Intelligent monitoring and strong discharge method and system for stray current of gas pipeline

Abstract

The present application relates to a kind of intelligent monitoring and strong discharge method and system of gas pipeline stray current, solve the technical problem that cannot effectively dynamic control direct current stray current.System includes: stray current monitoring device, for in the stray current environment of buried pipeline cathodic protection state, the voltage, current data of test piece are monitored simultaneously and packaged as monitoring data;Remote forced drainage equipment, for receiving driving data adjustment output parameter by distributed data link, and feedback operating condition;Strong discharge intelligent control platform, for receiving monitoring data by distributed data link, according to the monitoring data of single stray current monitoring device into the expected driving data of potentiostat by preset feedback correlation model, according to the monitoring data of stray current monitoring device distributed in interference area into the expected driving data of potentiostat by preset linkage response model.Constitute multiple-point, multiple-parameter, synchronous automatic monitoring and intelligent control for pipeline provide technical and equipment support.

Description

Technical Field

[0001] This invention relates to the field of cathodic protection technology for gas pipelines, specifically to an intelligent monitoring and forced drainage method and system for stray currents in gas pipelines. Background Technology

[0002] Urban rail transit systems generally use DC traction and running rail return current. Inevitably, current will leak from the running rail into the ground, forming stray currents that interfere with nearby buried oil and gas pipelines and other metal components. The cathodic protection potential of the affected pipeline will exhibit severe drift with large fluctuations in frequency and amplitude. Existing cathodic protection monitoring equipment generally uses daily timed monitoring to evaluate pipeline protection effectiveness. However, under stray current interference, the pipe body potential will exhibit dynamic fluctuations. Existing constant potential meters for drainage lack the ability to quickly and dynamically respond to stray currents and potentials detected by gas pipeline stray current monitoring equipment, failing to achieve the ideal effect of timely and accurate early warning and adjustment. The main reason is: With the rapid development of technologies such as the Internet, communications, and artificial intelligence, while existing intelligent cathodic protection systems have largely solved the problems of data measurement, transmission, and statistics, they still face challenges in handling the massive dynamic datasets generated by DC interference, which require sampling intervals for pipeline potential and current density to be less than 1s or 5s, or generally 10s to 30s, as stipulated in standards related to DC interference such as GB 50991-2014, SY / T 0087.4-2023, GB / T50698-2011, and SY / T 0087.6-2021. Cathodic protection platforms urgently need efficient algorithms for rapid analysis and processing of these datasets. Existing drainage power supplies, such as potentiostats, still rely on single-point control at the energized point, making it difficult to ensure the uniformity of cathodic protection potential distribution and the effectiveness of protection along the pipeline. At the same time, a dedicated algorithm has not yet been developed that can automatically calculate the adjustment amount of the potentiostat by continuously monitoring the de-energized potential of the test pile. The remote control of the equipment still requires manual assistance to analyze the cathodic protection data of discrete points in the pipeline, manually modify parameters, and issue remote commands. Potentiostats are difficult to achieve real-time and accurate control, resulting in under-protection or over-protection of gas pipelines. Summary of the Invention

[0003] To address the aforementioned problems, embodiments of the present invention provide an intelligent monitoring and forced drainage method and system for stray current in gas pipelines, solving the technical problem that existing monitoring methods cannot effectively and dynamically control DC stray current in pipelines under dynamic interference environments.

[0004] The intelligent monitoring and forced exhaust system for stray current in gas pipelines according to an embodiment of the present invention includes: Stray current monitoring equipment is used to synchronously monitor the voltage and current data of test pieces in a stray current environment under cathodic protection of buried pipelines, and encapsulate the data into monitoring data for uploading via a distributed data link. The remote forced drainage device is used to receive drive data through a distributed data link to adjust the output parameters of the potentiostat and provide feedback on the operating status. The forced drainage intelligent control platform is used to receive monitoring data through a distributed data link, convert the monitoring data of a single stray current monitoring device into the expected driving data of a remote forced drainage device according to a preset feedback correlation model, and convert the monitoring data of stray current monitoring devices distributed in the interference area into the expected driving data of a remote forced drainage device according to a preset linkage response model.

[0005] In one embodiment of the present invention, the forced discharge intelligent control platform includes: A monitoring data database is used for structured storage of real-time monitoring data, drive data, and operating condition data; The single-point feedback correlation module is used to quantify the expected parameters of a single point in the pipeline based on a preset feedback correlation model, and to form the expected driving data for the output parameters of the remote forced drainage equipment. The multi-point linkage response module is used to analyze the expected parameters of multiple points in the pipeline based on the preset linkage response model to form the expected driving data for the output parameters of the remote forced drainage equipment. The intelligent control central system is used to call single-point feedback correlation modules and / or multi-point linkage response modules to process monitoring data, forming a human-computer interaction interface for data display and data configuration.

