A phosphorescence temperature measurement working wavelength selection method, device, medium and product

Abstract

The present application discloses a method, device, medium and product for selecting a working wavelength for phosphorescence temperature measurement, which relates to the field of phosphorescence temperature measurement technology. The method includes: reading all wavelengths in spectral data to obtain wavelength data; traversing all bandwidths of each wavelength in the wavelength data to obtain bandwidth data corresponding to each wavelength; obtaining a number of band combinations based on the wavelength data and bandwidth data; using each band combination to establish a light intensity ratio and temperature mapping model; deleting the light intensity ratio and temperature mapping model corresponding to the system error greater than a preset threshold, and then deleting the light intensity ratio and temperature mapping model corresponding to the minimum random error with a random error greater than a preset multiple, and finally determining the result of the selection of the working wavelength for phosphorescence temperature measurement based on this. The present application provides a method for automatic calculation and selection, which does not require manual calculation and can be automatically calculated and selected based on spectral data. At the same time, it solves the problems of large uncertainty in calibration results and low temperature measurement accuracy in the calibration process of the mapping relationship model.

Description

Technical Field

[0001] The present application relates to the technical field of phosphorescence temperature measurement, and in particular to a method, device, medium and product for selecting a working wavelength for phosphorescence temperature measurement. Background Art

[0002] As the heart of an aircraft, the Brayton cycle operates within an aircraft engine, whose efficiency and thrust-to-weight ratio are determined by the temperature in front of the turbine. To achieve even higher efficiency and thrust-to-weight ratios, increasing the temperature in front of the turbine has become a development trend in advanced aircraft engines. This has led to new challenges in protecting the hot-end components of aircraft engines. Accurate measurement of hot-end component temperatures directly determines the accuracy of the engine's thermal analysis system and cooling design, and is therefore crucial to the safety and lifespan of the entire aircraft engine.

[0003] The harsh operating environment of aircraft engine hot-end components poses significant challenges to traditional temperature measurement technologies, such as thermocouples and infrared temperature measurement. These technologies are already facing development bottlenecks. Thermocouples disrupt the surface temperature field and are difficult to install on rotating components. Infrared temperature measurement is significantly affected by surface emissivity and complex gas atmospheres. Phosphorescence temperature measurement overcomes these challenges, offering advantages such as non-contact operation, a wide temperature measurement range, high accuracy, and independence from emissivity and gas composition.

[0004] Phosphorescence temperature measurement involves doping rare earth ions into thermal barrier coatings. When excited by excitation light, the rare earth ions emit phosphorescence. The ratio of the intensity of characteristic phosphorescence peaks is related to temperature. By measuring the intensity ratio of these peaks and combining it with a pre-calibrated relationship between intensity ratio and temperature, the surface temperature can be determined. Currently, the selection of characteristic peaks is done manually by selecting appropriate peaks from the spectrum to establish a mapping relationship between intensity ratio and temperature. This computation is time-consuming, the results vary from person to person, and there is significant uncertainty, making it impossible to establish an ideal mapping model for temperature measurement performance. Summary of the Invention

[0005] The purpose of this application is to provide a method, equipment, medium and product for selecting the working wavelength of phosphorescence temperature measurement, which can automatically calculate and select based on spectral data, and at the same time solve the problems of large uncertainty of calibration results and low temperature measurement accuracy in the calibration process of the mapping relationship model.

[0006] To achieve the above objectives, this application provides the following solutions:

[0007] In a first aspect, the present application provides a method for selecting a phosphorescence temperature measurement working wavelength, comprising:

[0008] Acquiring a plurality of spectral data of phosphorescent materials;

[0009] Read all wavelengths in the spectral data to obtain wavelength data;

[0010] Traversing all bandwidths of each wavelength in the wavelength data to obtain bandwidth data corresponding to each wavelength;

[0011] Acquire a plurality of band combinations according to the wavelength data and the bandwidth data; each of the band combinations includes two working bands; each of the working bands includes one of the wavelengths and a corresponding bandwidth;

[0012] Using each of the waveband combinations to establish a light intensity ratio and temperature mapping model;

[0013] Calculating the systematic error of each of the light intensity ratio and temperature mapping models when performing phosphorescence temperature measurement;

[0014] Deleting the light intensity ratio and temperature mapping models corresponding to the system error being greater than a preset threshold, to obtain a plurality of first light intensity ratio and temperature mapping models;

[0015] Calculating the random error of each of the first light intensity ratio and temperature mapping models, and obtaining the minimum random error;

[0016] The first light intensity ratio and temperature mapping model corresponding to the minimum random error whose random error is greater than a preset multiple is deleted to obtain a second light intensity ratio and temperature mapping model;

[0017] The phosphorescence temperature measurement working wavelength selection result is determined according to the second light intensity ratio and the wavelength combination corresponding to the temperature mapping model.

[0018] Optionally, the light intensity ratio and temperature mapping model is:

[0019]

[0020] Where I1 and I2 are the phosphorescence intensities of the two working bands, FIR is the light intensity ratio corresponding to the working band combination, B is the coefficient determined by fitting, ΔE is the energy level difference, and k B is the Boltzmann constant, T is the temperature, and C is the coefficient determined by fitting.

[0021] Optionally, the reading of all wavelengths in the spectral data to obtain wavelength data; and traversing all bandwidths of each wavelength to obtain bandwidth data corresponding to each wavelength specifically include:

[0022] Read all wavelengths in the spectral data at intervals of 0.85 nm to obtain wavelength data;

[0023] Taking 5 times the minimum step size of the spectrometer as the traversal step size, and the traversal range from the minimum step size of the spectrometer to 200 times the minimum step size of the spectrometer, all bandwidths of each wavelength are traversed to obtain the bandwidth data corresponding to each wavelength.

