Inflow and seepage checking method and system for drainage pipe network

Abstract

The invention provides a drainage pipe network inflow and seepage checking method and system. The method comprises the steps that an initial rainfall data set in a monitoring area is acquired; based on a preset rainfall standard, screening the initial rainfall data set, and determining a candidate rainfall data set; determining a rainfall influence index of each piece of candidate rainfall data in the candidate rainfall data set; based on the rainfall influence index of each piece of candidate rainfall data, screening the candidate rainfall data set, and determining target rainfall data; and obtaining monitoring data in the drainage pipe network in the same period as the target rainfall data, and carrying out inflow and infiltration checking on the drainage pipe network based on the monitoring data. According to the scheme disclosed by the invention, the inflow and infiltration problems of the drainage pipe network can be accurately checked.

Description

Technical Field

[0001] The present disclosure relates to the technical field of urban drainage management and water environment engineering, and particularly to a method and system for detecting inflow and infiltration in a drainage pipe network. Background Art

[0002] The urban drainage system is a giant grid system deeply buried underground with a complex structure, and it is difficult to visually monitor due to its concealment. Defects in the sewage pipe network, such as misconnected joints and pipe network damage, will cause rainwater to flow in during rainfall, resulting in a sharp increase in the water volume of the sewage pipe network, affecting the efficiency of sewage collection and treatment, and in severe cases, it will also cause overflow pollution and waterlogging disasters. When diagnosing the problem of rainfall inflow and infiltration in the drainage pipe network in the prior art, only based on the quantitative calculation results of inflow and infiltration, lacking in-depth analysis and comprehensive consideration of the actual situation of the pipe network, resulting in the lack of pertinence and scientific nature of relevant maintenance and management strategies. Summary of the Invention

[0003] The present disclosure provides a method and system for detecting inflow and infiltration in a drainage pipe network to at least solve the above technical problems existing in the prior art.

[0004] According to a first aspect of the present disclosure, there is provided a method for detecting inflow and infiltration in a drainage pipe network, the method comprising:

[0005] Obtaining an initial rainfall data set within a monitoring area;

[0006] Based on a preset rainfall standard, screening the initial rainfall data set to determine a candidate rainfall data set;

[0007] Determining rainfall impact indicators for each candidate rainfall data in the candidate rainfall data set;

[0008] Based on the rainfall impact indicators of each candidate rainfall data, screening the candidate rainfall data set to determine target rainfall data;

[0009] Obtaining monitoring data within the drainage pipe network that is contemporaneous with the target rainfall data, and detecting inflow and infiltration in the drainage pipe network based on the monitoring data.

[0010] In an implementable embodiment, the monitoring data includes flow data at multiple flow monitoring points within the drainage pipe network; correspondingly,

[0011] The detecting inflow and infiltration in the drainage pipe network based on the monitoring data includes:

[0012] Based on the flow data at each flow monitoring point, determining its rainfall inflow and infiltration value;

[0013] Determining the monitoring points with rainfall inflow and infiltration values greater than a preset threshold as key detection points.

[0014] In an implementable embodiment, the rainfall inflow and infiltration value of each flow monitoring point is determined according to the following formula:

[0015]

[0016] wherein, RDII represents the rainfall inflow and infiltration value; R0 represents the cumulative rainfall of the current day; Q t represents the flow data at time t of the current day; QH t represents the flow data at time t of the previous day; n is the total number of flow data of the current day.

[0017] In an implementable embodiment, the rainfall influence index of each candidate rainfall data in the candidate rainfall data set is determined according to the following formula:

[0018]

[0019] wherein, P represents the rainfall influence index; a represents the rainfall amount weight coefficient, and its value range is between 0.1 and 0.9; b represents the rainfall duration weight coefficient, and its value range is between 0.1 and 0.9, and the values of a and b need to satisfy a + b = 1; RR represents the preset rainfall amount; TT represents the preset rainfall duration; R0 represents the cumulative rainfall of the current day; R1 represents the cumulative rainfall of the previous rainfall day; R2 represents the cumulative rainfall of the rainfall day before the previous rainfall day; H0 represents the number of dry days before the current day; H1 represents the number of dry days before the previous rainfall day; C represents the rainfall amount change coefficient of the current day; T represents the rainfall duration of the current day; q represents the rainfall intensity of the current day.

[0020] In an implementable embodiment, the initial rainfall data includes the cumulative rainfall of the current day; correspondingly,

[0021] screening the initial rainfall data set based on the preset rainfall standard to determine the candidate rainfall data set, including:

[0022] Determining the initial rainfall data with the cumulative rainfall of the current day in the initial rainfall data set greater than the preset rainfall standard as the candidate rainfall data set.

[0023] In an implementable embodiment, the method further includes:

[0024] Using a geographic information system to determine the rainfall monitoring points in the monitoring area and the flow monitoring points in the drainage pipes;

[0025] Obtaining the minute-level rainfall data through the rain gauges at the rainfall monitoring points;

[0026] Obtaining the minute-level flow data through the flow meters at the flow monitoring points.

[0027] In one implementable manner, obtaining the initial rainfall data set within the monitoring area includes:

[0028] Based on the minute-level rainfall data, obtaining the initial rainfall data set.

[0029] Obtaining the monitoring data within the drainage pipe network that is contemporaneous with the target rainfall data includes:

[0030] Based on the minute-level flow data, obtaining the monitoring data.

[0031] In one implementable manner, screening the candidate rainfall data set based on the rainfall impact index of each candidate rainfall data to determine the target rainfall data includes:

[0032] Sorting the rainfall impact indexes of each candidate rainfall data from small to large;

[0033] Determining the candidate rainfall data corresponding to the preset number of rainfall impact indexes with the top rankings as the target rainfall data.

