Self-heating anti-freezing drainage pipeline system for plateau permafrost region and control method of self-heating anti-freezing drainage pipeline system

Abstract

The invention provides a self-heating anti-freezing drainage pipeline system for a plateau permafrost region and a control method of the self-heating anti-freezing drainage pipeline system, and belongs to the technical field of engineering drainage in cold regions. According to the self-heating anti-freezing drainage pipeline system for the plateau permafrost region and the control method of the self-heating anti-freezing drainage pipeline system, the self-heating anti-freezing drainage pipeline system comprises a self-heating pipeline module, an energy supply module and an intelligent control module, and the self-heating pipeline module comprises a pipeline body and an integrated electric heating layer. By arranging the pipeline system composed of the self-heating pipeline module, the energy supply module and the intelligent control module, the integrated effect of energy self-supply, intelligent sensing and active anti-freezing in the plateau frozen soil area without the power grid is achieved, the unfreezing rate is calculated through captured data through configuration of the intelligent control module, and the unfreezing efficiency is improved. The parameter dynamically reflects the efficiency of freezing and melting, so that the system can accurately put energy based on the efficiency, and the problems of energy dependence and anti-freezing reliability are fundamentally solved.

Description

Technical Field

[0001] This invention relates to the field of drainage technology for cold region engineering, and more specifically, to a self-heating antifreeze drainage pipeline system and its control method for use in high-altitude permafrost regions. Background Technology

[0002] In high-altitude permafrost regions, especially in highly saline environments, freezing of drainage pipes due to low winter temperatures is a common problem threatening the normal operation of infrastructure. Because permafrost exhibits freeze-thaw cycles with seasonal changes, moisture migrates and crystallizes in the soil around the pipes at sub-zero temperatures, easily causing pipe blockage or even structural damage. Currently, the common solution in engineering is to increase the burial depth of the pipes to below the local freezing depth. However, the thickness of the permafrost layer in permafrost regions can reach several meters to tens of meters. Due to limitations in topography, geological conditions, and engineering costs, this passive protection method is often difficult to implement in practice. Especially for railway and highway drainage systems with dense linear engineering, deep excavation and burial will lead to a surge in costs and a significant increase in construction difficulty.

[0003] Existing defrosting technologies have significant drawbacks in terms of applicability and reliability. Heat tracing technology relies on a continuous power supply from an external power grid, making it unusable in high-altitude areas without grid coverage. It also has high energy consumption and long-term operating costs. Furthermore, it suffers from problems such as rapid aging of heating elements and localized overheating leading to insulation layer damage. Manual unblocking, as an emergency measure, requires operation in temperatures below -20°C, resulting in low efficiency for single unblocking operations and failing to address the fundamental problem of repeated freezing. The risk factor for operations in the oxygen-deficient environment of high altitudes is more than three times higher than in plains areas. Although wrapping with insulation materials can delay pipe freezing time through thermal resistance, under sustained low temperatures or extreme cold waves, the thermal resistance of the insulation layer is gradually broken down by the low temperature, eventually leading to complete pipe freezing. Moreover, corrosive ions in saline environments can accelerate the aging of insulation materials, causing a rapid decline in protective effectiveness. Summary of the Invention

[0004] To overcome the above deficiencies, the present invention provides a self-heating antifreeze drainage pipeline system and its control method for use in plateau permafrost regions, which overcomes or at least partially solves the above technical problems.

[0005] This invention is implemented as follows:

[0006] This invention provides a self-heating antifreeze drainage pipeline system for high-altitude permafrost regions, comprising a self-heating pipeline module, an energy supply module, and an intelligent control module. The self-heating pipeline module includes a pipeline body and an integrated electric heating layer, which is embedded in the inner wall of the pipeline body. The integrated electric heating layer uses a self-limiting heating wire. The energy supply module is electrically connected to the integrated electric heating layer and includes a solar photovoltaic system as the main energy source and a low-temperature resistant lithium battery pack as an energy storage unit. Both the integrated electric heating layer and the energy supply module are signal-connected to the intelligent control module. The intelligent control module includes a sensing unit for monitoring the internal state of the pipeline and a core controller. The sensing unit includes at least a temperature sensor for monitoring the medium temperature and a flow rate sensor for detecting the water flow state. The core controller is configured to: calculate the thawing rate of the pipeline in real time based on the data from the temperature sensor, and use the thawing rate as the core control parameter, combined with temperature and flow rate information, dynamically manage the start / stop, power level, and working time of the integrated electric heating layer.

