Oil pipeline pressure design determining system and method thereof
By dynamically assessing the real-time physical state and pressure-bearing capacity of oil pipelines and combining this with a hydraulic transient model to predict future pressure peaks, the problem of being unable to quantify pipeline performance degradation and predict transient pressure waves in traditional design has been solved, achieving closed-loop control of safety and efficiency.
Patent Information
- Application Number
- CN202511730604.6
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2025-11-24
- Publication Date
- 2026-02-27
AI Technical Summary
Traditional oil pipeline pressure design methods cannot quantify the real-time physical performance degradation of pipelines caused by factors such as corrosion and fatigue, and cannot proactively predict the complex transient pressure waves caused by pump start-up and shutdown, valve opening and closing, etc., leading to safety hazards and efficiency bottlenecks.
By collecting dynamic operating condition data and static physical data, and combining empirical degradation models and dynamic yield pressure models, the real-time physical state and pressure bearing capacity of the pipeline are evaluated. The future pressure peak is predicted using hydraulic transient models, the dynamic risk index is calculated, and closed-loop optimization control is executed.
It enables accurate assessment of the pipeline's true pressure-bearing capacity, proactive prediction of complex transient pressure waves, ensures closed-loop control of safety and efficiency, reduces safety hazards, and improves oil transportation efficiency.
Smart Images
Figure CN121580894A_ABST
Abstract
Description
Technical Field
[0001] This invention relates to the field of oil pipeline safe operation and pressure control technology, specifically to an oil pipeline pressure design and determination system and method. Background Technology
[0002] The safe and efficient operation of oil pipelines places stringent requirements on their pressure design. Traditional pressure design methods rely heavily on static assumptions, such as using a fixed pressure limit at the initial design stage as the operating boundary and assuming that pipeline performance remains constant during service. However, this static method has two major drawbacks: it cannot quantify the real-time physical performance degradation of the pipeline caused by factors such as corrosion and fatigue, resulting in the set pressure limit failing to reflect the pipeline's true pressure-bearing capacity; traditional static design cannot proactively predict complex transient pressure waves or abnormal surges caused by multiple asynchronous operations such as pump start-up and shutdown, and valve opening and closing. This dynamic mismatch between future instantaneous loads and real-time pressure-bearing capacity brings serious safety hazards and efficiency bottlenecks. Therefore, how to dynamically assess the true physical yield boundary of the pipeline and accurately predict future pressure peaks, thereby achieving closed-loop control of safety and efficiency, is a technical problem that urgently needs to be solved in this field. Summary of the Invention
[0003] To address the aforementioned technical problems, this invention provides a system and method for determining the pressure design of oil pipelines. Specifically, the technical solution of this invention is as follows: A method for determining the pressure design of an oil pipeline includes: S1: Collect dynamic operating condition data, and calculate the predicted peak pressure based on the dynamic operating condition data and the preset hydraulic transient model; S2 collects static physical data and material degradation parameters, and combines the static physical data and material degradation parameters to evaluate the real-time physical state factor through a preset empirical degradation model; S3, combining static physical data and real-time physical state factors, determines the real-time physical yield pressure through a dynamic yield pressure calculation model; S4, based on the predicted peak pressure and the real-time physical yield pressure, calculates the dynamic risk index; S5 determines the pipeline's operating status based on the dynamic risk index, preset safety efficiency threshold, and preset active defense threshold. The operating status includes the efficiency release zone, the stable observation zone, and the active defense zone. S6, in response to a determined operating state, performs closed-loop optimization control, including: When the operating state is in the efficiency release zone, an efficiency release control command to increase the average operating pressure is generated based on the real-time physical yield pressure and the safety efficiency threshold. When the operating status is in the stable observation zone, maintain the current operation and continuously monitor the dynamic risk index; When the operating state is in the active defense zone, based on the hydraulic transient model, real-time physical yield pressure and active defense threshold, the minimum adjustment control command to suppress the predicted pressure peak is calculated retrospectively and generated.
[0004] Preferably, the dynamic operating data includes: real-time pressure, flow rate, upstream pump speed, and downstream valve opening along the pipeline.
[0005] Preferably, static physical data include: pipe design diameter, initial wall thickness, and steel grade.
[0006] Preferably, the material degradation parameters include: wall thickness loss and service life.
