can be obtained. In actual use, the tracker is placed at a stable position near the tunnel segment, and marker spheres are placed at predetermined key positions. The instrument automatically locks onto and tracks the target, obtaining high-precision point coordinates through continuous pulse ranging. These key point data can serve as a geometric benchmark for subsequent operations, providing a highly reliable reference for deformation analysis.

[0063] The deviation calculation for pulse-type measurements focuses on the displacement deviation of key points. Let the coordinates of the corresponding control points in the design model be... The measured coordinates of the control points are Then the deviation vector at that point Deviation from scalar They are defined as follows: ; Based on the location of key points within the segment structure, it can be further decomposed. The components in the tangential, radial, and axial directions are used to analyze specific deformation forms such as vertical seam misalignment, circumferential seam asymmetry, or overall eccentricity. Pulse measurement results have high single-point accuracy, which can provide a benchmark for the overall registration and model alignment of phase point clouds, and can also be directly used to determine the value and direction of local geometric errors.

[0064] The instrument emits pulsed laser light and receives the reflected signal from the marker ball. The time difference between the laser's round trip is measured. Calculate the distance and simultaneously collect the horizontal angle. and pitch angle And by combining the coordinate transformation formula, the spatial coordinates of each marker ball are transformed to the global coordinate system: ; After all key points have been measured, the software will register and compare the measured coordinates with the corresponding control point coordinates in the design model, and calculate the deviation vector for each key point. and scalar deviation The system can decompose the deviation vector into radial, tangential, and axial components as needed to analyze specific deformation characteristics such as vertical joint misalignment, circumferential joint offset, or overall eccentricity. Finally, the system generates tables or visualizations of the deviation results, providing reliable data for the quantitative assessment of segment geometric deformation.

[0065] The testing process includes station setup, instrument installation and calibration, target point placement, data acquisition, coordinate calculation, and data processing. First, based on the spatial dimensions and installation environment of the tunnel segment being tested, several station locations are selected around it, ensuring unobstructed views and coverage of key structural surfaces within the test area. Several high-reflectivity spherical targets are placed on the outer surface of the tunnel segment and near the seams as measurement target points, and fixed reference targets are set up within the site to establish a measurement coordinate system. The distribution of these targets should ensure that the laser from each station can accurately track at least three common points for subsequent coordinate unification and error correction. Subsequently, the pulsed laser rangefinder or laser tracker is securely mounted on a tripod, and the instrument height and level are adjusted so that the optical axis is roughly aligned with the center of the test area. After the equipment is turned on, system calibration is performed through the control software, including self-checks of the ranging system, optical axis calibration, zeroing of the angle encoder, and input of meteorological parameters, to correct for the effects of temperature, air pressure, and humidity on laser propagation speed and ensure that the ranging accuracy meets the specified requirements. After calibration, measurement parameters are set in the measurement and control software, such as measurement mode, sampling frequency, tracking method, and data output format. For segment deformation detection, a continuous tracking measurement mode is generally used, with a high sampling frequency to ensure dynamic capture and high-precision positioning of key target points. During data acquisition, the laser emitter emits short-pulse lasers onto the surface of the marker sphere. The spatial coordinates of the reflection point are calculated by measuring the laser round-trip time and horizontal and vertical angle information. The system displays the ranging status and target point locking status in real time. Operators can fine-tune the instrument attitude or station position based on monitoring feedback to avoid data loss due to obstruction or attenuation of the reflected signal. After completing the measurement of all target points at a single station, the instrument is moved to the next station position, and the above installation, calibration, and acquisition steps are repeated until all stations cover the entire segment area. After acquisition, the software performs spatial registration and coordinate unification based on the common target point coordinates of multiple stations, calculates the rigid body transformation relationship between each station, and generates three-dimensional point data in a unified global coordinate system. For cases with slight registration deviations, the least squares method or weighted ICP algorithm can be used for secondary registration to improve overall data consistency. Finally, post-processing is performed on the point data in the unified coordinate system, including outlier removal, coordinate adjustment, surface fitting, and deformation analysis. By fitting and comparing the measured spatial points with the design model surface, the deviation values ​​of each measuring point and the overall deformation trend can be obtained, generating a deformation distribution map and error cloud map of the tunnel segment surface, providing a basis for subsequent structural deformation assessment and construction quality control.