[0007] In a preferred embodiment, the wall structure of the self-heating pipe module is configured from the inside out as an inner pipe layer, an integrated electric heating layer, an insulation layer, and an outer sheath. The inner pipe layer is made of high-density polyethylene, and the insulation layer is made of rigid polyurethane foam.

[0008] In a preferred embodiment, the self-regulating heating wires in the integrated heating layer are arranged in parallel and embedded in the inner tube layer.

[0009] In a preferred embodiment, the energy supply module also includes auxiliary energy, which is a thermoelectric generator.

[0010] In a preferred embodiment, the core controller calculates the thawing rate as follows: after determining that the pipeline has frozen and initiating heating, a preset sampling period Δt is used to continuously collect and store N temperature measurements {T1, T2, ..., T...} inside the pipeline over a past period W. N}, forming a sliding temperature time series data window; where the time window width is W=N×Δt;

[0011] The least squares method was used to perform linear regression analysis on N temperature measurements within the temperature time series data window. The slope KT of the best-fit line of the temperature time series data window was calculated and defined as the real-time thawing rate R, with the unit of real-time thawing rate R being °C / second.

[0012] In a preferred embodiment, the core controller is a low-power microcontroller with a pre-stored heating power mapping table in its memory corresponding to different defrosting rate R value ranges.

[0013] A method for a self-heating, anti-freezing drainage pipe for use in high-altitude permafrost regions includes the following steps:

[0014] S1: Preset temperature threshold, flow rate threshold, and target thawing rate related to the severity of freezing. ;

[0015] S2: Real-time monitoring of temperature T and flow velocity V inside the pipeline via sensing unit;

[0016] S3: When the conditions of T≤0℃ and V=0 are met, the pipeline is determined to be in a frozen state, the integrated electric heating layer is activated and the real-time defrosting rate R is calculated.

[0017] S4: Compare the real-time thawing rate R with the target thawing rate The system compares the results and intelligently controls the output power of the integrated electrothermal layer until the flow rate V returns to the normal range.

[0018] In a preferred embodiment, the specific strategy for intelligent control in step S4 includes:

[0019] When R < If the current heating power is insufficient to ensure rapid and effective defrosting, the integrated electric heating layer is controlled to increase power output.

[0020] When R= Or, if the current heating power is within the allowable error range, determine that the current heating power is appropriate and maintain the current power level to continue heating;

[0021] When R> If the current heating power is determined to be too high and energy is wasted, the integrated heating layer is controlled to reduce its power output until R drops back to near [the specified value]. The level.

[0022] In a preferred embodiment, in step S3, the core controller further executes a predictive control strategy based on a thermodynamic model, including:

[0023] S3.1: Real-time calculation of predicted freezing time (TTF), which is defined as the time required for the water in the pipe to drop from the current temperature to the freezing point under the current environmental heat dissipation conditions;

[0024] S3.2: Monitor and calculate the natural cooling rate K of the water in the pipe. Based on the volume and heat capacity of the water in the pipe, calculate the total heat that needs to be removed to cool it from the current temperature to the freezing point, i.e. the remaining safe enthalpy ΔH. Calculate the predicted freezing time TTF based on the natural cooling rate K and the remaining safe enthalpy ΔH.

[0025] S3.3: Preset time threshold TTF t， Compare the predicted freeze time (TTF) with the preset time threshold (TTF). t Compare them.

[0026] In a preferred embodiment, the triggering condition for intelligent control in step S4 includes the judgment result of the predictive control strategy:

[0027] When the predicted freeze time TTF is less than or equal to the time threshold TTF t At any time, regardless of whether the current medium temperature T in the pipeline is below 0℃ or the flow velocity V is zero, the core controller will immediately and actively start or increase the output power of the integrated electric heating layer to prevent the pipeline from entering a frozen state.

[0028] This invention provides a self-heating anti-freezing drainage pipeline system and its control method for use in high-altitude permafrost regions, the beneficial effects of which include:

[0029] 1. By setting up a pipeline system consisting of a self-heating pipeline module, an energy supply module, and an intelligent control module, the system achieves an integrated effect of energy self-sufficiency, intelligent sensing, and active antifreeze in permafrost areas on high-altitude plateaus without power grids. The configuration of the intelligent control module calculates the thawing rate based on the captured data. This parameter dynamically reflects the efficiency of freezing and thawing, enabling the system to make precise energy delivery based on this, fundamentally solving the problems of energy dependence and antifreeze reliability.

