Pipeline leakage monitoring method based on digital twinning

Abstract

This invention relates to the field of pipeline safety technology, specifically to a pipeline leak monitoring method based on digital twins. The method involves a data detection module that detects the physical entity data and operational data of the pipeline to determine its physical properties and operational status; a data processing module that collects and analyzes the detected operational data to determine if a leak has occurred; a digital twin-based pipeline model is constructed using the physical entity data and the leak information obtained from the analysis; the constructed digital twin-based pipeline model is simulated to verify its accuracy, and optimization is performed based on the simulation results. This invention uses a data detection module to detect real-time temperature, pressure, and vibration data at various locations along the pipeline, and a data processing module that collects the data detected by the data detection module and performs single-point and overall comparisons to achieve comprehensive monitoring of pipeline leaks, improving the accuracy and timeliness of pipeline leak monitoring.

Description

Technical Field

[0001] This invention relates to the field of pipeline safety technology, and in particular to a pipeline leakage monitoring method based on digital twins. Background Technology

[0002] With the rapid advancement of urbanization in my country, urban gas pipeline networks are constantly expanding and becoming increasingly large in scale. The intricate network of underground pipelines presents growing challenges to the construction and operation of urban gas pipeline networks. However, many cities have focused too much on above-ground facilities during construction, neglecting the scientific management of underground pipeline networks. This has led to frequent safety accidents in urban gas pipeline networks, seriously affecting the lives and property of the people. Cities urgently need to strengthen the scientific management of gas pipeline networks and utilize new-generation information technology to build pipeline leak monitoring systems to detect potential safety hazards early and prevent accidents before they occur.

[0003] Chinese Patent Publication No. CN115370838A discloses a pipeline and a pipeline leakage monitoring system, belonging to the field of pipeline safety technology. The pipeline is composed of alternating pipe sections and valves. Each pipe section includes an inner sleeve and an outer sleeve fitted outside the inner sleeve, and an annular cavity is formed between the inner sleeve and the outer sleeve. The two ends of the annular cavity are closed, and a support is provided in the annular cavity to connect the inner and outer sleeves into one unit. In addition, the pipeline is also equipped with a pressure measuring instrument to measure the pressure inside the annular cavity.

[0004] This shows that current pipeline leak monitoring is inefficient and untimely. Summary of the Invention

[0005] Therefore, this invention provides a pipeline leakage monitoring method based on digital twins to overcome the problems of low monitoring efficiency and untimely monitoring in the prior art.

[0006] To achieve the above objectives, the present invention provides a pipeline leak monitoring system based on digital twins, comprising:

[0007] The data detection module includes several temperature sensors, several pressure sensors, and several vibration sensors, used to detect real-time temperature parameters, real-time pressure parameters, and real-time vibration parameters at various locations in the pipeline.

[0008] The data processing module is used to collect, analyze, and process the real-time parameters detected by the data detection module to determine the leakage status of the pipeline. It compares the actual temperature, pressure, and vibration values ​​detected by the temperature, pressure, and vibration sensors with preset standard temperature, pressure, and vibration values ​​to determine whether leakage has occurred at various locations in the pipeline. It calculates the overall pipeline temperature evaluation value, overall pipeline pressure evaluation value, and overall pipeline vibration evaluation value based on the actual temperature values ​​detected by the temperature sensors, pressure values ​​detected by the pressure sensors, and vibration values ​​detected by the vibration sensors, and compares these values ​​with preset standard evaluation ranges for overall pipeline temperature, pressure, and vibration to determine whether the overall temperature, pressure, and vibration of the pipeline are abnormal. Finally, it calculates the overall pipeline leakage evaluation value based on the overall pipeline temperature evaluation value, overall pipeline pressure evaluation value, and overall pipeline vibration evaluation value, and compares this value with the overall pipeline leakage standard evaluation value to determine whether the entire pipeline is leaking.

[0009] The modeling module constructs a pipeline model based on digital twins based on the real-time parameters obtained by the data detection module and the analysis results of the real-time parameters by the data processing module.

[0010] The simulation module is used to simulate the digital twin-based pipeline model constructed by the modeling module to determine the accuracy of the digital twin-based pipeline model.

[0011] Furthermore, the pipeline to be tested is evenly divided into several test points according to a fixed length. For each test point, a temperature sensor, a pressure sensor, and a vibration sensor are set. Different standard temperature values, standard pressure values, and standard vibration values ​​are set for different test points. The actual temperature values, actual pressure values, and actual vibration values ​​of each test point are compared with the preset standard temperature values, standard pressure values, and standard vibration values ​​to determine whether the pipeline has leaked.

[0012] Furthermore, the comparison process for determining whether a pipeline has leaked includes single-point comparison and overall comparison. By comparing each detection point, the leakage situation at each location in the pipeline is determined. The single-point comparison includes single-point temperature comparison, single-point pressure comparison, and single-point vibration comparison. By summarizing the actual temperature values, actual pressure values, and actual vibration values ​​of each detection point, the overall pipeline leakage is determined. The overall comparison includes overall temperature comparison, overall pressure comparison, and overall vibration comparison.

[0013] Furthermore, different standard temperature ranges are set at different detection points. When comparing the temperature at any detection point, the relationship between the actual temperature value detected by the temperature sensor and the corresponding standard temperature range is used to determine whether a leak has occurred in the pipeline at that detection point. If the actual temperature value exceeds the standard temperature range, it is determined that a leak has occurred in the pipeline at that location.

[0014] Different standard pressure ranges are set at different detection points. When comparing the single-point pressure at any detection point, the relationship between the actual pressure value detected by the pressure sensor and the corresponding standard pressure range is used to determine whether a leak has occurred in the pipeline at the detection point. If the actual pressure value exceeds the standard pressure range, it is determined that a leak has occurred in the pipeline at that location.

[0015] Different standard vibration ranges are set at different detection points. When a single-point vibration comparison is performed at any detection point, the relationship between the actual vibration value detected by the vibration sensor and the corresponding standard vibration range is used to determine whether a leak has occurred in the pipeline at that detection point. If the actual vibration value exceeds the standard vibration range, it is determined that a leak has occurred in the pipeline at that location.

