Pressure Detection and Early Warning System and Method Based on Pipeline Network Data Acquisition

Abstract

The present invention relates to the field of data processing technology, and discloses a pressure detection early warning system and method based on pipeline network data collection. The system consists of four modules: a data collection module, a defect recognition module, a defect quantification module, and an early warning decision module; wherein the data collection module monitors pipeline data and status in real time; the defect recognition module determines whether the pipeline has an abnormality and identifies the type of abnormality; the defect quantification module analyzes the abnormality and evaluates the severity; and the early warning decision module issues an early warning signal according to the severity. The present invention can quickly and accurately identify and quantify abnormal conditions of the pipeline by real-time monitoring and analyzing the physical state of the pipeline, providing a scientific basis for maintenance and repair work, thereby improving the safety and reliability of the pipeline system.

Description

Technical Field

[0001] The present invention relates to the technical field of data processing, and in particular to a pressure detection and early warning system and method based on pipe network collected data. Background Art

[0002] In modern urban infrastructure, the pipe network system is a key component to ensure the normal operation of the city. The pipe network system includes various types such as water supply, drainage, and gas. Its safe and stable operation is directly related to the quality of life of urban residents and the efficiency of urban operation.

[0003] Traditional pipe network pressure detection mainly relies on manual inspections and fixed-point monitoring. This method is not only inefficient, but also difficult to achieve comprehensive coverage and prone to missing hidden dangers. With the development of Internet of Things technology, by deploying a large number of sensors in the pipe network system, real-time data such as pressure, flow, and temperature of the pipe network can be collected, which makes it possible for intelligent management of the pipe network. However, existing data processing methods often lack effective early warning mechanisms and cannot detect and deal with potential risks in a timely manner. Summary of the invention

[0004] In view of this, the present invention proposes a pressure detection early warning system and method based on pipeline network collection data, aiming to improve the safety and stability of the pipeline network system and realize timely early warning and processing of potential risks.

[0005] The present invention proposes a pressure detection and early warning system based on pipe network data collection, including a data collection module, a defect identification module, a defect quantification module and an early warning decision module;

[0006] Wherein, the data acquisition module is configured to monitor real-time data and physical conditions inside and outside the pipeline;

[0007] The defect recognition module is configured to determine whether the pipeline has an abnormality according to the real-time data; the defect recognition module is further configured to determine the type of the abnormality according to the real-time data and the physical state when it is determined that the pipeline has an abnormality;

[0008] The defect quantification module is configured to, when the defect identification module determines that the pipeline has an abnormality, perform quantitative analysis on the abnormality, and determine the severity of the abnormality of the pipeline according to the quantitative analysis result and the type of the abnormality;

[0009] The early warning decision module is configured to generate an early warning signal based on the severity of the abnormal situation of the pipeline.

[0010] Preferably, the real-time data includes the pressure, temperature and flow rate of the pipeline; the physical state includes the vibration frequency of the pipeline and the integrity of the weld at the joint.

[0011] Preferably, the defect identification module is configured to determine whether the pipeline has an abnormality according to the real-time data, including:

[0012] The pressure change rate per unit time is calculated based on the pressure, temperature and flow rate of the pipeline. The pressure change rate per unit time is calculated using the following formula:

[0013] ;

[0014] in, represents the pressure change rate per unit time; f represents the friction coefficient; L represents the pipe length; D represents the pipe diameter; ρ represents the fluid density; v represents the fluid flow rate; It represents the instantaneous rate of change of flow velocity to dynamic pressure; K represents the bending loss coefficient; represents the partial derivative of pressure with respect to temperature; Indicates the rate of temperature change per unit time.

[0015] Preferably, the calculation formula of the bending loss coefficient is:

[0016] ;

[0017] Wherein, Kelbow represents the loss coefficient of a 90° standard elbow; θ represents the elbow angle of the pipeline.

[0018] Preferably, the loss coefficient of the 90° standard elbow is calculated as follows:

[0019] ;

[0020] Where r represents the radius of curvature of the curved pipe; D represents the pipe diameter; and Re represents the Reynolds number.

[0021] Preferably, the defect recognition module is configured to determine whether the pipeline has an abnormality according to the real-time data; the defect recognition module is further configured to, when the result of the determination shows that the pipeline has an abnormality, determine the type of the abnormality according to the real-time data and the physical state, including:

[0022] Pre-set pressure change rate threshold, vibration frequency safety value and weld integrity threshold;

[0023] When the pressure change rate is less than or equal to the pressure change rate threshold, it is determined that there is no abnormality in the pipeline;

[0024] When the pressure change rate is greater than the pressure change rate threshold, it is determined that an abnormality exists in the pipeline;

[0025] When it is determined that the pipeline has an abnormality, a comparative analysis of the vibration frequency and the welding integrity is performed, and the type of the abnormality is determined based on the comparative analysis result.

