Release gas monitoring system and correction method for low-vacuum celestial body surface

Abstract

The invention discloses a released gas monitoring system on the surface of a low-vacuum celestial body, which is deployed on a lander and comprises a gas concentration detector used for measuring the gas concentration of a gas release source at a monitoring point; the wind field sensor is used for measuring wind speed and wind direction; the data processing unit is in communication connection with the gas concentration detector and the wind field sensor, receives measurement data and is configured to execute monitoring and correction of released gas; the gas concentration detector and the wind field sensor are fixedly mounted on the lander; the position condition of the monitoring point is that the included angle between the direction of the connecting line of the monitoring point and the gas release source and the real-time downwind direction of the gas release source is within the range of + / -preset angle, and the distance between the monitoring point and the gas release source does not exceed the preset distance. The invention further discloses a released gas monitoring and correcting method. The method has the remarkable technical effects that the measurement precision is high; the reliability is high; the universality is good; and engineering realization is easy.

Description

Technical Field

[0001] This invention belongs to the field of deep space exploration technology, and specifically relates to a gas release monitoring system and correction method for the surface of low-vacuum celestial bodies. Background Technology

[0002] As deep space exploration missions shift from remote sensing to sample return, accurately quantifying the flux of volatile gases released during the exploration process is crucial for understanding the evolution of celestial climates and searching for signs of life. Currently, in-situ mass spectrometry monitoring technology based on the static diffusion assumption has been successfully applied in high-vacuum environments such as the Moon. However, in low-vacuum, windy celestial bodies with surface atmospheric pressures exceeding approximately 0.1 Pa, such as Mars, Triton, and Pluto, the mean free path of gas molecules has shortened to a size comparable to or smaller than the characteristic size of the probe. Gas behavior satisfies the continuous medium assumption, and the Pekley number (Pe) is much greater than 1. This means that the gas transport mechanism has shifted from static diffusion to convection-dominated, fundamentally different from the ultra-high vacuum environment of the Moon. Due to this fundamental change in transport mechanism, existing static diffusion models introduce significant errors, for the following reasons: 1. Different transport mechanisms: In a low vacuum and windy environment, gas transport is dominated by convection (Peklay number Pe>>1) rather than molecular diffusion, resulting in a highly asymmetrical conical distribution of the gas plume and strong spatiotemporal heterogeneity of the concentration field.

[0003] 2. Lack of effective correction methods: Existing monitoring methods do not take into account the strong modulation effect of wind field on gas transport, and cannot establish a quantitative inversion relationship between the concentration at the monitoring point and the actual gas release rate (source strength), resulting in the measured value deviating significantly from the true value.

[0004] 3. Blindly deploying monitoring points: Due to a lack of understanding of the spatial distribution patterns of plumes, the deployment of monitoring points is often blind and can easily result in them being located outside the core area of ​​the plume due to changes in wind direction or improper placement, leading to invalid monitoring signals.

[0005] Therefore, there is an urgent need in this field for a technical solution that can adapt to the low-vacuum, windy surface environment of celestial bodies such as Mars, Triton, and Pluto, and can achieve accurate quantitative monitoring and source intensity inversion of volatile gases. Summary of the Invention

[0006] One of the objectives of this invention is to provide a gas release monitoring system for the surface of low-vacuum, windy celestial bodies such as Mars, Triton, and Pluto, to solve the problems of misjudgment of transport mechanisms and unreasonable deployment of monitoring points caused by ignoring wind fields when directly using existing technologies.

[0007] Another objective of this invention is to provide a calibration method that works in conjunction with the above-mentioned system, thereby solving the technical problem that existing technologies cannot accurately invert the true gas release source strength from concentration data at a single monitoring point.

[0008] To achieve the above objectives, the technical solution of this application provides a gas release monitoring system for the surface of a low-vacuum celestial body, deployed on a lander. The monitoring system includes: a gas concentration detector for measuring the gas concentration at the monitoring point of the gas release source; a wind field sensor for measuring wind speed and direction; and a data processing unit that is communicatively connected to the gas concentration detector and the wind field sensor, receives the measurement data, and is configured to perform gas release monitoring correction. The gas concentration detector and the wind field sensor are fixedly installed on the lander; the location conditions of the monitoring point are: the angle between the line connecting the monitoring point and the gas release source and the real-time downwind direction of the gas release source is within the range of ± preset angle, and the distance between the monitoring point and the gas release source does not exceed the preset distance.

[0009] As an improvement to the above system, the system includes multiple gas concentration detectors; the gas concentration detectors are connected to the data processing unit; the data processing unit is configured to select a gas concentration detector that meets the location conditions at the monitoring point based on the real-time wind direction measured by the wind field sensor, and receive its measurement data.

[0010] As another improvement to the above system, the gas concentration detector is fixed to the lander in one of the following three deployment methods; the three deployment methods are as follows: Deployment Method 1: The monitoring system includes a single gas concentration detector, with the gas concentration detector's inlet serving as the monitoring point. It is fixedly deployed downwind and meets the location conditions described above. Deployment Method Two: The monitoring system includes a gas concentration detector and a multi-channel air intake system. The multi-channel air intake system includes multiple sampling ports located at different locations of the gas release source, branch pipelines connecting each sampling port to the gas concentration detector, and valves for controlling the opening and closing of each branch pipeline. The data processing unit is further configured to control the valves based on the real-time wind direction measured by the wind field sensor to select at least one sampling port that meets the location conditions from the multiple sampling ports as a monitoring point, so that the gas concentration detector measures the gas concentration at the monitoring point. When multiple sampling ports are effective simultaneously, the average concentration is taken or the optimal value is selected based on signal quality. Deployment Method 3: Includes multiple gas concentration detectors, each fixedly deployed at different locations of the gas release source; the inlet of each gas concentration detector is its monitoring point; the data processing unit selects the measurement data of one or more gas concentration detectors whose monitoring points are located downwind and meet the location conditions, based on the real-time wind direction, as valid concentration input signals; when multiple gas concentration detectors are valid simultaneously, the average concentration is taken or the optimal value is selected based on signal quality.

