A sewage pipe dynamic health evaluation method and system based on a hydraulic model

Abstract

The application discloses a sewage pipeline dynamic health evaluation method and system based on a hydraulic model. The evaluation method comprises the following steps: collecting basic information related to the sewage pipeline; determining sewage pipeline health condition evaluation indexes according to the basic information, and performing artificial real-time input and update on non-hydraulic state evaluation index data, and performing real-time collection and input on key monitoring points of pipeline hydraulic state data; optimizing or dynamically adjusting parameters of a city pipeline network hydraulic model through real-time data, obtaining non-hydraulic state evaluation index data and pipeline hydraulic state data at any pipeline position according to the optimized or adjusted model, and obtaining a health evaluation result of the pipeline through comprehensive analysis of the two kinds of data. The application can accurately and dynamically reflect the actual operation state of all pipelines in a monitoring area, timely discover and prevent potential risks of the pipelines, and significantly improve the evaluation efficiency.

Description

Technical Field

[0001] This invention relates to the technical field of wastewater pipeline health assessment methods, and particularly to the technical field of wastewater pipeline health assessment methods based on hydraulic models. Background Technology

[0002] Wastewater pipeline systems, as a crucial component of urban infrastructure, play a vital role in ensuring the normal operation of cities and the daily lives of residents. However, with accelerated urbanization and aging infrastructure, wastewater pipeline systems face increasing challenges, such as pipe damage, blockages, and leaks. These problems not only affect the effectiveness of wastewater treatment but may also endanger the surrounding environment and residents' lives. Therefore, real-time dynamic assessment of the health status of wastewater pipeline systems is of great significance for ensuring their safe operation.

[0003] Traditional methods for assessing the health of wastewater pipelines mainly rely on regular inspections and maintenance, as well as static analysis based on historical data. While these methods can identify and resolve problems in the pipeline system to some extent, they have significant limitations. For example, regular inspections and maintenance require substantial human and material resources and are difficult to monitor in real time; static analysis based on historical data may not accurately reflect the actual operating status of the pipeline system, thus affecting the accuracy of the assessment results.

[0004] In recent years, with the development of technologies such as the Internet of Things, big data, and hydraulic models, more and more research has begun to focus on dynamic health assessment methods based on real-time data. For example, sensor technology is used to collect real-time operational data of pipeline systems, and combined with data analysis to assess the health status of the pipeline systems. In addition, there are some methods based on machine learning and artificial intelligence technologies, such as neural networks and support vector machines, which can improve the accuracy and reliability of assessment results by analyzing large amounts of real-time and historical data. For example, existing patent document CN216770671U discloses an online monitoring system for sewage pipe networks, which provides analytical data for assessing the drainage capacity of low-lying and flood-prone areas by monitoring the flow information of important nodes in the pipe network; existing patent document CN105373035A discloses a smart water management system that provides real-time monitoring data and forecasts sudden accidents, including pipe network nodes, sewage treatment equipment, control center, and detection equipment, which can collect various monitoring data and effectively manage data storage.

[0005] The existing technologies mentioned above have improved the real-time performance of sewage pipeline problem detection to some extent. However, in actual operation, they are basically static assessments of the health status of sewage pipelines and only focus on monitoring key nodes. They cannot reflect the overall operation of sewage pipelines and cannot provide real-time, dynamic assessments of the health status of sewage pipelines throughout the region. Summary of the Invention

[0006] To address the shortcomings of existing technologies, the present invention aims to provide a method and system for dynamic health assessment of sewage pipelines based on hydraulic models. This assessment method or system can perform real-time dynamic monitoring and systematic evaluation of the health status of sewage pipelines, and better reflect the changes and development trends in the health status of sewage pipelines.

