Boiler furnace temperature field simulation method, system, device and storage medium

Abstract

This application provides a method, system, device, and storage medium for simulating the temperature field of a boiler furnace. The method includes: generating an acoustic signal within the boiler furnace using probes at preset measuring points; adaptively filtering the acoustic signal in a simulation system to obtain a denoised signal; comparing the denoised signal with a standard template using a generalized cross-correlation method; correcting the propagation delay using the generalized cross-correlation method to obtain the signal propagation time between probes; obtaining the average temperature between each probe based on the propagation time; constructing the initial temperature field of the boiler furnace using an image reconstruction algorithm, wherein the image reconstruction algorithm considers prior furnace information during execution; and iteratively correcting the temperature field considering the bending effect of acoustic wave propagation, using the initial temperature field as the starting input for the first round of iteration correction; and obtaining the final simulation result of the temperature field after the iteration is completed. This application essentially replaces thermocouples, forming an effective boiler furnace temperature simulation scheme.

Description

Technical Field

[0001] This invention relates to the field of visualization simulation technology, and in particular to a method, system, device and storage medium for simulating the temperature field of a boiler furnace. Background Technology

[0002] Boiler furnace temperature field simulation refers to the process of creating a virtual model of the boiler furnace using computer technology, calculating the temperature at every point inside the furnace, and finally displaying the temperature distribution inside the furnace in a visual form.

[0003] In related technologies, traditional techniques generally employ contact-based measurement methods, using thermocouples or furnace flue gas temperature probes. However, due to the complex and harsh measurement environment of the furnace—high temperature, high dust, large space, and turbulence—contact measurement techniques are prone to problems such as coking, temperature drift, and rapid burnout, leading to frequent replacements and heavy maintenance workload. To address these issues, acoustic temperature measurement technology has emerged. Based on the principle that the speed of sound in a gas is proportional to the square root of the gas's absolute temperature, computed tomography (CT) technology is used to reconstruct the temperature field distribution of the furnace cross-section. However, due to boiler structural limitations and cost considerations, the number of probes is usually limited. Reconstructing a temperature field containing tens of thousands of pixels using only a few path detection data is extremely sensitive to measurement errors. Traditional reconstruction algorithms, such as filtered back projection and algebraic reconstruction techniques, can lead to blurred images or physical inaccuracies. Furthermore, the extremely uneven temperature distribution within the furnace results in uneven spatial distribution of sound velocity, causing the sound wave propagation path to be curved rather than straight, an effect that traditional reconstruction processes ignore.

[0004] Based on the above analysis of the development status of this technology field, the existing technologies lack a scheme that considers the prior information of the furnace as a regularization constraint on the basis of traditional image reconstruction algorithms, and considers the bending effect of sound wave propagation to iteratively correct and obtain the temperature field. Summary of the Invention

[0005] The purpose of this invention is to provide a method, system, device, and storage medium for simulating the temperature field of a boiler furnace, in order to solve the aforementioned problems in the prior art.

[0006] According to a first aspect of the present invention, a method for simulating the temperature field of a boiler furnace is provided, comprising: A sound wave signal is generated inside the boiler furnace through a probe at a preset measuring point; In the simulation system, the acoustic signal is adaptively filtered to obtain a denoised signal. Based on the denoised signal, a generalized cross-correlation method is used to compare it with a standard template. The propagation delay is corrected by the generalized cross-correlation method to obtain the propagation time of the signal between the probes. The average temperature between each probe is obtained based on the propagation time. An image reconstruction algorithm is used to construct the initial temperature field of the boiler furnace. The image reconstruction algorithm takes into account the prior information of the furnace during the execution process. Considering the bending effect of sound wave propagation, an iterative method is used to gradually correct the temperature field. The initial temperature field is used as the starting input for the first round of iterative correction, and the simulation result of the final temperature field is obtained after the iteration is completed.

