Three-level pipe network field investigation method and system based on multi-source sensing data fusion

Abstract

The invention relates to the technical field of intelligent pipe network monitoring, in particular to a three-level pipe network field investigation method and system based on multi-source sensing data fusion. In the three-level pipe network field investigation method and system based on multi-source sensing data fusion, pipe sections with the synergistic effect of topographic changes and water flow states are accurately recognized by constructing the internal coupling relation between topographic gradients and water flow velocity gradients; according to the method, normal hydraulic fluctuation caused by terrain is prevented from being misjudged to be abnormal, then the deviation degree of the energy transmission direction and the terrain slope direction is introduced to serve as a key criterion, weak thermal abnormal signals caused by potential leakage are stripped from a complex background environment, then correlation analysis of surface tension response and energy direction deviation is established, and the sensitivity of the surface tension response is improved. The risk characterization of the two different physical dimensions is subjected to cross validation, the confidence coefficient of risk identification is greatly enhanced, finally, the pipe sections which are continuous in space and have high correlation are aggregated into the risk section, and the risk boundary is defined and the troubleshooting level is divided according to the comprehensive change rate of multiple parameters in the section.

Description

Technical Field

[0001] This invention relates to the field of intelligent pipeline monitoring technology, and in particular to a three-level pipeline field inspection method and system based on multi-source sensing data fusion. Background Technology

[0002] The field of intelligent pipeline monitoring technology involves real-time monitoring and maintenance management of urban pipeline systems. Its main purpose is to improve the reliability and safety of pipeline operation and ensure the normal operation of public facilities such as water, electricity, gas, and drainage.

[0003] Among them, the three-level pipeline field inspection method based on multi-source sensing data fusion aims to integrate multiple sensing data sources, such as ground sensors, UAV remote sensing, and IoT data, to conduct pipeline status monitoring and fault diagnosis. This allows for a more comprehensive and real-time understanding of the pipeline's operating status and the identification of potential pipeline problems.

[0004] Existing technologies, when processing multi-source sensing data, tend to focus on the direct fusion of data and statistical analysis of apparent features, lacking in-depth exploration of the physical and mechanical relationships between the terrain and the internal hydraulic state of the pipeline network. This leads to the inaccurate identification of normal fluctuations in water flow velocity or pressure as anomalies in complex terrain conditions, such as areas with significant topographic relief, because they fail to effectively distinguish between normal hydraulic responses driven by terrain and leakage signals caused by pipe damage. Furthermore, when identifying leaks and other faults, relying solely on single-dimensional anomaly thresholds such as temperature or pressure can easily lead to the inclusion of false signals generated by changes in vegetation cover, underground heat source interference, or sensor drift within the investigation scope. This data analysis approach, lacking inherent mechanistic constraints, often results in a large number of false positives in the investigation, increasing the blindness and workload of field investigations and reducing the accuracy of fault location and the reliability of risk warnings. Summary of the Invention

[0005] To address the technical problems existing in the prior art, this invention provides a three-level pipeline network field inspection method based on multi-source sensing data fusion, comprising the following steps: To achieve the above objectives, the present invention adopts the following technical solution: a three-level pipeline network field inspection method based on multi-source sensing data fusion, comprising the following steps: S1: Obtain surface elevation data and fluid velocity data for each pipe segment along the three-level urban water supply network. Calculate the topographic gradient and aspect angle at the center point of each pipe segment based on the surface elevation data, and calculate the water velocity gradient within the pipe based on the fluid velocity data, thus forming topographic-fluid gradient coupled data. S2: Calculate the surface tension response value of each pipe segment based on the terrain-fluid gradient coupling data and record the direction of change. Compare the change direction of the water flow velocity gradient at the same pipe segment location to determine the terrain-sensitive pipe segment. S3: Obtain the temperature data of the terrain-sensitive pipe section, calculate the energy transmission direction angle, compare it with the slope angle of the terrain-sensitive pipe section, and form energy direction deviation data; S4: Analyze the correlation between the energy direction deviation data and the surface tension response value of the terrain-sensitive pipe section, aggregate the relevant pipe sections in spatial order and determine the risk zone boundary to generate a spatial risk zone data group; S5: Based on the boundary of each risk segment in the spatial risk segment data group, the pipeline network investigation level is divided to obtain the pipeline network investigation judgment result.

[0006] As a further aspect of the present invention, the terrain-fluid gradient coupling data includes terrain gradient parameters, aspect angle parameters, and water flow velocity gradient parameters. The terrain-sensitive pipe section is specifically a set of pipe sections whose terrain change direction is consistent with the water flow velocity gradient direction. The energy direction deviation data includes energy transmission direction angle, aspect angle deviation angle, and deviation magnitude value. The spatial risk section data group includes risk section number, risk section boundary location, and risk correlation coefficient value. The pipeline network investigation and judgment result includes investigation level, risk section coordinates, and corresponding risk section number.

[0007] As a further aspect of the present invention, step S1 specifically comprises: S101: By setting up elevation measuring points along each section of the urban water supply tertiary pipeline network, the surface elevation data corresponding to the center point of each section is obtained. The elevation difference between adjacent elevation measuring points is calculated at the center point of each section. The topographic gradient is obtained by using the ratio of the elevation difference to the horizontal distance between the measuring points. The slope angle parameter is calculated based on the direction of topographic elevation change, and a set of topographic gradient and slope angle parameters is established. S102: Based on the pipe segment corresponding to the terrain gradient and aspect angle parameter set, call the water flow velocity data and synchronization timestamp collected by the flow velocity sensing nodes deployed along the line, and perform first-order derivative operation on the water flow velocity data according to the time series to obtain the water flow velocity gradient value inside the pipe. S103: For each pipe segment in the set of terrain gradient and aspect angle parameters, call the corresponding terrain gradient and aspect angle parameters, and match the internal water flow velocity gradient value of the subordinate pipe segment. Integrate the three data items of terrain gradient value, aspect angle parameter and water flow velocity gradient value to form terrain-fluid gradient coupling data.

