Efficient anti-freezing and anti-blocking integrated induction heating system and method for oil and gas pipeline

Abstract

The invention discloses an efficient anti-freezing and anti-blocking integrated induction heating system and method for an oil and gas pipeline, belongs to the technical field of anti-freezing and anti-blocking of oil and gas pipelines, and aims at solving the problems that in the prior art, heating efficiency is low, energy consumption is huge, heating uniformity and adaptability are poor, the system integration degree is low, and the intelligent degree is insufficient. Comprising the steps of S1, induction heating unit arrangement and power management; s2, real-time temperature monitoring and data acquisition; s3, intelligent data analysis and precise heat management; the electromagnetic induction heating principle is adopted, the induction coil directly heats the pipeline and the internal medium, heat conduction loss and heat energy radiation loss of heating modes such as traditional resistance wires and heat tracing bands are reduced, the intelligent power management module can optimize power supply and power adjustment, and the self-adaptive environment and load adjustment strategy is combined, so that the self-adaptive load adjustment is achieved. The heating power can be automatically adjusted according to the environment temperature and the pipeline load, the anti-freezing and anti-blocking effect is guaranteed, meanwhile, energy consumption is remarkably reduced, and the burden of an electric power supply system is relieved.

Description

Technical Field

[0001] The present invention belongs to the technical field of anti-freezing and blocking of oil and gas pipelines, and in particular relates to an integrated induction heating system and method for efficiently preventing freezing and blocking of oil and gas pipelines. Background Art

[0002] With the increasing global demand for energy, oil and natural gas, as important energy resources, are widely used in many fields such as industry, transportation, and energy. However, during the transportation of oil and gas pipelines, due to changes in ambient temperature, especially in cold areas or in winter, the oil and gas in the pipelines are often affected by temperature, resulting in solidification, freezing, blockage and other problems. These problems not only affect the normal transportation of oil and gas, but may also cause safety hazards such as pipeline rupture, oil leakage, equipment damage, and even cause environmental pollution. Therefore, how to effectively prevent the freezing and blockage of oil and gas pipelines in cold conditions has become a key technical issue in oil and gas pipeline transportation.

[0003] Although the existing technology can play an anti-freeze role through electric belt heating, hot water steam heating and thermal circulation devices, it still has the following defects and shortcomings:

[0004] 1. Low heating efficiency and huge energy consumption: Traditional heating methods such as resistance wire heating, heating tape or steam heating have significant heat conduction loss and heat radiation loss. High energy consumption means that more complex power supply and monitoring communication systems are required, which increases system complexity and communication burden.

[0005] 2. Poor heating uniformity and adaptability: There is a lack of real-time, refined perception of parameters such as the temperature at key points in the pipeline and the medium status, as well as data-based intelligent control capabilities. The communication system is mainly used for simple status feedback and fails to effectively support closed-loop, on-demand precise thermal management.

[0006] 3. Low system integration and insufficient intelligence: Traditional heating systems are usually composed of multiple independent components installed on-site in a decentralized manner with complex wiring. The existing system lacks an efficient data acquisition network, edge and cloud collaborative computing capabilities, and intelligent decision-making remote control communication architecture. It is unable to achieve the efficient data interaction, centralized management and intelligent applications required by the integrated system, limiting the system's remote operation and maintenance and intelligence level.

[0007] Therefore, an efficient integrated induction heating system and method for preventing freezing and blockage of oil and gas pipelines is needed to solve the problems of low heating efficiency, huge energy consumption, poor heating uniformity and adaptability, low system integration and insufficient intelligence in the existing technology. Summary of the Invention

[0008] The object of the present invention is to provide an integrated induction heating system and method for preventing freezing and blocking of oil and gas pipelines in order to solve the problems raised in the above-mentioned background technology.

[0009] To achieve the above objectives, the present invention provides the following technical solution: an integrated induction heating system and method for preventing freezing and blocking of oil and gas pipelines, comprising the following steps:

[0010] S1. Induction Heating Unit Layout and Power Management: Multiple induction heating units are evenly arranged outside the oil and gas pipeline. Each induction heating unit consists of an induction coil and directly heats the pipeline and the medium inside the pipeline through the principle of electromagnetic induction heating. The intelligent power management module optimizes the power supply and power regulation of the heating units.

