Method and device for measuring flame temperature based on virtual multi-spectral radiation intensity

Abstract

The present invention provides a method and device for measuring flame temperature based on virtual multispectral radiation intensity. The method comprises: step S101, measuring m flame multispectral radiation intensity images using a multispectral imaging device; step S102, establishing a virtual multispectral radiation intensity model, including parameters for flame temperature and emissivity; step S103, setting the starting and ending wavelengths, fitting step size, and fitting order of the virtual multispectral radiation intensity; step S104, obtaining initial iteration values for the flame temperature and emissivity using a two-color method; step S105, iterating using a Newton iteration method until the flame temperature and emissivity no longer change, and then outputting the flame temperature and emissivity; step S106, substituting the flame temperature and emissivity outputted in step S105 for error analysis; and step S107, determining the flame temperature outputted in step S105 as the final flame temperature if the error is within an allowable range. The present invention provides reliable results and high accuracy.

Description

Technical Field

[0001] The present invention relates to the field of spectral technology, and in particular to a method and device for measuring flame temperature based on virtual multi-spectral radiation intensity. Background Art

[0002] Non-contact temperature measurement technology based on flame spontaneous radiation is an important measurement method. The advantages of radiation measurement technology are even more significant when measuring complex objects such as rocket engine combustion chambers and power plant boilers, where interference is not allowed. The flame temperature is coupled to the flame spectral radiation intensity. By solving the multi-spectral radiation intensity deviation equation system, the flame temperature spatial distribution can be reconstructed. However, due to the spectral resolution performance of the spectral detection equipment, when the spectral resolution of the detected spectral radiation intensity is low, the emergence of underdetermined matrices in the process of solving the multi-spectral radiation intensity deviation equation brings great difficulties to the solution of the flame temperature. Therefore, it is of great significance to invent a method based on virtual multi-spectral radiation intensity fitting technology that can achieve high-precision reconstruction of flame temperature using only low spectral resolution detection spectral radiation intensity. Summary of the Invention

[0003] The purpose of the embodiments of the present invention is to provide a method and device for measuring flame temperature based on virtual multispectral radiation intensity. The method and device for measuring flame temperature based on virtual multispectral radiation intensity overcome the uncertainty of temperature solution caused by the low spectral resolution performance of multispectral imaging equipment, and the results are reliable and highly accurate.

[0004] To achieve the above-mentioned object, an embodiment of the present invention provides a method for measuring flame temperature based on virtual multispectral radiation intensity, the method comprising: step S101, using a multispectral imaging device to measure m flame multispectral radiation intensity images; step S102, based on a polynomial emissivity model, establishing a virtual multispectral radiation intensity model, the virtual multispectral radiation intensity model including parameters of flame temperature and emissivity; step S103, setting the wavelength λ of the starting band of the virtual multispectral radiation intensity start , end band wavelength λ stop , fitting step length δλ and fitting order p; step S104, based on the starting band wavelength λ start , end band wavelength λ stop , fitting step length δλ and fitting order p, according to the m flame multispectral radiation intensity images, the iterative initial value of the flame temperature is obtained by the two-color method and the initial value of the emissivity Step S105: based on the iterative initial value of the flame temperature and the iterative initial value of the emissivity Based on the virtual multispectral radiation intensity model, the Newton iteration method is used to iterate until the flame temperature and the emissivity no longer change, and the flame temperature and the emissivity are output; in step S106, based on the virtual multispectral radiation intensity model, according to the m flame multispectral radiation intensity images, the flame temperature and emissivity output in step S105 are substituted for error analysis; in step S107, when the error is within the allowable range, the flame temperature output in step S105 is determined to be the final flame temperature; when the error is not within the allowable range, the fitting order p is increased and steps S104-S106 are repeated for iteration until the error is within the allowable range.

[0005] Preferably, the virtual multispectral radiation intensity model is:

[0006]

[0007] in, is the virtual multispectral radiation intensity, c1 and c2 are Planck's first and second constants respectively, λ is the wavelength, T is the flame temperature, and ε(λ) is the emissivity.

[0008] Preferably, step S104 includes:

[0009] Step S201, based on the fitting order p, obtain the wavelength according to the m flame multispectral radiation intensity images and wavelength The first virtual multi-spectral radiation intensity and the second virtual multi-spectral radiation intensity at ;

[0010] Step S202: Obtain the initial value of the flame temperature iteration according to the following formula: and the initial value of the emissivity

[0011]

[0012] in, is the first virtual multispectral radiation intensity, is the second virtual multispectral radiation intensity, δλ is the fitting step size, c1 and c2 are the first and second Planck constants respectively.

