A method and system for fiber-optic temperature measurement based on multi-exponential decomposition of fluorescence decay curves

Abstract

The present application relates to the technical field of fluorescence lifetime temperature measurement, and particularly relates to a fiber temperature measurement method and system based on fluorescence decay curve multi-exponential decomposition, wherein a discrete data point set of a fluorescence signal decaying over time is obtained, polynomial fitting is performed on the discrete data point set to obtain a polynomial function, the polynomial function is decomposed into a multi-exponential decomposition result of a plurality of exponential functions superimposed, a fluorescence lifetime corresponding to an exponential component with the largest amplitude coefficient is selected as a characteristic fluorescence lifetime, and a temperature value corresponding to the characteristic fluorescence lifetime is obtained based on a pre-stored temperature mapping relationship of the characteristic fluorescence lifetime, so that through discrete data acquisition, polynomial fitting denoising, multi-exponential decomposition and characteristic fluorescence lifetime extraction, and in combination with the pre-stored temperature mapping relationship of the characteristic fluorescence lifetime, high-precision and high-stability temperature measurement in a complex environment is realized.

Description

Technical Field

[0001] This invention relates to the field of fluorescence lifetime thermometry, and in particular to an optical fiber thermometry method and system based on multi-exponential decomposition of fluorescence decay curves. Background Technology

[0002] Fluorescence lifetime thermometry is an important non-contact temperature measurement technology. Its core principle is based on the temperature-sensitive characteristics of fluorescent materials: the fluorescence intensity emitted by a specific fluorescent substance after excitation decays exponentially over time, and the time constant of the decay process (i.e., fluorescence lifetime τ) has a strictly single-valued functional relationship with temperature. By accurately measuring the fluorescence lifetime, the ambient temperature can be obtained. This technology has significant advantages such as strong electromagnetic interference resistance, fast response speed, and high spatial resolution, making it irreplaceable in scenarios with strong electromagnetic interference, such as hotspot temperature measurement in power equipment.

[0003] Currently, the mainstream methods for extracting fluorescence lifetime mainly include the least squares fitting method and the integral method. The least squares fitting method directly uses a single exponential or double exponential model to iteratively fit the collected discrete decay data. In ideal scenarios with high signal-to-noise ratio, it can obtain a certain measurement accuracy. The integral method solves the fluorescence lifetime by calculating the area ratio of the decay curve in different time windows, and has relatively strong noise resistance.

[0004] However, these existing technical solutions have a core drawback: they all directly process the raw, noisy discrete data and lack effective multi-exponential decomposition and principal component identification mechanisms. In actual power scenarios, fluorescent signals are easily affected by factors such as electromagnetic radiation from equipment and optical path loss, resulting in a decrease in signal-to-noise ratio. At the same time, multi-exponential decay phenomena caused by multiple luminescent centers or energy transfer are common in actual fluorescent materials. This makes it difficult for existing methods to effectively suppress noise interference and to stably separate the temperature-sensitive principal component in multi-exponential decay, ultimately leading to insufficient temperature measurement accuracy and repeatability. Summary of the Invention

[0005] The technical problem to be solved by the present invention is to provide an optical fiber temperature measurement method and system based on the multi-exponential decomposition of fluorescence decay curves, which can achieve high-precision and high-stability temperature measurement in complex environments.

[0006] To solve the above-mentioned technical problems, the first technical solution adopted by the present invention is as follows: A fiber optic temperature measurement method based on multi-exponential decomposition of fluorescence attenuation curves includes the following steps: S1. Obtain multiple discrete data points of the fluorescence signal that decays over time to obtain a set of discrete data points characterizing the fluorescence decay curve. S2. Perform polynomial fitting on the discrete data point set to obtain a polynomial function used to characterize the fluorescence decay curve; S3. Decompose the polynomial function into a superposition of multiple exponential functions to obtain a multi-exponential decomposition result used to describe the fluorescence decay curve; S4. Select the exponential component with the largest amplitude coefficient from the multi-exponential decomposition results, and take the fluorescence lifetime corresponding to the exponential component as the characteristic fluorescence lifetime of the fluorescence decay curve. S5. Based on the characteristic fluorescence lifetime and the pre-stored mapping relationship between the characteristic fluorescence lifetime and temperature, obtain the temperature value corresponding to the characteristic fluorescence lifetime.

