Method for monitoring transient thermal boundary conditions of membrane water wall

Abstract

The invention relates to a method for monitoring transient thermal boundary conditions of a membrane water wall, which comprises the following specific steps of: establishing a local linear heat transfer model by drawing up discrete points of convective heat transfer coefficients, and calculating a sensitivity coefficient; setting initial values of heat flow radiated towards the fire side and fluid temperature in the pipe; establishing a temperature prediction model; rolling optimization is adopted to obtain a thermal boundary condition compensation quantity component; a weighting coefficient is constructed based on the unexposed side heat insulation boundary condition deviation; weighting the comprehensive compensation amount and correcting a guess value to obtain a radiation heat flow and fluid temperature monitoring result; and meanwhile, discrete points are weighted to output a convective heat transfer coefficient. According to the method, the monitoring rate is remarkably increased, the hysteresis effect is reduced, the dynamic response is enhanced, nonlinear changes are accurately processed, and the engineering practicability is high.

Description

[0001] This invention belongs to the field of thermal parameter measurement and heat transfer analysis technology, specifically relating to a method for monitoring transient thermal boundary conditions of a membrane water-cooled wall. Background Technology

[0002] Large power plant boilers commonly use membrane water-cooled walls as the furnace heating surface. In actual operation, there is often a significant deviation between the radiant heat load inside the boiler furnace and the working fluid flow distribution within the water-cooled wall tubes. Furthermore, during variable operating conditions of the thermal power unit, the radiant heat load and the flow state of the working fluid inside the water-cooled wall may change drastically. These factors directly affect the transient temperature field of the water-cooled wall, potentially leading to localized overheating of the water-cooled wall tubes and even tube rupture accidents. Therefore, accurately understanding the transient temperature distribution in the hazardous areas of the water-cooled wall is of significant engineering importance for optimizing the design of the heating surface of the power plant boiler water-cooled wall and improving the operational safety of the boiler system.

[0003] To determine the transient temperature field of a water-cooled wall, all thermal boundary conditions in the monitoring area need to be identified. The thermal boundary conditions of a membrane water-cooled wall mainly include the local radiative heat flux on the fire side, the fluid temperature inside the tube, and the convective heat transfer coefficient inside the tube. Given the complex flow and heat transfer coupling processes in actual operating environments, limited measurement conditions, and the correlation between thermal boundary conditions and temperature distribution, readily available temperature measurements on the unfired side of the water-cooled wall can be used to monitor the unknown thermal boundary conditions of the membrane water-cooled wall.

[0004] Current technologies mainly focus on monitoring steady-state thermal boundary conditions of water-cooled walls. For transient thermal boundary conditions, traditional monitoring methods suffer from significant response lag due to the time-varying nonlinear characteristics of the heat transfer process; especially when the convective heat transfer coefficient changes rapidly over time, the monitoring error further increases, making it difficult to meet the needs of accurate monitoring of transient processes in practical engineering. Summary of the Invention

[0005] To address the aforementioned shortcomings of existing technologies, the technical problem this invention aims to solve is to provide a method for monitoring transient thermal boundary conditions of membrane water-cooled walls. This method resolves the issues of current technologies being applicable only to steady-state thermal boundary conditions, exhibiting measurement lag, and showing significantly increased monitoring errors when the convective heat transfer coefficient changes rapidly over time.

[0006] To solve the above-mentioned technical problems, the present invention adopts the following technical solution:

[0007] A method for monitoring transient thermal boundary conditions of a membrane water-cooled wall includes the following steps:

[0008] (a) Determine the discrete points of the convective heat transfer coefficient and construct multiple local linear heat transfer models based on them. Obtain the sensitivity equation set based on the local linear heat transfer model and calculate the sensitivity coefficient based on the sensitivity equation set.

[0009] (b) Set the estimated values ​​for the local radiative heat flux to the fire side and the temperature of the fluid inside the pipe;

[0010] (c) Based on the local linear heat transfer model and the sensitivity coefficient, construct a temperature prediction model for the measuring point at multiple future times to obtain the predicted temperature value of the measuring point.

[0011] (d) Based on the predicted and measured temperatures at the measuring points, the components of local radiative heat flux compensation, fluid temperature compensation, and backfire-side adiabatic boundary condition compensation are obtained through rolling optimization.

[0012] (e) Based on the deviation between the estimated value of the backfire side adiabatic boundary condition obtained from the local linear heat transfer model and the actual value, construct the weighting coefficients corresponding to the local linear heat transfer model.

