Method and system for pressure monitoring of long distance water pipelines

Abstract

The present application relates to the technical field of pipeline monitoring, and particularly relates to a pressure monitoring method and system for long-distance water delivery pipeline, which comprises the following steps: collecting pressure time series signals of the water delivery pipeline; calculating the equivalent impedance of the boundary node based on the static topology model and real-time operation state parameters, and calculating the pressure wave reflection coefficient of the boundary node based on the equivalent impedance; triggering a suspected transient event in response to the pressure time series signals, performing forward numerical simulation based on the pressure wave reflection coefficient, extracting cross-correlation matching features, subtracting the reflection component from the pressure time series signals according to the corresponding cross-correlation matching features to obtain a residual transient signal; extracting the time difference based on the residual transient signal to calculate the distance of the abnormal source, and extracting the peak amplitude based on the residual transient signal to perform hierarchical determination. The present application significantly improves the reliability of abnormal source positioning in long-distance complex topology pipeline.

Description

Technical Field

[0001] This invention relates to the field of pipeline monitoring technology, specifically to a pressure monitoring method and system for long-distance water transmission pipelines. Background Technology

[0002] Long-distance water pipelines are core infrastructure for regional water resource allocation, especially in inland provinces with significant topographic relief and uneven water resource distribution. A single water transmission trunk line often stretches for tens or even hundreds of kilometers, traversing complex terrains such as mountains and ravines. The pipelines are subjected to continuous operating pressure under high head and large flow rates. Once a pipeline leaks or bursts, it not only causes a large loss of water resources but may also trigger geological disasters or secondary safety accidents. Therefore, real-time online monitoring of pipeline pressure status has extremely high engineering value.

[0003] Current technologies generally employ pipeline monitoring schemes based on pressure transient analysis, deploying high-frequency pressure sensors at intervals along the pipeline, with sampling frequencies typically ranging from 64Hz to 256Hz. When a leak or rupture occurs in the pipeline, the anomaly point synchronously generates pressure transient waves, i.e., water hammer waves, which propagate towards both ends at a water hammer wave velocity of approximately 1200m / s to 1400m / s. By measuring the time difference between the arrival of the transient wave at two adjacent sensors, and combining this with the known wave velocity and sensor spacing, the location of the anomaly source can be calculated using the time difference of arrival formula. This method has already seen relatively mature engineering applications in short-distance, simple-topology pipe sections.

[0004] However, in the actual operation of long-distance water pipelines, multiple intermediate boundary nodes are inevitably set along the pipeline route, including pressure regulating valves, maintenance valves, booster pump stations, and cross-sections with abrupt changes in pipe diameter. When pressure transient waves propagate to these nodes, reflection occurs due to the mismatch in hydraulic impedance between the two sides of the pipeline, generating secondary reflected waves. Operating parameters such as valve opening and pump station operating speed continuously change dynamically during actual scheduling, causing the hydraulic impedance of each boundary node to drift in real time, thus affecting the accurate removal of reflected interference. The corresponding reflection coefficient is not a constant value. When the operating state changes, a deviation occurs between the arrival time of the reflected wave predicted based on the static reflection coefficient and the actual arrival time. The residual reflected wave component and the primary transient wave excited by the real anomaly source are highly aliased in the time domain. The time difference of arrival algorithm extracts the time difference from this aliased signal, which is actually the mixed time difference of the primary wave and the residual reflected wave, rather than the pure time difference from the real anomaly source to the two sensors. Ultimately, this leads to a systematic shift or even complete failure of the positioning results, resulting in missed or false alarms. Summary of the Invention

[0005] To address the existing technical problem that the reflection coefficients of multiple intermediate boundary nodes in long-distance water transmission pipelines dynamically change with operating conditions, leading to the failure of pressure transient wave source localization, this invention provides a pressure monitoring method and system for long-distance water transmission pipelines.