[0026] Preferably, when it is determined that the pipeline has an abnormality, a comparative analysis of the vibration frequency and the welding integrity is performed, and the type of the abnormality is determined based on the comparative analysis result, including:

[0027] When the vibration frequency is less than or equal to the vibration frequency safety value and the welding integrity is greater than or equal to the welding integrity threshold, it is determined that the type of the abnormal situation is interference by environmental factors;

[0028] When the vibration frequency is greater than the vibration frequency safety value and the welding integrity is greater than or equal to the welding integrity threshold, the type of the abnormal situation is determined to be a structural abnormality caused by vibration;

[0029] When the vibration frequency is less than or equal to the vibration frequency safety value and the welding integrity is less than the welding integrity threshold, the type of the abnormal situation is determined to be weld damage;

[0030] When the vibration frequency is greater than the vibration frequency safety value and the welding integrity is less than the welding integrity threshold, the type of the abnormal situation is determined to be a comprehensive abnormality.

[0031] Preferably, the defect quantification module is configured to, when the defect identification module determines that the pipeline has an abnormality, perform quantitative analysis on the abnormality, and determine the severity of the abnormality of the pipeline according to the quantitative analysis result and the type of the abnormality, including:

[0032] When the type of the abnormal situation is the presence of environmental factors interference, the defect quantification module determines the degree of influence of environmental factors on pipeline operation by analyzing the correlation between environmental noise data and pipeline pressure data;

[0033] When the type of the abnormal condition is a structural abnormality caused by vibration, the defect quantification module evaluates the potential risk of structural damage by calculating the deviation between the vibration frequency and the standard vibration frequency, combining the pipeline material properties and historical vibration data;

[0034] When the type of the abnormal situation is weld damage, the defect quantification module detects the area and depth of the weld using ultrasonic detection technology or radiographic detection technology to quantify the degree of damage;

[0035] When the type of the abnormal situation is a comprehensive abnormality, the defect quantification module comprehensively utilizes the pressure change rate, the vibration frequency and the weld integrity to perform quantitative analysis on the comprehensive abnormal situation of the pipeline.

[0036] Preferably, the defect quantification module is configured to, when the defect identification module determines that the pipeline has an abnormality, perform quantitative analysis on the abnormality, and judge the severity of the abnormality of the pipeline according to the quantitative analysis result and the type of the abnormality, further comprising:

[0037] The influence of environmental factors on pipeline operation is obtained through the following calculation formula:

[0038] ;

[0039] ;

[0040] Where E represents the environmental impact coefficient; Corr p,e Represents the correlation coefficient between pressure data and environmental noise data; MaxCorr p,e Indicates the historical maximum correlation coefficient, used for standardization; Var noise Represents the variance of environmental noise; Var pressure Indicates the variance of pipeline pressure; Impact env Environmental factors impact index;

[0041] The vibration risk assessment index is obtained by the following calculation formula:

[0042] ;

[0043] ;

[0044] Among them, V d Indicates the vibration deviation coefficient; f act Indicates the actual vibration frequency; f std Indicates the standard vibration frequency; S f Represents the structural fatigue coefficient; H v Represents the standard deviation of historical vibration data; R mat Indicates the vibration resistance of the material; R v represents the vibration risk assessment index;

[0045] The weld damage assessment index is obtained by the following calculation formula:

[0046] ;

[0047] ;

[0048] ;

[0049] Among them, A d Indicates weld damage area coefficient; D dIndicates weld damage depth coefficient; A dam Indicates the weld damage area; A total Indicates the total area of ​​the weld; D dam Indicates the weld damage depth; D max Indicates the maximum allowable depth of the weld; I weld Represents the weld damage assessment index;

[0050] The comprehensive evaluation index is obtained through the following calculation formula;

[0051] ;

[0052] ;

[0053] ;

[0054] ;

[0055] ;

[0056] Among them, ΔP norm Indicates the normalized rate of pressure change; ΔP min and ΔP max Respectively represent the minimum and maximum value of the pressure change rate; f v,norm Indicates the vibration frequency standard; f v,min and f v,max Respectively represent the minimum and maximum values ​​of the vibration frequency; W v,norm Indicates the standardization of weld integrity; W min and W max Respectively represent the minimum and maximum values ​​of weld integrity; w ΔP 、w fv 、w W Respectively represent the weights of pressure change rate, vibration frequency and weld integrity; I comp Represents a comprehensive evaluation index.

[0057] The present invention also proposes a pressure detection and early warning method based on pipeline network collected data, and the pressure detection and early warning method based on pipeline network collected data is implemented by the above-mentioned pressure detection and early warning system based on pipeline network collected data.

