Boiler wall surface stress monitoring system and method based on reverse heat conduction calculation

Abstract

The invention belongs to the technical field of thermal equipment monitoring, and particularly relates to a boiler wall surface stress monitoring system and method based on reverse heat conduction calculation. The problem that a traditional monitoring method is slow in response and large in error under the rapid variable working condition is solved. Boiler wall surface temperature data are collected in real time through a high dynamic response temperature sensor array, and after smooth processing is conducted through a Savitzky-Golay filter, a three-dimensional transient temperature field is reconstructed through a finite volume method and a space propulsion method. And further, thermal stress and pressure stress are calculated in combination with material parameters, and equivalent stress is obtained by adopting a von-Mises criterion. The system realizes a grading early warning mechanism, can automatically adjust boiler operation parameters according to the stress overrun degree, forms a monitoring-evaluation-control closed loop, and provides technical guarantee for safe operation of the boiler.

Description

TECHNICAL FIELD

[0001] The present application belongs to the technical field of heat equipment monitoring, and particularly relates to a boiler wall surface stress monitoring system and method based on reverse heat conduction calculation. BACKGROUND

[0002] In the power generation, chemical industry, petroleum and other industries, boilers and pressure vessels bear high temperature and high pressure load for a long time. The thick-walled components (such as headers, steam drums, pipes, etc.) of the boilers and pressure vessels will generate significant thermal stress when they are rapidly started and stopped or operated under variable load, which may cause fatigue damage, creep failure or even pipe burst. The traditional monitoring methods have the following problems: the quasi-steady state assumption error is large, which cannot accurately reflect the transient thermal stress change and cannot meet the actual needs. The dynamic response of industrial thermometers is poor, which cannot accurately measure the transient temperature of the fluid. The estimation of heat transfer coefficient is not accurate, which leads to the deviation of thermal stress calculation. The existing methods are difficult to apply to complex geometric structures (such as headers with openings). In the aspect of thermal stress calculation, the traditional quasi-steady state assumption error is large, which cannot accurately reflect the transient thermal stress change. At the same time, the estimation of heat transfer coefficient is not accurate, which leads to the deviation of thermal stress calculation. For example, in the detection of boiler economizer leakage in power plants, the traditional method is to stop the boiler and reduce the temperature after the possible leakage is found, then to remove the insulation bricks and to check visually by a person who drills into the boiler. This method not only causes economic loss due to shutdown, but also has high safety risk in high temperature environment. The leakage detection relies on naked eyes, which may miss some leakage. Acoustic detection is more advanced, but it is too sensitive to environmental noise. The background noise is large when the boiler is running, which may interfere with the detection results. When the leakage is too small, the acoustic signal is not obvious, which may not be detected. Infrared detection also has some problems, such as the observation effect is affected by the dust on the flue light window, the internal leakage point may be blocked by the outer pipe, the cost is high, the operation is complex, and professional equipment is needed. For complex geometric structure monitoring, the existing methods are difficult to apply to complex geometric structures such as headers with openings. For example, traditional detection methods are difficult to detect some hidden parts, while industrial endoscopes can detect without damaging the measured surface, but also have limitations. For example, in the common inspection methods of boilers and pressure vessels, visual inspection can only find surface problems and cannot detect hidden defects and faults; ultrasonic detection requires professional equipment and experienced operators, which is costly; magnetic powder detection requires the detected part to be a magnetic material and has high requirements for the surface treatment of the equipment; pressure test requires professional equipment and operators, and the equipment needs to be strictly protected to avoid accidents. In the monitoring of boiler drum water level, the differential pressure type water level meter cannot accurately measure the average density of the water in the single chamber balance container, and there is a difference between the calculation of the water in the drum as saturated water and the actual sub-saturated state, which leads to inevitable errors. The double-color water level meter lacks temperature compensation because the water temperature in the measuring cylinder is different from the saturated water temperature in the drum, which still has water level error after position correction in high pressure environment. The zero water level of the electric contact water level meter is different from the normal water level of the drum, and the water level fluctuation in the electrode type water level meter cannot correspond to it, which is not accurate in monitoring the water level of the super-high pressure, sub-critical boiler drum.

