Pipe network defect detection system and method based on rain sewage pipe network transformation

Abstract

The invention belongs to the technical field of pipe network transformation defect detection, and particularly relates to a pipe network defect detection system and method based on rain sewage pipe network transformation. According to the method, joint evaluation of construction disturbance and pipe network structure response is achieved, the accuracy of reconstruction design is improved, quantitative evaluation of the construction influence range and the influence degree is achieved, high-risk sections are recognized in advance, more complete defect information is obtained based on multi-modal detection, and the accuracy of defect recognition is improved; by adopting pipeline CCTV detection video data and acoustic data conjoint analysis, pipeline geometric defects, pipeline internal leakage and abnormal acoustic characteristics can be identified at the same time, the problem of incomplete information of a single detection means is solved, the reliability of defect evaluation is improved, the construction disturbance type is associated with the defect type, the pertinence of risk evaluation is improved, and the risk evaluation efficiency is improved. Therefore, the risk performance of different defects in different construction stages can be accurately predicted, and the method has higher engineering applicability.

Description

Technical Field

[0001] This invention belongs to the field of pipeline network renovation defect detection technology, specifically relating to a pipeline network defect detection system and method based on stormwater and sewage pipeline network renovation. Background Technology

[0002] With the acceleration of urbanization, stormwater and sewage pipe networks, as a crucial component of urban infrastructure, directly impact urban drainage capacity and environmental quality through their safety and operational reliability. However, long-term operating stormwater and sewage pipe networks commonly suffer from defects such as aging, settlement, damage, and leakage. During urban pipe network renovation projects, construction disturbances (such as excavation, backfilling, equipment vibration, and temporary loading) may further exacerbate changes in the pipe network structure and hydraulic state, potentially leading to pipe network damage or accidents. Therefore, accurate detection and risk assessment of pipe network defects are of paramount importance before renovation construction.

[0003] Traditional methods often ignore the disturbance effect of the construction process on the pipeline network structure and hydraulic state, making it difficult to accurately assess the sensitivity and risk of the pipeline segment during the renovation. They rely on a single detection method, such as video or acoustic detection, which cannot simultaneously obtain information on the geometric shape and leakage status of defects, resulting in incomplete description of defect characteristics. They usually cannot combine the pipeline network structural response, hydraulic response and construction disturbance conditions to quantify the risk of defects, and lack construction priority ranking and scientific intervention strategies. Summary of the Invention

[0004] The purpose of this invention is to provide a pipeline defect detection system and method based on stormwater and sewage pipeline renovation, which can improve the safety, efficiency and scientific nature of construction decision-making in stormwater and sewage pipeline renovation projects by combining construction disturbance parameters, pipeline structure and hydraulic characteristics, and defect feature information.

[0005] The specific technical solution adopted by this invention is as follows: A method for detecting pipeline defects based on stormwater and sewage pipeline renovation includes: Obtain construction planning data for the stormwater and sewage pipe network renovation project, and obtain construction disturbance parameters based on the construction planning data; Obtain the basic structural data and hydraulic data of the pipeline network to be modified, and obtain the structural response value and hydraulic response value of the pipe segment corresponding to the basic structural data and hydraulic data under the construction disturbance effect based on the construction disturbance parameters. Pipe sections whose structural or hydraulic response values ​​exceed a preset threshold are identified as sensitive sections for modification, and corresponding sensitivity values ​​are generated based on the response values ​​of the sensitive sections. Defect detection is performed on the sensitive sections to be modified, and the corresponding defect feature information is obtained based on the defect detection. Obtain the defect type and construction disturbance type, and obtain the fusion weight based on the defect type and construction disturbance type; The defect feature information is combined with the sensitivity value of the corresponding modification sensitive section and the fusion weight to generate a defect risk index. Based on the defect risk index, multiple defects are sorted and classified to identify those that need to be addressed first on the critical path of construction, and corresponding modification priority results and construction intervention suggestions are output.

[0006] In a preferred embodiment, construction planning data for the stormwater and sewage pipe network renovation project is obtained, and construction disturbance parameters are obtained based on the construction planning data, including: Obtain construction planning data for the stormwater and sewage pipe network renovation project. This data includes construction procedures, equipment operation methods, and engineering geological conditions. The vibration impact of the construction equipment's vibration waves on the surrounding soil and pipeline network during the excavation process is obtained based on the operating mode of the construction equipment and the engineering geological conditions. The changes in water flow status within the pipe during construction are obtained based on the construction procedures. Obtain construction load information, including excavation unloading, backfill loading or temporary surcharge, and combine it with engineering geological conditions to obtain the bearing capacity changes of the pipe body and surrounding soil during construction. The vibration impact, water flow state changes, and load changes are summarized as construction disturbance parameters.

[0007] In a preferred embodiment, the basic structural data and hydraulic data of the pipeline network to be modified are obtained. Based on the construction disturbance parameters, the structural response values ​​and hydraulic response values ​​of the pipe segments corresponding to the basic structural data and hydraulic data under the construction disturbance are obtained, including: Obtain the basic structural data and hydraulic data of the pipeline network to be modified; The material strength and burial depth of each pipe segment are obtained based on the basic structural data, and the corresponding structural weight is obtained based on the material strength. The structural weight includes vibration influence weight, load change weight and burial weight. The structural response values ​​of the corresponding pipe section under construction disturbance are obtained based on the burial depth, vibration impact, load change and structural weight. Based on hydraulic data, obtain multiple historical flow rates, multiple historical water levels, current flow rate, and current water level for each pipe section; Hydraulic weights are obtained based on changes in water flow conditions, including water level weights and flow rate weights. The hydraulic response value is obtained based on multiple historical flow rates, multiple historical water levels, current flow rate, current water level, and hydraulic weight.

