A valve internal leakage qualitative trend analysis method and device based on a valve temperature field

Abstract

The present application relates to valve leakage monitoring technical field, specifically to a kind of valve leakage qualitative trend analysis method and device based on valve temperature field suitable for nuclear power plant main steam pipeline air extraction pipeline valve.It includes: according to the temperature signal of real-time acquisition pipeline outer wall, the temperature of corresponding several points of pipeline inner wall is automatically calculated with pipeline inner wall temperature calculation module along with time change;Based on the time series temperature variation characteristic parameter extraction of pipeline inner wall temperature signal, including the temperature change rate along the axial direction of pipeline and the temperature change rate along with time change establish the functional relationship of valve leakage flow under different flow conditions, and establish valve leakage detection model in combination with time series temperature variation characteristic parameter;Valve leakage detection device is actually applied, and based on the actual situation of application, the above-mentioned modeling step is repeated, and valve leakage model is continuously optimized.A beneficial effect is that the accuracy of predicting valve leakage flow is improved.

Description

Technical Field

[0001] This invention relates to the field of valve internal leakage monitoring technology, specifically to a method and apparatus for qualitative trend analysis of valve internal leakage based on valve temperature field, applicable to valves in the extraction pipeline of the main steam pipeline of a nuclear power plant. Background Technology

[0002] In nuclear power plants, valves on the main steam extraction lines operate under constant high temperature and pressure. Once a leak occurs, the valves are continuously subjected to the high-temperature, high-pressure steam, causing the leak to worsen and severely impacting the plant's economic efficiency. Due to the large number of valves in nuclear power plants, maintenance personnel cannot conduct comprehensive and detailed inspections of all valves in a timely manner. Therefore, it is necessary to use advanced instruments and equipment for real-time monitoring of early-stage leaks in nuclear power plant valves to effectively ensure the economic efficiency and safety of nuclear power plant operations.

[0003] Currently, valve leak detection methods mainly include infrared thermal imaging, ultrasonic leak detectors, acoustic emission, and pressure leak detection. However, for nuclear power plants with complex environments and large-scale systems, all of these leak detection methods have certain limitations.

[0004] For example, ultrasonic leak detection is easily affected by external environmental noise or pipeline vibration in power plants; pressure leak detection is not sensitive to micro-leakage; infrared thermal imaging, without the addition of additional heating or cooling devices, is difficult to capture the subtle temperature difference changes between upstream and downstream caused by micro-leakage in valves, and in most cases, the environment in which power plant valves are located cannot be equipped with additional heating or cooling devices. Summary of the Invention

[0005] The purpose of this invention is to provide a method and apparatus for qualitative trend analysis of valve internal leakage based on valve temperature field. Multiple temperature sensors are installed circumferentially and radially in the downstream pipeline, and the analysis is based on time-series temperature change characteristic parameters (temperature change rate along the pipe diameter). and the rate of temperature change over time By establishing a dynamic internal leakage monitoring model, the leakage flow rate of valve internal leakage can be estimated, thereby realizing real-time monitoring of valve internal leakage, improving the reliability of nuclear power valves, and reducing operation and maintenance costs.

[0006] The technical solution of the present invention is as follows: A valve internal leakage qualitative trend analysis device based on valve temperature field includes a main steam pipeline, an extraction pipeline, a steam valve, a main pipeline steam pressure sensor, a main pipeline steam temperature sensor, a main pipeline steam flow sensor, a valve downstream pipe wall temperature sensor, a data acquisition device, and a valve internal leakage detection terminal. The main steam pipeline is respectively equipped with a main pipeline steam pressure sensor, a main pipeline steam temperature sensor, and a main pipeline steam flow sensor. The main steam pipeline is connected to an extraction pipeline, and a steam valve is connected to the extraction pipeline. A valve downstream pipe wall temperature sensor is installed on the downstream pipe of the steam valve. The valve downstream pipe wall temperature sensor is connected to the signal acquisition device, and the signal acquisition device is connected to the valve internal leakage detection terminal.

[0007] Temperature sensors for the downstream pipe wall are installed circumferentially and radially on the downstream pipe of the steam valve.

