Method for visualizing internal flow field of MEMS gas chromatography column based on background schlieren

Abstract

This invention discloses a method for visualizing and detecting the internal flow field of a MEMS gas chromatograph column based on background schlieren imaging, relating to the fields of microelectromechanical systems (MEMS) and microfluidics. The method includes the following steps: S1, preparation of the MEMS micro gas chromatograph column chip; S2, establishment of the background schlieren optical link; S3, acquisition of the reference image; S4, acquisition of the flow image; S5, extraction of the displacement field; S6, inversion from displacement to refractive index / density gradient; S7, reconstruction and visualization output of flow field quantities such as velocity / pressure; S8, localization of local defects and updating of structural parameters; S9, experimental-simulation closed-loop iterative optimization. This invention applies BOS quantitative visualization technology to the internal diagnostics of MEMS-grade chromatographic columns, enabling rapid closed-loop correction and iteration of CFD models, reducing theoretical plate height, increasing the number of theoretical plates, reducing pressure drop, and increasing peak capacity. This provides a reliable experimental verification and optimization method for next-generation high-resolution, low-power, miniaturized aerospace-grade chromatographic columns.

Description

Technical Field

[0001] This invention belongs to the field of microelectromechanical systems (MEMS) and microfluidics technology, and more specifically, it relates to a method for visualizing and optimizing the internal flow field of a MEMS micro gas chromatography column based on background schlieren. Background Technology

[0002] During the operation of a manned spacecraft in orbit, the atmospheric environment inside the cabin must always remain safe, stable, and controllable. The real-time balance of oxygen, carbon dioxide, trace volatile organic compounds (VOCs), and nitrogen partial pressure is directly related to the astronauts' safety and the success or failure of the mission. Traditionally, platforms such as space stations rely on benchtop gas chromatographs or mass spectrometers to monitor atmospheric composition. However, these devices are bulky, power-consuming, and require frequent maintenance, which can no longer meet the stringent requirements of "lightweight, low power consumption, and high reliability" for long-term deep space stays. To address this, microelectromechanical systems (MEMS) technology has been introduced into the field of gas analysis, compressing traditional chromatographic columns that are several meters long into centimeter-scale chips, and achieving efficient separation through serpentine or spiral channels combined with elliptical / cylindrical microcolumn arrays. Typical chip structure: A serpentine channel, 200–300 μm deep and 200–250 μm wide, is formed on a silicon-based or glass substrate using deep reactive ion etching (DRIE). Elliptical micropillars (60 μm major axis, 30 μm minor axis) are arranged at specific intervals within the channel, and the surface is then covered with a PDMS, MOFs, or ionic liquid stationary phase. The overall chip size is only 20 mm × 10 mm × 0.5 mm, with a theoretical plate number of 8000–10000 platesm⁻¹, a pressure drop of 5–10 kPa, and the ability to complete ppm-level detection of C1–C4 alkanes or CO2 and O2 within tens of seconds.

[0003] In practical applications of micro gas chromatography columns, due to limitations in chip structure design and minor deviations in the manufacturing process, the local flow field within the channel often exhibits inhomogeneity. For example, reflux zones easily form inside bends, low-velocity wakes are generated at the microcolumn's trailing edge, and local eddy diffusion is intensified. These problems can lead to peak broadening, column efficiency degradation, and even baseline drift, severely impacting detection accuracy and reliability. During ground-based experimental phases, these potential defects are difficult to detect and correct in a timely manner, potentially leading to serious consequences such as monitoring failure, false alarms, or excessive inerting in real-world applications.

[0004] Currently, the industry generally adopts a two-stage verification process of "endpoint voltage drop - offline CFD" as the closest existing technical solution. This method is simple in hardware and intuitive in operation, and has become a "must-do" for many universities and aerospace research institutes before delivering chips. However, it has the following objective shortcomings:

[0005] Space blind zone: It can only provide the average pressure drop of the "entire column" and cannot distinguish local anomalies such as backflow in bends and micro-column wake vortices; Environmental blind zone: The ground's constant gravity and isothermal conditions are vastly different from the microgravity and cyclic thermal cycling conditions in space, resulting in low reliability of the CFD correction model; Cyclic blind zone: The chip needs to be repeatedly disassembled and reassembled on the ground test bench, with a single verification cycle of 1-2 weeks, which cannot meet the requirements for real-time optimization in orbit; Visualization blind zone: There are no real-time images, and it is impossible to link with the ECLSS fault diagnosis system, making it difficult to achieve life prediction and early warning.

