2256 results about "Sample collection" patented technology

The invention discloses a security event log real-time monitoring and analyzing system and method for a power grid communication network, and relates to the technical field of network security management. The causal relationship graph building module is used for building a causal relationship graph of the target power grid communication network; the multi-dimensional correlation analysis module is used for collecting and analyzing multi-source heterogeneous log data in real time; the abnormal security event identification module is used for identifying an abnormal security event according to the causal relationship graph and the multi-dimensional correlation analysis result; and the attack chain tracking response module is used for tracking the attack chain. According to the method, the technical problem that the existing power grid communication network security monitoring lacks tracking of abnormal event evolution from the time dimension and cannot accurately identify and track a multi-stage attack chain is solved, and the effects of dynamically tracking the evolution process of the abnormal event and identifying a potential attack chain by establishing a time causal chain graph are achieved. And the detection precision and the response speed of the attack behavior are improved.

The invention relates to the technical field of artificial intelligence rescue, and discloses an unmanned aerial vehicle and robot dog rescue emergency system and method, and the system comprises an unmanned aerial vehicle cluster module which is used for air data collection, communication guarantee and emergency material distribution; the robot dog cluster module is used for ground environment detection, sample collection and special task execution; the communication cooperation module is used for ensuring information intercommunication and task cooperation between air-ground equipment; the central control module provides task instructions for the unmanned aerial vehicle cluster and the robot dog cluster; the human-computer interaction interface module is used for realizing effective communication between rescue workers and the system; the modules work cooperatively, multi-source data acquisition, three-dimensional scene reconstruction, semantic segmentation, risk assessment, fire spreading prediction and decision support information generation of a disaster site are realized, and a reliable basis is provided for rescue command decision.

A remote test apparatus is configured to simulate an environment of at least one remotely located room and configured to receive at least one air sample from the at least one remotely located room. The apparatus includes a sealed enclosure forming an interior cavity and including an inlet in connection with the at least one remotely located room and an outlet in connection with a sample collection unit. The sample collection unit is configured to communicate the at least one air sample from the remotely located room at a first flow rate. The apparatus further includes at least one sensor disposed in the interior cavity and at least one air transfer unit configured to transfer test air from the interior cavity of the sealed enclosure to the at least one sensor at a second flow rate.

The invention discloses a karst underground river system multi-source pollution comprehensive quantitative traceability method, which comprises the following steps: S1, multi-dimensional sample collection and new pollutant screening: carrying out multi-period sampling on a water body, measuring conventional water quality indexes and nitrogen and oxygen isotopes, screening new pollutants, and carrying out targeted quantification on characteristic new pollutants; s2, principal component analysis dimension reduction and pollution factor identification: carrying out principal component analysis on conventional indexes and new pollutant data, extracting principal components of which the cumulative contribution rate exceeds 85%, identifying composite pollution factors, and eliminating secondary interference factors; s3, nitrogen and oxygen isotope auxiliary verification and denitrification elimination: eliminating denitrification interference by utilizing the ratio of delta 15N-NO3 <-> to delta 18O-NO3 <-> in combination with underground water burial depth and runoff velocity, and distinguishing the nitrate source as a chemical fertilizer, soil nitrogen or sewage and wastewater; and S4, PMF model optimization and pollution source quantification: inputting the conventional indexes and the new pollutant concentration matrix into a PMF model, and analyzing the contribution rate of each pollution source.

The invention discloses a soil heavy metal content estimation method and device, and relates to the technical field of soil heavy metal estimation.The method comprises the steps of sample collection and data acquisition, specifically, based on geographic information of a research area, soil samples are collected through a layered and partitioned sampling method; according to the method, comprehensive and accurate collection and data acquisition of soil samples are realized through a layered and partitioned sampling method in combination with a high-precision positioning and measuring instrument, the sample representativeness and the data accuracy are ensured, and through an improved correlation analysis algorithm and a depth model based on feature fusion, the soil sampling accuracy is improved. Accurate analysis and efficient modeling of correlation between environmental magnetic parameters and heavy metal content are realized, prediction precision is improved, dynamic optimization of model parameters is realized by applying a self-adaptive step length strategy in model verification and optimization, model stability and generalization ability are guaranteed, and all modules of the device work cooperatively, so that the reliability of the device is improved. And deep analysis of heavy metal sources and migration and transformation rules is realized by using a geochemical analysis module and related models.