[0007] According to a second aspect of the present invention, a boiler furnace temperature field simulation system is provided, comprising: The initial detection module is used to generate acoustic signals in the boiler furnace through a probe at a preset measuring point; The time estimation module is used to perform adaptive filtering on the acoustic signal in the simulation system to obtain a denoised signal. Based on the denoised signal, it is compared with a standard template using a generalized cross-correlation method. The propagation delay is corrected by the generalized cross-correlation method to obtain the propagation time of the signal between the probes. The temperature field simulation module is used to obtain the average temperature between each probe based on the propagation time, and to construct the initial temperature field of the boiler furnace using an image reconstruction algorithm. The image reconstruction algorithm takes into account the prior information of the furnace during the execution process. The iterative correction module is used to gradually correct the temperature field in an iterative manner, taking into account the bending effect of sound wave propagation. The initial temperature field is used as the starting input for the first round of iterative correction, and the simulation result of the final temperature field is obtained after the iteration is completed.

[0008] According to a third aspect of the present invention, an electronic device is provided, comprising: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the computer program, when executed by the processor, implements the steps of the boiler furnace temperature field simulation method provided in the first aspect of the present disclosure.

[0009] According to a fourth aspect of the present invention, a computer-readable storage medium is provided, on which an information transmission implementation program is stored, which, when executed by a processor, implements the steps of the boiler furnace temperature field simulation method provided in the first aspect of the present disclosure.

[0010] The technical solution provided by the embodiments of the present invention has the following beneficial effects: the signal processing method combining adaptive filtering and generalized cross-correlation can accurately estimate the sound wave aircraft time in the environment of extremely high background noise and strong reverberation of boilers, providing a reliable data foundation for reconstruction; the image reconstruction algorithm considers the prior information of the furnace as a physical constraint during execution, solving the problem of inverse problem unsuitability caused by the small number of probes, and can still reconstruct a stable and reliable temperature field under sparse data conditions; the sound ray bending effect is corrected by iterative method, making the reconstruction model more in line with physical reality.

[0011] It should be understood that the above general description and the following detailed description are exemplary and explanatory only, and are not intended to limit this disclosure. Attached Figure Description

[0012] To more clearly illustrate the technical solutions in one or more embodiments of this specification or in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments recorded in this specification. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0013] Figure 1 This is a flowchart of the boiler furnace temperature field simulation method according to an embodiment of the present invention; Figure 2 This is a schematic diagram of the preset measuring points in an embodiment of the present invention; Figure 3 This is a schematic diagram of a boiler furnace temperature field simulation system according to an embodiment of the present invention; Figure 4 This is a schematic diagram of an electronic device according to an embodiment of the present invention. Detailed Implementation

[0014] To enable those skilled in the art to better understand the technical solutions in one or more embodiments of this specification, the technical solutions in one or more embodiments of this specification will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of this specification, and not all of the embodiments. Based on one or more embodiments of this specification, all other embodiments obtained by those skilled in the art without creative effort should fall within the protection scope of this document.

[0015] Method Implementation Examples According to an embodiment of the present invention, a method for simulating the temperature field of a boiler furnace is provided. Figure 1 This is a flowchart of the boiler furnace temperature field simulation method according to an embodiment of the present invention, as follows: Figure 1 As shown, the boiler furnace temperature field simulation method according to an embodiment of the present invention specifically includes: In step S110, an acoustic signal is generated inside the boiler furnace by a probe at a preset measuring point, specifically including: The preset measurement points are obtained by comparing the simulation results by changing the measurement point positions. In other words, the optimal configuration is obtained by comparison under the same boiler furnace scale scenario in the past. At each preset measurement point, a transceiver probe is set. Preferably, the specific sound wave signal to be selected is also determined through a pre-comparison method to obtain a better one; Each probe transmits acoustic signals to all the remaining probes, forming a mesh structure of linear acoustic signals. Figure 2 This is a schematic diagram of the preset measurement points in an embodiment of the present invention, as shown below. Figure 2 As shown, the optimal arrangement of furnace temperature field measurement points is demonstrated, with 8 transceiver probes installed.

