Medium temperature calculation method for external clamping type flow sensor

Abstract

The invention discloses an external clamping type flow sensor medium temperature calculation method, and relates to the technical field of testing and metering, and the method comprises the steps: obtaining the outer wall temperature measurement values of two sensors through a temperature collection device; by means of double-temperature-probe averaging treatment, accidental errors of single-point measurement are effectively reduced, three heat transfer mechanisms of heat transfer, solid heat conduction and convection-radiation combined heat dissipation are constructed, a fluid dynamic criterion is introduced to accurately calculate a convection heat transfer coefficient, quantitative heat transfer models outside and inside the tube are constructed, and the heat transfer efficiency is improved. By introducing an empirical formula dynamically coupled with the environment wind speed and a fluid mechanics criterion correlation formula based on the Reynolds number criterion, scene self-adaption accurate calculation of the key heat exchange coefficient is achieved, iterative correction of fluid physical property parameters is combined, and through iterative calculation and real-time correction of the physical property parameters, the real-time correction of the fluid physical property parameters is achieved. A three-layer progressive error correction system of dynamic time correction, scene database correction and multi-dimensional anti-interference correction is established, and high precision and high reliability of temperature calculation are achieved.

Description

Technical Field

[0001] This invention relates to the field of testing and measurement technology, and in particular to a method for calculating the medium temperature of an external clamp-on flow sensor. Background Technology

[0002] Clip-on ultrasonic flow sensors are widely used due to their advantages such as convenient installation and no need to damage the pipeline structure. Currently, some clip-on ultrasonic flow sensors have built-in temperature sensors to attempt to obtain temperature-related data. The accurate calculation of fluid flow rate is highly dependent on the actual temperature of the medium. The density, viscosity, sound velocity, and other key parameters of the fluid vary significantly at different temperatures, directly affecting the accuracy of flow measurement. However, in current technology, even though these clip-on flow sensors with built-in temperature sensors can collect pipe wall temperature, there is a lack of an accurate calculation method to convert the pipe wall temperature into the actual temperature of the medium inside the pipe.

[0003] In existing technologies, ultrasonic clamp-on flow sensors with built-in temperature sensors have significant drawbacks in temperature application: most simply approximate the pipe wall temperature collected by the sensor as the medium temperature, failing to consider the influence of multiple factors such as pipe heat conduction losses, ambient temperature, pipe insulation layer, and fluid velocity on temperature transmission, resulting in a large deviation between the pipe wall temperature and the actual medium temperature; the few solutions that attempt temperature correction also suffer from poor correction effects because they do not incorporate the core principles of thermodynamics and fluid mechanics to build a systematic calculation model, failing to meet the requirements of high-precision flow measurement for medium temperature data. Therefore, there is an urgent need for a scientific and accurate calculation method to deduce the true temperature of the medium inside the pipe based on the known pipe wall temperature collected by the built-in temperature sensor.

[0004] To address the aforementioned technical shortcomings, a solution is proposed. Summary of the Invention

[0005] The purpose of this invention is to construct a multi-parameter coupled temperature calculation based on the thermodynamic heat conduction law and the fluid mechanics convection heat transfer principle. By using the known pipe wall temperature collected by the sensor and related auxiliary parameters, the true temperature of the medium inside the pipe can be accurately deduced, providing reliable data support for high-precision flow rate calculation and adapting to various complex fluid transportation scenarios.

