Distributed settlement intelligent sensing and data acquisition system for mudflat photovoltaic pile foundation

Abstract

The invention discloses a mudflat photovoltaic pile foundation distributed settlement intelligent sensing and data acquisition system, and belongs to the technical field of intelligent sensing systems.The system comprises a datum plane setting module which is used for setting a main datum plane and a plurality of sub datum planes according to spatial distribution of a mudflat photovoltaic pile foundation; the region division module is used for dividing the plurality of beach photovoltaic pile foundations into a plurality of sub-regions in a set space range, and calculating the average main reference surface elevation of each sub-region; the processing module is used for identifying whether the mud flat photovoltaic pile foundation is settled or not according to the single mud flat photovoltaic pile foundation in each sub-region; the analysis and comparison module is used for comparing a difference value with a preset deformation threshold value after the settlement of the tidal flat photovoltaic pile foundation is identified; and the intelligent acquisition and positioning module automatically triggers a preset data acquisition process when the difference value exceeds a preset deformation threshold value. According to the method, the sub datum planes are arranged in the height direction of the pile body, so that the comprehensiveness and spatial resolution of deformation monitoring are improved.

Description

Technical Field

[0001] This invention relates to the field of intelligent sensing system technology, and in particular to an intelligent sensing and data acquisition system for distributed settlement of photovoltaic pile foundations in tidal flats. Background Technology

[0002] Photovoltaic pile foundations refer to pile foundation structures installed in coastal tidal flats to support photovoltaic power generation systems. They typically adopt fixed or floating pile foundation designs to utilize vast tidal flat resources to generate clean energy while avoiding the occupation of agricultural land.

[0003] In existing technologies, settlement monitoring of photovoltaic pile foundations on tidal flats mainly relies on setting a single measuring point at the top of the pile, periodically collecting the elevation data of the pile top using a level or fixed sensor, and comparing it with the initial reference surface to determine whether the pile foundation has experienced uniform settlement.

[0004] However, this traditional method has significant limitations: its single-point measurement mode can only acquire the elevation change at the top of the pile, and cannot detect distributed deformation modes such as bending, tilting, or deep deflection that may occur along the height of the pile. Especially for photovoltaic pile foundations with a large slenderness ratio, the overall stability assessment needs to integrate the top settlement and pile deformation behavior, while single-point data is difficult to reveal the risk of local stress concentration or gradual bending, resulting in delayed deformation early warning and insufficient comprehensive assessment. Therefore, there is an urgent need to provide an intelligent sensing and data acquisition system for distributed settlement of photovoltaic pile foundations in tidal flats to solve the above problems. Summary of the Invention

[0005] The technical problem to be solved by the present invention is to overcome the fact that the existing single-point measurement mode can only obtain the elevation change of the pile top and cannot sense the distributed deformation modes such as bending, tilting or deep deflection that may occur in the pile body along the height direction. Especially for photovoltaic pile foundations with large slenderness ratio, the overall stability assessment needs to combine the top settlement and pile body deformation behavior. However, single-point data is difficult to reveal the risk of local stress concentration or gradual bending, resulting in the disadvantage of delayed deformation early warning and insufficient integrity assessment. The present invention provides an intelligent sensing and data acquisition system for distributed settlement of tidal flat photovoltaic pile foundations.

[0006] To solve the above-mentioned technical problems, one technical solution adopted by the present invention is: to provide a distributed settlement intelligent sensing and data acquisition system for tidal flat photovoltaic pile foundations, including a reference surface setting module, a region division module, a processing module, an analysis and comparison module, and an intelligent acquisition and positioning module;

[0007] The reference plane setting module sets a main reference plane and several sub-reference planes according to the spatial distribution of photovoltaic pile foundations on the tidal flats;

[0008] The region division module divides multiple tidal flat photovoltaic pile foundations into several sub-regions based on a set spatial range, and obtains the initial principal reference surface elevation and initial sub-reference surface elevation of all tidal flat photovoltaic pile foundations in each sub-region, and calculates the average principal reference surface elevation of each sub-region.

[0009] The processing module calculates, for each individual tidal flat photovoltaic pile foundation in each sub-region, the first deviation between the elevation of its uppermost initial sub-reference plane and the average main reference plane elevation, and after a preset time period, recalculates the second deviation between the elevation of the uppermost initial sub-reference plane and the main reference plane elevation of the same tidal flat pile foundation in the same sub-region based on the same main reference plane elevation; by comparing whether the difference between the first deviation and the second deviation exceeds a preset settlement threshold, it identifies whether the tidal flat photovoltaic pile foundation has settled.

[0010] The analysis and comparison module, after identifying that the photovoltaic pile foundation on the tidal flat has settled, compares the difference with a preset deformation threshold.

[0011] The intelligent acquisition and positioning module automatically triggers a preset data acquisition process for the target tidal flat photovoltaic pile foundation when the difference exceeds the preset deformation threshold, and locates the specific deformation part of the tidal flat photovoltaic pile foundation based on the data acquired by the preset data acquisition process.

[0012] The present invention is further configured such that: the uppermost sub-reference surface in the reference surface setting module is located at the top of the tidal flat photovoltaic pile foundation, the lowermost sub-reference surface is located at the bottom of the tidal flat photovoltaic pile foundation, and several sub-reference surfaces are distributed on both sides of the main reference surface along the pile height direction of the tidal flat photovoltaic pile foundation, covering the overall height range of all tidal flat photovoltaic pile foundations.

[0013] The present invention is further configured such that the steps for setting the main reference plane and several sub-reference planes are as follows:

[0014] S1. Obtain initial spatial positioning data of all tidal flat photovoltaic pile foundations within the target area. Based on the initial spatial positioning data, calculate the center point of the planar distribution of all tidal flat photovoltaic pile foundations. Calculate the spatial Euclidean distance between each tidal flat photovoltaic pile foundation and the center point. Sort all tidal flat photovoltaic pile foundations in ascending order according to the spatial Euclidean distance. Select the tidal flat photovoltaic pile foundation ranked first in the sorting and define it as a reference pile foundation. Measure the spatial coordinate points of the reference pile foundation evenly distributed at a preset distance along the pile height direction. Based on the spatial coordinate points, calculate its geometric central axis. Define the plane perpendicular to the geometric central axis and passing through the midpoint of the geometric central axis calculated from the spatial coordinate points evenly distributed at the preset distance as the main reference plane. The midpoint of the geometric central axis defines the spatial position of the main reference plane, and the direction of the geometric central axis defines the normal vector direction of the main reference plane.

[0015] S2. Based on the determined main reference plane and its normal vector direction, along the geometric center axis in the upward and downward directions, a series of virtual planes parallel to the main reference plane are defined at preset equal intervals or at preset non-equal intervals according to the characteristics of the pile structure. The virtual planes are sub-reference planes. The uppermost sub-reference plane must be located at the designed position of the top of the reference pile foundation, and the lowermost sub-reference plane must be located at the designed position of the bottom of the reference pile foundation.

[0016] S3. Simultaneously apply steps S1 and S2 to all other tidal flat photovoltaic piles in the target area except for the reference pile, to complete the unified setting of the main reference surface and sub-reference surface system for all tidal flat photovoltaic piles in the entire monitoring area.

[0017] The present invention is further configured such that the division steps of the several sub-regions in the region division module are as follows:

[0018] Q1. Based on the spatial position and normal vector direction of the main reference plane, the spatial coordinates of each tidal flat photovoltaic pile foundation are orthogonally projected onto the main reference plane to obtain the projection point set of all tidal flat photovoltaic pile foundations. The spatial Euclidean distance between each point in the projection point set is calculated. According to the preset adjacency threshold, the projection points with mutual spatial Euclidean distance less than the adjacency threshold are dynamically aggregated into an initial sub-region core point group. And a preliminary sub-region boundary is generated with each initial sub-region core point group as the center.

