A wind power tower drum concentricity control method and system

Abstract

The present application relates to the technical field of structural engineering, and particularly relates to a wind power tower drum concentricity control method and system. The method comprises the following steps: obtaining wind power tower drum installation reference data; determining ring piece circle center offset based on the wind power tower drum installation reference data to obtain ring piece offset data; performing concentricity detection based on the ring piece offset data to generate initial concentricity data; performing deviation analysis based on the initial concentricity data to obtain deviation data; identifying deviation abnormal ring pieces based on the deviation data to obtain abnormal ring piece data; performing ring opening deformation detection based on the abnormal ring piece data to obtain ring opening deformation data; and performing stability analysis based on the ring opening deformation data to obtain stability data. The present application improves the wind power tower drum installation precision and the concentricity control rate based on the structural engineering technology.

Description

Technical Field

[0001] This invention relates to the field of structural engineering technology, and in particular to a method and system for controlling the concentricity of wind turbine towers. Background Technology

[0002] As the capacity of wind turbine units continues to increase, the height and diameter of wind turbine towers are also growing. The structural precision and installation quality of these towers have a significant impact on the overall operational safety of the turbine. As the main load-bearing structure of a wind turbine, the tower is assembled section by section on-site from multiple ring segments. The concentricity control of these segments directly affects the overall verticality, load-bearing capacity, and fatigue life of the tower. However, existing methods for controlling tower installation concentricity still have the following shortcomings: Traditional control methods mainly rely on manual measurement and experience-based corrections, lacking comprehensive analysis based on multi-dimensional parameters such as ring segment offset, flange warping, and ring joint deformation. This can easily lead to the gradual accumulation of ring segment installation errors, ultimately causing overall tower tilting. During long-term operation, the tower flange surface is subjected to wind loads, vibrations, and temperature gradients, making it prone to warping deformation and joint misalignment. This can lead to stress concentration in connecting bolts and localized fatigue damage, which existing detection methods struggle to identify and compensate for early damage. Existing gasket compensation and fine-tuning methods are mostly static calculations, lacking dynamic modeling and evaluation of the stress state of the ring plates, material elastic-plastic characteristics and fatigue trends during actual installation, making it difficult to guarantee the stability and safety of the tower during long-term operation. Summary of the Invention

[0003] Therefore, it is necessary for the present invention to provide a method and system for controlling the concentricity of wind turbine towers in order to solve at least one of the above-mentioned technical problems.

[0004] To achieve the above objectives, a method for controlling the concentricity of wind turbine towers includes the following steps: Step S1: Obtain the wind turbine tower installation reference data; determine the ring center offset based on the wind turbine tower installation reference data to obtain the ring offset data; perform concentricity detection based on the ring offset data to generate initial concentricity data; Step S2: Perform deviation analysis based on the initial concentricity data to obtain deviation data; identify abnormal ring pieces based on the deviation data to obtain abnormal ring piece data; Step S3: Detect ring deformation based on abnormal ring plate data to obtain ring deformation data; perform stability analysis based on ring deformation data to obtain stability data; and detect flange warping based on stability data to obtain flange warping data. Step S4: Perform ring gasket compensation analysis based on flange warping data to obtain gasket compensation data; perform tilt fine-tuning based on gasket compensation data, calculate wind turbine tower concentricity, and generate concentricity assessment results.

[0005] This invention achieves early quantitative control of tower concentricity by acquiring benchmark data and detecting ring center offset during the initial installation stage, avoiding the accumulation of errors caused by relying on manual experience and improving installation accuracy. After obtaining the initial detection results, further deviation analysis and identification of abnormal rings allow for precise location of the deviation source, preventing the offset problem from amplifying during the progressive assembly of rings and effectively improving the controllability of the tower assembly process. Combining abnormal ring deformation detection with stability analysis enables early detection of potential instability risks caused by geometric irregularities or uneven stress during the installation stage. Furthermore, flange warping detection identifies… To prevent potential misalignment and deformation trends during operation, the system reduces bolt stress concentration and fatigue damage in later stages of operation. Based on this, ring shim compensation analysis and data generation allow installation corrections to move beyond static empirical calculations and achieve refined adjustments based on deformation trends and stress conditions, ensuring the compensation effect better matches the actual stress environment. Finally, tilt fine-tuning and concentricity calculation and evaluation based on the compensation data not only provide dynamic feedback on tower assembly quality but also enable real-time corrections during construction, significantly improving the overall verticality and structural stability of the tower, thereby enhancing the long-term safe and reliable operation of the wind turbine.

[0006] Preferably, step S1 specifically includes: Step S11: Obtain the installation reference data for the wind turbine tower; Step S12: Determine the installation position of the ring plate based on the wind turbine tower installation reference data, and obtain the ring plate installation position data; Step S13: Identify the center reference based on the ring installation position data; Step S14: Calculate the center offset based on the center reference to obtain the ring offset data; Step S15: Perform concentricity detection based on the ring offset data to generate initial concentricity data.

[0007] This invention ensures the consistency and accuracy of measurement references by utilizing installation benchmark data, providing a reliable foundation for subsequent analysis. Based on this, determining the ring plate installation position enables real-time monitoring and correction of the ring plate installation process, effectively avoiding cumulative errors caused by human error. Further identification of the center benchmark ensures the overall geometric consistency of the tower assembly, providing a basis for accurate calculation of the center offset. Calculating the center offset quantifies minute deviations of the ring plates, forming intuitive offset data for timely detection of installation anomalies. Finally, combining the offset data with concentricity testing allows for rapid generation of initial concentricity data, enabling the evaluation of tower verticality and structural accuracy early in the installation process. This prevents errors from gradually amplifying, ensuring the overall load-bearing capacity and operational stability of the tower, and providing reliable data support for subsequent deformation detection, compensation, and dynamic optimization.

[0008] Preferably, step S15 specifically includes: Step S151: Compare the ring offset data with the centerline of the wind turbine tower to obtain centerline comparison data; Step S152: Calculate the concentricity deviation based on the centerline comparison data to obtain the concentricity deviation data; Step S153: Perform deviation trend analysis based on concentricity deviation data to obtain deviation trend data; Step S154: Determine the concentricity level based on the deviation trend data to obtain the initial concentricity data.

[0009] This invention achieves dynamic quantification and graded evaluation of wind turbine tower concentricity by introducing centerline comparison, deviation calculation, trend analysis, and grade determination on the basis of ring offset detection, resulting in significant benefits. Centerline comparison allows for precise comparison between actual ring offset and design benchmarks, avoiding misjudgments caused by single offset values. Concentricity deviation calculation transforms complex geometric offsets into quantifiable indicators, providing an intuitive basis for subsequent judgments. Further deviation trend analysis using the deviation data not only identifies current installation errors but also predicts the direction of error development and cumulative risks, allowing for proactive compensation measures. Finally, grade determination of deviation trends transforms complex offset results into standardized initial concentricity data, facilitating rapid understanding and application by engineers, ensuring controllable accuracy during tower installation and the long-term safety and stability of the structure.

[0010] Preferably, step S3 specifically includes: Step S31: Extract the ring boundary based on the abnormal ring data to obtain the ring boundary data; Step S32: Perform geometric contour fitting based on the ring boundary data to obtain the ring contour data; Step S33: Perform ellipticity analysis based on the ring profile data to obtain the ring geometric deviation data; Step S34: Determine the deformation of the ring based on the geometric deviation data of the ring, and obtain the deformation data of the ring; Step S35: Perform stability analysis based on the annular deformation data to obtain stability data; Step S36: Perform flange face warpage detection based on stability data to obtain flange face warpage data.

[0011] This invention achieves full-process quantitative control of the geometric state and mechanical stability of the tower annulus through steps such as annulus boundary extraction, contour fitting, ellipticity analysis, deformation judgment, stability analysis, and flange warpage detection, yielding significant benefits. Boundary extraction accurately captures the true boundary information of the annulus, avoiding overall judgment bias caused by local anomalies; geometric contour fitting transforms complex boundary data into a regularized contour expression, facilitating subsequent mathematical analysis and structural comparison; ellipticity analysis effectively reveals whether the annulus exhibits a non-circular tendency, thereby quantifying geometric deviations and reflecting installation accuracy; deformation judgment based on geometric deviations enables rapid identification of annulus morphological anomalies, reducing the uncertainty of manual judgment; stability analysis using deformation data not only assesses the impact of local anomalies on overall structural safety but also predicts potential instability risks in advance; finally, flange warpage detection combined with stability results enables full-link monitoring from geometric deformation to the state of the connection surface, ensuring the accuracy of the tower assembly process and long-term reliability during operation.

[0012] Preferably, step S35 specifically includes: Step S351: Extract the displacement field of the annular piece based on the annular deformation data to obtain displacement field data; Step S352: Perform stress analysis on the ring connection part based on the displacement field data to obtain the connection stress data; Step S353: Calculate the stiffness of the ring structure based on the connection force data to obtain the structural stiffness data; Step S354: Identify weak areas of the ring plate based on structural stiffness data to obtain weak area distribution data; Step S355: Perform ring plate stability analysis based on weak zone distribution data to obtain stability data.

