Underground gas sampling detection system and method

Abstract

The invention discloses an underground gas sampling detection system and method in the technical field of gas detection. The method comprises the following steps: acquiring underground gas sampling data acquired by a self-adaptive sampling module; based on underground gas sampling data, after the target volume flow is calculated through a dynamic flow control equation, the power of a micro-flow pump of the self-adaptive sampling module is adjusted in real time; based on underground gas sampling data, after a leakage risk index is calculated in real time through a leakage risk index equation, whether nitrogen blowback purification is started or not is judged; and based on underground gas sampling data, predicting the concentration through the steady-state concentration prediction model, and judging whether to trigger the start of the micro gas chromatograph-mass spectrometer or not. The influence of air pressure fluctuation is eliminated through dynamic flow control, the sample spatial representativeness is ensured, the thermorheological effect is overcome through a temperature compensation mechanism, and the sampling precision is greatly improved.

Description

Technical Field

[0001] The present invention relates to an underground gas sampling and detection system and method, belonging to the technical field of gas detection. Background Art

[0002] Underground gas sampling and detection are generally achieved through gas detectors. A gas detector is an instrument and tool for detecting gas leakage concentration, including: portable gas detectors, handheld gas detectors, fixed gas detectors, online gas detectors, etc. It mainly uses gas sensors to detect the types of gases present in the environment. A gas sensor is a sensor used to detect the composition and content of gases.

[0003] In the prior art, underground gas sampling methods mainly rely on passive diffusion samplers or simple pump suction devices. Static sampling cannot reflect the spatio-temporal dynamic changes of gas concentration (especially in areas with complex geological structures), resulting in insufficient sample representativeness. Summary of the Invention

[0004] The purpose of the present invention is to overcome the deficiencies in the prior art and provide an underground gas sampling and detection system and method. By dynamically controlling the flow rate, the influence of air pressure fluctuations is eliminated to ensure the spatial representativeness of the sample. The temperature compensation mechanism overcomes the thermorheological effect, and the sampling accuracy is greatly improved.

[0005] To achieve the above purpose, the present invention is implemented by the following technical solutions:

[0006] In the first aspect, the present invention provides an underground gas sampling and detection method, including:

[0007] Obtain the underground gas sampling data collected by the adaptive sampling module;

[0008] Based on the underground gas sampling data, after calculating the target volume flow rate through the dynamic flow control equation, adjust the micro-flow pump power of the adaptive sampling module in real time;

[0009] Based on the underground gas sampling data, calculate the leakage risk index in real time through the leakage risk index equation, and determine whether to start nitrogen backwashing and purification;

[0010] Based on the underground gas sampling data, predict the concentration through the steady-state concentration prediction model, and determine whether to trigger the start of the micro gas chromatography-mass spectrometry instrument.

[0011] Further, the adaptive sampling module includes a multi-stage anti-blocking probe, a piezoelectric ceramic micro-flow pump, and a distributed temperature and pressure sensor array. The multi-stage anti-blocking probe is the terminal component in direct contact with the formation. The tip of the probe penetrates the ground surface and the main body is buried at the target sampling depth. The distributed temperature and pressure sensor array is integrated at key axial nodes inside the probe, with a set arranged every 0.5 meters along the length of the probe. It includes a temperature sensor embedded in the outer wall of the probe and a pressure sensor installed in the air flow channel inside the probe. The piezoelectric ceramic micro-flow pump is installed in the ground base control box and is connected to the probe base flange through a pressure-resistant pipeline, with the distance from the probe inlet not exceeding 1.5 meters.

[0012] Further, the calculation formula for the target volume flow rate is:

[0013]

[0014] In the formula: Q set is the target volume flow rate; d is the inner diameter of the sampling probe; P s is the absolute pressure at the sampling point; P a is the environmental reference pressure; ρ is the gas density under standard conditions; K t is the temperature compensation coefficient; ΔT is the temperature difference between the probe and the environment; C d is the flow resistance correction factor.

[0015] Further, the calculation formula for the leakage risk index is:

[0016]

[0017] In the formula: R L is the leakage risk index; t0 is the starting time of monitoring; t is the current time; is the pipeline pressure change rate; λ is the pressure attenuation coefficient; τ is the integral time variable; T is the temperature; is the axial temperature gradient; α is the heat conduction weight factor.

[0018] Further, determining whether to start nitrogen backflush purification includes: starting the nitrogen backflush purification program to remove the residual gas in the pipeline when the leakage risk index is greater than 0.85, otherwise not starting.

