An industrial park underground sewage pipe network leakage comprehensive detection method and system

Abstract

The present application belongs to the technical field of pipe network leakage detection, in order to solve the problem of inaccurate pipe network leakage detection, difficult to detect large area, etc., a kind of industrial park underground sewage pipe network leakage comprehensive detection method and system are proposed, the ground electromagnetic method is used for overall detection of the area to be detected, the collected data is inverted by using prior constraint, and the detection section of suspected leakage anomaly is judged according to the resistivity profile;The suspected leakage anomaly detection section is further detected by using high-density resistivity method and induced polarization method, the grid is refined based on the electromagnetic method result and prior information, the directionality smoothing constraint and minimum gradient support are introduced to constrain the inversion of the collected data, and the leakage area is located;The authenticity of the measured leakage area is judged by sampling, and the leakage area is located by peeping measurement through pipeline robot;Through the cooperation of multiple methods, the rapid identification and delineation of the pipe network leakage risk area in industrial park are realized.

Description

Technical Field

[0001] This invention belongs to the technical field of pipeline leakage detection, and in particular relates to a comprehensive detection method and system for underground sewage pipeline leakage in industrial parks. Background Technology

[0002] The statements in this section are merely background information related to the present invention and do not necessarily constitute prior art.

[0003] As a core infrastructure for maintaining production activities and environmental safety in industrial parks, the underground sewage pipe network's leakage prevention performance is crucial. Leakage not only leads to the loss of wastewater resources and increases treatment costs, but more seriously, it can cause industrial wastewater containing toxic and harmful pollutants such as heavy metals and persistent organic compounds to seep into the ground, causing irreversible soil and groundwater pollution and posing a long-term threat to the regional ecological environment and human health. Therefore, achieving efficient and accurate detection and diagnosis of potential leakage hazards in industrial park underground sewage pipe networks is an urgent need for environmental risk prevention and control and the safe operation and maintenance of infrastructure.

[0004] Currently, leakage detection methods for underground sewage pipe networks can be mainly divided into the following categories, but each has significant technical bottlenecks and is difficult to meet the high-requirement detection tasks in the complex environment of industrial parks:

[0005] First, traditional geophysical exploration methods suffer from significant ambiguity in industrial zone applications, making precise location difficult. Methods such as high-density resistivity, induced polarization, ground-penetrating radar, and transient electromagnetic methods have been attempted for detecting underground anomalies. These methods infer potential leakage areas by detecting differences in the physical properties of the underground medium (such as resistivity and dielectric constant). However, the underground environment of industrial parks is exceptionally complex. Noise, complex geological formations, pipeline depth, and the inhomogeneity of backfill soil all generate strong electromagnetic interference. Furthermore, the accuracy of geophysical methods decreases with depth; electrical and electromagnetic methods only achieve meter-level accuracy, making it difficult to detect small leaks and potentially leading to misjudgments. Therefore, they cannot serve as reliable independent evidence for leak identification.

[0006] Secondly, direct detection methods are inefficient, ineffective, and costly, making them unsuitable for large-scale preliminary screening. Closed-circuit television (CCTV) inspection systems can visually detect internal defects such as cracks and misalignments in pipelines, but their detection speed is slow, their scope is relatively macroscopic and superficial, and they are subject to requirements regarding water and sediment levels within the pipeline network. If the water / sludge level exceeds a specified threshold, the pipeline robot will be obstructed. Conducting indiscriminate CCTV inspections of the entire industrial park's pipeline network would incur enormous time and economic costs, making it impractical from an engineering perspective. Sampling detection methods are target-oriented and generally used for post-event verification. Because underground sewage pipelines in chemical industrial parks are often contaminated, the chemical elements in the surrounding soil layers differ from those in the surrounding strata. Current technologies often involve drilling to collect soil samples and monitoring wells to collect groundwater samples, analyzing the water's chemical characteristics to determine the type and concentration of pollutants. However, this method is invasive, costly, and typically only used for defining the extent of severe contamination, not for the early proactive detection of potential leaks.

[0007] The aforementioned existing technology has the following problems:

[0008] First, although traditional geophysical survey methods (such as electromagnetic methods, ground penetrating radar, high-density resistivity methods, and induced polarization methods) are easy to carry, simple to measure, and low in cost, they are prone to problems such as noise, complex strata, and pipeline burial depth, which lead to multiple solutions and make it impossible to give reliable conclusions.

[0009] Second, while direct detection methods can clearly show the defects in the measured area, they also have drawbacks, such as difficulty in widespread adoption. For example, CCTV single-segment measurement is costly and is affected by factors such as water level, mud level, and road construction; borehole sampling cannot determine whether a pipe is leaking, but can only provide auxiliary verification. Both methods are difficult to widely implement.

[0010] Therefore, there is an urgent need for a comprehensive detection method that can systematically reduce ambiguity and improve detection efficiency and positioning accuracy, so as to achieve low-cost, high-efficiency and verifiable diagnosis of leakage points and their impact range in industrial park sewage pipe networks, and provide direct and quantitative decision-making basis for subsequent repairs. Summary of the Invention

[0011] To overcome the shortcomings of the existing technology, this invention provides a comprehensive detection method and system for underground sewage pipe network leakage in industrial parks. Through multi-method collaborative and progressive exploration, it can quickly identify and delineate leakage risk areas in pipe networks of large-scale chemical industrial parks, greatly improving investigation efficiency and reducing investigation costs.

[0012] To achieve the above objectives, the present invention adopts the following technical solution:

[0013] In a first aspect, the present invention provides a comprehensive detection method for leakage in underground sewage pipe networks in industrial parks, comprising:

[0014] The ground electromagnetic method is used to conduct overall detection of the area to be tested in the industrial park. The area to be tested is investigated and surveyed to obtain prior information. Prior constraints are used to invert the collected data to obtain the resistivity profile. Based on the resistivity profile, the detection section suspected of leakage is identified.

[0015] For suspected leakage anomalies, the high-density resistivity method and the induced polarization method are used for further detection. Based on the electromagnetic method results and prior information, the mesh is refined. Directional smoothing constraints and minimum gradient support are introduced to inversely constrain the data of the high-density resistivity method and the induced polarization method. The leakage area is located by combining the resistivity profile and the polarization profile.

[0016] The system takes samples from the identified leakage areas to determine the authenticity of the leakage. For the actual leakage areas, a pipeline robot is used to inspect and measure them to accurately locate the leakage areas.

[0017] Secondly, the present invention provides a comprehensive detection system for leakage in underground sewage pipe networks in industrial parks, comprising:

[0018] The electromagnetic detection module is configured to: conduct overall ground electromagnetic detection of the area to be tested in the industrial park, investigate and survey the area to be tested, obtain prior information about the area, use prior constraints to invert the collected data to obtain a resistivity profile, and determine the detection section suspected of leakage based on the resistivity profile.

[0019] The electrical detection module is configured to: further detect suspected leakage anomalies using high-density resistivity method and induced polarization method; refine the mesh based on electromagnetic method results and prior information; introduce directional smoothing constraints and minimum gradient support to invert constraints on the data of high-density resistivity method and induced polarization method; and locate the leakage area by combining resistivity profile and polarization profile.

[0020] The authenticity detection module is configured to: sample the located leakage area to determine the authenticity of the leakage in the measured area;

[0021] The pipeline robot inspection module is configured to use a pipeline robot to visually measure and accurately locate the actual leakage area.

[0022] Thirdly, the present invention provides an electronic device including a memory and a processor, and computer instructions stored in the memory and running on the processor, wherein the computer instructions, when executed by the processor, perform the method described in the first aspect.

[0023] Fourthly, the present invention provides a computer-readable storage medium for storing computer instructions, which, when executed by a processor, perform the method described in the first aspect.

[0024] Fifthly, the present invention provides a computer program product, including a computer program that, when executed by a processor, implements the method described in the first aspect.

[0025] The above one or more technical solutions have the following beneficial effects:

[0026] In this invention, an electromagnetic method is used for rapid screening, and high-density resistivity method and excited polarization method are used for detailed investigation of key sections. Sampling and testing are conducted to verify authenticity. A multi-layered progressive technology system using pipeline robots for precise positioning and detection effectively overcomes the limitations of traditional single detection methods. Through multi-method collaborative progressive exploration, it is possible to quickly identify and delineate leakage risk areas in pipeline networks of large-scale chemical industrial parks, greatly improving investigation efficiency and reducing investigation costs.