[0019] Q2. For each of the preliminary sub-region boundaries, calculate the geometric centroid position of all projection points within it, and perform boundary optimization adjustment based on the overlap between the geometric centroid position and the adjacent preliminary sub-region boundaries. At the same time, introduce the uniformity of the initial main reference surface elevation value of the tidal flat photovoltaic pile foundation in each of the sub-regions as a constraint condition, and iteratively optimize the preliminary sub-region boundaries to form the sub-region division result.

[0020] The present invention is further configured such that: the initial main reference surface elevation in the region division module is acquired by an inclinometer and measuring rod device deployed on each tidal flat photovoltaic pile foundation; the initial sub-reference surface elevation is acquired by a displacement sensor installed at a preset position on each sub-reference surface;

[0021] The steps for calculating the average principal datum elevation for each sub-region are as follows:

[0022] For each sub-region divided in step Q2, the original observation values ​​of the initial master reference elevation of all tidal flat photovoltaic pile foundations within it are extracted to form the original elevation dataset of the sub-region.

[0023] Q4. Preprocess the original elevation dataset, remove data points that exceed the preset abnormal threshold, and fill in the removed locations using the normal elevation values ​​of adjacent tidal flat photovoltaic pile foundations through linear interpolation to generate the effective elevation dataset of the sub-region.

[0024] Q5. Calculate the average principal datum elevation based on the effective elevation dataset, specifically by summing the initial principal datum elevation values ​​of all tidal flat photovoltaic piles in the effective elevation dataset to obtain the sum of the initial principal datum elevations of the sub-region, and then dividing the sum of the initial principal datum elevations by the total number of tidal flat photovoltaic piles included in the effective elevation dataset. The quotient is the average principal datum elevation of the sub-region.

[0025] The average elevation of the principal datum plane remains constant.

[0026] The present invention is further configured such that: the method for obtaining the preset settlement threshold in the processing module is as follows: during the initial operation phase of the system, the time series data of the initial main reference surface elevation of all tidal flat photovoltaic pile foundations in each sub-region within a preset historical learning period is obtained, the standard deviation of the initial main reference surface elevation value in the time series data is calculated, and the preset multiple of the standard deviation is set as the preset settlement threshold of the sub-region.

[0027] If the difference exceeds the preset settlement threshold, it is determined that the photovoltaic pile foundation on the tidal flat has settled.

[0028] The present invention is further configured such that the preset deformation threshold in the analysis and comparison module is greater than the preset settlement threshold.

[0029] The present invention is further configured such that: the intelligent acquisition and positioning module automatically triggers a preset data acquisition process for the target tidal flat photovoltaic pile foundation, and locates the specific deformation parts of the tidal flat photovoltaic pile foundation based on the data acquired according to the preset data acquisition process.

[0030] T1. When the difference output by the analysis and comparison module exceeds the preset deformation threshold, the high-frequency data acquisition mode is automatically started. The elevation data of the current sub-reference surface is collected in real time for each sub-reference surface on the target tidal flat photovoltaic pile foundation. The elevation change between the current elevation data of each sub-reference surface and the initial sub-reference surface elevation is calculated. The elevation change of all sub-reference surfaces arranged in order of the height of the tidal flat photovoltaic pile foundation is combined into a sequence of span values ​​distributed along the vertical direction of the tidal flat photovoltaic pile foundation.

[0031] T2. Based on the span value sequence, analyze the variation law of all span values ​​in the span value sequence along the height direction of the photovoltaic pile body in the tidal flat: detect the change value of the elevation change between adjacent sub-reference planes in the span value sequence. If the absolute value of the change value exceeds the abrupt change judgment threshold preset according to historical settlement data, the interval between adjacent sub-reference planes is marked as a candidate deformation interval. At the same time, the average change rate of the span value in the candidate deformation interval at different heights is calculated using a preset sliding window method. The candidate deformation intervals whose average change rate exceeds the gradient judgment threshold preset according to the material deformation characteristics are identified as potential bending or tilting intervals.

[0032] T3. Perform spatial correlation analysis on the candidate deformation interval and the potential bending or tilting interval: if there is an intersection between the two, the overlapping area is determined to be the specific part of the pile foundation bending or shear deformation; if there is no intersection, the average rate of change of the candidate deformation interval is further calculated. When the average rate of change continuously exceeds the preset gradient judgment threshold, the candidate deformation interval is classified as an independent compression deformation part, and the potential bending or tilting interval is determined as the overall deflection-dominant area. The deformation part location result and deformation mode classification information are output.

[0033] The present invention is further configured such that: in step T3, if there is an intersection between the two, that is, if the candidate deformation interval and the potential bending or tilting interval coincide in vertical space or the boundary distance is less than the preset adjacency tolerance, the specific judgment method is as follows:

[0034] T301. Extract the upper and lower vertical height coordinates of the candidate deformation interval and the upper and lower vertical height coordinates of the potential bending or tilting interval respectively. Calculate the height span value of each of the candidate deformation interval and the potential bending or tilting interval based on the upper and lower vertical height coordinates. Compare the upper vertical height coordinate of the candidate deformation interval with the lower vertical height coordinate of the potential bending or tilting interval, and simultaneously compare the lower vertical height coordinate of the candidate deformation interval with the upper vertical height coordinate of the potential bending or tilting interval. Determine the relative positional relationship of the candidate deformation interval and the potential bending or tilting interval in the vertical direction based on the comparison results.

[0035] T302. Based on the relative positional relationship, calculate the vertical overlap distance or nearest boundary distance between the candidate deformation interval and the potential bending or tilting interval: If the vertical height range of the candidate deformation interval and the potential bending or tilting interval overlaps, then the vertical distance of the overlapping portion is the vertical overlap distance; if the candidate deformation interval and the potential bending or tilting interval do not overlap in the vertical direction, then the calculation is based on the positional relationship of the candidate deformation interval above or below the potential bending or tilting interval in the vertical direction: If the candidate deformation interval is above the potential bending or tilting interval, then calculate the lower limit coordinate of the vertical height of the candidate deformation interval minus... The absolute value of the difference between the upper limit of the vertical height coordinates of the potential bending or tilting interval is used as the nearest boundary interval distance. If the candidate deformation interval is located below the potential bending or tilting interval, the absolute value of the difference between the lower limit of the vertical height coordinates of the potential bending or tilting interval and the upper limit of the vertical height coordinates of the candidate deformation interval is calculated and used as the nearest boundary interval distance. The calculated vertical overlap distance or the nearest boundary interval distance is compared with the preset adjacency tolerance. If the vertical overlap distance is greater than zero, or the nearest boundary interval distance is less than or equal to the adjacency tolerance, it is determined that the candidate deformation interval and the potential bending or tilting interval have an intersection.

[0036] The beneficial effects of this invention are as follows:

[0037] 1. This invention achieves distributed synchronous elevation monitoring of tidal flat photovoltaic pile foundations from pile top to pile bottom by setting multiple sub-reference planes along the pile height direction. This overcomes the shortcomings of traditional single-point measurement, which cannot detect deformation modes such as pile bending, tilting or deep deflection, and significantly improves the comprehensiveness and spatial resolution of deformation monitoring.