[0008] In a preferred embodiment, pipe sections whose structural or hydraulic response values ​​exceed a preset threshold are identified as sensitive sections for modification, and corresponding sensitivity values ​​are generated based on the response values ​​of these sensitive sections, including: Obtain preset thresholds, including preset structural response thresholds and preset hydraulic response thresholds; Determine whether the structural response value or hydraulic response value exceeds the corresponding preset structural response threshold or preset hydraulic response threshold. If the structural response value exceeds the preset structural response threshold, the corresponding pipe section is determined to be a sensitive section for modification. If the structural response value does not exceed the preset structural response threshold, the corresponding pipe section is determined to be a normal modification section. If the hydraulic response value exceeds the preset hydraulic response threshold, the corresponding pipe section is determined to be a sensitive section for modification. If the hydraulic response value does not exceed the preset hydraulic response threshold, the corresponding pipe section is determined to be a normal modification section; Sensitivity values ​​are generated based on the structural or hydraulic response values ​​corresponding to the sections identified as sensitive to modification.

[0009] In a preferred embodiment, defect detection is performed on the sensitive section to be modified, and corresponding defect feature information is obtained based on the defect detection, including: Defect detection is carried out on sensitive sections of the pipeline, including CCTV inspection and acoustic inspection. Based on the CCTV inspection of the pipeline, the defect areas on the inner wall of the pipeline are identified, and the size, shape and surface morphology features of the defect areas are extracted. Based on the sound signals obtained from acoustic detection, the location of the abnormal sound in the pipe is identified, and the intensity of the abnormal sound at the location of the abnormal sound is obtained. The size, shape, surface morphology, location of abnormal sound, and intensity of abnormal sound in the defect area within the same pipe section are combined to generate defect feature information.

[0010] In a preferred embodiment, the defect type and construction disturbance type are obtained, and a fusion weight is obtained based on the defect type and construction disturbance type, including: Obtain the defect type and construction disturbance type; Obtain the weight correspondence table, which includes multiple defect types in the vertical index and multiple construction disturbance types in the horizontal index, as well as the fusion weight corresponding to each defect type and construction disturbance type. The fusion weight includes morphological feature weight, sound intensity weight and sensitivity weight. Based on each defect type and construction disturbance type, the corresponding defect type in the vertical index and the construction disturbance type in the horizontal index are matched, and the corresponding fusion weight is obtained from the weight mapping table.

[0011] In a preferred embodiment, the defect feature information is combined with the sensitivity value of the corresponding modification-sensitive section and a fusion weight is used to perform a fusion calculation to generate a defect risk index, including: Obtain the corresponding surface morphology feature values ​​and abnormal sound intensity values ​​based on the defect feature information; The defect risk index for each defect is obtained based on surface morphology characteristics, abnormal sound intensity, sensitivity, and fusion weight.

[0012] In a preferred embodiment, multiple defects are sorted and graded according to a defect risk index to identify the defects that need to be addressed first on the critical path of construction, and the corresponding modification priority results and construction intervention suggestions are output, including: The defect risk index of each sensitive section to be modified will be sorted in descending order to generate a risk ranking table and the corresponding risk level. Based on the construction planning data, obtain the corresponding critical path of construction, identify the sensitive sections of the renovation located on the critical path and whose risk level exceeds the preset level, and mark them as high-risk defects. Based on high-risk defects, a modification priority result is generated to clarify the order of defect treatment, and specific construction intervention measures are recommended for each defect in the modification priority result.

[0013] The present invention also provides a pipeline defect detection system based on stormwater and sewage pipeline network renovation, used in the aforementioned pipeline defect detection method based on stormwater and sewage pipeline network renovation, comprising: The construction disturbance module is used to obtain construction planning data for stormwater and sewage pipe network renovation projects and to obtain construction disturbance parameters based on the construction planning data. The response value module is used to obtain the basic structural data and hydraulic data of the pipeline network to be modified, and to obtain the structural response value and hydraulic response value of the pipe segment corresponding to the basic structural data and hydraulic data under the construction disturbance effect based on the construction disturbance parameters. The sensitivity module is used to identify pipe sections whose structural or hydraulic response values ​​exceed a preset threshold as sensitive sections for modification, and to generate corresponding sensitivity values ​​based on the response values ​​of the sensitive sections. The defect detection module is used to detect defects in the sensitive sections to be modified and to obtain the corresponding defect feature information based on the defect detection. The fusion weight module is used to obtain the defect type and construction disturbance type, and to obtain the fusion weight based on the defect type and construction disturbance type; The defect risk module is used to combine defect feature information with the sensitivity value of the corresponding modification sensitive section and perform fusion calculation to generate a defect risk index. The defect intervention module is used to sort and classify multiple defects according to the defect risk index, identify the defects that need to be addressed first on the critical path of construction, and output the corresponding modification priority results and construction intervention suggestions.

[0014] And, a pipeline defect detection terminal based on stormwater and sewage pipeline renovation, comprising: One or more processors; A storage device on which one or more programs are stored; When one or more programs are executed by one or more processors, the one or more processors implement a pipeline defect detection method based on the renovation of rainwater and sewage pipeline networks.

[0015] The technical effects achieved by this invention are as follows: This invention achieves joint evaluation of construction disturbance and pipeline structure response, improving the accuracy of retrofit design, quantitatively assessing the scope and degree of construction impact, and early identification of high-risk sections. Based on multimodal detection, it obtains more complete defect information, improving the accuracy of defect identification. By jointly analyzing pipeline CCTV inspection video data and acoustic data, it can simultaneously identify pipeline geometric defects, internal pipeline leaks, and abnormal acoustic characteristics, overcoming the incomplete information problem of single detection methods and improving the reliability of defect evaluation. It correlates construction disturbance types with defect types, improving the targeting of risk assessment, enabling accurate prediction of the risk performance of different defects at different construction stages, and has higher engineering applicability. It enables dynamic retrofit priority decision-making under the critical path of construction, improving construction safety and efficiency, and providing intervention suggestions that can directly guide construction, enhancing the engineering practice value of the method. Attached Figure Description

[0016] Figure 1 This is a flowchart of the method provided by the present invention; Figure 2 This is a system module diagram provided by the present invention. Detailed Implementation

[0017] To make the above-mentioned objects, features and advantages of the present invention more apparent and understandable, the specific embodiments of the present invention will be described in detail below with reference to the accompanying drawings.

[0018] Many specific details are set forth in the following description in order to provide a full understanding of the invention. However, the invention may also be practiced in other ways different from those described herein, and those skilled in the art can make similar extensions without departing from the spirit of the invention. Therefore, the invention is not limited to the specific embodiments disclosed below.

