44 results about "Analysis sample" patented technology

The invention relates to the technical field of particulate matter sampling analysis, and discloses a full-automatic multi-point sampling system and method for particulate matters in a large flue. The system comprises an analysis module for acquiring airflow data through an airflow parameter sensor; the arrangement module is used for optimizing sampling point positions according to the airflow data; the monitoring module monitors particulate matter distribution in real time; the acquisition module is used for acquiring samples by adopting a gradient constant-speed strategy; the generation module is used for analyzing the sample to generate a component characteristic spectrum; and the fusion module comprehensively analyzes and generates a detection report. According to the application, full-automatic multi-point sampling and comprehensive analysis of the particulate matters in the large flue are realized, the defects of strong dependence on manual operation, limited sampling point positions, incapability of adapting to a complex flue environment and the like in a traditional sampling method are overcome, and the accuracy, representativeness and working efficiency of particulate matter sampling are improved.

The invention discloses a coke on-line automatic sampling, sample preparation and detection system which comprises a sampling unit, a sample preparation unit and a refined sample unit, the sample preparation unit comprises a first-stage division unit, a material collection bin unit, a coke multi-stage screening unit, a rotary drum screening unit, a packaging unit, a first-stage crushing unit and a mobile robot; the sampling unit is connected with the first-stage division unit, the first-stage division unit is connected with the material collecting bin unit, an analysis sample and a moisture sample are arranged in the material collecting bin unit, and the moving route of the mobile robot is divided into an analysis sample route and a moisture sample route. The invention further discloses a method for carrying out coke online automatic sampling and sample preparation detection by utilizing the coke online automatic sampling and sample preparation detection system. According to the coke online automatic sampling, sample preparation and detection system and method, the mobile robot is added, online automatic sampling, sample preparation and physical analysis are connected together, the route is simplified, detection is real-time, and data are more representative.

A method for calculating total organic carbon (TOC) for a sample location includes obtaining an intact core soil sample from a sample location, the core soil sample having a depth and mass; transferring a predetermined fixed mass M from the intact core soil sample into an analysis sample container to obtain an analysis sample; and providing a subsample of the analysis sample for soil organic carbon (SOC) concentration testing.

The present invention addresses the problem of providing an analysis method with which it is possible to simply analyze an object to be analyzed in a solid sample. The analysis method according to the present invention performs any one of predetermined operations 1 to 4, and establishes a regression equation on the basis of the obtained signal intensity value and the amount of an object to be analyzed contained in a standard sample film removed by laser irradiation. And calculates the amount of the object to be analyzed in the solid analysis sample containing the object to be analyzed removed by the laser irradiation using a regression equation.

The present application discloses a method, device and medium for optimizing and updating a model of generative artificial intelligence, which is used to reduce the space occupancy of repeated training data when training behavior analysis models for different behaviors to be analyzed. The method of the present application includes: obtaining engineering data to be trained; extracting initial sample data from the engineering data according to the behavior to be analyzed; performing data cleaning on the initial sample data set to obtain a target sample data set; determining model parameters according to the behavior to be analyzed, and obtaining target model training data from the target sample data set; using a batch training method to train the model corresponding to the behavior to be analyzed through the target model training data, and outputting a basic model; combining the basic model with generative artificial intelligence to obtain a target artificial intelligence; monitoring the dynamics of the analysis samples through the target artificial intelligence, and fine-tuning the basic model; monitoring the convergence state after the basic model is fine-tuned; deploying the updated model as the basic model of the target artificial intelligence.

The invention relates to the technical field of label noise of table data, a distance measurement-based method and a neural network-based method are currently common label noise screening methods, and the methods are difficult to distinguish wrongly labeled samples and difficult samples with fuzzy categories near a decision boundary; according to the table data noise recognition and correction method based on Stein scoring, the difference of the attribution degree between sample and data feature distribution and label export distribution is analyzed, and the logarithmic probability density gradient of a sample is estimated through a diffusion model; moving the sample along a gradient represented by a scoring function by using a gradient method until the sample is converged to a centroid, forming a moving track moving from an original position of a sample space to a high-density centroid of data of a domain, and calculating the data feature distribution by comparing the differences of the directions and lengths of the moving track of the sample in the data feature distribution and the distribution exported by the label. Samples of potential tag errors in the tabular data are identified and tags thereof are corrected.