[0011] S2. Real-time temperature monitoring and data acquisition: Multiple temperature sensors are deployed at key locations on oil and gas pipelines to monitor the pipeline surface temperature and the temperature of the medium inside the pipeline in real time. Each sensor transmits data to the central control unit via a wireless network, building an efficient data acquisition network. The system also monitors relevant parameters such as ambient temperature and pipeline pressure, providing accurate real-time data support.

[0012] S3. Intelligent Data Analysis and Precision Thermal Management: The central control unit uses edge computing technology to analyze and process real-time temperature data and pipeline media conditions, dynamically adjusting the heating power and operating mode of each induction heating unit. The system uses intelligent algorithms to optimize thermal management strategies and achieve personalized heating for different pipeline areas and conditions.

[0013] S4. Automatic closed-loop feedback control: During the heating process, the system adjusts the heating power of the induction heating unit in real time through the feedback data provided by the temperature sensor. The system implements closed-loop control based on the dynamic changes of the temperature difference between the inside and outside of the pipeline and the medium state.

[0014] S5. Intelligent remote control and early warning: The system implements comprehensive remote monitoring and control through a centralized management platform and remote communication network. Users can view the heating status of oil and gas pipelines through PC terminals and remotely adjust heating parameters. The system automatically detects and reports potential faults during operation, notifying maintenance personnel in advance. Troubleshooting or parameter adjustments can also be performed remotely.

[0015] S6. System Integration and Intelligent Decision-Making: With an integrated design, all heating units, temperature sensors, control units, and communication equipment are integrated into the same system architecture, reducing the complexity of on-site wiring. Through collaborative computing between edge computing and the cloud, the system's computing power and intelligent decision-making capabilities are enhanced. The cloud platform aggregates and analyzes data from the entire system, provides optimization suggestions, and supports historical data storage and subsequent optimization.

[0016] S7, Adaptive environment and load regulation: The system automatically adjusts the heating strategy according to changes in ambient temperature and pipeline load. When the ambient temperature is low, the system will automatically increase the heating power to prevent the pipeline from freezing; when the load is light, the system will reduce the heating power to save energy.

[0017] S8. Redundancy and fault switching: The key components of the system adopt a redundant design. When a system component fails, other components can automatically take over its function to ensure uninterrupted heating process. The fault diagnosis system automatically switches to the backup system when an abnormality occurs and notifies the user to repair it.

[0018] It should be noted in the scheme that in the induction heating unit arrangement and power management steps, the induction heating unit is composed of multiple embedded induction coils, and the power of each induction coil can be automatically adjusted according to the temperature of the medium in the pipeline and the surface temperature of the pipeline.

[0019] It is further worth mentioning that, in the real-time temperature monitoring and data collection steps, the temperature sensors are arranged at intervals of one sensor every 20 meters.

[0020] It should be further explained that in the intelligent data analysis and precise thermal management steps, the heating power adjustment model is:

[0021] P i (t) = α·T set -β·ΔT i (t)+γ·H load (t)

[0022] Where, P i (t) is the heating power of the i-th induction heating unit at time t,

[0023] T set is the set pipe temperature,

[0024] ΔT i (t) = T pipe (t)-T set is the temperature deviation of the pipeline at the i-th position,

[0025] H load (t) is the current load of the pipeline, reflecting the flow state of the medium in the pipeline.

[0026] α, β, and γ are weight coefficients, which are optimized through machine learning or experience.

[0027] As a preferred embodiment, in the automatic closed-loop feedback control step, the closed-loop control model is:

[0028]

[0029] Where, ΔP i (t) is the power change of induction heating unit i at time t,

[0030] T pipe (t) is the current pipe temperature,

[0031] T set is the target temperature,

[0032] K p is the proportional gain, K d are differential gains, which are used to adjust the speed and smoothness of the response respectively.

[0033] As a preferred embodiment, in the system integration and intelligent decision-making steps, the decision optimization model is:

[0034]

[0035] Where D(t) is the comprehensive decision output at time t,

[0036] T i (t) is the temperature at the i-th position,

[0037] P i (t) is the power of the i-th heating unit,

[0038] λ i ,μ i is the weight coefficient, based on the priority of different pipeline areas,

[0039] Cost(t) is the cost function calculated based on system performance or energy consumption,

[0040] η is the cost impact coefficient.