[0058] Compared with the prior art, the present invention has the following beneficial effects:

[0059] 1. Improved the accuracy of identifying pipeline abnormalities and the speed of response. By real-time monitoring of the physical state of the pipeline, such as the pressure change rate, vibration frequency, and weld integrity, combined with pre-set thresholds, it is possible to quickly determine whether there are abnormalities in the pipeline and accurately identify the type of abnormality. This helps to take timely measures to prevent potential accidents.

[0060] 2. Achieved quantitative analysis of pipeline abnormalities. Through the defect quantification module, in-depth analysis of abnormalities can be performed to quantitatively evaluate the impact of environmental factors, vibration risks, weld damage levels, and comprehensive abnormalities. This helps to more accurately evaluate the health of the pipeline and provide a scientific basis for maintenance and repair work.

[0061] 3. Optimized maintenance and repair decisions. By quantifying the analysis results, the severity of abnormal conditions in the pipeline can be judged, so that a more reasonable maintenance and repair plan can be formulated. This helps to improve maintenance efficiency, reduce maintenance costs, and ensure the safe operation of the pipeline.

[0062] 4. A pressure detection and early warning method based on pipeline network data collection is provided. This method can detect potential abnormal conditions in a timely manner by real-time monitoring and analysis of the physical state of the pipeline, and send out alerts to relevant personnel through the early warning system. This helps to take measures in advance to avoid or mitigate the impact of accidents.

[0063] 5. Applicable to various types of pipeline systems. The present invention is not only applicable to energy transmission pipelines such as oil and natural gas, but also to municipal pipeline systems such as urban water supply and drainage. This makes the present invention have broad application prospects and practical value.

[0064] In summary, the present invention can quickly and accurately identify and quantify abnormal conditions of pipelines by real-time monitoring and analysis of the physical state of pipelines, providing a scientific basis for maintenance and repair work, thereby improving the safety and reliability of pipeline systems. BRIEF DESCRIPTION OF THE DRAWINGS

[0065] Various other advantages and benefits will become apparent to those of ordinary skill in the art by reading the detailed description of the preferred embodiments below. The accompanying drawings are only for the purpose of illustrating the preferred embodiments and are not to be considered as limiting the present invention. Moreover, the same reference symbols are used throughout the accompanying drawings to represent the same components. In the accompanying drawings:

[0066] Figure 1 This is a functional block diagram of the pressure detection and early warning system based on pipeline network collection data of the present invention. DETAILED DESCRIPTION

[0067] Exemplary embodiments of the present disclosure will be described in more detail below with reference to the accompanying drawings. Although exemplary embodiments of the present disclosure are shown in the accompanying drawings, it should be understood that the present disclosure can be implemented in various forms and should not be limited by the embodiments described herein. On the contrary, these embodiments are provided in order to enable a more thorough understanding of the present disclosure and to fully convey the scope of the present disclosure to those skilled in the art. It should be noted that, in the absence of conflict, the embodiments of the present invention and the features described in the embodiments can be combined with each other. The present invention will be described in detail below with reference to the accompanying drawings and in combination with the embodiments.

[0068] like Figure 1 As shown, this embodiment provides a pressure detection and early warning system based on pipe network collection data, including a data collection module, a defect identification module, a defect quantification module and an early warning decision module;

[0069] Wherein, the data acquisition module is configured to monitor real-time data and physical conditions inside and outside the pipeline;

[0070] The defect recognition module is configured to determine whether the pipeline has an abnormality according to the real-time data; the defect recognition module is further configured to determine the type of the abnormality according to the real-time data and the physical state when the result of the determination shows that the pipeline has an abnormality;

[0071] The defect quantification module is configured to, when the defect identification module determines that the pipeline has an abnormality, perform quantitative analysis on the abnormality, and determine the severity of the abnormality of the pipeline according to the quantitative analysis result and the type of the abnormality;

[0072] The early warning decision module is configured to generate an early warning signal based on the severity of the abnormal situation of the pipeline.

[0073] It is understandable that this embodiment proposes an innovative pressure detection and early warning system, which works based on the data collected by the pipeline network. The system mainly includes four core modules: data acquisition module, defect identification module, defect quantification module and early warning decision module. These modules work together to ensure the efficient operation and accurate early warning of the system.

[0074] Specifically, the data acquisition module is carefully designed to monitor the real-time data and physical status of the pipeline inside and outside in real time. The purpose of this module is to ensure that any subtle changes that may affect the safe operation of the pipeline can be captured in time. By continuously collecting data, this module provides reliable basic information for subsequent modules.

[0075] The defect identification module uses the real-time data provided by the data acquisition module to determine whether there are any abnormalities in the pipeline. When an abnormality is detected, the module further analyzes the real-time data and physical status to determine the specific type of abnormality. This process involves complex algorithms and logical judgments to ensure that various potential defects can be accurately identified.

