Intelligent acquisition and analysis system of water conservancy operation state fused with spatial information

Abstract

The application discloses a water conservancy operation state intelligent acquisition and analysis system fused with spatial information and relates to the technical field of water conservancy data acquisition and analysis. A terminal processing unit in the system obtains the geodetic height of the installation position of the first terminal by subtracting the obtained final height difference from the received manhole cover reference geodetic height, and calculates the real three-dimensional geodetic coordinates of the first terminal in combination with the corresponding geodetic plane coordinates and the horizontal offset vector of the center of the manhole cover and the installation position of the first terminal in the geodetic plane coordinate system. The application integrates laser ranging, barometric altimetry and inclination measurement in the inspection well, calculates the real three-dimensional geodetic coordinates of the terminal in real time by combining the reference geodetic height provided by the RTK of the inspection terminal and the horizontal offset vector of the terminal and the center of the manhole cover, and writes the real three-dimensional geodetic coordinates into the storage and uploads the real three-dimensional geodetic coordinates for updating. The scheme effectively overcomes the technical defects that the actual spatial position of the traditional terminal coordinates is drifted due to settlement and deformation while the terminal coordinates are fixed and unchanged.

Description

Technical Field

[0001] This invention relates to the field of water conservancy data acquisition and analysis technology, specifically to an intelligent acquisition and analysis system for water conservancy operation status that integrates spatial information. Background Technology

[0002] Water conservancy monitoring is a core support for urban water security and disaster prevention and mitigation. Traditional monitoring methods still have significant shortcomings in terms of spatial information fusion, terminal positioning accuracy, and data reliability in complex environments. Currently, fixed data acquisition terminals such as water level and flow sensors deployed in drainage pipe network inspection wells usually rely on the initial measurements taken during construction. However, during long-term operation, due to factors such as ground subsidence, well deformation, water erosion, and maintenance disturbances, the actual spatial position of these fixed data acquisition terminals often shifts to some extent. Existing systems often lack effective autonomous positioning and calibration mechanisms to address this terminal position shift, leading to a mismatch between monitoring data and geospatial information. This, to some extent, affects the accuracy of boundary conditions in hydrological models and the precision of urban flooding simulation. Meanwhile, for mobile inspection operations, most existing inspection terminals rely on ordinary GNSS single-point positioning. Their horizontal and vertical accuracy is often insufficient to meet the requirements of refined operation and maintenance of water conservancy facilities, and they lack comprehensive perception capabilities of the underground environment, open channel water level and pipeline spatial relationship. Furthermore, in open channel water level monitoring, pressure water level sensors are prone to zero drift due to long-term immersion in water, while traditional manual water gauge readings mainly rely on subjective visual estimation by inspection personnel. This method is inefficient, inconsistent, and lacks efficient image-assisted correction methods.

[0003] Furthermore, existing systems primarily employ online hydrological and hydrodynamic models for numerical simulation when dealing with pipeline overflows and flooding. While this mechanism offers high accuracy, it involves substantial computational time, hindering rapid response and real-time risk map push notifications at the edge. Moreover, in channel health diagnosis, current technologies often fail to adequately consider flow direction constraints and channel geometry when interpolating and reconstructing water levels along the channel, leading to a high misjudgment rate in identifying silted and leaking sections, thus failing to meet the practical needs of precise operation and maintenance. In summary, there is an urgent need to construct a comprehensive water conservancy operation status acquisition and analysis system that integrates high-precision spatial positioning, multi-source data self-calibration, rapid response, and intelligent judgment to address the pain points of the existing technologies. Summary of the Invention

[0004] The purpose of this invention is to provide an intelligent system for collecting and analyzing the operational status of water conservancy projects that integrates spatial information, so as to solve the problems mentioned in the background art.

[0005] To address the aforementioned technical problems, this invention provides the following technical solution: an intelligent data acquisition and analysis system for water conservancy operation status integrating spatial information, comprising multiple fixed intelligent acquisition terminals deployed in the monitoring area, at least one mobile inspection terminal carried by inspection personnel, and a GIS platform server communicatively connected to both. The fixed intelligent acquisition terminals include a first type of terminal installed inside inspection wells. This first type of terminal integrates a water level or flow sensor, a laser ranging module, a barometer, an inclinometer, a first short-range wireless communication module, and a terminal processing unit. The first type of terminal stores its own device identifier and the code of the inspection well to which it belongs. The mobile inspection terminal integrates an RTK positioning module, a barometer, an inertial measurement unit (IMU), a camera, a second short-range wireless communication module, and an inspection processing unit. The mobile inspection terminal is equipped with a centering auxiliary tool to keep the phase center of the RTK antenna vertically aligned with the center point of the target manhole cover during inspection operations. The GIS platform server stores the reference geodetic height of each manhole cover, the correspondence between the device identifier of the first type of terminal inside the manhole and the code of the manhole, and the geodetic plane coordinates of each manhole. When executing the downhole terminal spatial positioning self-calibration process: The mobile inspection terminal moves to the top of the target manhole cover, obtains the current geodetic coordinates through its RTK positioning module, and collects the wellhead air pressure value through its barometer; the mobile inspection terminal retrieves the reference geodetic height of the manhole cover from the GIS platform server, and wakes up the corresponding first-type terminal downhole through the second short-range wireless communication module, and sends the obtained reference geodetic height, wellhead air pressure value and geodetic coordinates to the first-type terminal downhole. After the first type of terminal is woken up, it measures the first distance from its installation position to the inner wall of the manhole cover through the laser ranging module, collects the air pressure value in the well through its own barometer, and measures its tilt angle relative to the plumb line through the inclinometer. The terminal processing unit of the first type of terminal calculates the pressure difference based on the difference between the wellhead gas pressure and the wellbore gas pressure, and uses the obtained tilt angle to correct the obtained first distance to the vertical distance. The obtained pressure difference and the vertical distance are then fused to obtain the final height difference from the terminal to the wellhead. Specifically, the calculation formula for correcting the obtained first distance to the vertical distance using the obtained tilt angle is as follows: ; in, Indicates vertical distance; This indicates the first distance from its own installation position to the inner wall of the manhole cover, measured by the laser ranging module. It represents the angle of inclination of itself relative to the vertical line, as measured by an inclinometer. The terminal processing unit obtains the geodetic height of the first type of terminal installation position by subtracting the final elevation difference from the received manhole cover reference geodetic height, and calculates the true three-dimensional geodetic coordinates of the first type of terminal by combining the corresponding geodetic plane coordinates with the pre-calibrated horizontal offset vector of the manhole cover center and the installation position of the first type of terminal in the geodetic plane coordinate system. The first type of terminal writes the obtained real three-dimensional geodetic coordinates into its internal storage and uploads them to the GIS platform server to update its spatial points.