[0019] Further, the steady-state concentration prediction model is:

[0020]

[0021] In the formula: C pred (t) is the predicted concentration at time t; C0 is the initial background concentration; A kis the adsorption coefficient of the k-th component; β is the diffusion kinetic parameter; t is the current moment; n is the number of target gas components; ε is the concentration change rate threshold; q is the confidence factor; C i is the historical concentration sequence; m is the number of detections; is the average concentration.

[0022] Further, determining whether to trigger the start of the micro gas chromatography-mass spectrometry instrument includes: in response to trigger the start of the micro gas chromatography-mass spectrometry instrument when, otherwise do not trigger.

[0023] In a second aspect, the present invention provides an underground gas sampling and detection system, including:

[0024] Data acquisition module: acquiring underground gas sampling data collected by the adaptive sampling module;

[0025] Flow rate adjustment module: based on the underground gas sampling data, after calculating the target volume flow rate through the dynamic flow rate control equation, adjust the micro flow pump power of the adaptive sampling module in real time;

[0026] Leakage detection module: based on the underground gas sampling data, after calculating the leakage risk index in real time through the leakage risk index equation, determine whether to start nitrogen backflushing and purification;

[0027] Concentration prediction module: based on the underground gas sampling data, predict the concentration through the steady-state concentration prediction model, and determine whether to trigger the start of the micro gas chromatography-mass spectrometry instrument.

[0028] In a third aspect, the present invention provides an underground gas sampling and detection device, including a processor and a storage medium;

[0029] The storage medium is used to store instructions;

[0030] The processor is used to operate according to the instructions to execute the steps of the method according to any one of the above.

[0031] In a fourth aspect, the present invention provides a computer-readable storage medium, on which a computer program is stored, and when the program is executed by a processor, the steps of the method according to any one of the above are implemented.

[0032] Compared with the prior art, the beneficial effects achieved by the present invention:

[0033] This solution eliminates the influence of air pressure fluctuations through dynamic flow control, ensuring the representativeness of the sample space. The temperature compensation mechanism overcomes the thermorheological effect, greatly improving the sampling accuracy. It solves the problem that static sampling cannot reflect the spatio-temporal dynamic changes of gas concentration (especially in areas with complex geological structures), resulting in insufficient sample representativeness. The leakage risk index quantitatively evaluates to achieve pollution warning, and the self-purification system reduces the probability of cross-contamination to a negligible level, enhancing the anti-pollution ability. The steady-state prediction model avoids ineffective transient sampling, and the multi-component parallel analysis shortens the response cycle, essentially optimizing the detection efficiency. Edge-cloud collaborative computing reduces the frequency of manual intervention, and the adaptive probe design extends the maintenance cycle, structurally reducing the operation and maintenance costs. BRIEF DESCRIPTION OF THE DRAWINGS

[0034] The accompanying drawings forming a part of this invention are used to provide a further understanding of the invention. The schematic embodiments and descriptions thereof of the invention are used to explain the invention and do not constitute an improper limitation to the invention. In the drawings:

[0035] Figure 1 It is a schematic flow chart of a method for underground gas sampling and detection provided in Embodiment 1 of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0036] The present invention will be described in detail below with reference to the drawings and in combination with embodiments. It should be noted that, without conflict, the embodiments and features in the embodiments of the present invention can be combined with each other.

[0037] The following detailed descriptions are all exemplary descriptions, aiming to provide further detailed descriptions of the present invention. Unless otherwise specified, all technical terms used in the present invention have the same meaning as commonly understood by those of ordinary skill in the art to which the present invention pertains. The terms used in the present invention are only for the purpose of describing specific embodiments and are not intended to limit the exemplary embodiments of the present invention.

[0038] Embodiment 1:

[0039] An underground gas sampling and detection method. This solution is implemented by an adaptive sampling module, an edge computing module, an on-line detection module, and a cloud analysis platform. Among them: The adaptive sampling module includes a multi-stage anti-blocking probe (with a self-cleaning coating), a piezoelectric ceramic micro-flow pump (response time < 50 ms), and a distributed temperature and pressure sensor array. The multi-stage anti-blocking probe is the terminal component in direct contact with the formation. The tip of the probe penetrates the ground surface (e.g., drills into soil / rock formation), and the main body is buried at the target sampling depth (e.g., 10 - 50 m underground); The distributed temperature and pressure sensor array is integrated at the key axial nodes inside the probe, with a set arranged every 0.5 meters along the length of the probe (a total of 3 - 5 sets), including a temperature sensor embedded in the outer wall of the probe (in direct contact with the soil) and a pressure sensor installed in the gas flow channel inside the probe (monitoring gas pressure). The piezoelectric ceramic micro-flow pump is installed in the ground base control box and is connected to the probe base flange through a pressure-resistant pipeline, with a distance ≤ 1.5 meters from the probe inlet (reducing gas transmission lag). The edge computing module includes a flow control unit (deploying a dynamic flow control algorithm) and a real-time leakage risk assessment unit. The on-line detection module includes a micro gas chromatography - mass spectrometry (GC-MS).