[0016] In step S120, the acoustic signal is adaptively filtered in the simulation system to obtain a denoised signal. Based on the denoised signal, a generalized cross-correlation method is used to compare it with a standard template. The propagation delay is corrected using the generalized cross-correlation method to obtain the propagation time of the signal between the probes. Specifically, this includes: Perform adaptive filtering in the Matlab simulation system; The ambient noise without sound wave signal is simulated by a high noise and strong reverberation model, and the parameters of the adaptive filter are initialized. The adaptive filter is used to generate an inverse signal that cancels out the ambient noise. The noise component of the sound wave signal is suppressed by the inverse signal to obtain a noise-reduced signal.

[0017] Obtain the standard template of the signal stored at the current probe transmitter. The standard template is the original and pure acoustic signal at the acoustic transmitter that has not been interfered with by the furnace environment. The denoised signal and the standard template are input into a generalized cross-correlation method. The denoised signal is slid relative to the standard template, and the similarity at each sliding position is calculated point by point. That is, the similarity between the denoised signal segment and the entire standard template. The time coordinate corresponding to the peak similarity in the global region is used as the propagation time. Since signals change over time, they can be compared over time. The generalized cross-correlation method is used to observe signal delay, i.e., the propagation time of the physical propagation angle. The method has a built-in cross-correlation function. The horizontal axis of this function is time, which is used to determine the time coordinate corresponding to the peak of similarity in the global spectrum, and the vertical axis is similarity.

[0018] In step S130, the average temperature between each probe is obtained based on the propagation time, and an image reconstruction algorithm is used to construct the initial temperature field of the boiler furnace. The image reconstruction algorithm considers prior information about the furnace during execution, specifically including: The average temperature is calculated using the square root formula that describes the relationship between propagation time and temperature. ,in, The speed of sound is used to indirectly determine the propagation time. Represents a constant. Indicates temperature.

[0019] Use filtered back projection or algebraic reconstruction methods as image reconstruction algorithms; In the process of performing the image reconstruction algorithm, the prior information of the furnace is used as a physical constraint. The physical constraints include the average temperature invariance constraint, the temperature change smoothness constraint, the value range constraint, and the flame structure region constraint. The average temperature constrain means that the average temperature between probes remains constant; the temperature change smoothness constraint means that the temperature in adjacent areas changes continuously without drastic jumps; the value range constraint mandates that the temperature at each point in the temperature field must fall within a preset, physically reasonable range; the flame structure region constraint guides the reconstruction algorithm to form a macroscopic structure that conforms to the common sense of combustion, that is, there is a relatively continuous high-temperature core area and a temperature gradient that decreases towards the surrounding water-cooled walls.

[0020] Preferably, when using the algebraic reconstruction method, truncated singular value decomposition is used as a regularization constraint while using physical constraints. Since the number of probes is small, truncated singular value decomposition serves as a mathematical filter to ensure the smoothness and stability of the temperature field construction; only physical constraints are used when performing filtered back projection. Constructing a complete two-dimensional pixel temperature map based on a sparse mesh structure as the initial temperature field is equivalent to... Figure 2 Divide the grid into small grids and fill in the temperature.