[0006] In a first aspect, the present invention provides a pressure monitoring method for a long-distance water transmission pipeline, comprising: acquiring a static topology model of the water transmission pipeline and real-time operating status parameters of boundary nodes, and collecting pressure time-series signals of the water transmission pipeline; calculating the equivalent impedance of the boundary nodes based on the static topology model and the real-time operating status parameters, and calculating the pressure wave reflection coefficient of the boundary nodes based on the equivalent impedance; responding to a suspected transient event triggered by the pressure time-series signal, performing forward numerical simulation based on the pressure wave reflection coefficient, extracting cross-correlation matching features, subtracting the reflection component from the pressure time-series signal according to the corresponding cross-correlation matching features to obtain a residual transient signal; extracting the time difference based on the residual transient signal to calculate the distance to the anomaly source, and extracting the peak amplitude based on the residual transient signal for graded judgment.

[0007] By tracking the hydraulic impedance of each boundary node in real time and accurately removing known boundary reflection interference from the original pressure signal, the pipeline pressure status is monitored. This effectively reduces the impact of reflection interference while ensuring positioning accuracy, thus significantly improving the reliability of anomaly source location in long-distance, complex topology pipelines.

[0008] Preferably, the step of obtaining the static topology model of the water transmission pipeline and the real-time operating status parameters of the boundary nodes includes: constructing the static topology model of the water transmission pipeline, recording the pipe segment parameters and boundary element parameters; continuously polling the real-time operating status parameters of each boundary node, wherein the real-time operating status parameters include the current opening percentage of the valve node, and the current rotational speed and inlet / outlet pressure difference of the pump station node.

[0009] Preferably, the step of calculating the equivalent impedance of the boundary node based on the static topology model and the real-time operating state parameters includes: introducing the valve flow coefficient as a characterizing quantity of the opening change according to the valve factory calibration curve; and dynamically correcting the denominator of the baseline formula of the valve steady-state equivalent impedance by multiplying it by the valve flow coefficient to obtain the equivalent impedance of the valve node.

[0010] The hydraulic impedance of each boundary node is upgraded from a static constant to an instantaneous variable dynamically derived from the existing engineering hydraulic baseline formula, so that the reflection coefficient can closely follow the actual scheduling state drift and eliminate the mismatch between the static reflection coefficient and the actual working condition.

[0011] Preferably, the step of calculating the equivalent impedance of the boundary node based on the static topology model and the real-time operating state parameters further includes: solving the instantaneous flow rate based on the current rotational speed and rated rotational speed of the pump station node, combined with the pump similarity law; calculating the steady-state impedance baseline based on the instantaneous flow rate and the measured instantaneous pressure difference, and obtaining the equivalent impedance of the pump station node.

[0012] Preferably, the step of calculating the pressure wave reflection coefficient of the boundary node based on the equivalent impedance includes: determining the characteristic impedance of the pipe segment according to the elastic water hammer theory; and calculating the pressure wave reflection coefficient of the boundary node based on the characteristic impedance of the incident side pipe segment and the equivalent impedance of the transmission side.

[0013] Preferably, the step of triggering a suspected transient event in response to the pressure time series signal includes: calculating the upper quartile and lower quartile of the steady-state pressure sequence and obtaining the interquartile range; taking the trigger threshold as the sum of 1.5 times the upper quartile and the interquartile range according to the Tukey criterion; and determining a suspected transient event in response to the appearance of a sudden change component in the pressure time series signal with an amplitude exceeding the trigger threshold.

[0014] Preferably, the step of performing forward numerical simulation based on the pressure wave reflection coefficient, extracting cross-correlation matching features, and subtracting the reflection component from the pressure time series signal according to the corresponding cross-correlation matching features to obtain the residual transient signal includes: performing forward numerical simulation of the pipeline using the characteristic line method with the pressure wave reflection coefficient to generate a theoretical response waveform; extracting the cross-correlation matching features between the simulated response waveform and the measured waveform; and gradually identifying and subtracting the reflection component contributed by each boundary node from the measured signal according to the corresponding cross-correlation matching features to obtain the residual transient signal at each monitoring unit.