[0024] Optionally, determining the phosphorescence temperature measurement working wavelength selection result according to the wavelength combination corresponding to the second light intensity ratio and the temperature mapping model specifically includes:

[0025] Acquire a band combination corresponding to the second light intensity ratio and temperature mapping model to obtain second band combination data;

[0026] Read all wavelengths in the second wavelength band combination data at intervals of 0.17 nm to obtain second wavelength data;

[0027] Using the minimum step size of the spectrometer as the traversal step size, and the traversal range from the minimum step size of the spectrometer to 200 times the minimum step size of the spectrometer, traversing all bandwidths of each wavelength in the second wavelength data to obtain second bandwidth data corresponding to each wavelength;

[0028] Acquire a plurality of second wavelength band combinations according to the second wavelength data and the second bandwidth data; each second wavelength band combination includes two second operating wavelength bands; each second operating wavelength band includes a second wavelength and a corresponding second bandwidth;

[0029] establishing a second light intensity ratio and temperature mapping model using each of the second waveband combinations;

[0030] Calculating the systematic error of each of the second light intensity ratio and temperature mapping models when performing phosphorescence temperature measurement;

[0031] Deleting the second light intensity ratio and temperature mapping models corresponding to the system error being greater than a preset threshold, to obtain a plurality of third light intensity ratio and temperature mapping models;

[0032] Calculating a random error of each of the third light intensity ratio and temperature mapping models;

[0033] The second wavelength combination corresponding to the third light intensity ratio and the temperature mapping model with the smallest random error is used as the optimal working wavelength combination.

[0034] Optionally,

[0035] The light intensity ratio and temperature mapping models corresponding to the system error being greater than a preset threshold are deleted to obtain a plurality of first light intensity ratio and temperature mapping models, specifically including:

[0036] The light intensity ratio and temperature mapping models corresponding to the system error greater than 0.5% are deleted to obtain several first light intensity ratio and temperature mapping models;

[0037] The step of deleting the first light intensity ratio and temperature mapping model corresponding to the minimum random error having a random error greater than a preset multiple to obtain a second light intensity ratio and temperature mapping model specifically includes:

[0038] The first light intensity ratio and temperature mapping model corresponding to the minimum random error whose random error is greater than 1.1 times is deleted to obtain a second light intensity ratio and temperature mapping model.

[0039] Optionally, calculating the systematic error of each of the light intensity ratio and temperature mapping models when performing phosphorescence temperature measurement specifically includes:

[0040] For each of the light intensity ratio and temperature mapping models:

[0041] Predicting temperature using the light intensity ratio and temperature mapping model to obtain a predicted value;

[0042] Calculating the difference between the predicted value and the true value;

[0043] The difference is divided by the true value to obtain the systematic error.

[0044] Optionally, calculating the random error of each of the first light intensity ratio and temperature mapping models specifically includes:

[0045] For each of the first light intensity ratio and temperature mapping models;

[0046] Obtaining a band combination corresponding to the first light intensity ratio and temperature mapping model;

[0047] Calculating the standard deviation of the light intensity ratio measured by performing n experiments according to the waveband combination;

[0048] The random error of the first light intensity ratio and temperature mapping model is obtained by dividing the standard deviation by square root n and then by the average light intensity ratio; the average light intensity ratio is the average light intensity ratio measured by n experiments based on the band combination.

[0049] In a second aspect, the present application provides a computer device comprising: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement any one of the above-described phosphorescence temperature measurement working wavelength selection methods.

[0050] In a third aspect, the present application provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements any of the above-described phosphorescence temperature measurement working wavelength selection methods.

[0051] In a fourth aspect, the present application provides a computer program product, comprising a computer program, which, when executed by a processor, implements any one of the above-described phosphorescence temperature measurement working wavelength selection methods.

[0052] According to the specific embodiments provided in this application, this application discloses the following technical effects:

[0053] The present application provides a method, device, medium and product for selecting a working wavelength for phosphorescence temperature measurement, which reads all wavelengths in spectral data to obtain wavelength data; traverses all bandwidths of each wavelength in the wavelength data to obtain bandwidth data corresponding to each wavelength; obtains several band combinations based on the wavelength data and the bandwidth data; each band combination includes two working bands; each working band includes one wavelength and a corresponding bandwidth; uses each band combination to establish a light intensity ratio and temperature mapping model; calculates the systematic error of each light intensity ratio and temperature mapping model when performing phosphorescence temperature measurement; deletes the light intensity ratio and temperature mapping model corresponding to a system error greater than a preset threshold to obtain several first light intensity ratio and temperature mapping models; calculates the random error of each first light intensity ratio and temperature mapping model and obtains the minimum random error; deletes the first light intensity ratio and temperature mapping model corresponding to the minimum random error whose random error is greater than a preset multiple to obtain a second light intensity ratio and temperature mapping model; and determines the phosphorescence temperature measurement working wavelength selection result based on the band combination corresponding to the second light intensity ratio and temperature mapping model. This application provides an automatic calculation and selection method that eliminates the need for manual calculations. This solves the current problem of manually selecting characteristic peaks from the spectrum to establish a mapping relationship between light intensity ratio and temperature. This calculation is time-consuming, the results vary from person to person, there is significant uncertainty, and it is impossible to establish a mapping relationship model with optimal temperature measurement performance. This application can automatically calculate and select based on spectral data, while also solving problems such as large uncertainty in calibration results and low temperature measurement accuracy that exist in the calibration process of the mapping relationship model. BRIEF DESCRIPTION OF THE DRAWINGS

