Quantitative analysis method for the influence of gas species and their concentrations on fleet signals

Abstract

The quantitative analysis method for the influence of gas types and their concentrations on FLEET signals belongs to the technical field of aerodynamic test testing. In order to solve the problem of application of FLEET technology in quantitative identification of gas components and concentrations, the test system is built; under the condition of single gas test, the influence of gas pressure on the signal intensity of FLEET is analyzed; under the condition of different types of single gas test, the influence of the gas pressure of different types of gas on the signal intensity of FLEET is analyzed; under the condition of combined gas test, the influence of the gas pressure of combined gas on the signal intensity of FLEET is analyzed; under the condition of single gas test, the influence of gas pressure on the life of FLEET signal is analyzed; under the condition of combined gas test, the influence of the gas pressure of combined gas on the life of FLEET signal is analyzed. The quantitative characterization of the influence of gas types and their concentrations on FLEET signals is realized.

Description

Technical Field

[0001] This invention belongs to the field of aerodynamic testing technology, specifically involving a quantitative analysis method for the influence of gas type and concentration on FLEET signals. Background Technology

[0002] With the deepening research on high-enthalpy flow, plasma flow, and complex gas reaction processes, non-contact gas tracing and diagnostic technologies based on laser-induced fluorescence have received widespread attention in fields such as aerodynamic testing, combustion diagnostics, and high-temperature gas property measurement. Femtosecond laser electronic excitation tagging (FLEET), as a novel molecular labeling and tracing method, utilizes femtosecond lasers to directly excite molecules in a gas to form fluorescent labels. It offers advantages such as no need for external tracer particles, high temporal resolution, and minimal disturbance to the flow field, demonstrating good applicability in high-speed, high-temperature, and unsteady gas environments.

[0003] In existing research, FLEET technology is mainly used for flow field velocity measurement and flow structure visualization. The generation of its fluorescence signal is closely related to parameters such as gas molecule type, gas concentration, and ambient pressure. However, in practical applications, the FLEET signal intensity and lifetime vary significantly under different gas and gas combinations, directly affecting signal detectability, measurement accuracy, and the feasibility of experimental schemes. Especially under low-pressure or complex gas composition conditions, the FLEET fluorescence signal is often weak and easily interfered with by background light, scattered light, and random noise, making quantitative determination of gas composition and concentration difficult.

[0004] Existing methods for analyzing FLEET signals largely focus on qualitative comparisons or empirical judgments, lacking a systematic and repeatable experimental procedure for quantitatively evaluating the impact of different gas types and combinations on FLEET signal intensity and lifetime under controlled pressure conditions. Furthermore, traditional image processing methods suffer from insufficient stability in signal region extraction, background suppression, and signal intensity quantification, making it difficult to establish unified evaluation criteria across different experimental conditions. This limits the further application of FLEET technology in the quantitative identification of gas components and concentrations.

[0005] Therefore, there is an urgent need for a gas composition characterization method based on FLEET signal intensity and lifetime analysis. By constructing a controlled gas environment and combining it with stable image processing and signal quantization strategies, a systematic characterization of FLEET signal intensity and lifetime under different gas and their combinations can be achieved, thereby providing a reliable basis for the discrimination of gas composition and concentration. Summary of the Invention

[0006] The problem this invention aims to solve is the application of FLEET technology in the quantitative identification of gas components and concentrations, and proposes a quantitative analysis method for the influence of gas types and their concentrations on FLEET signals.

[0007] To achieve the above objectives, the present invention provides the following technical solution:

[0008] A quantitative analysis method for the influence of gas type and concentration on FLEET signals, comprising the following steps:

[0009] S1. Set up the experimental system;

[0010] S2. Under single-gas test conditions, analyze the effect of gas pressure on FLEET signal intensity;

[0011] S3. Under different single-gas test conditions, analyze the influence of gas pressure on FLEET signal intensity for different types of gases;

[0012] S4. Under the combined gas test conditions, analyze the effect of gas pressure on FLEET signal intensity;

[0013] S5. Under single-gas test conditions, analyze the effect of gas pressure on the lifetime of the FLEET signal;

[0014] S6. Under the combined gas test conditions, analyze the effect of the combined gas pressure on the FLEET signal lifetime.