[0006] To achieve the above objectives, the present invention adopts the following technical solution: a method for calculating the medium temperature of an external clamp-on flow sensor, comprising the following steps: Step 1: Obtain the outer wall temperature measurement values ​​of the two sensors through the temperature acquisition device, and obtain the pipe outer wall temperature after averaging. Obtain the ambient temperature and ambient wind speed through the environmental parameter acquisition device, and obtain the inherent parameters of the pipe, including the pipe inner diameter, pipe wall thickness, and thermal conductivity of the pipe material. Step 2: Based on the thermodynamic laws of heat conduction and the principle of convective heat transfer, analyze the quantitative relationships of convective heat transfer, heat conduction, and combined convective-radiative heat dissipation, and construct the steady-state thermal balance equation. Step 3: Calculate the heat transfer coefficient dynamically using empirical formulas and fluid dynamics criteria, adjust the convective heat dissipation intensity dynamically based on wind speed, calculate the convective heat transfer coefficient based on turbulence, and iteratively correct the fluid properties until the temperature converges. Step 4: Based on the steady-state heat balance equation and the heat transfer coefficient calculation results, eliminate the intermediate variable of inner wall temperature and derive the value of the true medium temperature T3; Step 5: Based on the scenarios of unsteady heat transfer, contact deviation, and environmental interference, a multi-dimensional correction mechanism is introduced. The dynamic correction coefficient is adapted to the temperature change conditions. A scenario-based correction factor library is established for secondary correction calculation results. The input data is processed by moving average-Kalman filtering for noise reduction. The contact state factor and vibration correction term are introduced to enhance the robustness of the model. The wind speed dynamic weighted stability calculation heat transfer coefficient is established. The atmospheric radiation correction coefficient k3 is introduced to correct the radiation heat transfer error under high temperature environment.

[0007] Furthermore, the outer wall temperature measurements from the two sensors are acquired using temperature acquisition equipment, and the average value is then used to obtain the pipe's outer wall temperature. The specific process is as follows: The temperature of the outer wall of the pipeline is obtained by direct contact between at least two temperature sensing units symmetrically arranged on the body of the external clamp-on flow sensor and the outer wall of the pipeline. The data dimension is unified by a standardized storage format, and the average or weighted average of the measured values ​​of each sensing unit is taken as T1.

[0008] Furthermore, the steady-state thermal balance model is specifically a set of equations established under the steady-state heat transfer assumption, including the following process: The heat transfer process in a piping system mainly includes three stages: convective heat transfer between the fluid and the inner wall of the pipe, heat conduction through the pipe wall, and combined convective and radiative heat dissipation between the outer wall of the pipe and the environment. Heat balance equation: ; in, The heat transfer through convection between the fluid and the inner wall of the pipe, according to Newton's law of cooling, ; A1 is the inner wall area of ​​the pipe. d is the inner diameter of the pipe, L is the length of the pipe section measured by the sensor, T3 is the actual temperature of the medium inside the pipe, and T4 is the temperature of the inner wall of the pipe. Q2: The heat conduction through the pipe wall, according to Fourier's law of heat conduction... ; Q3: Total heat dissipation between the pipe's outer wall and the environment, including convective heat dissipation Q31 and radiative heat dissipation Q32. ; A2 is the outer wall area of ​​the pipe, A2 = π·(d + 2δ)·L; h1 is the heat transfer coefficient of the outer wall of the pipe, which is related to the ambient wind speed. The heat transfer coefficient h1 of the outer wall of the pipe is calculated according to the empirical formula for ambient wind speed. The empirical formula is: ; ε is the emissivity of the outer wall of the pipe, and σ is the Stefan-Boltzmann constant. = .

[0009] Furthermore, based on the steady-state heat balance equation and the heat transfer coefficient calculation results, the intermediate variable of the inner wall temperature is eliminated, and the value of the true medium temperature T3 is derived. The specific process is as follows: By using the heat balance equations Q1 = Q2 = Q3 and the calculated h1 and h2, and eliminating T4 by solving the simultaneous equations, the formula for calculating the true temperature T3 of the medium is finally derived: ; Substitute the calculated value of Q3 into the formula to solve for T3.

[0010] Furthermore, the iterative correction of fluid property parameters until temperature convergence also includes iterative optimization steps: Set an initial estimate for the actual temperature T3 of the medium; Based on the current T3 estimate, determine or update the fluid's physical properties, including density, viscosity, specific heat capacity, and thermal conductivity. The convective heat transfer coefficient h2 was recalculated using the updated fluid properties. Based on the recalculated h2, a new calculated value for T3 is obtained by solving the heat balance model. Determine whether the deviation between the new calculated T3 value and the current estimated value is less than the preset tolerance; If not, use the new calculated T3 value as the estimate for the next iteration; if yes, output the final true temperature T3 of the medium.