[0008] The valve downstream pipe wall temperature sensors are evenly distributed at 30° intervals around the circumference of the pipe.

[0009] The valve downstream pipe wall temperature sensor is a thermocouple sensor.

[0010] A qualitative trend analysis method for valve internal leakage based on valve temperature field includes the following steps:

[0011] Step 1: Based on the real-time collected temperature signal of the outer wall of the pipe, the temperature change of several points on the inner wall of the pipe over time is automatically calculated by the pipe inner wall temperature calculation module.

[0012] Step 2: Extract time-series temperature variation characteristic parameters based on the pipe inner wall temperature signal, including the rate of temperature change along the pipe axis. and the rate of temperature change over time

[0013] Step 3: Establish the functional relationship between valve leakage flow rate under different flow conditions, and establish a valve internal leakage detection model based on time-series temperature variation characteristic parameters;

[0014] Step 4: Apply the valve internal leakage detection device to actual applications, and based on the actual application situation, repeat the above modeling steps to continuously optimize the valve internal leakage model.

[0015] Step 1 involves calculating the outer wall temperature using the following equations and boundary conditions:

[0016] Governing equations:

[0017]

[0018] Definite solution conditions:

[0019]

[0020] u=T1 ρ=b External wall temperature measurement conditions (3)

[0021] u=T0 ρ=a Inner wall temperature condition (4)

[0022] In the formula: T ∞ T0 is the ambient temperature; T1 is the outer wall temperature measured by the thermocouple; h is the convective heat transfer system; k is the thermal conductivity coefficient of the outer wall of the cylinder; B i =bh / k is the Biot number; given the outer wall radius b and the inner wall radius a, calculate the inner wall temperature T0;

[0023] The general solution of equation (1) is:

[0024] u=A+Blnρ (5)

[0025] Using the convective heat dissipation conditions of the outer wall (2) and the collected outer wall temperature conditions (3), the following can be solved:

[0026] A = T1 + B i (T1-T ∞ lnb (6)

[0027] B = -B i (T1-T ∞ (7)

[0028] Thus, the inner wall temperature is obtained:

[0029]

[0030] In step 2, the time-series temperature change characteristic parameters include the rate of temperature change along the pipe axis. and the rate of temperature change over time By arranging thermocouple fields at positions of -250, -200, -100, 50, 100, and 150 mm upstream and downstream of the pipeline valve, the temperature change trend along the pipeline axis after internal leakage of the valve is obtained. The temperature curves along the pipe diameter at the bottom and top of the pipeline are fitted using the least squares method, and then the temperature change rate T along the pipe diameter at the bottom and top of the pipeline is obtained. 1底 and T 1顶 Select a temperature measurement point 350mm downstream of the valve, statistically analyze the temperature change at this point over a period of time, and calculate the rate of temperature change T over time. 2底 and T 2顶 .

[0031] In step 3, based on experimental research, a highly accurate CFD pipeline valve flow field simulation model is established for various common valves; when the temperature T of the steam in the main steam pipeline... 主 Pressure P 主 Traffic Q 主When the valve type and the diameter D of the extraction pipeline change, the boundary conditions of the CFD pipeline valve flow field simulation model are set according to various parameter values ​​to obtain the temperature field data inside the pipeline after valve leakage under these conditions. Then, based on the simulation data, a valve internal leakage detection model is established to obtain the valve leakage flow rate Q. leak The functional relationship between the valve leakage flow rate and the temperature field inside the pipeline is established. Finally, based on real-time temperature field data monitored by thermocouples on the outer wall of the pipeline, the valve leakage flow rate Q is calculated using the functional relationship between the valve leakage flow rate and the temperature field inside the pipeline. leak .

