58results about How to "Overcome precision" patented technology

The invention belongs to the technical field of humidifiers, and relates to a heating integrated humidifier which comprises a water tank and a base, a containing cavity used for containing liquid and water vapor mixture is formed in the water tank, and an air inlet and an air outlet which are communicated with the containing cavity are formed in the water tank; the water tank is provided with a heat conduction plate, one side of the heat conduction plate is located in the containing cavity, and the other side of the heat conduction plate is provided with a heating element in close contact. And the base is used for supplying energy to the heat conducting plate.

The invention discloses a method for calculating the wave load borne by a pile based on machine vision, and the method comprises the steps: collecting and obtaining a water surface image sequence containing the pile, carrying out the image processing of the water surface image sequence, obtaining a flow field image, carrying out the post-processing of the flow field image, and obtaining an optimized flow field image, the flow field is comprehensively monitored through machine vision, and accurate recognition of the flow field where the pile is located is improved; calibration of a preset image scaling is carried out on the optimized flow field image, pixel coordinates in the optimized flow field image are converted into actual coordinates, pile periphery data under a corresponding flow field are obtained based on a particle image velocimetry (PIV) algorithm, and a velocity vector field of fluid particles can be obtained through the particle image velocimetry algorithm (PIV); the flow velocity distribution, vortex and other fluid mechanics parameters of the whole water area are further deduced, pile periphery data under the corresponding flow field can be obtained, then the wave load borne by the pile is obtained based on the Morison equation, and the defect that according to an existing wave load method, due to the fact that the working environment of underwater ocean engineering structures is complex and severe or the safety requirement is high, the wave load is poor is overcome. The problems of low wave load accuracy and high investment cost are solved, and the accuracy and efficiency of the wave load borne by the pile are greatly improved.

The invention discloses a lithium battery SOC-SOH joint estimation method based on mechanism and data fusion driving, and the method comprises the following steps: firstly, carrying out the training of a prediction model of a least square support vector machine (LSSVM, LSSVM) through a multi-dimensional data set after phase space reconstruction; and then, establishing a state equation based on an ampere-hour integral method and a capacity fading empirical model, establishing an IUPF observation equation through an LSSVM prediction model, and substituting the IUPF observation equation into an improved unscented particle filter algorithm (IUPF, Intermediate UPF) to perform state estimation and parameter updating. And finally, the updated LSSVM model parameters are iterated to a training data set, so that the combined prediction of the SOC (State OfCharge) and the SOH (State OfHealth) of the battery and the online updating of the data driving model are realized. According to the lithium battery SOC-SOH joint estimation method based on mechanism and data fusion driving provided by the invention, joint estimation of the state of charge SOC and the state of health SOH of the lithium battery is realized, and state noise and measurement noise of the system are considered, so that the precision and stability of a battery state estimation result are ensured.

The invention discloses a river network water pollution tracing method which comprises the following steps: firstly, acquiring river network data, inputting the river network data into MIKE software, constructing a hydrodynamic model of a river network, and verifying the hydrodynamic model; dividing the whole river network into a plurality of river reaches by taking water quality monitoring points as nodes, and inputting river network data corresponding to each river reach into the verified hydrodynamic model to obtain simulation data of each river reach; preprocessing the simulation data of each river reach, inputting the preprocessed simulation data into a gating circulation unit, and constructing a regression model of each river reach; and tracing by using the regression model. According to the method, MIKE software is adopted to simulate the pollutant diffusion condition, so that data supplementation is carried out under the condition that monitoring data is sparse, pollutant tracing is carried out in combination with a regression model, hydrodynamic simulation data is used as input of the regression model, the precision and density of a data set can be improved, and the accuracy and the density of the data set are improved. And accurate positioning of the pollution source and the pollution source parameters is realized.