[0006] Therefore, although the existing "endpoint pressure drop + offline CFD" process exists and is widely used, it cannot solve the flow field reliability problem of MEMS-μGC in long-term aerospace missions. There is an urgent need for a new "non-invasive, high-resolution, and closed-loop" new technology path. Summary of the Invention

[0007] The technical problem this invention aims to solve is to provide a method for visualizing and optimizing the internal flow field of MEMS micro gas chromatographs based on background-oriented schlieren (BOS). This method applies BOS quantitative visualization technology to the internal diagnostics of MEMS-grade chromatographic columns, allowing for intuitive observation and analysis of the flow field distribution within the micro gas chromatographic column. It enables the early detection and correction of inhomogeneities in the flow field, such as reflux zones and low-speed wakes. Using BOS measurement results, existing design-level CFD models are rapidly closed-loop calibrated and iterated, improving structural optimization efficiency and shortening the development cycle. Furthermore, by precisely eliminating local eddy diffusion and reducing mass transfer resistance, the method ultimately achieves the comprehensive performance goals of reducing the theoretical height on plate (HETP), increasing the theoretical plate number, reducing pressure drop, and increasing peak capacity. This provides a reliable experimental verification and optimization method for next-generation high-resolution, low-power, miniaturized aerospace-grade chromatographic columns.

[0008] To solve the above-mentioned technical problems, the technical solution adopted by the present invention is: a method for visualizing, detecting, and optimizing the internal flow field of a MEMS micro gas chromatography column based on background schlieren, comprising the following steps:

[0009] A method for visualizing and optimizing the internal flow field of a MEMS micro gas chromatograph column based on background schlieren, including chip preparation, background schlieren optical link construction, reference image acquisition, flow image acquisition, displacement field extraction, refractive index gradient and density gradient inversion, velocity field and pressure field reconstruction and visualization output, local defect judgment and structural parameter update, and experimental-simulation closed-loop constraints and iterative optimization steps.

[0010] S1. MEMS Micro Gas Chromatography Column Chip Preparation: The chip to be tested is installed in a temperature-controlled mounting base or temperature-controlled box to ensure stable operation under preset experimental conditions. The chip includes a serpentine microchannel structure formed on a substrate, with the channels periodically bending along the flow direction and a micro-column array arranged inside. The chip is controlled by constant temperature or programmed temperature rise through the temperature-controlled box, while a stable pressure or flow boundary condition is applied at the chip inlet to form a repeatable and comparable stable flow field state.

[0011] S2. Background schlieren optical link construction: A high-contrast striped background is set on the back of the chip and a uniform LED backlight source is configured; a telecentric optical system is arranged on the other side of the chip and coupled with a high-speed CMOS camera to suppress perspective error and magnification change, so that the displacement of the background stripes is only caused by refraction disturbance caused by the flow field.

[0012] S3. Reference Image Acquisition: Under conditions of no flow field refraction disturbance, acquire a reference image of the background stripes as a reference for subsequent displacement field calculations.

[0013] S4. Flow image acquisition: Start the carrier gas flow under the set inlet pressure or flow conditions to form an actual working flow field inside the chip and acquire flow images containing flow field refraction and disturbance information.

[0014] S5. Displacement field extraction: Perform cross-correlation calculation on the reference image and the flow image to extract the two-dimensional displacement field of the background stripes on the image plane. The displacement field is proportional to the integral of the flow field refractive index gradient along the direction of light propagation.

[0015] S6. Inversion from displacement field to refractive index gradient and density gradient: Based on the relationship between light deflection angle and refractive index gradient, combined with displacement inversion formula, the refractive index gradient distribution of the flow field is obtained; then, according to the Gladstone-Dale equation, the refractive index gradient field is linearly mapped to the gas density gradient field to obtain the density distribution information inside the chip.

[0016] S7. Reconstruction and Visualization Output of Velocity and Pressure Fields Based on Density Field: Based on the measured density field, combined with the known mass flow rate or volumetric flow rate at the inlet as boundary conditions, the local velocity distribution is inferred from the mass conservation relationship to obtain the complete velocity field; combined with the chip operating temperature and the gas equation of state, the pressure field distribution is calculated from the density field; the obtained velocity and pressure fields are output in the form of contour maps, vector maps, or profile distributions to identify abnormal flow structures.

[0017] S8. Local Defect Judgment and Structural Parameter Update Based on Flow Field Evaluation Indicators: Based on the velocity field and pressure field, velocity consistency evaluation indicators and vortex intensity quantitative evaluation parameters are introduced to determine local flow anomaly areas; by analyzing velocity distribution consistency, low-velocity stagnation zone range and vortex intensity, the channel depth-to-width ratio, micro-pillar spacing, micro-pillar arrangement angle or geometric shape parameters are adjusted to generate new combinations of structural parameters.

[0018] S9. Experiment-Simulation Closed-Loop Constraints and Iterative Optimization: The measured density field and velocity field are introduced into the computational fluid dynamics simulation model as constraints. The difference between the measured and simulation results is used as the basis for model correction to update the inlet boundary conditions, local flow resistance parameters, or wall equivalent roughness parameters. After each round of structural parameter updates, the velocity consistency index, channel total pressure drop, and vortex intensity are comprehensively evaluated. The iteration is terminated when the convergence condition is met; otherwise, S1 to S8 are re-executed to form a closed-loop iterative optimization.