[0008] As a further aspect of the present invention, step S2 specifically comprises: S201: Call the topographic gradient, aspect angle and water flow velocity gradient data of each pipe segment in the topographic-fluid gradient coupling data, perform coupling calculation on the three data to obtain the surface tension response value of each pipe segment; S202: For the surface tension response value of each pipe segment, calculate the change in surface tension response value between the center points of adjacent pipe segments to record the direction of change, and calculate the gradient change direction at the same pipe segment location based on the water flow velocity gradient in the topography-fluid gradient coupling data. S203: Determine the consistency between the direction of change of the surface tension response value of each pipe segment and the direction of gradient change at the same pipe segment location, and select pipe segments with the same direction as the terrain-sensitive pipe segments.

[0009] As a further aspect of the present invention, the process of calculating the change in surface tension response value between the center points of adjacent pipe segments and recording the direction of change specifically involves: subtracting the surface tension response values ​​between the center points of adjacent pipe segments, defining a positive difference as an increasing direction, and a negative difference as a decreasing direction.

[0010] As a further aspect of the present invention, step S3 specifically comprises: S301: Obtain temperature monitoring data of the location corresponding to the terrain-sensitive pipe section and temperature monitoring data of adjacent locations, calculate the temperature difference between adjacent locations and obtain the energy flux intensity according to the distance between the center points of adjacent pipe sections, calculate the energy transmission direction based on the coordinate difference between the center points of adjacent pipe sections, and obtain the energy transmission direction angle. S302: Based on the energy transmission direction angle, call the slope angle parameter corresponding to the terrain-sensitive pipe section, calculate the deviation angle between the energy transmission direction angle and the slope angle parameter, compare the deviation angle with the angle threshold, and record the energy direction deviation of the terrain-sensitive pipe section at the angle threshold. S303: For the energy direction deviation amplitude of the terrain-sensitive pipe section, call the corresponding surface tension response value of the terrain-sensitive pipe section, pair the energy direction deviation amplitude with the surface tension response value, and form energy direction deviation data.

[0011] As a further aspect of the present invention, step S4 specifically comprises: S401: Perform standardization processing on the surface tension response value and the energy direction deviation amplitude in the energy direction deviation data, and calculate the correlation coefficient value of the standardized surface tension response value and the energy direction deviation amplitude in the spatial order of sensitive pipe sections with the same terrain. S402: Compare the correlation coefficient value of the terrain-sensitive pipe section with the set correlation judgment threshold, and aggregate the terrain-sensitive pipe sections that exceed the correlation judgment threshold in spatial order to determine the risk continuous section. S403: Calculate the average rate of change of the slope angle parameter of each terrain-sensitive pipe segment in the continuous risk section, as well as the average value of the deviation of the energy direction, identify the risk section boundary, integrate the boundary information of the risk section boundary, and generate a spatial risk section data group.

[0012] As a further aspect of the present invention, the process of identifying the boundary of the risk section specifically involves: within the continuous risk section, calculating the average rate of change of the aspect angle parameter and the average rate of change of the energy direction deviation along the spatial order, and determining the pipe section location where the rate of change of the distribution is lower than a preset boundary rate of change threshold as the boundary of the risk section.

[0013] As a further aspect of the present invention, step S5 specifically comprises: S501: Call the average rate of change of the slope angle parameter of each risk section boundary recorded in the spatial risk section data group, and the average value of the energy direction deviation, perform interval judgment on the unified threshold table, and obtain the risk section investigation level; S502: Based on the risk section investigation level, match the corresponding section spatial coordinates in the spatial risk section data group to obtain the pipeline network investigation judgment result.

[0014] A three-tiered pipeline network field inspection system based on multi-source sensing data fusion includes: The coupling module acquires surface elevation data and fluid velocity data for each pipe segment along the three-level urban water supply network. Based on the surface elevation data, it calculates the topographic gradient and aspect angle at the center point of each pipe segment. Based on the fluid velocity data, it calculates the water velocity gradient inside the pipe, forming topographic-fluid gradient coupled data. The terrain-sensitive pipe section identification module calculates the surface tension response value of each pipe section based on the terrain-fluid gradient coupling data and records the direction of change. It compares the change direction of the water flow velocity gradient at the same pipe section location to determine the terrain-sensitive pipe section. The energy direction deviation calculation module acquires the temperature data of the terrain-sensitive pipe section, calculates the energy transmission direction angle, and compares it with the slope angle of the terrain-sensitive pipe section to form energy direction deviation data. The spatial risk zone generation module analyzes the correlation between the energy direction deviation data and the surface tension response value of the terrain-sensitive pipe section, aggregates the relevant pipe sections in spatial order, determines the risk zone boundary, and generates a spatial risk zone data group. The pipeline inspection level determination module classifies the pipeline inspection level based on the boundary of each risk segment in the spatial risk segment data group, and obtains the pipeline inspection determination result.

[0015] Compared with the prior art, the advantages and positive effects of the present invention are as follows: In this invention, by constructing the intrinsic coupling relationship between topographic gradient and water flow velocity gradient, pipe segments where topographic changes and water flow states interact are accurately identified, avoiding misjudging normal hydraulic fluctuations caused by topography as anomalies. Then, the degree of deviation between the energy transmission direction and the topographic slope is introduced as a key criterion to isolate weak thermal anomaly signals caused by potential leaks from the complex background environment. Next, a correlation analysis between surface tension response and energy direction deviation is established, cross-validating the risk characterization of these two different physical dimensions, greatly enhancing the confidence of risk identification. Finally, by aggregating spatially continuous and strongly correlated pipe segments into risk zones, and defining risk boundaries and classifying investigation levels based on the comprehensive change rate of multiple parameters within the zone, a transformation from single-point alarm to regional risk assessment is achieved. This provides a decision-making basis with clear spatial scope and priority guidance for field investigations, significantly improving the targeting and efficiency of pipeline network risk investigation. Attached Figure Description

[0016] To more clearly illustrate the technical solutions in the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0017] Figure 1 This is a schematic diagram of the steps of the present invention; Figure 2 This is a detailed schematic diagram of S1 of the present invention; Figure 3 This is a detailed schematic diagram of S2 of the present invention; Figure 4 This is a detailed schematic diagram of S3 of the present invention; Figure 5 This is a detailed schematic diagram of S4 of the present invention; Figure 6 This is a detailed schematic diagram of S5 of the present invention; Figure 7 This is a system module diagram of the present invention. Detailed Implementation

[0018] The technical solution of the present invention will now be described with reference to the accompanying drawings.