[0015] Furthermore, in step S1, the experimental system is connected as follows: high-pressure gas source I, pressure reducing valve I, and vacuum chamber are connected in sequence; high-pressure gas source II, pressure reducing valve II, and vacuum chamber are connected in sequence; the vacuum chamber is also connected to a precision digital pressure gauge and a vacuum pump. The laser emitted by the femtosecond laser is reflected by mirror II onto mirror I, and then projected through a plano-concave lens and a plano-convex lens before illuminating the vacuum chamber. The imaging system is used to capture FLEET signal images in the vacuum chamber. The computer device is connected to the imaging system and is used to store the FLEET signal images captured by the imaging system and process the images to obtain the intensity information of the FLEET signal.

[0016] Furthermore, in step S1, the imaging system, vacuum chamber, plano-convex lens, plano-concave lens, mirror I, and mirror II are placed on the lifting platform. The lifting platform is used to adjust the optical path to ensure that the FLEET signal image is generated and acquired at the center position of the vacuum chamber.

[0017] Furthermore, the imaging system in step S1 consists of a high-speed camera, an image intensifier, and a telephoto lens.

[0018] Furthermore, the specific implementation method of step S2 includes the following steps:

[0019] S2.1. Close pressure reducing valve I, use a vacuum pump to evacuate the vacuum chamber to a vacuum environment, and record the initial pressure using a pressure gauge. The imaging system was used to acquire FLEET signal images corresponding to the initial pressure. By adjusting pressure reducing valve I to increase the gas pressure in stages, and simultaneously recording the pressure while acquiring FLEET signal images, a pressure sequence is obtained. and FLEET signal image sequence m represents the total number of pressure conditions. For the m-th pressure, This is the FLEET signal image corresponding to the m-th pressure.

[0020] S2.2. For Random noise in the image is eliminated using a small-range Gaussian filter, followed by binarization. The edge point set of the FLEET signal is extracted using the Canny edge detection method. The left boundary of the FLEET signal is obtained by taking the minimum and maximum values ​​in the horizontal direction of the edge point set. and right boundary The upper boundary of the FLEET signal is obtained by taking the maximum and minimum values ​​in the vertical direction. and lower boundary Based on these four boundaries, a rectangular frame is determined as a mask:

[0021]

[0022] in, This represents the coordinates of a pixel in an image;

[0023] Then, by expanding the rectangle to increase the boundary of the region, we obtain a larger rectangle boundary, resulting in:

[0024]

[0025]

[0026]

[0027]

[0028] Where k is the proportionality coefficient. The left boundary of the expanded FLEET signal. The right boundary of the expanded FLEET signal. The lower boundary of the expanded FLEET signal. This represents the upper boundary of the expanded FLEET signal.

[0029] The enlarged mask for:

[0030] ;

[0031] S2.3. For the FLEET signal image corresponding to the i-th pressure... Calculate the background mean by performing a mean calculation on all pixels in the background region. Calculate the mean of all pixels with a value of 0. Then to Calculate the background mean to obtain the background mean sequence. ;

[0032] S2.4. For the FLEET signal image corresponding to the i-th pressure... Calculate the strength of the FLEET signal, i.e., for Sort the gray values ​​of all pixels in the first 20% of the dataset, and calculate the average gray value of all pixels with the largest gray values. Then to Calculate the intensity of the FLEET signal to obtain the FLEET signal intensity sequence. ;

[0033] S2.5. All of them and Subtracting the corresponding signals yields the intensity sequence of the FLEET signal after removing background interference. ,in Let be the strength of the m-th FLEET signal;

[0034] S2.6. Determine the maximum value in the intensity sequence of the analyzed FLEET signal. To obtain the corresponding pressure It was determined that under this gas, at a pressure of The strongest FLEET signal is obtained at that time.

[0035] Furthermore, the specific implementation method of step S3 includes the following steps:

[0036] S3.1. Following the method in step S2, experiments were conducted under different gas conditions, including nitrogen, oxygen, and air. Under each gas condition, the gas pressure in the vacuum chamber was changed, and the corresponding FLEET signal images were acquired. The FLEET signal intensity corresponding to different pressures under each gas condition was calculated, and the maximum FLEET signal intensity and its corresponding pressure under each gas condition were determined. ;

[0037] S3.2. Record the maximum FLEET signal intensity for each gas species. And the corresponding pressure under these gas conditions. Then the These are the optimal gas conditions for obtaining the maximum FLEET signal strength.