[0032] In step 3, the modeling process of the valve internal leakage detection model is as follows: based on CFD simulation data, the time-series temperature change characteristic parameters T1 and T2 are extracted through step 2; then, based on the least squares method, polynomial fitting is performed on the leakage flow rate and individual characteristic parameters to determine the polynomial order of the leakage flow rate and each characteristic parameter; then, based on the polynomial order relationship between the leakage flow rate and each characteristic parameter, a multivariate equation of the leakage flow rate and all temperature characteristic parameters is established, as shown in formula (9); through multiple sets of characteristic parameters extracted from the simulation data, the multivariate equation is solved based on the multivariate linear regression model to obtain the functional relationship between the leakage flow rate and multiple temperature characteristic parameters; finally, the regression coefficient P value and the goodness of fit R are used to determine the relationship between the leakage flow rate and multiple temperature characteristic parameters. 2 Based on the verification and experimental data, and through triple verification analysis, the optimal functional relationship between valve leakage flow and pipeline temperature field was obtained, thus completing the modeling of the valve internal leakage detection model.

[0033] Q leak =α0+α1T1+α2T1 2 +...+α n T1 n +α n+1 T2+α n+2 T2 2 +...+α n+m T2 m (9)

[0034] In step 4, the circumferential and radial temperature monitoring parameters of the outer wall of the pipe are obtained based on real-time monitoring of the thermocouple field; the temperature data of several points on the inner wall of the pipe are calculated through step 1; relevant temperature characteristic parameters are extracted according to step 2; the extracted temperature parameters are input into the established valve internal leakage detection model to calculate the theoretical leakage flow rate of the valve; finally, the theoretical leakage flow rate is compared with the actual leakage flow rate measured on site. If the error is too large, steps 1-3 above are repeated to iteratively optimize the valve internal leakage detection model based on the temperature field until the error is less than 10%.

[0035] The beneficial effects of this invention are as follows: The device installs temperature sensors circumferentially and radially on the pipe wall downstream of the valve, and uses a thermocouple with good thermal conductivity and high viscosity to fix it to the outer wall of the pipe, achieving comprehensive monitoring of steam flow and gas-liquid changes in the downstream extraction pipeline. Through the pipe inner wall temperature calculation module, the pipe inner wall temperature is calculated based on the pipe outer wall temperature, and then the valve leakage flow rate is predicted based on the pipe inner wall temperature field. Compared with the method of directly using the pipe outer wall temperature to detect valve internal leakage, this method has better accuracy. This method uses the time-series temperature change signal of the downstream pipe wall to calculate the valve leakage flow rate, and combines it with the time factor to establish a dynamic valve internal leakage detection model, effectively improving the accuracy of detecting valve leakage flow rate. The internal leakage detection model not only considers the flow factors of the extraction pipeline, but also comprehensively considers the influence of different flow conditions of the main steam pipeline on valve internal leakage. By establishing the functional relationship between the main steam pipeline flow conditions, time-series temperature change characteristic parameters, and valve leakage flow rate, the valve internal leakage detection model is completed. By comprehensively analyzing the relationships between various factors affecting valve internal leakage, a functional relationship between valve leakage flow and fluid factors is established, thereby improving the accuracy of valve leakage flow prediction. Attached Figure Description

[0036] Figure 1 A schematic diagram of a valve internal leakage qualitative trend analysis device based on valve temperature field provided by the present invention;

[0037] Figure 2 A schematic diagram showing the installation location of the pipe wall sensor and the calculation of the pipe wall temperature;

[0038] Figure 3 The axial temperature data of the pipeline under test conditions;

[0039] Figure 4 The overall flowchart of the qualitative trend analysis method for valve internal leakage based on valve temperature field provided by the present invention is shown below.

[0040] Figure 5 A detailed flowchart of the modeling method for valve internal leakage detection.

[0041] In the diagram: 1. Main steam pipeline, 2. Extraction pipeline, 3. Steam valve, 4. Main pipeline steam pressure sensor, 5. Main pipeline steam temperature sensor, 6. Main pipeline steam flow sensor, 7. Post-valve pipe wall temperature sensor, 8. Data acquisition device, 9. Valve internal leakage detection terminal. Detailed Implementation

[0042] The present invention will be further described in detail below with reference to the accompanying drawings and specific embodiments.