[0007] Preferably, in S2, the real-time physical state factors are evaluated and obtained through a preset empirical degradation model, including: Calculate the effective wall thickness reduction based on the wall thickness loss and the initial wall thickness; Based on the years of operation and a preset aging weight coefficient, the fatigue aging reduction of materials is calculated using an exponential decay model. The real-time physical state factor is obtained by multiplying the effective wall thickness reduction by the material fatigue aging reduction.
[0008] Preferably, in S3, the real-time physical yield pressure is determined through a dynamic yield pressure calculation model, including: The real-time effective wall thickness is calculated by multiplying the initial wall thickness by the real-time physical state factor. Based on the yield strength corresponding to the steel grade, the real-time effective wall thickness, and the pipe design diameter, the real-time physical yield pressure is obtained by solving the yield formula for thin-walled cylinders.
[0009] Preferably, in S6, when the operating state is in the efficiency release zone, an efficiency release control command is generated, including: The target average operating pressure is determined based on the real-time physical yield pressure at the weakest point along the entire line and the safety efficiency threshold. Generate efficiency release control commands to increase the average operating pressure to the target average operating pressure.
[0010] Preferably, in S6, when the operating state is the active defense zone, a minimum adjustment control command is generated, including: By retracing the hydraulic transient model, the key boundary conditions that lead to the predicted pressure peak are identified. Calculate the minimum adjustment amount for the critical boundary conditions and use the minimum adjustment amount as the minimum adjustment amount control command; The minimum adjustment amount ensures that the new predicted risk index obtained after simulation and correction by the minimum adjustment amount is less than or equal to the active defense threshold.
[0011] A system for determining the pressure design of an oil pipeline, comprising: The data acquisition module is used to collect dynamic operating condition data, static physical data, and material degradation parameters; The pressure calculation module is used to calculate the predicted peak pressure based on dynamic operating condition data and a preset hydraulic transient model. The condition assessment module is used to combine static physical data and material degradation parameters to evaluate and obtain real-time physical state factors through a preset empirical degradation model. The yield boundary module is used to combine static physical data with real-time physical state factors to determine the real-time physical yield pressure through a dynamic yield pressure calculation model. The risk calculation module is used to calculate the dynamic risk index based on the predicted peak pressure and the real-time physical yield pressure. The status classification module is used to determine the pipeline's operating status based on the dynamic risk index, preset safety efficiency threshold, and preset active defense threshold. The operating status includes the efficiency release zone, the stable observation zone, and the active defense zone. A closed-loop control module is used to perform closed-loop optimization control in response to a determined operating state. The closed-loop control module includes: The efficiency release unit is used to generate an efficiency release control command to increase the average operating pressure based on the real-time physical yield pressure and the safety efficiency threshold when the operating state is in the efficiency release zone. The stable observation unit is used to maintain the current operation and continuously monitor the dynamic risk index when the operating status is in the stable observation zone; The active defense unit is used to backtrack and generate the minimum adjustment control command to suppress the predicted pressure peak when the operating state is in the active defense zone, based on the hydraulic transient model, real-time physical yield pressure and active defense threshold.
[0012] Compared with the prior art, the present invention has the following beneficial effects: 1. This invention can combine the initial physical data of the pipeline with real-time degradation parameters such as wall thickness loss and service life, and accurately evaluate the pipeline's true physical pressure bearing capacity at the current moment through empirical degradation model and dynamic yield pressure model, overcoming the shortcomings of traditional methods that rely on fixed pressure upper limits and cannot reflect the degradation of pipeline performance over time. 2. This invention utilizes a hydraulic transient model and combines dynamic operating data such as upstream pump speed and downstream valve opening to achieve forward-looking prediction of future composite transient pressure waves and abnormal surges, solving the technical problem that traditional static design cannot predict future instantaneous loads. 3. This invention calculates a dynamic risk index by comparing the predicted future pressure peak with the real-time physical yield pressure of the pipeline, thereby establishing a clear quantitative assessment relationship between future load and current capacity, and solving the safety hazards caused by the dynamic mismatch between the two. 4. This invention divides pipelines into different operating states based on a dynamic risk index and performs closed-loop optimization control: when the risk is high, it can actively backtrack the model and generate minimum adjustment instructions to suppress the impending pressure peak; when the risk is low, it can automatically calculate the optimal operating pressure under the safety efficiency threshold and generate instructions to increase the average operating pressure, thereby significantly improving oil transportation efficiency while ensuring safety. Attached Figure Description
[0013] The present invention will be further explained below with reference to the accompanying drawings and embodiments: Figure 1 This is a flowchart of the method of the present invention.