[0038] Furthermore, the specific implementation method of step S4 includes the following steps:

[0039] S4.1. Based on the optimal gas conditions obtained in step S3, adjust pressure reducing valve I to adjust the pressure to the level determined in step S3. Then, under different gas conditions, the pressure reducing valve II was adjusted to increase the pressure in steps. While recording the pressure, FLEET signal images were acquired to obtain the pressure sequence of the combined gas. Image sequences corresponding to the pressure sequences of combined gases ;

[0040] S4.2. Then, based on the image sequence corresponding to the pressure sequence of the combined gas. The FLEET signal intensity of the combined gas is calculated according to the method in step S2, and the result is obtained. ,in The m-th FLEET signal strength of the combined gas;

[0041] S4.3. Through analysis The maximum value in To obtain the corresponding pressure Under the current combined gas conditions, the total gas pressure is determined to be... And the high-pressure gas source I (1) provides gas pressure of At that time, the strongest Fleet signal is obtained;

[0042] S4.4. Judgment The result obtained in step S2 ,if > If the result is positive, it proves that the current combined gas conditions produce a stronger FLEET signal compared to the single gas conditions; otherwise, it will not.

[0043] The beneficial effects of this invention are:

[0044] This invention discloses a quantitative analysis method for the influence of gas type and concentration on FLEET signals. By constructing a controllable experimental environment with varying gas pressures and types, the method systematically acquires the FLEET signal intensity and its variation characteristics under different gas conditions, thus achieving a quantitative characterization of the influence of gas type and concentration on FLEET signals. This invention introduces a stable processing flow for FLEET signal image processing and signal quantization. It determines the signal region through contour extraction, constructs an extended rectangular mask, and effectively separates the signal region from the background region, thereby significantly suppressing the influence of background light, scattered light, and random noise on signal intensity calculation. The method of statistically analyzing the brightest pixels within the mask region is used to quantify the FLEET signal intensity, giving the obtained signal indicators clear physical meaning and good repeatability. This facilitates comparative analysis under different experimental conditions and provides technical support for the application of FLEET technology in gas composition and concentration discrimination and related flow diagnostics. Attached Figure Description

[0045] Figure 1 This is a flowchart of a quantitative analysis method for the influence of gas type and concentration on FLEET signals according to the present invention;

[0046] Figure 2 This is a schematic diagram of the experimental system described in this invention;

[0047] Figure 3 This is a schematic diagram of the components of the vacuum chamber of the present invention;

[0048] Among them, 1 is high-pressure gas source I, 2 is high-pressure gas source II, 3 is pressure reducing valve I, 4 is pressure reducing valve II, 5 is high-precision digital display pressure gauge, 6 is imaging system, 7 is vacuum chamber, 8 is plano-convex lens, 9 is plano-concave lens, 10 is reflector I, 11 is reflector II, 12 is femtosecond laser, 13 is computer device, 14 is lifting platform, 15 is vacuum pump, 16 is flange, 17 is optical glass, and 18 is the overall observation room. Detailed Implementation

[0049] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be further described in detail below with reference to the accompanying drawings and specific embodiments. It should be understood that the specific embodiments described herein are only for explaining the invention and are not intended to limit the invention; that is, the described specific embodiments are merely a part of the embodiments of the invention, and not all of them. The components of the specific embodiments of the invention described and shown in the accompanying drawings can generally be arranged and designed in various different configurations, and the invention may also have other embodiments.

[0050] Therefore, the following detailed description of specific embodiments of the invention provided in the accompanying drawings is not intended to limit the scope of the claimed invention, but merely to illustrate selected specific embodiments of the invention. All other specific embodiments obtained by those skilled in the art based on these specific embodiments without inventive effort are within the scope of protection of this invention.

[0051] To further understand the invention's content, features, and effects, the following specific embodiments are provided, along with accompanying drawings. Figure 1 - Appendix Figure 3 Detailed explanation is as follows:

[0052] Example 1:

[0053] A quantitative analysis method for the influence of gas type and concentration on FLEET signals, comprising the following steps:

[0054] S1. Construct the test system, which includes high-pressure gas source I1, high-pressure gas source II2, pressure reducing valve I3, pressure reducing valve II4, high-precision digital display pressure gauge 5, imaging system 6, vacuum chamber 7, plano-convex lens 8, plano-concave lens 9, reflector I10, reflector II11, femtosecond laser 12, computer device 13, lifting platform 14, and vacuum pump 15.