The invention discloses a wired insulation on-line monitoring method and system based on digital intelligent power supply storage, and the method comprises the steps: firstly collecting and preprocessing a power interference signal, extracting feature information from the signal through a wavelet transform technology, and then carrying out the classification and prediction of a cable insulation state through a Transform model. The method not only can effectively identify the health state, the slight aging state and the severe aging state of the cable, but also is high in detection precision and good in real-time performance, overcomes the problems that an existing monitoring method is insufficient in real-time performance and low in detection precision in a complex electric power environment, and remarkably improves the reliability and efficiency of cable insulation monitoring.

The invention belongs to the technical field of measurement, and particularly relates to a method and a system for measuring a large complex curved surface part based on a combined relay method. According to the invention, the laser tracker and the three-dimensional scanner are combined, the three-dimensional scanner carries out partition measurement on a large complex curved surface part, and the laser tracker is used for direct measurement and is also used for tracking and positioning the three-dimensional scanner. According to the invention, a coordinate transformation matrix between the three-dimensional scanner and the laser tracker is established through common point optimization, and error correction of data measured by the three-dimensional scanner is realized. The laser tracker is used for precisely positioning each station transfer process of the three-dimensional scanner, and then the benchmark of point cloud data obtained through measurement of different partitions is unified. And finally, directly measuring a special area in the to-be-measured large complex curved surface part through the laser tracker so as to complete all measurement tasks. The problem that in the prior art, accurate and efficient measurement of large complex curved surface parts is difficult to achieve is solved.

The invention relates to a magnetizing control method and related equipment thereof, and relates to the technical field of magnetizing control. A specific embodiment of the method comprises the following steps: in response to starting of magnetizing operation, obtaining current magnetizing current values in a plurality of magnetizing channels in a magnetizing operation process; determining a target magnetizing voltage value corresponding to each magnetizing channel according to a preset magnetizing current value, a magnetizing channel mapping table and the current magnetizing current value; wherein the magnetizing channel mapping table comprises a corresponding relation between a preset magnetizing current value and a target magnetizing voltage value in each magnetizing channel; and according to the target magnetizing voltage value, executing magnetizing operation of the target product in the corresponding magnetizing channel. According to the embodiment, it is guaranteed that the magnetizing current of each channel is consistent, then the magnetic field consistency of each channel is guaranteed, the magnetizing current control effect is improved, and the magnetizing operation precision and the magnetizing efficiency are improved.

The application relates to a basketball video highlight automatic generation method and system based on multi-modal feature fusion, and belongs to the technical field of computer vision and multimedia intelligent analysis. The method comprises the following steps: S1, extracting and aligning a visual feature sequence and an audio feature sequence; S2, using bidirectional LSTM to perform time sequence coding on the audio-visual feature, constructing a cross-modal attention mechanism taking audio as a query and vision as a key value, and obtaining multi-modal fusion features; S3, inputting the fusion features into a 1D CNN to output a frame-by-frame highlight event probability sequence; S4, performing peak value searching based on an adaptive threshold of the probability sequence to obtain a coarse-grained timestamp; S5, taking the coarse-grained timestamp as a center to intercept local features, inputting the local features into bidirectional LSTM to predict starting and ending offsets, and obtaining accurate start and end time boundaries; and S6, clipping and splicing to generate a highlight video according to the accurate boundaries. The application realizes audio-visual semantic depth alignment through an audio-guided visual attention mechanism, and improves boundary positioning accuracy through a coarse-precision two-stage positioning architecture.

This invention discloses a quantitative test strip for HBV PreS1 antibody based on the AIE molecule, its preparation method, and its applications, relating to the fields of molecular biology, immunology, and biodetection technology. The test strip includes a sample pad, a labeling pad, a nitrocellulose membrane (NC membrane), an absorbent pad, and a base plate. The NC membrane detection line is coated with HBV PreS1 antigen to capture PreS1 antibodies in the sample. The labeling pad contains an immobilized Anti-Human IgG antibody conjugated to the AIE molecule, which binds to the PreS1 antibodies in the sample to form an immune complex. The test strip of this invention enables rapid detection of PreS1 antibodies and achieves enhanced fluorescence in the detection results. Combined with a fluorescence reader or fluorescence card reader, the detection results can be digitally and quantitatively analyzed. It is simple to operate, rapid in detection, and significantly improves detection sensitivity and enables quantitative analysis.