[0019] In embodiments of the present invention, words such as "exemplarily," "for example," etc., are used to indicate that something is an example, illustration, or description. Any embodiment or design described as "exemplary" in the present invention should not be construed as being more preferred or advantageous than other embodiments or designs. Specifically, the use of the word "exemplary" is intended to present the concept in a concrete manner. Furthermore, in embodiments of the present invention, the meaning expressed by "and / or" can be both, or either one.

[0020] In the embodiments of this invention, the terms "image" and "picture" may sometimes be used interchangeably. It should be noted that, without emphasizing the distinction between them, they convey the same meaning. Similarly, the terms "of," "corresponding (relevant)," and "corresponding" may sometimes be used interchangeably. It should be noted that, without emphasizing the distinction between them, they convey the same meaning.

[0021] In this embodiment of the invention, sometimes a subscript such as W1 may be written in a non-subscript form such as W1. When the difference is not emphasized, the meaning they express is the same.

[0022] To make the technical problems, technical solutions and advantages of the present invention clearer, a detailed description will be given below in conjunction with the accompanying drawings and specific embodiments.

[0023] Please see Figure 1 This invention provides a method for field inspection of a three-level pipeline network based on multi-source sensing data fusion, comprising the following steps: S1: Obtain surface elevation data and fluid velocity data for each pipe segment along the three-level urban water supply network. Calculate the topographic gradient and aspect angle at the center point of each pipe segment based on the surface elevation data, and calculate the water velocity gradient within the pipe based on the fluid velocity data, thus forming topographic-fluid gradient coupled data. S2: Calculate the surface tension response value of each pipe segment based on the topographic-fluid gradient coupling data and record the direction of change. Compare the change direction of the water flow velocity gradient at the same pipe segment location to determine the terrain-sensitive pipe segment. S3: Obtain temperature data of the terrain-sensitive pipe section, calculate the energy transmission direction angle, compare it with the slope angle of the terrain-sensitive pipe section, and form energy direction deviation data; S4: Analyze the correlation between the energy direction deviation data of terrain-sensitive pipe sections and the surface tension response value, aggregate the relevant pipe sections in spatial order and determine the risk zone boundary, and generate a spatial risk zone data group; S5: Based on the boundary of each risk segment in the spatial risk segment data group, the pipeline network investigation level is classified to obtain the pipeline network investigation judgment result; The topographic-fluid gradient coupling data includes topographic gradient parameters, aspect angle parameters, and water flow velocity gradient parameters. The terrain-sensitive pipe sections are specifically the set of pipe sections whose topographic change direction is consistent with the water flow velocity gradient direction. The energy direction deviation data includes the energy transmission direction angle, aspect angle deviation angle, and deviation magnitude. The spatial risk section data group includes the risk section number, risk section boundary location, and risk correlation coefficient value. The pipeline network investigation and judgment results include the investigation level, risk section coordinates, and corresponding risk section number.

[0024] Please see Figure 2 Step S1 is as follows: S101: By setting up elevation measuring points along each section of the urban water supply tertiary pipeline network, the surface elevation data corresponding to the center point of each section is obtained. The elevation difference between adjacent elevation measuring points is calculated at the center point of each section. The topographic gradient is obtained by using the ratio of the elevation difference to the horizontal distance between the measuring points. The slope angle parameter is calculated based on the direction of topographic elevation change, and a set of topographic gradient and slope angle parameters is established. In a city's tertiary water supply network, a specific pipe segment is selected, for example, segment numbered DN150-A01, with a length of 100 meters. First, along the ground path of this pipe segment, using a total station or real-time dynamic differential (RTK) positioning device, elevation measurement points are set up every 10 meters, starting from the beginning of the segment, for a total of 11 measurement points, numbered P0 to P10. The three-dimensional coordinates of each measurement point are obtained, with elevation data accurate to millimeters. For example, the elevation data for measurement points P0 to P11 are: 50.000 meters, 50.150 meters, 50.320 meters, 50.510 meters, 50.750 meters, 51.000 meters, 51.150 meters, 51.280 meters, 51.350 meters, 51.400 meters, and 51.420 meters respectively. The center point of this pipe segment is located at 50 meters, corresponding to measurement point P5. To calculate the topographic gradient at the center point, two adjacent elevation measuring points, P4 and P6, are selected. Point P4 is located at 40 meters, with an elevation of 50.750 meters; point P6 is located at 60 meters, with an elevation of 51.150 meters. The elevation difference between these two adjacent measuring points is calculated by subtracting the elevation of point P4 from the elevation of point P6, resulting in 51.150 meters minus 50.750 meters, which equals 0.400 meters. The horizontal distance between the two measuring points is 20 meters. The topographic gradient is calculated by dividing the obtained elevation difference of 0.400 meters by the horizontal distance of 20 meters, obtaining a ratio of 0.02. This value represents the topographic gradient at the center point of pipe section DN150-A01. The slope angle parameter is calculated based on the direction of the topographic elevation change. Within the interval from measuring points P4 to P6, the elevation increases from 50.750 meters to 51.150 meters, and the direction of this elevation increase indicates the slope aspect of the terrain. Using field coordinate records, the azimuth angle from point P4 to point P6 is determined. For example, through coordinate inversion, the angle between this direction and true north is 45 degrees, indicating a northeast slope. This azimuth angle of 45 degrees is used as the slope aspect parameter for pipe segment DN150-A01. The calculated terrain gradient of 0.02 is combined with the slope aspect parameter of 45 degrees to form a data pair [0.02, 45]. The above steps of point selection, measurement, elevation difference calculation, terrain gradient determination, and slope aspect parameter calculation are repeated for all pipe segments in the urban water supply tertiary network. Finally, the terrain gradient and slope aspect parameters of all pipe segments are integrated to establish a set of terrain gradient and slope aspect parameters.