[0034] In one implementable manner, the method further includes:

[0035] Based on the influence of rainfall factors on rainfall inflow and infiltration, determining the numerical values of the rainfall amount weight coefficient and the rainfall duration weight coefficient.

[0036] According to the second aspect of the present disclosure, a drainage pipe network inflow and infiltration inspection system is provided, and the system includes:

[0037] A data acquisition module, configured to acquire an initial rainfall data set within a monitoring area;

[0038] A data processing module, configured to screen the initial rainfall data set based on a preset rainfall standard to determine a candidate rainfall data set;

[0039] The data processing module is further configured to determine the rainfall impact index of each candidate rainfall data in the candidate rainfall data set;

[0040] The data processing module is further configured to screen the candidate rainfall data set based on the rainfall impact index of each candidate rainfall data to determine the target rainfall data;

[0041] The data processing module is further configured to acquire the monitoring data within the drainage pipe network that is contemporaneous with the target rainfall data, and perform an inflow and infiltration inspection on the drainage pipe network based on the monitoring data.

[0042] According to the third aspect of the present disclosure, an electronic device is provided, including:

[0043] At least one processor; and

[0044] A memory communicatively connected to the at least one processor; wherein,

[0045] The memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor to enable the at least one processor to execute the method described in the present disclosure.

[0046] According to a fourth aspect of the present disclosure, there is provided a non-transitory computer-readable storage medium storing computer instructions for causing a computer to execute the method described in the present disclosure.

[0047] The method and system for detecting inflow and infiltration in a drainage pipe network according to the present disclosure screen rainfall events by considering multiple key indicators in rainfall data, thereby determining representative target rainfall data. Further, by combining the monitoring data in the drainage pipe network, accurate positioning of problem pipe sections is achieved. This method not only improves the management efficiency of drainage pipes, but also significantly improves their operating level, providing strong support for the optimization and maintenance of the drainage system.

[0048] It should be understood that the content described in this part is not intended to identify the key or important features of the embodiments of the present disclosure, nor is it used to limit the scope of the present disclosure. Other features of the present disclosure will become easily understood through the following description. BRIEF DESCRIPTION OF THE DRAWINGS

[0049] By referring to the accompanying drawings and reading the following detailed description, the above and other objects, features, and advantages of the exemplary embodiments of the present disclosure will become readily understandable. In the drawings, several embodiments of the present disclosure are shown in an exemplary and non-limiting manner, wherein:

[0050] In the drawings, the same or corresponding reference numerals indicate the same or corresponding parts.

[0051] Figure 1 Shows a schematic flow chart of the implementation of the method for detecting inflow and infiltration in a drainage pipe network according to an embodiment of the present disclosure;

[0052] Figure 2 Shows the schematic composition structure of the system for detecting inflow and infiltration in a drainage pipe network according to an embodiment of the present disclosure Figure 1 ;

[0053] Figure 3 Shows the schematic composition structure of the system for detecting inflow and infiltration in a drainage pipe network according to an embodiment of the present disclosure Figure 2 ;

[0054] Figure 4 Shows a schematic diagram of the inflow and infiltration analysis under the target rainfall data according to an embodiment of the present disclosure;

[0055] Figure 5 The figure shows a schematic diagram of the composition structure of an electronic device according to an embodiment of the present disclosure. Detailed implementation manners

[0056] To make the objectives, features, and advantages of the present disclosure more obvious and understandable, the technical solutions in the embodiments of the present disclosure will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present disclosure. Obviously, the described embodiments are only a part of the embodiments of the present disclosure, rather than all the embodiments. Based on the embodiments in the present disclosure, all other embodiments obtained by those skilled in the art without creative efforts belong to the scope of protection of the present disclosure.

[0057] According to the first aspect of the embodiments of the present disclosure, a method for investigating inflow and infiltration in a drainage pipe network is provided. As Figure 1 shown, the method includes the following steps:

[0058] Step 101: Obtain an initial rainfall data set within a monitoring area.

[0059] In a monitoring area where a drainage pipe network is laid underground, rainfall data is first collected through monitoring devices such as rain gauges. These devices continuously record rainfall conditions during the monitoring period to ensure the comprehensiveness and continuity of the data. The collected rainfall data is processed to form an initial rainfall data set. In an implementable manner, to ensure the representativeness of the data, the monitoring period needs to include at least 7 days of dry-day records and at least three rainfall events with a rainfall amount exceeding 10 mm to eliminate the influence of accidental factors on subsequent calculations.

[0060] Step 102: Based on a preset rainfall standard, screen the initial rainfall data set to determine a candidate rainfall data set.

[0061] The preset rainfall standard refers to a pre-set rainfall screening standard, such as a rainfall amount reaching 10 mm within 2 hours. Based on the preset rainfall standard, the initial rainfall data set is preliminarily screened. The aim is to screen out typical rainfall events that meet specific conditions from a large amount of rainfall data to form a candidate rainfall data set. This ensures that the screened rainfall data is representative and valuable for analysis.

[0062] Step 103: Determine the rainfall impact index for each candidate rainfall data in the candidate rainfall data set.

[0063] The rainfall impact index is the comprehensive evaluation result in terms of the matching degree of rainfall amount, rainfall duration, and rainfall intensity and total amount in the rainfall data. Specifically, the differences between the rainfall amount in the rainfall data and the preset rainfall amount, the rainfall duration and the preset rainfall duration, and the rainfall intensity on the current day and the total rainfall amount are respectively determined. The comprehensive evaluation result of these three parts is the rainfall impact index.

[0064] Step 104: Screen the candidate rainfall data set based on the rainfall impact index of each candidate rainfall data to determine the target rainfall data.