[0011] As another improvement to the above system, the data processing unit is further configured to: determine the validity of the current monitoring point based on the real-time wind direction; if the current monitoring point is invalid, wait for the wind direction to change.

[0012] As an improvement to the above system, the preset angle is 30°.

[0013] As a further improvement to the above system, the preset distance is 1.5m.

[0014] To achieve the above objectives, this application also provides a method for monitoring and correcting the released gases on the surface of a low-vacuum celestial body, executed within the monitoring system, characterized by comprising the following steps: Step S1: Parameter calibration; A model was built by simulating a low-vacuum environment, including: Concentration-wind direction angle quantitative relationship model; Quantitative model of the negative power law relationship between wind speed and model parameters; A source region gas emission correction concentration model is used to establish the source region center concentration C0 and the equivalent concentration C0 along the prevailing wind direction. 10 Quantitative correlation; Source strength inversion relationship model; Simulation experiments were conducted by adjusting wind speed and direction to predetermine the initial model parameters of the target gas under a specific low vacuum environment of the target celestial body, and the quantitative relationship model was determined through wind tunnel experiments for calibration. Step S2: Real-time measurement; collect the following data: The gas concentration C at the monitoring point of the gas release source 1， Real-time wind speed V, real-time wind direction angle α; Step S3: Source region concentration correction; The gas concentration C1 at the monitoring point is corrected back to the equivalent concentration C0 of the gas release source along the prevailing wind axis; where... First, substitute the gas concentration C1 and wind direction angle α into the concentration-wind direction angle quantitative relationship model calibrated in step S1, and obtain the equivalent concentration C in the prevailing wind direction through model inversion calculation. 10； The model parameter σ in the concentration-wind direction angle quantitative relationship model is calculated based on the wind speed V through the wind speed-model parameter negative power law quantitative relationship model. Subsequently, using the source region gas release correction concentration model, the correction concentration C0 of the gas release source region at this wind speed was calculated.

[0015] Step S4: Source strength inversion; where, Substitute the corrected source region concentration C0 and real-time wind speed V into the source intensity inversion relationship model calibrated in step S1 to calculate the volume source term S. Integrating S over the geometric volume of the release source yields the total source strength of the gas release.

[0016] As an improvement to the above correction method, the concentration-wind direction angle quantitative relationship model is as follows: ; ...(1) Where C1 represents the gas concentration at different points on the horizontal secant line perpendicular to the prevailing wind direction within the observation surface, x represents the distance from the monitoring point on the secant line to the intersection of the prevailing wind axis and the horizontal secant line, α represents the wind direction angle, μ represents the distance from the horizontal secant line to the monitoring point, and σ represents the model parameters to be calibrated; the concentration value at wind direction angle α = 0° is C. 10 ; The quantitative model for the negative power law relationship between wind speed and model parameters is as follows: ...(2) Where a, b, and σ are the model parameters calibrated in step S1; V is the wind speed; The corrected concentration model for the gas released from the source region is as follows: C0 = k × C 10 m ... (3) Where C0 is the corrected concentration of the gas released from the source region. k and m are the model parameters calibrated in step S1; The source strength inversion relationship model is as follows: (4) Where S is the volume source term to be determined, and V is the wind speed.

[0017] As a further improvement to the above correction method, in step S1, quantitative relationship model parameters of the target gas under specific low vacuum and temperature conditions of the target celestial body are pre-determined through a low-pressure wind tunnel calibration experiment, specifically including: In a low-pressure wind tunnel, a simulated environment is built and the target gas is injected. Data collection: Under different wind speeds V, the gas concentration C1 at different angles α and distances downwind was measured; Model parameter calibration includes the following: Formula (1) for the quantitative relationship model of concentration-wind direction angle: For each set wind speed V, the concentration-angle data collected at that wind speed is fitted with a Gaussian function to obtain the model parameter σ corresponding to that wind speed; In order to establish a reliable quantitative relationship, the model parameter σ at at least three different wind speeds V needs to be obtained. Formula (2) for the quantitative relationship model of wind speed-model parameter negative power law: Perform linear regression of different wind speeds V and corresponding model parameters σ in double logarithmic coordinates to determine the specific values ​​of the correction coefficients a and b; Formula (3) of the source region correction concentration model: by measuring the concentration C0 at the center of the source region and the concentration C on the downwind axis of the prevailing wind. 10 A quantitative relationship between the two was established, and the correction coefficients k and m were determined.

[0018] As a further improvement to the above correction method, step S2: real-time measurement also includes: judging the validity of the monitoring point; if yes, triggering the gas concentration detector to perform measurement; if no, waiting for wind direction change.

[0019] Compared with the prior art, the advantages of this application are: The system and method of this application aim to overcome the challenge of strong spatial heterogeneity of gas plumes in convective transport-dominated environments by coupling real-time wind field data. This enables precise quantitative monitoring and source intensity inversion of locally released gases (including but not limited to sampled volatiles and naturally erupted gases), and is applicable to the surfaces of low-vacuum, windy celestial bodies such as Mars, Triton, and Pluto. Compared with existing technologies, this invention has the following significant technical advantages: 1. High measurement accuracy: By introducing wind field correction, the applicability error of the static diffusion model in low vacuum windy environment is fundamentally overcome, and the inversion accuracy of volatile release source strength is improved by orders of magnitude.