[0007] The second technical solution adopted in this invention is: A fiber optic temperature measurement system based on the multi-exponential decomposition of fluorescence decay curves includes one or more processors and a memory. The memory stores a computer program, which, when executed by the processor, implements the aforementioned method.

[0008] The beneficial effects of this invention are as follows: This scheme first obtains a discrete data point set of fluorescence signals that decay over time. A polynomial function is obtained by fitting the discrete data point set with a polynomial. This polynomial function is then decomposed into a multi-exponential decomposition result of multiple exponential functions. The fluorescence lifetime corresponding to the exponential component with the largest amplitude coefficient is selected as the characteristic fluorescence lifetime. Based on the mapping relationship between the characteristic fluorescence lifetime and a pre-stored temperature, the temperature value corresponding to the characteristic fluorescence lifetime is obtained. This scheme does not directly process the original discrete fluorescence decay data but adds an intermediate step of polynomial fitting. By fitting the discrete data point set with a polynomial function, it can effectively smooth the random noise introduced by factors such as electromagnetic radiation and optical path loss in the original data, forming a continuous and stable decay model. This avoids noise directly interfering with the lifetime extraction process and solves the measurement result fluctuation problem caused by directly processing noisy data in existing technologies, significantly improving the stability and repeatability of temperature measurement. Simultaneously, this scheme decomposes the polynomial function into a superposition of multiple exponential functions, which is consistent with the multiple luminescence centers or... The physical nature of multi-exponential decay caused by energy transfer, compared to the shortcomings of existing technologies that struggle to separate multi-exponential components, allows this decomposition process to accurately analyze each lifetime component in the decay curve, providing a foundation for the accurate extraction of subsequent characteristic lifetimes and making the method applicable to more complex practical application scenarios. By selecting the fluorescence lifetime corresponding to the exponential component with the largest amplitude coefficient as the characteristic fluorescence lifetime, it ensures that the extracted lifetime parameter is the core component that dominates the fluorescence decay process and has the strongest temperature correlation. This selection logic is objectively quantified, avoiding errors caused by subjective selection of fitting models, and effectively eliminating interference from non-temperature-sensitive components, providing reliable core parameters for high-precision temperature inversion. The entire scheme deeply integrates data processing technology with the principle of fluorescence lifetime temperature measurement, ensuring both the rigor of mathematical processing and adherence to the physical laws of fluorescence decay. At the same time, temperature is solved through pre-stored mapping relationships, eliminating the need for complex real-time calculations, balancing measurement accuracy and temperature measurement efficiency, and meeting the stringent requirements of real-time performance and reliability in scenarios such as hotspot temperature measurement of power equipment. Attached Figure Description

[0009] Figure 1 This is a flowchart of the fiber optic temperature measurement method based on the multi-exponential decomposition of fluorescence attenuation curves according to the present invention. Figure 2 This is a graph showing the characteristic fluorescence lifetime versus temperature mapping relationship of the fiber optic thermometry method based on the multi-exponential decomposition of fluorescence decay curves of the present invention. Figure 3 This is a connection block diagram of the fiber optic temperature measurement system based on the multi-exponential decomposition of fluorescence attenuation curves according to the present invention. Label Explanation: 1. Processor; 2. Memory. Detailed Implementation

[0010] To explain in detail the technical content, objectives, and effects of the present invention, the following description is provided in conjunction with the embodiments and accompanying drawings.

[0011] Please refer to Figure 1 as well as Figure 2 The first technical solution adopted in this invention is: A fiber optic temperature measurement method based on multi-exponential decomposition of fluorescence attenuation curves includes the following steps: S1. Obtain multiple discrete data points of the fluorescence signal that decays over time to obtain a set of discrete data points characterizing the fluorescence decay curve. S2. Perform polynomial fitting on the discrete data point set to obtain a polynomial function used to characterize the fluorescence decay curve; S3. Decompose the polynomial function into a superposition of multiple exponential functions to obtain a multi-exponential decomposition result used to describe the fluorescence decay curve; S4. Select the exponential component with the largest amplitude coefficient from the multi-exponential decomposition results, and take the fluorescence lifetime corresponding to the exponential component as the characteristic fluorescence lifetime of the fluorescence decay curve. S5. Based on the characteristic fluorescence lifetime and the pre-stored mapping relationship between the characteristic fluorescence lifetime and temperature, obtain the temperature value corresponding to the characteristic fluorescence lifetime.

