2936results about "Scattering properties measurements" patented technology

The invention discloses a multi-mode end point detection system and method for a semiconductor dry process, and relates to the field of gas concentration detection. A gas absorption cell; the reference light path adjusting unit comprises an adjustable attenuator used for adjusting signals; the first photoelectric detector is used for detecting a transmission signal; the second photoelectric detector is used for detecting a reference signal; the lateral scattered light detector is used for detecting a scattered signal of the particulate matters in the gas absorption tank; and the signal processing unit is in signal connection with the first photoelectric detector, the second photoelectric detector and the lateral scattering light detector and is used for performing compensation calculation on the transmission signal based on the reference signal and the scattering signal so as to obtain a corrected gas absorption signal. By adopting the scheme, measurement signal distortion caused by optical mirror surface pollution and particulate matter scattering interference in a semiconductor tail gas optical detection technology is avoided.

The invention relates to the technical field of surveying and mapping information processing, and discloses a surveying and mapping information intelligent analysis and visualization system based on the Internet of Things. According to the system, a building space data acquisition terminal acquires geometric feature point cloud and environmental parameters of the surface of a building structure in real time through distributed Internet of Things nodes; the multi-source heterogeneous data fusion engine performs space-time alignment processing on the geometric feature point cloud to generate a building total-factor topological skeleton with an absolute coordinate system; the three-dimensional topological relation reconstruction module is used for extracting a spatial constraint relation of building components according to the topological skeleton and establishing a hierarchical building information model capable of being edited in a parameterized manner; and the dynamic visual rendering platform is used for generating a multi-scale spatial index based on the hierarchical building information model, and driving real-time light and shadow effects and interactive sectioning analysis. According to the system, full-process automatic processing and dynamic visualization of building surveying and mapping data are realized.

The invention relates to the technical field of exploration, and discloses a water depth inversion method and system based on a multispectral remote sensing image, which utilizes an independent verification sample set to carry out hierarchical precision evaluation, and analyzes model performance differences according to dimensions such as a water depth range and a substrate type. Error propagation of links such as atmospheric correction and water level correction is quantified through full-chain uncertainty analysis, an uncertainty quantification model of ensemble learning is constructed, and a pixel-level precision distribution diagram is generated. Therefore, according to the technical scheme, a closed-loop dynamic adaptation framework is formed by systematically integrating multi-temporal data dynamic modeling and an uncertainty quantification mechanism, a spatio-temporal variation compensation mechanism is embedded in the whole process from data acquisition to result verification, the interference of spatial-temporal heterogeneity of water optical characteristics on water depth inversion is effectively dealt with, and the accuracy of water depth inversion is improved. The problems of parameter mismatch and precision reduction of the water depth inversion model caused by dynamic change of optical characteristics of a coastal water body in seasonal and tidal scales are solved.

The invention discloses a multi-mode laser radar networked atmospheric parameter collaborative monitoring system and monitoring method, and relates to the technical field of atmospheric monitoring, and the method comprises the steps: deploying multi-mode laser radar nodes, synchronously collecting multi-source atmospheric parameters for preprocessing, and obtaining a fusion feature matrix; transmitting the fusion feature matrix to an edge computing node through dynamic networking, and aggregating the edge node through federal learning to realize cloud fusion; the method comprises the following steps: constructing a space-time dynamic graph based on laser radar nodes and a space-time dependency relationship between the nodes, decomposing space-time dynamic correlation into a stable item and a non-stable item through space-time decoupling, and updating space-time dynamic graph data by adopting an alternating optimization strategy through online learning; and constructing a prediction model, taking the real-time feature flow obtained by cloud fusion as input, detecting an abnormal event by predicting atmospheric parameters, and performing pollution traceability. According to the invention, high-precision and real-time monitoring of atmospheric parameters is realized through multi-mode cooperative sensing, intelligent fusion analysis and dynamic optimization decision.

The invention discloses a soil water content inversion method and system based on L-band dual-polarization data and a medium, and belongs to the field of remote sensing technology and environment monitoring. The system comprises an SAR data acquisition module, an optical data processing module, a vegetation scattering separation module, an inversion model construction module, a spatial distribution calculation module and a risk assessment module, wherein the SAR data acquisition module is used for regularly acquiring L-band dual-polarized SAR data of a target area; the optical data processing module assists in identifying and separating vegetation scattering components by calculating vegetation indexes; the vegetation scattering separation module is used for extracting pure soil back scattering signals; the inversion model building module is used for training and optimizing a soil water content inversion model based on the pure soil back scattering signals and field sampling data; the spatial distribution calculation module is used for calculating a spatial distribution diagram of the surface soil water content of the target area; and the risk assessment module is used for carrying out landslide risk grade division and early warning management.