[0020] 2. High reliability: By confining the monitoring points to the downwind cone angle of a preset angle (preferably ±30°), it is ensured that the monitoring signal always comes from the core area of ​​the plume, effectively avoiding data failure caused by wind direction deviation or improper deployment.

[0021] 3. Good universality: The physical laws upon which this invention is based (convection-dominated, plume cone distribution) are universally applicable to all rarefied to low-vacuum atmospheres (e.g., surface pressure from approximately 0.1 Pa to 5 × 10⁻⁶ Pa). 3 The study of celestial surfaces with dynamic wind fields, such as Mars, Triton, and Pluto, provides a common technical means for future deep space exploration missions.

[0022] 4. Easy to implement in engineering: The system of this application is based on existing sensor technology, the method is streamlined, and it is easy to integrate and implement in the computer system of the detection mission. Attached Figure Description

[0023] Figure 1 This is a schematic diagram illustrating the deployment of a gas release monitoring system on the surface of a low-vacuum celestial body, as described in a specific implementation.

[0024] Figure 2 This is a schematic diagram showing the layout of multiple monitoring and sampling points for a gas release monitoring system on the surface of a low-vacuum celestial body, as described in a specific implementation.

[0025] Figure 3 The flowchart illustrates a method for monitoring and correcting released gases on the surface of a low-vacuum celestial body, as described in a specific embodiment. Detailed Implementation

[0026] The technical solutions provided in this application are further illustrated below with reference to the embodiments.

[0027] Terminology Definition To make the objectives, technical solutions, and advantages of this invention clearer, the key terms used in this invention are defined below: 1. Gas Concentration Detector: This refers to a complete gas concentration measurement device installed on the lander. It includes a core gas analyzer (such as a mass spectrometer or spectrometer), an air intake system, an electronic control unit, and other auxiliary components.

[0028] 2. Monitoring Point: This refers to the actual physical spatial location where the released gas is sampled and its concentration measured. In this invention, it serves as the reference point for all spatial geometric calculations and concentration data acquisition. Specifically: In a single-point fixed monitoring scheme, the monitoring point is the fixed air inlet of the gas concentration detector. In a scheme equipped with a multi-inlet system, the monitoring point refers to the selected sampling port.

[0029] 3. Core gas analyzer: refers to the physical component (such as mass spectrometer, spectrometer, etc.) in the gas concentration detector that performs gas type identification and concentration measurement.

[0030] 4. Multi-inlet gas system: refers to a system that includes multiple sampling ports, connecting pipelines and valve control components, used to selectively deliver gas samples from different spatial locations (monitoring points) to the core gas analyzer.

[0031] 5. Wind field sensor: refers to an instrument used to measure wind speed and direction (such as a three-dimensional ultrasonic anemometer).

[0032] 6. Data processing unit: refers to a computing device that receives measurement data and executes the correction method of the present invention.

[0033] Unless otherwise stated, the terms used in this invention shall have the meanings defined herein.

[0034] This invention provides a monitoring system and method that integrates an optimized deployment scheme and a dedicated correction algorithm. The core of the technical solution lies in revealing the spatial distribution law (Gaussian distribution within a set cone angle, such as ±30° cone angle) and transport law (negative power law relationship between concentration and wind speed) of gas plumes under low vacuum and windy conditions, and establishing a complete and accurate inversion technology chain from single-point monitoring concentration to the actual source strength of gas release.

[0035] As a specific embodiment of this application, a gas release monitoring system for the surface of a low-vacuum celestial body is deployed on a lander. The monitoring system includes: a gas concentration detector for measuring the gas concentration at a monitoring point from a gas release source; a wind field sensor for measuring wind speed and direction; and a data processing unit communicatively connected to the gas concentration detector and the wind field sensor, receiving measurement data and configured to perform gas release monitoring correction. In this specific embodiment, the gas concentration detector refers to a complete gas concentration measurement device installed on the lander, which internally includes at least one core gas analyzer (such as a mass spectrometer) and may selectively include a multi-intake system. The monitoring point refers to the physical location where gas concentration measurement is actually performed: when a single core gas analyzer is fixedly deployed, the monitoring point is the inlet location of that core gas analyzer; when equipped with a multi-intake system, the monitoring point is the selected sampling port location.

[0036] The gas concentration detector and the wind field sensor are fixedly installed on the lander to ensure the stability of their relative positions; wherein, the line connecting the monitoring point of the gas concentration detector and the gas release source is located within the cone angle range of downwind ± preset angle of the real-time wind direction of the gas release source, and the distance between the detector and the gas release source does not exceed the preset distance range.

[0037] Combination Figure 1 The specific explanation is as follows: The gas concentration monitoring system, deployed on a lander on the surface of a celestial body, is used to capture effective volatile gas signals. Its key lies in the optimized layout of monitoring points. The system includes a gas concentration detector, a wind field sensor, and a data processing unit, used to measure the gas concentration at the monitoring points from the gas release source.

[0038] 1. System composition and connection relationships: Gas release source: usually the sampling drilling site of the lander, located near the surface of a celestial body between the lander's legs (such as near the surface of Mars, Triton, etc.).

[0039] The gas concentration detector is fixedly installed on the lander structure, such as the bottom of the platform or on the outriggers, to ensure that its relative position to the gas release source is stable; the wind field sensor is installed at a location that can accurately measure the wind field near the gas release source.