[0027] In this invention, differentiated electromagnetic instrument deployment, electrode placement, and data acquisition strategies were designed to address the complex surface cover conditions above different sewage pipelines in chemical industrial parks. For example, bentonite was used to cover electrodes on cement surfaces, and local vegetation was cleared for supplementary measurements. For the electromagnetic method, a priori information-constrained inversion method was employed, which improved the accuracy of anomaly identification around pipelines by approximately 30%, enhancing the accuracy of anomaly detection. For data processing of the high-density resistivity method and the induced polarization method, the electromagnetic method measurement results were combined with park information to refine the grid around pipeline burial depth and suspected leaks. Directional smoothing constraints and minimum gradient support were introduced into the inversion algorithm to improve the accuracy of leak detection and reduce ambiguity. This ensured the effective implementation and data quality of the electromagnetic method, high-density resistivity method, and induced polarization method under different road surface conditions. Subsequently, the pipeline robot CCTV inspection could flexibly adopt various preprocessing and operation modes according to the water level and siltation status inside the pipeline, ensuring successful acquisition of clear images of the pipeline interior even under complex conditions, improving the practicality and environmental adaptability of the method.

[0028] In this invention, a correlation verification relationship was established between ground geophysical anomalies (resistivity, polarizability) and pipeline structural defects (leakage, misalignment, disconnection) by matching the spatial distribution and trend consistency between these anomalies and defects detected by robots inside the pipeline. Defects detected by the pipeline robot were uniformly quantified and the degree of leakage was assessed. This dual verification mechanism of "surface signal anomalies - visible evidence inside the pipe" significantly reduces the ambiguity of geophysical interpretation, enabling precise spatial location of leak points and accurate diagnosis of defect types and levels, providing a reliable basis for subsequent repairs.

[0029] Advantages of additional aspects of the invention will be set forth in part in the description which follows, and in part will be obvious from the description, or may be learned by practice of the invention. Attached Figure Description

[0030] The accompanying drawings, which form part of this invention, are used to provide a further understanding of the invention. The illustrative embodiments of the invention and their descriptions are used to explain the invention and do not constitute an improper limitation of the invention.

[0031] Figure 1 This is a flowchart of the comprehensive detection method for leakage in underground sewage pipe networks in industrial parks, as described in this embodiment of the invention.

[0032] Figure 2 This is a schematic diagram of the selection of electromagnetic electrode spacing and the distribution of measuring lines in an embodiment of the present invention;

[0033] Figure 3 This is a schematic diagram showing the selection of electrode spacing and the distribution of measurement lines for the high-density electrical resistivity and excited polarization methods in embodiments of the present invention;

[0034] Figure 4 This is a schematic cross-sectional view of the resistivity inversion result obtained by electromagnetic method in an embodiment of the present invention;

[0035] Figure 5 This is a schematic cross-sectional view of the resistivity and polarizability results obtained from data measured by the high-density resistivity method and the excited polarization method in this embodiment of the invention. Detailed Implementation

[0036] It should be noted that the following detailed descriptions are exemplary and intended to provide further illustration of the invention. Unless otherwise specified, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention pertains.

[0037] It should be noted that the terminology used herein is for the purpose of describing particular implementations only and is not intended to limit the exemplary implementations of the present invention.

[0038] Where there is no conflict, the embodiments and features in the embodiments of the present invention can be combined with each other.

[0039] Example 1

[0040] This embodiment discloses a comprehensive detection method for leakage in underground sewage pipe networks in industrial parks, including:

[0041] The ground electromagnetic method is used to conduct overall detection of the area to be tested in the industrial park. The area to be tested is investigated and surveyed to obtain prior information. Prior constraints are used to invert the collected data to obtain the resistivity profile. Based on the resistivity profile, the detection section suspected of leakage is identified.

[0042] For suspected leakage anomalies, high-density resistivity method and induced polarization method are used for detection. The grid is refined based on the electromagnetic method results and prior information. The data of high-density resistivity method and induced polarization method are inverted. The leakage area is located by combining resistivity profile and polarization profile.

[0043] Sampling is performed on the identified leakage area to determine the authenticity of the leakage; for areas where leakage is confirmed, a pipeline robot is used for inspection to accurately locate the leakage area.

[0044] This embodiment employs electromagnetic rapid screening, utilizes high-density resistivity and excited polarization methods for detailed investigation of key sections, samples and tests for authenticity, and utilizes a multi-level progressive technology system for pipeline robot location detection. This effectively overcomes the limitations of traditional single detection methods, enabling rapid identification and delineation of leakage risk areas in large-scale industrial park pipeline networks, significantly improving investigation efficiency and reducing investigation costs.

[0045] The following is a detailed description of the comprehensive detection method for leakage in underground sewage pipe networks in industrial parks proposed in this embodiment:

[0046] Step 1: First, conduct on-site surveys in the chemical industrial park to be tested, and determine the location and length of the sewage pipeline through personnel interviews, data collection, organization and analysis.

[0047] Plan the electromagnetic detection route based on the pipeline network distribution and topographic map (electromagnetic detection should cover all pipelines). Based on the actual surface coverage of buried pipelines within the park area, as well as the maximum single measurement segment length of the instrument and the length of the detected pipeline, determine the measurement lines. For example, if the longest single measurement segment is am, and the total length of sewage pipelines within the park is L, then it is necessary to divide the measurement into n ≥ L / a segments. Since the electromagnetic method requires two measurement lines on the left and right sides for each pipeline, the total measurement length A ≥ 2L.

[0048] The detection method for each section is determined based on the surrounding environment of the pipeline. See Figure 2 GPS positioning was used during data collection to record the latitude and longitude of the measurement points. For areas with no surface cover, one measuring line was placed on each side and above the pipe in each measurement section. If the diameter of the sewage well is D, the data collection interval d is 1~2 m, and d≥D. The spacing between the measuring lines is dm. 测 For measurements ≥5D, the data acquisition frequency is generally set to 2 Hz. For sections with flower beds or vegetation covering the ground, electromagnetic instruments cannot be used to measure in a straight line as originally designed. It is advisable to appropriately increase the distance between the two parallel measuring lines and lay out measuring lines perpendicular to the pipeline at an appropriate density in the middle for supplementary measurements. Only the vegetation needs to be cleared locally. This method can efficiently and with low loss, the electrical measurement of the pipeline can be carried out.

[0049] Complete the necessary preparations before measurement. Prepare a geodetic conductivity meter; at least three personnel are required for electromagnetic detection: two for installing and transporting the instrument, and one for data collection. The inductive electromagnetic geodetic conductivity meter emits a sinusoidal alternating electromagnetic field (primary field) into the ground through a transmitting coil. The primary field generates a secondary magnetic field within the underground target. Both the secondary and primary fields are received by the receiving coil, and the conductivity can be calculated using the following formula. .

[0050] (1)

[0051] in, The magnetic field received by the receiving coil; The secondary magnetic field received by the receiving coil; It is a horizontal dipole mode; It is the vacuum permittivity; ω is the angular frequency; s is the distance between the transmitting and receiving coils.

[0052] Record the work date and weather information. Determine the data acquisition mode based on whether there are tall structures or trees obstructing the view, selecting either GPS positioning acquisition mode or fixed-point acquisition mode (significant obstructions above the measurement point will affect GPS positioning accuracy). Before starting work, select an appropriate data acquisition frequency. Operators are not allowed to carry signal transmitting devices such as mobile phones or smartwatches, and interference from such devices should be minimized during operation.

[0053] During the work, areas with abnormal data collection should be marked on-site for easy identification later. Record data in areas with clearly visible pipelines or conduits to facilitate subsequent data processing.

[0054] After data acquisition, import the field measurement data stored in the measurement host into the computer using a data cable. Check the number of abnormal points in the measurement data and the GPS recording information to make a preliminary assessment of the data quality and decide whether to re-acquire the data. Edit the imported data to convert it into a format that the inversion software can recognize. When converting the format, set parameters such as coordinates, device height above the ground, pitch angle, and roll angle.

[0055] First, the data is preprocessed, including removing negative values ​​and determining the distance of each coil data point from the GPS recording point. Since electromagnetic measurement results are difficult to accurately describe leakage, this embodiment first uses multi-source prior information for constrained inversion. The pipeline burial depth is determined through field surveys and historical data. (Unit: m), pipe diameter The resistivity of the pipe material (unit: ), stratigraphic interface thickness Soil resistivity distribution Based on historical data of pipeline defects, prior information on the location of anomalies was statistically obtained.

