Optical fiber sensing based method for temperature measurement of an aeroengine

Abstract

The application discloses an aero-engine temperature measurement method based on optical fiber sensing, relates to the technical field of optical fiber sensing and spectrum measurement, establishes a spectrum sensing principle, establishes a temperature and spectrum characteristic corresponding relation, designs a rare earth oxide sensitive element and combines the sensitive element with an engine component, constructs an optical system, collects spectrum signals after the action of the sensitive element and transmits the spectrum signals to a spectrometer, carries out filtering, correction and feature extraction on the spectrum signals, obtains spectrum characteristic parameters, calculates temperature data based on a temperature sensing equation, obtains corrected temperature data through extrapolation and correction in a temperature interval, and transmits the corrected temperature data to a control end for display, storage and early warning. Through optimization of sensitive element design, optical system construction and data processing, the application forms a complete temperature collection, processing, analysis and transmission link, and can realize real-time, accurate and anti-interference temperature measurement under extreme conditions above 2000 DEG C.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of optical fiber sensing and spectrum measurement, and in particular to an aero-engine temperature measurement method based on optical fiber sensing. BACKGROUND

[0002] During the combustion and high-speed operation of an aero-engine, the surface temperature of its key components often exceeds 2000℃. The existing contact thermocouple and infrared radiation measurement methods have the problems of slow response speed, susceptibility to strong background radiation interference, poor real-time performance, and difficulty in stably obtaining accurate data under complex structures. Optical fiber sensing technology provides a feasible approach for engine temperature measurement due to its advantages of resistance to electromagnetic interference, remote transmission, and adaptation to extreme environments. However, under the condition of ultra-temperature range, how to realize stable extraction of spectral signals, rapidity of data processing, and consistency of the whole process is still a technical difficulty to be solved.

[0003] At present, the Chinese patent with application number CN202110600572.3 discloses an aero-engine high-temperature component optical fiber temperature measurement system and temperature field reconstruction method, which includes a plurality of femto optical fiber grating temperature sensors; an optical fiber grating wavelength demodulation module connected with the optical fiber grating sensor through a flange joint, and then connected with a computer through a network interface; a temperature data processing module in communication connection with the optical fiber grating wavelength demodulation module; a temperature data synthesis module in communication connection with the temperature data processing module, used for establishing the mapping relationship of the optical fiber grating temperature sensor coordinates, temperature values and colors; and a display module in communication connection with the temperature data synthesis module, displaying the real-time temperature of different positions on the surface of the aero-engine high-temperature component, realizing temperature field reconstruction.

[0004] The related technology is difficult to realize stable, real-time and high-precision temperature measurement under the ultra-temperature range environment of an aero-engine. SUMMARY

[0005] The technical problem solved by the present application is that the existing technology is difficult to realize stable, real-time and high-precision temperature measurement under the ultra-temperature range environment of an aero-engine.

[0006] To solve the above technical problems, the present application provides the following technical solutions:

[0007] The aero-engine temperature measurement method based on optical fiber sensing includes the following steps:

[0008] Step S1: determining the effect of temperature on spectral signals based on the theory of spectroscopy, forming a set of spectral characteristic parameters and establishing a temperature sensing equation;

[0009] Step S2: selecting rare earth oxides to prepare optical fiber sensing elements and fixing them on the engine area, so that the incident light interacts with the sensing elements to generate modulated spectral signals;

[0010] Step S3, collecting the spectral signal by the light collection probe and transmitting it to the spectrometer through the optical fiber for analysis;

[0011] Step S4, filtering and baseline correction of the spectral signal, extracting the absorption intensity ratio and spectral line shape parameters as temperature-sensitive parameters;

[0012] Step S5, substituting the temperature-sensitive parameters into the temperature sensing equation to calculate the temperature data, combining the historical data in the temperature interval for extrapolation correction to obtain the corrected temperature data;

[0013] Step S6, transmitting the corrected temperature data to the control end for real-time display, storage and abnormality judgment, triggering an alarm and outputting information when exceeding the preset threshold;