[0040] Data processing unit: Typically configured as an embedded computer or central processing unit on the lander. This data processing unit communicates with the gas concentration detector and wind field sensor via wired or wireless means, receives measurement data, and is configured to perform all calculation steps of the correction method described below.

[0041] 2. Core improvements and working principle of the system: The innovative improvement of this monitoring system lies mainly in the optimized deployment strategy of monitoring points, which follows the core principles discovered through research: The location of the monitoring point must ensure that the line connecting it to the gas release source is within the cone angle range of ± a preset angle downwind of the current real-time wind direction (preferably within ±30° cone angle range), and the distance from the gas release source does not exceed the preset distance range (e.g., 1.5m).

[0042] Technical Principle: This invention, through numerical simulation and physical analysis, reveals that in a low-vacuum, windy environment, the main body of the released gas plume is confined to a cone angle range of ±30° downwind. Outside this area, the gas concentration rapidly decreases to an ineffective level. This deployment principle is the physical basis for ensuring that the monitoring point is always located in the core area of ​​the gas plume (concentration ≥ 1% of the peak concentration), thereby obtaining an effective concentration signal.

[0043] Deployment Method 1 (Fixed Deployment of Single Core Gas Analyzer): The gas concentration detector includes a core gas analyzer (such as a mass spectrometer). During the mission design phase, based on the prevailing wind direction statistics at the landing site, the air inlet (i.e., monitoring point) of the core gas analyzer is fixedly deployed within a ±30° cone angle area downwind of the most likely occurrence, with a distance of no more than 1.5m from the center of the gas release source area.

[0044] Deployment Method Two (Single Core Gas Analyzer Combined with Multi-Inlet System): The gas concentration detector includes a core gas analyzer (such as a mass spectrometer) and a multi-inlet system. The multi-inlet system includes multiple sampling ports located at different locations from the gas release source, branch pipelines connecting each sampling port to the core gas analyzer, and valves for controlling the opening and closing of each branch pipeline. The data processing unit selectively controls the valves to connect specific sampling ports based on the real-time wind direction, enabling the core gas analyzer to measure the gas concentration at the corresponding sampling port. The selected sampling port serves as a monitoring point, and the line connecting it to the gas release source is located within a cone angle range of downwind ± a preset angle from the real-time wind direction, and the distance from the gas release source does not exceed a preset distance range.

[0045] Deployment Method 3 (Fixed Deployment of Multiple Core Gas Analyzers): The gas concentration detector comprises multiple core gas analyzers (such as multiple mass spectrometers), each fixedly deployed at different locations from the gas release source. The inlet of each core gas analyzer is its monitoring point. The data processing unit, based on the real-time wind direction, selects the measurement data from one or more core gas analyzers whose monitoring points are located within ±30° of the current downwind cone angle and at the required distance, as the valid concentration input signal C1. When multiple core gas analyzers are simultaneously effective, the average concentration value can be taken, or the optimal value can be selected based on signal quality.

[0046] As another alternative, more complex configuration, the gas concentration detector may include multiple core gas analyzers, each of which can be independently connected to a multi-inlet system. However, this increases the system complexity and weight and is typically used only when conditions permit and it is necessary.

[0047] The location and number of sampling ports are optimized based on historical climate data and seasonal prevailing wind direction statistics of the landing area. For example, in areas with highly concentrated prevailing winds, sampling ports can be asymmetrically deployed at predetermined angular intervals (e.g., 30°) downwind of the prevailing wind and in adjacent sectors (e.g., covering ±90°), with a distance of no more than 1.5m from the source area. In areas with variable wind directions, a wider or approximately uniform deployment strategy is adopted. This method ensures, with minimal hardware resources, that monitoring points (or effective sampling ports) are located within an effective ±30° cone angle in most wind directions, thereby achieving system robustness under resource optimization.

[0048] The data processing unit is configured to: dynamically calculate the line direction connecting each potential monitoring point (the sampling port in deployment method two or the air inlet of each core gas analyzer in implementation method three) to the release source based on real-time wind direction data provided by the wind field sensor; and automatically select measurement data from one or more monitoring points whose straight-line distance from the source is within a preset range and whose direction is within ±30° of the current real-time downwind direction as an effective concentration input signal C1 for subsequent processing. This method can effectively cope with instantaneous changes in wind direction.

[0049] As a specific embodiment of this application, this application also provides a method for monitoring and correcting released gases on the surface of a low-vacuum celestial body. The method operates within the data processing unit of the aforementioned system, and its core lies in using real-time wind field data to establish a quantitative inversion model between the concentration at the monitoring point and the intensity of the release source.

[0050] A physical model is constructed by simulating a specific vacuum environment (e.g., pressure approximately 600 Pa, temperature approximately 210 K) of a target low-vacuum windy celestial body (such as Mars). An initial quantitative relationship model between the target gas (e.g., water vapor) and the wind field is obtained through simulation. This model is then further calibrated and determined using wind tunnel experiments to finalize the quantitative relationship model, which is used for concentration correction and source strength retrieval during the on-orbit execution phase. In this invention, the low-vacuum environment specifically refers to a pressure higher than approximately 0.1 Pa to 5 × 10⁻⁶ K. 3 Pa, with temperatures typically ranging from 35K to 350K. The lower pressure limit of approximately 0.1 Pa is a physical threshold ensuring that gas behavior satisfies the continuous medium assumption and that wind convection transport effects dominate (Peklat number Pe >> 1), which forms the basis for all correction models in this invention. This invention is particularly illustrated using a Martian surface environment with a pressure of approximately 600 Pa and a temperature of approximately 190K to 300K as a typical example.