[0056] This embodiment uses an objective function for an industrial park pipeline scenario and introduces prior constraints:

[0057] (2)

[0058] in, For data fitting terms; For smoothing constraints; These are prior information constraint terms, which are related to multiple prior constraint functions; and These are the smoothness constraint weight parameters and the prior constraint weight parameters, respectively. When As the size increases, the model is forced to become smoother, and the boundaries of anomalous bodies become blurred, which helps suppress noise but results in a loss of detail (especially for small-scale anomalous bodies); when Reducing the size allows for more dramatic changes in the model, enabling the depiction of sharper boundaries and details, but also makes it more sensitive to noise. As the resistivity increases, the inversion results tend to align with prior information. For example, forcing the resistivity at the pipe location to approach the theoretical value of the pipe material, or forcing a jump in physical properties at a known formation interface; when When reducing, prior information serves only as a weak reference, and the inversion mainly relies on data and smoothing constraints.

[0059] First, constraints are imposed on the stratigraphic interfaces, assuming the stratigraphic interfaces are known. Apply interface continuity constraints :

[0060] (3)

[0061] in, yes A component, This is the interface constraint strength factor, which increases with increasing interface reliability; It is the depth of the k-th known geological interface. For example, it can be known from borehole data or regional geological maps that there is a stable interface between a clay layer and a sand layer at a depth of 2.5 meters. This indicates the spatial location of the model immediately below the k-th known geological interface; This indicates the spatial location of the model immediately adjacent to the k-th known geological interface; This represents the resistivity value at the center point of the interface grid.

[0062] Then, the pipe position is constrained by defining a constraint region around the pipe. Apply material-related resistivity constraints :

[0063] (4)

[0064] in, It is the value of the pipeline electrical constraint term. A component; is a spatial set representing the three-dimensional spatial region where the known pipe is located; i is the i-th grid cell located in the pipe region; It is the model resistivity, and it is the resistivity value of the i-th grid cell; and These are the resistivity and normalization factor of the pipe material, respectively. The value depends on the situation. If the resistivity of the material itself naturally fluctuates greatly, then it should be set to... The value is 30% to 50%. If the resistivity of the material itself is uniform, then take... For the same value, if the material is severely corroded or has been in service for more than 20 years, then take [the value]. 2 to 3 times, to weaken the constraints.

[0065] For fiberglass pipes, the composition is usually glass fiber, unsaturated polyester resin, epoxy resin, a small amount of quartz sand and calcium carbonate, and its resistivity is usually taken as... For reinforced concrete pipes, the structure is made of reinforced concrete, and the resistivity is typically taken as 200~500 Ω·m; for double-wall corrugated pipes, the structure is made of high-density polyethylene and polyvinyl chloride, and the resistivity is typically taken as greater than... These three are common materials for sewage pipes. If other types are available, the parameters can be replaced according to the actual situation.

[0066] Based on pipeline burial depth information, near the pipeline Imposing stricter constraints :

[0067] (5)

[0068] in, It is the value of the gradient constraint term in the region near the pipe. A component; It is the pipeline constraint coefficient, and its value is larger in the area near the pipeline. It is a spatial set, specifically referring to the adjacent area surrounding a known pipeline. It is usually defined as a strip of space centered on the pipeline axis, extending to both sides and downwards within a certain range (for example, 1-2 meters on each side of the pipeline in the horizontal direction, and 1-3 meters from the top of the pipeline to below the bottom of the pipeline in the vertical direction). Represents the gradient vector The modulus (length) quantifies the intensity of the overall spatial variation of the model parameters at point i. The larger the value, the more drastic the change in physical properties near that point. Squaring it aims to amplify the contribution of the gradient value.

[0069] Based on the reliability of the above prior information, the constraint strength is dynamically adjusted:

[0070] (6)

[0071] Where n is the nth iteration; These are the initial values ​​for the prior constraint weights; This represents the prior constraint weights obtained after n iterations. The confidence level of prior information is used to represent the reliability of a certain prior information itself. The higher the value, the more certain and reliable the information is. This is a data quality indicator; the higher the value, the more reliably the data can reflect the true underground structure.

[0072] Based on the content and quality of prior information, formula (6) is used to rely more on prior constraints in areas with poor data and more on data in areas with good data, thereby optimizing the quality and reliability of the solution in the space.

[0073] and The values ​​follow the rules in Table 1:

[0074] Table 1:

[0075]

[0076] After preprocessing, a suitable model and number of layers are selected. In this embodiment, based on the actual situation of the industrial park's sewage pipe network, a hierarchical initial model based on prior information is constructed:

[0077] (7)

[0078] in, It is a step function; Let K be the prior conductivity of the k-th layer; This is the initial model function, used to represent the initial state of the subsurface resistivity as a function of depth z, assumed based on prior information before the inversion begins. It serves as the starting point for subsequent iterative optimizations; Used to represent the spatial range of the k-th layer, since it is only located at depth z in the k-th layer ( ≤ The value is equal to 1 only when it is internal, thus setting the corresponding a priori resistivity. Activation is then performed to construct a piecewise constant initial model that conforms to the known geological stratification structure.

[0079] Data is inverted using software (including but not limited to Aarhus Workbench), and appropriate filters are selected for averaging. Absolute and relative uncertainties are added to increase the signal-to-noise ratio. The software provides an empty-constraint inversion that is a 1D inversion with 3D constraints, including constraints along resistivity lines, between lines, and between layers. It also provides an investigation depth for each inversion model, indicating the reliability of the data at each layer for easier interpretation.

[0080] Inversion begins, iteration commences, and it automatically stops when the error is less than 1%. The iteration intensity decreases with the number of iterations.

[0081] (8)

[0082] Where n is the number of iterations; It is the decay time constant; It is the process decay prior weight during the nth iteration; These are the initial weights of the prior constraints.

[0083] Formula (8) controls the inversion process, allowing the inversion to rely more on prior constraints for rapid guidance in the early stages and more on data for accurate convergence in the later stages.

[0084] Formulas (6) and (8) together provide precise constraints on the inversion process:

[0085] =

[0086] Based on the inversion results of electromagnetic measurements, each profile is analyzed to determine its electrical structure and anomalous zones. During the analysis, known information is used to eliminate false anomalies caused by interference factors such as topography and local inhomogeneities; the forward and inversion test results are compared to study the characteristics and nature of anomalies; and potential leakage anomalies in the detection sections are identified.

[0087] In electromagnetic inversion results, areas within approximately 3 meters above / below the pipe depth, where the underground solid medium is unevenly layered, exhibiting resistance fluctuations greater than 50 Ω·m or resistance less than 3 Ω·m, are considered to have significant leakage or defect characteristics. It is recommended to set up high-density resistivity and induced polarization (IP) measurement lines for these areas. Furthermore, if the industrial park provides data on soil pollution near underground pipelines, indicating severely polluted areas, it is also recommended to designate these areas for high-density resistivity and IPI detection.

[0088] Step 2: Detection is performed using the high-density resistivity method and the excited polarization method.

[0089] The layout of the survey lines and the type of electrodes used in the high-density resistivity method and the induced polarization method need to be discussed separately based on the specific ground planning conditions. For dirt roads, stainless steel electrodes are used, fixed in the soil, and the electrodes need to penetrate about 10 cm below the road surface. A double-line method is used, with 64 electrodes per measurement and an electrode spacing of 1 m. Considering that the direction of pipeline leakage is unknown, measurements need to be taken on both sides of the pipeline. For areas with long measurement sections, the roller method is considered. See [link to relevant documentation]. Figure 3 .

[0090] The rolling method involves repeatedly "rolling" measurements along a survey line exceeding the length of a fixed electrode array to achieve a single, high-density, and seamless acquisition of underground two-dimensional cross-sectional data for the entire survey line. Its core principle is to deploy a fixed number of electrodes (e.g., 64) as a single array along the survey line to complete the initial data acquisition. Subsequently, the entire electrode array is rolled forward approximately half the length along the survey line, overlapping the data from the old and new sections before proceeding to the next round of acquisition. This process is repeated, like a measuring tape, until the entire target profile is covered. This method deploys electrodes in a single setup, and a programmable controller enables automatic and rapid switching and data acquisition of electrode combinations. It can simultaneously acquire apparent resistivity and apparent polarizability data, significantly improving fieldwork efficiency and data density, and providing a foundation for subsequent detailed inversion and interpretation.