[0043] This invention addresses the problems in the background art by providing a valve internal leakage monitoring method for nuclear power plant operation and maintenance. A method and apparatus for qualitative trend analysis of valve internal leakage based on the valve temperature field can automatically test, analyze, and determine whether typical valves have internal leakage, micro-leakage, or other types of leakage based on changes in the downstream pipe wall temperature under leakage conditions, and preliminarily estimate the leakage amount.

[0044] like Figure 1 As shown, a device for qualitative trend analysis of valve internal leakage based on valve temperature field includes a main steam pipeline 1, an extraction pipeline 2, a steam valve 3, a main pipeline steam pressure sensor 4, a main pipeline steam temperature sensor 5, a main pipeline steam flow sensor 6, a downstream pipe wall temperature sensor 7, a data acquisition device 8, and a valve internal leakage detection terminal 9. The main steam pipeline 1 is equipped with the main pipeline steam pressure sensor 4, the main pipeline steam temperature sensor 5, and the main pipeline steam flow sensor 6. The main steam pipeline 1 is connected to the extraction pipeline 2, and the extraction pipeline 2 is connected to the steam valve 3. Figure 2 As shown, downstream pipe wall temperature sensors 7 are installed circumferentially and radially in the pipe downstream of valve 3. These sensors are evenly distributed at 30° intervals circumferentially. The downstream pipe wall temperature sensors 7 are thermocouple sensors, which are easy to manufacture, simple in structure, have high accuracy, a very large measurement range, low inertia, and can transmit signals over long distances. A thermocouple sensor is mounted on the pipe wall using a heat-conducting and highly adhesive adhesive, thereby reducing thermal resistance, improving measurement accuracy, and preventing destructive operations such as grinding of the pipe. Twelve sensors are installed in one ring, arranged at certain intervals radially in multiple rings within 50mm of the downstream pipe. This measures the temperature change trend of steam along the radial direction of the pipe after valve leakage. Combining the circumferential and radial temperature sensors downstream of the valve enables effective and comprehensive monitoring of the specific changes in steam within the downstream pipe. The downstream pipe wall temperature sensors 7 are connected to a signal acquisition device 8, which in turn is connected to a valve internal leakage detection terminal 9.

[0045] The device of this invention uses thermocouples as the physical means of implementation. Based on the above description of the valve internal leakage detection device, temperature measuring points are distributed and installed at multiple cross-sections downstream of the steam valve 3 to monitor the downstream pipe wall temperature in real time. The signal acquisition device 8 includes a data acquisition card and signal transmission wires. Based on the above-mentioned downstream temperature sensor 7, the acquired downstream temperature field signal is transmitted in real time to the data acquisition card of the data acquisition device 8 via the signal transmission wires. The data acquisition card then transmits the temperature signal in real time to the valve internal leakage detection terminal 9. The valve internal leakage detection terminal 9 determines whether the valve is leaking and estimates the valve leakage flow rate based on the downstream temperature signal. The valve internal leakage detection terminal 9 includes a pipe inner wall temperature calculation module and a valve internal leakage detection module.

[0046] The pipe inner wall temperature calculation module is based on the principles of the cylindrical heat conduction differential equation and the energy conservation equation. It establishes relevant model algorithms to automatically convert the temperature at each pipe outer wall measuring point collected by the thermocouple to the temperature of the corresponding pipe inner wall. The conversion result is then transmitted to the valve internal leakage detection module for subsequent evaluation of valve internal leakage.

[0047] The valve internal leakage detection module consists of several functional modules, including data preprocessing, feature extraction, model training, and model evaluation. Based on the converted temperature data of various measuring points on the inner wall of the pipeline, the time-series temperature variation characteristic parameters are extracted through data preprocessing and feature extraction modules. First, based on the least squares method, polynomial fitting is performed between the valve leakage flow rate and each individual characteristic parameter to determine the polynomial order of the valve leakage flow rate with each characteristic parameter, establishing a multivariate relationship equation between the valve leakage flow rate and all characteristic parameters. Based on experimental data under different leakage flow conditions, a multivariate linear regression model is used to solve the multivariate equation, obtaining the coefficients of the multivariate equation for valve leakage flow rate, the goodness of fit, and the regression coefficients of each characteristic parameter. Finally, the valve internal leakage detection model is trained, and the valve internal leakage is evaluated based on temperature field data.