[0019] Furthermore, the MEMS micro gas chromatography column chip includes a serpentine microchannel structure formed on a substrate, with a microcolumn array arranged inside the channel to regulate the carrier gas flow path and enhance mass transfer and separation efficiency.

[0020] Furthermore, the background schlieren optical link includes setting a high-contrast striped background and a uniform LED backlight source on the back of the chip, and arranging a telecentric optical system and a high-speed CMOS camera on the other side of the chip to suppress perspective error and magnification variation.

[0021] Furthermore, the reference image is a background stripe image acquired under conditions of no flow field refraction disturbance; the flow image is an image acquired when the carrier gas flows to form an actual flow field under set inlet pressure or flow rate conditions.

[0022] Furthermore, the displacement field extraction is achieved by cross-correlation calculation of the reference image and the flow image, and the resulting two-dimensional displacement field is proportional to the integral of the flow field refractive index gradient along the direction of light propagation.

[0023] Furthermore, the inversion of the refractive index gradient and density gradient is based on the relationship between the light deflection angle and the refractive index gradient, and combined with the Gladstone-Dale equation, the refractive index gradient field is linearly mapped to the gas density gradient field to obtain the density distribution information inside the chip.

[0024] Furthermore, the reconstruction of the velocity field and pressure field is based on the measured density field, combined with the inlet mass flow rate or volume flow rate boundary conditions and the mass conservation relationship to infer the local velocity distribution, and then combined with the gas state equation to calculate the pressure field from the density field, and output in the form of contour maps, vector maps or profile distribution.

[0025] Furthermore, the local defect determination and structural parameter update introduce quantitative parameters such as velocity consistency evaluation index and vortex intensity. By analyzing the velocity distribution consistency, the range of low-speed retention zone and vortex intensity, the channel depth-to-width ratio, micro-pillar spacing, micro-pillar arrangement angle or micro-pillar geometry parameters are adjusted.

[0026] Furthermore, the experimental-simulation closed-loop constraint and iterative optimization introduces the measured density field and velocity field into the computational fluid dynamics simulation model. The difference between the measured and simulation results is used as the basis for model correction. The inlet boundary conditions, local flow resistance parameters or wall equivalent roughness parameters are updated, and the velocity consistency, channel total pressure drop and vortex intensity are comprehensively evaluated until the convergence condition is met.

[0027] Furthermore, the telecentric optical system includes a telecentric lens, with the fringe period, telecentric magnification, and pixel size set collaboratively to achieve submicron-level displacement resolution at the microchannel scale.

[0028] The beneficial effects of adopting the above technical solution are as follows:

[0029] From a technical perspective:

[0030] 1. Non-contact flow field diagnosis

[0031] This invention is the first to apply BOS (Background-Oriented Schlieren) quantitative visualization technology to the internal diagnosis of MEMS-level chromatographic columns. It can obtain the spatial distribution of velocity, density and pressure in one go without inserting probes or adding tracer particles in the microchannels, breaking through the limitations of traditional computational fluid dynamics (CFD) which can only provide theoretical predictions and experimental methods which can only measure the pressure difference between the inlet and outlet.

[0032] 2. High-fidelity experimental closed loop

[0033] This invention directly injects measured flow field data into the numerical model, enabling rapid iteration of "design-verification-correction"; the differences between flow details and simulation results are quickly discovered and used for the next round of structural optimization, significantly compressing the development cycle.

[0034] 3. Visual representation of complex microstructures

[0035] Low-speed regions, vortex pairs, or local shock waves caused by three-dimensional features such as serpentine bends and elliptical micropillar arrays can be clearly captured, providing a visual basis for fine adjustment of key parameters such as channel aspect ratio and micropillar arrangement angle.

[0036] 4. Strong environmental adaptability: The entire optical path and imaging unit are small in size and have no moving scanning components, which can ensure long-term stable operation under extreme conditions such as programmed temperature rise, high pressure difference and microgravity.

[0037] From an application perspective:

[0038] 1. Performance Improvement

[0039] By promptly eliminating reflux and eddy currents, the separation efficiency and pressure drop of the chromatographic column are improved simultaneously, and the trace gas detection capability is significantly enhanced, meeting the dual requirements of sensitivity and response speed in aerospace, vehicle-mounted, and on-site emergency scenarios.

[0040] 2. Cost and cycle advantages

[0041] Structural defects can be located early, reducing repeated fabrication and packaging; the core components of the system are all conventional industrial-grade devices, which are easy to maintain, and the overall investment is significantly lower than that of traditional laser diagnostic platforms.

[0042] 3. User-friendly system-level integration

[0043] The diagnostic unit is compatible with existing MEMS chip packaging and can be directly embedded into existing environmental control or fuel monitoring modules to achieve real-time visual early warning of gas leaks, thereby improving the reliability and autonomous maintenance capabilities of the entire system.

