87results about How to "Preserve integrity" patented technology

The invention discloses a grinding workpiece edge shape detection method and system based on machine learning, and the method comprises the steps: obtaining an original image of a grinding workpiece, and carrying out the preliminary image preprocessing; denoising the image and enhancing edge information by combining image filtering and mathematical morphology image processing; based on a second-order differential operator, edge detection is carried out in combination with the morphological gradient, and a workpiece edge contour is obtained; performing feature extraction on the image by using a convolutional neural network, automatically learning workpiece edge features, and constructing and training an edge detection model; acquiring a workpiece image in real time, inputting the workpiece image into the edge detection model for detection, and dynamically correcting the model; and S6, outputting a final edge detection result. According to the invention, by combining image preprocessing, composite image filtering, second-order differential operator and morphological gradient edge detection and feature extraction and model construction of the convolutional neural network, high-precision and robust detection of the edge of the grinding workpiece is realized.

The invention discloses a large model reasoning method and device based on sensitive information protection and related equipment. The method comprises the steps that firstly, an original input text is obtained, sensitive entities in the original input text are detected through a named entity recognition NER model, relation extraction and attribute extraction are conducted, and a sensitive information knowledge graph is constructed; then, screening sensitive information in the original input text according to the knowledge graph, and replacing the sensitive information to generate a desensitized input text; next, calling a first large model of the server side, and executing a specified task by using the desensitized input text to obtain a result text; and finally, calling a second large model of the user side, and restoring the sensitive information in the result text by using the original input text, the desensitized input text and the result text to obtain a complete text. Large models configured at different ends are utilized, sensitive information is protected, and meanwhile practicability of result texts is taken into account.

The arc-shaped end face dynamic deformation suspended ceiling structure comprises a keel, a plurality of arc-shaped decorative plates arranged in a staggered mode and a light guide illumination structure are connected to the lower portion of the keel, connecting plates are arranged at the two ends of each arc-shaped decorative plate, and the end of each arc-shaped decorative plate is connected with the connecting plate on the corresponding side. The connecting plate is a U-shaped groove plate with an upward opening, a lamp hiding groove is formed in the upper concave portion of the connecting plate, a lamp is arranged in the lamp hiding groove, and the end of the light guide illumination structure is fixedly connected with the lamp. The arc-shaped decorative plates are fixedly connected with the connecting plates through bolts, a plurality of lifting rods and a plurality of supporting rods are arranged on the keel, the arc-shaped decorative plates are fixedly connected with the keel through the supporting rods, the middle and the other end of the light guide illumination structure are connected with the keel in a lifting mode through the lifting rods, and the light guide illumination structure is deformed through lifting of the lifting rods. Dynamic deformation of light and the whole ceiling arc is achieved, the lamp is hidden through the lamp hiding groove, the light is refracted to the lower portion through the light guide strip for illumination, the irradiation area is effectively increased, glare is reduced, the ceiling structure does not need to be damaged, installation is convenient, and maintenance and replacement are convenient.

The present invention relates to the field of non-standard automation technology, in particular to an end cap rotary cutting assembly system and method for an injection-molded bottle body, comprising an injection molding machine, an injection molding transfer mechanism, a conveying mechanism, a first positioning mechanism, a first clamping mechanism, a rotary cutting mechanism, a second positioning mechanism, a second clamping mechanism and an end cap assembly mechanism, wherein the injection molding machine is used for bottle body injection molding, the injection molding transfer mechanism comprises an injection molding material picking component and an injection molding conveying component, the injection molding material picking component is used for grabbing the injection-molded bottle body on the injection molding machine and placing it on the injection molding conveying component, the injection molding conveying component is used for conveying the bottle body toward the conveying mechanism, the conveying mechanism is used for bottle body conveying, the first positioning mechanism is used for positioning the bottle body on the conveying mechanism, the first clamping mechanism is used for clamping the positioned bottle body and conveying it toward the rotary cutting mechanism, and the rotary cutting mechanism is used for ring cutting at the port on the bottle body; the present invention realizes full-chain automated operation from injection molding to end cap assembly through integrated and automated design.

