4231 results about "Optical spectrometer" patented technology

The invention provides a water quality heavy metal pollution detection method and system based on Raman spectrum. The method comprises the following steps: collecting a water sample through a water area to be detected, and scanning the water sample by adopting a Raman spectrometer to generate an original Raman spectrogram; based on the original Raman spectrogram, using a wavelet transform algorithm to perform de-noising processing, reducing background interference, using a principal component analysis technology to extract characteristic peaks, and generating a heavy metal preliminary prediction result; based on the preliminary heavy metal prediction result, constructing a heavy metal concentration prediction model by applying a partial least squares regression algorithm, performing quantitative analysis, evaluating prediction accuracy by adopting a cross validation technology, and generating a heavy metal actual concentration result; and based on the actual heavy metal concentration result, comparing with a water quality safety standard, evaluating a pollution condition, and generating a water quality heavy metal pollution detection report. The technical scheme provided by the invention has high sensitivity, can efficiently denoise and accurately predict, and provides a scientific means for monitoring and treating heavy metal pollution of water.

The invention discloses a PCB (printed circuit board) back drilling stub length detection device and method, and belongs to the technical field of PCB detection, the PCB back drilling stub length detection device comprises a broadband light source, the output end of the broadband light source is connected with an optical fiber coupler, and one end, deviating from the broadband light source, of the optical fiber coupler is respectively connected with a first optical fiber collimator and a second optical fiber collimator; the first optical fiber collimator is provided with a lens and a reflector on an optical transmission path; the second optical fiber collimator is provided with a galvanometer on a light transmission path, and a scanning lens is arranged in the light emitting direction of the galvanometer; and the optical fiber coupler is also connected with a spectrograph. On the basis of the low-coherence light interference principle, the PCB back drilling stub length detection device is designed, the output power and the output bandwidth of a broadband light source are correspondingly adjusted, the insertion loss of an optical fiber coupler is controlled, the collection rate of a spectrograph is adjusted, finally, the axial resolution reaches 5 micrometers, the transverse resolution reaches 10 micrometers, and the requirements that the diameter is smaller than 0.1 mm, and the detection precision is larger than 0.1 mm can be met. And detecting the stub length of the deep micropore with the depth of less than 10mm.

The invention relates to the technical field of new energy aluminum alloy precision casting multi-modal quality monitoring, in particular to a new energy aluminum alloy precision casting multi-modal quality monitoring device and method. According to the technical scheme, the new energy aluminum alloy precision casting multi-mode quality monitoring device comprises a quality monitoring device body, an infrared thermal imager probe, a germanium single crystal protection lens, an integrated spectrometer probe debugging port, an acoustic detection microphone array and a honeycomb acoustic shielding cover. An infrared thermal imager probe is arranged on one side of the quality monitoring device main body, and a germanium single crystal protection lens is arranged on the outer side of the infrared thermal imager probe; synchronous acquisition and fusion analysis of multi-physical field data are realized by integrating six modes of spectrum, infrared thermal imaging, vibration, machine vision, acoustics and pressure deformation, and meanwhile, when the shrinkage risk is predicted by the infrared thermal imaging, a die-casting process compensation mechanism is automatically triggered to kill defects in the germination stage, so that the defect rate is greatly reduced.

The invention discloses a self-adaptive full-band efficiency correction method for an LIBS (laser-induced breakdown spectroscopy). The method comprises the following steps: for each laser pulse, inputting collected spectral data into a trained physical information deep network to obtain a current plasma temperature; when the current plasma temperature is not in a preset ideal temperature interval, predicting by using a physical information deep network to obtain an optimal laser energy adjustment sequence; wherein energy adjustment is performed according to the optimal laser energy adjustment sequence, so that a future temperature sequence can be converged to a preset ideal temperature interval; controlling an energy controller of the laser to emit a next laser pulse according to the optimal laser energy adjustment sequence to obtain a stable plasma; and after the stable plasma is obtained, collecting target spectral data, and outputting a full-band efficiency calibration curve according to the target spectral data. And high-precision and high-robustness full-band efficiency correction can be realized in a complex and changeable real environment.