[0015] By progressively stripping away known boundary reflections through forward numerical simulation, the input signal of the time difference of arrival algorithm is restored to a pure state containing only the primary wave of the real anomaly source, thus improving the reliability of anomaly source localization under long-distance complex topology pipelines.

[0016] Preferably, the step of extracting the time difference based on the residual transient signal to calculate the distance to the anomaly source includes: performing a generalized cross-correlation operation on the residual transient signals at two adjacent monitoring units to extract the time difference of arrival of a transient wave; and calculating the distance to the anomaly source based on the time difference, the pipe length between adjacent monitoring units, and the water hammer wave velocity.

[0017] Preferably, the step of extracting the peak amplitude based on the residual transient signal for classification includes: extracting the peak amplitude of a first transient wave in the residual transient signal; constructing an instantaneous reference amplitude using the water hammer formula as a baseline, and dividing the peak amplitude by the instantaneous reference amplitude to obtain a normalized anomaly intensity index; and performing a three-level classification based on the relative position of the normalized anomaly intensity index and the classification threshold.

[0018] The benchmark amplitude of the normalized anomaly intensity index is generated synchronously with the real-time flow velocity based on the existing water hammer formula, which makes the intensity criterion adaptable to the operating conditions and reduces false alarms and false negatives in variable flow scenarios.

[0019] Secondly, the present invention provides a pressure monitoring system for a long-distance water pipeline, including a processor and a memory, wherein the memory stores computer program instructions, and when the computer program instructions are executed by the processor, the aforementioned pressure monitoring method for a long-distance water pipeline is implemented.

[0020] By adopting the above technical solution, a computer program for the pressure monitoring method of a long-distance water pipeline is generated and stored in a memory so that it can be loaded and executed by a processor. A terminal device can then be made based on the memory and the processor for convenient use.

[0021] This invention adjusts the hydraulic impedance of each boundary node from a static constant to an instantaneous variable dynamically derived based on existing engineering hydraulic baseline formulas, enabling the reflection coefficient to closely follow the actual scheduling state drift and eliminating the mismatch between the static reflection coefficient and the actual working conditions.

[0022] By progressively stripping away known boundary reflections through forward numerical simulation, the input signal of the time-of-arrival algorithm is restored to a pure state containing only the primary wave of the real anomaly source. The benchmark amplitude of the normalized anomaly intensity index is generated synchronously with the real-time flow velocity based on the existing water hammer formula, making the intensity criterion adaptable to operating conditions. This reduces false alarms and missed alarms in variable flow scenarios and improves the reliability of anomaly source location under long-distance complex topology pipelines. Attached Figure Description

[0023] The above and other objects, features, and advantages of exemplary embodiments of the present invention will become readily apparent upon reading the following detailed description with reference to the accompanying drawings. In the drawings, several embodiments of the invention are illustrated by way of example and not limitation, and like or corresponding reference numerals denote like or corresponding parts, wherein:

[0024] Figure 1 This is a flowchart illustrating a pressure monitoring method for long-distance water pipelines according to the present invention.

[0025] Figure 2 This is a comparison chart showing the trend of normalized positioning error changing with the test condition number under multiple working conditions between the existing method and the method of the present invention in the embodiments of the present invention. Detailed Implementation

[0026] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0027] The specific embodiments of the present invention will now be described in detail with reference to the accompanying drawings.

[0028] This invention discloses a pressure monitoring method for long-distance water transmission pipelines, referring to... Figure 1 This includes steps S1-S4:

[0029] S1. Pipeline topology modeling and real-time acquisition of boundary node status.

[0030] In an optional embodiment, during the system initialization phase, the as-built drawings and field survey data of the water pipeline can be integrated to construct a static topology model of the pipeline in the form of a directed graph. Each directed edge in the graph corresponds to a homogeneous pipe segment, and its pipe diameter is recorded. Wall thickness Pipe elastic modulus Pipe section length and design flow Each node in the diagram corresponds to a boundary element, including pressure regulating valves, maintenance valves, booster pump stations, or pipe diameter abrupt change sections, and its type identification and installation location mileage station are recorded. The accuracy of the static topology model directly determines the reliability of subsequent boundary node impedance calculations. Therefore, during the data entry stage, the as-built drawings and on-site measured data need to be cross-checked, and the on-site measured values ​​should be used as the standard for pipe section parameters where there are discrepancies.

