2820 results about "Optical spectrometer" patented technology

The invention discloses a gastrodia elata quality detection method based on a computer vision technology, relates to the technical field of intelligent detection, and is used for solving the problems of low detection efficiency and poor recognition accuracy in traditional gastrodia elata detection. According to the invention, synchronous acquisition and preprocessing of multi-source data are carried out through an industrial camera, an infrared imager, a 3D scanning device and a spectrometer, a multi-scale feature extraction algorithm is utilized to generate quality feature vectors containing forms, textures, colors and defects, and a cross-modal three-dimensional characteristic spectrum is constructed. The deep learning model is combined to realize automatic quality evaluation and grading; when the reject ratio exceeds a threshold value, main influence factors of unqualified products are analyzed, and an interpretable quality evaluation report is generated; the precise detection of the quality of the gastrodia elata is realized; and the detection efficiency and the identification accuracy are effectively improved.

Embodiments include systems for determining one or more properties of an object. In an embodiment, a system includes a gripping element, a light source, a probe element including an optical fiber, a spectrometer, and a processor. The gripping element is configured to grasp the object. The light source is configured to illuminate the object. The probe element is operatively coupled to the gripping element. The optical fiber is configured to transmit reflected light from the object. The spectrometer configured to: (i) receive the transmitted reflected light from the optical fiber and (ii) generate spectral data based on the received transmitted reflected light. The processor is configured to: (i) receive the generated spectral data from the spectrometer and (ii) determine one or more properties of the object based on the received generated spectral data.

The invention provides a multi-source fusion spectrum cross-domain high-precision prediction method and system based on transfer learning. The method comprises the following steps: S1, acquiring spectrograms collected by a spectral imaging device under multiple wavelengths; s2, extracting various types of features from the spectrogram; s3, training a fusion model to obtain a trained fusion model; and S4, inputting a to-be-predicted spectrum into the trained fusion model, and outputting a result. According to the invention, 10 <-4 > nm-level wavelength prediction can be achieved in a common industrial camera system, and the level of a scientific research-level grating spectrometer (0.001-0.002 nm) can be reached / exceeded; on a narrow-band, middle-band and wide-band multi-scene cross-domain data set, the mean absolute error (MAE) can be reduced from the nanoscale to the magnitude of 10 <-4 > nm, and excellent robustness is kept under the conditions of noise, feature deficiency and few samples.

The invention discloses an underground gas storage gas monitoring method and system based on optical fiber spectrum analysis. The method comprises the following steps: S1, optical fiber network deployment: arranging a corrosion-resistant optical fiber sensor network in a gas storage; s2, spectral data acquisition: transmitting light with a specific wavelength to a gas chamber at the tail end of an optical fiber through a Fourier transform infrared spectrometer, and acquiring a transmitted spectrum after interaction of gas and light; s3, spectrum decoupling and concentration calculation: based on a peak pattern fitting algorithm of the Lambert-Beer law, decoupling the infrared spectrum characteristics of the mixed gas, matching a standard spectrum database, and calculating the concentration of each gas component; s4, constructing a three-dimensional gas model: according to the position of the optical fiber sensor and the gas concentration data, establishing a gas migration model to predict a leakage position and a movement direction; according to the method, the trend, the component distribution, the concentration change and the potential leakage risk of the gas in the storage are effectively evaluated, and technical support is provided for the safety, the effectiveness and the economical efficiency of operation of the gas storage.

The invention provides a spectral data optimization method and device, computer equipment and a storage medium, and relates to the technical field of semiconductor detection.The method comprises the steps that original spectral data output by a spectrograph is obtained, and the central wavelength value of the original spectral data of each frame is calculated; querying from a preset database according to the central wavelength value to obtain a corresponding instrument linear function; and processing each frame of original spectral data and the corresponding instrument linear function by adopting a deconvolution algorithm to obtain optimized real spectral data. According to the scheme, algorithm compensation is carried out on each frame of spectral data, so that system distortion introduced by the spectrometer can be accurately compensated in a full spectrum range, the extraction precision of spectral features is greatly improved, and the magnitude order improvement of measurement precision is realized; in addition, the optimized spectral data more truly reflects the physical characteristics of the tested sample, the dependence of an optical model on empirical parameters is reduced, and the generalization ability and prediction reliability of the model are improved.

