Drainage management system based on data analysis

Abstract

The invention relates to the technical field of drainage management, in particular to a drainage management system based on data analysis, which comprises a pipe network pressure monitoring module, a rainfall trend analysis module, a drainage facility management module, an underground water dynamic monitoring module and a maintenance priority scheduling module. According to the invention, the operation state of the drainage system is timely predicted and adjusted through comprehensive data analysis, the monitoring capability of pressure, rainfall, pump station state and underground water level is improved, the accurate real-time data processing capability allows the system to rapidly identify potential risk areas, the pump station flow and underground water management are optimized, and the system reliability is improved. The continuous tracking and real-time adjustment mechanism not only reduces the potential of system overload or equipment failure, but also reduces manual inspection errors and operation cost through scientific maintenance scheduling optimization, and meanwhile, can perform early warning at the early risk stage to ensure the stable operation of the drainage system, so that the safety of the drainage system is ensured. Therefore, the efficiency and reliability of urban drainage management are improved.

Description

Technical Field

[0001] The present invention relates to the technical field of drainage management, and particularly to a drainage management system based on data analysis. Background Art

[0002] Drainage management technology involves designing, constructing, operating, and optimizing infrastructure for controlling water flow to prevent floods, improve water quality, and ensure the sustainable use of water resources. This field not only includes traditional engineering methods such as the construction of pipelines, pumping stations, and drainage ditches, but also the use of information technology and data analysis to monitor, predict, and manage urban and rural drainage systems. Through real-time data collection and analysis, flood risk can be predicted more effectively, water levels can be regulated, and the operation of drainage facilities can be optimized, thereby reducing the impact on the environment and improving economic efficiency.

[0003] Among them, the drainage management system based on data analysis collects various hydrological, meteorological, and infrastructure status data, and uses data analysis to process and analyze the data, so as to achieve real-time monitoring and management of the performance of the drainage system. Its main uses include preventing flood disasters, improving urban drainage efficiency, reducing environmental pollution, and supporting urban planning and sustainable development decision-making. It can help manage water resources more scientifically and ensure the safety and health of communities and ecosystems.

[0004] The prior art cannot immediately obtain and process data from pipe networks, meteorology, or groundwater, resulting in a lack of effective early warning and regulation measures in the face of sudden rainfall or system overload. Especially in extreme weather such as heavy rain and waterlogging, the existing systems rely on lagging prediction data or outdated historical models for scheduling, and cannot achieve efficient and real-time drainage control. This lagging response not only affects drainage efficiency, but also causes local drainage systems to be overloaded, thereby triggering floods. In addition, the traditional systems rely on manual inspections to monitor the load of pipe networks and the status of equipment, lacking comprehensive data support and intelligent scheduling functions, resulting in a lag in system maintenance response and affecting drainage effects. Summary of the Invention

[0005] The purpose of the present invention is to solve the disadvantages existing in the prior art, and to propose a drainage management system based on data analysis.

[0006] To achieve the above purpose, the present invention adopts the following technical solutions: A drainage management system based on data analysis, the system includes: The pipe network pressure monitoring module collects data from pressure sensors in the drainage pipe network, analyzes the pressure distribution deviation of each node, identifies the areas where the pressure fluctuation exceeds the normal operating range, and obtains the abnormal pressure index of the pipe network; The rainfall trend analysis module obtains rainfall data from regional weather stations, identifies cumulative rainfall events that exceed the normal bearing range, calculates the deviation from the current rainfall event, and obtains the rainfall deviation magnitude; The drainage facility management module calls the abnormal pressure index of the pipe network and the rainfall deviation magnitude, analyzes the drainage load of each pumping station, identifies the areas where the load exceeds the operating capacity of the pumping station, adjusts the flow output of the pumping station, and calculates the key flow adjustment amplitude to obtain the pumping station flow adjustment index; The groundwater dynamic monitoring module collects groundwater level and flow velocity data based on the rainfall deviation magnitude, identifies the recharge amount that exceeds the groundwater bearing capacity, calculates the groundwater infiltration rate, and obtains the groundwater dynamic change rate; The maintenance priority scheduling module calls the abnormal pressure index of the pipe network, the pumping station flow adjustment index, and the groundwater dynamic change rate, calculates the operating load of the drainage pipe network, identifies the areas where the operating load exceeds the maintenance threshold, calculates the urgency of pipe network maintenance, and obtains the pipe network maintenance priority.

[0007] The improvements of the present invention are that the abnormal pressure index of the pipe network includes pressure reading difference, fluctuation frequency, and abnormal area location information; the rainfall deviation magnitude includes rainfall intensity index, cumulative amount comparison result, and historical deviation analysis result; the pumping station flow adjustment index includes adjustment amplitude, operating status monitoring information, and load balance assessment result; the groundwater dynamic change rate includes water level change speed, recharge over-standard identification information, and infiltration rate measurement; the pipe network maintenance priority includes maintenance requirement level, historical maintenance comparison result, and over-standard load area identification result.