[0051] The quantitative relationship model and initial parameters are shown in the following formulas, and these models also form the mathematical basis for subsequent real-time inversion: a) Quantitative relationship model between concentration and wind direction angle The concentration value when the wind angle α = 0° is C 10 ; ; ...(1) Formula (1) represents the relationship between the concentration at each point on the horizontal secant line perpendicular to the prevailing wind direction and the wind direction angle, where C1 is the gas concentration (mol / m³) at different points on the horizontal secant line. 3 x is the abscissa of the secant (m), with its origin (x=0) located on the axis where the wind direction angle is 0°. α is the wind direction angle corresponding to the monitoring point. μ is the abscissa of the intersection point of the main wind direction axis and the horizontal secant passing through the monitoring point and perpendicular to the main wind direction. σ is the model parameter (standard deviation) to be calibrated. y represents the horizontal distance from the monitoring point to the origin, such as... Figure 1 As shown. Figure 1 This is a schematic diagram of the system deployment. It shows the lander (dashed box), wind direction (gray arrow), drilling release source (P), lander outriggers (1, 2, 3, 4), and monitoring point S (single point example) located within a ±30° cone angle α downwind. Point O is the origin of the horizontal secant line passing through monitoring point S. C 10 The gas concentration is when α=0.

[0052] b) Quantitative relationship model of wind speed-model parameters with negative power law The wind speed (v) and model parameters (σ) in logarithmic coordinates have a linear relationship, as follows: ...(2) The simulation calculation values ​​of calibration coefficients a and b are: a = -0.8 and b = -0.01, which can be calibrated through wind tunnel experiments.

[0053] c) Source region gas release concentration correction model: C0 = k × C 10 m ...(3) Where C0 is the corrected concentration of the gas released from the source region. The simulation calculation values ​​of the calibration constants k and m are k=1.6 and m=1.02, respectively, and can be calibrated through wind tunnel experiments.

[0054] d) Source-strength inversion relationship model: ...(4) Where S is the volume source term to be determined (mol / (m)). 3 ·s)), V is the wind speed (m / s); the specific numbers in formula (4) are derived from the simulation calculation values ​​of the established physical model.

[0055] like Figure 3 As shown, the calibration method includes the following steps performed sequentially: Step S1: Model parameter calibration (ground preparation stage).

[0056] This step is completed on the ground and aims to obtain the parameters a, b, k, m in the model formulas (1)-(4) through low-pressure wind tunnel simulation experiments.

[0057] Step S2: Real-time measurement (on-orbit execution phase).

[0058] During the celestial surface sampling drilling process, the system simultaneously collects the following data: The steady-state concentration data C1 at the monitoring point comes from the core gas analyzer deployed according to the above principles. Real-time wind speed V. Real-time wind direction angle α, i.e., the angle by which the line connecting the monitoring point and the release source deviates from the prevailing wind direction.

[0059] Step S3: Source region concentration correction.

[0060] The purpose of this step is to correct the concentration C1 at the monitoring point back to the equivalent concentration C0 of the release source on the main wind direction axis.

[0061] First, substitute C1 and α into the concentration-wind direction angle Gaussian distribution model formula (1) calibrated in step S1, and obtain the equivalent concentration value C in the prevailing wind direction (when α=0°) through model inversion calculation. 10 .

[0062] The model parameter σ can be calculated from the wind speed V using formula (2).

[0063] Subsequently, using the C0 (source region center concentration) and C20 pre-established through simulation and experimentation, 10 The quantitative correlation formula (3) is used to calculate the corrected concentration C0 of the gas release source area at this wind speed.

[0064] Step S4: Source strength inversion.

[0065] Based on the corrected source area concentration and real-time wind speed, this step calculates the actual gas release rate according to formula (4).

[0066] Substitute the corrected source concentration C0 and the real-time wind speed V into the source intensity inversion relationship model calibrated in step S1 to directly calculate the volumetric source term S.

[0067] Finally, by integrating S over the geometric volume of the release source, the total source strength of the gas (mol / s) can be obtained.

[0068] The preferred embodiment of the present invention will now be described in detail with reference to the accompanying drawings. This embodiment uses an application on the surface of Mars as an example, but the present invention is not limited thereto.

[0069] 1. System Hardware Configuration and Layout Reference Figure 1 The image shows the lander (dash box), wind direction (gray arrow), drilling gas release source (P), lander legs (1,2,3,4), and monitoring point S located within a cone angle a of ±30° downwind (single-point deployment example).

[0070] The monitoring system implemented here is deployed on a Mars lander. The lander typically comprises a main platform and several outriggers. Figure 1 (The legs are shown as 1, 2, 3, and 4).

[0071] Gas release source (P): This is typically the location on the Martian surface between the landing vehicle's legs where it performs sampling and drilling operations.

[0072] The monitoring system includes the following core components: 1) Gas Concentration Detector: In this embodiment, a mass spectrometer is used as the core gas analyzer for the gas concentration detector, with sufficient sensitivity to detect volatile gas concentration changes at the ppb level. This gas concentration detector is fixedly installed at the bottom of the lander platform, with its air inlet facing the Martian surface and located within a ±30° cone angle downwind of the gas release source. The location of this air inlet is defined as monitoring point P1, used to collect gas concentration data.

[0073] 2) Wind field sensor: A three-dimensional ultrasonic anemometer is used, which is fixedly installed on the top of the lander platform to measure wind speed (V) and wind direction (θ) in real time.