[0016] Furthermore, based on the single-point temperature comparison, the actual temperature values ​​of all detection points are integrated, including renumbering the number of detection points with excessively low temperatures and the number of detection points with excessively high temperatures. This allows for the calculation of the overall pipeline temperature evaluation value, which is then compared with the overall pipeline temperature standard evaluation range to determine whether the overall pipeline temperature is abnormal. If the overall pipeline temperature evaluation value exceeds the overall pipeline temperature standard evaluation range, the overall pipeline temperature is abnormal, and the system issues a temperature abnormality command. The data processing module then performs a detailed analysis of the abnormalities in overall pressure and overall vibration to determine whether the overall pipeline is leaking.

[0017] Based on the single-point pressure comparison, the actual pressure values ​​of all detection points are integrated, including renumbering the number of detection points with excessively low pressure and the number of detection points with excessively high pressure. The overall pipeline pressure evaluation value is then calculated and compared with the overall pipeline pressure standard evaluation range to determine whether the overall pipeline pressure is abnormal. If the overall pipeline pressure evaluation value exceeds the overall pipeline pressure standard evaluation range, the overall pipeline pressure is abnormal, and the system issues a pressure abnormality command. The data processing module performs a detailed analysis of the abnormalities in overall temperature and overall vibration to determine whether the overall pipeline is leaking.

[0018] Based on the single-point vibration comparison, the actual vibration values ​​of all detection points are integrated, including renumbering the number of detection points with excessively low vibration and the number of detection points with excessively high vibration. The overall pipeline vibration evaluation value is then calculated and compared with the overall pipeline vibration standard evaluation range to determine whether the overall pipeline vibration is abnormal. If the overall pipeline vibration evaluation value exceeds the overall pipeline vibration standard evaluation range, the overall pipeline vibration is abnormal, and the system issues a vibration abnormality command. The data processing module then performs a detailed analysis of the abnormalities in overall temperature and overall pressure to determine whether the overall pipeline is leaking.

[0019] Furthermore, for any detection point, if its actual temperature value exceeds its corresponding standard temperature range, the detection point is classified into low-temperature points and high-temperature points. The low-temperature point has an actual temperature value less than the lowest temperature value of the standard temperature range, and each low-temperature point is equipped with a low-temperature calculation compensation parameter for its impact on the overall pipeline temperature evaluation value. The high-temperature point has an actual temperature value greater than the highest temperature value of the standard temperature range, and each high-temperature point is equipped with a high-temperature calculation compensation parameter for its impact on the overall pipeline temperature evaluation value.

[0020] Wherein, the low-temperature calculation compensation parameter is negatively correlated with the actual temperature value of the low-temperature point, and the high-temperature calculation compensation parameter is positively correlated with the actual temperature value of the high-temperature point;

[0021] For any detection point, if its actual pressure value exceeds its corresponding standard pressure range, the detection point is classified into low-pressure points and high-pressure points. The low-pressure points have actual pressure values ​​less than the minimum pressure value of the standard pressure range, and each low-pressure point is equipped with a low-pressure calculation compensation parameter for its impact on the overall pipeline pressure evaluation value. The high-pressure points have actual pressure values ​​greater than the maximum pressure value of the standard pressure range, and each high-pressure point is equipped with a high-pressure calculation compensation parameter for its impact on the overall pipeline pressure evaluation value.

[0022] The low-pressure calculation compensation parameter is negatively correlated with the actual pressure value of the low-pressure point, and the high-pressure calculation compensation parameter is positively correlated with the actual pressure value of the high-pressure point.

[0023] For any detection point, if its actual vibration value exceeds its corresponding standard vibration range, the detection point is classified into low-frequency points and high-frequency points. The low-frequency points have actual vibration values ​​less than the lowest vibration value of the standard vibration range, and each low-frequency point is equipped with a low-frequency calculation compensation parameter for its impact on the overall pipeline vibration evaluation value. The high-frequency points have actual vibration values ​​greater than the highest vibration value of the standard vibration range, and each high-frequency point is equipped with a high-frequency calculation compensation parameter for its impact on the overall pipeline vibration evaluation value.

[0024] The low-frequency calculation compensation parameter is negatively correlated with the actual vibration value of the low-frequency point, and the high-frequency calculation compensation parameter is positively correlated with the actual vibration value of the high-frequency point.

[0025] Furthermore, the overall pipeline leakage evaluation value is calculated based on the overall pipeline temperature evaluation value, the overall pipeline pressure evaluation value, and the overall pipeline vibration evaluation value.

[0026] If the overall pipeline leakage evaluation value is greater than the overall pipeline leakage standard evaluation value, then the overall pipeline is determined to have leaked. The overall pipeline leakage standard evaluation value is set in the system.

[0027] When calculating the overall pipeline leakage evaluation value, a first calculation compensation parameter is set for the overall pipeline leakage evaluation value based on the first difference between the arithmetic mean of the overall pipeline temperature standard evaluation value and the lowest standard evaluation value of the overall pipeline temperature and the overall pipeline temperature evaluation value; a second calculation compensation parameter is set for the overall pipeline leakage evaluation value based on the second difference between the overall pipeline pressure standard evaluation value and the lowest standard evaluation value of the overall pipeline pressure and the overall pipeline pressure evaluation value; and a third calculation compensation parameter is set for the overall pipeline leakage evaluation value based on the third difference between the overall pipeline vibration standard evaluation value and the lowest standard evaluation value of the overall pipeline vibration and the overall pipeline vibration evaluation value.

[0028] Furthermore, when the data processing module determines whether the entire pipeline is leaking,

[0029] If the first calculated compensation parameter is greater than or equal to the first calculated compensation evaluation value, the data processing module determines that the first difference meets the single judgment condition for the pipeline to leak as a whole.

[0030] If the second calculated compensation parameter is greater than or equal to the second calculated compensation evaluation value, the data processing module determines that the second difference meets the single judgment condition for the overall pipeline leakage.

[0031] If the third calculated compensation parameter is greater than or equal to the third calculated compensation evaluation value, the data processing module determines that the third difference meets the single judgment condition for the overall pipeline leakage.

[0032] The data processing module is configured with the first calculated compensation evaluation value.

[0033] The data processing module is configured with the second calculated compensation evaluation value.

[0034] The data processing module contains the third calculated compensation evaluation value.

[0035] Furthermore, based on the number of items whose differences meet a single judgment criterion, the alarm levels for overall pipeline leakage are classified.

