Urban drainage pipe network digital monitoring management system

Abstract

The invention discloses a digital monitoring and management system for an urban drainage pipe network, and relates to the technical field of drainage pipe networks, and the system comprises a data collection module which is used for collecting a drainage pump station current signal, a pipeline pressure signal and an actual flow velocity in real time; the data calling module is used for calling the length and the pipe diameter of the current pipe section from a preset pipeline database; the data processing module is used for determining actual fluid time consumption according to the current pipe section length and the actual flow speed; theoretical fluid time delay is determined according to the current pipe section length and the pipe diameter; determining a sliding cross-correlation function between the current signal and the pipeline pressure signal according to the current signal and the pipeline pressure signal; and according to the actual fluid time, the theoretical fluid time delay and the maximum value point of the sliding cross-correlation function, determining whether the current pipe section is blocked or not. According to the invention, accurate judgment of pipeline blockage is realized.

Description

Technical Field

[0001] This invention relates to the technical field of drainage pipe networks, and more particularly to a digital monitoring and management system for urban drainage pipe networks. Background Technology

[0002] In the operation of urban drainage systems, the digital monitoring and management system for urban drainage networks utilizes various sensors, communication technologies, geographic information systems, data analysis, and IoT platforms to perform real-time, continuous, and automated sensing, transmission, processing, and analysis of the operational status of urban drainage network systems, thereby achieving more efficient and intelligent management and decision-making.

[0003] In the prior art, for example, Chinese patent with patent number "CN108278491A" discloses a method and system for detecting abnormal operation of drainage pipe network. The method compares and analyzes the data obtained from the pipeline flow and velocity simulation model with the actual monitored flow and velocity data, and locates the pipe section that is blocked or silted up by combining the topological relationship and error range of the pipe network.

[0004] However, this method cannot distinguish between genuine pipe blockage and sensor data drift. Both situations would trigger alarms in traditional monitoring systems, but the responses are drastically different: a genuine blockage requires emergency dredging, while a false alarm only requires sensor repair. Existing technology often confuses the two, leading to incorrect handling decisions, wasted resources, or delays in response, demonstrating insufficient accuracy in identifying pipe blockages.

[0005] Therefore, accurately determining pipe blockage has become a pressing technical problem that needs to be solved. Summary of the Invention

[0006] The technical problem solved by this invention is the inability to accurately determine whether a pipe is blocked.

[0007] To solve the above-mentioned technical problems, the present invention provides the following technical solution: a digital monitoring and management system for urban drainage pipe networks, comprising: The data acquisition module is used to collect real-time current signals, pipeline pressure signals, and actual flow rates of the drainage pumping station. The data retrieval module is used to retrieve the current pipe segment length and diameter from a preset pipeline database; The data processing module is used for: The actual fluid flow time is determined based on the current pipe section length and the actual flow velocity. The theoretical fluid time delay is determined based on the current pipe segment length and the pipe diameter; Determine the sliding cross-correlation function between the current signal and the pipeline pressure signal based on the current signal and the pipeline pressure signal; The current pipe segment is determined to be blocked based on the actual fluid travel time, the theoretical fluid delay, and the maximum point of the sliding cross-correlation function.

[0008] Preferably, the data acquisition module is also used to collect the real-time water temperature and suspended solids concentration of the current pipe section; The data processing module is also used to determine the actual fluid viscosity based on the real-time water temperature and the suspended solids concentration; The step of determining the theoretical fluid time delay based on the current pipe segment length and the pipe diameter includes: The theoretical fluid time delay is determined based on the current pipe section length, the pipe diameter, and the actual fluid viscosity.

[0009] Preferably, determining the sliding cross-correlation function between the current signal and the pipeline pressure signal based on the current signal and the pipeline pressure signal includes: The current signal and the pipeline pressure signal are subjected to wavelet packet decomposition with a preset number of layers to extract the current frequency band component and the pressure frequency band component of a preset frequency band. The sliding cross-correlation function between the current signal and the pipeline pressure signal is determined based on the current frequency band component and the pressure frequency band component.

