585 results about "Sample area" patented technology

The invention provides a preparation method of a transmission electron microscope ultrathin sample with a cross section of an electron beam sensitive material, which comprises the following steps: selecting a specific region as a to-be-extracted sample region for the electron beam sensitive material by adopting an electron beam imaging technology; depositing a protective layer on the surface of the to-be-extracted sample area by adopting an electron beam and / or an ion beam; bombarding a to-be-extracted sample area by utilizing a high-energy ion beam, extracting an electron beam sensitive material cross section sample from the to-be-extracted sample area, and fixing the extracted sample to a metal bracket; performing pre-thinning treatment on the extracted sample by using a focused ion beam to obtain a first thinned sample of which the thickness is reduced to be less than a first thickness; and transferring the first thinned sample into a micro-beam fixed-point ion thinning system, and carrying out multi-time stepped low-energy ion beam fine thinning treatment on the first thinned sample by using inert gas ion micro-beams to obtain a second thinned sample which is clean in surface and free of a surface ion damage layer and has the thickness reduced to be less than a second thickness, and taking the second thinned sample as a transmission electron microscope ultrathin sample.

The invention provides a quality control system and method for a foamed asphalt mixture, relates to the field of intelligent detection, and adopts an image recognition and detection technology based on machine vision to carry out gridding segmentation and sample performance local image block semantic coding on a sample image after the foamed asphalt mixture is compacted. And then spatial semantic enhancement is carried out on the semantic coding features of the performance local image blocks of each sample, so that whether the material performance meets a preset standard or not is intelligently judged according to energy global aggregation of the semantic enhancement features of the performance local image blocks of each sample after spatial semantic enhancement. Therefore, by analyzing the image of the whole sample area, the quality of the whole material can be comprehensively reflected. And meanwhile, tiny defects possibly neglected by a traditional method can be detected, so that comprehensive, accurate and intelligent quality control of the foamed asphalt mixture is realized.

The invention discloses a water body remote sensing recognition method based on hyperspectral data simulation and U-net. The water body remote sensing recognition method comprises the following steps: A, data collection and preprocessing; b, selecting and manufacturing a sample area; c, data simulation; d, derived parameters are calculated; e, manufacturing a training sample and a verification sample; f, training a U-net network model; g, multispectral water body detection; and H, precision evaluation. According to the method, a high-quality training sample is obtained through a hyperspectral remote sensing image, multispectral data of different sensors are simulated, the problem that the reusability of water body classification samples among different multispectral satellites and at different geographic distances and time is not sufficient is solved, the multispectral data Landsat8 and Sentinel2 are taken as examples, and the reusability of the water body classification samples is improved. It is proved that by means of the method, easily-confused ground objects such as building shadows and cloud shadows in the water body recognition process can be effectively removed, and on the basis of accurately extracting large-area rivers and lakes, the recognition precision of small lakes and ponds is improved.

The invention provides a rice growth model construction method and system based on salt stress, and relates to the technical field of growth model.The rice growth model construction method comprises the steps that firstly, monitoring points are arranged in a planting sample area, and soil conductivity data of different depths are obtained through a multi-depth soil conductivity sensor and a Kriging interpolation method; collecting root system density, a multispectral remote sensing image and a leaf area index, and calculating a canopy salt stress index; measuring the concentration of related ions to obtain a sodium adsorption ratio, and establishing a salt stress coefficient by combining the soil conductivity and the irrigation volume; fusing canopy and soil stress indexes to generate a stress comprehensive index, and introducing a salinity feedback item to represent the crop compensation capability; and finally, constructing a hybrid machine learning model by adopting a convolutional neural network and a long-short-term memory network to realize rice growth dynamic prediction. According to the method, multi-dimensional salinity stress quantification of a soil-crop system is realized, and decision support is provided for salinization treatment in precision agriculture.

A medium processing apparatus includes a liquid applier, a post-processing device, and circuitry. The liquid applier applies liquid to a part of a medium, the medium being at least one medium. The post-processing device binds a bundle of media including the medium to which the liquid is applied by the liquid applier. The circuitry controls operations of the liquid applier and the post-processing device. The circuitry causes the liquid applier to apply different amounts of liquid to a plurality of sample areas in the medium.