[0066] Finally, a deviation vector graphic and a numerical table are generated, such as... Figure 7 , Figure 8 As shown, this pulse measurement method has the advantages of a large ranging range, high single-point accuracy, and strong operational stability. By setting up a small number of high-precision measurement points, spatial constraints and error corrections can be provided for phase scanning data, enabling precise positioning of key control points.

[0067] After completing phase scanning and pulse measurement, this invention achieves the unification and complementarity of the two measurement results through data fusion technology. Phase scanning provides high-density point cloud data of the outer surface of the tube segment, which can reflect the overall geometric shape and local deformation characteristics; while pulse tracking measurement provides high-precision coordinate information of key control points, which can be used as a constraint benchmark for point cloud registration and accuracy verification.

[0068] The fusion process first unifies the coordinates of the two types of data, using the same marker sphere as a reference to transform the phase point cloud and pulse measurement points to the same coordinate system. Then, through point cloud sparsification and key point matching, spatial alignment between the pulse measurement results and the phase point cloud is achieved. After alignment, using the high-precision pulse point position as a control benchmark, the overall position and attitude of the phase point cloud are corrected, thereby eliminating cumulative scanning errors and multi-station stitching deviations.

[0069] After data fusion, the system integrates high-density point cloud morphology information with high-precision control point coordinates to generate a unified geometric model. This fused model maintains the complete geometric features of phase-based scanning while inheriting the high-precision positioning attributes of pulse-based measurement. Through subsequent deviation analysis and visualization, features such as the overall deformation distribution of the tunnel segments, key point deviations, and seam misalignments can be obtained, significantly improving the reliability and spatial accuracy of the detection results.

[0070] This fusion method effectively combines the high resolution of phase scanning with the high precision of pulse measurement, realizing a unified expression of wind power hybrid tower segment shape inspection from "full surface area" to "precise key points," providing data support for subsequent tower assembly verification, installation posture adjustment, and manufacturing quality assessment.

[0071] Example 4 Example 4 provides a specific process for quality inspection of the wind power hybrid tower segments under test using the three-dimensional laser joint inspection method for wind power hybrid tower segments.

[0072] During the inspection phase, a phase-type 3D laser scanner or a pulsed laser tracking system is first used to perform full-surface measurements on the single-ring segment, acquiring high-density point cloud data. Spatial deviations at each measurement point are calculated by spatial alignment with the design model. Then, using the segment's geometric center as a reference, the outer surface of the segment is divided into six regions: top left, top middle, top right, bottom left, bottom middle, and bottom right. The system calculates the extreme deviation points and their spatial locations for each region, reflecting the segment's circumferential deformation characteristics in both the circumferential and vertical directions. These extreme deviations serve as the basic input parameters for the vertical joint misalignment prediction model.

[0073] During the prediction phase, a calculation logic for vertical joint misalignment is established based on the deviation values ​​and deformation directions of each zone. A positive deviation value indicates that the shape deviates outward relative to the design model, defined as "outward turning"; a negative deviation value indicates inward deformation, defined as "inward tilting". When two adjacent segments have the same deformation type at the corresponding height of the vertical joint (i.e., both outward turning or both inward tilting), their deformation effects cancel each other out; when the deformation types on both sides are opposite (i.e., one side outward turning and the other side inward tilting), their deviation effects are added together. This logic is used to calculate the theoretical maximum misalignment at each vertical joint position after the four segments are assembled into a ring.