The invention discloses a refrigerant adjusting method, device and system. The method comprises the steps that the current refrigerant temperature difference between the first refrigerant temperature of an inlet of the air-cooled condenser and the second refrigerant temperature of an outlet of the air-cooled condenser is obtained; the current deviation between the current refrigerant temperature difference and the temperature difference reference value is determined; under the condition that the current deviation is not within the first range, a feedback control model based on a real-time error is called, the opening degree of a first adjusting valve is adjusted according to the current deviation, so that the deviation between the adjusted refrigerant temperature difference between the inlet and the outlet of the air-cooled condenser and the temperature difference reference value is within the first range, and the first adjusting valve communicates with the air-cooled condenser; according to the scheme, the fluctuation of the key heat exchange parameter (temperature difference) is actively restrained within a set reasonable range, system performance degradation or operation risks caused by large drifting of parameters are effectively avoided, stable and reliable operation of the whole system is guaranteed, and the technical problem that the operation stability of an evaporation cold and heat pump unit system is low can be solved.

This invention belongs to the interdisciplinary field of artificial intelligence and geological resource assessment, specifically relating to a method and system for predicting the energy storage potential of salt caverns based on multi-source geological information. It aims to address the problems of low prediction accuracy and difficulty in balancing breadth and precision in existing technologies due to single-source data, static models, and lack of adaptive capabilities. The method includes: acquiring multi-source data such as seismic, well logging, core, and geostress data; constructing a geological feature fusion vector containing seven core parameters; establishing a high-dimensional nonlinear mapping model driven by a deep neural network; dynamically adjusting the prediction range based on data coverage density and confidence level; and achieving continuous model iteration through online incremental learning. The system integrates data quality assessment, anomaly handling, and distributed computing modules. By adopting the above technical solutions, this application can achieve a significant improvement in prediction accuracy and adaptive intelligent adjustment of the prediction range.

The invention relates to the technical field of semiconductor detection, discloses a semiconductor image processing method, and particularly relates to an image template matching result evaluation method and system and a readable storage medium. According to the embodiment of the invention, the edge point corresponding to each edge point in the to-be-matched image, namely the edge image, in the template image is constructed, the inner point set of the template image is constructed based on the edge points to serve as the target feature for evaluating the to-be-matched image, and then the point which changes most violently in the inner point set is determined as the optimal edge point. The optimal edge point is used as an optimal point for evaluating the positions of the template image and the image to be matched; based on the edge point position error of the optimal edge point and the matched edge point, the deviation between single point positions is determined, finally, the average deviation of the deviation of the multiple point positions serves as the final deviation between the two images, and evaluation of the accuracy of the matching result is achieved through the deviation.

The invention discloses a quantitative grading method for carbon emission in a production stage of a power transformer. The method comprises the following specific steps: after data are collected, firstly calculating a production link carbon footprint and a product use link carbon footprint of a to-be-evaluated transformer product, and calculating a production carbon efficiency ratio of the to-be-evaluated transformer product on the basis of the production link carbon footprint and the product use link carbon footprint; secondly, through data standardization integration processing, calculating the information entropy and the information utility value of each evaluation index, thereby determining the index weight; and finally, calculating the square value of the weighted mahalanobis distance of the to-be-evaluated product, and substituting the square value into a centesimal system grading algorithm to obtain a product production carbon footprint evaluation score and a corresponding grade. According to the method, the transformer quality parameters, the production stage carbon footprint and the use stage carbon footprint are integrated and unified, a traditional carbon efficiency ratio concept is optimized, multi-dimensional and refined grading of the transformer production stage carbon footprint is achieved, and the defects of an existing method in the aspects of comprehensiveness and accuracy are overcome.