[0038] 2. This invention calculates the average principal reference elevation of each sub-region using a region division module as a dynamic reference, and combines the graded comparison of settlement threshold and deformation threshold to comprehensively evaluate the settlement at the top of the pile foundation and the overall deformation behavior of the pile body, providing a multi-dimensional and more reliable data foundation for the overall stability analysis of photovoltaic pile foundations with large slenderness ratios;

[0039] 3. After identifying excessive settlement, this invention automatically triggers a high-frequency data acquisition and intelligent analysis process. By analyzing the variation pattern of the span value sequence along the pile body, it can accurately locate the specific location of local stress concentration or progressive bending risk, effectively solving the problems of delayed early warning and insufficient integrity assessment in traditional methods, and improving the initiative and accuracy of safe operation and maintenance. Attached Figure Description

[0040] Figure 1 This is a system flowchart of the present invention;

[0041] Figure 2 This is a flowchart illustrating the specific content of the data acquisition process of the present invention. Detailed Implementation

[0042] The preferred embodiments of the present invention will now be described in detail with reference to the accompanying drawings, so that the advantages and features of the present invention can be more easily understood by those skilled in the art, thereby providing a clearer and more explicit definition of the scope of protection of the present invention.

[0043] Please see Figure 1 - Figure 2 A distributed settlement intelligent sensing and data acquisition system for tidal flat photovoltaic pile foundations includes a reference surface setting module, a region division module, a processing module, an analysis and comparison module, and an intelligent acquisition and positioning module.

[0044] The reference plane setting module sets a main reference plane and several sub-reference planes according to the spatial distribution of photovoltaic pile foundations on the tidal flats;

[0045] The region division module divides multiple tidal flat photovoltaic pile foundations into several sub-regions based on a set spatial range, and obtains the initial principal reference surface elevation and initial sub-reference surface elevation of all tidal flat photovoltaic pile foundations in each intelligent sensing system sub-region, and calculates the average principal reference surface elevation of each intelligent sensing system sub-region.

[0046] The processing module calculates the first deviation between the initial sub-datum elevation of the topmost intelligent sensing system and the average main datum elevation of the intelligent sensing system for a single tidal flat photovoltaic pile foundation in each intelligent sensing system sub-region. After a preset time period, based on the same main datum elevation, it recalculates the second deviation between the initial sub-datum elevation of the topmost intelligent sensing system and the main datum elevation of the intelligent sensing system for the same tidal flat photovoltaic pile foundation in the same intelligent sensing system sub-region. By comparing whether the difference between the first and second deviations of the intelligent sensing system exceeds a preset settlement threshold, it identifies whether the tidal flat photovoltaic pile foundation has settled.

[0047] The analysis and comparison module compares the difference in the intelligent sensing system with the preset deformation threshold after it detects that the photovoltaic pile foundation on the tidal flat has settled.

[0048] The intelligent acquisition and positioning module automatically triggers a preset data acquisition process for the target tidal flat photovoltaic pile foundation when the difference in the intelligent sensing system exceeds the preset deformation threshold of the intelligent sensing system, and locates the specific deformation part of the tidal flat photovoltaic pile foundation based on the data acquired by the preset data acquisition process.

[0049] The beneficial effects of this system lie in the fact that through the collaborative work of the reference surface setting module, area division module, processing module, analysis and comparison module, and intelligent acquisition and positioning module, a complete intelligent sensing system is constructed, realizing distributed and automated monitoring of settlement of photovoltaic pile foundations on tidal flats. The system can accurately identify settlement and assess the degree of deformation, and automatically trigger a high-frequency data acquisition and positioning mechanism when the threshold exceeds the standard, thereby improving monitoring accuracy, response speed and reliability, and effectively ensuring the safety of pile foundations.

[0050] One embodiment of the present invention is as follows: the uppermost intelligent sensing system sub-reference plane in the intelligent sensing system reference plane setting module is located at the top of the tidal flat photovoltaic pile foundation, the lowermost intelligent sensing system sub-reference plane is located at the bottom of the tidal flat photovoltaic pile foundation, and several intelligent sensing system sub-reference planes are distributed on both sides of the intelligent sensing system main reference plane along the pile height direction of the tidal flat photovoltaic pile foundation, and cover the overall height range of all tidal flat photovoltaic pile foundations.

[0051] The steps for setting up the main reference plane and several sub-reference planes of the intelligent sensing system are as follows:

[0052] S1. Obtain the initial spatial positioning data of all tidal flat photovoltaic piles within the target area. Based on the initial spatial positioning data of the intelligent sensing system, calculate the center point of the planar distribution of all tidal flat photovoltaic piles. Calculate the spatial Euclidean distance between each tidal flat photovoltaic pile and the center point of the intelligent sensing system. Sort all tidal flat photovoltaic piles in ascending order according to the spatial Euclidean distance. Select the tidal flat photovoltaic pile at the top of the sorted list and define it as the reference pile. Measure the spatial coordinate points of the reference pile of the intelligent sensing system, which are evenly distributed at a preset distance along the pile height direction. Based on the spatial coordinate points of the intelligent sensing system, calculate its geometric center axis. Define the plane perpendicular to the geometric center axis of the intelligent sensing system and passing through the midpoint of the calculated intelligent sensing system geometric center axis obtained from the spatial coordinate points evenly distributed at a preset distance as the main reference plane. The midpoint of the geometric center axis of the intelligent sensing system defines the spatial position of the main reference plane of the intelligent sensing system, and the direction of the geometric center axis of the intelligent sensing system defines the normal vector direction of the main reference plane of the intelligent sensing system.

[0053] Initial spatial positioning data includes its design or as-built coordinates;

[0054] The method for calculating the center point of the planar distribution of all tidal flat photovoltaic pile foundations is as follows: it is obtained by calculating the mean value of the planar coordinates of all tidal flat photovoltaic pile foundations;

[0055] The calculation steps for the spatial Euclidean distance between each tidal flat photovoltaic pile and the center point of the intelligent sensing system are as follows: Based on the planar coordinates of each tidal flat photovoltaic pile in the initial spatial positioning data of the intelligent sensing system and the planar coordinates of the center point of the planar distribution of all tidal flat photovoltaic piles of the intelligent sensing system, extract the difference between the X-axis coordinates and the Y-axis coordinates of these two sets of coordinates in the preset two-dimensional Cartesian coordinate system. Sum the square of the difference between the X-axis coordinates and the square of the difference between the Y-axis coordinates of the intelligent sensing system. Then, perform a square root operation on the summation result of the intelligent sensing system. The obtained value is the spatial Euclidean distance between each tidal flat photovoltaic pile and the center point of the intelligent sensing system.

[0056] The method for measuring the spatial coordinate points of the reference pile foundation, which are evenly distributed at a preset distance along the height of the pile, is as follows: On the surface of the reference pile foundation of the intelligent sensing system, a series of measurement points are marked along its height at a preset distance of the intelligent sensing system. Using a total station or laser rangefinder and other precision measuring equipment, with the fixed point at the bottom of the pile foundation as the measurement reference, the three-dimensional coordinate values ​​of each measurement point of the intelligent sensing system in the preset three-dimensional spatial coordinate system are measured in sequence to obtain a set of spatial coordinate points that are evenly distributed at the height and accurately reflect the geometric shape of the pile.

[0057] The optimal value of the preset distance needs to take into account the pile height, monitoring accuracy requirements and economy. For tidal flat photovoltaic piles with a height of 10 to 20 meters, the preset distance is usually set to 0.5 to 1.0 meters. This range can ensure sufficient spatial resolution to capture the slight deformation of the pile while avoiding excessive data volume and high processing costs due to too many measurement points.

