CN-122016927-A - Online evaluation method for heat insulation performance of pipeline

CN122016927ACN 122016927 ACN122016927 ACN 122016927ACN-122016927-A

Abstract

The invention provides an online evaluation method for heat preservation performance of a pipeline, and belongs to the technical field of monitoring of heat preservation performance of pipelines. The method solves the problem that the prior art relies on personnel experience to judge and the performance evaluation is inaccurate. The on-line evaluation method for the heat preservation performance of the pipeline comprises the steps of collecting actual measurement temperature of the outer surface of the heat preservation layer, collecting environment temperature, wind speed and medium temperature in the pipeline, obtaining comprehensive heat exchange coefficients of the outer surface of the pipeline and air in the current environment, constructing a heat preservation layer outer surface temperature prediction model, adjusting heat preservation layer thermal resistance through an iterative optimization algorithm to enable root mean square error between the predicted temperature of the outer surface of the heat preservation layer and the actual measurement temperature of the outer surface of the heat preservation layer obtained through the prediction model to be minimum, and evaluating the heat preservation performance state of the corresponding heat preservation layer according to a ratio by taking the heat preservation layer thermal resistance at the moment as optimal heat preservation layer thermal resistance and design thermal resistance when the root mean square error is smaller than a preset threshold value. The invention can ensure accurate and reliable evaluation results of the heat preservation state of the pipeline under different climates and working conditions.

Inventors

LOU YONGSHENG
WU TAO
ZHANG JI
LI JIE
YE YONGWANG
XU XINYE

Assignees

台州市特种设备检验检测研究院

Dates

Publication Date: 20260512
Application Date: 20260414

Claims (10)