[0006] The intelligent monitoring and forced drainage method for stray current in gas pipelines according to embodiments of the present invention includes: Within the range of interference of DC stray current on gas pipelines, remote forced drainage devices are installed, and stray current monitoring devices are installed at key locations along the gas pipelines. Control each stray current monitoring device to dynamically collect voltage and current data at each key location, and dynamically collect the operating parameters of the remote forced drainage device. The synchronously packaged voltage and current data and operating parameters are stored in a structured data format to form synchronous monitoring data. For a single critical location, the corresponding synchronous monitoring data is processed using a feedback correlation model to predict subsequent interference data, thereby forming a predictive optimization of the output parameters of the remote forced drainage equipment and forming single-segment protection for the pipeline. For all critical locations, the corresponding predicted subsequent interference data is processed using a linkage response model to form a predictive optimization of the output parameters of the remote forced drainage equipment, thus forming multi-segment protection for the pipeline.

[0007] In one embodiment of the present invention, the key locations include the locations where the pipeline runs parallel to, intersects with, or crosses the DC traction track / running track.

[0008] In one embodiment of the present invention, the voltage and current data include the test piece's on-state potential, the test piece's off-state potential, and the DC current density flowing through the test piece.

[0009] In one embodiment of the present invention, the step of using a feedback correlation model to process the corresponding synchronous monitoring data to predict subsequent interference data and form a prediction optimization of the output parameters of the remote forced drainage device includes: The monitoring data for the next cycle is predicted by processing the monitoring data from previous cycles using the first regression model. The second regression model is used to establish a control mapping relationship between monitoring data and output parameters of remote forced drainage equipment. The second regression model adjusts the output parameters of the remote forced drainage equipment based on the predictive monitoring data, and judges whether the protection effect is achieved at a single critical location based on the power failure potential data in the monitoring data during the adjustment process. The first regression model was optimized based on the protective effect after regulation.

[0010] In one embodiment of the present invention, the first regression model adopts the XGBoost model, and the hyperparameters of the XGBoost model are optimized by the particle swarm optimization (PSO) algorithm. The second regression model adopts one of the linear regression model, ridge regression model, and support vector regression model.

[0011] In one embodiment of the present invention, whether the protection effect is achieved includes: Set up a timed long-term control process and use synchronous monitoring data during the control period to determine whether the gas pipeline is under-protected or over-protected.

[0012] In one embodiment of the present invention, the step of using a linkage response model to process the corresponding predicted subsequent interference data to form a prediction optimization of the output parameters of the remote forced drainage device includes: Determine the predictive monitoring dataset for the next period based on the monitoring data from each stray current monitoring device within the same period; The output parameter set of the remote forced drainage equipment for the next cycle is determined based on the predictive monitoring dataset; The output parameters of the remote forced drainage device for the next cycle are determined based on the maximum value of the parameter in the output parameter set.

[0013] The intelligent monitoring and forced exhaust system for stray current in gas pipelines according to an embodiment of the present invention includes: The node setting device is used to set up remote forced drainage equipment within the interference range of DC stray current on gas pipelines, and to set up stray current monitoring equipment at key locations of gas pipelines. The data storage device is used to control the stray current monitoring devices to dynamically collect voltage and current data at key locations and to dynamically collect the operating parameters of the remote forced drainage device. The synchronously packaged voltage and current data and operating parameters are stored in a structured format to form synchronous monitoring data. Feedback correlation device is used to process the corresponding synchronous monitoring data for a single key location using a feedback correlation model to predict subsequent interference data, thereby forming a predictive optimization of the output parameters of the remote forced drainage equipment and forming single-segment protection of the pipeline. The linkage response device is used to process the corresponding predicted subsequent interference data at all critical locations using the linkage response model, thereby forming a predicted optimization of the output parameters of the remote forced drainage equipment and forming multi-segment protection for the pipeline.

[0014] The intelligent monitoring and forced drainage method and system for stray current in gas pipelines, as described in this invention, integrates real-time synchronous monitoring of multiple pipeline locations to generate expected parameters, while simultaneously achieving intelligent control of stray current in multiple sections. Thus, in a dynamic DC stray current interference environment, the remote forced drainage device and the gas pipeline stray current monitoring device jointly regulate according to expectations, achieving timely and accurate early warning and adjustment effects. This provides technical and equipment support for realizing "multi-point, multi-parameter, synchronous" automatic monitoring and intelligent control of gas pipelines. Attached Figure Description

[0015] Figure 1 The diagram shown is a schematic representation of the architecture of an intelligent monitoring and forced drainage system for stray current in gas pipelines according to an embodiment of the present invention.

[0016] Figure 2 The diagram shown is a schematic diagram of the equipment connection of an intelligent monitoring and forced exhaust system for stray current in gas pipelines according to an embodiment of the present invention.

[0017] Figure 3 The diagram shown is a flowchart illustrating an embodiment of the intelligent monitoring and forced drainage method for stray current in gas pipelines according to the present invention.

[0018] Figure 4 The diagram shown is a schematic representation of the application process of the feedback correlation model in the intelligent monitoring and forced drainage method for stray current in gas pipelines according to an embodiment of the present invention.

[0019] Figure 5 The diagram shown is a schematic representation of the application process of the linkage response model in the intelligent monitoring and forced drainage method for stray current in gas pipelines according to an embodiment of the present invention.

[0020] Figure 6 The diagram shown is a schematic representation of the architecture of an intelligent monitoring and forced drainage system for stray current in gas pipelines according to an embodiment of the present invention.