[0044] 4. Potential for cross-industry promotion

[0045] The same solution can be easily adapted for use in fuel cell microchannels, microreactors, and chip heat dissipation, providing a universal visualization diagnostic tool for various microscale flow devices. Attached Figure Description

[0046] Figure 1 This is a schematic diagram illustrating the basic principles of background shading;

[0047] Figure 2 This is a schematic diagram of the BOS experiment for measuring the internal flow field of a miniature gas chromatography column.

[0048] Figure 3 It refers to the developmental form of the gas jet and the displacement of background particles after passing through the gas jet; Detailed Implementation

[0049] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those of ordinary skill in the art without creative effort are within the scope of protection of this application.

[0050] In the structural optimization of existing MEMS micro gas chromatographs, computational fluid dynamics (CFD) simulations and steady-state pressure drop / flow rate experiments are primarily used to obtain internal flow field information. However, CFD can only provide idealized and theoretical velocity fields and pressure distributions, failing to reflect actual processing errors, wall roughness, and real flow distortions caused by non-uniform stationary phase coating. Traditional steady-state tests can only measure the total pressure difference between the inlet and outlet, unable to provide crucial details such as local velocity gradients, eddy current distribution, and secondary flow structure along the flow path. Therefore, existing methods struggle to accurately locate local structural defects that lead to peak broadening, increased mass transfer resistance, or abnormal pressure drops, severely limiting further improvements in separation efficiency, analysis speed, and power consumption control of the chromatographic column.

[0051] like Figure 1-3 As shown, the basic experimental equipment used in the Background Schlieren (BOS) experimental system includes a light source, a background particle board, a camera, and a flow field region. When the background particle board is placed behind the jet flow field, compared to the case without a jet, light is deflected when passing through the flow field under test. This causes the same particle on the background board to fall at different positions in the camera lens under the conditions of having and not having a jet. The image without a jet is the original image, and the image with a jet is the experimental image. In the experiment, this phenomenon is simultaneously manifested by a series of particles on the background board, that is, they undergo regular displacement simultaneously. This makes it possible to observe a clear and distinguishable jet outline in the acquired image when the jet image is captured by the camera. BOS technology evolved from flow visualization technology. It uses liquid to reduce light, converting unobservable fluid changes into visible image changes. BOS technology has attracted widespread attention due to its many advantages and occupies an important position in combustion, heat transfer, and wind tunnel experiments. This technology can be applied to harsh industrial environments and complex flow field conditions. BOS technology has the following advantages:

[0052] 1) Using computer image processing technology, background schlieren can digitally analyze background images, thereby enabling quantitative measurement of the density field. This method possesses excellent spatiotemporal resolution and high robustness.

[0053] 2) Using background schlieren technology, we do not need to rely on complex precision optical devices. This not only solves the problem of limited detection area caused by lens size, but also provides a wide field of view. At the same time, this method reduces the need for laboratory environment and equipment costs, making it more suitable for real-world engineering practice. Furthermore, due to the feasibility of BOS technology, we can easily capture flow phenomena from different perspectives using multiple cameras, making it possible to construct jet models. Background imaging technology does not require a large number of precision optical devices. This solves the problem of measurement range limitations due to lens size, enabling wide-angle observation; simultaneously, it reduces the need for experimental environment and equipment costs, making it suitable for practical engineering applications. In addition, BOS technology facilitates multi-camera, multi-angle flow field measurements, providing possibilities for jet reconstruction.

[0054] 3) Background schlieren technology also allows the selection of the natural environment as its image, thus expanding the measurement range. Therefore, BOS technology is more suitable for flow field observation in complex environments.

[0055] Despite its advantages, the application of BOS technology also faces certain limitations. For example, it requires an additional background particle image plate to ensure experimental results, and it has high requirements for the light source; only when the expected brightness level is reached can accurate measurements be guaranteed. Furthermore, BOS technology has strict regulations regarding the size of the flow area. Because of the introduction of the camera and background plate, the flow area must have sufficient space to meet the requirements. If the flow area is too small or the natural light is insufficient, this method will struggle to detect the density of the flow area.

[0056] The principle of background schlieren technology is demonstrated below. When analyzing a flow field, light rays deviate from their original path due to changes in refractive index, bending in the direction of increasing refractive index. Using BOS technology, the change in the first spatial derivative of the refractive index parallel to the camera's optical path can be sensitively captured, and the degree of observed light deflection can be used to determine the refractive index transition of the fluid, thus revealing changes in fluid density. The deflection of light as it passes through the airflow causes a significant horizontal or vertical shift in the background pattern. To achieve this effect, two images need to be captured: a reference image without any deflection and a flow pattern including density changes. Background schlieren technology uses the deflection of light after passing through the flow field to reflect changes in the flow field's refractive index. First, a background pattern without flow field interference is captured as a reference image. Then, a new image is captured with flow field interference and used as the measurement image. Finally, through a correlation algorithm, the displacement of corresponding points in the two background images is extracted to obtain the light deflection information. The experimental principle is shown in the figure.