[0036] If the first difference, the second difference, and the third difference all meet a single judgment condition, a level three alarm signal will be issued to stop the pipeline operation in a timely manner.

[0037] If two or more of the first difference, second difference, and third difference meet a single judgment condition, a first-level alarm signal is issued, and the data detection module controls the pipeline to be detected again to determine whether a false alarm has occurred.

[0038] This invention also discloses a pipeline leak monitoring method based on digital twins, characterized by comprising:

[0039] Step S1: Detect the physical entity data and operational data of the pipeline through the data detection module to determine the physical properties and operational status of the pipeline;

[0040] Step S2: The data processing module collects the detected operating data, analyzes and processes the operating data, and determines whether the pipeline has leaked.

[0041] Step S3: Construct a pipeline model based on digital twin using the physical entity data from step S1 and the pipeline leakage information obtained from the analysis and processing in step S2.

[0042] Step S4: Simulate the pipeline model based on digital twin constructed in step S3 to verify the accuracy of the model, and optimize it based on the simulation results.

[0043] Compared with existing technologies, the beneficial effects of this invention are as follows: This invention discloses a pipeline leakage monitoring system based on digital twins, including a data detection module, a data processing module, a modeling module, and a simulation module, wherein: the data detection module is used to detect real-time temperature parameters, real-time pressure parameters, and real-time vibration parameters at various locations in the pipeline; the data processing module is used to collect, analyze, and process the real-time parameters detected by the data detection module to determine the leakage status of the pipeline; by comparing the actual temperature values, actual pressure values, and actual vibration values ​​detected by the temperature sensors, pressure sensors, and vibration sensors with preset standard temperature values, standard pressure values, and standard vibration values, it determines whether a leak has occurred at various locations in the pipeline; and by calculating the overall pipeline temperature evaluation value based on the actual temperature values ​​detected by the temperature sensors and the actual pressure values ​​detected by the pressure sensors... The overall pipeline pressure evaluation value and the actual vibration values ​​detected by each vibration sensor are used to calculate the overall pipeline vibration evaluation value. This value is then compared with preset overall pipeline temperature standard evaluation values, overall pipeline pressure standard evaluation values, and overall pipeline vibration standard evaluation values ​​to determine if the overall pipeline temperature, pressure, and vibration are abnormal. Based on the overall pipeline temperature evaluation value, overall pipeline pressure evaluation value, and overall pipeline vibration evaluation value, the overall pipeline leakage evaluation value is calculated and compared with the overall pipeline leakage standard evaluation value to determine if a leak has occurred. The modeling module is used to construct a pipeline model based on digital twins based on the real-time parameters obtained by the data detection module and the analysis results of the real-time parameters by the data processing module. The simulation module is used to simulate the pipeline model based on digital twins constructed by the modeling module to determine the accuracy of the digital twin-based pipeline model. It reduces the complexity of building digital twin models, shortens the development cycle, and enables rapid construction of digital twin models. By optimizing the constructed digital twin-based pipeline model through the simulation module, the optimal digital twin pipeline model for the corresponding target business is obtained, ensuring the accuracy of the constructed digital twin pipeline model, realizing comprehensive monitoring of pipeline leaks, and improving the accuracy and timeliness of pipeline leak monitoring. Attached Figure Description

[0044] Figure 1 A flowchart of a pipeline leak monitoring method based on digital twins;

[0045] Figure 2 This is a schematic diagram of a pipeline leak monitoring system based on digital twins.

[0046] Figure 3 This is a schematic diagram of the internal structure of the pipeline;

[0047] The diagram includes: temperature sensor 1, pressure sensor 2, and vibration sensor 3. Detailed Implementation

[0048] To make the objectives and advantages of the present invention clearer, the present invention will be further described below with reference to embodiments; it should be understood that the specific embodiments described herein are merely for explaining the present invention and are not intended to limit the present invention.

[0049] Preferred embodiments of the present invention will now be described with reference to the accompanying drawings. Those skilled in the art should understand that these embodiments are merely illustrative of the technical principles of the present invention and are not intended to limit the scope of protection of the present invention.

[0050] It should be noted that in the description of this invention, the terms "upper", "lower", "left", "right", "inner", "outer", etc., which indicate the direction or positional relationship, are based on the direction or positional relationship shown in the drawings. This is only for the convenience of description and is not intended to indicate or imply that the device or element must have a specific orientation, or be constructed and operated in a specific orientation. Therefore, it should not be construed as a limitation of this invention.

[0051] Furthermore, it should be noted that, in the description of this invention, unless otherwise explicitly specified and limited, the terms "installation," "connection," and "linking" should be interpreted broadly. For example, they can refer to a fixed connection, a detachable connection, or an integral connection; they can refer to a mechanical connection or an electrical connection; they can refer to a direct connection or an indirect connection through an intermediate medium; and they can refer to the internal connection of two components. Those skilled in the art can understand the specific meaning of the above terms in this invention according to the specific circumstances.

[0052] Please see Figures 1-3 As shown, Figure 1 A flowchart of a pipeline leak monitoring method based on digital twins; Figure 2 This is a schematic diagram of a pipeline leak monitoring system based on digital twins. Figure 3 This is a schematic diagram of the internal structure of the pipeline.

[0053] This invention provides a pipeline leak monitoring method based on digital twins, comprising:

[0054] Step S1: Detect the physical entity data and operational data of the pipeline through the data detection module to determine the physical properties and operational status of the pipeline;

[0055] Step S2: The data processing module collects the detected operating data, analyzes and processes the operating data, and determines whether the pipeline has leaked.

[0056] Step S3: Construct a pipeline model based on digital twin using the physical entity data from step S1 and the pipeline leakage information obtained from the analysis and processing in step S2.

[0057] Step S4: Simulate the pipeline model based on digital twin constructed in step S3 to verify the accuracy of the model, and optimize it based on the simulation results.

[0058] Specifically, the pipeline leak monitoring system based on digital twins in this embodiment includes,

[0059] The data detection module includes a temperature sensor 1, a pressure sensor 2, and a vibration sensor 3, used to detect the real-time temperature parameters, real-time pressure parameters, and real-time vibration parameters of the pipeline.