[0065] Based on the rainfall impact index of each candidate rainfall data, further screen the rainfall data in the candidate rainfall data set, and screen out the rainfall data with smaller rainfall impact index data, which is determined as more typical and representative rainfall data and used as the target rainfall data.

[0066] Step 105: Obtain the monitoring data in the drainage pipe network during the same period as the target rainfall data, and conduct an inflow and infiltration inspection of the drainage pipe network based on the monitoring data.

[0067] After determining the target rainfall data, collect the monitoring data in the drainage pipe network during the same period as the target rainfall data from the flow measurement devices in the drainage pipe network. These data include the flow data of multiple monitoring points in the drainage pipe network. Based on these monitoring data, calculate the rainfall inflow and infiltration value (such as RDII value) of each monitoring point. Then, based on the rainfall inflow and infiltration value, determine the pipe section where the key inspection points are located. In an implementable embodiment, after the calculation is completed, the calculation results are displayed through a data visualization interface, enabling the management personnel to intuitively understand the rainfall situation and its impact on the drainage system. Using the Geographic Information System (GIS) to visually display the analysis results on the map can accurately identify the high-risk areas and problem-prone areas of rainfall inflow and infiltration. Based on these identification results, relevant personnel can carry out the corresponding fine inspection work of the drainage pipe network, and propose a rectification plan according to the actual situation of the drainage pipe network and the quantitative calculation results of rainfall inflow and infiltration, so as to improve the operation efficiency and level of the drainage pipe network.

[0068] The method for inspecting the inflow and infiltration of the drainage pipe network in this embodiment screens the rainfall events by considering multiple key indicators in the rainfall data, so as to determine the representative target rainfall data. Further, combined with the flow information in the drainage pipe network, the accurate positioning of the problem pipe section is realized. This method not only improves the management efficiency of the drainage pipes, but also significantly improves its operation level, providing strong support for the optimization and maintenance of the drainage system.

[0069] In an embodiment of the present disclosure, the method further includes: using the Geographic Information System to determine the rainfall monitoring points in the monitoring area and the flow monitoring points in the drainage pipes; obtaining the minute-level rainfall data through the rain gauges at the rainfall monitoring points; and obtaining the minute-level flow data through the flow meters at the flow monitoring points.

[0070] First, use GIS (Geographic Information System) to determine the rainfall monitoring points within the monitoring area and the flow monitoring points within the drainage pipes. Specifically, considering factors such as urban terrain features, building density, and historical rainfall records, layout through GIS technology to ensure uniform and targeted deployment of rain gauges within the monitoring area. For high-risk areas such as areas prone to waterlogging, low-lying areas, and around large public facilities, increase the deployment density of rain gauges to comprehensively cover these key areas and ensure the representativeness of rainfall data. In this embodiment, equipment with high precision and automatic calibration functions is preferably selected. It can not only provide accurate rainfall data but also automatically calibrate to ensure the long-term stability and reliability of the data. At the same time, the rain gauge can also be combined with Internet of Things technology to achieve real-time data upload.

[0071] Similarly, use GIS technology to locate key nodes such as the main pipes in the drainage pipe network, the inlet and outlet of pump stations, and large intersections, and set them as flow monitoring points. Ensure that at least one monitoring point is equipped for every kilometer of the main pipe, and appropriately add more according to the importance and actual situation of the key nodes to achieve comprehensive and accurate monitoring of the pipe network flow. In this embodiment, non-contact ultrasonic flow meters or electromagnetic flow meters and other high-precision equipment are preferably selected as the flow meters to ensure stable operation even in bad weather, and accurately record and transmit flow data.

[0072] Then, through the previously deployed rain gauges and flow meters, minute-level rainfall data and minute-level flow data are obtained respectively. Among them, the minute-level rainfall data refers to the rainfall per minute in a day, and the minute-level flow data refers to the flow per minute in a day.

[0073] Hereinafter, taking the tipping bucket rain gauge as an example, the acquisition of minute-level rainfall data will be described in detail. Within each minute, the rain gauge detects the number of times the tipping bucket flips. If the number of flips is 0, it means there is no effective rainfall in that minute, and at this time, the device will not send data to save battery power and communication costs. When the number of detected flips is greater than 0, the device will send the accumulated number of flips in the previous minute to the data processing module. After receiving this data, the data processing module calculates the rainfall in millimeters for that minute based on the number of flips and the rainfall in millimeters corresponding to each flip (determined according to the specific model and specifications of the rain gauge), and obtains the minute-level rainfall data.

[0074] Taking a Doppler flowmeter as an example, the acquisition of minute-level flow data is described in detail. The Doppler flowmeter is also connected to the data processing module through a wireless network (such as 4G / 5G, LoRa, NB-IoT, etc.), and can collect data on parameters such as liquid level, flow velocity, and flow rate in real time. The Doppler flowmeter collects these data every minute to obtain minute-level flow data, and packs and uploads them to the data processing module every preset time (such as 15 minutes). This can not only ensure the real-time nature of the data, but also reduce the communication frequency and extend the service life of the device battery.

[0075] In an embodiment of the present disclosure, the obtaining of the initial rainfall data set in the monitoring area includes: obtaining the initial rainfall data set based on the minute-level rainfall data.

[0076] At a specific time of each day (such as 2:00 am), the data processing module automatically aggregates and processes the minute-level rainfall data of the previous day to obtain data such as cumulative rainfall, rainfall duration, rainfall intensity, rainfall variation coefficient, and number of dry days. These data together constitute the initial rainfall data of a rainfall. The initial rainfall data of all rainfall events within the monitoring period are combined to form an initial rainfall data set.