[0012] As can be seen from the above description, the beneficial effects of the present invention are as follows: This scheme first obtains a discrete data point set of fluorescence signals that decay over time. A polynomial function is obtained by fitting the discrete data point set with a polynomial. This polynomial function is then decomposed into a multi-exponential decomposition result of multiple exponential functions. The fluorescence lifetime corresponding to the exponential component with the largest amplitude coefficient is selected as the characteristic fluorescence lifetime. Based on the mapping relationship between the characteristic fluorescence lifetime and a pre-stored temperature, the temperature value corresponding to the characteristic fluorescence lifetime is obtained. This scheme does not directly process the original discrete fluorescence decay data but adds an intermediate step of polynomial fitting. By fitting the discrete data point set with a polynomial function, it can effectively smooth the random noise introduced by factors such as electromagnetic radiation and optical path loss in the original data, forming a continuous and stable decay model. This avoids noise directly interfering with the lifetime extraction process and solves the measurement result fluctuation problem caused by directly processing noisy data in existing technologies, significantly improving the stability and repeatability of temperature measurement. Simultaneously, this scheme decomposes the polynomial function into a superposition of multiple exponential functions, which is consistent with the multiple luminescence centers or... The physical nature of multi-exponential decay caused by energy transfer, compared to the shortcomings of existing technologies that struggle to separate multi-exponential components, allows this decomposition process to accurately analyze each lifetime component in the decay curve, providing a foundation for the accurate extraction of subsequent characteristic lifetimes and making the method applicable to more complex practical application scenarios. By selecting the fluorescence lifetime corresponding to the exponential component with the largest amplitude coefficient as the characteristic fluorescence lifetime, it ensures that the extracted lifetime parameter is the core component that dominates the fluorescence decay process and has the strongest temperature correlation. This selection logic is objectively quantified, avoiding errors caused by subjective selection of fitting models, and effectively eliminating interference from non-temperature-sensitive components, providing reliable core parameters for high-precision temperature inversion. The entire scheme deeply integrates data processing technology with the principle of fluorescence lifetime temperature measurement, ensuring both the rigor of mathematical processing and adherence to the physical laws of fluorescence decay. At the same time, temperature is solved through pre-stored mapping relationships, eliminating the need for complex real-time calculations, balancing measurement accuracy and temperature measurement efficiency, and meeting the stringent requirements of real-time performance and reliability in scenarios such as hotspot temperature measurement of power equipment.

[0013] Furthermore, in step S1, the specific process of obtaining multiple discrete data points of the fluorescence signal that decays over time is as follows: A fluorescent material at the end of an optical fiber is excited using a pulsed light source, and the fluorescence signal, which decays over time, is acquired via a photodetector and a data acquisition circuit. discrete data points Where i = 1, 2, ..., N, For the i-th sampling time point, The fluorescence intensity corresponds to the sampling time point.

[0014] As can be seen from the above description, the signal acquisition architecture of pulsed light source-fiber optic cable-photodetector can ensure the stability and consistency of fluorescence signal excitation and reception, providing a high-quality raw data foundation for subsequent data processing and avoiding modeling errors caused by improper acquisition methods. The standardized format of the acquired discrete data points can directly serve the subsequent polynomial fitting process, achieving seamless connection between signal acquisition and data modeling, and improving the engineering feasibility of the entire technical solution.

[0015] Furthermore, in step S2, the expression for the polynomial function is: ; in, For polynomial coefficients, Let be the order of each term in the polynomial. It is the largest order of the polynomial and satisfies , , For time.

[0016] As can be seen from the above description, polynomial functions, as a classic smoothing modeling tool, can effectively suppress random noise in the original collected data, form a continuous and smooth decay model, and solve the problem of noise interference in the original data from the source.

[0017] Furthermore, in step S3, the expression for the multi-exponential decomposition result is: ; in, The number of exponential components. It is a natural constant. =2.718281828459... For the first The amplitude coefficient of each exponential component, For the first The decay coefficient of each exponential component.