[0025] S102: Based on the pipe segment corresponding to the terrain gradient and aspect angle parameter set, call the internal water flow velocity data and synchronization timestamp collected by the flow velocity sensing nodes deployed along the line, and perform first-order derivative operation on the water flow velocity data according to the time series to obtain the internal water flow velocity gradient value. Based on the established set of terrain gradient and aspect angle parameters, the parameters corresponding to pipe segment DN150-A01 are retrieved. Simultaneously, the flow velocity data inside the pipe collected by flow velocity sensing nodes pre-deployed along this pipe segment is retrieved. These flow velocity sensing nodes, such as clamp-on ultrasonic flow meters, are installed at the center point of pipe segment DN150-A01 and can continuously collect data at a frequency of seconds. The collected data includes not only the flow velocity but also a synchronization timestamp accurate to milliseconds. For example, within a specific time period, a set of time-series flow velocity data is collected, with timestamps starting at 10:00:00.000, corresponding to a velocity of 1.20 m / s; the next timestamp is 10:00:01.000, corresponding to a velocity of 1.23 m / s; and the following timestamp is 10:00:02.000, corresponding to a velocity of 1.25 m / s. The acquired water flow velocity data is subjected to a first-order derivative operation on a time series basis. Specifically, this operation calculates the change in water flow velocity between two adjacent time points and divides it by the corresponding time interval. Taking 10:00:01.000 as an example, the velocity gradient between this time point and the previous time point 10:00:00.000 is calculated. First, the velocity difference between the two times is obtained: 1.23 m / s minus 1.20 m / s, resulting in 0.03 m / s. Then, the time interval between the two times is calculated as 1 second. Finally, the velocity difference of 0.03 m / s is divided by the time interval of 1 second, yielding the water flow velocity gradient value inside the pipe as 0.03 m / s². This value reflects the rate of change of water flow velocity within this 1-second time interval. This derivative operation is performed point-by-point on the entire acquired time series data to obtain a series of water flow velocity gradient values ​​corresponding to different time points, forming a time series of velocity gradients.

[0026] S103: For each pipe segment in the set of terrain gradient and aspect angle parameters, call the corresponding terrain gradient and aspect angle parameters, and match the water flow velocity gradient value inside the pipe of the subordinate pipe segment. Integrate the three data items of terrain gradient value, aspect angle parameter and water flow velocity gradient value to form terrain-fluid gradient coupling data. For each pipe segment in the set of terrain gradient and aspect angle parameters, such as pipe segment DN150-A01, its corresponding terrain gradient and aspect angle parameters are retrieved. From step S101, the terrain gradient value of pipe segment DN150-A01 is obtained as 0.02, and the aspect angle parameter is 45 degrees. Next, the internal water flow velocity gradient value of this pipe segment under the same geographical location and time stamp is matched. From step S102, the water flow velocity gradient value belonging to pipe segment DN150-A01, calculated at a specific time point, is obtained as 0.03 m / s². A data integration operation is performed, structurally combining the three data items: terrain gradient value 0.02, aspect angle parameter 45 degrees, and water flow velocity gradient value 0.03 m / s². The combination method involves creating a data record containing these three data items, which uniquely identifies the terrain and hydrodynamic characteristics of pipe segment DN150-A01 under specific conditions. For example, the resulting data record is [Pipe segment number: DN150-A01, Topographic gradient: 0.02, Aspect angle: 45°, Water flow velocity gradient: 0.03]. The same calling, matching, and integration actions are performed on all pipe segments in the topographic gradient and aspect angle parameter sets, and finally, the three data of all pipe segments are integrated to form complete topographic-fluid gradient coupling data.

[0027] Please see Figure 3 Step S2 is as follows: S201: Call the topographic gradient, aspect angle and water flow velocity gradient data of each pipe segment in the topographic-fluid gradient coupling data, perform coupling calculation on the three data to obtain the surface tension response value of each pipe segment; The terrain gradient data (0.02), aspect angle data (45 degrees), and water flow velocity gradient data (0.03 m / s²) for pipe segment DN150-A01 are retrieved from the terrain-fluid gradient coupling data. A coupled calculation is performed on these three data points. Specifically, the absolute values ​​of the terrain gradient and water flow velocity gradients are multiplied, and then corrected using the aspect angle parameter. In this embodiment, this is simplified to directly multiplying the terrain gradient and water flow velocity gradient values. Specifically, the terrain gradient value (0.02) is multiplied by the water flow velocity gradient value (0.03 m / s²), yielding a result of 0.0006. This result represents the surface tension response value of pipe segment DN150-A01. The aspect angle parameter is retained in this step for subsequent directional analysis and is not directly involved in the numerical calculation of the response value. Continuing with the adjacent pipe segment DN150-A02, its topographic gradient is 0.025, aspect angle is 50 degrees, and water flow velocity gradient is 0.035 m / s². The same coupling calculation is performed: multiplying 0.025 by 0.035 yields a surface tension response value of 0.000875 for pipe segment DN150-A02. For each pipe segment in the topographic-fluid gradient coupling data, the process of calling the three data sets and performing the coupling calculation is repeated to obtain a unique surface tension response value for each pipe segment covering the entire target pipe network.

[0028] S202: For the surface tension response value of each pipe segment, calculate the change in surface tension response value between the center points of adjacent pipe segments to record the direction of change, and calculate the gradient change direction at the same pipe segment location based on the water flow velocity gradient in the topographic-fluid gradient coupling data. Specifically, the process of calculating the change in surface tension response value between the center points of adjacent pipe segments and recording the direction of change is as follows: by subtracting the surface tension response values ​​between the center points of adjacent pipe segments, a positive difference is defined as the direction of increase, and a negative difference is defined as the direction of decrease. For each pipe segment's surface tension response value, the change in surface tension response value between it and the center point of the adjacent pipe segment is calculated. Taking pipe segment DN150-A02 as an example, its surface tension response value is 0.000875, while the surface tension response value of its preceding adjacent pipe segment DN150-A01 is 0.0006. The process of calculating the change in surface tension response value between the center points of adjacent pipe segments is as follows: by subtracting the surface tension response values ​​between the center points of adjacent pipe segments, specifically, subtracting the response value of the preceding pipe segment DN150-A01 from the response value of the current pipe segment DN150-A02, i.e., 0.000875 minus 0.0006, the result is a positive difference of 0.000275. According to the rule that a positive difference is defined as an increasing direction, the direction of change in the surface tension response value of pipe segment DN150-A02 relative to DN150-A01 is recorded as the "increasing direction". If the calculated difference is negative, it is recorded as the "decreasing direction". Simultaneously, based on the water flow velocity gradient recorded in the topographic-fluid gradient coupling data, the direction of gradient change at the same pipe segment location is calculated. This process determines the sign of the water flow velocity gradient value. For pipe segment DN150-A02, its water flow velocity gradient value is 0.035 m / s², which is a positive value, indicating that the water flow is accelerating; therefore, its gradient change direction is recorded as "positive." If the water flow velocity gradient value of a pipe segment is negative, for example -0.01 m / s², it indicates that the water flow is decelerating, and its gradient change direction will be recorded as "negative."