[0008] The improvements of the present invention are that the pipe network pressure monitoring module includes: The pressure data collection sub-module collects the data of the pressure sensors in the drainage pipe network, monitors the readings of the pressure sensors at each node, records the pressure value every minute, screens out the invalid data of the pressure value, and fills in the missing data points to obtain the pipe network pressure time series data; The abnormal fluctuation analysis sub-module analyzes the pressure change amplitude between adjacent time points based on the pipe network pressure time series data, and uses the formula: ; Calculate the average value of the pressure fluctuation amplitude , screen out the time periods that exceed the normal pressure fluctuation, and locate the abnormal pressure fluctuation intervals, where represents the total number of data points in the time series, represents the pressure value at the th time point, represents the pressure value at the th time point; The pressure distribution deviation calculation sub-module matches the abnormal pressure fluctuation interval with the topological structure data of the drainage pipe network, analyzes the pressure distribution deviation of each node, identifies the areas where the pressure fluctuation exceeds the normal range, and obtains the abnormal pressure index of the pipe network.

[0009] The improvement of the present invention is that the rainfall trend analysis module includes: The rainfall data acquisition sub-module acquires the rainfall data of the regional meteorological station, extracts the intensity and duration of each rainfall, records the rainfall time series data, and establishes a rainfall event data set; The cumulative rainfall calculation sub-module is based on the rainfall event data set and uses the formula: ; Calculate the cumulative rainfall of each rainfall event , and compare it with the data of the bearing capacity of the regional drainage system, and screen out the rainfall events that exceed the normal bearing range to obtain the over-bearing rainfall events, where represents the total number of rainfall time points, represents the th rainfall intensity at the time point, represents the th rainfall duration at the time point; The rainfall deviation analysis sub-module is based on the over-bearing rainfall events and combines historical rainfall data to calculate the deviation between the current rainfall event and the historical rainfall event to obtain the rainfall deviation magnitude.

[0010] The improvement of the present invention is that the drainage facility management module includes: The pump station status evaluation sub-module calls the abnormal pressure index of the pipe network and the rainfall deviation magnitude, collects the operation status data of the current drainage pump station, including the influent flow rate, the effluent flow rate and the start-stop status of the pump station, calculates the operation efficiency of each pump station, and analyzes the stability of the current operation status in combination with the pump station operation curve to generate a pump station operation status evaluation value; The drainage load identification sub-module is based on the pump station operation status evaluation value and uses the formula: ; Calculate the drainage load of the pump station , and compare it with the maximum operation capacity of the pump station, and screen out the areas that exceed the operation capacity of the pump station to obtain the overloaded pump station areas, where represents the number of time points in the monitoring period of the pump station, represents the th influent flow rate at the time point, represents the th effluent flow rate at the time point; The pump station flow rate adjustment sub-module adjusts the flow rate output of the corresponding pump station based on the overloaded pump station area, calculates the adjustment range of the key flow rate, and obtains the pump station flow rate adjustment index.

[0011] The improvement of the present invention is that the groundwater dynamic monitoring module includes: The groundwater monitoring sub-module, based on the rainfall deviation magnitude, uses groundwater monitoring equipment to collect the groundwater levels and flow velocities at different monitoring points, records the changes in water levels, stores the data at time intervals, and establishes a groundwater monitoring data set; The groundwater bearing capacity identification sub-module, based on the groundwater monitoring data set, analyzes the time series changes in water levels and flow velocities, and uses the formula: ; Calculate the groundwater recharge and identify the areas where the groundwater bearing capacity is exceeded to obtain overloaded groundwater areas. Among them, represents the number of monitoring periods, represents the water level at the current moment of the th monitoring point, represents the water level at the previous moment, represents the current flow velocity of the th monitoring point, represents the th monitoring point's infiltration area, represents the th monitoring point's groundwater transmission time; The groundwater change prediction sub-module, based on the overloaded groundwater areas, calculates the groundwater infiltration rate, combines historical water level change data, and predicts the future trend of groundwater level changes to obtain the groundwater dynamic change rate.

[0012] The present invention is improved in that the maintenance priority scheduling module includes: The operation load calculation sub-module calls the pipeline network abnormal pressure index, the pump station flow adjustment index, and the groundwater dynamic change rate, extracts the abnormal pressure values of the pipeline network nodes, analyzes the flow change amounts of its adjacent pipe segments, and combines the groundwater dynamic change rate, using the formula: ; Calculate the change amount of the operation load of each pipe segment , and identify the areas where the operation load exceeds the maintenance threshold. Among them, represents the abnormal pressure value of the th node, represents the abnormal pressure value of the th node, represents the flow adjustment value of the th pipe segment, represents the groundwater dynamic change rate, is the total number of pipe segments in the pipeline network; The maintenance urgency calculation sub-module calls the area where the operating load exceeds the maintenance threshold, collects the maintenance historical data of the target area, calculates the abnormal pressure frequency and the number of maintenance failures during the maintenance period, and calculates the pipe network maintenance urgency based on the current change of the operating load; The maintenance task screening sub-module, based on the pipe network maintenance urgency, sorts by urgency, analyzes the distribution of maintenance resources, selects the high-priority maintenance tasks that can be supported by the current maintenance resources, and generates the pipe network maintenance priority.