[0021] In step S140, considering the bending effect of sound wave propagation, the temperature field is iteratively corrected step by step. The initial temperature field is used as the starting input for the first round of iterative correction. After the iteration is completed, the simulation result of the final temperature field is obtained, which specifically includes: The initial temperature field assumes that the sound waves between the probes are straight lines. However, for a medium like a boiler with uneven sound velocity, the sound waves tend to travel a longer distance in the high-temperature zone and bypass the low-temperature zone, naturally forming a curve. In the current iteration process, i.e. the current temperature field, the curvature of the sound wave is adaptively adjusted according to the temperature distribution in the current temperature field by ray tracing, and the simulated transmission time of the sound wave after adjusting the curvature is simulated by path integration. The propagation time obtained by the generalized cross-correlation method is used as the benchmark value. The simulated transmission time is the result of actual statistics based on the current temperature field. The difference between the simulated transmission time and the benchmark value is calculated. The difference can be used as a standard to judge right and wrong and to clarify the direction of iteration. The temperature field is readjusted based on the difference. The temperature field is readjusted based on the difference, specifically as follows: if the difference ΔT>0, it means that the theoretical time is longer than the actual time, and it is speculated that the temperature field is generally low in the sound wave path region, so the temperature within the preset range of the route is adaptively increased; if the difference ΔT<0, it means that the theoretical time is shorter than the actual time, and it is speculated that the temperature field is generally high in the sound wave path region, so the temperature within the preset range of the route is adaptively decreased. The system determines whether the difference between the current temperature field and the previous temperature field is less than a preset threshold. This means comparing the temperature field after readjustment with the final output temperature field of the previous round. This is achieved by calculating the norm of the difference across the entire field, i.e., subtracting each pixel, and obtaining a representative value from the difference matrix through root mean square error, etc. If the temperature field difference is less than the preset threshold, the iteration terminates, and the time difference value also converges. Otherwise, the temperature field is readjusted and used as the current temperature field for the initial iteration of the next round.

[0022] The method further includes: In step S150, the simulation results of the final temperature field are visualized, forming visualized information including regional temperature maps, isotherm maps, and three-dimensional temperature maps. This facilitates operators to promptly determine whether the temperature distribution and flame center have shifted, preventing local overheating and overheating of the water-cooled wall. The acoustic measurement point unit will utilize the existing observation holes and soot blowing reserved holes of the boiler.

[0023] The embodiments of the present invention involve a central processing unit, a furnace measuring point unit, a sound wave generating unit, a sound wave receiving unit, a DCS communication unit, and an image output unit.

[0024] In summary, addressing the existing problems, this invention presents a boiler furnace temperature field simulation method. It employs a signal processing approach combining adaptive filtering and generalized cross-correlation, enabling accurate estimation of acoustic flight time in environments with extremely high background noise and strong reverberation, providing a reliable data foundation for reconstruction. The image reconstruction algorithm considers prior furnace information as a physical constraint. When using algebraic reconstruction, it incorporates truncated singular value decomposition as a regularization constraint alongside physical constraints, handling mathematical noise during the solution process and resolving the inverse problem's inadequacy due to a limited number of probes. Even under sparse data conditions, it can still reconstruct a stable and reliable temperature field. An iterative method corrects the acoustic ray bending effect, making the reconstruction model more physically accurate. Finally, it generates multi-mode visualized information results, facilitating intuitive judgment and adjustment of the flame center position, guiding adjustments to the secondary damper opening, preventing flame center deviation, and preventing furnace coking. It also allows for intuitive judgment and adjustment of combustion in local high-temperature areas, reducing NOx concentration. The overall solution replaces thermocouples, enabling online measurement of furnace outlet flue gas temperature throughout the entire cycle from ignition to full load, forming an important and intuitive boiler furnace temperature simulation scheme.

[0025] System Implementation Examples According to an embodiment of the present invention, a boiler furnace temperature field simulation system is provided. Figure 3 This is a schematic diagram of a boiler furnace temperature field simulation system according to an embodiment of the present invention, as shown below. Figure 3 As shown, the boiler furnace temperature field simulation system according to an embodiment of the present invention specifically includes: The initial detection module 30 is used to generate acoustic signals in the boiler furnace through a probe at a preset measuring point, specifically for: Pre-determined measurement points are obtained by comparing simulation results with changes in the measurement point positions. Each of the pre-determined measurement points is equipped with a transceiver probe. Each probe transmits acoustic signals to all the remaining probes, forming a mesh structure of linear acoustic signals.

