432 results about "High spatial resolution" patented technology

The invention discloses a multi-frame photoacoustic image reconstruction method based on optical flow alignment and depth feature fusion. The method comprises the following steps: S1, obtaining photoacoustic signal data; s2, reconstructing a photoacoustic cross-sectional image; s3, performing optical flow calculation and image alignment; and S4, training the deep feature fusion network. According to the method, through optical flow motion correction and a potential space learning mechanism, space-time information and complementary features in the aligned multiple frames of images are dynamically integrated, complementary information in the multiple frames of images is adaptively fused, noise is suppressed, and finally reconstruction of high signal-to-noise ratio and high spatial resolution images of biological tissues is achieved. Experimental results show that the method can significantly improve image quality, recover image distortion and detail loss caused by motion and noise, and provide a new effective scheme for promoting robust clinical application of a photoacoustic imaging technology.

The invention discloses a living blood vessel and lymph multi-parameter quantitative photoacoustic microscopic imaging system which comprises a high repetition frequency laser source, a photoacoustic scanning probe and a molecular imaging device. Through the cooperation of the multi-wavelength fast switching laser and the high-speed scanning probe, synchronous, dynamic and quantitative imaging of vascular function parameters and lymph concentration in a living tissue microenvironment is realized. The system has a video-level imaging rate and can capture a rapid biological process; through coaxial design of dispersion correction and a photoacoustic focus, high spatial resolution and high signal-to-noise ratio of a multispectral image are guaranteed; and the compact probe design realizes large-range scanning. The technology provides a powerful in-vivo visualization tool for research on life science problems such as tumor evolution and drug metabolism.

The invention discloses a deep learning-based satellite remote sensing collapsible loess foundation evaluation method, which comprises the following steps of: acquiring an optical remote sensing image, a radar remote sensing image and an infrared remote sensing image of a target area, and preprocessing; collapsibility feature weighted data are screened, and feature weights are distributed; feature extraction is carried out through a local space exhibition structure and a multi-layer Transform structure of the collapsibility foundation evaluation network; collapsibility area self-supervised collaborative learning is carried out, and self-supervised training is carried out based on spatial correlation, pseudo labels and spatial consistency regular terms; and carrying out risk grade division on the target area, and outputting a collapsibility risk result of each spatial position. According to the method, multi-mode remote sensing and deep learning are fused, high-precision intelligent partitioning of the collapsible loess foundation is achieved, and the method has the advantages of being self-adaptive, low in manpower and high in spatial resolution.

The invention provides a rock-soil moisture content and permeability testing system and method based on electromagnetic waves and infrared rays, and particularly relates to the technical field of geotechnical engineering testing and multi-source signal detection. According to the test system, construction of a rock-soil permeability experiment is realized through a rock-soil sample permeability test platform, the electromagnetic wave detection module realizes perception of a water-containing state in rock-soil, and the infrared thermal imaging module realizes perception of a wet boundary and seepage expansion characteristics of a rock-soil surface. The data acquisition and control module realizes integral control of a penetration experiment and acquisition of dielectric characteristics and infrared images, the signal fusion and inversion module realizes fusion of the dielectric characteristics and the infrared images and joint inversion of dynamic moisture content and penetration performance, and the result processing and visualization module realizes visual display of an inversion result; the method has the remarkable advantages of non-destructiveness, real-time performance, high spatial resolution, high adaptability, intelligent processing capacity and the like, and comprehensive characterization of the permeability behavior and the moisture content evolution process of the rock and soil sample is achieved.

The invention relates to the technical field of biomedical imaging, and discloses a photoacoustic-ultrasonic volume imaging method and system based on an annular ultrasonic array, and the method comprises the steps: reconstructing a two-dimensional photoacoustic image and a two-dimensional ultrasonic image; after photoacoustic imaging and ultrasonic synthetic aperture imaging of one imaging plane are completed, the annular ultrasonic array is moved in the direction perpendicular to the imaging plane, photoacoustic images and ultrasonic images of all the imaging planes are repeatedly executed on the next imaging plane, rebuilt and stacked, and a three-dimensional photoacoustic volume image and a three-dimensional ultrasonic volume image are formed; performing spatial pulse response deconvolution processing on the three-dimensional photoacoustic volume image; and fusing the processed three-dimensional photoacoustic volume image and the three-dimensional ultrasonic volume image to generate a three-dimensional bimodal volume image. According to the invention, high-time-resolution opto-acoustic-ultrasonic bimodal three-dimensional imaging is realized by using an annular ultrasonic array and motion scanning, and the high spatial resolution of the image is further ensured through a series of technologies.

