Long-distance water pipeline leakage rapid positioning method

Abstract

The application provides a long-distance water conveying pipeline leakage rapid positioning method, and relates to the technical field of pipeline leakage detection, and the specific steps comprise: the method first divides pipeline regions and sections according to geographical environment data, forms a continuous section sequence according to the water flow direction, collects historical monitoring data and leakage types of each section, generates fluid transmission abnormality coefficients, structure thermal deformation coefficients, and flow difference values and water pressure ratio values of the current section and the previous section, constructs a leakage type identification model for different regions, trains the model with historical time period data as input and corresponding leakage types as labels, inputs the data of the current time period, and rapidly and accurately predicts the current leakage type and position of the water conveying pipeline. The application adopts a hierarchical management strategy of first zoning and then sectioning, and constructs a leakage type identification model for different regions, so that efficient positioning and accurate judgment of long-distance water conveying pipeline leakage are realized.

Description

Technical Field

[0001] This invention relates to the field of pipeline leakage detection technology, specifically a method for rapid location of leaks in long-distance water transmission pipelines. Background Technology

[0002] Long-distance water transmission projects occupy a crucial position in the modern water resource allocation system, bearing the heavy responsibility of supplying large-scale water to cities, industries, and agriculture. They are essential infrastructure for ensuring the water needs of socio-economic development and residential life. Water pipelines are like the "water arteries" of a city; leaks not only cause significant waste of water resources but can also trigger secondary disasters such as ground subsidence and road damage, and even threaten the safety of surrounding buildings. Therefore, timely and accurate location of leaks is of great significance for ensuring the stable operation of the water transmission system and reducing economic losses and environmental risks.

[0003] Currently, in the field of long-distance water pipeline leakage monitoring, most methods involve setting up monitoring points along the entire length to collect flow and water pressure data in real time. By analyzing data changes such as abnormal drops in flow and sudden decreases in water pressure, the likelihood of leakage can be preliminarily determined, and the leakage area can be located. However, long-distance water pipelines often traverse complex and diverse geographical environments, encompassing different landforms such as mountains, plains, rivers, and cities, with significant differences in climate conditions, soil properties, and geological structures. These geographical environmental factors directly interfere with the accuracy and stability of flow and water pressure data.

[0004] CN119618479A discloses a method and system for tracing and identifying leakage sources in water diversion projects. The method includes the following steps: setting up monitoring points in the water diversion project, collecting temperature, pressure, and flow velocity data from key monitoring points, performing time-series analysis on the parameters, analyzing water flow dynamics and environmental changes in real time, and generating status monitoring data. This method utilizes status monitoring data to analyze environmental changes near the leakage point and identifies abnormal changes through simulation and comparative analysis, enabling more accurate prediction and location of leakage points. Entropy increase calculations assess the energy state before and after leakage, further accurately predicting the leakage location and time. Simulating energy flow under differentiated environmental conditions improves the accuracy of seepage path identification, achieving more efficient leakage source location. This makes the entire leakage tracing and identification process more systematic and scientific, significantly enhancing the safety supervision and maintenance efficiency of water conservancy facilities.

[0005] However, the following shortcomings exist. As stated above, due to different geographical environments, climatic conditions, and pipeline operating conditions, the leakage situation of water transmission pipelines varies. Ignoring the differences in the geographical environment along long-distance water transmission pipelines and relying solely on temperature, pressure, and flow velocity data to monitor the location of leaks cannot fully account for the interference of geographical factors on the data. For example, complex terrain in mountainous areas may cause false fluctuations in pressure data, and temperature changes under extreme climates may mask temperature anomalies caused by leaks. This makes it difficult for this method to accurately capture leakage characteristics in real complex geographical environments, leading to the risk of misjudgment and missed detection of leaks, and hindering the accurate location and effective monitoring of leaks in long-distance water transmission pipelines.

[0006] The information disclosed in the background section is only intended to enhance the understanding of the background of this disclosure, and therefore may include information that does not constitute prior art known to those skilled in the art. Summary of the Invention

[0007] The purpose of this invention is to provide a method for rapid location of leaks in long-distance water pipelines, so as to solve the problems mentioned in the background art.

[0008] To achieve the above objectives, the present invention provides the following technical solution:

[0009] A method for rapid location of leaks in long-distance water pipelines, comprising the following steps:

[0010] S1. Considering the significant differences in the geographical environment along the long-distance water transmission pipeline, measurement points are set at equal intervals along the axial direction of the long-distance water transmission pipeline to collect its geographical environment data and process it to generate a comprehensive score. Based on the comprehensive score, the water transmission pipeline is divided into different regions, and each region is further divided into multiple segments at equal intervals. All segments are sorted according to the direction of water flow to form a continuous segment sequence, and monitoring data and leakage types of each segment in the segment sequence are collected in the historical time period.

[0011] S2. Perform feature extraction on the monitoring data of each section to obtain the flow characteristic parameters, water pressure characteristic parameters, temperature characteristic parameters and strain characteristic parameters of each section;

[0012] S3. Based on flow rate and water pressure characteristic parameters, the fluid transmission anomaly coefficient is obtained to measure the degree of fluid transmission affected by leakage. Based on temperature and strain characteristic parameters, the structural thermal deformation coefficient is obtained to assess the risk of damage to the pipeline structure due to thermal deformation. Based on the flow rate and water pressure characteristic parameters of the current section and the previous section, the flow rate difference and water pressure ratio of the current section are obtained to capture the changing characteristics of fluid transmission status between adjacent sections.

[0013] S4. Construct corresponding leakage type identification models for different regions. Take the geographical environment data, fluid transmission anomaly coefficient, structural thermal deformation coefficient, flow difference and water pressure ratio of each section belonging to the same region in the historical time period as input, and take the actual leakage type of the corresponding section as the label output to train the leakage type identification model.

[0014] S5. Input the geographical environment data, fluid transmission anomaly coefficient, structural thermal deformation coefficient, flow rate difference and water pressure ratio of each section within the current time period into the corresponding leakage type identification model to predict the actual leakage type of each section within the current time period, thereby achieving rapid location of leakage in long-distance water transmission pipelines.

[0015] Furthermore, the geographic environmental data includes altitude, slope, and temperature.

[0016] Furthermore, the leakage type is one or more of the following: no leakage, single-point leakage, multi-point leakage, and local rupture leakage. The flow characteristic parameters include the mean flow rate, the variance of the flow rate, and the rate of change of the flow rate. The water pressure characteristic parameters include the mean water pressure, the variance of the water pressure, and the amplitude of the water pressure fluctuation. The temperature characteristic parameters include the rate of change of temperature and the duration of abnormal temperature points. The strain characteristic parameters include the maximum strain value and the frequency of strain change.

[0017] Furthermore, the altitude, slope, and temperature are standardized. The standardized altitude, slope, and temperature values ​​are then compared with their baseline values ​​to calculate the deviations from the baseline values, using the following formulas:

[0018]

[0019]

[0020]

[0021] in, , , The first The deviation values ​​of altitude, slope, and temperature at each measurement point. , , The first The altitude, slope, and temperature of each measurement point. , , These are the baseline values ​​for altitude, slope, and temperature, respectively. For the index of the measurement point, , The number of measurement points;

[0022] The overall score is calculated based on the deviations in altitude, slope, and temperature, and their respective weights, using the following formula:

[0023]

[0024] in, For the first A comprehensive score for each measurement point;

[0025] In the formula, This is the weighting coefficient for the altitude deviation value. This is the weighting coefficient for the slope deviation value. The weighting coefficient for the temperature deviation value is... On this basis, let .