[0006] Furthermore, the first type of terminal calculates the pressure difference based on the difference between the wellhead gas pressure and the wellbore gas pressure, using the following calculation formula: ; in, This represents the pressure difference, where k represents the pre-calibrated conversion factor between pressure difference and pressure difference; Indicates the gas pressure inside the well; This indicates the wellhead gas pressure.

[0007] Furthermore, during the fusion processing of the obtained pressure difference and vertical distance by the terminal processing unit of the first type of terminal, when the absolute value of the difference between the obtained pressure difference and vertical distance is within a preset confidence threshold, the weighted average of the obtained pressure difference and vertical distance is taken as the final height difference, and the weighting weight is determined based on the prior accuracy of laser ranging and barometric altimetry; when the absolute value of the difference between the obtained pressure difference and vertical distance exceeds the preset confidence threshold, a measurement abnormality is determined, a fault prompt is generated, and the one with higher nominal accuracy between the obtained pressure difference and vertical distance is selected as the final height difference. The terminal processing unit calculates the true three-dimensional geodetic coordinates of the first type of terminal as (Xdev, Ydev, Hdev), where the value of Hdev is equal to the difference between the received reference geodetic height of the manhole cover and the final height difference. The corresponding geodetic plane coordinates are denoted as (Xrtk, Yrtk). The pre-calibrated horizontal offset vector representing the plane offset between the center of the manhole cover and the installation position of the first type of terminal is denoted as (Δx, Δy). The value of Xdev is equal to the difference between Xrtk and Δx. The value of Ydev is equal to the difference between Yrtk and Δy.

[0008] Furthermore, the first type of terminal also includes an acoustic transceiver module; after two adjacent first type terminals have completed self-calibration, one terminal transmits an acoustic signal, and the other terminal receives and records the propagation time, calculates the acoustic propagation distance, and compares the propagation distance with the corresponding drainage pipe axis design length stored in the GIS platform server. If the deviation between the propagation distance and the corresponding drainage pipe axis design length stored in the GIS platform server exceeds a preset verification threshold, a spatial point anomaly alarm is generated.

[0009] Specifically, the self-calibration process also includes an auxiliary verification step for adjacent inspection wells: The GIS platform server also stores the design length of the drainage pipe axis between adjacent inspection wells, denoted as Lpipe; After both terminal A in the first inspection well and terminal B in the second inspection well have completed self-calibration, terminal A transmits acoustic pulse signals into the pipeline through its acoustic transceiver module, and terminal B receives the signals through its own acoustic transceiver module and records the signal propagation time, denoted as t. The following formulas are used to calculate the propagation distance of sound waves along a pipe: ; Where Dcalc represents the propagation distance of the sound wave along the pipe; vso represents the equivalent propagation speed of the sound wave in the air medium inside the pipe, which is obtained by pre-experimental calibration or real-time compensation based on the ambient temperature inside the pipe. The propagation distance Dcalc of the obtained sound wave along the pipe is compared with the design length Lpipe of the corresponding drainage pipe axis. If |Dcalc-Lpipe| exceeds the preset verification threshold, a spatial point anomaly alarm is generated, triggering a review of the calibration results of the relevant terminals.

[0010] Furthermore, the system also includes a second type of terminal deployed beside an open channel or river and a water gauge set near the second type of terminal; the second type of terminal integrates at least a water level sensor; the GIS platform server also stores the geodetic coordinates of each water gauge, the geodetic height of the reference point at the bottom of the water gauge, and the effective scale length of the water gauge. The mobile inspection terminal is also used to perform water level image recognition and sensor drift correction processes, specifically including: The mobile inspection terminal moves to the vicinity of the target water gauge and captures an image of the water gauge containing the complete and valid scale segment through a camera. Simultaneously, it records the camera's three-dimensional geodetic coordinates obtained by the RTK positioning module and the camera's attitude angles obtained by the inertial measurement unit (IMU) at the time of capture. The attitude angles include azimuth, pitch, and roll angles. The mobile inspection terminal retrieves the reference parameters of the water gauge from the GIS platform server. The inspection processing unit processes the water gauge image, identifies the boundary line between the water surface and the water gauge body, obtains the pixel row coordinates of the boundary line in the image, and identifies at least three known geodetic height scale feature points and their pixel row coordinates in the image. The inspection processing unit, based on the principle of cross-ratio invariance, uses the correspondence between the pixel row coordinates of at least three scale feature points and the known geodetic height to calculate the true water level geodetic height corresponding to the water surface boundary line.