The invention discloses an intelligent sorting method and device for a positive electrode material of a retired lithium ion battery based on a spectrum method, and the device is connected in series with a pretreatment module, a cleaning module, an identification module and a sorting module through a conveying belt in a supporting module to form an automatic sorting assembly line. Pre-treating the retired battery to obtain a clean positive plate; an X-ray fluorescence spectrophotometer in the recognition module collects the spectrum of the positive plate and transmits the spectrum to an industrial personal computer, and the spectrum is preprocessed and then input into a classifier library; the classifier library comprises a main classifier and an increment classifier based on element and spectral shape dual channels, if the output confidence reaches a preset threshold value, the material category is judged, otherwise, the spectrum is temporarily stored as an unknown spectrum; after unknown spectrums are accumulated to a set number, new categories are identified through a clustering algorithm, and a lightweight dichotomy increment classifier is trained and added into a classifier library; and the sorting module drives the hydraulic pushing hand to sort the positive plates according to the identification result. Through cooperative evolution of the main classifier and the increment classifier, the sorting precision is effectively improved.

An optical device includes: a first optical system; and a second optical system. The first optical system includes a first light splitting device configured to split measurement light emitted from a first light source into a first measurement light and a second measurement light and then mix the split measurement light, a first mirror configured to add a first modulation signal by being moved in an entering direction of the first measurement light and reflecting the first measurement light, a second mirror configured to reflect the second measurement light, and a first light receiving device configured to receive the measurement light including a sample-derived signal and the first modulation signal and output a first light receiving signal. The second optical system includes a second light source configured to emit laser light, an optical modulator configured to add a second modulation signal to the laser light, and a second light receiving device configured to receive the laser light including a displacement signal generated by reflection on the first mirror and the second modulation signal and output a second light receiving signal.

The invention relates to a total primary productivity high-precision downscaling method based on a multi-scale attention mechanism, and belongs to the technical field of remote sensing. According to the method, the technical problems of fuzzy details, fuzzy boundaries and insufficient fitting precision of the existing GPP downscaling technology in a complex terrain region are solved. According to the technical scheme, an Enhanced Multi-scale Residual Attention Network (EMSRAN) model is constructed, multi-source remote sensing data including a medium-resolution imaging spectrometer (MODIS) GPP product and a terrestrial satellite auxiliary factor are integrated, data preprocessing, sample generation and model training and optimization are carried out, and a high-resolution GPP image is output. Technical effects include significant improvement of spatial detail reduction ability, enhancement of heterogeneous ecosystem adaptability, enhancement of boundary definition expression, and improvement of carbon cycle research data reliability.

The invention discloses an ultrasonic phased array driven graphene oxide flow stripping and closed-loop regulation and control system and method, and the system comprises an ultrasonic phased array module, and a piezoelectric transducer array element in the ultrasonic phased array module controls sound beam focusing and energy distribution through a phase delay controller, and carries out the stripping of graphite oxide flowing in a flow channel; a micro-Raman spectrometer in the micro-fluidic-Raman detection module collects characteristic peak data of a graphene oxide sheet layer in a micro-fluidic chip in real time and sends the characteristic peak data to a signal analysis unit; and the feedback control module is used for receiving the layer number distribution data output by the signal analysis unit, dynamically adjusting ultrasonic parameters of the phase delay controller, and controlling the diverter valve to guide substandard products into a secondary treatment channel and finally return the substandard products to the flow channel for stripping again. The system and the method for stripping the graphene oxide based on coupling of the ultrasonic phased array and the micro-fluidic chip have the advantages of efficient stripping, accurate detection, closed-loop optimization and the like.

The invention provides a spectrograph wavelength calibration method, device and equipment and a medium, and the method comprises the steps: obtaining the spectral data of a spectrograph at different temperatures, and obtaining the spectral data of the spectrograph at different temperatures according to the pixel positions of a characteristic wavelength point at different temperatures and the pixel position of the characteristic wavelength point at a preset reference temperature; determining the pixel position offset of the characteristic wavelength point at different temperatures, and calibrating the wavelength of the spectrograph according to the pixel position offset of the characteristic wavelength point at different temperatures; in the process of calibrating the wavelength of the spectrograph, the wavelength drift caused by the pixel position offset of the characteristic wavelength point at different temperatures is fully considered, the output error of the wavelength of the spectrograph is reduced, and the wavelength output accuracy of the spectrograph is improved.