The invention belongs to the technical field of cell engineering and biochemical detection, and particularly relates to an erythrocyte membrane with a complete structure and a preparation method and application thereof. The red blood cells are split by limiting the components of the release liquid, the conditions are mild, protein components such as hemoglobin in the red blood cells can be released, the cell attributes are removed, the integrity of the internal skeleton structure and the activity of the membrane surface antigen are reserved, the complete structure of the red cell membrane is kept, meanwhile, the key blood group antigen on the surface is reserved, and the effect is good. The problem of antigenicity reduction caused by erythrocyte membrane fragmentation is avoided. After the erythrocytes are lysed, the nanoparticles are coupled to the surface of the erythrocyte membrane, so that the agglutination reaction of the erythrocyte membrane under the induction of the antibody can be visualized. The engineering red blood cell biological membrane is preserved by adopting a fixed program, so that the damage of ice crystals to the engineering red blood cell biological membrane can be effectively avoided, the antigenicity of the membrane is not influenced, the membrane can be preserved for a long time at normal temperature, and the shelf life can be prolonged to two years or more.

The invention discloses a nondestructive testing method for pipe cutting decision of an austenitic steel pipe. The nondestructive testing method comprises the following steps: pretreating the surface of a to-be-tested 18Cr-8Ni series austenitic steel pipe to specified roughness; calibrating and detecting relative permeability values of a plurality of positions of the pretreated steel pipe under set parameters by using a permeability meter; comparing each measured relative permeability value with a pre-established corresponding steel grade aging rating threshold database; and according to the proportion of the detection points exceeding the threshold value, whether the 18Cr-8Ni series austenite steel pipes need to be subjected to pipe cutting sampling or not is decided. According to the method, the quantitative relation between the relative permeability and the aging degree of the material is established through nondestructive testing of the relative permeability of the 18Cr-8Ni series austenite steel pipe in service, so that the aging level of the metallographic structure is evaluated, and a basis is provided for on-site pipe cutting decision.

The invention provides a fault root cause determination method and device, electronic equipment, a storage medium and a product, and belongs to the technical field of cloud computing. The method comprises the steps that after a target service requested by a target service request fails, tracking data, log data and index data corresponding to each node are acquired based on node information of at least one node on a service path corresponding to the target service request, and the nodes provide a service interface called in the process for the target service; performing feature extraction on the tracking data, the log data and the index data corresponding to each node to obtain a tracking feature vector, a log feature vector and an index feature vector corresponding to each node; fusing the tracking feature vector, the log feature vector and the index feature vector corresponding to at least one node to obtain a total fusion feature vector; and determining a fault root cause of the target service based on the total fusion feature vector. The fault root cause determination efficiency can be improved, and the determination cost can be reduced.

The invention relates to the technical field of Korla bergamot pear detection, and discloses a Korla bergamot pear organic acid content nondestructive detection method, which comprises: collecting a bergamot pear sample with consistent maturity, no damage and complete surface layer; the surface is wiped with absolute ethyl alcohol and then naturally air-dried, only the surface layer is subjected to vacuum freeze drying and smashing, and the integrity of a main body is reserved; according to the method, ICP-MS, HT-IRMS and GC-MS / EMIS are combined with an HS-HPME extraction technology, multi-dimensional detection of mineral elements, isotope contents and ratios and volatile components is carried out, and an isotope and element characteristic database and a regional characteristic volatile substance fingerprint spectrum are constructed; analyzing and screening characteristic indexes through orthogonal partial least squares, and eliminating interference factors; and establishing a linear discrimination model, forming an organic acid content detection and origin identification integrated technical system, and optimizing detection parameters. According to the method, rapid and nondestructive testing and source area traceability are realized, and reliable technical support is provided for quality evaluation of the Korla bergamot pears.

The utility model relates to the technical field of vegetable washing, in particular to a bubble vegetable washing machine which comprises a vegetable washing machine body, the vegetable washing machine body comprises a machine box, a material groove is formed in the machine box, a conveying net belt is arranged in cooperation with the material groove, a first mounting frame is arranged at the top of the material groove, and a spraying pipe is arranged on the first mounting frame through a bearing; a supporting frame matched with the conveying mesh belt is arranged on the material tank, a second mounting frame is arranged on the supporting frame, a plurality of flushing pipes are arranged on the second mounting frame through bearings, flushing heads are arranged on the flushing pipes, one end of each of the spraying pipe and the flushing pipes is sealed, and the other end of each of the spraying pipe and the flushing pipes is provided with a water inlet pipe through a sealing bearing; a rotation adjusting structure is arranged between the spraying pipe and the washing pipe, a high-low frequency bubble generating structure matched with the material groove is arranged in the machine box, the washing angle of vegetables during washing can be flexibly adjusted, the washing sufficiency is improved, and the erosion effect on the vegetables in the washing process is reduced.