[0040] The specific working process is as follows: The probe penetrates the formation to the target depth, starts three-dimensional flow field modeling, realizes isokinetic sampling through dynamic flow control, triggers pipeline self-purification when the leakage risk exceeds the threshold, and triggers automatic detection when the steady-state concentration is predicted.

[0041] In this embodiment, the flow control unit of the edge computing module calculates the target volume flow based on the dynamic flow control equation, and adjusts the power of the micro-flow pump in real time to ensure that the gas enters the analysis pipeline in a laminar flow state. The calculation formula is:

[0042]

[0043] In the formula: Q set is the target volume flow (m 3 / s), which comes from the set value of the control system; d is the inner diameter of the sampling probe (m), which comes from the probe model parameters; P s is the absolute pressure at the sampling point (Pa), which comes from the real-time data of the pressure sensor; P a is the environmental reference pressure (Pa), which comes from the data of the atmospheric pressure sensor; ρ is the gas density under standard conditions (kg / m 3 ), which comes from the gas type database; K t is the temperature compensation coefficient (1 / ℃), which comes from the material thermal expansion coefficient table; ΔT is the temperature difference between the probe and the environment (℃), which comes from the difference of the dual temperature sensors; C d is the flow resistance correction factor, which comes from the flow field simulation calibration value.

[0044] In this embodiment, the leakage risk real-time assessment unit of the edge computing module calculates the leakage risk index in real time based on the leakage risk index equation. When the leakage risk index > 0.85 (set threshold), the leakage risk real-time assessment unit starts the nitrogen backflush purification program to remove the residual gas in the pipeline. The calculation formula is as follows:

[0045]

[0046] In the formula: R L is the leakage risk index (dimensionless), which is the basis for judging the risk level; t0 is the starting time of monitoring; t is the current time; is the pipeline pressure change rate (Pa / s), which is derived from the differential value of the high-frequency pressure sensor; λ is the pressure attenuation coefficient (1 / s), which is derived from the pipeline sealing calibration parameters; τ is the integration time variable; T is the temperature (°C), which is derived from the distributed temperature sensor array data; is the axial temperature gradient (°C / m), which is derived from the spatial difference calculation of the sensor; α is the heat conduction weight factor, which is derived from the experimental value of the material thermal conductivity.

[0047] In this embodiment, the cloud analysis platform predicts the concentration at time t according to the steady-state concentration prediction model. When it triggers the start of GC-MS to avoid transient sampling.

[0048]

[0049] In the formula: C pred (t) is the predicted concentration at time t (ppm); C0 is the initial background concentration (ppm), which is derived from the previous detection data; A k is the adsorption coefficient of the kth component, which is derived from the gas-solid interaction database; β is the diffusion kinetic parameter (1 / s), which is derived from the porous medium simulation results; n is the number of target gas components, which is derived from the detection task configuration file; ε is the concentration change rate threshold; q is the confidence factor (default 0.05); C i is the historical concentration sequence (from the previous m detections); m is the number of detections; C is the concentration average.

[0050] For methane monitoring in a landfill, three groups of probes (depth 15m / 25m / 35m) are arranged in the monitoring area, and the zero points of the temperature and pressure sensors are calibrated. The edge computing module obtains P s = 102.3 kPa, ΔT = 8.2 °C (data source: sensor) in real time, and calculates Q set = 0.17 L / min, controls the micropump speed to 2450 rpm, and dynamically adjusts the flow rate to maintain The risk assessment unit detects that abnormally rises to 12 °C / m, and calculates R L= 0.92 (> threshold 0.85), immediately start the 0.5 MPa nitrogen backflush for 30 seconds. Based on the data of the previous 10 minutes, the cloud platform predicts that the change rate of C pred (t) approaches 0, and sends a start command to the on-line detection module, and the GC-MS completes the synchronous analysis of methane / CO2 / H2S.

[0051] Compared with the traditional technology, this solution eliminates the influence of air pressure fluctuations through dynamic flow control, ensures the representativeness of the sample space, overcomes the thermorheological effect through the temperature compensation mechanism, and greatly improves the sampling accuracy; the leakage risk index quantitatively evaluates to achieve pollution warning, and the self-purification system reduces the probability of cross-contamination to a negligible level, enhancing the anti-pollution ability; the steady-state prediction model avoids invalid transient sampling, and the multi-component parallel analysis shortens the response cycle, essentially optimizing the detection efficiency; the edge-cloud collaborative computing reduces the frequency of manual intervention, and the adaptive probe design extends the maintenance cycle, structurally reducing the operation and maintenance costs.