[0013] This invention forms a complete analytical chain from geometric deformation to mechanical performance through steps such as annular displacement field extraction, stress analysis of connection points, structural stiffness calculation, weak zone identification, and stability analysis. This effectively improves the scientific rigor and reliability of tower concentricity control, yielding significant benefits. Displacement field extraction directly reflects the overall and local displacement distribution of the annular segments under deformation, avoiding reliance on single-point data while neglecting the overall response. Stress analysis of connection points reveals the actual stress conditions of bolts, welds, and flange areas, providing a basis for identifying stress concentration and fatigue risks. Structural stiffness calculation quantifies the deformation resistance of different areas, ensuring a comprehensive understanding of the overall tower stiffness distribution. Weak zone identification based on stiffness results helps accurately locate potential weak points, preventing potential problems from escalating into structural issues. Finally, stability analysis combining weak zone distribution with the overall stress state not only assesses the safety margin of the tower under complex loads but also provides decision support for subsequent compensation, reinforcement, and optimization design, thereby significantly improving the long-term operational safety and structural reliability of the tower.

[0014] Preferred, preferred, step S36 specifically is as follows: Step S361: Perform stress detection on the ring material based on stability data to obtain the stress data of the ring material; Step S362: Perform elastoplastic characteristic analysis based on the stress data of the ring material to obtain elastoplastic data; Step S363: Calculate fatigue deformation based on the elastoplastic data to obtain fatigue deformation data; Step S364: Identify the deformation trend of the flange surface based on fatigue deformation data; Step S365: Perform flange warping analysis based on the flange deformation trend to obtain flange warping data.

[0015] This invention, through steps such as ring material stress detection, elastoplastic characteristic analysis, fatigue deformation calculation, flange deformation trend identification, and warpage analysis, enables multi-level dynamic evaluation from material stress to structural deformation, yielding significant benefits. Material stress detection accurately reflects the stress level of the ring under actual operating conditions, providing reliable input for subsequent mechanical performance analysis; elastoplastic characteristic analysis distinguishes between the elastic response and plastic deformation process of the ring material, thus realistically depicting the deformation mechanism of the structure under complex loads; fatigue deformation calculation predicts cumulative deformation under long-term operation based on the material's elastoplastic characteristics, helping to identify fatigue failure risks in advance; deformation trend identification links local fatigue effects with overall flange deformation, intuitively showing the evolution of the flange under different load conditions; and the final warpage analysis quantifies the deformation amplitude and distribution characteristics of the flange, providing data support for gasket compensation, fine-tuning, and structural optimization, significantly improving the tower's installation accuracy and long-term operational stability.

[0016] Preferably, step S365 specifically includes: Identify high-deformation areas of the flange plate based on the deformation trend of the flange surface; Grain morphology data were obtained by detecting the grain morphology in the high-deformation region of the annular plate. Grain distribution data is obtained by analyzing the grain morphology data. Grain boundary stress concentration data is obtained by detecting grain boundary stress concentration based on grain distribution data. Grain slip analysis was performed based on grain boundary stress concentration data to obtain grain slip data; Flange face warpage is determined based on grain slip data, and flange face warpage data is obtained.

[0017] This invention enables comprehensive tracing of warping mechanisms from macroscopic structure to microscopic material by progressively detecting and analyzing flange deformation trends, grain morphology, grain distribution, grain boundary stress concentration, and grain slip. It has significant beneficial effects. Identifying high-deformation regions can accurately pinpoint the areas of the flange face most severely stressed and deformed, providing targeted targets for subsequent microscopic inspections. Grain morphology detection can reveal the microstructural changes of materials under complex loads, avoiding the limitations of analysis based solely on macroscopic geometric parameters. Grain distribution analysis can quantify the orientation and arrangement characteristics of grains within the material, thereby reflecting the uniformity and potential weakening trends of various regions of the structure. Grain boundary stress concentration detection can capture stress hotspots at the microscopic level, accurately identifying dangerous locations prone to microcrack initiation. Grain slip analysis can reveal the plastic deformation mechanism of materials under stress, thus explaining the relationship between local warping and overall structural instability. Finally, warping determination can achieve an effective mapping from microscopic material mechanisms to macroscopic structural deformation, providing a scientific basis for the prediction, compensation, and optimization of tower flange face warping, and helping to significantly improve the accuracy of tower installation and the safety and reliability of long-term operation.

[0018] Preferably, step S4 specifically includes: Step S41: Analyze the deformation of the circumferential joint based on the flange warping data to obtain the joint deformation data; Step S42: Calculate the gasket thickness requirement based on the joint deformation data to obtain the gasket thickness data; Step S43: Perform gasket arrangement optimization analysis based on gasket thickness data to obtain gasket arrangement data; Step S44: Evaluate the overall ring compensation effect based on the gasket arrangement data to obtain gasket compensation data; Step S45: Perform tilt fine-tuning based on shim compensation data to obtain tilt fine-tuning data; Step S46: Calculate the concentricity of the wind turbine tower based on the tilt fine-tuning data and generate the concentricity assessment results.

[0019] This invention achieves full-chain optimization of wind turbine tower concentricity control through continuous analysis of ring joints, gasket thickness, arrangement optimization, compensation evaluation, tilt fine-tuning, and concentricity calculation, yielding significant benefits. Joint deformation analysis accurately identifies misalignments and local deformation characteristics at ring joints, providing a quantitative basis for subsequent compensation design. Gasket thickness requirement calculation transforms geometric errors into operable compensation parameters, achieving a direct mapping from error to compensation. Gasket arrangement optimization ensures both compensation accuracy and installation feasibility, as well as structural stress uniformity, avoiding new imbalances caused by local over-compensation. Overall compensation effect evaluation verifies the effectiveness of compensation measures at the overall ring scale, ensuring compensation not only acts locally but also improves overall concentricity. Tilting fine-tuning further eliminates residual installation errors after compensation, allowing the tower to maintain verticality and structural symmetry even with increased cumulative height. The final concentricity evaluation result quantifies installation accuracy and provides data support for subsequent operation and maintenance, achieving closed-loop control from detection and compensation to correction, effectively improving tower installation accuracy, load-bearing capacity, and long-term operational reliability.

[0020] Preferably, step S45 specifically includes: Step S451: Adjust the ring height based on the shim compensation data to obtain the ring height data; Step S452: Identify the tilting trend of the ring joint based on the ring height data; Step S453: Generate a tilt fine-tuning scheme based on the tilt trend of the ring joint; Step S454: Correct the ring plate installation position based on the tilt fine-tuning scheme to obtain the corrected ring plate installation position; Step S455: Perform tilt fine-tuning evaluation based on the ring plate installation correction position to obtain tilt fine-tuning data.

[0021] This invention adjusts the ring height based on shim compensation data, effectively correcting height differences caused by manufacturing errors and installation deviations, and avoiding cumulative errors between rings. Furthermore, it identifies the tilting trend of the ring joints, enabling early detection of potential misalignment risks during tower assembly and providing a basis for subsequent corrections. A tilt fine-tuning scheme is further generated, allowing for targeted compensation and avoiding uncertainties arising from traditional manual experience. By correcting the ring installation position, the ring assembly is made to better conform to design benchmarks, improving installation accuracy and concentricity. Finally, a tilt fine-tuning execution evaluation provides dynamic feedback on the correction effect during installation, ensuring the fine-tuning measures are truly effective. This achieves full-process control over ring installation accuracy, reducing problems such as joint misalignment, flange warping, and localized stress concentration in bolts, improving the overall verticality and structural stability of the tower, extending fatigue life, and enhancing long-term operational safety.

[0022] Preferably, this specification also provides a wind turbine tower concentricity control system for executing the wind turbine tower concentricity control method described above. The wind turbine tower concentricity control system includes: The concentricity detection module is used to acquire the wind turbine tower installation reference data; determine the ring center offset based on the wind turbine tower installation reference data to obtain the ring offset data; and perform concentricity detection based on the ring offset data to generate initial concentricity data. The deviation analysis module is used to perform deviation analysis based on the initial concentricity data to obtain deviation data; based on the deviation data, it identifies the abnormal ring pieces and obtains the abnormal ring piece data. The stability analysis module is used to detect ring deformation based on abnormal ring plate data to obtain ring deformation data; to perform stability analysis based on the ring deformation data to obtain stability data; and to detect flange face warping based on the stability data to obtain flange face warping data. The gasket compensation module is used to perform ring gasket compensation analysis based on flange warping data to obtain gasket compensation data; based on the gasket compensation data, it performs tilt fine-tuning and calculates the concentricity of the wind turbine tower to generate concentricity assessment results. Attached Figure Description

[0023] Other features, objects, and advantages of the invention will become more apparent from the following detailed description of non-limiting embodiments with reference to the accompanying drawings: Figure 1 This is a flowchart illustrating the steps of a wind turbine tower concentricity control method according to the present invention. Figure 2 This is a detailed flowchart of step S1 in the present invention; Figure 3 This is a detailed flowchart of step S15 in the present invention; The realization of the objective, functional features and advantages of the present invention will be further explained in conjunction with the embodiments and with reference to the accompanying drawings. Detailed Implementation

[0024] The technical method of this invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of this invention. Based on the embodiments of this invention, all other embodiments obtained by those skilled in the art without inventive effort are within the scope of protection of this invention.

