Method and device for analyzing sensing performance of optical gas sensor coated with micro-nanofiber on surface

Abstract

The invention provides a sensing performance analysis method and device for an optical gas sensor coated with a micro-nano optical fiber on the surface, and the method comprises the steps: building a relation between input light intensity and light intensity after passing through an optical fiber loop cavity for one time, introducing extra loss, and obtaining a ring-down time variation; analyzing the influence of temperature and wavelength on the refractive index of the surrounding medium; the reaction capacity of the material to the gas is determined through microcosmic gas adsorption characteristic simulation and optical characteristic simulation, and various gases do not need to be introduced for detection again and again, so that time and resources are saved. In combination with optical characteristics and multi-physical field simulation analysis, a theoretical basis can be provided for the optical gas-sensitive sensing regulation and control performance of the micro-nano optical fiber coating material, and the ring-down time is optimized in an optical fiber ring-down cavity ring-down gas detection technology.

Description

Technical Field

[0001] The invention relates to electrical engineering, and in particular to a method and device for analyzing the performance of optical gas-sensitive sensors coated with micro-nano optical fibers on the surface. Background Art

[0002] In recent years, gas-insulated switchgear has been rapidly promoted and applied in my country. In particular, with the construction and transformation of urban power grids, rail transit, and large industrial and mining enterprises in my country, new and higher requirements for switchgear such as miniaturization, intelligence, maintenance-free, and full working conditions have been put forward. The demand for high-performance and high-quality inflatable cabinets in China is becoming more and more intense. Once a gas-insulated device fails, the fully enclosed structure of the device itself will make fault location and maintenance very difficult. Optical fiber sensing has the advantages of intrinsic safety, anti-electromagnetic interference, and multiplexing. As an ideal device-built-in distributed real-time fault monitoring method, it has been studied and applied to power equipment such as gas-insulated switchgear, ring network cabinets, and transformers. Micro-nano optical fiber is a new type of micro-nano device with a diameter of sub-wavelength magnitude. Its transmission light wave can break through the traditional sensing limit and propagate axially along the surface of the optical fiber in the form of evanescent field. It is extremely sensitive to changes in the optical properties of the surrounding medium. Therefore, the surface coating of gas-sensitive materials can enhance the optical gas-sensitive sensing capability of micro-nano optical fiber. By detecting the changes in the optical signal before and after gas adsorption, high-sensitivity gas detection based on micro-nano optical fiber optical gas-sensitive sensing can be achieved, providing a new idea for built-in gas sensing. The selection of gas-sensitive materials is the key to micro-nano fiber optic sensing gas detection technology. In terms of theoretical research, the surface-coated micro-nano fiber optic sensing mechanism is currently explained only by constructing the relationship between the optical properties of micro-nano fiber optic coating materials and the transmission properties of micro-nano fiber optics. There are few studies that deeply analyze how gas adsorption affects the optical properties of coating materials, which makes it difficult to provide guidance for the selection of coating materials. Summary of the invention

[0003] The purpose of the present invention is to address the deficiencies of the above-mentioned prior art and provide a method and device for analyzing the performance of optical gas sensing of surface-coated micro-nano optical fibers, to provide a theoretical basis for regulating the performance of optical gas sensing of micro-nano optical fiber coating materials, and to optimize the ring-down time in the fiber ring cavity ring-down gas detection technology.

[0004] To achieve the above object, the present invention adopts the following technical solutions: The present invention provides a method for analyzing the performance of surface-coated micro-nano optical fiber gas sensing, comprising the following steps: S1. Establish the relationship between the input light intensity and the light intensity after passing through the fiber loop cavity once, introduce additional loss, and obtain the ring-down time variation; S2. Analyze the effects of temperature and wavelength on the refractive index of the surrounding medium.

[0005] Further, in S1, the input light intensity The light intensity after passing through the fiber loop cavity once The relationship between them is: ; in, is the speed of light in vacuum; is the inherent loss of the system, ; is the optical fiber absorption coefficient; is the insertion loss of each component; is the optical coupling loss; is the optical path of the fiber loop cavity; is the core refractive index; For time; When the light intensity after the fiber loop cavity is Attenuation to input light intensity of The time required is the ring-down time , ; In actual measurement situations, when the system detects gas, it will be affected by external actions on the optical fiber sensor, which will introduce additional losses. , the ring-down time becomes: ; The change in ring-down time is: ; in, is the change in ring-down time; It can be seen that the refractive index of the surrounding medium has the most significant impact on the optical fiber sensor and is also the additional loss The main cause.