[0007] The technical solution of the present invention is as follows:

[0008] A dynamic health assessment method for sewage pipelines based on a hydraulic model, comprising:

[0009] S1 constructs a basic database unit, including: matching and storing the basic data of sewage pipes in the monitoring area obtained by collection and / or testing with the distribution location of sewage pipes on the GIS map of the monitoring area, so as to obtain a basic database unit integrated with the GIS system;

[0010] S2 constructs a data acquisition unit, which can extract influencing factors, i.e. evaluation indicators, related to the health status of sewage pipelines from the basic database unit, and record the collected pipeline non-hydraulic state index data and pipeline hydraulic state index data of key monitoring points in real time.

[0011] S3 constructs a hydraulic model calculation unit. The hydraulic model calculation unit can establish an urban drainage network hydraulic model based on the storm management model SWMM, according to the basic data of sewage pipes stored in the basic database unit and their distribution location on the GIS map of the monitoring area. The urban drainage network hydraulic model is calibrated and verified by the real-time pipe hydraulic status index data of key monitoring points obtained in S2, and its input parameters are adjusted in real time to obtain a dynamic drainage network hydraulic model. Furthermore, the hydraulic status index data of any sewage pipe location in the monitoring area is extracted through the dynamic drainage network hydraulic model, that is, the key hydraulic status index data. The key hydraulic status index data and the non-hydraulic status index data entered in real time by S2 together constitute a comprehensive evaluation index system for the health status of sewage pipes.

[0012] S4 constructs a health assessment calculation unit, which can score the health status of any sewage pipe in the monitoring area in real time based on the comprehensive evaluation index system of the sewage pipe health status, and obtain the dynamic score of the health status of any sewage pipe.

[0013] S5 constructs a dynamic update unit, which can update and store the dynamic score obtained by the health assessment calculation unit in real time and correspond it with the distribution location of sewage pipes on the GIS map of the monitoring area;

[0014] S6 constructs a report generation unit, which can generate a health assessment report for the sewage pipeline system based on the dynamic scores stored in the dynamic update unit and its historical data.

[0015] Through the above technical solutions, the evaluation method of the present invention can conduct regular or continuous monitoring and evaluation of the health status of sewage pipelines, and can better reflect the changes and trends in the health status of sewage pipelines.

[0016] Based on the units constructed above, this invention can maintain a comprehensive record of basic information of sewage pipelines, input and update evaluation index information in real time, collect flow monitoring data in real time, dynamically update hydraulic models, extract hydraulic state data at any pipeline location in real time, calculate sewage pipeline health status scores in real time, and dynamically generate sewage pipeline health reports.

[0017] Compared with traditional static health assessment methods, the above technical solutions of the present invention can adjust the hydraulic model parameters using real-time collected monitoring data, thereby achieving the purpose of real-time simulation and calculation, which can more accurately reflect the actual operating status of the pipeline system; it can conduct comprehensive analysis and evaluation of the pipeline system, identify potential problems in the pipeline system, and take timely measures to repair the pipeline or prevent pipeline system failures, thereby improving the safety and reliability of the pipeline system.

[0018] In some specific implementations, the report generation unit can generate a health assessment report for the sewage pipeline system based on dynamically updated scoring data and historical scoring data. The report includes detailed information such as the damage status and flow rate of each sewage pipeline, analyzes the development trend and existing problems of the pipeline health status, and proposes corresponding pipeline maintenance suggestions and risk prevention measures.

[0019] According to some preferred embodiments of the present invention, the basic data of the sewage pipeline includes: the geographical location of the sewage pipeline installation, material type, specifications, service life, maintenance records, operating parameters, historical monitoring data, and CCTV inspection data; wherein, the specifications include pipe length and pipe diameter; the operating parameters include flow rate, flow velocity, pressure, and water level within the pipeline; the historical monitoring data includes the historical flow rate and historical water level of the pipeline; the CCTV inspection data includes the types of structural and functional defects of the sewage pipeline and the location of the defect distribution; wherein, the types of structural defects include one or more of corrosion, cracking, deformation, misalignment, disconnection, intrusion, and leakage; the types of functional defects include one or more of sludge accumulation, scaling, debris, puddles, blockage, and tree root penetration.