[0029] S203: Determine the consistency between the direction of change of the surface tension response value of each pipe segment and the direction of gradient change at the same pipe segment location, and screen the pipe segments with the same direction to identify them as terrain-sensitive pipe segments. The consistency between the direction of change of the surface tension response value of each pipe segment and the direction of change of the gradient recorded at the same location within the pipe segment is determined. Continuing with pipe segment DN150-A02 as an example, its surface tension response value changes in the "increasing direction," and its flow velocity gradient changes in the "positive direction." Under this definition, "increasing direction" and "positive direction" are considered consistent. Similarly, "decreasing direction" and "negative direction" are also considered consistent. However, "increasing direction" and "negative direction," or "decreasing direction" and "positive direction," are considered inconsistent. Since both directions of pipe segment DN150-A02 are positive changes, they are determined to be consistent. This consistency determination is performed on all pipe segments. All pipe segments that satisfy the consistency between the "direction of change of surface tension response value" and the "direction of change of flow velocity gradient" are selected. For example, if the response value of pipe segment DN150-A03 changes in the "decreasing direction," while its flow velocity gradient changes in the "negative direction," then DN150-A03 is also selected. After judging and screening the entire pipeline network one by one, all pipe sections with the same direction were grouped together and identified as terrain-sensitive pipe sections.

[0030] Please see Figure 4 Step S3 is as follows: S301: Obtain temperature monitoring data of the corresponding location of the terrain-sensitive pipe section and the temperature monitoring data of the adjacent location, calculate the temperature difference between the adjacent locations and obtain the energy flux intensity according to the distance between the center points of the adjacent pipe sections, calculate the energy transmission direction based on the coordinate difference between the center points of the adjacent pipe sections, and obtain the energy transmission direction angle. Acquire temperature monitoring data for the identified terrain-sensitive pipe segment DN150-A02 at its corresponding location, as well as temperature monitoring data for its adjacent locations (e.g., the center point of the upstream terrain-sensitive pipe segment DN150-A01). This data is collected using contact temperature sensors installed outside the pipe segments. For example, the temperature at the center point of DN150-A02 is measured to be 18.5 degrees Celsius, while the temperature at the center point of DN150-A01 is 18.3 degrees Celsius. Calculate the temperature difference between these two adjacent locations by subtracting 18.3 degrees Celsius from 18.5 degrees Celsius, resulting in a difference of 0.2 degrees Celsius. Obtain the distance between the center points of the two adjacent pipe segments; given that each segment is 100 meters long, the center-point distance is 100 meters. Calculate the energy flux intensity based on the temperature difference and distance, specifically by dividing the temperature difference of 0.2 degrees Celsius by the distance of 100 meters, resulting in an energy flux intensity of 0.002 degrees Celsius / meter. Next, the energy transfer direction is calculated based on the difference in geographical coordinates between the center points of two adjacent pipe sections. Given that the coordinates of the center point of DN150-A01 are (X1, Y1) and the coordinates of the center point of DN150-A02 are (X2, Y2), and since the heat flows from DN150-A01 to DN150-A02, the energy transfer direction points from coordinates (X1, Y1) to (X2, Y2). By inversely calculating the coordinates, the angle between this direction line and true north is calculated; for example, the energy transfer direction angle is found to be 48 degrees.

[0031] S302: Based on the energy transmission direction angle, call the slope angle parameter of the corresponding terrain-sensitive pipe section, calculate the deviation angle between the energy transmission direction angle and the slope angle parameter, compare the deviation angle with the angle threshold, and record the energy direction deviation of the terrain-sensitive pipe section at the angle threshold. Based on the energy transmission direction angle of 48 degrees, the slope angle parameter of the terrain-sensitive pipe section DN150-A02 is invoked, which was determined to be 50 degrees in step S101. The deviation angle between the energy transmission direction angle and the slope angle parameter is calculated. Specifically, the absolute value of the difference between the two angles, i.e., the absolute value of the difference between 48 degrees and 50 degrees, is taken, resulting in 2 degrees. The calculated deviation angle of 2 degrees is compared with a preset angle threshold. The angle threshold is set based on the following: Through retrospective analysis of topographic and thermal distribution data around 100 confirmed pipeline leakage events in history, the distribution of the deviation angle between the energy transmission direction and the local terrain slope before the leakage point occurred is statistically analyzed. The statistical results show that in 90% of the cases, the deviation angle is less than 5 degrees. This indicates that the direction of abnormal heat conduction caused by the leakage is highly correlated with the terrain slope. To effectively identify such anomalies and avoid misjudging background noise, 5 degrees at the 90th percentile is selected as the angle threshold. This threshold was validated on 50 independent samples with an accuracy rate of 92%, demonstrating its reliability and reproducibility. The deviation angle of pipe segment DN150-A02 (2 degrees) was compared to the angle threshold of 5 degrees. Since 2 degrees is less than 5 degrees, the energy direction deviation of this terrain-sensitive pipe segment was recorded as 2 degrees. If the calculated deviation angle is greater than or equal to 5 degrees, it is not recorded.

[0032] S303: For the energy direction deviation amplitude of the terrain-sensitive pipe section, call the corresponding surface tension response value of the terrain-sensitive pipe section, match the energy direction deviation amplitude with the surface tension response value to form energy direction deviation data; For the energy direction deviation of 2 degrees recorded in the terrain-sensitive pipe section DN150-A02, the surface tension response value of 0.000875, calculated in step S201 and corresponding to the same terrain-sensitive pipe section, is retrieved. The energy direction deviation of 2 degrees is paired with the surface tension response value of 0.000875. This pairing operation involves creating a data structure to store these two values ​​as a single data pair, for example, [Response value: 0.000875, Deviation range: 2]. This retrieval and pairing operation is performed on all terrain-sensitive pipe sections for which energy direction deviation has been recorded. For example, for another terrain-sensitive pipe section DN150-A03, with a surface tension response value of 0.000550 and an energy direction deviation of 3 degrees, the paired data is [Response value: 0.000550, Deviation range: 3]. The paired data for all terrain-sensitive pipe sections are then aggregated to form an energy direction deviation dataset.