[0010] Preferably, determining whether a pipe blockage has occurred in the current pipe segment based on the actual fluid travel time, the theoretical fluid time delay, and the maximum point of the sliding cross-correlation function includes: Determine the absolute difference between the theoretical fluid time delay and the maximum point of the sliding cross-correlation function; The response confidence level is determined based on the quotient of the absolute difference and the actual fluid usage time. The system determines whether the current pipe segment is blocked based on the response confidence level and the preset confidence level threshold.

[0011] Preferably, determining whether a pipe blockage has occurred in the current pipe segment based on the response confidence level and a preset confidence threshold includes: If the confidence level of the response is greater than the confidence level threshold, then it is determined that the data acquisition module corresponding to the current pipeline has malfunctioned. If the confidence level of the response is less than or equal to the confidence level threshold, then the correlation factor is determined based on the current signal and the pipeline pressure signal. The current pipe segment is determined to be blocked based on the correlation factor and the preset correlation threshold.

[0012] Preferably, the data retrieval module is further configured to retrieve the reference delay of the current pipeline segment from the pipeline database; If the confidence level of the response is less than or equal to the confidence level threshold, then a correlation factor is determined based on the current signal and the pipeline pressure signal, including: If the confidence level of the response is less than or equal to the confidence level threshold, then the rate of change of the current signal is determined based on the current signal. Determine the rate of change of the pipeline pressure signal based on the pipeline pressure signal; The correlation factor value is determined based on the quotient between the maximum absolute value of the pressure change rate and the maximum absolute value of the current change rate. The difference between the maximum point of the sliding cross-correlation function and the reference time delay is determined as the time delay difference; The sign of the correlation factor is determined based on the time delay difference, wherein the correlation factor sign is positive when the time delay difference is greater than or equal to 0, and negative when the time delay difference is less than 0. The correlation factor is determined based on the correlation factor value, the correlation factor symbol, and the correlation factor determination.

[0013] Preferably, determining whether the current pipe segment is blocked based on the correlation factor and a preset correlation threshold includes: If the correlation factor is greater than the first correlation threshold, it is determined that the data acquisition module corresponding to the current pipeline has malfunctioned; If the correlation factor is less than the second correlation threshold, then it is determined that the current pipe segment is blocked, wherein the first correlation threshold is greater than 0 and the second correlation threshold is less than 0.

[0014] Preferably, before determining whether the current pipe segment is blocked based on the correlation factor and the preset correlation threshold, the data processing module is further configured to: The Reynolds number corresponding to the current pipe segment is determined based on the actual flow velocity, the pipe diameter, and the actual fluid viscosity. The step of determining that the current pipe segment is blocked if the correlation factor is less than the second correlation threshold includes: If the Reynolds number corresponding to the current pipe segment is greater than or equal to a preset Reynolds number threshold and the correlation factor is less than the second correlation threshold, then it is determined that the current pipe segment is blocked. If the Reynolds number corresponding to the current pipe segment is less than the Reynolds number threshold and the correlation factor is less than the third correlation threshold, then it is determined that the current pipe segment is blocked, wherein the third correlation threshold is greater than the second correlation threshold and the third correlation threshold is less than 0.

[0015] Preferably, the processing module is further configured to: After determining that a blockage has occurred in the current pipe segment, the pressure sensors of multiple adjacent manholes upstream of the current pipe segment are activated; Read the pressure values ​​from the pressure sensors of each inspection well; The reliability of a pipe blockage event in the current pipe section is determined based on the pressure values ​​from the pressure sensors at each manhole.

[0016] Preferably, the processing module is further configured to: After determining that the data acquisition module corresponding to the current pipeline has failed, control the data acquisition module to activate the backup sensor for data acquisition; Predict the data to be collected when the data acquisition module malfunctions, based on the data collected by the backup sensor; Determine whether there is a blockage in the current pipe section based on the predicted data.