1. The on-line evaluation method for the heat preservation performance of the pipeline is characterized by comprising the following steps of: S1, data acquisition, namely acquiring the actually measured temperature of the outer surface of the heat-insulating layer of a plurality of measuring points along the pipeline in a preset period And collect the ambient temperature Wind speed Medium temperature in pipeline ; S2, carrying out inversion calculation of dynamic thermal resistance, and executing the following substeps on each measuring point: s21, according to the wind speed External diameter of pipeline heat-insulating layer Ambient temperature Kinematic viscosity of ambient air below And air physical parameters Obtaining a comprehensive heat exchange coefficient h of the outer surface of the pipeline and air in the current environment; s22, constructing a heat-insulating layer outer surface temperature prediction model for establishing medium temperature Ambient temperature Thermal resistance of heat insulation layer Thermal resistance of pipe wall Comprehensive heat exchange coefficient h and predicted temperature of outer surface of heat preservation layer A calculated relationship between the two; S23, measuring the temperature by using the outer surface of the heat-insulating layer of each measuring point Adjusting the thermal resistance of the heat preservation layer to be a target value through an iterative optimization algorithm The predicted temperature of the outer surface of the heat-insulating layer obtained by the predicted model of the temperature of the outer surface of the heat-insulating layer With the outer surface of the heat-insulating layer The root mean square error RMSE between them is minimal; s24, stopping iterative optimization when the Root Mean Square Error (RMSE) is smaller than a preset threshold value, and heating resistance of the heat insulation layer at the moment The output is the optimal thermal resistance of the heat insulation layer of the measuring point ; S3, evaluating performance according to the optimal thermal resistance value of each measuring point With a preset design thermal resistance And evaluating the thermal insulation performance state of the corresponding thermal insulation layer position.
2. The method for online evaluation of heat insulation performance of a pipeline according to claim 1, wherein in the step S21, the step of obtaining the integrated heat exchange coefficient h includes: obtaining Reynolds number by equation one The first formula is: Wherein, the Is the kinematic viscosity of the ambient air, through the ambient temperature Obtaining by looking up a table; The diameter of the heat-insulating layer of the pipeline; By ambient temperature Obtaining air physical parameters by looking up a table ; Obtaining the number of noose by equation two The formula II is as follows: ; Number of noose The definition is as follows: ; The comprehensive heat exchange coefficient h is obtained by deformation: Wherein, the Is the thermal conductivity of air.
3. The method according to claim 1 or 2, wherein in the step S22, the step of predicting the external surface temperature of the heat insulation layer includes: Determination of Heat flux Density by equation three Wherein The heat transferred through the wall surface of the pipeline in unit area and unit time is represented by the formula III: ; ; Wherein, the Is the temperature of the medium in the pipeline, In order to be at the temperature of the environment, For the total thermal resistance of each layer, Is the thermal resistance of the pipe wall, , For the thickness of the tube wall, The heat conductivity coefficient of the pipe is the heat conductivity coefficient of the pipe; is the convective thermal resistance of the outer surface, ; Based on the heat flux density The heat-insulating layer external surface temperature prediction model is constructed as follows: ; = ; ; Wherein, the For the temperature drop of the tube wall, In order to reduce the temperature of the heat-insulating layer, In order to achieve the heat flux density, The temperature is predicted for the outer surface of the heat-insulating layer.
4. The method according to claim 1 or 2, wherein in step S23, the thermal resistance of the insulation layer is adjusted by an iterative optimization algorithm The operation of (1) comprises: setting a thermal resistance update step length : ; Wherein, the For the gradient of the kth iteration, ; For the hessian matrix approximation, For a dynamically adjusted damping coefficient, The temperature is predicted for the outer surface of the heat-insulating layer of the ith measuring point, Is used as the thermal resistance of the heat-insulating layer, Predicting the deviation between the temperature and the measured value of the outer surface of the heat-insulating layer for the i-th measuring point; The thermal resistance of the heat preservation layer after each iteration optimization algorithm is adjusted is set as : Wherein, the The thermal resistance of the heat preservation layer is adjusted through the kth iterative optimization algorithm.
5. The method for online evaluation of insulation performance of a pipeline according to claim 4, wherein in the step S3, stopping the iterative optimization further comprises: Calculating thermal resistance of heat insulation layer after each iterative optimization algorithm is adjusted Sum of squares of residuals of (2) : ; Wherein n is the number of valid measurement points in the calculation unit, The predicted temperature and the measured value of the outer surface of the heat preservation layer of the ith measuring point are respectively obtained; Calculating the residual square sum of the current iteration step Sum of squares of residuals from previous iteration step Absolute value of variation of (2) : ; When (when) When the residual error threshold value is smaller than the preset residual error threshold value, thermal resistance of the heat insulation layer at the moment The output is the optimal thermal resistance of the heat insulation layer of the measuring point 。
6. The method for online evaluation of thermal insulation performance of a pipeline according to claim 5, wherein thermal resistance of the insulation layer is adjusted by an iterative optimization algorithm Further comprising the operations of: comparing the residual square sum of the current iteration step Sum of squares of residuals from previous iteration step ; If it is Determining that iterative updates are valid while reducing damping coefficients For the next iteration; If it is Determining that the iteration update is invalid, and maintaining While increasing the damping coefficient For the next iteration.
7. The method for online evaluation of insulation performance of a pipeline according to claim 1, wherein in the step S23, stopping the iterative optimization further comprises: setting the maximum iteration number ; When (when) And stopping iterative optimization.
8. The method according to claim 1, wherein in the step S23, the root mean square error RMSE is obtained by calculating the formula four: RMSE= wherein n is the number of valid measurement points in the calculation unit, The predicted temperature and the measured value of the outer surface of the heat preservation layer of the ith measuring point are respectively obtained.
9. The method for online evaluation of insulation performance of a pipeline according to claim 1, wherein in the step S3, the performance evaluation further comprises: Optimal thermal resistance value based on each measuring point Calculating real-time heat flux density : ; Calculating real-time heat per acquisition period : , Wherein, the Is the heat exchange area of the pipe section, , The diameter of the insulating layer; is the length of the pipe section; counting accumulated heat loss energy in period : , Wherein, the In order to count the number of acquisitions in a cycle, Is the acquisition period.
10. The on-line assessment method according to claim 1 or 9, wherein the on-line assessment method further comprises a defect type deducing step of: actually measuring the temperature from the outer surface of the heat-insulating layer Ambient humidity RH and the optimal thermal resistance Extracting at least two characteristics including a temperature spatial distribution form, a thermal resistance spatial distribution characteristic, a thermal resistance time change rate, an average relative humidity value and humidity-thermal resistance correlation; Matching the extracted features with a plurality of defect types defined in a preset defect feature library; and outputting the defect type or defect probability according to the matching result.