[0018] As can be seen from the above description, by using the exponential approximation technique, an efficient numerical decomposition method, the polynomial model can be reduced to a multi-exponential superposition form that conforms to the physical nature of fluorescence decay. This can accurately separate multiple lifetime components and solve the problem that existing technologies cannot handle multi-exponential decay.

[0019] Furthermore, in step S3, the fluorescence lifetime corresponding to each exponential component satisfies the following condition: ; in For fluorescence lifetime, For the first The decay coefficient of each exponential component.

[0020] As described above, converting the abstract attenuation coefficient obtained from decomposition into a fluorescence lifetime parameter with clear physical meaning establishes a crucial bridge between data processing and temperature measurement, ensuring that the data processing results can directly serve the temperature measurement target. The conversion relationship is simple and direct, with high computational efficiency, and does not require complex mapping algorithms, ensuring that the data processing results can be quickly converted into temperature measurement parameters, thus improving the efficiency of the entire temperature measurement process.

[0021] Furthermore, in step S4, the specific process of selecting the exponential component with the largest amplitude coefficient is as follows: By comparing the amplitude coefficients of all exponential components in the multi-exponential decomposition results, the exponential component with the largest amplitude coefficient is selected, and the fluorescence lifetime corresponding to the exponential component is determined as the characteristic fluorescence lifetime of the fluorescence decay curve.

[0022] As can be seen from the above description, by comparing the amplitude coefficients to select the exponential components, the errors caused by the subjective selection of fitting models in the existing technology are avoided. The objective and quantitative selection rules significantly improve the reliability and consistency of the feature lifetime. The selected exponential components have the strongest correlation with temperature and can effectively suppress the interference of non-temperature-sensitive components, ensuring that the feature extraction results directly serve the high-precision temperature measurement needs and further improve the temperature measurement accuracy.

[0023] Furthermore, in step S5, the pre-stored mapping relationship between characteristic fluorescence lifetime and temperature is established in the following way: At least 11 temperature points with equal distances are selected evenly within the temperature measurement range. The characteristic fluorescence lifetime corresponding to each temperature point is obtained through experimental calibration, thus forming a mapping relationship between the characteristic fluorescence lifetime and temperature.

[0024] As can be seen from the above description, the calibration scheme using multiple calibration points at equal intervals ensures that the mapping relationship can fully cover the entire temperature measurement range, providing sufficient sample data for subsequent segmented fitting and ensuring the accuracy of temperature conversion. Establishing the mapping relationship through experimental calibration can effectively offset interference factors in practical applications such as individual differences in fluorescent materials and optical path loss, improving the practicality and robustness of the system and enabling it to adapt to different application environments.

[0025] Furthermore, the temperature measurement range is 0℃ to +200℃.

[0026] Furthermore, the mapping relationship is obtained by segmented lookup table. All experimental calibration points are divided into multiple segments, and each segment is fitted with a straight line. For any measured fluorescence lifetime, the segment to which it belongs is first determined, and then the corresponding temperature value is calculated through the segment equation.

[0027] As can be seen from the above description, replacing complex polynomial fitting with piecewise linear fitting can significantly improve temperature conversion efficiency while ensuring temperature measurement accuracy, thus meeting the needs of real-time temperature measurement scenarios. The lookup table method has low hardware computing resource requirements, making it easy to implement in resource-limited devices such as embedded systems. It solves the resource consumption problem of complex algorithms in engineering applications and expands the application scenarios of the technology.

[0028] Please refer to Figure 3 The second technical solution adopted in this invention is: A fiber optic temperature measurement system based on the multi-exponential decomposition of fluorescence decay curves includes one or more processors 1 and a memory 2. The memory 2 stores a computer program, which, when executed by the processor 1, implements the above-described method.

[0029] As can be seen from the above description, the beneficial effects of the present invention are as follows: The processor 1 executes computer programs to integrate algorithms such as polynomial fitting, multi-exponential decomposition, and piecewise table lookup with the fluorescence temperature measurement process into an automated process, ensuring the consistency and stability of the technology implementation and avoiding errors caused by manual operation. The system has a simple structure, requiring only the processor 1 and memory 2 to achieve the integration of multiple technologies without the need for complex dedicated hardware, reducing the engineering cost of technology integration, facilitating integration into existing power equipment monitoring systems, and having good compatibility and scalability.