The invention provides an exosome enrichment method based on a boric acid modified capture material. The method comprises the following steps: adding a boric acid modified capture material into a solution to be enriched, adjusting the pH value to 7.8-8.5 with Tris-HCl, carrying out mild oscillation incubation at 2-8 DEG C for 5-60 min, centrifuging, and collecting the precipitate; and gently washing the precipitate by using a PBS (Phosphate Buffer Solution) containing fructose or glucose, adding an eluent, eluting at 2-8 DEG C for 5-30 minutes, and centrifuging to obtain a supernatant rich in exosome. The exosome enrichment method disclosed by the invention is simple, efficient, rapid and low in cost; the obtained exosome is intact in form and high in purity, the biological activity of the exosome is not affected, and the exosome has important practical value and popularization prospects.

This invention discloses a machining process for tortuous parts made of fiber-reinforced composite materials, comprising the following steps: tooling design, part clamping and positioning, rough machining of area AB, failure handling, finish machining of area AB, rough machining of area C, finish machining of area C, removal of end faces, and finished product inspection. This invention provides a machining process for tortuous parts made of fiber-reinforced composite materials. By designing specialized tooling according to the part's shape and introducing failure handling, it reduces the waste of plywood raw materials compared to traditional machining processes. It also solves the problems of stress deformation and datum misalignment during the machining of tortuous parts made of fiber-reinforced composite materials, possessing significant economic and social value.

The present invention relates to a graphene material. Disclosed are a graphene powder and its preparation method and application. The graphene powder is a stack of graphene sheets. The graphene powder involves in its Raman spectrum a D peak and a G peak with peak heights of ID and IG respectively, where ID / IG is 0.10 or less. The graphene powder in accordance with the present disclosure can be applied in conductive composite materials, anti-corrosion coatings, heat dissipation composite materials. In particular, when used in lithium-ion batteries, it can significantly reduce electrode internal resistance and improve battery stability at any current rates.

The invention provides an automatic pteroceltis tatarinowii peeling machine which can peel pteroceltis tatarinowii with different diameters, meanwhile, the integrity of pteroceltis tatarinowii peels is reserved to the maximum extent, the automatic pteroceltis tatarinowii peeling machine comprises a conveying module, a first extrusion module, a second extrusion module and a peeling module, and the conveying module is arranged at the front end and the rear end of the peeling module; the first extrusion module is located above the conveying module at the front end of the peeling module, and the second extrusion module is located above the conveying module at the rear end of the peeling module. The conveying module drives the pteroceltis tatarinowii to move in the axial direction; the first extrusion module and the second extrusion module are used for pressing the pteroceltis tatarinowii onto the conveying rollers; the peeling module comprises a cutting knife module and a tearing module, when the pteroceltis tatarinowii moves in the axial direction, each cutting knife cuts a cutting seam parallel to the axial direction of the pteroceltis tatarinowii on the pteroceltis tatarinowii, and the depth of the cutting seam in the radial direction of the pteroceltis tatarinowii is not smaller than the thickness of the bark of the pteroceltis tatarinowii; when the pteroceltis tatarinowii with the bark divided into strips moves from front to back in the axial direction, the cutting edge of each cutter cuts into the end of the pteroceltis tatarinowii.

The utility model discloses an amanita spore collecting device which comprises a supporting rod, a gravity base is installed at the lower end of the supporting rod, a connecting base is fixedly installed at the upper end of the supporting rod, an installing base is fixedly installed at the upper end of the connecting base, a petal base is rotationally connected to the surface of the installing base, and a collecting paper bowl is installed on the inner side of the petal base. An elastic sleeve is integrally connected to the middle of the interior of the collection paper bowl; an air blower in the middle of a mounting seat is used for blowing air from the bottom of an amanita strain, spores in a gill are blown into a collection paper bowl, collection of the amanita spores is completed, an opening structure on one side of a valve seat is combined with a rotating structure arranged between the supporting rod and a gravity base, so that the supporting rod is inclined, the valve seat is made to be close to the strain, and the spores in the amanita strain are collected. Therefore, the whole strain does not need to be collected for spore collection, the integrity of the strain is reserved, and the actual culture quantity and the overall medicinal value of the amanita are not influenced.