[0019] Secondly, the term "an embodiment" or "embodiment" as used herein refers to a specific feature, structure, or characteristic that may be included in at least one implementation of the present invention. The phrase "in a preferred embodiment" appearing in different places throughout this specification does not necessarily refer to the same embodiment, nor is it a single or selective embodiment that mutually excludes other embodiments.

[0020] Furthermore, the present invention will be described in detail with reference to the schematic diagrams. When describing the embodiments of the present invention in detail, the schematic diagrams are merely examples for ease of explanation and should not limit the scope of protection of the present invention.

[0021] Please see the appendix Figure 1 As shown, a method for detecting pipeline defects based on stormwater and sewage pipeline renovation is provided, including: S1. Obtain construction planning data for the stormwater and sewage pipe network renovation project, and obtain construction disturbance parameters based on the construction planning data; S2. Obtain the basic structural data and hydraulic data of the pipeline network to be modified, and obtain the structural response value and hydraulic response value of the pipe segment corresponding to the basic structural data and hydraulic data under the construction disturbance based on the construction disturbance parameters. S3. Identify pipe sections whose structural or hydraulic response values ​​exceed a preset threshold as sensitive sections for modification, and generate corresponding sensitivity values ​​based on the response values ​​of the sensitive sections for modification. S4. Perform defect detection on the sensitive sections to be modified, and obtain the corresponding defect feature information based on the defect detection. S5. Obtain the defect type and construction disturbance type, and obtain the fusion weight based on the defect type and construction disturbance type; S6. Combine the defect feature information with the sensitivity value of the corresponding modification sensitive section and perform fusion calculation to generate the defect risk index; S7. Sort and classify multiple defects according to the defect risk index, obtain the defects that need to be dealt with first on the critical path of construction, and output the corresponding modification priority results and construction intervention suggestions.

[0022] As described in steps S1 to S7 above, construction planning data for the stormwater and sewage pipe network renovation project is obtained, including construction procedures, equipment operation methods, and engineering geological conditions. By analyzing the construction planning data, multiple disturbances that may affect the surrounding soil and pipe network during construction are extracted, including vibration effects from equipment operation, changes in water flow state caused by construction procedures, and changes in the bearing capacity of the pipe body and surrounding soil caused by construction loads. These together constitute construction disturbance parameters. The foundation structure data (such as material strength, burial depth, and structural layout) and hydraulic data (such as historical flow and water level) of the pipe network to be renovated are obtained. The construction disturbance parameters are then applied to the structural and hydraulic conditions corresponding to the pipe section, and the pipe section corresponding to the foundation structure data and hydraulic data is obtained during construction. The structural and hydraulic response values ​​under disturbance are pre-set with structural and hydraulic response thresholds. When the structural or hydraulic response value of a certain pipe section exceeds the corresponding threshold, it indicates that the pipe section is more sensitive to construction disturbances and is thus identified as a sensitive section for modification. A sensitivity value is generated based on the amplitude of the response value, and multimodal defect detection is performed on the sensitive section for modification. This includes pipeline CCTV inspection (identifying geometric and appearance features such as cracks, damage, and detachment on the inner wall of the pipe by analyzing image sequences) and acoustic inspection (identifying the location and intensity of abnormal sound sources in the pipeline through sound signals, reflecting leakage or internal cavitation). The two types of detection information are summarized to generate complete defect feature information for each defect. Based on the detected defect type (such as cracks), the system is further refined. The system identifies and combines defect characteristics (such as corrosion, flaking, etc.) with construction disturbance types (such as vibration disturbance, hydraulic disturbance, load-bearing disturbance, etc.). It matches corresponding fusion weights from a pre-defined weighting table, integrates defect feature information, sensitivity values, and fusion weights, and calculates a defect risk index for each defect through a weighted average. Based on this index, multiple defects are ranked and risk-classified. Combined with the critical path in the construction plan, defects located in critical construction sections and with high risk levels are identified. The system then generates modification priority results and corresponding construction intervention suggestions to guide the priority treatment of the highest-risk pipe sections during construction. This achieves a joint assessment of construction disturbance and pipeline structure response, improving the accuracy of modification design and the scope and degree of impact on construction. Quantitative assessment enables early identification of high-risk sections. Multimodal detection provides more complete defect information, improving the accuracy of defect identification. Joint analysis of pipeline CCTV inspection video data and acoustic data simultaneously identifies geometric defects, internal leaks, and abnormal acoustic characteristics, overcoming the incomplete information of single detection methods and improving the reliability of defect evaluation. Correlation between construction disturbance types and defect types enhances the targeting of risk assessment, allowing for accurate prediction of the risk performance of different defects at different construction stages. This results in greater engineering applicability, enabling dynamic modification priority decisions under the critical path of construction, improving construction safety and efficiency, providing intervention suggestions that directly guide construction, and enhancing the engineering practice value of the method.

[0023] In a preferred embodiment, construction planning data for the stormwater and sewage pipe network renovation project is obtained, and construction disturbance parameters are obtained based on the construction planning data, including: S101. Obtain construction planning data for the stormwater and sewage pipe network renovation project. The construction planning data includes construction procedures, operation mode of construction equipment, and engineering geological conditions. S102. Based on the operating mode of the construction equipment and the engineering geological conditions, obtain the vibration impact of the construction equipment vibration waves on the surrounding soil and pipelines during the excavation process. S103. Obtain the changes in water flow status in the pipe during construction based on the construction procedures; S104. Obtain construction load information, including excavation unloading, backfill loading or temporary surcharge, and obtain the bearing capacity changes of the pipe body and surrounding soil during construction in combination with engineering geological conditions. S105, and summarize the vibration impact, water flow state change, and bearing capacity change into construction disturbance parameters.

