1508 results about "Sample collection" patented technology

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 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 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 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 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 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.

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 health evaluation, in particular to a group image health evaluation method and system based on intestinal flora, and the method comprises the steps: collecting intestinal flora samples of a target group through a standardized process, and obtaining microbial sequence information through a high-throughput sequencing technology; microflora diversity characteristics and core flora characteristics are extracted through strain identification and relative abundance analysis, individual flora characteristics are compared with a healthy population reference database, health state scores are calculated, health grades are divided, population health grade distribution is counted, and the population health grade distribution is calculated. And generating a group health evaluation report containing a visual chart and text analysis. According to the method, a complete technical system from sample collection to health strategy making is established, systematic evaluation of the group health state from the perspective of intestinal flora is achieved, and the limitation of a traditional method in group health early evaluation is overcome. The method is suitable for health monitoring of different scales of groups, and provides effective technical support for public health management and health service.

The application discloses a sample refrigeration storage device and a sample pipeline analysis system. The sample refrigeration storage device comprises a refrigeration storage area, a refrigeration storage area frame, a refrigeration placing rack and a first refrigeration mechanism; a refrigeration operation area, an operation area frame, a sample sorting mechanism, a sample rack loading mechanism and a second refrigeration mechanism, the operation area frame is communicated with the storage area frame to form a closed cavity, the sample sorting mechanism and the sample rack loading mechanism can cooperate to load out the sample to be loaded out on the refrigeration placing rack through an entrance and exit, and load the sample to be loaded in into the refrigeration placing rack through the entrance and exit; a sample transmission track; and a central control system. Since the sample sorting mechanism is located in the refrigeration operation area, when the sample is retained, the second refrigeration mechanism makes the sample in a low-temperature environment, reduces the corruption and invalidation of the sample, reduces the sample collection frequency, and improves the sample detection efficiency.

The invention provides a device for collecting a nasal secretion sample. The device includes a sample collection member comprising a material for collecting a predetermined volume of a nasal secretion sample. The device further includes a handle and an elongated support member extending between the handle and the sample collection member and for supporting the sample collection member. The device is adapted for a user holding the handle to locate the sample collection member in contact with tissue at a target location inside the nasal cavity where the sample collection member collects a predetermined volume of a nasal secretion sample.

The invention discloses a transformer oil sample automatic collection method and device based on vision and impedance control, and the method comprises the steps: determining a relative position between an oil taking injector and an oil taking port in a transformer oil sample collection process, and determining an ideal pose of the oil taking injector controlled by a mechanical arm to reach an oil taking port mark based on the relative position; based on image information collected in real time by an image taking device arranged on the mechanical arm, a space coordinate transformation matrix of the ideal pose at the oil taking opening mark and the actual pose of the image taking device is calculated; on the basis of the ideal pose and the space coordinate transformation matrix which are calculated in real time, according to a control law of pose deviation design, a visual servo control rule for the pose of the oil taking injector is determined; based on interaction between the working environment and the tail end of the mechanical arm, a butt joint depth control rule of an oil taking injector and an oil taking opening is determined through an impedance controller; based on a visual servo control rule and a butt joint depth control rule, butt joint of an oil taking injector and an oil taking opening is controlled, and transformer oil sample collection is carried out.

The invention relates to the technical field of collection equipment, in particular to a sample collection device for diesel engine gas detection. A first pipe opening, a second pipe opening and a third pipe opening are formed in the pipe body; a collecting barrel is installed in the first pipe opening, a limiting mechanism used for being connected with a flue of a diesel engine is installed on the second pipe opening, a flow monitoring mechanism is installed on the third pipe opening, and the particulate matter collecting barrel, the flow monitoring mechanism and the flue connecting mechanism are integrated on one pipe body, so that particulate matter collection and gas flow measurement are synchronously carried out; measurement errors caused by fluctuation of working conditions are greatly reduced, and the accuracy and reliability of detection data are improved.

A system configured to collect a representative sample of dried grain from an industrial grain dryer to inform the dryer's automatic temperature controller includes: a plurality of drop tubes each having a top end and a bottom end, wherein the top end of each drop tube is communicatively coupled to a respective dump chute of the grain dryer and configured to receive a respective partial grain sample from the dump chute; connective tubing communicatively coupling the bottom ends of the plurality of drop tubes; an air blower communicatively coupled to a proximal end of the connective tubing, wherein the air blower is configured to propel the partial grain samples distally through the connective tubing; and a collection box communicatively coupled to a distal end of the connective tubing, wherein the collection box is configured to receive and aggregate the partial grain samples into a combined sample for moisture testing.

Provision of construction geological survey sampling equipment. The present invention includes a boring pipe for drilling holes, and a sampling mechanism is provided within the boring pipe, the sampling mechanism including a sampling disk. By combining the sampling disk and a plurality of independent sampling tubes, the sampling tubes can be sequentially protruded from the sampling hole at different depths with a single penetration of the boring pipe, thereby achieving continuous layer-by-layer sample collection, one or more samplings at the same position, and continuous sampling at different positions, without the need for intermediate sampling tube replacement or secondary drilling, thereby improving sampling efficiency, accuracy, and versatility.