[0021] Figure 7The diagram shown is a schematic diagram of the architecture of an electronic device according to an embodiment of the present invention. Detailed Implementation

[0022] To further illustrate the technical means and effects of the present invention in achieving its intended purpose, the following detailed description of the specific implementation methods, structures, features, and effects of the present invention, in conjunction with the accompanying drawings and preferred embodiments, is provided below.

[0023] An embodiment of the present invention provides an intelligent monitoring and forced exhaust system for stray current in gas pipelines, as follows: Figure 1 As shown. In Figure 1 In this embodiment, the following are included: The stray current monitoring device 100 is used to synchronously monitor the voltage and current data of the test piece in a stray current environment under cathodic protection of buried pipelines, and encapsulate the data into monitoring data for uploading via a distributed data link.

[0024] Those skilled in the art will understand that stray current environment mainly refers to the strong DC stray current environment experienced by buried pipelines parallel to or intersecting with the DC traction tracks of rail transit facilities such as subways and light rails. Voltage and current data include the monitored test piece's on-state potential, off-state potential, and DC current density flowing through the test piece. Monitoring data can accurately determine the effectiveness of cathodic protection (based on the test piece's off-state potential). The stray current interference section can be precisely located based on the coordinates of the monitoring equipment, serving as feedback input for the closed-loop control of the stray current suppression device. The monitoring synchronization period can be preset or adjusted according to the threshold deviation trend of various data types. The data link is constructed using common communication technologies, such as 4G / 5G, WiFi, or LoRa. An integrated structure is used to integrate relevant monitoring equipment and power supplies, and a unified scheduling synchronization control mechanism maintains microsecond to millisecond-level instantaneous power outages and sampling, ensuring the accuracy and reliability of the power outage potential data. The monitoring data is synchronously transmitted by encapsulating various data types in a time sequence.

[0025] The remote forced drainage device 200 is used to receive drive data through a distributed data link to adjust the output parameters of the potentiostat and provide feedback on the operating status.

[0026] Those skilled in the art will understand that existing (forced drainage) potentiostats typically only collect the potential near the anode output, at the energized point, to adjust their output current. Since the energized point is itself at a high-current output port, soil resistance and current field distortion lead to a significant IR drop, and stray currents further cause drastic potential jumps and distortions. This makes the fundamental error of the potentiostat control uncontrollable and unable to compensate for and protect pipelines at remote locations, bends, crossings, or in high-resistance areas. By establishing a data link for the potentiostat to continuously receive advanced-processed drive data, timely adjustments to the potentiostat's output parameters are achieved, allowing key output parameters such as output voltage and current to respond based on the comprehensiveness of the data processed in the advanced process. In one embodiment of this invention, the response hysteresis does not exceed 10 seconds. Real-time feedback of the operating status of voltage and current output parameters via the data link effectively provides controlled state feedback for the potentiostat, quantifying the output effect of the controlled equipment.

[0027] The forced drainage intelligent control platform 300 is used to receive monitoring data through a distributed data link, convert the monitoring data of a single stray current monitoring device into expected driving data of a remote forced drainage device according to a preset feedback correlation model, and convert the monitoring data of stray current monitoring devices distributed in the interference area into expected driving data of a remote forced drainage device according to a preset linkage response model.

[0028] Those skilled in the art will understand that the forced-discharge intelligent control platform possesses computing power, storage resources, and network communication resources. It continuously receives monitoring data from various stray current monitoring devices in the stray current interference environment via network resources, systematically stores the monitoring data using storage resources, and processes the monitoring data using specific pre-set models using computing power resources to predict single or comprehensive protection states, generating corresponding pipe segment drive data, which is then distributed to the potentiostat in a timely manner via network resources. Simultaneously, a control center system for human-machine interaction is formed using computing power resources to display monitoring data and configure drive parameters for manual intervention. Specifically, a pre-set feedback correlation model is used to calculate the quantitative relationship between the expected parameters at a single location point on the pipeline and the expected output parameters of the potentiostat. A pre-set linkage response model is used to determine the quantitative relationship between the expected parameters at multiple locations on the pipeline and the expected output parameters of the potentiostat.

[0029] The intelligent monitoring and forced drainage system for stray current in gas pipelines of this invention integrates real-time synchronous monitoring of multiple pipeline locations to generate expected parameters, while simultaneously achieving intelligent control of stray current in multiple sections. Thus, under dynamic DC stray current interference environments, the potentiostat and the gas pipeline stray current monitoring equipment jointly regulate the system according to expectations, achieving timely and accurate early warning and adjustment. This realizes integrated control of stray current at multiple locations and intelligent regulation of forced drainage equipment, providing technical and equipment support for the "multi-point, multi-parameter, synchronous" automatic monitoring and intelligent control of gas pipelines.

[0030] like Figure 1 As shown, in one embodiment of the present invention, the forced discharge intelligent control platform 300 includes: Monitoring data database 310 is used for structured storage of real-time monitoring data, drive data, and operating condition data.

[0031] Relational databases are used to structure and store time-series monitoring data and related data, and the response efficiency of database technology is used to achieve real-time storage, request and operation.

[0032] The single-point feedback correlation module 320 is used to quantify the expected parameters of a single point in the pipeline according to the preset feedback correlation model, and form the expected driving data of the output parameters of the remote forced drainage equipment.

[0033] To address real-time interference at a single location point, a real-time monitoring data processing procedure is established for that location point. This procedure involves calculating the expected monitoring values ​​for the next acquisition cycle, thus generating the expected driving data processing.