[0014] The step S5 includes the following sub-steps:

[0015] Step S501, substituting the temperature-sensitive parameters into the temperature sensing equation established in step S1 for calculation to obtain real-time temperature data;

[0016] The calculation process includes substituting the temperature-sensitive parameters into the temperature sensing equation coefficient for solving and interpolation calculation to generate real-time temperature data corresponding to the time sequence of the current spectral signal;

[0017] Step S502, stability checking of the real-time temperature data, eliminating discrete abnormal points caused by spectral signal fluctuation, and using sliding average or weighted smoothing method to process continuous sampling results, and outputting the smoothed real-time temperature sequence;

[0018] Step S503, when detecting that the smoothed real-time temperature sequence enters the temperature interval, extracting temperature reference data matched with the current engine working condition from the historical temperature database, and performing time sequence alignment;

[0019] Joint analysis of the smoothed real-time temperature sequence and the reference data, using a polynomial regression algorithm to calculate the temperature interval temperature prediction result, and outputting the temperature interval temperature data;

[0020] Step S504, extracting a spectral correction factor from the spectral signal obtained in step S3, the spectral correction factor reflecting the nonlinear response of the spectral characteristic parameter in the temperature interval;

[0021] Using the spectral correction factor to correct the temperature interval temperature data output in step S503 to obtain the corrected temperature data.

[0022] Preferably, the step S1 includes the following sub-steps:

[0023] In step S101, based on the theory of spectroscopy, the form of the effect of temperature on the spectral signal is determined, which includes line broadening, intensity ratio, and line shape change. Based on the theory of spectroscopy and experimental calibration data, a temperature response model of the spectral signal is established, which is used to describe the influence of temperature change on the spectral characteristic parameters. Based on the temperature response model of the spectral signal, the fitting correlation of different forms of action to temperature change is calculated, and the parameters that meet the preset threshold are selected as effective spectral characteristic parameters to form a target spectral characteristic parameter set.

[0024] In step S102, in combination with the engine temperature working condition, a rare earth sensitive material with suitable visible light absorption characteristics is selected, and a temperature sensing equation corresponding to the monotonous spectrum characteristic is established.

[0025] In step S103, the consistency of the temperature sensing equation and the measured spectral signal data within the allowable error range is verified through environmental experiments, and the applicable range of the temperature sensing equation in the temperature interval is established.

[0026] The temperature sensing equation in step S103 meets the following conditions:

[0027] Without the need for external physical reference comparison, the measurement results in the experimental interval are extrapolated to above 2000℃, and the error is kept within the preset range.

[0028] Preferably, the step S2 comprises the following sub-steps:

[0029] In step S201, a rare earth oxide sensitive material is selected, which has a melting point higher than 2100K and has discrete absorption energy levels and significant thermal coupling energy levels.

[0030] In step S202, a borosilicate inorganic adhesive and a sol-gel method are used to coat or embed the sensitive material on the surface of the engine blade or the engine inner wall.

[0031] In step S203, the size and heat capacity of the sensitive element are controlled.

[0032] In step S204, color-developing rare earth ions are added during the preparation of the thermal barrier coating and the ceramic coating.

[0033] Preferably, the step S3 comprises the following sub-steps:

[0034] In step S301, a blackbody radiation is used as a continuous spectrum light source, and a laser light source is configured to supplement specific band energy according to experimental requirements.

[0035] In step S302, the transmission signal and the reflection signal after the background radiation is affected by the sensitive element are collected by a light collection probe.

[0036] Step S303, coupling the transmission signal and the reflection signal to the spectrometer for spectral analysis by using a light path combining free space and optical fiber;

[0037] Step S304, setting a filtering link and an impedance matching link in the light path and circuit design, and outputting the optical spectrum signal.