[0048] based on Figure 1 The valve internal leakage detection device shown uses a data acquisition device 8 to collect the downstream temperature field signal in real time through multiple temperature measuring points installed at multiple cross-sections downstream of valve 3, and transmits the temperature signal to the valve internal leakage detection terminal 9 in real time. The pipe inner wall temperature calculation module of the terminal 9 automatically converts the temperature of the measuring points on the outer wall of the pipe to the temperature of the corresponding measuring points on the inner wall of the pipe. Then, based on the temperature signal of the measuring points on the inner wall of the pipe, it extracts the time-series temperature change characteristic parameters and automatically calculates the leakage amount of the valve internal leakage through the established valve internal leakage detection model based on the temperature field.

[0049] A qualitative trend analysis method for valve internal leakage based on valve temperature field includes the following steps:

[0050] Step 1: Based on the real-time collected temperature signal of the outer wall of the pipe, the temperature change of several points on the inner wall of the pipe over time is automatically calculated by the pipe inner wall temperature calculation module.

[0051] The pipe inner wall temperature calculation module is based on a conversion function algorithm for the pipe inner and outer wall temperatures established using the differential equation of cylindrical heat conduction. Based on real-time temperature changes on the pipe outer wall measured by a data acquisition device, the module automatically calculates the temperature changes over time at corresponding points on the pipe inner wall. This reduces errors in valve leakage detection caused by pipe thermal resistance, thereby improving the accuracy of valve leakage calculations. Figure 2For a simplified top view of a single-layer cylindrical pipe cross-section, the outer wall of the cylinder represents thermocouple temperature measuring points, and the corresponding dotted points on the inner wall represent the inner wall temperature measuring points after conversion by the pipe inner wall temperature calculation module. The principle for calculating the pipe inner wall temperature is as follows: assuming the pipe material properties do not change over time and there is no internal heat deposition, when a steady state is reached, the outer wall temperature can be calculated using the following equations and boundary conditions:

[0052] Governing equations:

[0053]

[0054] Definite solution conditions:

[0055]

[0056] u=T1 ρ=b (External wall temperature measurement conditions) (3)

[0057] u=T0 ρ=a (Inner wall temperature condition) (4)

[0058] In the formula: T ∞ T0 is the ambient temperature; T1 is the outer wall temperature measured by the thermocouple; h is the convective heat transfer system; k is the thermal conductivity coefficient of the outer wall of the cylinder; B i =bh / k is the Biot number; given the outer wall radius b and the inner wall radius a, calculate the inner wall temperature T0.

[0059] The general solution of equation (1) is:

[0060] u=A+Blnρ (5)

[0061] Using the convective heat dissipation conditions of the outer wall (2) and the collected outer wall temperature conditions (3), the following can be solved:

[0062] A = T1 + B i (T1-T ∞ lnb (6)

[0063] B = -B i (T1-T ∞ (7)

[0064] Thus, the inner wall temperature is obtained:

[0065]

[0066] Step 2: Extract time-series temperature variation characteristic parameters based on the pipe inner wall temperature signal, including the rate of temperature change along the pipe axis. and the rate of temperature change over time

[0067] After a valve in the main steam pipeline's extraction line leaks, the leaking steam may undergo vapor-liquid changes upon cooling, and the steam flow will cause continuous temperature changes within the pipeline. By extracting time-series temperature change characteristic parameters from the temperature data, compared to calculating constant features such as average temperature, we can better characterize the temperature change trend within the pipeline after valve leakage, thus improving the accuracy of estimating valve leakage flow rate.