[0025] Furthermore, the accompanying drawings are merely illustrative of the invention and are not necessarily drawn to scale. The same reference numerals in the drawings denote the same or similar parts, and therefore repeated descriptions of them will be omitted. Some block diagrams shown in the drawings are functional entities and do not necessarily correspond to physically or logically independent entities. These functional entities can be implemented in software, in one or more hardware modules or integrated circuits, or in different network and / or processor methods and / or microcontroller methods.

[0026] It should be understood that although the terms "first," "second," etc., may be used herein to describe various units, these units should not be limited by these terms. These terms are used merely to distinguish one unit from another. For example, without departing from the scope of the exemplary embodiments, a first unit may be referred to as a second unit, and similarly, a second unit may be referred to as a first unit. The term "and / or" as used herein includes any and all combinations of one or more of the associated listed items.

[0027] To achieve the above objectives, please refer to Figures 1 to 3 This invention provides a method for controlling the concentricity of wind turbine towers, the method comprising the following steps: Step S1: Obtain the wind turbine tower installation reference data; determine the ring center offset based on the wind turbine tower installation reference data to obtain the ring offset data; perform concentricity detection based on the ring offset data to generate initial concentricity data; In this embodiment, installation reference data needs to be obtained. This data comes from a three-dimensional laser rangefinder and an electronic plumb line deployed on the tower foundation platform. The laser rangefinder is a Leica P50 with a ranging accuracy of ±1.0 mm and a measuring range of 1 m to 120 m. The electronic plumb line has an accuracy of 0.1″. The three-dimensional coordinates of the outer edge points of each ring are obtained through the laser rangefinder, and the coordinates of the center are fitted using the least squares method to calculate the geometric center of each ring. The installation reference center is positioned by the plumb line at the center of the foundation platform and projected onto each installation plane, and this point is taken as the ideal center. The offset distance and offset direction between the fitted center of the ring and the reference center are calculated to obtain the ring center offset. The offset direction is expressed in polar coordinates, the offset angle is in °, and the offset distance is in mm. The offset data is recorded and input into the concentricity detection module. The initial concentricity data is generated using the ratio of the offset data to the ring radius r. The calculation formula is as follows: The numerical values ​​are accurate to three decimal places and serve as the basic input for subsequent analysis.

[0028] Step S2: Perform deviation analysis based on the initial concentricity data to obtain deviation data; identify abnormal ring pieces based on the deviation data to obtain abnormal ring piece data; In this embodiment, the concentricity value of each ring segment is specified to be within the limit that the concentricity deviation of a single ring segment shall not exceed 0.3%, and the cumulative deviation shall not exceed H / 1200 (H is the tower height in meters). If the test result exceeds the above threshold, the ring segment is judged as an abnormal ring segment. During the deviation analysis, the data processing unit used is a PLC-based hardware calculation module. After the concentricity value is input, the system automatically calculates the exceedance situation. Taking a tower height of 100m as an example, the cumulative allowable deviation is 83.3mm. When the deviation of a single ring segment is greater than 0.3% of its radius or the cumulative value exceeds 83.3mm, it is automatically marked as an abnormal ring segment, and abnormal ring segment data is generated. The data format is (ring segment number, offset value, offset angle, and exceedance type). All abnormal ring segment data is stored in a dedicated industrial database and a CSV format data file is generated for subsequent ring deformation detection.

[0029] Step S3: Detect ring deformation based on abnormal ring plate data to obtain ring deformation data; perform stability analysis based on ring deformation data to obtain stability data; and detect flange warping based on stability data to obtain flange warping data. In this embodiment, the detection uses a high-precision three-coordinate laser scanner (accuracy 0.02mm, scanning frequency 500Hz) to perform a 360° full-circumference scan of the inner wall of the ring, acquiring measurement point data every 2° of the inner diameter of the ring, resulting in 180 measurement point coordinates. The measurement points are fitted to an ideal circle, and the radial offset value of each measurement point is calculated. The radial offset threshold is set to ±2mm; areas exceeding the threshold are identified as local deformation areas. The obtained radial offset distribution is the ring deformation data. Subsequently, the stability of the deformed area is analyzed using the finite element analysis method, with the ring material parameters (Q345D steel, yield strength 345MPa, elastic modulus...) used... The input (Poisson's ratio 0.3) is used in the calculation module, and combined with the detected offset curve, wind load simulation is applied (design wind speed 50m / s, equivalent wind pressure). The structural stress and deformation trends are calculated to generate stability data. Following this stability analysis, electronic interferometry is used to detect warpage on the flange surface. This method involves arranging four interferometric measurement points on the flange surface at 90° intervals. The flatness difference is measured using a laser interferometer; a difference exceeding 1.5 mm is considered a warpage area, and the warpage data is recorded.

[0030] Step S4: Perform ring gasket compensation analysis based on flange warping data to obtain gasket compensation data; perform tilt fine-tuning based on gasket compensation data, calculate wind turbine tower concentricity, and generate concentricity assessment results.

[0031] In this embodiment, adjustable-thickness shims are arranged in the warped area. The shims are made of 65Mn spring steel with thicknesses ranging from 0.5mm to 5.0mm, with a grading accuracy of 0.5mm. The required compensation thickness is calculated by measuring the warped height difference. For example, when the maximum warped height difference is 3.2mm, a 3.0mm thick shim is placed in the corresponding area, and 1.0mm and 0.5mm thick shims are arranged around it to ensure a uniform transition and uniform contact pressure distribution. After compensation, a tilt fine-tuning scheme is generated based on the shim distribution. The scheme is recorded as the compensation circumferential angle, shim thickness, and installation torque. Subsequently, the circumferential installation angle is re-measured using a high-precision electronic level (resolution 0.01mm / m), and the installation position is corrected based on the measured data. After correction, the concentricity of the tower is recalculated based on the center coordinates, using the same formula. If the ΔC value is less than 0.3% and the cumulative deviation is less than H / 1200, the final concentricity assessment result is generated. The result format is (ring number, corrected offset, cumulative concentricity deviation), and the data is uniformly stored in the central monitoring unit.

[0032] Preferably, step S1 specifically includes: Step S11: Obtain the installation reference data for the wind turbine tower; In this embodiment, a measurement reference point is set on the tower foundation platform, and a three-dimensional laser rangefinder and an electronic plumb line are used for synchronous measurement. The three-dimensional laser rangefinder is a LeicaScanStationP50, with a ranging accuracy of ±1.0 mm, a scanning frequency of 500,000 points / second, and a measurement range of 0.5 m to 120 m; the electronic plumb line is a LeicaNA2, with an accuracy of 0.1″. The specific operating procedure is as follows: A total station reference point is established at the center of the tower foundation platform, and a vertical reference line is established using the electronic plumb line. Then, the three-dimensional laser rangefinder is used to perform a 360° scan around the reference point to obtain the three-dimensional coordinate data of the foundation platform plane. The reference data includes X, Y, and Z axis coordinate values, recorded to three decimal places. The platform diameter is 20 m, and the scanning point spacing is 5 mm, ultimately forming a point cloud data file of the reference plane. By calculating the least-squares fitted plane equation of the platform surface point cloud, the installation reference plane is obtained; the installation center point is determined within this plane, and this point is calibrated with the vertical reference line of the plumb line to obtain the installation reference data.

[0033] Step S12: Determine the installation position of the ring plate based on the wind turbine tower installation reference data, and obtain the ring plate installation position data; In this embodiment, a positioning laser projector projects the theoretical installation circumference of the ring plate onto a reference plane. The radius of this circumference is the designed outer radius r of the tower, for example, the outer radius of the tower bottom is 2500mm, with an accuracy requirement of ±2mm. Then, the ring plate is hoisted onto the platform. Laser displacement sensors (model KeyenceLK-G3000, measurement range 0–300mm, resolution 0.01mm) distributed at four equiangular positions on the outer edge of the ring plate are used to measure the distance from the outer wall of the ring plate to the reference circumference in real time. Each sensor has a fixed measurement position at 0°, 90°, 180°, and 270° azimuth angles. By reading the difference between the four distance values ​​and the theoretical radius, the offset between the ring plate and the reference circumference is determined. The ring plate installation position data consists of the three-dimensional coordinates of the ring plate's geometric center point and the actual deviation from the outer wall to the reference circumference, with the coordinate unit being mm and the deviation accuracy retained to two decimal places. The installation location data of the ring piece is saved in tabular form, with the format (ring piece number, measuring point azimuth, measured distance, deviation value, and coordinates of the installation center point), as input for subsequent center reference identification.