[0041] As a preferred embodiment, in the step of adaptively adjusting the environment and load, the adaptive adjustment model is:

[0042]

[0043] Where, P adjust (t) is the adjusted heating power,

[0044] P base Is the basic power, representing the system default power,

[0045] T env (t) is the ambient temperature,

[0046] T set is the target temperature,

[0047] H load (t) is the current pipeline load,

[0048] H max For maximum load,

[0049] α, β are the proportional coefficients of power adjustment according to environmental changes and load.

[0050] As a preferred embodiment, the efficient anti-freezing and anti-blocking integrated induction heating method for oil and gas pipelines is implemented, which comprises:

[0051] Heating core module: provides the core function of pipeline induction heating, realizes rapid heating and prevents freezing and blocking.

[0052] Intelligent temperature control module: real-time monitoring of pipeline temperature, automatic adjustment of heating intensity, and maintenance of stable temperature.

[0053] Power regulation module: control heating power output, adapt to different pipe diameter, flow and environmental temperature.

[0054] Thermal load adaptive module: according to the characteristics of pipeline fluid and external environment changes, dynamically optimize the heating strategy.

[0055] Data acquisition and analysis module: collect temperature, pressure, flow and other data, provide basis for control decision.

[0056] Remote monitoring module: support system remote viewing, adjustment and alarm, facilitate operation and maintenance.

[0057] Fault detection and protection module: detect overheating, short circuit and other system abnormalities, automatically trigger safety protection.

[0058] Energy efficiency optimization module: real-time monitoring and optimization of energy consumption, reduce energy waste.

[0059] Environmental adaptation module: adjust heating strategy according to external temperature and humidity changes, ensure stable operation in extreme environment.

[0060] System integration and communication module: realize data transmission and cooperation of each module, ensure coordinated and efficient operation of the whole system.

[0061] Compared with the prior art, the efficient anti-freezing and anti-blocking integrated induction heating system and method for oil and gas pipelines provided by the present application has at least the following beneficial effects:

[0062] (1) By adopting electromagnetic induction heating principle, the induction coil directly heats the pipeline and the internal medium, reducing the heat conduction loss and heat energy radiation loss of traditional resistance wire, heat tracing band and other heating methods. Intelligent power management module can optimize power supply and power regulation, combined with adaptive environment and load regulation strategy, can automatically adjust the heating power according to the environmental temperature and pipeline load, while ensuring the effect of anti-freezing and anti-blocking, significantly reducing the energy consumption, reducing the burden of power supply system.

[0063] (2) By deploying multiple high-precision temperature sensors at key locations on the pipeline and building an efficient data acquisition network, real-time monitoring of parameters such as pipeline surface temperature, internal medium temperature, ambient temperature, and pipeline pressure can be achieved. Based on edge computing and intelligent algorithms, the collected data can be quickly analyzed and processed, and the power and working mode of each induction heating unit can be dynamically adjusted. Combined with the automatic closed-loop feedback control model, personalized and precise heating of the pipeline in different areas and under different conditions can be achieved, effectively solving the problems of poor uniformity and lack of fine-grained regulation of traditional heating methods.

[0064] (3) Through integrated design, the heating unit, temperature sensor, control unit and communication equipment are integrated into the same system architecture, which greatly reduces the complexity of on-site wiring. Through edge computing and cloud collaborative computing architecture, the system's computing power and intelligent decision-making level are improved. In conjunction with the centralized management platform and remote communication network, all-round remote monitoring, parameter adjustment and fault warning are realized. At the same time, modular design and redundant fault switching mechanism improve the reliability, maintainability and scalability of the system, and effectively support the efficient data interaction and centralized management needs of the integrated system. BRIEF DESCRIPTION OF THE DRAWINGS

[0065] Figure 1 is a flow chart of the method of the present invention;

[0066] Figure 2 This is a system block diagram of the present invention. DETAILED DESCRIPTION

[0067] The following will be combined with the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the embodiments described are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of the present invention.

[0068] The present invention will be further described below with reference to the embodiments.

[0069] See also Figure 1-2 The present invention provides an integrated induction heating system and method for preventing freezing and blocking of oil and gas pipelines, comprising the following steps:

[0070] S1. Induction Heating Unit Layout and Power Management: Multiple induction heating units are evenly arranged outside the oil and gas pipeline. Each induction heating unit consists of an induction coil and directly heats the pipeline and the medium inside the pipeline through the principle of electromagnetic induction heating. The intelligent power management module optimizes the power supply and power regulation of the heating units.