The invention provides a data detection method and system, a detection device, computer equipment and a storage medium, and the method comprises the steps: obtaining a detection signal of each wafer surface in a planetary reaction cavity, and cutting the detection signal based on a trigger signal to obtain a first signal sequence and a second signal sequence; processing the first signal sequence by adopting a classification model to obtain a material type on each wafer; querying a corresponding optical model based on the material type; and performing iterative optimization on the optical model, the first signal sequence and the second signal sequence by adopting a decoupling algorithm to obtain a temperature detection value and a reflectivity detection value. According to the method, the original detection signal is segmented into the independent signal sequences based on the trigger signal, then the material type is determined according to the independent signal sequences, the corresponding optical model is selected according to the material type, and finally the temperature detection value and the reflectivity detection value with high accuracy are obtained through decoupling according to the optical model. Accurate analysis of a single wafer signal is realized, and process repeatability and stability are greatly improved.

Methods and devices for analyzing a sample from a subject are provided. A device includes one or more coherent light sources and one or more partially coherent light sources. The light sources are configured to emit first and second wavelengths of electromagnetic radiation towards an imaging chamber configured to hold blood cells. The light sources are aligned to illuminate a single common area of the imaging chamber. The device includes optics positioned to receive light from the imaging chamber, and a detector in optical communication with the optics. The detector is configured to detect fluorescence emission and backscatter from blood cells when present in the imaging chamber. The device includes mixers / unmixers configured to replicate and mix first and second signals representative of the responses to the first and second wavelengths after interacting with the plurality of blood cells to generate spectro-spatial responses.

The invention relates to the technical field of material testing, and particularly discloses an intelligent quality detection method and system for a micro-mineral bio-organic fertilizer, local thermal excitation is applied to a fertilizer sample through a micro-area thermal pulse excitation device, a gas release kinetic curve and a spectrum change track are synchronously collected, and a gas spectrum coupling data cube is constructed; performing differential transformation and modal decomposition on the time sequence feature set, extracting transient response feature vectors and generating an activity response distribution diagram; establishing component-activity correlation analysis, and decoupling biological metabolic activity and matrix background interference through feature separation and a comparative learning strategy to obtain a dynamic metabolic fingerprint; constructing a multi-dimensional feature space by using the dynamic metabolic fingerprints and the apparent characteristic parameters, and performing information aggregation and feature reconstruction by using a graph convolutional network to generate a comprehensive quality index; and finally, realizing quality grade judgment based on a quality characteristic pyramid structure, and establishing a dynamic early warning mechanism by analyzing time sequence evolution characteristics of the activity response distribution diagram.

The invention relates to the technical field of machine vision and optical detection, in particular to a tea color automatic evaluation method and system based on machine vision. The method comprises the following steps: constructing a stable and repeatable optical measurement environment and calculating radiation baseline parameters; performing multi-band polarization sequence imaging on the tea sample to obtain original data with spectrum and structural characteristics; separating mirror surface and diffuse reflection components on the surfaces of the tea leaves, and performing spectrum consistency correction by combining a radiation baseline; performing multiband spectrum reconstruction and normalization processing on the basis of the corrected diffuse reflection image, mapping to a CIE Lab color space, extracting pixel-level brightness, chromaticity and color distribution statistical indexes, and generating a color feature vector in combination with spatial weighting matrix optimization; a final score is calculated by constructing a quantitative evaluation and grade judgment model and integrating perception color separation, drying calibration color separation and a penalty term, and a grade result is output. According to the method, objective, accurate and automatic evaluation of the color of the tea leaves is realized.

A regional soil moisture monitoring method based on airborne spectral reconstruction optical satellite remote sensing, the method comprising: acquiring satellite remote sensing data of a region to be monitored, and collecting unmanned aerial vehicle remote sensing data of a local region in the region to be monitored; on the basis of the unmanned aerial vehicle remote sensing data of the local region, performing spectral reconstruction on the satellite remote sensing data of the region to be monitored, so as to obtain reconstructed satellite spectral data of the satellite remote sensing data; and inputting the reconstructed satellite spectral data into a pre-trained soil moisture inversion model, so as to obtain the soil moisture content of the region to be monitored. Therefore, soil moisture is accurately and quickly monitored.