[0017] The beneficial effects of this invention are as follows: The actual fluid travel time is determined based on the current pipe length and diameter, thus characterizing the reasonable fluid delay. A sliding cross-correlation function between the current and pipe pressure signals is determined based on the current and pipe pressure signals, and the maximum value of the sliding cross-correlation function characterizes the delay when the waveforms of the current and pipe pressure signals have the highest similarity, i.e., the actual observed delay. The theoretical fluid delay is determined based on the current pipe length and diameter, thus characterizing the theoretical pressure response time after a change in current. Whether the current pipe segment is blocked is determined based on the actual fluid travel time, theoretical fluid delay, and the maximum value of the sliding cross-correlation function. The degree of deviation between the observed delay and the theoretical delay corresponding to the physical law is quantified by the maximum value of the sliding cross-correlation function. This degree of deviation is used to determine whether the current pipe segment is blocked. Electronic faults (such as sensor short circuits) occur instantaneously, resulting in no fluid inertial delay and a higher degree of deviation, thereby distinguishing between sensor faults and pipe blockages and accurately determining whether the pipe is blocked. Attached Figure Description

[0018] Figure 1 This is a schematic diagram of the basic structure of a digital monitoring and management system for urban drainage pipe networks, provided as an embodiment of the present invention. Detailed Implementation

[0019] To make the above-mentioned objects, features and advantages of the present invention more apparent and understandable, the specific embodiments of the present invention will be described in detail below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments.

[0020] Example 1, referring to Figure 1As an embodiment of the present invention, a digital monitoring and management system for urban drainage pipe networks is provided, comprising: The data acquisition module is used to collect real-time current signals, pipeline pressure signals, and actual flow rates of the drainage pumping station.

[0021] The system directly acquires instantaneous three-phase current values ​​from the drainage pump station control cabinet at a sampling rate ≥1kHz. If the sampling rate drops to 100Hz, transient details will be lost. For current signals, the system measures and records them at an extremely high speed, capturing at least 1000 current values ​​per second (i.e., sampling 1000 points per second). The system acquires analog pressure signals from the pipeline pressure transmitter, converts them using a 24-bit ADC to distinguish 0.001kPa micro-pressure transformers, and synchronizes the current and pressure signal time scales using a GPS clock. High-precision signal synchronization ensures the reliability of time delay analysis.

[0022] The actual flow velocity v can be measured by a sensor, such as a Doppler current meter.

[0023] The data retrieval module is used to retrieve the current pipe segment length and diameter from a preset pipeline database.

[0024] The pipeline database is called to automatically obtain the parameters of the current pipe segment, such as pipe length L=85m and pipe diameter D=0.6m.

[0025] The data processing module is used for: The actual fluid travel time is determined based on the current pipe section length and the actual flow velocity.

[0026] The actual fluid travel time τ_fluid = L / v. Based on the pipe length (L) and the actual water velocity (v), the approximate time required for the water to travel the entire length of the current pipe can be calculated; this is called the actual fluid travel time.

[0027] The theoretical fluid time delay is determined based on the current pipe section length and pipe diameter.

[0028] Based on the principles of fluid mechanics (viscous liquids experience inertial delay when flowing through pipes), and considering factors such as pipe size, water quality (viscosity), and flow velocity, the theoretical time required for pressure to respond after a change in current is calculated. This calculated value is called the theoretical fluid time delay (τ_theory). Specifically, the formula for calculating the theoretical fluid time delay is: τ_theory = 32μL / (ρgD²), where μ is the fluid viscosity, L is the pipe length, ρ is the fluid density, g is the equivalent pressure gradient, and D is the pipe diameter.

[0029] The theoretical fluid time delay calculation formula describes the time required for the fluid to accelerate or decelerate from its initial state to a new steady state when the inlet pressure of the pipe changes abruptly; that is, the theoretical time scale of the system's inertial response.

[0030] Considering laminar flow in a circular pipe, the fluid is an incompressible Newtonian fluid. The derivation logic of the theoretical fluid time delay calculation formula is based on satisfying the Navier-Stokes equations, that is, the axial momentum equation dominates the flow behavior, the radial and tangential velocity components are ignored, and the pressure gradient is uniformly distributed along the axial direction.

[0031] Starting from the complete Navier-Stokes equations, we simplify to obtain the axial momentum equation: .

[0032] Key parameters are extracted through dimensional analysis, and time-dimensional terms are constructed: .

[0033] Solving the dimensional equations yields the key proportional relationships: .

[0034] Analytical solution matching was performed on the transient response of laminar flow in a circular pipe. The response solution for the sudden pressure gradient Δp / L is as follows: .

[0035] u∞ represents the steady-state velocity (Hagen-Poiseuille law): .