[0058] The plane perpendicular to the geometric center axis of the intelligent sensing system and passing through the midpoint of the geometric center axis of the intelligent sensing system calculated from the spatial coordinate points of the intelligent sensing system that are uniformly distributed according to the preset distance of the intelligent sensing system is defined as the principal reference plane. The specific method for obtaining the plane is as follows: Based on the geometric center axis of the intelligent sensing system reference pile foundation and its midpoint, firstly determine the spatial direction vector of the geometric center axis of the intelligent sensing system, then construct a plane equation whose normal vector is parallel to the direction vector of the geometric center axis, and translate the plane so that it passes through the midpoint of the geometric center axis of the intelligent sensing system. This translated plane that satisfies the condition that the normal vector is in the same direction as the geometric center axis is defined as the principal reference plane.

[0059] S2. Based on the established main reference plane of the intelligent sensing system and its normal vector direction, along the geometric center axis of the intelligent sensing system, in the upward and downward directions, according to the preset equal spacing or the preset non-equal spacing based on the characteristics of the pile body structure, define a series of virtual planes parallel to the main reference plane of the intelligent sensing system. The virtual planes of the intelligent sensing system are the sub-reference planes. The uppermost sub-reference plane must be located at the designed position of the pile top of the intelligent sensing system reference pile foundation, and the lowermost sub-reference plane must be located at the designed position of the pile bottom of the intelligent sensing system reference pile foundation, so as to ensure that all sub-reference planes together cover the complete pile body range and possible deformation range of the intelligent sensing system reference pile foundation.

[0060] The optimal value of the preset equal spacing is mainly determined based on the pile height and the expected deformation mode resolution to be monitored. It is usually set to 0.5 meters to 2.0 meters. This spacing range can generate a sufficient number of sub-reference planes to effectively capture the bending or tilting deformation characteristics of the pile, while avoiding the waste of computing resources due to excessive density of virtual planes.

[0061] Non-uniform spacing based on pile structure characteristics: Non-uniform spacing based on pile structure characteristics refers to using smaller spacing values ​​to densify the sub-reference planes in areas of pile stress concentration or where the structural form changes (such as the load application point at the pile top, the constraint part at the pile bottom, or the section change of the pile body), while using larger spacing values ​​in the middle section where the pile stress changes gently, thereby achieving a balance between optimized allocation of monitoring resources and accurate capture of deformation in key parts of the pile body;

[0062] The process of defining a virtual plane: Using the defined main reference plane of the intelligent sensing system as a spatial reference, and according to its normal vector direction, along the geometric center axis of the reference pile foundation of the intelligent sensing system, a series of planes parallel to the main reference plane of the intelligent sensing system are generated according to preset equal or non-equal spacing parameters. These generated planes are the virtual planes (sub-reference planes) covering the entire height of the pile. The uppermost and lowermost virtual planes need to cover the design positions of the pile top and pile bottom, respectively.

[0063] S3. Simultaneously apply steps S1 and S2 to all other tidal flat photovoltaic piles in the target area except for the intelligent sensing system reference pile, to complete the unified setting of the main reference surface and sub-reference surface system of all tidal flat photovoltaic piles in the entire monitoring area, and establish a spatial reference benchmark for subsequent elevation acquisition and deformation analysis.

[0064] This embodiment constructs a unified and accurate spatial reference benchmark system by accurately calculating the spatial relationship between the pile foundation and the center point, optimizing the measurement layout, and scientifically setting the reference surface and spacing parameters. This effectively improves the accuracy, reliability, and efficiency of monitoring the settlement and deformation of photovoltaic pile foundations in tidal flats, laying a solid foundation for subsequent automated monitoring and safety early warning.

[0065] One embodiment of the present invention is as follows: the steps for dividing several sub-regions of the intelligent sensing system in the intelligent sensing system region division module are as follows:

[0066] Q1. Based on the spatial position and normal vector direction of the main reference plane of the intelligent sensing system, the spatial coordinates of each tidal flat photovoltaic pile foundation are orthogonally projected onto the main reference plane of the intelligent sensing system to obtain the projection point set of all tidal flat photovoltaic pile foundations. The spatial Euclidean distance between each point in the projection point set of the intelligent sensing system is calculated. According to the preset adjacency threshold, the projection points whose spatial Euclidean distance is less than the adjacency threshold of the intelligent sensing system are dynamically aggregated into the initial sub-region core point group. The initial sub-region boundary is generated with each initial sub-region core point group of the intelligent sensing system as the center.

[0067] The optimal value of the preset adjacency threshold needs to take into account the stability of the tidal flat geological conditions, the typical design spacing of photovoltaic pile foundations, and the requirements of monitoring accuracy. For tidal flat photovoltaic power stations with pile foundation spacing in the range of 5 to 10 meters, the adjacency threshold is usually set to 1.5 to 2.5 times the average spacing of the pile foundations. This value range can ensure that pile foundations with similar locations and geological conditions are reasonably aggregated to reflect the local settlement trend, while avoiding the sub-region division being too coarse due to an excessively large threshold, which would obscure local details, or the sub-region division being too fragmented due to an excessively small threshold, which would increase the computational complexity.

[0068] Q2. For each preliminary sub-region boundary of the intelligent sensing system, calculate the geometric centroid position of all projection points within it, and optimize the boundary based on the overlap between the geometric centroid position of the intelligent sensing system and the boundary of the preliminary sub-region of the adjacent intelligent sensing system. At the same time, introduce the uniformity of the initial main reference surface elevation value of the tidal flat photovoltaic pile foundation within each intelligent sensing system sub-region as a constraint condition, and iteratively optimize the boundary of the preliminary sub-region of the intelligent sensing system to form a formal sub-region division result that is spatially continuous and has a balanced monitoring load.

[0069] The method for calculating the geometric centroid position of all projection points is as follows: Based on the projection point set of all tidal flat photovoltaic pile foundations within the boundary of the preliminary sub-region of the intelligent sensing system, extract the plane coordinates of each projection point in the two-dimensional coordinate system of the main reference plane of the intelligent sensing system, calculate the arithmetic mean of the X-axis coordinate value and the arithmetic mean of the Y-axis coordinate value of all projection points respectively, and take the two-dimensional coordinate point determined by the two arithmetic mean as the geometric centroid position of all projection points within the boundary of the preliminary sub-region.

[0070] The uniformity of the initial master reference elevation value of the tidal flat photovoltaic pile foundation within each sub-region of the intelligent sensing system is introduced as a constraint condition. The specific content of the iterative optimization of the boundary of the initial sub-region of the intelligent sensing system is as follows: In each boundary optimization iteration, the standard deviation of the initial master reference elevation value of all tidal flat photovoltaic pile foundations within the current initial sub-region boundary is calculated and compared with the elevation distribution uniformity threshold preset based on historical data or engineering experience. If the standard deviation exceeds the threshold, it indicates that the elevation difference of the pile foundations in the sub-region is too large, which may affect the representativeness of the subsequent average master reference elevation. At this time, the boundary adjustment procedure needs to be initiated to fine-tune the initial sub-region boundary to include or exclude specific pile foundations, so that the standard deviation of the pile foundation elevation value in the adjusted sub-region is reduced to within the threshold. This iterative process continues until the elevation distribution uniformity of all sub-regions meets the requirements or reaches the preset maximum number of iterations, and finally forms a formal sub-region division result that is spatially continuous and has a balanced monitoring load.