[0024] As described in steps S101 to S105 above, the construction planning data for the stormwater and sewage pipe network renovation project is read, including construction procedures (excavation, support, backfilling, etc.), construction equipment operation mode (equipment type, operating frequency, vibration level, etc.), and engineering geological conditions (soil type, density, moisture content, etc.). The operation of construction equipment will generate vibration waves in the excavation area. These vibrations propagate through the soil and will cause additional vibration effects on the surrounding soil and underground pipe network. Based on the construction equipment operation mode (such as vibration frequency and power) and engineering geological conditions (such as soil wave impedance, damping characteristics, etc.), the project will be further refined. The study estimates the propagation and attenuation law of vibration waves and samples the pipe vibration response within a preset time window, calculating the mean value as the vibration impact quantity. This vibration impact quantity reflects the degree of mechanical disturbance that construction equipment may cause to the pipe network. Construction procedures (such as excavation, temporary diversion, interception, and backfilling) will change the instantaneous hydraulic environment of the stormwater and sewage pipe network. Based on the type and duration of the construction procedure, the study collects data on the changes in water flow velocity within the pipe during construction, calculates the mean water flow velocity within a set time period, and obtains the water flow state change quantity. This water flow state change quantity is used to quantify the impact of construction on the pipe network. The disturbance intensity caused by hydraulic conditions within the pipe (such as flow velocity, water level, and head loss) will result in various load changes during construction, including excavation unloading (stress release due to soil removal), backfill loading (increased earth pressure due to layer-by-layer compaction of backfill material), and temporary surcharges (additional loads generated by the temporary storage of construction materials or machinery). By acquiring this construction load information and combining it with engineering geological conditions (such as soil elastic modulus and Poisson's ratio), the additional stress acting on the pipe and surrounding soil during construction can be calculated. The average value of the data during construction is then used to obtain the bearing capacity variation. This method is used to reflect changes in the bearing capacity of the pipe body and the surrounding soil. It summarizes the impact of vibration, changes in water flow state, and changes in bearing capacity to form construction disturbance parameters. Construction disturbance parameters are a quantitative expression of the comprehensive impact of construction on the pipeline network. Construction disturbance is quantified from three dimensions: vibration, hydraulics, and bearing capacity, forming comprehensive construction disturbance parameters. This improves the accuracy of describing the impact of construction. Compared with the traditional method of judging the strength of construction impact based solely on experience, it has higher objectivity and reliability. It incorporates construction equipment, procedures, and geological conditions into the calculation, improving the adaptability of the project.

[0025] In a preferred embodiment, the basic structural data and hydraulic data of the pipeline network to be modified are obtained. Based on construction disturbance parameters, the structural response values ​​and hydraulic response values ​​of the corresponding pipe segments under construction disturbance are obtained, including: S201. Obtain the basic structural data and hydraulic data of the pipeline network to be modified; S202. Obtain the material strength and burial depth of each pipe segment based on the basic structure data, and obtain the corresponding structural weight based on the material strength. The structural weight includes vibration influence weight, load change weight and burial weight. S203. Obtain the structural response value of the corresponding pipe section under construction disturbance based on the burial depth, vibration impact, load change and structural weight. S204. Obtain multiple historical flow rates, multiple historical water levels, current flow rate, and current water level for each pipe section based on hydraulic data; S205. Obtain hydraulic weights based on changes in water flow state, whereby hydraulic weights include water level weights and flow rate weights. S206. Obtain the hydraulic response value based on multiple historical flow rates, multiple historical water levels, current flow rate, current water level, and hydraulic weight.

[0026] As described in steps S201 to S206 above, basic data of the pipeline network to be modified is obtained, including basic structural data (pipe diameter, material, burial depth, pipe age, interface type, etc.) and hydraulic data (historical flow rate, water level records, and current flow rate and water level). This data describes the current state of the pipeline network. The structural response is affected by multiple factors, including material strength, burial depth, and construction disturbance. Based on the material type recorded in the basic structural data, material strength parameters are obtained, and the structural weight corresponding to the material is determined using a pre-set weight table. This includes vibration impact weight (different materials have different sensitivities to vibration disturbance), bearing capacity change weight (different materials and wall thicknesses have different bearing capacities for additional stress), and burial weight (the deeper the burial, the stronger the soil buffer, and the lower the weight). The pre-set weight table is established based on engineering experience and theoretical parameters of the foundation and pipeline, ensuring that the weight selection is repeatable and has an engineering basis. Based on the vibration impact and bearing capacity change in the construction disturbance parameters, combined with the burial depth and structural weight of each pipe section, the structural response value under construction disturbance is calculated. The formula for calculating the structural response value is as follows: In the formula, J represents the structural response value, h represents the burial weight, H represents the burial depth, d represents the vibration influence weight, D represents the vibration influence amount, c represents the load change weight, and C represents the load change amount. h + d + c = 1. The structural response value reflects the degree of stress change that the pipe section may face during construction. Multiple historical flow rates, multiple historical water levels, current flow rates, and current water levels are extracted from hydraulic data to form a time series of the pipe section's hydraulic state. The hydraulic response depends on the influence of flow rate and water level on the pipeline's functional state. Based on the change in water flow state, the corresponding water level weight (reflecting the sensitivity of water level changes to pipeline pressure and leakage) and flow rate weight (reflecting the sensitivity of flow velocity changes to scouring, siltation, and transient effects) are read from a preset weight table. The hydraulic weight table is preset based on different pipe network types and usage scenarios to ensure project applicability. Based on historical flow rates, historical water levels, current flow rates, and current water levels, and combined with the hydraulic weights, the hydraulic response value is calculated. The formula for calculating the hydraulic response value is: In the formula, S represents the hydraulic response value, i represents the number of multiple historical flow rates and multiple historical water levels, i=1,2,3…n, and q represents the flow weight. Let i be the i-th historical traffic. Let w represent the current flow rate, and w represent the water level weight. Let i be the i-th historical water level. The current water level is represented by q+w=1. The hydraulic response value reflects whether construction disturbance may lead to turbulent water flow, sudden changes in local water level, or abnormal water flow conditions. A construction disturbance response system with two dimensions, structure and hydraulics, is established. The weights of material strength and burial depth are introduced to improve the accuracy of structural analysis. At the same time, historical data and current data are used to make the hydraulic response assessment more reliable. A preset weight table is adopted to make the calculation process repeatable and standardized, avoiding the uncertainty of human experience judgment, which is conducive to consistent application in different projects.