[0011] Furthermore, the mobile inspection terminal is also used to realize the drift correction of the water level sensor of the second type of terminal; The inspection processing unit obtains the water level value output by the water level sensor of the second type of terminal at the same time, and calculates the absolute value of the difference between the actual water level and the sensor water level; if the absolute value of the difference between the actual water level and the sensor water level is greater than the corresponding dynamic threshold, a zero-point drift correction instruction is generated, and the zero-point drift correction instruction is sent to the second type of terminal through the edge computing gateway to modify the zero-point offset stored inside the second type of terminal, and bind and store the correction record with the GIS point of the corresponding water gauge. The dynamic threshold is obtained by querying the threshold bound in the preset form based on the historical water level fluctuation range of the measuring point and the sensor's nominal accuracy. The calculation formula involved in modifying the zero-point offset stored internally in the second type of terminal in this invention is as follows: ; in, This represents the updated zero-point offset stored internally in the second type of terminal; This represents the zero-point offset stored internally in the second type of terminal before the update. This indicates the water level value output by the water level sensor of the second type of terminal at the target water gauge at the corresponding time. This indicates the actual water level at the corresponding moment.

[0012] Furthermore, the system also includes an edge computing gateway, which internally stores a pre-generated flood lookup table (LUT). The flood lookup table (LUT) is generated as follows: Based on the digital elevation model (DEM), a multi-flow direction algorithm is used to divide the urban surface into several catchment areas. For each drainage network node, with a preset overflow volume increment as the step size, the volume filling method is used to simulate the distribution of surface water accumulation range and water depth corresponding to different overflow volumes offline, and establish the mapping relationship between overflow volume, water accumulation range, and water depth. The volume filling method takes the network node as the center and prioritizes the allocation of water accumulation volume to the neighboring grid with the lowest DEM elevation until the cumulative filling volume equals the current overflow volume, and records the water depth value of each grid. The edge computing gateway acquires water level data uploaded by each type of terminal in real time. When the water level of any node exceeds the ground elevation corresponding to that node, it calculates the current overflow volume and uses this overflow volume as an index to retrieve the obtained flood lookup table (LUT), directly mapping the corresponding water accumulation range and water depth distribution, generating a flood risk patch and pushing it to the mobile inspection terminal. The calculation formula involved in calculating the current overflow volume in this invention is as follows: ; Where Awell represents the cross-sectional area of ​​the inspection well; h represents the ground elevation corresponding to the node; h represents the water level of the corresponding node. If multiple nodes overflow simultaneously, spatial overlay analysis is performed on the multiple sets of water accumulation range polygons obtained from the retrieval. The water depth value of the overlapping area is taken as the maximum value of the water depth from each source, and a synthetic waterlogging risk patch is generated and pushed to the mobile inspection terminal.

[0013] Furthermore, the edge computing gateway also obtains the forecast rainfall within a preset time period in the future, and converts the forecast rainfall into the predicted overflow increment of each node in the corresponding pipeline network according to the preset time and area unit lines of each catchment area; after superimposing the predicted overflow increment onto the current overflow volume, it retrieves the obtained flood lookup table (LUT) again to generate a waterlogging evolution trend map and pushes it.

[0014] Specifically, the calculation formulas for obtaining the predicted overflow increment of each node in the corresponding pipeline network are as follows: ; in, γ represents the predicted overflow increment of the corresponding node in the corresponding pipe network; c represents the runoff coefficient; Rforecast represents the forecast rainfall within the preset future time period; Acatch represents the catchment area of ​​the corresponding node in the corresponding pipe network; γ represents the runoff reduction coefficient, which is determined by the runoff characteristics of the time and area unit line. Furthermore, the GIS platform server is also equipped with a channel seepage and siltation identification module, used to perform the following operations: Extract the centerline of the target channel from GIS data and mark the flow direction to construct a one-dimensional curve coordinate (the coordinate value increases along the water flow direction); obtain discrete water points collected by fixed terminals and mobile inspections along the line at the same flow level, and project each discrete water point onto the centerline of the target channel to obtain the curve coordinates and geodetic height of each discrete water point; For any position to be estimated on the center line of the channel, the water surface line is reconstructed using a spatial interpolation algorithm with flow direction constraints. Only the measured water points upstream of the corresponding position to be estimated are selected to participate in the interpolation calculation. When there are not enough upstream measuring points, the nearest downstream measuring point is selected and extrapolated according to the preset hydraulic gradient. Specifically, in the process of selecting the measured water level points upstream of the corresponding location to be estimated for interpolation calculation, the weight of each measuring point is determined by the following calculation formula: ; in, Indicates the weight of the corresponding measurement point; This indicates any position to be estimated on the channel center's online platform; This represents the curve coordinates of the corresponding water point obtained by projecting the corresponding water point onto the centerline of the channel; This represents the normal offset of the corresponding water point obtained by projecting it onto the channel centerline; Indicates the relevant scale parameters along the route; The normal-related scale parameters are represented, both of which are determined through calibration based on the channel cross-sectional shape and hydraulic characteristics; the water level value at the location to be estimated is obtained, denoted as... The The express The water level at the corresponding measuring point is at ground level. The reconstructed water surface line along the channel is subtracted from the designed channel bottom elevation line. This difference is then compared with the historical health benchmark difference at the same flow rate. Based on the direction and degree of deviation of the difference in continuous channel sections, suspected siltation or leakage sections are automatically marked, and a risk channel section map is generated and pushed to the mobile inspection terminal. Specifically, if the difference between the reconstructed water surface line and the historical health benchmark difference at the same flow rate is greater than a preset siltation threshold at multiple consecutive locations along the channel, the channel section is marked as a suspected siltation section. If the result of subtracting the reconstructed water surface line from the historical health benchmark difference at the same flow rate is greater than a preset leakage threshold, the channel section is marked as a suspected leakage section. Otherwise, the channel section is determined to be normal.