[0026] Furthermore, the water pipeline areas are divided based on a comprehensive score, and the specific process is as follows:

[0027] Filter out the comprehensive score from all measurement points These measurement points, whether continuously or scattered in space, are grouped into a region, named the region. ;

[0028] Select all measurement points that meet the comprehensive score The measurement points are used to divide the pipe sections corresponding to these measurement points into regions, which are named regions. ;

[0029] Select all measurement points that meet the comprehensive score The measurement points are used to divide the pipe sections corresponding to these measurement points into regions, which are named regions. ;

[0030] in, This is the threshold for the overall score.

[0031] Furthermore, based on the characteristic parameters of flow rate and water pressure, the fluid transport anomaly coefficient is obtained, according to the following formula:

[0032]

[0033] in, The fluid transport anomaly coefficient for the section;

[0034] In the formula, The average flow rate is... For flow variance, The average rate of change of flow rate This is the average water pressure. For water pressure variance, This refers to the amplitude of water pressure fluctuation. This is the baseline value for the average flow rate. This serves as the baseline value for the flow variance. This is the baseline value for the average water pressure. This serves as the baseline value for the water pressure variance. This serves as the baseline value for the average rate of change of flow rate. This serves as the baseline value for the water pressure fluctuation amplitude;

[0035] In the formula, This is the weighting coefficient for the interaction term between the ratio of the flow mean to its baseline value and the ratio of the flow variance to its baseline value. This is the weighting coefficient for the interaction term between the ratio of the mean water pressure to its reference value and the ratio of the variance of water pressure to its reference value. The weighting coefficients for the interaction terms of the ratio of the average rate of change of flow rate to its reference value and the ratio of the amplitude of water pressure fluctuation to its reference value, in On this basis, let .

[0036] Furthermore, based on temperature and strain characteristic parameters, the structural thermal deformation coefficient is obtained using the following formula:

[0037]

[0038] in, The structural thermal deformation coefficient of the section;

[0039] In the formula, The average rate of temperature change. The duration of the abnormal temperature point. For the maximum strain, The frequency of strain change This serves as a benchmark for the average rate of temperature change. This serves as a baseline value for the duration of abnormal temperature points. This is the reference value for the maximum strain. This serves as the reference value for the average strain variation frequency;

[0040] In the formula, This is a weighting factor for the ratio of the average rate of temperature change to its reference value. This is a weighting factor for the ratio of the duration of an abnormal temperature point to its baseline value. The weighting factor is the ratio of the maximum strain value to its reference value. The weighting coefficient for the ratio of the average frequency of strain variation to its reference value is... On this basis, let .

[0041] Furthermore, based on the flow rate and water pressure characteristic parameters of the current section and the previous section, the flow rate difference and water pressure ratio of the current section are obtained, according to the following formula:

[0042]

[0043]

[0044] in, For the first The difference in flow rate between each segment, For the first Water pressure ratio of each section For the first Average traffic flow in each segment For the first Average traffic flow in each segment For the first Average water pressure in each section For the first Average water pressure in each section For the index of the segment, , This refers to the number of sections of the water pipeline.

[0045] Compared with the prior art, the beneficial effects of the present invention are:

[0046] This invention takes into account the significant differences in the geographical environment along long-distance water pipelines and adopts a hierarchical management strategy of first dividing the area into zones and then into segments. Based on the comprehensive score of the geographical environment, the pipeline area is divided into regions, and then the regions are further subdivided into segments at equal intervals. This gradual division method conforms to the gradual change of the geographical environment, avoids data mutation caused by sudden environmental changes, and ensures that the collected data truly reflects the pipeline's operating status, eliminates environmental interference factors, and provides an accurate and reliable data foundation.

[0047] Strain data has been added, which reflects the stress and deformation of the pipeline caused by geographical environmental factors. In this way, the impact of different geographical environments and pipeline operating conditions on water pipeline leakage is fully considered, making the collected data more accurately reflect the true state of the pipeline and thus improving the accuracy of leakage judgment.

[0048] Based on the collection of multi-dimensional data, feature extraction is performed on the monitoring data to obtain rich feature parameters. Based on these feature parameters, fluid transmission anomaly coefficient and structural thermal deformation coefficient are generated, as well as the flow difference and water pressure ratio between the current section and the previous section. The above parameters are combined and input into the leakage type identification model constructed for different areas. By learning the correspondence between parameters and leakage types in historical data, the model can quickly and accurately predict the leakage type of the current section, realizing efficient location and accurate judgment of leakage in long-distance water transmission pipelines. Attached Figure Description

[0049] Figure 1 This is a schematic diagram of the overall method flow of the present invention. Detailed Implementation

[0050] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be further described in detail below with reference to specific embodiments.

[0051] It should be noted that, unless otherwise defined, the technical or scientific terms used in this invention should have the ordinary meaning understood by one of ordinary skill in the art to which this invention pertains. The terms "first," "second," and similar terms used in this invention do not indicate any order, quantity, or importance, but are merely used to distinguish different components. Terms such as "comprising" or "including" mean that the element or object preceding the word encompasses the elements or objects listed following the word and their equivalents, without excluding other elements or objects. Terms such as "connected" or "linked" are not limited to physical or mechanical connections, but can include electrical connections, whether direct or indirect. Terms such as "upper," "lower," "left," and "right" are used only to indicate relative positional relationships; when the absolute position of the described object changes, the relative positional relationship may also change accordingly.

[0052] Example 1:

[0053] Please see Figure 1 The present invention provides a technical solution:

[0054] A method for rapid location of leaks in long-distance water pipelines, comprising the following steps:

[0055] S1. Considering the significant differences in the geographical environment along the long-distance water transmission pipeline, measurement points are set at equal intervals along the axial direction of the long-distance water transmission pipeline to collect its geographical environment data and process it to generate a comprehensive score. Based on the comprehensive score, the water transmission pipeline is divided into different regions, and each region is further divided into multiple segments at equal intervals. All segments are sorted according to the direction of water flow to form a continuous segment sequence, and monitoring data and leakage types of each segment in the segment sequence are collected in the historical time period.

[0056] Based on the above embodiments, the geographic environment data includes altitude, slope, and temperature. The methods for collecting altitude, slope, and temperature are as follows:

[0057] By setting measurement points at equal intervals along the axial direction of long-distance water transmission pipelines, for example, setting a measurement point every 100 meters or 200 meters, we can obtain more comprehensive geographical environmental data along the pipeline and ensure the continuity and representativeness of the data.

[0058] A level is used to measure the elevation difference between two points. At different measurement points, the height of each measurement point relative to a certain reference surface is obtained. These height values ​​are the elevation data along the water pipeline. Each measurement point is measured multiple times, and the average elevation of the same measurement point is calculated as the elevation of all measurement points in the water pipeline.

[0059] The slope data is calculated using topographic surveying tools, specifically a total station. The total station can measure the changes in terrain along the pipeline. By calculating the elevation difference and horizontal distance between adjacent measurement points, the slope of each section along the pipeline is obtained using the slope formula: slope = arctan(elevation difference / horizontal distance × 100%). Each measurement point is measured multiple times, and the average slope of the same measurement point is calculated as the slope of each measurement point in the water transmission pipeline.

[0060] Temperature sensors are installed along the water pipeline. These sensors can monitor and record the temperature information of the environment around the pipeline in real time. The temperature sensors will collect temperature data at different measurement points along the pipeline. Each measurement point is measured multiple times, and the average temperature of the same measurement point is calculated as the temperature of each measurement point in the water pipeline.

[0061] Based on the above embodiments, the altitude, slope, and temperature are standardized. The standardized altitude, slope, and temperature values ​​are then compared with their reference values ​​to calculate the deviation values ​​of altitude, slope, and temperature. The formulas used are as follows:

[0062]

[0063]

[0064]

[0065] in, , , The first The deviation values ​​of altitude, slope, and temperature at each measurement point. , , The first The altitude, slope, and temperature of each measurement point. , , These are the baseline values ​​for altitude, slope, and temperature, respectively. For the index of the measurement point, , The number of measurement points;

[0066] Among them, the baseline values ​​for altitude, slope and temperature can be obtained from geographic information systems and urban meteorological departments. Then, the obtained altitude, slope and temperature data are calculated and statistical quantities such as average or median are used to represent the altitude, slope and temperature of the area, and these are used as the baseline values ​​for altitude, slope and temperature.