[0077] The specific obtaining method is as follows:

[0078] Cumulative rainfall: Add up the millimeters of all minute-level rainfall data recorded on the previous day to obtain the cumulative rainfall. Rainfall duration: Determine whether the millimeters of the minute-level rainfall data recorded on the previous day are greater than the minimum threshold of minute rainfall. When it is greater than the threshold, the counter is incremented by one, and the total number of the finally obtained counter is divided by 60 to obtain the rainfall duration. Among them, the minimum threshold of minute rainfall is set to prevent the calculation value of rainfall duration from being too large caused by small deviations in rainfall data due to equipment failures or on-site working conditions. The value of the minimum threshold of minute rainfall can be set according to actual needs, such as 0.1 - 0.3 millimeters. Rainfall intensity: Divide the cumulative rainfall by the rainfall duration to obtain the rainfall intensity. The existing method for determining rainfall intensity is usually to divide the cumulative rainfall by 24 hours or the duration hours from the start to the end of rainfall. This method will include a large number of non-rainfall minute times in the calculation. On the one hand, it will result in a small rainfall intensity value, and on the other hand, it cannot reflect the difference in rainfall duration when comparing different rainfall events, which is not conducive to the screening of typical rainfall. Rainfall variation coefficient: The rainfall variation coefficient is an index reflecting the speed of intensity change during rainfall. It can be obtained by dividing the standard deviation of the millimeters of the minute-level rainfall recorded on the previous day by the cumulative rainfall. The specific calculation formula is CV = σ / R - , where CV is the rainfall variation coefficient, σ is the standard deviation of rainfall, and R -is the cumulative rainfall. Number of dry days: The number of dry days is the number of consecutive days without rain before this rainfall event. Starting from the previous day, compare the rainfall with the set minimum daily rainfall threshold day by day. When the cumulative rainfall of the current day is less than or equal to the threshold, the counter is incremented; otherwise, the counting stops and the total count of the counter is recorded, which is the number of dry days. Among them, setting the minimum daily rainfall threshold is to include the number of days with minor rainfall that does not affect the operation of the sewage system in the calculation of the number of dry days. When the rainfall is small, there will be no rainfall infiltration phenomenon, and minor rainfall does not affect the sewage pipe network system. This value can be determined according to the situation, such as 1 - 3 millimeters. In addition, it can also be obtained by querying historical meteorological data.

[0079] Compared with the existing data recording method that only records a single rainfall amount, in this embodiment, by obtaining multi-dimensional rainfall characteristic data, such as cumulative rainfall, rainfall duration, rainfall intensity, rainfall variation coefficient, and number of dry days, etc., it can more comprehensively and effectively describe the rainfall characteristics, providing richer and more multi-dimensional basic data support for identifying typical rainfall events.

[0080] In an embodiment of the present disclosure, obtaining the monitoring data in the drainage pipe network that is contemporaneous with the target rainfall data includes: obtaining the monitoring data based on the minute-level flow data.

[0081] At a specific time every day (such as 0:00 midnight), the data processing module automatically aggregates and processes the minute-level flow data of the previous day to generate a series of key flow indicators, such as daily total flow and daily average flow, and uses these key flow indicators as the monitoring data.

[0082] The specific obtaining method is as follows:

[0083] Effective flow duration: Check whether the flow data per minute exceeds the preset minimum flow threshold. Whenever it exceeds this threshold, the counter is incremented. Finally, convert the total value of the counter to hours to obtain the effective flow duration. The minimum flow threshold is used to remove minor flow fluctuations caused by equipment accuracy or environmental factors, and its value range can be adjusted between 0.01 - 0.1 cubic meters per hour according to actual needs. Daily total flow: Accumulate the flow data per minute of the previous day. Average flow: Obtain it by dividing the daily total flow by the effective flow duration. Compared with the traditional method of simply dividing the daily total flow by 24 hours, this method can more accurately reflect the actual situation of fluid flow and the characteristics of flow changes.

[0084] On the basis of retaining minute-level flow data, this embodiment also obtains multi-dimensional information such as daily total flow, effective flow duration, and average flow, providing strong data support for comprehensively and accurately describing the flow characteristics of the drainage network. It not only deepens the understanding of the flow change pattern of the drainage network but also helps to identify typical flow events, providing more detailed and multi-dimensional data support for the point flow conditions in the inflow and infiltration monitoring of the drainage network.

[0085] In one embodiment of the present disclosure, the initial rainfall data includes the cumulative rainfall of the day; correspondingly, screening the initial rainfall data set based on a preset rainfall standard to determine a candidate rainfall data set includes: determining the initial rainfall data with the cumulative rainfall of the day greater than the preset rainfall standard in the initial rainfall data set as the candidate rainfall data set.

[0086] The preset rainfall standard refers to a pre-set rainfall screening standard. For example, it is required that the daily cumulative rainfall is within ±20% of a certain specific rainfall (such as 10 mm of rainfall in 2 hours). Then, the initial rainfall data with the daily cumulative rainfall meeting the preset rainfall standard is used as the candidate rainfall data set.

[0087] In one embodiment of the present disclosure, the rainfall impact index P of each candidate rainfall data can be calculated according to the following formula (1):

[0088]

[0089] Among them, P represents the rainfall impact index; a represents the rainfall amount weight coefficient, and its value range is from 0.1 to 0.9; b represents the rainfall duration weight coefficient, and its value range is from 0.1 to 0.9, and the values of a and b need to satisfy a + b = 1; RR represents the preset rainfall amount (mm); TT represents the preset rainfall duration (hours); R0 represents the cumulative rainfall of the day (mm); R1 represents the cumulative rainfall of the previous rainfall day; R2 represents the cumulative rainfall of the rainfall day before the previous rainfall day; H0 represents the number of dry days before the day; H1 represents the number of dry days before the previous rainfall day; C represents the rainfall change coefficient of the day; T represents the rainfall duration of the day (hours); q represents the rainfall intensity of the day (mm / hour). In an implementable manner, the values of the rainfall amount weight coefficient a and the rainfall duration weight coefficient b can be determined based on the influence of rainfall factors on rainfall inflow and infiltration. Rainfall factors include total rainfall, dry period, rainfall peak, and rainfall duration, etc. For example, the analytic hierarchy process can be used. If the inflow and infiltration analysis pays more attention to the influence of total amount and dry period, a higher value can be assigned to the rainfall amount weight coefficient a. If the inflow and infiltration analysis pays more attention to the peak or duration influence, a higher value can be assigned to the rainfall duration weight coefficient b.