[0054] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0055] Figure 1 This is a diagram of the application environment of a method for selecting a working wavelength for phosphorescence temperature measurement in one embodiment of the present application;

[0056] Figure 2 A schematic flow chart of a method for selecting a working wavelength for phosphorescence temperature measurement provided in one embodiment of the present application;

[0057] Figure 3 A schematic diagram of a pure phosphorescence spectrum provided in one embodiment of the present application;

[0058] Figure 4 A schematic diagram of error distribution provided in an embodiment of the present application;

[0059] Figure 5 A schematic diagram of the structure of a computer device provided in one embodiment of the present application. DETAILED DESCRIPTION

[0060] The following will be combined with the drawings in the embodiments of this application to clearly and completely describe the technical solutions in the embodiments of this application. Obviously, the embodiments described are only part of the embodiments of this application, not all of the embodiments. Based on the embodiments in this application, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of this application.

[0061] As the core power component of an aircraft, aircraft engines have a crucial impact on all aspects of aircraft performance. From early centrifugal turbojets to single-spool axial-flow turbojets, from twin-spool turbojets to low-bypass turbofans, and finally to high-bypass turbofans, modern aircraft engines have shown a development trend of increasing bypass ratios, rising pressure ratios, and rising turbine inlet temperatures (referred to as "two wide and one high").

[0062] The ever-increasing technical specifications of aircraft engines mean that the working environment of their core hot-end components (such as turbine blades, turbine disks, support bearings, etc.) will be more harsh than imagined. The coexistence of high temperature, high pressure and high-speed rotation, and the combined effects of multiple influencing factors make the hot-end components extremely susceptible to damage and failure. Therefore, the overall development of aircraft engines in the future will be more difficult, and more structural strength and working performance tests will be required to determine the performance and working reliability of their hot-end components. The main characteristics of these tests are: complex technology, multiple links, large workload, large investment, and long cycle time. They require reliable testing technology to provide useful information and data. The temperature of the hot-end components of aircraft engines is a key parameter of the hot-end components. Accurate acquisition of the temperature of the hot-end components of aircraft engines directly determines the accuracy of the engine thermal analysis system and cooling design, and is related to the safety and service life of the hot-end components.

[0063] The harsh operating environment of aircraft engine hot-end components poses significant challenges to traditional temperature measurement technologies, such as thermocouples and infrared temperature measurement. These technologies are already facing development bottlenecks. Thermocouples can disrupt the surface temperature field and are difficult to install on rotating components. Infrared temperature measurement is significantly affected by surface emissivity and the complex atmosphere of the gas.

[0064] Phosphorescence temperature measurement technology can overcome these challenges, offering advantages such as non-contact operation, a wide temperature measurement range, high temperature measurement accuracy, and independence from emissivity and gas composition. Phosphorescence temperature measurement involves doping rare earth ions into thermal barrier coatings. When excited by excitation light, the rare earth ions emit phosphorescence. The ratio of the intensity of the characteristic phosphorescence peaks is temperature-dependent. By measuring the intensity ratio of the characteristic phosphorescence peaks and combining it with a pre-calibrated relationship between intensity ratio and temperature, the temperature of the surface being measured can be determined. Currently, the selection of characteristic peaks in the phosphorescence spectrum is performed manually by selecting appropriate peaks from the spectrum to establish a mapping between intensity ratio and temperature. There is no method for screening combinations of characteristic peaks.

[0065] With the development of aircraft engines, technical indicators such as turbine inlet temperature continue to increase, posing significant challenges to the design of hot-end components. This requires reliable testing technology to support this design. However, the harsh operating environment of hot-end components poses significant challenges to traditional temperature measurement technologies, such as thermocouples and infrared temperature measurement. These technologies are already facing development bottlenecks. Phosphorescence temperature measurement technology can overcome these challenges, offering advantages such as non-contact operation, a wide temperature measurement range, high accuracy, and immunity to emissivity and gas composition. The principle of phosphorescence temperature measurement is that the ratio of the intensity of characteristic phosphorescence peaks is related to temperature. By measuring the intensity ratio of these peaks and combining it with a pre-calibrated relationship between intensity ratio and temperature, temperature information can be obtained. However, the selection of characteristic peaks in the phosphorescence spectrum is currently performed manually, with the appropriate peaks selected from the spectrum to establish a mapping between intensity ratio and temperature. This computational effort is time-consuming, the results vary widely, and there is significant uncertainty, making it difficult to establish an optimal mapping model for temperature measurement performance. This application establishes a characteristic peak combination evaluation method based on error analysis theory, develops an automatic selection algorithm for characteristic peaks of rare earth ion emission spectra, selects characteristic peak combinations with high temperature measurement accuracy, and solves the problems of large uncertainty in calibration results and low temperature measurement accuracy in the calibration process of the mapping relationship model.

[0066] The purpose of this application is to provide a method, equipment, medium and product for selecting the working wavelength of phosphorescence temperature measurement, which can automatically calculate and select based on spectral data, and at the same time solve the problems of large uncertainty of calibration results and low temperature measurement accuracy in the calibration process of the mapping relationship model.

[0067] In order to make the above-mentioned purposes, features and advantages of the present application more obvious and easy to understand, the present application is further described in detail below with reference to the accompanying drawings and specific implementation methods.