[0011] Furthermore, a multi-dimensional correction mechanism is introduced. By dynamically adjusting the correction coefficient to adapt to sudden temperature changes, a scenario-based correction factor library is established to perform secondary correction calculations. The specific process is as follows: The raw data sequence obtained directly from the sensors, including pipe outer wall temperature, ambient temperature, fluid flow rate and ambient wind speed, is subjected to time-series filtering. The time-series filtering process employs two or more combinations of moving average filtering, median filtering, and Kalman filtering to eliminate random noise, impulse interference, and trend drift in the original data. A dynamic time correction factor is introduced to compensate for the transient process of the thermal equilibrium model when the medium temperature or ambient temperature changes rapidly. Establish and maintain a scenario correction factor database, which stores multiple sets of predefined combination correction coefficients, each set of combination correction coefficients being associated with a specific combination of working conditions and scenarios; The dimensions of the combined working conditions include at least two of the following: pipe material, pipe wall thickness, insulation material, insulation thickness, and fluid type. Based on the pipe parameters, insulation layer condition, and fluid type in the actual measurement scenario, query the scenario correction factor database to obtain the corresponding combined correction coefficients; The obtained combined correction coefficients are used to perform a secondary calibration on the actual temperature of the medium calculated based on the thermal balance model.

[0012] Furthermore, a contact state factor and a vibration correction term are introduced to enhance the robustness of the model. The specific process is as follows: Real-time and periodic assessment of the contact status between the temperature probe of the clamp-on flow sensor and the outer wall of the pipe; Based on the evaluation results, a contact thermal resistance correction factor is determined; Perform the following operations using the contact thermal resistance correction factor: The measured value of the pipe outer wall temperature T1 is directly corrected; The thermal resistance term of the pipe wall and the calculation formula for the amount of heat conducted are revised in the heat balance model. Obtain parameters related to the pipeline vibration intensity, and calculate an additional heat exchange correction term based on the vibration intensity parameters; An additional heat exchange correction term is introduced into the steady-state heat balance equation to quantify and compensate for the impact of mechanical vibration on the pipeline heat conduction efficiency and the overall heat transfer process.

[0013] Furthermore, an atmospheric radiation correction factor k3 is introduced to correct for radiative heat transfer errors under high-temperature conditions. The specific steps are as follows: Establish a dynamic weighted model for wind speed, used to calculate based on ambient wind speed. The measured values ​​and their changing trends are used to dynamically adjust the weighting parameters in the empirical formula used to calculate the heat transfer coefficient h1 of the outer wall of the pipe, so as to stabilize the calculation results of h1. An atmospheric radiation correction coefficient k3 is introduced to correct the calculated value of the heat dissipation Q32 from the outer wall of the pipe in the heat balance model under high temperature environment or strong solar radiation scenario, so as to compensate for the error caused by the ambient background radiation to the measurement.

[0014] In summary, due to the adoption of the above technical solution, the beneficial effects of the present invention are: This clamp-on flow sensor medium temperature calculation method effectively reduces single-point measurement random errors and improves the reliability of pipe outer wall temperature characterization by averaging the values ​​from dual temperature probes. It constructs three major heat transfer mechanisms: convective heat transfer, solid conduction, and combined convection-radiation heat dissipation. Fluid dynamics criteria are introduced to accurately calculate the convective heat transfer coefficient, and a quantitative heat transfer model is built for both the outside and inside of the pipe. By introducing empirical formulas dynamically coupled with ambient wind speed and fluid dynamics criteria based on Reynolds number, scenario-adaptive and accurate calculation of key heat transfer coefficients is achieved. Combined with iterative correction of fluid property parameters, flow calculation errors are corrected from the source through iterative calculation and real-time correction of property parameters. A three-layer progressive error correction system is established, consisting of dynamic time correction, scenario-based database correction, and multi-dimensional anti-interference correction. This system can adaptively compensate for unsteady operating conditions, complex environmental interference, and changes in installation conditions, ensuring the robustness and reliability of the algorithm in real industrial scenarios and achieving high accuracy and high reliability in temperature calculation. Attached Figure Description

[0015] Figure 1 A schematic diagram of the method steps of the present invention is shown. Detailed Implementation

[0016] 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, and 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.