[0071] S2. Real-time temperature monitoring and data acquisition: Multiple temperature sensors are deployed at key locations on oil and gas pipelines to monitor the pipeline surface temperature and the temperature of the medium inside the pipeline in real time. Each sensor transmits data to the central control unit via a wireless network, building an efficient data acquisition network. The system also monitors relevant parameters such as ambient temperature and pipeline pressure, providing accurate real-time data support.

[0072] S3. Intelligent Data Analysis and Precision Thermal Management: The central control unit uses edge computing technology to analyze and process real-time temperature data and pipeline media conditions, dynamically adjusting the heating power and operating mode of each induction heating unit. The system uses intelligent algorithms to optimize thermal management strategies and achieve personalized heating for different pipeline areas and conditions.

[0073] S4. Automatic closed-loop feedback control: During the heating process, the system adjusts the heating power of the induction heating unit in real time through the feedback data provided by the temperature sensor. The system implements closed-loop control based on the dynamic changes of the temperature difference between the inside and outside of the pipeline and the medium state.

[0074] S5. Intelligent remote control and early warning: The system implements comprehensive remote monitoring and control through a centralized management platform and remote communication network. Users can view the heating status of oil and gas pipelines through PC terminals and remotely adjust heating parameters. The system automatically detects and reports potential faults during operation, notifying maintenance personnel in advance. Troubleshooting or parameter adjustments can also be performed remotely.

[0075] S6. System Integration and Intelligent Decision-Making: With an integrated design, all heating units, temperature sensors, control units, and communication equipment are integrated into the same system architecture, reducing the complexity of on-site wiring. Through collaborative computing between edge computing and the cloud, the system's computing power and intelligent decision-making capabilities are enhanced. The cloud platform aggregates and analyzes data from the entire system, provides optimization suggestions, and supports historical data storage and subsequent optimization.

[0076] S7, Adaptive environment and load regulation: The system automatically adjusts the heating strategy according to changes in ambient temperature and pipeline load. When the ambient temperature is low, the system will automatically increase the heating power to prevent the pipeline from freezing; when the load is light, the system will reduce the heating power to save energy.

[0077] S8. Redundancy and fault switching: The key components of the system adopt a redundant design. When a system component fails, other components can automatically take over its function to ensure uninterrupted heating process. The fault diagnosis system automatically switches to the backup system when an abnormality occurs and notifies the user to repair it.

[0078] Further as Figure 1As shown, it is worth mentioning that in the induction heating unit arrangement and power management steps, the induction heating unit is composed of multiple embedded induction coils, and the power of each induction coil can be automatically adjusted according to the temperature of the medium in the pipeline and the temperature of the pipeline surface. The embedded induction coil is directly arranged on the outer wall of the pipeline, which reduces the loss of heat conducted through media such as air in traditional heating methods, and makes electromagnetic energy more concentratedly converted into thermal energy of the pipeline and the internal medium, and the basic heating efficiency is significantly improved. At the same time, each coil can adjust the power in real time according to the temperature of the medium in the pipeline and the temperature of the pipeline surface, avoiding the "overheating" waste caused by overall unified heating, while meeting the requirements. Energy consumption is minimized while preventing freezing and blockage, and it is particularly suitable for scenarios where the temperature differences between different areas of the pipeline are large. The embedded design enables the coil to form a more stable structural connection with the pipeline, reducing the problems of coil displacement or poor contact caused by vibration, environmental erosion, etc. after on-site installation, and improving long-term operational stability. The automatic power adjustment function enables the system to dynamically respond to fluctuations in the medium temperature and surface temperature in the pipeline, such as changes in medium flow and sudden drops in ambient temperature. By adjusting the output power in real time, it maintains the pipeline temperature stable, avoiding the risk of freezing or equipment loss caused by excessive temperature fluctuations, and enhancing the system's adaptability to complex working conditions.