[0013] Preferably, step S201 includes:

[0014] Step S301: construct a Vandermonde matrix and generate a linear equation system based on the m flame multispectral radiation intensity images:

[0015] Step S302: Perform QR decomposition on the Vandermonde matrix and solve the orthogonal matrix Q of Q T , the inverse matrix R -1, solve the virtual multispectral radiation intensity fitting polynomial coefficient x by the following formula:

[0016] x=R -1 Q T I r ;

[0017] Step S303: fitting the polynomial coefficient x according to the virtual multi-spectral radiation intensity, and obtaining the wavelength by the following formula: and wavelength The first virtual multispectral radiation intensity and the second virtual multispectral radiation intensity at time:

[0018]

[0019] Among them, x1, x2…x p+1 is the polynomial coefficient of the virtual multispectral radiation intensity fitting, p is the fitting order, λ v is the wavelength.

[0020] Preferably, step S105 includes:

[0021] Step S401: Obtain a virtual multispectral radiation intensity deviation equation according to the virtual multispectral radiation intensity model:

[0022]

[0023] Among them, q0, q1, q2…q n are the emissivity polynomial coefficients, c1 and c2 are Planck's first and second constants, λ is the wavelength, T is the flame temperature, I virutal (λ, T) is the virtual multispectral radiation intensity;

[0024] Step S402, adding a small deviation to the derivative point of the virtual multi-spectral radiation intensity deviation equation to calculate the flame temperature partial derivative and the polynomial coefficient partial derivative of the derivative point;

[0025] Step S403, solving the flame temperature iterative correction value and the polynomial coefficient iterative correction value based on the least squares method according to the virtual multi-spectral radiation intensity deviation equation and the flame temperature partial derivative and the polynomial coefficient partial derivative at the derivation point;

[0026] In step S404, the initial value is iteratively corrected according to the following formula until the flame temperature and the emissivity no longer change, and the flame temperature and the emissivity are output:

[0027]

[0028] in, and are the iterative correction values of the emissivity polynomial coefficient and flame temperature, respectively.

[0029] An embodiment of the present invention further provides a device for measuring flame temperature based on virtual multispectral radiation intensity, characterized in that the device includes: a radiation measurement unit, a model building unit, an iteration unit, and an error analysis unit, wherein the radiation measurement unit is used to execute step S101, using a multispectral imaging device to measure m flame multispectral radiation intensity images; the model building unit is used to execute step S102, based on a polynomial emissivity model, to establish a virtual multispectral radiation intensity model, wherein the virtual multispectral radiation intensity model includes parameters of flame temperature and emissivity; the iteration unit is used to execute the following steps: step S103, setting the wavelength λ of the starting band of the virtual multispectral radiation intensity start , end band wavelength λ stop , fitting step length δλ and fitting order p; step S104, based on the starting band wavelength λ start , end band wavelength λ stop , fitting step length δλ and fitting order p, according to the m flame multispectral radiation intensity images, the iterative initial value of the flame temperature is obtained by the two-color method and the initial value of the emissivity Step S105: based on the iterative initial value of the flame temperature and the iterative initial value of the emissivity Based on the virtual multispectral radiation intensity model, the Newton iteration method is used to iterate until the flame temperature and the emissivity no longer change, and the flame temperature and the emissivity are output; the error analysis unit is used to perform the following steps: step S106, based on the virtual multispectral radiation intensity model, according to the m flame multispectral radiation intensity images, substitute the flame temperature and emissivity output in step S105 for error analysis; step S107, when the error is within the allowable range, determine that the flame temperature output in step S105 is the final flame temperature; when the error is not within the allowable range, increase the fitting order p and repeat steps S104-S106 for iteration until the error is within the allowable range.

[0030] Preferably, the virtual multispectral radiation intensity model is:

[0031]

[0032] in, is the virtual multispectral radiation intensity, c1 and c2 are Planck's first and second constants respectively, λ is the wavelength, T is the flame temperature, and ε(λ) is the emissivity.

[0033] Preferably, the iteration unit is configured to perform the following steps:

[0034] Step S201, based on the fitting order p, obtain the wavelength according to the m flame multispectral radiation intensity images and wavelength The first virtual multi-spectral radiation intensity and the second virtual multi-spectral radiation intensity at ;

[0035] Step S202: Obtain the initial value of the flame temperature iteration according to the following formula: and the initial value of the emissivity

[0036]

[0037] in, is the first virtual multispectral radiation intensity, is the second virtual multispectral radiation intensity, δλ is the fitting step size, c1 and c2 are the first and second Planck constants respectively.