[0034] The multi-point linkage response module 330 is used to analyze the expected parameters of multiple locations in the pipeline based on the preset linkage response model to form the expected driving data for the output parameters of the remote forced drainage equipment.

[0035] To address interference from multiple locations, a real-time monitoring data processing procedure is implemented, involving the calculation of expected monitoring values ​​for multiple locations in the next acquisition cycle, resulting in the anticipated comprehensive driving data processing. This process optimizes the maximum protection range and effectiveness.

[0036] The intelligent control central system 340 is used to call the single-point feedback correlation module and / or multi-point linkage response module to process monitoring data and form a human-computer interaction interface for data display and data configuration.

[0037] The intelligent control hub system is deployed in the form of an application. The monitoring data acquisition process, the real-time monitoring data processing process at single and multiple locations, and the driving data formation process are displayed in an orderly manner in the human-machine interface. At the same time, it provides control interfaces for data display and interactive interfaces for driving data configuration.

[0038] The intelligent monitoring and forced exhaust system for stray current in gas pipelines in this embodiment of the invention forms a modular intelligent control hub system through resource and functional encapsulation. This ensures the real-time performance and high scalability of data acquisition and processing.

[0039] An embodiment of the present invention provides an intelligent monitoring and forced exhaust system for stray current in gas pipelines, as follows: Figure 2 As shown. In Figure 2 In this embodiment, the stray current monitoring device 100 is based on existing intelligent cathodic protection test piles, adopts mature insulation, wiring, and fixing methods, and also includes: Reference electrode 110 is used to provide a stable reference potential, providing a comparison benchmark for the measurement of tube-to-ground potential, on-state potential, and off-state potential; Self-corrosion test piece 120 is used to monitor the natural corrosion rate; it is made of the same material as the pipe and the exposed area follows standard specifications. Replaceable polarization test piece 130, used for measuring on-current / off-current potential; made of the same material as the pipe and with exposed area conforming to standard specifications; The ER corrosion probe 140 is used for real-time monitoring of corrosion rate and quantification of stray current corrosion tendency; it is buried at the same depth, on the same plane, and at intervals with the self-corroding test piece. Stray current test piece 150 is used to determine the intensity of stray current inflow / outflow based on current density. It is made of the same material and has the same area as the self-corroding test piece, and its current density is measured independently for stray current risk assessment. Different types of test pieces are used in conjunction with built-in or external electrical control measuring instruments in existing test piles to form an orderly measurement process and cycle.

[0040] The underground layout of each test piece, probe, and electrode forms a specific distribution pattern based on the reference electrode. For example... Figure 2 As shown, in one embodiment of the present invention, on the same side of the intelligent test post for cathodic protection of the pipeline, a reference electrode 110 is set at the same depth as the pipeline, 50-70 cm away from the pipeline. Each test piece and probe is configured in pairs, symmetrically arranged on both sides of the reference electrode 110 with the reference electrode 110 as the center along the pipeline direction, with the adjacent spacing of each test piece and probe maintained at 50-70 cm. The test piece or probe can be synchronously selected for availability by forming a signal feedback switch for the uplink signal line through a controlled switching circuit. The on / off control methods of the controlled switching circuit mainly include electromagnetic relays, MOSFETs, solid-state relays, etc., to orderly control the test pieces and probes on the same side of the reference electrode 110. By orderly switching the test pieces and probes on both sides of the reference electrode 110, signal verification between the two sets of test pieces and probes on both sides at the same setting depth can be formed, improving the signal acquisition accuracy and reliability.

[0041] In one embodiment of the present invention, a set of sensing devices consists of test pieces or probes arranged in pairs along the pipeline direction on both sides of the reference electrode 110. At least two other sets of sensing devices are set at the same depth as the reference electrode. The first set of sensing devices is 50 cm away from the pipeline, the second set is 90 cm away from the pipeline, and the third set is 120 cm away from the pipeline. Alternatively, the distances between each set of sensing devices and the pipeline are progressively smaller. By utilizing the differences in distance between each set of sensing devices and the pipeline, the availability is synchronously selected through a corresponding controlled switching circuit. This obtains the regional monitoring directionality within the area affected by stray current interference, forming a quantitative basis for the error within the regional area, providing a quantitative basis for excluding soil factors, and improving the accuracy and reliability of signal acquisition.

[0042] like Figure 2 As shown, in one embodiment of the present invention, the stray current monitoring device 100 includes: The public network communication module 160 is used to access the public wireless network and maintain the communication link, periodically uploading the monitoring data collected and packaged by the cathodic protection smart test pile. The public network communication module can adopt a 4G / 5G communication module, and the communication connection can be controlled through the existing signal processing module of the cathodic protection smart test pile, which can control the data encryption and transmission period definition in the communication link.

[0043] The solar module 170 is used to generate and store electrical energy through photovoltaic conversion. The solar module utilizes a common product series to ensure efficient conversion, storage, and power supply of solar energy.

[0044] like Figure 2 As shown, in one embodiment of the present invention, the remote forced drainage device 200 is based on an existing forced drainage potentiostat, employing mature insulation, wiring, and fixing methods, and further includes: The two-way communication module 210 is used to access the public wireless network and maintain the communication link as needed, receive drive data, and provide feedback on operating condition data. The two-way communication module can adopt a 4G / 5G communication module, and the communication connection, data reception, and data feedback are controlled by the existing signal processing module of the potentiostat.