The application discloses a strawberry sugar content efficient nondestructive detection method based on an intelligent algorithm, and comprises the following steps: acquiring a plurality of strawberry spectrum data and sugar content reference values, and dividing the strawberry spectrum data into a training set, a verification set and a test set; performing wavelet denoising and polynomial baseline correction on the spectrum data to obtain preprocessed data; extracting key characteristic wavelengths from the preprocessed data, and constructing an initial SVM model based on the key characteristic wavelengths; optimizing the initial SVM model by using the training set to obtain an optimized SVM model; acquiring target strawberry spectrum data, and inputting the optimized SVM model to obtain a detection result. The application realizes rapid, nondestructive and accurate detection of the sugar content of strawberries, and provides technical support for intelligent development of the strawberry industry.

The utility model relates to a rice drying and dust removing device, including main box body and the drying cylinder of rotation connection in main box body, be equipped with a plurality of through -hole on the drying cylinder, the main box body upper end is connected with the air supply spare, the main box body bottom is connected with the collection spare, the technical scheme of the present application has the beneficial technical effect: through the rotation design and through -hole structure of drying cylinder, cooperate air supply spare and form dynamic air circulation, realize the fast and even drying of rice, utilize the dust and moisture that the collection spare's negative pressure adsorption effect synchronously removes the dust and moisture that rice surface adheres, significantly improve processing efficiency and rice cleanness. Moreover, the rotation design of drying cylinder makes rice in the drying process present the tumbling state, avoids the partial overheating or extrusion breakage and uneven drying problem caused by the long time stationary of rice in the traditional drying mode. Cooperate the even air supply of through -hole, maximum limit keeps the integrity and nutrient component of rice, has improved the evenness of drying. The problem that the prior art is prone to drying incompletely is solved.

The invention belongs to the technical field of flow detection, and particularly relates to an ultrasonic flow fusion method and system based on multiple modalities, and the method comprises the following steps: S100, constructing a modal number selection model in advance; s200, a first probe and a second probe are adopted to send a first transmitting signal and a second transmitting signal respectively, and a first receiving signal and a second receiving signal are collected correspondingly; s201, a corresponding mode selection number is matched in the mode number selection model; s202, at least three modes are selected from the modes according to the mode selection number, and the selected at least three modes are divided into at least two mode groups; s203, the volume flow is obtained through calculation according to the modal group; and S205, a flow mean value is calculated according to the at least two volume flows, and compared with flow measurement in a single mode, the flow measurement precision in a large-pipe-diameter scene is greatly improved.

The invention belongs to the technical field of image processing, and particularly relates to an ultrasonic medical image enhancement method based on deep learning, which comprises the following steps: establishing an ultrasonic medical image enhancement model, training the ultrasonic medical image enhancement model, and performing image enhancement through the trained ultrasonic medical image enhancement model. According to the method, the visual effect of the ultrasonic image can be effectively improved, key details in the image are reserved, the enhancement effect of the ultrasonic medical image is improved, and the integrity of the contour and the clarity of the structure of the medical image are ensured; through end-to-end training and optimization, the optimal strategy for enhancing the visual effect from the ultrasonic medical image can be automatically learned, manual intervention is not needed, and the convenience and practicability of operation are improved.

The invention discloses cation modified nano graphene oxide and a preparation method thereof, the transverse size of the cation modified nano graphene oxide is 10-100 nm, the surface of the cation modified nano graphene oxide is non-covalently bound with organic quaternary ammonium salt cations through electrostatic interaction, and the organic quaternary ammonium salt cations are provided by a cationic surfactant. According to the invention, electrostatic interaction is combined with a quaternary ammonium salt cationic surfactant, and a hydrophobic long alkyl chain of the quaternary ammonium salt cationic surfactant is exposed outwards, so that the product can be stably dispersed in various organic solvents such as methanol, ethanol, acetone, ethyl acetate, N-methyl pyrrolidone (NMP), N, N-dimethylformamide (DMF), dichloromethane and the like; the limitation that traditional nano graphene oxide is only limited to a water phase is avoided, and the compatibility and application potential in the fields of polymer composite materials, oil paint, high-performance resin and the like are improved.