[0038] Preferably, the iteration unit is configured to perform the following steps:

[0039] Step S301: construct a Vandermonde matrix and generate a linear equation system based on the m flame multispectral radiation intensity images:

[0040] Step S302: Perform QR decomposition on the Vandermonde matrix and solve the orthogonal matrix Q of Q T , the inverse matrix R -1 , solve the virtual multispectral radiation intensity fitting polynomial coefficient x by the following formula:

[0041] x=R -1 Q T I r ;

[0042] Step S303: fitting the polynomial coefficient x according to the virtual multi-spectral radiation intensity, and obtaining the wavelength by the following formula: and wavelength The first virtual multispectral radiation intensity and the second virtual multispectral radiation intensity at time:

[0043]

[0044] Among them, x1, x2…x p+1 is the polynomial coefficient of the virtual multispectral radiation intensity fitting, p is the fitting order, λ v is the wavelength.

[0045] Preferably, the iteration unit is configured to perform the following steps:

[0046] Step S401: Obtain a virtual multispectral radiation intensity deviation equation according to the virtual multispectral radiation intensity model:

[0047]

[0048] Among them, q0, q1, q2…q n are the emissivity polynomial coefficients, c1 and c2 are Planck's first and second constants, λ is the wavelength, T is the flame temperature, I virutal (λ, T) is the virtual multispectral radiation intensity;

[0049] Step S402, adding a small deviation to the derivative point of the virtual multi-spectral radiation intensity deviation equation to calculate the flame temperature partial derivative and the polynomial coefficient partial derivative of the derivative point;

[0050] Step S403, solving the flame temperature iterative correction value and the polynomial coefficient iterative correction value based on the least squares method according to the virtual multi-spectral radiation intensity deviation equation and the flame temperature partial derivative and the polynomial coefficient partial derivative at the derivation point;

[0051] In step S404, the initial value is iteratively corrected according to the following formula until the flame temperature and the emissivity no longer change, and the flame temperature and the emissivity are output:

[0052]

[0053] in, and are the iterative correction values of the emissivity polynomial coefficient and flame temperature, respectively.

[0054] Through the above technical solution, the embodiment of the present invention provides a method and device for measuring flame temperature based on virtual multispectral radiation intensity, using a multispectral imaging device to measure the multispectral radiation intensity image of the flame, using two-dimensional multispectral radiation intensity data as input data and calculating the virtual multispectral radiation intensity based on the virtual multispectral radiation intensity fitting technology, and solving the flame temperature according to the Newton iteration method, overcoming the uncertainty of temperature solution caused by the low spectral resolution performance of the multispectral imaging device, and achieving reliable results with high accuracy.

[0055] Other features and advantages of the embodiments of the present invention will be described in detail in the subsequent detailed description. BRIEF DESCRIPTION OF THE DRAWINGS

[0056] The accompanying drawings are used to provide a further understanding of the embodiments of the present invention and constitute a part of the specification. Together with the following detailed description, they are used to explain the embodiments of the present invention, but do not constitute a limitation of the embodiments of the present invention. In the accompanying drawings:

[0057] Figure 1 is a flow chart of a method for measuring flame temperature based on virtual multi-spectral radiation intensity provided by one embodiment of the present invention;

[0058] Figure 2 25 measured flame multispectral radiation intensity images provided by an embodiment of the present invention;

[0059] Figure 3 Schematic diagram of the change of the sum of squares of the residuals of the fitted radiation intensity and "detected radiation intensity - fitted radiation intensity" with the fitting order p provided by one embodiment of the present invention;

[0060] Figure 4 1 is a schematic diagram of a reconstructed two-dimensional spatial distribution of flame temperature provided by an embodiment of the present invention;

[0061] Figure 5 This is a structural block diagram of a device for measuring flame temperature based on virtual multi-spectral radiation intensity provided by one embodiment of the present invention.

[0062] Description of Reference Numerals

[0063] 1Radiation measurement unit 2Model building unit

[0064] 3 Iteration unit 4 Error analysis unit DETAILED DESCRIPTION

[0065] The following describes the specific implementation of the embodiment of the present invention in detail with reference to the accompanying drawings. It should be understood that the specific implementation described herein is only used to illustrate and explain the embodiment of the present invention and is not used to limit the embodiment of the present invention.

[0066] Figure 1 FIG. 1 is a flow chart of a method for measuring flame temperature based on virtual multi-spectral radiation intensity provided by an embodiment of the present invention. Figure 1 As shown, the method includes:

[0067] Step S101, using a multispectral imaging device to measure m flame multispectral radiation intensity images;

[0068] The embodiment of the present invention uses a multispectral imaging device to measure the flame multispectral radiation intensity image, and outputs 25 spectral radiation intensity images with a spatial resolution of 409 (H) × 217 (V) within the measurement band of the multispectral imaging device, such as Figure 2 As shown, the multi-spectral radiation intensity detected at each position can be obtained.