[0091] Data acquisition for each survey line was performed using the gradient method, with a power supply current of 200mA. During data acquisition, the grounding resistance of the electrodes was ensured to be less than 1kΩ, and there were no faulty electrodes or electrodes with excessively high resistance (>3kΩ). For areas near manhole covers where the ground surface is covered by sidewalks or cement roads, the electrical resistivity instrument could not perform measurements along a straight line as originally designed. In this embodiment, the electrodes were wrapped with bentonite instead of being fixed in the soil to enhance conductivity and overcome the high surface resistance. If the effect was not satisfactory, additional measurements could be performed by laying survey lines of appropriate density perpendicular to the pipeline in the middle of each survey line. Vegetation was also cleared locally, enabling efficient and low-loss electrical resistivity measurements of the pipeline.

[0092] Both the high-density resistivity method (ERT) and the induced polarization method (IP) use similar instruments (such as the ABEM system) for observation. Their basic principles are as follows: ERT injects current into the ground, and the current field distribution changes according to the difference in resistivity of different media. By inverting the measured data, a resistivity distribution image is obtained, thereby distinguishing the underground media. The IP method measures the polarization effect generated by the medium during the injection of current into the ground. The polarizability parameter characterizes the difference in discharge rate and time of different media after charging. This characteristic reflects the induced polarization property of the medium, and is thus used to identify and distinguish different underground media.

[0093] Since both electrical exploration methods are based on the principle of injecting current into the ground, their implementation relies on electrodes directly coupled to the earth. To ensure effective power supply and measurement, the electrodes must maintain good conductive contact with the surrounding medium (soil). When the surface soil is dry, it is often necessary to water it to reduce contact resistance. If the electrode cannot be directly inserted into a hardened surface such as a concrete road, it is wrapped with hydrated bentonite. Utilizing its good plasticity, adhesion, and conductivity, a stable conductive channel is established between the electrode and the hardened surface, overcoming the difficulties in electrode placement.

[0094] High-density electrical resistivity and induced polarization (EPP) survey lines will be laid out using impedance meters (including but not limited to the Abem-Terrimeter impedance instrument manufactured by IRIS) and a sufficient number and length of cables. Several sections of the road recommended for electromagnetic method testing will be surveyed, and the total planned detection area length will be determined. L The number of rollers detected by electrical methods, namely high-density resistivity method and excited polarization method b The relationship satisfies: , b ∈N, where a is the electrode spacing. E This represents the number of electrodes in a single measurement profile.

[0095] Because the measurement profiles obtained by high-density electrical resistivity tomography (EDT) and excited polarization methods exhibit an inverted trapezoidal shape that is wider at the top and narrower at the bottom, to ensure that the maximum effective detection depth can cover the entire detection area, the total length of the actual detection area needs to be greater than the total length of the planned detection area. The total length of the actual detection area is the initial measurement length. The additional length after rolling b times The superposition of.

[0096] The principle of resistivity calculation follows Archie's Law (Archie, 1942), and the formula is as follows:

[0097] (9)

[0098] (10)

[0099] in, Resistivity; The resistivity of the water body; Saturation; Porosity; The particle size distribution; The bonding coefficient; The saturation index; is the surface resistivity.

[0100] Polarizability is calculated using the Cole-Cole model:

[0101] (11)

[0102] in, Polarizability; The resistivity of the water body; It represents the DC resistivity.

[0103] The resolution of data obtained by high-density resistivity method and excited polarization method decreases with increasing depth. Therefore, a model is adopted in which the thickness of each layer increases with increasing depth.

[0104] In this embodiment, the existing prior information of the park is used to refine the grid, and directional smoothing constraints and minimum gradient support are introduced into the model for inversion. The software selection includes, but is not limited to, Res2Dinvx.

[0105] First, convert the imported data into a format that the inversion software can recognize, and check for outlier data points. Perform preliminary processing, including deleting negative values ​​and removing outlier data. When converting the format, parameters such as the measurement method, number of electrodes, and electrode distance must be set.

[0106] Based on the electromagnetic method detection results and the actual geological stratification information of the pilot park, the mesh density was increased near the pipeline interface:

[0107] (12)

[0108] in, Let be the depth of the k-th geological interface; To calculate the thickness of the refined mesh layer at the current depth z; The thickness of the background mesh layer; This represents the vertical distance from the current calculated location z to the k-th geological interface. This represents the encryption range coefficient.

[0109] Establish an adaptive encryption zone around the pipeline:

[0110] (13)

[0111] (14)

[0112] in, The radius of influence of the pipeline is usually taken as 2-3 times the pipeline diameter; The adaptive horizontal grid width for the area near the pipe, its value ≤ ; The width of the background horizontal grid; The adaptive vertical grid layer thickness for the pipeline burial depth area, its value ≤ ; It is the thickness of the background vertical mesh layer; z is the straight-line distance between the current grid calculation point and the pipeline axis projected onto the horizontal plane; z is the current depth. Represents the current depth z to the pipeline burial depth The absolute value of the vertical distance.

[0113] During the inversion iteration process, the mesh is dynamically adjusted according to the resistivity gradient, and the mesh is automatically refined in areas with large gradients.

[0114] (15)

[0115] in, This is the updated horizontal grid width; This is the current, unoptimized, horizontal grid width; It is the mesh adaptive strength coefficient; It is the magnitude of the resistivity gradient vector; This is used to represent the grid scaling factor, which determines whether the grid is encrypted or immutable.

[0116] Under the constraints of the formula, the final inversion grid will follow the following principles: the thickness of the first layer is less than the effective detection depth of the minimum quadrupole array or the minimum apparent depth of the data point; the thickness of each layer increases by 10% with the increase of depth, and the deepest layer should contain the effective measurement depth of the survey line; if the measured ground resistance is less than 1 kΩ, the grid width is not greater than the electrode spacing; if the measured ground resistance is greater than 1 kΩ, the grid width is not greater than 0.5 times the electrode spacing.

[0117] After generating the mesh, set appropriate inversion parameters and begin the inversion. To address the banded anomalies caused by pipe leakage discovered during the inversion process, a directional smoothing constraint was introduced.

[0118] (16)

[0119] in, and The smoothness in the horizontal and vertical directions can be controlled separately and can be adaptively adjusted according to abnormal shapes; This represents the value of the anisotropic smoothing constraint term; This represents the rate of change of the model along the pipeline direction; This represents the rate of change of the model in the depth direction.

[0120] Introducing Minimum Gradient Support (MGS) to enhance anomaly boundaries:

[0121] (17)

[0122] in, For the value of the focus constraint term; The degree to which model m changes drastically at the i-th grid cell is a local value; The focusing parameter is a very small positive number (0.01), which decreases with iteration.

[0123] and These are all constraints on the electrical inversion process; It applies a directional fuzz to the inversion results. If the leakage may extend a long distance in the horizontal direction, but the vertical direction changes abruptly, such as a strip-shaped leakage at the pipeline, this constraint will forcefully smooth the leakage in the horizontal direction, making it smooth. This helps to connect anomalies at the same depth on adjacent survey lines, forming a continuous "leakage zone", and allows for drastic changes in the vertical direction. This helps to clearly show the "leakage zone" at the pipeline burial depth, rather than blurring it into a color block. Based on the macroscopic form, it sharpens the edges of real anomalies to make their outlines clear; at the same time, it removes noise fluctuations in uniform areas to make the background cleaner, which is to constrain the inversion at the microscopic level.

[0124] During the iteration process, an uncertainty calculation is performed on each inversion result, calculating the inversion uncertainty of each grid cell, and automatically refining the grid for cells with high uncertainty.

[0125] (18)

[0126] in, is the uncertainty of the grid in the i-th row and j-th column; J is the sensitivity matrix, which represents the relationship between changes in the underground model and changes in surface observation data. The larger J is, the more sensitive and accurate the data is. It is a data weight matrix that gives higher weight to high-quality, low-noise data; It is a regularization parameter that controls the strength of the constraint; It is the model constraint matrix, used to constrain the inversion by using multi-source prior information.

[0127] After the iteration is completed, the inversion results are saved. The measurement data of the high-density resistivity method and the excited polarization method are mainly apparent resistivity and apparent polarizability, generating resistivity profile and polarizability profile for each measurement segment.