The invention relates to the technical field of forest image processing, in particular to a forest information extraction method based on a remote sensing image. The method comprises the following steps: obtaining remote sensing image data of a forest area and a GPS positioning sample place area, and carrying out sample area remote sensing image processing and vegetation index analysis to obtain vegetation index data corresponding to each forest type in the sample area; performing end member component reflectivity analysis on the remote sensing image data of the sample area to obtain spectral reflectivity values corresponding to all end member components of the forest in the sample area; performing mixed pixel decomposition on a corresponding sample area remote sensing image in the sample area remote sensing image data in combination with a linear mixed pixel decomposition model so as to generate an abundance map of each ground feature type of the sample area; and carrying out pixel forest information classification extraction on each ground feature type abundance map of the sample region to obtain each forest type distribution map of the sample region. According to the invention, different forest information in the remote sensing image can be obtained by integrating the surface reflectance and the vegetation index.

The invention relates to the technical field of microscopic biological observation, in particular to a microscopic biological observation method based on a digital microscope. Firstly, original point cloud of a sample area on an objective table is obtained through structured light scanning, noise points are removed, point cloud density is optimized by adjusting scanning intensity for multiple times, high-precision and low-noise preprocessed point cloud is generated, then a reference plane is fitted in combination with the structured light point cloud, and obstacle and non-obstacle features are extracted. Detecting a second center coordinate of the bounding box by using a YOLO model, obtaining a third center coordinate through Hough circle detection, generating a standard coordinate by fusing multi-source coordinates, generating a global path based on a grid map and an RRT algorithm, predicting a track in real time, calculating a minimum Euclidean distance with an obstacle, dynamically inserting a B spline transit point to avoid a dangerous area, and ensuring a safe distance. Finally, collecting sample images in real time along the path and extracting microorganism characteristics; the technical problem that the efficiency is low when a traditional microscope is used for acquiring a microorganism image in a sample is solved.

The invention provides a digital wetland ecological environment monitoring system, which comprises an intelligent sensing terminal deployed in a wetland experiment sample area and used for collecting multi-source heterogeneous wetland monitoring data and transmitting the multi-source heterogeneous wetland monitoring data to information transmission equipment; the information transmission equipment is used for receiving, transmitting, summarizing, storing and analyzing the multi-source heterogeneous wetland monitoring data; and the wetland data center is used for acquiring the summarized multi-source heterogeneous wetland monitoring data through information transmission equipment, providing data analysis service on line by utilizing a distributed calculation and analysis technology and a data mining tool on the basis of the multi-source heterogeneous wetland monitoring data, and providing data service for the application service center and the intelligent decision center. According to the invention, multi-source heterogeneous data is integrated, wetland ecological monitoring related management applications and data services are integrated to a unified monitoring platform, and application of the system in ecological evaluation and simulation prediction is realized, so that informatization, digitization and intelligence of wetland ecological monitoring are further realized.

The invention relates to the technical field of performance detection, in particular to a heat insulation performance detection process for an energy-saving and environment-friendly curtain wall material. Comprising the following steps: S1, cutting a sample; step S2, performing pretreatment; s3, performance testing is carried out; s4, calculating the actual thermal conductivity of the to-be-detected sample according to the actual temperature difference and the heat source condition. According to the invention, the sample area is divided into two types and temperature distribution analysis is carried out to effectively judge the accuracy of the thermal imaging image, and corresponding regulation and control are carried out according to the analysis result, so that the reliability and accuracy of the test are improved, the sample is ensured to be uniformly heated in the test process, local overheating or supercooling is avoided, and the test efficiency is improved. By monitoring a real-time displacement field and environmental parameters, whether jitter or heat flow disturbance exists in the test process can be identified, and the reliability of test data is further ensured; and comparing the calculated actual heat conductivity with a related standard to judge whether the heat insulation performance of the sample meets the requirement or not.

The invention relates to the technical field of data analysis, and further relates to a forest pest and disease identification method based on data analysis, and the method comprises the steps: 1, obtaining an aviation orthoimage of a target forest region and a trapping point count in a set time interval, and associating the trapping count to a sample region unit according to the recent affiliation; 2, a composite simplex complex composed of a plaque layer, a sample area layer and a trapping layer is constructed on a forest map grid, counter examples are screened out through a two-stage verifier, and then suspected pest and disease damage triggering units are output; step 3, establishing a disease and insect pest atlas database, and describing typical modes by disease type topological fingerprints; and carrying out similarity judgment on the topological evidence packet and the disease type topological fingerprint to generate a disease type, a range and a credibility level, and carrying out layering labeling on a forest map grid. According to the method, the fine-grained structure change of diseases and insect pests can be captured in an early stage, and the recognition accuracy and interpretability are improved through multi-source evidence synthesis.