[0030] 2. By setting the real-time defrosting rate R and the target defrosting rate The intelligent control strategy, based on the comparison results, achieves optimized control effects that realize precise power servoing while balancing defrosting efficiency and energy economy. This strategy ensures that the system always operates around the target efficiency, achieving the best balance between performance and energy consumption.

[0031] 3. By incorporating the predicted freezing time (TTF) into the triggering conditions of the intelligent control in step S4, the risk of pipeline freezing and blockage is fundamentally eliminated. This is achieved when the calculated TTF is less than or equal to the preset TTF. t When the pipeline is about to freeze in the foreseeable future, the core controller will exceed the judgment conditions based on the current state and immediately and proactively start or increase the output power of the integrated electric heating layer, ensuring that the system can eliminate the risk before freezing actually occurs, greatly improving the reliability and sophistication of the system. Attached Figure Description

[0032] To more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings used in the embodiments will be briefly introduced below. It should be understood that the following drawings only show some embodiments of the present invention and should not be regarded as a limitation of the scope. For those skilled in the art, other related drawings can be obtained from these drawings without creative effort.

[0033] Figure 1This is a cross-sectional layered structure diagram of the self-heating pipe of the present invention;

[0034] Figure 2 This is a schematic diagram of the overall structure of the system of the present invention;

[0035] In the diagram: 1. Pipe body; 11. Inner pipe layer; 12. Integrated electric heating layer; 13. Insulation layer; 14. Outer sheath; 2. Solar photovoltaic panel; 3. Energy storage and control box; 4. Thermoelectric generator; 5. Inspection well. Detailed Implementation

[0036] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0037] Reference Figures 1-2This invention provides a technical solution: a self-heating antifreeze drainage pipeline system and its control method for use in high-altitude permafrost regions. The system includes a self-heating pipeline module, an energy supply module, and an intelligent control module. The self-heating pipeline module comprises a pipeline body 1 and an integrated electric heating layer 12, which is embedded in the inner wall of the pipeline body 1. The integrated electric heating layer 12 uses a self-limiting heating wire with a positive temperature coefficient effect. The energy supply module is electrically connected to the integrated electric heating layer 12 to supply power. The energy supply module includes a solar photovoltaic system as the main energy source and a low-temperature resistant lithium battery pack as an energy storage unit. The solar photovoltaic system specifically consists of solar photovoltaic panels 2, which generate electricity using solar energy. Both the integrated electric heating layer 12 and the energy supply module are signal-connected to the intelligent control module. The intelligent control module includes a sensing unit for monitoring the internal state of the pipeline and a core controller. The sensing unit includes at least a temperature sensor for monitoring the medium temperature and a flow velocity sensor for detecting the water flow state. The core controller is configured to: calculate the thawing rate of the pipeline in real time based on the data from the temperature sensor, and use the thawing rate as the core control parameter, combining temperature and flow velocity signals... The system dynamically manages the start / stop, power level, and operating time of the integrated electric heating layer 12. By setting up a pipeline system consisting of a self-heating pipeline module, an energy supply module, and an intelligent control module, it achieves an integrated effect of energy self-sufficiency, intelligent sensing, and active antifreeze in permafrost areas without power grids. The integrated electric heating layer 12 uses a self-limiting heating wire, whose positive temperature coefficient effect comes from the inherent characteristics of the functional material. The physical law that its resistivity increases significantly with temperature gives the electric heating layer an inherent self-regulating power and anti-overheating capability. The energy supply module is designed for the specific application scenario of abundant solar energy resources in plateau areas but lack of conventional power grids. The solar photovoltaic system is responsible for energy collection as the main energy source, and the low-temperature resistant lithium battery pack is responsible for energy storage and release as the energy storage unit. The configuration of the intelligent control module uses the medium temperature and water flow status data monitored by its sensing unit to obtain real-time measurements from temperature sensors and flow rate sensors. The thawing rate is calculated from the above data. This parameter dynamically reflects the efficiency of freezing and thawing, enabling the system to make precise energy delivery based on this, fundamentally solving the problems of energy dependence and antifreeze reliability.