[0076] Once the defect identification module determines that there is an abnormality in the pipeline, the defect quantification module comes into play. This module conducts in-depth quantitative analysis of the abnormality and evaluates its impact on pipeline safety. By combining the quantitative analysis results with the type of abnormality, the defect quantification module can accurately determine the severity of the pipeline abnormality and provide a scientific basis for subsequent early warning decisions.

[0077] Finally, the early warning decision module generates an early warning signal based on the severity of the abnormal condition of the pipeline. This module takes into account various factors, including the type of defect, its severity, and the possible impact on pipeline safety. Based on this information, the early warning decision module can generate corresponding early warning signals to remind relevant personnel to take necessary measures to prevent potential safety accidents.

[0078] In summary, the pressure detection and early warning system in this embodiment realizes real-time monitoring of pipeline pressure status, accurate identification of abnormal conditions, quantitative analysis and scientific early warning through the close cooperation of four core modules, thereby greatly improving the safety and reliability of pipeline operation.

[0079] In some embodiments of the present application, the real-time data includes pressure, temperature and flow of the pipeline; the physical state includes the vibration frequency of the pipeline and the integrity of the weld at the joint.

[0080] It is understandable that the real-time data collection of this embodiment includes real-time monitoring and recording of the pressure, temperature and flow rate inside the pipeline. These data can reflect the current working status and operating environment of the pipeline, thereby providing an important reference for the safe operation of the pipeline. Specifically, the pressure data of the pipeline can reveal whether there are abnormal pressure fluctuations inside the pipeline, which may indicate potential leakage or blockage problems; the temperature data helps to evaluate the thermal state of the medium inside the pipeline, so as to determine whether there is overheating or insufficient cooling; the flow data can reflect whether the rate of the pipeline transporting the medium is normal and whether there are abnormal flow fluctuations.

[0081] In addition, in this embodiment, the monitoring of the physical state includes real-time detection of the vibration frequency of the pipeline and evaluation of the integrity of the weld at the pipeline joint. The vibration frequency data of the pipeline can help us understand whether there is abnormal vibration in the pipeline during operation, which may be caused by unstable flow of the internal medium or external environmental factors. By analyzing the vibration frequency, potential mechanical failures or structural problems can be discovered in time. The integrity evaluation of the weld at the pipeline joint can ensure the sealing and structural stability of the pipeline connection and prevent leakage or breakage accidents caused by weld defects. By regularly inspecting and evaluating the integrity of the weld, potential welding defects can be discovered and repaired in time, thereby ensuring the overall safety and reliability of the pipeline system.

[0082] In some embodiments of the present application, when the defect identification module is configured to determine whether the pipeline has an abnormal condition according to the real-time data, it includes:

[0083] The pressure change rate per unit time is calculated based on the pressure, temperature and flow rate of the pipeline. The pressure change rate per unit time is calculated using the following formula:

[0084] ;

[0085] in, represents the pressure change rate per unit time; f represents the friction coefficient; L represents the pipe length; D represents the pipe diameter; ρ represents the fluid density; v represents the fluid flow rate; It represents the instantaneous rate of change of flow velocity to dynamic pressure; K represents the bending loss coefficient; represents the partial derivative of pressure with respect to temperature; Indicates the rate of temperature change per unit time.

[0086] It is understood that the defect identification module of this embodiment is designed and configured to determine whether there is an abnormality in the pipeline based on real-time data. Specifically, the module will perform a series of calculation and analysis steps to ensure that the operating status of the pipeline meets the predetermined safety standards. In these steps, the module will first focus on the three key parameters of the pipeline: pressure, temperature and flow.

[0087] In order to assess whether there are potential problems in the pipeline, the module calculates the pressure change rate per unit time. This calculation process is achieved through a specific calculation formula, in which the pressure change rate represents the pressure change rate per unit time; f represents the friction coefficient, which reflects the degree of friction between the fluid and the pipe wall when it flows in the pipe; L represents the length of the pipe, which has a direct impact on the pressure change rate; D represents the diameter of the pipe, which determines the cross-sectional area of ​​the fluid flow; ρ represents the density of the fluid, which affects the inertia of the fluid; v represents the flow rate of the fluid, which is directly related to the change in dynamic pressure; dv / dt represents the instantaneous rate of change of the flow rate to the dynamic pressure, which reflects the immediate impact of the change in flow rate on the pressure change; K represents the bending loss coefficient, which takes into account the impact of the curved part of the pipe on the pressure loss; dP / dT represents the partial derivative of pressure with respect to temperature, which describes the sensitivity of pressure to temperature changes; ΔT represents the temperature change rate per unit time, which reflects the impact of temperature changes on pressure changes.

[0088] Through this calculation formula, the defect identification module can comprehensively consider the impact of multiple factors on pipeline pressure changes, so as to more accurately determine whether there is an abnormality in the pipeline. This comprehensive analysis method not only improves the accuracy of detection, but also can detect potential problems in a timely manner, thereby avoiding possible accidents and losses.