[0017] Example 1: like Figure 1 As shown, a method for calculating the medium temperature of an external clamp-on flow sensor includes the following steps: Step 1: Obtain the outer wall temperature measurement values ​​of the two sensors through the temperature acquisition device, and obtain the pipe outer wall temperature after averaging. Obtain the ambient temperature and ambient wind speed through the environmental parameter acquisition device, and obtain the inherent parameters of the pipe, including the pipe inner diameter, pipe wall thickness, and thermal conductivity of the pipe material. Step 2: Based on the thermodynamic laws of heat conduction and the principle of convective heat transfer, analyze the quantitative relationships of convective heat transfer, heat conduction, and combined convective-radiative heat dissipation, and construct the steady-state thermal balance equation. Step 3: Calculate the heat transfer coefficient dynamically using empirical formulas and fluid dynamics criteria, adjust the convective heat dissipation intensity dynamically based on wind speed, calculate the convective heat transfer coefficient based on turbulence, and iteratively correct the fluid properties until the temperature converges. Step 4: Based on the steady-state heat balance equation and the heat transfer coefficient calculation results, eliminate the intermediate variable of inner wall temperature and derive the value of the true medium temperature T3; Step 5: Based on the scenarios of unsteady heat transfer, contact deviation and environmental interference, a multi-dimensional correction mechanism is introduced. The dynamic correction coefficient is adapted to the temperature change condition. A scenario-based correction factor library is established for secondary correction calculation results. The input data is processed by moving average-Kalman filtering for noise reduction. The contact state factor and vibration correction term are introduced to enhance the robustness of the model. The wind speed dynamic weighted stable calculation heat transfer coefficient is established. The atmospheric radiation correction coefficient k3 is introduced to correct the radiation heat transfer error under high temperature environment. A dynamic correction coefficient k1 is introduced to correct Q3 and adapt to unsteady heat transfer scenarios. k1 is derived based on the heat transfer time constant and includes sudden changes in medium temperature and fluctuations in ambient temperature. Establish a scenario-based correction factor database for different pipe materials and insulation layer thicknesses, and perform secondary correction on the calculation results by looking up tables; To address interference in industrial settings, a multi-dimensional anti-interference design has been added: Data preprocessing anti-interference: For T1, T2, v1, and v2, a combination of moving average filtering and Kalman filtering is used to eliminate random noise and trend interference; Model robustness optimization: A contact state correction factor k2 is introduced to correct the temperature measurement deviation caused by poor contact between the sensor probe and the pipe wall; a pipe vibration correction term ΔQ is introduced into the heat balance equation to quantify the impact of vibration on the pipe heat conduction efficiency. Environmental disturbance adaptive correction: A dynamic weighted model of wind speed is established to stabilize the calculation of h1; an atmospheric radiation correction coefficient k3 is introduced to correct the radiative heat transfer error under high temperature environment.

[0018] The outer wall temperature of the pipe is obtained by acquiring the measured values ​​of the outer wall temperature from two sensors using a temperature acquisition device, and then averaging the values. The specific process is as follows: The temperature of the outer wall of the pipeline is obtained by direct contact between at least two temperature sensing units symmetrically arranged on the body of the external clamp-on flow sensor and the outer wall of the pipeline. The data dimension is unified by a standardized storage format, and the average or weighted average of the measured values ​​of each sensing unit is taken as T1.