[0003] In the invention patent with publication number CN117195623A, a boiler pipe wall temperature monitoring method and system based on finite element analysis are proposed. This method needs to obtain data such as boiler drum, operating boundary conditions, and steam pressure to establish pipe wall thermal stress model and stress field model, and adopts sequential coupling method for thermal analysis. However, this device mainly focuses on monitoring the combustion process in the furnace and monitoring the slagging condition, and needs a large amount of boundary condition data such as steam pressure, which may be difficult to obtain; it relies on complex finite element model and sequential coupling analysis, the calculation process is time-consuming, and the early warning mechanism only performs corresponding early warning without real-time intervention for boiler operation. For the problems of inaccurate reflection of transient thermal stress changes, poor dynamic response of industrial thermometers, inaccurate estimation of heat transfer coefficient, and adaptability of complex geometric structure for thick-walled components thermal stress monitoring, no targeted solutions are given.

[0004] In the invention patent with publication number CN119914876, a boiler operation data acquisition method is mentioned, but the sensor type, number, and arrangement are not specified, and whether the dynamic response characteristics are considered is also not mentioned. In addition, this method uses adaptive encryption when meshing, but the number of mesh layers is not specified, and the stiffness matrix and fluid coupling matrix need to be iteratively solved in the calculation process. This method has the following problems: the sensor arrangement and data acquisition method are not clear, which may not accurately capture the thermal stress changes; the calculation process is complex and needs to be iteratively solved, which is low in calculation efficiency; and in this scheme, the early warning module sets three risk levels, but the control logic only involves adjusting the operating parameters, and there is no mention of direct linkage control with stress overrun. SUMMARY

[0005] The present application provides a boiler wall surface stress monitoring system and method based on inverse heat conduction calculation to solve the technical problem that the conventional monitoring method cannot accurately capture the transient thermal stress changes of thick-walled components in the boiler under rapid variable operating conditions, resulting in significant errors in the evaluation of fatigue damage, creep failure, and pipe burst risk.

[0006] To achieve the above purpose, the present application adopts the following technical solutions: A boiler wall surface stress monitoring method based on inverse heat conduction calculation, comprising the following steps: Collecting real-time boiler wall surface temperature data; According to the boiler wall surface temperature data, a three-dimensional transient temperature field is constructed, and the heat transfer coefficient and real-time temperature distribution data are outputted; According to the heat transfer coefficient and real-time temperature distribution data, the thermal stress and pressure stress of the boiler pressure-bearing component are calculated, and the equivalent stress is calculated according to the thermal stress and pressure stress; A stress threshold is set, stress evaluation is performed according to the equivalent stress and the stress threshold, and pre-warning, alarm or emergency shutdown is performed according to the evaluation result; and the boiler combustion temperature is adjusted according to different alarms.

[0007] The root constructs a three-dimensional transient temperature field according to the boiler wall surface temperature data, and outputs heat transfer coefficients and real-time temperature distribution data, specifically: based on real-time boiler wall surface temperature data, a finite volume method is used to discretize the heat conduction equation, and a 4-layer radial grid is used to reconstruct the temperature field to construct a three-dimensional transient temperature field, and according to the three-dimensional transient temperature field, a spatial marching method is used to recursively propagate the temperature distribution from the outer wall to the inner wall layer by layer, and heat transfer coefficients and temperature distribution data are output.

[0008] The finite volume method discretizes the heat conduction equation, specifically: the calculation region is divided into multiple control volumes, the energy conservation principle is applied to each control volume, the heat conduction equation is integrated on the control volume to obtain a discretization equation, and each node temperature value is obtained by iteratively solving the discretization equation, and the finite volume method discretizes the heat conduction equation as follows:

[0009] In the formula, is the specific heat capacity, is the density, is the transient change of the temperature field with time, are the heat flow densities in the x, y and z directions respectively.

[0010] The finite volume method discretizes the heat conduction equation, which combines the temperature change rate, and the temperature change rate is calculated based on the central difference method, and the calculation formula is as follows:

[0011] In the formula, represents the instantaneous change speed of the wall temperature with time, represents the time step, represents the normalization factor, represents the integral average wall temperature on the wall thickness, represents the i-th time point.