[0128] Analysis of resistivity and polarizability profiles identifies areas of leakage where significant low resistivity (generally consistently below 5 Ω·m) and low polarizability (below 3.94 mV / V) are observed in the soil covering and beneath the pipeline. These leakage areas are mostly located within and below the pipeline's burial depth (2-4 m), directly reflecting increased soil conductivity (decreased resistivity). This effectively delineates potentially high-risk sections for pipeline leakage or soil contamination, providing crucial guidance for subsequent precise detection.

[0129] Step 3: Select the key sections marked by the electromagnetic method, the suspected leakage detection areas located by the high-density electrical resistivity tomography and induced polarization methods as groundwater monitoring wells and soil sampling points.

[0130] Based on existing wells at the site, water samples were collected using Belle tubes, with two samples collected from each monitoring well. Water sample testing was conducted using a multi-parameter analyzer and laboratory experiments. Analysis of the test data determined the leakage section, and other methods were used to pinpoint the final key areas. During sampling, the color, turbidity, and other physical properties of the water were observed, and relevant water quality parameters in the flowing water were measured on-site using portable instruments. Sampling was only permitted after the readings remained continuous and stable. Sampling record forms and sampling labels were promptly completed on-site. Soil samples were taken from some leakage areas using a Dutch drill, and the soil composition was analyzed.

[0131] By comparing parameters such as chemical composition and electrical conductivity of monitoring wells and soil sampling points, and combining them with the resistivity shown in the electrical resistivity test results, the authenticity of leakage in the tested area can be further determined.

[0132] Based on the detection results from electromagnetic methods, high-density resistivity methods, and excited polarization methods, the leakage area that ultimately requires precise location is narrowed down and determined. A pipeline CCTV robot is then used for visual inspection to identify the type of defect causing the leakage. Pipeline CCTV robot inspection flexibly employs pre-treatment and operational modes such as airbag sealing, pumping, sludge removal, and high-pressure towing, depending on the water level and siltation conditions within the pipeline. Based on field inspection experience, we have specified the CCTV robot inspection method as follows: a. For conventional pipelines, when the water level in the pipeline is <40% of the pipe cross-section S... 管 Mud level < 20%S 管 a. Can be measured directly; b. When the water level in the water accumulation pipe is >40%S 管 a. When the mud level is <20%, the water level needs to be lowered (including but not limited to methods such as sealing the airbag and pumping water) before measurement; c. For mud-filled pipes, when the water level is <30% and the mud level is >40%, the mud level needs to be lowered (including but not limited to methods such as pumping mud); d. For viscous mud pipes, when the water level is <10% and the mud level is between 20% and 50%, and the mud is viscous, this situation may be caused by concentrated sewage discharge from the chemical industry or malicious local sewage discharge from enterprises. The viscous mud greatly hinders the movement of the robot, and the measurement can be completed by using a high-pressure vehicle to drag it and local dredging.

[0133] Based on the results of CCTV pipeline robot measurements, the location, amount, and type of pipeline leakage can be obtained. By following the above process, leakage defect detection of the entire park can be completed with the highest efficiency and low cost. Subsequently, pipeline repair plans or suggestions can be written based on the above information.

[0134] Information on pipe leaks detected by CCTV (leakage, misalignment, disconnection, foreign object penetration, etc.) is used to establish a correlation between electrical anomalies and structural defects in the pipeline. The various types of defects detected by CCTV are quantified into a Pipeline Defect Comprehensive Index (PDCI), where a higher value indicates a more severe defect. The formula is as follows:

[0135] (19)

[0136] in, The score for identifying the i-th type of defect at position x is derived from the assignment table in the technical specification, which is based on the "Technical Specification for Inspection and Evaluation of Urban Drainage Pipelines" (CJJ 181-2012). For example, the classification and score of defects such as "leakage" are as follows: Level 4 (spraying leak) is assigned 10 points, Level 3 (gushing leak) is assigned 5 points, Level 2 (line leak) is assigned 2 points, and Level 1 (dripping leak) is assigned 0.5 points. Other types of defects, such as "misalignment" and "disconnection", are similar to "leakage" and are calculated according to the defect level. It is the contribution weight coefficient of various defects, reflecting the difference in the ability of different types of defects to change the electrical properties of the soil due to sewage leakage. Based on historical cases, the leakage score is defined as 0.5, misalignment as 0.2, disconnection as 0.2, foreign object penetration and other types of defects as 0.1. The spatial impact factor simulates the spatial range of the impact of different types of defects on the soil outside the pipeline. For example, if the direct leakage has a large impact range, it can be taken as 1.2~1.5, and if the impact is more concentrated, it can be taken as 1.0.

[0137] Calculate the electrical anomaly intensity SGA(x) to reflect the intensity of leakage electrical anomaly:

[0138] (20)

[0139] in, and Let x be the resistivity and polarizability values ​​at a distance x and a depth z along a certain survey line; and The resistivity and polarizability values ​​are for the non-permeable region in the background strata. and These are the relative weights of resistivity and polarizability in indicating leakage, respectively, and their sum is 1. Typically... > ; Indicates the burial depth of the pipeline a certain range nearby Within the range, select the highest abnormal value and ensure that the signal is associated with the pipeline; This is a depth focusing function used to enhance signals near the burial depth of the pipeline and suppress other interferences such as noise.

[0140] Evaluate the spatial consistency between geophysical methods and CCTV detection:

[0141] (twenty one)

[0142] Evaluate the consistency of the numerical trend changes between the two, and calculate the overall defect strength:

[0143] (twenty two)

[0144] Wherein, NCC is the normalized correlation coefficient, used to evaluate the spatial alignment between the leakage location measured by geophysical methods (electromagnetic and electrical methods) and the leakage location measured by CCTV, with a maximum value of 1; MS is the matching index, with a value between 0 and 1, and a higher value indicates a higher correlation between the two; r is the Pearson correlation coefficient, used to evaluate the consistency of the numerical trends between the two. These are used to reconcile the weights for spatial alignment and trend consistency, respectively.

[0145] The MS value meets the criteria in Table 2.

[0146] Table 2:

[0147] Matching Index MS Spatial Consistency Index (NCC) Correlation of numerical trend changes r Verification conclusions and engineering significance Confidence 0.7~1 Height ≥ 0.8 Strength ≥ 0.7 The leakage is abnormally obvious, confirming that it is an area requiring repair. high 0.5~0.7 Medium 0.5~0.8 Medium 0.5~0.7 Pipeline defects are the primary cause of ground anomalies; repairs are recommended after verification through a few borehole drills. middle 0~0.5 Low <0.5 Weak <0.5 Abnormal leakage may be caused by other factors, and interference needs to be eliminated. Low

[0148] If it is necessary to determine the leakage rate, the water tightness test method for unpressurized pipelines can be used to check the pipeline integrity and calculate the leakage rate. The water tightness test is a method for measuring leakage. It involves sealing two adjacent manholes with an airbag, cleaning the pipeline section, filling it with water and soaking it for 24 hours, observing it for 30 minutes at a specified test head, calculating the amount of water leaked, and inspecting the pipeline and the outer wall of the manhole for leakage, thereby evaluating the water tightness of the pipeline section.

[0149] A leakage detection report can be written based on the detection results of this method.

[0150] This embodiment constructs a multi-level, progressive technical system encompassing "rapid screening using electromagnetic methods—detailed investigation of key sections using electrical methods—sampling and testing—precise internal positioning via CCTV—water tightness test," effectively overcoming the limitations of traditional single-method detection. For example, using only CCTV pipeline robots is costly, inefficient, and prone to blind spots; relying solely on ground geophysical exploration results is highly ambiguous and unverifiable. Through multi-method collaborative and progressive exploration, it is possible to rapidly identify and delineate leakage risk areas in pipeline networks across large chemical industrial parks, significantly improving investigation efficiency and reducing investigation costs.

[0151] This embodiment employs a priori information-constrained inversion for the electromagnetic method, which improves the accuracy of identifying anomalies around the pipeline by 30%, enhancing the overall anomaly identification rate. For data processing using the high-density resistivity method and the excited polarization method, electromagnetic measurement results are combined with park information to refine the mesh around the pipeline burial depth and suspected leaks. Directional smoothing constraints and minimum gradient support are introduced for inversion, improving the accuracy of leak detection and reducing ambiguity.