The invention relates to the technical field of spinning quality detection, and discloses a jute spinning product quality detection method and system based on an intelligent sensor. The method comprises the following steps: acquiring real-time process parameters of a jute spinning production line, and synchronously capturing yarn surface temperature field distribution in combination with an infrared thermal imager; performing space-time alignment processing on the yarn tension fluctuation data and the temperature field distribution to generate a fused dynamic process characteristic matrix; according to the tension gradient change rate and the temperature field abnormal region coordinates in the dynamic process characteristic matrix, dividing potential occurrence sections of yarn quality defects; a microstructure image of the yarn in the potential generation section is extracted, a fiber arrangement angle deviation value is measured through a polarized light interferometer, and fiber molecular bond vibration frequency data is obtained in combination with a Raman spectrometer; and inputting the fiber arrangement angle deviation value and the molecular bond vibration frequency data into a cascade quality analysis model, and outputting a quantitative index set of the internal structure defects of the yarns.

The invention discloses an on-line detection method for volatile organic compounds in waste gas, and belongs to the field of waste gas emission monitoring, the detection method comprises the following specific steps: I, starting a quantum cascade laser frequency comb of a middle infrared band, calibrating various parameters of the quantum cascade laser frequency comb, and ensuring to cover a characteristic absorption area of the volatile organic compounds in the waste gas; iI, inputting the waste gas into a gas detection chamber through a sampling pipeline, monitoring the state of the waste gas in real time, and dynamically adjusting the conditions of the gas detection chamber according to various collected signals; the device can capture instantaneous fluctuation of waste gas concentration in real time, meets the high-speed dynamic emission monitoring requirement, has extremely high coherence and narrow linewidth, can analyze tiny spectral line differences which cannot be distinguished by a traditional spectrograph, remarkably improves the detection precision and the recognition capability, ensures that a measurement result still keeps consistency and high reliability under different working conditions, and is suitable for large-scale popularization and application. The signal-to-noise ratio is obviously improved, the power drift is reduced, and long-time stable operation is realized.

The invention relates to the technical field of spectrum baseline correction, and provides a spectrograph baseline correction method and system based on improved empirical mode decomposition, and the method comprises the following steps: employing a sliding window smoothing method, and carrying out the preprocessing of obtained measurement spectrum data; an improved empirical mode decomposition algorithm is adopted, fitting is carried out on the preprocessed measurement spectrum data to obtain baseline data, and the improved empirical mode decomposition algorithm adopts least square fitting to construct upper and lower boundary envelopes of the spectrum data; subtracting the baseline data obtained by fitting from the obtained measurement spectrum data to obtain the measurement spectrum data after the baseline is removed; and sequentially carrying out abnormal point detection and removal, spectral power calibration and wavelength calibration on the measured spectral data after baseline removal to obtain spectral data after baseline correction. The spectral baseline is identified by improving empirical mode decomposition, the stability and boundary adaptability of mode decomposition are enhanced, and a more accurate baseline fitting result is obtained.

The invention provides a method for detecting a gas production state after thermal runaway of a battery, which comprises the following steps: placing a lithium battery in a closed anti-explosion tank, heating to trigger runaway, constructing a coupling matrix through pressure and temperature data acquired by a dynamic pressure compensation model, and correcting pressure distribution by using a nonlinear thermodynamic equation; analyzing the concentration of gas components by adopting a Fourier transform infrared spectrometer, and calculating the total gas production amount by combining multiple regression analysis; and quantizing energy dissipation based on a second law of thermodynamics to generate an energy release characteristic matrix, mapping the energy release characteristic matrix to a high-dimensional space to generate a risk index, and finally predicting thermal runaway probability distribution through a support vector machine. According to the method, high-precision measurement and analysis of the gas production rate in the thermal runaway process of the battery are realized through dynamic pressure compensation, multi-dimensional gas component analysis and nonlinear thermodynamic modeling, and the testing efficiency and the early warning capability of the battery are improved.

The invention relates to the technical field of engineering plastic detection, and particularly discloses an aging detection and evaluation method and system suitable for nylon 6 in a marine environment, the system comprises nylon 6 as a core layer, an aging response color-changing material as a surface layer and a middle layer located between the core layer and the surface layer; the thickness of the middle layer is 200-250 [mu] m, and the composite conductive film is transferred to the position 0.2 mm below the surface of the nylon 6 component in a hot pressing mode; the thickness of the surface layer is 0-200 microns and is realized by spraying an aging response color-changing material solution. By integrating the specially designed aging response color-changing material and the conductive film into the nylon 6 matrix, real-time, visual and efficient detection of the aging process is realized. According to the method, the problem that equipment such as a traditional optical fiber spectrometer is complex and expensive is solved, the convenience of field detection is greatly improved through double signal output of color gradient indication and simple electronic reading, and a brand new technical solution is provided for life prediction and preventive maintenance of nylon 6 components in ocean engineering.