[0068] Explanation of terms used in this application:

[0069] 1. Phosphorescence: Phosphorescence is a cold-state luminescence form that is different from thermal luminescence. Its characteristic is that luminescence can be stimulated by means other than heating, such as ultraviolet excitation, electron beam impact, etc. When the excitation light stimulates the phosphorescent material, it causes the electron energy level to jump to a high energy level, which then drops back to a low energy level after a certain period of time, and releases energy in the process. Part of the energy causes lattice vibration and is eventually released in the form of heat; the other part of the energy is released in the form of luminescence, including fluorescence and phosphorescence. The duration of fluorescence is less than 10 -8 s, phosphorescence duration is 10 -5 s to 10 -3 s, which is manifested as a long afterglow after the end of the excitation.

[0070] 2. Phosphorescence Thermometry: This technology utilizes the mapping relationship between the spectral characteristics or lifetime characteristics of the photoluminescence of phosphorescent materials, such as rare earth ions, and temperature to perform temperature measurements. This technology includes both the intensity ratio method and the lifetime decay method. This patent only covers the intensity ratio method. In the field of aircraft engines, rare earth ions are typically doped into thermal barrier coatings, causing them to emit phosphorescence when excited by excitation light. This allows for temperature measurement of the thermal barrier coating and, in turn, characterizes the temperature of the hot-end component surface coated with the thermal barrier coating.

[0071] 3. Thermal coupling energy level: Thermal coupling energy level refers to the energy level spacing range of 200 to 2000 cm in a certain system. -1 Due to the influence of heat, all energy states tend to balance and reach a unified state. In this state, the ratio of the number of particles in the thermally coupled energy level follows the Boltzmann distribution and changes with temperature.

[0072] 4. Intensity Ratio Temperature Measurement Principle: The intensity ratio method is based on thermal coupling energy levels. The number of particles distributed at the thermal coupling energy levels is proportional to the luminescence intensity. Different thermal coupling energy levels emit phosphorescence with different wavelengths, which are reflected as different characteristic peaks in the phosphorescence emission spectrum. Temperature measurement is performed by mapping the intensity ratio of the characteristic peaks corresponding to the thermal coupling energy levels in the phosphorescence emission spectrum to the temperature. Recent studies have also shown that non-thermal coupling energy levels can also be used for intensity ratio temperature measurement.

[0073] 5. Light intensity ratio and temperature mapping model: According to the principle of phosphorescence intensity ratio temperature measurement, the emission spectrum of phosphorescent materials contains operating band combinations (including central wavelength and bandwidth) corresponding to the thermally coupled energy level or non-thermally coupled energy level of rare earth ions. The following relationship exists between the phosphorescence intensity ratio of the operating band combination and temperature:

[0074]

[0075] Where I1 and I2 are the phosphorescence intensities of the two working bands, FIR is the light intensity ratio corresponding to the working band combination, B is the coefficient determined by fitting, ΔE is the energy level difference, and k B is the Boltzmann constant, T is the temperature, and C is the coefficient determined by fitting.

[0076] 6. Characteristic peaks of phosphorescence spectrum: Characteristic peaks in the phosphorescence spectrum corresponding to thermal coupling energy levels that can be used for temperature measurement.

[0077] The phosphorescence temperature measurement wavelength selection method provided in the embodiment of the present application can be applied to Figure 1 In the application environment shown, the terminal 102 communicates with the server 104 via a network. The data storage system can store data that the server 104 needs to process. The data storage system can be set up separately, integrated on the server 104, or placed on the cloud or other servers. The terminal 102 can send the spectral data to be processed to the server 104. After receiving the spectral data to be processed, the server 104 reads all wavelengths in the spectral data to obtain wavelength data; traverses all bandwidths of each wavelength in the wavelength data to obtain bandwidth data corresponding to each wavelength; obtains a plurality of band combinations based on the wavelength data and the bandwidth data; each of the band combinations includes two working bands; each of the working bands includes one of the wavelengths and a corresponding bandwidth; uses each of the band combinations to establish a light intensity ratio and temperature mapping model; calculates the systematic error of each of the light intensity ratio and temperature mapping models when performing phosphorescence temperature measurement; deletes the light intensity ratio and temperature mapping models corresponding to the system error greater than a preset threshold to obtain a plurality of first light intensity ratio and temperature mapping models; calculates the random error of each of the first light intensity ratio and temperature mapping models and obtains the minimum random error; deletes the first light intensity ratio and temperature mapping model corresponding to the minimum random error whose random error is greater than a preset multiple to obtain a second light intensity ratio and temperature mapping model; and determines the phosphorescence temperature measurement working wavelength selection result based on the band combination corresponding to the second light intensity ratio and temperature mapping model. The server 104 can feed back the phosphorescence temperature measurement working wavelength selection result to the terminal 102. In addition, in some embodiments, the phosphorescence temperature measurement working wavelength selection method can also be implemented independently by the server 104 or the terminal 102. For example, the terminal 102 can directly process the spectral data to be processed, or the server 104 can obtain the spectral data to be processed from the data storage system and process it.

[0078] Terminal 102 may include, but is not limited to, various desktop computers, laptops, smartphones, tablet computers, IoT devices, and portable wearable devices. IoT devices may include smart speakers, smart TVs, smart air conditioners, and smart car devices. Portable wearable devices may include smart watches, smart bracelets, and head-mounted devices. Server 104 may be implemented as a standalone server or a server cluster consisting of multiple servers, or may be a cloud server.