[0067] The overall score is calculated based on the deviations in altitude, slope, and temperature, and their respective weights, using the following formula:

[0068]

[0069] in, For the first The comprehensive score of each measurement point is used to evaluate the geographical suitability of different measurement points by combining the deviation values ​​of altitude, slope and temperature. The smaller the comprehensive score, the better the geographical suitability of the measurement point.

[0070] Based on this, it should be noted that:

[0071] when The smaller the value, the higher the value. The smaller the difference between the altitude of a measurement point and the reference altitude, the closer the hydrostatic pressure and hydrodynamic forces that the pipeline experiences at that point are to the ideal state, which is more conducive to the normal operation of the pipeline, and thus makes the geographical environment of the measurement point more suitable, resulting in a smaller overall score.

[0072] when The smaller, the more likely it is to be the first The closer the slope of each measurement point is to the ideal slope of the design, the more reasonable the flow velocity of the water at that point can be maintained. This prevents the water flow from scouring and abrading the pipe due to an excessively large slope, and also prevents problems such as poor water flow and impurity deposition due to an excessively small slope. This is more conducive to the long-term stable operation of the pipeline, and thus makes the geographical environment of the measurement point more suitable, resulting in a lower comprehensive score.

[0073] when The smaller the value, the better. The smaller the difference between the temperature at each measurement point and the suitable operating temperature of the pipe material, the more acceptable the thermal expansion and contraction effect of the pipe material due to temperature changes will be. This can effectively prevent situations such as loosening of pipe connections and accelerated material aging caused by excessively high temperatures, or freezing of water inside the pipe due to excessively low temperatures. Consequently, the geographical suitability of the measurement point will be better, resulting in a lower overall score.

[0074] Therefore, the overall score is positively correlated with the deviation values ​​of altitude, slope, and temperature.

[0075] Furthermore, the impacts of each geographic environmental data point on geographic suitability are independent and additive. In other words, the change in each parameter affects the overall score independently of other parameters, and their combined impact can be reflected by simple addition.

[0076] In summary, the functional relationship between the overall score and the deviation values ​​of altitude, slope, and temperature can be expressed using the above linear summation form.

[0077] In the formula, This is the weighting coefficient for the altitude deviation value. This is the weighting coefficient for the slope deviation value. The weighting coefficient for the temperature deviation value;

[0078] Long-distance water pipelines often traverse diverse terrains, and changes in altitude directly impact the hydrostatic pressure they withstand. Significant altitude deviations can lead to excessively high pressure in localized areas, exceeding the material's tolerances and causing serious accidents such as pipeline rupture. For example, in mountainous water transmission projects, if pipelines are laid from low to high altitudes, the altitude difference can cause immense pressure at the bottom of the pipeline. This pressure variation is crucial to pipeline safety. Different altitudes can also affect the physical properties of water, such as boiling point and density, thus influencing the dynamic characteristics of water flow. These changes can lead to unstable water flow within the pipeline, affecting transmission efficiency and water quality. Therefore, altitude deviations play a critical role in the normal operation and safety of pipelines and should be given significant weight. .

[0079] The slope primarily affects the flow velocity and scouring of water within a pipe. A suitable slope ensures a moderate flow velocity, preventing impurities from settling due to excessively slow flow, or pipe wear and tear caused by excessively fast flow. However, compared to altitude, the impact of slope on pipe safety is relatively indirect. In engineering design and construction, slope can be adjusted and controlled through engineering measures such as constructing slope protection walls and retaining walls. These measures can mitigate the adverse effects of slope deviation to some extent. Therefore, the weighting coefficient for slope deviation is important. relatively Smaller.

[0080] The impact of temperature on pipelines is mainly reflected in thermal expansion and contraction, and may lead to problems such as pipeline material aging and water freezing. In most cases, by taking appropriate insulation, heat insulation, or adding antifreeze, the impact of temperature deviations on pipelines can be effectively reduced. Moreover, temperature changes are usually a gradual process, unlike deviations in altitude and slope that can immediately and severely affect pipeline operation. As long as temperature factors are given appropriate attention during design and operation, the risks they bring can be well controlled. Therefore, the weighting coefficient of temperature deviation values... Relatively small.

[0081] In conclusion, On this basis, let ;

[0082] As one implementation method, The range of values ​​is , The range of values ​​is , The range of values ​​is The specific value is set by technical personnel according to the actual situation, and no restrictions are imposed here.

[0083] Based on the above embodiments, water pipeline areas are divided according to a comprehensive score. The specific process is as follows:

[0084] Filter out the comprehensive score from all measurement points These measurement points, whether continuously or scattered in space, are grouped into a region, named the region. ;

[0085] Select all measurement points that meet the comprehensive score The measurement points are used to divide the pipe sections corresponding to these measurement points into regions, which are named regions. ;

[0086] Select all measurement points that meet the comprehensive score The measurement points are used to divide the pipe sections corresponding to these measurement points into regions, which are named regions. ;

[0087] in, The threshold for the comprehensive score is determined by referring to the statistical parameters of the comprehensive score, such as the mean, median, and standard deviation. For example, if the comprehensive score approximately follows a normal distribution, the threshold can be set accordingly. Let the average score be the sum of the average and a standard deviation, i.e. .

[0088] Based on the above embodiments, the leakage type is one or more of the following combinations: no leakage, single-point leakage, multi-point leakage, and localized rupture leakage.

[0089] Based on the above embodiments, compared to directly dividing into segments, dividing into regions first and then into segments has the following technical advantages:

[0090] First, directly dividing the pipeline into sections using a uniform standard ignores the differences in the geographical environment along the pipeline route. Instead, generating a comprehensive score based on geographical environmental data and then dividing different areas ensures a relatively consistent geographical environment within each area. Further dividing these areas into sections ensures that each section is situated in a more similar environmental context. For example, areas with complex geological conditions differ from those with stable geological conditions in terms of the causes and characteristics of leakage. By first dividing the area into zones and then into sections, the analysis of leakage problems can be narrowed down to areas with similar environmental characteristics, thus allowing for more precise location of the leakage point.

[0091] Secondly, the geographical environment of different regions has varying effects on pipelines, leading to differences in leakage characteristics. By first dividing the region into areas, it is possible to establish a more accurate relationship between leakage characteristics and relevant data for each region, providing a more reliable basis for subsequent leakage analysis.

[0092] Third, segments within the same region are influenced by similar geographical environments, making their data more comparable. For example, in areas with significant temperature differences, the temperature change trends of different segments will show commonalities. This allows for the rapid identification of outlier segments during data analysis. Conversely, directly dividing the region into segments presents greater challenges for comparative data analysis due to the significant differences in the environments of different segments.

[0093] Fourth, while the geographical environment changes gradually in space, the changes in data such as flow rate, water pressure, temperature, and strain of water pipelines are not entirely synchronous or sensitive to these changes. For example, in areas transitioning from plateaus to plains, geographical environmental data such as altitude and slope gradually change, but parameters such as flow rate and water pressure in water pipelines may remain relatively stable within a certain range. Even if the parameters of sections are the same on either side of such transitional areas, they will be classified into different regions due to the different overall characteristics of the geographical environment. This method of first dividing the area into zones and then segmenting it can better adapt to the gradual changes in the geographical environment and improve the accuracy of pipeline condition analysis.