[0014] Figure 2 This is a structural diagram of the system of the present invention. Detailed Implementation
[0015] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be further described in detail below with reference to specific embodiments.
[0016] Example 1: Please see Figure 1 A method for determining the pressure design of an oil pipeline, comprising: S1: Collect dynamic operating condition data, and calculate the predicted peak pressure based on the dynamic operating condition data and the preset hydraulic transient model; S2 collects static physical data and material degradation parameters, and combines the static physical data and material degradation parameters to evaluate the real-time physical state factor through a preset empirical degradation model; S3, combining static physical data and real-time physical state factors, determines the real-time physical yield pressure through a dynamic yield pressure calculation model; S4, based on the predicted peak pressure and the real-time physical yield pressure, calculates the dynamic risk index; S5 determines the pipeline's operating status based on the dynamic risk index, preset safety efficiency threshold, and preset active defense threshold. The operating status includes the efficiency release zone, the stable observation zone, and the active defense zone. S6, in response to a determined operating state, performs closed-loop optimization control, including: When the operating state is in the efficiency release zone, an efficiency release control command to increase the average operating pressure is generated based on the real-time physical yield pressure and the safety efficiency threshold. When the operating status is in the stable observation zone, maintain the current operation and continuously monitor the dynamic risk index; When the operating state is in the active defense zone, based on the hydraulic transient model, real-time physical yield pressure and active defense threshold, the minimum adjustment control command to suppress the predicted pressure peak is calculated retrospectively and generated.
[0017] Dynamic operating data includes: real-time pressure, flow rate, upstream pump speed, and downstream valve opening along the pipeline.
[0018] Static physical data include: pipe design diameter, initial wall thickness, and steel grade.
[0019] Material degradation parameters include: wall thickness loss and service life.
[0020] This embodiment provides a method for determining the pressure design of an oil pipeline. This method realizes the entire process from data acquisition, real-time evaluation, forward-looking prediction to dynamic closed-loop control through a complete technical closed loop. The purpose of S1 is to proactively capture the superposition of complex transient pressure waves caused by multiple asynchronous operations, such as pump start-up and shutdown, valve opening and closing, i.e., abnormal surges, which traditional static designs cannot handle. In this embodiment, the dynamic operating condition data is acquired in real time from the pipeline's SCADA data acquisition and monitoring control system, which provides boundary condition data. This dynamic operating condition data is a set of parameters that change over time, serving to provide real-time input for the hydraulic model. In this embodiment, it includes: the upstream pump unit speed. and downstream valve opening These two serve as the core boundary conditions of the model, as well as the real-time pressure along the pipeline used for condition monitoring and model calibration. and traffic ; The preset hydraulic transient model is a mathematical and physical model used to describe the transient response of fluid pressure and flow rate inside the pipe. Its function is to reproduce the propagation, reflection and superposition of pressure waves. In this embodiment, the model is preferably the method of characteristics (MOC) known in the art. The process of calculating and obtaining the predicted peak pressure is as follows: the system collects... and As input, a forward-looking simulation calculation is performed using the MOC model to calculate the pipeline's position in a very short future time step. Afterwards, all locations along the line Predicted peak pressure ;this This refers to the maximum instantaneous load that the system needs to defend against in the future; The purpose of S2 is to abandon the static assumption of constant pipeline performance in traditional design, and instead accurately quantify the real physical health state of the pipeline at the current moment. Collecting static physical data: This static physical data refers to the inherent physical properties of the pipeline at the initial design and construction stage, serving as a basis for calculations. In this embodiment, this data is obtained from design drawings or a database, including: pipeline design diameter. Initial wall thickness and steel grade It defines the initial yield strength of steel; Material degradation parameters are collected: These parameters are measured data reflecting the performance degradation of the pipeline during its service life. In this embodiment, these data include: the current estimated wall thickness loss obtained by extrapolating from historical detection data and a preset corrosion rate model. and / or discrete point wall thickness loss data collected by fixed corrosion monitoring sensors along the line, as well as the number of years of operation obtained from the operation log. ; The real-time physical state factors are obtained through evaluation using a pre-set empirical degradation model: the system will collect... , and static data Substituting the values into a pre-defined empirical degradation model, the real-time physical state factor is calculated. Real-time physical state factor This is a key parameter defined in this invention. Its function