[0026] The time estimation module 32 is used to adaptively filter the acoustic signal in the simulation system to obtain a denoised signal. Based on the denoised signal, it compares it with a standard template using a generalized cross-correlation method. The propagation delay is corrected using the generalized cross-correlation method to obtain the signal propagation time between the probes. Specifically, it is used for: Perform adaptive filtering in the Matlab simulation system; The ambient noise without sound wave signal is simulated by a high noise and strong reverberation model, and the parameters of the adaptive filter are initialized. The adaptive filter is used to generate an inverse signal that cancels out the ambient noise. The noise component of the sound wave signal is suppressed by the inverse signal to obtain a noise-reduced signal.

[0027] Obtain the standard template of the signal stored at the current probe transmitter; The denoised signal and the standard template are input into a generalized cross-correlation method. The denoised signal is slid relative to the standard template, and the similarity at each sliding position is calculated point by point. The time coordinate corresponding to the peak similarity in the global data is used as the propagation time.

[0028] The temperature field simulation module 34 is used to obtain the average temperature between each probe based on the propagation time, and to construct the initial temperature field of the boiler furnace using an image reconstruction algorithm. The image reconstruction algorithm considers prior furnace information during execution, specifically for: Calculate the average temperature using the square root formula that describes the relationship between propagation time and temperature; The image reconstruction algorithm uses either filtered back projection or algebraic reconstruction. During the execution of the image reconstruction algorithm, the prior information of the furnace is used as a physical constraint. The physical constraints include the constraint of constant average temperature, the constraint of smoothness of temperature change, the constraint of value range, and the constraint of flame structure region. When using algebraic reconstruction, truncated singular value decomposition is used as a regularization constraint while using physical constraints. A complete two-dimensional pixel temperature map is constructed based on the sparse mesh structure as the initial temperature field.

[0029] The iterative correction module 36 is used to progressively correct the temperature field using an iterative method, taking into account the bending effect of sound wave propagation. The initial temperature field is used as the starting input for the first round of iterative correction. After the iterations are completed, the simulation result of the final temperature field is obtained. Specifically, it is used for: In the current iteration process, i.e. the current temperature field, the curvature of the sound wave is adaptively adjusted according to the temperature distribution in the current temperature field by ray tracing, and the simulated transmission time of the sound wave after adjusting the curvature is simulated. The propagation time obtained by the generalized cross-correlation method is used as the benchmark value. The difference between the simulated transmission time and the benchmark value is calculated. The temperature field is readjusted based on the difference and it is determined whether the difference between the current temperature field and the current temperature field is less than a preset threshold. If the temperature field difference is less than the preset threshold, the iteration terminates. Otherwise, the temperature field is readjusted as the current temperature field at the beginning of the next iteration.

[0030] The system further includes: The visualization module 38 is used to visualize the simulation results of the final temperature field, forming visualization information including regional temperature maps, isotherm maps, and three-dimensional temperature maps.

[0031] In summary, addressing the existing problems, this invention presents a boiler furnace temperature field simulation system. It employs a signal processing method combining adaptive filtering and generalized cross-correlation, accurately estimating acoustic flight time in environments with extremely high background noise and strong reverberation, providing a reliable data foundation for reconstruction. The image reconstruction algorithm considers prior furnace information as a physical constraint. When using algebraic reconstruction, it incorporates truncated singular value decomposition as a regularization constraint alongside physical constraints, handling mathematical noise during the solution process and resolving the inverse problem's inadequacy due to a limited number of probes. Even under sparse data conditions, it can still reconstruct a stable and reliable temperature field. An iterative method corrects the acoustic ray bending effect, making the reconstruction model more physically accurate. Finally, it generates multi-mode visualized information results, facilitating intuitive judgment and adjustment of the flame center position, guiding adjustments to the secondary damper opening, preventing flame center deviation, and preventing furnace coking. It also allows for intuitive judgment and adjustment of combustion in local high-temperature areas, reducing NOx concentration. The overall solution replaces thermocouples, enabling online measurement of furnace outlet flue gas temperature throughout the entire cycle from ignition to full load, forming an important and intuitive boiler furnace temperature simulation scheme.