[0015] Compared with the prior art, the beneficial effects achieved by the present invention are: (1) This invention integrates laser ranging, barometric altimetry and tilt measurement in the inspection well. By using the reference geodetic height and wellhead plane coordinates provided by the inspection terminal RTK, combined with the horizontal offset vector between the terminal and the center of the well cover, the real three-dimensional geodetic coordinates of the terminal are calculated in real time and written into storage and uploaded for updates. This solution effectively overcomes the technical defects of traditional terminal coordinates being fixed for a long time while the actual spatial position drifts due to settlement and deformation. (2) This invention integrates the pressure difference and the vertical distance measured by laser ranging. When the deviation between the two is within the confidence threshold, a weighted average is used. The weights are reasonably allocated by the prior accuracy of different sensors, which effectively reduces the random error of a single sensor. When the deviation exceeds the limit, the measurement abnormality is actively judged and a fault prompt is generated. The one with higher nominal accuracy is selected as the output to avoid writing incorrect calibration data and enhance the anti-interference ability of the system in complex well environments. (3) This invention uses a mobile inspection terminal to capture water level images and accurately calculates the actual water level geodetic height through the principle of projective transformation and cross ratio invariance, avoiding subjective estimation errors by inspection personnel. At the same time, it compares the output value with that of a fixed water level sensor. When the deviation exceeds the dynamic threshold, a zero-point drift correction command is automatically generated. The judgment criteria are dynamically adjusted according to the sensor's nominal accuracy and historical water level fluctuation range to achieve accurate compensation for sensor drift. (4) This invention utilizes DEM and multi-flow direction algorithm to construct a lookup table for overflow volume, water accumulation range and water accumulation depth offline. When running online, it directly calculates the overflow volume by the difference between node water level and ground elevation and quickly retrieves LUT to generate waterlogging risk patches, thus avoiding the large amount of time consumed by online iterative calculation of traditional numerical models. (5) The present invention converts the forecast rainfall in the future time period into the overflow increment of the pipeline node through the unit line of the catchment area and superimposes it on the current overflow volume. The LUT is retrieved again to generate the waterlogging trend patch, so that the system has the ability to predict in advance. To a certain extent, it can assist the operation and maintenance personnel to deploy emergency resources in advance and effectively reduce the loss of waterlogging disaster. (6) This invention introduces a spatial interpolation strategy with flow direction constraints, selects only the measured water point upstream of the location to be estimated to participate in the interpolation, and combines the dual-scale Gaussian weight allocation along the direction and the normal direction to fully consider the unidirectional characteristics of channel water flow and the influence of cross-sectional geometry, effectively avoiding the physical inconsistency problem caused by traditional unconstrained interpolation; after the difference between the reconstructed water surface line and the designed channel bottom is calculated, it is compared with the historical health benchmark, and the suspected siltation section and leakage section are automatically distinguished according to the deviation direction and degree of continuous channel sections, providing accurate section positioning basis for channel dredging and seepage prevention maintenance. Attached Figure Description

[0016] The accompanying drawings are provided to further illustrate the invention and form part of the specification. They are used in conjunction with embodiments of the invention to explain the invention and do not constitute a limitation thereof. In the drawings: Figure 1 This is a schematic diagram of the intelligent acquisition and analysis system for water conservancy operation status that integrates spatial information, as per the present invention. Detailed Implementation

[0017] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0018] Please see Figure 1 This embodiment provides an intelligent data acquisition and analysis system for water conservancy operation status that integrates spatial information. It includes multiple fixed intelligent data acquisition terminals deployed in the monitoring area, at least one mobile inspection terminal carried by inspection personnel, and a GIS platform server communicatively connected to both. The fixed intelligent data acquisition terminals include a first type of terminal installed in a manhole. This first type of terminal integrates a water level or flow sensor, a laser ranging module, a barometer, an inclinometer, a first short-range wireless communication module, and a terminal processing unit. The first type of terminal stores its own device identifier and the code of the manhole it belongs to. The mobile inspection terminal integrates an RTK positioning module, a barometer, an inertial measurement unit (IMU), a camera, a second short-range wireless communication module, and an inspection processing unit. The mobile inspection terminal is equipped with a centering auxiliary tool to keep the phase center of the RTK antenna vertically aligned with the center point of the target manhole cover during inspection operations. The system also includes a second type of terminal deployed beside open channels or rivers and water gauges set near the second type of terminal; the second type of terminal integrates at least a water level sensor; the GIS platform server also stores the geodetic coordinates of each water gauge, the geodetic height of the bottom reference point of the water gauge, and the effective scale length of the water gauge. The mobile inspection terminal is also used to perform water level image recognition and sensor drift correction processes, specifically including: The mobile inspection terminal moves to the vicinity of the target water gauge and captures an image of the water gauge containing the complete and valid scale segment through a camera. Simultaneously, it records the camera's three-dimensional geodetic coordinates obtained by the RTK positioning module and the camera's attitude angles obtained by the inertial measurement unit (IMU) at the time of capture. The attitude angles include azimuth, pitch, and roll angles. The mobile inspection terminal retrieves the reference parameters of the water gauge from the GIS platform server. The inspection processing unit performs tilt correction on the water gauge image based on the camera attitude angle, so that the water gauge body in the image is vertical; it performs grayscale conversion, edge detection and Hough line transform on the corrected image, extracts the edge of the water gauge body, identifies the boundary line between the water surface and the water gauge body, and obtains the pixel row coordinates of the boundary line in the image; at the same time, it identifies at least three scale feature points with known actual elevations, and obtains the pixel row coordinates of each scale feature point and its corresponding geodetic height value. The inspection processing unit considers the projection relationship between the vertical line of the water gauge on the image and the vertical line of the object as a one-dimensional projective transformation. Based on the principle of cross ratio invariance, it uses the pixel coordinates and geodetic height values ​​of the at least three known elevation scale feature points to calculate the true water level geodetic height corresponding to the water surface boundary line.