[0006] Furthermore, in S2, the effect of temperature on the refractive index of the surrounding medium is: The expressions for medium density and optical properties and temperature are: ; in, is the refractive index of the surrounding medium; is temperature; is the medium density; is the refractive index coefficient; Since temperature changes will cause the refractive index of the surrounding medium to change, thus causing the ring-down time to change, then: ; Right now, ;in, is the additional loss due to temperature.

[0007] Further, Perform denoising optimization processing to obtain the objective function for: ; in, For the The measured signal of the secondary decomposed initial signal; is a variable; For the Second decomposition of the initial signal into Gaussian white noise; is the number of times the initial signal is decomposed; Introducing the equality constraint matrix , then the denoised signal for: ; in, is a positive parameter; is the step size parameter; is the projection vector; ,Right now H = [ H 1 , H 2 , … H r ] , Yes = ∑ i = 1 r H i a i = b ; Independent Updates , when updating After the stage: ; ; but, .

[0008] Furthermore, in S2, the wavelength variation relationship is: ; in, is the central wavelength of the incident signal; is the sensitivity coefficient; is the additional loss under wavelength variation; When optical signals of different wavelengths are transmitted in optical fibers, the transmission performance of the signals is optimized: ; in, is the grating period; is the signal value corresponding to different wavelengths; is a fixed value; for The optical fiber absorption coefficient of a gas at a specific wavelength; is the optical fiber absorption coefficient at a specific wavelength; The relationship between the absorption coefficient and the gas concentration is: d N ( l ) = S ⋅ c [ N ] ( l ) ; in, is the cross-sectional area of ​​the absorption surface; c [ N ] ( l ) for Gas concentration; but: L ( l ) = S ⋅ x F ( l ) ( c [ 1 ] ( l ) + c [ 2 ] ( l ) + ⋯ c [ N ] ( l ) ) ; In order to avoid the error caused by the interference signal, the sample data residual is calculated as: ; in, is the number of training samples; is the ideal output value; is the actual output value; ; ; in, For Update After the stage The particle velocity of each particle; For the The position of a particle; is a constant.

[0009] Among them, a particle refers to a basic search unit in the algorithm, representing a potential solution in the solution space, and performs targeted optimization on the final gas detection data to avoid errors caused by interference signals; Update to The solution is in After the first iteration, update the particle position and velocity to enter the Iterates and updates the individual and global optimal solutions simultaneously.

[0010] Furthermore, a surface-coated micro-nano optical fiber optical gas sensing performance control device is implemented by the surface-coated micro-nano optical fiber optical gas sensing performance analysis method, comprising: Function signal generator 1: generates a specific pulse signal to modulate the laser and drive the laser to output laser of a specific wavelength band; Laser 2: emits laser signals of a specific wavelength; Isolator 3: ensures that the optical signal can be transmitted in one direction to avoid interference caused by the light source; The first coupler 501 and the second coupler 502 are used to realize optical signal transmission and redistribution, with a splitting ratio of 90:10; Photodetector 6: converts optical signals into electrical signals; Oscilloscope 7: Displays the electrical signal output by the detector and processes and analyzes it on the PC.

[0011] Furthermore, the function signal generator 1 sends out a periodic pulse signal, which outputs a corresponding pulse waveform optical signal after passing through the laser 2, and then passes through the isolator 3 to ensure that the optical signal is not interfered; The optical signal is input from the low splitting ratio end of the first coupler 501, and then output from the low splitting ratio end of the second coupler 502 to the photodetector 6 after passing through the gas chamber 8; The optical signal is output from the high splitting ratio end of the second coupler 502 to the optical fiber loop cavity 9, forming a complete cycle; The photodetector 6 converts the optical signal at the low splitting ratio end into an electrical signal, and finally displays the waveform through the oscilloscope 7. The signal transmission in the oscilloscope 7 is processed through the PC end, and the obtained waveform data is analyzed and optimized.