Performance evaluation and structural optimization methods for a high-power semiconductor laser chip, and a performance evaluation system for a high-power semiconductor laser chip. The performance evaluation method for a high-power semiconductor laser chip comprises: providing a window on an N-side electrode of a chip to be tested (step 1); keeping the chip in an operating state (step 2); allowing a quantum well active region of the chip to generate spontaneous emission, so that the spontaneous emission is imaged outside the chip (step 3); acquiring, by means of a spectrograph, a spectrum of the spontaneous emission outside the chip and obtaining a two-dimensional distribution of a quantum well temperature of the chip in the operating state; and acquiring, by means of a CCD camera, an image of the spontaneous emission imaging outside the chip and obtaining a two-dimensional distribution of charge carriers in the quantum well of the chip in the operating state (step 4). According to the performance evaluation and structural optimization methods for a high-power semiconductor laser chip, the distributions of the temperature and the charge carrier concentration in the quantum well of the chip to be tested in the operating state in which the resolution is freely adjusted can be obtained. Operations of the methods are convenient, and implementation is simple and easy, thereby efficiently improving the accuracy of an evaluation result.

The invention discloses an intelligent carbon anode quality detection system, particularly relates to the field of electrolytic aluminum, and comprises a data acquisition module, a data preprocessing module, a data analysis module and a comprehensive judgment module. According to the method, a full-process data acquisition system covering raw materials, forming, roasting and appearance is constructed, accurate acquisition of multi-source data is realized by using equipment such as an X-ray fluorescence spectrometer and a hydraulic sensor, the problem of dispersion of traditional detection data is solved, and the detection accuracy of the multi-source data is improved through multi-stage pretreatment methods such as outlier elimination, sliding window filtering, temperature compensation and wavelet noise reduction. Dimension difference and sensor noise interference are effectively eliminated, and data reliability is improved. A multi-level evaluation model composed of a raw material comprehensive index, forming energy density, roasting maturity and appearance integrity is innovatively established, and intelligent comprehensive evaluation and accurate grading management and control of the carbon anode quality are achieved in combination with a dynamic weighting comprehensive quality index formula and a four-level grading mechanism.

The invention provides a soil stress monitoring method based on a distributed echo wall optical fiber cavity array, which innovatively utilizes a plurality of echo wall structures to realize distributed multi-point monitoring of soil stress in the same optical fiber, and accurately reflects the spatial distribution of the soil stress by monitoring the resonant frequency change of the echo wall structures; the method comprises the following steps: testing connection; monitoring the resonant frequency of the echo wall of the optical fiber echo wall array sensor; a wide-spectrum light source is adopted to excite an optical fiber to generate an optical signal, after the optical signal is transmitted by the optical fiber, when the optical signal passes through echo wall structures with different diameters of the optical fiber echo wall array sensor, the optical signal resonates at resonant frequencies of the echo wall structures, so that resonant trapped waves on multiple frequencies appear in a transmitted spectrum measured by a spectrograph; monitoring the resonant frequency change of the echo wall structure caused by the soil stress, and obtaining the spatial distribution information of the soil stress.

The invention discloses an LIBS (laser-induced breakdown spectroscopy) technology-based probe gun for online detection of molten steel components, comprising: a cylindrical shell, an upper cylinder opening of which is provided with an optical fiber receiving head electrically connected with a spectrometer; the laser emitting system is used for emitting high-energy pulse laser to penetrate through a lower barrel opening of the barrel-shaped shell to excite atoms on the surface of the molten steel, and plasma is formed; the signal acquisition system is used for coupling a spectral signal emitted by the plasma to the optical fiber receiving head, and an acquisition light path is formed between the plasma and the optical fiber receiving head; and the gas protection system is used for carrying out coaxial purging on the laser action area and the signal acquisition area so as to form an inert gas protection barrier around the plasma and on the peripheral side of the acquisition light path. The probe gun adopts inert gas to protect a barrier, has multiple effects of inhibiting generation of an oxide layer, reducing local temperature, reducing steam scattering and weakening continuous background radiation, and can improve the signal acquisition capability of the probe gun.