[0055] Furthermore, in step S1, the experimental system is connected as follows: high-pressure gas source I1, pressure reducing valve I3, and vacuum chamber 7 are connected in sequence; high-pressure gas source II2, pressure reducing valve II4, and vacuum chamber 7 are connected in sequence; vacuum chamber 7 is also connected to a precision digital pressure gauge 5 and a vacuum pump 15; the laser emitted by the femtosecond laser 12 is reflected by mirror II11 onto mirror I10, and then projected through a plano-concave lens 9 and a plano-convex lens 8 before illuminating the vacuum chamber 7; the imaging system 6 is used to capture FLEET signal images inside the vacuum chamber 7; the computer device 13 is connected to the imaging system 6 and is used to store the FLEET signal images captured by the imaging system 6 and process the images to obtain the intensity information of the FLEET signal.

[0056] Furthermore, in step S1, the imaging system 6, vacuum chamber 7, plano-convex lens 8, plano-concave lens 9, reflector I 10, and reflector II 11 are placed on the lifting platform 14, and the optical path is adjusted using the lifting platform 14 to ensure that the FLEET signal image is generated and acquired at the center position of the vacuum chamber 7.

[0057] Furthermore, the imaging system in step S1 consists of a high-speed camera, an image intensifier, and a telephoto lens.

[0058] Furthermore, the high-pressure gas source I1 and the high-pressure gas source II2 are used to provide gases of different types and concentrations, and respectively provide gas environments with different pressures, gas components and concentrations in the vacuum chamber 7.

[0059] The high-pressure gas source I1 and high-pressure gas source II2 supply gases corresponding to different chemical compositions required for the experiment. For example, gas source I may provide nitrogen or helium, while gas source II provides oxygen or high-purity air. The gases are delivered through corresponding gas pipelines, and the pressure and flow rate entering the vacuum chamber are precisely regulated by pressure reducing valves. The gases have different concentrations and compositions to simulate real environmental conditions.

[0060] The high-pressure gas source I1 and the high-pressure gas source II2 need to have high stability;

[0061] The pressure reducing valve I13 is used to control the high-pressure gas source I1 to supply gas with controllable pressure to the vacuum chamber 7.

[0062] The pressure reducing valve II4 is used to control the high-pressure gas source II2 to supply gas with controllable pressure to the vacuum chamber 7.

[0063] The function of pressure reducing valves I13 and II4 is to precisely regulate the gas pressure from the high-pressure gas source and stabilize it within the range required for the experiment. By adjusting the pressure reducing valves, the gas flow rate is ensured to be stable, and pressure changes can be dynamically adjusted according to experimental needs, ensuring that the gas pressure entering the vacuum chamber is always controllable and stable.

[0064] The high-precision digital pressure gauge 5 is used to display the real-time pressure inside the vacuum chamber 7, ensuring that the air pressure in the vacuum chamber 7 is always kept within the set range.

[0065] The imaging system 6 is used to capture FLEET signals. The imaging system 6 includes a high-speed camera, an image intensifier, and a telephoto lens, capable of capturing FLEET signal images with high precision. The high-speed camera has an extremely high frame rate, enabling it to capture rapidly changing FLEET signals. The high-speed camera has an image resolution of 14 bits or higher, allowing for the subdivision of gray levels (signal strength) into more levels, improving image accuracy and detail. The image intensifier increases the brightness of the signal, preventing the loss of weak FLEET signals during imaging. The telephoto lens is used to precisely align with the target area in the vacuum chamber, ensuring a clear and accurate image.

[0066] The vacuum chamber 7 is a completely sealed structure used to provide a stable vacuum environment and control the concentration and pressure of gas components. The wall material of the vacuum chamber 7 is made of high-pressure resistant and corrosion-resistant material to ensure that it can withstand the operational requirements under different pressure environments.

[0067] The plano-convex lens 8 is used to control the convergence position and size of the laser beam, thereby achieving laser beam shaping.

[0068] The plano-concave lens 9 is used to cause the laser beam to diverge. After the laser beam passes through the plano-concave lens, the divergence angle increases, which in turn provides conditions for the convergence of the plano-convex lens 8.

[0069] The plano-convex lens 8 controls the convergence of the beam by changing the focusing distance, thereby meeting the laser beam size requirements in different experimental needs.

[0070] The function of the plano-concave lens 9 is to increase the divergence angle of the laser beam. The expanded laser beam can be further adjusted by the plano-convex lens to ensure that the laser can effectively propagate and be positioned in the vacuum chamber.