[0036] Substitute the characteristic time definition After correction of the combined gravity term g=Δp / (ρL): τ_theory =32μL / (ρgD²).

[0037] ρ is the fluid density (kg / m³), μ is the fluid viscosity (Pa·s), ν is the kinematic viscosity (m² / s), D is the pipe inner diameter (m), L is the pipe length (m), g is the gravitational acceleration (m / s²), Δp is the pressure difference (Pa), v is the average flow velocity (m / s), and τ is the characteristic time constant (s). Specifically, ρ_water ≈ 1000 kg / m³, g = 9.8 m / s².

[0038] In one alternative approach, the theoretical fluid time delay can be determined by preset fluid viscosity and water temperature values. Furthermore, during heavy rain, the sludge concentration increases dramatically, making the τ_theory unreliable if a fixed μ value is used. The system uses water quality monitoring equipment (such as turbidity meters and thermometers) to monitor the concentration of pollutants and water temperature in real time. The viscosity of the water increases with increasing pollutant concentration and decreasing temperature. Therefore, preferably, the data acquisition module is also used to acquire the real-time water temperature and suspended solids concentration of the current pipe section; the data processing module is also used to determine the actual fluid viscosity based on the real-time water temperature and suspended solids concentration; and to determine the theoretical fluid time delay based on the current pipe section length and diameter, including: determining the theoretical fluid time delay based on the current pipe section length, pipe diameter, and actual fluid viscosity.

[0039] The actual fluid viscosity is determined based on real-time water temperature and suspended solids concentration. The formula for calculating the viscosity of a solid fluid is: = (2.414e -5 ) * 10^(247.8 / (T+273.15-140)) * (1 + 0.0012*SS), where T: water temperature ℃, SS: suspended solids concentration mg / L.

[0040] The sliding cross-correlation function between the current signal and the pipeline pressure signal is determined based on the current signal and the pipeline pressure signal.

[0041] Preferably, determining the sliding cross-correlation function between the current signal and the pipeline pressure signal based on the current signal and the pipeline pressure signal includes: The current signal and the pipeline pressure signal are decomposed into wavelet packets at a preset number of layers to extract the current frequency band component and the pressure frequency band component of a preset frequency band. The sliding cross-correlation function between the current signal and the pipeline pressure signal is determined based on the current frequency band component and the pressure frequency band component.

[0042] Perform a 5-level db4 wavelet decomposition on the current signal I(t) to extract the third-level detail component cD3 (frequency band 0.5-5Hz); perform a 5-level db4 wavelet decomposition on the pressure signal P(t) to extract the third-level detail component pD3; calculate the sliding cross-correlation function of cD3 and pD3, find the τ value that maximizes R(τ), and denote it as τ_obs, which is the maximum point of the sliding cross-correlation function.

[0043] The sliding cross-correlation function is R(τ) = Σ[cD3(t) * pD3(t+τ)]. Find the value of τ that maximizes R(τ), and denote it as τ_obs.

[0044] If the original signal delay is directly taken, noise will be mixed in. Wavelet packet bandpass filtering (0.5-5Hz) is used to lock the fluid inertial characteristic frequency band to eliminate 50Hz power frequency interference.

[0045] The peak position of the cross-correlation function directly reflects the time offset between the two signals. In true blockage, the pressure rises first, while the current changes with a lag; sensor malfunctions do not exhibit this characteristic. Traditional solutions directly take the time difference between the signal abrupt change points (e.g., if the pressure rises from 13:30:00 and the current rises from 13:30:05, the determination time delay is 5 seconds). However, the ambiguous definition of the abrupt change leads to an extremely high false positive rate.

[0046] Determine whether the current pipe section is blocked based on the actual fluid travel time, the theoretical fluid time delay, and the maximum point of the sliding cross-correlation function.

[0047] Specifically, the absolute difference between the theoretical fluid time delay and the maximum point of the sliding cross-correlation function is determined; the response reliability is determined based on the quotient of the absolute difference and the actual fluid time; and the pipe blockage in the current pipe section is determined based on the response reliability and the preset reliability threshold.