[0012] The thermal stress calculation method of the boiler pressure component is as follows: based on the heat transfer coefficient and the temperature distribution data, combined with the elastic modulus, the thermal expansion coefficient and the Poisson's ratio material parameters, based on the generalized Hooke's law, considering the strain caused by temperature change, the calculation formula is as follows:

[0013] In the formula, is the thermal stress tensor component; is the strain tensor component; for body strain; for Kronecker symbol; for thermal expansion coefficient, for temperature change amount, for elastic modulus, for Poisson's ratio.

[0014] The pressure stress of the boiler pressure part is calculated, specifically: the pressure stress is caused by the internal pressure and the mechanical stress caused by the internal pressure, for the fillet transition area, the curvature radius weighting correction coefficient is used wherein, is the fillet transition radius, is the characteristic size related to the fillet transition area; for the opening edge, the equivalent elliptical hole theory is used for stress redistribution; for the welding joint, the material anisotropy correction factor is introduced for calculation.

[0015] The equivalent stress is calculated, the von-Mises criterion is used to calculate the equivalent stress, and the calculation formula is:

[0016] wherein, , , is the three principal stresses of the thermal stress tensor.

[0017] The collected real-time boiler wall temperature data and retrograde data are preprocessed, the collected data is smoothed by using a 9-point moving filter and a Savitzky-Golay filter based on a polynomial regression, and the digital filter calculation formula is as follows:

[0018] wherein, is the data point after Savitzky-Golay filter processing, is the original collected data point, is the data point time considered at present, is the sampling time interval.

[0019] The real-time boiler wall temperature data includes the outer surface temperature of the boiler pressure part and the temperature near the inner surface.

[0020] A boiler wall stress monitoring system based on reverse heat conduction calculation, comprising a data acquisition module; a data processing module, a stress calculation module and an alarm module; The data acquisition module is used for collecting real-time boiler wall temperature data; The data processing module is used for constructing a three-dimensional transient temperature field according to the boiler wall temperature data, and outputting heat transfer coefficients and real-time temperature distribution data; The stress calculation module is used to calculate the thermal stress and pressure stress of the boiler pressure-bearing components based on the heat transfer coefficient and real-time temperature distribution data, and calculate the equivalent stress based on the thermal stress and pressure stress; The alarm module is used to set a stress threshold, perform stress assessment based on the equivalent stress and stress threshold, and issue an early warning, alarm or emergency shutdown based on the assessment results; and adjust the boiler combustion temperature accordingly based on different alarms.

[0021] Compared with the prior art, the present invention has the following beneficial effects: The present invention provides a boiler wall stress monitoring system and method based on reverse heat conduction calculation. It does not require measuring the fluid temperature. The three-dimensional temperature field is reconstructed only by the outer wall temperature and the temperature near the inner surface. The temperature distribution is solved recursively from the outer wall to the inner wall, avoiding the high time consumption of traditional iterative calculations. Only four layers of finite volume grids are required to ensure calculation accuracy. At the same time, a 9-point Savitzky-Golay filter is used to smooth the temperature data to improve stability. The time derivative calculation adopts central difference + filtering to reduce numerical oscillation. The temperature field and stress field distribution are monitored in real time, and an alarm is triggered or the boiler operating parameters are automatically adjusted when the stress exceeds the limit. The present invention not only improves the accuracy and efficiency of boiler wall stress monitoring, but also enhances the system's dynamic response capability and adaptability to complex geometric structures, ultimately achieving real-time safety monitoring and intervention of boiler operation, and providing reliable protection for the safe operation and life assessment of the boiler.