[0071] The combination of the plano-convex lens 8 and the plano-concave lens 9 enables flexible control over the shape and diameter of the light beam.

[0072] The reflector I 10 and the reflector II 11 are used to guide the laser beam emitted by the laser 12 into the optical path.

[0073] The I10 and the II11 reflector are coated with a high reflectivity coating to ensure that the laser is minimized when it is reflected.

[0074] The femtosecond laser 12 is used to provide a femtosecond pulsed laser beam as the excitation source for the FLEET signal.

[0075] The femtosecond laser 12 can generate extremely short light pulses with a time width on the femtosecond (fs) level, enabling the system to capture the transiently changing FLEET signal.

[0076] The computer device 13 is used to store the FLEET signal images captured by the imaging system 6, and to process the images to obtain the intensity information of the FLEET signal, thereby analyzing the concentration and composition of the gas.

[0077] The lifting platform 14 is used to adjust the positions of the vacuum chamber 7, the plano-convex lens 8, the plano-concave lens 9, the reflector I 10, and the reflector II 11 to ensure that the FLEET signal can be generated and collected at the center position of the vacuum chamber 7.

[0078] The lifting platform 14 is also used to adjust the position of the imaging system 6 so that the imaging system 6 can accurately acquire the FLEET signal image at the center position.

[0079] The vacuum pump 15 is used to create an extremely low initial vacuum environment for the vacuum chamber 7, reducing the pressure inside the vacuum chamber from normal atmospheric pressure to near-vacuum. This process provides the basis for subsequent stepped pressure testing using a high-pressure gas source. By gradually increasing the gas pressure, the vacuum chamber can provide a pressure environment according to a predetermined pressure gradient.

[0080] like Figure 2 The core components of the vacuum chamber 7 are shown, including the flange 16, optical glass 17, and the observation chamber assembly 18.

[0081] The flange 16 is used to connect the various components of the vacuum chamber 7, ensuring a tight connection and seal of all parts during operation. The flange is CF35 specification and equipped with six threaded holes for connection to other equipment or pipelines. The flange not only provides mechanical strength but also ensures airtightness, prevents gas leakage, and guarantees the stability of the vacuum chamber 7.

[0082] The optical glass 17 serves as the transparent portion of the window in the vacuum chamber 7, providing the function of an optical window to ensure that laser beams or optical signals can pass through smoothly without interference. Preferably, the optical glass 17 is made of JGS1 quartz material, which possesses high light transmittance, high temperature resistance, and radiation resistance. The optical glass 17 can withstand high pressure changes under vacuum conditions. The optical glass 17 is sealed to the flange 16 via a rubber ring to ensure airtightness between the optical glass and the vacuum chamber 7, preventing gas leakage.

[0083] The observation chamber 18 is an important component of the vacuum chamber 7. The design of the entire observation chamber ensures the airtightness and stability of the optical glass 17. It provides an optical entrance for observation and experiments within the vacuum chamber 7. Through the optical glass 17, external devices can observe the experimental process within the vacuum chamber 7 in real time, ensuring visibility and monitoring during the experiment.

[0084] S2. Under single-gas test conditions, analyze the effect of gas pressure on FLEET signal intensity;

[0085] Furthermore, the specific implementation method of step S2 includes the following steps:

[0086] S2.1. Close pressure reducing valve I3, use vacuum pump 15 to evacuate vacuum chamber 7 to a vacuum environment, and use pressure gauge 5 to record the initial pressure. The imaging system 6 was used to acquire FLEET signal images corresponding to the initial pressure. By adjusting the pressure reducing valve I3 to increase the gas pressure in stages, and simultaneously recording the pressure while acquiring FLEET signal images, a pressure sequence is obtained. and FLEET signal image sequence m represents the total number of pressure conditions. For the m-th pressure, This is the FLEET signal image corresponding to the m-th pressure.

[0087] S2.2. For Random noise in the image is eliminated using a small-range Gaussian filter, followed by binarization. The edge point set of the FLEET signal is extracted using the Canny edge detection method. The left boundary of the FLEET signal is obtained by taking the minimum and maximum values ​​in the horizontal direction of the edge point set. and right boundary The upper boundary of the FLEET signal is obtained by taking the maximum and minimum values ​​in the vertical direction. and lower boundary Based on these four boundaries, a rectangular frame is determined as a mask:

[0088]

[0089] in, This represents the coordinates of a pixel in an image;

[0090] Then, by expanding the rectangle to increase the boundary of the region, we obtain a larger rectangle boundary, resulting in:

[0091]

[0092]

[0093]

[0094]

[0095] Where k is the proportionality coefficient. The left boundary of the expanded FLEET signal. The right boundary of the expanded FLEET signal. The lower boundary of the expanded FLEET signal. This represents the upper boundary of the expanded FLEET signal.