[0069] Step S102: establishing a virtual multi-spectral radiation intensity model based on the polynomial emissivity model, wherein the virtual multi-spectral radiation intensity model includes parameters of flame temperature and emissivity;

[0070] Wherein, the virtual multispectral radiation intensity model is:

[0071]

[0072] in, is the virtual multispectral radiation intensity, c1 and c2 are Planck's first and second constants respectively, λ is the wavelength, T is the flame temperature, and ε(λ) is the emissivity.

[0073] Step S103: Setting the virtual multi-spectral radiation intensity starting band wavelength λ start , end band wavelength λ stop , fitting step size δλ and fitting order p;

[0074] The embodiment of the present invention can set the starting wavelength of the virtual multi-spectral radiation intensity to start =650nm, end band wavelength λ stop =950nm, fitting step δλ=1nm and fitting order p=2.

[0075] Step S104: based on the starting wavelength λ start , end band wavelength λ stop , fitting step δλ and fitting order p are used to obtain the iterative initial value of the flame temperature by the two-color method based on the m flame multispectral radiation intensity images. and the initial value of the emissivity

[0076] Wherein, step S104 specifically includes:

[0077] According to the m flame multispectral radiation intensity images, a Vandermonde matrix is constructed and a linear equation system is generated (the embodiment of the present invention uses 25 flame multispectral radiation intensity images):

[0078]

[0079] Among them, x1, x2…x p+1 is the polynomial coefficient of the virtual multispectral radiation intensity fitting, p is the fitting order, I r is the multispectral radiation intensity corresponding to the flame multispectral radiation intensity image, λ r is the wavelength corresponding to the flame multispectral radiation intensity image.

[0080] Perform QR decomposition on the Vandermonde matrix and solve for the orthogonal matrix Q of Q T , the inverse matrix R -1 , solve the virtual multispectral radiation intensity fitting polynomial coefficient x by the following formula:

[0081] x=R -1 Q T I r (3)

[0082] According to the virtual multi-spectral radiation intensity fitting polynomial coefficient x, the wavelength is obtained by the following formula and wavelength The first virtual multispectral radiation intensity and the second virtual multispectral radiation intensity at time:

[0083]

[0084] Among them, x1, x2…x p+1 is the polynomial coefficient of the virtual multispectral radiation intensity fitting, p is the fitting order, λ v is the wavelength.

[0085] The iterative initial value of the flame temperature is obtained according to the following formula and the initial value of the emissivity

[0086] in, is the first virtual multispectral radiation intensity, is the second virtual multispectral radiation intensity, δλ is the fitting step size, c1 and c2 are the first and second Planck constants respectively.

[0087] Step S105: based on the iterative initial value of the flame temperature and the iterative initial value of the emissivity Iterating based on the virtual multi-spectral radiation intensity model using a Newton iteration method until the flame temperature and the emissivity no longer change, and outputting the flame temperature and the emissivity;

[0088] Wherein, step S105 specifically includes:

[0089] According to the virtual multi-spectral radiation intensity model, the virtual multi-spectral radiation intensity deviation equation is obtained:

[0090]

[0091] Among them, q0, q1, q2…q n are the emissivity polynomial coefficients, c1 and c2 are Planck's first and second constants, λ is the wavelength, T is the flame temperature, I virutal (λ, T) is the virtual multispectral radiation intensity;

[0092] A small deviation is added to the derivative point of the virtual multi-spectral radiation intensity deviation equation, and the flame temperature partial derivative and polynomial coefficient partial derivative of the derivative point are calculated by the following formula:

[0093]

[0094] Among them, δT and δqi are the small deviations of the flame temperature and emissivity polynomial coefficients, respectively.

[0095] According to the virtual multi-spectral radiation intensity deviation equation and the partial derivatives of the flame temperature and the polynomial coefficients at the derivation point, the flame temperature iterative correction value and the polynomial coefficient iterative correction value are solved by the following formula based on the least squares method:

[0096]

[0097] in, and are the iterative correction values of the emissivity polynomial coefficients and flame temperature, respectively, which can be solved by the least squares method.

[0098] The initial value is iteratively modified according to the following formula until the flame temperature and the emissivity no longer change, and the flame temperature and the emissivity are output:

[0099]

[0100] in, and are the iterative correction values of the emissivity polynomial coefficient and flame temperature, respectively.