[0045] The potentiostat is directly connected to a 220V AC power supply. The power supply motherboard converts it into a DC regulated power supply. The positive terminal of the regulated power supply output is connected to the anode ground bed, and the negative terminal is connected to the pipeline.

[0046] like Figure 2 As shown, in one embodiment of the present invention, the forced discharge intelligent control platform 300 includes a general-purpose server, and further includes: The broadband communication module 350 is used to access the broadband network, maintain the communication link, receive drive data and operating status data, and send drive data. The broadband communication module can be a 4G / 5G communication module or a gigabit LAN card. It integrates and extends the communication link between the public wireless network and the local basic broadband network, enabling the converged transmission of distributed high-frequency data.

[0047] Depending on the deployment environment of Runjian, the general-purpose servers include: The data processing server 360 is used to deploy firewalls and databases. One side of the broadband communication module establishes a data link with the router of the broadband network, and the other side of the broadband communication module establishes a data link with the database through the firewall.

[0048] The control center server 370 is used to deploy a data processing framework, a data display framework, and a human-machine interface. The data processing framework accesses the database to process monitoring data and feedback operational data. The data display framework transforms the processed data into graphical data. The human-machine interface processes the graphical data to create a user interface that controls the display of monitoring data and the configuration of driving data. In one embodiment of the invention, the data processing framework uses Lodash, the data display framework uses Chart.js, and the human-machine interface uses a general-purpose touchscreen or an authorized tablet computer.

[0049] By providing a two-tier server architecture, the control permissions for data acquisition, fusion, and access are separated from the data processing permissions for device driving, display, and interaction, forming a relatively independent control area. This ensures the security of automated data acquisition and the human controllability of device feedback-driven control within the automatic control closed loop.

[0050] An embodiment of the present invention provides an intelligent monitoring and forced drainage method for stray current in gas pipelines, as follows: Figure 3 As shown. In Figure 3 In this embodiment, the following are included: Step 400: Within the range of interference of DC stray current on the gas pipeline, install remote forced drainage equipment and stray current monitoring equipment at key locations along the gas pipeline.

[0051] Within the interference range of DC stray currents, remote forced drainage devices are installed according to the principles of uniform protection potential, reduced protection blind zones, and lower total current demand. Based on the parallel, intersecting, or crossing patterns of pipelines with DC traction tracks / running rails, key locations prone to stray current interference are identified, and stray current monitoring devices are installed. These stray current monitoring devices form distributed monitoring data acquisition nodes within the interference range.

[0052] Step 500: Control each stray current monitoring device to dynamically collect voltage and current data at each key location, and dynamically collect the operating parameters of the remote forced drainage device. Store the synchronously packaged voltage and current data and operating parameters in a structured format to form synchronous monitoring data.

[0053] Dynamic data acquisition is generated according to a preset period, and the period can be dynamically acquired based on the interference intensity of stray currents. Voltage and current data at key locations include, but are not limited to, the energized potential of the test piece, the de-energized potential of the test piece, and the DC current density flowing through the test piece. The output voltage and current of remote forced drainage equipment are easily affected by soil resistance and current field distortion, causing the output parameters to often fail to reflect the true potential. Acquiring the output voltage and current of remote forced drainage equipment can provide feedback on operating parameters. Encapsulating and structured storing the voltage and current data at each key location and the operating parameters of the remote forced drainage equipment according to time sequence can obtain dynamic interference data on the distribution of DC stray currents within the interference range, forming monitoring data and providing a comprehensive data foundation for subsequent protection optimization.

[0054] Step 600: For a single critical location, use the feedback correlation model to process the corresponding synchronous monitoring data to predict subsequent monitoring data, form a prediction optimization of the output parameters of the remote forced drainage equipment, and form single-segment protection of the pipeline.

[0055] Those skilled in the art will understand that dynamic interference from stray DC currents within the interference range can persist at a single critical location. For pipeline protection at a single critical location, a feedback correlation model is used to process real-time monitoring data and optimize the predicted output parameters of remote forced drainage equipment. This ensures that the pipeline protection potential at the critical location remains stable within the threshold range, avoiding tracking lag.

[0056] Step 700: For all critical locations, use the linkage response model to process the corresponding predicted subsequent monitoring data, form the predicted optimization of the output parameters of the remote forced drainage equipment, and form multi-segment protection of the pipeline.

[0057] Based on pipeline protection at a single critical location, a linkage response model is used to comprehensively consider the dynamic interference at each critical location within the stray current interference range. Based on the predicted output parameters of the corresponding remote forced drainage device formed by monitoring data, the output parameters of the remote forced drainage device at the next moment are formed according to the maximum value in the data set of each predicted output parameter. This enables the gas pipeline within the interference range to be protected at multiple points, and realizes intelligent monitoring and forced drainage of stray current in the gas pipeline.