[0057] The distance from the centerline of the gas jet to the background plate. Let be the distance from the centerline of the gas jet to the center of the camera lens. Light rays are deflected due to changes in the refractive index of the medium; the deflection angle can be expressed by the following formula:

[0058] (1-1)

[0059] (1-2)

[0060] In the formula and These are the deflection angles. The components in the x and y directions, Let be the air refractive index, and n be the refractive index of the flow field through which the light passes. From equations 1-1 and 1-2, it can be seen that the deflection of light is only related to the refractive index gradient component perpendicular to the direction of light propagation. According to... Figure 1 The geometric relationships shown allow us to obtain the displacement of a spot on the image plane:

[0061] (1-3)

[0062] (1-4)

[0063] It can be seen from equations 1-3 to 1-4 that when , When parameters such as f are fixed, the displacement of the background point array on the image is proportional to the integral of the refractive index gradient of the flow field along the light propagation path. This indicates that the directly measured displacement of the background points corresponds to the refractive index gradient of the flow field.

[0064] The relationship between the refractive index n of the flow field and the density ρ of the flow medium is given by the Gladstone-Dale equations:

[0065] (1-5)

[0066] Where G(λ) is the Gladstone-Dale coefficient, a coefficient related to the wavelength of light, and its value is:

[0067] (1-6)

[0068] Gladstone-Dale's law proves that there is a linear relationship between the refractive index and density of the flow field.

[0069] Thus, the above formula proves that the particle offset Δx in the BOS experimental results image exhibits a functional relationship with the flow field density, where all coefficients are constants, including the camera focal length f and the distance Z from the flow field to the background plate. A The distance Z from the flow field to the background plateB Since the Gladstone-Dale coefficient G(λ) and the air refractive index n0 are both constants, they can be represented by a single coefficient A.

[0070] Based on the obtained density field, and using the known mass flow rate or volumetric flow rate applied at the inlet as boundary conditions, the following conditions are satisfied within the microchannel according to the mass conservation law:

[0071]

[0072] in, This represents the local velocity vector. Under the condition of discrete channel cross-sections, the local velocity distribution at each location can be deduced by jointly solving for the density field ρ and the inlet flow constraint. Thus, the complete velocity field is obtained. Furthermore, given the known chip operating temperature T, the gas law is applied:

[0073]

[0074] Where p is the local pressure and R is the gas constant, the corresponding pressure field distribution is calculated from the density field ρ.

[0075] Based on the above principles, this invention proposes a method for optimizing the internal flow field of a miniature gas chromatography column using Background Schlieren (BOS) visualization technology. Through BOS technology, the flow field distribution inside the miniature gas chromatography column can be visually observed and analyzed, allowing for the early detection and correction of inhomogeneities in the flow field, such as reflux zones and low-speed wakes. This method enables optimization of the column structure during ground-based experimental stages, increasing the number of plate separations and enhancing detection accuracy and reliability. The specific steps are as follows:

[0076] S1, MEMS micro gas chromatography column chip preparation

[0077] In step S1, the MEMS micro gas chromatograph chip to be tested is installed in a temperature-controlled mounting base or temperature-controlled box to ensure that the chip operates stably under preset experimental conditions.

[0078] The MEMS micro gas chromatography column chip includes a serpentine microchannel structure formed on a substrate, wherein the microchannels are periodically bent along the flow direction and a microcolumn array is arranged inside the channel; the microcolumn array is used to regulate the carrier gas flow path and enhance mass transfer and separation efficiency.

[0079] During the experiment, the temperature control box is used to control the overall temperature of the chip, either constant or programmed. At the same time, stable pressure or flow boundary conditions are applied at the chip inlet to form a repeatable and comparable stable flow field state inside the chip, providing basic operating conditions for subsequent optical detection and quantitative inversion.

[0080] S2, Background Schlieren Optical Link Construction

[0081] In step S2, an optical imaging link for background schlieren detection is constructed.

[0082] Specifically, a high-contrast striped background is set on the back of the MEMS micro gas chromatograph column chip, and a uniform LED backlight source is configured to make the striped background form a stable and uniform transmission illumination condition in the imaging direction; a telecentric optical system is arranged on the other side of the chip and coupled to a high-speed CMOS camera.

[0083] A telecentric optical system is used to suppress perspective errors and magnification changes during the imaging process, so that the small displacement of the background fringes on the image plane is caused only by the refractive disturbance caused by the flow field inside the chip, thereby improving the accuracy of the correspondence between the subsequent displacement measurement results and the actual microscale flow.

[0084] S3, Baseline Image Acquisition

[0085] In step S3, a background stripe reference image is acquired under conditions of no flow field refraction disturbance.

[0086] In practice, by shutting off the flow of carrier gas at the chip inlet or keeping the gas inside the chip stationary under the same temperature and pressure conditions, the light is not affected by the refraction caused by changes in flow field density when passing through the chip.