[0079] Further as Figure 1 As shown, it is worth mentioning that in the real-time temperature monitoring and data acquisition steps, the temperature sensors are arranged at an interval of one sensor every 20 meters. The 20-meter interval can form a relatively dense monitoring network at the key positions of the pipeline, which not only avoids the problems of increased equipment cost, data redundancy and increased wiring complexity caused by too dense sensor arrangement, but also prevents the temperature monitoring blind spots caused by too large an interval, ensuring effective coverage of the overall temperature distribution state of the pipeline, and achieving an optimal balance between accurate perception and economic feasibility; there is a certain spatial attenuation characteristic in pipeline heat transfer, and the 20-meter interval is compatible with the thermal conduction efficiency of the oil and gas pipeline, which can ensure that the temperature data collected by the sensor can truly reflect the temperature change trend between adjacent monitoring points, reduce the temperature data distortion caused by excessive distance, and at the same time, the interval can meet the system's real-time response requirements to temperature changes, provide timely and effective data input for automatic closed-loop feedback control, and ensure the timeliness and accuracy of heating power adjustment.

[0080] Further as Figure 1 As shown, it is worth noting that in the intelligent data analysis and precise thermal management steps, the heating power adjustment model is:

[0081] P i (t) = α·T set -β·ΔT i (t)+γ·H load (t)

[0082] Where, P i (t) is the heating power of the i-th induction heating unit at time t,

[0083] T set is the set pipe temperature,

[0084] ΔT i (t) = T pipe (t)-T set is the temperature deviation of the pipeline at the i-th position,

[0085] H load (t) is the current load of the pipeline, reflecting the flow state of the medium in the pipeline.

[0086] α, β, and γ are weight coefficients, which are optimized through machine learning or experience. The model dynamically calculates the heating power by combining the three key parameters of the set pipeline temperature, pipeline temperature deviation, and current pipeline load with the weight coefficients to ensure that the output power of each induction heating unit accurately matches the actual demand of the pipeline, avoiding "overheating" or "underheating" problems. The set temperature, real-time temperature deviation, and medium load status are innovatively integrated into the same calculation model, breaking through the traditional adjustment method that only relies on a single temperature parameter, and realizing a multi-dimensional and accurate assessment of heating needs. According to the temperature differences and medium flow state differences at different locations of the pipeline, the model can separately calculate the power of each induction heating unit, providing a quantitative basis for personalized heating strategies in different areas and working conditions of the pipeline, and improving the overall anti-freeze and blockage effect.

[0087] Further as Figure 1 As shown, it is worth noting that in the automatic closed-loop feedback control step, the closed-loop control model is:

[0088]

[0089] Where, ΔP i (t) is the power change of induction heating unit i at time t,

[0090] T pipe (t) is the current pipe temperature,

[0091] T set is the target temperature,

[0092] K p is the proportional gain, K dis a differential gain, respectively used for adjusting the speed and stability of the response; the model calculates the power change in real time based on the deviation of the current pipe temperature and the target temperature through proportional gain and differential gain, ensures that the heating power can quickly respond to the pipe temperature fluctuation, avoids the problems of temperature overshoot or lag, maintains the pipe temperature stable in the target range, innovatively incorporates the temperature deviation and temperature change rate into the same control model, breaks through the limitations of traditional single deviation regulation, and realizes the dual precise control of the temperature "static deviation" and "dynamic change trend".

[0093] Further as shown in Figure 1 , it is worth noting that in the system integration and intelligent decision-making step, the decision optimization model is:

[0094]

[0095] wherein D(t) is the comprehensive decision output at time t,

[0096] T i (i) is the temperature of the i-th position,

[0097] P i (i) is the power of the i-th heating unit,

[0098] λ i , μ i are weight coefficients based on the priority of different pipe regions,

[0099] Cost(t) is a cost function calculated according to system performance or energy consumption,

[0100] η is the influence coefficient of the cost; the model generates a comprehensive decision output by integrating the temperature of the i-th position, the power of the i-th heating unit, and the system cost function, in combination with the weight coefficients, achieving a multi-objective balance of temperature guarantee, power control, and energy cost, avoiding the problem of losing one thing for another caused by single parameter decision-making; innovatively fusing the three core parameters of temperature, power, and cost into a unified decision output through weight coefficients, breaking through the limitations of traditional single index decision-making, and realizing comprehensive evaluation and optimization of system operation status.