[0060] The data processing module is used to collect, analyze, and process the real-time parameters detected by the data detection module to determine the leakage status of the pipeline. It compares the actual temperature, pressure, and vibration values ​​detected by the temperature, pressure, and vibration sensors with preset standard temperature, pressure, and vibration values ​​to determine whether leakage has occurred at various locations in the pipeline. It calculates the overall pipeline temperature evaluation value, overall pipeline pressure evaluation value, and overall pipeline vibration evaluation value based on the actual temperature values ​​detected by the temperature sensors, pressure values ​​detected by the pressure sensors, and vibration values ​​detected by the vibration sensors, and compares these values ​​with preset standard evaluation ranges for overall pipeline temperature, pressure, and vibration to determine whether the overall temperature, pressure, and vibration of the pipeline are abnormal. Finally, it calculates the overall pipeline leakage evaluation value based on the overall pipeline temperature evaluation value, overall pipeline pressure evaluation value, and overall pipeline vibration evaluation value, and compares this value with the overall pipeline leakage standard evaluation value to determine whether the entire pipeline is leaking.

[0061] The modeling module constructs a pipeline model based on digital twins based on the real-time parameters obtained by the data detection module and the analysis results of the real-time parameters by the data processing module.

[0062] The simulation module is used to simulate the digital twin-based pipeline model constructed by the modeling module to determine the accuracy of the digital twin-based pipeline model.

[0063] This invention uses a data detection module to detect real-time temperature, pressure, and vibration parameters at various locations along a pipeline. A data processing module collects, analyzes, and processes these real-time parameters to determine pipeline leakage. It compares the actual temperature, pressure, and vibration values ​​detected by the temperature, pressure, and vibration sensors with preset standard values ​​to determine if leakage has occurred at any location. Furthermore, it calculates an overall pipeline temperature evaluation value, an overall pipeline pressure evaluation value, and an overall pipeline vibration evaluation value based on the actual temperature, pressure, and vibration values ​​detected by the temperature, pressure, and vibration sensors, and compares these values ​​with preset standard evaluation values ​​to determine if the overall pipeline temperature, pressure, and vibration are abnormal. Finally, it calculates an overall pipeline leakage evaluation value based on the overall temperature, pressure, and vibration evaluation values ​​and compares this value with the overall pipeline leakage standard evaluation value to determine if a leak has occurred. This comprehensive monitoring of pipeline leaks improves the accuracy and timeliness of leak detection.

[0064] Specifically, in step S1 of this embodiment, the pipeline to be tested is evenly divided into several testing points according to a fixed length, including a first testing point A1, a second testing point A2, ..., an nth testing point An. For any testing point, a temperature sensor 1, a pressure sensor 2, and a vibration sensor 3 are set. The actual temperature value, actual pressure value, and actual vibration value of each testing point are obtained according to the set temperature sensor 1, pressure sensor 2, and vibration sensor 3. The relationship between the actual temperature value, actual pressure value, and actual vibration value of each testing point and the preset standard temperature value, standard pressure value, and standard vibration value is used to determine whether the pipeline has leaked. In the process of determination, it is necessary to compare the single-point temperature, single-point pressure, and single-point vibration with the overall temperature, overall pressure, and overall vibration.

[0065] Specifically, in this embodiment, a standard maximum temperature value is set for the i-th detection point Ai. and standard minimum temperature value Obtain the actual temperature value of the i-th detection point Ai. Let i = 1, 2, ..., n. Perform single-point temperature comparison for the i-th detection point Ai.

[0066] like If the temperature at detection point Ai is normal, it is determined that there is no leak in the pipe at that location.

[0067] like If the temperature at detection point Ai is too low, it is determined that there is a leak in the pipeline at that location.

[0068] like If the temperature at detection point Ai is too high, it is determined that there is a leak in the pipeline at that location.

[0069] Specifically, in this embodiment, the actual temperature values ​​of all detection points are integrated to determine whether the overall pipeline temperature is abnormal. The number of detection points with excessively low temperatures is obtained, and a first temperature score is calculated. The number of detection points with excessively high temperatures is obtained, and a second temperature score is calculated, including...

[0070] 1) Renumber the number of detection points with excessively low temperatures, designating them as the first low-temperature point A11, the second low-temperature point A12, ..., the m-th low-temperature point A1m.

[0071] 2) Renumber the number of detection points with excessively high temperatures, designating them as the first high-temperature point A21, the second high-temperature point A22, ..., the kth high-temperature point A2k.

[0072] To determine whether the overall temperature of the pipeline is abnormal, calculate the overall pipeline temperature evaluation value S1, and set...

[0073]

[0074] in, Let y be the actual temperature value of the high-temperature point. T1x is the actual temperature value of the y-th high-temperature point, and Dx is the low-temperature calculation compensation parameter for the overall pipeline temperature evaluation value S1 based on the actual temperature value of the x-th low-temperature point. The high-temperature calculation compensation parameter... Depending on the location of different inspection points on the pipeline, the high-temperature calculation parameters vary. The value of the low-temperature calculation compensation parameter Dx varies depending on the location of the different detection points on the pipeline.

[0075] If S11≤S1≤S10, then the overall temperature of the pipeline is considered normal.

[0076] If S1 < S11 or S1 > S10, the overall temperature of the pipeline is determined to be abnormal.

[0077] Among them, S10 is the highest standard evaluation value for the overall temperature of the pipeline.

[0078] S11 is the lowest standard evaluation value for the overall temperature of the pipeline.

[0079] Specifically, in this embodiment, the low-temperature calculation compensation parameter Dx is negatively correlated with the absolute value of the actual temperature value T1x at the x-th low-temperature point.

[0080] Dx=1 / (α1+|T1x|)

[0081] Wherein, α1 is the first negative feedback compensation parameter of the low-temperature calculation compensation parameter Dx.

[0082] The high-temperature calculation compensation parameter Ey is positively correlated with the actual temperature value T2y of the y-th high-temperature point.

[0083]

[0084] Where e is the high-temperature calculation adjustment parameter of the actual temperature value T2y at the y-th high-temperature point, relative to the high-temperature calculation compensation parameter Ey.