[0087] In this state, a reference image of the background fringes is acquired and saved by a high-speed CMOS camera. The reference image is used to characterize the initial position distribution of the background fringes on the image plane under the condition of no refraction disturbance, and serves as a reference for subsequent displacement field calculation.

[0088] S4, Motion Image Acquisition

[0089] In step S4, the carrier gas flow is started under the set inlet pressure or flow rate conditions, so that the actual working flow field is formed in the microchannel inside the MEMS micro gas chromatograph column chip.

[0090] When light passes through the internal flow field of the chip, the spatial variation in gas density distribution along the channel direction and cross-sectional direction leads to the generation of a refractive index gradient, causing the light propagation direction to be deflected, thereby causing a slight displacement of the background fringes on the imaging plane of the high-speed CMOS camera.

[0091] Under this flow condition, flow images containing information on flow field refraction and disturbance are acquired and saved. The flow images can be single-frame images or continuous time-series images acquired when it is necessary to analyze transient flow characteristics.

[0092] S5, Displacement Field Extraction

[0093] In step S5, the reference image obtained in step S3 and the flow image obtained in step S4 are processed to extract the two-dimensional displacement fields Δx and Δy of the background stripes on the image plane.

[0094] In practice, the reference image and the moving image are first registered to eliminate the overall displacement caused by optical system installation errors or environmental drift. Then, a displacement calculation method based on cross-correlation is used to match the corresponding background stripe regions and calculate their displacement distribution on the image plane.

[0095] To meet the detection requirements of small refractive disturbances at the microchannel scale, the displacement solution preferably adopts a subpixel cross-correlation algorithm to obtain a displacement vector field with a resolution higher than that of a single pixel, providing basic input data for subsequent inversion calculations of refractive index gradient and density gradient.

[0096] S6. Inversion from displacement field to refractive index gradient and density gradient

[0097] In step S6, the two-dimensional displacement fields Δx and Δy of the background stripes obtained in step S5 are inverted to obtain the refractive index gradient and density gradient distribution of the internal flow field of the MEMS micro gas chromatograph column.

[0098] According to the principle of background schlieren imaging, light rays are deflected when passing through a flow field with a refractive index gradient. The deflection angle components in the x and y directions are εx and εy, respectively. The deflection angle and the refractive index gradient satisfy the following relationship:

[0099]

[0100]

[0101] Where n0 is the air refractive index, n is the refractive index at the corresponding position when light passes through the flow field, and z is the direction of light propagation. Based on the geometry of the imaging system, the displacements Δx and Δy of the background fringes on the image plane satisfy the following relationship with the refractive index gradient of the flow field:

[0102]

[0103]

[0104] Where ZA is the distance from the flow field centerline to the background plate, ZB is the distance from the flow field centerline to the center of the camera lens, and f is the camera focal length. From equations (1-3) and (1-4), it can be seen that, under the condition that ZA, ZB, and f are fixed, the image plane displacements Δx and Δy are proportional to the integral of the refractive index gradient along the ray propagation path in the flow field. Based on the above relationship, numerical inversion of the displacement fields Δx and Δy can obtain the refractive index gradient distribution of the flow field. Furthermore, according to the Gladstone–Dale equation:

[0105]

[0106]

[0107] Where G(λ) is the Gladstone–Dale coefficient and ρ is the gas density, the refractive index gradient field is linearly mapped to the gas density gradient field, thus obtaining the density distribution information inside the MEMS micro gas chromatography column.

[0108] S7. Reconstruction and Visualization Output of Velocity and Pressure Fields Based on Density Field

[0109] In step S7, based on the gas density distribution ρ obtained in step S6, the velocity and pressure fields inside the MEMS micro gas chromatography column are reconstructed and calculated. During the operation of the micro gas chromatography column, the carrier gas flow is under low Mach number conditions and can be considered as a compressible but weakly compressible flow. Given the mass flow rate or volumetric flow rate applied at the inlet as boundary conditions, according to the mass conservation law, the following conditions are satisfied within the microchannel:

[0110]

[0111] in, This represents the local velocity vector. Under the condition of discrete channel cross-sections, the local velocity distribution at each location can be deduced by jointly solving for the density field ρ and the inlet flow constraint. Thus, the complete velocity field is obtained. Furthermore, given the known chip operating temperature T, the gas law is applied:

[0112]

[0113] Where p is the local pressure and R is the gas constant, the corresponding pressure field distribution is calculated from the density field ρ. The obtained velocity and pressure fields are visualized as two-dimensional contour maps, velocity vector maps, or cross-sectional distributions along the serpentine channel direction, used to identify abnormal flow structures such as backflow phenomena in the serpentine bend region, low-speed wake vortices at the trailing edge of micropillars, and local flow stagnation zones.

[0114] S8. Local defect determination and structural parameter updating based on flow field evaluation indicators

[0115] In step S8, the velocity field and pressure field obtained in step S7 are quantitatively evaluated to locate the local structural defect regions that affect the separation performance of the micro gas chromatography column.