is to comprehensively quantify the degree of reduction in the physical integrity of the pipeline due to corrosion and fatigue aging with a dimensionless value between 0 and 1. Indicates a brand new pipeline. The closer to 0, the more severe the degradation; The purpose of S3 is to calculate the pipeline's... The true pressure-bearing capacity at any given moment, i.e., its physical yield limit; this is a revolutionary alternative to the traditional fixed MAOP maximum permissible operating pressure. The real-time physical yield pressure is determined through a dynamic yield pressure calculation model: The system uses a dynamic yield pressure calculation model, which is a dynamic improvement on the known physical formula, combined with the static physical data obtained in step S2, especially... , , and the calculated real-time physical state factor To determine the pipeline in Real-time physical yield pressure at location Real-time physical yield pressure The actual pressure threshold at which the pipeline undergoes plastic deformation, i.e., yielding, at this location and time is expressed in Pascals (Pa), representing the pipeline's real-time structural capacity. The purpose of S4 is to normalize the comparison between the future load S1 and the current capacity S3 in order to quantify the safety margin. The dynamic risk index is calculated as follows: the predicted peak pressure obtained by the system based on S1. The real-time physical yield pressure obtained from S3 The dynamic risk index is calculated by division. ; In this embodiment, the calculation formula, namely the load-to-capacity ratio (Demand-to-CapacityRatio), is:
[0021] in, This is a dynamic risk index, dimensionless, calculated in step S4 of this procedure. To predict the peak pressure, the unit is Pa, which is obtained from step S1; The real-time physical yield pressure, in Pa, is determined by step S3. this The physical meaning of the value is very clear: Indicates safety; This means that the predicted pressure peak will exceed the actual yield limit of the pipeline, i.e., yield failure is predicted to occur. The purpose of S5 is to classify the overall safety status of the entire pipeline based on the risk assessment of S4, so that S6 can adopt differentiated control strategies. Determine the operating status of the pipeline: The system is located along the entire pipeline. Find the maximum value of the dynamic risk index, that is The system will Compare with two preset thresholds; Preset safety efficiency threshold For example, 0.85 defines an optimal operating limit; this threshold is set to balance long-term fatigue damage with short-term economic benefits. For instance, based on the material's SN curve and the preset pipeline design life, the allowable daily average cumulative fatigue damage limit can be calculated, and this limit can be converted into a corresponding risk index. ; Preset active defense threshold For example, 0.95 must be less than 1, and its function is to define a safe and optimal intervention threshold; the basis for setting this threshold is to reserve the necessary reaction time for the control system S6 to execute defensive actions; for example, if the system detects... The entire closed-loop response time from executing the minimum adjustment control command to suppressing the pressure wave is: ,but The value of must ensure The safety margin represented is sufficient in this It can absorb the instantaneous impact of pressure waves within a short period of time without yielding; Based on the comparison results, the operating status is determined to be one of the following three: Efficiency release zone: when hour; Stable observation zone: when hour; Active defense zone: when hour; S6 is the final execution end of the method of the present invention. Its purpose is to automatically execute the optimal control action according to the hierarchical operation status of S5, so as to realize a closed loop of safety and efficiency. When the operating state is in the efficiency release zone: the system determines that the current safety margin is sufficient, based on the real-time physical yield pressure calculated by S3. and the security efficiency threshold set by S5 This generates an efficiency release control command; the function of this command is to increase the average operating pressure of the pipeline. To improve conveying efficiency; When the operating status is in the stable observation zone: the system determines that it is operating within the normal range, maintains the current operation, does not issue control commands, and continuously monitors the dynamic risk index calculated by S4; When the system is in the active defense zone: the system determines that danger is imminent; at this time, the system no longer passively accepts attacks. Instead of directly addressing the underlying causes, the system actively intervenes in the formation of the problem; the system is based on the hydraulic transient model of S1 and the real-time physical yield pressure of S3. and S5's active defense threshold It performs a backtracking calculation to generate a control command with a minimum adjustment amount to suppress the predicted pressure peak; this command, for example, fine-tunes the speed of a pump, actively... Lower it, reduce its risk to the following.
[0022] Example 2: In S2, real-time physical state factors are evaluated and obtained through a pre-defined empirical degradation model, including: Calculate the effective wall thickness reduction based on the wall thickness loss and the initial wall thickness; Based on the years of operation and a preset aging weight coefficient, the fatigue aging reduction of materials is calculated using an exponential decay model. The real-time physical state factor is obtained by multiplying the effective wall thickness reduction by the material fatigue aging reduction.