[0019] The mobile inspection terminal is also used to realize the drift correction of the water level sensor of the second type of terminal; The inspection processing unit obtains the water level value output by the water level sensor of the second type of terminal at the same time, and calculates the absolute value of the difference between the actual water level and the sensor water level; if the absolute value of the difference between the actual water level and the sensor water level is greater than the corresponding dynamic threshold, a zero-point drift correction instruction is generated, and the zero-point drift correction instruction is sent to the second type of terminal through the edge computing gateway to modify the zero-point offset stored inside the second type of terminal, and bind and store the correction record with the GIS point of the corresponding water gauge. The dynamic threshold is obtained by querying the threshold bound in the preset form based on the historical water level fluctuation range of the measuring point and the sensor's nominal accuracy. The calculation formula involved in modifying the zero-point offset stored internally in the second type of terminal in this invention is as follows: ; in, This represents the updated zero-point offset stored internally in the second type of terminal; This represents the zero-point offset stored internally in the second type of terminal before the update. This indicates the water level value output by the water level sensor of the second type of terminal at the target water gauge at the corresponding time. This indicates the actual water level at the corresponding moment.

[0020] The GIS platform server stores the reference geodetic height of each manhole cover, the correspondence between the device identifier of the first type of terminal inside the manhole and the code of the manhole, and the geodetic plane coordinates of each manhole. When executing the downhole terminal spatial positioning self-calibration process: The mobile inspection terminal moves to the top of the target manhole cover, obtains the current geodetic coordinates through its RTK positioning module, and collects the wellhead air pressure value through its barometer; the mobile inspection terminal retrieves the reference geodetic height of the manhole cover from the GIS platform server, and wakes up the corresponding first-type terminal downhole through the second short-range wireless communication module, and sends the obtained reference geodetic height, wellhead air pressure value and geodetic coordinates to the first-type terminal downhole. After the first type of terminal is woken up, it measures the first distance from its installation position to the inner wall of the manhole cover through the laser ranging module, collects the air pressure value in the well through its own barometer, and measures its tilt angle relative to the plumb line through the inclinometer. The terminal processing unit of the first type of terminal calculates the pressure difference based on the difference between the wellhead gas pressure and the wellbore gas pressure. The calculation formula involved is as follows: ; in, This represents the pressure difference, where k represents the pre-calibrated conversion factor between pressure difference and pressure difference; Indicates the gas pressure inside the well; This indicates the wellhead gas pressure.

[0021] The obtained first distance is corrected to a vertical distance using the obtained tilt angle. Specifically, during the fusion processing of the obtained air pressure difference and vertical distance by the terminal processing unit of the first type of terminal, when the absolute value of the difference between the obtained air pressure difference and vertical distance is within a preset confidence threshold, the weighted average of the obtained air pressure difference and vertical distance is taken as the final height difference. The weighting weight is determined based on the prior accuracy of laser ranging and air pressure measurement. When the absolute value of the difference between the obtained air pressure difference and vertical distance exceeds the preset confidence threshold, a measurement abnormality is determined, a fault prompt is generated, and the one with higher nominal accuracy between the obtained air pressure difference and vertical distance is selected as the final height difference. The terminal processing unit calculates the true three-dimensional geodetic coordinates of the first type of terminal as (Xdev, Ydev, Hdev), where the value of Hdev is equal to the difference between the received reference geodetic height of the manhole cover and the final height difference. The corresponding geodetic plane coordinates are denoted as (Xrtk, Yrtk). The pre-calibrated horizontal offset vector representing the plane offset between the center of the manhole cover and the installation position of the first type of terminal is denoted as (Δx, Δy). The value of Xdev is equal to the difference between Xrtk and Δx. The value of Ydev is equal to the difference between Yrtk and Δy.

[0022] The obtained pressure difference and vertical distance are fused to obtain the final pressure difference from the terminal to the wellhead; Specifically, the calculation formula for correcting the obtained first distance to the vertical distance using the obtained tilt angle is as follows: ; in, Indicates vertical distance; This indicates the first distance from its own installation position to the inner wall of the manhole cover, measured by the laser ranging module. It represents the angle of inclination of itself relative to the vertical line, as measured by an inclinometer. The first type of terminal also includes an acoustic transceiver module; after two adjacent first type terminals have completed self-calibration, one terminal transmits an acoustic signal, and the other terminal receives and records the propagation time, calculates the acoustic propagation distance, and compares the propagation distance with the corresponding drainage pipe axis design length stored in the GIS platform server. If the deviation between the propagation distance and the corresponding drainage pipe axis design length stored in the GIS platform server exceeds the preset verification threshold, a spatial point abnormality alarm is generated.