[0034] Step S13: Identify the center reference based on the ring installation position data; In this embodiment, a circle fitting method is used to perform geometric calculations on the measurement point data of the outer wall of the ring. The coordinates of the four equiangular measurement points of the outer wall obtained in step S12 are imported into the fitting program, and the coordinates of the center of the actual installation circle of the ring are calculated using the least squares circle fitting algorithm. The fitting formula is as follows: ,in Let be the coordinates of the center of the circle to be determined. Let the radius be . Minimize by iterative calculation The coordinates of the center of the circle can be obtained by solving the problem. The required fitting accuracy is that the sum of squared residuals is less than... When the range is exceeded, more measuring points need to be added, for example, four more measuring points at 45°, 135°, 225°, and 315° for refitting. The obtained center coordinates are compared and converted with the reference point coordinate system (established by the installation reference in step S11) to finally generate the center reference data. The output format of the center reference data is (ring number, center X coordinate, center Y coordinate, radius value, fitting residual), and it is saved to a dedicated engineering database to ensure the completeness and accuracy of the input for subsequent center offset calculations.

[0035] Step S14: Calculate the center offset based on the center reference to obtain the ring offset data; In this embodiment, the installation reference center coordinates are called. The actual center coordinates of the ring obtained in step S13 Perform the difference operation; the offset calculation formula is as follows: The calculation accuracy is 0.01mm. Taking the bottom of the tower as an example, if the coordinates of the installation reference center are (0,0) and the actual center coordinates of the ring are (3.2,-1.5), then the offset... The offset direction is expressed in polar coordinates, and the calculation formula is as follows: In this example, the offset angle is The final annular piece offset data includes two parameters: offset distance and offset direction. The data format is (annular piece number, offset distance in mm, offset angle in °). All data are stored in sorted order by annular piece number. Error exceeding the limit is marked as a red warning when the offset is >5mm, and marked as green normal when the offset is ≤5mm, ensuring that the detection process has a quantitative calculation basis.

[0036] Step S15: Perform concentricity detection based on the ring offset data to generate initial concentricity data.

[0037] In this embodiment, the concentricity calculation formula is used. ,in This is the offset of the center of the circle. Design the radius of the ring piece. For example, if the ring piece radius is 2500mm, and the offset is 3.53mm, then the concentricity... , that is 0.141%. This value is compared with the allowable concentricity deviation of 0.3% for a single ring segment specified in the standard specification GB / T 50308-2017. If the detected value is less than this threshold, it is determined as qualified. The detection operation is performed by the industrial computing unit PLC. The PLC collects the offset data of the ring segment, automatically performs formula calculation, and generates initial concentricity data. The format of the initial data is (ring segment number, radius, offset, concentricity percentage), with the precision retained to three decimal places. If the concentricity of a certain ring segment exceeds the threshold, the PLC will mark the ring segment number as abnormal in the result file and record the cumulative deviation at the same time. The calculation formula of cumulative deviation is . All detection data are transmitted to the central monitoring server via Ethernet and displayed in real time on the engineering monitoring interface, so as to ensure the quantification, accuracy and traceability of concentricity detection.

[0038] Preferably, step S15 is specifically: Step S151: comparing the offset data of the ring segment with the center line of the wind power tower drum to obtain center line comparison data; In this embodiment, a spatial reference for the center line of the wind power tower drum is established. The center line is determined by the laser beam emitted by a vertical laser plummet on the tower foundation platform, a laser plummet of model LeicaLDT-05 is used, and the verticality error does not exceed 0.5mm / 50m. The offset data of the ring segment are measured by four laser displacement sensors, which are respectively arranged at the positions of 0°, 90°, 180° and 270° on the outer edge of the ring segment. Each sensor measures the horizontal distance from the outer wall of the ring segment to the central reference line, with an accuracy of 0.01mm. During comparison, the offset data of the ring segment are uniformly projected into the reference coordinate system. The origin of the coordinate system is set at the center of the tower foundation, the Z axis coincides with the laser beam of the laser plummet, and the X and Y axes are respectively arranged along the horizontal reference direction of the foundation. During the comparison process, the measurement data are input into the industrial computer through the PLC acquisition unit, the computer compares the offset value of each measurement point with the theoretical position of the center line one by one, and records the difference. The comparison result is output in the form of a data table, including (measurement point number, measured offset value, theoretical value of center line, difference), the data accuracy is 0.01mm, and the data out-of-limit marking threshold is set to 5mm. When the difference exceeds the threshold, it is automatically marked as abnormal, so as to obtain complete center line comparison data.

[0039] Step S152: calculating the concentricity deviation according to the center line comparison data, so as to obtain concentricity deviation data; In this embodiment, the tower design radius *r* is determined, a value provided by the design drawings; for example, the radius of the bottom ring is 2500 mm. Then, the difference data obtained in step S151 is called, and the offset differences of all measuring points are statistically analyzed according to the ring number. The deviation calculation is performed by an industrial computer using a dedicated data processing program. Input parameters include the ring number, ring radius *r*, and the measurement point difference. During processing, the system performs a weighted average of the differences of the four measuring points for each ring, with a weighting factor of 0.25 for each point, ensuring that the data results are not biased towards any single point. The final output is concentricity deviation data, including (ring number, ring radius, average offset value, and deviation percentage). The percentage calculation uses the ring radius as the denominator and the average offset value as the numerator, accurate to three decimal places. The output results are transmitted from the PLC to a central database via Ethernet and stored in a data file named "Deviation Detection Record Table." Each data record includes a timestamp and the ring number to ensure data traceability. A grading system was set in the concentricity deviation data. When the deviation percentage was greater than 0.3%, it was marked as "out of limit" and when it was less than or equal to 0.3%, it was marked as "normal".

[0040] Step S153: Perform deviation trend analysis based on concentricity deviation data to obtain deviation trend data; In this embodiment, the deviation data of multiple ring segments are arranged in order of ring segment number, which is consistent with the actual installation order of the tower. For example, the tower is numbered 1 to N from bottom to top, and each ring segment has corresponding deviation data. During the analysis, the computer calls a time series analysis program to plot the deviation values ​​of each ring segment as an offset curve, with the ring segment number on the horizontal axis and the deviation percentage on the vertical axis. The curve trend is identified by a quadratic polynomial fitting method, using the least squares method. A residual sum of squares less than 0.5 is considered a valid fit. When the curve shows a continuous upward trend, it is determined to be an offset accumulation; when the curve shows alternating positive and negative offsets, it is determined to be a fluctuation trend. In addition, the program also calculates the rate of change of the deviation value. When the rate of change of the deviation of adjacent ring segments exceeds 0.1%, it is recorded as "rapid deviation". The deviation trend data is saved in two forms: a table and a curve file. The table content includes (ring segment number, deviation percentage, rate of change, trend type), and the curve file is in CSV format, saving all fitting points of the deviation curve. All trend data and deviation data are stored in a database for subsequent concentricity level determination.

[0041] Step S154: Determine the concentricity level based on the deviation trend data to obtain the initial concentricity data.

[0042] In this embodiment, a grading standard is established. The grading is divided into three levels: Level 1 is Excellent, with a deviation percentage ≤ 0.15% and a stable trend or fluctuation range less than 0.05%; Level 2 is Good, with a deviation percentage between 0.15% and 0.3%, and a slight cumulative trend; Level 3 is Poor, with a deviation percentage > 0.3%, or exhibiting rapid deviation. The judgment process is automatically completed by a central industrial computer. The input data is the deviation trend table output in step S153, and the system judges according to the aforementioned threshold standards. The grade of each ring piece is judged separately, and the judgment result is stored as initial concentricity data. The data format is (ring piece number, deviation percentage, deviation trend, grade), with the grade represented numerically: 1 for Excellent, 2 for Good, and 3 for Poor. To ensure accuracy, after the judgment is completed, the system generates a complete concentricity grade report in PDF format, which includes a judgment result table, a deviation curve graph, and a grade statistical distribution histogram. All files have automatically generated numbers and timestamps for archiving and subsequent retrieval. The final initial concentricity data is directly used in subsequent installation quality evaluation and correction stages.

[0043] Preferably, step S3 specifically includes: Step S31: Extract the ring boundary based on the abnormal ring data to obtain the ring boundary data; In this embodiment, a high-precision laser scanner is used to perform a full-coverage scan of the annular splicing area. The laser scanner model is limited to a 3D laser scanning device with a ranging accuracy of 0.05mm. The collected point cloud data is arranged at 0.1° intervals along the circumference to ensure that the point cloud density at the annular boundary is 1000 points / cm. 2 The point cloud data was then filtered using statistical filtering to remove isolated points exceeding the mean ± 2 standard deviations, thus eliminating noise interference during scanning. In the processed point cloud, the ring edges were extracted using a threshold segmentation method, with the threshold set to the set of points with a reflection intensity below 0.6 to ensure the continuity of edge points. The final ring boundary data was stored in polar coordinates, with each boundary point containing two parameters: radius r and angle θ. The resolution of the radius data was controlled at 0.01 mm, and the angle resolution at 0.05°. This ring boundary data provides direct input for subsequent geometric contour fitting.