[0019] The steady-state thermal equilibrium model is specifically a set of equations established under the assumption of steady-state heat transfer, including the following process: The heat transfer process in a piping system mainly includes three stages: convective heat transfer between the fluid and the inner wall of the pipe, heat conduction through the pipe wall, and combined convective and radiative heat dissipation between the outer wall of the pipe and the environment. Heat balance equation: ; in, The heat transfer through convection between the fluid and the inner wall of the pipe, according to Newton's law of cooling, ; A1 is the inner wall area of ​​the pipe. d is the inner diameter of the pipe, L is the length of the pipe section measured by the sensor, T3 is the actual temperature of the medium inside the pipe, and T4 is the temperature of the inner wall of the pipe. Q2: The heat conduction through the pipe wall, according to Fourier's law of heat conduction... Q3: Total heat dissipation between the pipe's outer wall and the environment, including convective heat dissipation Q31 and radiative heat dissipation Q32. ; When dynamically correcting the heat dissipation Q3 , A2 is the outer wall area of ​​the pipe, A2 = π·(d + 2δ)·L; h1 is the heat transfer coefficient of the outer wall of the pipe, which is related to the ambient wind speed. The heat transfer coefficient h1 of the outer wall of the pipe is calculated according to the empirical formula for ambient wind speed. The empirical formula is: ; ε is the emissivity of the outer wall of the pipe, and σ is the Stefan-Boltzmann constant. = ; Use k3 for correction hour, .

[0020] Based on the steady-state heat balance equation and the heat transfer coefficient calculation results, the intermediate variable of the inner wall temperature is eliminated, and the value of the true medium temperature T3 is derived. The specific process is as follows: By using the heat balance equations Q1 = Q2 = Q3 and the calculated h1 and h2, and eliminating T4 by solving the simultaneous equations, the formula for calculating the true temperature T3 of the medium is finally derived: ; Substitute the calculated value of Q3 into the formula to solve for T3.

[0021] Iteratively correcting fluid properties until temperature convergence also includes iterative optimization steps: Set an initial estimate for the actual temperature T3 of the medium; Based on the current T3 estimate, determine or update the fluid's physical properties, including density, viscosity, specific heat capacity, and thermal conductivity. The convective heat transfer coefficient h2 was recalculated using the updated fluid properties. Based on the recalculated h2, a new calculated value for T3 is obtained by solving the heat balance model. Determine whether the deviation between the new calculated T3 value and the current estimated value is less than the preset tolerance; If not, use the new calculated T3 value as the estimate for the next iteration; if yes, output the final true temperature T3 of the medium.

[0022] A multi-dimensional correction mechanism is introduced, which adapts to sudden temperature changes through dynamic correction coefficients and establishes a scenario-based correction factor library for secondary correction calculation results. The specific process is as follows: The raw data sequence obtained directly from the sensors, including pipe outer wall temperature, ambient temperature, fluid flow rate and ambient wind speed, is subjected to time-series filtering. The time-series filtering process employs two or more combinations of moving average filtering, median filtering, and Kalman filtering to eliminate random noise, impulse interference, and trend drift in the original data. A dynamic time correction factor is introduced, which is derived theoretically or experimentally calibrated based on the heat transfer time constant, to compensate for the transient process of the heat balance model when the medium temperature or ambient temperature changes rapidly. Establish and maintain a scenario correction factor database, which stores multiple sets of predefined combination correction coefficients, each set of combination correction coefficients being associated with a specific combination of working conditions and scenarios; The dimensions of the combined working conditions include at least two of the following: pipe material, pipe wall thickness, insulation material, insulation thickness, and fluid type. Based on the pipe parameters, insulation layer condition, and fluid type in the actual measurement scenario, query the scenario correction factor database to obtain the corresponding combined correction coefficients; The obtained combined correction coefficients are used to perform a secondary calibration on the actual temperature of the medium calculated based on the thermal balance model.

[0023] To enhance the robustness of the model, a contact state factor and a vibration correction term are introduced. The specific process is as follows: Real-time and periodic assessment of the contact status between the temperature probe of the clamp-on flow sensor and the outer wall of the pipe; Based on the evaluation results, a contact thermal resistance correction factor is determined by evaluating the contact state between the sensor and the pipe wall in real time. Perform the following operations using the contact thermal resistance correction factor: The measured value of the pipe outer wall temperature T1 is directly corrected; The thermal resistance term of the pipe wall and the calculation formula for the amount of heat conducted are revised in the aforementioned heat balance model; Obtain parameters related to the pipeline vibration intensity, and calculate an additional heat exchange correction term based on the vibration intensity parameters; The additional heat exchange correction term is introduced into the steady-state heat balance equation to quantify and compensate for the impact of mechanical vibration on the pipeline heat conduction efficiency and the overall heat transfer process.