The invention discloses an ultrahigh-spatial-resolution time-broadening framing camera and a framing imaging method, and solves the problem that the spatial resolution of a system is reduced due to spatial dispersion caused by the space charge effect of electrons in the transition process of an existing time-broadening framing camera. According to the invention, the characteristic that the spinning period of the photoelectrons moving in a drift magnetic field is only related to the magnetic field intensity and is irrelevant to the speed distribution of the photoelectrons overflowing from the microstrip line structure is utilized, that is, the photoelectrons overflowing from the microstrip line structure drift for a fixed time; the phase of the photoelectron circular motion is consistent with the initial phase of the photoelectron when the photoelectron overflows from the microstrip line structure, that is, by designing the magnetic field intensity and the microstrip line structure voltage, it is ensured that the photoelectron advancing in a spinning mode reaches the traveling wave gating framing tube after the integer period circular motion in the magnetic drift tube; that is, the circumferential phase of the electrons reaching the traveling wave gating framing tube is the same as the phase when the photoelectrons overflow, so that the spatial resolution of the camera reaches the optimal system.

The invention discloses an image matching method and device, equipment, a storage medium and a product, and relates to the technical field of image matching, and the image matching method comprises the steps: obtaining different-source to-be-matched images at different visual angles; sequentially performing feature extraction on the images to be matched through a preset feature point matching model to obtain key points and descriptors in each image to be matched, and performing matching on the key points based on the descriptors to obtain initial matching points obtained through initial matching, the number of channels in a convolutional layer of the preset feature point matching model is negatively correlated with the spatial resolution of the to-be-matched image, the change degree of the number of channels in a first stage is smaller than the change degree of the number of channels in a second stage, and the first stage and the second stage are determined based on the spatial resolution; and performing error filtering on the initial matching point to obtain a filtered target matching point. According to the invention, when an image with high spatial resolution is processed at an early stage, the calculation cost can be significantly reduced by reducing the number of channels.

The invention relates to a method for analyzing and / or monitoring process parameters and / or component data during an additive manufacturing process, comprising the following steps: generating a target parameter set of a component to be additively manufactured, the target parameter set comprising high spatial resolution data relating to target process parameters and / or target component data; performing a plurality of additive manufacturing steps to produce a sub-region of the component; detecting measurement data of process parameters of manufacturing steps of the sub-region and / or component data of the sub-region; combining the detected measurement data in order to form an actual data set; analyzing the detected measurement data; and storing the actual data set and the target data set in the data set.

The present application relates to a capillary array, its manufacturing method, and use. The capillary array includes a plurality of parallel-axially arranged capillaries made of a first glass, each of which has an inner wall provided with a low-refractive-index layer whose refractive index is lower than that of a liquid scintillator, and a light-absorbing layer made of a second glass between any two adjacent capillaries. The capillary array includes a capillary region in which T1 - T2 is 30 to 50°C, where T1 is the softening point of the first glass and T2 is the softening point of the second glass, and the thermal expansion coefficient of the first glass is α1. The capillary region is made of a third glass, which is disposed outside the capillary region and in contact with the outer surface of the capillary region, and has a softening point of T3, where T2 - T3 is 50 to 100°C, and the thermal expansion coefficient of the third glass is α3, where α1 - α3 is 2×10. -7 ~10×10 -7 / °C. The technical problem to be solved by the present application is to manufacture a capillary array such that a liquid scintillator optical fiber panel manufactured using the capillary array has high spatial resolution, high hole diameter uniformity, high numerical aperture, and high coupling efficiency, and the manufacturing process is simple.

The invention provides a wide-field magnetic field imaging method based on sparse sampling and Bayesian estimation, and belongs to the field of magnetic field imaging. The method comprises the following steps: constructing an NV color center system, measuring and recording information of a magnetic field to be measured; selecting a small number of discrete sampling points to measure magnetic field intensity data in an imaging field of view of a measured area; the method comprises the following steps of: constructing an error correlation function among pixel points in a measured area, establishing a Bayesian estimation model, and predicting the magnetic field intensity of unmeasured pixel points in a full field of view by taking magnetic field intensity data of a small number of discrete sampling points as observed quantity to obtain a preliminarily reconstructed magnetic field distribution image; selecting a plurality of reference points in the measured area, acquiring nominal magnetic field values and actually measured magnetic field values of the reference points, and calibrating the preliminarily reconstructed magnetic field distribution image by adopting a mean value proportion correction mode; on the premise that the number of sampling points is greatly reduced, magnetic field distribution reconstruction with high spatial resolution and high structural similarity is achieved, and therefore imaging efficiency and reliability are improved.