[0079] In an exemplary embodiment, Figure 2 As shown, a method for selecting a phosphorescence temperature measurement wavelength is provided. The method is executed by a computer device, specifically a computer device such as a terminal or a server, or a terminal and a server. In the embodiment of the present application, the method is applied to Figure 1 The server 104 in the example is used as an example to illustrate the method, which includes the following steps S1 to S10.

[0080] This example is used to calibrate a rare earth ion emission peak intensity ratio versus temperature mapping model. During this mapping model calibration experiment, phosphorescence spectra at different temperatures must be collected. This example proposes simultaneously collecting both phosphorescence and background radiation spectra at different temperatures, capturing each spectrum 20 times at each temperature.

[0081] S1. Acquire several spectral data of phosphorescent materials.

[0082] In this embodiment, 20 groups of phosphorescence spectra collected at each temperature were subtracted from 20 groups of background radiation spectra to obtain 20 groups of pure phosphorescence spectra at each temperature. For YSZ:Dy material, the phosphorescence spectra and background radiation spectra at different temperatures were collected and offset corrected to obtain pure phosphorescence spectra. Figure 3 shown.

[0083] S2. Read all wavelengths in the spectral data to obtain wavelength data. In this embodiment, all wavelengths in the spectral data are read at intervals of 0.85 nm to obtain wavelength data.

[0084] S3. Traverse all bandwidths of each wavelength in the wavelength data to obtain bandwidth data corresponding to each wavelength. In this embodiment, 5 times the minimum step size of the spectrometer is used as the traversal step size, and the traversal range is from the minimum step size of the spectrometer to 200 times the minimum step size of the spectrometer. All bandwidths of each wavelength are traversed to obtain bandwidth data corresponding to each wavelength.

[0085] S4. Acquire several band combinations according to the wavelength data and the bandwidth data; each band combination includes two working bands; each working band includes one wavelength and a corresponding bandwidth.

[0086] The working band is defined by the central wavelength and bandwidth. Different phosphor materials have different emission spectra corresponding to different wavelength ranges. Taking YSZ:Dy as an example, its emission spectrum is as follows: Figure 3 The emission wavelength range includes 450nm-500nm and 540nm-620nm, among which 450nm-500nm is the commonly used working band combination range. Therefore, when optimizing the band combination of the phosphorescent material YSZ:Dy, the initial traversal range of the center wavelength of the working band combination is 450nm-500nm. The larger the traversal step size, the higher the calculation efficiency, and the smaller the traversal step size, the higher the calculation accuracy. In order to ensure high calculation accuracy while improving calculation efficiency, this embodiment sets two rounds of traversal. In the first round of traversal, the calculation step size of the center wavelength is set to 0.85nm (the minimum step size of the spectrometer used in this laboratory is 0.17nm, and 0.85nm is 5 times the minimum step size of the spectrometer), the traversal range of the bandwidth is from the minimum step size of the spectrometer to 200 times the minimum step size of the spectrometer, and the traversal step size is set to 5 times the minimum step size of the spectrometer. In the second round of traversal, the calculation step size of the center wavelength is set to 0.17nm, the traversal range of the bandwidth is from the minimum step size of the spectrometer to 200 times the minimum step size, and the traversal step size is set to the minimum step size of the spectrometer.

[0087] S5. Establish a light intensity ratio and temperature mapping model using each of the waveband combinations.

[0088] Specifically, in this embodiment, spectral data is input into the program, and then the possible operating bands in the spectrum are traversed. According to the principle of temperature measurement using the phosphorescence intensity ratio method, the emission spectrum of phosphorescent materials contains operating band combinations corresponding to the thermally coupled energy levels of rare earth ions or the non-thermally coupled energy levels. The phosphorescence intensity ratio of each operating band combination and temperature have the following relationship, that is, the light intensity ratio and temperature mapping model is:

[0089]

[0090] Where I1 and I2 are the phosphorescence intensities of the two working bands, FIR is the light intensity ratio corresponding to the working band combination, B is the coefficient determined by fitting, ΔE is the energy level difference, and k B is the Boltzmann constant, T is the temperature, and C is the coefficient determined by fitting.

[0091] S6. Calculate the systematic error of each light intensity ratio and temperature mapping model when performing phosphorescence temperature measurement.

[0092] The calculation process of the system error is as follows: for each of the light intensity ratio and temperature mapping models:

[0093] Predicting temperature using the light intensity ratio and temperature mapping model to obtain a predicted value;

[0094] Calculating the difference between the predicted value and the true value;

[0095] The difference is divided by the true value to obtain the systematic error.

[0096] S7. Delete the light intensity ratio and temperature mapping models corresponding to system errors greater than a preset threshold, thereby obtaining a plurality of first light intensity ratio and temperature mapping models. In this embodiment, the light intensity ratio and temperature mapping models corresponding to system errors greater than 0.5% are deleted, thereby obtaining a plurality of first light intensity ratio and temperature mapping models. 0.5% is the preset threshold selected in this embodiment; different values ​​may be used for different phosphorescent materials and different application scenarios.

[0097] S8. Calculate the random error of each of the first light intensity ratio and temperature mapping models, and obtain the minimum random error.

[0098] The random error calculation process is as follows: for each of the first light intensity ratio and temperature mapping models;

[0099] Obtaining a band combination corresponding to the first light intensity ratio and temperature mapping model;

[0100] Calculating the standard deviation of the light intensity ratio measured by performing n experiments according to the waveband combination;

[0101] The random error of the first light intensity ratio and temperature mapping model is obtained by dividing the standard deviation by square root n and then by the average light intensity ratio; the average light intensity ratio is the average of the light intensity ratios measured by n experiments based on the band combination.