The invention belongs to the technical field of high-performance composite materials, and discloses a carbon fiber reinforced thermoplastic composite material performance database, a construction method and application thereof, and the method comprises the following steps: S1, database structure construction; s2, experimental sample collection and data standardization; s3, feature engineering and variable reduction; s4, training a machine learning model; s5, constructing and verifying an adaptive model; and S6, data expansion and feedback optimization. According to the method, material performance prediction and formula parameter reverse design under target performance are realized through systematic acquisition and normalization processing of three types of data of material components, preparation process and performance characterization and building of a nonlinear mapping model among a material structure, a process and performance through a machine learning method. The database can be used for intelligently recommending a high-performance composite material combination scheme, is suitable for rapid screening and customized development of various thermoplastic composite materials, effectively reduces the research and development cost and development cycle, and improves the material design efficiency.

The invention relates to the technical field of biomedicine, in particular to a hepatic cell differentiation degree evaluation method based on multi-omics data, which comprises the steps of sample collection and preprocessing, transcriptomics, proteomics and metabonomics data analysis, multi-omics data integration and modeling and result output. By integrating multi-level biological information, a multi-dimensional scoring model is constructed, the liver cell differentiation state is quantitatively evaluated, and a standardized grading system is provided for clinic. The method can solve the limitation of single omics analysis, improves the evaluation accuracy and reliability, has universality, can be popularized to other malignant tumor research, and assists precise medical development.

The invention belongs to the technical field of aircraft oil leakage monitoring, and relates to an aircraft oil leakage detection method based on a high-sensitivity mass spectrometry technology, and the method comprises the steps: obtaining a time-resolved mass spectrogram of aviation kerosene molecules in a sample testing stage, and storing the time-resolved mass spectrogram in a database; then oil gas molecules are captured at leakage-prone points of an aircraft pipeline system through a gas collection probe, the captured oil gas molecules are transmitted to an ion source end of a proton transfer reaction mass spectrometer through a negative pressure transmission system to be ionized to generate ions, and the ions are analyzed by a mass analysis system to obtain a mass spectrum; comparing the mass spectrogram obtained by analysis with a time-resolved mass spectrogram in a database, and judging whether leakage occurs or not; based on the method, the problems of insufficient anti-interference capability, difficulty in sample collection and the like of a high-sensitivity mass spectrum oil gas leak detection method can be solved in a targeted manner, and the functions of environmental interference suppression, efficient collection of oil gas molecules, improvement of spatial scanning resolution and the like can be realized at the same time.

The present invention discloses a three-dimensional fluorescence portable water quality analyzer for pollution component determination and source tracing, and relates to the technical field of water quality analysis, the analyzer comprises the following components: a sample collection and processing module for collecting a water sample from a to-be-detected water body, filtering to remove impurities, and diluting the water sample according to a self-adaptive dilution multiple algorithm; fluorescence intensity information of a water sample under different excitation wavelengths and emission wavelengths is obtained through the three-dimensional fluorescence detection module, rich three-dimensional fluorescence spectrum data is formed, the real-time fluorescence lifetime imaging module is introduced, and by measuring the fluorescence lifetime of a fluorescent substance and utilizing the principle that different fluorescent substances have different fluorescence lifetime characteristics, the real-time fluorescence lifetime of the water sample is obtained. Various pollution components in the water sample are further distinguished and recognized, the pollution components can be accurately distinguished through fluorescence lifetime measurement and imaging, the accuracy of pollution component judgment is greatly improved, and a reliable basis is provided for accurate treatment of water quality pollution.

The invention provides a near infrared spectrum qualitative discrimination method and system, and the method comprises the steps: collecting a near infrared spectrum data set, and converting a one-dimensional spectrum sequence into a polar coordinate image; constructing a lightweight convolutional network architecture, and processing the polar coordinate image; k samples of each type are dynamically extracted from the training set, a support set is constructed based on the K samples and a few-sample strategy, and a query support similarity matrix is constructed through a cosine similarity algorithm; and judging the test set based on the query support similarity matrix, the support set and a preset threshold to obtain the highest similarity between the test set and the support set, and if the highest similarity exceeds the preset threshold, judging that the test set is a corresponding category. According to the method, the cost and time of sample collection and preparation can be reduced, the feature information of the spectral data is effectively extracted, and the method has relatively high flexibility during discrimination.