The application discloses a high-rotation flying body flight parameter multi-field synchronous measurement and fusion method and system, the method utilizes a meteorological balloon to detect atmospheric parameters such as air pressure, temperature, humidity and wind direction and wind speed under current atmospheric conditions, arranges an unmanned aerial vehicle array networking as a relay node of a communication link, forms a data transmission link of a measuring device and a ground computing center, and performs positioning and monitoring on a flying body landing point. Under a unified space-time reference, target field distributed measurement and in-situ measurement data are subjected to "real-time + after-the-fact" information fusion, and the estimation precision of the whole trajectory flight parameters of the high-rotation flying body is improved. The method overcomes the limitations of conventional target field testing devices and testing means, and has the advantages of high time resolution, high spatial resolution, high signal signal-to-noise ratio, high information availability and high system integration.

A system and method for distributed temperature and strain sensing using Chirp-Pulse Coherent Optical Time-Domain Reflectometry (CP-COTDR) utilizes optical flow processing. The method involves constructing a two-dimensional (2-D) waterfall data array from collected CP-COTDR frames. Optical flow processing is applied directly to the 2-D data to estimate the local shift of features caused by external perturbations. The optical flow is preferably calculated using a weighted least squares method with an adaptive analysis window based on the local flatness of signal derivatives. This approach provides versatile and high spatial resolution, reduces accumulative errors, and enables efficient data processing compared to conventional cross-correlation techniques.

The invention discloses an underground structure scanning method for a controlled active source. According to the method, a known signal generated by an active source is equivalent to a record of a virtual station, the virtual station and an actual six-component seismograph station form a station pair, and the phase velocity of a wave under the distance is estimated through a phase difference / travel time difference between the virtual station and the actual six-component seismograph station and a geometric distance relationship between the source and the station; the obtained phase velocity is actually equivalent to a frequency dispersion curve at the midpoint of the connecting line of the source and the station, so that the phase velocity-depth structure from the source to the midpoint of the station can be obtained by performing inversion by using the obtained frequency dispersion curve; as the active source moves in the measurement area, a group of signals can be generated at different positions respectively, and a series of virtual midpoints are formed for the single-station six-component seismograph, so that the density of measurement points is remarkably increased in space. On the basis, through combination with an inversion result of a single station, three-dimensional underground velocity structure modeling with high credibility and high spatial resolution can be realized.

The invention relates to the technical field of hyperspectral image processing, and particularly discloses a hyperspectral image fusion method and system based on variance guidance and heavy tail estimation, and the method comprises the steps: obtaining a low-spatial-resolution hyperspectral image and a panchromatic image; performing up-sampling on the low-spatial-resolution hyperspectral image to obtain an up-sampled image; obtaining an absolute difference value weight according to the channel-by-channel variance of the low-spatial-resolution hyperspectral image and the up-sampling image; performing channel-by-channel spatial fusion by means of absolute difference weight, and injecting high-frequency information of the panchromatic image into the up-sampling image to obtain a preliminary fusion image; performing spectral correlation correction learning on the preliminary fusion image through an attention mechanism to obtain spectral mixed output; through a feedforward network, obtaining an up-sampling image subjected to variance guide processing; and obtaining a high-spatial-resolution hyperspectral image through a residual block and convolution. According to the invention, accurate selection and fusion of the spatial-spectral features are realized.

The invention discloses a semiconductor resistivity nondestructive testing method and system based on modulation light reflection, relates to the technical field of semiconductor resistivity detection, and aims to accurately measure a modulation component delta R / R of light reflectivity through a light reflection modulation signal so as to calculate the semiconductor resistivity and further realize quantitative measurement of the semiconductor resistivity. The sensor has ultrahigh sensitivity, can detect tiny carrier concentration change, and is very sensitive to electrical properties of surface and near-surface areas; meanwhile, the spatial resolution is high, and the micron-scale light spot at the sample is suitable for micro-area measurement; a complete optical method does not cause any damage to the sample; various types of samples can be measured; the measuring speed is fast, and the system can be easily integrated in a production line for real-time monitoring.