[0058] The intelligent monitoring and forced drainage method for stray current in gas pipelines in this invention senses the dynamic changes of stray current by collecting monitoring data at key locations. It then predicts the output parameters of remote forced drainage equipment based on the monitoring data to form dynamic pipeline protection in response to these dynamic changes. Simultaneously, it establishes a flexible adaptive mechanism to meet the protection needs of different pipeline sections within the range of DC stray current interference. This achieves integrated monitoring and control, effectively reducing the corrosion risk of gas pipelines in dynamic DC stray current interference environments.

[0059] The application process of feedback correlation model in intelligent monitoring and forced exhaust methods for stray current in gas pipelines is as follows: Figure 4 As shown. Combined with Figure 3 and Figure 4 As shown, in one embodiment of the present invention, step 600, the processing procedure of the feedback correlation model includes: Step 610: Based on the first regression model, process the previous period monitoring data to predict the next period monitoring data.

[0060] In one embodiment of the present invention, the first regression model employs an XGBoost model. The hyperparameters of XGBoost (such as learning rate, tree depth, and subsample ratio) are optimized using a particle swarm optimization (PSO) algorithm to improve prediction accuracy and generalization ability. The XGBoost model is trained using historical monitoring data to learn the temporal patterns and nonlinear relationships between variables in the historical data. This ultimately forms a prediction of the next period's monitoring data based on previous periodic monitoring data. The predicted monitoring data generated by the first regression model serves as the feedforward control input for the subsequent control strategy of the potentiostat. Figure 3 As shown, the first regression model is used to predict the test piece potential (energized / de-energized) and current density in the next cycle by using historical time-series data of the monitoring data of the previous nine cycles (such as the test piece energized potential, the test piece de-energized potential, the DC current density flowing through the test piece, and the output current of the potentiostat).

[0061] Step 620: Based on the second regression model, establish the regulation mapping relationship between the monitoring data and the output parameters of the remote forced drainage equipment.

[0062] In one embodiment of the present invention, the second regression model employs regression models such as linear regression, ridge regression, and support vector regression to form a functional relationship fit between deterministic variables, utilizing R... 2 The mean squared error is used to evaluate model performance and ensure the accuracy and reliability of the regression relationship. For example... Figure 3 As shown, in one embodiment of the present invention, a quantitative relationship is formed among the test piece de-energization potential, the output current of the potentiostat, and the test piece current density, and a mapping model from protection state to control action is constructed.

[0063] Step 630: The second regression model adjusts the output parameters of the remote forced drainage equipment based on the predicted monitoring data, and judges whether the protection effect is achieved at a single key location based on the power failure potential data in the monitoring data during the adjustment process.

[0064] like Figure 4 As shown, the determination of the power-off potential data of the target sample in the synchronous monitoring data of the control process is based on -0.85V. CSE ~ -1.20V CSE The required output current of the potentiostat can be deduced from the power-off potential, or the protection potential can be determined based on the current. In one embodiment of the invention, a 5-minute control process is set, and synchronous monitoring data during the control period is used to determine whether the gas pipeline is under-protected or over-protected.

[0065] Step 640: Optimize the first regression model based on the protective effect after regulation.

[0066] If most of the power outage potentials in the monitoring data collected during the control process are outside the protection range, the parameters of the first regression model will be retrained and adjusted based on the newly collected monitoring data.

[0067] After adjusting the parameters, the first regression model adjusts the output parameters of the potentiostat based on the newly predicted monitoring data. Optimization ends when the power failure potential measured by the stray current monitoring device is within the protection range.

[0068] The intelligent monitoring and forced drainage method for stray currents in gas pipelines in this invention utilizes two regression models in synergy to predict the output current of the potentiostat in the next moment. The first regression model predicts the test piece potential and current density for the next cycle to clarify future protection requirements, while the second regression model calculates the current value that the potentiostat needs to output to meet these requirements. This achieves proactive and precise control of the cathodic protection system, effectively suppressing stray current interference and ensuring pipeline safety.

[0069] The application process of the linkage response model in the intelligent monitoring and forced exhaust method of stray current in gas pipelines is as follows: Figure 5 As shown. Combined with Figure 3 and Figure 5 As shown, in one embodiment of the present invention, step 700, the processing procedure of the linkage response model includes: Step 710: Determine the predictive monitoring dataset for the next period based on the monitoring data from each stray current monitoring device within the same period.

[0070] The set of predicted monitoring data for each key location within the interference area in the next cycle is obtained based on the first regression model. Figure 5 In the same period, each key location uses the corresponding previous monitoring data to predict the predicted monitoring data for the next period.

[0071] Step 720: Determine the output parameter set of the remote forced drainage device for the next cycle based on the predictive monitoring dataset.

[0072] The set of corresponding output parameters of the potentiostat at each key location within the interference area in the next cycle is obtained based on the second regression model. Figure 5 In this process, based on the predicted monitoring data of each key location in the next cycle, the corresponding output parameters (U) of the potentiostat at each key location in the next cycle are generated. n I n ), n=1,2,3,...,n. The output parameters of the potentiostat required to overcome stray current at the nth critical position, including potential and current values.

[0073] Step 730: Determine the output parameters of the remote forced drainage device for the next cycle based on the maximum value of the parameters in the output parameter set.