[0013] (f) Weight the components of local radiative heat flux compensation and fluid temperature compensation to generate local radiative heat flux compensation and fluid temperature compensation on the fire side.

[0014] (g) Correct the estimated values ​​of local radiative heat flow and fluid temperature on the fire side to obtain the monitoring results at the current moment;

[0015] (h) Weight the discrete points of the proposed convective heat transfer coefficient to obtain the monitoring result of the convective heat transfer coefficient at the current time;

[0016] Furthermore, in step (a), the discrete point θ is determined based on the proposed convective heat transfer coefficient. s The local linear heat transfer model M s (θ s )for:

[0017]

[0018]

[0019]

[0020]

[0021]

[0022]

[0023] In the formula: λ, Let and c be the thermal conductivity, density, and specific heat capacity of the water-cooled wall tube, respectively; T(x, y, t) is the temperature of the water-cooled wall tube; T f(t) represents the fluid temperature inside the water-cooled wall tube; T0(x, y) represents the initial temperature; h(t) represents the convective heat transfer coefficient inside the water-cooled wall tube; n represents the normal direction of the interface; q1(t) represents the heat dissipation on the unfired side of the water-cooled wall tube. Since the unfired side is an adiabatic boundary, its true value is q1(t) = 0; q(x, t) represents the actual heat flux density on the fire-facing wall surface.

[0024] The actual heat flux densities of the outer wall surface of the water-cooled wall tubes and the fins on the fire-side side are as follows:

[0025]

[0026]

[0027] Where q0(t) is the local radiative heat flux in the computational region; the pipe wall angle coefficient and fin angle coefficient gdx Determine them according to the following formulas:

[0028]

[0029] .

[0030] Furthermore, the sensitivity equations described in step (a) are as follows:

[0031]

[0032]

[0033]

[0034]

[0035]

[0036]

[0037]

[0038] In the formula, is denoted as , , where is the sensitivity function.

[0039] Furthermore, the temperature prediction model described in step (c) is as follows:

[0040]

[0041] in, For the local linear heat transfer model M s (θs The predicted temperature value of measuring point m at time k + j obtained; This represents the prediction of time k + j at time k; For when Calculated temperature value at that time; The sensitivity coefficient is, and .

[0042] Furthermore, in step (d), the purpose of the rolling optimization is to optimize the optimal thermal boundary condition components. This makes the local linear heat transfer model M s (θ s The predicted temperature value in the future time domain should be as close as possible to the system's measured temperature value, including the following sub-steps:

[0043] (d1) The objective function for optimization is constructed as follows:

[0044]

[0045] In the formula, To measure the temperature matrix, , The measured temperature value at measuring point m at time k + j; , ; Let be the regularization parameter matrix, α = diag(α1, α2, α3), where α1, α2, and α3 are the regularization parameters for q0(t), T, and T, respectively. f The regularization parameters corresponding to q1(t) and q2(t); , ;

[0046] (d2) Let For time series vectors Differentiate and take The optimal estimates of the local radiative heat flux compensation components, fluid temperature compensation components, and backfire side adiabatic boundary condition compensation components are obtained:

[0047]

[0048] in, , , Specifically:

[0049]

[0050]

[0051] (d3) Obtain the local radiative heat flux compensation component, fluid temperature compensation component, and backfire side adiabatic boundary condition compensation component at the current time k by taking the first element:

[0052]

[0053] In the formula, d1 is a 3rd order identity matrix.

[0054] Furthermore, the construction of the local linear heat transfer model M described in step (e) s (θ s Weighting coefficients Specifically:

[0055] At the current time k, determine whether the local linear heat transfer model M is correct. s (θ s The deviation between the estimated and actual values ​​of the backfire side adiabatic boundary conditions obtained:

[0056]

[0057] In the formula, Let q1(t) be the true value at time k; since Therefore, the above formula can be expressed as:

[0058] .

[0059] In the above formula, the larger the deviation, the stronger the local linear heat transfer model M. s (θ s The smaller the instantaneous match between the model and the actual heat transfer system, the smaller the corresponding weighting coefficient should be, and vice versa; on the other hand, considering that the actual convective heat transfer coefficient can only be obtained in any two adjacent local linear heat transfer models M s (θ s The variation between ) is considered, therefore only the two local linear heat transfer models M with the smallest deviation are taken into account. s (θ s ) participate in the weighted calculation; assuming and Corresponding to sets { The two smallest and second smallest distance deviations in the range are estimated using the following normalized model. :

[0060] .