[0094] S2. Perform feature extraction on the monitoring data of each section to obtain the flow characteristic parameters, water pressure characteristic parameters, temperature characteristic parameters and strain characteristic parameters of each section;

[0095] Based on the above embodiments, the flow characteristic parameters include the mean flow rate, the variance of the flow rate, and the rate of change of the flow rate; the water pressure characteristic parameters include the mean water pressure, the variance of the water pressure, and the amplitude of water pressure fluctuation; the temperature characteristic parameters include the rate of change of temperature and the duration of abnormal temperature points; and the strain characteristic parameters include the maximum strain value and the frequency of strain change.

[0096] Based on the above embodiments, the mean flow rate, variance of flow rate, and average rate of change of flow rate are calculated using the following formulas:

[0097]

[0098]

[0099]

[0100] in, The average traffic volume over the same time period. For the first time period The flow rate at any given moment. For the first time period The flow rate at any given moment. The time interval between two adjacent moments. The variance of traffic flow within the same time period. The average rate of change of traffic flow over the same time period. For indexing time, , The number of moments;

[0101] The following formulas are used to calculate the mean water pressure, the variance of water pressure, and the amplitude of water pressure fluctuation:

[0102]

[0103]

[0104]

[0105] in, This represents the average water pressure over the same time period. For the first The water pressure value at that moment. The variance of water pressure within the same time period. This refers to the amplitude of water pressure fluctuation within the same time period. The maximum water pressure value at all times. This represents the minimum water pressure value at all times.

[0106] The following formulas are used to calculate the average rate of temperature change and the duration of abnormal temperature points:

[0107]

[0108]

[0109] in, The average rate of temperature change over the same time period. The duration of abnormal temperature points within the same time period. For the first The temperature value at that moment. For the first The temperature value at that moment. The moment when the abnormal temperature state begins. This is the moment when the abnormal temperature state ends;

[0110] Abnormal temperature conditions refer to situations where the temperature of the surrounding environment or the internal medium of a long-distance water pipeline deviates from its normal fluctuation range during operation. The normal fluctuation range can be determined based on historical climate data of the pipeline's location and pipeline design standards. An abnormal temperature state is defined as when the temperature exceeds the upper limit or falls below the lower limit of the normal fluctuation range. For example, during normal operation of a section of pipeline, the internal medium temperature is typically stable between 10°C and 20°C. If the temperature exceeds this range at a certain moment, such as reaching 25°C or 5°C, then an abnormal temperature state is entered.

[0111] The formulas used to calculate the maximum strain and strain change frequency are as follows:

[0112]

[0113]

[0114] in, It represents the maximum strain value among all times within the same time period. For the first The strain value at each moment. The frequency of strain change within the same time period. The total number of strain changes, This represents the total duration of the time period.

[0115] Among them, strain change refers to an effective change in strain value, defined as: within a time period Within t2, the total number of times the strain value changes from one state to another.

[0116] Based on the above embodiments, the methods for collecting flow rate, water pressure, temperature, strain values ​​at different times within the same time period, as well as the start time of abnormal temperature state, the end time of abnormal temperature state, the total number of strain changes, and the total duration of the time period within the same time period are as follows:

[0117] The electromagnetic flow meter is installed in the straight section of the pipeline, and the electromagnetic flow meter acquires flow data at different times in real time according to the set sampling frequency.

[0118] Pressure sensors are installed at key locations in the pipeline, such as the starting point, branch points, and diameter changes. The changes in water pressure at these locations at different times can reflect the pressure status of the entire system. The pressure sensors convert the pressure signals they sense at different times into electrical signals and collect data according to the set sampling frequency.

[0119] Inside the pipeline, temperature sensors (such as thermocouples or resistance temperature detectors) are installed. The temperature sensors acquire temperature values ​​at different times in real time according to a set sampling frequency. At the same time, temperature thresholds (such as upper and lower limits) are preset. When the temperature value collected at a certain moment exceeds the upper limit or falls below the lower limit, the system automatically records that moment as the start of the abnormal temperature state. When the temperature value returns to the normal range (between the upper and lower limits) at subsequent moments, the system immediately records that moment as the end of the abnormal temperature state.

[0120] Strain gauges or strain sensors are attached or installed at critical stress points in water pipes, such as bends, tee connections, reducers, and sections crossing obstacles or subjected to significant external forces. The strain sensors acquire strain values ​​in real time at a set sampling frequency. A strain change amplitude threshold is set (a change exceeding this threshold is considered a valid change). When the strain value change exceeds this threshold at a certain moment, the system accumulates and counts the number of strain changes to obtain the total number of strain changes. Simultaneously, the system automatically records the time of each strain change. By calculating the time difference between the first and last strain change, and adding this time difference to the time between the last strain change and the end of the time period, the total duration of the time period is obtained.

[0121] S3. Based on flow rate and water pressure characteristic parameters, the fluid transmission anomaly coefficient is obtained to measure the degree of fluid transmission affected by leakage. Based on temperature and strain characteristic parameters, the structural thermal deformation coefficient is obtained to assess the risk of damage to the pipeline structure due to thermal deformation. Based on the flow rate and water pressure characteristic parameters of the current section and the previous section, the flow rate difference and water pressure ratio of the current section are obtained to capture the changing characteristics of fluid transmission status between adjacent sections.

[0122] Based on the above embodiments, the fluid transport anomaly coefficient is obtained based on the characteristic parameters of flow rate and water pressure, according to the following formula:

[0123]

[0124] in, The fluid transmission anomaly coefficient is used to measure the degree to which fluid transport is affected by leakage, by combining six indicators: mean flow rate, flow rate variance, average flow rate change rate, mean water pressure, water pressure variance, and water pressure fluctuation amplitude. The larger the fluid transmission anomaly coefficient, the greater the degree to which fluid transport is affected by leakage, and therefore the more likely leakage is to occur.

[0125] In the formula, This is the baseline value for the average flow rate. This serves as the baseline value for the flow variance. This is the baseline value for the average water pressure. This serves as the baseline value for the water pressure variance. This serves as the baseline value for the average rate of change of flow rate. This serves as the baseline value for the water pressure fluctuation amplitude;

[0126] Among them, the benchmark values ​​for mean flow rate, variance flow rate, mean water pressure, variance water pressure, average rate of change of flow rate, and fluctuation range of water pressure are calculated by collecting a large amount of historical flow rate and water pressure data of water transmission pipelines under normal operating conditions, and using these historical data as benchmark values.

[0127] Based on this, it should be noted that:

[0128] If there is a leak at a certain point in the pipeline, water will continue to flow out from the damaged point under the action of pressure difference. In order to maintain the normal water supply downstream, the upstream water source will continue to replenish, making the average flow rate in the pipeline larger than the baseline value. This continuous abnormal increase in flow rate not only increases the overall water transport burden of the pipeline, but also generates a stronger scouring force on the area around the leak point, gradually expanding the damaged area at the leak point, further increasing the risk of leakage, which is directly reflected in the increase of the fluid transmission anomaly coefficient.

[0129] When the flow variance increases relative to its baseline value, it means that the flow fluctuation becomes more severe. In a normally operating water pipeline, the flow should remain relatively stable. An increase in variance is likely caused by the instability of the water flow at the leakage point. The water flow at the leakage point is affected by a variety of complex factors, such as uneven pressure distribution within the pipeline and irregularities in the pipeline structure around the leakage point. This causes the leakage water flow to exhibit irregular changes, which in turn leads to greater fluctuations in the flow throughout the pipeline. Frequent and large fluctuations in flow generate alternating stress on the pipeline wall, similar to how metal materials are prone to fatigue under repeated stress. Under the long-term action of this alternating stress, the mechanical properties of the pipeline material gradually decline, and weak points in the pipeline are more likely to experience crack propagation and seal failure, greatly increasing the possibility of pipeline leakage. The fluid transmission anomaly coefficient also increases accordingly.