[0101] Step S106, based on the virtual multispectral radiation intensity model, according to the m flame multispectral radiation intensity images, substitute the flame temperature and emissivity output in step S105 to perform error analysis;

[0102] In this embodiment of the present invention, the error analysis can be performed using the following formula:

[0103]

[0104] Step S107, determining whether the error is within the allowable range;

[0105] Step S108, when the error is within the allowable range, determining the flame temperature outputted in step S105 as the final flame temperature;

[0106] When the error is not within the allowable range, the fitting order p is increased and steps S104 to S106 are repeated for iteration until the error is within the allowable range.

[0107] In this embodiment of the present invention, error analysis is performed using formula (10) in step S106. If the residual sum of squares is less than the allowable error, the current iteration value is the true flame temperature. If the error is greater than the allowable range, the virtual multispectral radiation intensity fitting order p is increased (for example, p+1), and the fitting is re-performed, and the temperature and emissivity polynomial coefficients are iterated.

[0108] The above embodiment of the present invention uses a multi-spectral imaging device to measure the multi-spectral radiation intensity of the scramjet combustion chamber flame. Figure 2 The two-dimensional multi-spectral radiation intensity is used as the correlation data for the calculation example. The flame is generated by igniting kerosene through multi-path sliding arcs in the scramjet combustion chamber. The total temperature of the incoming flow is 1600K, the total pressure is 1.65Mpa, and the kerosene flow rate is 23.2g / s. The flame multi-spectral radiation intensity at the coordinate (200, 40) (spectral resolution: 10nm) is selected for iterative fitting of the virtual multi-spectral radiation intensity (spectral resolution: 1nm). The residual sum of squares of the fitted radiation intensity and "detected radiation intensity-fitted radiation intensity" obtained based on the virtual multi-spectral radiation intensity fitting technology of the present invention changes with the fitting order p as shown below: Figure 3 shown. Figure 4 The two-dimensional spatial distribution of flame temperature reconstructed based on the method proposed in this invention is given.

[0109] Figure 5 FIG. 1 is a block diagram of a device for measuring flame temperature based on virtual multi-spectral radiation intensity provided by an embodiment of the present invention. Figure 5 As shown, it is characterized in that the device includes: a radiation measurement unit 1, a model building unit 2, an iteration unit 3 and an error analysis unit 4, wherein the radiation measurement unit 1 is used to perform step S101, using a multispectral imaging device to measure m flame multispectral radiation intensity images; the model building unit 2 is used to perform step S102, based on a polynomial emissivity model, to establish a virtual multispectral radiation intensity model, the virtual multispectral radiation intensity model including parameters of flame temperature and emissivity; the iteration unit 3 is used to perform the following steps: step S103, setting the wavelength λ of the starting band of the virtual multispectral radiation intensity start , end band wavelength λ stop , fitting step length δλ and fitting order p; step S104, based on the starting band wavelength λ start , end band wavelength λ stop , fitting step length δλ and fitting order p, according to the m flame multispectral radiation intensity images, the iterative initial value of the flame temperature is obtained by the two-color method and the initial value of the emissivity Step S105: based on the iterative initial value of the flame temperature and the initial value of the iteration of the emissivity Based on the virtual multispectral radiation intensity model, the Newton iteration method is used to iterate until the flame temperature and the emissivity no longer change, and the flame temperature and the emissivity are output; the error analysis unit 4 is used to perform the following steps: step S106, based on the virtual multispectral radiation intensity model, according to the m flame multispectral radiation intensity images, substitute the flame temperature and emissivity output in step S105 for error analysis; step S107, when the error is within the allowable range, determine that the flame temperature output in step S105 is the final flame temperature; when the error is not within the allowable range, increase the fitting order p and repeat steps S104-S106 for iteration until the error is within the allowable range.

[0110] Preferably, the virtual multispectral radiation intensity model is:

[0111]

[0112] in, is the virtual multispectral radiation intensity, c1 and c2 are Planck's first and second constants respectively, λ is the wavelength, T is the flame temperature, and ε(λ) is the emissivity.

[0113] Preferably, the iterative unit 3 is configured to perform the following steps:

[0114] Step S201, based on the fitting order p, obtain the wavelength according to the m flame multispectral radiation intensity images and wavelength The first virtual multi-spectral radiation intensity and the second virtual multi-spectral radiation intensity at ;

[0115] Step S202: Obtain the initial value of the flame temperature iteration according to the following formula: and the initial value of the emissivity

[0116]

[0117] in, is the first virtual multispectral radiation intensity, is the second virtual multispectral radiation intensity, δλ is the fitting step size, c1 and c2 are the first and second Planck constants respectively.