[0013] Compared with the prior art, the advantages and positive effects of the present invention are as follows: In the present invention, by comprehensively analyzing data, the operation state of the drainage system is predicted and adjusted in a timely manner, the monitoring capabilities of pressure, rainfall, pump station state, and groundwater level are improved, and the accurate real-time data processing capabilities allow the system to quickly identify potential risk areas, optimize the pump station flow and groundwater management, so as to achieve an immediate response to emergencies. This continuous tracking and real-time adjustment mechanism not only reduces the potential of system overload or equipment failure, but also reduces the human inspection error and operation cost through scientific maintenance scheduling optimization, and can give early warnings at the early stage of risks to ensure the stable operation of the drainage system, thereby improving the efficiency and reliability of urban drainage management. Brief Description of the Drawings

[0014] Figure 1 is the system flow chart of the present invention; Figure 2 is the flow chart of the pipe network pressure monitoring module in the present invention; Figure 3 is the flow chart of the rainfall trend analysis module in the present invention; Figure 4 is the flow chart of the drainage facility management module in the present invention; Figure 5 is the flow chart of the groundwater dynamic monitoring module in the present invention; Figure 6 is the flow chart of the maintenance priority scheduling module in the present invention. Detailed Embodiments

[0015] In order to make the objectives, technical solutions, and advantages of the present invention clearer and more understandable, the present invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not used to limit the present invention. <M

[0016] In the description of the present invention, it should be understood that the orientation or positional relationship indicated by terms such as "length", "width", "upper", "lower", "front", "rear", "left", "right", "vertical", "horizontal", "top", "bottom", "inner", "outer", etc. is based on the orientation or positional relationship shown in the drawings. It is only for the convenience of describing the present invention and simplifying the description, rather than indicating or implying that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation. Therefore, it should not be construed as a limitation to the present invention. In addition, in the description of the present invention, the meaning of "a plurality of" is two or more, unless otherwise specifically defined.

[0017] Embodiment: Please refer to Figure 1 , the present invention provides a technical solution: A drainage management system based on data analysis includes: The pipe network pressure monitoring module collects data from the pressure sensors of the drainage pipe network, continuously monitors each detection node, records the pressure readings per minute, locates abnormal pressure fluctuations through fluctuation analysis of the continuous readings, matches with the topological structure data of the drainage pipe network, analyzes the pressure distribution deviation of each node, compares the pressure difference with adjacent nodes, identifies the areas where the pressure fluctuation exceeds the normal operating range, and obtains the pipe network abnormal pressure index; The rainfall trend analysis module obtains the rainfall data of the regional weather station, extracts the intensity and duration of each rainfall, calculates the cumulative rainfall of each rainfall event, compares it with the drainage system carrying capacity of the region, identifies the cumulative rainfall events that exceed the normal carrying range, and combines with historical rainfall data to calculate the deviation from the current rainfall event, and obtains the rainfall deviation magnitude; The drainage facility management module calls the pipe network abnormal pressure index and the rainfall deviation magnitude, obtains the operating status of the drainage pump stations, analyzes the drainage load of each pump station, identifies the areas where the load exceeds the operating capacity of the pump station, adjusts the flow output of the pump station, and calculates the key flow adjustment amplitude to obtain the pump station flow adjustment index; The groundwater dynamic monitoring module, based on the rainfall deviation magnitude, uses groundwater monitoring equipment to collect groundwater level and flow velocity data, analyzes the time series change of the data, identifies the recharge amount that exceeds the groundwater carrying capacity, calculates the groundwater infiltration rate, and predicts the change trend of the groundwater level to obtain the groundwater dynamic change rate; The maintenance priority scheduling module calls the pipe network abnormal pressure index, the pump station flow adjustment index and the groundwater dynamic change rate, calculates the operating load of the drainage pipe network, identifies the areas where the operating load exceeds the maintenance threshold, collects and analyzes the maintenance history of the target area, calculates the pipe network maintenance urgency, screens the maintenance tasks with the top-ranked urgency, and obtains the pipe network maintenance priority.

[0018] The abnormal pressure indicators of the pipe network include pressure reading differences, fluctuation frequencies, and abnormal area location information. The rainfall deviation magnitudes include rainfall intensity indicators, cumulative quantity comparison results, and historical deviation analysis results. The pump station flow adjustment indicators include adjustment amplitudes, operation status monitoring information, and load balance assessment results. The dynamic change rate of groundwater includes water level change speeds, recharge over-standard identification information, and seepage rate measurements. The pipe network maintenance priorities include maintenance requirement levels, historical maintenance comparison results, and over-standard load area identification results.

[0019] Please refer to Figure 2 , the pipe network pressure monitoring module includes: The pressure data collection sub-module collects the data of the pressure sensors in the drainage pipe network, monitors the readings of the pressure sensors at each node, records the pressure value once per minute, screens out the invalid data of the pressure value, and fills in the missing data points to obtain the pipe network pressure time series data; The pressure sensors arranged at each node of the drainage pipe network can obtain real-time pressure data. The readings of the pressure sensors at each node are affected by flow fluctuations, external environments, and equipment performance. Therefore, when collecting data, it is necessary to preprocess the sensor readings, record the pressure value once per minute to form stable time series data. The storage of the time series data needs to include timestamps and the corresponding pressure values. Abnormal data is screened, and the screening criteria include detecting whether there are mutation values, that is, the difference between the current pressure value and the pressure value at the previous time point exceeds the set threshold. For example, if the normal operating pressure range of the pipe network is from 0.3 MPa to 0.7 MPa, then when the pressure value at a certain time point exceeds this range or the pressure mutation between adjacent time points exceeds 0.2 MPa, it is marked as invalid data and excluded. For missing data, the time interpolation method is used for filling, that is, the interpolation data is calculated using the pressure values at adjacent time points. For example, if the pressure data is lost at a certain moment, and the pressure values at the previous and subsequent time points are 0.45 MPa and 0.50 MPa respectively, then the pressure value at this moment is interpolated and calculated as 0.475 MPa, so as to ensure data integrity and avoid calculation deviations caused by data loss, and obtain the pipe network pressure time series data.