[0020] According to some preferred embodiments of the present invention, step S1 further includes organizing the basic data of the sewage pipeline before storing it, wherein the organizing includes data deduplication and invalid data removal.

[0021] According to some preferred embodiments of the present invention, S2 specifically includes:

[0022] S21 uses data analysis methods to extract some of the most relevant influencing factors, i.e., evaluation indicators, from the basic database units to form a comprehensive evaluation indicator system for the health status of sewage pipelines.

[0023] S22 divides the evaluation indicators in the comprehensive evaluation index system into pipeline hydraulic state indicators and other non-hydraulic state indicators;

[0024] S23 Determine the location of key monitoring points in the sewage pipeline, install pipeline flow meters at the key monitoring points, and collect pipeline hydraulic status data at the key monitoring points in real time;

[0025] S24 updates and inputs the data of the non-hydraulic state indicators and the pipeline hydraulic state data of the key monitoring points in real time, which together constitute the data acquisition unit;

[0026] The hydraulic state indicators of the pipeline include the flow rate, flow velocity, and water level.

[0027] According to some preferred embodiments of the present invention, the data analysis method includes a statistical analysis method, a correlation analysis method, and a weighted evaluation method based on expert knowledge and practical engineering experience. The statistical analysis method includes performing statistical analysis on basic data in the basic database unit to identify the data types affecting the health status of sewage pipelines, i.e., key factors. The correlation analysis method includes comparing the identified key factors pairwise to select some evaluation indicators that are most relevant to the health status of sewage pipelines. The weighted evaluation method based on expert knowledge and practical engineering experience includes comprehensively considering the weights of the obtained evaluation indicators based on expert knowledge and practical engineering experience, arranging the obtained evaluation indicators according to their weights to form a comprehensive evaluation index system for the health status of sewage pipelines.

[0028] According to some preferred embodiments of the present invention, step S3 specifically includes:

[0029] S31 stores basic data of sewage pipes and their distribution on the GIS map of the monitoring area in the basic database unit built on S1, and constructs a hydraulic model of urban drainage network through the storm management model SWMM.

[0030] S32 uses the real-time pipeline hydraulic state data of key monitoring points obtained by S2 to calibrate and verify the obtained urban drainage network hydraulic model, and obtains the verified drainage network hydraulic model.

[0031] S33 uses the flow data of the pipeline in the real-time pipeline hydraulic state index data of the key monitoring points obtained by S2 to deduce the input parameters of the verified drainage network hydraulic model, and adjusts the input parameters to obtain the dynamic drainage network hydraulic model.

[0032] S34 extracts pipeline hydraulic status index data at any location of sewage pipeline within the monitoring area through the dynamic drainage network hydraulic model, obtains key hydraulic status index data, and together with the non-hydraulic status index data recorded in real time in the data acquisition unit, constitutes a comprehensive evaluation index system for the health status of sewage pipelines.

[0033] According to some preferred embodiments of the present invention, step S33 further includes:

[0034] S331 preprocesses the real-time pipeline hydraulic status data collected from key monitoring points. The pipeline hydraulic status data is mainly pipeline flow data.

[0035] S332 performs data statistics on the pre-processed real-time pipeline hydraulic state data to obtain the model input parameters that need to be updated in real time, namely the per capita sewage quota.

[0036] S333 adjusts the parameters of the drainage network hydraulic model based on data that needs to be updated in real time.

[0037] The preprocessing includes one or more of the following: data cleaning, outlier detection and removal, and data interpolation.

[0038] According to some preferred embodiments of the present invention, in step S4, the real-time scoring is achieved by one or more of the following methods: hierarchical analysis, fuzzy comprehensive evaluation, and grey relational analysis.

[0039] According to some preferred embodiments of the present invention, S4 specifically includes:

[0040] S41 selects appropriate evaluation methods, such as analytic hierarchy process, fuzzy comprehensive evaluation method, and grey relational analysis method, based on the constructed health status evaluation index system to assess the health status of sewage pipelines.