The invention discloses an ion adsorption type rare earth ore prospecting method based on a multi-element composite mineralization mode, and belongs to the technical field of rare earth ore geological exploration. The method comprises the following steps: firstly, collecting the existing exploration and research data of the known granite weathered crust type rare earth deposit; analyzing the ore-forming basic elements of the known granite weathering crust ion adsorption type rare earth ore deposit; then field geological survey and sample collection are carried out on the known granite weathered crust ion adsorption type rare earth ore deposit; determining each metallogenic mode element by utilizing analysis test data and field survey data; analyzing the formation cause of the ore deposit, establishing a prospecting mark, and constructing a multi-component composite mineralization mode of the granite weathering crust type rare earth ore deposit. And finally, prospecting target area prediction is carried out. For the known high-altitude granite weathering crust ion adsorption type rare earth deposit, multiple exploration technologies are organically fused, the special environment of the high-altitude area is optimized, a multi-element composite mineralization mode is constructed, and brand-new theoretical guidance and technical means are provided for prospecting of ion adsorption type rare earth ore in the high-altitude area.

The invention discloses a sampling device for engineering geological survey, which is used for solving the problems that the sampling device is low in sampling efficiency and cannot obtain a plurality of samples at one time, and relates to the field of geological survey, the sampling device comprises a drilling barrel for drilling, a sampling mechanism is arranged in the drilling barrel, and the sampling mechanism comprises a sampling disc; the sampling disc is provided with at least two pipe seats which are distributed in an annular array, the pipe seats are used for installing sampling pipes, each sampling pipe is composed of an outer pipe and an inner pipe, a driving part is arranged on one side of each outer pipe and used for driving the corresponding inner pipe to move in the axial direction of the outer pipe, the sampling disc is connected with the first rotating part, and at least one sampling hole is formed in the drilling cylinder; through cooperation of the sampling mechanism, the rotary sampling disc and the multiple independent sampling pipes, the sampling pipes can be triggered to sequentially stretch out of the sampling holes at different depths by one-time drilling of the drilling barrel, continuous layered sample collection and single-time or multi-time sampling at the same position are achieved, sampling pipe replacement or secondary drilling in the midway is not needed, and the sampling efficiency is improved. And the sampling efficiency, accuracy and diversity are improved.

The invention relates to an animal wound multi-modal intelligent identification method based on artificial intelligence, and the method comprises the steps: carrying out the feature extraction and semantic constraint through multi-modal sample collection and metadata extraction, employing an image preprocessing and text natural language processing technology, and combining a mixed visual model of a convolutional neural network and a visual Transform, and a large language model. A cross-modal attention mechanism and a semantic trigger are utilized to realize feature reweighting, clinical standard soft boundary constraints are introduced, and fuzzy semantic rules are converted into learnable constraints in a feature space, so that the accuracy and consistency of model judgment are improved. The method has adaptive optimization and incremental learning capabilities, and is beneficial to improving generalization and clinical applicability of exposure level intelligent judgment under different animals and complex wound types.

The utility model relates to the technical field of ecological environment detection, in particular to an underwater plankton sampling device which comprises a main body, a sampling driving component is arranged in the main body, and a control collecting component is fixedly connected in the main body; according to the utility model, the sampling depth can be accurately controlled by utilizing the depth sensor, in order to meet different research requirements, the tube wheel is driven by the motor to wind the sinking tube, and the automatic control driving mechanism can quickly complete sampling and can drive the sampling barrel to move up and down in water to realize sampling at different depths, so that the sampling efficiency is improved. The microprocessor is used for controlling the operation of the depth control mechanism and the driving mechanism, automatic sampling is realized, the inner wall of the sampling barrel is smooth, attachment and damage of plankton in the sampling process are avoided, automatic sampling is realized through the control unit, the operation is simple, and the use is easy; the sample collection container can be used for storing sampled plankton samples, so that the samples are prevented from being polluted.

The invention discloses a soil nitrogen leaching capacity monitoring method based on a frequency domain reflectometry, and relates to the technical field of soil water environment monitoring, in particular to a nitrogen leaching online monitoring method based on the frequency domain reflectometry (FDR), the Darcy law and a Van Genuchten (VG) model. And a monitoring method with high precision and sensitivity, multi-parameter synchronous detection and low cost is provided for the soil nitrogen leaching capacity. Comprising the following steps: 1, collecting and pretreating a soil sample; 2, placing the treated soil sample in a soil experiment cylinder; 3, inserting the multi-parameter sensors into the soil experiment cylinder in a layered manner; 4, 1000 ml of water is injected, and data acquisition is carried out; and 5, realizing soil nitrogen leaching capacity monitoring in combination with a Darcy law and a VG model.