The invention relates to the technical field of bioinformatics, in particular to a homologous protein searching method based on scale invariant feature transformation and pre-filtering, and the method comprises the steps: obtaining # imgabs0 #-carbon atom coordinates in a to-be-compared protein structure, calculating a corresponding distance matrix, extracting a feature description vector matrix of the distance matrix by using an SIFT (scale invariant feature transform) algorithm, and obtaining a feature description vector matrix of the to-be-compared protein structure; the matrix is mapped to a high-dimensional spherical surface, candidate protein structures meeting pre-filtering conditions are rapidly screened out from a large-scale protein database through a spherical surface partition pre-filtering algorithm, and the to-be-compared protein structure and the feature description vector matrix of the candidate protein structures are accurately compared through GPU acceleration. And generating a protein structure comparison result, and further determining the homologous protein corresponding to the to-be-compared protein. Therefore, the comparison speed is increased while the comparison precision is kept, the defect that efficiency and precision are difficult to consider in the prior art is overcome, and the method is suitable for rapid search and efficient comparison of a large-scale protein database.

The utility model discloses an alignment mechanism for pole piece detection, include: base plate, and its both ends end face respectively fixedly be equipped with mounting seat, the first slider and the second slider of sliding setting in the mounting seat, the adjusting end of mounting seat is fixedly equipped with first drive assembly, and the output shaft of first drive assembly is connected and drives corresponding slider sliding, the first pivot assembly of fixedly equipped on the first slider and two second pivot assemblies of fixedly equipped on the second slider, be equipped with the alignment plate of center round hole and racecourse type through -hole, first pivot assembly is worn in center round hole, and two second pivot assemblies are respectively worn in the racecourse type through -hole that sets up parallel to the alignment plate length direction, the pole piece detection camera of fixedly equipped in the alignment plate middle part edge position, through the automatic control of first drive assembly and second drive assembly, has realized the automation of alignment process, has improved alignment efficiency and precision greatly.

The invention discloses a stroke emergency identification method and system combining TOPSIS and artificial intelligence, belongs to the technical field of stroke early warning, and solves the problem that the existing method cannot accurately capture facial feature points in an emergency state, resulting in insufficient response speed and accuracy during judgment through a TOPSIS method. Identifying facial parameter information in the preprocessing set based on a multi-view feature positioning model, generating a facial expression identification result, identifying and analyzing the facial expression identification result and the preprocessing set by a stroke analysis model, and calculating a stroke risk level of the patient; according to the method, the stroke analysis model based on TOPSIS and artificial intelligence is pre-constructed, and the stroke analysis model cooperates with the multi-view feature positioning model and the flexible trigger mechanism, so that the stroke analysis model quickly responds to the recognition results of the multi-view feature positioning model and the flexible trigger mechanism; the multi-view feature positioning model can analyze multi-angle face parameter information.

This invention belongs to the field of equipment inspection technology and discloses an intelligent inspection and positioning method and system based on Bluetooth and NFC. The method includes: receiving Bluetooth signals from available Bluetooth devices through an intelligent inspection and positioning terminal, and sorting valid inspection points based on the access time of each Bluetooth signal to generate a time series representing the inspector's movement route, thereby automatically tracking the inspector's movement route; when at least two assigned inspection areas are identified, comparing the number of shared inspection points between different assigned inspection areas with an intersection threshold value to determine key inspection areas or ordinary inspection areas, and then generating an inspection route. This invention reconstructs the inspector's movement route based on the time series of Bluetooth signal access, improving the authenticity and objectivity of the inspector's movement route, and by transforming inspection planning into a dynamic response, improving the overall efficiency and targeting of inspection work.