[0041] Based on real-time extracted hydraulic state evaluation index data and real-time updated non-hydraulic state evaluation index data, S42 calculates the health status score of any sewage pipeline within the monitoring area using the selected evaluation method.

[0042] According to some preferred embodiments of the present invention, S5 specifically includes:

[0043] S51 will match and store the real-time sewage pipeline health status score data obtained by the health assessment calculation unit with the distribution location of the sewage pipeline on the GIS map of the monitoring area;

[0044] S52 writes the correlated real-time health status score data into the sewage pipeline scoring data to record the historical health status score changes of each pipeline.

[0045] S53 regularly or in real time updates the GIS map of sewage pipes in the monitored area to show the current health status and potential problems of each sewage pipe.

[0046] S54 provides relevant departments with a visual display of the health status of sewage pipelines, facilitating real-time monitoring and decision-making, and improving the efficiency and effectiveness of sewage pipeline management.

[0047] According to some preferred embodiments of the present invention, S6 specifically includes:

[0048] S61 summarizes detailed information such as the health status, damage status, and flow rate of each sewage pipeline based on evaluation index data and dynamically updated scoring data;

[0049] S62 analyzes the development trend and existing problems of the health status of each sewage pipeline in order to identify and prevent potential risks in a timely manner;

[0050] Based on the analysis results, S63 proposes corresponding pipeline maintenance suggestions and risk prevention measures to help management departments formulate effective pipeline management strategies.

[0051] S64 integrates the analysis results, recommendations, and measures into a health assessment report for the wastewater pipeline system, so that management departments can review and refer to it;

[0052] S65 generates health assessment reports regularly or as needed to ensure that management is aware of the real-time health status and potential problems of the wastewater pipeline system.

[0053] The present invention further provides a dynamic health assessment system for sewage pipelines based on a hydraulic model that applies the above-mentioned evaluation method, which includes the basic database unit, data acquisition unit, hydraulic model calculation unit, health assessment calculation unit, dynamic update unit, and report generation unit.

[0054] The present invention has the following beneficial effects:

[0055] (1) Compared with traditional static health assessment methods, the evaluation method of the present invention can realize real-time monitoring of the health status of sewage pipelines, better reflect the changes and trends in the health status of sewage pipelines, and help to discover and prevent potential risks in a timely manner.

[0056] (2) The evaluation method of the present invention uses a hydraulic model for dynamic health assessment. The hydraulic model can use real-time collected monitoring data to simulate and calculate the pipeline system in real time, thereby more accurately reflecting the actual operating status of the pipeline system and improving the accuracy of the assessment.

[0057] (3) The evaluation system of the present invention can more comprehensively assess the health status of sewage pipelines, improve the efficiency and accuracy of management and maintenance, and provide strong support for urban sewage treatment and environmental protection. Attached Figure Description

[0058] Figure 1 This is a flowchart illustrating the construction of a dynamic health assessment system for urban sewage pipelines in an embodiment of the present invention;

[0059] Figure 2 This is a diagram illustrating the basic database unit in an embodiment of the present invention;

[0060] Figure 3 This is a diagram illustrating the data acquisition unit in an embodiment of the present invention;

[0061] Figure 4 This is a diagram illustrating the hydraulic model effect of the urban drainage network in an embodiment of the present invention.

[0062] Figure 5 This is a diagram showing the composition of the sewage pipeline evaluation index system in an embodiment of the present invention. Detailed Implementation

[0063] The present invention will now be described in detail with reference to embodiments and accompanying drawings. However, it should be understood that the embodiments and drawings are for illustrative purposes only and do not constitute any limitation on the scope of protection of the present invention. All reasonable modifications and combinations included within the inventive spirit of the present invention fall within the scope of protection of the present invention.