[0085] The standard maximum temperature value described in this embodiment The standard minimum temperature At that time, the first negative feedback compensation parameter α1 = -28.75, the high-temperature calculation adjustment parameter e = 0.002, the highest standard evaluation value of the overall pipeline temperature S10 = 10, the lowest standard evaluation value of the overall pipeline temperature S11 = -10, when the temperature of all detection points is the standard temperature value, the overall pipeline temperature evaluation value S1 = 4.8, which meets the standard evaluation range of the overall pipeline temperature. When the actual temperature value of all low-temperature points T1x = -73℃, then the low-temperature calculation compensation parameter Dx = 0.023. When the actual temperature value of all high-temperature points T1x = -73℃, then the low-temperature calculation compensation parameter Dx = 0.023. When the high temperature calculation compensation parameter Ey=0.3, the overall pipeline temperature evaluation value S1=43.321 is calculated. Since it is not within the standard evaluation range of the overall pipeline temperature, the overall pipeline temperature is determined to be abnormal.

[0086] Specifically, in this embodiment, a standard maximum pressure value is set for the i-th detection point Ai. and standard minimum pressure value ', Obtain the actual pressure value at the i-th detection point Ai. i = 1, 2, ..., n,

[0087] Perform single-point pressure comparison at the i-th detection point Ai.

[0088] like If the pressure at the detection point Ai is normal, it is determined that there is no leak in the pipeline at that location.

[0089] like If the pressure at detection point Ai is too low, it indicates a leak in the pipeline at that location.

[0090] like If the pressure at detection point Ai is too high, it is determined that there is a leak in the pipeline at that location.

[0091] Specifically, in this embodiment, the actual pressure values ​​of all detection points are integrated to determine whether the overall pipeline pressure is abnormal, the number of detection points with excessively low pressure is obtained, and a first pressure score is calculated; the number of detection points with excessively high pressure is obtained, and a second pressure score is calculated, including...

[0092] 1) Renumber the number of detection points with excessively low pressure, designating them as the first low-pressure point A11, the second low-pressure point A12, ..., the p-th low-temperature point A1p.

[0093] 2) Renumber the number of detection points with excessively high pressure, and designate them as the first high-pressure point A21, the second high-pressure point A22, ..., the qth high-pressure point A2q.

[0094] Determine whether the overall pipeline pressure is abnormal, calculate the overall pipeline pressure evaluation value S2, and set...

[0095]

[0096] in, Let y be the actual pressure value at the y-th high-pressure point. F1x is the actual pressure value at the y-th high-pressure point, and Gx is the low-pressure calculation compensation parameter for the actual pressure value at the x-th low-pressure point, relative to the overall pipeline pressure evaluation value S2. The high-pressure calculation compensation parameter is... Depending on the location of different inspection points on the pipeline, the high-pressure calculation parameters vary. The value of the low-pressure calculation compensation parameter Gx varies depending on the location of the different detection points on the pipeline.

[0097] If S21≤S2≤S20, then the overall pressure of the pipeline is considered normal.

[0098] If S2 < S21 or S2 > S20, the overall pressure of the pipeline is determined to be abnormal.

[0099] Among them, S20 is the highest standard evaluation value for the overall pipeline pressure.

[0100] S21 is the minimum standard evaluation value for the overall pipeline pressure.

[0101] Specifically, in this embodiment, the low-pressure calculation compensation parameter Gx is negatively correlated with the actual pressure value F1x at the x-th low-pressure point.

[0102] Gx = 1 / (α2 + F1x)

[0103] Wherein, α2 is the second negative feedback compensation parameter of the low-voltage calculation compensation parameter Gx.

[0104] The high-pressure calculation compensation parameter Hy is positively correlated with the actual pressure value F2y at the y-th high-pressure point.

[0105]

[0106] Where w is the actual pressure value F2y at the y-th high-pressure point, adjusted by the high-pressure calculation compensation parameter Hy.

[0107] The standard maximum pressure value described in this embodiment Standard minimum pressure value At this time, the second negative feedback compensation parameter α2 = 1.38, the high-pressure calculation adjustment parameter w = 0.29, the highest standard evaluation value of the overall pipeline pressure S20 = 0.009, the lowest standard evaluation value of the overall pipeline pressure S21 = 0.0001, and when the pressure at all detection points is the standard pressure value, the overall pipeline pressure evaluation value S2 = 0.001, which meets the standard evaluation range of the overall pipeline pressure. When the actual pressure value F1x at all low-pressure points is 0.01 MPa, the low-pressure calculation compensation parameter Gx = 0.72. When the actual pressure value F2y at all high-pressure points is 0.40 MPa, the high-pressure calculation compensation parameter Hy = 0.12. The calculated overall pipeline pressure evaluation value S2 = 0.041 is not within the standard evaluation range of the overall pipeline pressure, and the overall pipeline pressure is determined to be abnormal.

[0108] Specifically, in this embodiment, a standard maximum vibration value is set for the i-th detection point Ai. and standard minimum vibration value ', obtain the actual vibration value of the i-th detection point Ai. i = 1, 2, ..., n,

[0109] Single-point vibration comparison is performed at the i-th detection point Ai.

[0110] like If the vibration at the detection point Ai is normal, it is determined that there is no leak in the pipeline at that location.

[0111] like If the vibration at the detection point Ai is too low, it is determined that there is a leak in the pipeline at that location.

[0112] like If the vibration at the detection point Ai is too high, it is determined that there is a leak in the pipeline at that location.

[0113] Specifically, in this embodiment, the actual vibration values ​​of all detection points are integrated to determine whether the overall pipeline is vibrating abnormally. The number of detection points with excessively low vibration is obtained, and a first vibration score is calculated. The number of detection points with excessively high vibration is obtained, and a second vibration score is calculated, including...

[0114] 1) Renumber the number of detection points with excessively low vibration, designating them as the first low-frequency point A11, the second low-frequency point A12, ..., the r-th low-frequency point A1r.

[0115] 2) Renumber the detection points with excessive vibration, designating them as the first high-frequency point A21, the second high-frequency point A22, ..., the z-th high-frequency point A2z.

[0116] To determine whether the entire pipeline is vibrating abnormally, calculate the overall pipeline vibration evaluation value S3, and set...

[0117]

[0118] in, The actual vibration value at the y-th high-frequency point. V1x is the actual vibration value at the y-th high-frequency point, and Ox is the low-frequency compensation parameter for the overall pipeline vibration evaluation value S3 based on the actual vibration value at the x-th low-frequency point. The high-frequency compensation parameter is... Depending on the location of different inspection points on the pipeline, high-frequency calculation parameters are used. The value of the low-frequency calculation compensation parameter Ox varies depending on the location of the different detection points on the pipeline.