[0031] After the pipeline is officially put into monitoring operation, the real-time operating status parameters of each boundary node are continuously polled at time intervals no less than the preset polling frequency via industrial Ethernet or 4G / 5G wireless channel. For example, the preset polling frequency can be 1Hz. For valve nodes, their current opening percentage is collected. For pump station nodes, their current rotational speed is collected. and inlet / outlet pressure difference For pipe sections with abrupt changes in diameter, their geometric parameters are fixed and do not require dynamic acquisition. The aforementioned real-time state parameters, together with the static topology model, constitute a snapshot of the pipeline's dynamic operating state, serving as the input basis for subsequent boundary node hydraulic impedance calculations.

[0032] Furthermore, a high-frequency pressure monitoring unit is deployed at preset intervals along the pipeline at boundary nodes. The specific interval is adaptively determined based on the total pipeline length and terrain complexity; for example, the preset interval can be 5km to 15km. Each unit integrates a piezoresistive pressure sensor with a range of not less than 2.5MPa. The sampling frequency is preset based on the frequency characteristics of water hammer waves; for example, the sampling frequency can be set to 256Hz. It is also equipped with a local clock synchronization module, which uses GPS timing to control the clock synchronization accuracy to a preset level that meets the positioning accuracy requirements; for example, the clock synchronization accuracy can be controlled to be better than 1μs. Since the subsequent time difference of arrival calculation is extremely sensitive to the consistency of the time base of each monitoring unit, clock drift will directly introduce positioning errors.

[0033] In this way, through the coordinated use of static topology modeling and dynamic state polling, the system can obtain a complete snapshot containing both pipeline geometric parameters and the instantaneous operating status of each boundary node in each sampling period, thus providing a complete and time-aligned input basis for subsequent impedance dynamic calculation.

[0034] S2, Dynamic calculation of boundary node impedance.

[0035] For each homogeneous pipe segment in the pipeline, according to the elastic water hammer theory, its characteristic impedance is... Determined by existing formulas: ;in The water hammer wave velocity of this pipe section, The density of water, It is the acceleration due to gravity. The cross-sectional area of ​​the pipe section is the flow area. All the above parameters are directly read from the static topology model and are fixed physical quantities.

[0036] For valve nodes, their equivalent hydraulic resistance With opening degree In the field of engineering hydraulics, the existing baseline formula for the steady-state equivalent impedance of a valve is the ratio of pressure difference to flow rate. ;in and These represent the design differential pressure and design flow rate of the valve under rated operating conditions, respectively. Since this baseline formula only applies to steady-state scenarios with a constant valve opening, this invention introduces a valve flow coefficient based on the valve's factory calibration curve. As an objective measure of changes in aperture. With opening The mapping relationship is stored in the system database as a piecewise linear interpolation table. The equivalent impedance is negatively correlated with the valve opening degree. Based on this physical correspondence, the denominator of the existing baseline formula is dynamically corrected by multiplying it by the valve flow coefficient to obtain the improved formula for the valve equivalent impedance:

[0037]

[0038] For pump station nodes, their equivalent impedance The derivation uses the existing steady-state impedance equation of the pump and the existing similarity law as dual baselines. The existing steady-state impedance baseline is: ;in , For the pump station at its rated speed The design pressure differential and design flow rate are given by the flow rate term from the existing pump similarity law:

[0039]

[0040] The instantaneous flow rate at the current rotational speed can be solved as follows: The instantaneous flow rate and the measured instantaneous pressure difference are compared. Substituting the steady-state impedance baseline and rearranging, we obtain the improved formula for the equivalent impedance of the pump station:

[0041]

[0042] The improved formula replaces the rated pressure difference in the numerator with the measured instantaneous pressure difference, reflecting the current actual working state of the pump station; at the same time, it multiplies the instantaneous speed ratio in the denominator to reflect the flow drift under the similarity law.