This application discloses a depth optimization method, apparatus, and storage medium for industrial images, relating to the field of image processing technology. This application preprocesses the original RGB image and a depth prior map containing real physical scale, and labels target data points. A frozen target monocular depth estimation model outputs a relative depth prediction map with continuous geometric structure. The blank areas of the depth prior map are pre-filled with the target data point weights to obtain a dense depth map. The dense depth map, the relative depth prediction map, and the original RGB image are then jointly input into a conditional depth optimization network to correct depth edges, geometric abrupt changes, and noisy regions. Based on real scale information, calibration is performed. This approach achieves density enhancement, high spatial resolution, and refined geometric structure of the depth map while preserving the real physical scale, effectively improving the integrity, accuracy, and edge robustness of industrial depth images.

The application belongs to the technical field of photon imaging detection, and particularly relates to a photon counting imaging detection system based on a mixed anode. The system comprises a vacuum sealed tube detector composed of a window coated with a photocathode, a microchannel plate stack and a mixed anode, and a signal processing circuit. The photocathode is used for converting photons incident through the window into photoelectrons. The microchannel plate stack is used for converting the photoelectrons into electron clouds. The mixed anode comprises a strip anode and a delay line anode arranged orthogonally, and the mixed anode transmits the collected charge short pulses of each channel to the signal processing circuit. The signal processing circuit calculates the two-dimensional coordinates of the photons based on the collected charge short pulses of each channel, and then transmits the two-dimensional coordinates of the photons to a terminal for imaging display. The application provides a photon counting imaging detection system based on a cross strip-delay line mixed anode, and solves the problem that the existing position sensitive anode detector cannot simultaneously have high spatial resolution and high temporal resolution.

The invention provides a sea ice thickness extraction method and device based on unmanned aerial vehicle laser point cloud rapid classification. The method comprises the steps of obtaining laser point cloud data collected by an unmanned aerial vehicle platform; determining a local sea surface elevation reference based on the laser point cloud data; based on the local sea surface elevation reference, ship point cloud is identified through relative height screening and spatial clustering, and geometric feature verification is carried out on a clustering result; after sea water points and ship point clouds are excluded from the laser point cloud data, spatial clustering is carried out on the remaining point clouds to identify sea freezing point clouds; and based on the local sea surface elevation datum and the sea ice point cloud, extracting the sea ice thickness. According to the method, the advantages of high spatial resolution and high cost performance of the unmanned aerial vehicle are utilized, a refined point cloud processing technology is matched, classification is rapid and accurate, thickness extraction precision is high, the method adapts to a polar region complex observation environment, reliable data support can be provided for polar region navigation channel development, navigation safety investigation and climate change research in real time, and the method has remarkable practical value.

The invention discloses a single-particle electrode material rate capability characterization method based on optical imaging. Comprising the following steps: constructing an electrochemical test configuration allowing optical observation, executing constant-current charging and discharging under a controlled magnification, synchronously acquiring optical data, defining characterization parameters related to the magnification based on the optical data, and evaluating the magnification performance of the single-particle electrode material. According to the method, the real-time response of the particles in the charging and discharging process is obtained through optical imaging, quantitative analysis of the magnification response under the single particle scale is achieved, the problem of particle behavior averaging in a macroscopic test is solved, and the accuracy and the resolution capacity of material performance evaluation are improved. The method is easy and convenient to operate, high in testing efficiency and suitable for high-throughput and high-spatial-resolution characterization of the rate performance of the electrode material.

The application discloses a dielectric high-space-resolution trap imaging method and system based on a scanning probe microscope, and the method comprises the following steps: recording a sample surface topography image sequence and a surface potential image sequence after removing a voltage; correcting image offset according to the surface topography image sequence, and extracting surface potential decay data of each pixel point from the corrected surface potential image sequence; determining trap distribution information of each pixel point by fitting and calculation according to the surface potential decay data of each pixel point; and forming deep and shallow trap energy level peak value images and / or deep and shallow trap density peak value images corresponding to the film surface topography according to the trap distribution information of all pixel points and the original positions of the pixel points. The method directly images the trap characteristics of a sample at a nanometer scale, and has the advantages of high spatial resolution and intuitive comparison.