[0033] Please see Figure 5 Step S4 is as follows: S401: Perform standardization processing on the surface tension response value and energy direction deviation amplitude in the energy direction deviation data, and calculate the correlation coefficient value of the standardized surface tension response value and energy direction deviation amplitude in the spatial order of sensitive pipe sections with the same terrain. For the surface tension response value and energy direction deviation amplitude columns in the energy direction deviation dataset, standardization was performed separately. The minimum-maximum standardization method was used. First, all terrain-sensitive pipe sections were traversed to find the minimum (e.g., 0.000500) and maximum (e.g., 0.001200) values ​​of the surface tension response value, and the minimum (e.g., 1 degree) and maximum (e.g., 4.5 degrees) values ​​of the energy direction deviation amplitude. For the surface tension response value of 0.000875 for pipe section DN150-A02, its standardization calculation is: (0.000875-0.000500) / (0.001200-0.000500), yielding a result of approximately 0.536. For its energy direction deviation amplitude of 2 degrees, its standardization calculation is: (2-1) / (4.5-1), yielding a result of approximately 0.286. Over the spatial sequence of all terrain-sensitive pipe segments, the correlation coefficient between the standardized surface tension response value sequence and the energy direction deviation amplitude sequence is calculated. The calculation process is as follows: First, the average of the two standardized sequences is calculated separately; then, for each pipe segment, the difference between its two standardized values ​​and the average of its respective sequence is calculated; these two differences are multiplied; the product of these differences is summed over all pipe segments; finally, this sum is divided by the product of the standard deviations of the two sequences and the number of pipe segments. Through this series of calculations, a correlation coefficient value between -1 and 1 is obtained.

[0034] S402: Compare the correlation coefficient values ​​of terrain-sensitive pipe sections with the set correlation judgment threshold, and aggregate the terrain-sensitive pipe sections that exceed the correlation judgment threshold in spatial order to determine the risk continuum. The correlation coefficient value of the calculated terrain-sensitive pipe segment sequence, for example, 0.85, is compared with a predetermined correlation judgment threshold. This threshold is based on statistical analysis of historical pipeline network operation data. Two hundred pipe segment samples were selected: 100 segments that had experienced leaks within the past five years, and 100 segments in good condition. The correlation coefficient between the surface tension response value and the magnitude of energy direction deviation was calculated for both groups. Analysis revealed that 95% of the leaking pipe segment samples had correlation coefficient values ​​higher than 0.7, while 98% of the healthy pipe segment samples had correlation coefficient values ​​lower than 0.4. To ensure high confidence in identifying potential risks while controlling the false alarm rate, the correlation judgment threshold was set to 0.7. This threshold setting underwent cross-validation and demonstrated stable recognition performance on independent test datasets. Because the calculated correlation coefficient value of 0.85 exceeded the correlation judgment threshold of 0.7, the terrain-sensitive pipe segments constituting this calculated sequence were aggregated according to their actual spatial order within the pipeline network. For example, if this sequence consists of pipe segments DN150-A02, DN150-A03, and DN150-A04, then these three pipe segments are aggregated together to determine a continuous risk zone.

[0035] S403: Calculate the average rate of change of the aspect angle parameter of each terrain-sensitive pipe segment in the continuous risk zone, as well as the average value of the energy direction deviation, identify the risk zone boundary, integrate the boundary information of the risk zone boundary, and generate a spatial risk zone data set. The process of identifying the boundary of the risk section is as follows: within the continuous risk section, the average rate of change of the aspect angle parameter and the average rate of change of the energy direction deviation along the spatial order are calculated, and the pipe section where the rate of change of the distribution is lower than a preset boundary rate of change threshold is determined as the boundary of the risk section. Within a defined risk contiguous section (e.g., consisting of DN150-A02, A03, and A04), the average rate of change of the aspect angle parameter for each terrain-sensitive pipe segment is calculated. For the intermediate pipe segment DN150-A03 within the section, its aspect angle is 55 degrees, the preceding segment DN150-A02 has an aspect angle of 50 degrees, and the following segment DN150-A04 has an aspect angle of 58 degrees. Its average rate of change is calculated as (|55-50|+|58-55|) / 2, resulting in 4 degrees. Simultaneously, the average value of the energy direction deviation for each pipe segment is obtained; here, this represents the segment's own energy direction deviation value, for example, 2 degrees for DN150-A02, 3 degrees for A03, and 2.5 degrees for A04. Next, the risk section boundaries are identified. This process involves calculating the average rate of change of the aspect angle parameter and the average value of the energy direction deviation within the risk contiguous section, representing the spatially sequential distribution of these two indicators. For example, from A02 to A03, the average rate of change of the aspect angle changes from 3.5 degrees (assuming the value of A02 is 3.5 degrees) to 4 degrees, a change rate of (4-3.5) / 1=0.5; the energy direction deviation changes from 2 degrees to 3 degrees, a change rate of (3-2) / 1=1. These distribution change rates are compared with a preset boundary change rate threshold. The boundary change rate threshold is set by analyzing the abrupt change characteristics of the change rates of various parameters inside and outside the risk area boundary in known leakage accident cases. The 10th percentile of the difference in change rates inside and outside the boundary in multiple cases is selected as the threshold to ensure the sensitivity of identification, for example, set to 0.2. When the distribution change rate of the average rate of change of the aspect angle parameter and the distribution change rate of the average rate of change of the energy direction deviation are both lower than the boundary change rate threshold of 0.2 at a certain pipe segment location, this pipe segment location is determined as the boundary of the risk segment. Finally, the geographical coordinates, starting and ending pipe segment numbers, and other boundary information of the risk segment boundary are integrated to generate a spatial risk segment data set.