[0119] If S31≤S3≤S30, then the overall vibration of the pipeline is considered normal.

[0120] If S3 < S30 or S3 > S31, then the overall vibration of the pipeline is determined to be abnormal.

[0121] Among them, S30 is the highest standard evaluation value for overall pipeline vibration.

[0122] S31 is the minimum standard evaluation value for overall pipeline vibration.

[0123] Specifically, in this embodiment, the low-frequency calculation compensation parameter Ox is negatively correlated with the actual vibration value V1x at the x-th low-frequency point.

[0124] Ox = 1 / (α3 + V1x)

[0125] Wherein, α3 is the third negative feedback compensation parameter of the low-frequency calculation compensation parameter Ox.

[0126] The high-frequency calculation compensation parameter Jy is positively correlated with the actual vibration value V2y at the y-th high-frequency point.

[0127]

[0128] Where u is the high-frequency calculation adjustment parameter of the actual vibration value V2y at the y-th high-frequency point, relative to the high-frequency calculation compensation parameter Jy.

[0129] The standard maximum vibration value described in this embodiment The standard minimum vibration value At this time, the third negative feedback compensation parameter α3 = 0.93, the high-frequency calculation adjustment parameter u = 0.056, the highest standard evaluation value of the overall pipeline vibration S30 = 0.5, the lowest standard evaluation value of the overall pipeline vibration S31 = -0.5, when the vibration of all detection points is the standard vibration value, the overall pipeline vibration evaluation value S3 = -0.14, which meets the standard evaluation range of the overall pipeline vibration. When the actual vibration value of all low-frequency points V1x = 0.1 mm / s, the low-frequency calculation compensation parameter Ox = 0.97. When the actual vibration value of all high-frequency points V2y = 6 mm / s, the high-frequency calculation compensation parameter Jy = 0.336. The calculated overall pipeline vibration evaluation value S3 = 1.919 is not within the standard evaluation range of the overall pipeline vibration, and the overall pipeline vibration is judged to be abnormal.

[0130] Specifically, in this embodiment, the overall pipeline leakage evaluation value S0 is calculated based on the overall pipeline temperature evaluation value S1, the overall pipeline pressure evaluation value S2, and the overall pipeline vibration evaluation value S3.

[0131]

[0132] Wherein, λ1 is the first calculation compensation parameter for the overall leakage evaluation value S0 of the pipeline, which is the first difference between the arithmetic mean of the highest standard evaluation value S10 of the overall pipeline temperature and the lowest standard evaluation value S11 of the overall pipeline temperature and the first difference between the overall pipeline temperature evaluation value S1. The value of the first calculation compensation parameter λ1 is determined by the first difference. The larger the first difference, the larger the value of the first calculation compensation parameter λ1.

[0133] λ2 is the second calculation compensation parameter for the overall pipeline leakage evaluation value S0, which is the second difference between the arithmetic mean of the highest standard evaluation value S20 and the lowest standard evaluation value S21 of the overall pipeline pressure and the overall pipeline pressure evaluation value S2. The value of the second calculation compensation parameter λ2 is determined by the second difference. The larger the second difference, the larger the value of the second calculation compensation parameter λ2.

[0134] λ3 is the third calculation compensation parameter for the overall pipeline leakage evaluation value S0, which is the third difference between the arithmetic mean of the highest standard evaluation value S30 and the lowest standard evaluation value S31 of the overall pipeline vibration and the overall pipeline vibration evaluation value S3. The value of the third calculation compensation parameter λ3 is determined by the third difference. The larger the third difference, the larger the value of the third calculation compensation parameter λ3.

[0135] If S0 > S00, then the entire pipeline is determined to be leaking.

[0136] If S0≤S00, then it is determined that the pipeline as a whole has not leaked.

[0137] S00 is the overall pipeline leakage standard evaluation value.

[0138] Specifically, in this embodiment

[0139] If λ1≥λ1', then the first difference is determined to meet the single criterion for overall pipeline leakage.

[0140] If λ2≥λ2', then the second difference is determined to meet the single criterion for overall pipeline leakage.

[0141] If λ3 ≥ λ3', then the third difference is determined to meet the single criterion for overall pipeline leakage.

[0142] Wherein, λ1' is the first calculated compensation evaluation value.

[0143] λ2' is the second calculated compensation evaluation value.

[0144] λ3' is the third calculated compensation evaluation value.

[0145] Specifically, in this embodiment, the alarm level for overall pipeline leakage is classified based on the number of items whose differences meet a single judgment condition.

[0146] If the first difference, the second difference, and the third difference all meet a single judgment condition, a level three alarm signal will be issued to stop the pipeline operation in a timely manner.

[0147] If two or more of the first difference, second difference, and third difference meet a single judgment condition, a first-level alarm signal is issued, and the data detection module controls the pipeline to be detected again to determine whether a false alarm has occurred.

[0148] This invention discloses a pipeline leakage monitoring system based on digital twins, comprising a data detection module, a data processing module, a modeling module, and a simulation module. The data detection module is used to detect real-time temperature parameters, real-time pressure parameters, and real-time vibration parameters at various locations along the pipeline. The data processing module is used to collect, analyze, and process the real-time parameters detected by the data detection module to determine the leakage status of the pipeline. It compares the actual temperature, pressure, and vibration values ​​detected by the temperature, pressure, and vibration sensors with preset standard temperature, pressure, and vibration values ​​to determine whether a leak has occurred at any location along the pipeline. It calculates the overall pipeline temperature evaluation value based on the actual temperature values ​​detected by the temperature sensors and the overall pipeline pressure evaluation value based on the actual pressure values ​​detected by the pressure sensors. The system calculates the overall pipeline vibration evaluation value based on the actual vibration values ​​detected by each vibration sensor and compares them with preset standard evaluation values ​​for overall pipeline temperature, pressure, and vibration to determine whether the overall pipeline temperature, pressure, and vibration are abnormal. It then calculates the overall pipeline leakage evaluation value based on the overall pipeline temperature, pressure, and vibration evaluation values ​​and compares it with the overall pipeline leakage standard evaluation value to determine whether a leak has occurred. The modeling module constructs a digital twin-based pipeline model based on real-time parameters obtained from the data detection module and the analysis results of the real-time parameters from the data processing module. The simulation module simulates the digital twin-based pipeline model constructed by the modeling module to determine the accuracy of the digital twin-based pipeline model. It reduces the complexity of building digital twin models, shortens the development cycle, and enables rapid construction of digital twin models. By optimizing the constructed digital twin-based pipeline model through the simulation module, the optimal digital twin pipeline model for the corresponding target business is obtained, ensuring the accuracy of the constructed digital twin pipeline model, realizing comprehensive monitoring of pipeline leaks, and improving the accuracy and timeliness of pipeline leak monitoring.