The invention provides an intelligent sorting method and system for radioactive substances. The method comprises the following steps: synchronously detecting surface element composition and radiation intensity of a radioactive substance through an X-ray fluorescence spectrometer, and constructing a spatial difference matrix of element abundance distribution and a radiation gradient topological graph; the three-dimensional coordinates, the pressure threshold value and the shape adaptation parameters of the target grabbing position are determined on the basis, the curvature radius of the clamping jaw deformation contour is dynamically adjusted, and the error of the dynamic geometric envelope and the contour template is converged to be within the threshold value; finally, when the clamping jaw reaches a target position, the area of the heat shrinkage material is activated to be heated according to the radiation intensity abrupt change boundary coordinates, a sealed isolation layer synchronously expanded with the dynamic geometric envelope is generated, and safe grabbing and sealed isolation of radioactive substances are achieved. According to the technical scheme, accurate grabbing of radioactive substances, error self-adaptive compensation and synchronous isolation of radiation leakage can be achieved, and the sorting safety and efficiency are improved.

The invention belongs to the technical field of ocean water color and ocean ecology, and relates to a near-field actual measurement data set construction method and system for ocean net primary productivity, and the method comprises the steps: collecting profile data observed by a biogeochemical buoy BGC-Argo; s2, respectively performing data quality control processing on the Chl-a profile data and the bbp (700) profile data to obtain profile data after quality control; s3, based on the profile data after quality control, matching remote sensing parameters of a medium-resolution imaging spectrometer (MODIS); wherein the remote sensing parameters comprise photosynthetically active radiation (PAR) and a diffusion attenuation coefficient Kd (490) at a 490nm wave band; s4, on the basis of the profile data after quality control, PAR and Kd (490), utilizing a CbPM model to calculate marine net primary productivity NPP profile data; and S5, carrying out integration on the NPP profile data in a true light layer depth range to obtain NPP data of water column integration. The method can economically and efficiently obtain a large number of NPP samples actually measured in the near field, and makes up for the deficiency of existing actually measured data.

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.

The invention belongs to the technical field of spectral measurement, and particularly discloses a non-contact high-temperature detector based on a visible light spectrometer and a full-spectrum method, which comprises a full-spectrum collection system and a spectral analysis system. The output end of the full-spectrum collection system is connected with the input end of the spectral analysis system; the light splitting module is used for acquiring spontaneous radiation light of a to-be-detected target and carrying out dispersion light splitting on the radiation light to obtain visible light full-band spectral data; and the spectral analysis system is used for analyzing and processing the visible light full-band spectral data to obtain the spectrum of the to-be-detected target, and obtaining the temperature based on the spectrum of the to-be-detected target, so that the precision of temperature detection can be remarkably enhanced.

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.

An on-chip mid-infrared micro-ring resonant cavity microfluidic spectrometer is integrated on a substrate material and comprises a spot size converter, an optical coupler, a microfluidic module, a micro-ring resonant cavity, a miniature thin-film resistance heater, a sequential control power supply module, an optical filtering system and a photoelectric detector array. Selective filtering is performed on an input optical signal, and the flow and flow velocity of liquid or gas to be detected are controlled by using the microfluidic module, so that selective absorption of spectral components of the liquid or gas to be detected is realized. In addition, the invention also discloses a mid-infrared integrated optical chip micro-fluidic multiphase detection device comprising the spectrometer and a detection method thereof, the device also comprises a pumping and reference light source module and an on-chip mid-infrared frequency comb generation module, a broadband frequency comb is generated as a light source, a photoelectric detector array is used for collecting signals, and the detection precision is improved. The detection and inversion of the type and concentration of multi-component liquid or gas to be detected are realized, and the on-chip, real-time and micro detection of multi-component substances is realized.

The invention relates to the field of farmland ecological protection, in particular to a salinization farmland protection forest configuration optimization system and method, and the system comprises a salinization monitoring module, an edge calculation module, a database, a three-dimensional model module, a model optimization module and a configuration scheme optimization module. The salinization monitoring module acquires data through an unmanned aerial vehicle and a hyperspectral imaging spectrometer and determines a soil salinity distribution state, the edge calculation module receives the data and carries out protection forest configuration model calculation, the database stores a calculation model and soil salinity and vegetation growth state data, and the three-dimensional model module generates a three-dimensional spatial-temporal model of forest growth. The model optimization module utilizes deep reinforcement learning to optimize a soil salinity and underground water level simulation model, the protection forest configuration effect is improved, the configuration scheme optimization module generates an optimal protection forest configuration scheme, a complex interaction process is accurately represented, and an efficient and accurate technical means is provided for ecological protection of salinized farmland.