[0038] Preferably, the step S4 comprises the following sub-steps:

[0039] Step S401, converting the optical spectrum signal into an electrical signal and performing filtering and noise suppression;

[0040] Step S402, performing baseline correction on the optical spectrum signal to eliminate background drift;

[0041] Step S403, extracting spectral feature parameters corresponding to the monotonic change of temperature in the optical spectrum signal, the spectral feature parameters including absorption intensity ratio and spectral line morphology parameters, performing ratio calculation on the spectral feature parameters, and outputting temperature-sensitive parameters;

[0042] Step S404, limiting the calculation amount and speed of the extraction process of step S403, the calculation amount and speed being less than preset calculation amount threshold and speed threshold.

[0043] Preferably, the step S6 comprises the following sub-steps:

[0044] Step S601, transmitting the corrected temperature data to the control end through the optical fiber;

[0045] Step S602, displaying the corrected temperature data in real time, storing data, and performing trend analysis at the control end to establish a temperature monitoring database;

[0046] Step S603, when the corrected temperature data exceeds the preset threshold, triggering an alarm mechanism and generating an alarm information;

[0047] Step S604, transmitting the alarm information to the engine control system.

[0048] Preferably, the selection and preparation of the sensitive element in step S2 have the following requirements:

[0049] The selected rare earth oxide sensitive material presents discrete absorption spectral lines in the visible light region and has a significant thermal coupling level;

[0050] The color-producing rare earth ion doping needs to maintain mechanical properties and thermal stability in the ceramic thermal barrier coating;

[0051] The overall heat capacity of the sensitive element is lower than the preset heat capacity threshold.

[0052] Preferably, the extraction of the spectral feature parameters in step S403 comprises:

[0053] The filtered and baseline-corrected spectral signal is analyzed in real time, two preset specific wavelength band absorption intensity ratios are selected as temperature-sensitive features, and background radiation noise is suppressed and the calculation process is optimized.

[0054] The present application has the following advantages: through the optimization of the sensitive element design, optical system construction and data processing, the present application forms a complete temperature collection, processing, analysis and transmission link, and can realize real-time, accurate and anti-interference temperature measurement under extreme conditions above 2000℃. BRIEF DESCRIPTION OF DRAWINGS

[0055] Figure 1 The step flowchart of the aero-engine temperature measurement method based on optical fiber sensing provided by an embodiment of the present application is shown. DETAILED DESCRIPTION

[0056] In order to make the above-mentioned objects, features and advantages of the present application more obvious and easy to understand, the specific embodiments of the present application will be described in detail below with reference to the accompanying drawings. Obviously, the described embodiments are part of the embodiments of the present application, rather than all the embodiments.

[0057] Embodiments, with reference to Figure 1 , an aero-engine temperature measurement method based on optical fiber sensing is provided, which comprises the following steps:

[0058] Step S1: based on the theory of spectroscopy, the effect of temperature on the spectral signal is determined, a set of spectral characteristic parameters is formed, and a temperature sensing equation is established.

[0059] Step S2: rare earth oxides are selected to prepare optical fiber sensitive elements, which are fixed on the engine area, so that the incident light interacts with the sensitive elements to generate modulated spectral signals.

[0060] Step S3: the spectral signal is collected by a light collection probe and transmitted to a spectrometer for analysis through an optical fiber.

[0061] Step S4: the spectral signal is filtered and baseline-corrected, and the absorption intensity ratio and spectral line shape parameters are extracted as temperature-sensitive parameters.

[0062] Step S5: the temperature-sensitive parameters are substituted into the temperature sensing equation to calculate the temperature data, and the historical data is combined to extrapolate and correct the temperature data in the temperature range, to obtain the corrected temperature data.

[0063] Step S6: the corrected temperature data is transmitted to the control end for real-time display, storage and abnormality judgment, and when the preset threshold is exceeded, an alarm is triggered and information is output.

[0064] The application provides an aero-engine temperature measurement method based on optical fiber sensing, and through optimization of sensitive element design, optical system construction and data processing, a complete temperature collection, processing, analysis and transmission link is formed, and real-time, accurate and anti-interference temperature measurement can be realized under extreme conditions above 2000 DEG C.