[0089] In some embodiments of the present application, the calculation formula of the bending loss coefficient is:

[0090] ;

[0091] Wherein, Kelbow represents the loss coefficient of a 90° standard elbow; θ represents the elbow angle of the pipeline.

[0092] It can be understood that the formula for calculating the bending loss coefficient in this embodiment can more accurately calculate the flow loss at a specific bend angle, thereby providing a more reliable basis for pipeline design and optimization.

[0093] In some embodiments of the present application, the loss coefficient of the 90° standard elbow is calculated as follows:

[0094] ;

[0095] Where r represents the radius of curvature of the curved pipe; D represents the pipe diameter; and Re represents the Reynolds number.

[0096] It can be understood that the formula of this embodiment can calculate the loss coefficient of the 90° standard elbow according to the curvature radius of the curved pipe, the pipe diameter and the Reynolds number of the fluid, so as to further evaluate the flow characteristics of the fluid in the pipeline system.

[0097] In some embodiments of the present application, the defect recognition module is configured to determine whether the pipeline has an abnormality according to the real-time data; the defect recognition module is further configured to, when the result of the determination is that the pipeline has an abnormality, determine the type of the abnormality according to the real-time data and the physical state, including:

[0098] Pre-set pressure change rate threshold, vibration frequency safety value and weld integrity threshold;

[0099] When the pressure change rate is less than or equal to the pressure change rate threshold, it is determined that there is no abnormality in the pipeline;

[0100] When the pressure change rate is greater than the pressure change rate threshold, it is determined that an abnormality exists in the pipeline;

[0101] When it is determined that the pipeline has an abnormality, a comparative analysis of the vibration frequency and the welding integrity is performed, and the type of the abnormality is determined based on the comparative analysis result.

[0102] It is understandable that the defect recognition module of this embodiment is designed and configured to determine whether an abnormality has occurred in the pipeline based on real-time data. In addition, the defect recognition module has a further function, that is, when the judgment result shows that an abnormality has occurred in the pipeline, the specific type of the abnormality can be further determined by combining the real-time data and the physical state of the pipeline. In order to achieve this function, the defect recognition module pre-sets several key threshold parameters, including the pressure change rate threshold, the vibration frequency safety value, and the weld integrity threshold.

[0103] Specifically, when the pressure change rate in the real-time data is less than or equal to the pre-set pressure change rate threshold, the defect recognition module will determine that there is no abnormality in the pipeline. On the contrary, if the pressure change rate is greater than the pressure change rate threshold, the defect recognition module will determine that there is an abnormality in the pipeline. Once it is determined that there is an abnormality in the pipeline, the defect recognition module will further compare and analyze the vibration frequency and welding integrity. By comparing and analyzing these data, the defect recognition module can more accurately determine the specific type of abnormality, thereby providing an important reference for subsequent maintenance and repair work.

[0104] In some embodiments of the present application, when it is determined that the pipeline has an abnormal condition, a comparison analysis of the vibration frequency and the welding integrity is performed, and the type of the abnormal condition is determined according to the comparison analysis result, including:

[0105] When the vibration frequency is less than or equal to the vibration frequency safety value and the welding integrity is greater than or equal to the welding integrity threshold, it is determined that the type of the abnormal situation is interference by environmental factors;

[0106] When the vibration frequency is greater than the vibration frequency safety value and the welding integrity is greater than or equal to the welding integrity threshold, the type of the abnormal situation is determined to be a structural abnormality caused by vibration;

[0107] When the vibration frequency is less than or equal to the vibration frequency safety value and the welding integrity is less than the welding integrity threshold, the type of the abnormal situation is determined to be weld damage;

[0108] When the vibration frequency is greater than the vibration frequency safety value and the welding integrity is less than the welding integrity threshold, the type of the abnormal situation is determined to be a comprehensive abnormality.

[0109] It is understandable that in this embodiment, when the system detects an abnormality in the pipeline, a series of analysis steps will be performed. First, the system will perform a detailed comparative analysis of the vibration frequency and welding integrity of the pipeline. Through this comparative analysis, the system can more accurately determine the specific type of abnormality. Specifically, the analysis results can be divided into the following situations:

[0110] First, if the detected vibration frequency is less than or equal to the preset vibration frequency safety value, and the weld integrity is greater than or equal to the set weld integrity threshold, the system will determine that the current abnormal situation is caused by environmental interference. In this case, it may be due to some changes in the external environment, such as temperature, humidity or other physical factors, that caused the pipeline to vibrate abnormally, but the welded part was not seriously damaged.

[0111] Secondly, if the detected vibration frequency is greater than the preset vibration frequency safety value, and the weld integrity is still greater than or equal to the set weld integrity threshold, the system will determine that the current abnormality is a structural abnormality caused by vibration. In this case, the vibration frequency of the pipeline exceeds the safety range, but the welded part remains intact, which may mean that some structural parts of the pipeline have problems due to excessive vibration.