[0152] This embodiment establishes a corresponding verification relationship between "ground low resistivity / low polarizability anomalies—pipeline structural defects (leakage, misalignment, disconnection)" by spatiotemporal matching and comprehensive interpretation of ground geophysical exploration anomalies (resistivity, polarizability) and CCTV-detected defects inside the pipeline. By uniformly quantifying and assessing the degree of leakage for defects detected by CCTV, this dual verification mechanism significantly reduces the ambiguity of geophysical interpretation, enabling precise spatial location of leak points and accurate diagnosis of defect types and levels, providing a reliable basis for subsequent repairs.

[0153] The detection scheme in this embodiment employs differentiated instrument deployment and data acquisition strategies tailored to the complex surface cover conditions above various sewage pipelines within the chemical industrial park. This ensures the effective implementation and data quality of electromagnetic and electrical methods under different road surface conditions. Simultaneously, the CCTV pipeline robot inspection system can flexibly employ various pre-processing and operational modes, such as airbag sealing, pumping, dredging, and high-pressure towing, based on the water level and siltation status within the pipeline. This ensures the successful acquisition of clear images of the pipeline interior even under complex conditions, enhancing the method's practicality and environmental adaptability.

[0154] The final output of this embodiment includes not only the type and location of leakage points, but also allows for the subsequent classification of pipeline defects based on the output of this embodiment, and the proposal of targeted repair technology suggestions matching the defect type (such as leakage, misalignment, foreign object penetration, etc.), providing systematic technical support for the implementation of precise, efficient and economical pipeline maintenance and groundwater pollution source control in chemical industrial parks.

[0155] The technical solution of this embodiment is illustrated below with a specific example:

[0156] The total area of ​​the chemical industrial park in this example is 11.73 km². 2 Through interviews with relevant personnel, data collection and analysis, and on-site reconnaissance at the chemical industrial park to be tested, the total length of the sewage pipeline was determined to be 30 km. A total of 120 testing sections, each 250 m long, were established, covering the entire 30 km pipeline. The total detection length is approximately 75 km.

[0157] For sections without surface cover, a measuring line is laid out on each side and above the pipeline in each measurement section. GPS positioning and data acquisition are used, with a data acquisition interval of 1 m and a measuring line spacing of 5 m. For measurement sections with flower beds or vegetation cover, the spacing between the two parallel measuring lines is increased to 5 m. In the middle, measuring lines perpendicular to the pipeline are laid out at an appropriate density (2 m spacing) for supplementary measurements. The vegetation is cleared locally for efficient measurement.

[0158] A geoelectric conductivity meter was prepared, and three personnel were assigned: two to install and move the instrument, and one to collect data. The working date and weather information were recorded. The data acquisition mode was determined based on the presence of tall structures or trees obstructing the view, selecting either GPS positioning or fixed-point acquisition mode.

[0159] Before starting work, the data acquisition frequency was set to 2 Hz, and operators were prohibited from carrying mobile phones, smartwatches, or other signal-transmitting devices. During work, areas with abnormal data were marked on-site. Data was recorded in areas with clearly visible pipelines and conduits to facilitate later data processing.

[0160] After data acquisition, import the field measurement data stored in the measurement host into the computer using a data cable. Check the number of abnormal points in the measurement data and the GPS recording information to make a preliminary assessment of the data quality and decide whether to re-acquire the data. Edit the imported data format, setting parameters such as coordinates, device height above the ground, pitch angle, and roll angle during format conversion.

[0161] First, the data is preprocessed, including removing negative values ​​and the distance of each coil data from the GPS recording point. After the preprocessing is completed, the improved objective function mentioned above is introduced to constrain the stratum interface (0~1 m is loam, 1~1.5 m is clay, and below 3 m is clay), pipeline burial depth (-1.5~3 m), pipeline material (reinforced concrete pipeline, resistivity is 200~500 Ω·m), etc. Through the constraints of formula (6), we can rely more on prior constraints in areas with poor data and rely more on data in areas with good data. Based on the prior information, a hierarchical initial model is constructed. The data is inverted through Aarhus Workbench, and a suitable filter is selected to average the data. The inversion begins, and the iteration stops when the error is less than 1%. The results are then exported.

[0162] Based on the inversion results of electromagnetic measurements, each profile was analyzed, and the results of forward modeling and geophysical methods were compared to study the anomaly characteristics and properties, and the electrical structure and anomaly zones in the profiles were determined. Nine sections suspected of leakage were selected from the 75 km electromagnetic survey line for analysis. For ease of identification, they are designated as F4, F6, F8, B2, W8, F3, W10, W9, and W7, with an average length of 0.5–2 km per section.

[0163] Analysis revealed significant anomalies in the resistivity profiles along the sewage pipelines W8 and W10. Within the pipeline burial depth (approximately 1.5–3 m) and a range of approximately 3 m below it, the resistivity distribution of the underground medium was extremely uneven, exhibiting areas of drastic localized resistance fluctuations (exceeding 50 Ω·m). These areas manifested as low- or high-resistivity anomalies with significantly different electrical properties from the surrounding medium, and the stratification interfaces were indistinct. This unevenness and drastic fluctuation in electrical structure strongly suggests an alteration in the electrical properties of the soil at this location, most likely due to leakage defects in the pipelines, leading to continuous sewage seepage and changes in the moisture content, ion concentration, and pore structure of the surrounding soil, indicating a high risk of leakage. The W8 pipeline is 750 m long, with a total survey line length of approximately 2.25 km measured from west to east. The electromagnetic inversion results are as follows: Figure 4 As shown, a significant low-resistivity region can be clearly seen at 450 m and 650 m in the pipe and below the pipe. Figure 4 The dark blue area), and the high-resistivity area where it meets the ground above ( Figure 4 The measurements taken in the red and green alternating areas (north side roadside and south side flowerbed) correspond to those above the pipeline, showing low and high resistance phenomena in similar locations. In contrast, some electrical anomalies were also detected in sections W7 and W9, but the overall magnitude and range of the anomalies were weaker than those in the two sections mentioned above, requiring further investigation and confirmation. Along the combined sewer and stormwater pipelines of Phoenix Fourth Road and Phoenix Eighth Road, the resistivity profiles were relatively clear and continuous, with no drastic electrical fluctuations of similar scale found, suggesting a low risk of leakage. Electromagnetic profiles of lines B2, F3, F4, F6, and F8 showed that the internal structure of the pipelines was intact, with no obvious defects such as leakage, rupture, or misalignment in the pipe walls, indicating good pipeline functionality. These sections showed uniform electrical structure and no obvious leakage anomalies.

[0164] Electromagnetic detection successfully identified W8 and W10 as key suspected leakage sections, and some sections of W7 and W9 as secondary key concern sections. Therefore, W7, W8, W9, and W10 were designated as sections for detailed detection using high-density resistivity method and induced polarization method.

[0165] An Abem-Terrimeter impedance meter manufactured by IRIS was used to set up electrical resistivity measurement lines. For dirt roads, such as W7 road, stainless steel and non-polarizing electrodes were used, fixed in the soil, with the electrodes penetrating approximately 10 cm below the road surface. A double-line method was employed, using four roller-based measurements. Measurements were taken on both sides of the pipeline, with 64 electrodes used in each measurement, for a total of 192 electrodes. The electrode spacing was 1 m, and each measurement line was 191 m long, meeting the requirements. The total length of the survey line is Electrode No. 1 of the survey line is located on the west side of the survey line. Data acquisition for each survey line is performed using the gradient method, with a power supply current set to 200mA. During data acquisition, the electrode grounding resistance is always less than 1kΩ. For hardened pavements, such as W8, W9, and W10, the stainless steel electrodes are wrapped with bentonite to ensure they stand upright on the pavement, maintaining good contact at the bottom.

[0166] W8 employs a two-stage rolling method for detection, with 64 electrodes used in each measurement, for a total of 128 electrodes. The electrode spacing is 1m, and each measurement line is 127m long, measuring from east to west, meeting the requirements. The actual measured length is Electrode No. 1 of the survey line is located on the east side of the survey line. W9 employs the roller method with four measurements, each using 64 electrodes, for a total of 192 electrodes. The electrode spacing is 1m, and the length of a single survey line is 191m, meeting the requirements. The total length of the survey line is Electrode No. 1 of the survey line is located on the east side of the survey line. W10 employs a single rolling method for detection, with 64 electrodes used in each measurement, for a total of 96 electrodes. The electrode spacing is 1m, and the length of a single survey line is 95m, meeting the requirements. The total length of the survey line is Electrode No. 1 of the survey line is located on the east side of the survey line.