[0071] The initial main reference plane elevation of the intelligent sensing system in the area division module is collected by inclinometers and measuring rods deployed on each tidal flat photovoltaic pile foundation. The inclinometers are fixedly installed in the middle of the measuring rods connecting adjacent pile foundations to measure the tilt angle of the measuring rods caused by the relative displacement of the tidal flat photovoltaic pile foundations in real time. The tilt angle data is converted into digital signals by the signal analysis module and then sent to the area division module by the data transmission module. The area division module calculates the initial elevation value of each pile foundation relative to the main reference plane based on the received tilt angle data of the intelligent sensing system and the preset pile foundation spacing, according to geometric relationships. The initial sub-reference plane elevation of the intelligent sensing system is determined by deploying... Displacement sensors at preset positions on each sub-datum plane collect data. The intelligent sensing system displacement sensors adopt a vibrating wire design, and their measurement direction is perpendicular to the sub-datum plane, which can sensitively capture the displacement changes of the structure in the vertical direction. The frequency signal output by the intelligent sensing system displacement sensor is read and preliminarily processed by the reading device to ensure accurate signal transmission. The data acquisition unit converts the intelligent sensing system frequency signal into specific settlement and displacement data, and sends the intelligent sensing system displacement data to the area division module through a wireless network. The area division module superimposes the received intelligent sensing system displacement data with the initial main datum plane elevation of the intelligent sensing system to generate the initial sub-datum plane elevation at each sub-datum plane.

[0072] The steps for calculating the average principal reference elevation of the intelligent sensing system in each sub-region of the intelligent sensing system are as follows:

[0073] For each sub-region of the intelligent sensing system that was divided in step Q2 of the intelligent sensing system, the original observation values ​​of the initial master reference surface elevation of the intelligent sensing system of all the tidal flat photovoltaic pile foundations within it are extracted to form the original elevation dataset of the intelligent sensing system sub-region.

[0074] Q4. Preprocess the original elevation dataset of the intelligent sensing system, remove data points that deviate from other values ​​in the dataset by more than a preset abnormal threshold due to sensor momentary failure or communication interference, and fill in the removed locations with the normal elevation values ​​of adjacent tidal flat photovoltaic pile foundations by linear interpolation to generate an effective elevation dataset for the sub-region of the intelligent sensing system.

[0075] Q5. Calculate the average principal datum elevation of the intelligent sensing system based on the effective data set of the intelligent sensing system elevation. Specifically, sum the initial principal datum elevation values ​​of the intelligent sensing system for all tidal flat photovoltaic piles in the effective data set of the intelligent sensing system elevation to obtain the sum of the initial principal datum elevations of the sub-region of the intelligent sensing system. Then divide the sum of the initial principal datum elevations of the intelligent sensing system by the total number of tidal flat photovoltaic piles included in the effective data set of the intelligent sensing system elevation. The quotient is the average principal datum elevation of the intelligent sensing system in the sub-region of the intelligent sensing system.

[0076] The average elevation of the principal reference plane in the intelligent sensing system remains constant.

[0077] This embodiment achieves reasonable clustering of pile foundations by setting an optimal adjacency threshold, optimizes sub-region division by calculating the geometric centroid, and ensures the representativeness of monitoring data by introducing elevation distribution uniformity constraints. This improves the scientificity and rationality of sub-region division, lays a solid foundation for subsequent accurate calculation of the average principal reference elevation and settlement identification, and effectively enhances the system's adaptability to the complex environment of tidal flats and the reliability of monitoring results.

[0078] One embodiment of the present invention is as follows: The method for obtaining the preset settlement threshold of the intelligent sensing system in the intelligent sensing system processing module is as follows: During the initial operation phase of the system, the time series data of the initial main reference surface elevation of the intelligent sensing system of all tidal flat photovoltaic pile foundations in each intelligent sensing system sub-region within a preset historical learning period are obtained, the standard deviation of the value of the initial main reference surface elevation of the intelligent sensing system in the intelligent sensing system time series data is calculated, and the preset multiple of the standard deviation of the intelligent sensing system is set as the preset settlement threshold of the intelligent sensing system sub-region.

[0079] The preset historical learning cycle is usually set to three to six months;

[0080] The standard deviation of the initial master datum elevation values ​​in the time series data of the intelligent sensing system is calculated as follows: Based on the time series data of the initial master datum elevation of each sub-region acquired during the historical learning period of the intelligent sensing system, firstly, the arithmetic mean of all initial master datum elevation values ​​in the time series is calculated; then, the difference between each initial master datum elevation value in the time series and the arithmetic mean is calculated, resulting in a series of deviations from the mean; next, each deviation from the mean is squared, and all these squared values ​​are summed to obtain the sum of squares of deviations from the mean; then, this sum of squares of deviations from the mean is divided by the total number of data points in the time series minus one (i.e., using the sample standard deviation calculation method) to obtain the variance; finally, the square root of the variance is taken, and the resulting value is the standard deviation of the initial master datum elevation values ​​in the time series data.

[0081] If the difference in the intelligent sensing system exceeds the preset settlement threshold, it is determined that the tidal flat photovoltaic pile foundation has settled; if the difference in the intelligent sensing system does not exceed the preset settlement threshold, it is determined that the tidal flat photovoltaic pile foundation is in a stable state. This system will record the current first deviation, second deviation, and difference in the intelligent sensing system, and update them as historical data of the normal state of the tidal flat photovoltaic pile foundation. At the same time, it will maintain the routine low-frequency data acquisition and monitoring cycle of the intelligent sensing system sub-region until the calculation process of the intelligent sensing system processing module is restarted again after the next preset time interval.

[0082] This embodiment acquires representative data by setting a reasonable historical learning period and uses rigorous standard deviation calculation to set an adaptive settlement threshold, achieving accurate and automatic identification and status determination of settlement of photovoltaic pile foundations in tidal flats, thus improving the intelligence level and reliability of the monitoring system.

[0083] Among them, the preset deformation threshold of the intelligent sensing system in the intelligent sensing system analysis and comparison module is greater than the preset settlement threshold of the intelligent sensing system.

[0084] One embodiment of the present invention is as follows: the intelligent sensing system's intelligent acquisition and positioning module automatically triggers a preset data acquisition process for the target tidal flat photovoltaic pile foundation, and locates the specific deformation parts of the tidal flat photovoltaic pile foundation based on the data acquired according to the preset data acquisition process.

[0085] T1. When the difference value of the intelligent sensing system output by the intelligent sensing system analysis and comparison module exceeds the preset deformation threshold of the intelligent sensing system, the high-frequency data acquisition mode is automatically started. The elevation data of the current intelligent sensing system sub-reference surface on the target tidal flat photovoltaic pile foundation is collected in real time. The elevation change between the current elevation data of each intelligent sensing system sub-reference surface and the initial elevation of the intelligent sensing system sub-reference surface is calculated. The elevation change values ​​of all intelligent sensing system sub-reference surfaces arranged in order of the height of the tidal flat photovoltaic pile foundation are combined into a sequence of span values ​​distributed along the vertical direction of the tidal flat photovoltaic pile foundation.

[0086] T2. Based on the span value sequence of the intelligent sensing system, analyze the variation law of all span values ​​in the span value sequence along the height direction of the photovoltaic pile body in the tidal flat: detect the change value of the elevation change of the intelligent sensing system between adjacent intelligent sensing system sub-reference planes in the span value sequence. If the absolute value of the change value of the intelligent sensing system exceeds the abrupt change judgment threshold preset according to the historical settlement data, the interval between adjacent intelligent sensing system sub-reference planes is marked as a candidate deformation interval. At the same time, the average change rate of the span values ​​in the candidate deformation interval of the intelligent sensing system at different heights is calculated using the preset sliding window method. The candidate deformation interval of the intelligent sensing system with the average change rate exceeding the gradient judgment threshold preset according to the material deformation characteristics is identified as a potential bending or tilting interval.