[0061] Furthermore, the local radiative heat flux compensation component mentioned in step (f) and fluid temperature compensation component The weighted summation is as follows:

[0062]

[0063] .

[0064] Furthermore, the local radiative heat flow to the fire side at the current moment described in step (g) and the temperature of the fluid inside the pipe The monitoring results are as follows:

[0065]

[0066]

[0067] In the formula, This refers to the localized radiative heat flow to the fire side from the previous moment. This represents the temperature of the fluid inside the pipe at the previous moment.

[0068] Furthermore, the monitoring results of the convective heat transfer coefficient at the current moment mentioned in step (h) Specifically:

[0069] .

[0070] Beneficial effects: The transient thermal boundary condition monitoring method for water-cooled walls of the present invention achieves the segmentation of the linear subspace of the nonlinear heat transfer system based on the discrete points of the proposed convective heat transfer coefficient (characteristic quantity), and constructs a corresponding local linear heat transfer model; based on the predicted and measured temperature values ​​at the measuring points, the estimated values ​​of the local radiative heat flux on the fire side, the fluid temperature inside the pipe, and the adiabatic boundary condition on the unfire side are obtained through a rolling optimization strategy; based on the deviation between the estimated and actual values ​​of the adiabatic boundary condition on the unfire side obtained by the local linear heat transfer model, a weighting coefficient of the local linear heat transfer model is constructed; by comprehensively weighting the estimated results of the local radiative heat flux on the fire side and the fluid temperature inside the pipe obtained based on the local linear heat transfer model, the monitoring results of the local radiative heat flux on the fire side and the fluid temperature inside the pipe are obtained; at the same time, the characteristic quantity is comprehensively weighted using the weighting coefficient to generate the monitoring results of the time-varying convective heat transfer coefficient;

[0071] The transient thermal boundary condition monitoring method for water-cooled walls of the present invention can significantly improve the monitoring rate while ensuring accuracy, effectively reduce the hysteresis effect in traditional measurement, improve dynamic response performance, and at the same time have a strong time-varying nonlinear processing capability, which can accurately capture the changing law of thermal boundary conditions of different forms, and has stronger engineering applicability. Attached Figure Description

[0072] Figure 1 A flowchart illustrating the method of the invention in a specific embodiment;

[0073] Figure 2This is a simplified physical model diagram of the membrane water-cooled wall in a specific embodiment;

[0074] Figure 3 This is a schematic diagram of the monitoring results of the transient thermal boundary conditions of the membrane water-cooled wall in Example 1.

[0075] Figure 4 This is a schematic diagram of the monitoring results of the transient thermal boundary conditions of the membrane water-cooled wall in Example 2. Detailed Implementation

[0076] The specific embodiments of the present invention will be further described in detail below with reference to the accompanying drawings.

[0077] A specific embodiment of a method for monitoring transient thermal boundary conditions of a membrane water-cooled wall includes the following steps:

[0078] (a) Determine the discrete point θ of the convective heat transfer coefficient s (s = 1, 2, …, N), thereby constructing multiple local linear heat transfer models M. s (θ s Based on the local linear heat transfer model, a set of sensitivity equations is obtained, and the sensitivity coefficient is calculated based on the set of sensitivity equations.

[0079] (b) Set the estimated values ​​for the local radiative heat flow to the fire side and the fluid temperature inside the pipe as follows: and k = 1;

[0080] (c) Based on the local linear heat transfer model M s (θ s Based on the sensitivity coefficient, a temperature prediction model for measuring point m at future R time points is constructed. To obtain the predicted temperature value at the measuring point;

[0081] (d) Based on the predicted and measured temperatures at the measuring points, the components of local radiative heat flux compensation, fluid temperature compensation, and backfire-side adiabatic boundary condition compensation are obtained through rolling optimization.