[0090] In one embodiment of the present disclosure, after determining the rainfall impact index P for each candidate rainfall data, the rainfall impact indices P are sorted from small to large. And a preset number of candidate rainfall data corresponding to the smaller rainfall impact indices P are selected as the target rainfall data. The preset number can be set according to the actual situation. For example, if it is set to 1, the candidate rainfall data with the smallest P value is selected as the target rainfall data.

[0091] In this embodiment, when screening typical rainfall events (i.e., target rainfall data), not only the current rainfall event is concerned, but also the impacts of the previous and the penultimate rainfall are comprehensively considered. In the case of continuous rainfall, the previous rainfall will have a significant impact on the inflow and infiltration conditions of the current rainfall, thus affecting the accuracy and representativeness of the analysis results. On the contrary, if the number of dry days before the current rainfall is long, its impact on the current calculation results is small. The calculation method of this embodiment considers a variety of key data, including rainfall intensity, rainfall amount variation coefficient, and the number of dry days, etc., making the process of screening typical rainfall events more scientific and effective. In addition, this method also considers the severity of the intensity change during the rainfall process and the impact of recent continuous rainfall on inflow and infiltration, and introduces a weight distribution mechanism, which can flexibly adjust the screening weights of rainfall amount and rainfall duration according to management requirements.

[0092] In one embodiment of the present disclosure, the monitoring data includes the flow data of multiple flow monitoring points in the drainage pipe network; correspondingly, the inflow and infiltration investigation of the drainage pipe network based on the monitoring data includes: determining the rainfall inflow and infiltration value of each flow monitoring point based on the flow data of each flow monitoring point; and determining the monitoring points with the rainfall inflow and infiltration value greater than the preset threshold as the key investigation points.

[0093] In one embodiment of the present disclosure, the rainfall inflow and infiltration value of each flow monitoring point corresponding to the target rainfall data can be determined by the following formula (2):

[0094]

[0095] wherein, RDII represents the rainfall inflow and infiltration value; R0 represents the cumulative rainfall amount (millimeters) of the current day; Q t represents the flow data (cubic meters per day) at time t of the current day; QH t represents the flow data (cubic meters per day) at time t of the previous day, and n is the total number of daily flow data, generally 1440.

[0096] After obtaining the rainfall inflow and infiltration value of each monitoring point, the monitoring points with the rainfall inflow and infiltration value greater than the preset threshold can be determined as the key investigation points. Then, corresponding fine investigation work on the pipe sections where the key investigation points are located is carried out for the drainage pipe network to improve the investigation efficiency.

[0097] For a better understanding of the above embodiments, a specific implementation manner is provided below for illustration:

[0098] Taking the drainage pipe network in the central area of a certain city as an example, this area has frequent rainfall and large rainfall amounts, and the drainage pipe network faces a relatively large pressure of inflow and infiltration.

[0099] First, rain gauges are evenly and specifically arranged in this area. Flow meters are arranged at 5 main nodes of the drainage pipe network in this area. The data obtained by the rain gauges and flow meters are transmitted to the data processing module through the data communication network.

[0100] Based on the data of 8 rainfall events recorded by the rain gauges within the monitoring period, the initial rainfall data set obtained is shown in Table 1 below:

[0101] Table 1

[0102]

[0103] Based on the data collected by the flow meters in the drainage pipe network, the monitoring data obtained is shown in Table 2 below:

[0104] Table 2

[0105]

[0106] The preset rainfall standard is set to 12 mm ± 20% (9.6 mm - 14.4 mm) of rainfall within 2 hours. The data that meet the preset rainfall standard are screened out, including the third rainfall event, the fourth rainfall event, and the fifth rainfall event. The data of these three rainfall events are determined as the candidate rainfall data set.

[0107] The following information for each rainfall event in the candidate rainfall data set is determined, as shown in Table 3:

[0108] Table 3

[0109]

[0110]

[0111] According to the above formula (1), the rainfall impact index P corresponding to each rainfall event is determined, and the data shown in Table 4 below is obtained:

[0112] Table 4

[0113]

[0114] As can be obtained from Table 4, the rainfall of the third rainfall event is P = 0.83, the rainfall of the fourth rainfall event is P = 1.23, and the rainfall of the fifth rainfall event is P = 0.70. Sort the values of P from small to large. It can be seen that the fifth rainfall event is the closest to the preset rainfall requirement. Therefore, the fifth rainfall event is selected as the screened rainfall event. The rainfall data corresponding to the fifth rainfall event is the target rainfall data.

[0115] Retrieve the Doppler flow data of 5 monitoring points in the drainage pipe network during the same period as the fifth rainfall event. For each flow monitoring point, calculate the RDII value corresponding to rainfall inflow and infiltration through the above formula (2). The calculation results are shown in Table 5 below:

[0116] Table 5

[0117]

[0118] According to the RDII values of each monitoring point, sort the degree of rainfall inflow and infiltration during rainfall for each pipe section. From largest to smallest, they are monitoring point 3, monitoring point 4, monitoring point 5, monitoring point 2, and monitoring point 1. This shows that the rainfall inflow and infiltration rates at monitoring point 3 and monitoring point 4 are relatively large during rainfall. Therefore, tools such as GIS should be used to accurately locate the pipe sections where monitoring point 3 and monitoring point 4 are located first. And carry out corresponding detailed inspections of the drainage pipe network to accurately identify problem areas. Then, according to the actual situation of the drainage pipe network and the quantitative calculation results of rainfall inflow and infiltration at monitoring points 3 and 4, propose a pipe network renovation plan to improve the operation efficiency and level of the drainage pipe network.