[0022] The present invention achieves real-time monitoring of thermal stress in thick-walled pressure components of the boiler by collecting boiler wall temperature data and calculating thermal and pressure stresses in real time. Reconstructing the three-dimensional transient temperature field using outer wall temperature data avoids the difficulty of directly measuring inner wall temperature and improves the accuracy and efficiency of temperature field calculations. The heat conduction equation is discretized using the finite volume method, the calculation region is divided into multiple control volumes, and the principle of energy conservation is applied to each control volume, thereby improving the accuracy of temperature field calculations. The temperature distribution is recursively extrapolated layer by layer from the outer wall to the inner wall, effectively solving the time-consuming problem of traditional iterative calculations and improving computational efficiency. A Savitzky-Golay filter based on local polynomial regression is used to smooth the temperature data, effectively suppressing measurement noise, improving the accuracy of temperature derivative calculations, and enhancing the system's dynamic data processing capabilities. Stress concentration factor corrections are introduced for complex geometric locations (such as fillets, openings, and welded joints) to improve the accuracy of stress calculations. Through a graded warning mechanism and an adaptive control unit, the system can automatically adjust boiler combustion parameters based on the degree of stress overrun, forming a closed-loop control system and improving the intelligent level of boiler operation. BRIEF DESCRIPTION OF THE DRAWINGS Figure 1 This is an overall architecture diagram of a boiler wall stress monitoring system based on reverse heat conduction calculation in an embodiment of the present invention; Figure 2 Temperature data smoothing flowchart in the embodiment of the present application; Figure 3 Finite volume meshing diagram of cylindrical pressure monitoring element in the embodiment of the present application; Figure 4 Steam header wall surface 500 s temperature and equivalent thermal stress distribution in the embodiment of the present application. DETAILED DESCRIPTION

[0023] In order to further understand the content of the present application, the present application is described in detail below in combination with the drawings and specific embodiments. It should be understood that the embodiments are only used to explain the present application and are not limited.

[0024] The embodiments of the present application are described in detail below in combination with the drawings.

[0025] Embodiment 1 The present embodiment proposes a boiler wall surface stress monitoring method based on inverse heat conduction calculation, including the following steps: Collecting real-time boiler wall surface temperature data; According to the boiler wall surface temperature data, a three-dimensional transient temperature field is constructed, and the heat transfer coefficient and real-time temperature distribution data are outputted; According to the heat transfer coefficient and real-time temperature distribution data, the thermal stress and pressure stress of the boiler pressure-bearing component are calculated, and the equivalent stress is calculated according to the thermal stress and pressure stress; Setting a stress threshold, stress evaluation is performed according to the equivalent stress and the stress threshold, and pre-warning, alarm or emergency shutdown is performed according to the evaluation result; according to different alarms, the corresponding boiler combustion temperature adjustment is performed.

[0026] Based on the above method steps, a detailed description is given as follows: In the present embodiment, the monitored element is a horizontal cylinder with water at the lower part and steam at the upper part. The outer radius is r out =0.1775 m and the wall thickness (r out -r in ) = 0.05 m, which is made of P91 steel. The thermal physical parameters are: thermal conductivity k = 29 W / (m·K), specific heat capacity c = 486 J / (kg·K), and density ρ = 7750 kg / m 3 . The mechanical parameters are: elastic modulus E = 1.96 × 10 5 MPa, thermal expansion coefficient β = 1.32 × 10 -5 K, and Poisson's ratio v = 0.3.

[0027] A plurality of high dynamic response fluid temperature sensors are uniformly distributed on the insulating layer of the outer surface of the pressure-bearing component in a combination of annular array and axial gradient; optionally, temperature sensors are arranged near the inner surface, arranged at a distance of 6-10 mm from the inner surface. In this embodiment, 7 armored K-type thermocouples are uniformly arranged on the outer wall of the horizontal cylinder monitoring element in the circumferential direction, and the arrangement positions are point 22, point 23, point 24, point 25, point 26, point 27 and point 28. The collection device is NI cDAQ-9188XT for collecting temperature data of the outer wall of the header, the sampling frequency is ≥10Hz, and the real-time boiler wall surface temperature data is collected through the armored K-type thermocouple; the real-time boiler wall surface temperature data includes the outer surface temperature of the boiler pressure-bearing component and the temperature near the inner surface.

[0028] The collected real-time boiler wall surface temperature data is subjected to data preprocessing, and a 9-point moving filter is used to smooth the collected data based on a local polynomial regression Savitzky-Golay filter, as shown in Figure 2 The digital filter calculation formula is as follows:

[0029] In the formula, is the data point after Savitzky-Golay filter processing, is the original collected data point, is the current considered data point time, is the sampling time interval.