[0020] The abnormal fluctuation analysis sub-module analyzes the pressure change amplitude between adjacent time points based on the pipe network pressure time series data, and uses the formula: ; Calculate the mean value of the pressure fluctuation amplitude , screen out the time periods with abnormal pressure fluctuations beyond the normal range, and locate the abnormal pressure fluctuation intervals. Among them, represents the total number of data points in the time series, represents the th pressure value at the time point, represents the th pressure value at the time point; When analyzing the pressure change amplitude between adjacent time points and calculating the pressure fluctuation, first calculate the pressure change amount at each time point, that is, the difference between the pressure value at the current time point and the pressure value at the previous time point. The absolute value is used to prevent the positive and negative directions from canceling out the pressure fluctuation. For example, if a time period , and the pressure values at each time point are 0.42 MPa, 0.45 MPa, 0.48 MPa, 0.46 MPa, and 0.44 MPa in sequence, then the average value of the pressure fluctuation amplitude is calculated as follows: ; ; For a time period with abnormal pressure fluctuation, if the normal pressure fluctuation range is 0.02 MPa, and the calculated is greater than this value, it is determined that abnormal pressure fluctuation occurs in this time period, and the time period is marked to locate the abnormal pressure fluctuation interval.

[0021] Based on the abnormal pressure fluctuation interval, the pressure distribution deviation calculation sub-module matches with the topological structure data of the drainage network, analyzes the pressure distribution deviation of each node, identifies the area where the pressure fluctuation exceeds the normal range, and obtains the abnormal pressure index of the network; Matches with the topological structure data of the drainage network, analyzes the pressure distribution deviation of each node. For the calculation of the pressure distribution deviation of each node, first extract the pressure data of each node within the corresponding abnormal pressure fluctuation interval, and calculate the average pressure value of each node. For example, if the pressure data of a node within the abnormal fluctuation interval are 0.48 MPa, 0.52 MPa, and 0.50 MPa, then the average pressure value of this node is . Subsequently, calculate the pressure difference between the pressure value of this node and the pressure of the adjacent node. If the pressure value of the adjacent node is 0.55 MPa, then the pressure deviation value of this node is MPa. Then, calculate the mean square deviation of all node pressure deviation values to determine whether it exceeds the preset threshold. For example, if the normal pressure deviation mean square threshold is 0.03 MPa, and the calculated mean square deviation exceeds this range, then identify this area as an abnormal pressure area and obtain the abnormal pressure index of the network.

[0022] Please refer to Figure 3 , the rainfall trend analysis module includes: The rainfall data acquisition sub-module acquires the rainfall data of the regional meteorological station, extracts the intensity and duration of each rainfall, and records the rainfall time series data to establish a rainfall event dataset; Acquires the rainfall data of the regional meteorological station. The regional meteorological station usually includes automatic rain gauges, remote sensing rainfall monitoring equipment, etc. The equipment can record the rainfall amount at specific time intervals. Set the rainfall monitoring frequency to 10-minute intervals, and obtain the rainfall amount and the corresponding rainfall duration , record the start time and end time of each rainfall event, and filter out rainfall data with a rainfall interval of less than 30 minutes as the same rainfall event. For example, in a certain area, 2mm of rainfall is recorded from 10:00 to 10:10, and 3mm of rainfall is recorded from 10:10 to 10:20. If there is no rainfall from 10:20 to 10:30, the first two data are classified as one rainfall event. If there is rainfall again from 10:30 to 10:40, it is classified as a new rainfall event. Further extract rainfall data and calculate the rainfall intensity of each rainfall event. and duration The data are sorted and stored in time series according to the timestamp information of the rainfall event. If there are missing data or abnormal values (such as negative rainfall or extreme values greater than 100 mm / h), interpolation processing is required. Linear interpolation or sliding average method is often used to repair the data. For example, if the rainfall data from 10:10 to 10:20 is missing, it can be interpolated based on the rainfall data from 10:00 to 10:10 and 10:20 to 10:30. Finally, all rainfall event data are sorted into time series data sets and stored in chronological order.