The invention particularly provides a thermal elastohydrodynamic lubrication reliability evaluation method for a wind power sliding bearing. The method comprises the following steps: acquiring evidence measurement combination parameters; converting the evidence measurement combination parameters into probability measurement combination parameters, and determining mean value data of the probability measurement combination parameters; constructing a sample collection center based on the probability measurement combination parameters, substituting the sample collection center into the thermal elastohydrodynamic oil film iteration analysis model, and outputting minimum oil film thickness data; constructing a quadratic polynomial response surface function based on the current oil film safety threshold value, and selectively updating the sample collection center based on the quadratic polynomial response surface function to enable the sample collection center to approach the maximum possible failure focal element; determining credibility data and likelihood data of thermal elastohydrodynamic lubrication of the wind power sliding bearing based on the maximum possible failure focal element; and changing an oil film safety threshold value, and circularly executing the steps to obtain a thermal elastohydrodynamic lubrication reliability analysis result of the wind power sliding bearing. The accuracy of reliability is ensured, and the calculation cost is reduced.

The present invention provides a device for quantitatively collecting surface phytoplankton samples, comprising a sampling tube, wherein a bottom opening is provided at the bottom of the sampling tube, an annular baffle is provided on the inner side of the lower part of the sampling tube, an inlet valve is hinged on the baffle, a baffle is provided above the baffle, the inlet valve is connected to a float through a pull rope, the pull rope is passed through a hanging ring, the float is located above the baffle, a water outlet is provided on the lower side wall of the sampling tube, the water outlet is located above the baffle, a scale is provided on the side wall of the sampling tube, the starting end of the scale is flush with the center line of the water outlet, a side-permeable top cover is provided on the top of the sampling tube, a handle is provided above the side-permeable top cover, a float ring is detachably provided on the upper part of the outer wall of the sampling tube, and a counterweight is detachably provided on the lower part of the outer wall of the sampling tube; the sampling tube can be conveniently used for daily manual sample collection, and can also be applied to a buoy monitoring system, so that surface phytoplankton samples around the buoy body can be collected through auxiliary facilities, thereby improving the accuracy of the buoy monitoring system.

The invention relates to the technical field of component analysis, and discloses an X-ray fluorescence spectrum-based rock and ore silicate component analysis method, which comprises the following steps: S1, sample collection and pretreatment: collecting, crushing and drying an initial sample, S2, sample tabletting preparation, S3, standard sample preparation, S4, X-ray fluorescence spectrum analysis, and S5, data processing and result analysis. According to the method, a complex interference characteristic mode between elements can be automatically captured through an established deep learning model and learning of a large number of known components and fluorescence spectrum data, and in an example of correcting interference between multiple elements in rocks and mines, the model can utilize a network structure of the model and comprises an established convolutional layer, a pooling layer and a full-connection layer. Effective information is extracted from multiple groups of sample data, the interference relation between elements is accurately learned, and compared with a traditional method, the precision of analyzing the content of silicate components in rock ore is remarkably improved, so that a measurement result is closer to a real value.

The invention relates to a method for generating audio deep learning training data based on an adversarial neural network (GAN), which is a data synthesis technology based on a generative adversarial network (GAN) and is used for generating audio training samples of scarce categories so as to effectively expand the diversity of a data set. According to the method, the generation capability of the GAN model is utilized to simulate the audio samples of the rare category, and the problem that the samples of the rare category are insufficient in a traditional data set can be solved. Through the technology, researchers can reduce the cost of manually collecting samples, the consumption of human resources is greatly reduced, and the universality of the data set in category coverage is ensured at the same time. In addition, the generated diversified samples can enhance the generalization ability of the model, so that the model is more stable when processing changeful data in the real world. According to the method, the training efficiency of the model can be effectively improved, the robustness of the model in different scenes can be improved, and the precision and practicability of an audio classification task in specific field application are further promoted.

The invention discloses a method for depicting and analyzing a heavy non-aqueous phase pollution site based on microbial structure information, which comprises the following steps of: based on a historical geological survey report and a historical leakage event, defining a pollution analysis area, and constructing a site pollution conceptual model by combining high-density resistivity with a stable isotope tracer method; performing sample collection and detection on the target area to obtain area sample detection information; performing microflora analysis according to the regional sample detection information, and judging a potential pollution retention region of the target region to obtain pollution region analysis information; carrying out multi-source data coupling by combining pollution area analysis information and area sample detection information, and carrying out pollution field three-dimensional description on a target area to obtain an area DNAPLs pollution condition diagram; a degradation function gene interaction network is constructed, restoration potential grading is performed on a target area, and area restoration suggestion is performed, so that the limitation of a traditional investigation method is broken through, and accurate analysis and restoration assistance of pollution distribution are realized.