[0130] When the average water pressure increases relative to its baseline value, on the one hand, if there is a blockage in the pipeline, the water flow is obstructed, and the kinetic energy of the fluid is converted into pressure energy, causing the water pressure upstream of the blockage point to rise. This excessively high water pressure acts on the pipeline wall for a long time, exceeding the pressure resistance limit of the pipeline material, which can easily cause the pipeline to deform or even rupture, leading to leakage. On the other hand, when there is leakage in the pipeline, the water flows out at the leakage point, causing the cross-sectional area of ​​the water flow in the pipeline to decrease. According to the fluid continuity equation, the flow velocity will increase, and according to Bernoulli's equation, the pressure decreases where the flow velocity increases. In order to maintain the energy balance of the overall water flow, the upstream water pressure will rise accordingly. The increased water pressure further intensifies the pressure effect on various parts of the pipeline, especially in relatively weak links such as welds and connections, which are more likely to leak due to excessive pressure, increasing the risk of leakage and the fluid transmission anomaly coefficient.

[0131] When the water pressure variance increases relative to its benchmark value, it indicates that the fluctuation range and instability of the water pressure have increased significantly. The stability of water pressure in the pipeline is crucial for maintaining normal water supply. Leaks are one of the important factors causing water pressure instability. The sudden outflow of water or the dynamic changes in the leakage situation at the leak point will cause rapid changes in the water pressure in the surrounding area. This pressure change will propagate along the pipeline, causing the water pressure of the entire pipeline system to fluctuate greatly. Frequent and large-amplitude water pressure fluctuations will have a strong impact and squeezing effect on the sealing components of the pipeline, such as rubber sealing rings, accelerating the wear and aging of the seals and reducing their sealing performance. At the same time, it will make the weld seams of the pipeline more prone to cracks due to repeated pressure changes, greatly increasing the probability of pipeline leakage and increasing the fluid transmission anomaly coefficient.

[0132] When the average rate of change of flow rate increases relative to its baseline value, it indicates that the flow rate changes faster per unit time. In a normally operating water transmission system, the flow rate change is usually relatively gentle and within a reasonable range. If the average rate of change increases, it is likely due to a leak in the pipeline that disrupts the flow state. For example, a sudden change in the flow at the leak point can cause a sharp change in the local flow rate, which in turn affects the flow rate of the entire pipeline. This rapid change in flow rate generates a strong water hammer effect inside the pipeline, similar to a strong shock wave generated instantaneously in the pipeline. This generates a huge impact force on the pipeline wall and connectors. The repeated action of the water hammer effect on the pipeline can easily cause the pipeline to loosen, deform, or even break, greatly increasing the possibility of leakage in the water transmission pipeline. As a result, the fluid transmission anomaly coefficient increases.

[0133] When the fluctuation range of water pressure increases relative to its reference value, it means that the fluctuation of water pressure within a certain period of time far exceeds the normal range. Pipeline leakage is one of the common causes of such large water pressure fluctuations. Dynamic changes in water flow at the leakage point, such as the large and small leakage volume and the instability of the leakage direction, will cause drastic changes in water pressure in the area surrounding the leakage point. Moreover, this pressure disturbance will be rapidly propagated to the entire pipeline system through the water flow. The large fluctuation of water pressure makes the pressure state of the pipeline extremely unstable, which will seriously affect the fatigue life of the pipeline material. Under such an unstable pressure environment for a long time, the pipeline is prone to develop micro-cracks in stress concentration areas, such as pipe bends and diameter changes, which will gradually expand and eventually lead to pipeline leakage. The possibility of leakage in water transmission pipelines increases, and the fluid transmission anomaly coefficient increases accordingly.

[0134] In summary, the fluid transport anomaly coefficient of the section is positively correlated with the mean flow rate, flow rate variance, average flow rate change rate, mean water pressure, flow rate variance, and flow rate fluctuation amplitude.

[0135] An increase in the mean flow rate reflects an anomaly in the overall water delivery flow, while an increase in the variance of the flow rate indicates aggravated flow fluctuations. When both anomalies occur simultaneously, their impact on leakage risk is not simply additive, but rather mutually reinforcing and amplifying. Therefore, ( )and( Multiplying the mean and variance of the flow indicates the synergistic effect of the flow mean and the flow variance.

[0136] An increase in average water pressure may lead to excessively high local pressure in the pipeline, while an increase in water pressure variance indicates drastic water pressure fluctuations. The combination of these two factors can cause more severe damage to weak points in the pipeline, such as sealing components and welds, accelerating leakage. Therefore, using ( )and( The multiplication of these values ​​reflects the synergistic effect of the mean water pressure and the variance of water pressure.

[0137] An increased average rate of change in flow rate indicates drastic changes in water flow conditions, making it prone to water hammer effects. Increased water pressure fluctuations lead to unstable pressure on the pipeline. The combined effect of these two factors can cause greater damage to the pipeline and increase the likelihood of leakage. Therefore, using ( )and( The product of these factors takes into account the synergistic relationship between the average rate of change of flow rate and the amplitude of water pressure fluctuation.

[0138] In summary, the weighted summation formula described above is used to characterize the functional relationship between the fluid transport anomaly coefficient and the mean flow rate, flow rate variance, average flow rate change rate, mean water pressure, water pressure variance, and water pressure fluctuation amplitude of the section.

[0139] In the formula, This is the weighting coefficient for the interaction term between the ratio of the flow mean to its baseline value and the ratio of the flow variance to its baseline value. This is the weighting coefficient for the interaction term between the ratio of the mean water pressure to its reference value and the ratio of the variance of water pressure to its reference value. The weighting coefficients for the interaction terms of the ratio of the average rate of change of flow rate to its reference value and the ratio of the amplitude of water pressure fluctuation to its reference value;

[0140] When a pipeline leaks, the average flow rate increases significantly to maintain downstream water supply. This not only increases the pipeline's water transport burden but also intensifies water erosion at the leak point, directly reflecting the impact of the leak on water delivery. For example, in the early stages of a leak, the upstream may increase its water supply to ensure downstream water availability due to water leakage, causing the average flow rate to rise rapidly. This change is a direct signal of a leak and is closely related to the likelihood of a leak.

[0141] Unstable water flow at the leak point leads to increased flow variance, and the alternating stress generated by large flow fluctuations directly threatens the integrity of the pipeline structure. Under long-term alternating stress, the pipeline is more prone to damage, thus increasing the likelihood of leakage. The more significant the increase in flow variance, the greater the disruption to water flow stability caused by the leakage, and the higher the probability of more serious leakage.

[0142] Changes in the mean and variance of flow rate have a direct and significant impact on leakage; their interaction can intuitively and significantly reflect the effect of leakage on fluid transport. In actual monitoring, when both parameters show abnormal changes simultaneously, the probability of leakage is extremely high, therefore they are given considerable weight. This allows the fluid transport anomaly coefficient to more prominently reflect such high-risk situations.

[0143] An increase in average water pressure can be caused by various factors, including blockages and leaks. Its impact on leaks is relatively indirect, transmitted through intermediate factors such as the location and extent of the blockage and the pipe's pressure resistance. For example, a partial blockage in a pipe can lead to increased water pressure. If the pipe itself has insufficient pressure resistance, it may deform and rupture, resulting in leakage. However, this process involves multiple factors, and an increase in water pressure does not necessarily lead to leakage. Therefore, judging the likelihood of leakage solely based on changes in average water pressure involves a degree of uncertainty.

[0144] Dynamic changes in water flow at the leak point cause water pressure fluctuations that propagate and affect pipe sealing components and welds. However, the propagation process of water pressure fluctuations is complex, involving various factors such as water flow characteristics and pipe structure, and its effect on leakage is not direct. For example, slight water pressure fluctuations may not immediately lead to leakage; only when the amplitude and duration of the fluctuations reach a certain level will they damage sealing components and welds, increasing the risk of leakage.