[0023] The accumulated rainfall calculation submodule is based on the rainfall event dataset and uses the formula: ; Calculate the cumulative rainfall for each rainfall event , and compared with the carrying capacity data of the regional drainage system, the rainfall events that exceed the normal carrying range are screened out to obtain the over-load rainfall events, among which, Represents the total number of rainfall time points, Representative The rainfall intensity at a given time point, Representative Duration of rainfall at a time point; Taking a rainfall event as an example, if a rainfall event contains data at three time points, they are mm / h, min, mm / h, min, mm / h, min, the cumulative rainfall is calculated as follows: ; Calculated rainfall accumulation Comparing with the regional drainage system carrying capacity data, the drainage system carrying capacity threshold is set to 5mm. If it is greater than the threshold, it is determined as an event beyond the bearing capacity. For example, if the cumulative rainfall of a rainfall event is 6.2 mm, then mark this event as a rainfall event beyond the bearing range. Further screen all rainfall events beyond the threshold to obtain rainfall events beyond the bearing capacity.

[0024] Based on the rainfall events beyond the bearing capacity, the rainfall deviation analysis sub-module combines historical rainfall data to calculate the deviation between the current rainfall event and historical rainfall events, and obtains the rainfall deviation magnitude. Retrieve similar historical rainfall events from the historical rainfall database, calculate the deviation between the current rainfall event and historical rainfall events, and extract the cumulative rainfall of historical rainfall events. Calculate the deviation value between the current rainfall event and historical rainfall events. The calculation formula is where is the cumulative rainfall of the historical rainfall event. If the cumulative rainfall of a historical rainfall event is 3.8 mm and the cumulative rainfall of the current rainfall event is 6.2 mm, then calculate the deviation magnitude as follows: The calculated rainfall deviation magnitude is used to evaluate the abnormality degree of the current rainfall event. Further calculate all rainfall events, and finally sort out the deviation magnitude data of all rainfall events.

[0025] Please refer to Figure 4 The drainage facility management module includes: The pump station status evaluation sub-module calls the abnormal pressure index of the pipe network and the rainfall deviation magnitude, collects the operation status data of the current drainage pump station, including the inlet flow rate, outlet flow rate and the start-stop status of the pump station, calculates the operation efficiency of each pump station, and combines the pump station operation curve to analyze the stability of the current operation status and generate the pump station operation status evaluation value. Obtain the operation status data of each drainage pump station, including the real-time inlet flow rate, outlet flow rate and the start-stop status of the pump station. First, obtain the real-time inlet flow rate of the pump station. and the outlet flow rate and record them in time series. If the inlet flow rate of a pump station is 120 m³ / h and the outlet flow rate is 100 m³ / h from 09:00 to 09:10, and the inlet flow rate is 140 m³ / h and the outlet flow rate is 110 m³ / h from 09:10 to 09:20, then the operation status of this pump station can be quantified as the flow rate change trend. Next, analyze the start-stop status of the pump station, extract the timestamps of each pump start and stop, and combine the operation records to judge the operation cycle of the pump station. For example, if a pump station starts at 09:00 and stops at 09:30, then its operation cycle is 30 minutes. Subsequently, calculate the operation efficiency of each pump station, using the ratio of the inlet flow rate to the outlet flow rate as a reference. The calculation formula is as follows: , where if the inlet flow rate of a certain pumping station is 120 m³ / h and the outlet flow rate is 100 m³ / h, its operating efficiency is calculated as follows: , finally, combined with the operation curve of the pumping station, analyze the stability of the current operation state. If the operation efficiency of the pumping station is stable within the range of 0.8 - 0.9 in multiple time periods, it is considered that its state is stable. If there are large fluctuations, such as the operation efficiency drops to 0.5 or rises to 1.0 in a certain time period, there is an abnormality. All evaluation results are summarized to generate the evaluation value of the operation state of the pumping station.

[0026] The drainage load identification sub-module, based on the evaluation value of the operation state of the pumping station, uses the formula: ; Calculate the drainage load of the pumping station , compare it with the maximum operation capacity of the pumping station, screen the areas that exceed the operation capacity of the pumping station to obtain the overloaded pumping station areas, where represents the number of time points in the monitoring period of the pumping station, represents the inlet flow rate at the th time point, represents the th time point; m³ / h, m³ / h; m³ / h, m³ / h; m³ / h, m³ / h; m³ / h, m³ / h; Then the calculation is as follows: ; ; The calculated drainage load of the pumping station is compared with the maximum operation capacity of the pumping station. The maximum operation capacity of a certain pumping station is 120 m³ / h. If the calculated value exceeds this value, it is determined that the pumping station is in an overloaded state. The load of a certain pumping station is 130 m³ / h, which is greater than its maximum operation capacity, so it is marked as an overloaded pumping station to obtain the overloaded pumping station area.

[0027] The pumping station flow rate adjustment sub-module, based on the overloaded pumping station area, adjusts the flow rate output of the corresponding pumping station, calculates the adjustment amplitude of the key flow rate, and obtains the pumping station flow rate adjustment index; Adjust the flow output of the corresponding pumping station and calculate the adjustment range of the key flow. First, obtain the current water output flow of each overloaded pumping station and the upper limit of the operating capacity . Let the target adjusted flow be . The calculation formula is as follows: . Among them, if the current water output flow of a pumping station is 100 m³ / h and the maximum operating capacity is 120 m³ / h, the adjusted flow is calculated as follows: . Apply the calculated adjustment range of the key flow to the overloaded pumping station, adjust the flow output, and obtain the pumping station flow adjustment index