[0032] Electronic device examples Figure 4 This is a schematic diagram of an electronic device according to an embodiment of the present invention. The electronic device 400 may include at least one processor 410 and a memory 420. The processor 410 can execute instructions stored in the memory 420. The processor 410 is communicatively connected to the memory 420 via a data bus. In addition to the memory 420, the processor 410 can also be communicatively connected to an input device 430, an output device 440, and a communication device 450 via the data bus.

[0033] Processor 410 can be any conventional processor, such as a commercially available CPU. Processors may also include graphics processing units (GPUs), field-programmable gate arrays (FPGAs), systems-on-chips (SoCs), application-specific integrated circuits (ASICs), or combinations thereof.

[0034] The memory 420 can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as static random access memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic storage, flash memory, magnetic disk or optical disk.

[0035] In this embodiment of the present disclosure, the memory 420 stores executable instructions, and the processor 410 can read the executable instructions from the memory 420 and execute the instructions to implement all or part of the steps of the boiler furnace temperature field simulation method in any of the exemplary embodiments described above.

[0036] Computer-readable storage medium embodiments In addition to the methods and systems described above, exemplary embodiments of this disclosure may also be a computer program product or a computer-readable storage medium storing the computer program product, the computer product including computer program instructions that can be executed by a processor to implement all or part of the steps described in any of the boiler furnace temperature field simulation methods in the exemplary embodiments described above.

[0037] Computer program products can be written in any combination of one or more programming languages ​​to perform the operations of the embodiments of this application. Programming languages ​​include object-oriented programming languages ​​such as Java and C++, as well as conventional procedural programming languages ​​such as C or similar languages, and scripting languages ​​(e.g., Python). The program code can be executed entirely on the user's computing device, partially on the user's device, as a standalone software package, partially on the user's computing device and partially on a remote computing device, or entirely on a remote computing device or server.

[0038] Computer-readable storage media may be any combination of one or more readable media. A readable medium may be a readable signal medium or a readable storage medium. A readable storage medium may be, for example,, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination thereof. More specific examples of readable storage media include: static random access memory (SRAM) having one or more electrically connected wires; electrically erasable programmable read-only memory (EEPROM); erasable programmable read-only memory (EPROM); programmable read-only memory (PROM); read-only memory (ROM); magnetic storage; flash memory; magnetic disk or optical disk; or any suitable combination thereof.

[0039] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, and not to limit them; although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some or all of the technical features; and these modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of the present invention.

Claims

1. A method for simulating the temperature field of a boiler furnace, characterized in that, include: A sound wave signal is generated inside the boiler furnace through a probe at a preset measuring point; In the simulation system, the acoustic signal is subjected to adaptive filtering to obtain a noise-reduced signal. Based on the noise-reduced signal, a generalized cross-correlation method is used to compare it with a standard template. The propagation delay is corrected by the generalized cross-correlation method to obtain the propagation time of the signal between the probes. The average temperature between each probe is obtained based on the propagation time, and the initial temperature field of the boiler furnace is constructed using an image reconstruction algorithm, wherein the prior information of the furnace is considered during the execution of the image reconstruction algorithm. Considering the bending effect of sound wave propagation, an iterative method is used to gradually correct the temperature field. The initial temperature field is used as the starting input for the first round of iterative correction, and the simulation result of the final temperature field is obtained after the iteration is completed.

2. The method according to claim 1, characterized in that, The method further includes: The simulation results of the final temperature field are visualized to form visualized information including regional temperature maps, isotherm maps, and three-dimensional temperature maps.

3. The method according to claim 1, characterized in that, The specific steps involved in generating acoustic signals within the boiler furnace using a probe at a preset measuring point include: A preset measuring point is obtained by comparing the simulation results by changing the measuring point position. A transceiver probe is set at each of the preset measuring points. Each probe transmits the acoustic signal to all the remaining probes, forming a mesh structure of the acoustic signal in a linear form.