[0087] The optimal value of the preset abrupt change judgment threshold needs to comprehensively consider the elastic modulus of the materials used in the photovoltaic pile foundation of the tidal flat, the structural dimensions of the pile body, and the critical strain characteristics that characterize the structural damage of the pile body in the historical settlement data. It is usually set to 2 to 3 times the standard deviation of the change value of the elevation change of the intelligent sensing system in the historical settlement data sequence when the pile body is in the elastic deformation stage. This value range can effectively filter out normal data fluctuations caused by environmental noise or short-term load fluctuations, while ensuring a high sensitivity response to structural abrupt damage such as crack development or local crushing that may occur in the pile body.

[0088] The specific steps for calculating the average rate of change of span values ​​within the candidate deformation interval of the intelligent sensing system at different heights using the preset sliding window method are as follows: Based on the span value sequence of the intelligent sensing system, a preset sliding window in the height direction is set with the starting height of the candidate deformation interval of the intelligent sensing system as the benchmark; the window is moved sequentially along the pile height direction, and the algebraic sum of all span values ​​within each window is calculated. Then, this algebraic sum is divided by the height span value of the window to obtain the average rate of change of the span value with height within the current window; the average rate of change of all windows is calculated sequentially to form a distribution sequence of the average rate of change of span values ​​within the candidate deformation interval of the intelligent sensing system.

[0089] The optimal value of the preset gradient judgment threshold is mainly based on the yield strain limit of the tidal flat photovoltaic pile foundation material and the maximum allowable bending curvature of the pile body. It is usually set as the rate of change of unit height corresponding to the critical bending curvature of the pile body entering the plastic deformation stage, which is determined by experimental data on material deformation characteristics. This threshold is used to distinguish between the elastic bending of the pile body and the plastic bending or tilting deformation that may cause permanent damage.

[0090] T3. Perform spatial correlation analysis on the candidate deformation range and potential bending or tilting range of the intelligent sensing system: If there is an intersection between the two, the overlapping area is determined to be the specific part of the pile foundation bending or shear deformation; if there is no intersection, the average change rate of the intelligent sensing system in the candidate deformation range of the intelligent sensing system is further calculated. When the average change rate of the intelligent sensing system continuously exceeds the preset gradient judgment threshold, the candidate deformation range of the intelligent sensing system is classified as an independent compression deformation part, and the potential bending or tilting range is determined as the overall deflection-dominant area. The deformation part location result and deformation mode classification information are output.

[0091] When the average rate of change of the intelligent sensing system continuously exceeds the preset gradient judgment threshold, it means that the average rate of change exceeds the preset gradient judgment threshold in multiple consecutive (e.g., 3 or more) preset acquisition cycles.

[0092] T4. Based on the location results of the deformed parts and the classification information of the deformation mode of the intelligent sensing system output in step T3, and combined with the deformation magnitude of the corresponding parts in the value sequence of the intelligent sensing system, the preset early warning rule library is called to generate a comprehensive early warning report for the target tidal flat photovoltaic pile foundation of the intelligent sensing system. The report includes the specific deformation parts, deformation modes, severity levels and suggested treatment measures, and is automatically pushed to the operation and maintenance management platform.

[0093] In step T3 of the intelligent sensing system, if there is an intersection between the two, that is, if the candidate deformation region of the intelligent sensing system and the potential bending or tilting region coincide in vertical space or the boundary distance is less than the preset adjacency tolerance, the specific judgment method is as follows:

[0094] T301. Extract the upper and lower vertical height coordinates of the candidate deformation range of the intelligent sensing system, and the upper and lower vertical height coordinates of the potential bending or tilting range of the intelligent sensing system. Calculate the height span value of each of the candidate deformation range and the potential bending or tilting range based on the upper and lower vertical height coordinates of the intelligent sensing system. Compare the upper vertical height coordinates of the candidate deformation range with the lower vertical height coordinates of the potential bending or tilting range, and simultaneously compare the lower vertical height coordinates of the candidate deformation range with the upper vertical height coordinates of the potential bending or tilting range. Determine the relative positional relationship of the candidate deformation range and the potential bending or tilting range in the vertical direction based on the comparison results.

[0095] The method for extracting the upper and lower vertical height coordinates of the candidate deformation range of the intelligent sensing system, as well as the upper and lower vertical height coordinates of the potential bending or tilting range of the intelligent sensing system, is as follows: From the three-dimensional pile foundation model built into the intelligent acquisition and positioning module of the intelligent sensing system, locate the pile segments corresponding to the candidate deformation range and the potential bending or tilting range of the intelligent sensing system, and read the Z-axis coordinate value of the top boundary of the pile segment in the preset global coordinate system as the upper vertical height coordinate, and read the Z-axis coordinate value of the bottom boundary of the pile segment as the lower vertical height coordinate; the three-dimensional pile foundation model is a parameterized simplified model automatically generated during system initialization based on the initial spatial positioning data of the intelligent sensing system and the pile foundation design parameters (diameter, length), reflecting the automation and integration capabilities of the system;

[0096] T302. Based on the relative positional relationship of the intelligent sensing system, calculate the vertical overlap distance or nearest boundary distance between the candidate deformation range and the potential bending or tilting range of the intelligent sensing system: If the vertical height ranges of the candidate deformation range and the potential bending or tilting range overlap, the vertical distance of the overlapping portion is the vertical overlap distance; if the candidate deformation range and the potential bending or tilting range do not overlap vertically, the calculation is based on the positional relationship of the candidate deformation range above or below the potential bending or tilting range: If the candidate deformation range is above the potential bending or tilting range, calculate the lower limit coordinate of the vertical height of the candidate deformation range minus the distance of the potential bending or tilting range. The absolute value of the difference between the upper limit coordinate of the vertical height of the sensing system and the lower limit coordinate of the vertical height of the sensing system is used as the nearest boundary distance. If the candidate deformation range of the intelligent sensing system is located below the potential bending or tilting range of the intelligent sensing system, the absolute value of the difference between the lower limit coordinate of the vertical height of the intelligent sensing system in the potential bending or tilting range and the upper limit coordinate of the vertical height of the intelligent sensing system in the candidate deformation range is used as the nearest boundary distance. The calculated vertical overlap distance or the nearest boundary distance of the intelligent sensing system is compared with the preset adjacency tolerance of the intelligent sensing system. If the vertical overlap distance of the intelligent sensing system is greater than zero, or the nearest boundary distance of the intelligent sensing system is less than or equal to the adjacency tolerance of the intelligent sensing system, it is determined that there is an intersection between the candidate deformation range and the potential bending or tilting range of the intelligent sensing system, and the spatial range of the intersection range is recorded as the final specific location of bending or shear deformation.

[0097] The optimal value of the preset adjacency tolerance depends on the spacing of the sub-reference planes of the intelligent sensing system along the pile height and the spatial resolution requirements of pile deformation monitoring. It is usually set to one-half to one-third of the average spacing between adjacent sub-reference planes of the intelligent sensing system. This setting can ensure that closely adjacent intervals in vertical space that may have deformation correlation can be correctly identified as having an intersection, avoiding the omission of correlated deformation areas due to small coordinate measurement errors or model discretization errors.