The invention belongs to the technical field of gas detection, and relates to a ship exhaust gas multi-component synchronous online monitoring system and method based on a laser Raman spectrum. The system comprises a sampling module, a preprocessing module, an analysis module, a data processing module, a blowback module and a flow measurement module. The method comprises the following steps: starting and self-checking the system; sample collection, pretreatment and flow velocity measurement; laser excitation and signal acquisition; carrying out spectrum analysis and concentration inversion; data output and system maintenance; and performing periodic automatic calibration. According to the invention, a complete monitoring process chain from sampling, pretreatment, flow measurement, analysis to back flushing is creatively integrated. The high-efficiency pretreatment and back flushing design greatly reduces the influence of high-dust and high-humidity environment on the analysis system, and ensures the long-term stability and reliability of the system.

The invention discloses an agent application system for controlling agents, which relates to the technical field of artificial intelligence and comprises the following modules: a first agent, a low-code model fine tuning module, a task evaluation and sample acquisition module, a user feedback module and an iterative optimization module. Based on an open source language large model, performing fine tuning through a data set with a reasoning process, performing fine tuning on a task execution strategy according to user feedback, evaluating task execution accuracy, execution time and resource consumption, and storing high-quality task execution data to a database; collecting and numeralizing user feedback, and optimizing a task execution strategy of the intelligent agent; fine-tuning hyper-parameters of the first intelligent agent through data in a low-code model fine-tuning module database to generate a second intelligent agent; based on the data of the low-code fine tuning module, the execution capability of the agent is continuously improved. The method can adapt to various complex task requirements, and the accuracy and efficiency of task execution and the resource utilization rate are remarkably improved.

The invention belongs to the technical field of vanadium enrichment mechanisms of phosphorus vanadium ores, and discloses a research method of a vanadium enrichment mechanism in a diagenetic stage of phosphorus vanadium ores, which comprises the following steps: S1, sample collection and treatment; s2, rock ore identification and mineral composition analysis; s3, analyzing the occurrence state and microcell morphology of vanadium; s4, performing geochemical analysis on the whole rock; s5, in-situ microcell geochemical analysis is carried out; s6, phosphorus nodule analysis; s7, comprehensive analysis and mineralization model establishment; according to the method, mineralogy, total rock geochemistry, micro-area surface scanning and other multi-scale and multi-means research methods are comprehensively utilized, and the vanadium occurrence state, the ore-forming fluid evolution and the phosphorus-vanadium coupling relation are finely described; in-situ microcell geochemical analysis is introduced into phosphorus nodule analysis, the internal structure, the growth sequence and element distribution of the phosphorus nodule are directly revealed, obvious frontier and systematicness are achieved, and reliable theoretical support is provided for accurate exploration of vanadium ore resources and green and efficient dressing and smelting process research and development.

The invention discloses a biological sample information data management method and system, and relates to the technical field of biological sample management, the system comprises a sample collection device, a management terminal, a sample storage device and a mobile terminal, and the specific steps are as follows: collecting a biological sample and performing preprocessing operation; performing quality inspection operation on the biological samples, and establishing a biological sample library; planning the storage position of the biological sample in the storage box, and monitoring the storage environment in real time; introducing a retrieval and sharing mechanism; remote application for use is provided through the mobile terminal; and the display panel displays the data information in real time. According to the method, standardization, structuring and traceability of sample information can be ensured, a management scheme for links such as sample collection, numbering, classification, storage, updating and retrieval is provided, efficient access and long-term storage of biological sample information are ensured, structured recording processing operation is performed on basic information, experimental data, sample states and the like of biological samples, and the efficiency is improved. And the data can be classified, queried and updated as required.

Provided herein are systems and methods for collecting biological samples. The sample may be collected using a sample collection device, where the device is configured to prevent oxidation of the sample within the device. The sample collection device may include a component that absorbs oxygen within the device. The sample collection device may be used to preserve the sample for transport. The sample collection device may be used to preserve the sample for later analysis. The sample collection device may include a membrane with one or more test areas for detecting one or more target analytes within the sample.