[0023] Based on Example 1, this embodiment specifically defines the process of evaluating and obtaining the real-time physical state factor through a preset empirical degradation model in step S2; the design of this model is a technical innovation of this invention. In this embodiment, the real-time physical state factor The calculation process is as follows: Based on wall thickness loss With initial wall thickness The effective wall thickness reduction, i.e., the degree of integrity due to corrosion, is calculated using the following expression: ; Based on years of operation and preset aging weight coefficient The fatigue aging reduction of materials, i.e., the degree of integrity caused by long-term service, is estimated using an exponential decay model. Its expression is: ; Multiplying the effective wall thickness reduction by the material fatigue aging reduction yields the final result. ; The complete mathematical expression for this pre-defined empirical degradation model is:
[0024] in, The real-time physical state factor is dimensionless and is calculated by step S2. It characterizes the current state of the tube relative to its initial state. To estimate the wall thickness loss, the unit is meters, and it is obtained by extrapolation based on historical detection data and / or by fixed sensor data in step S2. The initial wall thickness, in meters, is provided by the static physical data in step S2; The operating period is measured in years and is provided by the operating record in step S2. α is the aging weighting coefficient for the material, which is a preset calibration value. To further clarify its determination method, this value can be obtained through regression analysis on a set of historical pipe section maintenance data; for example, collecting data from multiple service years... Pipe section samples were collected, and their corresponding material property degradation indices were measured. By and By performing least squares fitting, the optimal value can be determined. Value; here and These are historical dataset variables used to calibrate the model, and are different from the real-time running years input during model runtime. Furthermore, to ensure the physical meaning of the model, real-time physical state factors are considered. The calculation results are used to apply boundary constraints, that is... This ensures that when wall thickness is lost... Greater than or equal to the initial wall thickness At that time, state factor The value is at least 0, thus avoiding physical failure. Those skilled in the art will understand that the empirical degradation model shown is a simplified calculation method that decouples corrosion and fatigue aging as independent factors. In practical applications, more complex coupled damage models that consider the synergistic effect of corrosion and fatigue can also be used, and these improvements all fall within the protection scope of this invention.
[0025] Example 3: In S3, the real-time physical yield pressure is determined through a dynamic yield pressure calculation model, including: The real-time effective wall thickness is calculated by multiplying the initial wall thickness by the real-time physical state factor. Based on the yield strength corresponding to the steel grade, the real-time effective wall thickness, and the pipe design diameter, the real-time physical yield pressure is obtained by solving the yield formula for thin-walled cylinders.
[0026] Based on Example 1, this embodiment provides specific limitations on the process of determining the real-time physical yield pressure through the dynamic yield pressure calculation model in step S3. In this embodiment, the dynamic yield pressure calculation model is a dynamic improvement of the Barlow formula, a well-known yield formula for thin-walled cylinders, and its calculation logic is as follows: Initial wall thickness The real-time physical state factor calculated by multiplying by S2 The real-time effective wall thickness is calculated. ; Real-time effective wall thickness This is a core innovative definition of the present invention, and its function is... It will contain dimensionless health factors in S2. The equivalent load-bearing wall thickness with physical meaning was translated back, with the dimension of meters; Based on the yield strength corresponding to the steel grade The real-time effective wall thickness obtained in step 1 and pipe design diameter The real-time physical yield pressure is obtained by solving the yield formula of a thin-walled cylinder. ; The complete mathematical expression for this model is:
[0027] in, The real-time physical yield pressure, in Pa, is calculated in step S3 of this section, i.e., the pressure at which the pipeline... The actual physical compressive strength of the location; The yield strength corresponding to the steel grade is in Pa, and is obtained by looking up the table from the static physical data in step S2. The pipe design diameter, in meters, is provided by the static physical data from step S2. Right now The real-time effective wall thickness, in meters, is calculated in step S3 of this procedure. Its input is... From static data, The output from step S2; further, to ensure the physical meaning of the model and the robustness of the calculation in step S4, the real-time physical yield pressure is... The calculation results are used to apply boundary constraints, that is... ,in It is set to a preset minimum positive value to prevent division by zero errors in S4.
[0028] Example 4: In S6, when the operating state is in the efficiency release zone, an efficiency release control command is generated, including: The target average operating pressure is determined based on the real-time physical yield pressure at the weakest point along the entire line and the safety efficiency threshold. Generate efficiency release control commands to increase the average operating pressure to the target average operating pressure.