[0030] Please refer to Figure 1 and Figure 2 As shown, Embodiment 1 of the present invention is as follows: Please refer to Figure 1 A fiber optic temperature measurement method based on multi-exponential decomposition of fluorescence decay curves includes the following steps: S1. Obtain multiple discrete data points of the fluorescence signal that decays over time to obtain a set of discrete data points characterizing the fluorescence decay curve. In step S1, the specific process of obtaining multiple discrete data points of the fluorescence signal that decays over time is as follows: A fluorescent material at the end of an optical fiber is excited using a pulsed light source, and the fluorescence signal, which decays over time, is acquired via a photodetector and a data acquisition circuit. discrete data points Where i = 1, 2, ..., N, For the i-th sampling time point, The fluorescence intensity corresponds to the sampling time point.

[0031] S2. Perform polynomial fitting on the discrete data point set to obtain a polynomial function used to characterize the fluorescence decay curve; In step S2, the expression for the polynomial function is: ; in, For polynomial coefficients, Let be the order of each term in the polynomial. It is the largest order of the polynomial and satisfies , , For time.

[0032] The order M of the polynomial satisfies the following condition: When constructing the polynomial, the value of M should be chosen so that the polynomial can both capture the decay trend and smooth out noise. When the value of M is greater than 10, it basically approximates the decay trend of discrete data and eliminates most of the noise. Generally, processing N=100~200 sampling points can completely capture the decay trend and smooth out noise.

[0033] S3. Decompose the polynomial function into a superposition of multiple exponential functions to obtain a multi-exponential decomposition result used to describe the fluorescence decay curve; In step S3, the expression for the multi-exponential decomposition result is: ; in, The number of exponential components. It is a natural constant. =2.718281828459... For the first The amplitude coefficient of each exponential component, For the first The decay coefficient of each exponential component.

[0034] In step S3, the fluorescence lifetime corresponding to each exponential component satisfies the following condition: ; in For fluorescence lifetime, For the first The decay coefficient of each exponential component.

[0035] S4. Select the exponential component with the largest amplitude coefficient from the multi-exponential decomposition results, and take the fluorescence lifetime corresponding to the exponential component as the characteristic fluorescence lifetime of the fluorescence decay curve. In step S4, the specific process of selecting the exponential component with the largest amplitude coefficient is as follows: By comparing the amplitude coefficients of all exponential components in the multi-exponential decomposition results, the exponential component with the largest amplitude coefficient is selected, and the fluorescence lifetime corresponding to the exponential component is determined as the characteristic fluorescence lifetime of the fluorescence decay curve.

[0036] S5. Based on the characteristic fluorescence lifetime and the pre-stored mapping relationship between the characteristic fluorescence lifetime and temperature, obtain the temperature value corresponding to the characteristic fluorescence lifetime.

[0037] In step S5, the pre-stored mapping relationship between characteristic fluorescence lifetime and temperature is established in the following way: At least 11 temperature points with equal distances were uniformly selected within the temperature measurement range (0℃~+200℃). The characteristic fluorescence lifetime corresponding to each temperature point was obtained through experimental calibration, thus forming a mapping relationship between the characteristic fluorescence lifetime and temperature.

[0038] The mapping relationship is obtained by segmented lookup table. All experimental calibration points are divided into multiple segments, and each segment is fitted with a straight line. For any measured fluorescence lifetime, the segment to which it belongs is first determined, and then the corresponding temperature value is calculated through the segment equation.

[0039] The specific implementation steps of the fiber optic temperature measurement method based on the multi-exponential decomposition of fluorescence attenuation curves described above are as follows: First, implement data collection: A fluorescent material at the end of an optical fiber is excited using a pulsed light source, and N discrete data points of the fluorescence signal decaying over time are acquired via a photodetector and a data acquisition circuit. Where i = 1, 2, ..., N, For the i-th sampling time point, The fluorescence intensity corresponds to the sampling time point.

[0040] Secondly, polynomial modeling is performed: For N discrete data points Perform polynomial fitting to construct an M-order polynomial function. This allows the polynomial function to best approximate the discrete data points. The expression is: ; in, For polynomial coefficients, Let be the order of each term in the polynomial. It is the largest order of the polynomial and satisfies , , For time.