[0149] The calculation compensation parameters and calculation adjustment parameters described in this invention serve two purposes: first, to balance the left and right dimensions of the formula; and second, to adjust the numerical results. In this embodiment, no specific values ​​are assigned. Furthermore, in this embodiment, each calculation formula is used to intuitively reflect the adjustment relationship between the values, such as positive correlation or negative correlation. Unless otherwise specified, the values ​​of parameters that are not specifically limited are all taken as positive.

[0150] The technical solution of the present invention has been described above with reference to the preferred embodiments shown in the accompanying drawings. However, it will be readily understood by those skilled in the art that the scope of protection of the present invention is obviously not limited to these specific embodiments. Without departing from the principles of the present invention, those skilled in the art can make equivalent changes or substitutions to the relevant technical features, and the technical solutions after these changes or substitutions will all fall within the scope of protection of the present invention.

[0151] The above description is merely a preferred embodiment of the present invention and is not intended to limit the invention. Various modifications and variations can be made to the present invention by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the scope of protection of the present invention.

Claims

1. A pipeline leak monitoring system based on digital twins, characterized in that, include, The data detection module includes several temperature sensors, several pressure sensors, and several vibration sensors, used to detect real-time temperature parameters, real-time pressure parameters, and real-time vibration parameters at various locations in the pipeline. The data processing module is used to collect, analyze, and process the real-time parameters detected by the data detection module to determine the leakage status of the pipeline. It compares the actual temperature, pressure, and vibration values ​​detected by the temperature, pressure, and vibration sensors with preset standard temperature, pressure, and vibration values ​​to determine whether leakage has occurred at various locations in the pipeline. It calculates the overall pipeline temperature evaluation value, overall pipeline pressure evaluation value, and overall pipeline vibration evaluation value based on the actual temperature values ​​detected by the temperature sensors, pressure values ​​detected by the pressure sensors, and vibration values ​​detected by the vibration sensors, and compares these values ​​with preset standard evaluation ranges for overall pipeline temperature, pressure, and vibration to determine whether the overall temperature, pressure, and vibration of the pipeline are abnormal. Finally, it calculates the overall pipeline leakage evaluation value based on the overall pipeline temperature evaluation value, overall pipeline pressure evaluation value, and overall pipeline vibration evaluation value, and compares this value with the overall pipeline leakage standard evaluation value to determine whether the entire pipeline is leaking. The modeling module constructs a pipeline model based on digital twins based on the real-time parameters obtained by the data detection module and the analysis results of the real-time parameters by the data processing module. The simulation module is used to simulate the pipeline model based on digital twins constructed by the modeling module to determine the accuracy of the pipeline model based on digital twins. The pipeline to be tested is evenly divided into several test points according to a fixed length. For each test point, a temperature sensor, a pressure sensor and a vibration sensor are set. Different standard temperature values, standard pressure values ​​and standard vibration values ​​are set for different test points. The actual temperature values, actual pressure values ​​and actual vibration values ​​of each test point are compared with the preset standard temperature values, standard pressure values ​​and standard vibration values ​​to determine whether the pipeline has leaked. The comparison process for determining whether a pipeline is leaking includes single-point comparison and overall comparison. Single-point comparison at each detection point determines the leakage situation at each location in the pipeline. This single-point comparison includes single-point temperature comparison, single-point pressure comparison, and single-point vibration comparison. Overall comparison, which combines the actual temperature, pressure, and vibration values ​​from each detection point, determines whether the entire pipeline is leaking. This overall comparison includes overall temperature comparison, overall pressure comparison, and overall vibration comparison. Different standard temperature ranges are set at different detection points. When comparing the temperature at any single detection point, the relationship between the actual temperature value detected by the temperature sensor and the corresponding standard temperature range is used to determine whether there is a leak in the pipeline at the detection point. If the actual temperature value exceeds the standard temperature range, it is determined that there is a leak in the pipeline at that location. Based on the single-point temperature comparison, the actual temperature values ​​of all detection points are integrated, including renumbering the number of detection points with excessively low temperatures and the number of detection points with excessively high temperatures. The overall pipeline temperature evaluation value is then calculated and compared with the standard evaluation range for the overall pipeline temperature to determine whether the overall pipeline temperature is abnormal. If the overall pipeline temperature evaluation value exceeds the standard evaluation range for the overall pipeline temperature, the overall pipeline temperature is abnormal, and the system issues a temperature abnormality command. The data processing module then performs a detailed analysis of the abnormalities in overall pressure and overall vibration to determine whether the overall pipeline is leaking. For any detection point, if its actual temperature value exceeds its corresponding standard temperature range, the detection point is classified into low-temperature points and high-temperature points. The low-temperature points have actual temperatures less than the lowest temperature value of the standard temperature range, and each low-temperature point is equipped with a low-temperature calculation compensation parameter for its impact on the overall pipeline temperature evaluation value. Similarly, the high-temperature points have actual temperatures greater than the highest temperature value of the standard temperature range, and each high-temperature point is equipped with a high-temperature calculation compensation parameter for its impact on the overall pipeline temperature evaluation value. The low-temperature calculation compensation parameter is negatively correlated with the actual temperature value of the low-temperature point, and the high-temperature calculation compensation parameter is positively correlated with the actual temperature value of the high-temperature point.

2. The pipeline leak monitoring system based on digital twins according to claim 1, characterized in that, Different standard pressure ranges are set at different detection points. When comparing the single-point pressure at any detection point, the relationship between the actual pressure value detected by the pressure sensor and the corresponding standard pressure range is used to determine whether a leak has occurred in the pipeline at the detection point. If the actual pressure value exceeds the standard pressure range, it is determined that a leak has occurred in the pipeline at that location. Different standard vibration ranges are set at different detection points. When a single-point vibration comparison is performed at any detection point, the relationship between the actual vibration value detected by the vibration sensor and the corresponding standard vibration range is used to determine whether a leak has occurred in the pipeline at that detection point. If the actual vibration value exceeds the standard vibration range, it is determined that a leak has occurred in the pipeline at that location.