The invention belongs to the technical field of environmental monitoring, and particularly relates to a super-resolution fluorescence imaging analysis method based on hypersensitive fluorescent quantum dots. The quantum dots have high water solubility and stability, and can emit narrow-bandwidth fluorescence due to unique optical properties of the quantum dots. According to the invention, a quantum dot luminescent material is adopted to construct an ultra-high resolution microscope system which can be used for observing composite behaviors between micropollutants and quantum dots on a microscopic scale, and a three-dimensional fluorescence microspectrometer and a computer vision algorithm are integrated; the whole reaction process is deduced according to the evolution of the three-dimensional fluorescence spectrum between the micro-pollutants and the quantum dots in different space (concentration), time (reaction process) and chemical dimensions, and a multi-dimensional fingerprint spectrum is formed according to the whole reaction process and is used for identifying and tracing the micro-pollutants. The method has the advantages of being high in detection speed, high in fingerprint performance and less in interference of background factors.

The invention discloses a paclitaxel drug resistance SERS (Surface Enhanced Raman Scattering) substrate and a detection method. Belongs to the technical field of drug resistance detection. The SERS substrate is mixed with ultrapure water after centrifuging a silver nanoparticle-sodium citrate suspension, and the mixture is dropwise added to a silicon wafer and dried to form a coffee ring structure. During detection, cancer tissue crushing liquid is dropwise added to the center of the substrate, SERS signals are collected through a Raman spectrometer and compared with a pre-established drug resistance / sensitivity spectrum database, and drug resistance is judged according to characteristic peaks at 820 cm <-1 >, 1180 cm <-1 >, 1270 cm <-1 > and 1450 cm <-1 >. The method is easy and convenient to operate, short in detection time (within 10 minutes), high in sensitivity and suitable for rapid screening of paclitaxel drug resistance of breast cancer patients.

The invention discloses a traceable cavity ring-down spectrometer system with a self-calibration function, and is applied to the technical field of gas concentration detection. The device comprises an optical cavity ring-down main body, a dynamic generation module and a reference analysis module which are connected in sequence, wherein the optical cavity ring-down main body comprises a laser light source, a beam splitter, an optical fiber isolator, a lens, a first reflecting lens, a first aluminum ring, a sample cell, a second aluminum ring, a cross shaft type universal coupling control device and a second reflecting lens which are arranged along a laser light path; the dynamic generation module comprises a high-purity gas inlet, a gas purifier, a dynamic generation device, a standard gas outlet and a three-way electromagnetic valve which are arranged along a gas path; the reference analysis module comprises an instrument standard gas inlet, a reference analyzer and a standard gas storage box which are arranged along the gas path. According to the method, the influence of instrument drift on analysis data caused by the use environment and instrument part loss of the online instrument is avoided, and the accuracy and the quantity value traceability of the instrument analysis data are guaranteed.

Aspects relate to a compact and low-cost gas analyzer that can be used for different types of gas analysis, such as air quality analysis. The gas analyzer can include a light source, a gas cell configured to receive a sample (e.g., a gas under test), a spectral sensor including a spectrometer and a detector, and an artificial intelligence (AI) engine. Light can enter the gas cell and interact with the sample to produce output light that may be measured by the spectral sensor. The resulting spectrum produced by the spectral sensor may be analyzed by the AI engine to produce a result. The gas analyzer further includes a self-calibration component configured to enable calibration of the sample spectrum to compensate for spectral drift of the spectral sensor.