[0038] Reference Figures 1-2The self-heating pipe module's pipe wall structure, from the inside out, consists of an inner pipe layer 11, an integrated electric heating layer 12, an insulation layer 13, and an outer sheath 14. The inner pipe layer 11 is made of high-density polyethylene or fiberglass, and the insulation layer 13 is made of rigid polyurethane foam. By setting up a multi-layered composite pipe wall structure consisting of the inner pipe layer 11, integrated electric heating layer 12, insulation layer 13, and outer sheath 14, it achieves an integrated effect of synergistic pressure bearing, efficient heating, extreme insulation, and robust protection. The inner pipe layer 11 is made of high-density polyethylene or... Made of fiberglass, its material meets the stringent requirements of cold-region engineering for pipeline corrosion resistance, flexibility and long service life. The integrated electric heating layer 12 is composited in the pipe wall as the core heat source, realizing the direct and uniform transfer of heat from the inside of the pipe to the medium. The insulation layer 13 is made of rigid polyurethane foam. Utilizing the extremely low thermal conductivity of this material, a high-efficiency thermal barrier is built outside the electric heating layer to minimize the radial loss of heat to the surrounding frozen soil environment, thereby significantly improving the overall thermal utilization efficiency of the system and reducing operating energy consumption.

[0039] Reference Figures 1-2 The self-regulating heating wires in the integrated heating layer 12 are arranged in parallel and embedded in the inner tube layer 11. The embedding method is co-extrusion or winding. By setting the self-regulating heating wires to be arranged in parallel and embedded in the inner tube layer 11, the system safety and lifespan are improved. The parallel method is based on the reliability principle of circuit design. This connection method ensures that even if a single heating wire fails, the current can still pass through other parallel branches, and the entire heating layer can still work normally, which greatly improves the fault tolerance of the system. Co-extrusion molding can make the heating wires and the plastic of the inner tube layer 11 combine into a dense whole in the molten state, while winding and then coating is a mature secondary processing technology. Both methods can ensure that the heating layer and the pipe structure are seamlessly connected, which optimizes the heat conduction efficiency, avoids local overheating caused by poor contact, and provides excellent mechanical protection.

[0040] Reference Figures 1-2 The energy supply module also includes auxiliary energy, which is a thermoelectric generator 4 installed at the pipeline inspection well 5. Specifically, it is a thermoelectric generator plate, which is used to generate electricity by utilizing the temperature difference between the inside of the pipeline and the ambient air, as an auxiliary or emergency power source. By setting up auxiliary energy including the thermoelectric generator 4, it can provide continuous power supplement to the system during periods of insufficient solar energy, such as nighttime, continuous cloudy days, or extreme cold waves. The thermoelectric generator plate is specifically installed at the pipeline inspection well 5, capturing the significant temperature gradient between the inside of the pipeline and the frigid ambient air to generate electricity, and its output electrical energy serves as an auxiliary or emergency power source.

[0041] Reference Figures 1-2The core controller calculates the thawing rate as follows: After determining that the pipeline has frozen and initiating heating, it continuously collects and stores N temperature measurements {T1, T2, ..., T...} inside the pipeline over a past period W, within a preset sampling period Δt. N}, forming a sliding temperature time series data window; where the time window width is W=N×Δt;

[0042] The least squares method is used to perform linear regression analysis on N temperature measurements within a temperature time series data window. The slope KT of the best-fit line for the temperature time series data window is calculated and defined as the real-time thawing rate R, with the unit of R being °C / second. By setting the calculation method for the thawing rate R, a basis for intelligent power control is provided. In this method, the sampling period Δt and the time window width W (W=N×Δt) are derived from the preset parameters of the system based on the thermal inertia of the pipeline and the control response speed requirements. Continuous temperature measurements {T1,T2,...,T... N The data is derived from the periodic data acquisition and storage of the temperature sensor according to the sampling period Δt. The thawing rate R quantifies the rate at which the pipe temperature rises per unit time, and directly reflects the heating efficiency and the speed of ice melting.

[0043] Reference Figures 1-2 The core controller uses a low-power microcontroller, whose memory pre-stores a heating power mapping table corresponding to different defrosting rate R value ranges. By setting a low-power microcontroller as the core controller and pre-stores the heating power mapping table corresponding to different defrosting rate R value ranges in its memory, the system achieves fast, stable, and energy-saving power level control. The heating power mapping table is a data set on the correspondence between defrosting rate R value ranges and optimal heating power levels, established through numerous experiments during the system's development and debugging phases. This mapping table is pre-stored in the controller's memory, enabling the controller to quickly match and output the most suitable power level based on the real-time calculated R value through a table lookup method, avoiding complex real-time calculations and optimizing response speed and control stability.