[0064] Example 1

[0065] See attached document Figure 1 According to the technical solution of the present invention, a dynamic health assessment system for sewage pipelines in a river basin of a certain city is established, including:

[0066] S1: Constructing the basic database unit

[0067] Specifically, this includes: mapping and storing the basic data of sewage pipes within the monitoring area obtained through collection and / or testing to their distribution locations on the GIS map of the monitoring area, thus obtaining a basic database unit integrated with the GIS system, as shown in the appendix. Figure 2 As shown.

[0068] The basic data of the sewage pipeline includes the geographical location of the sewage pipeline installation, material type, specifications, service life, maintenance records, operating parameters, historical monitoring data, and CCTV (Closed Circuit Television, central control industrial pipeline endoscopic camera) inspection data;

[0069] The specifications include pipe length and pipe diameter; operating parameters include flow rate, flow velocity, pipe pressure, and water level; historical monitoring data includes historical flow rate and historical water level; and CCTV inspection data includes the types and locations of structural and functional defects in the sewage pipeline.

[0070] Structural defects include corrosion, cracking, deformation, misalignment, disconnection, intrusion, and leakage; functional defects include mud accumulation, scale buildup, debris, puddles, blockage, and root penetration.

[0071] It also includes organizing the basic data before storing it, and the organizing includes data deduplication and invalid data removal.

[0072] In some specific embodiments, the underlying data is preferably stored in the shp format.

[0073] Through the above steps, this invention can comprehensively collect and organize various types of information related to sewage pipelines.

[0074] S2: Constructing the data acquisition unit

[0075] Specifically, it includes:

[0076] S21 uses data analysis methods to extract influencing factors, i.e., evaluation indicators, related to the health status of sewage pipelines from basic database units.

[0077] Based on the evaluation indicators, S22 extracts historical data of non-hydraulic state evaluation indicators from the basic database unit integrated with the GIS system. When the data information of the sewage pipeline evaluation indicators changes, relevant personnel need to complete the real-time entry and update of the non-hydraulic state evaluation indicator attribute information table.

[0078] S23 Determine the location of key monitoring points for sewage pipelines, install pipeline flow meters at key monitoring points, collect pipeline hydraulic state data at key monitoring points in real time, facilitate the calibration and verification of the hydraulic model calculation unit for the drainage network hydraulic model, and update the model input parameters;

[0079] S24, based on the evaluation indicators, the real-time recording and updating of non-hydraulic state indicators and the real-time collection of pipeline hydraulic state data from monitoring points together constitute a data acquisition unit.

[0080] Furthermore, in some specific embodiments, the data analysis methods used in S21 include statistical analysis methods, correlation analysis methods, and weighted evaluation methods based on expert knowledge and practical engineering experience. The statistical analysis methods include analyzing historical data in the basic database units to identify key factors affecting the health status of sewage pipelines. The correlation analysis methods include pairwise comparisons of the identified key factors to select the evaluation indicators most relevant to the health status of sewage pipelines. The weighted evaluation method based on expert knowledge and practical engineering experience includes determining a comprehensive evaluation index system for the health status of sewage pipelines by comprehensively considering the weights of each evaluation indicator based on expert knowledge and practical engineering experience. Combining the above analysis methods, an evaluation index system for the health status of sewage pipelines is determined.

[0081] Among them, the hydraulic status indicators of the pipeline include the flow rate, flow velocity, and water level.

[0082] In the above steps, the evaluation indicator data can be entered and updated in real time by relevant personnel. The resulting data collection unit is shown in the attached document. Figure 3 As shown.

[0083] S3: Construction of hydraulic model calculation units:

[0084] Specifically, it includes:

[0085] The basic data on sewage pipes and their distribution on the GIS map of the monitoring area, stored in the basic database unit built on S1, can be used to construct a hydraulic model of the urban drainage network based on the Storm Water Management Model (SWMM), as shown in the attached figure. Figure 4 As shown. The drainage network hydraulic model can simulate the hydraulic state of the sewage pipeline under dry weather conditions. The relevant input parameters include the population of the monitoring area, the per capita sewage quota, and the sewage time variation curve.