[0030] Based on the data after data filtering, the central difference method is used to calculate the temperature change rate, and the calculation formula is as follows:

[0031] In the formula, represents the instantaneous change speed of wall temperature with time, represents the time step, represents the normalization factor, represents the integral average wall temperature on the wall thickness, represents the i-th time point.

[0032] Based on the real-time boiler wall surface temperature data after data filtering, the finite volume method is used to discretize the heat conduction equation, and 4 layers of radial grids are used for grid division to realize temperature field reconstruction. The grid division is as follows: 4 layers of radial grids, 12 nodes in the circumferential direction. The grid thickness of the 4 layers of radial grids is 12.5 mm, the angle span of the zhouxiang5 grid is 30°, and the grid division is as shown in Figure 3The division helps to capture the temperature gradient and thermal stress distribution along the thickness direction, which is crucial for evaluating the thermal response of the header under thermal load; and helps to capture the thermal distribution and stress change of the header wall surface in the circumferential direction, especially for headers with complex geometry or openings, and the circumferential grid division can ensure the accuracy of the calculation. The calculation area is divided into a plurality of control bodies, the energy conservation principle is applied to each control body, the heat conduction equation is integrated on the control body to obtain a discretization equation, and the temperature value of each node is obtained by iteratively solving the discretization equation to construct a three-dimensional transient temperature field. The finite volume method discretizes the heat conduction equation as follows:

[0033] wherein, is the specific heat capacity, is the density, is the transient change of the temperature field with time, is the heat flux density in the x, y, and z directions, respectively.

[0034] According to the above three-dimensional transient temperature field, the spatial propagation method is used to recursively propagate the temperature distribution from the outer wall to the inner wall layer by layer, and the heat transfer coefficient and temperature distribution data are output. According to the heat transfer coefficient and real-time temperature distribution data, the thermal stress and pressure stress of the boiler pressure part are calculated, and the equivalent stress is calculated according to the thermal stress and pressure stress. In the embodiment, the thermal stress calculation method of the boiler pressure part is as follows: based on the heat transfer coefficient and temperature distribution data, combined with the material parameters of the elastic modulus, thermal expansion coefficient and Poisson's ratio, based on the generalized Hook's law, considering the strain caused by temperature change, the calculation formula is as follows:

[0035] wherein, is the thermal stress tensor component; is the strain tensor component; is the bulk strain; is the Kronecker symbol; is the thermal expansion coefficient, is the temperature change, is the elastic modulus, is the Poisson's ratio. At this time, .

[0036] The pressure stress of the boiler pressure part is calculated, specifically: the pressure stress is caused by the internal pressure and the mechanical stress caused by the internal pressure. For the round corner transition area, a curvature radius weighting correction coefficient is used; for the opening edge, the equivalent elliptical hole theory is used for stress redistribution; for the welding joint, a material anisotropy correction factor is introduced for calculation.

[0037] The equivalent stress calculation adopts von-Mises criterion to calculate the equivalent stress, and the calculation formula is:

[0038] In the formula, are three principal stresses of the thermal stress tensor. The temperature and stress cloud map based on the stress calculation results is shown in Figure 4

[0039] The stress threshold is set, the equivalent stress is compared with the stress threshold in real time, the stress evaluation is carried out according to the equivalent stress and the stress threshold, and the pre-warning, alarm or emergency shutdown is carried out according to the evaluation result. The stress threshold is set according to the three-level alarm mechanism, and the boiler combustion parameters are automatically adjusted according to different stress overrun degrees; specifically as follows: When σ < 0.8σy, normal monitoring; when 0.8σy<σ<0.9σy, reduce the temperature rising rate by 20%; when 0.9σy<σ<1.0σy, maintain the current temperature; when σ>1.0σy, emergency cooling. In this embodiment, a real-time display interface is also provided, including temperature / stress cloud map Figure 4 ), key point trend curve and safety state indicating lamp.