[0065] Step S1 includes the following sub-steps:

[0066] Step S101, based on the theory of spectroscopy, the form of action of temperature in the spectral signal is determined, the form of action includes line broadening, intensity ratio and line shape change, based on the theory of spectroscopy and experimental calibration data, a temperature response model of the spectral signal is established, the temperature response model is used to describe the influence law of temperature change on the spectral characteristic parameter, based on the temperature response model of the spectral signal, the fitting correlation degree of different action forms to temperature change is calculated, the parameter meeting the preset threshold is selected as the effective spectral characteristic parameter, and a target spectral characteristic parameter set is formed.

[0067] Step S102, in combination with the engine temperature working condition, a rare earth sensitive material suitable for visible light absorption characteristics is selected, and a temperature sensing equation corresponding to the monotonous spectrum characteristic is established.

[0068] Step S103, the consistency of the temperature sensing equation and the measured spectral signal data within the allowable error range is verified through the temperature environment experiment, and the applicable range of the temperature sensing equation in the temperature interval is established.

[0069] The temperature sensing equation in step S103 meets the following conditions:

[0070] Without external physical reference comparison, the measurement results in the experimental interval are extrapolated to above 2000 DEG C.

[0071] Step S2 includes the following sub-steps:

[0072] Step S201, a rare earth oxide sensitive material is selected, the rare earth oxide sensitive material has a melting point higher than 2100K and has discrete absorption energy levels and significant thermal coupling energy levels.

[0073] Step S202, using borosilicate inorganic adhesive and sol-gel method, the sensitive material is coated or embedded on the surface of the engine blade or the engine inner wall.

[0074] Step S203, the size and heat capacity of the sensitive element are controlled.

[0075] Step S204, in the preparation process of the thermal barrier coating and the ceramic coating, color-developing rare earth ions are added.

[0076] The selection and preparation of the sensitive element in step S2 have the following requirements:

[0077] The selected rare earth oxide sensitive material presents discrete absorption spectral lines in the visible light region and has significant thermal coupling energy levels.

[0078] The color-developing rare earth ion doping needs to maintain mechanical properties and thermal stability in the ceramic thermal barrier coating.

[0079] The overall heat capacity of the sensitive element is lower than a preset heat capacity threshold.

[0080] In order to reduce the intensity of background radiation and avoid strong infrared radiation during combustion, the wavelength range of the detection spectrum is selected in the visible light region. Accordingly, the temperature sensing sensitive material should have transition absorption of visible light. In order to distinguish the continuous blackbody radiation spectrum, the absorption spectrum of the temperature sensing sensitive material should be discrete spectral lines. In order to significantly reflect the influence of temperature on the spectrum, the temperature sensing sensitive material should have thermally coupled energy levels and these energy levels participate in light absorption transition.

[0081] The sensitive material participates in the construction of the sensing system in the form of a sensitive element. The sensitive element should be able to quickly realize heat exchange with the temperature measuring object. Therefore, the sensitive element and the temperature measuring object should have stable and good thermal contact. The sensitive element should be able to realize dynamic thermal equilibrium with the temperature measuring object in real time. Therefore, the heat capacity of the element itself should be small. The sensitive element itself should be able to withstand the super-temperature range to be measured without changing the sensing characteristics.

[0082] Step S3 includes the following sub-steps:

[0083] Step S301, using blackbody radiation as a continuous spectrum light source, and configuring a laser light source to supplement specific band energy according to experimental requirements.

[0084] Step S302, collecting the transmission signal and the reflection signal of the background radiation after the action of the sensitive element through the light collection probe.

[0085] Step S303, using a combination of free space and optical fiber to couple the transmission signal and the reflection signal to the spectrometer for spectral analysis.

[0086] Step S304, setting a light filtering link and an impedance matching link in the optical circuit design, and outputting the spectral signal.

[0087] The complete sensing and detection system includes a light source and a photoelectric conversion device. The light source needs to be determined according to the type of spectrum used in the experiment. The wireless sensing method measures the spectrum by collecting the light signal transmitted in the free space through the optical element.

[0088] Step S4 includes the following sub-steps:

[0089] Step S401, converting the spectral signal into an electrical signal and performing filtering and noise suppression.