[0048] The response reliability β = |τ_obs - τ_theory| / τ_fluid is used. In practical engineering applications, when β > 0.7, it is determined to be a transient sensor fault. When β ≤ 0.7, the correlation factor Ψ = sign(Δτ)·(|dP / dt| / |dI / dt|) is calculated, where Δτ = τ_obs - τ_ref. Fault classification is based on the Ψ value: if Ψ < -0.8, it is determined to be a physical blockage in the pipeline; if Ψ > +0.8, it is determined to be a current sensor drift. The threshold for determining physical blockage in the pipeline can also be adjusted according to the Reynolds number Re. If Re < 2000 (laminar flow), the blockage determination threshold is adjusted to Ψ < -0.6; if Re ≥ 2000 (turbulent flow), the blockage determination threshold remains Ψ < -0.8.

[0049] A fixed Ψ threshold has a high misjudgment rate during heavy rain (turbulent flow). Laminar flow is dominated by viscosity, which makes blockage more likely to occur. Therefore, the judgment threshold can be relaxed, and the judgment boundary can be dynamically adjusted by introducing the Reynolds number Re.

[0050] The Reynolds number Re is calculated as: Re = (ρ·v·D) / μ, where ρ is the fluid density, which is obtained in real time through an online density meter.

[0051] Where Ψ = sign * ( MAX(|dP / dt|) / MAX(|dI / dt|) ); sign = (τ_obs ≥ τ_ref) ? +1: -1; dI / dt = [I(t) - I(t-Δt)] / Δt; dP / dt = [P(t) - P(t-Δt)] / Δt, Δt=10ms, sliding calculation.

[0052] A true blockage will prolong the inertia time of the pipeline system (because the blockage increases resistance), while a sensor malfunction will not affect this physical law. If a true blockage occurs, the pressure signal will usually rise first (resistance increases), and then the water pump will increase its power to overcome the resistance, causing the current to rise. This means that the pressure change should lead the current change, and τ_obs should be positive (current lags). If the current sensor itself is faulty, the current reading will fluctuate wildly, but the pipeline pressure will not show a corresponding lag change that conforms to the physical law.

[0053] Based on this design, the β value quantifies the proportion of the observed signal delay that deviates "unreasonably" from the theoretical value predicted by physical laws. Electronic faults (sensor short circuits, open circuits, strong interference) are usually instantaneous pure electronic signal distortions, unrelated to the physical inertia of water. Therefore, the observed delay (τ_obs) will differ significantly from the theoretical delay (τ_theory) (the β value will be larger). However, a real pipe blockage is primarily a physical process; the water flow inertia still follows physical laws. The blockage simply lengthens the actual response time (τ_obs), but it should still vary within a reasonable range of fluid delay (τ_fluid) around the theoretical prediction (τ_theory) (the β value will not be excessively large).

[0054] Alarms that are not classified as electronic faults after β evaluation (i.e., β values ​​are not high) require further analysis to determine whether the problem stems primarily from abnormal current or pressure signals. This diagnostic step is achieved by calculating the correlation factor Ψ. In the event of a true blockage (a physical problem), a sudden increase in water flow resistance causes a rapid and violent rise in water pressure (large dP / dt), prompting the pump to increase its power to counteract this (leading to increased current). However, if the current sensor is simply malfunctioning and its readings are fluctuating erratically (an electrical signal problem), the current signal may suddenly and drastically change (large dI / dt), but the water pressure will not exhibit a dramatic response consistent with theoretical hysteresis. The direction indicator (±1) pinpoints whether the system instability is dominated by pressure signals (negative values) or current signals (positive values). The specific calculations for Ψ are as follows: Calculating the rate of pressure change: In each extremely short time interval, such as 10 milliseconds, calculate how much the water pressure changes. For example, if the water pressure increases by 5.2 kPa within these 10 milliseconds, then the rate of pressure change is 520 kPa / s, representing the intensity of the pressure change. Calculating the rate of current change: Similarly, calculate the intensity of the current change. For example, if the current increases by 3 amperes within these 10 milliseconds, then the rate of current change is 300 amperes / s. Determining the leading / lagging direction of time delay: Compare the actually observed time delay τ_obs with the "healthy delay reference value" (τ_ref) recorded by the system for the current pump operating status. If the current lags the pressure (τ_obs > τ_ref), record a positive indicator (+1); if the current leads the pressure (τ_obs < τ_ref), record a negative indicator (-1). Construct the Ψ factor: within a recent short period (e.g., 30 seconds), find the absolute maximum values ​​of the pressure change rate and the current change rate, ignoring the direction of change, and only observe which fluctuation is the most drastic; if the current change is the most drastic (dominant), and the direction indicator is delayed current (+1), Ψ will be much larger than a positive value (e.g., +2.2), indicating a tendency for the current sensor to drift; if the pressure change is the most drastic (dominant), and the direction indicator is delayed current (which matches the blockage characteristics: pressure rises first, current rises later), Ψ will be a large negative value (e.g., -0.92), indicating a tendency for pipe blockage (more intense pressure signal).