[0074] In the output parameter set, the output parameters of the remote forced drainage device for the next cycle are formed based on the maximum value of each type of parameter. This provides multi-point protection for the gas pipeline within the interference range, enabling intelligent monitoring and forced drainage of stray currents in the gas pipeline. Figure 5 In the next cycle, the output parameters for effective protection of each critical location (pipe segment) within the interference range are as follows: I = max(I1, I2, I3, ..., I n ) U = max(U1, U2, U3, ..., U n ) The intelligent monitoring and forced drainage method for stray current in gas pipelines in this embodiment of the invention utilizes the output parameters of remote forced drainage devices at key locations to form an output parameter envelope for large-scale protection of multiple pipeline segments, ensuring timely anti-interference and high-efficiency energy saving during periodic regulation.

[0075] An embodiment of the present invention provides an intelligent monitoring and forced exhaust system for stray current in gas pipelines, as follows: Figure 6 As shown. In Figure 4 In this embodiment, the following are included: The node setting device 40 is used to set up a remote forced drainage device within the interference range of DC stray current on the gas pipeline, and to set up stray current monitoring devices at key locations of the gas pipeline. Data storage device 50 is used to control each stray current monitoring device to dynamically collect voltage and current data at each key location, and to dynamically collect operating parameters of the remote forced drainage device. It performs structured data storage on the synchronously packaged voltage and current data and operating parameters to form synchronous monitoring data. Feedback correlation device 60 is used to process the corresponding synchronous monitoring data for a single key location using a feedback correlation model to predict subsequent interference data, thereby forming a predictive optimization of the output parameters of the remote forced drainage equipment and forming single-segment protection of the pipeline. The linkage response device 70 is used to process the corresponding predicted subsequent interference data for all critical locations using the linkage response model, thereby forming a predicted optimization of the output parameters of the remote forced drainage equipment and forming multi-segment protection for the pipeline.

[0076] like Figure 5 As shown, in one embodiment of the present invention, the feedback correlation device 60 includes: The monitoring data prediction module 61 is used to process the monitoring data of the previous period according to the first regression model to predict the monitoring data of the next period. The output parameter mapping module 62 is used to form a control mapping relationship between monitoring data and output parameters of the remote forced drainage device based on the second regression model. The output parameter prediction module 63 is used by the second regression model to adjust the output parameters of the remote forced drainage equipment according to the predicted monitoring data, and to determine whether the protection effect of a single key position is achieved based on the power failure potential data in the monitoring data during the adjustment process. The monitoring, prediction and optimization module 64 is used to optimize the first regression model based on the protection effect after regulation.

[0077] like Figure 6 As shown, in one embodiment of the present invention, the linkage response device 70 includes: The single prediction fusion module 71 is used to determine the prediction monitoring dataset for the next period formed by the monitoring data of each stray current monitoring device within the same period. A single output fusion module 72 is used to determine the output parameter set of the remote forced drainage device for the next cycle based on the predictive monitoring dataset; The fusion output quantization module 73 is used to determine the output parameters of the remote forced drainage device for the next cycle based on the maximum value of the parameters in the output parameter set.

[0078] This application also provides an electronic device, the structure of which is as follows: Figure 7 As shown, the electronic device 4000 includes at least one processor 4001, a memory 4002, and a bus 4003. At least one processor 4001 is electrically connected to the memory 4002. The memory 4002 is configured to store at least one computer-executable instruction, and the processor 4001 is configured to execute the at least one computer-executable instruction to perform the steps of the intelligent monitoring and forced drainage method for stray current in gas pipelines provided in any embodiment or optional implementation of this application.

[0079] Furthermore, the processor 4001 can be an FPGA (Field-Programmable Gate Array) or other devices with logic processing capabilities, such as an MCU (Microcontroller Unit) or a CPU (Central Processing Unit).

[0080] This application also provides another computer-readable storage medium storing a computer program that, when executed by a processor, implements the steps of the intelligent monitoring and forced drainage method for stray current in gas pipelines provided in any embodiment or optional implementation of this application.

[0081] The computer-readable storage media provided in this application include, but are not limited to, any type of disk (including floppy disk, hard disk, optical disk, CD-ROM, and magneto-optical disk), ROM (Read-Only Memory), RAM (Random Access Memory), EPROM (Erasable Programmable Read-Only Memory), EEPROM (Electrically Erasable Programmable Read-Only Memory), flash memory, magnetic cards, or optical cards. In other words, readable storage media include any medium by which a device (e.g., a computer) stores or transmits information in a readable form.

[0082] The above description is merely a preferred embodiment of the present invention and is not intended to limit the present invention in any way. Although the present invention has been disclosed above with reference to preferred embodiments, it is not intended to limit the present invention. Any person skilled in the art can make some modifications or alterations to the above-disclosed technical content to create equivalent embodiments without departing from the scope of the present invention. Any simple modifications, equivalent changes and alterations made to the above embodiments based on the technical essence of the present invention without departing from the scope of the present invention shall still fall within the scope of the present invention.

Claims

1. An intelligent monitoring and forced exhaust system for stray current in gas pipelines, characterized in that, include: Stray current monitoring equipment is used to synchronously monitor the voltage and current data of test pieces in a stray current environment under cathodic protection of buried pipelines, and encapsulate the data into monitoring data for uploading via a distributed data link. The remote forced drainage device is used to receive drive data through a distributed data link to adjust the output parameters of the potentiostat and provide feedback on the operating status. The forced drainage intelligent control platform is used to receive monitoring data through a distributed data link, convert the monitoring data of a single stray current monitoring device into the expected driving data of a remote forced drainage device according to a preset feedback correlation model, and convert the monitoring data of stray current monitoring devices distributed in the interference area into the expected driving data of a remote forced drainage device according to a preset linkage response model.