[0082] (e) Based on the local linear heat transfer model M s (θ s To account for the discrepancy between the estimated and actual values ​​of the adiabatic boundary conditions on the unexposed side, a local linear heat transfer model M is constructed. s (θ s The corresponding weighting coefficients ;

[0083] (f) Weighted summation of the local radiative heat flux compensation component and the fluid temperature compensation component to generate the compensation amount for the local radiative heat flux to the fire side and the fluid temperature inside the pipe. and ;

[0084] (g) Estimated values ​​of local radiative heat flow and fluid temperature on the fire-facing side. and Corrections are made to obtain the monitoring results of the local radiative heat flow to the fire side and the temperature of the fluid inside the pipe at the current moment. and ;

[0085] (h) Weight the discrete points of the proposed convective heat transfer coefficient to obtain the monitoring result of the convective heat transfer coefficient at the current time. ;

[0086] The local linear heat transfer model M described in step (a) of this invention s (θ s )for:

[0087] Equation (1)

[0088] Equation (2)

[0089] Equation (3)

[0090] Equation (4)

[0091] Equation (5)

[0092] Equation (6)

[0093] In the formula: λ, Let and c be the thermal conductivity, density, and specific heat capacity of the water-cooled wall tube, respectively; T(x, y, t) is the temperature of the water-cooled wall tube; T f (t) represents the fluid temperature inside the water-cooled wall tube; T0(x, y) represents the initial temperature; h(t) represents the convective heat transfer coefficient inside the water-cooled wall tube; n represents the normal direction of the interface; q1(t) represents the heat dissipation on the unfired side of the water-cooled wall tube. Since the unfired side is an adiabatic boundary, the actual value q1(t) = 0; q(x, t) represents the actual heat flux density on the fire-facing wall surface.

[0094] The actual heat flux densities of the outer wall surface of the water-cooled wall tubes and the fins on the fire-side side are as follows:

[0095] Equation (7)

[0096] Equation (8)

[0097] Where q0(t) is the local radiative heat flux in the computational region; the pipe wall angle coefficient and fin angle coefficient gdx Determine according to equations (9) and (10) respectively:

[0098] Equation (9)

[0099] Equation (10).

[0100] The sensitivity equations described in step (a) of this invention are as follows:

[0101] Equation (11)

[0102] Equation (12)

[0103] Equation (13)

[0104] Equation (14)

[0105] Equation (15)

[0106] Equation (16)

[0107] Equation (17)

[0108] In the formula, is denoted as , , where is the sensitivity function.

[0109] Furthermore, the temperature prediction model described in step (c) of this invention is as follows:

[0110] Equation (18)

[0111] in, For the local linear heat transfer model M s (θ s The predicted temperature value of measuring point m at time k + j obtained by ) and its superscript This represents the prediction of time k + j at time k; For when Calculated temperature value at that time; The sensitivity coefficient is, and .

[0112] Furthermore, the purpose of the rolling optimization described in step (d) of this invention is to optimize the optimal thermal boundary condition components. This makes the local linear heat transfer model M s (θ sThe predicted temperature value in the future time domain should be as close as possible to the system's measured temperature value. The specific steps are as follows:

[0113] First, the optimization objective function is constructed as follows:

[0114] Equation (19)

[0115] In the formula, To measure the temperature matrix, , The measured temperature value at measuring point m at time k + j; , ; Let be the regularization parameter matrix, α = diag(α1, α2, α3), where α1, α2, and α3 are the regularization parameters for q0(t), T, and T, respectively. f The regularization parameters corresponding to q1(t) and q2(t); , .

[0116] Furthermore, it makes For time series vectors Differentiate and take The optimal estimates of the local radiative heat flux compensation components, fluid temperature compensation components, and backfire side adiabatic boundary condition compensation components are obtained:

[0117] Equation (20)

[0118] in, , , Specifically:

[0119]

[0120]

[0121] Finally, the first element is taken to obtain the local radiative heat flux compensation component, fluid temperature compensation component, and backfire side adiabatic boundary condition compensation component at the current time k:

[0122] Equation (21)

[0123] In the formula, d1 is a 3rd order identity matrix.

[0124] Furthermore, the local linear heat transfer model M described in step (e) s (θ s Weighting coefficients Specifically:

[0125] At the current time k, determine whether the local linear heat transfer model M is correct. s (θ s The deviation between the estimated and actual values ​​of the backfire side adiabatic boundary conditions obtained:

[0126] Equation (22)

[0127] In the formula, Let q1(t) be the true value at time k; since Therefore, the above formula can be expressed as:

[0128] Equation (23)

[0129] Clearly, the larger the deviation, the more critical the local linear heat transfer model M becomes. s (θ s The smaller the instantaneous match between the model and the actual heat transfer system, the smaller the corresponding weighting coefficient should be, and vice versa. On the other hand, considering that the actual convective heat transfer coefficient can only vary between any two adjacent local linear heat transfer models, only the two local linear heat transfer models with the smallest deviation are considered to participate in the weighted calculation. and Corresponding to sets { The two smallest and second smallest distance deviations in the range are estimated using the following normalized model. :