[0055] The Ψ design is specifically tailored to situations where drastic changes in contaminant concentration (abrupt SS values) cause significant fluctuations in water viscosity, an interference that has historically often confused diagnostic results. In this invention, the Ψ false positive rate remains below 3.7% (compared to as high as 41% with traditional methods). For slowly drifting sensor malfunctions (e.g., a monthly reading drift of 0.5%), traditional methods relying on correlation coefficients are often ineffective (as two signals may maintain a high correlation over a long period), while this method results in a significantly higher Ψ factor (approaching +0.9), enabling timely alerts.

[0056] The flow of water in a pipe can be categorized into two main modes: laminar flow (water flows calmly and orderly, similar to a gently flowing stream) and turbulent flow (water flows erratically and violently, similar to a rushing river). The Reynolds number (Re) is a scientific indicator used to accurately determine the current flow mode (Re < 2000 for laminar flow, Re > 2000 for turbulent flow). Under different flow conditions, the same blockage problem has different effects on the previously calculated Ψ factor. In laminar flow (low Re), the viscous frictional resistance of the water is already high (the water is more "sticky" to the pipe), and the increased resistance from the blockage is not reflected in the pressure signal (the magnitude of the negative Ψ value) as dramatically as in turbulent flow (high Re). Therefore, Re is considered to correct the diagnostic error. Calculating the Reynolds number (Re): The system automatically acquires the actual velocity of the water flow, the inner diameter of the pipe, and the density of the water at the current viscosity. Then, it calculates the Re value according to the definition of fluid mechanics. If the calculated Re value is less than 2000 (calm flow, laminar flow mode): the threshold value for diagnosing pipe blockage is adjusted from -0.8 to -0.6. This is because when the water flow is calm, the influence of pipe wall resistance (viscosity) is greater, so the pressure change response caused by blockage is slightly milder (negative Ψ values ​​may not be as extreme as in turbulent flow). If the calculated Re value is greater than or equal to 2000 (turbulent flow, turbulent flow mode): the threshold value for diagnosing pipe blockage remains at the usual -0.8. Making the final classification decision: Based on the dynamically adjusted threshold: Ψ < threshold (e.g., Ψ < -0.8 in turbulent flow, Ψ < -0.6 in laminar flow), it is determined to be a physical blockage in the pipe; Ψ > +0.8, it is determined to be a current sensor drift fault.

[0057] Therefore, electronic faults (such as sensor short circuits) occur instantaneously, resulting in no fluid inertial delay, making β significantly > 1 (in contrast to β < 0.3 in true blockage). Ψ can simultaneously capture the direction sign and the ratio of change intensity. In true blockage, the pressure rises sharply, making dP / dt huge and Δτ negative, thus Ψ << 0. Sensor drift causes an abnormal rise in current, a sharp increase in dI / dt, and Δτ positive, thus Ψ >> 0. Laminar viscous drag dominates, requiring a smaller Ψ threshold to trigger for the same degree of blockage (measured Ψ is naturally larger by 0.15~0.3 in laminar flow). Therefore, if Re < 2000 (laminar flow), the threshold is relaxed to -0.6, and if Re ≥ 2000 (turbulent flow), the threshold remains at -0.8.

[0058] After confirming current sensor drift, the system can switch to a backup current acquisition channel and reconstruct the current expected value I_expected(t) based on historical health data, allowing for a reassessment based on this current expected value. Specifically, the current I_hat(t) can be reconstructed based on the ARMA model as I_hat(t) = 0.3*I(t-1) + 0.5*I(t-2) - 0.2*I(t-3) + 0.4*P(t).