[0024] An atmospheric radiation correction factor k3 is introduced. k3 mainly depends on environmental parameters looked up in a table to correct for radiative heat transfer errors under high-temperature conditions. The specific steps are as follows: Establish a dynamic weighted model for wind speed, used to calculate based on ambient wind speed. The measured values ​​and their changing trends are used to dynamically adjust the weighting parameters in the empirical formula used to calculate the heat transfer coefficient h1 of the outer wall of the pipe, so as to stabilize the calculation results of h1. An atmospheric radiation correction coefficient k3 is introduced to correct the calculated value of the heat dissipation Q32 of the outer wall of the pipe in the heat balance model under high temperature environment or strong solar radiation scenario, so as to compensate for the error caused by the ambient background radiation to the measurement. This embodiment uses an existing mature ultrasonic clamp-on flow sensor (with built-in temperature sensor) as the basis for data acquisition. This sensor is compatible with DN100 carbon steel pipes with a diameter of 100mm, a thermal conductivity λ1 = 45 W / (m·K), and a wall thickness δ = 5mm. It has two built-in temperature sensors, symmetrically installed at both ends of the sensor body and the pipe contact surface. The probe is in close contact with the outer wall of the pipe through a thermally conductive silicone pad, and can output the average value of the pipe wall temperature. The structure and basic acquisition function of the above sensor are all existing technologies. This embodiment focuses on demonstrating the specific application process of the calculation method of the present invention.

[0025] Algorithm Example: Taking the measurement of tap water flow rate as an example (the fluid is water, and the standard physical properties at room temperature are: density) viscosity Specific heat capacity thermal conductivity ; The specific implementation steps are as follows: 1. Parameter Acquisition: The temperature of the outer wall of the pipe is measured by a built-in temperature sensor. If the two sensors measure 25.2℃ and 25.4℃ respectively, take the average value, which is the ambient temperature. Ambient wind speed Measuring fluid flow rate ; 2. Calculate the heat transfer coefficient h1 of the outer wall of the pipe: Substitute into the empirical formula - 3. Calculate the convective heat transfer coefficient h2: Reynolds number ; Prandtl number ; Nusel number ; Convective heat transfer coefficient ; Pipe outer wall area ; Convection heat dissipation ; Heat dissipation Q32 = 0.8 × 5.67 × 10⁻ 8×0.0691×(298.45 4 - 293.25 4 ) ≈ 1.8 W; Total heat dissipation Q3 = 7.2 + 1.8 = 9 W; Derivation of the true temperature T3 of the medium: Since Q1 = Q2 = Q3 = 9 W, substituting into the formula, we get: T3 = 25.3 + [9×ln((0.1 + 2×0.005) / 0.1)] / (2π×45×0.2) + 9 / (3584×π×0.1×0.2) ≈ 25.3 + 0.015 + 0.401 ≈ 25.7℃; By iteratively correcting the values, T3 = 25.7℃ was substituted into the fluid property parameters and h2 and T3 were recalculated, finally yielding T3 = 25.8℃. Accuracy verification: The actual measurement value of the insertion temperature sensor was 25.7℃, and the measurement error of this algorithm was only 0.1℃, which meets the requirements of industrial measurement. Flow rate calculation: Based on T3 = 25.8℃, the density and viscosity parameters of water are corrected, and the flow rate is calculated to obtain an accurate flow rate value.

[0026] The setting of the interval and threshold is for the purpose of facilitating comparison. The size of the threshold depends on the amount of sample data and the number of bases set by those skilled in the art for each set of sample data; as long as it does not affect the ratio between the parameter and the quantized value.