[0090] Step S402, baseline correction is performed on the spectral signal to eliminate background drift.

[0091] Step S403, a spectral feature parameter corresponding to the monotonic change of temperature is extracted from the spectral signal, the spectral feature parameter includes an absorption intensity ratio and a spectral line shape parameter, a temperature sensitive parameter is calculated by ratio calculation on the spectral feature parameter.

[0092] Step S404, the calculation amount and speed of the extraction process of step S403 are limited, and the calculation amount and speed are less than the preset calculation amount threshold and speed threshold.

[0093] The collected spectral data needs to be processed by baseline removal, noise reduction and other conventional processes before extracting appropriate spectral features that change monotonically with temperature as temperature sensing signals. This signal must meet certain requirements, and the calculation amount required for extracting the signal should be small to meet the requirements of rapid and real-time testing. It is necessary to consider the dependence on the spectral scanning function of the experimental system to avoid the limitation of the response time characteristics of the system by the spectral scanning time or integration time, and to facilitate the realization of a practical sensor device without wavelength scanning components.

[0094] Step S5 includes the following sub-steps:

[0095] Step S501, the temperature sensitive parameter is substituted into the temperature sensing equation established in step S1 for calculation to obtain real-time temperature data.

[0096] The calculation process includes substituting the temperature sensitive parameter according to the temperature sensing equation coefficient for solving and interpolation calculation to generate real-time temperature data corresponding to the time sequence of the current spectral signal.

[0097] Step S502, the stability of the real-time temperature data is checked, and the discrete abnormal points caused by the fluctuation of the spectral signal are removed, and the sliding average or weighted smoothing method is used to process the continuous sampling results, and the smoothed real-time temperature sequence is output.

[0098] Step S503, when the smoothed real-time temperature sequence enters the temperature interval, the temperature reference data matched with the current engine working condition is extracted from the historical temperature database, and the time sequence is aligned.

[0099] The smoothed real-time temperature sequence and the reference data are jointly analyzed, a polynomial regression algorithm is used to calculate the temperature prediction result in the temperature interval, and the temperature data in the temperature interval is output.

[0100] Step S504, a spectral correction factor is extracted from the spectral signal obtained in step S3, the spectral correction factor reflects the nonlinear response of the spectral feature parameter in the temperature interval.

[0101] The temperature interval temperature data output in step S503 is corrected by using a spectral correction factor to obtain corrected temperature data.

[0102] In the theory of spectroscopy, absolute temperature appears in the form of kT in theoretical expressions of spectral line broadening, fluorescence intensity ratio, energy transfer probability, etc., so it is possible to measure temperature by changes in line width, spectral intensity ratio, and even spectral profile shape. As long as the experimental phenomena and the rules of the theoretical expressions are consistent within the error range, the correctness of the theoretical expressions as the required sensing equation can be proved, and the sensing equation can be directly used without calibration in a higher temperature range than the experimental temperature.

[0103] Step S6 includes the following sub-steps:

[0104] In step S601, the corrected temperature data is transmitted to the control end through an optical fiber.

[0105] In step S602, the corrected temperature data is displayed in real time, stored and trend analyzed at the control end to establish a temperature monitoring database.

[0106] In step S603, when the corrected temperature data exceeds a preset threshold, an alarm mechanism is triggered and alarm information is generated.

[0107] In step S604, the alarm information is transmitted to the engine control system.

[0108] Among the existing spectral temperature measurement principles that meet the conditions, the spectral line broadening method requires a high-resolution spectrometer, and the thermal broadening sensitivity of solid sensitive materials is relatively low. The fluorescence intensity ratio temperature measurement technology is used in a temperature range above 500℃. On the one hand, the continuously increasing blackbody radiation background becomes the baseline of the actual measured spectrum, and the baseline cannot be ideally removed, reducing the signal-to-noise ratio. On the other hand, the thermal quenching caused by temperature rise is reflected in the decrease of fluorescence signal intensity, also leading to a decrease in signal-to-noise ratio. Through literature research, based on the measurement results and experience of previous research, the present application forms an absorption spectral intensity ratio temperature measurement mechanism.