[0023] Specifically, the self-calibration process also includes an auxiliary verification step for adjacent inspection wells: The GIS platform server also stores the design length of the drainage pipe axis between adjacent inspection wells, denoted as Lpipe; After both terminal A in the first inspection well and terminal B in the second inspection well have completed self-calibration, terminal A transmits acoustic pulse signals into the pipeline through its acoustic transceiver module, and terminal B receives the signals through its own acoustic transceiver module and records the signal propagation time, denoted as t. The following formulas are used to calculate the propagation distance of sound waves along a pipe: ; Where Dcalc represents the propagation distance of the sound wave along the pipe; vso represents the equivalent propagation speed of the sound wave in the air medium inside the pipe, which is obtained by pre-experimental calibration or real-time compensation based on the ambient temperature inside the pipe. The propagation distance Dcalc of the obtained sound wave along the pipe is compared with the design length Lpipe of the corresponding drainage pipe axis. If |Dcalc-Lpipe| exceeds the preset verification threshold, a spatial point anomaly alarm is generated, triggering a review of the calibration results of the relevant terminals.

[0024] The terminal processing unit obtains the geodetic height of the first type of terminal installation position by subtracting the final elevation difference from the received manhole cover reference geodetic height, and calculates the true three-dimensional geodetic coordinates of the first type of terminal by combining the corresponding geodetic plane coordinates with the pre-calibrated horizontal offset vector of the manhole cover center and the installation position of the first type of terminal in the geodetic plane coordinate system. The first type of terminal writes the obtained real three-dimensional geodetic coordinates into its internal storage and uploads them to the GIS platform server to update its spatial points.

[0025] The system also includes an edge computing gateway, which internally stores a pre-generated flood lookup table (LUT). The flood lookup table (LUT) is generated as follows: Based on the digital elevation model (DEM), a multi-flow direction algorithm is used to divide the urban surface into several catchment areas. For each drainage network node, with a preset overflow volume increment as the step size, the volume filling method is used to simulate the distribution of surface water accumulation range and water depth corresponding to different overflow volumes offline, and establish the mapping relationship between overflow volume, water accumulation range, and water depth. The volume filling method takes the network node as the center and prioritizes the allocation of water accumulation volume to the neighboring grid with the lowest DEM elevation until the cumulative filling volume equals the current overflow volume, and records the water depth value of each grid. The edge computing gateway acquires water level data uploaded by each type of terminal in real time. When the water level of any node exceeds the ground elevation corresponding to that node, it calculates the current overflow volume and uses this overflow volume as an index to retrieve the obtained flood lookup table (LUT), directly mapping the corresponding water accumulation range and water depth distribution, generating a flood risk patch and pushing it to the mobile inspection terminal. The calculation formula involved in calculating the current overflow volume in this invention is as follows: ; Where Awell represents the cross-sectional area of ​​the inspection well; h represents the ground elevation corresponding to the node; h represents the water level of the corresponding node. If multiple nodes overflow simultaneously, spatial overlay analysis is performed on the multiple sets of water accumulation range polygons obtained from the retrieval. The water depth value of the overlapping area is taken as the maximum value of the water depth from each source, and a synthetic waterlogging risk patch is generated and pushed to the mobile inspection terminal.

[0026] The edge computing gateway also obtains the forecast rainfall within a preset time period, and converts the forecast rainfall into the predicted overflow increment of each node in the corresponding pipeline network according to the preset time and area unit lines of each catchment area; after superimposing the predicted overflow increment onto the current overflow volume, it retrieves the obtained inundation lookup table (LUT) again, generates a waterlogging evolution trend map, and pushes it.

[0027] Specifically, the calculation formulas for obtaining the predicted overflow increment of each node in the corresponding pipeline network are as follows: ; in, γ represents the predicted overflow increment of the corresponding node in the corresponding pipe network; c represents the runoff coefficient; Rforecast represents the forecast rainfall within the preset future time period; Acatch represents the catchment area of ​​the corresponding node in the corresponding pipe network; γ represents the runoff reduction coefficient, which is determined by the runoff characteristics of the time and area unit line. The GIS platform server also includes a channel seepage and siltation identification module, used to perform the following operations: Extract the centerline of the target channel from GIS data and mark the flow direction to construct a one-dimensional curve coordinate (the coordinate value increases along the water flow direction); obtain discrete water points collected by fixed terminals and mobile inspections along the line at the same flow level, and project each discrete water point onto the centerline of the target channel to obtain the curve coordinates and geodetic height of each discrete water point; For any position to be estimated on the center line of the channel, the water surface line is reconstructed using a spatial interpolation algorithm with flow direction constraints. Only the measured water points upstream of the corresponding position to be estimated are selected to participate in the interpolation calculation. When there are not enough upstream measuring points, the nearest downstream measuring point is selected and extrapolated according to the preset hydraulic gradient. Specifically, in the process of selecting the measured water level points upstream of the corresponding location to be estimated for interpolation calculation, the weight of each measuring point is determined by the following calculation formula: ; in, Indicates the weight of the corresponding measurement point; This indicates any position to be estimated on the channel center line; This represents the curve coordinates of the corresponding water point obtained by projecting the corresponding water point onto the centerline of the channel; This represents the normal offset distance of the corresponding water point obtained by projecting the corresponding water point onto the channel centerline; Indicates the relevant scale parameters along the route; The normal-related scale parameters are represented, both of which are determined through calibration based on the channel cross-sectional shape and hydraulic characteristics; the water level value at the location to be estimated is obtained, denoted as... The The express The water level at the corresponding measuring point is at ground level. The reconstructed water surface line along the channel is subtracted from the designed channel bottom elevation line. This difference is then compared with the historical health benchmark difference at the same flow rate. Based on the direction and degree of deviation of the difference in continuous channel sections, suspected siltation or leakage sections are automatically marked, and a risk channel section map is generated and pushed to the mobile inspection terminal. Specifically, if the difference between the reconstructed water surface line and the historical health benchmark difference at the same flow rate is greater than a preset siltation threshold at multiple consecutive locations along the channel, the channel section is marked as a suspected siltation section. If the result of subtracting the reconstructed water surface line from the historical health benchmark difference at the same flow rate is greater than a preset leakage threshold, the channel section is marked as a suspected leakage section. Otherwise, the channel section is determined to be normal.