The present application provides a method for performance evaluation and structure optimization of a high-power semiconductor laser chip, and a system for performance evaluation. Wherein the method for performance evaluation of a high-power semiconductor laser chip comprises: setting a window in an N-surface electrode of a chip to be tested; maintaining the chip to be tested in an operating state, wherein spontaneous radiation is generated in an active area of a quantum well of the chip to be tested; imaging the spontaneous radiation at a position outside the chip to be tested; acquiring, by using a spectrometer outside the chip to be tested, a spectrum of the spontaneous radiation to obtain a two-dimensional distribution of temperature of the quantum well of the chip to be tested in the operating state; and acquiring, by using a CCD camera outside the chip to be tested, an image of the spontaneous radiation to obtain a two-dimensional distribution of carriers in the quantum well of the chip to be tested in the operating state. The method for performance evaluation and structure optimization of a high-power semiconductor laser chip provided by the present application can get the temperature distribution and the carrier concentration distribution of the chip to be tested in the operating state with a resolution that is freely adjustable, the operation is convenient and easy to implement, and the accuracy of evaluation results is effectively improved.

The invention relates to a self-coherence optical fiber interference device and method for simultaneously measuring morphology and thickness. The device comprises a light source module (1), a measurement light path (2), a compensation light path (3), a spectrograph (4), a mechanical motion module (6) and a data processing module (5), the measuring light path (2) comprises an optical fiber circulator (21), an optical fiber retroreflector (22) and an optical probe (23) and is used for realizing focusing measurement and enabling reflected light of the end face of the optical fiber retroreflector (22) and reflected light of a transparent object to be measured to return; reflected light of the end face of the optical fiber retroreflector (2) and reflected light of the transparent object to be measured form a measuring light beam, and the measuring light beam enters the compensation light path (3); the compensation light path (3) comprises an optical fiber splitter (31), an optical fiber delay line (32) and an optical fiber coupler (33), the measuring light beam is subjected to optical path compensation to generate a compensation light beam, and the compensation light beam and the measuring light beam are combined and input into the spectrograph (4) together.

The invention discloses a laser cleaning method for a magnesium-based foil, and belongs to the technical field of magnesium ion battery manufacturing. According to the laser cleaning method for the magnesium-based foil, the magnesium-based foil is magnesium foil or magnesium alloy foil, and the method comprises the following steps that laser cleaning is conducted on the magnesium-based foil through a laser device, and a laser beam conducts 45-degree cross filling path scanning on the surface of the magnesium-based foil; monitoring a plasma spectral line of laser ablation in real time by using a plasma spectrometer; based on the dynamic change of the magnesium characteristic plasma spectral line intensity, the cleaning parameters of the laser are adjusted; and after cleaning is completed, an oxide layer on the surface of the magnesium-based foil is removed. 45-degree cross filling path scanning is adopted, heat accumulation of a repeated scanning area can be reduced, during 45-degree cross filling, adjacent scanning lines cover in a cross mode, heat distribution is more uniform, heat of the scanning area can be reduced, and therefore the problems of local overheating and negative plate perforation or structural damage caused by too high energy are avoided.

The invention discloses an SERS (Surface Enhanced Raman Scattering) detection method for paclitaxel drug concentration in blood of a breast cancer patient, and belongs to the technical field of detection. The method comprises the following steps: performing acetonitrile two-step precipitation centrifugal treatment on a blood sample to obtain a detection sample; the method comprises the following steps: constructing a high-sensitivity SERS substrate (the volume ratio of gold nanoparticles to ethanol is 1: (90-100), and a film is formed on a water-cyclohexane interface) through self-assembly of gold nanoparticles on a liquid-liquid interface; the method comprises the following steps: dropwise adding a sample into a substrate, and detecting characteristic peaks of 1024cm <-1 > and 1053cm <-1 > by using a portable Raman spectrometer (785nm, 30mW, 0.5 s); and calculating the paclitaxel concentration in combination with a pre-established quantitative curve. The method is easy and convenient to operate and suitable for clinical bedside rapid monitoring.