[0119] According to the second aspect of the embodiments of the present disclosure, a drainage pipe network inflow and infiltration inspection system is provided, as Figure 2 shown. The system includes:

[0120] A data acquisition module 201 for acquiring an initial rainfall data set within a monitoring area;

[0121] A data processing module 202 for screening the initial rainfall data set based on a preset rainfall standard to determine a candidate rainfall data set;

[0122] The data processing module 202 is further configured to determine a rainfall impact index for each candidate rainfall data in the candidate rainfall data set;

[0123] The data processing module 202 is further configured to screen the candidate rainfall data set based on the rainfall impact index of each candidate rainfall data to determine target rainfall data;

[0124] The data processing module 202 is further configured to acquire monitoring data in the drainage pipe network during the same period as the target rainfall data, and perform an inflow and infiltration inspection on the drainage pipe network based on the monitoring data.

[0125] In one embodiment of the present disclosure, the monitoring data includes flow rate data of multiple flow rate monitoring points in the drainage pipe network; correspondingly, the data processing module 202 is further configured to determine respective rainfall inflow and infiltration values based on the flow rate data of each monitoring point; and determine the monitoring points with rainfall inflow and infiltration values greater than a preset threshold as key investigation points.

[0126] In one embodiment of the present disclosure, the data processing module 202 is further configured to determine the inflow and infiltration value of each monitoring point according to the following formula:

[0127]

[0128] wherein, RDII represents the rainfall inflow and infiltration value; R0 represents the cumulative rainfall of the current day; Q t represents the flow rate data at time t of the current day; QH t represents the flow rate data at time t of the previous day; and n is the total number of flow rate data of the current day.

[0129] In one embodiment of the present disclosure, the initial rainfall data includes the cumulative rainfall of the current day; correspondingly, the data processing module 202 is further configured to determine the combination of the initial rainfall data with the cumulative rainfall of the current day in the initial rainfall data set greater than the preset rainfall standard as the candidate rainfall data set.

[0130] In one embodiment of the present disclosure, the data acquisition module 201 is further configured to use a geographic information system to determine the rainfall monitoring points in the monitoring area and the flow rate monitoring points in the drainage pipes; obtain minute-level rainfall data through the rain gauges at the rainfall monitoring points; and obtain minute-level flow rate data through the flow meters at the flow rate monitoring points.

[0131] In one embodiment of the present disclosure, the data acquisition module 201 is further configured to obtain the initial rainfall data set based on the minute-level rainfall data. And obtain the monitoring data based on the minute-level flow rate data.

[0132] The following provides a specific composition structure of a drainage pipe network inflow and infiltration investigation system, as Figure 3 shown. The system includes a data acquisition module 201 and a data processing module 202. Among them, the data acquisition module 201 includes a monitoring network construction module 2011 and a data collection and recording module 2012, and the data processing module 202 includes an index calculation and intelligent identification module 2021 and a result output and feedback module 2022.

[0133] Among them, the monitoring network construction module 2011 includes an intelligent rain gauge monitoring network construction module and an intelligent flowmeter monitoring network construction module (not shown in the figure). The intelligent rain gauge monitoring network is used to determine the deployment points of rain gauges in the monitoring area by combining factors such as terrain, climate, and rainfall frequency. The intelligent flowmeter monitoring network construction module is used to determine the deployment points of flowmeters in the drainage pipe network.

[0134] The data acquisition and recording module 2012 includes a rainfall data acquisition and recording module and a drainage pipe network flow data acquisition and recording module (not shown in the figure). The rainfall data acquisition and recording module is connected to the rain gauge through a wireless network, real-time collects rainfall data, and forms minute-level rainfall data. The drainage pipe network flow data acquisition and recording module is connected to the flowmeter through a wireless network, real-time collects flow data, and forms minute-level flow data.

[0135] The index calculation and intelligent recognition module 2021 is used to perform preprocessing such as cleaning on the collected rainfall data, remove outliers and operations, and screen out target rainfall data based on the preprocessed rainfall data. Specifically, the above formula (1) can be used to determine the rainfall impact index of the rainfall data. In this process, methods such as AHP (Analytic Hierarchy Process), entropy weight method, or machine learning method can be used to assign reasonable weights to indicators such as rainfall amount, rainfall duration, number of dry days before rainfall, and rainfall variation coefficient. Then, a machine learning model (such as support vector machine, decision tree, neural network, etc.) is constructed using the rainfall data. The rainfall impact index collected and calculated in real-time is input into the trained model, and the model outputs a judgment result on whether the current rainfall event has a significant influent and infiltration impact. In an implementable manner, different thresholds can be set to judge the risk level of the rainfall event.

[0136] The result output and feedback module 2022 is used to perform rainfall influent and infiltration calculation based on the flow data in the same period as the target rainfall data, and determine the key investigation points. And the calculation results are displayed through a visualization interface so that users can intuitively view the rainfall situation and its impact on the drainage system. For example Figure 4 as shown in the interface, where curve 1 represents the pipe network flow on rainy days, curve 2 represents the pipe network flow on dry days, and curve 3 represents the RDII value. It can also automatically trigger an early warning mechanism and notify relevant personnel by means of text messages, emails, or application push. According to the preset scheduling plan, automatically or assist relevant personnel to optimize the drainage system scheduling to reduce the impact of influent and infiltration on the drainage system. Finally, based on the determined key investigation points, the analysis results are displayed on the map using GIS to intuitively display the areas with high risk of rainfall influent and infiltration and prominent problems.