[0029] Based on Example 1, this embodiment specifically defines the process of generating efficiency release control instructions in step S6 when the running state is the efficiency release zone; When the system evaluation enters the efficiency release zone, that is... At that time, the control logic is as follows: Based on the real-time physical yield pressure at the weakest point along the entire line and the safety efficiency threshold, the target average operating pressure is determined: The system iterates through all the calculations obtained by S3. Find its minimum value ,in This is the weakest point along the entire line, meaning the point with the lowest physical load-bearing capacity. The system determines a target average operating pressure. ; In this embodiment, the calculation of the target average operating pressure follows the efficiency-optimal control law defined in this invention:
[0030] in, The target average operating pressure, in Pa, is calculated in step S6 and will be used as the pressure setpoint of the SCADA system in the next control cycle. The physical yield boundary at the weakest point along the entire line, with dimensions Pa, is determined by iterating through the output of S3. The minimum value is obtained; The safety efficiency threshold is dimensionless and preset by S5. Generate efficiency release control commands to increase the average operating pressure to the target average operating pressure: The system calculates... Then, an efficiency release control command is generated, for example, one used to adjust the speed of the upstream pump unit. The instruction is sent to the SCADA system for execution to drive the actual mean operating pressure of the pipeline. Gradually increase to the newly calculated target average operating pressure .
[0031] Example 5: In S6, when the operating state is the active defense zone, a minimum adjustment control command is generated, including: By retracing the hydraulic transient model, the key boundary conditions that lead to the predicted pressure peak are identified. Calculate the minimum adjustment amount for the critical boundary conditions and use the minimum adjustment amount as the minimum adjustment amount control command; The minimum adjustment amount ensures that the new predicted risk index obtained after simulation and correction by the minimum adjustment amount is less than or equal to the active defense threshold.
[0032] Based on Example 1, this embodiment specifically defines the process of generating the minimum adjustment control command in step S6 when the running state is the active defense zone; When the system assessment enters the active defense zone, that is... At that time, the control logic is as follows: By retracing back the hydraulic transient model, the key boundary conditions leading to the predicted pressure peak are identified: the system executes proactive defense logic; it retraces back the hydraulic transient model (MOC) used in S1 to identify which one or more key boundary conditions, such as the upstream pump, are at fault. rotational speed or downstream valve Valve opening The change in is the main reason why S1 predicts that Pp exceeds the safety threshold; Calculate the minimum adjustment amount for critical boundary conditions: The system adjusts for the identified critical boundary conditions, such as... Calculate a minimum adjustment amount ; The minimum adjustment amount ensures that the new predicted risk index obtained after simulation, after correction by the minimum adjustment amount, is less than or equal to the active defense threshold. Minimum adjustment amount The calculation is a process of solving a constrained optimization problem, the constraint condition of which is the safety optimal control objective defined in this invention:
[0033] in, The new predictive risk index is dimensionless and was calculated in the backtracking simulation. The new peak pressure obtained from the simulation after correction has dimensions in Pa; this is a composite function that represents the hydraulic model using S1, but with an assumed, adjusted boundary condition as input. The pressure peak value was obtained by resimulating; The real-time physical yield pressure, in Pa, is calculated from S3 and is a known boundary in this constraint. The active defense threshold is dimensionless and preset by S5. The system solves the above inequalities to obtain the conditions. The minimum value is determined and sent to the SCADA system as a minimum adjustment control command for execution. For example, the command is to adjust the pump... Reduce speed .
[0034] Example 6: Please see Figure 2 A system for determining the pressure design of an oil pipeline, comprising: The data acquisition module is used to collect dynamic operating condition data, static physical data, and material degradation parameters; The pressure calculation module is used to calculate the predicted peak pressure based on dynamic operating condition data and a preset hydraulic transient model. The condition assessment module is used to combine static physical data and material degradation parameters to evaluate and obtain real-time physical state factors through a preset empirical degradation model. The yield boundary module is used to combine static physical data with real-time physical state factors to determine the real-time physical yield pressure through a dynamic yield pressure calculation model. The risk calculation module is used to calculate the dynamic risk index based on the predicted peak pressure and the real-time physical yield pressure. The status classification module is used to determine the pipeline's operating status based on the dynamic risk index, preset safety efficiency threshold, and preset active defense threshold. The operating status includes the efficiency release zone, the stable observation zone, and the active defense zone. A closed-loop control module is used to perform closed-loop optimization control in response to a determined operating state. The closed-loop control module includes: The efficiency release unit is used to generate an efficiency release control command to increase the average operating pressure based on the real-time physical yield pressure and the safety efficiency threshold when the operating state is in the efficiency release zone. The stable observation unit is used to maintain the current operation and continuously monitor the dynamic risk index when the operating status is in the stable observation zone; The active defense unit is used to backtrack and generate the minimum adjustment control command to suppress the predicted pressure peak when the operating state is in the active defense zone, based on the hydraulic transient model, real-time physical yield pressure and active defense threshold.