[0040] Embodiment 2 Based on the boiler wall stress monitoring method based on reverse heat conduction calculation proposed in embodiment 1, this embodiment proposes a boiler wall stress monitoring system based on reverse heat conduction calculation. The reverse heat conduction calculation method is used to monitor the thermal stress of the thick-walled pressure components of the boiler in real time. As shown in Figure 1 , the system includes a data acquisition module, a data processing module, a stress calculation module and an alarm module, aiming to improve the safety and reliability of the boiler operation.

[0041] The data acquisition module uses a high dynamic response temperature sensor arranged near the outer surface and the inner surface of the boiler pressure component to acquire real-time boiler wall temperature data. The data processing module includes a multi-channel data acquisition unit, a digital filter unit, a time derivative calculation unit and a reverse heat conduction calculation unit. The data acquisition unit is used to acquire temperature data from the data acquisition module at a sampling frequency of ≥10Hz; the digital filter unit uses a Savitzky-Golay filter based on local polynomial regression to smooth the temperature data; the time derivative calculation unit uses the finite volume method to discretize the heat conduction equation, and recursively propagates the temperature distribution from the outer wall to the inner wall layer by layer to construct a three-dimensional transient temperature field, and outputs the heat transfer coefficient and real-time temperature distribution data.

[0042] ​​​The stress calculation module, based on temperature field data and material parameters (such as elastic modulus, thermal expansion coefficient, Poisson's ratio), applies generalized Hooke's law and von-Mises criterion to perform thermal stress and pressure stress of the boiler pressure components, and equivalent stress thermal stress calculation.

[0043] The alarm module is used to set a stress threshold, perform stress evaluation, and perform early warning, alarm or emergency shutdown according to the evaluation result, realize a multi-level early warning mechanism, and automatically adjust the boiler operating parameters according to the stress overrun degree, forming an adaptive control. It also integrates a visual interface to display temperature field and stress field cloud maps in real time. Through the recording of real-time data, continuous data analysis is performed to form historical trend curves and display them on the visual interface for data analysis by the staff.

[0044] Through the synergistic effect of the above-mentioned data acquisition module, data processing module, stress calculation module and alarm module, real-time monitoring of the thermal stress of the thick-walled pressure components of the boiler is realized, the thermal stress monitoring accuracy is improved, and the transient thermal stress change is monitored in real time; the boiler operating parameters are automatically adjusted according to the temperature field and stress field distribution, the safety and economy of the boiler operation are improved, and reliable technical support is provided for the safe operation of the boiler.

[0045] In addition, it should be understood that although the present specification is described in terms of embodiments, not every embodiment contains only one independent technical solution, and the description of the specification is only for the sake of clarity. The skilled person should consider the specification as a whole, and the technical solutions in each embodiment can be appropriately combined to form other embodiments that the skilled person can understand. The above is only to illustrate the technical idea of the present application, and cannot limit the protection scope of the present application. Any modification made on the basis of the technical solutions of the present application falls within the protection scope of the claims of the present application.

Claims

1. A boiler wall stress monitoring method based on reverse heat conduction calculation, characterized in that: The following steps are involved: Collect real-time boiler wall temperature data; Based on the boiler wall temperature data, a three-dimensional transient temperature field is constructed, and the heat transfer coefficient and real-time temperature distribution data are output; Calculate the thermal stress and pressure stress of boiler pressure-bearing components based on the heat transfer coefficient and real-time temperature distribution data, and calculate the equivalent stress based on the thermal stress and pressure stress; Set stress thresholds, conduct stress assessments based on equivalent stress and stress thresholds, and issue early warnings, alarms, or emergency shutdowns based on the assessment results; adjust boiler combustion temperature accordingly based on different alarms.

2. A boiler wall stress monitoring method based on reverse heat conduction calculation according to claim 1, characterized in that: The method constructs a three-dimensional transient temperature field based on the boiler wall temperature data, and outputs the heat transfer coefficient and real-time temperature distribution data. Specifically, based on the real-time boiler wall temperature data, the finite volume method is used to discretize the heat conduction equation, and a four-layer radial grid is used to reconstruct the temperature field to construct a three-dimensional transient temperature field. Based on the three-dimensional transient temperature field, the space advancement method is used to recursively deduce the temperature distribution layer by layer from the outer wall to the inner wall, and the heat transfer coefficient and temperature distribution data are output.