[0074] 3) Data Processing Unit: The data processing unit is a data processing and control unit. This data processing unit is connected to the mass spectrometer and ultrasonic anemometer via cables, receives their measurement data, and has a built-in dedicated software program to perform the calibration methods described below.

[0075] 2. Implementation process of the calibration method Reference Figure 3 The flowchart of the calibration method shown corresponds to steps S1-S4 described in the technical solution of this invention. The entire process is divided into two stages: ground preparation and on-orbit execution.

[0076] Phase 1: Ground preparation and parameter calibration (Step S1) This phase, completed in the Earth laboratory, aims to establish a mathematical model and determine key parameters for subsequent on-orbit inversion through low-pressure wind tunnel calibration experiments.

[0077] (1) Set up a simulated environment: Reproduce the typical environmental conditions of the Martian surface in a low-pressure wind tunnel (pressure: about 600 Pa, temperature: 190 K to 300 K range) and inject the target gas (e.g., water vapor).

[0078] (2) Data collection: Under different wind speeds (V: 1~10m / s), the gas concentration (C1), the concentration at the source center (C0), and the concentration along the downwind axis (C0) at different angles (α) and distances downwind were measured. 10 ).

[0079] (3) Model parameter calibration: Concentration-wind direction angle model (Formula 1): Gaussian function fitting is performed on the concentration-angle data collected at each specific wind speed to obtain a series of model parameters (standard deviation σ) that correspond one-to-one with the wind speed. Usually, at least three σ values ​​at different wind speeds are required for subsequent analysis.

[0080] Wind speed-model parameter relationship (Formula 2): Perform linear regression on logarithmic coordinates to determine the specific values ​​of coefficients a and b for different wind speeds (V) and their corresponding standard deviations (σ). For example, calibration experiments yielded a = -0.80, b = -0.01.

[0081] Source region correction concentration model (Formula 3): By measuring the concentration at the center of the source region (C0) and the concentration along the downwind axis of the prevailing wind (C... 10 To establish a quantitative relationship between the two, the coefficients k and m are calibrated. For example, the calibration experiment yields: k = 1.60, m = 1.02.

[0082] (4) Parameter solidification: The calibrated coefficients (a, b, k, m) and the final determined mathematical model (formulas 1-4) are burned into the memory of the data processing unit.

[0083] Phase 2: Real-time on-orbit measurement and inversion (steps S2-S4) This phase is executed automatically during Mars surface sampling operations.

[0084] 1) Step S2: Real-time measurement The system starts up, and the wind field sensor continuously measures the real-time wind speed (V). real ) and real-time wind direction (θ) real ).

[0085] The data processing unit uses real-time wind direction (θ) real Given the fixed location of monitoring point P1 and the source P, calculate the real-time wind direction angle (α) relative to the prevailing wind direction of the line connecting P1 and the source P. real ).

[0086] Validity judgment: The data processing unit judges α real Is the absolute value ≤ 30°? If yes, the gas concentration detector is triggered to measure at monitoring point P1 and record a stable concentration reading (C1). If not, the current monitoring point is deemed invalid, and the system waits for a change in wind direction or (in a multi-point deployment scheme) selects another valid monitoring point.

[0087] In this single-point implementation, assuming α real Within the effective scope, continue with subsequent steps.

[0088] 2) Step S3: Source region concentration correction The data processing unit calls the pre-stored formula (2) and uses the real-time wind speed V real Calculate the model parameter σ under the current wind conditions.

[0089] Then, the pre-stored formula (1) is called to measure the concentration C1 and the wind direction angle α. real Substituting the calculated σ into the equation, we can deduce the equivalent concentration C on the downwind axis (α=0°) of the prevailing wind. 10 . Finally, the pre-stored formula (3) is invoked, and C is used. 10 The corrected concentration C0 in the release source region was calculated. 1) Step S4: Source Strength Inversion The data processing unit calls the pre-stored source strength inversion model (Formula 4) and combines the corrected source concentration C0 and real-time wind speed V. real Substitute the values ​​and directly calculate the volumetric release source strength S of the gas (unit: mol / (m²)). 3 s)).

[0090] Finally, based on the volume of soil disturbed by the sampling drilling operation (V) soil(where S is a known task parameter). Integrating with respect to S yields the total gas release source strength Q (in mol / s): Q = S × V soil ; As an alternative implementation method (multi-monitoring point deployment): Reference Figure 2 In areas with variable wind direction, a better implementation scheme based on a multi-sampling system can be adopted. The emission source P is represented by a triangle indicating a gas concentration detector, with small solid circles around it representing multiple monitoring sampling points. Gray arrows indicate wind direction; the data processing unit can dynamically select effective monitoring sampling points based on wind direction. The system includes a core mass spectrometer fixedly mounted on the lander platform and a multi-intake system. The multi-intake system contains multiple (e.g., eight) sampling ports, arranged in a ring around the bottom of the lander platform at predetermined angular intervals (e.g., 30°) centered on the emission source P. Each sampling port is connected via a pipe to the inlet of a multi-port selector valve, the outlet of which is connected to the inlet of the core mass spectrometer.

[0091] The data processing unit can select which sampling port's gas is sent to the mass spectrometer by controlling the valve selection. During on-orbit operation, the data processing unit dynamically calculates the wind direction angle of the line connecting each sampling port and the release source based on the real-time wind direction. Subsequently, it automatically opens the valves corresponding to one or more sampling ports located within a ±30° cone angle downwind of the current location, and uses the concentration data obtained from the core gas analyzer as the valid C1 value for subsequent calibration procedures. This solution achieves effective monitoring of multiple locations using only a single core gas analyzer, realizing an optimal balance between resource optimization and system performance.