[0028] It should be noted that, in this document, relational terms such as "first" and "second" are used only to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such process, method, article, or apparatus.

[0029] Finally, it should be noted that the above descriptions are merely preferred embodiments of the present invention and are not intended to limit the present invention. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art can still modify the technical solutions described in the foregoing embodiments or make equivalent substitutions for some of the technical features. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. A water conservancy operation status intelligent acquisition and analysis system integrating spatial information, comprising multiple fixed intelligent acquisition terminals deployed in the monitoring area, at least one mobile inspection terminal carried by inspection personnel, and a GIS platform server communicating with both, characterized in that, The fixed intelligent data acquisition terminal includes a first type of terminal installed inside the inspection well. The first type of terminal integrates a water level or flow sensor, a laser ranging module, a barometer, an inclinometer, a first short-range wireless communication module, and a terminal processing unit. The first type of terminal stores its own device identifier and the code of the inspection well to which it belongs. The mobile inspection terminal integrates an RTK positioning module, a barometer, an inertial measurement unit (IMU), a camera, a second short-range wireless communication module, and an inspection processing unit. The GIS platform server stores the reference geodetic height of each manhole cover, the correspondence between the device identifier of the first type of terminal inside the manhole and the code of the manhole, and the geodetic plane coordinates of each manhole. When executing the downhole terminal spatial positioning self-calibration process: The mobile inspection terminal moves to the top of the target manhole cover, obtains the current geodetic coordinates through its RTK positioning module, and collects the wellhead air pressure value through its barometer; the mobile inspection terminal retrieves the reference geodetic height of the manhole cover from the GIS platform server, and wakes up the corresponding first-type terminal downhole through the second short-range wireless communication module, and sends the obtained reference geodetic height, wellhead air pressure value and geodetic coordinates to the first-type terminal downhole. After the first type of terminal is woken up, it measures the first distance from its installation position to the inner wall of the manhole cover through the laser ranging module, collects the air pressure value in the well through its own barometer, and measures its tilt angle relative to the plumb line through the inclinometer. The terminal processing unit of the first type of terminal calculates the pressure difference based on the difference between the wellhead gas pressure and the wellbore gas pressure, and uses the obtained tilt angle to correct the obtained first distance to the vertical distance. The obtained pressure difference and the vertical distance are then fused to obtain the final height difference from the terminal to the wellhead. The terminal processing unit obtains the geodetic height of the first type of terminal installation position by subtracting the final elevation difference from the received manhole cover reference geodetic height, and calculates the true three-dimensional geodetic coordinates of the first type of terminal by combining the corresponding geodetic plane coordinates with the pre-calibrated horizontal offset vector of the manhole cover center and the installation position of the first type of terminal in the geodetic plane coordinate system. The first type of terminal writes the obtained real three-dimensional geodetic coordinates into its internal storage and uploads them to the GIS platform server to update its spatial points.

2. The intelligent data acquisition and analysis system for water conservancy operation status integrating spatial information according to claim 1, characterized in that, The first type of terminal calculates the pressure difference based on the difference between the wellhead pressure and the wellbore pressure, using the following formula: ； in, This represents the pressure difference, where k represents the pre-calibrated conversion factor between pressure difference and pressure difference; Indicates the gas pressure inside the well; This indicates the wellhead gas pressure.

3. The intelligent data acquisition and analysis system for water conservancy operation status integrating spatial information according to claim 1, characterized in that, During the fusion processing of the obtained air pressure difference and vertical distance by the terminal processing unit of the first type of terminal, when the absolute value of the difference between the obtained air pressure difference and vertical distance is within a preset confidence threshold, the weighted average of the obtained air pressure difference and vertical distance is taken as the final height difference, and the weighting weight is determined based on the prior accuracy of laser ranging and air pressure measurement; when the absolute value of the difference between the obtained air pressure difference and vertical distance exceeds the preset confidence threshold, the measurement is judged to be abnormal, a fault prompt is generated, and the one with higher nominal accuracy between the obtained air pressure difference and vertical distance is selected as the final height difference; The terminal processing unit calculates the true three-dimensional geodetic coordinates of the first type of terminal as (Xdev, Ydev, Hdev), where the value of Hdev is equal to the difference between the received reference geodetic height of the manhole cover and the final height difference. The corresponding geodetic plane coordinates are denoted as (Xrtk, Yrtk). The pre-calibrated horizontal offset vector representing the plane offset between the center of the manhole cover and the installation position of the first type of terminal is denoted as (Δx, Δy). The value of Xdev is equal to the difference between Xrtk and Δx. The value of Ydev is equal to the difference between Yrtk and Δy.

4. The intelligent data acquisition and analysis system for water conservancy operation status integrating spatial information according to claim 1, characterized in that, The first type of terminal also includes an acoustic transceiver module; after two adjacent first type terminals have completed self-calibration, one terminal transmits an acoustic signal, and the other terminal receives and records the propagation time, calculates the acoustic propagation distance, and compares the propagation distance with the corresponding drainage pipe axis design length stored in the GIS platform server. If the deviation between the propagation distance and the corresponding drainage pipe axis design length stored in the GIS platform server exceeds the preset verification threshold, a spatial point abnormality alarm is generated.