[0043] Within each sampling period, the system updates the impedance of all boundary nodes along the entire line using the method described above, forming a set of impedance sequences that evolve continuously over time. Subsequently, for each adjacent pipe segment in the pipeline topology diagram... Boundary nodes The pressure wave reflection coefficient at the current moment is calculated using the following formula. :

[0044]

[0045] in The characteristic impedance of the incident side pipe section is a fixed value. It is the equivalent impedance on the transmission side, including the dynamic component of the valve or pump station.

[0046] Thus, by combining existing hydraulic baseline formulas, real-time collected valve opening, pump station speed, and inlet / outlet pressure difference, the system can obtain a set of dynamic reflection coefficients that strictly correspond to the current scheduling state in each sampling cycle, eliminating the mismatch between static reflection coefficients and actual operating conditions, and laying the foundation for accurate removal of subsequent reflection interference.

[0047] S3. Gradual stripping of known boundary reflections based on forward numerical simulation.

[0048] In this optional embodiment, the triggering criteria for suspected transient events can be derived in real time from the rolling window steady-state pressure data based on Tukey's objective anomaly criteria. Each pressure monitoring unit continuously maintains a sliding statistical window, the window length of which is preset and determined according to the pipeline scheduling cycle. For example, the window length can be taken as the steady-state pressure sequence of the past 24 hours, and the upper quartile of the sequence is calculated in real time. and lower quartile And from this, we can obtain the interquartile range:

[0049]

[0050] According to the Tukey criteria, the trigger threshold is set as follows:

[0051]

[0052] In response to any monitoring unit acquiring a pressure timing signal with an amplitude exceeding The system identifies the sudden change component as a suspected transient event. This criterion is generated by the statistical characteristics of the current pipe section's steady-state operating data, and is automatically updated as the operating conditions drift, and is strongly bound to the operation scheduling status.

[0053] In response to a suspected event, the system initiates synchronous capture of pressure data across the entire pipeline. The capture window length is based on the total pipeline length. With wave speed Adaptive determination This ensures that all data from a single transient wave during a complete round-trip propagation cycle are included in the analysis window.

[0054] Within the analysis window, the system uses the suspected event trigger time as a starting point and the already calculated sequence of reflection coefficients for all boundary nodes along the entire line. The method of characteristics is used to perform forward numerical simulation of the pipeline. Assume a virtual location on the pipeline... A pressure pulse of unit intensity is applied at a given location. The theoretical response waveform generated at each monitoring unit is calculated after reflection and transmission through each boundary node during the propagation of this pulse along the entire line. The cross-correlation matching characteristics between the simulated and measured response waveforms are extracted. Based on these characteristics, the reflected components contributed by each boundary node are gradually identified and subtracted from the measured signals to obtain the residual transient signals at each monitoring unit. .

[0055] It should be noted that there are many other ways to achieve forward simulation in this field, and those skilled in the art can choose different time steps and spatial discretization precisions according to the actual topological complexity of the pipeline and the computing resource conditions.

[0056] Because the dynamic interference from known boundary reflections is stripped away in real time, the residual signal The non-zero components remaining in the residual signal originate only from a transient wave excited by a real anomaly point in the pipeline, thus improving the signal-to-noise ratio of the residual signal and providing a clean input for subsequent precise positioning.

[0057] Thus, by combining the dynamic reflection coefficient sequence with forward numerical simulation, the system identifies and strips the reflections of the known boundary along the entire line step by step, so that the input signal of the subsequent time-of-arrival algorithm returns to a pure state containing only the primary wave of the real anomalous source.

[0058] S4. Location of residual signal anomaly sources and adaptive hierarchical early warning.

[0059] Next, for two adjacent monitoring units and residual signal at and Perform generalized cross-correlation to extract the time difference of arrival of a transient wave from the two residual signals. Since the residual signal has undergone reflection interference removal, the extracted signal... This directly corresponds to the pure propagation time difference from the actual anomaly source to the two monitoring units; therefore, by using the above... Substituting into the following formula, we obtain the distance from the anomaly source to the upstream monitoring unit. distance :

[0060]

[0061] in The length of the pipe section between two adjacent monitoring units. This represents the water hammer wave velocity of this pipe section.