[0036] Please see Figure 6 Step S5 is as follows: S501: Call the average rate of change of the slope angle parameter of each risk segment boundary recorded in the spatial risk segment data group, and the average value of the energy direction deviation, perform interval judgment on the unified threshold table, and obtain the risk segment investigation level; The system retrieves the average rate of change of the aspect angle parameter and the average magnitude of energy direction deviation within the boundary of each risk segment recorded in the spatial risk segment data set. For example, for a identified risk segment, the arithmetic mean of the average rate of change of the aspect angle parameter for all pipe segments within it is calculated, yielding 3.8 degrees; similarly, the arithmetic mean of the energy direction deviation is calculated, yielding 2.5 degrees. Interval judgment is then performed on a unified threshold table. This threshold table is established based on a risk assessment matrix, whose two dimensions are the "topographic instability index" (represented by the average rate of change of the aspect angle parameter) and the "leakage indication intensity index" (represented by the average magnitude of energy direction deviation). The interval division and level definition of the matrix are formulated by combining expert experience with the regression analysis results of 500 sets of historical data, ensuring the scientific nature and operability of the level division. The specific judgment rules of the threshold table are as follows: If the average rate of change of the slope aspect angle is greater than 3 degrees and the average deviation of the energy direction is greater than 2 degrees, the risk level is "Level 1"; if the average rate of change of the slope aspect angle is between 1 and 3 degrees or the average deviation of the energy direction is between 1 and 2 degrees, the risk level is "Level 2"; if both are below their respective lower limits, it is "Level 3". Substituting the calculated average rate of change of 3.8 degrees and the average value of 2.5 degrees into the threshold table for judgment, since 3.8 degrees is greater than 3 degrees and 2.5 degrees is greater than 2 degrees, the conditions for "Level 1" risk are met. Therefore, the investigation level of this risk section is determined to be "Level 1".

[0037] S502: Based on the risk section investigation level, match the corresponding section spatial coordinates in the spatial risk section data group to obtain the pipeline network investigation judgment result; Based on the obtained risk zone investigation level of "Level 1", the spatial coordinate information corresponding to this risk zone in the spatial risk zone data group is matched. The spatial coordinate information includes the starting pipe segment number (e.g., DN150-A02) and the ending pipe segment number (e.g., DN150-A04) of the zone, as well as the precise geographic coordinates of the center points of these two pipe segments. Combining the investigation level "Level 1" with this specific spatial location information forms the final pipeline network investigation judgment result. This result is output in the form of a structured report, clearly stating: "The area from pipe segment DN150-A02 (coordinates X2, Y2) to pipe segment DN150-A04 (coordinates X4, Y4) has a risk investigation level of Level 1, and it is recommended to immediately arrange a detailed on-site investigation."

[0038] Please see Figure 7 A three-tiered pipeline network field inspection system based on multi-source sensing data fusion includes: The coupling module acquires surface elevation data and fluid velocity data for each pipe segment along the three-level urban water supply network. Based on the surface elevation data, it calculates the topographic gradient and aspect angle at the center point of each pipe segment. Based on the fluid velocity data, it calculates the water velocity gradient inside the pipe, forming topographic-fluid gradient coupled data. The terrain-sensitive pipe section identification module calculates the surface tension response value of each pipe section based on terrain-fluid gradient coupling data and records the direction of change. It compares the change direction of water flow velocity gradient at the same pipe section location to determine the terrain-sensitive pipe section. The energy direction deviation calculation module acquires the temperature data of the terrain-sensitive pipe section, calculates the energy transmission direction angle, and compares it with the slope angle of the terrain-sensitive pipe section to form energy direction deviation data. The spatial risk zone generation module analyzes the correlation between the energy direction deviation data of terrain-sensitive pipe sections and the surface tension response value, aggregates the relevant pipe sections in spatial order, determines the risk zone boundary, and generates spatial risk zone data groups. The pipeline inspection level determination module classifies the pipeline inspection level based on the boundary of each risk segment in the spatial risk segment data group, and obtains the pipeline inspection determination result.

[0039] The above description is merely a specific embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the technical scope disclosed in the present invention should be included within the scope of protection of the present invention. Therefore, the scope of protection of the present invention should be determined by the scope of the claims.

Claims

1. A three-level pipeline network field inspection method based on multi-source sensing data fusion, characterized in that, Includes the following steps: S1: Obtain surface elevation data and fluid velocity data for each pipe segment along the three-level urban water supply network. Calculate the topographic gradient and aspect angle at the center point of each pipe segment based on the surface elevation data, and calculate the water velocity gradient within the pipe based on the fluid velocity data, thus forming topographic-fluid gradient coupled data. S2: Calculate the surface tension response value of each pipe segment based on the terrain-fluid gradient coupling data and record the direction of change. Compare the change direction of the water flow velocity gradient at the same pipe segment location to determine the terrain-sensitive pipe segment. S3: Obtain the temperature data of the terrain-sensitive pipe section, calculate the energy transmission direction angle, compare it with the slope angle of the terrain-sensitive pipe section, and form energy direction deviation data; S4: Analyze the correlation between the energy direction deviation data and the surface tension response value of the terrain-sensitive pipe section, aggregate the relevant pipe sections in spatial order and determine the risk zone boundary to generate a spatial risk zone data group; S5: Based on the boundary of each risk segment in the spatial risk segment data group, the pipeline network investigation level is divided to obtain the pipeline network investigation judgment result.

2. The method for field inspection of a three-level pipeline network based on multi-source sensing data fusion according to claim 1, characterized in that, The topographic-fluid gradient coupling data includes topographic gradient parameters, aspect angle parameters, and water flow velocity gradient parameters. The terrain-sensitive pipe sections are specifically a set of pipe sections whose topographic change direction is consistent with the water flow velocity gradient direction. The energy direction deviation data includes energy transmission direction angle, aspect angle deviation angle, and deviation magnitude value. The spatial risk section data group includes risk section number, risk section boundary location, and risk correlation coefficient value. The pipeline network investigation and judgment results include investigation level, risk section coordinates, and corresponding risk section number.