[0052] Example Two:

[0053] An underground gas sampling and detection system that can implement the underground gas sampling and detection method described in Example One, including:

[0054] Data acquisition module: Acquire the underground gas sampling data collected by the adaptive sampling module;

[0055] Flow regulation module: Based on the underground gas sampling data, after calculating the target volume flow through the dynamic flow control equation, adjust the power of the micro-flow pump of the adaptive sampling module in real time;

[0056] Leakage detection module: Based on the underground gas sampling data, after calculating the leakage risk index in real time through the leakage risk index equation, determine whether to start the nitrogen backflush purification;

[0057] Concentration prediction module: Based on the underground gas sampling data, predict the concentration through the steady-state concentration prediction model, and determine whether to trigger the start of the micro gas chromatography-mass spectrometry.

[0058] Example Three:

[0059] The embodiment of the present invention also provides an underground gas sampling and detection device that can implement the underground gas sampling and detection method described in Example One, including a processor and a storage medium;

[0060] The storage medium is used to store instructions;

[0061] The processor is used to operate according to the instructions to execute the steps of the following method:

[0062] Acquire the underground gas sampling data collected by the adaptive sampling module;

[0063] Based on underground gas sampling data, the target volume flow is calculated through the dynamic flow control equation, and the micro-flow pump power of the adaptive sampling module is adjusted in real time;

[0064] Based on underground gas sampling data, the leakage risk index is calculated in real time through the leakage risk index equation to determine whether to start nitrogen backwash purification;

[0065] Based on underground gas sampling data, the concentration is predicted by a steady-state concentration prediction model to determine whether to trigger the start-up of the micro gas chromatography-mass spectrometry instrument.

[0066] Embodiment 4:

[0067] The embodiment of the present invention further provides a computer-readable storage medium, which can implement the underground gas sampling and detection method described in the first embodiment, and stores a computer program thereon, which implements the steps of the following method when the program is executed by a processor:

[0068] Acquiring underground gas sampling data collected by an adaptive sampling module;

[0069] Based on underground gas sampling data, the target volume flow is calculated through the dynamic flow control equation, and the micro-flow pump power of the adaptive sampling module is adjusted in real time;

[0070] Based on underground gas sampling data, the leakage risk index is calculated in real time through the leakage risk index equation to determine whether to start nitrogen backwash purification;

[0071] Based on underground gas sampling data, the concentration is predicted by a steady-state concentration prediction model to determine whether to trigger the start-up of the micro gas chromatography-mass spectrometry instrument.

[0072] It is known from common technical knowledge that the present invention can be implemented by other embodiments that do not deviate from its spirit or essential features. Therefore, the above disclosed embodiments are only illustrative in all respects and are not exclusive. All changes within the scope of the present invention or within the scope equivalent to the present invention are included in the present invention.

[0073] It will be appreciated by those skilled in the art that embodiments of the present invention may be provided as methods, systems or computer program products. Therefore, the present invention may take the form of a complete hardware embodiment, a complete software embodiment or an embodiment combining software and hardware. Moreover, the present invention may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0074] The present invention is described with reference to the flowcharts and / or block diagrams of methods, apparatuses (systems) and computer program products according to embodiments of the present invention. It should be understood that each flow and / or block in the flowchart and / or block diagram, and the combination of flows and / or blocks in the flowchart and / or block diagram, can be realized by computer program instructions. These computer program instructions can be provided to the processor of a general-purpose computer, a special-purpose computer, an embedded processor or other programmable data processing devices to generate a machine, so that the instructions executed by the processor of the computer or other programmable data processing devices generate means for realizing the functions specified in one flow Figure 1 one flow or multiple flows and / or blocks Figure 1 or in multiple blocks.

[0075] These computer program instructions can also be stored in a computer-readable memory that can direct a computer or other programmable data processing device to work in a specific manner, so that the instructions stored in the computer-readable memory generate a manufactured article including instruction means, and the instruction means realizes the functions specified in one flow Figure 1 one flow or multiple flows and / or blocks Figure 1 or in multiple blocks.

[0076] These computer program instructions can also be loaded onto a computer or other programmable data processing device, so that a series of operation steps are executed on the computer or other programmable device to generate a computer-implemented process, and thus the instructions executed on the computer or other programmable device provide steps for realizing the functions specified in one flow Figure 1 one flow or multiple flows and / or blocks Figure 1 or in multiple blocks.