[0044] Step S32: Perform geometric contour fitting based on the ring boundary data to obtain the ring contour data; In this embodiment, the least squares fitting method is used to fit the geometric contour of the boundary point cloud. A high-precision industrial computing terminal is selected as the fitting tool, and the fitting process is limited to two steps: point-by-point fitting and overall residual optimization. The first step involves preliminary fitting using 72 key boundary points selected at 5° intervals to generate an initial contour curve. The second step calculates the overall error between the initial fitting result and all boundary points, using the sum of squared residuals as the error function. If the sum of residuals exceeds... Then the fitting parameters will be automatically adjusted until the sum of the residuals is less than 0.1 mm. 2 Up to this point. The fitted curve type is explicitly limited to a family of quadratic curves, including ellipses, circles, or quasi-ellipses. The fitting parameters include the major axis length *a*, the minor axis length *b*, and the center coordinates. The calculation accuracy of each parameter is controlled within 0.01 mm. After fitting, the generated ring contour data is stored in the form of a vector curve, and the average deviation value between the fitted curve and the original boundary points is marked. This deviation value is required to be less than 0.05 mm.

[0045] Step S33: Perform ellipticity analysis based on the ring profile data to obtain the ring geometric deviation data; In this embodiment, after the geometric contour fitting is completed, ellipticity analysis is performed on the ring contour data. Specifically, the fitting result is compared with the ideal circular contour. First, the major axis *a* and minor axis *b* of the fitted ellipse are calculated, and the ellipticity *E* = *a* / *b* is set. To ensure the rigor of the analysis, the difference between the ellipticity *E* and 1 is used as a deviation index for quantification. The judgment threshold is set to 0.005; when the absolute value of *E-1* is greater than this threshold, a geometric deviation is determined to exist in the ring. Furthermore, the direction of the ellipse's principal axis needs to be analyzed, calculating the angle between the major axis and the ring's docking reference line. The threshold for the angle deviation is set to 0.2°. If the deviation exceeds this value, it is considered a directional deviation in geometric shape. The final generated ring geometric deviation data includes three types of data: ellipticity value, lengths of the major and minor axes, and the angle between the major axis and the reference direction. All data precision is controlled to three decimal places.

[0046] Step S34: Determine the deformation of the ring based on the geometric deviation data of the ring, and obtain the deformation data of the ring; In this embodiment, the judgment logic compares the geometric deviation data with the standard ring assembly tolerance. The standard tolerance values ​​are specified by the manufacturing specifications: ellipticity deviation must not exceed 0.003, major-minor axis difference must not exceed 0.15mm, and major axis included angle deviation must not exceed 0.1°. During the analysis, firstly, the ellipticity deviation is extracted; if the deviation exceeds 0.003, it is judged as elliptical distortion. Secondly, the major-minor axis difference is extracted; if it is greater than 0.15mm, it is judged as radial deformation. Finally, the major axis included angle deviation is compared; if it is greater than 0.1°, it is judged as directional offset. Through this triple judgment method, complete ring deformation data is formed, including deformation type (elliptical distortion, radial deformation, directional offset), deformation value, and corresponding out-of-limit status. All deformation data is stored in tabular form to ensure data format consistency and facilitate subsequent analysis and retrieval.

[0047] Step S35: Perform stability analysis based on the annular deformation data to obtain stability data; In this embodiment, the radial deformation values ​​in the annular deformation data are compared with the annular bearing capacity standard. The bearing capacity standard is that the radial offset of a single point must not exceed 0.2 mm; if it exceeds this standard, it is marked as a structurally unstable point. Next, the deformation distribution along the circumference of the annular piece is extracted and statistically analyzed at sampling points every 15°. The circumferential non-uniformity index is calculated, defined as the difference between the maximum and minimum deformation values, with a threshold of 0.3 mm. If this threshold is exceeded, the overall annular stability is deemed insufficient. Finally, the radial and circumferential non-uniformity results are combined to form stability data, which includes the overall stability level of the annular piece, the number of local unstable regions, and a numerical stability index (value range 0~1, accuracy 0.01). This data provides input for subsequent flange warping detection.

[0048] Step S36: Perform flange face warpage detection based on stability data to obtain flange face warpage data.

[0049] In this embodiment, a contact coordinate measuring machine (CMM) is used. The CMM probe resolution is set to 0.01 mm, and measuring points are arranged at 30° intervals along the circumference of the flange face, for a total of 12 measuring points. First, the height values ​​of each measuring point on the flange face are extracted and compared with the height of the ring plate design reference surface. Next, the height difference between any two points is calculated. If the height difference exceeds 0.05 mm, it is marked as local warping. Then, all height differences are statistically analyzed, the maximum warping value is calculated, and compared with the warping threshold of 0.2 mm. If it exceeds the threshold, it is recorded as an overall warping anomaly. The final generated flange face warping data includes the height of each measuring point, the local warping value, the maximum warping degree, and a warping distribution map. All data is output in a standardized inspection report format for subsequent assembly correction.

[0050] Preferably, step S35 specifically includes: Step S351: Extract the displacement field of the annular piece based on the annular deformation data to obtain displacement field data; In this embodiment, distributed strain gauges and high-resolution displacement sensors are installed on the surface of the ring plate. The strain gauges are limited to resistance strain gauges with a sensitivity coefficient set to 2.1, and the spacing between measuring points is controlled at 50 mm. The displacement sensors are laser displacement sensors with a resolution of at least 0.01 mm, and measuring points are arranged at 10° intervals along the circumference of the ring plate. The acquired data includes two components: radial displacement and axial displacement, with a sampling frequency of 100 Hz to ensure the integrity of the displacement data during dynamic welding. The acquired displacement data is transmitted via wired connection to the data acquisition module, where a 16-bit A / D converter converts the analog signals into digital signals. During the data processing stage, interpolation is performed on the displacement data of all sampling points, using cubic spline interpolation to generate a continuous displacement distribution curve. The final displacement field data includes three types of data: radial displacement distribution, axial displacement distribution, and radial-axial composite displacement field, with a resolution controlled at 0.01 mm. The displacement field matrix is ​​stored in a two-dimensional array for subsequent force analysis.

[0051] Step S352: Perform stress analysis on the ring connection part based on the displacement field data to obtain the connection stress data; In this embodiment, after obtaining the displacement field data, a stress analysis needs to be performed on the ring-plate connection area. The analysis targets the weld connection area and the bolt fixing area between the ring plates. First, the displacement gradient of the weld area is extracted based on the displacement field data, and the strain distribution along the weld length is calculated, requiring a resolution of no less than [specified value]. Then, considering the material parameters of the welded joint, the material is Q345 steel, with a yield strength of 345 MPa and an elastic modulus of [missing value]. With a Poisson's ratio of 0.3, strain data is converted into stress data. For bolted connections, tensile and shear forces are calculated based on the radial displacement difference at the ring opening. The bolt diameter is set to M36, and the tensile stiffness is determined according to... Calculation. The stress analysis employs a partitioned statistical method, dividing the ring into 24 equal partitions. Each partition outputs three types of stress parameters: axial force, radial force, and shear force. The output connection stress data must be accurate within ±5N, in a tabular format, with fields including partition number, force direction, and numerical value. This data provides input for subsequent structural stiffness calculations.

[0052] Step S353: Calculate the stiffness of the ring structure based on the connection force data to obtain the structural stiffness data; In this embodiment, the stress data and displacement field data of the annular plate are compared to obtain the deformation under unit load. Specifically, the average value of the stress data and the corresponding displacement value are taken within each partition to calculate the stiffness coefficient. The stiffness unit is set to... The calculation accuracy is controlled within For the weld area, stiffness calculations need to consider the weld cross-sectional area, with a weld height of 8mm, a weld width of 10mm, and a weld length corresponding to the arc length of each zone. For the bolt area, stiffness calculations need to consider the bolt cross-sectional area and the material's elastic modulus. The cross-sectional area of ​​an M36 bolt is... During the calculation process, if the stiffness of a certain region is less than... If the area is identified as low stiffness, it is marked as such. The final structural stiffness data includes the region number, weld stiffness, bolt stiffness, and total stiffness, stored in matrix form with a resolution set to [resolution value missing]. .

[0053] Step S354: Identify weak areas of the ring plate based on structural stiffness data to obtain weak area distribution data; In this embodiment, the weak zone identification criterion is set as stiffness lower than... Or, the stiffness difference between adjacent regions exceeds 15%. The identification process is as follows: First, the structural stiffness data is traversed, and all regions below the threshold are identified and marked as candidate weak regions. Second, the stiffness difference between adjacent regions is calculated; if the difference is greater than the threshold, the transition region is also classified as a weak region. Finally, the distribution of weak regions is statistically analyzed, and the angular range and total area of ​​weak regions are calculated. The angular range is in degrees, and the area is in millimeters. 2 The output data on weak region distribution includes the number of weak regions, the range of their distribution angles, their area size, and their identification number. This data is used for subsequent stability analysis to ensure that the impact of weak regions on overall performance is quantitatively assessed.