[0167] The field measurement data stored in the measurement host was imported into the computer using a data cable. The imported data was converted into a format recognizable by the inversion software. Abnormal data points were checked and removed. During the format conversion, parameters such as the measurement method, number of electrodes, and electrode distance were set. Res2Dinv electrical resistivity inversion software was used for data processing. Archie's law was used to calculate resistivity, and the Cole-Cole model was used to calculate polarizability.

[0168] Based on the electromagnetic method measurement results constraining the electrical method measurement data, the mesh is densified near the pipe interface (1.5~3 m). The mesh is dynamically adjusted according to the resistivity gradient, and the mesh is automatically densified in areas with large gradients.

[0169] Set appropriate inversion parameters and begin the inversion. Introduce directional constraints and minimum gradient support to address the banded anomalies in the electromagnetic method results, strengthen the anomaly boundaries, and perform inversion on the data. During the iteration process, calculate the uncertainty of each grid cell and automatically refine the grids with high uncertainties. Stop iterating when the error is less than 1%, save the inversion data, and import the data into the Res2Dinv electrical inversion software. The software automatically generates resistivity and polarizability profiles for each measurement segment.

[0170] Analyze the inversion results. This embodiment uses W8 as an example; its electrical resistivity measurement line runs from east to west, and the results are as follows: Figure 5As shown. The survey line is directly above the pipeline. This section of the pipeline is a newly installed pipeline within the park, with a bottom burial depth of approximately 2.7m or more. The resistivity profile results show no significant abrupt changes along the entire length of the survey line, and exhibit clear stratification. The resistivity is high (>33.7Ω·m) within a depth of 0~0.75m, presumably due to the hardened surface. The resistivity is relatively high below 0.75m within the pipeline area, and relatively low above and below the pipeline, which is basically consistent with the resistivity distribution in most areas of the unpaved road survey line. The polarizability profile results differ from those of the soil road along the entire length of the survey line. Some areas exhibit high polarizability (>13.1 mV / V). The polarizability variation is more pronounced around the 104m mark of the survey line, with values ​​ranging from 0.645 to 32.4 mV / V. For example, within the 104-112m range, the polarizability abruptly changes from high (>17.7 mV / V) to low (<1.18 mV / V) from the ground surface to the bottom of the pipeline. This corresponds to the large low-resistivity area observed at 650m along the W8 electromagnetic method detection line, both within and below the pipeline. Figure 5 The dark blue area verifies the rationality of the electromagnetic detection results.

[0171] Areas suspected of leakage, located using geophysical methods, were selected as groundwater monitoring wells, and soil sampling points were also chosen accordingly. Water samples were collected using Bayer tubes from each monitoring well, with two samples collected from each well. Soil samples were taken from selected areas using a Dutch drill for analysis of soil composition. In the water sample analysis, monitoring wells located in high-risk leakage areas indicated by both electromagnetic and high-density electrical resistivity methods (such as key sections W8 and W10) showed significant anomalies in characteristic pollutant concentrations. Concentrations of typical characteristic pollutants in the industrial park, such as fluoride, petroleum hydrocarbons, toluene, and 1,2-dichloroethane, were detected, significantly higher than background levels. Simultaneously, the conductivity and other indicators of these water samples also increased, reflecting the impact of high-ion-concentration wastewater infiltration on the groundwater. Soil sampling analysis showed that the same characteristic pollutants were detected in the soil layers corresponding to areas with low resistivity anomalies in the electrical resistivity method, and their vertical distribution showed a trend of migration downwards from the pipe depth. The soil moisture content and salinity were significantly higher in the anomalous area, which is highly consistent with the causes of the "low resistivity and low polarizability" physical properties revealed by the electrical method.

[0172] Based on the detection results from electromagnetic methods, high-density resistivity methods, and excited polarization methods, the leak areas requiring precise location were narrowed down and identified as W7, W8, W9, and W10. Furthermore, to verify the accuracy and reliability of the electromagnetic induction detection results, CCTV pipeline robot inspections were also conducted on sections F4 and F8, where the electromagnetic profiles showed uniform electrical structure and no obvious leakage anomalies. The pipeline CCTV robot was used for inspection and measurement from west to east. Pre-treatment and operation modes, such as airbag sealing, pumping, dredging, and high-pressure towing, were flexibly adopted according to the water level and siltation conditions within the pipeline. For example, in sections F4 and F8, where the data showed sticky mud, high-pressure towing was used. In sections W7-W10, where some areas had excessive water accumulation and localized siltation, possibly due to malicious sewage discharge by the enterprise, airbag sealing and pumping were used. All pipeline measurements were completed.

[0173] Based on the results of CCTV pipeline robot measurements, the location, amount, and type of pipeline leaks were determined. Taking the W8 survey line as an example, it is 750m long and includes 18 survey sections. This underground pipeline is a sewage pipeline, entirely constructed of reinforced concrete with a diameter of DN1200. The pipeline contains 40% silt and no water flow, allowing for direct robot measurement.

[0174] CCTV's pipeline robot measurement results showed that all 17 sections of the pipeline had defects of varying sizes, totaling 39. The measurement results using the W8-channel electromagnetic method were taken at a point 650m in... Figure 4 ) and the low resistivity and low polarizability at 104~112m (this method is reverse measurement, actually corresponding to 638~646m) measured by high-density electrical resistivity and excited polarization methods (the latter two methods are reverse measurements, actually corresponding to 638~646m). Figure 5 For example, after inspection by CCTV pipeline robot, 9 Class 1 defects (leaking) were found in the 638-646m reinforced concrete pipeline inspection section, verifying the correctness of electromagnetic and electrical detection methods.

[0175] At one point of leakage, the calculated PDCI peak value was observed at 15m, corresponding to three CCTV leakage defects. Simultaneously, the SGA also showed a significant peak value, with a calculated NCC value of 0.85. =0.80, and the overall defect strength MS=0.83, which corresponds to a high-confidence conclusion that the ground anomaly was directly caused by the pipeline leakage defect at this location, significantly reducing the ambiguity of geophysical methods.

[0176] Since this case does not require leakage volume measurement, but only the location and size of the leakage to provide a basis for developing a repair plan, a water tightness test is not necessary, and the case is now concluded.

[0177] This invention provides a comprehensive method for detecting leaks in underground sewage pipe networks in industrial parks. Through a multi-layered, progressive technical process—"preliminary screening using electromagnetic methods—detailed investigation using electrical methods—soil and water sample verification—precise location using CCTV endoscopy—water tightness test"—it overcomes the problems of ambiguity and inaccurate location associated with traditional single-method detection. This method utilizes a dual verification mechanism of ground geophysical anomalies and internal pipe defects, combined with pollution characteristic analysis of groundwater and soil samples, to achieve precise diagnosis of the location, type, and impact range of leaks, providing direct and quantifiable decision-making basis for subsequent remediation. The specific parameters and thresholds involved in this method are empirical reference values. Practitioners should adjust them accordingly based on specific geological conditions, pipe materials, and pollution characteristics to adapt to the leakage detection needs of different industrial park environments.

[0178] Example 2

[0179] The purpose of this embodiment is to provide a comprehensive detection system for leakage in underground sewage pipe networks in industrial parks, including:

[0180] The electromagnetic detection module is configured to: conduct overall ground electromagnetic detection of the area to be tested in the industrial park, investigate and survey the area to be tested, obtain prior information about the area, use prior constraints to invert the collected data to obtain a resistivity profile, and determine the detection section suspected of leakage based on the resistivity profile.

[0181] The electrical detection module is configured to: further detect suspected leakage anomalies using high-density resistivity method and induced polarization method; refine the mesh based on electromagnetic method results and prior information; introduce directional smoothing constraints and minimum gradient support to invert constraints on the data of high-density resistivity method and induced polarization method; and locate the leakage area by combining resistivity profile and polarization profile.

[0182] The authenticity detection module is configured to: sample the located leakage area to determine the authenticity of the leakage in the measured area;

[0183] The pipeline robot inspection module is configured to use a pipeline robot to visually measure and accurately locate the actual leakage area.