[0145] The interaction term between the mean and variance of water pressure has a weaker, more direct, and less forceful impact on leakage than flow-related parameters. In practice, when water pressure-related parameters are abnormal, the likelihood of leakage is relatively low, or further assessment using more parameters is necessary. Weight less than This is to reasonably reflect its importance in assessing the possibility of leakage.

[0146] Water hammer caused by leakage leads to an increase in the average rate of change of flow rate, which affects pipe walls and connections through impact force. However, the generation and action of this impact force involve complex physical processes such as sudden changes in water flow and pipe response. For example, the magnitude of the impact force generated by water hammer is related to various factors such as the location of the leak, pipe material, and water flow velocity. An increase in the average rate of change of flow rate does not necessarily mean that leakage has occurred; other factors must be considered. Therefore, its correlation with the likelihood of leakage is relatively weak.

[0147] Dynamic changes in water flow at the leakage point cause drastic fluctuations in water pressure, which propagate and affect the fatigue life of pipe materials. However, this process also involves complex water flow propagation and changes in material mechanics. Moreover, pipe materials themselves possess a certain degree of fatigue resistance, and slight water pressure fluctuations will not immediately trigger leakage. Only long-term or significant water pressure fluctuations can gradually reduce the performance of pipe materials and increase the risk of leakage; their impact on the likelihood of leakage is relatively indirect and delayed.

[0148] The impact of these two parameters on leakage is complex and indirect, acting through multiple intermediate physical processes. In actual monitoring, when these two parameters are abnormal, the likelihood of leakage is relatively low, or requires long-term observation and more data to determine the leakage risk. Compared to the first two sets of parameters, their impact on leakage is less direct and significant. By minimizing the weight, the fluid transport anomaly coefficient is used to reasonably allocate the contribution of each parameter to the judgment of leakage probability during comprehensive evaluation.

[0149] In conclusion, On this basis, let .

[0150] As one implementation method, The value range is 0.4-0.6. The value range is 0.3-0.4. The value range is 0.1-0.3. The specific value is set by the technical personnel according to the actual situation and is not restricted here.

[0151] Based on the above embodiments, the structural thermal deformation coefficient is obtained based on temperature and strain characteristic parameters, using the following formula:

[0152]

[0153] in, The structural thermal deformation coefficient of a section is used to assess the risk of damage to the pipeline structure due to thermal deformation by combining four indicators: average temperature change rate, duration of abnormal temperature points, maximum strain value, and average change frequency. The larger the structural thermal deformation coefficient, the greater the risk of damage to the pipeline structure in that section due to thermal deformation, and therefore the more likely leakage is to occur.

[0154] In the formula, This serves as a benchmark for the average rate of temperature change. This serves as a baseline value for the duration of abnormal temperature points. This is the reference value for the maximum strain. This serves as the reference value for the average strain variation frequency;

[0155] Among them, the benchmark values ​​for the average rate of temperature change, duration of abnormal temperature points, maximum strain value, and average strain change frequency are calculated by collecting a large amount of historical temperature and strain data of water pipelines under normal operating conditions, and using these historical data as benchmark values.

[0156] Based on this, it should be noted that:

[0157] If the average rate of temperature change is greater than the baseline value, it means that the temperature change in the pipeline is more drastic per unit time. In water pipeline systems, temperature changes are usually relatively stable. When the average rate of temperature change increases abnormally, it is likely due to leakage in the pipeline. The water at the leakage point undergoes rapid and abnormal heat exchange with the surrounding environment. Water has a high specific heat capacity, and its leakage flow carries a large amount of heat, causing a sharp change in the local temperature field of the pipeline. This rapid temperature change will cause uneven thermal expansion and contraction of the pipeline material, forming thermal stress inside the pipeline. Under such thermal stress for a long time, the microstructure of the pipeline material will gradually be damaged, producing microcracks. As time goes by, these microcracks continue to expand, which may eventually lead to pipeline rupture, thereby increasing the possibility of leakage in the water pipeline and increasing the risk of damage to the pipeline structure due to thermal deformation, thus increasing the structural thermal deformation coefficient.

[0158] If the duration of abnormal temperature points is longer than the baseline value, it indicates that certain locations on the pipeline are in an abnormal temperature state for an extended period. Under normal circumstances, the temperature at various points in a water pipeline should be within a reasonable range and relatively stable. The prolonged presence of abnormal temperature points is highly likely due to leaks in the pipeline. The leaking water continuously exchanges heat with the surrounding environment, causing the temperature at that location to deviate from the normal level. For example, leaking hot water will continuously heat the surrounding soil and the area around the pipeline, leading to persistent abnormal temperatures. This prolonged abnormal thermal environment will accelerate the aging of pipeline materials, especially for plastic pipes, reducing their toughness and increasing their brittleness. Metal pipes may experience accelerated corrosion, severely affecting the structural strength and sealing of the pipeline, greatly increasing the likelihood of leaks in the water pipeline, and increasing the risk of damage to the pipeline structure due to thermal deformation, thereby increasing the structural thermal deformation coefficient.

[0159] If the maximum strain value is larger than the reference value, it indicates that the maximum deformation the pipeline is experiencing exceeds the normal range. During water transportation, the pipeline itself will experience strain due to factors such as internal water pressure and external soil pressure, but the strain value should be within a controllable range. When the maximum strain value increases, it may be due to leakage in the pipeline. The pipeline wall around the leakage point is affected by the scouring of water flow and pressure changes, and bears additional stress. This additional stress is superimposed on the normal operating stress, causing the pipeline to deform significantly at that location. Moreover, the stability of the overall pipeline structure may also be compromised by the local deformation caused by leakage, resulting in a redistribution of stress in other parts, further increasing the overall maximum strain value. Excessive strain can change the crystal structure of the pipeline material, weakening the material's load-bearing capacity and significantly increasing the probability of cracks. This, in turn, significantly increases the possibility of leakage in the water transportation pipeline, making the risk of damage to the pipeline structure due to thermal deformation greater, thereby increasing the structural thermal deformation coefficient.

[0160] If the average strain variation frequency is larger than the reference value, it means that the strain state of the pipeline changes more frequently per unit time. In a normally operating pipeline, the strain variation frequency is relatively stable and low. An increase in the average strain variation frequency is likely closely related to pipeline leakage. The instability of water flow and dynamic pressure changes at the leakage point will cause the pipeline wall to bear stresses of different directions and magnitudes at different times, resulting in continuous changes in the strain state of the pipeline. For example, the impact of water flow at the leakage point will cause the pipeline wall to be subjected to a large pressure instantaneously, resulting in strain. Subsequently, the water flow fluctuates and the pressure decreases, and the strain changes again. This frequent strain change is similar to the fatigue process of metallic materials, which will cause the pipeline material to gradually fatigue and damage, reducing its crack resistance. With the accumulation of time, the pipeline is more likely to develop cracks in weak parts, providing channels for leakage. The possibility of leakage in water pipelines increases, and the risk of damage to the pipeline structure due to thermal deformation is greater, thereby increasing the structural thermal deformation coefficient.

[0161] In summary, the structural thermal deformation coefficient of the section is positively correlated with the average rate of temperature change, the duration of abnormal temperature points, the maximum strain value, and the average frequency of strain change.

[0162] Furthermore, the effects of various temperature and strain characteristic parameters on the risk of damage to the pipeline structure due to thermal deformation are independent and additive. That is, the changes in the average rate of temperature change, the duration of abnormal temperature points, the maximum strain value, and the average strain change frequency all affect the structural thermal deformation coefficient independently of the others. For example, changes in the average rate of temperature change primarily affect the likelihood of leakage through changes in material stress caused by thermal expansion and contraction; this process is largely unaffected by the direct interference of the average strain change frequency. The duration of abnormal temperature points mainly affects leakage due to the aging of the pipeline material, and its direct interaction with the maximum strain value is relatively weak. Since they each influence leakage risk through different physical mechanisms, their combined effect can be represented by simple addition.