The application discloses a malware large model adaptive analysis system based on improved GRPO and dynamic and static cooperation, comprising a collection execution module, a static feature extraction module, a log processing module, a prompt word engineering module, an LLM analysis module, an evaluation feedback module, an analysis strategy optimization module and a weight optimization module, and also discloses a method.The beneficial effects of the application are that the static features of the sample file to be analyzed are intelligently fused with dynamic behavior logs, complete analysis context is provided for the LLM, comprehensive and high-precision threat determination of dynamic and static combination is realized, the optimal analysis strategy can be selected according to the log size, the large log is processed by using the context-aware block mechanism, and therefore, the analysis quality is guaranteed while the efficiency and cost are taken into account.

Embodiments of the present disclosure provide a method, an electronic device, and a computer program product for analyzing samples. The method includes acquiring a set of feature representations associated with a set of samples. The set of samples illustratively have classification information for indicating classifications of the set of samples. The method further includes adjusting the set of feature representations so that distances between feature representations of samples corresponding to the same classification are less than a first distance threshold. The method further includes training a classification model based on the adjusted set of feature representations and the classification information. The classification model is illustratively configured to receive an input sample and determine a classification of the input sample. In this manner, a relatively accurate classification model can be trained using a small number of samples, thereby reducing computation time and required computation capacity.

The invention relates to the technical field of waste heat utilization, in particular to a method for utilizing cooling circulating water of an analytical sampler at an outlet of a washing tower of a water-coal-slurry gasification furnace, which comprises the following steps: the circulating water enters the analytical sampler at the outlet of the washing tower of the gasification furnace; after the circulating water absorbs heat and is heated, the heated circulating water enters the temperature tracing pipeline through the cooling circulating water pipeline; the temperature tracing pipeline is connected to the analysis sampling pipeline in a winding manner, the heating circulating water provides heat for the analysis sampling pipeline through the pipe wall of the temperature tracing pipeline, and then the heating circulating water becomes cooling circulating water; the process gas in the gasification furnace enters an analysis sampler, and the cooled and extracted gas sample enters an analysis instrument for analysis and detection. The heating circulating water generated after the analysis sampler is cooled is directly used for heat tracing of the analysis sampling pipeline, waste heat absorbed by the circulating water is fully recycled, a heat tracing device does not need to be additionally arranged, the temperature of a gas sample in the sampling pipeline can be effectively maintained, and condensation of easily-condensed components in the sample due to temperature reduction is avoided.

The application relates to the technical field of marine meteorological data assimilation, in particular to a marine meteorological data assimilation method based on self-adaptive scale decomposition. An original data set is acquired and preprocessed to obtain a two-dimensional matrix. Based on an empirical orthogonal function analysis method EOF, dimension reduction is carried out on the initial matrix to obtain a spatial mode which does not change with time. A spatial self-adaptive scale reduction model is constructed by using the correlation of points on the spatial mode. Grid setting is carried out on the spatial self-adaptive scale reduction model to obtain an optimized multiple network. A target functional is determined and scale-by-scale assimilation is carried out to obtain an analysis field. An accuracy calculation formula and an accuracy threshold value are determined. Sample observation values and sample analysis values of a sample to be analyzed are acquired, and the accuracy is calculated. The two-dimensional matrix is extracted and processed by the EOF, the spatial self-adaptive scale reduction model is obtained, and scale-by-scale assimilation of adaptive matching of spatial characteristics is realized.

The embodiment of the invention provides a data analysis method and device and a storage medium, and belongs to the technical field of data processing and computers.The method comprises the steps that a target data set is obtained, and the target data set comprises text files of at least one format; carrying out asynchronous preprocessing on the target data set to obtain processed data, wherein the asynchronous preprocessing comprises data analysis and interpolation processing; various statistical analyses are conducted on the processed data to obtain analysis results, the analysis results comprise inspection result values and inspection types, and data feature analysis, sample size evaluation, distribution inspection and effect size calculation are conducted according to the inspection result values and the inspection types to obtain comprehensive evaluation data; determining an optimal statistical method combination according to the comprehensive evaluation data to determine an optimal analysis result; and setting an AI assistant for interpreting and describing the optimal analysis result to obtain an analysis report. According to the method, the data statistical analysis efficiency is improved.