[0027] In a preferred embodiment, pipe sections whose structural or hydraulic response values ​​exceed a preset threshold are identified as sensitive sections for modification, and corresponding sensitivity values ​​are generated based on the response values ​​of these sensitive sections, including: S301. Obtain preset thresholds, wherein the preset thresholds include preset structural response thresholds and preset hydraulic response thresholds; S302. Determine whether the structural response value or hydraulic response value exceeds the corresponding preset structural response threshold or preset hydraulic response threshold. If the structural response value exceeds the preset structural response threshold, the corresponding pipe section is determined to be a sensitive section for modification. If the structural response value does not exceed the preset structural response threshold, the corresponding pipe section is determined to be a normal modification section. If the hydraulic response value exceeds the preset hydraulic response threshold, the corresponding pipe section is determined to be a sensitive section for modification. If the hydraulic response value does not exceed the preset hydraulic response threshold, the corresponding pipe section is determined to be a normal modification section; S303. Generate sensitivity values ​​based on the structural or hydraulic response values ​​corresponding to the sections identified as sensitive to modification.

[0028] As described in steps S301 to S303 above, preset thresholds for determining whether a pipe section is sensitive are obtained. These include a preset structural response threshold (used to determine whether structural stress or deformation exceeds limits under construction disturbance) and a preset hydraulic response threshold (used to determine whether changes in water flow affect the normal operation of the pipe section). These thresholds are preset based on industry standards, pipe material strength standards, historical monitoring data, or expert experience to ensure the judgment criteria are engineering-appropriate. The pipe section is determined to be a sensitive section for modification by comparing its structural response value with its hydraulic response value to see if they exceed the corresponding thresholds. If the structural response value exceeds the structural response threshold, it is determined to be a structurally sensitive section; if it does not exceed the threshold, it is determined to be a structurally normal section. Similarly, if the hydraulic response value exceeds the hydraulic response threshold, it is determined to be a hydraulically sensitive section; if it does not exceed the threshold, it is determined to be a hydraulically normal section. If any response value exceeds a threshold, the pipe section is determined to be a sensitive section for modification, ensuring... All potential risk points are identified without overlooking any hidden dangers. For pipe sections identified as sensitive to renovation, corresponding sensitivity values ​​are generated to quantify their sensitivity to construction disturbances. If both the structural and hydraulic response values ​​of the same pipe section exceed thresholds, their values ​​are compared, and the larger response value is selected as the core input. The larger the response value, the stronger the impact of construction disturbances. A larger value is selected to ensure that the sensitivity reflects the most important source of risk. The selected response value is input into a preset sensitivity lookup table. The corresponding sensitivity value is matched through the response value range. The lookup table method standardizes the sensitivity values, avoids errors from manual calculations, and improves the consistency and reproducibility of the method. By using dual-dimensional threshold judgments of structural and hydraulic responses, potential high-risk pipe sections are not overlooked. This method can handle both structural and hydraulic risks simultaneously, improving the accuracy of the judgment. The introduction of a lookup table sensitivity generation method enhances the standardization of the results.

[0029] In a preferred embodiment, defect detection is performed on the sensitive section to be modified, and corresponding defect feature information is obtained based on the defect detection, including: S401. Conduct defect detection on sensitive sections of the pipeline, including pipeline CCTV inspection and acoustic inspection. S402. Obtain the detection image sequence based on the pipeline CCTV inspection, identify the defect area on the inner wall of the pipeline based on the detection image sequence, and extract the size, shape and surface morphology features of the defect area. S403. Based on the sound signal obtained from acoustic detection, identify the location of the abnormal sound in the pipeline and obtain the intensity of the abnormal sound at the location of the abnormal sound. S404. Merge the size, shape, surface morphology features, location of abnormal sound and intensity of abnormal sound of defect areas within the same pipe section to generate defect feature information.

[0030] As described in steps S401 to S404 above, two technical approaches are used for defect identification: CCTV visual inspection and acoustic inspection. CCTV inspection, based on video image sequences, uses image processing and deep learning algorithms to identify visible defects (such as cracks, breaks, detachments, and corrosion) on the inner wall of the pipe. Acoustic inspection uses sensors to collect sound signals propagating inside the pipe and identifies the location and intensity of abnormal sound emissions through frequency domain analysis and time-frequency analysis to identify hidden defects that are difficult to detect with the naked eye (such as leaks and structural voids). Based on the CCTV inspection image sequence, defect areas are extracted using image segmentation, edge detection, and pixel clustering techniques, and size features (area, length, width, and depth estimation), shape features (crack direction, roundness, aspect ratio, etc.), and surface morphology features (roughness, corrosion) are obtained. The acoustic detection section processes sound signals through envelope detection, short-time Fourier transform (STFT), and spectral analysis to locate the source of abnormal sound. It also quantifies the amplitude, energy, and frequency distribution of the abnormal sound. The intensity of the abnormal sound reflects the severity of potential defects, such as leakage or cavity size. Features from both visual and acoustic sources are matched and fused within the same pipe section coordinate system to achieve spatial alignment of defect information. Size, shape, and surface morphology features are merged with acoustic anomaly features to generate unified defect feature information. Multi-source fusion provides a more comprehensive and accurate description of pipeline defects than single-source detection. While CCTV inspection can identify visible defects, acoustic detection can detect hidden defects that are difficult to detect visually, such as microcracks, leaks, and voids. The combination of both significantly improves defect identification coverage and accuracy.

[0031] In a preferred embodiment, the defect type and construction disturbance type are obtained, and a fusion weight is obtained based on the defect type and construction disturbance type, including: S501. Obtain the defect type and construction disturbance type; S502. Obtain the weight correspondence table, which includes multiple defect types in the vertical index and multiple construction disturbance types in the horizontal index, as well as the fusion weight corresponding to each defect type and construction disturbance type. The fusion weight includes morphological feature weight, sound intensity weight and sensitivity weight. S503. Based on each defect type and construction disturbance type, match the corresponding defect type in the vertical index and the construction disturbance type in the horizontal index, and obtain the corresponding fusion weight from the weight correspondence table.