[0109] For sensitive materials, the multiple lanthanide 4f electrons have rich split energy levels near the ground state, and suitable near-ground thermal coupling energy levels can be selected, with an energy level spacing of about tens to hundreds of wave numbers; the absorption transition of the discrete energy level to the higher excited state energy level is linear in the spectrum; there is strong absorption in the visible light range, which means that the material has color under white light illumination. The melting point of rare earth oxides is generally more than 2100K. Therefore, it can be determined that the fast selection standard of sensitive materials is: colored, rare earth oxides. Praseodymium oxide, neodymium oxide, dysprosium oxide and the like are ideal sensitive materials. In order to adapt to higher use temperature, colored multi-component oxides such as rare earth borates, aluminates and silicates can be prepared as sensitive materials according to the material selection standard. The present application will select suitable sensitive materials through literature research and experimental exploration based on the measurement results and experience of previous studies.

[0110] For sensitive elements, the sensitive material is coated on the surface of the object to be measured by using borosilicate inorganic adhesive. When the measured object has a coating, such as the thermal barrier coating of the engine blade, the color-changing rare earth ions can be incorporated into the ceramic-based coating during the preparation of the ceramic-based coating. A small amount of rare earth ion doping will not change the mechanical properties and thermal properties of the ceramic coating, and some rare earths are already listed as toughening agents in the material formula of the coating. The present application will explore different methods and reasonably design the structure of the sensitive element.

[0111] In the design and construction of the optical system, the blackbody radiation background of the detected object itself is also a good continuous spectrum light source, which is suitable for absorption spectrum application. In addition, the experimental system needs to additionally configure a laser light source system, use a light collection probe to aim at the sensitive material (sample), collect the signal light transmitted by the background radiation through the sensitive material, couple it to an optical fiber, and then input it into a spectrometer. The absorption spectrum measurement and analysis system constructed by combining free space with optical fiber is relatively stable and reliable. According to the definition of the sensing signal (spectral characteristic parameter), the intensity data of the transmitted / reflected light is processed, converted into an electrical signal and filtered and denoised.

[0112] In the processing and analysis of signal data, the integral intensity ratio needs to read the absorption intensities of two wave bands, and the result of real-time division operation depends on the theoretical sensing equation corresponding to the temperature, without frequency sweeping process, so that the spectral system detects temperature more quickly and accurately.

[0113] The resistance-voltage conversion of Wheatstone bridge is a division operation, which corresponds to the proportional calculation of light intensity in the bridge analysis method of spectrum. Two specific wavelengths (wave bands) are screened by filters, and impedance photosensitive elements are used as two active arms of the Wheatstone bridge to detect light of two wavelengths respectively, and the output voltage of the bridge is proportional to the light intensity ratio, which directly realizes the photoelectric detection of temperature. The present application will properly process and analyze the signal data according to the specific situation, optimize the processing method of the measurement signal based on the progress of the stage experiment and the sensing performance of the measurement system without passing through the temperature zone, and develop the signal data processing and analysis suitable for the measurement of the aero-engine.

[0114] The present application is based on the theory of spectroscopy, and uses the measured absorption spectrum, emission spectrum and scattering spectrum to obtain the dynamic change of spectral profile, establish the quantum reference of temperature detection expressed by the theory of spectroscopy, obtain a new sensing theory suitable for the measurement of the engine in the super-temperature range, and guide the design of the sensor. Under the background of the establishment of the quantum reference of temperature detection expressed by the theory of spectroscopy, the method of coupling the extraction of spectral characteristics with the fitting of sensing equation is used to guide the design of the sensor and the construction of the system, and the spectroscopic temperature measurement method conforming to the quantum reference is developed, so that a new non-contact optical measurement method suitable for the real-time monitoring requirement of the aero-engine is provided.