[0044] The table is shown below:

[0045]

[0046] A method for controlling self-heating antifreeze drainage pipes in high-altitude permafrost regions includes the following steps:

[0047] S1: Preset temperature threshold, flow rate threshold, and target thawing rate related to the severity of freezing. ;

[0048] S2: Real-time monitoring of temperature T and flow velocity V inside the pipeline via sensing unit;

[0049] S3: When the conditions of T≤0℃ and V=0 are met, it is determined that the pipeline has entered a frozen state, the integrated electric heating layer 12 is activated and the real-time defrosting rate R is calculated.

[0050] S4: Compare the real-time thawing rate R with the target thawing rate The comparison is performed, and the output power of the integrated electric heating layer 12 is intelligently controlled according to the comparison results until the flow rate V returns to the normal range. By setting a complete control step including preset threshold, real-time monitoring, status judgment, rate calculation and intelligent power control, the system achieves the effect of fully automated intelligent management from the identification and confirmation of freezing risk to efficient defreezing. The target defreezing rate is a preset empirical value or optimized value. The real-time monitored temperature T and flow rate V are derived from the continuous operation of temperature sensor and flow rate sensor. The judgment logic T≤0℃ and V=0 in step S3 combines the freezing temperature conditions and the phenomenon of flow stagnation, providing a clear and executable judgment criterion for the pipeline to enter the freezing state.

[0051] The specific strategies for intelligent control in step S4 include:

[0052] When R < If the current heating power is insufficient to ensure rapid and effective defrosting, the integrated electric heating layer 12 is controlled to increase power output.

[0053] When R= Or, if the current heating power is within the allowable error range, determine that the current heating power is appropriate and maintain the current power level to continue heating;

[0054] When R> If the current heating power is determined to be too high and energy is wasted, the integrated electric heating layer 12 is controlled to reduce the power output until R drops back to near the specified level. The level is determined by setting the real-time defrosting rate R relative to the target defrosting rate. The intelligent control strategy, based on the comparison results, achieves optimized control effects that balance defrosting efficiency and energy economy, when R < When R = When R > 1, it indicates that the power delivery is just right, so the current power is maintained. When the power output is too high, it indicates that excessive power may lead to heat waste or excessively high local water temperature. Therefore, the power output is reduced. This strategy ensures that the system always operates around the target efficiency, achieving the best balance between performance and energy consumption.

[0055] In step S3, the core controller also executes a predictive control strategy based on a thermodynamic model, including:

[0056] S3.1: Real-time calculation of predicted freezing time (TTF), which is defined as the time required for the water in the pipe to drop from the current temperature to the freezing point under the current environmental heat dissipation conditions;

[0057] S3.2: Monitor and calculate the natural cooling rate K of the water in the pipe. Based on the volume and heat capacity of the water in the pipe, calculate the total heat that needs to be removed to cool it from the current temperature to the freezing point, i.e. the remaining safe enthalpy ΔH. Calculate the predicted freezing time TTF based on the natural cooling rate K and the remaining safe enthalpy ΔH.

[0058] S3.3: Preset time threshold TTF t， Compare the predicted freeze time (TTF) with the preset time threshold (TTF). t By comparing the results, a predictive control strategy based on a thermodynamic model is introduced in step S3, which provides proactive defense against pipe freezing. The core parameter of this strategy, the predicted freezing time (TTF), is the time required for the water in the pipe to cool from its current temperature to its freezing point under the current environmental heat dissipation conditions. First, historical data from temperature sensors is analyzed, and a linear fit is performed using the least squares method. The slope of the resulting straight line is the cooling rate K. Then, the water volume is determined based on the pipe's inner diameter and water level. Combining this with the specific heat capacity of water and the current temperature T, the total heat removed to cool the water to 0°C, i.e., the remaining safe enthalpy (ΔH), is calculated. This is then combined with the system's equivalent heat capacity (P). Finally, the predicted freezing time (TTF) can be obtained. The system heat capacity equivalent (where the system heat capacity equivalent is a preset parameter related to the pipe material and the total heat capacity of the water body) is obtained, along with the time threshold TTF. t The safety margin, which is derived from the system's preset parameters, represents the advance time at which the system deems intervention necessary.