[0101] Further as shown in Figure 1 , it is worth noting that in the adaptive environment and load regulation step, the adaptive regulation model is:

[0102]

[0103] wherein P adjust (t) is the adjusted heating power,

[0104] P base is the basic power, representing the default power of the system,

[0105] T env (t) is the ambient temperature,

[0106] T set is the target temperature,

[0107] H load (t) is the current pipeline load,

[0108] H max is the maximum load,

[0109] α, β are proportional coefficients for adjusting power according to environmental changes and load; the model automatically adjusts the heating power based on the dynamic changes of the ambient temperature, the current load and the maximum load of the pipeline, so that the system can respond to the fluctuations of the external environment and the medium flow state in real time, ensuring that the heating strategy accurately matches the actual demand; innovatively coupling the environmental temperature, pipeline load and basic power through mathematical model calculation, breaking through the limitations of traditional single parameter adjustment, realizing comprehensive response to double variables of environment and load.

[0110] Further as Figure 2 illustrated, it is worth noting that the efficient anti-freezing and blocking integrated induction heating method for oil and gas pipelines described above comprises:

[0111] Heating core module: provides the core function of pipeline induction heating, realizes rapid heating and prevents freezing and blocking.

[0112] Intelligent temperature control module: real-time monitoring of pipeline temperature, automatic adjustment of heating intensity, and maintenance of stable temperature.

[0113] Power regulation module: control heating power output, adapt to different pipe diameter, flow and environmental temperature.

[0114] Thermal load adaptive module: dynamically optimize heating strategy according to pipeline fluid characteristics and external environmental changes.

[0115] Data acquisition and analysis module: collect temperature, pressure, flow and other data, provide basis for control decision.

[0116] Remote monitoring module: support system remote viewing, adjustment and alarm, convenient for operation and maintenance.

[0117] Fault detection and protection module: detect system abnormalities such as overheating and short circuit, automatically trigger safety protection.

[0118] Energy efficiency optimization module: real-time monitoring and optimization of energy consumption, reduce energy waste.

[0119] Environmental adaptation module: adjust heating strategy according to external temperature and humidity changes, ensure stable operation in extreme environment.

[0120] System integration and communication module: realize the data transmission and cooperation of each module, and ensure the coordinated and efficient operation of the whole system.

[0121] The scheme has the following working process:

[0122] Step one: evenly arrange multiple induction heating units outside the oil and gas pipeline, each induction heating unit is composed of an induction coil, directly heat the pipeline and the medium in the pipeline through electromagnetic induction heating principle, through intelligent power management module, optimize the power supply and power regulation of heating unit;

[0123] Step two: multiple temperature sensors are arranged at key positions of the oil and gas pipeline to monitor the surface temperature of the pipeline and the temperature of the medium in the pipeline in real time, each sensor transmits data to the central control unit through wireless network, builds an efficient data acquisition network, the system also monitors environmental temperature, pipeline pressure and other related parameters, and provides accurate real-time data support;

[0124] Step three: based on real-time temperature data and pipeline medium state, the central control unit uses edge computing technology to analyze and process the collected data, dynamically adjusts the heating power and working mode of each induction heating unit, the system optimizes the heat management strategy through intelligent algorithm, and realizes personalized heating in different areas and different states of the pipeline;

[0125] Step four: during the heating process, the system adjusts the heating power of the induction heating unit in real time according to the feedback data provided by the temperature sensor, and according to the dynamic changes of the temperature difference between the inside and outside of the pipeline and the medium state, the system realizes closed-loop control;

[0126] Step five: the system realizes all-round remote monitoring and control through centralized management platform and remote communication network, users can check the heating state of oil and gas pipeline through PC terminal, remotely adjust heating parameters, automatically detect and report potential fault problems during system operation, notify maintenance personnel in advance, and troubleshoot or adjust parameters through remote operation;

[0127] Step six: integrated design is adopted, all heating units, temperature sensors, control units and communication equipment are integrated in the same system architecture, reducing the complexity of field wiring, improving the computing power and intelligent decision-making level of the system through edge computing and cloud collaborative computing, the cloud platform realizes data aggregation and analysis of the whole system, provides optimization suggestions and supports historical data storage and later optimization;

[0128] Step seven: the system automatically adjusts the heating strategy according to the change of environmental temperature and pipeline load, when the environmental temperature is low, the system will automatically increase the heating power to ensure that the pipeline is not frozen; when the load is light, the system will reduce the heating power to save energy;

[0129] Step 8: The key components of the system adopt a redundant design. When a system component fails, other components can automatically take over its function to ensure uninterrupted heating process. The fault diagnosis system automatically switches to the backup system when an abnormality occurs and notifies the user to repair it.