[0032] As described in steps S501 to S503 above, the defect type (such as cracks, corrosion, deformation, node misalignment, etc.) and construction disturbance type (such as excavation, trenchless crossing, vibration construction, ground load changes, etc.) of each pipe segment to be analyzed are obtained. A weight correspondence table is pre-constructed, with the row index representing the defect type and the column index representing the construction disturbance type. The intersection of the row and column indices represents the fusion weight, including morphological feature weight (the importance of image features), sound intensity weight (the importance of acoustic anomaly intensity), and sensitivity weight (the risk sensitivity of the defect under the corresponding construction disturbance). When the system inputs the defect type and construction disturbance type, it finds the corresponding value by looking up the table. The corresponding weight combinations, through a query mechanism, control the calculation of the subsequent defect risk index, ensuring that multi-source features participate in the comprehensive judgment in an appropriate proportion. By simultaneously considering defect type and construction disturbance type, dynamic selection of weights is achieved, avoiding a general risk assessment approach. This makes defect analysis in different scenarios more accurate. The relationship between morphological features, sound intensity, and sensitivity is not fixed. Different scenarios are graded through a weight correspondence table, making the results more logically sound and scientifically grounded. The weight correspondence table can be continuously expanded and adjusted based on engineering experience, historical data, or industry standards, exhibiting good maintainability and scalability, and is applicable to various municipal pipeline renovation projects.

[0033] In a preferred embodiment, defect feature information is combined with the sensitivity value of the corresponding modification-sensitive section and fusion weights for fusion calculation to generate a defect risk index, including: S601. Obtain the corresponding surface morphology feature value and abnormal sound intensity value based on the defect feature information; S602. Obtain the defect risk index corresponding to each defect based on the surface morphology characteristic value, abnormal sound intensity value, sensitivity value and fusion weight.

[0034] As described in steps S601 to S602 above, based on the defect detection results, surface morphology feature values ​​(quantified from morphological features such as size, shape, damage depth, and cracking degree) and abnormal sound intensity values ​​(quantified from leakage sound intensity in acoustic detection) are extracted for each defect. Based on the surface morphology feature values, abnormal sound intensity values, sensitivity values, and fusion weights, the defect risk index corresponding to each defect is calculated. The formula for calculating the defect risk index is as follows: In the formula, F represents the defect risk index, b represents the morphological feature weight, B represents the surface morphological feature value, y represents the sound intensity weight, Y represents the abnormal sound intensity value, m represents the sensitivity weight, and M represents the sensitivity value. b+y+m=1. By utilizing data from three dimensions—visual defects, acoustic defects, and construction sensitivity—the risk index no longer relies solely on a single sensor or indicator, thus significantly improving the comprehensiveness of defect evaluation. By integrating weights to reflect the matching relationship between different defects and different construction disturbances, the calculation method can be automatically adjusted for different engineering scenarios, avoiding misjudgments caused by uniform weighting. The risk index not only reflects the severity of the defect itself but also combines the sensitivity to construction disturbances, enabling early identification of defects most likely to worsen during construction and improving the ability to pre-control risks before construction.

[0035] In one preferred embodiment, multiple defects are ranked and classified according to a defect risk index to identify the defects that require priority treatment on the critical path of construction. The corresponding modification priority results and construction intervention suggestions are then output, including: S701. Sort the defect risk index of each sensitive section for modification in descending order to generate a risk ranking table and the corresponding risk level. S702. Obtain the corresponding critical path of construction based on the construction planning data, identify the sensitive sections of the renovation located on the critical path and whose risk level exceeds the preset level, and mark them as high-risk defects. S703. Generate renovation priority results based on high-risk defects to clarify the order of defect treatment, and output specific construction intervention measures suggestions for each defect in the renovation priority results.

[0036] As described in steps S701 to S703 above, the defect risk indices are sorted from highest to lowest. A higher defect risk index indicates a greater likelihood of the defect worsening under construction disturbances, posing a higher threat to pipeline safety. The risk indices are categorized into high, medium, and low levels, forming a risk ranking table and corresponding risk levels. Construction planning data is obtained, and the critical path of the renovation project is identified (i.e., the construction nodes or pipe sections most sensitive to the overall progress and whose sequence must be strictly controlled). The ranked defects are matched with the critical path to determine which high-risk defects are located on the critical path. These defects are marked as high-risk defects for focused attention and early treatment before construction. Based on the ranking of high-risk defects, a renovation priority result is generated, clarifying the order of defect treatment. The system prioritizes and provides construction intervention suggestions for each defect, such as reinforcement measures, temporary supports, adjustments to the construction sequence, or avoiding high-risk construction sections. Combining priorities and intervention measures ensures reasonable resource allocation and controllable construction risks during construction. By ranking and classifying risks through risk indices, the construction team can identify which defects are most likely to worsen on the critical path, thus enabling targeted construction interventions to avoid secondary damage or accidents to the pipeline network. Once the renovation priorities are clear, limited manpower, equipment, and materials can be prioritized for high-risk defects, optimizing the allocation of construction resources while ensuring a reasonable construction sequence on the critical path and improving construction efficiency. By combining risk indices with the critical path of construction, defects that may lead to project delays or safety accidents can be identified in advance, allowing for preventative measures to be taken and reducing the probability of accidents.

[0037] Please see the appendix Figure 2 As shown, the present invention also provides a pipeline defect detection system based on stormwater and sewage pipeline network renovation, used in the aforementioned pipeline defect detection method based on stormwater and sewage pipeline network renovation, comprising: The construction disturbance module is used to obtain construction planning data for stormwater and sewage pipe network renovation projects and to obtain construction disturbance parameters based on the construction planning data. The response value module is used to obtain the basic structural data and hydraulic data of the pipeline network to be modified, and to obtain the structural response value and hydraulic response value of the pipe segment corresponding to the basic structural data and hydraulic data under the construction disturbance effect based on the construction disturbance parameters. The sensitivity module is used to identify pipe sections whose structural or hydraulic response values ​​exceed a preset threshold as sensitive sections for modification, and to generate corresponding sensitivity values ​​based on the response values ​​of the sensitive sections. The defect detection module is used to detect defects in the sensitive sections to be modified and to obtain the corresponding defect feature information based on the defect detection. The fusion weight module is used to obtain the defect type and construction disturbance type, and to obtain the fusion weight based on the defect type and construction disturbance type; The defect risk module is used to combine defect feature information with the sensitivity value of the corresponding modification sensitive section and perform fusion calculation to generate a defect risk index. The defect intervention module is used to sort and classify multiple defects according to the defect risk index, identify the defects that need to be addressed first on the critical path of construction, and output the corresponding modification priority results and construction intervention suggestions.