[0068] Among them, the time-series temperature change characteristic parameters include the rate of temperature change along the pipe axis. and the rate of temperature change over time like Figure 1 As shown, by arranging [something] at positions such as -250, -200, -100, 50, 100, and 150 mm upstream and downstream of the pipeline valve, [something is done]. Figure 2 The cross-sectional thermocouple field is used to obtain the temperature change trend along the pipeline axis after valve internal leakage, such as... Figure 3 This example illustrates the monitored axial temperature change in a pipe. The temperature change trends at the top and bottom of the pipe cross-section are evident. Therefore, the least squares method is used to fit the temperature curves along the pipe diameter at the top and bottom, thus obtaining the rate of temperature change T along the pipe diameter at the top and bottom of the pipe. 1底 and T 1顶 Furthermore, based on actual field experience in measuring valve internal leakage temperature, a significant temperature change occurs 350mm downstream of the valve, which can effectively characterize valve internal leakage fault information. The temperature at a measurement point 350mm downstream of the valve is selected, and the temperature change at this point over a period of time (e.g., 1 minute) is statistically analyzed to calculate the rate of temperature change T over time. 2底 and T 2顶 .

[0069] Step 3: Establish the functional relationship between valve leakage flow rate under different flow conditions, and build a valve internal leakage detection model based on time-series temperature variation characteristic parameters.

[0070] The process for establishing valve internal leakage detection models under different flow conditions is as follows: Figure 4 As shown. First, based on experimental research, a highly accurate CFD simulation model of the flow field of various common valves in the pipeline is established; when the temperature T of the steam in the main steam pipeline is... 主 Pressure P 主 Traffic Q 主 When the valve type and the diameter D of the extraction pipeline change, the boundary conditions of the CFD pipeline valve flow field simulation model are set according to various parameter values ​​to obtain the temperature field data inside the pipeline after valve leakage under these conditions. Then, based on the simulation data, a valve internal leakage detection model is established to obtain the valve leakage flow rate Q. leak The functional relationship between the valve leakage flow rate and the temperature field inside the pipeline is established. Finally, based on real-time temperature field data monitored by thermocouples on the outer wall of the pipeline, the valve leakage flow rate Q is calculated using the functional relationship between the valve leakage flow rate and the temperature field inside the pipeline. leak .

[0071] The detailed process for modeling the valve internal leakage detection model is as follows: Figure 5 As shown. First, based on the CFD simulation data, the time-series temperature variation characteristic parameters T1 and T2 are extracted through step 2; then, based on the least squares method, polynomial fitting is performed on the leakage flow rate and each characteristic parameter to determine the polynomial order of the leakage flow rate and each characteristic parameter; then, based on the polynomial order relationship between the leakage flow rate and each characteristic parameter, a multivariate equation of the leakage flow rate and all temperature characteristic parameters is established, as shown in formula (9); next, through multiple sets of characteristic parameters extracted from a large amount of simulation data, the multivariate equation is solved based on the multivariate linear regression model to obtain the functional relationship between the leakage flow rate and multiple temperature characteristic parameters; finally, through Figure 5 The regression coefficients p-values ​​and goodness-of-fit R-values ​​shown are... 2 Based on a small amount of experimental data and after triple verification analysis, the optimal functional relationship between valve leakage flow and pipeline temperature field was obtained, and the valve internal leakage detection model was completed.

[0072] Q leak =α0+α1T1+α2T1 2 +...+α n T1 n +α n+1 T2+α n+2 T2 2 +...+α n+m T2 m (9)

[0073] In the formula, α0, α1, α2, ..., α n ,α n+1 ,α n+2 ,...,α n+m Solving for coefficients in a multivariate equation; The rate of temperature change along the axial direction of the pipe; The rate of temperature change over time at 350 mm downstream of the valve; n and m represent the leakage flow rate Q, respectively. leak The order of the polynomials T1 and T2.

[0074] Step 4: Apply the valve internal leakage detection device to actual applications, and based on the actual application situation, repeat the above modeling steps to continuously optimize the valve internal leakage model.

[0075] A valve internal leakage detection device was installed on the downstream pipe wall to conduct practical field applications of valve internal leakage detection. Real-time monitoring of the thermocouple field yielded circumferential and radial temperature parameters of the pipe's outer wall. The pipe inner wall temperature calculation module from step 1 automatically calculated temperature data for several points on the pipe's inner wall. Relevant temperature characteristic parameters were then extracted from step 2. These extracted temperature parameters were input into the established valve internal leakage detection model to calculate the theoretical leakage flow rate. Finally, the theoretical leakage flow rate was compared with the actual leakage flow rate measured on-site. If the error was too large, the above steps were repeated to iteratively optimize the temperature field-based valve internal leakage detection model until the error was less than 10%.