[0163] In summary, the functional relationship between the structural thermal deformation coefficient, the average rate of temperature change, the duration of abnormal temperature points, the maximum strain value, and the average frequency of change can be expressed using the above linear summation form.

[0164] In the formula, This is a weighting factor for the ratio of the average rate of temperature change to its reference value. This is a weighting factor for the ratio of the duration of an abnormal temperature point to its baseline value. The weighting factor is the ratio of the maximum strain value to its reference value. The weighting coefficient for the ratio of the average strain variation frequency to its reference value;

[0165] The average rate of temperature change directly reflects the drastic change in temperature within a pipeline per unit time. When this rate increases compared to a baseline value, it causes uneven thermal expansion and contraction of the pipeline material, creating thermal stress within the pipeline. This thermal stress begins to damage the pipeline structure at the microstructural level. Under long-term action, microcracks propagate rapidly, directly threatening the structural integrity of the pipeline and leading to a sharp increase in the risk of pipeline rupture and leakage. Its effect is direct and rapid; the time interval between abnormal temperature changes and the emergence of structural damage risk is relatively short, making its impact on pipeline structural damage risk most significant. Therefore, it is given the highest weight. .

[0166] The duration of abnormal temperatures reflects the cumulative effect of pipelines being in abnormal temperature conditions. While prolonged abnormal temperatures may not cause structural damage as quickly as rapid temperature changes, they accelerate the aging of pipeline materials, such as reducing the toughness of plastic pipes and intensifying corrosion of metal pipes, gradually weakening the pipeline's structural strength and sealing performance. However, this effect is a relatively slow process; the time required for abnormal temperatures to lead to a significant decline in material properties and the risk of leakage is relatively long. Compared to the average rate of temperature change, its impact on the risk of pipeline structural damage is slightly weaker in both speed and directness. Less than .

[0167] An increase in the maximum strain indicates that the pipeline is undergoing deformation beyond the normal range, typically caused by water erosion and pressure changes at the leakage point. While excessive strain can alter the crystal structure of the pipeline material and weaken its load-bearing capacity, the material itself possesses a certain resistance to deformation. In the initial stage of increased maximum strain, the pipeline will not immediately fail or leak; stress accumulation over a period of time is required before serious problems such as cracks appear. Its impact on the risk of pipeline structural damage is a combined result of external stress and the material's inherent properties, and is not as direct as the effect of temperature changes on the internal stress of the material. Less than .

[0168] An increase in the average strain variation frequency indicates frequent changes in the pipeline's strain state, similar to the fatigue process of metallic materials, leading to gradual fatigue damage. However, material fatigue damage is a long-term cumulative process; compared to the previous parameters, its destructive effect on the pipeline structure requires a longer period of strain cycles to become apparent. Moreover, in the early stages of fatigue damage, the pipeline's structural integrity can still be maintained, and the increase in leakage risk is relatively slow. Therefore, it has the least impact on the risk of damage to the pipeline structure due to thermal deformation, and its corresponding weighting coefficient is... Also the smallest.

[0169] In conclusion, On this basis, let .

[0170] As one implementation method, The value range is 0.4-0.6. The value range is 0.2-0.3. The value range is 0.25-0.4. The value range is 0.05-0.2. The specific value is set by the technical personnel according to the actual situation and is not restricted here.

[0171] Based on the above embodiments, the flow rate difference and water pressure ratio of the current section are obtained based on the flow rate and water pressure characteristic parameters of the current section and the previous section, according to the following formula:

[0172]

[0173]

[0174] in, For the first The difference in flow rate between each segment, For the first Water pressure ratio of each section For the first Average traffic flow in each segment For the first Average traffic flow in each segment For the first Average water pressure in each section For the first Average water pressure in each section For the index of the segment, This refers to the number of sections of the water pipeline.

[0175] S4. For different regions, construct corresponding leakage type identification models. Take the geographical environment data, fluid transmission anomaly coefficient, structural thermal deformation coefficient, flow difference and water pressure ratio of each section belonging to the same region in the historical time period as input, and take the actual leakage type of the corresponding section as the label output to train the leakage type identification model.

[0176] Specifically, for the actual leakage type, for visible leakage points, the leakage type is preliminarily determined by observing the leakage location, shape, and leakage medium on site. The leakage type is one or more of the following combinations: no leakage, single-point leakage, multi-point leakage, and local rupture leakage.

[0177] Based on the above embodiments, the leakage type identification model is constructed using a deep learning network based on a multilayer perceptron. The deep neural network of the multilayer perceptron includes an input layer, a first hidden layer, a second hidden layer, a third hidden layer, and an output layer. The first hidden layer, the second hidden layer, and the third hidden layer each have at least two neurons and all use ReLU (corrected linear unit) as the activation function.

[0178] In the leakage type identification model, the input features of the deep learning network of the multilayer perceptron include: geographical environment data, fluid transport anomaly coefficient, structural thermal deformation coefficient, flow rate difference and water pressure ratio, a total of 7 features.

[0179] The structure of a deep learning network with a multilayer perceptron is as follows:

[0180] Input layer: Receives input from 7 features;

[0181] The first hidden layer has 128 neurons and uses ReLU as the activation function.

[0182] The second hidden layer has 64 neurons and also uses the ReLU activation function;

[0183] The third hidden layer has 32 neurons and uses the ReLU activation function;

[0184] Output layer: has 1 neuron, which outputs the actual leakage type of the corresponding segment.

[0185] The training process for the leakage type identification model is as follows:

[0186] The training process uses historical geographical environmental data, fluid transport anomaly coefficients, structural thermal deformation coefficients, flow rate differences, and water pressure ratios for each segment belonging to the same region as input, and the actual leakage type of the corresponding segment as the label output. Mean squared error is used as the loss function. When the mean squared error is within a certain range... When the range is within the specified range, the training of the leakage type identification model is completed.

[0187] Building upon the above embodiments, the correlation between the characteristics of data collected from different regions and leakage types exhibits specificity. For example, in one region, flow rate difference might be a key indicator for identifying single-point leakage; while in another region, the rate of temperature change is closely related to localized rupture leakage. By constructing dedicated models for different regions, the unique connections between data characteristics and leakage types in each region can be deeply explored, enabling the models to more accurately identify leakage types based on these characteristics. Therefore, it is necessary to construct corresponding leakage type identification models for different regions and use geographical environmental data as an input parameter for these models.

[0188] Based on the above embodiments, introducing the flow difference and water pressure ratio between adjacent sections as model inputs has the following advantages:

[0189] First, flow rate difference and water pressure ratio can reflect the changes in the pipeline between different sections. Under normal circumstances, the flow rate and water pressure of adjacent sections should have a certain continuity and stability. If abnormal flow rate difference or water pressure ratio occurs, it may mean that there are some special conditions between these two adjacent sections, such as pipeline leakage or local blockage, which can help to find possible anomalies or leakage locations.

[0190] Secondly, relying solely on flow rate and water pressure data from a single section to determine leakage can be susceptible to interference from various factors, leading to low accuracy. However, the flow rate difference and water pressure ratio between adjacent sections can serve as indicators of relative change, more clearly highlighting differences from normal conditions. By using these differences and ratios as model inputs, the model can better capture leakage-related features, thereby improving the accuracy of locating the leak's location and type, and reducing the possibility of misjudgments and omissions.

[0191] Third, leakage in water pipelines varies under different geographical environments, climatic conditions, and pipeline operating conditions. The flow rate difference and water pressure ratio between adjacent sections can, to some extent, reflect the combined impact of these environmental and operating factors on the pipeline system. Even under different operating conditions and environments, as long as pipeline leakage or other abnormalities occur, the flow rate and water pressure relationship between adjacent sections will usually change accordingly, and these changes can be reflected in the flow rate difference and water pressure ratio. Therefore, introducing these parameters as model inputs can enhance the model's adaptability to different operating conditions and environments, enabling the model to function more stably and improving positioning accuracy.