Description

Online evaluation method for heat insulation performance of pipeline Technical Field The invention belongs to the technical field of pipeline heat preservation performance monitoring, and relates to an online pipeline heat preservation performance assessment method. Background In the industrial fields of petroleum, chemical industry, electric power, central heating and the like, the heat preservation performance of the pipeline directly relates to the energy efficiency and the safety of the system. At present, the distributed optical fiber temperature measurement technology has been primarily applied to pipeline temperature monitoring. According to the technology, the temperature sensing optical cable is laid on the outer surface of the heat-insulating layer of the pipeline, so that the temperature distribution measurement in long distance and continuous space can be realized, and the possibility of finding local overheat or abnormal temperature is provided. However, existing monitoring schemes based on this technology still have significant limitations: the data value is not fully mined, namely, only the visualization of the temperature field is realized, and the result depends on the experience of personnel to judge and can not be automatically converted into quantitative evaluation of the equivalent thermal resistance of the heat preservation layer. The failure traceability is lacking, namely that whether the surface temperature abnormality is caused by the immersion of the heat insulation layer, physical damage and insufficient thickness or simply caused by the change of the ambient wind speed is difficult to distinguish, so that the maintenance decision is blind. The model has insufficient adaptability, most methods adopt a simplified steady-state model, and the calculation error of heat loss is large under variable working conditions such as medium temperature fluctuation, day-night temperature difference and the like. In summary, how to break through the limitation of the prior art in the aspects of data deep utilization, fault intelligent tracing and model dynamic adaptability, develop an evaluation method which can integrate multi-source monitoring data, adapt to variable working conditions, realize on-line quantitative inversion and automatic diagnosis of heat preservation performance parameters, become key technical challenges for ensuring that the evaluation result of the heat preservation state of the pipeline can be kept accurate and reliable under different climates and operation working conditions, and have important significance for improving the energy efficiency management level of the pipeline system and realizing predictive maintenance. Disclosure of Invention The invention aims to solve the problems in the prior art, and provides an online evaluation method for the heat preservation performance of a pipeline, which aims to solve the technical problem of ensuring accurate and reliable evaluation results of the heat preservation state of the pipeline under different climates and working conditions. The invention aims at realizing the technical scheme that the pipeline heat preservation performance on-line evaluation method comprises the following steps: S1, data acquisition, namely acquiring the actually measured temperature of the outer surface of the heat-insulating layer of a plurality of measuring points along the pipeline in a preset period And collect the ambient temperatureWind speedMedium temperature in pipeline; S2, carrying out inversion calculation of dynamic thermal resistance, and executing the following substeps on each measuring point: s21, according to the wind speed External diameter of pipeline heat-insulating layerAmbient temperatureKinematic viscosity of ambient air belowAnd air physical parametersObtaining a comprehensive heat exchange coefficient h of the outer surface of the pipeline and air in the current environment; s22, constructing a heat-insulating layer outer surface temperature prediction model for establishing medium temperature Ambient temperatureThermal resistance of heat insulation layerThermal resistance of pipe wallComprehensive heat exchange coefficient h and predicted temperature of outer surface of heat preservation layerA calculated relationship between the two; S23, measuring the temperature by using the outer surface of the heat-insulating layer of each measuring point Adjusting the thermal resistance of the heat preservation layer to be a target value through an iterative optimization algorithmThe predicted temperature of the outer surface of the heat-insulating layer obtained by the predicted model of the temperature of the outer surface of the heat-insulating layerWith the outer surface of the heat-insulating layerThe root mean square error RMSE between them is minimal; s24, stopping iterative optimization when the Root Mean Square Error (RMSE) is smaller than a preset threshold value, and heating resistance of the heat insulation layer at th