Claims

1. A device for qualitative trend analysis of valve internal leakage based on valve temperature field, characterized in that: The system includes a main steam pipeline, an extraction pipeline, steam valves, a main pipeline steam pressure sensor, a main pipeline steam temperature sensor, a main pipeline steam flow sensor, a downstream pipe wall temperature sensor, a data acquisition device, and a valve internal leakage detection terminal. The main steam pipeline is equipped with the main pipeline steam pressure sensor, main pipeline steam temperature sensor, and main pipeline steam flow sensor. The main steam pipeline is connected to an extraction pipeline, which is connected to a steam valve. A downstream pipe wall temperature sensor is installed on the downstream pipe of the steam valve. The downstream pipe wall temperature sensor is connected to the signal acquisition device, which is connected to the valve internal leakage detection terminal. The analysis device is used for qualitative trend analysis of valve internal leakage based on the valve temperature field, including the following steps: Step 1: Based on the real-time collected temperature signal of the outer wall of the pipe, the temperature change of several points on the inner wall of the pipe over time is automatically calculated by the pipe inner wall temperature calculation module. Step 1 involves calculating the outer wall temperature using the following equations and boundary conditions: Governing equations: （1）， Definite solution condition: Convection heat dissipation conditions (2). External wall temperature measurement conditions (3). Inner wall temperature conditions (4). In the formula: Ambient temperature; This refers to the temperature of the inner wall. The temperature of the outer wall collected by the thermocouple; For convective heat transfer systems, The thermal conductivity coefficient of the outer wall of the cylinder is _____. Given the Biot number; the outer wall radius is known. Inner wall radius Calculate the inner wall temperature ; The general solution of equation (1) is: （5）， Using the convective heat dissipation conditions of the outer wall (2) and the collected outer wall temperature conditions (3), we can solve for: （6）， （7）， Thus, the inner wall temperature is obtained: （8）， Step 2: Extract time-series temperature variation characteristic parameters based on the pipe inner wall temperature signal, including the rate of temperature change along the pipe axis. and the rate of temperature change over time ; Step 3: Establish the functional relationship between valve leakage flow rate under different flow conditions, and establish a valve internal leakage detection model based on time-series temperature variation characteristic parameters; Step 4: Apply the valve internal leakage detection device to actual applications, and based on the actual application situation, repeat the above modeling steps to continuously optimize the valve internal leakage model.

2. The valve internal leakage qualitative trend analysis device based on valve temperature field as described in claim 1, characterized in that: Temperature sensors for the downstream pipe wall are installed circumferentially and radially on the downstream pipe of the steam valve.

3. The valve internal leakage qualitative trend analysis device based on valve temperature field as described in claim 1, characterized in that: The valve downstream pipe wall temperature sensors are evenly distributed at 30° intervals around the circumference of the pipe.

4. The valve internal leakage qualitative trend analysis device based on valve temperature field as described in claim 1, characterized in that: The valve downstream pipe wall temperature sensor is a thermocouple sensor.

5. A method for qualitative trend analysis of valve internal leakage based on valve temperature field, characterized in that: Includes the following steps: Step 1: Based on the real-time collected temperature signal of the outer wall of the pipe, the temperature change of several points on the inner wall of the pipe over time is automatically calculated by the pipe inner wall temperature calculation module. Step 1 involves calculating the outer wall temperature using the following equations and boundary conditions: Governing equations: （1）， Definite solution condition: Convection heat dissipation conditions (2). External wall temperature measurement conditions (3). Inner wall temperature conditions (4). In the formula: Ambient temperature; This refers to the temperature of the inner wall. The temperature of the outer wall collected by the thermocouple; For convective heat transfer systems, The thermal conductivity coefficient of the outer wall of the cylinder is _____. Given the Biot number; the outer wall radius is known. Inner wall radius Calculate the inner wall temperature ; The general solution of equation (1) is: （5）， Using the convective heat dissipation conditions of the outer wall (2) and the collected outer wall temperature conditions (3), we can solve for: （6）， （7）， Thus, the inner wall temperature is obtained: （8）， Step 2: Extract time-series temperature variation characteristic parameters based on the pipe inner wall temperature signal, including the rate of temperature change along the pipe axis. and the rate of temperature change over time ; Step 3: Establish the functional relationship between valve leakage flow rate under different flow conditions, and establish a valve internal leakage detection model based on time-series temperature variation characteristic parameters; Step 4: Apply the valve internal leakage detection device to actual applications, and based on the actual application situation, repeat the above modeling steps to continuously optimize the valve internal leakage model.