[0118] Preferably, the iterative unit 3 is configured to perform the following steps:

[0119] Step S301: construct a Vandermonde matrix and generate a linear equation system based on the m flame multispectral radiation intensity images:

[0120] Step S302: Perform QR decomposition on the Vandermonde matrix and solve the orthogonal matrix Q of Q T , the inverse matrix R -1 , solve the virtual multispectral radiation intensity fitting polynomial coefficient x by the following formula:

[0121] x=R -1 Q T I r ;

[0122] Step S303: fitting the polynomial coefficient x according to the virtual multi-spectral radiation intensity, and obtaining the wavelength by the following formula: and wavelength The first virtual multispectral radiation intensity and the second virtual multispectral radiation intensity at time:

[0123]

[0124] Among them, x1, x2…x p+1 is the polynomial coefficient of the virtual multispectral radiation intensity fitting, p is the fitting order, λ v is the wavelength.

[0125] Preferably, the iterative unit 3 is configured to perform the following steps:

[0126] Step S401: Obtain a virtual multispectral radiation intensity deviation equation according to the virtual multispectral radiation intensity model:

[0127]

[0128] Among them, q0, q1, q2…q n are the emissivity polynomial coefficients, c1 and c2 are Planck's first and second constants, λ is the wavelength, T is the flame temperature, I virutal (λ, T) is the virtual multispectral radiation intensity;

[0129] Step S402, adding a small deviation to the derivative point of the virtual multi-spectral radiation intensity deviation equation to calculate the flame temperature partial derivative and the polynomial coefficient partial derivative of the derivative point;

[0130] Step S403, solving the flame temperature iterative correction value and the polynomial coefficient iterative correction value based on the least squares method according to the virtual multi-spectral radiation intensity deviation equation and the flame temperature partial derivative and the polynomial coefficient partial derivative at the derivation point;

[0131] In step S404, the initial value is iteratively corrected according to the following formula until the flame temperature and the emissivity no longer change, and the flame temperature and the emissivity are output:

[0132]

[0133] in, and are the iterative correction values of the emissivity polynomial coefficient and flame temperature, respectively.

[0134] The above-mentioned apparatus for measuring flame temperature based on virtual multi-spectral radiation intensity and the above-mentioned method for measuring flame temperature based on virtual multi-spectral radiation intensity are similar to the embodiments and are not described in detail here.

[0135] Those skilled in the art will appreciate that the embodiments of the present application can be provided as methods, systems, or computer program products. Therefore, the present application can adopt the form of a complete hardware embodiment, a complete software embodiment, or an embodiment in combination with software and hardware. Moreover, the present application can adopt the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to magnetic disk storage, CD-ROM, optical storage, etc.) that contain computer-usable program code.

[0136] The present application is described with reference to the flowcharts and / or block diagrams of the methods, devices (systems), and computer program products according to the embodiments of the present application. It should be understood that each process and / or box in the flowchart and / or block diagram, as well as the combination of the processes and / or boxes in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the steps in the process. Figure 1 a process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0137] These computer program instructions may also be stored in a computer readable memory that can direct a computer or other programmable data processing device to work in a specific manner, so that the instructions stored in the computer readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 a process or multiple processes and / or boxes Figure 1 The function specified in one or more boxes.

[0138] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operational steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing the instructions executed on the computer or other programmable device for implementing the process. Figure 1 a process or multiple processes and / or boxes Figure 1 A step that specifies a function in one or more boxes.

[0139] In a typical configuration, a computing device includes one or more processors (CPUs), input / output interfaces, network interfaces, and memory.

[0140] The memory may include non-permanent memory in a computer-readable medium, random access memory (RAM) and / or non-volatile memory in the form of read-only memory (ROM) or flash RAM. The memory is an example of a computer-readable medium.

[0141] Computer-readable media includes permanent and non-permanent, removable and non-removable media that can be implemented by any method or technology to store information. The information can be computer-readable instructions, data structures, program modules or other data. Examples of computer storage media include, but are not limited to, phase change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technology, compact disc read-only memory (CD-ROM), digital versatile disc (DVD) or other optical storage, magnetic cassettes, magnetic tape, magnetic disk storage or other magnetic storage devices or any other non-transmission media that can be used to store information that can be accessed by a computing device. As defined herein, computer-readable media does not include transitory computer-readable media (transitory media), such as modulated data signals and carrier waves.

[0142] It should also be noted that the terms "comprises," "includes," or any other variations thereof are intended to encompass non-exclusive inclusion, such that a process, method, commodity, or apparatus that includes a list of elements includes not only those elements but also other elements not explicitly listed, or elements inherent to such process, method, commodity, or apparatus. In the absence of further limitations, an element defined by the phrase "comprising a..." does not preclude the presence of additional identical elements in the process, method, commodity, or apparatus that includes the element.