[0059] The triggering conditions for intelligent control in step S4 include the judgment result of the predictive control strategy:

[0060] When the predicted freeze time TTF is less than or equal to the time threshold TTF t Regardless of whether the current medium temperature T in the pipeline is below 0℃ or the flow velocity V is zero, the core controller immediately and actively starts or increases the output power of the integrated electric heating layer 12 to prevent the pipeline from freezing. By incorporating the prediction of the freezing time TTF into the triggering conditions of the intelligent control in step S4, the risk of pipeline freezing and blockage is fundamentally eliminated. When the calculated TTF is less than or equal to the preset TTF... t When the pipeline is about to freeze in the foreseeable future, the core controller will exceed the judgment conditions based on the current state and immediately and actively start or increase the output power of the integrated electric heating layer 12, ensuring that the system can eliminate the risk before freezing actually occurs, greatly improving the reliability and advancement of the system.

[0061] Specifically, the working process or principle of this self-heating anti-freezing drainage pipeline system and its control method for use in high-altitude permafrost regions is as follows: During use, pipeline sections with an integrated PTC heating layer and insulation layer 13 are prefabricated in a factory. During construction, trenches are excavated, pipelines are laid, and socket-sealed connections are made using conventional methods. Simultaneously, the power lines of each pipeline section are connected in parallel to the main line, ultimately leading to the energy storage and control box 3 inside the inspection well 5. Solar panels and thermoelectric generators 4 are installed, and their outputs are connected to the control box. After completing the connection of all sensors and control lines, system debugging is performed, and settings are configured. Once the temperature and flow rate thresholds are met, the system can begin automatic operation. After power-on, the system enters standby monitoring mode. The sensing unit of the intelligent control module begins to continuously collect the medium temperature T and water flow rate V inside the pipeline at a preset sampling period Δt. The core controller continuously reads this data as the basis for all control logic judgments. The controller analyzes the historical data returned by the temperature sensor, calculates the remaining safe enthalpy ΔH, and calculates the predicted freezing time TTF using a formula. This parameter quantifies how much time is left before the pipeline freezes in its current state. The system presets a safe margin time threshold TTF. t When the calculated TTF ≤ TTF t Regardless of whether the current temperature is below 0℃ or the flow rate is zero, the core controller will immediately and proactively start or increase the output power of the integrated electric heating layer 12 for preventative heating, fundamentally preventing freezing. When the core controller simultaneously detects that the temperature T≤0℃ and the flow rate V=0, the controller immediately starts the integrated electric heating layer 12 to begin heating and simultaneously starts the real-time defrosting rate R calculation program. After starting heating, the system calculates the real-time defrosting rate R. The controller has a pre-stored mapping table in its memory, and the controller compares the real-time calculated R value with the preset target defrosting rate. The comparisons are made, and the optimal power level is quickly matched using a lookup table.

Claims

1. A self-heating, anti-freezing drainage pipeline system for use in high-altitude permafrost regions, characterized in that: The system includes a self-heating pipe module, an energy supply module, and an intelligent control module. The self-heating pipe module includes a pipe body (1) and an integrated electric heating layer (12). The integrated electric heating layer (12) is embedded in the inner wall of the pipe body (1). The integrated electric heating layer (12) uses a self-limiting heating wire. The energy supply module is electrically connected to the integrated electric heating layer (12). The energy supply module includes a solar photovoltaic system as the main energy source and a low-temperature resistant lithium battery pack as an energy storage unit. The integrated electric heating layer (12) and the energy supply module are both signal-connected to the intelligent control module. The intelligent control module includes a sensing unit for monitoring the internal state of the pipe and a core controller. The sensing unit includes at least a temperature sensor for monitoring the temperature of the medium and a flow rate sensor for detecting the state of the water flow. The core controller is configured to: calculate the thawing rate of the pipe in real time based on the data from the temperature sensor, and use the thawing rate as the core control parameter, combined with temperature and flow rate information, to dynamically manage the start-up, shutdown, power level, and working time of the integrated electric heating layer (12).