[0074] Considering that actual on-site assembly is usually based on bottom alignment, meaning the vertical misalignment at the bottom of the segment is forced to be zero, the top misalignment needs to be compensated and corrected based on the calculation results. The compensation amount is determined according to the offsetting or additive relationship of the deformation types on both sides of the bottom. After correction, the assembly error and the reference error are added together to obtain the final predicted vertical misalignment value. This calculation process not only reflects the influence of the segment's own shape deformation on the assembly deviation, but also considers the influence of assembly fit relationships and bottom constraints, making the predicted results closer to the actual assembly state.

[0075] In a specific test, the measurement method of the present invention was used to test four newly manufactured tube segments, and the deviation values ​​of six regions for each tube segment were obtained. The results are shown in Table 1. Table 1: Deviation in six regions of the tunnel segment.

[0076]

[0077] Based on the measured data, the segments were assembled into a ring in the order of I15-1 / HC-41, I15-2 / HC-41, I15-3 / HC-37, and I15-4 / HC-36. The theoretical misalignment at the top and bottom of each vertical joint was calculated according to the aforementioned judgment logic. Since the bottom misalignment was forcibly limited to 0mm during on-site assembly, the calculation results were compensated and corrected to ensure consistency between the prediction and the actual results. The corrected prediction results are shown in Table 2.

[0078] Table 2: Example of prediction results.

[0079]

[0080] As demonstrated in this embodiment, this method comprehensively considers the shape deviation distribution, deformation direction, and assembly constraints of the six regions of the tunnel segment, achieving quantifiable prediction from point cloud deviation to assembly misalignment. This method can identify areas with significant shape deviations during the wind turbine hybrid tower manufacturing stage, providing a basis for mold correction and assembly optimization, thereby effectively reducing the risk of circumferential seam misalignment and improving tower assembly accuracy and ring consistency.

[0081] The preferred embodiments of the present invention have been described in detail above. It should be understood that those skilled in the art can make numerous modifications and variations based on the concept of the present invention without creative effort. Therefore, all technical solutions that can be obtained by those skilled in the art based on the concept of the present invention through logical analysis, reasoning, or limited experimentation on the basis of existing technology should be within the scope of protection defined by the claims.

Claims

1. A three-dimensional laser combined inspection method for wind turbine hybrid tower segments, characterized in that, Includes the following steps: For the wind power hybrid tower segments under test, marker balls are deployed. Based on the marker balls, phase-type three-dimensional laser scanning is used to obtain the deviation cloud map of the segment surface deformation, and pulse-type laser tracking is used to obtain the point coordinates of the marker balls. Convert the deviation cloud map to global coordinates, and correct the deviation cloud map based on the point coordinates to obtain the corrected deviation cloud map; Obtain the corrected deviation cloud map of all the wind turbine hybrid tower segments to be tested, and determine whether the quality of the wind turbine hybrid tower segments to be tested is qualified.

2. The three-dimensional laser joint inspection method for wind power hybrid tower segments according to claim 1, characterized in that, The number of marker balls shall not be less than four, and at least three marker balls shall not be collinear.

3. The three-dimensional laser combined inspection method for wind power hybrid tower segments according to claim 1 or 2, characterized in that, The marker balls are placed on the left edge, right edge, top, bottom, joint, and bolt holes of the wind turbine hybrid tower segment to be tested.

4. The three-dimensional laser combined inspection method for wind power hybrid tower segments according to claim 1 or 2, characterized in that, Two or more reflective spheres are placed on the measuring base of the phase scanner or the testing frame of the wind turbine hybrid tower segment to be tested.

5. The three-dimensional laser joint inspection method for wind power hybrid tower segments according to claim 1, characterized in that, The phase-type three-dimensional laser scanning includes the following steps: scanning the wind power hybrid tower segment to be tested multiple times to obtain multiple point cloud data; stitching the multiple point cloud data together based on the coordinates of the marker ball in the multiple point cloud data to obtain the overall point cloud data; and calculating the deviation cloud map based on the overall point cloud data and the design model of the wind power hybrid tower segment to be tested.