2. The intelligent monitoring and forced drainage system for stray current in gas pipelines according to claim 1, characterized in that, The forced discharge intelligent control platform includes: A monitoring data database is used for structured storage of real-time monitoring data, drive data, and operating condition data; The single-point feedback correlation module is used to quantify the expected parameters of a single point in the pipeline based on a preset feedback correlation model, and to form the expected driving data for the output parameters of the remote forced drainage equipment. The multi-point linkage response module is used to analyze the expected parameters of multiple points in the pipeline based on the preset linkage response model to form the expected driving data for the output parameters of the remote forced drainage equipment. The intelligent control central system is used to call single-point feedback correlation modules and / or multi-point linkage response modules to process monitoring data, forming a human-computer interaction interface for data display and data configuration.

3. A method for intelligent monitoring and forced drainage of stray current in gas pipelines, characterized in that, include: Within the range of interference of DC stray current on gas pipelines, remote forced drainage devices are installed, and stray current monitoring devices are installed at key locations along the gas pipelines. Control each stray current monitoring device to dynamically collect voltage and current data at each key location, and dynamically collect the operating parameters of the remote forced drainage device. The synchronously packaged voltage and current data and operating parameters are stored in a structured data format to form synchronous monitoring data. For a single critical location, the corresponding synchronous monitoring data is processed using a feedback correlation model to predict subsequent interference data, thereby forming a predictive optimization of the output parameters of the remote forced drainage equipment and forming single-segment protection for the pipeline. For all critical locations, the corresponding predicted subsequent interference data is processed using a linkage response model to form a predictive optimization of the output parameters of the remote forced drainage equipment, thus forming multi-segment protection for the pipeline.

4. The intelligent monitoring and forced drainage method for stray current in gas pipelines according to claim 3, characterized in that, The key locations include those where pipelines run parallel to, intersect with, or cross DC traction tracks / running rails.

5. The intelligent monitoring and forced drainage method for stray current in gas pipelines according to claim 3, characterized in that, The voltage and current data include the test piece's on-state potential, the test piece's off-state potential, and the DC current density flowing through the test piece.

6. The intelligent monitoring and forced drainage method for stray current in gas pipelines according to claim 3, characterized in that, The step of using a feedback correlation model to process the corresponding synchronous monitoring data to predict subsequent interference data and form a predictive optimization of the output parameters of the remote forced drainage device includes: The monitoring data for the next cycle is predicted by processing the monitoring data from previous cycles using the first regression model. The second regression model is used to establish a control mapping relationship between monitoring data and output parameters of remote forced drainage equipment. The second regression model adjusts the output parameters of the remote forced drainage equipment based on the predictive monitoring data, and judges whether the protection effect is achieved at a single critical location based on the power failure potential data in the monitoring data during the adjustment process. The first regression model was optimized based on the protective effect after regulation.

7. The intelligent monitoring and forced drainage method for stray current in gas pipelines according to claim 6, characterized in that, The first regression model uses the XGBoost model, and the hyperparameters of the XGBoost model are optimized by the particle swarm optimization (PSO) algorithm. The second regression model uses one of the following: linear regression model, ridge regression model, and support vector regression model.

8. The intelligent monitoring and forced drainage method for stray current in gas pipelines according to claim 3, characterized in that, Whether the protection effect is achieved includes: Set up a timed long-term control process and use synchronous monitoring data during the control period to determine whether the gas pipeline is under-protected or over-protected.

9. The intelligent monitoring and forced drainage method for stray current in gas pipelines according to claim 8, characterized in that, The process of using a linkage response model to process the corresponding predicted subsequent interference data to form a prediction optimization of the output parameters of the remote forced drainage device includes: Determine the predictive monitoring dataset for the next period based on the monitoring data from each stray current monitoring device within the same period; The output parameter set of the remote forced drainage equipment for the next cycle is determined based on the predictive monitoring dataset; The output parameters of the remote forced drainage device for the next cycle are determined based on the maximum value of the parameter in the output parameter set.

10. An intelligent monitoring and forced exhaust system for stray current in gas pipelines, characterized in that, include: The node setting device is used to set up remote forced drainage equipment within the interference range of DC stray current on gas pipelines, and to set up stray current monitoring equipment at key locations of gas pipelines. The data storage device is used to control the stray current monitoring devices to dynamically collect voltage and current data at key locations and to dynamically collect the operating parameters of the remote forced drainage device. The synchronously packaged voltage and current data and operating parameters are stored in a structured format to form synchronous monitoring data. Feedback correlation device is used to process the corresponding synchronous monitoring data for a single key location using a feedback correlation model to predict subsequent interference data, thereby forming a predictive optimization of the output parameters of the remote forced drainage equipment and forming single-segment protection of the pipeline. The linkage response device is used to process the corresponding predicted subsequent interference data at all critical locations using the linkage response model, thereby forming a predicted optimization of the output parameters of the remote forced drainage equipment and forming multi-segment protection for the pipeline.

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