The invention belongs to the technical field of ecological environment protection, and particularly relates to a method and system for determining a biodiversity key area based on the population number in an area range, and the method comprises the steps: collecting and analyzing key data, such as an environment influence coefficient, a species diversity index and a population density value; and combining the established threat factor quantification standard and the weight distribution system, and adopting a scientific calculation model to obtain the threat coefficient of each sample region. Then, through setting a reasonable threat coefficient threshold value, screening out a key region of biodiversity protection; spatial analysis is carried out by utilizing a GIS technology, distribution and mutual relations of the key areas in geographic space are determined, and priority ranking is further carried out according to threat degrees and protection values. The invention aims to provide accurate, rapid and resource-focused decision support for biodiversity protection.

The invention discloses a pulse thermal imaging sequence key frame extraction method based on robust principal component analysis, and the method comprises the steps: firstly calculating a difference image between adjacent images of an original thermal image sequence, solving the L1 norm of a difference result, and determining a starting frame of pulse excitation according to the maximum value of the L1 norm; decomposing the thermal image sequence by using robust principal component analysis, and extracting a key frame according to the sparsity of a sparse matrix; and finally, extracting a sample region in the thermal image by using a local maximum entropy threshold segmentation method to obtain a thermal image key frame sequence containing the sample region. According to the method, manual key frame screening and ROI clipping in the prior art can be perfectly replaced, the space-time distribution characteristics of the thermal imaging sequence are fully utilized, a complete and efficient pulse thermal imaging sequence key frame automatic extraction algorithm framework is developed, and the defect recognition efficiency and the automation level are improved in practical application.

Disclosed are systems, devices and methods for quantifying unique features of an object such as an artistic work to identify and authenticate the object and specific characteristics thereof using multi-spectral diagnostic characterization techniques and analytical algorithms. In some aspects, a method for creating an identification for an object includes acquiring image data of an object in two or more electromagnetic spectrums along a coordinated array of sample regions of the object; analyzing the acquired image data to produce a quantitative data set including specific characteristics of the object associated with the two or more electromagnetic spectrums for each sample region; generating a digital identification associated with a unique data fingerprint, based on the specific characteristics, in which the digital identification solely corresponds to the object; and storing the generated digital identification.

The invention provides a high-throughput multi-view automatic positioning light sheet microscopic imaging method. The method comprises the following steps: automatically identifying the size of a sample, presetting parameters, and carrying out preliminary scanning; splicing imaging data in real time; globally and automatically positioning a sample area; planning a shooting path; and multi-target area high-throughput shooting parameters are optimized. A microscope large-view high-flux rapid imaging method based on a real-time image automatic splicing and positioning technology is combined with a real-time splicing function of shot imaging data and an automatic positioning function of a sample position in an image to rapidly search specific position area information of a sample; and shooting imaging and data storage of the experimental sample are realized by automatically optimizing shooting configuration parameters. The invention further provides a high-throughput multi-view automatic positioning light sheet microscopic imaging system adopting the method, and shooting imaging and data processing can be rapidly and accurately carried out on a target large sample.

The invention provides a photosensitive imaging method, which comprises the following steps of: opening a bin door (22) of an automatic bin entering and exiting device (11) of a photosensitive imager (10), and exposing a photosensitive chip assembly (65); a sample (70) is placed on the photosensitive chip assembly (65), and then the bin door (22) is closed; lightening the whole backlight assembly (66) to irradiate the photosensitive chip assembly (65) and the sample (70) on the photosensitive chip assembly (65); the photosensitive chip assembly (65) collects an image and identifies the position of the sample (70), and determines a sample area (71) and a non-sample area (72); sequentially lighting different colors of light of the local backlight assembly (66) so that only the sample area (71) is provided with backlight and the non-sample area (72) is not provided with backlight; the signal values of the backlight samples (70) of different colors are obtained through the photosensitive chip assembly (65), and a color image of the samples (70) is synthesized in combination with a software algorithm. According to the photosensitive imaging method, the signal-to-noise ratio of the image can be increased, the color image is obtained, and simultaneous detection of multiple samples is supported.