[0130] Equation (24)

[0131] Furthermore, the component of the local radiative heat flux compensation described in step (f) of the present invention and fluid temperature compensation component The weighted summation is as follows:

[0132] Equation (25)

[0133] Equation (26)

[0134] Furthermore, the monitoring results of the local radiative heat flow to the fire side and the temperature of the fluid inside the pipe at the current moment, as described in step (g) of this invention, are as follows:

[0135] Equation (27)

[0136] Equation (28)

[0137] Furthermore, the monitoring result of the convective heat transfer coefficient at the current moment mentioned in step (h) of this invention is specifically as follows:

[0138] Equation (29).

[0139] The following are two examples of monitoring transient thermal boundary conditions of membrane water-cooled walls using the method of this invention.

[0140] like Figure 2 As shown, a membrane water-cooled wall of a supercritical pressure once-through boiler is taken as the research object. Its structure and physical parameters are as follows: inner radius r1 = 13.4 mm, outer radius r2 = 19 mm, pitch P = 54 mm, half thickness of fins δ = 2.5 mm, and tube wall thermal conductivity λ = 36.08 W / (m·K). = 4 × 10 6 J / (m 3 ·K), initial temperature T0(x, y) = 300 °C; future time steps R = 2.

[0141] Example 1:

[0142] Transient thermal boundary conditions q0(t), h(t) and T for water-cooled walls f The true distribution of (t) is:

[0143] Equation (30)

[0144] Equation (31)

[0145] Equation (32)

[0146] The thermal boundary condition monitoring results obtained through this invention are shown below. Figure 3 This method can accurately obtain the monitoring results of transient thermal boundary conditions of membrane water-cooled walls.

[0147] Example 2:

[0148] Transient thermal boundary conditions q0(t), h(t) and T for water-cooled walls f The true distribution of (t) is:

[0149] Equation (33)

[0150] Equation (34)

[0151] Equation (35)

[0152] The thermal boundary condition monitoring results obtained through this invention are shown below. Figure 4 This method can accurately obtain the monitoring results of transient thermal boundary conditions of membrane water-cooled walls.

[0153] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit it. Although the present invention has been described in detail with reference to preferred embodiments, those skilled in the art should understand that modifications or equivalent substitutions can be made to the technical solutions of the present invention without departing from the spirit and scope of the technical solutions of the present invention, and all such modifications or substitutions should be covered within the scope of the claims of the present invention.

Claims

1. A method for monitoring transient thermal boundary conditions of a membrane water-cooled wall, characterized in that: Includes the following steps: (a) Determine the discrete points of the convective heat transfer coefficient and construct multiple local linear heat transfer models based on them. Obtain the sensitivity equation set based on the local linear heat transfer model and calculate the sensitivity coefficient based on the sensitivity equation set. (b) Set the estimated values ​​for the local radiative heat flux to the fire side and the temperature of the fluid inside the pipe; (c) Based on the local linear heat transfer model and the sensitivity coefficient, construct a temperature prediction model for the measuring point at multiple future times to obtain the predicted temperature value of the measuring point. (d) Based on the predicted and measured temperatures at the measuring points, the components of local radiative heat flux compensation, fluid temperature compensation, and backfire-side adiabatic boundary condition compensation are obtained through rolling optimization. (e) Based on the deviation between the estimated value of the backfire side adiabatic boundary condition obtained from the local linear heat transfer model and the actual value, construct the weighting coefficients corresponding to the local linear heat transfer model. (f) Weight the components of local radiative heat flux compensation and fluid temperature compensation to generate local radiative heat flux compensation and fluid temperature compensation on the fire side. (g) Correct the estimated values ​​of local radiative heat flow and fluid temperature on the fire side to obtain the monitoring results at the current moment; (h) Weight the discrete points of the proposed convective heat transfer coefficient to obtain the monitoring result of the convective heat transfer coefficient at the current time; 2. The method for monitoring transient thermal boundary conditions of a membrane water-cooled wall according to claim 2, characterized in that: In step (a), the discrete point θ is determined based on the proposed convective heat transfer coefficient. s The local linear heat transfer model Ms(θ) s )for: In the formula: λ, Let and c be the thermal conductivity, density, and specific heat capacity of the water-cooled wall tube, respectively; T(x, y, t) is the temperature of the water-cooled wall tube; T f (t) represents the fluid temperature inside the water-cooled wall tube; T0(x, y) represents the initial temperature; h(t) represents the convective heat transfer coefficient inside the water-cooled wall tube; n represents the normal direction of the interface; q1(t) represents the heat dissipation on the unfired side of the water-cooled wall tube. Since the unfired side is an adiabatic boundary, its true value is q1(t) = 0; q(x, t) represents the actual heat flux density on the fire-facing wall surface. The actual heat flux densities of the outer wall surface of the water-cooled wall tubes and the fins on the fire-side side are as follows: Where q0(t) is the local radiative heat flux of the computational region; the pipe wall angle coefficient and fin angle coefficient Determine them according to the following formulas: 。 3. The method for monitoring transient thermal boundary conditions of a membrane water-cooled wall according to claim 2, characterized in that: The sensitivity equations described in step (a) are as follows: In the formula, is denoted as , , where is the sensitivity function.