[0041] The order M of the polynomial satisfies the following condition: When constructing the polynomial, the value of M should be chosen so that the polynomial can both capture the decay trend and smooth out noise. When the value of M is greater than 10, it basically approximates the decay trend of discrete data and eliminates most of the noise. Generally, processing N=100~200 sampling points can completely capture the decay trend and smooth out noise.

[0042] Third, perform exponential term decomposition and superposition: decompose and superimpose the polynomial function obtained in the above steps. The result of the multi-exponential decomposition is expressed as a superposition of multiple exponential functions: ; or ; in, The number of exponential components. It is a natural constant. =2.718281828459... For the first The amplitude coefficient of each exponential component, For the first The decay coefficient of each exponential component.

[0043] The fluorescence lifetime corresponding to each exponential component satisfies the following condition: ; in For fluorescence lifetime, For the first The decay coefficient of each exponential component.

[0044] Fourth, characteristic fluorescence lifetime extract: In the algebraic sum of L exponential functions (exponential components), each exponential function corresponds to an amplitude coefficient. and fluorescence lifetime Compare the amplitude coefficients of each exponential component. Select the component with the largest amplitude coefficient. The corresponding fluorescence lifetime The characteristic fluorescence lifetime of the fluorescence decay curve Because the fluorescence decay curve is a quasi-exponential curve, analysis of experimental data shows that the component with the largest amplitude coefficient... It accounts for about 60% of all amplitudes; therefore, its corresponding single exponential curve and corresponding... It is easy to identify.

[0045] The following method uses a 10th-order polynomial to fit 142 discrete data points corresponding to 11 temperatures (0°C, 20°C, 40°C, 60°C, 80°C, 100°C, 120°C, 140°C, 160°C, 180°C, and 200°C), and then approximates this polynomial using the superposition of five exponential functions. The 10th-order polynomial fitting is then used to obtain the polynomial coefficients. arrive (From lower to higher degree terms). Five exponents are superimposed and fitted to obtain... arrive There are a total of 5 exponential function coefficients and 5 exponential decay rates. (lambda), and calculate the corresponding 5 time constants. and characteristic fluorescence lifetime .

[0046] The specific data is as follows: 1. At 0 degrees Celsius: Table 1 shows the discrete data fitted by a 10th-order polynomial:

[0047] Table 1 The data obtained by fitting the five indices together are shown in Table 2:

[0048] Table 2 2. At 20 degrees Celsius: Table 3 shows the discrete data fitted by a 10th-order polynomial:

[0049] Table 3 The data obtained by fitting the five indices together is shown in Table 4:

[0050] Table 4 3. At 40 degrees Celsius: Table 5 shows the discrete data fitted by the 10th-order polynomial:

[0051] Table 5 The data obtained by fitting the five indices together are shown in Table 6:

[0052] Table 6 4. At 60 degrees Celsius: Table 7 shows the discrete data fitted by a 10th-order polynomial:

[0053] Table 7 The data obtained by fitting the five indices together are shown in Table 8:

[0054] Table 8 5. At 80 degrees: Table 9 shows the discrete data fitted by a 10th-order polynomial:

[0055] Table 9 The data obtained by fitting the five indices together are shown in Table 10:

[0056] Table 10 6. At 100 degrees: Table 11 shows the discrete data fitted by a 10th-order polynomial:

[0057] Table 11 The data obtained by fitting the five indices together are shown in Table 12:

[0058] Table 12 7. At 120 degrees: Table 13 shows the discrete data fitted by a 10th-order polynomial:

[0059] Table 13 The data obtained by fitting the five indices together are shown in Table 14:

[0060] Table 14 8. At 140 degrees: Table 15 shows the discrete data fitted by a 10th-order polynomial:

[0061] Table 15 The data obtained by fitting the five indices together are shown in Table 16:

[0062] Table 16 9. At 160 degrees: Table 17 shows the discrete data fitted by a 10th-order polynomial:

[0063] Table 17 The data obtained by fitting the five indices together is shown in Table 18:

[0064] Table 18 10. At 180 degrees: Table 19 shows the discrete data fitted by a 10th-order polynomial:

[0065] Table 19 The data obtained by fitting the five indices together is shown in Table 20:

[0066] Table 20 11. At 200 degrees: Table 21 shows the discrete data fitted by the 10th-order polynomial:

[0067] Table 21 The data obtained by fitting the five indices together is shown in Table 22:

[0068] Table 22 Characteristic fluorescence lifetime The trend of temperature variation is shown in Table 23 below:

[0069] Table 23 As shown in Table 23, the characteristic fluorescence lifetime decreases with increasing temperature. The system exhibits a monotonically decreasing rate of decay, which aligns with physical expectations.