[0115] Those skilled in the art will appreciate that embodiments of the present application can be readily used as a method, a system or a computer program product. Accordingly, the present application can take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present application can take the form of a computer program product on one or more computer-usable storage media (or computer- readable storage media) having computer-usable program code embodied in the medium. The medium can be any available storage media that can be accessed by a computer. By way of example, and not limitation, such computer-usable storage media can include RAM, ROM, EEPROM, CD-ROM or other optical disk storage, magnetic disk storage or other magnetic storage devices, or any other storage medium(s) that can be used to carry or store desired computer program code in the form of instructions or data structures and that can be accessed by a computer. Also, the present application can be embodied in a computer program product that can be traded as goods or merchandise, through the storage medium described above or any other suitable medium. Accordingly, the present application can be embodied in a computer program product that can be traded as goods or merchandise, through the storage medium described above or any other suitable medium. Computer program code embodied in a storage medium is said (referring to a program or code) to "cause a computer" (or Figure 1 one or more functions specified in the flow or flows and / or blocks Figure 1 one or more functions specified in the flow or flows and / or blocks

[0116] It should be noted that the above-mentioned embodiments are only used to illustrate but not to limit the technical solutions of the present application. Although the present application is described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical solutions of the present application can be modified or equivalent replaced without departing from the spirit and scope of the technical solutions of the present application, and they should be covered in the scope of the claims of the present application.

Claims

1. A method for measuring the temperature of an aeroengine based on optical fiber sensing, characterized in that, It comprises the following steps: Step S1, determining the effect of temperature on the spectral signal based on the theory of spectroscopy, forming a set of spectral characteristic parameters and establishing a temperature sensing equation; Step S2, selecting rare earth oxides to prepare fiber sensitive elements and fixing them in the engine area, so that the incident light interacts with the sensitive elements to generate a modulated spectral signal; Step S3, collecting the spectral signal through a light collection probe and transmitting it to a spectrometer through an optical fiber for analysis; Step S4, filtering and baseline correction of the spectral signal, extracting the absorption intensity ratio and spectral line shape parameters as temperature-sensitive parameters; Step S5, substituting the temperature-sensitive parameters into the temperature sensing equation to calculate the temperature data, and combining the historical data in the temperature range for extrapolation correction to obtain the corrected temperature data; Step S6, transmitting the corrected temperature data to the control end for real-time display, storage and abnormality judgment, triggering an alarm and outputting information when the preset threshold is exceeded; The step S5 comprises the following sub-steps: Step S501, substituting the temperature-sensitive parameters into the temperature sensing equation established in step S1 to calculate the real-time temperature data; The calculation process includes substituting the temperature-sensitive parameters into the temperature sensing equation and interpolation calculation according to the coefficients of the temperature sensing equation to generate real-time temperature data corresponding to the time sequence of the current spectral signal; Step S502, stability checking of the real-time temperature data, eliminating discrete abnormal points caused by spectral signal fluctuations, and processing continuous sampling results using sliding average or weighted smoothing method to output smoothed real-time temperature sequence; Step S503, when the smoothed real-time temperature sequence is detected to enter the temperature range, extracting temperature reference data matched with the current engine operating condition from the historical temperature database and performing time sequence alignment; Jointly analyzing the smoothed real-time temperature sequence and the reference data, calculating the temperature prediction result in the temperature range using a polynomial regression algorithm, and outputting the temperature range temperature data; Step S504, extracting a spectral correction factor from the spectral signal obtained in step S3, the spectral correction factor reflecting the nonlinear response of the spectral characteristic parameters in the temperature range; Using the spectral correction factor to correct the temperature range temperature data output in step S503 to obtain the corrected temperature data.