The invention provides a multi-dimensional stereo evaluation method and system based on construction drawing budget project quality management, and the method comprises the steps: obtaining a plurality of pieces of construction drawing data from a review management system, and carrying out the data cleaning of each piece of construction drawing data, so as to remove invalid data and abnormal values; performing format unification processing on the construction drawing data after data cleaning to obtain corresponding unification data, and analyzing the unification data from three dimensions of list deviation, two engineering differences and reason classification to obtain an analysis result; and generating a corresponding analysis report based on the analysis result, and optimizing construction drawing budget project quality management by using the analysis report. According to the method, the deviation between the construction drawing budget and the actual settlement is calculated to solve the problem of budget inaccuracy caused by list items, project amount changes and deviation factors, and the evaluation optimization strategy is formed by analyzing the data of the sample project and summarizing deviation reasons, so that the technical and economic management and control level of the construction drawing stage is effectively improved.

Provided is an automated analysis system comprising an analyzing unit that analyzes a sample, and a control unit that controls the analyzing unit, wherein the control unit receives, via a network, a diagnosis measurement parameter that defines a condition for a diagnosis measurement, and controls the analyzing unit in accordance with the diagnosis measurement parameter to automatically perform the diagnosis measurement. The automated analysis system includes, for example, a quality control sample storage unit that stores quality control samples, and a conveying unit that conveys the quality control samples between the quality control sample storage unit and the analyzing unit, wherein: the diagnosis measurement parameter specifies, as the condition, the quality control sample to be used in the diagnosis measurement; and the control unit controls the quality control sample storage unit, the conveying unit, and the analyzing unit in accordance with the diagnosis measurement parameters, supplies the specified quality control sample to the analyzing unit, and performs the diagnosis measurement.

The invention provides a sample delivery system for an analytical instrument, comprising: a valve assembly comprising one or more valves, the valve assembly configured to receive an external sample from a sample source; an external sample reservoir coupled via the valve assembly to a sample dilution junction, wherein the valve assembly is configurable to alternatively permit either (i) flow of the external sample from the sample source to the external sample reservoir or (ii) flow of the external sample from the external sample reservoir to the sample dilution junction; a first fluid pump to control a flow of the external sample from the external sample reservoir to the sample dilution junction; a second fluid pump to control a flow of diluent to the sample dilution junction, thereby diluting the external sample to produce a diluted sample; and an analysis sample reservoir configured to deliver an analysis sample contained therein to an analysis device of the analytical instrument, wherein the analysis sample reservoir is coupled via the valve assembly to the sample dilution junction, and wherein the valve assembly is configurable to alternatively permit either (i) flow of the external sample along a continuous flow path from the sample source to the analysis sample reservoir, thereby by-passing the external sample reservoir, or (ii) flow of the diluted sample from the sample dilution junction to the analysis sample reservoir.

An object of the present invention is to provide an analysis method in which analysis of an analysis object in a solid sample can be simply performed. An analysis method according to the present invention includes: creating a regression equation based on a value of a signal intensity obtained by performing any one of predetermined operation 1, 2, 3, or 4 and an amount of an analysis object that is removed by laser light irradiation in a standard sample film; and using the regression equation to calculate an amount of the analysis object that is removed by laser light irradiation in a solid analysis sample including the analysis object.

The invention provides a method for determining substance composition of an in-situ leached sample, and belongs to the technical field of process mineralogy. According to a traditional measurement method, sample pretreatment is mainly carried out in a sampling-ore grinding-division mode, finally, only a small amount of divided samples are taken to prepare automatic mineralogical analysis samples for analysis, and the problems that the representativeness of the samples is insufficient and the data deviation is large inevitably exist. According to the method, an in-situ leaching sample is pretreated and screened, then layered sample preparation is performed, samples prepared on different layers are subjected to retreatment sample preparation, testing is performed through automatic mineralogy, and then the content of each component in the in-situ leaching sample is calculated; according to the characteristics that an in-situ leaching sample is complex in mineral composition, sedimentation layering is obvious when an automatic mineralogy analysis sample is prepared, and the sampling representativeness of the sample is insufficient, a sample treatment and analysis test method is designed, and the content of each component in the in-situ leaching sample is accurately measured.

1. The name of the design product: bottle (screw thread vial). 2. The use of the design product: for trace sample analysis sample bottle. 3. The design points of the design product: in shape. 4. The picture or photo that best indicates the design points: combination state reference figure 1.