[0035] This embodiment provides a system for determining the pressure design of an oil pipeline. This system is the hardware and / or software entity for implementing the method. In this embodiment, the system, for example, a server deployed in a pipeline dispatch center, includes the following modules: Data acquisition module: Its purpose is to provide real-time and static data input for all subsequent calculations; in this embodiment, this module is used to perform the data acquisition steps in Embodiment 1, which acquires dynamic operating condition data as defined in Embodiment 1. , Static physical data as defined in Example 1, etc. , , and the material degradation parameters as defined in Example 1 , ; Pressure calculation module: Its purpose is to predict future transient pressure loads; in this embodiment, this module is used to perform the calculation part of S1, and calculates the predicted peak pressure based on dynamic operating condition data from the data acquisition module and a preset hydraulic transient model such as the MOC model. ; The condition assessment module aims to quantify the current physical degradation level of the pipeline. In this embodiment, this module executes S2, combining static physical data from the data acquisition module with material degradation parameters, and evaluates the real-time physical state factor using a preset empirical degradation model, such as the exponential decay model detailed in Embodiment 2. ; Yield boundary module: Its purpose is to determine the current true pressure-bearing capacity of the pipeline; in this embodiment, this module is used to execute S3, combining static physical data from the data acquisition module with real-time physical state factors from the state assessment module. The real-time physical yield pressure is determined using the improved Barlow formula of the dynamic yield pressure solution model. ; Risk calculation module: Its purpose is to normalize the assessment of safety margin; in this embodiment, this module is used to perform S4, based on the predicted peak pressure from the pressure calculation module. and real-time physical yield pressure from the yield boundary module The dynamic risk index was calculated. ; State classification module: Its purpose is to map continuous risk values to discrete control states; in this embodiment, this module is used to execute S5, based on the dynamic risk index from the risk calculation module. Preset safety efficiency threshold and preset active defense threshold Determine the pipeline's operational status: efficiency release zone, stable observation zone, or active defense zone. Closed-loop control module: Its purpose is to execute the decisions determined in S5 to achieve a closed loop of safety and efficiency; in this embodiment, this module is used to execute S6 and has three sub-units: Efficiency Release Unit: This unit is used to respond to the state of the efficiency release zone, based on... and Generate efficiency release control commands; Stable observation unit: This unit is used to respond to the stable observation zone state, maintain the current operation, and continuously monitor the dynamic risk index from the risk calculation module; Active defense unit: This unit is used to respond to the state of the active defense zone, based on the hydraulic transient model, real-time physical yield pressure, and active defense threshold. Backtracking calculations generate minimum adjustment control commands; The above are merely preferred embodiments of the present invention and are not intended to limit the present invention; any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the protection scope of the present invention.
[0036] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit it. Although the present invention has been described in detail with reference to preferred embodiments, those skilled in the art should understand that modifications or equivalent substitutions can be made to the technical solutions of the present invention without departing from the spirit and scope of the technical solutions of the present invention.
Claims
1. A method for determining the pressure design of an oil pipeline, characterized in that, include: S1: Collect dynamic operating condition data, and calculate the predicted peak pressure based on the dynamic operating condition data and the preset hydraulic transient model; S2 collects static physical data and material degradation parameters, and combines the static physical data and material degradation parameters to evaluate the real-time physical state factor through a preset empirical degradation model; S3, combining static physical data and real-time physical state factors, determines the real-time physical yield pressure through a dynamic yield pressure calculation model; S4, based on the predicted peak pressure and the real-time physical yield pressure, calculates the dynamic risk index; S5 determines the pipeline's operating status based on the dynamic risk index, preset safety efficiency threshold, and preset active defense threshold. The operating status includes the efficiency release zone, the stable observation zone, and the active defense zone. S6, in response to a determined operating state, performs closed-loop optimization control, including: When the operating state is in the efficiency release zone, an efficiency release control command to increase the average operating pressure is generated based on the real-time physical yield pressure and the safety efficiency threshold. When the operating status is in the stable observation zone, maintain the current operation and continuously monitor the dynamic risk index; When the operating state is in the active defense zone, based on the hydraulic transient model, real-time physical yield pressure and active defense threshold, the minimum adjustment control command to suppress the predicted pressure peak is calculated retrospectively and generated.