3. The boiler wall stress monitoring method based on reverse heat conduction calculation according to claim 2, characterized in that: The finite volume method discretizes the heat conduction equation as follows: the calculation area is divided into multiple control volumes, the energy conservation principle is applied to each control volume, the heat conduction equation is integrated over the control volume to obtain a discretized equation, and the temperature value of each node is obtained by iteratively solving the discretized equation. The finite volume method discretizes the heat conduction equation as follows: Where, is the specific heat capacity, density, is the transient change of temperature field over time, are the heat flux densities in the x, y, and z directions respectively.

4. The boiler wall stress monitoring method based on reverse heat conduction calculation according to claim 3 is characterized in that: The finite volume method discretizes the heat conduction equation and combines the temperature change rate. The temperature change rate is calculated based on the central difference method and the calculation formula is as follows: Where, represents the instantaneous rate of change of wall temperature over time, represents the time step, represents the normalization factor, represents the integrated average wall temperature over the wall thickness, represents the i-th time point.

5. The boiler wall stress monitoring method based on reverse heat conduction calculation according to claim 1, characterized in that: The thermal stress calculation method for the boiler pressure-bearing components is as follows: Based on real-time boiler wall temperature data, combined with elastic modulus, thermal expansion coefficient, and Poisson's ratio material parameters, based on generalized Hooke's law, and considering the strain caused by temperature changes, the calculation formula is as follows: Where, is the thermal stress tensor component; is the strain tensor component; is the body strain; is the Kronecker symbol; is the coefficient of thermal expansion, is the temperature change, is the elastic modulus, is Poisson's ratio.

6. The boiler wall stress monitoring method based on reverse heat conduction calculation according to claim 1, characterized in that: Calculate the pressure stress of the boiler pressure-bearing parts, specifically: the pressure stress is the mechanical stress caused by the internal pressure and, for the fillet transition area, the curvature radius weighted correction coefficient is used ,in, is the fillet transition radius, The characteristic dimensions related to the fillet transition area are as follows; for the edge of the opening, the equivalent elliptical hole theory is applied to perform stress redistribution; for the welded joint, the material anisotropy correction factor is introduced for calculation.

7. The boiler wall stress monitoring method based on reverse heat conduction calculation according to claim 1, characterized in that: The equivalent stress calculation adopts the von-Mises criterion to calculate the equivalent stress, and the calculation formula is: Where, 、 、 are the three principal stresses of the thermal stress tensor.

8. The boiler wall stress monitoring method based on reverse heat conduction calculation according to claim 1, characterized in that: The real-time boiler wall temperature data and the retrograde data collected are pre-processed, and a 9-point moving filter and a Savitzky-Golay filter based on polynomial regression are used to smooth the collected data. The digital filtering calculation formula is as follows: Where, is the data point processed by Savitzky-Golay filter, is the original collected data point, is the time of the data point currently considered, is the sampling time interval.

9. The boiler wall stress monitoring method based on reverse heat conduction calculation according to claim 8, characterized in that: The real-time boiler wall temperature data includes the outer surface temperature and the temperature near the inner surface of the boiler pressure-bearing components.

10. A boiler wall stress monitoring system based on reverse heat conduction calculation, based on a boiler wall stress monitoring method based on reverse heat conduction calculation according to any one of claims 1 to 9, characterized in that: Including data acquisition module; data processing module, stress calculation module and alarm module; The data acquisition module is used to collect real-time boiler wall temperature data; The data processing module is used to construct a three-dimensional transient temperature field based on the boiler wall temperature data and output the heat transfer coefficient and real-time temperature distribution data; The stress calculation module is used to calculate the thermal stress and pressure stress of the boiler pressure-bearing components based on the heat transfer coefficient and real-time temperature distribution data, and calculate the equivalent stress based on the thermal stress and pressure stress; The alarm module is used to set a stress threshold, perform stress assessment based on the equivalent stress and stress threshold, and issue an early warning, alarm or emergency shutdown based on the assessment results; and adjust the boiler combustion temperature accordingly based on different alarms.

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