2. The optical fiber sensor based temperature measurement method for an aero-engine as claimed in claim 1, wherein, The step S1 comprises the following sub-steps: Step S101, based on the theory of spectroscopy, the form of temperature in the spectral signal is determined, which includes line broadening, intensity ratio and line shape change, based on the theory of spectroscopy and experimental calibration data, a temperature response model of the spectral signal is established, which is used to describe the influence law of temperature change on the spectral characteristic parameters, based on the temperature response model of the spectral signal, the fitting correlation degree of different action forms to temperature change is calculated, the parameters meeting the preset threshold are selected as effective spectral characteristic parameters, and a set of target spectral characteristic parameters is formed; Step S102, combined with the engine temperature condition, a rare earth sensitive material suitable for visible light absorption characteristics is selected, and a temperature sensing equation corresponding to the spectral characteristic monotonically is established; Step S103, verify the consistency of the temperature sensing equation and the measured spectral signal data within the allowable error range through environmental experiments, and establish the applicable range of the temperature sensing equation in the temperature interval; The temperature sensing equation in step S103 meets the following conditions: Without external physical reference comparison, the measurement results in the experimental interval are extrapolated to above 2000℃, and the error is kept within the preset range.

3. The optical fiber sensor based gas turbine engine temperature measurement method as recited in claim 1, wherein, The step S2 includes the following sub-steps: Step S201, select a rare earth oxide sensitive material, the melting point of the rare earth oxide sensitive material is higher than 2100K and has discrete absorption energy level and significant thermal coupling energy level; Step S202, use borosilicate inorganic adhesive and sol-gel method to coat or embed the sensitive material on the surface of the engine blade or the engine inner wall; Step S203, control the size and heat capacity of the sensitive element; Step S204, add color-developing rare earth ions during the preparation of the thermal barrier coating and the ceramic coating.

4. The optical fiber sensor based gas turbine engine temperature measurement method as recited in claim 3, wherein, The step S3 includes the following sub-steps: Step S301, use blackbody radiation as a continuous spectrum light source, and configure a laser light source to supplement specific band energy according to experimental requirements; Step S302, collect the transmission signal and reflection signal of the background radiation after the action of the sensitive element through the light collection probe; Step S303, use the combination of free space and optical fiber to couple the transmission signal and reflection signal to the spectrometer for spectral analysis; Step S304, set the light filtering link and impedance matching link in the optical circuit and circuit design, and output the spectral signal.

5. The optical fiber sensor based gas turbine engine temperature measurement method as recited in claim 4, wherein, The step S4 includes the following sub-steps: Step S401, convert the spectral signal into an electrical signal and perform filtering and noise suppression; Step S402, baseline correction of the spectral signal to eliminate background drift; Step S403, extract the spectral feature parameters corresponding to the monotonic change of temperature in the spectral signal, the spectral feature parameters include absorption intensity ratio and spectral line shape parameters, perform ratio calculation on the spectral feature parameters, and output the temperature-sensitive parameters; Step S404, limit the calculation amount and speed of the extraction process in step S403, the calculation amount and speed are less than the preset calculation amount threshold and speed threshold.

6. The optical fiber sensor based gas turbine engine temperature measurement method as recited in claim 5, wherein, The step S6 includes the following sub-steps: Step S601, transmit the corrected temperature data to the control end through the optical fiber; Step S602, real-time display, data storage and trend analysis of the corrected temperature data in the control end, and establish a temperature monitoring database; Step S603, when the corrected temperature data exceeds the preset threshold, trigger the alarm mechanism and generate alarm information; Step S604, transmit the alarm information to the engine control system.

7. The optical fiber sensor based gas turbine engine temperature measurement method as recited in claim 6, wherein, The material selection and preparation of the sensitive element in step S2 have the following requirements: The selected rare earth oxide sensitive material presents discrete absorption spectral lines in the visible light region and has significant thermal coupling energy level; The color-developing rare earth ion doping needs to maintain mechanical properties and thermal stability in the ceramic thermal barrier coating; The overall heat capacity of the sensitive element is lower than the preset heat capacity threshold.

8. The optical fiber sensor based gas turbine engine temperature measurement method as recited in claim 7, wherein, The extraction of spectral feature parameters in step S403 includes: The filtered and baseline-corrected spectral signals are analyzed in real time, and two preset specific wavelength band absorption intensity ratios are selected as temperature-sensitive characteristics, and background radiation noise is suppressed and the calculation process is optimized.

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