[0112] In the third case, if the detected vibration frequency is less than or equal to the preset vibration frequency safety value, but the welding integrity is less than the set welding integrity threshold, the system will determine the current abnormal situation as weld damage. In this case, although the vibration frequency is within the safety range, the weld part is damaged, which may be caused by improper welding process or material aging.

[0113] The last case is that if the detected vibration frequency is greater than the preset vibration frequency safety value, and the weld integrity is also less than the set weld integrity threshold, the system will determine that the current abnormality is a comprehensive abnormality. In this case, the pipeline has vibrations beyond the safety range and the weld part is also damaged. This may be the result of multiple factors and requires further detailed inspection and analysis.

[0114] Through this detailed comparative analysis, the system can more accurately identify and classify pipeline anomalies, thereby providing strong support for subsequent maintenance and repair work.

[0115] In some embodiments of the present application, the defect quantification module is configured to, when the defect identification module determines that the pipeline has an abnormality, perform quantitative analysis on the abnormality, and determine the severity of the abnormality of the pipeline according to the quantitative analysis result and the type of the abnormality, including:

[0116] When the type of the abnormal situation is the presence of environmental factors interference, the defect quantification module determines the degree of influence of environmental factors on pipeline operation by analyzing the correlation between environmental noise data and pipeline pressure data;

[0117] When the type of the abnormal condition is a structural abnormality caused by vibration, the defect quantification module evaluates the potential risk of structural damage by calculating the deviation between the vibration frequency and the standard vibration frequency, combining the pipeline material properties and historical vibration data;

[0118] When the type of the abnormal situation is weld damage, the defect quantification module detects the area and depth of the weld using ultrasonic detection technology or radiographic detection technology to quantify the degree of damage;

[0119] When the type of the abnormal situation is a comprehensive abnormality, the defect quantification module comprehensively utilizes the pressure change rate, the vibration frequency and the weld integrity to perform quantitative analysis on the comprehensive abnormal situation of the pipeline.

[0120] It is understandable that the defect quantification module of this embodiment is designed to perform in-depth quantitative analysis of these abnormal conditions when the defect identification module determines that there are abnormal conditions in the pipeline. Through this quantitative analysis, the severity of the abnormal condition of the pipeline can be more accurately determined. Specifically, it includes the following situations:

[0121] First, when the abnormal situation is caused by environmental factors, the defect quantification module will determine the degree of impact of environmental factors on pipeline operation by analyzing the correlation between environmental noise data and pipeline pressure data. This method can effectively identify the contribution of environmental noise to pipeline pressure changes, thereby evaluating the potential impact of environmental factors on pipeline operation.

[0122] Secondly, when the abnormality is a structural abnormality caused by vibration, the defect quantification module will evaluate the potential risk of structural damage by calculating the deviation between the vibration frequency and the standard vibration frequency, combining the pipeline material characteristics and historical vibration data. This analysis method can reveal abnormal changes in vibration frequency, thereby predicting possible structural damage and providing a scientific basis for pipeline maintenance.

[0123] Third, when the abnormal situation is weld damage, the defect quantification module will use ultrasonic detection technology or X-ray detection technology to detect the area and depth of the weld to quantify the degree of damage. Through these advanced detection technologies, the damage range and depth of the weld can be accurately measured, providing accurate data support for subsequent repairs and replacements.

[0124] Finally, when the abnormal condition is a comprehensive abnormality, the defect quantification module will use the pressure change rate, vibration frequency and weld integrity to quantify the comprehensive abnormality of the pipeline. This method can comprehensively evaluate the operation status of the pipeline and provide a comprehensive abnormal condition evaluation result through multi-dimensional data analysis, thereby providing a more comprehensive reference for pipeline maintenance and repair.

[0125] Through the above-mentioned quantitative analysis method, abnormal conditions of pipelines can be identified and evaluated more accurately, providing strong technical support for the safe operation of pipelines.

[0126] In some embodiments of the present application, the defect quantification module is configured to, when the defect identification module determines that the pipeline has an abnormality, perform quantitative analysis on the abnormality, and judge the severity of the abnormality of the pipeline according to the quantitative analysis result and the type of the abnormality, further comprising:

[0127] The influence of environmental factors on pipeline operation is obtained through the following calculation formula:

[0128] ;

[0129] ;

[0130] Where E represents the environmental impact coefficient; Corr p,e Represents the correlation coefficient between pressure data and environmental noise data; MaxCorr p,e Indicates the historical maximum correlation coefficient, used for standardization; Var noise Represents the variance of environmental noise; Var pressure Indicates the variance of pipeline pressure; Impact env Environmental factors impact index;

[0131] The vibration risk assessment index is obtained by the following calculation formula:

[0132] ;

[0133] ;