The present invention relates to a composite non-Gaussian filtering method for inertial / polarization combined attitude determination. For an inertial / polarization combined attitude determination system that is simultaneously affected by inertial device drift, unknown incident light intensity coefficient, inertial navigation and polarization measurement noise, firstly, a tightly coupled model of an inertial / polarization combined attitude determination system containing an unknown incident light intensity coefficient is established; secondly, for a situation where the incident light intensity coefficient is known, a composite non-Gaussian filter containing inertial device drift compensation is designed to achieve real-time estimation of attitude posterior distribution; finally, an expectation-maximization iterative algorithm with an embedded composite non-Gaussian filter is designed to achieve online identification of the incident light intensity coefficient. The present invention can improve the attitude solution accuracy of an inertial / polarization combined attitude determination system under multi-source error conditions, improve the adaptability of an inertial / polarization combined attitude determination system to unknown environments and meteorological conditions, and can be applied to autonomous navigation tasks of various unmanned systems such as drones / vehicles / ships in complex environments.

The invention discloses a compound control method and system for a mechanical arm with a gap joint, and belongs to the technical field of engineering equipment control. Based on a six-degree-of-freedom mechanical arm nonlinear dynamic model containing a gap joint, control boundaries of a collision force feedforward module and a PD feedback module are determined by quantifying a coupling relation between a joint gap and collision force; then a composite control structure of'collision force feedforward compensation-PD feedback tracking 'is built based on the kinetic model, a feedforward module counteracts disturbance of nonlinear collision force on motion of the mechanical arm in advance by collecting joint collision force signals in real time and calculating reverse compensation torque, and a PD feedback module counteracts disturbance of nonlinear collision force on motion of the mechanical arm in advance by monitoring joint positions and posture deviation in real time; outputting a tracking torque to accurately correct a track error; the two layers of modules are nested and cooperatively work, the advantage of active disturbance suppression of feedforward control is exerted, the steady-state precision of trajectory tracking is guaranteed by means of PD feedback control, and the operation precision and reliability of the gap-containing joint mechanical arm are effectively improved.

The invention provides an L1 / L2 norm ratio regular minimization image restoration method based on an analytical model, and belongs to the field of signal and image processing inverse problems. In order to solve the problems that the reconstruction precision is limited and the algorithm robustness is insufficient under the conditions of undersampling, pixel loss, blurring and the like in the existing image restoration technology, an image restoration optimization model is established and solved by utilizing the inherent scale invariance and parameter freedom of an L1 / L2 norm ratio and combining the stability of signal representation under an analytical model. The geometric structure and texture details of the image can be stably recovered from under-sampled or damaged observation data, and the image recovery problem in various typical degradation scenes is effectively solved.

The invention belongs to the technical field of power plant indirect cooling circulating water treatment, and relates to an automatic control device and method for the quality of indirect cooling circulating water. Comprising an intelligent control cabinet, an alkali solution tank, an acid solution tank, a mixed ion exchanger, a condenser and an indirect cooling tower aluminum heat exchanger, a conductivity meter, a pH meter and a PLC (Programmable Logic Controller) are arranged in the intelligent control cabinet; the alkali solution tank is connected with a circulating water inlet pipeline; the acid solution tank is connected with a circulating water inlet pipeline; a pH electrode is arranged on the circulating water inlet pipeline; a conductivity electrode is arranged on the circulating water outlet pipeline; the condenser inlet is connected with the circulating water outlet pipeline; the condenser outlet is connected with the circulating water inlet pipeline; the circulating water outlet pipeline is connected with an inlet of the mixed ion exchanger; an outlet of the mixed ion exchanger is connected with an inlet of the condenser. According to the invention, accurate control of the water quality pH value and conductivity of the intercooling circulating water can be realized, so that system corrosion is effectively inhibited, the service life of equipment is prolonged, and safe and economical operation of a unit is guaranteed.