[0054] Step S355: Perform ring plate stability analysis based on weak zone distribution data to obtain stability data.

[0055] In this embodiment, the proportion of the total area of ​​the weak region is statistically analyzed. If the proportion exceeds 10% of the total area of ​​the ring sheet, it is considered to pose a potential stability risk. Secondly, the continuity of the distribution of the weak region along the circumference is calculated. If the continuous distribution angle exceeds 60°, it is determined to have insufficient circumferential stability. Thirdly, the location of the weak region is compared with the area of ​​maximum stress. If the weak region coincides with the area of ​​maximum stress, the stability level is further reduced. The final output stability data includes the stability level (represented by a scale of 0 to 3), the proportion of the weak region area, the range of continuous angles of the weak region, and the degree of overlap between the weak region and the stress area. The data storage format is a multi-field table, and each field is required to be given a quantitative value with precision controlled to two decimal places.

[0056] Preferably, step S36 specifically includes: Step S361: Perform stress detection on the ring material based on stability data to obtain the stress data of the ring material; In this embodiment, a combination of electrical strain gauge technology and ultrasonic velocity method is used. For the electrical strain gauge section, resistance strain gauges, model BX120-5AA, are uniformly arranged on the outer and inner walls of the ring, with a resistance value of [value missing]. The sensitivity coefficient is 2.1, and the spacing between the gauges is 100mm circumferentially and 200mm axially, covering the entire ring. Strain signals are input to a dynamic strain acquisition instrument via a three-wire connection, with a sampling frequency set to 1000Hz and an A / D conversion accuracy of 16 bits to ensure accurate strain data. The strain data is converted to stress data using a linear transformation formula, employing the elastic modulus of Q345D steel. The Poisson's ratio of 0.3 is used as a parameter. The ultrasonic velocity method uses a 5MHz longitudinal wave probe. Measurement points are arranged on the ring material to measure the sound velocity attenuation, and the stress value is inferred from the sound velocity vs. stress curve. The two test results are cross-checked; if the difference exceeds ±5%, the strain gauge data is taken as the standard. The final stress data for the ring material is generated by specifying the section number and stress magnitude (…). The system stores data in three categories: stress direction, etc., with precision controlled within a specified range. .

[0057] Step S362: Perform elastoplastic characteristic analysis based on the stress data of the ring material to obtain elastoplastic data; In this embodiment, stress data is compared with the yield strength of the material, and the yield strength of Q345D steel is limited to [value missing]. The stress value is less than 0.8 times the yield strength (i.e., The region with stress exceeding the yield strength is defined as the elastic region, the region with stress exceeding the yield strength is defined as the plastic region, and the region in between is defined as the elastoplastic transition region. For the elastic region, a linear stress-strain relationship is used for description; for the plastic region, hardening principles are used as a supplement, and the strengthening coefficient is calculated using the relationship between strain increment and stress increment in each region. The strengthening coefficient is set to [value missing]. For the transition zone, the nonlinear distribution of the stress-strain curve is obtained through piecewise interpolation. During the analysis, the annular plate is divided into 24 equal parts, and each part outputs an elastoplastic state identifier (0 for elasticity, 1 for plasticity, and 2 for elastoplastic transition). The final elastoplastic data includes four fields: partition number, average stress value, strain increment, and state identifier, stored as a two-dimensional table with a data accuracy of no less than 0.01%.

[0058] Step S363: Calculate fatigue deformation based on the elastoplastic data to obtain fatigue deformation data; In this embodiment, based on the elastoplastic state, the maximum principal stress in each region is used as the calculation input. Fatigue cyclic load parameters are collected using an acceleration sensor mounted on the tower, with a sensor sensitivity of [insert sensitivity here]. sampling frequency Monitoring the number of stress cycles under wind load and operational excitation. Cyclic stress amplitude and material properties. According to the curve comparison, the fatigue limit of Q345D steel is set as follows: If the stress amplitude exceeds this value, the calculation area enters a high-risk fatigue state. Using the Palmgren-Miner linear cumulative damage method, the number of cycles and stress level for each partition are accumulated to obtain a damage factor. If the damage factor exceeds 1.0, the region is determined to be a fatigue failure zone. Fatigue deformation data includes partition number, cyclic stress amplitude, cumulative damage factor, and residual life (expressed in hours), with an accuracy controlled to 1 hour. The final fatigue deformation matrix is ​​a 24×4 two-dimensional array.

[0059] Step S364: Identify the deformation trend of the flange surface based on fatigue deformation data; In this embodiment, fatigue deformation data is extracted from the edge region of the annular flange near the flange face, particularly the weld and bolt connection areas. If the residual life is less than 5000 hours or the damage factor exceeds 0.8, the area is marked as a high-risk area on the flange face. Subsequently, these high-risk areas are sorted circumferentially, and their continuous distribution angles are calculated. If the continuous angle exceeds 45°, the area is determined to have a circumferential deformation trend. Combined with radial data, if the cumulative radial deformation exceeds 2 mm, and this value exceeds the design allowable value of 1.5 mm, it is identified as a radial deformation trend. The trend identification output includes directional indicator (circumferential or radial), angle range, cumulative displacement, and life reduction ratio. The data is stored in tabular form, with the accuracy of each field controlled to 0.1 mm or 0.1%.

[0060] Step S365: Perform flange warping analysis based on the flange deformation trend to obtain flange warping data.

[0061] In this embodiment, a 3D laser scanner with a scanning accuracy of 0.05mm and a point cloud spacing of no more than 1mm is used. Point cloud data of the flange surface is obtained through scanning and compared with a standard design plane. First, plane fitting is performed to calculate the equation of the reference plane; then, all point cloud data are projected onto the reference plane, and the deviation between the flange surface and the reference plane is calculated. If the deviation exceeds ±1.5mm, the area is determined to be warped. The area of ​​the warped region is calculated using an integral method; if the area of ​​a single warped region is greater than 5000mm², the warped region is considered warped. 2 Areas with warpage are marked as key failure zones. The final generated flange warpage data includes four fields: warpage zone number, maximum warpage amount, warpage direction, and area, with data accuracy controlled to 0.05 mm. The analysis results are stored in both 3D point cloud plots and numerical tables to ensure traceability and engineering verification.

[0062] Preferably, step S365 specifically includes: Identify high-deformation areas of the flange plate based on the deformation trend of the flange surface; In this embodiment, a precision 3D laser scanner is used to collect point clouds on the surface of the ring sheet. The scanning accuracy is 0.05 mm, the point cloud spacing is 1 mm, and the entire flange area of ​​the ring sheet is covered. Using a 3D point cloud comparison method, the collected data is fitted to a standard design plane, and the reference plane is determined using the least squares method. By calculating the deviation value of each scanning point from the reference plane, a deviation matrix is ​​generated, with the matrix element accuracy controlled within 0.01 mm. A high deformation threshold is set to ±1.5 mm. Continuous areas with deviations exceeding the threshold are clustered according to the circumferential and radial directions, classifying continuous deviation areas into high deformation regions. Each high deformation region is identified by a number, start and end angles, radial length, and maximum deviation, forming a high deformation region data table for the ring sheet. Statistical analysis of the deviation direction shows the deformation concentration trend of the ring sheet in the circumferential or radial directions, with data accuracy maintained at 0.05 mm, facilitating subsequent grain morphology analysis and local stress calculation.

[0063] Grain morphology data were obtained by detecting the grain morphology in the high-deformation region of the annular plate. In this embodiment, a scanning electron microscope (SEM) was used to inspect the grain morphology. Grain size was measured using Backscattered Electron mode, with an operating voltage of 15 kV, a magnification of 5000x, and a resolution of [missing information]. Scan at least five different locations within the high-deformation region, acquiring an area of ​​at least [area not specified] at each location. Grain images were obtained. Grain boundaries were automatically extracted using image processing software, with the boundary detection threshold set to 90-220 grayscale values ​​(0-255) to remove noise points. The major axis, minor axis, and equivalent diameter of each grain were measured, and grain shape parameters, area, and orientation were recorded. A grain morphology data table was finally generated, including location number, major axis length, minor axis length, equivalent diameter, and aspect ratio. Data accuracy was controlled within [specific parameters]. .

[0064] Grain distribution data is obtained by analyzing the grain morphology data. In this embodiment, a two-dimensional coordinate grid is established on the surface of the annular sheet, and the grid size is set to... The grain centers are projected onto a grid, and the number and average size of grains within each grid cell are counted. A grain distribution matrix is ​​generated by calculating the local grain density (number of grains per unit area) and dimensional variance. The matrix records the grain density, average grain diameter, average aspect ratio, and variance for subsequent stress concentration analysis. Regions with anomalous distribution (density 1.5 times higher or 0.5 times lower than the average) are marked, and a grain distribution data table is generated, ensuring data accuracy is controlled within 0.01 μm to facilitate precise identification of grain boundary stress concentration regions.