[0038] The aforementioned construction disturbance module is used to acquire construction planning data for the stormwater and sewage pipe network renovation project, including construction procedures, equipment operation modes, and engineering geological conditions. Based on the construction planning data, the module calculates disturbance parameters generated during construction, including the impact of construction equipment vibration on the surrounding soil and pipe network, changes in water flow state within the pipe during construction, and changes in the bearing capacity of the pipe and surrounding soil under construction loads. The response value module acquires the foundation structure and hydraulic data of the pipe network to be renovated, and, in conjunction with the construction disturbance parameters, calculates the structural and hydraulic response values ​​of the pipe segment under construction disturbance. This includes calculating the structural response value based on material strength, burial depth, and structural weight, and calculating the hydraulic response value based on historical and current water flow information and hydraulic weight. This allows for the quantification of the impact of construction disturbance on the pipe network. The network may generate structural and hydraulic impacts. The sensitivity module, based on preset thresholds, identifies pipe sections with structural or hydraulic response values ​​exceeding these thresholds as sensitive sections for modification. Subsequently, sensitivity values ​​are generated based on the response values ​​to quantify the vulnerability of the pipe section to construction disturbances. The defect detection module performs defect detection on the sensitive sections, including CCTV inspection (extracting the size, shape, and surface features of defective areas on the pipe's inner wall) and acoustic inspection (obtaining the location and intensity of abnormal sounds). Visual and acoustic features are merged to form unified defect feature information, ensuring the comprehensiveness and reliability of the defect information. The weighting module obtains the defect type and construction disturbance type and matches the corresponding weights using a preset weight mapping table. The weights include morphological feature weights and sound weights. Intensity weight and sensitivity weight are used to describe the differences in sensitivity of different defects under different construction disturbance conditions. The defect risk module combines defect feature information with sensitivity values ​​and weights to calculate a defect risk index for each defect. This index quantifies the likelihood of defect deterioration during construction and its potential impact on construction and pipeline operation. The defect intervention module sorts and classifies multiple defects based on the defect risk index and identifies high-risk defects in conjunction with the critical path of construction, ultimately outputting the priority of modification results and construction intervention suggestions for each defect. This achieves precise management and decision support for defect risks before and during construction. Vibration, water flow, and load disturbance parameters obtained through the construction disturbance module enable a quantitative description of the impact of the construction process on the pipeline network. Defect risk assessment has shifted from static to dynamic analysis, better reflecting actual engineering conditions. It integrates visual features (CCTV inspection of pipelines) with acoustic features, combining sensitivity values ​​and weighting information to calculate a risk index, effectively reducing missed detection and false positive rates and improving the reliability of defect identification. The weighting module dynamically matches weights based on defect type and construction disturbance type, enabling differentiated assessment of defect sensitivity under different conditions, enhancing the precision and scientific rigor of risk judgment. The defect intervention module, combined with the construction critical path, prioritizes high-risk defects and outputs construction intervention suggestions, achieving proactive construction safety management and optimizing construction sequence, improving project efficiency. The risk index generated by fusing sensitivity values ​​and defect characteristics provides construction units with quantitative decision-making basis.To reduce the risk of accidents and pipeline operation during construction, and to improve the safety and economy of pipeline renovation projects.

[0039] And, a pipeline defect detection terminal based on stormwater and sewage pipeline renovation, comprising: One or more processors; A storage device on which one or more programs are stored; When one or more programs are executed by one or more processors, the one or more processors implement a pipeline defect detection method based on the renovation of rainwater and sewage pipeline networks.

[0040] The above description is merely a preferred embodiment of the present invention. It should be noted that those skilled in the art can make various improvements and modifications without departing from the principles of the present invention, and these improvements and modifications should also be considered within the scope of protection of the present invention. Structures, devices, and operating methods not specifically described or explained in this invention are implemented according to conventional methods in the art unless otherwise specified or limited.

Claims

1. A method for detecting pipeline defects based on stormwater and sewage pipeline renovation, characterized in that, include: Obtain construction planning data for the stormwater and sewage pipe network renovation project, and obtain construction disturbance parameters based on the construction planning data; Obtain the basic structural data and hydraulic data of the pipeline network to be modified, and obtain the structural response value and hydraulic response value of the pipe segment corresponding to the basic structural data and hydraulic data under the construction disturbance effect based on the construction disturbance parameters. Pipe sections whose structural or hydraulic response values ​​exceed a preset threshold are identified as sensitive sections for modification, and corresponding sensitivity values ​​are generated based on the response values ​​of the sensitive sections. Defect detection is performed on the sensitive sections to be modified, and the corresponding defect feature information is obtained based on the defect detection. Obtain the defect type and construction disturbance type, and obtain the fusion weight based on the defect type and construction disturbance type; The defect feature information is combined with the sensitivity value of the corresponding modification sensitive section and the fusion weight to generate a defect risk index. Based on the defect risk index, multiple defects are sorted and classified to identify those that need to be addressed first on the critical path of construction, and corresponding modification priority results and construction intervention suggestions are output.

2. The method for detecting pipeline defects based on stormwater and sewage pipeline renovation according to claim 1, characterized in that, Obtain construction planning data for the stormwater and sewage pipe network renovation project, and obtain construction disturbance parameters based on the construction planning data, including: Obtain construction planning data for the stormwater and sewage pipe network renovation project. This data includes construction procedures, equipment operation methods, and engineering geological conditions. The vibration impact of the construction equipment's vibration waves on the surrounding soil and pipeline network during the excavation process is obtained based on the operating mode of the construction equipment and the engineering geological conditions. The changes in water flow status within the pipe during construction are obtained based on the construction procedures. Obtain construction load information, including excavation unloading, backfill loading or temporary surcharge, and combine it with engineering geological conditions to obtain the bearing capacity changes of the pipe body and surrounding soil during construction. The vibration impact, water flow state changes, and load changes are summarized as construction disturbance parameters.