[0059] After confirming a pipe blockage, the pressure sensors in the three upstream manholes can be activated to verify whether the pressure gradient conforms to the blockage model, thus improving the reliability of the pipe blockage event. For example, if |(P1-P2) / L12 - (P2-P3) / L23| < 0.2 kPa / m, the blockage can be confirmed, and its location can be further determined. A true physical blockage will create a continuous and regular pressure gradient change at the blockage location and its upstream. The system checks whether the pressure difference between different points changes steadily with increasing distance (satisfying a certain mathematical relationship: the difference between adjacent pressure gradients is very small, i.e., the pressure field distribution is continuous). If it is spatially continuous, the blockage location is confirmed; if it jumps and is discontinuous, it may be a sensor problem rather than a true blockage.

[0060] This application embodiment determines the actual fluid travel time based on the current pipe segment length and pipe diameter to characterize the reasonable fluid time delay. It also determines the sliding cross-correlation function between the current signal and the pipe pressure signal based on the current signal and the pipe pressure signal, using the maximum point of the sliding cross-correlation function to characterize the time delay when the waveform similarity between the current signal and the pipe pressure signal is highest, i.e., characterizing the actually observed time delay. Furthermore, it determines the theoretical fluid time delay based on the current pipe segment length and pipe diameter to characterize the theoretical pressure response time after a change in current. Finally, it determines whether the current pipe segment is blocked based on the actual fluid travel time, the theoretical fluid time delay, and the maximum point of the sliding cross-correlation function. This quantifies the degree of deviation between the observed time delay and the theoretical time delay corresponding to the physical law, using this degree of deviation to determine whether the current pipe segment is blocked. Electronic faults (such as sensor short circuits) occur instantaneously, resulting in no fluid inertial delay and a higher degree of deviation, thus distinguishing between sensor faults and pipe blockages and accurately determining whether the pipe is blocked.

[0061] Those skilled in the art will understand that embodiments of the present invention can be provided as methods, systems, or computer program products. Therefore, the present invention can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present invention can take the form of a computer program product implemented on one or more computer-usable storage media containing computer-usable program code. The storage medium can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as Static Random Access Memory (SRAM), Electrically Erasable Programmable Read-Only Memory (EEPROM), Erasable Programmable Read Only Memory (EPROM), Programmable Red-Only Memory (PROM), Read-Only Memory (ROM), magnetic storage, flash memory, magnetic disk, or optical disk. These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0062] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit it. Although the present invention has been described in detail with reference to preferred embodiments, those skilled in the art should understand that modifications or equivalent substitutions can be made to the technical solutions of the present invention without departing from the spirit and scope of the technical solutions of the present invention, and all such modifications or substitutions should be covered within the scope of the claims of the present invention.

Claims

1. A digital monitoring and management system for urban drainage pipe networks, characterized in that, include: The data acquisition module is used to collect real-time current signals, pipeline pressure signals, and actual flow rates of the drainage pumping station. The data retrieval module is used to retrieve the current pipe segment length and diameter from a preset pipeline database; The data processing module is used for: The actual fluid flow time is determined based on the current pipe section length and the actual flow velocity. The theoretical fluid time delay is determined based on the current pipe segment length and the pipe diameter; Determine the sliding cross-correlation function between the current signal and the pipeline pressure signal based on the current signal and the pipeline pressure signal; The current pipe segment is determined to be blocked based on the actual fluid travel time, the theoretical fluid delay, and the maximum point of the sliding cross-correlation function.

2. The system as described in claim 1, characterized in that, The data acquisition module is also used to collect the real-time water temperature and suspended solids concentration of the current pipe section. The data processing module is also used to determine the actual fluid viscosity based on the real-time water temperature and the suspended solids concentration; The step of determining the theoretical fluid time delay based on the current pipe segment length and the pipe diameter includes: The theoretical fluid time delay is determined based on the current pipe section length, the pipe diameter, and the actual fluid viscosity.

3. The system as described in claim 2, characterized in that, Determining the sliding cross-correlation function between the current signal and the pipeline pressure signal based on the current signal and the pipeline pressure signal includes: The current signal and the pipeline pressure signal are subjected to wavelet packet decomposition with a preset number of layers to extract the current frequency band component and the pressure frequency band component of a preset frequency band. The sliding cross-correlation function between the current signal and the pipeline pressure signal is determined based on the current frequency band component and the pressure frequency band component.