[0134] Among them, V d Indicates the vibration deviation coefficient; f act Indicates the actual vibration frequency; f std Indicates the standard vibration frequency; S f Represents the structural fatigue coefficient; H v Represents the standard deviation of historical vibration data; R mat Indicates the vibration resistance of the material; R v represents the vibration risk assessment index;

[0135] The weld damage assessment index is obtained by the following calculation formula:

[0136] ;

[0137] ;

[0138] ;

[0139] Among them, A d Indicates weld damage area coefficient; D d Indicates weld damage depth coefficient; A dam Indicates the weld damage area; A total Indicates the total area of ​​the weld; D dam Indicates the weld damage depth; D max Indicates the maximum allowable depth of the weld; I weld Represents the weld damage assessment index;

[0140] The comprehensive evaluation index is obtained through the following calculation formula;

[0141] ;

[0142] ;

[0143] ;

[0144] ;

[0145] ;

[0146] Among them, ΔP norm Indicates the normalized rate of pressure change; ΔP min and ΔP maxRespectively represent the minimum and maximum value of the pressure change rate; f v,norm Indicates the vibration frequency standard; f v,min and f v,max Respectively represent the minimum and maximum values ​​of the vibration frequency; W v,norm Indicates the standardization of weld integrity; W min and W max Respectively represent the minimum and maximum values ​​of weld integrity; w ΔP 、w fv 、w W Respectively represent the weights of pressure change rate, vibration frequency and weld integrity; I comp Represents a comprehensive evaluation index.

[0147] The present invention also proposes a pressure detection and early warning method based on pipeline network collected data, and the pressure detection and early warning method based on pipeline network collected data is implemented by the above-mentioned pressure detection and early warning system based on pipeline network collected data.

[0148] Those skilled in the art will appreciate that the embodiments of the present application may be provided as methods, systems or computer program products. Therefore, the present application may take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware. Moreover, the present application may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program codes.

[0149] The present application is described with reference to the flowcharts and / or block diagrams of the methods, devices (systems) and computer program products according to the embodiments of the present application. It should be understood that each process and / or box in the flowchart and / or block diagram, as well as the combination of processes and / or boxes in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0150] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0151] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0152] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the above embodiments, ordinary technicians in the relevant field should understand that the specific implementation methods of the present invention can still be modified or replaced by equivalents. Any modification or equivalent replacement that does not depart from the spirit and scope of the present invention should be covered within the scope of protection of the claims of the present invention.

Claims

1. A pressure detection and early warning system based on pipe network collection data, characterized in that: It includes data acquisition module, defect identification module, defect quantification module and early warning decision module; Wherein, the data acquisition module is configured to monitor real-time data and physical conditions inside and outside the pipeline; The defect recognition module is configured to determine whether the pipeline has an abnormality according to the real-time data; the defect recognition module is further configured to determine the type of the abnormality according to the real-time data and the physical state when it is determined that the pipeline has an abnormality; The defect quantification module is configured to, when the defect identification module determines that the pipeline has an abnormality, perform quantitative analysis on the abnormality, and determine the severity of the abnormality of the pipeline according to the quantitative analysis result and the type of the abnormality; The early warning decision module is configured to generate an early warning signal based on the severity of the abnormal situation of the pipeline; The real-time data includes the pressure, temperature and flow of the pipeline; the physical state includes the vibration frequency of the pipeline and the integrity of the weld at the joint; When the defect identification module is configured to determine whether the pipeline has an abnormal condition according to the real-time data, it includes: The pressure change rate per unit time is calculated based on the pressure, temperature and flow rate of the pipeline. The pressure change rate per unit time is calculated using the following formula: ； in, represents the pressure change rate per unit time; f represents the friction coefficient; L represents the pipe length; D represents the pipe diameter; ρ represents the fluid density; v represents the fluid flow rate; It represents the instantaneous rate of change of flow velocity to dynamic pressure; K represents the bending loss coefficient; represents the partial derivative of pressure with respect to temperature; Indicates the rate of temperature change per unit time; The calculation formula of the bending loss coefficient is: ； Wherein, Kelbow represents the loss coefficient of a 90° standard elbow; θ represents the elbow angle of the pipe; The calculation formula of the loss coefficient of the 90° standard elbow is: ； Where r represents the radius of curvature of the curved pipe; D represents the pipe diameter; and Re represents the Reynolds number.

2. The pressure detection and early warning system based on pipeline network data collection according to claim 1 is characterized in that: The defect recognition module is configured to determine whether the pipeline has an abnormality according to the real-time data; The defect identification module is further configured to, when the result of the determination indicates that the pipeline has an abnormality, determine the type of the abnormality according to the real-time data and the physical state, including: Pre-set pressure change rate threshold, vibration frequency safety value and weld integrity threshold; When the pressure change rate is less than or equal to the pressure change rate threshold, it is determined that there is no abnormality in the pipeline; When the pressure change rate is greater than the pressure change rate threshold, it is determined that an abnormality exists in the pipeline; When it is determined that the pipeline has an abnormality, a comparative analysis of the vibration frequency and the welding integrity is performed, and the type of the abnormality is determined based on the comparative analysis result.