The invention discloses a fiber optic spectrometer for film thickness measurement. The fiber optic spectrometer comprises a control and data processing module, a detection module, a light source module and a light splitting module, the optical fiber coupling module couples wide-spectrum light of the light source module and then guides the light to the light splitting module; the light splitting module adopts a cross-type Czerny-Turner light path structure, and performs collimation, dispersion and focusing processing on light beams in sequence; the detection module is used for receiving the optical signal processed by the light splitting module and forming an interference pattern; and the control and data processing module is used for driving acquisition, completing pixel-wavelength calibration and calculating the film thickness based on an acquired interference pattern. According to the optical fiber spectrometer measurement method for film thickness measurement, the problem of low accuracy of real-time film thickness detection in the prior art is solved.

The invention provides a precise and small broadband hyperspectral imager, which is used for solving the technical problem that the existing broadband spectral imager from visible near-infrared to short-wave infrared for sceneries cannot meet the increasingly harsh imaging requirements. According to the small broadband hyperspectral imager, the front optical assembly of an off-axis two-reflection structure and the spectrometer assembly in a free-form surface reflector, optical path multiplexing and axis folding mode are adopted, the number of used lenses is greatly reduced, meanwhile, the length of a spectrometer is effectively reduced, and the imaging precision is improved. The volume and the weight of the spectral imager are greatly reduced; besides, front surfaces and rear surfaces of a first lens and a second lens in the spectrometer assembly are plated with broadband antireflection films from visible near-infrared to short-wave infrared according to light angles, and broadband detection from visible near-infrared to short-wave infrared can be realized in combination with a broadband refrigeration type detector. And the complexity and the installation and adjustment difficulty of the detector assembly and the circuit assembly are greatly reduced.

The invention relates to a cross-equipment quality parameter detection model construction method based on unsupervised domain adaptation. The method comprises the steps that a quality parameter detection basic model is constructed, a training data set used for training the quality parameter detection basic model is constructed, and when the training data set is used for conducting model training on the quality parameter detection basic model, at least based on a training method adaptive to an unsupervised domain, the quality parameter detection basic model is trained. A corresponding quality parameter detection target model is generated after model training; and during quality parameter detection, to-be-detected near infrared spectrum data of a to-be-detected sample is obtained, and the to-be-detected near infrared spectrum data is loaded to the quality parameter detection target model, so that the quality parameter detection target model is utilized to predict and output quality parameter information of the to-be-detected sample. According to the method, the technical bottleneck that the performance is severely reduced during cross-device application of the model due to spectrograph difference can be effectively solved.

The invention relates to the technical field of spectrum detection, and particularly discloses a preparation method of a microstructure enhanced optical fiber and a Raman spectrometer light collection system thereof, the system comprises: a light source assembly for generating laser and performing collimation treatment on the laser to make the collimated laser irradiate a to-be-detected sample; the detection area assembly is used for placing a to-be-detected sample and positioning the to-be-detected sample; the collection assembly is used for collecting Raman scattering light generated by the sample to be detected under laser irradiation based on the microstructure enhanced optical fiber, and the optical fiber end face of the microstructure enhanced optical fiber is provided with a micro-nano structure; the geometric parameters of the micro-nano structure are determined by global optimization by using the genetic algorithm to maximize the coupling efficiency of the unpolarized diffused light in a preset wavelength range as an optimization target; and the control analysis assembly is used for carrying out signal acquisition from the collected Raman scattering light and identifying component information corresponding to the to-be-detected sample through a preset component identification model based on a signal acquisition result.

The invention relates to the technical field of surface topography measurement, and discloses a spectral interference surface topography measurement method and device based on a metasurface. The device comprises a spectrograph, a white light source, an optical fiber, a focusing metasurface and a dispersion metasurface, the focusing metasurface and the dispersion metasurface are arranged in parallel and aligned, a spherical thin lens and a micro-nano structure are arranged on the two sides of the focusing metasurface respectively, and a reflecting metal film is arranged between the two sides; a semi-transparent and semi-reflective film and a micro-nano structure are arranged on the two sides of the dispersion metasurface respectively; the focusing metasurface is used for converging parallel incident light, one part of light serves as reference light and is reflected and focused on the reflective coating by the semi-transparent and semi-reflective film, and the other part of light serves as measuring light and penetrates through the semi-transparent and semi-reflective film; the dispersion metasurface is used for carrying out axial dispersion on light penetrating through the semi-transparent and semi-reflective film, monochromatic light focused on the to-be-measured surface returns along a light path and interferes with reference light, and a confocal signal or an interference signal is generated to calculate morphology information of the to-be-measured surface. By adopting the device, high-precision surface topography measurement can be realized in a narrow space.

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.