The invention is suitable for the technical field of material sintering, and provides a floating type sintering platform demolding and sampling device which comprises a sintering platform, a floating lower electrode module, a floating mold module, a lifting mold frame, a demolding and mold cleaning module and a sample collecting and electrode cleaning module. The lifting mold frame is provided with a first platform and a second platform, and the first platform penetrates through the floating lower electrode module through a first limiting groove to jack the floating mold module to a set height; the sample collecting and electrode cleaning module slides to the position below the mold module through the second limiting groove, and sample receiving and electrode cleaning are achieved. High-temperature online demolding can be achieved, the sample breaking risk is reduced, and the breaking problem caused by the difference of thermal expansion coefficients is avoided; the device integrates demolding, mold cleaning, electrode cleaning and sample collecting functions, is compact in structure, reduces the occupied area and complexity of equipment, prolongs the service life of the mold and the electrode, and improves the sample quality.

The invention discloses an atmospheric microparticulate monitoring device and method based on multi-mode sensing, and relates to the technical field of ecological environment monitoring. The device comprises a data acquisition system used for carrying out real-time sample acquisition and signal conversion on conventional pollution factors and meteorological parameters in air; the data analysis system is used for carrying out concentration analysis and early warning on the signals converted by the data acquisition system; the error evaluation system is used for performing error evaluation on the key indexes of the data acquisition system according to the acquired samples; and the data transmission system is used for carrying out cross-regional transmission on the sample acquired by the data acquisition system and the analysis result according to a sensitivity quantity algorithm based on an anonymous model. Real-time monitoring of atmospheric micro-particles with high accuracy and strong applicability is realized based on atmospheric monitoring standards independent of a meteorological monitoring framework, and reasonable adjustment of device parameters is realized by cooperation of the atomic fluorescence spectrometer and the enrichment sampling and pretreatment unit.

The invention discloses a mineral sample acquisition optimization method based on stratum change identification, and particularly relates to the technical field of mineral exploration sampling, comprising the following steps: acquiring lithologic characteristics, fault distribution, underground stress information and historical sampling data, fusing to form spatial reference data and generating a stratum change level distribution map, then constructing a sample collection candidate area map; generating a sampling path group and adjusting path layout according to the candidate area map, matching a sampling mode for each path, recording multiple types of data in real time in the sampling process and comparing the data with spatial reference data, and dynamically adjusting the sampling path or mode according to a comparison result; spatial reference data are generated through multi-source geological information fusion, and high-precision stratum change recognition is achieved; the sampling path layout is optimized in combination with disturbance distribution and operation constraint, so that the operation safety and the coverage integrity are improved; in the sampling process, response data are compared in real time, a sampling strategy is dynamically adjusted, and the geological consistency and reliability of a sampling result are ensured.

The invention discloses a mulberry important character QTL fine positioning method based on a chromosome segment replacement line, and relates to the technical field of molecular breeding. Comprising the following steps: S1, constructing a genotype-phenotype incidence matrix: screening backcross populations through high-heterozygosity parent hybridization and multi-generation backcross, and marking genomes of the screened backcross populations through targeted sequencing and recombination hot spots; s2, phenotype determination modeling: performing sample collection according to a test plant, and obtaining a hybrid model according to the environmental effect of the test plant and a covered CSSL line; and S3, gene screening: carrying out hub gene screening through the constructed co-expression network model and the hybrid model. According to the method, through multi-generation backcrossing, targeted sequencing and recombination hotspot analysis, dynamic labeling is performed on the genome, and a stepped coverage CSSL library is constructed, so that a QTL interval is effectively compressed, and the problem of fuzzy positioning caused by limited recombination events of a traditional F2 or RIL population is solved.

The invention discloses a mattress fabric comfort evaluation method, device and equipment and a storage medium. The method comprises the following steps: collecting objective data from a mattress fabric sample according to a plurality of indexes; performing range standardization processing on the objective data to obtain a range standardization value; performing weighted comprehensive calculation on the mattress fabric sample according to the range standardization value to obtain a weighted comprehensive score; performing clustering analysis on the objective data by adopting a clustering algorithm to obtain an optimal k value; dividing the mattress fabric sample into k levels according to the weighted comprehensive score, setting k comfort evaluation score ranges based on the k levels, and constructing a comfort evaluation model; and evaluating by using the comfort evaluation model. According to the method, the influence of a plurality of comfort level related indexes on the comfort level of the mattress fabric and the weight of the influence are comprehensively considered, the objective data are converted into the comfort level score of the mattress fabric, and the relation between the objective data and the comfort level of the mattress fabric is established, so that the comfort level evaluation effect of the mattress fabric can be improved.