[0096] The enlarged mask for:

[0097] ;

[0098] S2.3. For the FLEET signal image corresponding to the i-th pressure... Calculate the background mean by performing a mean calculation on all pixels in the background region. Calculate the mean of all pixels with a value of 0. Then to Calculate the background mean to obtain the background mean sequence. ;

[0099] S2.4. For the FLEET signal image corresponding to the i-th pressure... Calculate the strength of the FLEET signal, i.e., for Sort the gray values ​​of all pixels in the first 20% of the dataset, and calculate the average gray value of all pixels with the largest gray values. Then to Calculate the intensity of the FLEET signal to obtain the FLEET signal intensity sequence. ;

[0100] S2.5. All of them and Subtracting the corresponding signals yields the intensity sequence of the FLEET signal after removing background interference. ,in Let be the strength of the m-th FLEET signal;

[0101] S2.6. Determine the maximum value in the intensity sequence of the analyzed FLEET signal. To obtain the corresponding pressure It was determined that under this gas, at a pressure of The strongest FLEET signal is obtained at that time.

[0102] S3. Under different single-gas test conditions, analyze the influence of gas pressure on FLEET signal intensity for different types of gases;

[0103] Furthermore, the specific implementation method of step S3 includes the following steps:

[0104] S3.1. Following the method in step S2, experiments were conducted under different gas conditions, including nitrogen, oxygen, and air. Under each gas condition, the gas pressure in the vacuum chamber was changed, and the corresponding FLEET signal images were acquired. The FLEET signal intensity corresponding to different pressures under each gas condition was calculated, and the maximum FLEET signal intensity and its corresponding pressure under each gas condition were determined. ;

[0105] S3.2. Record the maximum FLEET signal intensity for each gas species. And the corresponding pressure under these gas conditions. Then the These are the optimal gas conditions for obtaining the maximum FLEET signal strength.

[0106] S4. Under the combined gas test conditions, analyze the effect of gas pressure on FLEET signal intensity;

[0107] Furthermore, the specific implementation method of step S4 includes the following steps:

[0108] S4.1. Based on the optimal gas conditions obtained in step S3, adjust pressure reducing valve I3 to adjust the pressure to the level determined in step S3. Then, under different gas conditions, the pressure reducing valve II4 was adjusted to increase the pressure in steps. While recording the pressure, FLEET signal images were acquired to obtain the pressure sequence of the combined gas. Image sequences corresponding to the pressure sequences of combined gases ;

[0109] S4.2. Then, based on the image sequence corresponding to the pressure sequence of the combined gas. The FLEET signal intensity of the combined gas is calculated according to the method in step S2, and the result is obtained. ,in The m-th FLEET signal strength of the combined gas;

[0110] S4.3. Through analysis The maximum value in To obtain the corresponding pressure Under the current combined gas conditions, the total gas pressure is determined to be... And the high-pressure gas source I1 provides gas pressure of At that time, the strongest Fleet signal is obtained;

[0111] S4.4. Judgment The result obtained in step S2 ,if > If the result is positive, it proves that the current combined gas conditions produce a stronger FLEET signal compared to the single gas conditions; otherwise, it will not.

[0112] S5. Under single-gas test conditions, analyze the effect of gas pressure on the lifetime of the FLEET signal;

[0113] Furthermore, the specific implementation method of step S5 includes the following steps:

[0114] S5.1. Adjust pressure reducing valve I to adjust the pressure to the same step sequence as in step S2. And record it, where m is the number of pressure conditions;

[0115] S5.2. For any , Given a high-speed camera with equal-interval imaging system weight, the FLEET signal images are acquired, resulting in FLEET signal images under different delays. , This means there was no delay. =n , The specified time interval;

[0116] S5.3. Based on the method in step S2 Calculate the FLEET signal strength Let the maximum possible grayscale value of the current bit depth image be... When there exists any , ,satisfy Therefore, it is assumed that the lifetime of the FLEET signal under this gas pressure condition is... ;

[0117] S5.4. For The lifetime sequence can be obtained using the method described above. Then there is =max For the longest lifespan, the corresponding This is the pressure condition with the longest lifespan under current gas conditions. ;