4. The method according to claim 1, characterized in that, The adaptive filtering process performed on the acoustic signal in the simulation system to obtain the noise-reduced signal specifically includes: Perform adaptive filtering in the Matlab simulation system; The ambient noise without sound wave signal is simulated by a high-noise, strong reverberation model, and the parameters of the adaptive filter are initialized. The adaptive filter is used to generate an inverse signal that cancels out the ambient noise, and the noise component of the sound wave signal is suppressed by the inverse signal to obtain the noise-reduced signal.

5. The method according to claim 1, characterized in that, The step of comparing the denoised signal with a standard template using a generalized cross-correlation method and correcting the propagation delay using the generalized cross-correlation method to obtain the signal propagation time between the probes specifically includes: Obtain the standard template of the signal stored at the current probe transmitter; The denoised signal and the standard template are input into a generalized cross-correlation method. The denoised signal is slid relative to the standard template, and the similarity at each sliding position is calculated point by point. The time coordinate corresponding to the peak similarity in the global data is used as the propagation time.

6. The method according to claim 1, characterized in that, The step of obtaining the average temperature between each probe based on the propagation time and constructing the initial temperature field of the boiler furnace using an image reconstruction algorithm specifically includes: The average temperature is calculated using the square root formula that describes the relationship between propagation time and temperature. The image reconstruction algorithm uses either filtered back projection or algebraic reconstruction. During the execution of the image reconstruction algorithm, prior information about the furnace is used as a physical constraint. The physical constraints include an invariant average temperature constraint, a smoothness constraint for temperature changes, a range constraint for values, and a constraint for the flame structure region. When using algebraic reconstruction, truncated singular value decomposition is used as a regularization constraint while using the physical constraints. A complete two-dimensional pixel temperature map is constructed based on the sparse mesh structure as the initial temperature field.

7. The method according to claim 1, characterized in that, The bending effect considering sound wave propagation is used to iteratively correct the temperature field. The initial temperature field is used as the starting input for the first round of iteration correction. After the iteration, the simulation results of the final temperature field are obtained, specifically including: In the current iteration process, i.e. the current temperature field, the curvature of the sound wave is adaptively adjusted according to the temperature distribution in the current temperature field by ray tracing, and the simulated transmission time of the sound wave after adjusting the curvature is simulated. The propagation time obtained by the generalized cross-correlation method is used as the reference value. The difference between the simulated transmission time and the reference value is calculated. The temperature field is readjusted according to the difference and it is determined whether the difference between the temperature field and the current temperature field is less than a preset threshold. If the temperature field difference is less than the preset threshold, the iteration terminates. Otherwise, the temperature field is readjusted as the current temperature field at the beginning of the next iteration.

8. A boiler furnace temperature field simulation system, characterized in that, include: The initial detection module is used to generate acoustic signals in the boiler furnace through a probe at a preset measuring point; The time estimation module is used to perform adaptive filtering on the acoustic signal in the simulation system to obtain a noise-reduced signal. Based on the noise-reduced signal, it compares it with a standard template using a generalized cross-correlation method. The propagation delay is corrected by the generalized cross-correlation method to obtain the propagation time of the signal between the probes. The temperature field simulation module is used to obtain the average temperature between each probe based on the propagation time, and to construct the initial temperature field of the boiler furnace using an image reconstruction algorithm, wherein the image reconstruction algorithm takes into account prior information of the furnace during execution. The iterative correction module is used to gradually correct the temperature field in an iterative manner, taking into account the bending effect of sound wave propagation. The initial temperature field is used as the starting input for the first round of iterative correction, and the simulation result of the final temperature field is obtained after the iteration is completed.

9. An electronic device, characterized in that, include: The memory, the processor, and the computer program stored in the memory and executable on the processor, wherein the computer program, when executed by the processor, implements the steps of the boiler furnace temperature field simulation method as described in any one of claims 1 to 8.

10. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores an implementation program for information transmission, which, when executed by a processor, implements the steps of the boiler furnace temperature field simulation method as described in any one of claims 1 to 8.

Images