[0086] S32 uses the real-time pipeline hydraulic state index data of key monitoring points obtained by S2 to calibrate and verify the obtained urban drainage network hydraulic model, and obtains the verified drainage network hydraulic model.

[0087] S33 uses the flow data of the pipeline in the real-time pipeline hydraulic state index data of the key monitoring points obtained by S2 to deduce the input parameters of the drainage network hydraulic model in the monitoring area, and makes real-time parameter adjustments to obtain the dynamic drainage network hydraulic model.

[0088] S34 extracts pipeline hydraulic state index data at any location of a sewage pipeline within the monitoring area using the dynamic drainage network hydraulic model, obtaining key hydraulic state index data. This data, together with the non-hydraulic state index data entered in real time by the data acquisition unit, constitutes a sewage pipeline evaluation index system, as shown in the appendix. Figure 5As shown.

[0089] Preferably, step S33 further includes:

[0090] S331 preprocesses the real-time pipeline hydraulic status data collected from key monitoring points. The pipeline hydraulic status data is mainly pipeline flow data.

[0091] S332 performs data statistics on the pre-processed real-time pipeline hydraulic state data to obtain the model input parameters that need to be updated in real time, namely the per capita sewage quota.

[0092] S333 adjusts the parameters of the hydraulic model for the drainage network using data that needs to be updated in real time.

[0093] More specifically, the preprocessing includes one or more of the following: data cleaning, outlier detection and removal, and data interpolation. Data cleaning primarily aims to check and handle missing values, duplicate values, and inconsistent data. For example, when data contains missing values, records containing missing values ​​can be deleted, or methods such as mean, median, or previous value can be used to fill in the missing values. Outlier detection can be implemented using methods such as IQR and Z-score. Data interpolation is used to estimate missing values ​​and can employ linear interpolation, polynomial interpolation, spline interpolation, etc.

[0094] More specifically, the data statistics can use average flow rate, calculated based on sewage monitoring flow rate data over a recent period (e.g., the most recent hour or the most recent day), and then update the per capita sewage quota based on the population.

[0095] More specifically, the parameters of the drainage network hydraulic model can be adjusted through the following methods: modifying the parameters related to the dry flow sewage volume of the inspection well in the .inp file so as to adjust the model according to the real-time updated comprehensive sewage quota; calling the SWMM dynamic link library (DLL) to implement timed simulation, combined with programming languages ​​such as Python, C++ and timed task libraries; and periodically extracting the simulation results of key hydraulic state indicators from the model's .out file, including the real-time load status and flow velocity of the sewage pipeline.

[0096] In the above steps of this invention, the model accuracy of the urban pipe network model is calibrated and verified using actual monitoring data, and the input parameters of the drainage pipe network hydraulic model are dynamically updated based on the real-time collected key point flow monitoring data; finally, the evaluation index data of the key hydraulic states simulated by the model can be extracted in real time.

[0097] In the urban drainage network hydraulic model constructed based on SWMM (Storm Water Management Model), basic information of the existing sewage pipeline network (such as pipeline length, pipe diameter, flow direction, etc.) and GIS map data of the monitoring area are collected. This step can construct the drainage network hydraulic model of the embodiment based on the basic data of sewage pipelines stored in the basic database unit constructed in S1 and their distribution location on the GIS map of the monitoring area. The drainage network hydraulic model simulates the hydraulic state of sewage pipelines under dry weather conditions. The relevant input parameters include population, per capita sewage quota, and sewage flow rate curve. The population represents the population in the monitoring area, and the sewage flow rate curve describes the change of sewage flow over time. The per capita sewage quota is calculated in real time by statistically analyzing the total sewage flow over a certain period of time using pre-processed real-time monitoring data and combining it with the population. This is an input parameter that needs to be dynamically adjusted for the drainage network hydraulic model.