[0028] Please refer to Figure 5 . The groundwater dynamic monitoring module includes: The groundwater monitoring sub-module, based on the rainfall deviation magnitude, uses groundwater monitoring equipment to collect the groundwater level and flow velocity data of the differential monitoring points, record the water level change situation, store the data at time intervals, and establish a groundwater monitoring data set; Using groundwater monitoring equipment to collect the groundwater level and flow velocity data of the differential monitoring points. First, select the monitoring points with different geological structures to obtain the groundwater level data. Set the collection time interval to 30 minutes. For example, at a certain monitoring point, the water level is recorded as 10.2 m at 09:00 and 10.5 m at 09:30, then the change amount is 0.3 m. When collecting the groundwater flow velocity, use the flow velocity sensor to record the water flow moving distance to calculate the average flow velocity per unit time. If the measured flow velocity from 09:00 to 09:30 is 0.04 m / s and the flow velocity from 09:30 to 10:00 is 0.05 m / s, the time continuity needs to be maintained when storing the data. Next, record the water level change situation, extract the data of each monitoring point, and form a time series curve. For example, at a certain monitoring point, the water level data from 09:00 to 12:00 are 10.2 m, 10.5 m, 10.8 m, and 11.0 m in sequence, then its change trend can be identified as rising by 0.8 m, and a groundwater monitoring data set is established

[0029] The groundwater bearing capacity identification sub-module, based on the groundwater monitoring data set, analyzes the time series changes of the water level and flow velocity, and uses the formula: ; Calculate the groundwater recharge , identify the areas that exceed the groundwater bearing capacity, and obtain the overloaded groundwater areas. Among them, represents the number of monitoring periods represents the water level of the th monitoring point at the current moment represents the water level at the previous moment represents the current flow velocity of the th monitoring point Represents the seepage area of the th monitoring point, represents the groundwater transmission time of the th monitoring point; If there are three monitoring points in a certain area and the measured data are as follows: Monitoring point 1: ; Monitoring point 2: ; Monitoring point 3: ; The calculation is as follows: ; ; ; The total calculation result is: ; Compare the calculation result with the groundwater bearing capacity threshold. If the set threshold is 4.5, it is determined that the area is overloaded and marked as an overloaded groundwater area.

[0030] The groundwater change prediction sub-module calculates the groundwater seepage rate based on the overloaded groundwater area, combines the historical water level change data, predicts the future trend of the groundwater level change, and obtains the groundwater dynamic change rate; First, extract the seepage rate data within the overloaded area , calculate its average seepage rate, and the calculation formula is as follows: , where, if there are three monitoring points in an overloaded area and their seepage rate data are as follows: Monitoring point 1: , Monitoring point 2: , Monitoring point 3: ; The calculation result is: , combine the historical water level change data, extract the water level change trend in the past 24 hours. For example, the water levels of a certain monitoring point in the past 24 hours are 10.2m, 10.4m, 10.8m, and 11.0m, and the calculated change rate is: , if , the calculation is as follows, , combine the groundwater seepage rate with the water level change rate to predict the future trend of the groundwater level change.

[0031] Please refer to Figure 6 , the maintenance priority scheduling module includes: The running load calculation sub-module calls the abnormal pressure index of the pipe network, the flow adjustment index of the pumping station, and the groundwater dynamic change rate, extracts the abnormal pressure values of the pipe network nodes, analyzes the flow change amount of its adjacent pipe segments, combines the groundwater dynamic change rate, and uses the formula: ; Calculate the change in the operating load of each pipe section , identify the areas where the operating load exceeds the maintenance threshold, where represents the abnormal pressure value of the th node, represents the abnormal pressure value of the th node, represents the flow adjustment value of the th pipe section, represents the dynamic change rate of groundwater, indicating the change in the groundwater level in the area where the pipe section is located, is the total number of pipe sections in the pipe network; Extract the abnormal pressure values of the pipe network nodes, analyze the change in the flow rate of their adjacent pipe sections, and combine with the dynamic change rate of groundwater to calculate the change in the operating load of each pipe section , first, measure the pressure data of each node in the pipe network and extract the abnormal pressure values of all nodes , and calculate the pressure difference between two adjacent nodes, that is , this difference represents the pressure gradient in the pipe section. In the example, if the pressure values of node 1 and node 2 in a pipe network system are and , respectively, then their pressure difference is . Then, call the flow adjustment index of the pumping station to extract the flow adjustment value of the current pipe section , this value measures the flow rate fluctuation of the current pipe section. If the flow adjustment value of a pumping station is , then its corresponding adjustment coefficient is used to normalize the pressure difference to evaluate the actual load of the pipe section. Further, combine with the dynamic change rate of groundwater to obtain the change in the groundwater level in the area of the pipe section, usually calculated through historical groundwater level monitoring data. For example, if the groundwater level in a certain area drops in one year, the corresponding is . According to the above data, apply the calculation formula: ; Substitute the example values. If is taken, and the data is as follows: , , , , , , , then the calculation is as follows: ; ; ; The calculated change in operating load is 2.26. The maintenance threshold is called to determine whether it exceeds the maintenance threshold. If the set maintenance threshold is 2.0, the current value has exceeded the threshold, and this area is identified as the area where the operating load exceeds the maintenance threshold.