[0062] After completing the position calculation, the peak amplitude of the first transient wave in the residual signal can be extracted. Because the amplitude of water hammer waves varies across different pipe sections and operating flow rates, using a fixed absolute value as the intensity criterion would result in numerous false alarms at low flow rates and missed alarms at high flow rates. Therefore, an instantaneous reference amplitude is constructed by introducing the existing Joukowsky water hammer formula as a baseline.

[0063]

[0064] in The density of water, The water hammer wave velocity of this pipe section, This represents the instantaneous flow velocity of the current pipe segment. The instantaneous flow velocity is determined by the real-time collected current flow rate. With respect to the cross-sectional area of ​​the pipe section Perform the calculation: Therefore, a normalized anomaly intensity index is constructed:

[0065]

[0066] This represents the degree of deviation between the measured residual amplitude and the theoretical water hammer benchmark at the current flow rate. The larger the value, the more severe the abnormal event. This index causes the intensity criterion to drift synchronously with the current operating flow rate.

[0067] against The classification criteria are used to calculate the median of the normalized anomaly intensity index historical sequence collected during the past steady-state operation period of the pipeline section. Absolute deviation from the median And thus construct a two-level hierarchical threshold:

[0068]

[0069]

[0070] in accordance with A three-level determination is made based on the relative position to the above two-level thresholds: when Below When this occurs, it indicates a minor leak, and the processor will send a check notification; when Between and When the leakage rate is between 0 and 1, it indicates a moderate leakage, at which point the processor will trigger a flow-limiting operation on the nearest valve; when... Exceed When this occurs, it indicates a risk of pipe burst. At this time, the processor will trigger the upstream pumping station to reduce its speed to maintain pressure and send an emergency alarm to the dispatch center. At the same time, it will also report the location of the abnormal source, the current operating pressure of the pipe section, and the estimated leakage flow. and The data is updated continuously along with the steady-state data of this pipe section.

[0071] like Figure 2 The figure shown is a comparison of the normalized positioning error of the existing method and the method of the present invention under multiple working conditions with the test working condition number. It can be observed that the positioning error of the existing method fluctuates greatly under each working condition and is at a high level overall, while the positioning error of the method of the present invention remains at a low and stable range under each working condition, indicating that the method of the present invention has stronger positioning stability and reliability under changing operating conditions.

[0072] In this way, while accurately locating the source of the anomaly, the system classifies the abnormal events according to an adaptive threshold that strictly corresponds to the current operating traffic, thereby reducing false alarms and missed alarms in variable traffic scenarios.

[0073] This invention also discloses a pressure monitoring system for long-distance water pipelines, including a processor and a memory. The memory stores computer program instructions, which, when executed by the processor, implement a pressure monitoring method for long-distance water pipelines according to the present invention.

Claims

1. A method for pressure monitoring of long-distance water transmission pipelines, characterized in that, include: Obtain the static topology model of the water transmission pipeline and the real-time operating status parameters of the boundary nodes, and collect the pressure time-series signal of the water transmission pipeline; Based on the static topology model and the real-time operating status parameters, the equivalent impedance of the boundary node is calculated, and the pressure wave reflection coefficient of the boundary node is calculated based on the equivalent impedance. In response to a suspected transient event triggered by the pressure time series signal, a forward numerical simulation is performed based on the pressure wave reflection coefficient to extract cross-correlation matching features. The reflection component is then subtracted from the pressure time series signal according to the corresponding cross-correlation matching features to obtain the residual transient signal. The time difference is extracted based on the residual transient signal to calculate the distance to the anomaly source, and the peak amplitude is extracted based on the residual transient signal for classification.