[0137] For the specific implementation of each module of the system, reference may be made to the implementation of the above-mentioned method for detecting inflow and infiltration in the drainage pipe network, which will not be elaborated here.

[0138] The system for detecting inflow and infiltration in the drainage pipe network provided by this solution realizes the comprehensive detection and optimized management of the inflow and infiltration conditions in the drainage pipe network through intelligent monitoring, data collection, index calculation and intelligent recognition, and result output and feedback. The system has a high level of automation and intelligence, and can accurately identify the risk level of rainfall events, providing scientific and intuitive decision-making support for management personnel.

[0139] According to the embodiments of the present disclosure, the present disclosure also provides an electronic device and a readable storage medium.

[0140] Figure 5 FIG. shows a schematic block diagram of an exemplary electronic device 800 that can be used to implement the embodiments of the present disclosure. The electronic device is intended to represent various forms of digital computers, such as, for example, a laptop computer, a desktop computer, a workbench, a personal digital assistant, a server, a blade server, a mainframe computer, and other suitable computers. The electronic device can also represent various forms of mobile devices, such as, for example, a personal digital processor, a cellular phone, a smart phone, a wearable device, and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely exemplary and are not intended to limit the implementation of the present disclosure described and / or claimed herein.

[0141] As Figure 5 shown, the device 800 includes a computing unit 801, which can perform various appropriate actions and processes according to a computer program stored in a read-only memory (ROM) 802 or a computer program loaded from a storage unit 808 into a random access memory (RAM) 803. In the RAM 803, various programs and data required for the operation of the device 800 can also be stored. The computing unit 801, the ROM 802, and the RAM 803 are connected to each other through a bus 804. An input / output (I / O) interface 805 is also connected to the bus 804.

[0142] A plurality of components in the device 800 are connected to the I / O interface 805, including: an input unit 806, such as a keyboard, a mouse, etc.; an output unit 807, such as various types of displays, speakers, etc.; a storage unit 808, such as a magnetic disk, an optical disc, etc.; and a communication unit 809, such as a network card, a modem, a wireless communication transceiver, etc. The communication unit 809 allows the device 800 to exchange information / data with other devices through a computer network such as the Internet and / or various telecommunication networks.

[0143] The computing unit 801 can be various general-purpose and / or special-purpose processing components with processing and computing capabilities. Some examples of the computing unit 801 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various dedicated artificial intelligence (AI) computing chips, various computing units running machine learning model algorithms, a digital signal processor (DSP), and any suitable processor, controller, microcontroller, etc. The computing unit 801 executes the various methods and processes described above, such as a method for detecting inflow and infiltration in a drainage pipe network. For example, in some embodiments, a method for detecting inflow and infiltration in a drainage pipe network can be implemented as a computer software program tangibly embodied in a machine-readable medium, such as the storage unit 808. In some embodiments, part or all of the computer program can be loaded and / or installed onto the device 800 via the ROM 802 and / or the communication unit 809. When the computer program is loaded into the RAM 803 and executed by the computing unit 801, one or more steps of the method for detecting inflow and infiltration in a drainage pipe network described above can be executed. Alternatively, in other embodiments, the computing unit 801 can be configured to execute a method for detecting inflow and infiltration in a drainage pipe network in any other suitable manner (e.g., by means of firmware).

[0144] Various embodiments of the systems and techniques described above in this document can be implemented in digital electronic circuit systems, integrated circuit systems, field-programmable gate arrays (FPGAs), application-specific integrated circuits (ASICs), application-specific standard products (ASSPs), systems on a chip (SOCs), complex programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various embodiments can include: being implemented in one or more computer programs that can be executed and / or interpreted on a programmable system including at least one programmable processor, which can be a special-purpose or general-purpose programmable processor, and can receive data and instructions from a storage system, at least one input device, and at least one output device, and transmit the data and instructions to the storage system, the at least one input device, and the at least one output device.

[0145] The program code for implementing the methods of the present disclosure can be written in any combination of one or more programming languages. These program codes can be provided to a processor or controller of a general-purpose computer, a special-purpose computer, or other programmable data processing device, such that when the program codes are executed by the processor or controller, the functions / operations specified in the flowchart and / or block diagram are implemented. The program code can be executed entirely on the machine, partially on the machine, as an independent software package partially on the machine and partially on a remote machine, or entirely on a remote machine or server.

[0146] In the context of this disclosure, a machine-readable medium can be a tangible medium that can contain or store a program for use by or in connection with an instruction execution system, apparatus, or device. A machine-readable medium can be a machine-readable signal medium or a machine-readable storage medium. A machine-readable medium can include, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, apparatus, or devices, or any suitable combination of the foregoing. More specific examples of a machine-readable storage medium would include an electrical connection based on one or more wires, a portable computer diskette, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or Flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.

[0147] In order to provide interaction with a user, the systems and techniques described herein can be implemented on a computer having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to the user; and a keyboard and a pointing device (e.g., a mouse or a trackball) by which the user can provide input to the computer. Other kinds of devices can also be used to provide interaction with the user; for example, the feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user can be received in any form (including acoustic input, speech input, or tactile input).

[0148] The systems and techniques described herein can be implemented in a computing system including backend components (e.g., as a data server), or a computing system including middleware components (e.g., an application server), or a computing system including frontend components (e.g., a user computer having a graphical user interface or a web browser through which the user can interact with an implementation of the systems and techniques described herein), or a computing system including any combination of such backend components, middleware components, or frontend components. The components of the system can be interconnected by any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include: a local area network (LAN), a wide area network (WAN), and the Internet.