[0012] The beneficial effects of the present invention are as follows: the material's ability to react to gas is determined by simulating microscopic gas adsorption characteristics and optical characteristics, without the need to repeatedly introduce various gases for detection, saving time and resources. Combining optical characteristics with multi-physical field simulation analysis can provide a theoretical basis for the optical gas-sensitive sensing control performance of micro-nano optical fiber coating materials, and in the fiber ring cavity ring-down gas detection technology, the ring-down time is optimized. At the same time, this method can quickly explore the material's ability to act on reference gases, provide a reference for the screening of coating materials, and has a wide range of practical application value. BRIEF DESCRIPTION OF THE DRAWINGS

[0013] Figure 1 A schematic diagram of a surface-coated micro-nano optical fiber optical gas sensing performance analysis device; Figure 2 It is the fitting diagram of ring-down time and SO2 concentration curve; Figure 3 Refractive index of graphene after adsorbing SO2, CO, CF4, SOF2, and SO2F2. DETAILED DESCRIPTION

[0014] In order to make the purpose, technical solution and advantages of the present invention more clearly understood, the present invention is further described in detail below in conjunction with the accompanying drawings. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not used to limit the present invention.

[0015] A method for analyzing the performance of surface-coated micro-nano optical fiber gas sensing, comprising the following steps: S1. Establish the relationship between the input light intensity and the light intensity after passing through the fiber loop cavity once, introduce additional loss, and obtain the ring-down time variation; S2. Analyze the effects of temperature and wavelength on the refractive index of the surrounding medium.

[0016] In S1, the input light intensity The light intensity after passing through the fiber loop cavity once The relationship between them is: ; in, is the speed of light in vacuum; is the inherent loss of the system, ; is the optical fiber absorption coefficient; is the insertion loss of each component; is the optical coupling loss; is the optical path of the fiber loop cavity; is the core refractive index; For time; When the light intensity after the fiber loop cavity is Attenuation to input light intensity of The time required is the ring-down time , ; In actual measurement situations, when the system detects gas, it will be affected by external actions on the optical fiber sensor, which will introduce additional losses. , the ring-down time becomes: ; The change in ring-down time is: ; in, is the change in ring-down time; It can be seen that the refractive index of the surrounding medium has the most significant impact on the optical fiber sensor and is also the additional loss The main cause.

[0017] In S2, the effect of temperature on the refractive index of the surrounding medium is: The expressions for medium density and optical properties and temperature are: ; in, is the refractive index of the surrounding medium; is temperature; is the medium density; is the refractive index coefficient; Since temperature changes will cause the refractive index of the surrounding medium to change, thus causing the ring-down time to change, then: ; Right now, ;in, is the additional loss due to temperature.

[0018] right Perform denoising optimization processing to obtain the objective function for: ; in, For the The measured signal of the secondary decomposed initial signal; is a variable; For the Second decomposition of the initial signal into Gaussian white noise; is the number of times the initial signal is decomposed; Introducing the equality constraint matrix , then the denoised signal for: ; in, is a positive parameter; is the step size parameter; is the projection vector; , H = [ H 1 , H 2 , … H r ] , H a = ∑ i = 1 r H i a i = b ; Independent Updates , when updating After the stage: ; ; but, .

[0019] In S2, the wavelength variation relationship is: ; in, is the central wavelength of the incident signal; is the sensitivity coefficient; is the additional loss under wavelength variation; When optical signals of different wavelengths are transmitted in optical fibers, the transmission performance of the signals is optimized: ; in, is the grating period; is the signal value corresponding to different wavelengths; is a fixed value; for The optical fiber absorption coefficient of a gas at a specific wavelength; is the optical fiber absorption coefficient at a specific wavelength; The relationship between the absorption coefficient and the gas concentration is: d N ( l ) = S ⋅ c [ N ] ( l ) ; in, is the cross-sectional area of ​​the absorption surface; c [ N ] ( l ) for Gas concentration; but: L ( l ) = S ⋅ x F ( l ) ( c [ 1 ] ( l ) + c [ 2 ] ( l ) + ⋯ c [ N ] ( l ) ) ; In order to avoid the error caused by the interference signal, the sample data residual is calculated as: ; in, is the number of training samples; is the ideal output value; is the actual output value; ; ; in, For Update After the stage The particle velocity of each particle; For the The position of a particle; is a constant.