3. The method for detecting pipeline defects based on stormwater and sewage pipeline renovation according to claim 1, characterized in that, Obtain the basic structural data and hydraulic data of the pipeline network to be modified. Based on the construction disturbance parameters, obtain the structural response values ​​and hydraulic response values ​​of the corresponding pipe segments under the construction disturbance, including: Obtain the basic structural data and hydraulic data of the pipeline network to be modified; The material strength and burial depth of each pipe segment are obtained based on the basic structural data, and the corresponding structural weight is obtained based on the material strength. The structural weight includes vibration influence weight, load change weight and burial weight. The structural response values ​​of the corresponding pipe section under construction disturbance are obtained based on the burial depth, vibration impact, load change and structural weight. Based on hydraulic data, obtain multiple historical flow rates, multiple historical water levels, current flow rate, and current water level for each pipe section; Hydraulic weights are obtained based on changes in water flow conditions, including water level weights and flow rate weights. The hydraulic response value is obtained based on multiple historical flow rates, multiple historical water levels, current flow rate, current water level, and hydraulic weight.

4. The method for detecting pipeline defects based on stormwater and sewage pipeline renovation according to claim 1, characterized in that, Pipe sections whose structural or hydraulic response values ​​exceed a preset threshold are identified as sensitive sections for modification. Corresponding sensitivity values ​​are generated based on the response values ​​of these sensitive sections, including: Obtain preset thresholds, including preset structural response thresholds and preset hydraulic response thresholds; Determine whether the structural response value or hydraulic response value exceeds the corresponding preset structural response threshold or preset hydraulic response threshold. If the structural response value exceeds the preset structural response threshold, the corresponding pipe section is determined to be a sensitive section for modification. If the structural response value does not exceed the preset structural response threshold, the corresponding pipe section is determined to be a normal modification section. If the hydraulic response value exceeds the preset hydraulic response threshold, the corresponding pipe section is determined to be a sensitive section for modification. If the hydraulic response value does not exceed the preset hydraulic response threshold, the corresponding pipe section is determined to be a normal modification section; Sensitivity values ​​are generated based on the structural or hydraulic response values ​​corresponding to the sections identified as sensitive to modification.

5. The method for detecting pipeline defects based on stormwater and sewage pipeline renovation according to claim 1, characterized in that, Defect detection is performed on the sensitive sections to be modified, and the corresponding defect feature information is obtained based on the defect detection, including: Defect detection is carried out on sensitive sections of the pipeline, including CCTV inspection and acoustic inspection. Based on the CCTV inspection of the pipeline, the defect areas on the inner wall of the pipeline are identified, and the size, shape and surface morphology features of the defect areas are extracted. Based on the sound signals obtained from acoustic detection, the location of the abnormal sound in the pipe is identified, and the intensity of the abnormal sound at the location of the abnormal sound is obtained. The size, shape, surface morphology, location of abnormal sound, and intensity of abnormal sound in the defect area within the same pipe section are combined to generate defect feature information.

6. The method for detecting pipeline defects based on stormwater and sewage pipeline renovation according to claim 1, characterized in that, Obtain the defect type and construction disturbance type, and obtain the fusion weight based on the defect type and construction disturbance type, including: Obtain the defect type and construction disturbance type; Obtain the weight correspondence table, which includes multiple defect types in the vertical index and multiple construction disturbance types in the horizontal index, as well as the fusion weight corresponding to each defect type and construction disturbance type. The fusion weight includes morphological feature weight, sound intensity weight and sensitivity weight. Based on each defect type and construction disturbance type, the corresponding defect type in the vertical index and the construction disturbance type in the horizontal index are matched, and the corresponding fusion weight is obtained from the weight mapping table.

7. The method for detecting pipeline defects based on stormwater and sewage pipeline renovation according to claim 6, characterized in that, The defect feature information is combined with the sensitivity value of the corresponding modification-sensitive section and fusion weights to generate a defect risk index, including: Obtain the corresponding surface morphology feature values ​​and abnormal sound intensity values ​​based on the defect feature information; The defect risk index for each defect is obtained based on surface morphology characteristics, abnormal sound intensity, sensitivity, and fusion weight.

8. The method for detecting pipeline defects based on stormwater and sewage pipeline renovation according to claim 1, characterized in that, Based on the defect risk index, multiple defects are sorted and classified to identify those that require priority handling on the critical construction path. Corresponding modification priority results and construction intervention suggestions are then output, including: The defect risk index of each sensitive section to be modified will be sorted in descending order to generate a risk ranking table and the corresponding risk level. Based on the construction planning data, obtain the corresponding critical path of construction, identify the sensitive sections of the renovation located on the critical path and whose risk level exceeds the preset level, and mark them as high-risk defects. Based on high-risk defects, a modification priority result is generated to clarify the order of defect treatment, and specific construction intervention measures are recommended for each defect in the modification priority result.

9. A pipeline defect detection system based on stormwater and sewage pipeline network renovation, applied to the pipeline defect detection method based on stormwater and sewage pipeline network renovation as described in any one of claims 1 to 8, characterized in that, include: The construction disturbance module is used to obtain construction planning data for stormwater and sewage pipe network renovation projects and to obtain construction disturbance parameters based on the construction planning data. The response value module is used to obtain the basic structural data and hydraulic data of the pipeline network to be modified, and to obtain the structural response value and hydraulic response value of the pipe segment corresponding to the basic structural data and hydraulic data under the construction disturbance effect based on the construction disturbance parameters. The sensitivity module is used to identify pipe sections whose structural or hydraulic response values ​​exceed a preset threshold as sensitive sections for modification, and to generate corresponding sensitivity values ​​based on the response values ​​of the sensitive sections. The defect detection module is used to detect defects in the sensitive sections to be modified and to obtain the corresponding defect feature information based on the defect detection. The fusion weight module is used to obtain the defect type and construction disturbance type, and to obtain the fusion weight based on the defect type and construction disturbance type; The defect risk module is used to combine defect feature information with the sensitivity value of the corresponding modification sensitive section and perform fusion calculation to generate a defect risk index. The defect intervention module is used to sort and classify multiple defects according to the defect risk index, identify the defects that need to be addressed first on the critical path of construction, and output the corresponding modification priority results and construction intervention suggestions.

10. A pipeline defect detection terminal based on stormwater and sewage pipeline renovation, characterized in that, include: One or more processors; A storage device on which one or more programs are stored; When one or more programs are executed by one or more processors, the one or more processors implement the pipeline defect detection method based on the renovation of rainwater and sewage pipelines as described in any one of claims 1 to 8.

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