The invention discloses a system and a method for classified sewage treatment, and belongs to the technical field of environmental engineering and water treatment. The system comprises the following components: an intelligent water quality detection module, which is used for real-time and accurate monitoring of COD, BOD, ammonia nitrogen, total phosphorus, suspended matter concentration and heavy metal content; the sectional bioreactor realizes deep removal of nitrogen and phosphorus and efficient biological treatment by flexibly adjusting reaction conditions of each section; the intelligent flocculation control module is used for automatically and accurately adjusting the adding amount of a flocculating agent, and is combined with integrated operation of efficient inclined tube precipitation and sludge concentration, so that the water quality of discharged water is stable, and the medicament consumption is reduced; the ultrafiltration membrane bioreactor effectively removes residual suspended matters and colloids, and ensures that the effluent stably reaches the standard for a long time through the synergistic effect of catalytic ozonation; and the sludge treatment module is used for realizing collaborative optimization management of sludge reduction, recycling and energy recycling.

The invention provides a photoacoustic measurement method and device, and the method comprises the steps: carrying out the photoacoustic measurement of a to-be-measured object through a photoacoustic measurement device, and extracting a reference value of a physical parameter of each film material according to an obtained reflectivity change signal; further acquiring a reflectivity change simulation signal based on the reference value of the physical parameter of the material so as to acquire a simulation value of the physical parameter of each film material; and performing weighted correction on the reference value by the simulation value to obtain a fitting value of the physical parameter of each film layer material. The fitting value of the physical parameter of each film layer material obtained by the technical scheme of the invention can reflect the change of the physical parameter of the material in the actual film layer growth process of the object to be measured, has higher accuracy as the initial value of the physical parameter of the simulation model, and is beneficial to optimizing the efficiency and precision of photoacoustic measurement of the thickness of the film layer.

The invention belongs to the technical field of unmanned aerial vehicle remote sensing and agriculture combination, and discloses an intelligent decision-making system and method for corn fertilization based on mechanism-data dual-drive fusion. The system comprises a mechanism simulation module, a data preprocessing module, a feature engineering module, a modeling module, a visualization module, a decision support module, a dynamic feedback correction module and a report generation and push module. According to the mechanism-data double-drive fusion-based intelligent decision-making system and method for corn fertilization, a large-area corn field block image is obtained in a short time through an unmanned aerial vehicle multispectral system, and the nitrogen diagnosis efficiency is improved; through a lightweight machine learning agent model, corn canopy leaf nitrogen nutrition parameters are accurately predicted, and a basis is provided for accurate fertilization; the system monitors the nitrogen nutrition status of the corn in real time, and provides possibility for dynamically adjusting a fertilization strategy; the multispectral remote sensing technology can perform nitrogen nutrition diagnosis under the condition of not damaging corn plants, and the corn growth environment is protected.

The present disclosure relates to a method and system for monitoring the road condition by a machine learning system and to a method for training the machine learning system. The methods include: providing or acquiring data by a sensor system of a vehicle, wherein the sensor system captures the surroundings of the vehicle (2) as training input data X; providing or acquiring data which characterize the road condition by means of a reference sensor fitted in or on the vehicle as training target values, and training the machine learning system. Training data, which include training input data X and training target values corresponding to these training input data X, are provided. The training data are used to adjust parameters of the machine learning system in such a manner that the machine learning system generates output data similar to the training target values when the training input data are input.

Device for identifying structure and composition of a fabric or textile, comprising: a chamber placing over the fabric or textile, with a microscopic camera attached to the chamber, for acquiring an image of the fabric or textile, , a chamber diffused light for illuminating the fabric or textile with diffused light reflected by the chamber, a chamber grazing light, for illuminating the fabric or textile with grazing light, and a rotating mechanism to orient the microscopic camera with the fabric woven alignment; a near infrared spectrometer attached to the surface plate where the fabric is set, to capture an absorption spectrum in multiple wavelengths, ranging from 1550-1950 nm, a white reference aligned over the near infrared spectrometer to calibrate the absorption spectrum and reduce the thickness influence of the fabric; an electronic system for light control, a software for interfacing and control of the acquisition and recognition processes, by carrying out the following steps: activating the chamber diffused light and the chamber grazing light; acquiring, from the microscopic camera, the acquired image; activating the near-infrared light source, acquiring, from the near-infrared spectrometer, the absorption spectrum; and detecting the structural identification and the composition of the textile or fabric, from the acquired image and the near infrared spectrum.