[0098] This embodiment achieves accurate and automatic identification and classification of deformation locations and modes (bending, shearing, compression) of photovoltaic pile foundations on tidal flats by scientifically setting mutation and gradient thresholds, accurately calculating the deformation rate using the sliding window method, and determining the correlation of deformation intervals based on accurate coordinate extraction and adjacency tolerance. This significantly improves the discrimination accuracy and intelligence level of the monitoring system and provides a reliable basis for subsequent maintenance decisions. Specific Implementation

[0099] In a tidal flat photovoltaic power station, the system is deployed for a pile foundation group with a height of 15 meters and a spacing of 8 meters;

[0100] The reference plane setting module first obtains the design coordinates of all pile foundations, calculates the center point of the plane distribution, and selects the pile foundation closest to the center point as the reference pile foundation. It then uses a total station to measure the coordinate sequence of the pile body at a preset distance of 0.75 meters to generate the geometric center axis and defines the main reference plane through the normal vector of the midpoint of the axis. Subsequently, it generates sub-reference planes along the axis at equal intervals of 1.0 meters, covering the pile top to the pile bottom.

[0101] The region division module projects the pile foundation coordinates onto the main reference plane, aggregates the projected points to form initial sub-regions with a 12-meter adjacency threshold (based on 1.5 times the average spacing of 8 meters), calculates the geometric centroid of the projected points in each sub-region, and iteratively adjusts the boundary to ensure that the standard deviation of the initial main reference plane elevation value of the pile foundation is lower than the preset threshold, thus ensuring uniform distribution.

[0102] The processing module collects the initial elevation using an inclinometer and a displacement sensor. Within a 3-month historical learning period, it calculates the standard deviation of the time series of the initial master reference elevation of each sub-region and sets twice the standard deviation as the settlement threshold. When the difference between the elevation of the uppermost sub-reference surface of a pile foundation and the average master reference elevation exceeds this threshold, settlement is determined to have occurred.

[0103] The analysis and comparison module further compares this difference with a higher deformation threshold. If it exceeds the threshold, the intelligent acquisition and positioning module is triggered: high-frequency data acquisition is started, the elevation change of all sub-datum surfaces of the pile body is calculated, a sequence of cross-values ​​is generated, and intervals where the abrupt change of adjacent sub-datum surface values ​​exceeds 2.5 times the historical standard deviation are detected as candidate deformation intervals. At the same time, a 1.5-meter sliding window is used to calculate the average rate of change of cross-values, and intervals that exceed the gradient corresponding to the material's critical curvature are marked as potential bending intervals. By extracting the vertical coordinates of the candidate intervals and potential intervals (based on the three-dimensional pile foundation model), the vertical overlap distance is calculated. If the overlap distance is greater than zero or the boundary interval is less than 0.25 meters of adjacency tolerance (one-quarter of the 1.0-meter spacing between sub-datum surfaces), the intersection area is determined to be a bending deformation location, and finally an early warning report containing deformation positioning and maintenance suggestions is generated.

[0104] The beneficial effects of this specific embodiment are that it achieves accurate and automated monitoring of settlement and deformation of tidal flat photovoltaic pile foundations through multi-module collaboration. The benchmark surface and regional division optimize the spatial reference system, the threshold adaptive mechanism and sliding window analysis improve the sensitivity and accuracy of deformation identification, and the intelligent acquisition triggering and three-dimensional positioning ensure the timeliness of risk response, significantly enhancing the reliability of the system and the efficiency of safe operation and maintenance of pile foundations in complex tidal flat environments.

[0105] The above description is merely an embodiment of the present invention and does not limit the patent scope of the present invention. Any equivalent structural or procedural transformations made based on the content of the present invention's specification and drawings, or direct or indirect applications in other related technical fields, are similarly included within the patent protection scope of the present invention.

Claims

1. A distributed settlement intelligent sensing and data acquisition system for tidal flat photovoltaic pile foundations, characterized in that: It includes a reference plane setting module, a region division module, a processing module, an analysis and comparison module, and an intelligent acquisition and positioning module; The reference plane setting module sets a main reference plane and several sub-reference planes according to the spatial distribution of photovoltaic pile foundations on the tidal flats; The region division module divides multiple tidal flat photovoltaic pile foundations into several sub-regions based on a set spatial range, and obtains the initial principal reference surface elevation and initial sub-reference surface elevation of all tidal flat photovoltaic pile foundations in each sub-region, and calculates the average principal reference surface elevation of each sub-region. The processing module calculates, for each individual tidal flat photovoltaic pile foundation in each sub-region, the first deviation between the elevation of its uppermost initial sub-reference plane and the average main reference plane elevation, and after a preset time period, recalculates the second deviation between the elevation of the uppermost initial sub-reference plane and the main reference plane elevation of the same tidal flat pile foundation in the same sub-region based on the same main reference plane elevation; by comparing whether the difference between the first deviation and the second deviation exceeds a preset settlement threshold, it identifies whether the tidal flat photovoltaic pile foundation has settled. The analysis and comparison module, after identifying that the photovoltaic pile foundation on the tidal flat has settled, compares the difference with a preset deformation threshold. The intelligent acquisition and positioning module automatically triggers a preset data acquisition process for the target tidal flat photovoltaic pile foundation when the difference exceeds the preset deformation threshold, and locates the specific deformation part of the tidal flat photovoltaic pile foundation based on the data acquired by the preset data acquisition process.

2. The intelligent sensing and data acquisition system for distributed settlement of photovoltaic pile foundations in tidal flats according to claim 1, characterized in that: The uppermost sub-reference surface in the reference surface setting module is located at the top of the tidal flat photovoltaic pile foundation, and the lowermost sub-reference surface is located at the bottom of the tidal flat photovoltaic pile foundation. Several sub-reference surfaces are distributed on both sides of the main reference surface along the pile height direction of the tidal flat photovoltaic pile foundation and cover the overall height range of all tidal flat photovoltaic pile foundations.

3. The intelligent sensing and data acquisition system for distributed settlement of photovoltaic pile foundations in tidal flats according to claim 2, characterized in that: The steps for setting the main datum plane and several sub-datum planes are as follows: S1. Obtain initial spatial positioning data of all tidal flat photovoltaic pile foundations within the target area. Based on the initial spatial positioning data, calculate the center point of the planar distribution of all tidal flat photovoltaic pile foundations. Calculate the spatial Euclidean distance between each tidal flat photovoltaic pile foundation and the center point. Sort all tidal flat photovoltaic pile foundations in ascending order according to the spatial Euclidean distance. Select the tidal flat photovoltaic pile foundation ranked first in the sorting and define it as a reference pile foundation. Measure the spatial coordinate points of the reference pile foundation evenly distributed at a preset distance along the pile height direction. Based on the spatial coordinate points, calculate its geometric central axis. Define the plane perpendicular to the geometric central axis and passing through the midpoint of the geometric central axis calculated from the spatial coordinate points evenly distributed at the preset distance as the main reference plane. The midpoint of the geometric central axis defines the spatial position of the main reference plane, and the direction of the geometric central axis defines the normal vector direction of the main reference plane. S2. Based on the determined main reference plane and its normal vector direction, along the geometric center axis in the upward and downward directions, a series of virtual planes parallel to the main reference plane are defined at preset equal intervals or at preset non-equal intervals according to the characteristics of the pile structure. The virtual planes are sub-reference planes. The uppermost sub-reference plane must be located at the designed position of the top of the reference pile foundation, and the lowermost sub-reference plane must be located at the designed position of the bottom of the reference pile foundation. S3. Simultaneously apply steps S1 and S2 to all other tidal flat photovoltaic piles in the target area except for the reference pile, to complete the unified setting of the main reference surface and sub-reference surface system for all tidal flat photovoltaic piles in the entire monitoring area.