[0027] The above formulas are all dimensionless calculations. The formulas are derived from software simulations based on a large amount of collected data to obtain the most recent real-world results. The preset parameters in the formulas are set by those skilled in the art according to the actual situation. In the two embodiments provided in this application, it should be understood that the disclosed methods can be implemented in other ways; for example, the device embodiments described above are merely illustrative, and the division of modules is merely a logical functional division. In actual implementation, there may be other division methods, such as multiple modules or components can be combined or integrated into another system, or some features can be ignored or not executed; another point is that the mutual coupling or direct coupling or communication connection shown or discussed may be through some interfaces, and the indirect coupling or communication connection of devices or modules may be electrical, mechanical or other forms. The above description is only a preferred embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any equivalent substitutions or modifications made by those skilled in the art within the scope of the technology disclosed in the present invention, based on the technical solution and inventive concept of the present invention, should be covered within the scope of protection of the present invention.

Claims

1. An outside clip-on flow sensor media temperature calculation method, characterized by, The method comprises the following steps: Step 1: Obtain the outer wall temperature measurement values of the two sensors through the temperature acquisition device, and obtain the pipeline outer wall temperature after mean value processing, and obtain the environmental temperature, environmental wind speed through the environmental parameter acquisition device, and obtain the pipeline inherent parameters including the pipeline inner diameter, pipeline wall thickness, and pipeline material thermal conductivity; Step 2: Based on the thermodynamic heat conduction law and the convection heat transfer principle, analyze the equivalent relationship of convection heat transfer, heat conduction, and combined convection-radiation heat dissipation, and construct a steady-state heat balance equation; Step 3: Dynamically calculate the heat transfer coefficient through the empirical formula and the fluid mechanics correlation formula, dynamically adjust the convection heat dissipation intensity combined with the wind speed, calculate the convection heat transfer coefficient based on the turbulent flow, and iteratively correct the fluid physical property parameters until the temperature converges; Step 4: According to the steady-state heat balance equation and the heat transfer coefficient calculation result, eliminate the intermediate variable inner wall temperature, and derive the numerical value of the medium real temperature T3; Step 5: According to the unsteady-state heat transfer, contact deviation and environmental interference scene, introduce a multi-dimensional correction mechanism, adapt to the temperature sudden change condition through dynamic correction coefficient, establish a scene correction factor library for secondary correction of the calculation result, use the sliding average-Kalman filter joint noise reduction processing input data, introduce the contact state factor and vibration correction term to enhance the model robustness, and establish a wind speed dynamic weighted stable calculation heat transfer coefficient, introduce the atmospheric radiation correction coefficient k3, and correct the radiation heat transfer error in the high temperature environment.

2. The method of claim 1, wherein, The pipeline outer wall temperature is measured by directly contacting the pipeline outer wall through at least two temperature sensing units symmetrically arranged on the outer clamp type flow sensor body, the data dimension is unified through a standardized storage format, and the average or weighted average of the measurement values of each sensing unit is taken as T1. The steady-state heat balance model is a set of equations established under the assumption of steady-state heat transfer, including the following processes:

3. The method of claim 1, wherein, The heat transfer process of the pipeline system mainly includes three links: fluid and pipeline inner wall convection heat transfer, pipeline wall heat conduction, and pipeline outer wall and environment combined convection-radiation heat dissipation According to the steady-state heat balance equation and the heat transfer coefficient calculation result, eliminate the intermediate variable inner wall temperature, and derive the numerical value of the medium real temperature T3, the specific process is as follows: Heat balance equation: ; wherein : convective heat transfer from the fluid to the inner wall of the pipe, according to Newton's cooling formula, ; A1 is the inner wall area of the pipe d is the inner diameter of the pipe, L is the length of the pipe measured by the sensor, T3 is the real temperature of the medium inside the pipe, and T4 is the temperature of the inner wall of the pipe. Q2: The heat transfer of the pipe wall, according to the Fourier heat transfer law, Q3: total heat dissipation of the outer wall of the pipeline to the environment, including convective heat dissipation Q31 and radiative heat dissipation Q32, ; A2 is the outer wall area of the pipeline, A2 = π·(d + 2δ)·L; h1 is the outer wall heat transfer coefficient of the pipeline, which is related to the environmental wind speed, the outer wall heat transfer coefficient h1 of the pipeline: calculated according to the empirical formula of the environmental wind speed, the empirical formula is: ; , ε is the emissivity of the outer pipe wall, σ is the Stefan-Boltzmann constant, = 0.5 .