[0149] A computer system can include a client and a server. The client and the server are generally remote from each other and typically interact through a communication network. The client-server relationship is generated by computer programs running on the respective computers and having a client-server relationship with each other. The server can be a cloud server, can also be a server of a distributed system, or a server incorporating a blockchain.

[0150] It should be understood that the various forms of processes shown above can be used, with steps reordered, added, or deleted. For example, the steps described in this disclosure can be executed in parallel, sequentially, or in a different order, as long as the desired results of the technical solution disclosed in this disclosure can be achieved, and no limitation is imposed herein.

[0151] In addition, the terms "first" and "second" are only used for descriptive purposes and cannot be construed as indicating or implying relative importance or implicitly specifying the quantity of the indicated technical features. Thus, features defined with "first" and "second" may explicitly or implicitly include at least one of such features. In the description of this disclosure, "a plurality of" means two or more, unless otherwise specifically defined.

[0152] As described above, the above are only specific embodiments of this disclosure, but the protection scope of this disclosure is not limited thereto. Any person skilled in the art within the technical scope disclosed in this disclosure can easily think of changes or substitutions, which should all be covered by the protection scope of this disclosure. Therefore, the protection scope of this disclosure should be subject to the protection scope of the claims.

Claims

1. A method for inspecting the inflow and infiltration of a drainage pipe network, characterized in that, The method comprises: Obtain the initial rainfall data set within the monitoring area; Based on a preset rainfall standard, the initial rainfall data set is screened to determine a candidate rainfall data set; Determining a rainfall impact index for each candidate rainfall data in the candidate rainfall data set; Based on the rainfall impact index of each candidate rainfall data, the candidate rainfall data set is screened to determine the target rainfall data; Acquire monitoring data in the drainage network that is concurrent with the target rainfall data, and conduct an inflow and infiltration inspection on the drainage network based on the monitoring data.

2. The method according to claim 1, wherein The monitoring data includes flow data of multiple flow monitoring points in the drainage network; accordingly, The inflow and infiltration investigation of the drainage network based on the monitoring data includes: Based on the flow data of each flow monitoring point, determine its rainfall inflow and infiltration value; The monitoring points where the rainfall inflow infiltration value is greater than the preset threshold are determined as key inspection points.

3. The method according to claim 2, wherein The rainfall inflow infiltration value of each flow monitoring point is determined according to the following formula: Among them, RDII represents the rainfall inflow and infiltration value; R0 represents the cumulative rainfall of the current day; Q t represents the flow data at time t of the current day; QH t represents the flow data at time t of the previous day; n is the total number of flow data of the current day.

4. The method according to claim 1, wherein The rainfall impact index of each candidate rainfall data in the candidate rainfall data set is determined according to the following formula: Among them, P represents the rainfall impact index; a represents the rainfall weight coefficient, and its value range is between 0.1 and 0.9; b represents the rainfall duration weight coefficient, and its value range is between 0.1 and 0.9, and the values ​​of a and b must satisfy a+b=1; RR represents the preset rainfall; TT represents the preset rainfall duration; R0 represents the cumulative rainfall on the day; R1 represents the cumulative rainfall on the previous rainy day; R2 represents the cumulative rainfall on the rainy day before the previous rainy day; H0 represents the number of dry days before the day; H1 represents the number of dry days before the previous rainy day; C represents the rainfall variation coefficient on the day; T represents the rainfall duration on the day; q represents the rainfall intensity on the day.

5. The method according to claim 1, wherein Initial rainfall data include the accumulated rainfall for the day; Accordingly, The screening of the initial rainfall data set based on the preset rainfall standard to determine the candidate rainfall data set includes: The initial rainfall data set whose accumulated rainfall on the day is greater than the preset rainfall standard is determined as the candidate rainfall data set.

6. The method according to claim 2, characterized in that, The method further comprises: Determine the rainfall monitoring points within the monitoring area and the flow monitoring points within the drainage pipe using a geographic information system; Obtain minute-level rainfall data through the rain gauge at the rainfall monitoring point; The minute-level flow data is obtained by using the flow meter at the flow monitoring point.

7. The method according to claim 6, characterized in that The step of obtaining an initial rainfall data set within the monitoring area includes: Based on the minute-level rainfall data, acquiring the initial rainfall data set; The obtaining of monitoring data in the drainage network concurrent with the target rainfall data includes: Based on the minute-level traffic data, the monitoring data is obtained.

8. The method according to claim 1, wherein The step of screening the candidate rainfall data set based on the rainfall impact index of each candidate rainfall data to determine the target rainfall data includes: Sort the rainfall impact index of each candidate rainfall data from small to large; Determine the candidate rainfall data corresponding to the preset number of rainfall impact indicators with higher rankings as the target rainfall data.

9. The method according to claim 4, characterized in that, The method further includes: Based on the influence of rainfall factors on rainfall runoff and infiltration, determine the values of the rainfall amount weight coefficient and the rainfall duration weight coefficient.

10. A drainage pipe network inflow and infiltration inspection system, characterized in that, The system includes: A data acquisition module, configured to acquire an initial rainfall data set within a monitoring area; A data processing module, configured to screen the initial rainfall data set based on a preset rainfall standard to determine a candidate rainfall data set; The data processing module is further configured to determine the rainfall impact indicators of each candidate rainfall data in the candidate rainfall data set; The data processing module is further configured to screen the candidate rainfall data set based on the rainfall impact indicators of each candidate rainfall data to determine the target rainfall data; The data processing module is further configured to acquire monitoring data in the drainage pipe network during the same period as the target rainfall data, and conduct runoff and infiltration inspections on the drainage pipe network based on the monitoring data.

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