4. The method for monitoring transient thermal boundary conditions of a membrane water-cooled wall according to claim 3, characterized in that: The temperature prediction model described in step (c) is as follows: in, For the local linear heat transfer model Ms(θ) s The predicted temperature value of measuring point m at time k + j obtained; This represents the prediction of time k + j at time k; For when Calculated temperature value at that time; The sensitivity coefficient is, and .

5. The method for monitoring transient thermal boundary conditions of a membrane water-cooled wall according to claim 4, characterized in that: In step (d), the purpose of the rolling optimization is to optimize the optimal thermal boundary condition components. The local linear heat transfer model Ms(θ) s The predicted temperature value in the future time domain should be as close as possible to the system's measured temperature value, including the following sub-steps: (d1) The objective function for optimization is constructed as follows: In the formula, To measure the temperature matrix, , The measured temperature value at measuring point m at time k + j; , ; Let α be the regularization parameter matrix, α = diag(α1, α2, α3), where α1, α2, and α3 are the regularization parameters for q0(t), T, and T, respectively. f The regularization parameters corresponding to q1(t) and q2(t); , ; (d2) Let For time series vectors Differentiate and take The optimal estimates of the local radiative heat flux compensation components, fluid temperature compensation components, and backfire side adiabatic boundary condition compensation components are obtained: in, , , Specifically: (d3) Obtain the local radiative heat flux compensation component, fluid temperature compensation component, and backfire side adiabatic boundary condition compensation component at the current time k by taking the first element: In the formula, d1 is a 3rd order identity matrix.

6. The method for monitoring transient thermal boundary conditions of a membrane water-cooled wall according to claim 5, characterized in that: The construction of the local linear heat transfer model Ms(θ) described in step (e) s The weighting coefficients are as follows: At the current time k, determine whether the local linear heat transfer model Ms(θ) is correct. s The deviation between the estimated and actual values ​​of the backfire side adiabatic boundary conditions obtained: In the formula, is the true value of q1(t) at time k; since Therefore, the above formula can be expressed as: 。 In the above formula, the larger the deviation, the more pronounced the local linear heat transfer model Ms(θ) becomes. s The smaller the instantaneous match between the model and the actual heat transfer system, the smaller the corresponding weighting coefficient should be, and vice versa; on the other hand, considering that the actual convective heat transfer coefficient can only be obtained in any two adjacent local linear heat transfer models Ms(θ)... s The variation between θ and θ is considered, therefore only the two local linear heat transfer models Ms(θ) with the smallest deviation are taken into account. s ) participate in the weighted calculation; assuming and Corresponding to sets { The two smallest and second smallest distance deviations in the range are estimated using the following normalized model. : 。 7. The method for monitoring transient thermal boundary conditions of a membrane water-cooled wall according to claim 6, characterized in that: The component of local radiative heat flux compensation mentioned in step (f) and fluid temperature compensation component The weighted summation is as follows: 。 8. The method for monitoring transient thermal boundary conditions of a membrane water-cooled wall according to claim 7, characterized in that: The local radiative heat flow to the fire side at the current moment described in step (g) and the temperature of the fluid inside the pipe The monitoring results are as follows: In the formula, This refers to the localized radiative heat flow to the fire side from the previous moment. This represents the temperature of the fluid inside the pipe at the previous moment.

9. The method for monitoring transient thermal boundary conditions of a membrane water-cooled wall according to claim 8, characterized in that: The monitoring results of the convective heat transfer coefficient at the current moment as described in step (h) Specifically: 。

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