[0130] In summary: By adopting the electromagnetic induction heating principle, the induction coil directly heats the pipeline and the internal medium, reducing the heat conduction loss and heat radiation loss of traditional heating methods such as resistance wire and heating tape. The intelligent power management module can optimize the power supply and power regulation. Combined with the adaptive environment and load regulation strategy, it can automatically adjust the heating power according to the ambient temperature and pipeline load, while ensuring the anti-freeze effect. At the same time, it significantly reduces energy consumption and reduces the burden on the power supply system; by deploying multiple high-precision temperature sensors at key positions of the pipeline, building an efficient data acquisition network, it can realize real-time monitoring of parameters such as pipeline surface temperature, internal medium temperature, ambient temperature, and pipeline pressure. Based on edge computing and intelligent algorithms, it can quickly analyze and process the collected data, and dynamically adjust each induction heating unit. The power and working mode of the element, combined with the automatic closed-loop feedback control model, realize personalized and precise heating in different areas and under different conditions of the pipeline, effectively solving the problems of poor uniformity and lack of fine regulation of traditional heating methods; through integrated design, the heating unit, temperature sensor, control unit and communication equipment are integrated into the same system architecture, which greatly reduces the complexity of on-site wiring. Through edge computing and cloud collaborative computing architecture, the system's computing power and intelligent decision-making level are improved. With the centralized management platform and remote communication network, all-round remote monitoring, parameter adjustment and fault warning are realized. At the same time, modular design and redundant fault switching mechanism improve the reliability, maintainability and scalability of the system, effectively supporting the efficient data interaction and centralized management needs of the integrated system.

[0131] While embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions, and variations may be made to these embodiments without departing from the principles and spirit of the invention, and that the scope of the invention is defined by the appended claims and their equivalents.

Claims

1. An efficient integrated induction heating method for preventing freezing and blocking of oil and gas pipelines, characterized in that: The following steps are involved: S1. Induction Heating Unit Layout and Power Management: Multiple induction heating units are evenly arranged outside the oil and gas pipeline. Each induction heating unit consists of an induction coil and directly heats the pipeline and the medium inside the pipeline through the principle of electromagnetic induction heating. The intelligent power management module optimizes the power supply and power regulation of the heating units. S2. Real-time temperature monitoring and data acquisition: Multiple temperature sensors are deployed at key locations on oil and gas pipelines to monitor the pipeline surface temperature and the temperature of the medium inside the pipeline in real time. Each sensor transmits data to the central control unit via a wireless network, building an efficient data acquisition network. The system also monitors relevant parameters such as ambient temperature and pipeline pressure, providing accurate real-time data support. S3. Intelligent Data Analysis and Precision Thermal Management: The central control unit uses edge computing technology to analyze and process real-time temperature data and pipeline media conditions, dynamically adjusting the heating power and operating mode of each induction heating unit. The system uses intelligent algorithms to optimize thermal management strategies and achieve personalized heating for different pipeline areas and conditions. S4. Automatic closed-loop feedback control: During the heating process, the system adjusts the heating power of the induction heating unit in real time through the feedback data provided by the temperature sensor. The system implements closed-loop control based on the dynamic changes of the temperature difference between the inside and outside of the pipeline and the medium state. S5. Intelligent remote control and early warning: The system implements comprehensive remote monitoring and control through a centralized management platform and remote communication network. Users can view the heating status of oil and gas pipelines through PC terminals and remotely adjust heating parameters. The system automatically detects and reports potential faults during operation, notifying maintenance personnel in advance. Troubleshooting or parameter adjustments can also be performed remotely. S6. System Integration and Intelligent Decision-Making: With an integrated design, all heating units, temperature sensors, control units, and communication equipment are integrated into the same system architecture, reducing the complexity of on-site wiring. Through collaborative computing between edge computing and the cloud, the system's computing power and intelligent decision-making capabilities are enhanced. The cloud platform aggregates and analyzes data from the entire system, provides optimization suggestions, and supports historical data storage and subsequent optimization. S7, Adaptive environment and load regulation: The system automatically adjusts the heating strategy according to changes in ambient temperature and pipeline load. When the ambient temperature is low, the system will automatically increase the heating power to prevent the pipeline from freezing; when the load is light, the system will reduce the heating power to save energy. S8. Redundancy and fault switching: The key components of the system adopt a redundant design. When a system component fails, other components can automatically take over its function to ensure uninterrupted heating process. The fault diagnosis system automatically switches to the backup system when an abnormality occurs and notifies the user to repair it.