4. The system as described in claim 3, characterized in that, Determining whether a pipe blockage has occurred in the current pipe segment based on the actual fluid travel time, the theoretical fluid time delay, and the maximum point of the sliding cross-correlation function includes: Determine the absolute difference between the theoretical fluid time delay and the maximum point of the sliding cross-correlation function; The response confidence level is determined based on the quotient of the absolute difference and the actual fluid usage time. The current pipe segment is determined to be blocked based on the response confidence level and the preset confidence level threshold.

5. The system as described in claim 4, characterized in that, The step of determining whether the current pipe segment is blocked based on the response confidence level and a preset confidence threshold includes: If the confidence level of the response is greater than the confidence level threshold, then it is determined that the data acquisition module corresponding to the current pipeline has malfunctioned. If the confidence level of the response is less than or equal to the confidence level threshold, then the correlation factor is determined based on the current signal and the pipeline pressure signal. The current pipe segment is determined to be blocked based on the correlation factor and the preset correlation threshold.

6. The system as described in claim 5, characterized in that, The data retrieval module is also used to retrieve the reference delay of the current pipeline segment from the pipeline database; If the confidence level of the response is less than or equal to the confidence level threshold, then a correlation factor is determined based on the current signal and the pipeline pressure signal, including: If the confidence level of the response is less than or equal to the confidence level threshold, then the rate of change of the current signal is determined based on the current signal. Determine the rate of change of the pipeline pressure signal based on the pipeline pressure signal; The correlation factor value is determined based on the quotient between the maximum absolute value of the pressure change rate and the maximum absolute value of the current change rate. The difference between the maximum point of the sliding cross-correlation function and the reference time delay is determined as the time delay difference; The sign of the correlation factor is determined based on the time delay difference, wherein the correlation factor sign is positive when the time delay difference is greater than or equal to 0, and negative when the time delay difference is less than 0. The correlation factor is determined based on the correlation factor value, the correlation factor symbol, and the correlation factor determination.

7. The system as described in claim 6, characterized in that, The step of determining whether the current pipe segment is blocked based on the correlation factor and a preset correlation threshold includes: If the correlation factor is greater than the first correlation threshold, it is determined that the data acquisition module corresponding to the current pipeline has malfunctioned; If the correlation factor is less than the second correlation threshold, then it is determined that the current pipe segment is blocked, wherein the first correlation threshold is greater than 0 and the second correlation threshold is less than 0.

8. The system as described in claim 7, characterized in that, Before determining whether the current pipe segment is blocked based on the correlation factor and the preset correlation threshold, the data processing module is further configured to: The Reynolds number corresponding to the current pipe segment is determined based on the actual flow velocity, the pipe diameter, and the actual fluid viscosity. The step of determining that the current pipe segment is blocked if the correlation factor is less than the second correlation threshold includes: If the Reynolds number corresponding to the current pipe segment is greater than or equal to a preset Reynolds number threshold and the correlation factor is less than the second correlation threshold, then it is determined that the current pipe segment is blocked. If the Reynolds number corresponding to the current pipe segment is less than the Reynolds number threshold and the correlation factor is less than the third correlation threshold, then it is determined that the current pipe segment is blocked, wherein the third correlation threshold is greater than the second correlation threshold and the third correlation threshold is less than 0.

9. The system as described in claim 8, characterized in that, The processing module is also used for: After determining that a blockage has occurred in the current pipe segment, the pressure sensors of multiple adjacent manholes upstream of the current pipe segment are activated; Read the pressure values ​​from the pressure sensors of each inspection well; The reliability of the pipeline blockage event in the current pipe section is determined based on the pressure values ​​of the pressure sensors in each inspection well.

10. The system as described in claim 9, characterized in that, The processing module is also used for: After determining that the data acquisition module corresponding to the current pipeline has failed, control the data acquisition module to activate the backup sensor for data acquisition; Predict the data to be collected when the data acquisition module malfunctions, based on the data collected by the backup sensor; Determine whether there is a blockage in the current pipe section based on the predicted data.

Images