The application discloses a kind of based on satellite fusion's near-shore sea area nutrient salt concentration remote sensing inversion method, comprising the following steps: S1, the original L1C data of the optical image of high spatial resolution satellite and low spatial resolution satellite are respectively carried out Rayleigh correction, obtain after Rayleigh correction remote sensing reflectance;S2, cloud and land pixel in after Rayleigh correction remote sensing reflectance data are carried out mask processing;S3, based on low space respectively satellite data constructs nutrient salt training dataset;S4, constructs cross-satellite fusion training dataset;S5, establish AutoGluon-DIN machine learning model and AutoGluon-DIP machine learning model based on low resolution satellite, and model training is carried out;S6, establish AutoGluon-transfer machine learning model of fusion high resolution and low resolution satellite, and model training is carried out;S7, sequentially apply AutoGluon-transfer machine learning, AutoGluon-DIN machine learning model, AutoGluon-DIP machine learning model after training to high resolution satellite, obtain high spatial resolution's near-shore sea area nutrient salt concentration remote sensing inversion product.

The invention discloses a movable muscle magnetic signal detection device, which comprises a magnetic shielding mechanism, an annular sensor array capable of scanning and moving, an arm positioning mechanism and a signal acquisition and processing system, and is characterized in that the magnetic shielding mechanism is used for shielding an environment magnetic field to form a near-zero magnetic measurement environment; the annular sensor array is used for surrounding an arm to collect multi-channel muscle magnetic signals generated by muscle movement, and the arm positioning mechanism is used for fixing the arm and determining a measurement position range. And the signal acquisition and processing system is used for synchronously acquiring a stimulation signal triggered by external stimulation, a multi-channel muscle magnetic signal from the annular sensor array and position information of the annular sensor array, and processing, tracing and positioning the multi-channel muscle magnetic signal. According to the device, miniaturization and mobility of muscle magnetic signal detection equipment are achieved, three-dimensional space distribution information of a muscle magnetic field can be obtained, the spatial resolution is remarkably improved, integrated analysis from signal detection to source positioning is achieved, and a reliable tool is provided for quantitative evaluation of neuromuscular functions.

This invention provides a wind erosion monitoring system and method based on distributed optical fiber, belonging to the field of optical-based wind and sand monitoring technology. It includes: constructing a wind erosion monitoring system comprising a linearly tunable laser, an optical isolator, a first coupler, an upper branch, a lower branch, a sand particle capture sensor, a photoelectric detection and acquisition module, and a host computer; utilizing the Rayleigh scattering signal of the linearly swept laser in the sensing optical fiber and the interference with a reference light, the vibration information distributed along the optical fiber is obtained by demodulating the beat frequency signal; combining the constructed sand particle impact and optical fiber coupling model, the dynamic strain generated by sand particle impact is converted into phase changes, realizing the acquisition of sand particle impact location, sand particle size, and sand particle quantity. This invention enables continuous distributed monitoring of wind and sand flows with high spatial resolution, and has advantages such as resistance to electromagnetic interference, strong environmental adaptability, and multi-parameter sensing, and can operate stably for a long time in harsh desert environments.

The invention discloses a device for testing illumination uniformity of fluorescent glass, and relates to the technical field of fluorescent glass illumination. The device comprises a carrying platform module, a laser light source module, an optical collection module and a spectral analysis module, the carrying platform module is used for carrying and fixing a fluorescent glass sample to be detected and driving the fluorescent glass sample to rotate; the laser light source module is used for generating and outputting an excitation light beam to act on the fluorescent glass sample, and a light emitting path is adjustable; the optical collection module is used for collecting an optical signal emitted by the fluorescent glass sample; and the spectral analysis module is connected with the optical path of the optical output port of the optical collection module and is used for receiving and analyzing the optical signal. The device is simple in structure, controllable in cost, convenient to operate, capable of achieving high-spatial-resolution automatic scanning, high in measurement precision and good in repeatability.

An elastic modulus of a viscoelastic body can be calculated with a high spatial resolution and in a relatively short measurement time. A projection image of an X-ray is detected with a detection unit by vibrating an object while maintaining a relative positional relationship between a first diffraction grating and a second diffraction grating. Then, an elastic modulus of the object is calculated based on a displacement amount of a wave due to the vibration in the projection image of the X-ray detected by the detection unit.