[0102] S2-S8 above are the first round of traversal. In the first round, the light intensity ratio of each working band is first calculated. Then, a mapping relationship model is established between the average light intensity ratio and temperature of 20 repeated experiments for each working band. The difference between the temperature predicted by the mapping relationship model and the actual temperature (measured by the thermocouple in the calibration furnace) is calculated and divided by the actual temperature as the systematic error. If the systematic error is ≤0.5%, the data set is retained and the random error of the data set is evaluated. Otherwise, the data set is not retained. The random error evaluation method is to divide the standard deviation of the light intensity ratio measured in the 20 experiments of the working band set by the square root of 20, and then divide it by the average value of the light intensity ratio measured in the 20 experiments.

[0103] If improving the wavelength accuracy of the operating band is not a concern, the optimal operating band combination can be directly selected from the retained data from the first round of traversal, with the combination having the smallest random error. If improving the wavelength accuracy of the operating band is a concern, all operating band combinations with a random error no greater than 1.1 times the minimum random error are selected as the optimal operating band range, and a second round of traversal is conducted within this range. (The purpose of selecting a random error no greater than 1.1 times the minimum random error is to reduce the computational effort in the second round of traversal. Based on irrelevance verification, settings of 1.1, 1.2, and 1.3 yielded the same results.)

[0104] S9. Delete the first light intensity ratio to temperature mapping model corresponding to the minimum random error for which the random error is greater than a preset multiple, to obtain a second light intensity ratio to temperature mapping model. In this embodiment, delete the first light intensity ratio to temperature mapping model corresponding to the minimum random error for which the random error is greater than 1.1 times, to obtain a second light intensity ratio to temperature mapping model.

[0105] S10. Determine a phosphorescence temperature measurement working wavelength selection result according to the second light intensity ratio and a wavelength combination corresponding to the temperature mapping model.

[0106] Specifically:

[0107] Acquire a band combination corresponding to the second light intensity ratio and temperature mapping model to obtain second band combination data;

[0108] Read all wavelengths in the second wavelength band combination data at intervals of 0.17 nm to obtain second wavelength data;

[0109] Using the minimum step size of the spectrometer as the traversal step size, and the traversal range from the minimum step size of the spectrometer to 200 times the minimum step size of the spectrometer, traversing all bandwidths of each wavelength in the second wavelength data to obtain second bandwidth data corresponding to each wavelength;

[0110] Acquire a plurality of second wavelength band combinations according to the second wavelength data and the second bandwidth data; each second wavelength band combination includes two second operating wavelength bands; each second operating wavelength band includes a second wavelength and a corresponding second bandwidth;

[0111] establishing a second light intensity ratio and temperature mapping model using each of the second waveband combinations;

[0112] Calculating the systematic error of each of the second light intensity ratio and temperature mapping models when performing phosphorescence temperature measurement;

[0113] Deleting the second light intensity ratio and temperature mapping models corresponding to the system error being greater than a preset threshold, to obtain a plurality of third light intensity ratio and temperature mapping models;

[0114] Calculating a random error of each of the third light intensity ratio and temperature mapping models;

[0115] The second wavelength combination corresponding to the third light intensity ratio and the temperature mapping model with the smallest random error is used as the optimal working wavelength combination.

[0116] In short, the above step S10 is the second round of traversal process. In the second round of traversal, the traversed wavelength range is defined by the center wavelength and bandwidth. The working band combination includes a band with a longer wavelength and a band with a shorter wavelength. The traversal range is defined separately. The center wavelength range of the band with a longer wavelength is taken as the minimum range of all working band combinations with a random error not greater than 1.1 times the minimum random error screened out in the first round. The same is true for the band with a shorter wavelength. The calculation step of the center wavelength is set to 0.17nm, and the traversal range of the bandwidth is from the minimum step of the spectrometer to 200 times the minimum step, and the traversal step is set to the minimum step of the spectrometer. The traversal process is consistent with the first round of traversal. After screening out all working band combinations with a systematic error ≤0.5%, their random errors are evaluated, and the working band combination with the smallest random error is taken as the optimal working band combination.

[0117] Within the traversal range, all possible operating band combinations are exhaustively enumerated. For each pair of operating band combinations, light intensity ratio and temperature mapping relationship models 1 to n are established. The systematic errors of models 1 to n are then evaluated. If the systematic error does not meet the requirements, the model is deleted; otherwise, it is accepted as the accurate model. Within the accurate models, the random errors of the models are further compared and analyzed. The model with the smallest random error is selected as the optimal model, and the operating band corresponding to this model becomes the optimal operating band for the two-dimensional phosphorescence temperature measurement system.

[0118] In this embodiment, for the yttria-stabilized zirconia material doped with dysprosium ions (YSZ:Dy), two temperature measurement bands were screened out within the temperature range of 532K-990K, as shown in Table 1 below:

[0119] Table 1 Optimization results of temperature measurement bands

[0120] Central wavelength (nm) Bandwidth (nm) Temperature measurement wavelength 1 460.5 19 Temperature measurement wavelength 2 493.5 25

[0121] In this embodiment, a band combination evaluation method is established based on error theory:

[0122] Based on the temperature measurement accuracy index and error theory, the temperature measurement error is allocated. The temperature measurement error is allocated to calibration error and measured error according to the principle of equal action. The calibration error is the error generated during the calibration process, and the measured error is the error generated during the actual temperature test. The calibration error can be further allocated to systematic error and random error according to the principle of equal action. The error allocation calculation formula is as follows:

[0123]

[0124] Where E is the temperature measurement error, e calibration is the calibration error, e measured is the measured error.