4. The method of claim 1, wherein, Through the heat balance equation Q1 = Q2 = Q3 and the calculated h1, h2, eliminate T4 through simultaneous equations, and finally derive the calculation formula of the medium real temperature T3: Substitute the calculated value of Q3 into the formula to solve T3. ； Iterative correction of fluid physical property parameters until temperature convergence also includes the following iterative optimization steps:

5. The method of claim 1, wherein, Set the initial estimated value of the medium real temperature T3; Based on the current T3 estimated value, determine or update the physical property parameters of the fluid, including density, viscosity, specific heat capacity and thermal conductivity; Recalculate the convection heat transfer coefficient h2 using the updated fluid physical property parameters; Based on the recalculated h2, solve the new T3 calculation value through the heat balance model; Determine whether the deviation between the new T3 calculation value and the current estimated value is less than the preset tolerance; ​ If not, the new T3 calculated value is taken as the estimated value for the next iteration; if yes, the final medium real temperature T3 is output.

6. The method of claim 1, wherein, A multi-dimensional correction mechanism is introduced, and a dynamic correction coefficient is used to adapt to temperature mutation conditions. A scenario correction factor library is established to perform secondary correction on the calculation results. The specific process is as follows: The original data sequence directly measured by the sensor, including the pipe outer wall temperature, the environment temperature, the fluid flow rate and the environment wind speed, is subjected to time series filtering processing. The time series filtering processing adopts two or more combination modes of sliding average filtering, median filtering and Kalman filtering to eliminate random noise, impulse interference and trend drift in the original data A dynamic time correction factor is introduced to compensate for the transient process of the heat balance model when the medium temperature or the environment temperature changes rapidly. A scenario correction factor database is established and maintained, and a plurality of groups of predefined combination correction coefficients are stored in the database, each group of combination correction coefficients being associated with a specific working condition scenario combination. The dimensions of the working condition scenario combination include at least two of the pipe material, the pipe wall thickness, the insulation layer material, the insulation layer thickness and the fluid category. According to the pipe parameters, the insulation layer condition and the fluid category in the actual measurement scenario, the corresponding combination correction coefficient is obtained by querying the scenario correction factor database. The combination correction coefficient is used to perform secondary calibration on the medium real temperature calculated based on the heat balance model.

7. The method of claim 1, wherein, The contact state factor and the vibration correction term are introduced to enhance the robustness of the model, and the specific process is as follows: The contact state between the temperature probe of the external clamping flow sensor and the pipe outer wall is evaluated in real time and periodically. Based on the evaluation result, a contact thermal resistance correction factor is determined. The contact thermal resistance correction factor is used to perform the following operations: Directly correct the measured value of the pipe outer wall temperature T1; Correct the thermal resistance term of the pipe wall in the heat balance model and the calculation formula of the heat conduction heat; Obtain a parameter related to the pipe vibration intensity, and calculate an additional heat exchange correction term based on the vibration intensity parameter. The additional heat exchange correction term is introduced into the steady-state heat balance equation to quantify and compensate for the influence of mechanical vibration on the pipe heat conduction efficiency and the overall heat transfer process.

8. The method of claim 1, wherein, The atmospheric radiation correction coefficient k3 is introduced to correct the radiation heat transfer error in high temperature environment, and the specific steps are as follows: Establish a dynamic weighted model for wind speed, used to calculate based on ambient wind speed. The measured values ​​and their changing trends are used to dynamically adjust the weighting parameters in the empirical formula used to calculate the heat transfer coefficient h1 of the outer wall of the pipe, so as to stabilize the calculation results of h1. The atmospheric radiation correction coefficient k3 is introduced to correct the calculation value of the pipe outer wall radiation heat dissipation Q32 in the heat balance model in high temperature environment or strong solar radiation scenario, so as to compensate for the error caused by the environmental background radiation to the measurement.

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