[0116] Preferably, a velocity uniformity evaluation index η is defined within the channel cross-section, and its calculation method is as follows:

[0117]

[0118] in, The local velocity magnitude at the i-th sampling point within the channel cross-section. The average velocity within the cross section is given by N, and the number of sampling points is given by N.

[0119] When the velocity uniformity index η in a certain channel area is lower than a preset threshold, it is determined that there is obvious flow nonuniformity in that area.

[0120] Simultaneously, the vortex structure at the trailing edge or bend of the micropillar is characterized by calculating the local vortex intensity, which is defined as the curl of the velocity field:

[0121]

[0122] When the vortex intensity shows a significant peak in a local area and coincides with the low-velocity stagnation zone, the area is determined to be a flow defect sensitive area.

[0123] For the flow defect sensitive area, according to the preset structure-flow field mapping rules, the channel aspect ratio, microcolumn spacing, microcolumn arrangement angle or microcolumn geometry parameters at the corresponding position are adjusted and updated to generate a new combination of micro gas chromatography column structure parameters.

[0124] S9. Experiment—Simulation Closed-Loop Constraints and Iterative Optimization

[0125] In step S9, the density distribution ρ and velocity field u obtained by actual measurement based on background schlieren technology are introduced into the computational fluid dynamics simulation model as constraints.

[0126] In practice, the measured density field or velocity field is compared with the simulation calculation results, and the difference is used as the basis for model correction. The inlet boundary conditions, local flow resistance parameters or wall equivalent roughness parameters in the simulation model are updated so that the simulation results gradually approach the experimental measurement results.

[0127] In this invention, by coordinating the setting of fringe period, telecentric magnification and pixel size, the system achieves submicron displacement resolution at the microchannel scale, thereby ensuring the measurability and repeatability of microscale refractive disturbances.

[0128] The diagnostic unit and the chromatographic column chip share the same temperature control box, eliminating the need for complex motion scanning components. This facilitates stable operation under programmed temperature rise, high pressure differential, and other conditions, and can be directly embedded into the system to achieve online / quasi-online diagnostics.

[0129] The BOS has been upgraded from a "laboratory optical demonstration" to an "embedded diagnostic module," emphasizing compact packaging and temperature control compatibility, directly serving the structural optimization and reliability verification of MEMS-μGC.

[0130] The above are merely preferred embodiments of the present invention, but the scope of protection of the present invention is not limited thereto. Any equivalent substitutions or modifications made by those skilled in the art within the scope of the technology disclosed in the present invention, based on the technical solution and inventive concept of the present invention, should be covered within the scope of protection of the present invention.

Claims

1. A method for visualizing and detecting the internal flow field of a MEMS gas chromatography column based on background schlieren, characterized in that, The process includes chip preparation, background schlieren optical link setup, reference image acquisition, flow image acquisition, displacement field extraction, refractive index gradient and density gradient inversion, velocity field and pressure field reconstruction and visualization output, local defect identification and structural parameter updating, and experimental-simulation closed-loop constraints and iterative optimization steps; the specific implementation steps are as follows: S1. MEMS Micro Gas Chromatography Column Chip Preparation: The chip to be tested is installed in a temperature-controlled mounting base or temperature-controlled box to ensure stable operation under preset experimental conditions. The chip includes a serpentine microchannel structure formed on a substrate, with the channels periodically bending along the flow direction and a micro-column array arranged inside. The chip is controlled by constant temperature or programmed temperature rise through the temperature-controlled box, while a stable pressure or flow boundary condition is applied at the chip inlet to form a repeatable and comparable stable flow field state. S2. Background schlieren optical link construction: A high-contrast striped background is set on the back of the chip and a uniform LED backlight source is configured; a telecentric optical system is arranged on the other side of the chip and coupled with a high-speed CMOS camera to suppress perspective error and magnification change, so that the displacement of the background stripes is only caused by refraction disturbance caused by the flow field. S3. Reference Image Acquisition: Under conditions of no flow field refraction disturbance, acquire a reference image of the background stripes as a reference for subsequent displacement field calculations. S4. Flow image acquisition: Start the carrier gas flow under the set inlet pressure or flow conditions to form an actual working flow field inside the chip and acquire flow images containing flow field refraction and disturbance information. S5. Displacement field extraction: Perform cross-correlation calculation on the reference image and the flow image to extract the two-dimensional displacement field of the background stripes on the image plane. The displacement field is proportional to the integral of the flow field refractive index gradient along the direction of light propagation. S6. Inversion from displacement field to refractive index gradient and density gradient: Based on the relationship between light deflection angle and refractive index gradient, combined with displacement inversion formula, the refractive index gradient distribution of the flow field is obtained; then, according to the Gladstone-Dale equation, the refractive index gradient field is linearly mapped to the gas density gradient field to obtain the density distribution information inside the chip. S7. Reconstruction and Visualization Output of Velocity and Pressure Fields Based on Density Field: Based on the measured density field, combined with the known mass flow rate or volumetric flow rate at the inlet as boundary conditions, the local velocity distribution is inferred from the mass conservation relationship to obtain the complete velocity field; combined with the chip operating temperature and the gas equation of state, the pressure field distribution is calculated from the density field; the obtained velocity and pressure fields are output in the form of contour maps, vector maps, or profile distributions to identify abnormal flow structures. S8. Local Defect Judgment and Structural Parameter Update Based on Flow Field Evaluation Indicators: Based on the velocity field and pressure field, velocity consistency evaluation indicators and vortex intensity quantitative evaluation parameters are introduced to determine local flow anomaly areas; by analyzing velocity distribution consistency, low-velocity stagnation zone range and vortex intensity, the channel depth-to-width ratio, micro-pillar spacing, micro-pillar arrangement angle or geometric shape parameters are adjusted to generate new combinations of structural parameters. S9. Experiment-Simulation Closed-Loop Constraints and Iterative Optimization: The measured density field and velocity field are introduced into the computational fluid dynamics simulation model as constraints. The difference between the measured and simulation results is used as the basis for model correction to update the inlet boundary conditions, local flow resistance parameters, or wall equivalent roughness parameters. After each round of structural parameter updates, the velocity consistency index, channel total pressure drop, and vortex intensity are comprehensively evaluated. The iteration is terminated when the convergence condition is met; otherwise, S1 to S8 are re-executed to form a closed-loop iterative optimization.