[0125]

[0126] Where Δ is the systematic error and δ is the random error.

[0127] For example, when the temperature measurement error is set to 1%, according to the principle of equal action of error distribution, the calibration error and the measured error are equal, and the calibration error and the measured error are both 0.71%. The calibration error is further distributed into systematic error and random error according to the principle of equal action, and the systematic error and random error are both 0.5%.

[0128] The obtained model is considered accurate when the mapping relationship model between light intensity ratio and temperature meets the systematic error specification. Under this premise, considering that as temperature increases, phosphorescence thermal quenching intensifies, phosphorescence intensity decreases, and phosphorescence signal repeatability decreases, resulting in an increase in random error in the calibration results, to explore a higher upper temperature measurement limit and higher temperature measurement precision, a characteristic band combination with the smallest random error is selected as the optimal operating band combination. The systematic error of the mapping relationship corresponding to this band combination meets the accuracy requirements, with high accuracy, minimal random error, and high precision. Therefore, the mapping relationship corresponding to this band combination is characterized by high accuracy and high precision.

[0129] This application proposes a working band selection method suitable for the intensity ratio phosphorescence temperature measurement mode. By establishing a band combination evaluation method, working band selection with high temperature measurement accuracy is achieved, solving the problems of large uncertainty in calibration results and low temperature measurement accuracy in the calibration process of the intensity ratio and temperature mapping relationship model.

[0130] The working band selection method proposed by the present invention comprises the following steps:

[0131] 1. Spectral data preprocessing: averaging multiple phosphorescence spectra and background radiation spectra collected at each temperature to support the calculation of systematic and random errors;

[0132] 2. Background radiation offset correction: subtract the background radiation spectrum from the average phosphorescence spectrum at each temperature to obtain the average pure phosphorescence spectrum at each temperature, eliminating the influence of background radiation;

[0133] 3. Construction of band combination evaluation system: A band combination evaluation system is established based on error theory and error requirements of the temperature measurement object, including systematic error requirements and random error requirements. The systematic error requirements are obtained according to the total error requirements, and the random error takes the minimum value.

[0134] 4. To implement the band optimization algorithm, first input the spectral data, traverse the possible working bands in the spectrum, establish a mapping relationship model between intensity ratio and temperature for each working band combination, and then optimize the working band combination based on the band combination evaluation system to obtain the final optimal working band.

[0135] This application establishes a characteristic peak combination evaluation method based on error analysis theory and develops an automatic selection algorithm for characteristic peaks of rare earth ion emission spectra to select working band combinations with high temperature measurement accuracy, thereby solving the problems of large uncertainty in calibration results and low temperature measurement accuracy in the calibration process of the mapping relationship model.

[0136] In an exemplary embodiment, a computer device is provided, which may be a server or a terminal. The computer device includes a processor, a memory, an input / output interface (I / O) and a communication interface. The processor, the memory and the input / output interface are connected via a system bus, and the communication interface is connected to the system bus via the input / output interface. The processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program and a database. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The input / output interface of the computer device is used to exchange information between the processor and an external device. The communication interface of the computer device is used to communicate with an external terminal via a network connection. When the computer program is executed by the processor, a method for selecting a phosphorescence temperature measurement working wavelength is implemented.

[0137] In an exemplary embodiment, a computer device is further provided, including a memory and a processor. The memory stores a computer program, and the processor implements the steps in the above method embodiments when executing the computer program.

[0138] In an exemplary embodiment, a computer-readable storage medium is provided, storing a computer program. When the computer program is executed by a processor, the steps in the above-mentioned method embodiments are implemented.

[0139] In an exemplary embodiment, a computer program product is provided, including a computer program. When the computer program is executed by a processor, the steps in the above method embodiments are implemented.

[0140] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, stored data, displayed data, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties, and the collection, use and processing of relevant data must comply with relevant regulations.

[0141] Those skilled in the art will understand that all or part of the processes in the above-mentioned embodiment methods can be implemented by instructing the relevant hardware through a computer program, and the computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to memory, database or other media used in the embodiments provided in this application may include at least one of non-volatile and volatile memory. Non-volatile memory may include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetic random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory may include random access memory (RAM) or external cache memory, etc. By way of illustration and not limitation, RAM may be in various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM).

[0142] The databases involved in the various embodiments provided herein may include at least one of a relational database and a non-relational database. Non-relational databases may include, but are not limited to, distributed databases based on blockchains. The processors involved in the various embodiments provided herein may include, but are not limited to, general-purpose processors, central processing units, graphics processing units, digital signal processors, programmable logic units, data processing logic units based on quantum computing, and the like.

[0143] The technical features of the above embodiments can be combined arbitrarily. To make the description concise, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0144] This document uses specific examples to illustrate the principles and implementation methods of this application. The description of the above examples is only intended to help understand the method and core concept of this application. At the same time, for those skilled in the art, based on the concept of this application, there may be changes in the specific implementation methods and application scope. In summary, the content of this specification should not be understood as limiting this application.