[0098] S4: Construction of the health assessment calculation unit:

[0099] Specifically, it includes:

[0100] Based on real-time simulated hydraulic conditions of sewage pipelines and a real-time database of sewage pipeline information, a suitable evaluation method is used to obtain a dynamic health status score for the sewage pipelines. Evaluation methods include, but are not limited to, the Analytic Hierarchy Process (AHP), entropy weight method, TOPSIS method, and fuzzy comprehensive evaluation, etc., and the appropriate method needs to be selected according to different evaluation objects and purposes. To more accurately assess the health status of sewage pipelines, for example, this embodiment uses fuzzy comprehensive evaluation (FCE) to determine the score, incorporating the fuzziness and uncertainty between multiple indicators into the evaluation process, and using the AHP to allocate the weights of each evaluation indicator. Then, considering the relative importance and scores of each indicator, the final score of the sewage pipeline health status is determined. Based on real-time hydraulic parameters of sewage pipelines and a real-time database of sewage pipeline parameter information, combined with the Python programming language, a Python environment is configured to use the ArcPy library for performing geographic information system tasks. ArcPy cursors can be used to traverse and manipulate the attribute tables of geographic feature classes. Corresponding programs can be written to periodically calculate the dynamic health score of the sewage pipelines.

[0101] The dynamic update unit is constructed by combining the programming language Python with ArcPy cursors to dynamically update the health score of each sewage pipe and write the data into the sewage pipe score data. This data is also matched and stored with the distribution location of the sewage pipes on the GIS map of the monitoring area. Furthermore, the health assessment data is visualized to provide decision-makers with intuitive data support and decision reference.

[0102] The report generation unit is constructed using the following method: based on dynamically updated scoring data and historical scoring data, the system generates a health assessment report for the sewage pipeline system, including detailed information such as the damage status and flow rate of each sewage pipeline, analyzes the development trend and existing problems of the pipeline health status, and proposes corresponding pipeline maintenance suggestions and risk prevention measures.

[0103] The above embodiments are merely preferred embodiments of the present invention, and the scope of protection of the present invention is not limited to the above embodiments. All technical solutions falling within the scope of the present invention's concept are within the scope of protection of the present invention. It should be noted that for those skilled in the art, improvements and modifications made without departing from the principles of the present invention should also be considered within the scope of protection of the present invention.

Claims

1. A method for dynamic health assessment of sewage pipelines based on a hydraulic model, characterized in that, It includes: S1 Constructs a basic database unit, including: matching and storing the basic data of sewage pipes in the monitoring area obtained by collection and / or testing with the distribution location of sewage pipes on the GIS map of the monitoring area, so as to obtain a basic database unit integrated with the GIS system; S2 Constructs a data acquisition unit, which can extract influencing factors, i.e. evaluation indicators, related to the health status of sewage pipelines from the basic database unit, and record the collected pipeline non-hydraulic state index data and pipeline hydraulic state index data of key monitoring points in real time. S3 constructs a hydraulic model calculation unit. This unit can establish an urban drainage network hydraulic model based on the stormwater management model (SWMM) using the basic data of sewage pipes stored in the basic database unit and their distribution on the GIS map of the monitoring area. The urban drainage network hydraulic model is calibrated and verified using the real-time pipe hydraulic status index data of key monitoring points obtained in S2, resulting in a verified drainage network hydraulic model. The input parameters of the verified drainage network hydraulic model are derived from the pipe flow data in the real-time pipe hydraulic status index data of key monitoring points obtained in S2, and the input parameters are adjusted in real time to obtain a dynamic drainage network hydraulic model. Furthermore, the hydraulic status index data of any sewage pipe location within the monitoring area is extracted from the dynamic drainage network hydraulic model, i.e., the key hydraulic status index data. The key hydraulic status index data and the real-time non-hydraulic status index data obtained in S2 together constitute a comprehensive evaluation index system for the health status of sewage pipes. S4 Construct a health assessment calculation unit. The health assessment calculation unit can score the health status of any sewage pipe in the monitoring area in real time based on the comprehensive evaluation index system of the health status of the sewage pipe, and obtain the dynamic score of the health status of any sewage pipe. S5 Construct a dynamic update unit, which can update and store the dynamic score obtained by the health assessment calculation unit in real time and correspond it with the distribution location of sewage pipes on the GIS map of the monitoring area; S6 Construct a report generation unit, which can generate a health assessment report of the sewage pipeline system based on the dynamic score stored in the dynamic update unit and its historical data; Specifically, S3 describes real-time adjustment of the input parameters, which includes: S331 preprocesses the real-time pipeline hydraulic status index data collected from key monitoring points; S332 performs data statistics on the pre-processed real-time pipeline hydraulic state index data to obtain the model input parameters that need to be updated in real time, namely the per capita sewage quota. S333 Adjusts the model parameters of the verified drainage network hydraulic model using data that needs to be updated in real time; The preprocessing includes one or more of the following: data cleaning, outlier detection and removal, and data interpolation.