2. The method for determining the pressure design of an oil pipeline according to claim 1, characterized in that, Dynamic operating data includes: real-time pressure, flow rate, upstream pump speed, and downstream valve opening along the pipeline.
3. The method for determining the pressure design of an oil pipeline according to claim 1, characterized in that, Static physical data include: pipe design diameter, initial wall thickness, and steel grade.
4. The method for determining the pressure design of an oil pipeline according to claim 1, characterized in that, Material degradation parameters include: wall thickness loss and service life.
5. The method for determining the pressure design of an oil pipeline according to claim 1, characterized in that, In S2, real-time physical state factors are evaluated and obtained through a pre-defined empirical degradation model, including: Calculate the effective wall thickness reduction based on the wall thickness loss and the initial wall thickness; Based on the years of operation and a preset aging weight coefficient, the fatigue aging reduction of materials is calculated using an exponential decay model. The real-time physical state factor is obtained by multiplying the effective wall thickness reduction by the material fatigue aging reduction.
6. The method for determining the pressure design of an oil pipeline according to claim 1, characterized in that, In S3, the real-time physical yield pressure is determined through a dynamic yield pressure calculation model, including: The real-time effective wall thickness is calculated by multiplying the initial wall thickness by the real-time physical state factor. Based on the yield strength corresponding to the steel grade, the real-time effective wall thickness, and the pipe design diameter, the real-time physical yield pressure is obtained by solving the yield formula for thin-walled cylinders.
7. The method for determining the pressure design of an oil pipeline according to claim 1, characterized in that, In S6, when the operating state is in the efficiency release zone, an efficiency release control command is generated, including: The target average operating pressure is determined based on the real-time physical yield pressure at the weakest point along the entire line and the safety efficiency threshold. Generate efficiency release control commands to increase the average operating pressure to the target average operating pressure.
8. The method for determining the pressure design of an oil pipeline according to claim 1, characterized in that, In S6, when the operating state is the active defense zone, a minimum adjustment control command is generated, including: By retracing the hydraulic transient model, the key boundary conditions that lead to the predicted pressure peak are identified. Calculate the minimum adjustment amount for the critical boundary conditions and use the minimum adjustment amount as the minimum adjustment amount control command; The minimum adjustment amount ensures that the new predicted risk index obtained after simulation and correction by the minimum adjustment amount is less than or equal to the active defense threshold.
9. A system for determining the pressure design of an oil pipeline, based on the method for determining the pressure design of an oil pipeline according to any one of claims 1-8, characterized in that, include: The data acquisition module is used to collect dynamic operating condition data, static physical data, and material degradation parameters; The pressure calculation module is used to calculate the predicted peak pressure based on dynamic operating condition data and a preset hydraulic transient model. The condition assessment module is used to combine static physical data and material degradation parameters to evaluate and obtain real-time physical state factors through a preset empirical degradation model. The yield boundary module is used to combine static physical data with real-time physical state factors to determine the real-time physical yield pressure through a dynamic yield pressure calculation model. The risk calculation module is used to calculate the dynamic risk index based on the predicted peak pressure and the real-time physical yield pressure. The status classification module is used to determine the pipeline's operating status based on the dynamic risk index, preset safety efficiency threshold, and preset active defense threshold. The operating status includes the efficiency release zone, the stable observation zone, and the active defense zone. A closed-loop control module is used to perform closed-loop optimization control in response to a determined operating state. The closed-loop control module includes: The efficiency release unit is used to generate an efficiency release control command to increase the average operating pressure based on the real-time physical yield pressure and the safety efficiency threshold when the operating state is in the efficiency release zone. The stable observation unit is used to maintain the current operation and continuously monitor the dynamic risk index when the operating status is in the stable observation zone; The active defense unit is used to backtrack and generate the minimum adjustment control command to suppress the predicted pressure peak when the operating state is in the active defense zone, based on the hydraulic transient model, real-time physical yield pressure and active defense threshold.