4. The intelligent sensing and data acquisition system for distributed settlement of photovoltaic pile foundations in tidal flats according to claim 3, characterized in that: The steps for dividing the sub-regions in the region division module are as follows: Q1. Based on the spatial position and normal vector direction of the main reference plane, the spatial coordinates of each tidal flat photovoltaic pile foundation are orthogonally projected onto the main reference plane to obtain the projection point set of all tidal flat photovoltaic pile foundations. The spatial Euclidean distance between each point in the projection point set is calculated. According to the preset adjacency threshold, the projection points with mutual spatial Euclidean distance less than the adjacency threshold are dynamically aggregated into an initial sub-region core point group. And a preliminary sub-region boundary is generated with each initial sub-region core point group as the center. Q2. For each of the preliminary sub-region boundaries, calculate the geometric centroid position of all projection points within it, and perform boundary optimization adjustment based on the overlap between the geometric centroid position and the adjacent preliminary sub-region boundaries. At the same time, introduce the uniformity of the initial main reference surface elevation value of the tidal flat photovoltaic pile foundation in each of the sub-regions as a constraint condition, and iteratively optimize the preliminary sub-region boundaries to form the sub-region division result.

5. The intelligent sensing and data acquisition system for distributed settlement of tidal flat photovoltaic pile foundations according to claim 4, characterized in that: The initial main reference surface elevation in the region division module is collected by inclinometers and measuring rods deployed on each tidal flat photovoltaic pile foundation; the initial sub-reference surface elevation is collected by displacement sensors installed at preset positions on each sub-reference surface. The steps for calculating the average principal datum elevation for each sub-region are as follows: For each sub-region divided in step Q2, the original observation values ​​of the initial master reference elevation of all tidal flat photovoltaic pile foundations within it are extracted to form the original elevation dataset of the sub-region. Q4. Preprocess the original elevation dataset, remove data points that exceed the preset abnormal threshold, and fill in the removed locations using the normal elevation values ​​of adjacent tidal flat photovoltaic pile foundations through linear interpolation to generate the effective elevation dataset of the sub-region. Q5. Calculate the average principal datum elevation based on the effective elevation dataset, specifically by summing the initial principal datum elevation values ​​of all tidal flat photovoltaic piles in the effective elevation dataset to obtain the sum of the initial principal datum elevations of the sub-region, and then dividing the sum of the initial principal datum elevations by the total number of tidal flat photovoltaic piles included in the effective elevation dataset. The quotient is the average principal datum elevation of the sub-region. The average elevation of the principal datum plane remains constant.

6. The intelligent sensing and data acquisition system for distributed settlement of photovoltaic pile foundations in tidal flats according to claim 5, characterized in that: The method for obtaining the preset settlement threshold in the processing module is as follows: during the initial operation phase of the system, the time series data of the initial main reference elevation of all tidal flat photovoltaic pile foundations in each sub-region within a preset historical learning period is obtained, the standard deviation of the initial main reference elevation values ​​in the time series data is calculated, and the preset multiple of the standard deviation is set as the preset settlement threshold of the sub-region. If the difference exceeds the preset settlement threshold, it is determined that the photovoltaic pile foundation on the tidal flat has settled.

7. The intelligent sensing and data acquisition system for distributed settlement of tidal flat photovoltaic pile foundations according to claim 6, characterized in that: The preset deformation threshold in the analysis and comparison module is greater than the preset settlement threshold.

8. The intelligent sensing and data acquisition system for distributed settlement of photovoltaic pile foundations in tidal flats according to claim 7, characterized in that: The intelligent acquisition and positioning module automatically triggers a preset data acquisition process for the target tidal flat photovoltaic pile foundation, and locates the specific deformation parts of the tidal flat photovoltaic pile foundation based on the data acquired according to the preset data acquisition process. T1. When the difference output by the analysis and comparison module exceeds the preset deformation threshold, the high-frequency data acquisition mode is automatically started. The elevation data of the current sub-reference surface is collected in real time for each sub-reference surface on the target tidal flat photovoltaic pile foundation. The elevation change between the current elevation data of each sub-reference surface and the initial sub-reference surface elevation is calculated. The elevation change of all sub-reference surfaces arranged in order of the height of the tidal flat photovoltaic pile foundation is combined into a sequence of span values ​​distributed along the vertical direction of the tidal flat photovoltaic pile foundation. T2. Based on the span value sequence, analyze the variation law of all span values ​​in the span value sequence along the height direction of the photovoltaic pile body in the tidal flat: detect the change value of the elevation change between adjacent sub-reference planes in the span value sequence. If the absolute value of the change value exceeds the abrupt change judgment threshold preset according to historical settlement data, the interval between adjacent sub-reference planes is marked as a candidate deformation interval. At the same time, the average change rate of the span value in the candidate deformation interval at different heights is calculated using a preset sliding window method. The candidate deformation intervals whose average change rate exceeds the gradient judgment threshold preset according to the material deformation characteristics are identified as potential bending or tilting intervals. T3. Perform spatial correlation analysis on the candidate deformation interval and the potential bending or tilting interval: if there is an intersection between the two, the overlapping area is determined to be the specific part of the pile foundation bending or shear deformation; if there is no intersection, the average rate of change of the candidate deformation interval is further calculated. When the average rate of change continuously exceeds the preset gradient judgment threshold, the candidate deformation interval is classified as an independent compression deformation part, and the potential bending or tilting interval is determined as the overall deflection-dominant area. The deformation part location result and deformation mode classification information are output.

9. The intelligent sensing and data acquisition system for distributed settlement of photovoltaic pile foundations in tidal flats according to claim 8, characterized in that: In step T3, if there is an intersection between the two, that is, if the candidate deformation interval and the potential bending or tilting interval coincide in vertical space or the boundary distance is less than the preset adjacency tolerance, the specific judgment method is as follows: T301. Extract the upper and lower vertical height coordinates of the candidate deformation interval and the upper and lower vertical height coordinates of the potential bending or tilting interval respectively. Calculate the height span value of each of the candidate deformation interval and the potential bending or tilting interval based on the upper and lower vertical height coordinates. Compare the upper vertical height coordinate of the candidate deformation interval with the lower vertical height coordinate of the potential bending or tilting interval, and simultaneously compare the lower vertical height coordinate of the candidate deformation interval with the upper vertical height coordinate of the potential bending or tilting interval. Determine the relative positional relationship of the candidate deformation interval and the potential bending or tilting interval in the vertical direction based on the comparison results. T302. Based on the relative positional relationship, calculate the vertical overlap distance or nearest boundary distance between the candidate deformation interval and the potential bending or tilting interval: If the vertical height range of the candidate deformation interval and the potential bending or tilting interval overlaps, then the vertical distance of the overlapping portion is the vertical overlap distance; if the candidate deformation interval and the potential bending or tilting interval do not overlap in the vertical direction, then the calculation is based on the positional relationship of the candidate deformation interval above or below the potential bending or tilting interval in the vertical direction: If the candidate deformation interval is above the potential bending or tilting interval, then calculate the lower limit coordinate of the vertical height of the candidate deformation interval minus... The absolute value of the difference between the upper limit of the vertical height coordinates of the potential bending or tilting interval is used as the nearest boundary interval distance. If the candidate deformation interval is located below the potential bending or tilting interval, the absolute value of the difference between the lower limit of the vertical height coordinates of the potential bending or tilting interval and the upper limit of the vertical height coordinates of the candidate deformation interval is calculated and used as the nearest boundary interval distance. The calculated vertical overlap distance or the nearest boundary interval distance is compared with the preset adjacency tolerance. If the vertical overlap distance is greater than zero, or the nearest boundary interval distance is less than or equal to the adjacency tolerance, it is determined that the candidate deformation interval and the potential bending or tilting interval have an intersection.

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