One embodiment of the mass spectrometry device according to the present invention comprises: a measurement unit (1) for performing mass spectrometry analysis on a plurality of target samples and a plurality of quality control samples in a predetermined order; a sample information storage unit (20) for pre-storing identification information capable of distinguishing the target samples and the quality control samples in a series of measurements on the plurality of target samples and the plurality of quality control samples; and a display processing unit (25, 251) for separating the measurement results for the target samples and / or the analysis results derived therefrom from the measurement results and the measurement results for the quality control samples and / or the analysis results derived therefrom from the measurement results, thereby creating display information in a predetermined format and displaying the two display information on a screen of the display unit. Thus, the analysis results of the target samples and the quality control samples can be easily distinguished on the display, and the validity of the measurement results and analysis results of the target samples can be accurately and efficiently evaluated.

A data analysis method, system, and storage medium based on a bioanalyzer are disclosed. The samples to be analyzed include the test sample and standards. The method includes: acquiring the target channel signal measured by the bioanalyzer and determining whether the sample to be analyzed is a single-peak or non-single-peak sample based on the histogram of the signal; for non-single-peak samples, calculating the proportion of positive microspheres using the signal intensity corresponding to the deepest trough of the histogram as a first threshold; for single-peak samples, calculating the proportion of positive microspheres based on a second threshold, which is determined based on the first threshold of multiple non-single-peak samples of the standards; and calculating the average target capture amount of a single positive microsphere in the sample to be analyzed based on the interval where the proportion of positive microspheres is located and / or the signal intensity information of the positive microspheres. This method effectively extends the detection dynamic range and achieves automated and standardized data analysis. This application also discloses a corresponding system and computer storage medium.

The application provides a polysilicon production equipment fault diagnosis method and device, a server and a storage medium, and relates to the field of equipment fault diagnosis. The method comprises the following steps: acquiring target equipment collected sample data and first historical sample data within a preset time window; determining a first set composed of equipment parameters and a second set composed of equipment parameters and corresponding upstream and downstream process parameters; further determining the first robust distance of the equipment parameters according to the equipment mean vector and the equipment covariance matrix; determining the second robust distance of the equipment parameters and the corresponding upstream and downstream process parameters according to the overall mean vector and the overall covariance matrix; if the first robust distance is greater than the first robust distance threshold and / or the second robust distance is greater than the second robust distance threshold, the running state is determined to be an abnormal state. The comprehensiveness of the diagnosis and the accuracy of the diagnosis result are ensured, the stability of the benchmark during diagnosis is ensured, and the diagnosis efficiency is improved.

According to the sample analysis system and the sample analysis method provided by the embodiment of the invention, the image acquisition device can obtain the sample image of the to-be-detected sample, the optical detection device can obtain the photoelectric data of the reaction liquid prepared by the to-be-detected sample, and the control device obtains the state information of the to-be-detected sample by analyzing the sample image; photoelectric data of the reaction liquid are analyzed to obtain state information of the reaction liquid, and specific interferent information is determined by integrating the state information of the two aspects, so that a basis is provided for interference elimination, and the accuracy of a sample detection result is improved.

The application relates to the technical field of coal sample analysis, in particular to a method and device for determining a critical difference of 3mm storage and inspection coal sample inter-laboratory comparison, wherein the method comprises the following steps: taking a dry basis as a reference, respectively determining detection difference values of 0.2mm analysis samples prepared by a sending laboratory and a receiving laboratory, and calculating a 1.2T value according to detection items and index ranges, wherein T is a reproducibility critical difference specified in a corresponding detection standard; and comparing the detection difference values with the 1.2T value, wherein if the detection difference value is less than or equal to the 1.2T value, it is determined that the 3mm storage and inspection coal sample inter-laboratory comparison is qualified, otherwise, it is determined that the 3mm storage and inspection coal sample inter-laboratory comparison is unqualified. Therefore, the method solves the problems that related technologies use a square root of 3T as a critical difference of 3mm storage and inspection coal sample inter-laboratory comparison, the allowed range is widened, most of the comparison samples can pass the determination, and the sensitivity of the comparison result to detection abnormalities and quality fluctuations is reduced.