6. The method for qualitative trend analysis of valve internal leakage based on valve temperature field as described in claim 5, characterized in that: In step 2, the time-series temperature change characteristic parameters include the rate of temperature change along the pipe axis. and the rate of temperature change over time By arranging thermocouple fields at positions of -250, -200, -100, 50, 100, and 150 mm upstream and downstream of the pipeline valve, the temperature change trend along the pipeline axis after internal leakage of the valve was obtained. The temperature curves along the pipe diameter at the bottom and top of the pipeline were fitted using the least squares method, and then the temperature change rate along the pipe diameter at the bottom and top of the pipeline was obtained. and The temperature at a point 350 mm downstream of the valve was selected, and the temperature change at that point was statistically analyzed over a period of time. The rate of temperature change over time was then calculated. and .

7. The method for qualitative trend analysis of valve internal leakage based on valve temperature field as described in claim 5, characterized in that: In step 3, a highly accurate CFD simulation model of the flow field of various common valves is established based on experimental research; when the temperature of the steam in the main steam pipeline... ,pressure ,flow When the valve type and the diameter D of the extraction pipeline change, the boundary conditions of the CFD pipeline valve flow field simulation model are set based on various parameter values ​​to obtain the temperature field data inside the pipeline after valve leakage under these conditions. Then, based on the simulation data, a valve internal leakage detection model is established to obtain the valve leakage flow rate. The functional relationship between valve leakage flow and the temperature field inside the pipeline is established. Finally, based on real-time temperature field data monitored by thermocouples on the outer wall of the pipeline, the valve leakage flow rate is calculated using the functional relationship between valve leakage flow rate and the temperature field inside the pipeline. .

8. The method for qualitative trend analysis of valve internal leakage based on valve temperature field as described in claim 7, characterized in that: In step 3, the modeling process for the valve internal leakage detection model is based on CFD simulation data, and the time-series temperature variation characteristic parameters are extracted in step 2. and Then, based on the least squares method, polynomial fitting is performed on the leakage flow rate and individual characteristic parameters respectively to determine the polynomial order of the leakage flow rate and each characteristic parameter; based on the polynomial order relationship between the leakage flow rate and each characteristic parameter, a multivariate equation of the leakage flow rate and all temperature characteristic parameters is established, as shown in formula (9); through multiple sets of characteristic parameters extracted from simulation data, the multivariate equation is solved based on the multivariate linear regression model to obtain the functional relationship between the leakage flow rate and multiple temperature characteristic parameters; finally, through the regression coefficient P value, goodness of fit, etc. Based on the verification and experimental data, and through triple verification analysis, the optimal functional relationship between valve leakage flow and pipeline temperature field was obtained, thus completing the modeling of the valve internal leakage detection model. （9）。 9. The method for qualitative trend analysis of valve internal leakage based on valve temperature field as described in claim 5, characterized in that: In step 4, real-time monitoring of the thermocouple field yields circumferential and radial temperature monitoring parameters of the pipe's outer wall; temperature data at several points on the pipe's inner wall are calculated using step 1; relevant temperature characteristic parameters are extracted based on step 2; the extracted temperature parameters are input into the established valve internal leakage detection model to calculate the theoretical leakage flow rate; finally, the theoretical leakage flow rate is compared with the actual leakage flow rate measured on-site. If the error is too large, steps 1-3 are repeated to iteratively optimize the temperature field-based valve internal leakage detection model until the error is less than [a certain value]. .

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