The application discloses a kind of acoustic-optical fusion's cold spring methane detection method, system, device and storage medium, comprising: obtaining first preprocessed acoustic measurement data and second preprocessed optical measurement data, obtains environmental measurement data;According to the acoustic measurement data, the optical measurement data and the environmental measurement data, form joint data;According to the joint data extraction joint feature, according to the joint feature determines current methane total concentration, according to the joint data determines current methane total leakage flux.The embodiment of the application can improve the accuracy of cold spring methane detection, and can be widely applied in gas detection technical field.

The invention provides a degassing-free transformer oil monitoring device and method. A transparent accommodating pipe is used for being communicated with an external transformer oil supply device; the laser detection assembly is arranged on one side of the transparent accommodating tube; the voltage regulation and control unit is connected with the transparent accommodating tube; the imaging assembly is arranged on one side of the transparent accommodating tube and is used for acquiring optical image data of the Tyndall phenomenon in the transformer oil sample under different voltage conditions; the data processing unit is used for setting a segmentation point in the middle position of a Tyndall light pillar based on the Tyndall light pillar in the image data collected by the imaging assembly, determining a standard deviation according to the ratio of the total number of gray pixels on the left side and the right side of the Tyndall light pillar, and determining a threshold value of the Tyndall light pillar according to the relation between the standard deviation and a preset threshold value range. And judging the existence state and distribution characteristics of the gas in the transformer oil sample. Degassing treatment is not needed, the process is simplified, sample pollution is avoided, and the monitoring accuracy and stability of the gas in the transformer oil are remarkably improved.

The invention belongs to the technical field of image processing, and particularly relates to an intelligent agricultural product pesticide residue detection method and system based on a spectrum technology, and the method comprises the steps: obtaining the hyperspectral reflectivity according to the original hyperspectrum, dark current and whiteboard image data; calculating an illumination confidence factor by using the average spectral intensity; performing linear scaling on the obtained standard biological matrix background spectrum according to the illumination confidence factor to obtain a local background estimated value and obtain a net residual spectrum; generating a pesticide residue distribution thermodynamic diagram by combining the cosine similarity of the net residual spectrum and the target pesticide standard fingerprint spectrum and the noise suppression weight based on the illumination confidence factor; and pesticide residue detection is carried out according to the statistical characteristics of the connected region of the suspected defect mask. Through adaptive background deduction and noise suppression, the problems of uneven curved surface illumination and strong background interference are solved, and the detection accuracy is improved.

The invention relates to the technical field of mineralogy, in particular to a complex iron mineral distinguishing and quantifying method and an iron mineral content analysis method, which innovatively combines chemical dissolution, automatic mineralogy analysis and a micro-area magnetic verification technology to realize distinguishing and quantifying of complex iron minerals. According to the analysis method, a closed and mutual verification analysis system is formed, acid treatment of carbonate, automatic mineralogy analysis of residual minerals, micro-area magnetic verification correction of misjudgment of maghemite, element surface scanning verification of mineralogy total quantification accuracy and a final calculation result, and closed verification of the total iron content of chemical analysis are combined, and therefore the comprehensive performance of the magnetic separation system is improved. The reliability of a final result is ensured and standardized popularization and application are facilitated.

The invention relates to the technical field of the Internet of Things, in particular to a real-time monitoring system for oil fume emission of an oil fume purifier based on the Internet of Things technology, and the real-time monitoring system is characterized in that oil fume concentration original data, environmental parameter data and historical oil fume data are acquired through a data acquisition module; the weighted filtering module dynamically distributes filtering weights based on the environmental parameter data, performs weighted fusion on the original data of the oil smoke concentration, and effectively inhibits environmental interference; the weighting correction module calls historical oil smoke data to establish a reference mode and distributes correction weights, secondary optimization is carried out on filtered data, and the data rationality is improved; the state evaluation and decision-making module calculates a comprehensive operation efficiency index based on the timeliness of the correction data, and generates graded early warning in combination with a concentration threshold value; according to the process, the data accuracy is optimized step by step, the problem of misjudgment caused by unreliability of single data is solved, and accurate early warning is achieved.