The invention relates to an ARIMA model-based general insurance loss ratio prediction method. The method comprises the steps of collecting historical actual loss data and historical loss data; preprocessing the collected data to obtain corresponding actual compensation time sequence data and compensation time sequence data; based on the actual compensation time sequence data and the compensation time sequence data, model parameters are determined by drawing an autocorrelation function ACF graph and a partial autocorrelation function PACF graph, and the model parameters are used for building a basic ARIMA model; on the basis of the actual compensation time sequence data and the compensation time sequence data, characteristic factors are determined through rule statistics; putting the characteristic factors into a basic ARIMA model, and verifying the model; and inputting the historical data of the compensation amount and the characteristic factor of the prediction time period into the verified ARIMA model, and outputting to obtain the compensation ratio corresponding to the prediction time period. Compared with the prior art, the method can improve the accuracy and stability of the loss ratio prediction through constructing the regional exclusive loss ratio prediction model.

The invention relates to the technical field of data processing of multi-source data fusion, and discloses an investigation data integration analysis method and system based on multi-source data fusion. According to the scheme, a multi-source sensor is deployed, original voltage is collected, and standardization is carried out in each physical quantity range; constructing temperature, pressure and vibration three-dimensional observation and states based on a unified time index, and setting initial values; recursive prediction is carried out by using a constant preserving model; counting a multi-measuring-point variance in a static window, determining observation noise in combination with the minimum quantization step size, and calculating fusion gain; linearly updating and correcting covariance, and then carrying out dimension-by-dimension amplitude limiting according to an abnormal upper limit; carrying out space averaging on the three-dimensional results of the multiple measuring points at each sampling moment, and carrying out rollback if necessary; and a fusion sequence and a statistical report are formed in the whole cycle. According to the method, the data scale is unified, subjective parameters and computing power burden are reduced, adaptive noise modeling along with the environment is achieved, stable noise suppression and fault resistance are achieved, and continuous output and comparable analysis are guaranteed.

The invention belongs to the technical field of flow detection, and particularly relates to a temperature-adaptive ultrasonic flow measurement method and system.The method comprises the steps that S101, a first probe and a second probe are adopted to send a first emission signal and a second emission signal respectively, and a first receiving signal and a second receiving signal are collected correspondingly; s102, selecting two modes from the plurality of modes; s103, respectively acquiring the forward and reverse flow time under the first mode and the second mode; s104, the volume flow is calculated according to the forward and reverse flow time in the S103; by means of the method, the temperature-adaptive ultrasonic flow measuring method capable of being applied to the large-pipe-diameter and large-flow pipeline is comprehensively provided, and the tedious temperature compensation process in the prior art is reduced.

The invention relates to the technical field of document merging, in particular to a document merging system and method, equipment and a medium, the system comprises an interaction and configuration module, a document analysis and routing module, a document merging module and a verification and repair module, and the verification and repair module is integrated in the system to be in communication connection with the document merging module. And the verification and repair module is used for verifying and repairing the page header and the page footer of the output document, so that the segments, the page header and the page footer of all the documents in the output document are kept in the original format before merging. By means of the mode, the multi-format documents can be intelligently, automatically and losslessly combined in batches, and it is ensured that the format and header and footer completeness of each document are reserved.

The application provides a kind of based on feature enhancement and composite model's ultra-short-term wind power prediction method, belongs to ultra-short-term wind power prediction technical field, this method includes: by calculating the mutual information of multiple meteorological characteristics and wind power output and normalizing, screening to obtain key features, and constructing wind power prediction fitness function, by minimizing wind power prediction fitness function, obtain enhanced input features;By introducing one-dimensional convolutional neural network and bidirectional long short gate recurrent unit, construct the residual network of bidirectional long short gate recurrent unit and convolutional neural network fusion, and introduce space-time attention mechanism, construct to obtain composite residual network ultra-short-term wind power prediction model;And use multiple meteorological characteristics and enhanced input features to predict to obtain ultra-short-term wind power prediction result;The application solves the problem that the influence of meteorological multi-scale fluctuation on output cannot be accurately grasped, prediction is disconnected, disturbance is not considered and prediction accuracy continues to decline with step increase.

The invention relates to the technical field of semiconductor equipment cleaning, and particularly discloses a shield component cleaning method which comprises the following steps of pre-protection, acid leaching, water leaching, gravity sand blasting, high-pressure water washing, ultrasonic cleaning, drying and packaging. In the pre-protection step, the bottom of the shield part is protected by using an acid and alkali resistant adhesive tape, and the four layers of PE bags are pressed by using a cover matched with the shield part and are pressed on the inner edge of the cover; the volume ratio of nitric acid to hydrofluoric acid in the acid leaching step is (5-7): 1; and in the gravity sand blasting step, aluminum oxide sand is adopted for carrying out surface sand blasting on the shield component, and the sand blasting pressure is 3-4 kg / cm < 2 >. The method for cleaning the shield component has the advantages of being short in film removing period, high in cleaning efficiency, safe, reliable and the like, the basic functions of the shield component can be effectively recovered, and repeatability and reliability of the PVD technology are guaranteed.