The present invention provides a surgical navigation method, system, medium and electronic device based on DSA images, and the method includes the following steps: Step 1, obtaining the patient's CT angiography data, extracting the vascular structure therefrom, and constructing a 3D vascular model. The present invention significantly reduces the situation of interactive overlap of vascular positions by constructing the preoperative CT angiography data into a 3D vascular model, and aligning it with the DSA image in real time during the operation, thereby avoiding the need for multiple projections, thereby reducing the patient's irradiation dosage, examination time, contrast agent dosage and economic burden, and also reducing equipment loss; by processing the DSA image and predicting the camera parameters through the CNN neural network model, the accuracy and effectiveness problems existing in the registration of two-dimensional images and three-dimensional images are effectively overcome. By simulating the generation and training of DSA images, the CNN model can accurately predict the camera parameters corresponding to the intraoperative DSA image, thereby achieving high-precision image registration and improving the safety and success rate of the operation.

The application discloses a kind of power grid architecture data processing method and system, belong to data processing field, this method includes: obtaining current project information, and current query set is constructed based on current project information;Obtain historical knowledge graph, extract structure information and construct historical query set;According to semantic query set obtained by large language model;Current query set, historical query set and semantic query set are confidence score, and initial decision group is obtained and fitness function is constructed;Obtain initial evaluation particle swarm, based on fitness function and compression factor iterative calculation, when reaching maximum iteration number or the average fitness of initial evaluation particle swarm meets preset fitness requirement, final evaluation particle swarm is obtained, to obtain final decision group, to complete power grid architecture data processing process based on final decision group.The power grid architecture data processing method disclosed in the application can optimize the data processing architecture of power grid, and improve data processing efficiency.

The image motion deblurring method based on a hybrid expert network belongs to the technical field of image processing and computer vision, and particularly relates to an image motion deblurring method based on a hybrid expert network; solves the technical problems of coarse-grained routing mechanism, sparse activation detail loss, imbalance between lightweight and precision, single feature fusion strategy, and difficulty in balancing precision and efficiency in the prior art; the method comprises the following steps: inputting a single-frame blurred image to be repaired into a hybrid expert deblurring model that has been trained, and reconstructing and outputting a clear image after deblurring. The image motion deblurring method based on a hybrid expert network is suitable for the fields of lightweight image visual perception, image restoration and deblurring processing.

The invention discloses a construction process of a main structure of a small-curvature teardrop-shaped cable tower, which is characterized by comprising the following steps: step 1: tower base construction; step 2: connection plate construction; step 3: tower column construction; step 4: lower cross beam construction; wherein step 2 includes steel anchor beam construction, steel anchor beam and corbel integral hoisting, and the installation of the embedded cable guide tube is carried out after the steel anchor beam system is installed and positioned, at which time the connecting bolts between the steel anchor beam and the steel corbel do not need to be tightened in place, and a gap is left for adjustment. If the accuracy requirement is not met, the position of the lower port is fine-tuned to the deviation meeting the accuracy requirement under the premise of meeting the smoothness requirement, and after the steel anchor beam is positioned, a longitudinal limit device of the steel anchor beam is installed, the limit device is perpendicular to the center line of the bridge tower, and the limit device is connected and fixed by a pre-embedded steel plate pre-embedded in the tower wall. The invention ensures the construction efficiency and assembly accuracy of the steel anchor beam and steel corbel unit assembly construction, and enables the main tower to have good technical guarantee.

The invention discloses a pose determination method and system of an underwater unmanned aerial vehicle, the method is applied to the underwater unmanned aerial vehicle, the underwater unmanned aerial vehicle is in radio communication connection with a receiver, and the underwater unmanned aerial vehicle is provided with a nine-axis gyroscope and a sensor; the pose determination method of the underwater unmanned aerial vehicle comprises the following steps: acquiring initial pose information of the nine-axis gyroscope and environment information of the sensor; obtaining intermediate attitude information of the underwater unmanned aerial vehicle according to the initial attitude information and the environment information; when the underwater unmanned aerial vehicle is located in a preset distance range of the receiver, receiving calibration information of the receiver; and performing pose calibration according to the calibration information and the intermediate pose information to obtain target pose information of the underwater unmanned aerial vehicle. According to the invention, the positioning accuracy of the underwater unmanned aerial vehicle is improved.