[0020] See also Figure 1 , a surface coated micro-nano optical fiber optical gas sensing performance control device, which is realized by the surface coated micro-nano optical fiber optical gas sensing performance analysis method, including: Function signal generator 1: generates a specific pulse signal to modulate the laser and drive the laser to output laser of a specific wavelength band; Laser 2: emits laser signals of a specific wavelength; Isolator 3: ensures that the optical signal can be transmitted in one direction to avoid interference caused by the light source; The first coupler 501 and the second coupler 502 are used to realize optical signal transmission and redistribution, with a splitting ratio of 90:10; Photodetector 6: converts optical signals into electrical signals; Oscilloscope 7: Displays the electrical signal output by the detector and processes and analyzes it on the PC.

[0021] The function signal generator 1 sends out a periodic pulse signal, which outputs a corresponding pulse waveform optical signal after passing through the laser 2, and then passes through the isolator 3 to ensure that the optical signal is not interfered; The optical signal is input from the low splitting ratio end of the first coupler 501, and then output from the low splitting ratio end of the second coupler 502 to the photodetector 6 after passing through the gas chamber 8; The optical signal is output from the high splitting ratio end of the second coupler 502 to the optical fiber loop cavity 9, forming a complete cycle; The photodetector 6 converts the optical signal at the low splitting ratio end into an electrical signal, and finally displays the waveform through the oscilloscope 7. The signal transmission in the oscilloscope 7 is processed through the PC end, and the obtained waveform data is analyzed and optimized.

[0022] The performance control method of surface-coated micro-nano optical fiber optical gas sensing is mainly based on the first-principles calculation of density functional theory. The optical gas sensing performance control method of the material is obtained through the simulation analysis of the molecular adsorption characteristics and optical characteristics. The material sensing characteristics are analyzed by comprehensive multi-physical field simulation. Combined, the performance of the material surface-coated micro-nano optical fiber gas sensing can be known. Density functional theory is based on quantum mechanics methods as the theoretical support. Through some physical analysis of the microscopic properties of various materials, the first step of the first-principles calculation of motion is to determine the chemical elements and external environment of the research system, and then analyze the results of the simulation calculation to obtain the initial data source, which provides the most appropriate data support for the subsequent actual experimental research.

[0023] All theoretical calculations of this technical solution are completed in Materials Studio software, among which the analysis of adsorption characteristics and optical properties is mainly calculated in two software packages, DMol3 and CASTEP in MS.

[0024] Taking the detection of SF6 decomposition component gases by using micro-nano optical fiber coated on the surface of graphene as an example, it was found through simulation analysis that graphene has the best gas sensing performance for SO2, which was then verified through experiments. The following steps are included: a. Establish and optimize graphene unit cells and gas molecules Find the graphene unit cell in the Materials Studio software, cut and extend the unit cell to obtain a supercell, and then set a vacuum layer of appropriate height to obtain a graphene crystal model. Then, build the gas molecule models of the decomposed components of SF6 in sequence. In order to obtain a more stable structural model, it is necessary to optimize the graphene supercell and each gas molecule, use the DMol3 function package for calculation, select the method used by the exchange-correlation functional, set the energy in the convergence tolerance, the maximum force between atoms and the maximum number of geometric optimization cycles, set the parameters related to the electronic Hamiltonian, including the self-consistent convergence standard, the maximum number of self-consistent cycles, the number of K-point grids, the type of nuclear processing method, etc. After the parameters are set, optimization can be performed. The optimized model is the basis for exploring the adsorption and optical properties.

[0025] b. Simulation analysis of adsorption characteristics After obtaining the substrate (graphene unit cell) optimization model, gas molecule optimization model and substrate adsorption gas optimization model, the substrate energy before adsorption, the adsorbed gas energy and the substrate energy after adsorption can be obtained in the outmol file, so as to obtain the reaction adsorption energy. The adsorption distance can be obtained by comparing the model before optimization with the model after optimization. For the optimized model, select Population analysis in the DMol3 function package to calculate the charge transfer amount, and the charge transfer amount can also be obtained in the outmol file. Comprehensive analysis of adsorption energy, adsorption distance and charge transfer amount shows that graphene has a better adsorption effect on SO2 gas and a stronger reaction.