Claims

1. A method for selecting a working wavelength for phosphorescence temperature measurement, characterized in that: The phosphorescence temperature measurement working wavelength selection method comprises: Acquiring a plurality of spectral data of phosphorescent materials; Read all wavelengths in the spectral data to obtain wavelength data; Traversing all bandwidths of each wavelength in the wavelength data to obtain bandwidth data corresponding to each wavelength; Acquire a plurality of band combinations according to the wavelength data and the bandwidth data; each of the band combinations includes two working bands; each of the working bands includes one of the wavelengths and a corresponding bandwidth; Using each of the waveband combinations to establish a light intensity ratio and temperature mapping model; Calculating the systematic error of each of the light intensity ratio and temperature mapping models when performing phosphorescence temperature measurement; Deleting the light intensity ratio and temperature mapping models corresponding to the system error being greater than a preset threshold, to obtain a plurality of first light intensity ratio and temperature mapping models; Calculating the random error of each of the first light intensity ratio and temperature mapping models, and obtaining the minimum random error; The first light intensity ratio and temperature mapping model corresponding to the minimum random error whose random error is greater than a preset multiple is deleted to obtain a second light intensity ratio and temperature mapping model; The phosphorescence temperature measurement working wavelength selection result is determined according to the second light intensity ratio and the wavelength combination corresponding to the temperature mapping model.

2. The phosphorescence temperature measurement working wavelength selection method according to claim 1, characterized in that: The light intensity ratio and temperature mapping model is: Where I1 and I2 are the phosphorescence intensities of the two working bands, FIR is the light intensity ratio corresponding to the working band combination, B is the coefficient determined by fitting, ΔE is the energy level difference, and k B is the Boltzmann constant, T is the temperature, and C is the coefficient determined by fitting.

3. The phosphorescence temperature measurement working wavelength selection method according to claim 1, characterized in that: reading all wavelengths in the spectral data to obtain wavelength data; Traverse all bandwidths of each wavelength to obtain bandwidth data corresponding to each wavelength, specifically including: Read all wavelengths in the spectral data at intervals of 0.85 nm to obtain wavelength data; Taking 5 times the minimum step size of the spectrometer as the traversal step size, and the traversal range from the minimum step size of the spectrometer to 200 times the minimum step size of the spectrometer, all bandwidths of each wavelength are traversed to obtain the bandwidth data corresponding to each wavelength.

4. The phosphorescence temperature measurement wavelength selection method according to claim 3, characterized in that: The determining of the phosphorescence temperature measurement working wavelength selection result according to the wavelength combination corresponding to the second light intensity ratio and the temperature mapping model specifically includes: Acquire a band combination corresponding to the second light intensity ratio and temperature mapping model to obtain second band combination data; Read all wavelengths in the second wavelength band combination data at intervals of 0.17 nm to obtain second wavelength data; Using the minimum step size of the spectrometer as the traversal step size, and the traversal range from the minimum step size of the spectrometer to 200 times the minimum step size of the spectrometer, traversing all bandwidths of each wavelength in the second wavelength data to obtain second bandwidth data corresponding to each wavelength; Acquire a plurality of second wavelength band combinations according to the second wavelength data and the second bandwidth data; each second wavelength band combination includes two second operating wavelength bands; each second operating wavelength band includes a second wavelength and a corresponding second bandwidth; establishing a second light intensity ratio and temperature mapping model using each of the second waveband combinations; Calculating the systematic error of each of the second light intensity ratio and temperature mapping models when performing phosphorescence temperature measurement; Deleting the second light intensity ratio and temperature mapping models corresponding to the system error being greater than a preset threshold, to obtain a plurality of third light intensity ratio and temperature mapping models; Calculating a random error of each of the third light intensity ratio and temperature mapping models; The second wavelength combination corresponding to the third light intensity ratio and the temperature mapping model with the smallest random error is used as the optimal working wavelength combination.

5. The phosphorescence temperature measurement wavelength selection method according to claim 1, characterized in that: The light intensity ratio and temperature mapping models corresponding to the system error being greater than a preset threshold are deleted to obtain a plurality of first light intensity ratio and temperature mapping models, specifically including: The light intensity ratio and temperature mapping models corresponding to the system error greater than 0.5% are deleted to obtain several first light intensity ratio and temperature mapping models; The step of deleting the first light intensity ratio and temperature mapping model corresponding to the minimum random error having a random error greater than a preset multiple to obtain a second light intensity ratio and temperature mapping model specifically includes: The first light intensity ratio and temperature mapping model corresponding to the minimum random error whose random error is greater than 1.1 times is deleted to obtain a second light intensity ratio and temperature mapping model.

6. The phosphorescence temperature measurement wavelength selection method according to claim 1, characterized in that: The calculating of the systematic error of each of the light intensity ratio and temperature mapping models when performing phosphorescence temperature measurement specifically includes: For each of the light intensity ratio and temperature mapping models: Predicting temperature using the light intensity ratio and temperature mapping model to obtain a predicted value; Calculating the difference between the predicted value and the true value; The difference is divided by the true value to obtain the systematic error.

7. The phosphorescence temperature measurement wavelength selection method according to claim 1, characterized in that: Calculating the random error of each of the first light intensity ratio and temperature mapping models specifically includes: For each of the first light intensity ratio and temperature mapping models; Obtaining a band combination corresponding to the first light intensity ratio and temperature mapping model; Calculating the standard deviation of the light intensity ratio measured by performing n experiments according to the waveband combination; The random error of the first light intensity ratio and temperature mapping model is obtained by dividing the standard deviation by square root n and then by the average light intensity ratio; the average light intensity ratio is the average of the light intensity ratios measured by n experiments based on the band combination.

8. A computer device comprising: A memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the phosphorescence temperature measurement wavelength selection method according to any one of claims 1 to 7.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the phosphorescence temperature measurement working wavelength selection method according to any one of claims 1 to 7 is implemented.

10. A computer program product comprising a computer program, characterized in that When the computer program is executed by a processor, the phosphorescence temperature measurement working wavelength selection method according to any one of claims 1 to 7 is implemented.

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