[0118] S6. Under the combined gas test conditions, analyze the effect of the combined gas pressure on the FLEET signal lifetime;

[0119] Furthermore, the specific implementation method of step S6 includes the following steps:

[0120] S6.1. Under the pressure condition with the longest lifespan described in step S5, adjust pressure reducing valve I to adjust the pressure of the optimal gas to the level determined in step S5. Then, under different gas conditions, the pressure reducing valve II was adjusted to increase the pressure in steps. While recording the pressure, FLEET signal images were acquired to obtain the pressure sequence. For any , Given a high-speed camera with equal-interval imaging system weight, the FLEET signal images are acquired, resulting in FLEET signal images under different delays. , This means there was no delay. =n , The specified time interval;

[0121] S5.2. Based on the method in step S2 Calculate the FLEET signal strength Let the maximum possible grayscale value of the current bit depth image be... When there exists any , ,satisfy Therefore, it is assumed that the lifetime of the FLEET signal under this gas pressure condition is... ;

[0122] S5.3. For The lifetime sequence can be obtained using the method described above. Then there is =max For the longest lifespan, the corresponding This is the pressure condition with the longest lifespan under current combined gas conditions. ;

[0123] S5.4. Judgment The result obtained in step S5 The size, if > This proves that the current combined gas conditions can achieve a longer FLEET signal lifetime compared to single gas conditions. Conversely, this will not be the case.

[0124] It should be noted that relational terms such as "first" and "second" are used merely to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitations, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes said element.

[0125] Although this application has been described above with reference to specific embodiments, various modifications can be made and components can be replaced with equivalents without departing from the scope of this application. In particular, as long as there is no structural conflict, the features in the specific embodiments disclosed in this application can be combined with each other in any way. The lack of an exhaustive description of these combinations in this specification is merely for the sake of brevity and resource conservation. Therefore, this application is not limited to the specific embodiments disclosed herein, but includes all technical solutions falling within the scope of the claims.

Claims

1. A quantitative analysis method for the influence of gas type and concentration on FLEET signals, characterized in that, Includes the following steps: S1. Set up the experimental system; S2. Under single-gas test conditions, analyze the effect of gas pressure on FLEET signal intensity; S3. Under different single-gas test conditions, analyze the influence of gas pressure on FLEET signal intensity for different types of gases; S4. Under the combined gas test conditions, analyze the effect of gas pressure on FLEET signal intensity; S5. Under single-gas test conditions, analyze the effect of gas pressure on the lifetime of the FLEET signal; S6. Under the combined gas test conditions, analyze the effect of the combined gas pressure on the FLEET signal lifetime.

2. The quantitative analysis method for the influence of gas type and concentration on FLEET signal according to claim 1, characterized in that, The connection relationship of the test system in step S1 is as follows: high pressure gas source I (1), pressure reducing valve I (3), and vacuum chamber (7) are connected in sequence; high pressure gas source II (2), pressure reducing valve II (4), and vacuum chamber (7) are connected in sequence; vacuum chamber (7) is also connected to a precision digital display pressure gauge (5) and a vacuum pump (15); the laser emitted by the femtosecond laser (12) is reflected by the reflector II (11) onto the reflector I (10), and then projected through the plano-concave lens (9) and the plano-convex lens (8) before irradiating the vacuum chamber (7); the imaging system (6) is used to capture the FLEET signal image in the vacuum chamber (7); the computer device (13) is connected to the imaging system (6) and is used to store the FLEET signal image captured by the imaging system (6) and process the image to obtain the intensity information of the FLEET signal.

3. The quantitative analysis method for the influence of gas type and concentration on FLEET signal according to claim 2, characterized in that, In step S1, the imaging system (6), vacuum chamber (7), plano-convex lens (8), plano-concave lens (9), mirror I (10), and mirror II (11) are placed on the lifting platform (14), and the optical path is adjusted using the lifting platform (14). Ensure that the FLEET signal image is generated and acquired at the center of the vacuum chamber (7).

4. The quantitative analysis method for the influence of gas type and concentration on FLEET signal according to claim 3, characterized in that, The imaging system in step S1 consists of a high-speed camera, an image intensifier, and a telephoto lens.

5. The quantitative analysis method for the influence of gas type and concentration on FLEET signal according to claim 4, characterized in that, The specific implementation method of step S2 includes the following steps: S2.