2. The pressure monitoring method for a long-distance water transmission pipeline according to claim 1, characterized in that, The acquisition of the static topology model and real-time operating status parameters of the water pipeline and its boundary nodes includes: Construct a static topology model of the water pipeline and record the pipe segment parameters and boundary element parameters; The system continuously polls the real-time operating status parameters of each boundary node, including the current opening percentage of the valve node and the current rotational speed and inlet / outlet pressure difference of the pump station node.

3. The pressure monitoring method for a long-distance water transmission pipeline according to claim 1, characterized in that, The calculation of the equivalent impedance of the boundary node based on the static topology model and the real-time operating state parameters includes: The valve flow coefficient is introduced as a characterizing quantity of the opening change based on the valve's factory calibration curve; The equivalent impedance of the valve node is obtained by dynamically correcting the denominator of the baseline formula for the steady-state equivalent impedance of the valve by multiplying the valve flow coefficient.

4. The pressure monitoring method for a long-distance water pipeline according to claim 1, characterized in that, The calculation of the equivalent impedance of the boundary node based on the static topology model and the real-time operating state parameters further includes: Based on the current and rated speeds of the pump station nodes, the instantaneous flow rate is solved using the pump similarity law; The steady-state impedance baseline is calculated based on the instantaneous flow rate and the measured instantaneous pressure difference, and the equivalent impedance of the pump station node is obtained.

5. The pressure monitoring method for a long-distance water transmission pipeline according to claim 1, characterized in that, The calculation of the pressure wave reflection coefficient of the boundary node based on the equivalent impedance includes: The characteristic impedance of the pipe section is determined based on the theory of elastic water hammer. The pressure wave reflection coefficient of the boundary node is calculated based on the characteristic impedance of the incident side pipe segment and the equivalent impedance of the transmission side.

6. The pressure monitoring method for a long-distance water transmission pipeline according to claim 1, characterized in that, The response to the pressure timing signal triggering a suspected transient event includes: Calculate the upper and lower quartiles of the steady-state pressure sequence and obtain the interquartile range; According to Tukey's rule, the trigger threshold is set to the sum of the upper quartile and the interquartile range of 1.5 times. In response to a sudden change in the amplitude of the pressure timing signal exceeding the trigger threshold, it is determined to be a suspected transient event.

7. The pressure monitoring method for a long-distance water transmission pipeline according to claim 1, characterized in that, The step of performing forward numerical simulation based on the pressure wave reflection coefficient, extracting cross-correlation matching features, and subtracting the reflection component from the pressure time series signal according to the corresponding cross-correlation matching features to obtain the residual transient signal includes: The pipeline is subjected to forward numerical simulation using the characteristic line method with the pressure wave reflection coefficient to generate the theoretical response waveform; Extract the cross-correlation matching features between the simulated response waveform and the measured waveform; Based on the corresponding cross-correlation matching characteristics, the reflection components contributed by each boundary node are gradually identified and subtracted from the measured signal to obtain the residual transient signal at each monitoring unit.

8. The pressure monitoring method for a long-distance water transmission pipeline according to claim 1, characterized in that, The step of extracting the time difference based on the residual transient signal to calculate the distance to the anomaly source includes: Perform generalized cross-correlation on the residual transient signals at two adjacent monitoring units to extract the time difference of arrival of a transient wave. The distance to the anomaly source is calculated based on the time difference, the pipe length between adjacent monitoring units, and the water hammer wave velocity.

9. The pressure monitoring method for a long-distance water transmission pipeline according to claim 1, characterized in that, The step of extracting peak amplitude based on the residual transient signal for classification includes: Extract the peak amplitude of the first transient wave from the residual transient signal; The instantaneous reference amplitude is constructed by introducing the water hammer formula as the baseline, and the peak amplitude is divided by the instantaneous reference amplitude to obtain the normalized anomaly intensity index; The three-level determination is based on the relative position of the normalized anomaly intensity index and the classification threshold.

10. A pressure monitoring system for a long-distance water transmission pipeline, characterized in that, include: Memory, used to store computer programs; A processor, configured to execute a computer program stored in the memory, implements the pressure monitoring method for long-distance water pipelines as described in any one of claims 1 to 9.

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