[0026] c. Optical characteristics simulation analysis After optimizing the unit cell and gas molecule model using the CASTEP software package, set the parameters such as the method used for the exchange-correlation functional, the plane wave cutoff energy, the number of K-point grids, the convergence accuracy of the self-consistent iteration, and the maximum number of iterations to calculate the optical properties of the substrate (graphene unit cell) and the substrate after adsorption of gas. When the calculation is observed to be successful, select the adsorption model of the selected substrate adsorbed gas to obtain the optical property diagram (imaginary part of the dielectric function, absorption coefficient, reflectivity, refractive index, etc.), and then you can clearly analyze the optical sensing performance through the changes in optical properties before and after gas adsorption. In this case, a typical SF6 decomposition component detection experiment was carried out through a fiber optic ring cavity ring-down gas detection system. The transmission loss of the optical fiber is an important property of the system to explore the gas detection capability. However, by analyzing the change in the refractive index, the change in the transmission loss of the coated optical fiber can be known. Therefore, this method is used to achieve optical gas sensing performance regulation. Figure 3 As shown, when the incident wavelength is 1530 nm, after graphene adsorbs SO2 gas, the refractive index becomes the smallest, and the difference in change before and after adsorption is the largest, indicating that graphene has the highest detection sensitivity for SO2 gas.

[0027] Embodiment 1 Based on the first principle calculation of density functional theory, the adsorption characteristics and optical properties of graphene on the decomposed component gases of SF6 are explored. The simulation results show that graphene has the best gas-sensing performance for SO2. According to the principle of fiber ring cavity ring-down technology, a fiber ring cavity ring-down (FLRD) gas detection platform is built. The prepared graphene-coated micro-nano optical fiber sensor is placed in the gas pool. Using a gas distributor, 50ppm, 100ppm, 150ppm, and 200ppm SO2 gas are further prepared, and the pulse decay waveform of the gas at different concentrations is measured to obtain the ring-down curve fitting results. Of course, temperature changes will affect the refractive index of the surrounding medium. At this time, the ring-down curve fitting results obtained will produce errors due to temperature changes. The signal converted by the photodetector is decomposed from signal noise to remove the noise signal processing to achieve the optimization of the ring-down curve fitting data. At the same time, optical signals of different wavelengths will also affect the refractive index of the surrounding medium when transmitted in the optical fiber. When the detection system uses lasers of different wavelengths, there will be errors caused by cross-interference signals. In order to avoid this situation, the data after wavelength conversion is optimized. Then the ring-down time values ​​at different concentrations were linearly fitted with the SO2 concentration to obtain the fitting curve R 2 is 0.995, such as Figure 2 As shown, it shows that there is a good linear relationship between the decay time and the SO2 concentration, that is, it can be verified that graphene can realize SO2 gas detection.

[0028] The above-mentioned embodiments only express the implementation methods of the present invention, and the descriptions thereof are relatively specific and detailed, but they cannot be understood as limiting the scope of the patent of the present invention. It should be pointed out that, for ordinary technicians in this field, several variations and improvements can be made without departing from the concept of the present invention, and these all belong to the protection scope of the present invention. Therefore, the protection scope of the patent of the present invention should be based on the attached claims.

Claims

1. A method for analyzing the performance of surface-coated micro-nano optical fiber gas sensing, characterized in that: The following steps are involved: S1. Establish the relationship between the input light intensity and the light intensity after passing through the fiber loop cavity once, introduce additional loss, and obtain the ring-down time variation; S2. Analyze the effects of temperature and wavelength on the refractive index of the surrounding medium.