The invention discloses a deep sampling method for geological exploration, and belongs to the field. A deep sampling method for geological exploration comprises the following steps: step 1, moving equipment to a to-be-sampled area, and fixing the equipment; 2, performing vibration type drilling on the to-be-sampled area; thirdly, soil discharged in the drilling process is conveyed to the side away from the drilled hole; step 4, after drilling to a specified depth, sampling the soil; 5, after the soil sample is taken out, backfilling is conducted on the soil accumulated at the drilled hole; the problems that when deep geology is sampled, operation is tedious, consumed time is long, the accuracy of geological survey results is poor, drilling efficiency is low, and equipment is prone to being damaged can be solved.

The invention discloses a hyperspectrum-based wheat variety identification method. The method comprises the following steps: establishing a hyperspectrum identification model set of a target variety; checking and screening to obtain a target variety hyperspectral recognition model; and detecting the purity of the to-be-detected wheat variety in the wheat blind sample by using the variety identification hyperspectral model. And constructing a hyperspectral recognition model set of the target variety, wherein the modeling process comprises the following steps: confirming a wheat grain sample area in a spectrum acquisition process, extracting an average spectrum of a wheat grain modeling sample and constructing a recognition model. Screening and optimization of a target variety hyperspectral recognition model: selecting a to-be-detected sample with known target variety purity; determining a wheat grain sample area during sample spectrum collection; identifying a target variety in the to-be-detected wheat grain sample, calculating the purity of the target variety, and comparing the purity of the target variety with a true purity value of the target variety to obtain a hyperspectral identification model of the wheat target variety for identifying the target variety.

The invention relates to a soil microorganism recovery index processing method and system and electronic equipment. The method comprises the following steps: collecting a soil sample in a gradient sample area, and measuring soil microbiological indexes and soil attributes; taking the soil microorganism indexes as a mother sequence, taking the soil attributes as subsequences, calculating correlation coefficients and correlation degrees between the subsequences and the mother sequence, and determining key soil attributes influencing soil microorganism recovery; determining a weight value of the key soil attribute; based on the numerical values of the key soil attributes in the original ecological reference area and the damaged unrepaired area, combining the weight values of the key soil attributes, and adopting an improved soil restoration index model to calculate and obtain a soil microorganism restoration index; the technical problem that in existing mining area ecological restoration evaluation, an original ecological system is not used as a benchmark, and the soil microorganism restoration degree cannot be quantitatively represented is solved, and the technical effect of achieving objective, comparable and quantifiable accurate evaluation of the soil ecological function restoration degree is achieved.

The invention relates to the technical field of mathematical geology and geological big data, and discloses a geochemistry and remote sensing image fusion method, system and device and a storage medium, and the method comprises the steps: constructing a WVTNet model comprising a wavelet transformation module and a feature weight distribution module, and carrying out the training; wherein the wavelet transformation module is used for performing multi-scale image decomposition on geochemical data and a multispectral remote sensing image of a sample region to obtain a first image local feature and a second image local feature of different scales; the feature weight distribution module is used for acquiring key features in the plurality of first image local features and the plurality of second image local features based on a visual attention mechanism and fusing the key features to obtain a sample fusion image; and inputting the target geochemical data and the target multispectral remote sensing image of the target area into the trained WVTNet model to obtain a target fusion image. According to the method, the reliability and the information density of the fused data are improved, so that subsequent data analysis work is facilitated.

An apparatus comprises: a focused ion beam (FIB) column within a vacuum chamber configured to direct ions comprising a mixture of protons and non-hydrogen ions onto a sample, wherein the kinetic energy of ions of the mixture is not greater than 50 kilo-electron-Volts (keV); and an X-ray detector configured to detect and measure X-rays that are emitted from the sample in response to the impingement of the protons and non-hydrogen ions onto the sample. The apparatus may further comprise an electron microscope column within the vacuum chamber configured to direct and focus a beam of electrons onto the sample and to detect secondary electrons or backscattered electrons that are emitted from the sample in response to the impingement of the beam of electrons onto the sample. The electron microscope may generate an image of a sample area that is milled by the FIB column.