5. The intelligent data acquisition and analysis system for water conservancy operation status integrating spatial information according to claim 1, characterized in that, The system also includes a second type of terminal deployed beside open channels or rivers and water gauges set near the second type of terminal; the second type of terminal integrates at least a water level sensor; the GIS platform server also stores the geodetic coordinates of each water gauge, the geodetic height of the bottom reference point of the water gauge, and the effective scale length of the water gauge. The mobile inspection terminal is also used to perform water level image recognition and sensor drift correction processes, specifically including: The mobile inspection terminal moves to the vicinity of the target water gauge and takes a picture of the water gauge containing the complete and effective scale segment through the camera. At the same time, it records the three-dimensional geodetic coordinates of the camera obtained by the RTK positioning module and the camera attitude angle obtained by the inertial measurement unit (IMU) at the time of shooting. The inspection processing unit processes the water gauge image, identifies the boundary line between the water surface and the water gauge body, obtains the pixel row coordinates of the boundary line in the image, and identifies at least three known geodetic height scale feature points and their pixel row coordinates in the image. The inspection processing unit, based on the principle of cross-ratio invariance, uses the correspondence between the pixel row coordinates of at least three scale feature points and the known geodetic height to calculate the true water level geodetic height corresponding to the water surface boundary line.

6. The intelligent data acquisition and analysis system for water conservancy operation status integrating spatial information according to claim 5, characterized in that, The mobile inspection terminal is also used to realize the drift correction of the water level sensor of the second type of terminal; The inspection processing unit obtains the water level value output by the water level sensor of the second type of terminal at the same time, and calculates the absolute value of the difference between the actual water level and the sensor water level; if the absolute value of the difference between the actual water level and the sensor water level is greater than the corresponding dynamic threshold, a zero-point drift correction instruction is generated, and the zero-point drift correction instruction is sent to the second type of terminal through the edge computing gateway to modify the zero-point offset stored inside the second type of terminal, and bind and store the correction record with the GIS point of the corresponding water gauge. The dynamic threshold is obtained by querying the preset form based on the historical water level fluctuation range of the measuring point and the sensor's nominal accuracy.

7. The intelligent data acquisition and analysis system for water conservancy operation status integrating spatial information according to claim 5, characterized in that, The system also includes an edge computing gateway, which internally stores a pre-generated flood lookup table (LUT). The flood lookup table (LUT) is generated as follows: Based on the digital elevation model (DEM), a multi-flow direction algorithm is used to divide the urban surface into several catchment areas. For each drainage network node, with a preset overflow volume increment as the step size, the volume filling method is used to simulate the distribution of surface water accumulation range and water depth corresponding to different overflow volumes offline, and establish the mapping relationship between overflow volume, water accumulation range, and water depth. The volume filling method takes the network node as the center and prioritizes the allocation of water accumulation volume to the neighboring grid with the lowest DEM elevation until the cumulative filling volume equals the current overflow volume, and records the water depth value of each grid. The edge computing gateway acquires water level data uploaded by each type of terminal in real time. When the water level of any node exceeds the ground elevation corresponding to the node, it calculates the current overflow volume and uses the overflow volume as an index to retrieve the obtained flood lookup table (LUT), directly mapping the corresponding water accumulation range and water depth distribution, generating an urban flooding risk map and pushing it to the mobile inspection terminal. If multiple nodes overflow simultaneously, spatial overlay analysis is performed on the multiple sets of water accumulation range polygons obtained from the retrieval. The water depth value of the overlapping area is taken as the maximum value of the water depth from each source, and a synthetic waterlogging risk patch is generated and pushed to the mobile inspection terminal.

8. The intelligent data acquisition and analysis system for water conservancy operation status integrating spatial information according to claim 7, characterized in that, The edge computing gateway also obtains the forecast rainfall within a preset time period, and converts the forecast rainfall into the predicted overflow increment of each node in the corresponding pipeline network according to the preset time and area unit lines of each catchment area; after superimposing the predicted overflow increment onto the current overflow volume, it retrieves the obtained inundation lookup table (LUT) again, generates a waterlogging evolution trend map, and pushes it.

9. The intelligent data acquisition and analysis system for water conservancy operation status integrating spatial information according to claim 5, characterized in that, The GIS platform server also includes a channel seepage and siltation identification module, used to perform the following operations: Extract the centerline of the target channel from GIS data and mark the flow direction to construct a one-dimensional curve coordinate system; obtain discrete water points collected by fixed terminals and mobile inspections along the channel at the same flow level, and project each discrete water point onto the centerline of the target channel to obtain the curve coordinates and geodetic height of each discrete water point; For any position to be estimated on the center line of the channel, the water surface line is reconstructed using a spatial interpolation algorithm with flow direction constraints. Only the measured water points upstream of the corresponding position to be estimated are selected to participate in the interpolation calculation. When there are not enough upstream measuring points, the nearest downstream measuring point is selected and extrapolated according to the preset hydraulic gradient. The difference between the reconstructed water surface line along the channel and the designed channel bottom elevation line is calculated, and this difference is compared with the historical health benchmark difference under the same flow level. Based on the direction and degree of deviation of the difference in continuous channel sections, suspected siltation sections or leakage sections are automatically marked, and a risk channel section map is generated and pushed to the mobile inspection terminal.

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