[0065] Grain boundary stress concentration data is obtained by detecting grain boundary stress concentration based on grain distribution data. In this embodiment, the grain distribution matrix is ​​imported into finite element micromodeling software to establish a grain mesh model of the high-deformation region of the annular plate, with the element size set to 1 / 10 of the average grain diameter. Actual operating loads are applied to the model, including circumferential tensile stress, radial compressive stress, and local stress at bolted connections, with load values ​​as follows: , Local stress in bolts The stress values ​​on each grain boundary were calculated using finite element analysis. The maximum principal stress and shear stress were recorded. Grain boundary regions exceeding the grain boundary yield strength of 180 MPa were marked as stress concentration areas. A grain boundary stress concentration data table was generated, with fields including grain boundary number, maximum principal stress, shear stress, and stress direction. The data accuracy was controlled to 0.1 MPa.

[0066] Grain slip analysis was performed based on grain boundary stress concentration data to obtain grain slip data; In this embodiment, a stress vector is applied to the marked stress concentration area, and the cumulative shear strain value inside the grain is calculated. The shear strain threshold is set to 0.002, and grain boundaries exceeding the threshold are determined to be slip regions. The analysis method uses a crystal plastic finite element micro-model with a mesh size of 1 / 20 of the average grain diameter to simulate the local slip of the ring under load. The slip direction, slip amount, and cumulative shear strain of each grain are recorded to generate a grain slip data table, with fields including grain number, slip amount (…). ), Slip direction angle ( ) and cumulative shear strain, with accuracy respectively and .

[0067] Flange face warpage is determined based on grain slip data, and flange face warpage data is obtained.

[0068] In this embodiment, the slip amount and direction are mapped to the three-dimensional coordinate system of the flange surface, and a warpage height field is generated by interpolation, with a grid spacing of 0.5 mm. The maximum warpage and average warpage gradient of the entire flange surface are statistically analyzed. If the local slippage accumulates to exceed... The area is then marked as a warping focus area. A flange face warping data table is generated, with fields including area number, maximum warping amount (mm), average warping gradient (mm / m), and location coordinates (x, y, z), with data precision of 0.01mm and 0.1mm / m respectively, for subsequent ring assembly compensation analysis.

[0069] Preferably, step S4 specifically includes: Step S41: Analyze the deformation of the circumferential joint based on the flange warping data to obtain the joint deformation data; In this embodiment, a three-dimensional coordinate measuring machine (CMM) is used to precisely scan the annular joint area with a scanning resolution of 0.05 mm and a point spacing of 1 mm, covering the entire circumferential and radial range of the annular joint. The scanned point cloud is fitted to a standard design geometry, and the point cloud coordinates are projected onto a reference plane to calculate the vertical deviation value of each joint point, with the deviation accuracy controlled within 0.01 mm. For areas with continuous deviation values ​​exceeding ±0.5 mm, cluster analysis is performed along the circumferential direction to determine the joint deformation areas. For each joint deformation area, the maximum deviation, average deviation, and deformation gradient are calculated, generating a joint deformation data table containing the joint number, deviation range, radial and circumferential positions, maximum deviation, and average deviation, providing a data foundation for subsequent gasket thickness calculations.

[0070] Step S42: Calculate the gasket thickness requirement based on the joint deformation data to obtain the gasket thickness data; In this embodiment, the required thickness of the gasket between the ring plates is calculated using the finite element method (FEM) stress analysis based on the joint deformation data. The joint deformation data is mapped onto the three-dimensional structural model of the ring plate, and the ring plate material parameters are loaded: steel plate elastic modulus 210 GPa, Poisson's ratio 0.3, and thickness 30 mm. According to the relationship between the maximum joint deviation and the gasket compression deformation, the gasket compression rate threshold is set to 0.2~0.5 mm. If it exceeds this range, the thickness is adjusted in segments. The required gasket thickness at each joint point is calculated, and the thickness values ​​are evenly distributed circumferentially to generate a gasket thickness data table. The fields include joint number, location coordinates, calculated thickness value, compression rate, and allowable material compression. The accuracy is controlled within 0.01 mm to ensure uniform stress on the gasket during installation.

[0071] Step S43: Perform gasket arrangement optimization analysis based on gasket thickness data to obtain gasket arrangement data; In this embodiment, the gasket thickness data is imported into the layout optimization program to establish a three-dimensional model of the ring joint layout. The layout rules are as follows: gaskets are evenly distributed along the joint, with a support point set every 50mm. The gasket thickness at each support point is the calculated value ±0.01mm. The gradient descent method is used to fine-tune the gasket thickness distribution, minimizing the joint deformation gradient and ensuring that the force on each support point does not exceed the material's allowable pressure of 120MPa. During the analysis, the positions of the ring connecting bolts remain fixed. The number, coordinates, and thickness of each gasket position are recorded, generating a gasket layout data table including the layout sequence number, ring joint number, position coordinates, and thickness information for overall compensation effect evaluation.

[0072] Step S44: Evaluate the overall ring compensation effect based on the gasket arrangement data to obtain gasket compensation data; In this embodiment, based on the gasket arrangement data, the thickness of each gasket is mapped onto the three-dimensional model of the ring, and finite element analysis software is used to simulate the overall stress on the ring. The applied load conditions include a bolt preload of 80 kN, a circumferential wind load of 1.2 kPa, and radial self-weight pressure. The material parameters are a steel plate elastic modulus of 210 GPa and a Poisson's ratio of 0.3. The maximum residual warpage, displacement gradient, and bolt stress distribution of the joint and flange surface after compensation are calculated. The results are compiled into a gasket compensation data table, with fields including ring number, joint location, maximum residual deviation after compensation, average deviation, and stress value, with an accuracy controlled to 0.01 mm, for use in subsequent tilt fine-tuning and concentricity calculations.

[0073] Step S45: Perform tilt fine-tuning based on shim compensation data to obtain tilt fine-tuning data; In this embodiment, the installation position of the ring piece is fine-tuned using shim compensation data. The fine-tuning operation employs a hydraulic jack and a high-precision laser target positioning device. The jack stroke is 0-10mm with an adjustment accuracy of 0.01mm, and the laser target measurement accuracy is 0.1mm. Based on the distribution of joint deviation after compensation, height fine-tuning is performed in circumferential segments, with each segment's adjustment range not exceeding ±0.5mm to avoid localized stress concentration. The adjustment position, adjustment amount, and direction are recorded for each adjustment segment, generating a tilt fine-tuning data table including segment number, ring piece number, fine-tuning amount, direction, and post-fine-tuning deviation value. Accuracy is controlled within 0.01mm to ensure the fine-tuning process is traceable and quantifiable.

[0074] Step S46: Calculate the concentricity of the wind turbine tower based on the tilt fine-tuning data and generate the concentricity assessment results.

[0075] In this embodiment, using the tower centerline as a reference, the offset between the center of each ring segment and the centerline is calculated, with the offset accuracy controlled within 0.01 mm. An overall concentricity distribution map is generated by accumulating the offsets of each ring segment, recording the maximum eccentricity, average eccentricity, and eccentricity direction. A concentricity evaluation result table is generated, with fields including ring segment number, center coordinate offset, maximum eccentricity, average eccentricity, and eccentricity angle, with accuracy controlled within 0.01 mm. This ensures that the concentricity data can be used for subsequent tower verticality adjustment and fatigue analysis.

[0076] Preferably, step S45 specifically includes: Step S451: Adjust the ring height based on the shim compensation data to obtain the ring height data; In this embodiment, based on the shim compensation data, the required thickness at each ring joint is mapped onto the three-dimensional geometric model of the ring to determine the ring installation height adjustment amount. The installation height adjustment is achieved using hydraulic jacks, with a maximum stroke of 10mm and an adjustment accuracy of 0.01mm. Each ring is equipped with four jacks, evenly distributed along the circumference. The ring height adjustment amount is determined based on the shim compensation thickness and the joint deformation gradient, with the single-point adjustment range controlled within ±0.5mm to avoid local stress concentration. The height adjustment operation is monitored in real-time using a laser rangefinder and a total station, with a measurement accuracy of 0.1mm. The height value of each jack is recorded through a data acquisition system, generating a ring height data table including the ring number, jack number, adjustment position, adjustment amount, and real-time measurement value, ensuring that the height adjustment process is traceable and quantifiable.

[0077] Step S452: Identify the tilting trend of the ring joint based on the ring height data; In this embodiment, the relative height difference along the circumference of each joint is calculated using the ring plate height data. A joint inclination curve is then plotted using the height difference between adjacent joint points and the circumferential position coordinates, with a curve resolution of 1 mm / point. The local slope is calculated by differentiating the joint inclination curve; if the slope exceeds... The sections are marked as high-inclination trend areas. Inclination trend data is correlated with ring numbers and joint numbers to generate an inclination trend database, including start and end positions, maximum inclination angle, average inclination angle, and inclination direction information, for use in fine-tuning scheme formulation. Inclination trend analysis uses numerical interpolation methods to process height data, smoothing the curve and eliminating measurement noise, ensuring the accuracy of the fine-tuning scheme.