The invention discloses a portable phenylalanine detector and a use method thereof, and belongs to the technical field of phenylalanine detection equipment.The portable phenylalanine detector comprises a liquid chromatograph body, the liquid chromatograph body comprises a plurality of detection units, the upper side wall of the detection unit on the uppermost side is fixedly connected with a pressure pump, and the upper side wall of the detection unit on the uppermost side is fixedly connected with a pressure sensor; the water outlet end of the pressure pump is fixedly connected with a liquid inlet pipe communicated with the uppermost detection unit, the upper side wall of the uppermost detection unit is fixedly connected with a storage box, the storage box is divided into a water storage area and a sample area, and cleaning water and a sample storage bottle are arranged in the water storage area and the sample area respectively. A conveying pipe is fixedly connected between every two adjacent detection units, and a liquid discharging pipe is fixedly connected to the detection unit on the lowermost side. And through the one-by-one detection assembly, the worker is helped to quickly deduce which section of pipeline and the adjacent detection unit are blocked.

The invention relates to a method for predicting landslide susceptibility by using a machine learning model and SBAS-InSAR deformation, and the method comprises the steps: obtaining an environment static factor and landslide catalog in a sample region, obtaining a dynamic factor based on an SBAS-InSAR technology, building a landslide prediction model based on a random forest algorithm, and carrying out the prediction of the landslide susceptibility. Inputting the static factor, the dynamic factor and the landslide record into a landslide prediction model for training; and inputting the environmental static factor and the dynamic factor of the to-be-detected area into the trained landslide prediction model to obtain a landslide susceptibility map. According to the landslide susceptibility mapping method, the earth surface deformation rate serves as a dynamic factor to be fused into landslide susceptibility evaluation, a scientific basis is provided for landslide prevention and disaster reduction, the earth surface rail rising deformation rate and the earth surface rail falling deformation rate are obtained, the earth surface deformation rate is integrated into a static factor data set, and the landslide susceptibility mapping accuracy is improved. After uniform data preprocessing is completed, static factor and dynamic factor data are input into the landslide prediction model for joint training and evaluation, and the method has the advantage of being high in precision.

The invention discloses a method and system for dynamically monitoring soft sandstone slope erosion, and relates to the technical field of geological disaster monitoring, and the method comprises the steps: building a monitoring sample area on a soft sandstone slope, obtaining initial terrain point cloud data, generating a reference digital elevation model, and recognizing a vegetation space pattern; collecting rainfall data in real time, and triggering an erosion monitoring program when rainfall parameters meet a preset triggering condition; acquiring real-time terrain point cloud data, generating a current digital elevation model and acquiring a slope fracture feature set; based on the elevation variation of the current digital elevation model and the reference digital elevation model, carrying out erosion intensity partitioning; determining an erosion regulation effect coefficient of each vegetation coverage subarea by combining vegetation spatial pattern data; and establishing an erosion risk assessment model, and outputting erosion sensitivity grading of the monitoring sample area and a key protection area identification result. According to the invention, automatic and high-precision dynamic monitoring of soft sandstone slope erosion is realized, and a scientific basis is provided for water and soil conservation and geological disaster prevention and control.

An intra prediction method includes: performing filtering processing on template samples corresponding to a target image block to obtain filtered template samples, where the template samples include at least part of reconstructed samples in a neighboring sample region of the target image block; obtaining, based on the filtered template samples, at least one intra prediction mode and an amplitude of the at least one intra prediction mode; determining, based on the amplitude of the at least one intra prediction mode, a target intra prediction mode from the at least one intra prediction mode; and determining, based on the target intra prediction mode, a target prediction value corresponding to the target image block.

A line-scan confocal scanning light-field microscopic imaging apparatus (10) and method. Said apparatus comprises: a microscope (100), a target biological sample being placed on a stage of the microscope (100); an excitation optical path (200), which is used for outputting a line-shaped light source for exciting fluorescence of the target biological sample; a line-scan hardware optical path (300), which is used for performing multi-dimensional scanning of the line-shaped light source to obtain a scanned light-field image; a microlens array (400), which is used for light-field modulation of the line-shaped light source to obtain a line-shaped light field; a camera (500), which is used for performing three-dimensional imaging on the basis of the line-shaped light field to obtain a three-dimensional image; and a control system (600), which is used for controlling the line-scan hardware optical path (300) and the camera (500) to execute a line-scan confocal action, so that the number of pixel rows exposed simultaneously at a same moment is consistent with a sample region illuminated by the line-shaped light source, so as to separate a sample fluorescence signal and a background fluorescence signal of the target biological sample, and, on the basis of the scanned light-field image and the three-dimensional image, generate a three-dimensional microscopic image with background fluorescence removed for the target biological sample. Therefore, the problem of background fluorescence in a scanning light-field microscopy system is solved.