3. The pressure detection and early warning system based on pipeline network data collection according to claim 2 is characterized in that: When it is determined that the pipeline has an abnormality, a comparative analysis of the vibration frequency and the welding integrity is performed, and the type of the abnormality is determined based on the comparative analysis results, including: When the vibration frequency is less than or equal to the vibration frequency safety value and the welding integrity is greater than or equal to the welding integrity threshold, it is determined that the type of the abnormal situation is interference by environmental factors; When the vibration frequency is greater than the vibration frequency safety value and the welding integrity is greater than or equal to the welding integrity threshold, the type of the abnormal situation is determined to be a structural abnormality caused by vibration; When the vibration frequency is less than or equal to the vibration frequency safety value and the welding integrity is less than the welding integrity threshold, the type of the abnormal situation is determined to be weld damage; When the vibration frequency is greater than the vibration frequency safety value and the welding integrity is less than the welding integrity threshold, the type of the abnormal situation is determined to be a comprehensive abnormality.

4. The pressure detection and early warning system based on pipeline network data collection according to claim 3 is characterized in that: The defect quantification module is configured to, when the defect identification module determines that the pipeline has an abnormality, perform quantitative analysis on the abnormality, and determine the severity of the abnormality of the pipeline according to the quantitative analysis result and the type of the abnormality, including: When the type of the abnormal situation is the presence of environmental factors interference, the defect quantification module determines the degree of influence of environmental factors on pipeline operation by analyzing the correlation between environmental noise data and pipeline pressure data; When the type of the abnormal condition is a structural abnormality caused by vibration, the defect quantification module evaluates the potential risk of structural damage by calculating the deviation between the vibration frequency and the standard vibration frequency, combining the pipeline material properties and historical vibration data; When the type of the abnormal situation is weld damage, the defect quantification module detects the area and depth of the weld using ultrasonic detection technology or radiographic detection technology to quantify the degree of damage; When the type of the abnormal situation is a comprehensive abnormality, the defect quantification module comprehensively utilizes the pressure change rate, the vibration frequency and the weld integrity to perform quantitative analysis on the comprehensive abnormal situation of the pipeline.

5. The pressure detection and early warning system based on pipeline network data collection according to claim 4 is characterized in that: The defect quantification module is configured to, when the defect identification module determines that the pipeline has an abnormality, perform quantitative analysis on the abnormality, and determine the severity of the abnormality of the pipeline according to the quantitative analysis result and the type of the abnormality, further comprising: The influence of environmental factors on pipeline operation is obtained through the following calculation formula: ； ； Where E represents the environmental impact coefficient; Corr p,e Represents the correlation coefficient between pressure data and environmental noise data; MaxCorr p,e Indicates the historical maximum correlation coefficient, used for standardization; Var noise Represents the variance of environmental noise; Var pressure Indicates the variance of pipeline pressure; Impact env Environmental factors impact index; The vibration risk assessment index is obtained by the following calculation formula: ； ； Among them, V d Indicates the vibration deviation coefficient; f act Indicates the actual vibration frequency; f std Indicates the standard vibration frequency; S f Represents the structural fatigue coefficient; H v Represents the standard deviation of historical vibration data; R mat Indicates the vibration resistance of the material; R v represents the vibration risk assessment index; The weld damage assessment index is obtained by the following calculation formula: ； ； ； Among them, A d Indicates weld damage area coefficient; D d Indicates weld damage depth coefficient; A dam Indicates the weld damage area; A total Indicates the total area of ​​the weld; D dam Indicates the weld damage depth; D max Indicates the maximum allowable depth of the weld; I weld Represents the weld damage assessment index; The comprehensive evaluation index is obtained through the following calculation formula; ； ； ； ； ； Among them, ΔP norm Indicates the normalized rate of pressure change; ΔP min and ΔP max Respectively represent the minimum and maximum value of the pressure change rate; f v,norm Indicates the vibration frequency standard; f v,min and f v,max Respectively represent the minimum and maximum values ​​of the vibration frequency; W norm Indicates the standardization of weld integrity; W min and W max Respectively represent the minimum and maximum values ​​of weld integrity; w ΔP 、w fv 、w W Respectively represent the weights of pressure change rate, vibration frequency and weld integrity; I comp Represents a comprehensive evaluation index.

6. A pressure detection and early warning method based on pipeline network collection data, characterized in that: The pressure detection and early warning method based on pipeline network collected data is implemented by the pressure detection and early warning system based on pipeline network collected data as described in any one of claims 1-5.

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