[0070] Fifth, temperature calibration and output: Based on a pre-defined series of equidistantly distributed temperature points, the corresponding characteristic fluorescence lifetimes were obtained through experimental calibration. With temperature mapping relationship The system calculates and outputs the current temperature value. To simplify the software's processing, this mapping relationship does not need to be fitted into a polynomial calculation formula; any characteristic fluorescence lifetime can be obtained through piecewise table lookup. With temperature The conversion.

[0071] Taking Y2SO2:Eu fluorescent material with a temperature range of 0℃ to +200℃ as an example, 11 temperature measurement points were uniformly selected for temperature calibration, and the characteristic fluorescence lifetime was determined. With temperature As shown in Table 1.

[0072]

[0073] Characteristic fluorescence lifetime With temperature mapping relationship like Figure 2 The 11 temperature measurement points were divided into 10 segments, each represented by a straight line, forming a broken line; for any fluorescence lifetime... First, determine which straight line segment it belongs to, then calculate the corresponding temperature value, thereby achieving any characteristic fluorescence lifetime. With temperature The conversion.

[0074] Please refer to Figure 3 Embodiment two of the present invention is as follows: A fiber optic temperature measurement system based on the multi-exponential decomposition of fluorescence decay curves includes one or more processors 1 and a memory 2. The memory 2 stores a computer program, which, when executed by the processor 1, implements the method in Embodiment 1.

[0075] In summary, the fiber optic temperature measurement method and system based on multi-exponential decomposition of fluorescence decay curves provided by this invention first acquires a set of discrete data points of fluorescence signals decaying over time. Then, a polynomial function is obtained by polynomial fitting of the discrete data point set. This polynomial function is decomposed into a multi-exponential decomposition result of multiple exponential functions. The fluorescence lifetime corresponding to the exponential component with the largest amplitude coefficient is selected as the characteristic fluorescence lifetime. Based on the mapping relationship between the characteristic fluorescence lifetime and a pre-stored temperature, the temperature value corresponding to the characteristic fluorescence lifetime is obtained. This scheme does not directly process the original discrete fluorescence decay data but adds an intermediate step of polynomial fitting. By fitting the discrete data point set with a polynomial function, it can effectively smooth the random noise introduced by factors such as electromagnetic radiation and optical path loss in the original data, forming a continuous and stable decay model. This avoids noise directly interfering with the lifetime extraction process and solves the problem of measurement result fluctuations caused by directly processing noisy data in existing technologies, significantly improving the stability and repeatability of temperature measurement. Furthermore, this scheme decomposes the polynomial function into a superposition of multiple exponential functions. This decomposition process, which addresses the multi-exponential decay inherent in real-world fluorescent materials due to multiple luminescent centers or energy transfer, overcomes the limitations of existing technologies that struggle to separate multi-exponential components. It precisely analyzes each lifetime component in the decay curve, providing a foundation for accurate extraction of characteristic lifetimes and making the method applicable to more complex real-world applications. By selecting the fluorescence lifetime corresponding to the exponential component with the largest amplitude coefficient as the characteristic fluorescence lifetime, it ensures that the extracted lifetime parameter is the core component that dominates the fluorescence decay process and has the strongest temperature correlation. This objective and quantifiable selection logic avoids errors caused by subjective model selection and effectively eliminates interference from non-temperature-sensitive components, providing reliable core parameters for high-precision temperature inversion. The entire scheme deeply integrates data processing technology with the principle of fluorescence lifetime thermometry, ensuring both mathematical rigor and adherence to the physical laws of fluorescence decay. Furthermore, it achieves temperature calculation through pre-stored mapping relationships, eliminating the need for complex real-time calculations and balancing measurement accuracy and efficiency. This meets the stringent requirements for real-time performance and reliability in scenarios such as hotspot temperature measurement in power equipment.

[0076] The above description is merely an embodiment of the present invention and does not limit the patent scope of the present invention. Any equivalent modifications made based on the content of the present invention specification and drawings, or direct or indirect applications in related technical fields, are similarly included within the patent protection scope of the present invention.