[0184] In further embodiments, the following is also provided:

[0185] An electronic device includes a memory and a processor, as well as computer instructions stored in the memory and running on the processor. When executed by the processor, the computer instructions perform the method described in Embodiment 1. For brevity, further details are omitted here.

[0186] It should be understood that in this embodiment, the processor can be a central processing unit (CPU), or it can be other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. The general-purpose processor can be a microprocessor or any conventional processor, etc.

[0187] Memory may include read-only memory and random access memory, and provides instructions and data to the processor. A portion of memory may also include non-volatile random access memory. For example, memory may also store information about the device type.

[0188] A computer-readable storage medium for storing computer instructions, which, when executed by a processor, perform the method described in Embodiment 1.

[0189] The method in Embodiment 1 can be directly implemented by a hardware processor, or implemented by a combination of hardware and software modules within the processor. The software modules can reside in readily available storage media in the art, such as random access memory, flash memory, read-only memory, programmable read-only memory, electrically erasable programmable memory, or registers. This storage medium is located in memory; the processor reads information from the memory and, in conjunction with its hardware, completes the steps of the above method. To avoid repetition, a detailed description is not provided here.

[0190] A computer program product includes a computer program that, when executed by a processor, implements the method described in Embodiment 1.

[0191] The present invention also provides at least one computer program product tangibly stored on a non-transitory computer-readable storage medium. The computer program product includes computer-executable instructions, such as instructions included in program modules, which execute in a device on a target real or virtual processor to perform the processes / methods described above. Typically, program modules include routines, programs, libraries, objects, classes, components, data structures, etc., that perform specific tasks or implement specific abstract data types. In various embodiments, the functionality of program modules can be combined or divided among program modules as needed. The machine-executable instructions for the program modules can execute within a local or distributed device. In a distributed device, the program modules can reside in both local and remote storage media.

[0192] The computer program code used to implement the methods of the present invention may be written in one or more programming languages. This computer program code may be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable data processing device, such that when executed by the computer or other programmable data processing device, the program code causes the functions / operations specified in the flowcharts and / or block diagrams to be implemented. The program code may be executed entirely on a computer, partially on a computer, as a stand-alone software package, partially on a computer and partially on a remote computer, or entirely on a remote computer or server.

[0193] In the context of this invention, computer program code or related data may be carried by any suitable carrier to enable a device, apparatus, or processor to perform the various processes and operations described above. Examples of carriers include signals, computer-readable media, and the like. Examples of signals may include electrical, optical, radio, sound, or other forms of propagation signals, such as carrier waves, infrared signals, etc.

[0194] Those skilled in the art will recognize that the units and algorithm steps described in conjunction with the embodiments herein can be implemented in electronic hardware or a combination of computer software and electronic hardware. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this application.

[0195] While the specific embodiments of the present invention have been described above in conjunction with the accompanying drawings, this is not intended to limit the scope of protection of the present invention. Those skilled in the art should understand that various modifications or variations that can be made by those skilled in the art without creative effort based on the technical solutions of the present invention are still within the scope of protection of the present invention.

Claims

1. A comprehensive detection method for leakage in underground sewage pipe networks in industrial parks, characterized in that, include: A ground-based electromagnetic method was used to conduct overall detection of the area to be tested in the industrial park. The area was surveyed and investigated to obtain prior information. Prior constraints were then used to invert the collected data to obtain a resistivity profile. Based on the resistivity profile, suspected leakage anomalies were identified in the detection sections. In the electromagnetic method data processing, prior constraint terms were introduced into the objective function of the pipeline scenario in the industrial park. Specifically: ； = ； in, For data fitting terms; For smoothing constraints; These are prior information constraint terms, which are related to multiple prior constraint functions; and These are the smoothness constraint weight parameters and the prior constraint weight parameters, respectively. These are the constraint weights in the nth iteration. is the initial weight of the prior constraints; n is the number of iterations; It is the decay time constant; The confidence level of prior information; For data quality indicators; For suspected leakage anomalies, the high-density resistivity method and the induced polarization method are used for further detection. Based on the electromagnetic method results and prior information, the mesh is refined. Directional smoothing constraints and minimum gradient support are introduced to inversely constrain the data of the high-density resistivity method and the induced polarization method. The leakage area is located by combining the resistivity profile and the polarization profile. In the data inversion process of electrical resistivity measurement, the directional smoothing constraint is: ； in, and Control the smoothness in the horizontal and vertical directions separately; This represents the rate of change of the model along the pipeline direction; This represents the rate of change of the model in the depth direction; The minimum gradient support is: in, The degree of drastic change in model m at the i-th grid cell; For focusing parameters; Before the data inversion from electrical resistivity measurements, the grid is first refined based on the electromagnetic method results and prior information. Specifically, the grid near the pipeline interface is refined according to the vertical distance from the current calculation location to the k-th geological interface and the background grid layer thickness. The adaptive horizontal grid width of the area near the pipeline is determined based on the pipeline's influence radius and the background horizontal grid width. The adaptive vertical grid layer thickness of the pipeline burial depth area is determined based on the background vertical grid layer thickness, the pipeline's influence radius, and the previously calculated location. During the inversion process, the grid is dynamically adjusted according to the resistivity gradient, and the grid is refined in areas with large gradients. The system takes samples from the identified leakage areas to determine the authenticity of the leakage. For the actual leakage areas, a pipeline robot is used to inspect and measure them to accurately locate the leakage areas.

2. The comprehensive detection method for leakage in underground sewage pipe networks in industrial parks as described in claim 1, characterized in that, The overall inspection of the area to be inspected in the industrial park was carried out using the terrestrial electromagnetic method, the high-density resistivity method, and the induced polarization method, respectively. Specifically: In electromagnetic surveying, for areas with no ground cover, a survey line is arranged on the left, right and above the pipeline for each survey section; for areas with flower beds or vegetation covering the ground, the distance between the two parallel survey lines is increased, and an equidistant survey line perpendicular to the pipeline is laid in the middle for supplementary surveying, and vegetation can be cleared locally. In the high-density resistivity method and the induced polarization method for measurement, for dirt roads, the electrodes are fixed in the soil. If the measurement line is long, the roller method is used for detection, and a measurement is performed on both sides of the pipeline. For the ground surface covered by hardened pavement such as sidewalks, bentonite is used to wrap the electrodes for measurement.

3. The comprehensive detection method for leakage in underground sewage pipe networks in industrial parks as described in claim 1, characterized in that, Also includes: The various types of defects detected by the pipeline robot are quantified into a comprehensive pipeline defect index based on the defect level score. The intensity of electrical anomalies reflecting leakage is calculated based on the resistivity and polarizability values ​​corresponding to the depth of the measuring line. The consistency between geophysical methods and pipeline robot detection in spatial location is assessed based on the comprehensive pipeline defect index and the intensity of electrical anomalies. By calculating the overall defect intensity and then assessing the consistency of numerical trend changes between geophysical methods and pipeline robots, precise spatial location of leak points and accurate diagnosis of defect types and levels were achieved.

4. A comprehensive detection system for leakage in underground sewage pipe networks in industrial parks, employing the comprehensive detection method for leakage in underground sewage pipe networks in industrial parks as described in any one of claims 1-3, characterized in that, include: The electromagnetic detection module is configured to: conduct overall ground electromagnetic detection of the area to be tested in the industrial park, investigate and survey the area to be tested, obtain prior information about the area, use prior constraints to invert the collected data to obtain a resistivity profile, and determine the detection section suspected of leakage based on the resistivity profile. The electrical detection module is configured to: detect suspected leakage anomalies using high-density resistivity method and induced polarization method; refine the grid based on electromagnetic detection results and prior information; introduce directional smoothing constraints and minimum gradient support to invert constraints on the data of high-density resistivity method and induced polarization method; and locate the leakage area by combining resistivity profile and polarization profile. The authenticity detection module is configured to: sample the located leakage area to determine the authenticity of the leakage in the measured area; The pipeline robot inspection module is configured to use a pipeline robot to visually measure and accurately locate the actual leakage area.

5. An electronic device, characterized in that, It includes a memory and a processor, as well as computer instructions stored in the memory and running on the processor, which, when executed by the processor, perform the method according to any one of claims 1-3.

6. A computer-readable storage medium, characterized in that, Used to store computer instructions, which, when executed by a processor, perform the method described in any one of claims 1-3.

7. A computer program product, characterized in that, Includes a computer program, which, when executed by a processor, implements the method described in any one of claims 1-3.

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