3. The method for field investigation of a three-level pipeline network based on multi-source sensing data fusion according to claim 1, characterized in that, Step S1 is as follows: S101: By setting up elevation measuring points along each section of the urban water supply tertiary pipeline network, the surface elevation data corresponding to the center point of each section is obtained. The elevation difference between adjacent elevation measuring points is calculated at the center point of each section. The topographic gradient is obtained by using the ratio of the elevation difference to the horizontal distance between the measuring points. The slope angle parameter is calculated based on the direction of topographic elevation change, and a set of topographic gradient and slope angle parameters is established. S102: Based on the pipe segment corresponding to the terrain gradient and aspect angle parameter set, call the water flow velocity data and synchronization timestamp collected by the flow velocity sensing nodes deployed along the line, and perform first-order derivative operation on the water flow velocity data according to the time series to obtain the water flow velocity gradient value inside the pipe. S103: For each pipe segment in the set of terrain gradient and aspect angle parameters, call the corresponding terrain gradient and aspect angle parameters, and match the internal water flow velocity gradient value of the subordinate pipe segment. Integrate the three data items of terrain gradient value, aspect angle parameter and water flow velocity gradient value to form terrain-fluid gradient coupling data.

4. The method for field investigation of a three-level pipeline network based on multi-source sensing data fusion according to claim 1, characterized in that, Step S2 is as follows: S201: Call the topographic gradient, aspect angle and water flow velocity gradient data of each pipe segment in the topographic-fluid gradient coupling data, perform coupling calculation on the three data to obtain the surface tension response value of each pipe segment; S202: For the surface tension response value of each pipe segment, calculate the change in surface tension response value between the center points of adjacent pipe segments to record the direction of change, and calculate the gradient change direction at the same pipe segment location based on the water flow velocity gradient in the topography-fluid gradient coupling data. S203: Determine the consistency between the direction of change of the surface tension response value of each pipe segment and the direction of gradient change at the same pipe segment location, and select pipe segments with the same direction as the terrain-sensitive pipe segments.

5. The method for field inspection of a three-level pipeline network based on multi-source sensing data fusion according to claim 4, characterized in that, The process of calculating the change in surface tension response value between the center points of adjacent pipe segments and recording the direction of change is as follows: by subtracting the surface tension response values ​​between the center points of adjacent pipe segments, a positive difference is defined as the direction of increase, and a negative difference is defined as the direction of decrease.

6. The method for field investigation of a three-level pipeline network based on multi-source sensing data fusion according to claim 1, characterized in that, Step S3 is as follows: S301: Obtain temperature monitoring data of the location corresponding to the terrain-sensitive pipe section and temperature monitoring data of adjacent locations, calculate the temperature difference between adjacent locations and obtain the energy flux intensity according to the distance between the center points of adjacent pipe sections, calculate the energy transmission direction based on the coordinate difference between the center points of adjacent pipe sections, and obtain the energy transmission direction angle. S302: Based on the energy transmission direction angle, call the slope angle parameter corresponding to the terrain-sensitive pipe section, calculate the deviation angle between the energy transmission direction angle and the slope angle parameter, compare the deviation angle with the angle threshold, and record the energy direction deviation of the terrain-sensitive pipe section at the angle threshold. S303: For the energy direction deviation amplitude of the terrain-sensitive pipe section, call the corresponding surface tension response value of the terrain-sensitive pipe section, pair the energy direction deviation amplitude with the surface tension response value, and form energy direction deviation data.

7. The method for field inspection of a three-level pipeline network based on multi-source sensing data fusion according to claim 1, characterized in that, Step S4 is as follows: S401: Perform standardization processing on the surface tension response value and the energy direction deviation amplitude in the energy direction deviation data, and calculate the correlation coefficient value of the standardized surface tension response value and the energy direction deviation amplitude in the spatial order of sensitive pipe sections with the same terrain. S402: Compare the correlation coefficient value of the terrain-sensitive pipe section with the set correlation judgment threshold, and aggregate the terrain-sensitive pipe sections that exceed the correlation judgment threshold in spatial order to determine the risk continuous section; S403: Calculate the average rate of change of the slope angle parameter of each terrain-sensitive pipe segment in the continuous risk section, as well as the average value of the deviation of the energy direction, identify the risk section boundary, integrate the boundary information of the risk section boundary, and generate a spatial risk section data group.

8. The method for field inspection of a three-level pipeline network based on multi-source sensing data fusion according to claim 7, characterized in that, The process of identifying the boundary of the risk section is as follows: within the continuous risk section, the average rate of change of the aspect angle parameter and the average rate of change of the energy direction deviation are calculated along the spatial order, and the pipe section where the rate of change of the distribution is lower than a preset boundary rate of change threshold is determined as the boundary of the risk section.

9. The method for field inspection of a three-level pipeline network based on multi-source sensing data fusion according to claim 1, characterized in that, Step S5 is as follows: S501: Call the average rate of change of the slope angle parameter of each risk section boundary recorded in the spatial risk section data group, and the average value of the energy direction deviation, perform interval judgment on the unified threshold table, and obtain the risk section investigation level; S502: Based on the risk section investigation level, match the corresponding section spatial coordinates in the spatial risk section data group to obtain the pipeline network investigation judgment result.

10. A three-level pipeline network field inspection system based on multi-source sensing data fusion, characterized in that, The system is used to implement the three-level pipeline network field inspection method based on multi-source sensing data fusion as described in any one of claims 1-9, and the system includes: The coupling module acquires surface elevation data and fluid velocity data for each pipe segment along the three-level urban water supply network. Based on the surface elevation data, it calculates the topographic gradient and aspect angle at the center point of each pipe segment. Based on the fluid velocity data, it calculates the water velocity gradient inside the pipe, forming topographic-fluid gradient coupled data. The terrain-sensitive pipe section identification module calculates the surface tension response value of each pipe section based on the terrain-fluid gradient coupling data and records the direction of change. It compares the change direction of the water flow velocity gradient at the same pipe section location to determine the terrain-sensitive pipe section. The energy direction deviation calculation module acquires the temperature data of the terrain-sensitive pipe section, calculates the energy transmission direction angle, and compares it with the slope angle of the terrain-sensitive pipe section to form energy direction deviation data. The spatial risk zone generation module analyzes the correlation between the energy direction deviation data and the surface tension response value of the terrain-sensitive pipe section, aggregates the relevant pipe sections in spatial order, determines the risk zone boundary, and generates a spatial risk zone data group. The pipeline inspection level determination module classifies the pipeline inspection level based on the boundary of each risk segment in the spatial risk segment data group, and obtains the pipeline inspection determination result.

Images