6. The three-dimensional laser joint inspection method for wind power hybrid tower segments according to claim 5, characterized in that, After acquiring the overall point cloud data, the ICP iterative nearest point algorithm is used to eliminate the error in the overall point cloud data. The overall point cloud data after eliminating the error is then preprocessed and the deviation cloud map is calculated with the design model of the wind power hybrid tower segment to be tested.

7. The three-dimensional laser joint inspection method for wind power hybrid tower segments according to claim 6, characterized in that, The preprocessing includes removing outliers, removing noise, filtering out background points, and homogenizing points.

8. The three-dimensional laser joint inspection method for wind power hybrid tower segments according to claim 4, characterized in that, The pulsed laser tracking includes the following constraints: The marker ball should be measured at least three times, and the standard deviation of the coordinates of the points measured each time should be less than 0.05 mm. The measured echo intensity reaches the preset effective value of the measuring equipment; The registration residual of the reflective spheres deployed on the measuring base or testing frame is less than 0.2 mm.

9. The three-dimensional laser joint inspection method for wind power hybrid tower segments according to claim 1, characterized in that, The global coordinates are constructed based on the design model or testing jig of the wind turbine hybrid tower segment to be tested. Using the center of the design model or testing frame as the origin of the coordinate system, the tower axis of the wind power hybrid tower segment under test as the Z-axis, the reference direction of the mid-baseline or midpoint of the wind power hybrid tower segment under test as the X-axis, and the circumferential tangent direction of the wind power hybrid tower segment under test as the Y-axis.

10. The three-dimensional laser joint inspection method for wind power hybrid tower segments according to claim 1, characterized in that, The process of converting the deviation cloud map to global coordinates includes: establishing an objective function about the point coordinates and the corresponding reflection spheres in the deviation cloud map by minimizing the sum of squared residuals; and converting the deviation cloud map to global coordinates under the constraint of point coordinates based on the objective function. The objective function is expressed by the following formula: ； in, Indicates weight; Represents the rotation matrix; The point represents the translation vector of the corresponding reflection sphere in the deviation cloud diagram, along with its coordinates. Indicates the coordinates of the point; This indicates the corresponding deviation contour map. The coordinates.

11. The three-dimensional laser joint inspection method for wind power hybrid tower segments according to claim 2, characterized in that, The step of correcting the deviation cloud map based on the point coordinates includes: calculating the common target residual between the point coordinates in the global coordinates and the deviation cloud map; if the common target residual is greater than a preset value, the corresponding marker ball is removed, and the deviation cloud map is re-converted to the global coordinates based on the point coordinates; if it is less than the preset value, the coordinates of the corresponding marker ball meet the requirements.

12. The three-dimensional laser joint inspection method for wind power hybrid tower segments according to claim 2, characterized in that, The obtained corrected deviation cloud map represents the deviation with different color distributions, and a deviation statistics table and feature point error curves are generated based on the corrected deviation cloud map.

13. The three-dimensional laser joint inspection method for wind power hybrid tower segments according to claim 2, characterized in that, The process of determining whether the quality of the wind turbine hybrid tower segments under test is qualified includes the following steps: The correction deviation cloud map of all the wind power hybrid tower segments to be tested is divided into zones. The misalignment of each wind power hybrid tower segment to be tested is obtained in combination with the design model. The quality of the wind power hybrid tower segments to be tested is judged based on the misalignment.

14. The three-dimensional laser joint inspection method for wind power hybrid tower segments according to claim 13, characterized in that, The misalignment includes the misalignment on both sides and the misalignment at the top. The misalignment on both sides is calculated based on the coordinates of the splicing joint of the two wind turbine hybrid tower segments under test at the same height. The top misalignment is calculated based on the bottom coordinate deviation, top coordinate deviation, and assembly error of the wind turbine hybrid tower segment under test.

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