The invention discloses an analysis sample scheduling system and scheduling method of an automatic analyzer, and the scheduling system comprises a sample sending cache track; the sample injection transfer track is at least provided with a first sample injection port and a second sample injection port, and a code scanning device is arranged on the sample injection transfer track and is used for scanning and identifying the samples and registering the samples to an upper computer to judge the priorities of the samples; when a sample is fed into the emergency treatment transfer track, the first sample inlet stops feeding the sample; detecting a cache track; the cache transfer unit is used for selecting to cache samples with low priorities or transfer samples with high priorities according to the priorities judged by the upper computer; the circulating transfer track is used for transferring the sample with the highest priority to the detection unit for detection and analysis; and a sample return unit. The purpose of detecting the samples according to different priorities in a grading manner is achieved, the samples needing emergency detection can be detected preferentially, the overall detection sequence is optimized, and the test flux is improved.

The invention discloses an oil-water layer evaluation method and device. The method comprises the following steps: extracting and calculating to obtain standard start time and standard end time of all group peaks of an analysis sample; extracting standard peak areas of all component peaks of the analysis sample according to the obtained data, and calculating the unit peak area of each component peak; according to different fluid properties, summarizing the unit peak area of each component peak of each analysis sample, and calculating each derived parameter of all analysis samples; establishing an oil-water layer evaluation chart based on derived parameters; calculating the unit peak area of each component peak of the analysis sample in the well to be evaluated, and calculating each derived parameter; and projecting each derived parameter of the to-be-evaluated well to the oil-water layer evaluation chart corresponding to the derived parameter, and determining the formation fluid property of the to-be-evaluated layer of the to-be-evaluated well. According to the method, the oil-water layer evaluation standard is established by utilizing new parameters and oil testing data in the same oil and gas reservoir, and the fluid property of the stratum can be evaluated quickly and accurately.

The invention relates to full-automatic sample transferring and butting equipment and a butting method. The full-automatic sample transferring and butting equipment comprises a conveying line, a sample box for X fluorescence analysis, a press-fitting device and a material transferring device, wherein the conveying line is used for conveying tray boxes containing sample fuse pieces; the press-fitting device is used for loading the tray boxes on the conveying line into the sample boxes for X-fluorescence analysis, or unloading the tray boxes in the sample boxes for X-fluorescence analysis onto the conveying line; and the material moving device is used for transferring the X fluorescence analysis sample box on the press-fitting device into the detection equipment, or transferring the X fluorescence analysis sample box in the detection equipment onto the press-fitting device. According to the full-automatic sample transferring and butting equipment and the butting method provided by the invention, the whole process work of automatically transporting the tray box containing the sample fuse pieces, loading the tray box to the sample box for X fluorescence analysis and transferring the tray box to the detection equipment can be realized, human intervention is not needed in the whole process, the manpower is saved, and the working efficiency is improved.

The present disclosure provides an improved workflow method for metabolic analysis of multiple samples in a sample set. The disclosed method utilizes a reference sample that represents the chemical complexity of the sample set. Analysis of the reference sample identifies relevant and irrelevant features, and based on these features, focuses the analysis on specific portions of the data obtained from each individual sample, thereby reducing the computational burden of analyzing all samples in the sample set. The present disclosure also provides a system for implementing the disclosed method.

The application discloses a label noise detection method based on a multi-time step loss sequence, utilizes a character recognition module to recognize characters from an input image; utilizes an MSL-MentorNet label noise detection module to analyze a loss sequence of the input image in a continuous training period according to a character recognition result, dynamically allocates sample weights to detect and filter noise labels, and feeds back screened data to a character recognition module to optimize model training. The application adopts an MSL-MentorNet label noise detection and noise filtering mechanism based on dynamic curriculum learning, analyzes a loss sequence of a sample in a continuous training period, utilizes a BiLSTM network to distinguish noise labels from clean difficult samples, and combines a linear scheduling strategy to gradually increase a training data amount. Based on the method of the application, the complex text image recognition accuracy can be improved, and the method is especially suitable for robust recognition and noise filtering of complex text images in scenarios such as ancient book digitization, historical document restoration, industrial OCR quality inspection and the like.

The present invention provides a method for detecting garden greening, which relates to the technical field of garden detection and includes the following steps: regional positioning; formulating a plan; collecting samples; analyzing samples; generating a report. The invention controls a plurality of insertion units to alternately insert into the soil through a climbing base, and cooperates with a horizontal adjustment mechanism to make the plurality of insertion units always insert into the soil plane at a fixed angle, so as to realize continuous soil sample collection by the sampling device on a slope with a large gradient; this method solves the technical problem that the prior art is difficult to be applied to the slope green space on a slope with a large gradient; and greatly improves the efficiency of garden greening detection.