[0092] An alternative to multi-monitoring deployment can be a fixed deployment of multiple core gas analyzers (as described in deployment method three above): the gas concentration detector comprises multiple core gas analyzers (such as multiple mass spectrometers), each fixedly positioned at a different location from the gas release source. The inlet of each core gas analyzer serves as its monitoring point. This method is typically used when conditions permit and it is necessary.

[0093] As another alternative, complex multi-monitoring configuration, the gas concentration detector can include multiple core gas analyzers, each independently connected to a multi-inlet system. However, this increases system complexity and weight. Similarly, this approach is typically used only when conditions permit and necessity dictate it.

[0094] Universality explanation: The above describes the implementation of this invention in detail using Mars as an example. It is important to emphasize that this invention addresses the common technical problem of "quantitative monitoring and inversion of gas in a low-vacuum, windy environment that satisfies the continuous medium assumption and where convective transport is dominant (Peklay number Pe>>1)". Its core principle—optimizing monitoring deployment and correcting concentrations using real-time wind field data to invert source strength—is based on this physical foundation and therefore has universal applicability.

[0095] The system architecture, deployment principles, and calibration methods of this invention are applicable to any celestial body with a surface atmospheric pressure higher than approximately 0.1 Pa and a dynamic wind field (such as Pluto and Triton). When applied to celestial bodies with significant differences in environmental parameters such as surface temperature and atmospheric composition, a suitable gas concentration detector must be selected, and all parameters in the quantitative relationship model (such as a, b, k, m, etc.) must be recalibrated in a low-pressure wind tunnel simulating the specific pressure, temperature, and atmospheric composition of the target celestial body. This implementation method, based on the same physical principle but adapted to the specific environment for parameter calibration, is still within the scope of protection of this invention.

[0096] Based on the above description of the specific embodiments of the present invention, the technical innovations and significant technical effects of the present invention can be summarized as follows: 1. Systematic Innovation: For the first time, a systematic solution was proposed that combines the "optimized layout principle of monitoring points (±30° cone angle) and distance from the source area not exceeding 1.5m" with the "concentration correction algorithm based on real-time wind field" for low-vacuum windy environments.

[0097] 2. Model innovation: For the first time, the relationship model of concentration, wind direction angle and velocity is applied to describe the quantitative distribution law of gas plume under this special environment, and a complete and accurate inversion chain from single-point monitoring concentration to source strength is established.

[0098] 3. Methodological Innovation: The proposed correction method has a clear process and achieves engineering operability through four steps: parameter calibration, real-time measurement, concentration correction, and source intensity inversion. It provides a universal technical path for solving the quantitative monitoring problem in such environments.

[0099] 4. Advantages of the Solution: Monitoring points can be fixed at a single point (meeting deployment principles) or dynamically selected at multiple points. The latter can effectively cope with drastic changes in wind direction and improve the system's robustness. System Structure Innovation: Two efficient implementation paths are proposed: one is a distributed measurement path, which deploys multiple independent gas concentration detectors (or multiple core analysis modules) to achieve parallel monitoring at multiple points; the other is a centralized measurement path, which adopts a centralized sampling scheme based on a multi-intake system and valves, using a core gas analyzer to poll and analyze the gas from sampling ports at different locations. The latter significantly reduces system weight, cost, and power consumption while ensuring monitoring effectiveness.

[0100] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit it. Although the present invention has been described in detail with reference to the embodiments, those skilled in the art should understand that modifications or equivalent substitutions to the technical solutions of the present invention do not depart from the spirit and scope of the technical solutions of the present invention, and all such modifications or substitutions should be covered within the scope of the claims of the present invention.

Claims

1. A gas release monitoring system for the surface of a low-vacuum celestial body, deployed on a lander, the monitoring system comprising: Gas concentration detectors are used to measure the gas concentration at the monitoring point from the gas release source; wind field sensors are used to measure wind speed and wind direction. The data processing unit is communicatively connected to the gas concentration detector and the wind field sensor, receives measurement data, and is configured to perform released gas monitoring correction. The gas concentration detector and the wind field sensor are fixedly installed on the lander; the location conditions of the monitoring point are: the angle between the line connecting the monitoring point and the gas release source and the real-time downwind direction of the gas release source is within the range of ± preset angle, and the distance between the monitoring point and the gas release source does not exceed the preset distance.

2. The monitoring system according to claim 1, characterized in that, It includes multiple gas concentration detectors; the gas concentration detectors are connected to the data processing unit; the data processing unit is configured to select gas concentration detectors that meet the location conditions at the monitoring point based on the real-time wind direction measured by the wind field sensor, and receive their measurement data.

3. The monitoring system according to claim 1, characterized in that, The gas concentration detector is fixed to the lander in one of the following three deployment methods: Deployment Method 1: The monitoring system includes a single gas concentration detector, with the gas concentration detector's inlet serving as the monitoring point. It is fixedly deployed downwind and meets the location conditions described above. Deployment Method Two: The monitoring system includes a gas concentration detector and a multi-channel air intake system. The multi-channel air intake system includes multiple sampling ports located at different locations of the gas release source, branch pipelines connecting each sampling port to the gas concentration detector, and valves for controlling the opening and closing of each branch pipeline. The data processing unit is further configured to control the valves based on the real-time wind direction measured by the wind field sensor to select at least one sampling port that meets the location conditions from the multiple sampling ports as a monitoring point, so that the gas concentration detector measures the gas concentration at the monitoring point. When multiple sampling ports are effective simultaneously, the average concentration is taken or the optimal value is selected based on signal quality. Deployment Method 3: Includes multiple gas concentration detectors, each fixedly deployed at different locations of the gas release source; the inlet of each gas concentration detector is its monitoring point; the data processing unit selects the measurement data of one or more gas concentration detectors whose monitoring points are located downwind and meet the location conditions, based on the real-time wind direction, as valid concentration input signals; when multiple gas concentration detectors are valid simultaneously, the average concentration is taken or the optimal value is selected based on signal quality.