The invention discloses a seawater all-component efficient separation system based on intelligent regulation and control, and relates to the technical field of seawater treatment. Full-flow closed-loop control from original seawater sample collection, multi-parameter water quality monitoring, ion concentration detection, component identification and path prediction, confinement nanofiltration and air flotation impurity removal, temperature control degassing and ion threshold separation, high-value ion enrichment and multi-path extraction to real-time feedback regulation is realized; through self-adaptive generation of a separation path and precise adjustment of process parameters, the problems that a traditional seawater resource extraction method is poor in component adaptation capacity, high in energy consumption, poor in target object selectivity and the like are solved, the whole separation system remarkably improves the extraction efficiency and selectivity of trace high-value ions, and the separation efficiency is improved. The operation energy consumption and the human intervention degree are reduced, and the system has the remarkable advantages of modular structure, intelligent operation and wide application scene.

The utility model discloses an accurate sampling system for a coal sample, and belongs to the technical field of coal sampling. The accurate coal sample sampling system comprises a sampling device, a conveying mechanism and a sample collector, the transportation mechanism and the sample collector are respectively positioned on the outer side of the sampling device; the sampling device comprises a shell, a material cavity, a material guide notch, a motor and a sampling head; the material cavity is positioned in the shell of the sampling device; the material guide notch is positioned at the lower end of the shell; the motor is located at the rear end of the shell and fixedly connected with the shell. The periphery of the sampling head is always attached to and propped against the inner wall of the material cavity; the sampling head further comprises a sampling port and a sampling inclined plate; a cavity is formed in the sampling head; the sampling port is positioned at one side end of the sampling head; a sampling inclined plate is arranged on the lower wall, abutting against the inner wall of the material cavity, of the opening end of the sampling port, one end of the sampling inclined plate is fixedly connected with the sampling port, and the other end of the sampling inclined plate abuts against the inner wall of the material cavity all the time. The system can realize full-automatic sampling and sample collection, and is compact and reasonable in structure, firm, durable, reliable in performance and easy to maintain and repair.

The present invention discloses a method for analyzing sources of Cd / Pb combined polluted farmland soil using bimetallic isotopes (Cd—Pb), comprising the following steps: collecting respectively a soil sample and risk source samples through a sample collection device; determining respectively Cd isotope ratio and Pb isotope ratio of the soil sample and the risk source samples; plotting by using the Cd isotope ratio and the Pb isotope ratio of the soil sample and the risk source samples as coordinates, to obtain a projection plot of the isotope ratios; recognizing a pollution end-member polluting farmland soil through the projection plot of the isotope ratios to obtain a recognition result for the pollution end-member, and then confirming the pollution end-member; and calculating a relative contribution rate of the pollution end-member, to obtain an analysis result for the source of isotopes. The present invention uses the two metal isotopes of Cd—Pb to mutually restrict and confirm each other to solve the problem of poor analytical accuracy caused by similar or overlapping isotope values of samples and isotope fractionation, and realizes accurate recognition and quantitative analysis for the source of heavy metals Cd / Pb pollution of farmland soil.

A method for quality control checking GC apparatus including at least a main column, a sample collection loop, and a detector in fluid communication with a multiport valve includes making first and second detector measurements when the multiport valve is set in corresponding first and second positions and a carrier gas inlet is open. The first position provides fluid communication between the carrier gas inlet, the sample collection loop, the main column, and the detector and the second position provides fluid communication between the carrier gas inlet, the main column, and the detector such that carrier gas bypasses the sample collection loop. The method further includes comparing the first and second detector measurements to check at least the sample loop and the multiport valve for leaks.

The invention relates to the technical field of spaceflight sealing, in particular to a multi-mode pressure sealing device and method for heating and extracting extraterrestrial star soil gas. The device comprises a transposition sealing disc, a positioning base disc and a distributed driving actuator, a flow guide funnel is arranged on the outer side of the transposition sealing disc, and a sample receiving station and a sealing station are arranged on the inner side of the transposition sealing disc; an interface cylinder is arranged on the outer side of the positioning base disc, and a sample receiving station hole is formed in the inner side of the positioning base disc; the distributed driving actuator is connected with the transposition sealing disc and the positioning base disc and used for driving the transposition sealing disc to conduct axial rising, station switching and axial sealing relative to the positioning base disc in a time-sharing mode. The problem of dynamic sealing failure under the extreme temperature difference and high particle invasion environment can be effectively solved, zero-leakage collection of star soil heating gas is achieved, the reliability and operation efficiency of gas sample collection in a deep space exploration task are remarkably improved, and mechanical interference or positioning deviation caused by compound motion of a traditional linkage mechanism is also avoided.