The invention relates to the technical field of a seabed substrate advanced detection device and method for a seabed mining vehicle, and provides a seabed substrate advanced detection device and method for a seabed mining vehicle, which can simultaneously obtain submarine topography and landform and detect multiple parameters of a seabed substrate. The deep sea detection system is matched with a mine car to ensure smooth proceeding of a rear mine car in deep sea bottom detection, and comprises a sea surface data processing system and a frame with the cross section in a structure shaped like a Chinese character'tian ', a master control device, a signal receiver and at least four detection modules arranged in a matrix are arranged on the frame, and the master control device is used for controlling the detection modules. The signal receiver is used for transmitting information of the detection module and the sea surface receiving device; the detection module comprises a side-scan sonar module used for rapidly obtaining the topography and landform in front, a transverse push toothed plate used for cutting into a soil body, a turbidity meter module used for measuring the concentration of suspended particles and dissolved matters in the seabed, and a pressing plate module used for obtaining the bearing capacity and the subsidence index of the seabed sediment.

The invention discloses an online quality monitoring method and system for fine dried noodle production and a storage medium. The method comprises the following steps: acquiring initial optical characteristic data of surface and internal tissues of the fine dried noodles, acquiring multiband reflection and transmission light signals through spectral analysis equipment, and determining initial characteristic distribution of surface dispersion and internal pore structures of the fine dried noodles; light source parameters are adjusted according to the initial optical characteristic data, and optimized light source parameter configuration is obtained; applying the optimized light source parameter configuration to a detection area through an optical fiber light guide technology to obtain scattering spectrum data; processing the scattered spectrum data to obtain an enhanced spectrum signal; analyzing the enhanced spectral signal through a spectral decomposition algorithm, and determining the tissue uniformity distribution of the fine dried noodles; according to the fine dried noodle tissue uniformity distribution, judging fine dried noodle quality indexes by adopting a classification algorithm to obtain a quality evaluation result; and generating real-time feedback data of the fine dried noodle production line according to a quality evaluation result, integrating quality indexes of multiple batches of fine dried noodles, and determining production optimization parameters.

The invention belongs to the related technical field of laser processing quality detection, and discloses a laser processing real-time defect monitoring device based on scattered light detection, which comprises a scattered light detection module, a signal processing module and a display early warning module, the detection module is used for realizing a scattered light detection function of focusing, filtering and attenuating; the signal processing module carries out various processing and enhancement on the detection signal based on a coordinate attention mechanism so as to obtain a defect judgment result; and the display early warning module is used for displaying data such as defect judgment results and the like, and giving alarms of different levels according to the severity of the defects. The invention further discloses a corresponding monitoring method. According to the invention, real-time and accurate identification of surface layer and subsurface layer defects in the laser processing process can be realized, so that the method is suitable for providing a more efficient and reliable solution for laser processing quality control in the fields of semiconductors, optical elements, aerospace and the like.

This invention discloses a method for transport of intensity diffraction tomography based on non-interferometric synthetic aperture. By acquiring through-focus intensity stacks under different illumination angles and performing three-dimensional Fourier domain half-space filtering (or 3D Hilbert transform equivalently) on the measured intensity stack, further combining with non-interferometric synthetic aperture, the 3D refractive index tomographic imaging in a non-interferometric manner without the need to meet matched illumination condition can be achieved. Leveraging the inherent advantage of synthetic aperture, the imaging resolution reaches the incoherent diffraction limit, resulting in high-resolution imaging results. The non-interferometric nature of TIDT-NSA offers a simple imaging optical setup, delivers speckle-free imaging quality, and is compatible with an off-the-shelf bright-field microscope.

The invention discloses a PVC film coating uniformity detection method based on spectral analysis, and relates to the technical field of optical detection, and the method comprises the following steps: S001, adopting a controllable incident illumination system with a multi-angle rotation function to carry out continuous angle scanning on the surface of a PVC film, collecting reflection spectrum intensity data in a corresponding wave band range according to different incident angles, and generating a spectrum data matrix containing interference characteristics; and S002, carrying out continuous wavelet transform processing on the spectral data matrix, carrying out multi-scale local decomposition on a spectral response signal, extracting and separating a periodic interference characteristic signal, and obtaining a purified spectral matrix after interference reduction. According to the method, through multi-angle spectrum collection and interference feature stripping, accurate identification of a coating thickness abnormal area and combination of strength indexes, spraying parameters are regulated and controlled, a detection-compensation-reinspection closed-loop mechanism is constructed, interference misjudgment is effectively avoided, and the accuracy and regulation and control efficiency of uniformity detection of the PVC film coating are improved.