2. The high-efficiency anti-freeze and anti-blocking integrated induction heating method for oil and gas pipelines according to claim 1 is characterized by: In the induction heating unit arrangement and power management step, the induction heating unit is composed of a plurality of embedded induction coils, and the power of each induction coil can be automatically adjusted according to the temperature of the medium in the pipeline and the surface temperature of the pipeline.

3. The high-efficiency integrated induction heating method for preventing freezing and blockage of oil and gas pipelines according to claim 1 is characterized in that: In the real-time temperature monitoring and data collection step, the temperature sensors are arranged at intervals of one sensor every 20 meters.

4. The high-efficiency anti-freezing and anti-blocking integrated induction heating method for oil and gas pipelines according to claim 1 is characterized in that: In the intelligent data analysis and precise thermal management steps, the heating power adjustment model is: P i (t)=α·T set -β·ΔT i (t)+γ·H load (t) Where, P i (t) is the heating power of the i-th induction heating unit at time t, T set is the set pipe temperature, ΔT i (t) = T pipe (t)-T set is the temperature deviation of the pipeline at the i-th position, H load (t) is the current load of the pipeline, reflecting the flow state of the medium in the pipeline. α, β, and γ are weight coefficients, which are optimized through machine learning or experience.

5. The high-efficiency integrated induction heating method for preventing freezing and blockage of oil and gas pipelines according to claim 1 is characterized in that: In the automatic closed-loop feedback control step, the closed-loop control model is: Where, ΔP i (t) is the power change of induction heating unit i at time t, T pipe (t) is the current pipe temperature, T set is the target temperature, K p is the proportional gain, K d are differential gains, which are used to adjust the speed and smoothness of the response respectively.

6. The high-efficiency integrated induction heating method for preventing freezing and blockage of oil and gas pipelines according to claim 1 is characterized in that: In the system integration and intelligent decision-making steps, the decision optimization model is: Where D(t) is the comprehensive decision output at time t, T i (t) is the temperature at the i-th position, P i (t) is the power of the i-th heating unit, λ i ,μ i is the weight coefficient, based on the priority of different pipeline areas, Cost(t) is the cost function calculated based on system performance or energy consumption, η is the cost impact coefficient.

7. The high-efficiency integrated induction heating method for preventing freezing and blockage of oil and gas pipelines according to claim 1 is characterized in that: In the adaptive environment and load adjustment step, the adaptive adjustment model is: Where, P adjust (t) is the adjusted heating power, P base Is the basic power, representing the system default power, T env (t) is the ambient temperature, T set is the target temperature, H load (t) is the current pipeline load, H max is the maximum load, α and β are proportional coefficients for adjusting power according to environmental changes and load.

8. The high-efficiency anti-freezing and anti-blocking integrated induction heating system for oil and gas pipelines according to claim 1 is characterized by: The method for implementing the high-efficiency anti-freezing and anti-blocking integrated induction heating method for an oil and gas pipeline according to any one of claims 1 to 7 comprises: Heating core module: provides the core function of pipeline induction heating, achieving rapid temperature rise and preventing freezing and blockage; Intelligent temperature control module: real-time monitoring of pipeline temperature, automatic adjustment of heating intensity, and maintaining stable temperature; Power regulation module: controls heating power output to adapt to different pipe diameters, flow rates and ambient temperatures; Heat load adaptive module: dynamically optimizes heating strategies based on pipeline fluid characteristics and external environmental changes; Data acquisition and analysis module: collects temperature, pressure, flow and other data to provide a basis for control decisions; Remote monitoring module: supports remote viewing, adjustment and alarm of the system, facilitating operation and maintenance; Fault detection and protection module: detects system anomalies such as overheating and short circuit, and automatically triggers safety protection; Energy efficiency optimization module: real-time monitoring and optimization of energy consumption to reduce energy waste; Environmental adaptation module: adjusts heating strategies according to changes in external temperature and humidity to ensure stable operation in extreme environments; System integration and communication module: realize data transmission and collaboration among modules to ensure the coordinated and efficient operation of the entire system.

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