Embodiments of the present application disclose a video decoding method, a video encoding method, a device, computer equipment and a storage medium. The video decoding method comprises: decoding encoded information of at least one block from an encoded video bitstream, the encoded information indicating whether a super-resolution encoding mode is applied to the at least one block, wherein the super-resolution encoding mode is applied in response to the at least one block being down-sampled from a high spatial resolution to a low spatial resolution by an encoder; and when the encoded information indicates that the super-resolution encoding mode is applied to the at least one block, generating a reconstructed block by using the super-resolution encoding mode to up-sample information of a first block in the at least one block, wherein the first block has the low spatial resolution, the reconstructed block has the high spatial resolution which is higher than the low spatial resolution, the at least one block comprises transform coefficients, and the reconstructed block comprises sample values in a spatial domain.

The application provides a kind of blood vessel anastomosis skill automatic evaluation method based on computer vision technology, it is related to video processing technical field, the method is to utilize unlabelled blood vessel anastomosis operation video data, visual feature extraction model is trained, obtains pre-trained visual feature extraction model, blood vessel anastomosis operation video data is extracted, and blood vessel anastomosis skill visual feature is obtained;Blood vessel anastomosis skill visual feature is up-sampled using high-resolution pyramid, and high spatial resolution feature map is obtained;Using a variety of downstream task models, high spatial resolution feature map is operated action class identification, target segmentation and tip position identification;Action time consumption is calculated using operation action class, motion trajectory is obtained using instrument tip position, suture binary mask is identified using target segmentation, multidimensional index is calculated, and blood vessel anastomosis skill automatic evaluation result is obtained.The application solves the problem that the prior art is difficult to improve small target recognition accuracy.

The invention discloses a hectometer-level greenhouse gas emission list generation method fused with vehicle-mounted underway observation, which comprises the following steps of: acquiring data through vehicle-mounted underway observation, eliminating background influence in observation data, performing quality control and preprocessing, determining an optimal space average scale and characteristic variables, dividing data subsets based on a spatial clustering analysis method, and generating a hectometer-level greenhouse gas emission list. A model is constructed and evaluated, and the rationality of characteristic values is checked; and constructing a model to simulate regional concentration, and carrying out emission list downscaling on the basis of a concentration quantification weight coefficient. According to the method, the problems of light population misallocation, heterogeneous interpolation extrapolation distortion and lack of high-resolution input of machine learning in a hectometer method in the prior art are solved; a set of greenhouse gas emission list with high spatial resolution is generated by fusing the emission list with kilometer-level or even higher resolution with vehicle-mounted underway observation data, and hectometer-level greenhouse gas emission data can be provided for cities.

The invention discloses a near-surface atmospheric pollutant deep learning prediction method based on hyper-spectral satellite remote sensing and ground observation data. The near-surface atmospheric pollutant deep learning prediction method comprises the following steps: preprocessing collected multi-source data; constructing an assimilation network adopting a convolutional neural process, ViT and ResNet combined architecture, training the assimilation network by using the preprocessed multi-source data, and generating an initial assimilation state at the current moment; and constructing a prediction network with the same architecture as the assimilation network, taking the initial assimilation state at the current moment as input, carrying out time extrapolation in combination with multi-source data at future moments, respectively constructing independent prediction networks at different future moments, carrying out independent training, and outputting pollutant concentration probability prediction results at different time periods in the future. Therefore, the probabilistic pollutant concentration prediction with high spatial resolution of 0.1 degree * 0.1 degree and 72-hour time efficiency is realized without depending on a chemical transmission model.

The application discloses a two-dimensional metal organic framework nanopore sensor and a preparation method and application thereof. The two-dimensional metal organic framework nanopore sensor comprises a two-dimensional metal organic framework film with first nanopores, a silicon nitride film with second nanopores and a silicon substrate which are sequentially stacked, the two-dimensional metal organic framework film is formed through liquid-liquid interface force self-assembly and is transferred in situ to the silicon nitride film to form. The two-dimensional nanopore film material adopted by the application is a metal organic framework of a porphyrin organic ligand, the hydrophobic porphyrin ligand has high affinity with DNA molecules and can interact with the DNA molecules, so that the speed of the DNA passing through the two-dimensional nanopore is slowed down, the problem of fast pore passing speed when the two-dimensional nanopore sensor detects and distinguishes short-chain DNA is solved, and the time resolution capability of the two-dimensional nanopore is greatly improved under the premise of guaranteeing high spatial resolution of the two-dimensional nanopore.