Claims

1. A fiber optic temperature measurement method based on multi-exponential decomposition of fluorescence decay curves, characterized in that, Includes the following steps: S1. Obtain multiple discrete data points of the fluorescence signal that decays over time to obtain a set of discrete data points characterizing the fluorescence decay curve. S2. Perform polynomial fitting on the discrete data point set to obtain a polynomial function used to characterize the fluorescence decay curve; S3. Decompose the polynomial function into a superposition of multiple exponential functions to obtain a multi-exponential decomposition result used to describe the fluorescence decay curve; S4. Select the exponential component with the largest amplitude coefficient from the multi-exponential decomposition results, and take the fluorescence lifetime corresponding to the exponential component as the characteristic fluorescence lifetime of the fluorescence decay curve. S5. Based on the characteristic fluorescence lifetime and the pre-stored mapping relationship between the characteristic fluorescence lifetime and temperature, obtain the temperature value corresponding to the characteristic fluorescence lifetime.

2. The fiber optic temperature measurement method based on multi-exponential decomposition of fluorescence decay curves according to claim 1, characterized in that, In step S1, the specific process of obtaining multiple discrete data points of the fluorescence signal that decays over time is as follows: A fluorescent material at the end of an optical fiber is excited using a pulsed light source, and the fluorescence signal, which decays over time, is acquired via a photodetector and a data acquisition circuit. discrete data points Where i = 1, 2, ..., N, For the i-th sampling time point, The fluorescence intensity corresponds to the sampling time point.

3. The fiber optic temperature measurement method based on multi-exponential decomposition of fluorescence decay curves according to claim 2, characterized in that, In step S2, the expression for the polynomial function is: ； in, For polynomial coefficients, Let be the order of each term in the polynomial. It is the largest order of the polynomial and satisfies , , For time.

4. The fiber optic temperature measurement method based on multi-exponential decomposition of fluorescence decay curves according to claim 1, characterized in that, In step S3, the expression for the multi-exponential decomposition result is: ； in, The number of exponential components. It is a natural constant. =2.718281828459... For the first The amplitude coefficient of each exponential component, For the first The decay coefficient of each exponential component.

5. The fiber optic temperature measurement method based on multi-exponential decomposition of fluorescence decay curves according to claim 4, characterized in that, In step S3, the fluorescence lifetime corresponding to each exponential component satisfies the following condition: ； in For fluorescence lifetime, For the first The decay coefficient of each exponential component.

6. The fiber optic temperature measurement method based on multi-exponential decomposition of fluorescence decay curves according to claim 1, characterized in that, In step S4, the specific process of selecting the exponential component with the largest amplitude coefficient is as follows: By comparing the amplitude coefficients of all exponential components in the multi-exponential decomposition results, the exponential component with the largest amplitude coefficient is selected, and the fluorescence lifetime corresponding to the exponential component is determined as the characteristic fluorescence lifetime of the fluorescence decay curve.

7. The fiber optic temperature measurement method based on multi-exponential decomposition of fluorescence attenuation curves according to claim 1, characterized in that, In step S5, the pre-stored mapping relationship between characteristic fluorescence lifetime and temperature is established in the following way: At least 11 temperature points with equal distances are selected evenly within the temperature measurement range. The characteristic fluorescence lifetime corresponding to each temperature point is obtained through experimental calibration, thus forming a mapping relationship between the characteristic fluorescence lifetime and temperature.

8. The fiber optic temperature measurement method based on multi-exponential decomposition of fluorescence decay curves according to claim 7, characterized in that, The temperature measurement range is 0℃ to +200℃.

9. The fiber optic temperature measurement method based on multi-exponential decomposition of fluorescence decay curves according to claim 7, characterized in that, The mapping relationship is obtained by segmented lookup table. All experimental calibration points are divided into multiple segments, and each segment is fitted with a straight line. For any measured fluorescence lifetime, the segment to which it belongs is first determined, and then the corresponding temperature value is calculated through the segment equation.

10. A fiber optic temperature measurement system based on multi-exponential decomposition of fluorescence decay curves, characterized in that, It includes one or more processors and a memory, the memory storing a computer program that, when executed by the processor, implements the method of any one of claims 1 to 9.

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