1. Close pressure reducing valve I (3), use vacuum pump (15) to evacuate vacuum chamber (7) to a vacuum environment, and use pressure gauge (5) to record the initial pressure. The imaging system (6) was used to acquire FLEET signal images corresponding to the initial pressure. By adjusting the pressure reducing valve I (3) to increase the gas pressure in a stepwise manner, the pressure is recorded while FLEET signal images are acquired to obtain the pressure sequence. and FLEET signal image sequence m represents the total number of pressure conditions. For the m-th pressure, This is the FLEET signal image corresponding to the m-th pressure. S2.

2. For Random noise in the image is eliminated using a small-range Gaussian filter, followed by binarization. The edge point set of the FLEET signal is extracted using the Canny edge detection method. The left boundary of the FLEET signal is obtained by taking the minimum and maximum values ​​in the horizontal direction of the edge point set. and right boundary The upper boundary of the FLEET signal is obtained by taking the maximum and minimum values ​​in the vertical direction. and lower boundary Based on these four boundaries, a rectangular frame is determined as a mask: ； in, This represents the coordinates of a pixel in an image; Then, by expanding the rectangle to increase the boundary of the region, we obtain a larger rectangle boundary, resulting in: ； ； ； ； Where k is the proportionality coefficient. The left boundary of the expanded FLEET signal. The right boundary of the expanded FLEET signal. The lower boundary of the expanded FLEET signal. This represents the upper boundary of the expanded FLEET signal. The enlarged mask for: ； S2.

3. For the FLEET signal image corresponding to the i-th pressure... Calculate the background mean by performing a mean calculation on all pixels in the background region. Calculate the mean of all pixels with a value of 0. Then to Calculate the background mean to obtain the background mean sequence. ; S2.

4. For the FLEET signal image corresponding to the i-th pressure... Calculate the strength of the FLEET signal, i.e., for Sort the gray values ​​of all pixels in the first 20% of the dataset, and calculate the average gray value of all pixels with the largest gray values. Then to Calculate the intensity of the FLEET signal to obtain the FLEET signal intensity sequence. ; S2.

5. All of them and Subtracting the corresponding signals yields the intensity sequence of the FLEET signal after removing background interference. ,in Let be the strength of the m-th FLEET signal; S2.

6. Determine the maximum value in the intensity sequence of the analyzed FLEET signal. To obtain the corresponding pressure It was determined that under this gas, at a pressure of The strongest FLEET signal is obtained at that time.

6. A quantitative analysis method for the influence of gas type and concentration on FLEET signals according to claim 5, characterized in that, The specific implementation method of step S3 includes the following steps: S3.

1. Following the method in step S2, experiments were conducted under different gas conditions, including nitrogen, oxygen, and air. Under each gas condition, the gas pressure in the vacuum chamber was changed, and the corresponding FLEET signal images were acquired. The FLEET signal intensity corresponding to different pressures under each gas condition was calculated, and the maximum FLEET signal intensity and its corresponding pressure under each gas condition were determined. ; S3.

2. Record the maximum FLEET signal intensity for each gas species. And the corresponding pressure under these gas conditions. Then the These are the optimal gas conditions for obtaining the maximum FLEET signal strength.

7. A quantitative analysis method for the influence of gas type and concentration on FLEET signals according to claim 6, characterized in that, The specific implementation method of step S4 includes the following steps: S4.

1. Based on the optimal gas conditions obtained in step S3, adjust the pressure reducing valve I (3) to adjust the pressure to the level determined in step S3. Then, under different gas conditions, the pressure reducing valve II (4) is adjusted to increase the pressure in a stepwise manner. While recording the pressure, FLEET signal images are acquired to obtain the pressure sequence of the combined gas. Image sequences corresponding to the pressure sequences of combined gases ; S4.

2. Then, based on the image sequence corresponding to the pressure sequence of the combined gas. The FLEET signal intensity of the combined gas is calculated according to the method in step S2, and the result is obtained. ,in The m-th FLEET signal strength of the combined gas; S4.

3. Through analysis The maximum value in To obtain the corresponding pressure Under the current combined gas conditions, the total gas pressure is determined to be... And the high-pressure gas source I (1) provides gas pressure of At that time, the strongest Fleet signal is obtained; S4.

4. Judgment The result obtained in step S2 ,if > If the result is positive, it proves that the current combined gas conditions produce a stronger FLEET signal compared to the single gas conditions; otherwise, it will not.

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