The embodiment of the invention provides a robot eyeball tracking control method and device, computer equipment, a computer readable storage medium and a computer program product, and belongs to the technical field of robots. The robot eyeball tracking control method comprises the following steps: determining a three-dimensional pose of a target object in a current camera coordinate system by using a binocular camera, and determining an expected camera extrinsic parameter of the target object at a target position based on the three-dimensional pose; obtaining current steering engine control data of eyeballs of the robot, and determining current camera external parameters from a pre-constructed mapping relation table based on the current steering engine control data; and determining the difference between the expected camera external parameter and the current camera external parameter, determining a steering engine control instruction of the robot eyeball at the next moment based on the difference and the mapping relation table, and driving the robot eyeball to move based on the steering engine control instruction. According to the technical scheme, the control problem caused by mechanical uncertainty of the composite steering engine can be effectively solved, and high-precision tracking control over the object by the eyeballs of the robot is achieved.

The invention discloses a change detection method and device based on an unmanned aerial vehicle scene, and the method comprises the steps: obtaining unmanned aerial vehicle flight remote sensing images in different periods, and carrying out the splicing of the remote sensing images in different periods, and obtaining a to-be-detected region image; inputting the to-be-detected area images in different periods into the trained deep learning model so as to detect change areas in different periods; wherein the trained deep learning model comprises feature extraction networks and region candidate networks corresponding to the feature extraction networks; the feature extraction network is composed of a plurality of feature pyramid networks, and different scale features are extracted from different feature pyramid networks; each region candidate network processes the extracted different scale features; and the candidate regions output by the different region candidate networks are fused and then used for change detection. The efficiency and precision of change detection and recognition are improved, and the defect that manual detection is poor in efficiency and precision is overcome.

The invention relates to the technical field of steel plate cutting, in particular to an automatic steel plate cutting device for high-resistance arched protective door production. The device comprises a conveying and feeding device, a cutting and discharging device and a discharging and stacking device, a mounting and clamping device is mounted below the cutting and discharging device, a detecting and marking device is mounted above the mounting and clamping device, and a waste recycling device is mounted on one side of the cutting and discharging device and below the cutting and discharging device. The conveying and feeding device is used for automatically conveying and feeding a steel plate and positioning the steel plate to a machining position for cutting, manual material carrying is replaced, machining efficiency is improved, meanwhile, machining continuity of equipment is achieved, the mounting and clamping device is used for clamping the steel plate raw material to the machining position, and machining deviation caused by displacement of the steel plate raw material during cutting machining is avoided; and meanwhile, the machining and positioning precision of the steel plate raw materials is improved, the detection lineation device is used for lineation on the steel plate raw materials according to cutting design to assist in determining whether the design is reasonable or not, and material waste is reduced.

The application discloses a preparation method of a silicon carbide membrane based on wettability difference induced hollow interface construction. The method introduces a carbon powder pore former with wettability difference from silicon carbide particles into a green support body, realizes slurry preferential spreading in the hydrophilic region and local retention in the hydrophobic region during the dip-coating process, and then induces the formation of an ordered hollow channel structure at the membrane-support interface. During the co-sintering process, the structure can effectively inhibit the penetration of the membrane slurry into the large pores of the support body, enhance the integrity of the membrane layer, and significantly reduce the interface mass transfer resistance. The obtained membrane layer has adjustable pore size and highly continuous surface structure, significantly improving the gas flux and dust filtration performance compared with traditional membranes, while shortening the preparation period and reducing the sintering energy consumption. The method is suitable for the construction of various asymmetric membrane structures, has good scalability and process compatibility, and provides a new way for the large-scale preparation of low-cost and high-performance silicon carbide membranes.