The invention discloses a radar HRRP deformation target recognition method based on feature correction, and the method comprises the steps: carrying out the preprocessing of the radar one-dimensional HRRP echo data of a to-be-recognized target, and obtaining the HRRP original target data; superposing block sparse signals with different sparseness and Gaussian white noise on the HRRP original target data to obtain HRRP deformation target data; constructing a lightweight feature extraction network, and performing pre-training by using HRRP original target data; a feature correction network comprising a multi-dimensional parallel feature correction module, a feature fusion module and a de-noising post-processing module is constructed, and training is carried out after the feature correction network is cascaded with the feature extraction network; and combining the feature extraction network with the feature correction network to obtain a deformation target identification model so as to realize identification and classification of a deformation target. According to the method, the intrinsic feature distribution of the deformed target can be effectively recovered, and the recognition accuracy and generalization ability of the non-cooperative target in a low signal-to-noise ratio environment are remarkably improved.

The invention relates to a video processing method based on audio and picture synchronization, and the method comprises the steps: screening candidate segments from a video material library according to the content inputted by a user, determining a target segment from the candidate segments based on a deep interaction algorithm and semantic entity correlation analysis, determining the video time length of the target segment, and outputting the video time length of the target segment. Determining the line number of the target segment based on the large language model, calculating a target playing duration according to the line number and a preset dubbing speed, judging whether the target segment has a duration deviation based on the target playing duration and the video duration, and if the target segment has the duration deviation, playing the target segment based on the target playing duration and the video duration. And performing adaptive speed change processing on the target clip to generate a final video clip. According to the method and the device, the problem that the audio and the picture of the video are asynchronous is solved, the speed change algorithm is dynamically optimized based on the deviation degree of the target playing duration and the video duration, and the integrity of the picture and the audio is kept while the audio and picture synchronization is ensured.

The invention discloses a lithium battery positive plate stripping and recycling method, and belongs to the technical field of battery recycling. The recycling method comprises the following steps: shearing the waste ternary positive plate to obtain first positive plate fragments; immersing the first positive plate fragments into a solution containing a monomer and an initiator, and enabling the solution to completely permeate into the first positive plate fragments to obtain second positive plate fragments; after in-situ polymerization, carrying out mechanical crushing and sorting to respectively obtain positive electrode black powder and a positive electrode current collector; wherein the waste ternary positive plate comprises a positive current collector and a positive material layer arranged on at least one surface of the positive current collector. According to the invention, the separation of the positive electrode active material layer and the positive electrode current collector is realized through the combination of interface in-situ embrittlement and mechanical crushing, and the problem that the recovery of the positive electrode material cannot meet the requirements of high yield, high purity and low damage at the same time is solved.

The application provides a high-temperature early warning probability calculation method and system based on dynamic updating and whole point scanning. The high-temperature early warning probability calculation method based on dynamic updating and whole point scanning comprises the following steps: S1, historical data acquisition and sequence construction; S2, whole point alarm interval calculation; S3, alarm threshold input and real-time monitoring; S4, real-time early warning probability judgment and display; S5, dynamic updating mechanism. The high-temperature early warning probability calculation method and system based on dynamic updating and whole point scanning provided by the application has the advantages that scientific probability output can be provided, and early warning prompts can be given at an earlier time of the day.

The invention relates to the technical field of big data analysis, in particular to a space-time big data acquisition and analysis system and method based on the Internet of Things, and the method comprises the following steps: inserting a drift compensation tag at the tail part of each time grid block, and outputting the time grid block with the drift compensation tag; combining the associated data items into a logic data unit; performing semantic isomorphic compression on the logic data unit and the data items with the same spatial hash codes at an edge node to generate a compression block with a spatial-temporal index; and the cloud server receives the compressed block, performs time conflict disambiguation and event-level causal reasoning on the spatio-temporal index by using a causal chain engine, and directly outputs drifting-free and redundancy-free spatio-temporal knowledge which is used for driving high-order application. According to the method, cross-space causal path matching and standard time sequence verification of the uploaded data are realized, and a plurality of actually occurring event-level causal chains can be automatically identified.