2. The method for analyzing the performance of surface-coated micro-nano optical fiber gas sensing according to claim 1, characterized in that: In S1, the input light intensity The light intensity after passing through the fiber loop cavity once The relationship between them is: ； in, is the speed of light in vacuum; is the inherent loss of the system, ; is the optical fiber absorption coefficient; is the insertion loss of each component; is the optical coupling loss; is the optical path of the fiber loop cavity; is the core refractive index; For time; When the light intensity after the fiber loop cavity is Attenuation to input light intensity of The time required is the ring-down time , ； In actual measurement situations, when the system detects gas, it will be affected by external actions on the optical fiber sensor, which will introduce additional losses. , the ring-down time becomes: ； The change in ring-down time is: ； in, is the change in ring-down time; It can be seen that the refractive index of the surrounding medium has the most significant impact on the optical fiber sensor and is also the additional loss The main cause.

3. The method for analyzing the performance of surface-coated micro-nano optical fiber gas sensing according to claim 2, characterized in that: In S2, the effect of temperature on the refractive index of the surrounding medium is: The expressions for medium density and optical properties and temperature are: ； in, is the refractive index of the surrounding medium; is temperature; is the medium density; is the refractive index coefficient; Since temperature changes will cause the refractive index of the surrounding medium to change, thus causing the ring-down time to change, then: ； Right now, ;in, is the additional loss due to temperature.

4. The method for analyzing the performance of surface-coated micro-nano optical fiber gas sensing according to claim 3, characterized in that: right Perform denoising optimization processing to obtain the objective function for: ； in, For the The measured signal of the secondary decomposed initial signal; is a variable; For the Second decomposition of the initial signal into Gaussian white noise; is the number of times the initial signal is decomposed; Introducing the equality constraint matrix , then the denoised signal for: ； in, is a positive parameter; is the step size parameter; is the projection vector; ,Right now ; Independent Updates , when updating After the stage: ； ； but, 。 5. The method for analyzing the performance of surface-coated micro-nano optical fiber gas sensing according to claim 4, characterized in that: In S2, the wavelength variation relationship is: ； in, is the central wavelength of the incident signal; is the sensitivity coefficient; is the additional loss under wavelength variation; When optical signals of different wavelengths are transmitted in optical fibers, the transmission performance of the signals is optimized: ； in, is the grating period; is the signal value corresponding to different wavelengths; is a fixed value; for The optical fiber absorption coefficient of a gas at a specific wavelength; is the optical fiber absorption coefficient at a specific wavelength; The relationship between the absorption coefficient and the gas concentration is: ； in, is the cross-sectional area of ​​the absorption surface; for Gas concentration; but: ； In order to avoid the error caused by the interference signal, the sample data residual is calculated as: ； in, is the number of training samples; is the ideal output value; is the actual output value; ； ； in, For Update After the stage The particle velocity of each particle; For the The position of a particle; is a constant.

6. A surface-coated micro-nano optical fiber optical gas sensing performance analysis device, characterized in that: The method is realized by a surface-coated micro-nano optical fiber optical gas sensing performance analysis method as claimed in any one of claims 1 to 5, comprising: Function signal generator (1): generates a specific pulse signal to modulate the laser and drive the laser to output laser light of a specific wavelength band; Laser (2): emits a laser signal of a specific wavelength; Isolator (3): ensures that the optical signal can be transmitted in one direction to avoid interference caused by the light source; The first coupler (501) and the second coupler (502): realize optical signal transmission and redistribution, with a splitting ratio of 90:10; Photodetector (6): converts light signals into electrical signals; Oscilloscope (7): displays the electrical signal output by the detector and processes and analyzes it on the PC.

7. The surface-coated micro-nano optical fiber optical gas sensing performance analysis device according to claim 6, characterized in that: The function signal generator (1) emits a periodic pulse signal, which passes through the laser (2) to output a corresponding pulse waveform optical signal, and then passes through the isolator (3) to ensure that the optical signal is not interfered with; The optical signal is input from the low splitting ratio end of the first coupler (501), then output through the air chamber (8), and then output from the low splitting ratio end of the second coupler (502) to the photodetector (6); The optical signal is output from the high splitting ratio end of the second coupler (502) to the optical fiber loop cavity (9), forming a complete cycle; The photoelectric detector (6) converts the optical signal at the low splitting ratio end into an electrical signal, and finally displays the waveform through the oscilloscope (7). The signal transmission in the oscilloscope (7) is processed through the PC end, and the obtained waveform data is analyzed and optimized.

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