[0143] The above are merely embodiments of the present application and are not intended to limit the present application. For those skilled in the art, the present application may have various changes and variations. Any modifications, equivalent replacements, improvements, etc. made within the spirit and principles of the present application should all be included within the scope of the claims of the present application.

Claims

1. A method for measuring flame temperature based on virtual multispectral radiation intensity, characterized in that: The method comprises: Step S101, using a multispectral imaging device to measure m flame multispectral radiation intensity images; Step S102: establishing a virtual multi-spectral radiation intensity model based on the polynomial emissivity model, wherein the virtual multi-spectral radiation intensity model includes parameters of flame temperature and emissivity; Step S103: Setting the virtual multi-spectral radiation intensity starting band wavelength λ start , end band wavelength λ stop , fitting step size δλ and fitting order p; Step S104: based on the starting wavelength λ start , end band wavelength λ stop , fitting step length δλ and fitting order p, according to the m flame multispectral radiation intensity images, the iterative initial value of the flame temperature is obtained by the two-color method and the initial value of the emissivity The process includes the following steps S301-S303: Step S301: construct a Vandermonde matrix and generate a linear equation system based on the m flame multispectral radiation intensity images: Among them, x1, x2…x p+1 is the polynomial coefficient of the virtual multispectral radiation intensity fitting, p is the fitting order, I r is the multispectral radiation intensity corresponding to the flame multispectral radiation intensity image, λ r is the wavelength corresponding to the flame multispectral radiation intensity image, Step S302: Perform QR decomposition on the Vandermonde matrix and solve the orthogonal matrix Q of Q T , the inverse matrix R -1 , solve the virtual multispectral radiation intensity fitting polynomial coefficient x by the following formula: x=R -1 Q T I r ; Step S303: fitting the polynomial coefficient x according to the virtual multi-spectral radiation intensity, and obtaining the wavelength by the following formula: and wavelength The first virtual multispectral radiation intensity and the second virtual multispectral radiation intensity at time: Among them, x1, x2…x p+1 is the polynomial coefficient of the virtual multispectral radiation intensity fitting, p is the fitting order, λ v is the wavelength; Step S105: based on the iterative initial value of the flame temperature and the iterative initial value of the emissivity Based on the virtual multispectral radiation intensity model, the Newton iteration method is used to iterate until the flame temperature and the emissivity no longer change, and the flame temperature and the emissivity are output; in step S106, based on the virtual multispectral radiation intensity model, according to the m flame multispectral radiation intensity images, the flame temperature and emissivity output in step S105 are substituted for error analysis; in step S107, when the error is within the allowable range, the flame temperature output in step S105 is determined to be the final flame temperature; when the error is not within the allowable range, the fitting order p is increased and steps S104-S106 are repeated for iteration until the error is within the allowable range.

2. The method for measuring flame temperature based on virtual multi-spectral radiation intensity according to claim 1, characterized in that: The virtual multispectral radiation intensity model is: in, is the virtual multispectral radiation intensity, c1 and c2 are Planck's first and second constants respectively, λ is the wavelength, T is the flame temperature, and ε(λ) is the emissivity.

3. The method for measuring flame temperature based on virtual multi-spectral radiation intensity according to claim 1, characterized in that: Step S104 further includes: The iterative initial value of the flame temperature is obtained according to the following formula and the initial value of the emissivity in, is the first virtual multispectral radiation intensity, is the second virtual multispectral radiation intensity, δλ is the fitting step size, c1 and c2 are the first and second Planck constants respectively.

4. The method for measuring flame temperature based on virtual multi-spectral radiation intensity according to claim 1, characterized in that: Step S105 includes: Step S401: Obtain a virtual multispectral radiation intensity deviation equation according to the virtual multispectral radiation intensity model: Among them, q0, q1, q2…q n are the emissivity polynomial coefficients, c1 and c2 are Planck's first and second constants, λ is the wavelength, T is the flame temperature, I virutal (λ, T) is the virtual multispectral radiation intensity; Step S402, adding a small deviation to the derivative point of the virtual multi-spectral radiation intensity deviation equation to calculate the flame temperature partial derivative and the polynomial coefficient partial derivative of the derivative point; Step S403, solving the flame temperature iterative correction value and the polynomial coefficient iterative correction value based on the least squares method according to the virtual multi-spectral radiation intensity deviation equation and the flame temperature partial derivative and the polynomial coefficient partial derivative at the derivation point; In step S404, the initial value is iteratively corrected according to the following formula until the flame temperature and the emissivity no longer change, and the flame temperature and the emissivity are output: in, and are the iterative correction values of the emissivity polynomial coefficient and flame temperature, respectively.