[0078] Step S453: Generate a tilt fine-tuning scheme based on the tilt trend of the ring joint; In this embodiment, based on the joint tilt trend, the high-tilt section is divided into several fine-tuning units, each with a length of 50-100mm. The fine-tuning scheme determines the required adjustment height and direction for each fine-tuning unit. The adjustment amount is calculated from the local tilt angle and joint deviation, and the unit adjustment range does not exceed ±0.5mm. The fine-tuning operation sequence follows the circumferential distribution of the ring piece, proceeding from the bottom to the top sequentially to prevent cumulative errors. The scheme records the number, start and end positions, adjustment amount, adjustment direction, and corresponding jack number of each fine-tuning unit, forming a complete tilt fine-tuning scheme table with an accuracy controlled within 0.01mm, facilitating subsequent implementation and operation reference.

[0079] Step S454: Correct the ring plate installation position based on the tilt fine-tuning scheme to obtain the corrected ring plate installation position; In this embodiment, the installation position of the ring piece is adjusted according to the fine-tuning scheme. The installation position correction is achieved through a combination of a sliding support on the ring piece base and hydraulic jacks. The jack stroke is 0-10mm, with an adjustment accuracy of 0.01mm, and the base allows for a horizontal displacement of ±5mm. The center coordinates and tilt angle of the ring piece are measured using a laser tracker with a measurement accuracy of 0.1mm, and the position data is recorded in real time. The jack movement is controlled according to the adjustment amount and direction of each unit in the fine-tuning scheme to achieve joint tilt correction. The ring piece installation correction position record includes the ring piece number, fine-tuning unit number, center coordinate correction amount, tilt correction angle, and jack position, generating an installation correction position data table to ensure that the correction position data can be used for evaluation and final concentricity verification.

[0080] Step S455: Perform tilt fine-tuning evaluation based on the ring plate installation correction position to obtain tilt fine-tuning data.

[0081] In this embodiment, after the ring plate is installed and corrected, a three-dimensional laser scan is used to precisely measure the entire ring plate with a point spacing of 1 mm and an accuracy of 0.05 mm. The height data of the circumference and radial direction of the corrected joint are collected. Based on the scan data, the actual tilt angle and height adjustment amount of each fine-tuning unit are calculated and compared with the fine-tuning scheme to calculate the execution error, with the error accuracy controlled within 0.01 mm. The actual adjustment amount, target adjustment amount, deviation value, and center coordinates of each unit are recorded to generate a tilt fine-tuning execution evaluation data table, providing a complete data foundation for subsequent concentricity calculations and ensuring that the fine-tuning implementation process is accurate, traceable, and quantifiable.

[0082] Therefore, the embodiments should be considered exemplary and non-limiting in all respects, and the scope of the invention is defined by the appended claims rather than the foregoing description. Thus, all variations falling within the meaning and scope of the equivalents of the application are intended to be included within the invention.

[0083] The above description is merely a specific embodiment of the present invention, enabling those skilled in the art to understand or implement the invention. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the invention. Therefore, the present invention is not to be limited to the embodiments shown herein, but is to be accorded the widest scope consistent with the principles and novel features of the invention herein.

Claims

1. A method for controlling the concentricity of a wind turbine tower, characterized in that, Includes the following steps: Step S1: Obtain the wind turbine tower installation reference data; determine the ring center offset based on the wind turbine tower installation reference data to obtain the ring offset data; Concentricity detection is performed based on the ring offset data to generate initial concentricity data. Step S1 specifically involves: Step S11: Obtain the installation reference data for the wind turbine tower; Step S12: Determine the installation position of the ring plate based on the wind turbine tower installation reference data, and obtain the ring plate installation position data; Step S13: Identify the center reference based on the ring installation position data; Step S14: Calculate the center offset based on the center reference to obtain the ring offset data; Step S15: Perform concentricity detection based on the ring offset data to generate initial concentricity data; Step S2: Perform deviation analysis based on the initial concentricity data to obtain deviation data; identify abnormal ring pieces based on the deviation data to obtain abnormal ring piece data; Step S3: Detect ring deformation based on abnormal ring plate data to obtain ring deformation data; perform stability analysis based on ring deformation data to obtain stability data; and detect flange face warping based on stability data to obtain flange face warping data. Specifically, Step S3 involves: Step S31: Extract the ring boundary based on the abnormal ring data to obtain the ring boundary data; Step S32: Perform geometric contour fitting based on the ring boundary data to obtain the ring contour data; Step S33: Perform ellipticity analysis based on the ring profile data to obtain the ring geometric deviation data; Step S34: Determine the deformation of the ring based on the geometric deviation data of the ring, and obtain the deformation data of the ring; Step S35: Perform stability analysis based on the annular deformation data to obtain stability data; Step S36: Perform flange face warpage detection based on stability data to obtain flange face warpage data; Step S4: Perform ring gasket compensation analysis based on flange warping data to obtain gasket compensation data; perform tilt fine-tuning based on gasket compensation data, and calculate the concentricity of the wind turbine tower to generate concentricity evaluation results. Step S4 specifically includes: Step S41: Analyze the deformation of the circumferential joint based on the flange warping data to obtain the joint deformation data; Step S42: Calculate the gasket thickness requirement based on the joint deformation data to obtain the gasket thickness data; Step S43: Perform gasket arrangement optimization analysis based on gasket thickness data to obtain gasket arrangement data; Step S44: Evaluate the overall ring compensation effect based on the gasket arrangement data to obtain gasket compensation data; Step S45: Perform tilt fine-tuning based on shim compensation data to obtain tilt fine-tuning data; Step S46: Calculate the concentricity of the wind turbine tower based on the tilt fine-tuning data and generate the concentricity assessment results.

2. The method for controlling the concentricity of wind turbine towers according to claim 1, characterized in that, Step S15 is as follows: Step S151: Compare the ring offset data with the centerline of the wind turbine tower to obtain centerline comparison data; Step S152: Calculate the concentricity deviation based on the centerline comparison data to obtain the concentricity deviation data; Step S153: Perform deviation trend analysis based on concentricity deviation data to obtain deviation trend data; Step S154: Determine the concentricity level based on the deviation trend data to obtain the initial concentricity data.

3. The method for controlling the concentricity of wind turbine towers according to claim 1, characterized in that, Step S35 is as follows: Step S351: Extract the displacement field of the annular piece based on the annular deformation data to obtain displacement field data; Step S352: Perform stress analysis on the ring connection part based on the displacement field data to obtain the connection stress data; Step S353: Calculate the stiffness of the ring structure based on the connection force data to obtain the structural stiffness data; Step S354: Identify weak areas of the ring plate based on structural stiffness data to obtain weak area distribution data; Step S355: Perform ring plate stability analysis based on weak zone distribution data to obtain stability data.

4. The method for controlling the concentricity of wind turbine towers according to claim 1, characterized in that, Step S36 is as follows: Step S361: Perform stress detection on the ring material based on stability data to obtain the stress data of the ring material; Step S362: Perform elastoplastic characteristic analysis based on the stress data of the ring material to obtain elastoplastic data; Step S363: Calculate fatigue deformation based on the elastoplastic data to obtain fatigue deformation data; Step S364: Identify the deformation trend of the flange surface based on fatigue deformation data; Step S365: Perform flange warping analysis based on the flange deformation trend to obtain flange warping data.

5. The method for controlling the concentricity of wind turbine towers according to claim 1, characterized in that, Step S45 is as follows: Step S451: Adjust the ring height based on the shim compensation data to obtain the ring height data; Step S452: Identify the tilting trend of the ring joint based on the ring height data; Step S453: Generate a tilt fine-tuning scheme based on the tilt trend of the ring joint; Step S454: Correct the ring plate installation position based on the tilt fine-tuning scheme to obtain the corrected ring plate installation position; Step S455: Perform tilt fine-tuning evaluation based on the ring plate installation correction position to obtain tilt fine-tuning data.

6. A wind turbine tower concentricity control system, characterized in that, For executing the wind turbine tower concentricity control method as described in claim 1, the wind turbine tower concentricity control system includes: The concentricity detection module is used to acquire the wind turbine tower installation reference data; determine the ring center offset based on the wind turbine tower installation reference data to obtain the ring offset data; and perform concentricity detection based on the ring offset data to generate initial concentricity data. The deviation analysis module is used to perform deviation analysis based on the initial concentricity data to obtain deviation data; based on the deviation data, it identifies the abnormal ring pieces and obtains the abnormal ring piece data. The stability analysis module is used to detect ring deformation based on abnormal ring plate data to obtain ring deformation data; to perform stability analysis based on the ring deformation data to obtain stability data; and to detect flange face warping based on the stability data to obtain flange face warping data. The gasket compensation module is used to perform ring gasket compensation analysis based on flange warping data to obtain gasket compensation data; based on the gasket compensation data, it performs tilt fine-tuning and calculates the concentricity of the wind turbine tower to generate concentricity assessment results.

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