[0077] 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 them. Although the present invention has been described in detail with reference to the above embodiments, those of ordinary skill in the art should understand that: modifications or equivalent replacements can still be made to the specific implementation manners of the present invention, and any modification or equivalent replacement that does not depart from the spirit and scope of the present invention shall be covered by the protection scope of the claims of the present invention.

Claims

1. An underground gas sampling and detection method, characterized in that Comprising: Obtaining underground gas sampling data collected by an adaptive sampling module; Based on the underground gas sampling data, after calculating the target volume flow rate through a dynamic flow control equation, the power of the micro flow pump of the adaptive sampling module is adjusted in real time; Based on the underground gas sampling data, after calculating the leakage risk index in real time through a leakage risk index equation, determining whether to start nitrogen backflush purification; Based on the underground gas sampling data, predicting the concentration through a steady-state concentration prediction model, and determining whether to trigger the start of a micro gas chromatography-mass spectrometry instrument.

2. The underground gas sampling and detection method according to claim 1, characterized in that, The adaptive sampling module includes a multi-stage anti-blocking probe, a piezoelectric ceramic micro flow pump, and a distributed temperature and pressure sensor array. The multi-stage anti-blocking probe is the terminal component in direct contact with the formation. The tip of the probe penetrates the ground surface and the main body is buried at the target sampling depth; the distributed temperature and pressure sensor array is integrated at key axial nodes inside the probe, with a group arranged every 0.5 meters along the length direction of the probe, including a temperature sensor embedded in the outer wall of the probe and a pressure sensor installed in the gas flow channel inside the probe; the piezoelectric ceramic micro flow pump is installed in the ground base control box and is connected to the probe base flange through a pressure-resistant pipeline, with a distance not exceeding 1.5 meters from the probe inlet.

3. The underground gas sampling and detection method according to claim 1, characterized in that, The calculation formula for the target volume flow rate is: Where: Q set is the target volumetric flow rate; d is the inner diameter of the sampling probe; P s is the absolute pressure at the sampling point; P a is the environmental reference pressure; ρ is the gas density under standard conditions; K t is the temperature compensation coefficient; ΔT is the temperature difference between the probe and the environment; C d is the flow resistance correction factor.

4. The underground gas sampling and detection method according to claim 1, characterized in that, The calculation formula for the leakage risk index is: Where: R L is the leakage risk index; t0 is the starting time of monitoring; t is the current time; is the pipeline pressure change rate; λ is the pressure attenuation coefficient; τ is the integration time variable; T is the temperature; is the axial temperature gradient; α is the heat conduction weight factor.

5. The underground gas sampling and detection method according to claim 1, characterized in that, it is determined that Whether to start nitrogen backflush purification includes: starting the nitrogen backflush purification program to remove the residual gas in the pipeline in response to the leakage risk index being greater than 0.85, otherwise not starting.

6. The underground gas sampling and detection method according to claim 1, characterized in that The steady-state concentration prediction model is: Where: C pred (t) is the predicted concentration at time t; C0 is the initial background concentration; A k is the adsorption coefficient of the k-th component; β is the diffusion kinetic parameter; t is the current time; n is the number of target gas components; ε is the concentration change rate threshold; q is the confidence factor; C i is the historical concentration sequence; m is the number of detections; is the average concentration.

7. The underground gas sampling and detection method according to claim 6, characterized in that, determining Whether to trigger the startup of the micro gas chromatography-mass spectrometry instrument, including: in response to When, trigger the startup of the micro gas chromatography-mass spectrometry instrument, otherwise do not trigger.

8. An underground gas sampling and detection system, characterized in that, Comprising: Data acquisition module: Obtaining underground gas sampling data collected by an adaptive sampling module; Flow adjustment module: Based on the underground gas sampling data, after calculating the target volume flow rate through a dynamic flow control equation, the power of the micro flow pump of the adaptive sampling module is adjusted in real time; Leakage detection module: Based on the underground gas sampling data, after calculating the leakage risk index in real time through a leakage risk index equation, determining whether to start nitrogen backflush purification; Concentration prediction module: Based on the underground gas sampling data, predicting the concentration through a steady-state concentration prediction model, and determining whether to trigger the start of a micro gas chromatography-mass spectrometry instrument.

9. An underground gas sampling and detection device, characterized in that, Comprising a processor and a storage medium; The storage medium is used to store instructions; The processor is used to operate according to the instructions to execute the steps of the method according to any one of claims 1 to 7.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the program is executed by the processor, the steps of the method according to any one of claims 1 to 7 are implemented.

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