2. The evaluation method according to claim 1, characterized in that, The basic data of the sewage pipeline includes: the geographical location of the sewage pipeline installation, material type, specifications, service life, maintenance records, operating parameters, historical monitoring data, and CCTV inspection data; wherein, the specifications include pipe length and pipe diameter; the operating parameters include flow rate, flow velocity, pressure, and water level within the pipeline; the historical monitoring data includes the historical flow rate and historical water level of the pipeline; the CCTV inspection data includes the types of structural and functional defects of the sewage pipeline and the location of the defect distribution; wherein, the types of structural defects include one or more of corrosion, cracking, deformation, misalignment, disconnection, intrusion, and leakage; the types of functional defects include one or more of sludge accumulation, scaling, debris, puddles, blockage, and tree root penetration.

3. The evaluation method according to claim 1, characterized in that, Step S1 also includes organizing the basic data of the sewage pipeline before storing it. The organizing includes data deduplication and invalid data removal.

4. The evaluation method according to claim 1, characterized in that, S2 specifically includes: S21 uses data analysis methods to extract some of the most relevant influencing factors, i.e., evaluation indicators, from the basic database units to form a comprehensive evaluation indicator system for the health status of sewage pipelines. S22 divides the evaluation indicators in the comprehensive evaluation index system into pipeline hydraulic state indicators and other non-hydraulic state indicators; S23 Determine the location of key monitoring points in the sewage pipeline, install pipeline flow meters at the key monitoring points, and collect pipeline hydraulic status data at the key monitoring points in real time; S24 Real-time updates and input of the non-hydraulic state index data and the pipeline hydraulic state data of the key monitoring points, which together constitute the data acquisition unit; The hydraulic state indicators of the pipeline include the flow rate, flow velocity, and water level.

5. The evaluation method according to claim 4, characterized in that, The data analysis methods include statistical analysis, correlation analysis, and a weighted evaluation method based on expert knowledge and practical engineering experience. The statistical analysis method involves performing statistical analysis on basic data in the basic database units to identify data types affecting the health status of sewage pipelines, i.e., key factors. The correlation analysis method involves comparing each identified key factor pairwise to select the evaluation indicators most relevant to the health status of sewage pipelines. The weighted evaluation method based on expert knowledge and practical engineering experience involves comprehensively considering the weights of the obtained evaluation indicators based on expert knowledge and practical engineering experience, arranging the evaluation indicators according to their weights to form a comprehensive evaluation indicator system for the health status of sewage pipelines.

6. The evaluation method according to claim 1, characterized in that, In step S4, the real-time scoring is achieved through one or more of the following methods: hierarchical analysis, fuzzy comprehensive evaluation, and grey relational analysis.

7. A dynamic health assessment system for sewage pipelines based on a hydraulic model, employing the evaluation method described in any one of claims 1-6, characterized in that, It includes the basic database unit, data acquisition unit, hydraulic model calculation unit, health assessment calculation unit, dynamic update unit, and report generation unit.

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