[0032] The maintenance urgency calculation sub-module calls the area where the operating load exceeds the maintenance threshold, collects the maintenance historical data of the target area, calculates the abnormal pressure frequency and the number of maintenance failures during the maintenance period, and calculates the pipeline network maintenance urgency based on the current change in operating load; Collect the maintenance historical data of the target area, extract the maintenance records of the past year, and count the abnormal pressure frequency and the number of maintenance failures. First, call the maintenance log of this area in the past year to obtain all maintenance events, and filter out the number of maintenance caused by abnormal pressure. For example, a certain area recorded 5 abnormal pressure events in the past 12 months, and each event recorded the corresponding time, abnormal pressure value and maintenance duration. Then, calculate the abnormal pressure frequency. The calculation of abnormal pressure frequency can be based on the ratio of the number of days with abnormalities in the whole year to the total number of days. For example, if there are 50 days with abnormal pressure events in this area within 365 days, the abnormal pressure frequency is calculated as follows: , that is, the occurrence probability of abnormal pressure in this area is 13.7%. Further, count the number of maintenance failures. If 15 maintenance failures occurred in this area in the past year, and 9 of them were caused by abnormal pressure, the occurrence probability of maintenance failures is calculated as follows: , that is, the proportion of maintenance failures caused by abnormal pressure in this area is 60%. Finally, based on the current change in operating load, comprehensively consider the abnormal pressure frequency and the occurrence probability of maintenance failures to calculate the pipeline network maintenance urgency. If the maintenance urgency calculation method is weighted summation, such as: ; where , , substitute into the calculation: ; The obtained pipeline network maintenance urgency is 0.3685.

[0033] The maintenance task screening sub-module sorts according to the pipeline network maintenance urgency, analyzes the distribution of maintenance resources, selects the high-priority maintenance tasks that can be supported by the current maintenance resources, and generates the pipeline network maintenance priority; Sort according to the urgency level and analyze the distribution of maintenance resources. First, sort all the areas exceeding the threshold in descending order of maintenance urgency. For example, if the maintenance urgencies of certain pipe network areas A, B, and C are 0.42, 0.37, and 0.35 respectively, the sorting result is A > B > C. Subsequently, call the currently available maintenance resource data and analyze the maintenance requirements of each area. For example, area A requires 5 groups of maintenance personnel, B requires 4 groups, and C requires 3 groups, while the currently disposable maintenance resources are 10 groups of personnel. Determine the priority areas that can be covered. In this case, prioritize the maintenance tasks in areas A and B, and finally obtain the pipe network maintenance priorities.

[0034] The above are only the preferred embodiments of the present invention and do not limit the present invention in other forms. Any person skilled in the art may use the disclosed technical content to make changes or modifications into equivalent embodiments with equivalent changes and apply them to other fields. However, as long as it does not depart from the technical solution content of the present invention, any simple modification, equivalent change, and modification made to the above embodiments based on the technical essence of the present invention still fall within the protection scope of the technical solution of the present invention.

Claims

1. A drainage management system based on data analysis, characterized in that, The system includes: The pipe network pressure monitoring module collects the data of the pressure sensors in the drainage pipe network, analyzes the pressure distribution deviation of each node, identifies the areas where the pressure fluctuation exceeds the normal operation range, and obtains the abnormal pressure index of the pipe network. The rainfall trend analysis module obtains the rainfall data of the regional weather station, identifies the cumulative rainfall events that exceed the normal carrying capacity, calculates the deviation from the current rainfall event, and obtains the rainfall deviation magnitude. The drainage facility management module calls the abnormal pressure index of the pipe network and the rainfall deviation magnitude, analyzes the drainage load of each pump station, identifies the areas where the load exceeds the operation capacity of the pump station, adjusts the flow output of the pump station, and calculates the key flow adjustment amplitude to obtain the pump station flow adjustment index. The groundwater dynamic monitoring module collects the groundwater level and flow velocity data based on the rainfall deviation magnitude, identifies the recharge amount that exceeds the groundwater carrying capacity, calculates the groundwater infiltration rate, and obtains the groundwater dynamic change rate. The maintenance priority scheduling module calls the abnormal pressure index of the pipe network, the pump station flow adjustment index, and the groundwater dynamic change rate, calculates the operation load of the drainage pipe network, identifies the areas where the operation load exceeds the maintenance threshold, calculates the urgency of pipe network maintenance, and obtains the pipe network maintenance priority.

2. The drainage management system based on data analysis according to claim 1, characterized in that, The abnormal pressure index of the pipe network includes the pressure reading difference, the fluctuation frequency, and the abnormal area location information. The rainfall deviation magnitude includes the rainfall intensity index, the cumulative amount comparison result, and the historical deviation analysis result. The pump station flow adjustment index includes the adjustment amplitude, the operation status monitoring information, and the load balance evaluation result. The groundwater dynamic change rate includes the water level change speed, the recharge over-standard identification information, and the infiltration rate measurement. The pipe network maintenance priority includes the maintenance requirement level, the historical maintenance comparison result, and the over-standard load area identification result.