A carbonation device for beverages includes a carbonation tank to receive a beverage to be carbonated and carbon dioxide so as to generate a carbonated beverage, carbonated with the carbon dioxide, and a dispensing device in fluid communication with the carbonation tank to dispense, through a duct, the carbonated beverage to a container for carbonated beverages, the carbonated beverage flowing along the duct in a flow direction.The carbonation device further includes a carbonation sensor associated with the duct and having a radiation source to generate a radiation which strikes the duct along an irradiation direction incident to the flow direction.The carbonation sensor also includes a first photodiode placed on the irradiation direction from a side opposite to the radiation source with respect to the duct, or as an alternative, a second photodiode placed along a diffusion direction substantially orthogonal to the irradiation direction.

The invention relates to the field of mining laser gas detection, in particular to a modulation and demodulation method and system for carrier noise suppression, and the modulation and demodulation method comprises the following steps: S1, generating a driving current sequence through a laser gas sensor; s2, collecting a light intensity sequence to carry out data reconstruction; s3, extracting a harmonic signal, sending the reconstructed sequence into a lock-in amplifier, and respectively extracting a second harmonic signal and a first harmonic signal; and S4, detecting the gas concentration through the ratio by using the mapping relation between the gas concentration and the ratio of the second harmonic signal to the first harmonic signal. According to the method, a continuous data discrete reconstruction technology is introduced into a modulation and demodulation process, and a reference time sequence is generated by utilizing the characteristics of a laser output signal, so that self-matching and dynamic adjustment of modulation frequency are realized, external signal interference is effectively avoided, and the harmonic extraction stability is improved; meanwhile, the hardware structure is simplified, and the adaptability of the system to different gas absorption spectral lines is enhanced.

The invention provides a semiconductor epitaxial growth parameter inversion method, a semiconductor epitaxial growth parameter inversion system, a semiconductor epitaxial growth parameter detection device and a related product, and relates to the technical field of semiconductor detection. The gas phase transmittance of a detection light path is further obtained, quantitative compensation is carried out on the actually measured reflection spectrum in the semiconductor epitaxial growth process, the compensated target reflection spectrum is closer to the real optical response of a semiconductor epitaxial film, and therefore spectral shape distortion and system errors caused by gas phase absorption superposition are effectively weakened. And the accuracy and the stability of the inverted growth parameters are obviously improved. Furthermore, the quantitative compensation value can be adaptively updated according to the fluctuation of the working condition, the inversion deviation introduced by the drift of the working condition is reduced, the consistency and comparability of the process are improved, and more reliable end point control and parameter closed-loop optimization can be conveniently realized.

The invention discloses an intelligent safety belt hook detection method and device based on artificial intelligence, an intelligent safety belt and a medium, and relates to the technical field of intelligent safety belts. The distance parameter is a distance value of the distance measuring sensor relative to the measured object, and the object category identification parameter comprises a parameter used for identifying the material of the measured object; when the distance parameter is smaller than a preset distance threshold value, inputting the distance parameter and the object category recognition parameter into a pre-trained object category recognition model, so that the object category recognition model outputs a material recognition result of the measured object; and determining whether the hook of the intelligent safety belt is hung back to the human body or not according to the material identification result and the preset material category. The real-time response speed and the detection real-time performance are effectively improved, whether the hook of the intelligent safety belt is correctly hung back to the human body or not can be effectively judged, and the detection accuracy is improved.

The invention relates to the technical field of information processing, in particular to the technical field of optical detection, and particularly relates to a two-dimensional material layer number identification method and equipment. A photoelectron chip composed of a semiconductor light source, a 2 * 2 waveguide beam splitter, a grating coupler, an on-chip spectrometer, a super lens and an optical detector is compact in structure and low in cost; a semiconductor light source emits an optical signal, the optical signal sequentially passes through a 2 * 2 waveguide beam splitter, a grating coupler and a super lens and then irradiates a two-dimensional material sample, a displacement table is used for carrying out accurate Z-axis focusing and XY plane scanning, reflection spectrum signals are collected in real time, spectrum characteristics are analyzed through an upper computer to determine layer number information, and finally a layer number distribution diagram is generated. According to the method, rapid, automatic and high-precision identification of the number of layers of the two-dimensional material is realized, and large-range scanning detection is facilitated.