2. The method for visualizing and detecting the internal flow field of a MEMS gas chromatography column based on background schlieren according to claim 1, characterized in that, The MEMS micro gas chromatography column chip includes a serpentine microchannel structure formed on a substrate, with a microcolumn array arranged inside the channel to regulate the carrier gas flow path and enhance mass transfer and separation efficiency.

3. The method for visualizing and detecting the internal flow field of a MEMS gas chromatography column based on background schlieren according to claim 1, characterized in that, The background schlieren optical link includes a high-contrast striped background on the back of the chip, a uniform LED backlight source, and a telecentric optical system and a high-speed CMOS camera arranged on the other side of the chip to suppress perspective error and magnification variation.

4. The method for visualizing and detecting the internal flow field of a MEMS gas chromatography column based on background schlieren according to claim 1, characterized in that, The reference image is a background stripe image acquired under conditions of no flow field refraction disturbance; the flow image is an image acquired when the carrier gas flows to form an actual flow field under set inlet pressure or flow rate conditions.

5. The method for visualizing and detecting the internal flow field of a MEMS gas chromatography column based on background schlieren according to claim 1, characterized in that, The displacement field extraction is achieved by cross-correlation calculation of the reference image and the flow image. The resulting two-dimensional displacement field is proportional to the integral of the flow field refractive index gradient along the direction of light propagation.

6. The method for visualizing and detecting the internal flow field of a MEMS gas chromatography column based on background schlieren according to claim 1, characterized in that, The inversion of the refractive index gradient and density gradient is based on the relationship between the light deflection angle and the refractive index gradient. Combined with the Gladstone-Dale equation, the refractive index gradient field is linearly mapped to the gas density gradient field to obtain the density distribution information inside the chip.

7. The method for visualizing and detecting the internal flow field of a MEMS gas chromatography column based on background schlieren according to claim 1, characterized in that, The reconstruction of the velocity and pressure fields is based on the measured density field. The local velocity distribution is inferred by combining the inlet mass flow rate or volume flow rate boundary conditions and the mass conservation relationship. The pressure field is then calculated from the density field using the gas equation of state and output in the form of contour maps, vector maps, or profile distributions.

8. The method for visualizing and detecting the internal flow field of a MEMS gas chromatography column based on background schlieren according to claim 1, characterized in that, The local defect determination and structural parameter update introduce quantitative parameters such as velocity consistency evaluation index and vortex intensity. By analyzing the velocity distribution consistency, the range of low-speed retention zone and vortex intensity, the channel depth-to-width ratio, micro-pillar spacing, micro-pillar arrangement angle or micro-pillar geometry parameters are adjusted.

9. The method for visualizing and detecting the internal flow field of a MEMS gas chromatography column based on background schlieren according to claim 1, characterized in that, The experimental-simulation closed-loop constraint and iterative optimization introduces the measured density field and velocity field into the computational fluid dynamics simulation model. The difference between the measured and simulation results is used as the basis for model correction. The inlet boundary conditions, local flow resistance parameters or wall equivalent roughness parameters are updated, and the velocity consistency, channel total pressure drop and vortex intensity are comprehensively evaluated until the convergence condition is met.

10. The method for visualizing and detecting the internal flow field of a MEMS gas chromatography column based on background schlieren according to claim 1, characterized in that, The telecentric optical system includes a telecentric lens, with fringe period, telecentric magnification and pixel size set collaboratively to achieve submicron displacement resolution at the microchannel scale.

Images