The application discloses a kind of intelligent switching water sample pretreatment system and method, system includes: combined sand filter sample barrel, for collecting water sample to be pretreated, initial water sample turbidity value acquisition is carried out, while water sample preliminary pre-filtering treatment is carried out;Positioning floating sampling device, for fixing to take supernatant after water sample settlement;Microfiltration module, for the microfiltration of ultrahigh turbidity water sample;Sample water transfer pump, for transmitting supernatant in combined sand filter sample barrel to microfiltration module;Sample collection barrel, for collecting and detecting water sample quantity after processing, for instrument or laboratory personnel to sample analysis;Valve assembly, by valve opening and closing, water sample is switched different pretreatment mode;Cleaning assembly, including rotary high-pressure spray head and self-heating ultrasonic cleaning device, for cleaning system after pretreatment internal residual adherend.

The invention discloses a Rongchang pig T2T genome assembly method. The method comprises the following steps: 1) collecting and sequencing a sample; 2) genome investigation and assembly; 3) genome annotation; wherein in the sequencing step, three sequencing technical means, namely, a three-generation gene sequencing technology PacBio, Nanopore PromethION 48 short reading and chromatin conception capture (HiC), are adopted, and the Rongchang pig genome is subjected to sequencing and sequence splicing together. The Contig N50 value of the genome is nearly three times that of Sscrofa11.1, and the improvement is mainly embodied in a complex genome region (centromere and telomere regions), so that the genome becomes the most complete genome available at present.

The invention discloses a key part point cloud segmentation method and system for navigation of an oil sample collection robot. The method comprises the following steps: carrying out sample perception enhancement on an input point cloud through a self-adaptive data intensifier; a CB-Transform module in the encoder is utilized, and local geometric features and global context information are fused through a two-stage attention mechanism; a C-VLAD module is adopted to carry out weighted residual clustering and cross-level simultaneous operation on the multi-scale features, and a comprehensive global descriptor is generated; and finally, the point cloud resolution is recovered through a decoder, and a segmentation result is output. According to the method, the problems of sparse point cloud labeling data, large equipment scale difference, complex geometric structure and the like in an industrial scene are effectively solved, the segmentation precision and robustness of key parts such as a valve and a flange are remarkably improved, the data labeling cost is reduced, and reliable technical support is provided for precise navigation and operation of an oil sample collection robot.

The invention provides a water soluble organic nitrogen property prediction method based on spectrum fingerprint information and machine learning and application. The method specifically comprises the following steps: research area selection, sample collection, pretreatment and related index detection. Preliminarily verifying the data set, screening representative spectrum indexes, and constructing a spectrum fingerprint information matrix; dividing a training set and a test set, using a machine learning method to construct prediction models by using the training set, and using the test set to perform performance evaluation on the prediction models; a prediction model with better performance is selected, a Shapley method is used for calculating the SHAP value of each characteristic value, and the key characteristic value with the dominant model influence degree is selected as a prediction variable to indicate the property characteristics of the soluble organic nitrogen in the research area. According to the method provided by the invention, the properties of the complex soluble organic nitrogen can be conveniently and efficiently preliminarily judged, the understanding of the current situation of the water ecological environment is further improved, and a certain technical support is provided for formulating water ecological environment protection measures.

The invention discloses a soil environment Cd metal monitoring method based on specific response of root exudates, which comprises the following steps: in a monitoring period, carrying out root exudates sample collection and soil sample collection on a to-be-monitored area, carrying out root environment perception and dynamic exudates capture based on the collected samples, and generating a root perception data set; a response mode between the soil environment Cd degree and root exudates is established, and an exudates response characteristic fingerprint spectrum is established; coupling the synchronously collected soil environment data to carry out feature importance analysis and regression modeling, quantifying interference rules of different environment factors on a secretion response mode, and generating an environment correction coefficient set; constructing an environmental cadmium analysis model by utilizing the secretion response characteristic fingerprint spectrum and the environmental correction coefficient set; and in the next monitoring period, acquiring real-time area monitoring data of the cadmium sampling points in the area to be monitored, importing the real-time area monitoring data into the environment cadmium analysis model to carry out area cadmium metal situation diagnosis, and carrying out early warning prompt.

The utility model discloses a sample collector for analyzing harmful microorganisms in vegetables, which comprises a bottom plate, a sample box fixedly mounted at the top of the bottom plate, a fixed block fixedly mounted on the left side of the sample box, a vertical shaft fixedly mounted at the top of the fixed block, a connecting block rotatably mounted on the vertical shaft, and a box cover fixedly mounted on the connecting block. A discharging hole is formed in the box cover, a switching mechanism is arranged in the sample box, six sample tubes are movably mounted on the switching mechanism, and the switching mechanism is used for controlling the six sample tubes to alternate. The vegetable perforating and sampling device is reasonable in design, local areas with microorganisms on vegetables can be perforated and cut through the perforating pipe, samples possibly clamped in the perforating pipe are cleaned through the material returning rod when the perforating pipe ascends, next time of perforating and sampling can be conveniently carried out, the sampling efficiency is improved, the disc frame can be controlled to rotate by 60 degrees every time, and the sampling efficiency is improved. Furthermore, the sample tube is replaced, so that the vegetable sample is conveniently received, and the sampling efficiency is further improved.