4. The monitoring system according to claim 1, characterized in that, The data processing unit is also configured to: determine the validity of the current monitoring point based on the real-time wind direction; if the current monitoring point is invalid, wait for the wind direction to change.

5. The monitoring system according to any one of claims 1-4, characterized in that, The preset angle is 30°.

6. The monitoring system according to any one of claims 1-4, characterized in that, The preset distance is 1.5m.

7. A method for monitoring and correcting released gases on the surface of a low-vacuum celestial body, executed by the monitoring system according to any one of claims 1-4, characterized in that, Includes the following steps: Step S1: Parameter calibration; A model was built by simulating a low-vacuum environment, including: Concentration-wind direction angle quantitative relationship model; Quantitative model of the negative power law relationship between wind speed and model parameters; A source region gas emission correction concentration model is used to establish the source region center concentration C0 and the equivalent concentration C0 along the prevailing wind direction. 10 Quantitative correlation; Source strength inversion relationship model; Simulation experiments were conducted by adjusting wind speed and direction to predetermine the initial model parameters of the target gas under a specific low vacuum environment of the target celestial body, and the quantitative relationship model was determined through wind tunnel experiments for calibration. Step S2: Real-time measurement; collect the following data: The gas concentration C at the monitoring point of the gas release source 1， Real-time wind speed V, real-time wind direction angle α; Step S3: Source region concentration correction; The gas concentration C1 at the monitoring point is corrected back to the equivalent concentration C0 of the gas release source along the prevailing wind axis; where... First, substitute the gas concentration C1 and wind direction angle α into the concentration-wind direction angle quantitative relationship model calibrated in step S1, and obtain the equivalent concentration C in the prevailing wind direction through model inversion calculation. 10； The model parameter σ in the concentration-wind direction angle quantitative relationship model is calculated based on the wind speed V through the wind speed-model parameter negative power law quantitative relationship model. Subsequently, using the source region gas release correction concentration model, the correction concentration C0 of the gas release source region at this wind speed was calculated. Step S4: Source strength inversion; where, Substitute the corrected source region concentration C0 and real-time wind speed V into the source intensity inversion relationship model calibrated in step S1 to calculate the volume source term S. Integrating S over the geometric volume of the release source yields the total source strength of the gas release.

8. The method for monitoring and correcting released gases on the surface of a low-vacuum celestial body according to claim 7, characterized in that, The quantitative relationship model between concentration and wind direction angle is as follows: ； ...(1)； Where C1 represents the gas concentration at different points on the horizontal secant line perpendicular to the prevailing wind direction within the observation surface, x represents the distance from the monitoring point on the secant line to the intersection of the prevailing wind axis and the horizontal secant line, α represents the wind direction angle, μ represents the distance from the horizontal secant line to the monitoring point, and σ represents the model parameters to be calibrated; the concentration value at wind direction angle α = 0° is C. 10 ; The quantitative model for the negative power law relationship between wind speed and model parameters is as follows: ....(2)； Where a, b, and σ are the model parameters calibrated in step S1; V is the wind speed; The corrected concentration model for the gas released from the source region is as follows: C0 = k× C 10 m ... (3) Where C0 is the corrected concentration of the gas released from the source region. k and m are the model parameters calibrated in step S1; The source strength inversion relationship model is as follows: . .(4) Where S is the volume source term to be determined, and V is the wind speed.

9. The method for monitoring and correcting released gases on the surface of a low-vacuum celestial body according to claim 7 or 8, characterized in that, In step S1, through low-pressure wind tunnel calibration experiments, the quantitative relationship model parameters of the target gas under the specific low vacuum and temperature environment of the target celestial body are determined in advance, specifically including: In a low-pressure wind tunnel, a simulated environment is built and the target gas is injected. Data collection: Under different wind speeds V, the gas concentration C1 at different angles α and distances downwind was measured; Model parameter calibration includes the following: Formula (1) for the quantitative relationship model of concentration-wind direction angle: For each set wind speed V, the concentration-angle data collected at that wind speed is fitted with a Gaussian function to obtain the model parameter σ corresponding to that wind speed; In order to establish a reliable quantitative relationship, the model parameter σ at at least three different wind speeds V needs to be obtained. Formula (2) for the quantitative relationship model of wind speed-model parameter negative power law: Perform linear regression of different wind speeds V and corresponding model parameters σ in double logarithmic coordinates to determine the specific values ​​of the correction coefficients a and b; Formula (3) of the source region correction concentration model: by measuring the concentration C0 at the center of the source region and the concentration C on the downwind axis of the prevailing wind. 10 A quantitative relationship between the two was established, and the correction coefficients k and m were determined.

10. The method for monitoring and correcting released gases on the surface of a low-vacuum celestial body according to claim 7 or 8, characterized in that, Step S2: Real-time measurement, which also includes: judging the validity of the monitoring point. If it is valid, the gas concentration detector is triggered to perform measurement; otherwise, the process waits for the wind direction to change.

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