[0192] S5. Input the geographical environment data, fluid transmission anomaly coefficient, structural thermal deformation coefficient, flow rate difference and water pressure ratio of each section within the current time period into the corresponding leakage type identification model to predict the actual leakage type of each section within the current time period, thereby achieving rapid location of leakage in long-distance water transmission pipelines.

[0193] The above formulas are all dimensionless calculations. The formulas are derived from software simulations based on a large amount of collected data to obtain the most recent real-world results. The preset parameters in the formulas are set by those skilled in the art according to the actual situation.

[0194] The above embodiments can be implemented, in whole or in part, by software, hardware, firmware, or any other combination thereof. When implemented in software, the above embodiments can be implemented, in whole or in part, as a computer program product. Those skilled in the art will recognize that the units and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented by software, electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution.

[0195] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment, depending on actual needs.

[0196] The above description is merely a specific embodiment of this application, but the scope of protection of this application is not limited thereto. Any changes or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in this application should be included within the scope of protection of this application.

Claims

1. A method for quickly locating a leak in a long distance water pipeline, characterized in that: The specific steps include: S1. Considering the significant differences in the geographical environment along the long-distance water transmission pipeline, measurement points are set at equal intervals along the axial direction of the long-distance water transmission pipeline to collect its geographical environment data and process it to generate a comprehensive score. Based on the comprehensive score, the water transmission pipeline is divided into different regions, and each region is further divided into multiple segments at equal intervals. All segments are sorted according to the direction of water flow to form a continuous segment sequence, and monitoring data and leakage types of each segment in the segment sequence are collected in the historical time period. S2. Perform feature extraction on the monitoring data of each section to obtain the flow characteristic parameters, water pressure characteristic parameters, temperature characteristic parameters and strain characteristic parameters of each section; S3. Based on flow rate and water pressure characteristic parameters, the fluid transmission anomaly coefficient is obtained to measure the degree of fluid transmission affected by leakage. Based on temperature and strain characteristic parameters, the structural thermal deformation coefficient is obtained to assess the risk of damage to the pipeline structure due to thermal deformation. Based on the flow rate and water pressure characteristic parameters of the current section and the previous section, the flow rate difference and water pressure ratio of the current section are obtained to capture the changing characteristics of fluid transmission status between adjacent sections. S4. For different regions, construct corresponding leakage type identification models. Take the geographical environment data, fluid transmission anomaly coefficient, structural thermal deformation coefficient, flow difference and water pressure ratio of each section belonging to the same region in the historical time period as input, and take the actual leakage type of the corresponding section as the label output to train the leakage type identification model. S5. Input the geographical environment data, fluid transmission anomaly coefficient, structural thermal deformation coefficient, flow rate difference and water pressure ratio of each section in the current time period into the corresponding leakage type identification model to predict the actual leakage type of each section in the current time period, so as to realize the rapid location of leakage in long-distance water transmission pipelines. The geographic environmental data includes altitude, slope, and temperature.

2. The method for rapid location of leakage in long-distance water transmission pipelines according to claim 1, characterized in that: The leakage type is one or more of the following: no leakage, single-point leakage, multi-point leakage, and local rupture leakage. The flow characteristic parameters include the mean flow rate, the variance of the flow rate, and the rate of change of the flow rate. The water pressure characteristic parameters include the mean water pressure, the variance of the water pressure, and the amplitude of the water pressure fluctuation. The temperature characteristic parameters include the rate of change of temperature and the duration of abnormal temperature points. The strain characteristic parameters include the maximum strain value and the frequency of strain change.

3. The method for rapid location of leakage in long-distance water transmission pipelines according to claim 1, characterized in that: The altitude, slope, and temperature are standardized. The standardized altitude, slope, and temperature values ​​are then compared with their baseline values ​​to calculate the deviation values, based on the following formula: in, , , The first The deviation values ​​of altitude, slope, and temperature at each measurement point. , , The first The altitude, slope, and temperature of each measurement point. , , These are the baseline values ​​for altitude, slope, and temperature, respectively. For the index of the measurement point, , The number of measurement points; The overall score is calculated based on the deviations in altitude, slope, and temperature, and their respective weights, using the following formula: in, For the first A comprehensive score for each measurement point; In the formula, This is the weighting coefficient for the altitude deviation value. This is the weighting coefficient for the slope deviation value. The weighting coefficient for the temperature deviation value is... On this basis, let .

4. The method for rapid location of leakage in long-distance water transmission pipelines according to claim 3, characterized in that: The water pipeline zones are divided based on a comprehensive score, and the specific process is as follows: Filter out the comprehensive score from all measurement points These measurement points, whether continuously or scattered in space, are grouped into a region, named the region. ; Select all measurement points that meet the comprehensive score The measurement points are used to divide the pipe sections corresponding to these measurement points into regions, which are named regions. ; Select all measurement points that meet the comprehensive score The measurement points are used to divide the pipe sections corresponding to these measurement points into regions, which are named regions. ; in, This is the threshold for the overall score.

5. The method for rapid location of leakage in long-distance water transmission pipelines according to claim 2, characterized in that: Based on the characteristic parameters of flow rate and water pressure, the fluid transport anomaly coefficient is obtained according to the following formula: in, The fluid transport anomaly coefficient for the section; In the formula, The average flow rate is... For flow variance, The average rate of change of flow rate This is the average water pressure. For water pressure variance, This refers to the amplitude of water pressure fluctuation. This is the baseline value for the average flow rate. This serves as the baseline value for the flow variance. This is the baseline value for the average water pressure. This serves as the baseline value for the water pressure variance. This serves as the baseline value for the average rate of change of flow rate. This serves as the baseline value for the water pressure fluctuation amplitude; In the formula, This is the weighting coefficient for the interaction term between the ratio of the flow mean to its baseline value and the ratio of the flow variance to its baseline value. This is the weighting coefficient for the interaction term between the ratio of the mean water pressure to its reference value and the ratio of the variance of water pressure to its reference value. The weighting coefficients for the interaction terms of the ratio of the average rate of change of flow rate to its reference value and the ratio of the amplitude of water pressure fluctuation to its reference value, in On this basis, let .

6. The method for rapid location of leakage in long-distance water transmission pipelines according to claim 2, characterized in that: Based on temperature and strain characteristic parameters, the structural thermal deformation coefficient is obtained using the following formula: in, The structural thermal deformation coefficient of the section; In the formula, The average rate of temperature change. The duration of the abnormal temperature point. For the maximum strain, The frequency of strain change This serves as a benchmark for the average rate of temperature change. This serves as a baseline value for the duration of abnormal temperature points. This is the reference value for the maximum strain. This serves as the reference value for the average strain variation frequency; In the formula, This is a weighting factor for the ratio of the average rate of temperature change to its reference value. This is a weighting factor for the ratio of the duration of an abnormal temperature point to its baseline value. The weighting factor is the ratio of the maximum strain value to its reference value. The weighting coefficient for the ratio of the average frequency of strain variation to its reference value is... On this basis, let .

7. The method for rapid location of leakage in long-distance water transmission pipelines according to claim 2, characterized in that: Based on the flow rate and water pressure characteristic parameters of the current section and the previous section, the flow rate difference and water pressure ratio of the current section are obtained, according to the following formula: in, For the first The difference in flow rate between each segment, For the first Water pressure ratio of each section For the first Average traffic flow in each segment For the first Average traffic flow in each segment For the first Average water pressure in each section For the first Average water pressure in each section For the index of the segment, , This refers to the number of sections of the water pipeline.

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