2. The self-heating anti-freezing drainage pipeline system for high-altitude permafrost regions according to claim 1, characterized in that, The wall structure of the self-heating pipe module is arranged from the inside to the outside as an inner pipe layer (11), an integrated electric heating layer (12), an insulation layer (13), and an outer sheath (14). The inner pipe layer (11) is made of high-density polyethylene, and the insulation layer (13) is made of rigid polyurethane foam.

3. A self-heating, anti-freezing drainage pipeline system for high-altitude permafrost regions according to claim 2, characterized in that, The self-regulating heating wires in the integrated heating layer (12) are arranged in parallel and embedded in the inner tube layer (11).

4. A self-heating, anti-freezing drainage pipeline system for high-altitude permafrost regions according to claim 1, characterized in that, The energy supply module also includes auxiliary energy, which is a thermoelectric generator (4).

5. A self-heating, anti-freezing drainage pipeline system for high-altitude permafrost regions according to claim 4, characterized in that, The core controller calculates the thawing rate as follows: after determining that the pipeline has frozen and initiating heating, a preset sampling period Δt is used to continuously collect and store N temperature measurements {T1, T2, ..., T...} inside the pipeline over a past period W. N }, forming a sliding temperature time series data window; where the time window width is W=N×Δt; The least squares method is used to perform linear regression analysis on the N temperature measurements within the temperature time series data window to calculate the slope KT of the best-fit line of the temperature time series data window, which is defined as the real-time thawing rate R, and the unit of the real-time thawing rate R is °C / second.

6. A self-heating, anti-freezing drainage pipeline system for high-altitude permafrost regions according to claim 5, characterized in that, The core controller is a low-power microcontroller, and its memory contains a heating power mapping table corresponding to different thawing rate R value ranges.

7. A control method for a self-heating anti-freezing drainage pipeline in a high-altitude permafrost region, applied to the self-heating anti-freezing drainage pipeline system for high-altitude permafrost regions as described in any one of claims 1-6, characterized in that, Includes the following steps: S1: Preset temperature threshold, flow rate threshold, and target thawing rate related to the severity of freezing. ; S2: Real-time monitoring of temperature T and flow velocity V inside the pipeline via sensing unit; S3: When the conditions of T≤0℃ and V=0 are met, the pipeline is determined to be in a frozen state, the integrated electric heating layer (12) is activated and the real-time thawing rate R is calculated. S4: Compare the real-time thawing rate R with the target thawing rate The comparison is made, and the output power of the integrated electrothermal layer (12) is intelligently controlled according to the comparison results until the flow rate V returns to the normal range.

8. A method for controlling self-heating antifreeze drainage pipelines in high-altitude permafrost regions according to claim 7, characterized in that, The specific strategies for intelligent control in step S4 include: When R < If the current heating power is insufficient to ensure rapid and effective defrosting, the integrated electric heating layer (12) is controlled to increase the power output. When R= Or, if the current heating power is within the allowable error range, determine that the current heating power is appropriate and maintain the current power level to continue heating; When R> If the current heating power is determined to be too high and energy is wasted, the integrated electric heating layer (12) is controlled to reduce the power output until R drops back to near the specified level. The level.

9. A method for controlling self-heating antifreeze drainage pipelines in high-altitude permafrost regions according to claim 7, characterized in that, In step S3, the core controller also executes a predictive control strategy based on a thermodynamic model, including: S3.1: Real-time calculation of predicted freezing time (TTF), which is defined as the time required for the water in the pipe to drop from the current temperature to the freezing point under the current environmental heat dissipation conditions; S3.2: Monitor and calculate the natural cooling rate K of the water in the pipe. Based on the volume and heat capacity of the water in the pipe, calculate the total heat that needs to be removed to cool it from the current temperature to the freezing point, i.e. the remaining safe enthalpy ΔH. Calculate the predicted freezing time TTF based on the natural cooling rate K and the remaining safe enthalpy ΔH. S3.3: Preset time threshold TTF t， Compare the predicted freeze time TTF with a preset time threshold TTF. t Compare them.

10. A self-heating, anti-freezing drainage pipeline system for high-altitude permafrost regions according to claim 7, characterized in that, The triggering conditions for intelligent control in step S4 include the judgment result of the predictive control strategy: When the predicted freeze time TTF is less than or equal to the time threshold TTF t At any time, regardless of whether the current medium temperature T in the pipeline is below 0°C or the flow rate V is zero, the core controller will immediately start or increase the output power of the integrated electric heating layer (12) to prevent the pipeline from entering a frozen state.

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