3. The pipeline leak monitoring system based on digital twin according to claim 2, characterized in that, Based on the single-point pressure comparison, the actual pressure values ​​of all detection points are integrated, including renumbering the number of detection points with excessively low pressure and the number of detection points with excessively high pressure. The overall pipeline pressure evaluation value is then calculated and compared with the overall pipeline pressure standard evaluation range to determine whether the overall pipeline pressure is abnormal. If the overall pipeline pressure evaluation value exceeds the overall pipeline pressure standard evaluation range, the overall pipeline pressure is abnormal, and the system issues a pressure abnormality command. The data processing module performs a detailed analysis of the abnormalities in overall temperature and overall vibration to determine whether the overall pipeline is leaking. Based on the single-point vibration comparison, the actual vibration values ​​of all detection points are integrated, including renumbering the number of detection points with excessively low vibration and the number of detection points with excessively high vibration. The overall pipeline vibration evaluation value is then calculated and compared with the overall pipeline vibration standard evaluation range to determine whether the overall pipeline vibration is abnormal. If the overall pipeline vibration evaluation value exceeds the overall pipeline vibration standard evaluation range, the overall pipeline vibration is abnormal, and the system issues a vibration abnormality command. The data processing module then performs a detailed analysis of the abnormalities in overall temperature and overall pressure to determine whether the overall pipeline is leaking.

4. The pipeline leak monitoring system based on digital twin according to claim 3, characterized in that, For any detection point, if its actual pressure value exceeds its corresponding standard pressure range, the detection point is classified into low-pressure points and high-pressure points. The low-pressure points have actual pressure values ​​less than the minimum pressure value of the standard pressure range, and each low-pressure point is equipped with a low-pressure calculation compensation parameter for its impact on the overall pipeline pressure evaluation value. The high-pressure points have actual pressure values ​​greater than the maximum pressure value of the standard pressure range, and each high-pressure point is equipped with a high-pressure calculation compensation parameter for its impact on the overall pipeline pressure evaluation value. Wherein, the low-pressure calculation compensation parameter is negatively correlated with the actual pressure value of the low-pressure point, and the high-pressure calculation compensation parameter is positively correlated with the actual pressure value of the high-pressure point; For any detection point, if its actual vibration value exceeds its corresponding standard vibration range, the detection point is classified into low-frequency points and high-frequency points. The low-frequency points have actual vibration values ​​less than the lowest vibration value of the standard vibration range, and each low-frequency point is equipped with a low-frequency calculation compensation parameter for its impact on the overall pipeline vibration evaluation value. The high-frequency points have actual vibration values ​​greater than the highest vibration value of the standard vibration range, and each high-frequency point is equipped with a high-frequency calculation compensation parameter for its impact on the overall pipeline vibration evaluation value. The low-frequency calculation compensation parameter is negatively correlated with the actual vibration value of the low-frequency point, and the high-frequency calculation compensation parameter is positively correlated with the actual vibration value of the high-frequency point.

5. The pipeline leak monitoring system based on digital twin according to claim 4, characterized in that, The overall pipeline leakage evaluation value is calculated based on the overall pipeline temperature evaluation value, the overall pipeline pressure evaluation value, and the overall pipeline vibration evaluation value. If the overall pipeline leakage evaluation value is greater than the overall pipeline leakage standard evaluation value, then the overall pipeline is determined to have leaked. The overall pipeline leakage standard evaluation value is set in the system. When calculating the overall leakage evaluation value of the pipeline, a first calculation compensation parameter is set for the overall leakage evaluation value based on the first difference between the arithmetic mean of the highest and lowest standard evaluation values ​​of the overall pipeline temperature and the overall pipeline temperature evaluation value; a second calculation compensation parameter is set for the overall leakage evaluation value based on the second difference between the arithmetic mean of the highest and lowest standard evaluation values ​​of the overall pipeline pressure and the overall pipeline pressure evaluation value; and a third calculation compensation parameter is set for the overall leakage evaluation value based on the third difference between the arithmetic mean of the highest and lowest standard evaluation values ​​of the overall pipeline vibration and the overall pipeline vibration evaluation value.

6. The pipeline leak monitoring system based on digital twin according to claim 5, characterized in that, When the data processing module determines whether the pipeline as a whole has leaked... If the first calculated compensation parameter is greater than or equal to the first calculated compensation evaluation value, the data processing module determines that the first difference meets the single judgment condition for the pipeline to leak as a whole. If the second calculated compensation parameter is greater than or equal to the second calculated compensation evaluation value, the data processing module determines that the second difference meets the single judgment condition for the overall pipeline leakage. If the third calculated compensation parameter is greater than or equal to the third calculated compensation evaluation value, the data processing module determines that the third difference meets the single judgment condition for the overall pipeline leakage. The data processing module contains a first calculated compensation evaluation value and a second calculated compensation evaluation value. The data processing module contains the third calculated compensation evaluation value.

7. The pipeline leak monitoring system based on digital twin according to claim 6, characterized in that, The alarm levels for overall pipeline leakage are classified based on the number of items that meet a single judgment criterion for each difference. If the first difference, the second difference, and the third difference all meet a single judgment condition, a level three alarm signal will be issued to stop the pipeline operation in a timely manner. If two or more of the first difference, second difference, and third difference meet a single judgment condition, a first-level alarm signal is issued, and the data detection module controls the pipeline to be detected again to determine whether a false alarm has occurred.

8. A monitoring method for a pipeline leakage monitoring system based on digital twins according to any one of claims 1-7, characterized in that, include, Step S1: Detect the physical entity data and operational data of the pipeline through the data detection module to determine the physical properties and operational status of the pipeline; Step S2: The data processing module collects the detected operating data, analyzes and processes the operating data, and determines whether the pipeline has leaked. Step S3: Construct a pipeline model based on digital twin using the physical entity data from step S1 and the pipeline leakage information obtained from the analysis and processing in step S2. Step S4: Simulate the pipeline model based on digital twin constructed in step S3 to verify the accuracy of the model, and optimize it based on the simulation results.

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