5. A device for measuring flame temperature based on virtual multi-spectral radiation intensity, characterized in that: The device comprises: Radiation measurement unit, model building unit, iteration unit and error analysis unit, wherein, The radiation measurement unit is used to perform step S101, using a multispectral imaging device to measure m flame multispectral radiation intensity images; The model building unit is used to execute step S102 to build a virtual multi-spectral radiation intensity model based on the polynomial emissivity model, wherein the virtual multi-spectral radiation intensity model includes parameters of flame temperature and emissivity; The iteration unit is used to perform the following steps: Step S103: Setting the virtual multi-spectral radiation intensity starting band wavelength λ start , end band wavelength λ stop , fitting step size δλ and fitting order p; Step S104: based on the starting wavelength λ start , end band wavelength λ stop , fitting step length δλ and fitting order p, according to the m flame multispectral radiation intensity images, the iterative initial value of the flame temperature is obtained by the two-color method and the initial value of the emissivity The process includes the following steps S301-S303: Step S301: construct a Vandermonde matrix and generate a linear equation system based on the m flame multispectral radiation intensity images: Among them, x1, x2…x p+1 is the polynomial coefficient of the virtual multispectral radiation intensity fitting, p is the fitting order, I r is the multispectral radiation intensity corresponding to the flame multispectral radiation intensity image, λ r is the wavelength corresponding to the flame multispectral radiation intensity image, Step S302: Perform QR decomposition on the Vandermonde matrix and solve the orthogonal matrix Q of Q T , the inverse matrix R -1 , solve the virtual multispectral radiation intensity fitting polynomial coefficient x by the following formula: x=R -1 Q T I r ; Step S303: fitting the polynomial coefficient x according to the virtual multi-spectral radiation intensity, and obtaining the wavelength by the following formula: and wavelength The first virtual multispectral radiation intensity and the second virtual multispectral radiation intensity at time: Among them, x1, x2…x p+1 is the polynomial coefficient of the virtual multispectral radiation intensity fitting, p is the fitting order, λ v is the wavelength; Step S105: based on the iterative initial value of the flame temperature and the initial value of the iteration of the emissivity Iterating based on the virtual multi-spectral radiation intensity model using a Newton iteration method until the flame temperature and the emissivity no longer change, and outputting the flame temperature and the emissivity; The error analysis unit is configured to perform the following steps: Step S106, based on the virtual multispectral radiation intensity model, according to the m flame multispectral radiation intensity images, substitute the flame temperature and emissivity output in step S105 to perform error analysis; Step S107, when the error is within the allowable range, determine the flame temperature output in step S105 as the final flame temperature; when the error is not within the allowable range, increase the fitting order p and repeat steps S104-S106 for iteration until the error is within the allowable range.

6. The device for measuring flame temperature based on virtual multi-spectral radiation intensity according to claim 5, characterized in that: The virtual multispectral radiation intensity model is: in, is the virtual multispectral radiation intensity, c1 and c2 are Planck's first and second constants respectively, λ is the wavelength, T is the flame temperature, and ε(λ) is the emissivity.

7. The device for measuring flame temperature based on virtual multi-spectral radiation intensity according to claim 5, characterized in that: The iteration unit is further configured to perform the following steps: The iterative initial value of the flame temperature is obtained according to the following formula and the initial value of the emissivity in, is the first virtual multispectral radiation intensity, is the second virtual multispectral radiation intensity, δλ is the fitting step size, c1 and c2 are the first and second Planck constants respectively.

8. The device for measuring flame temperature based on virtual multi-spectral radiation intensity according to claim 5, characterized in that: The iteration unit is used to perform the following steps: Step S401: Obtain a virtual multispectral radiation intensity deviation equation according to the virtual multispectral radiation intensity model: Among them, q0, q1, q2…q n are the emissivity polynomial coefficients, c1 and c2 are Planck's first and second constants, λ is the wavelength, T is the flame temperature, I virutal (λ, T) is the virtual multispectral radiation intensity; Step S402, adding a small deviation to the derivative point of the virtual multi-spectral radiation intensity deviation equation to calculate the flame temperature partial derivative and the polynomial coefficient partial derivative of the derivative point; Step S403, solving the flame temperature iterative correction value and the polynomial coefficient iterative correction value based on the least squares method according to the virtual multi-spectral radiation intensity deviation equation and the flame temperature partial derivative and the polynomial coefficient partial derivative at the derivation point; In step S404, the initial value is iteratively corrected according to the following formula until the flame temperature and the emissivity no longer change, and the flame temperature and the emissivity are output: in, and are the iterative correction values of the emissivity polynomial coefficient and flame temperature, respectively.

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