3. The drainage management system based on data analysis according to claim 1, characterized in that The pipe network pressure monitoring module includes: The pressure data collection sub-module collects the data of the pressure sensors in the drainage pipe network, monitors the readings of the pressure sensors at each node, records the pressure value every minute, filters out the invalid pressure value data, and fills in the missing data points to obtain the pipe network pressure time series data. The abnormal fluctuation analysis sub-module analyzes the pressure change amplitude between adjacent time points based on the pipe network pressure time series data, and uses the formula: ； Calculate the mean value of the pressure fluctuation amplitude , screen the time periods with abnormal pressure fluctuations, and locate the abnormal pressure fluctuation intervals, where represents the total number of time series data points, represents the pressure value at the th time point, represents the pressure value at the th time point; The pressure distribution deviation calculation sub-module matches the abnormal pressure fluctuation interval with the topological structure data of the drainage pipe network, analyzes the pressure distribution deviation of each node, identifies the areas where the pressure fluctuation exceeds the normal range, and obtains the abnormal pressure index of the pipe network.

4. The drainage management system based on data analysis according to claim 1, characterized in that, The rainfall trend analysis module includes: The rainfall data acquisition sub-module obtains the rainfall data of the regional weather station, extracts the intensity and duration of each rainfall, records the rainfall time series data, and establishes a rainfall event data set. The cumulative rainfall calculation sub-module uses the formula based on the rainfall event data set: ； Calculate the cumulative rainfall for each rainfall event , and compare it with the data on the carrying capacity of the regional drainage system to screen out rainfall events that exceed the normal carrying range, and obtain overloaded rainfall events. Among them, represents the total number of rainfall time points, represents the rainfall intensity at the th time point, and represents the rainfall duration at the The rainfall deviation analysis sub-module calculates the deviation between the current rainfall event and the historical rainfall event based on the overloaded rainfall event and combines the historical rainfall data to obtain the rainfall deviation magnitude.

5. The drainage management system based on data analysis according to claim 1, wherein The drainage facility management module includes: The pump station status evaluation sub-module calls the abnormal pressure index of the pipe network and the rainfall deviation magnitude, collects the operation status data of the current drainage pump station, including the influent flow rate, the effluent flow rate, and the start-stop status of the pump station, calculates the operation efficiency of each pump station, and analyzes the stability of the current operation status in combination with the pump station operation curve to generate a pump station operation status evaluation value; The drainage load identification sub-module is based on the pump station operation status evaluation value and uses the formula: ； Calculate the drainage load of the pumping station , compare it with the maximum operating capacity of the pumping station, screen the areas that exceed the operating capacity of the pumping station, and obtain the overloaded pumping station areas, where represents the number of time points during the monitoring period of the pumping station represents the inlet flow rate at the th time point outlet flow rate at the The pump station flow rate adjustment sub-module adjusts the flow rate output of the corresponding pump station based on the overloaded pump station area, calculates the adjustment range of the key flow rate, and obtains the pump station flow rate adjustment index.

6. The drainage management system based on data analysis according to claim 1, characterized in that, The groundwater dynamic monitoring module includes: The groundwater monitoring sub-module, based on the rainfall deviation magnitude, uses groundwater monitoring equipment to collect the groundwater level and flow velocity data of different monitoring points, records the water level change situation, stores the data at time intervals, and establishes a groundwater monitoring data set; The groundwater bearing capacity identification sub-module, based on the groundwater monitoring data set, analyzes the time series changes of the water level and flow velocity and uses the formula: ； Calculate the groundwater recharge , identify the areas that exceed the groundwater bearing capacity to obtain overloaded groundwater areas, where represents the number of monitoring periods represents the water level at the current moment of the th monitoring point represents the water level at the previous moment represents the current flow velocity of the th monitoring point represents the infiltration area of the th monitoring point represents the groundwater transmission time of the th monitoring point; The groundwater change prediction sub-module, based on the overloaded groundwater area, calculates the groundwater seepage rate, combines the historical water level change data, and predicts the future change trend of the groundwater level to obtain the groundwater dynamic change rate.

7. The drainage management system based on data analysis according to claim 1, characterized in that, The maintenance priority scheduling module includes: The operation load calculation sub-module calls the abnormal pressure index of the pipe network, the pump station flow rate adjustment index, and the groundwater dynamic change rate, extracts the pressure abnormal values of the pipe network nodes, analyzes the flow rate change amount of its adjacent pipe segments, and combines the groundwater dynamic change rate to use the formula: ； Calculate the change in the operating load of each pipe segment , identify the areas where the operating load exceeds the maintenance threshold, where represents the abnormal pressure value of the th node, represents the abnormal pressure value of the th node, represents the flow adjustment value of the th pipe segment, represents the groundwater dynamic change rate, is the total number of pipe segments in the pipe network; The maintenance urgency calculation sub-module calls the area where the operation load exceeds the maintenance threshold, collects the maintenance historical data of the target area, calculates the abnormal pressure frequency and the number of maintenance failures during the maintenance period, and calculates the pipe network maintenance urgency according to the current operation load change situation; The maintenance task screening sub-module, based on the pipe network maintenance urgency, sorts by urgency, analyzes the distribution of maintenance resources, selects the high-priority maintenance tasks that can be supported by the current maintenance resources, and generates the pipe network maintenance priority.

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