The invention provides a cold and hot dual-purpose transmission electron microscope in-situ sample rod. The cold and hot dual-purpose transmission electron microscope in-situ sample rod comprises a handle, a rod body and a rod head, the handle part is provided with an external power supply interface and a cold source conduit interface, and can be externally connected with a heating power supply, a cold source and the like, so that current, a cooling medium and the like flow into the rod head part of the sample rod to realize a heating or refrigerating function. The rod head part is provided with an objective table, a cooling medium guide pipe, a sample loading device, a heat sensitive element and an electrode assembly. The sample fixing device is used for fixing a sample; the heat-sensitive chip is used for measuring the temperature of the sample area; the heating electrode part is used for heating the sample part after being connected with a power supply so as to realize transmission electron microscope observation of the sample in a high-temperature environment. By using the in-situ sample rod disclosed by the invention, direct heating and refrigeration can be realized to create high-temperature and low-temperature detection environments, and the experimental operation process of in-situ testing is simplified.

The invention relates to a consumable device for sweat-based monitoring, the consumable device comprising a proximal part configured to contact with a user, and further comprising: a) a sweat induction means on the proximal part, comprising: i. a sweat promoter configured to contact the skin of a user, and ii. a microfluidic structure; and b) a sweat interrogation means, located distally to the sweat induction means and comprising: i. a sample area; and ii. a passive fluid pump configured to induce the flow of the liquid through the sample area. The microfluidic structure is configured to convey fluid from the sweat promoter to the sample area. The invention also relates to a sweat-monitoring system comprising: a consumable device as above and a sweat-based monitoring device, the sweat-based monitoring device comprising sensing means and processing means.

The invention discloses a sample sending process monitoring system fusing image recognition and geographical location information, comprising a multi-source information acquisition module for acquiring image information around a sample and geographical location information of the sample in a sample sending process; the sample sending abnormal behavior recognition module based on image recognition is used for detecting pedestrian abnormal behaviors, camera abnormal shielding and camera angle abnormal adjustment in a sample area according to the image information; the sample sending abnormal behavior recognition module based on the geographic position information is used for extracting space-time trajectory characteristics of the sample according to the geographic position information of the sample and detecting a time abnormal trajectory, a space abnormal trajectory and a space-time abnormal trajectory according to the space-time trajectory characteristics; and the early warning module is used for generating an abnormal behavior signal or a non-abnormal signal according to the detection result of the sample sending abnormal behavior and the abnormal track behavior, and sending early warning information according to the abnormal behavior signal. The method has the advantages of small algorithm size, easy migration, low cost and the like, and can improve the user experience.

A microscope system includes at least one illumination subsystem configured to produce and direct a light sheet toward a specimen region. The illumination subsystem includes a spatial adjustment apparatus configured to operate in a plurality of different modes, each operating mode configured to produce a light sheet having a different spatial status. The microscope system includes at least one detection subsystem arranged to collect fluorescence emitted from the specimen region due to an interaction between a specimen at the specimen region and a light sheet. The at least one detection subsystem includes a plurality of imaging devices, with each imaging device being associated with a different spatial status such that each imaging device is configured to record images of the fluorescence due to an interaction between a specimen at the specimen region and the light sheet of the associated spatial status.

The invention relates to the technical field of detection sample sealing, in particular to an instant-drying type slide sample sealing protection device which comprises a slide tray provided with a slide placing groove used for placing a slide; the linear driving module is connected with the slide tray and is used for driving the slide tray to linearly act; the glue adding module comprises a glue dripping head located above the moving path of the slide tray and is used for adding glue to the sample area of the slide; the glue scraping module comprises a scraping blade, and the scraping blade is located above the moving path of the slide tray and used for scraping glue on the slide; and the glue drying module is positioned on one side of the glue scraping module and is used for drying glue on the slide. According to the method, a brand new process is adopted, cover glass does not need to be placed on the slide, the problem of cover glass fragmentation and the problem of mounting medium pasting are avoided, the problem of mutual intersection of smear lamination storage is solved, the storage efficiency of a smear cabinet is improved, and rapid smear sealing can be achieved.