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 resolution-customizable micro spectrometer based on the transverse dispersion metasurface comprises a dispersion metasurface array structure and a focal plane pixel array, and the dispersion metasurface array structure comprises a plurality of dispersion metasurface sub-arrays which are distributed in an array mode and used for preliminary spectrum decoupling and directional convergence. The dispersion metasurface subarray comprises a plurality of dispersion metasurface units and all-dielectric substrates thereof, the dispersion metasurface units are nano-columns with four-fold symmetry, the nano-columns are periodically arranged, and the phase of transmission light is dynamically regulated and controlled according to the frequency omega of incident light. The focal position (x ', y') of the transmission light on the focal plane is in a linear mapping relation along with the change of the omega; the focal plane pixel array comprises a multi-element plane array composed of a plurality of pixels, and the multi-element plane array is in pixel-level registration with the dispersion metasurface sub-array. According to the invention, pixel-level precise condensation is realized, crosstalk is effectively inhibited, the detection precision is improved, and real snapshot spectral imaging is realized.

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.

The invention provides probe type mineral multi-element laser-induced breakdown spectroscopy detection equipment. The equipment is characterized in that a sealed quartz optical window is mounted on the side surface of a probe box; the laser faces the sealed quartz optical window and emits laser pulses to the detected mineral; the convex surface of the quartz crescent focusing lens faces the laser, the concave surface of the quartz crescent focusing lens faces the sealed quartz optical window, and laser pulses are focused on the surface of detected mineral to generate plasma; the dichroscope is used for reflecting the plasma emission light to the double-lens group; the emitted light is converged through the double-lens group to form a plasma image with weakened chromatic aberration; the spectrograph is coupled with the plasma image through an optical fiber mechanism and records spectrums of different wavebands; therefore, after the focus point of the reflected light of the crescent focusing lens is pushed far to the laser, the optical element is prevented from being damaged; the imaging chromatic aberration of a plasma image is reduced by the double-lens group; the optical fiber mechanism balances spectral intensities of different wavebands and suppresses a continuous spectrum through spatial resolution.

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 the field of optical detection, in particular to spectrum detection equipment for measuring the thickness of a coating film, and the spectrum detection equipment comprises a feeding unit which comprises an erecting assembly; the erecting assembly is used for placing a to-be-detected coating optical element, a turntable in the feeding unit can transfer the coating optical element to the position of the measuring unit, and two spectrum detectors in the measuring unit can measure the coating thickness of two surfaces of the coating optical element at the same time; compared with an existing measuring device, the designed spectrograph coating thickness measuring device has the advantages that firstly, the coating thicknesses on the two surfaces of a coating optical element can be measured at the same time at a time in the aspect of efficiency, the efficiency is doubled, and the spectrograph coating thickness measuring device is suitable for large-batch coating thickness measuring tasks; in the aspect of accuracy, when the coating thicknesses on the two surfaces of the coating optical element are measured at the same time, the coating optical element does not need to be taken out, turned over and then fed, the problem of turn-over errors is avoided, and the coating thickness of each surface is accurately measured.

The invention provides a food pollution detection method based on multi-wavelength spectrophotometry, and the method comprises the steps: transmitting light in a series of wavelength ranges to a food sample through a tunable multi-wavelength light source system, generating spectral response, collecting the spectral response through a high-resolution spectrometer, and forming a multi-dimensional spectral image, a deep learning algorithm is used for analyzing, identifying and distinguishing subtle spectral differences between natural components and potential pollutants in a food sample, a preliminary identification result is obtained, a self-adaptive wavelength selection mechanism is implemented, wavelength output of a light source is dynamically adjusted, spectral response data is obtained, and the spectral response data is compared with a preset food safety standard database. According to the technical scheme provided by the invention, natural components and potential pollutants in a food sample are efficiently and accurately recognized, and the sensitivity, specificity and accuracy of pollutant detection are remarkably improved.

The invention discloses a prospecting method and a prospecting system for mainly extracting soil micro-fine particles in a shallow coverage area, and the prospecting method comprises the following steps: separating a micro-fine particle part from a soil sample by adopting a wet screening method according to a preset particle size range to obtain a target micro-fine particle sample; the method comprises the following steps: for a target micro-fine particle sample, acquiring chemical component data through an X-ray fluorescence spectrophotometer, and determining the content and distribution characteristics of main elements in the sample; analyzing the mineral composition of the target micro-fine particle sample by adopting an X-ray diffractometer, and identifying the types and relative contents of main minerals in the sample; determining the particle size distribution of the target micro-fine particle sample through a laser particle size analyzer to obtain the proportion information of particles with different particle sizes in the sample; according to the geophysical data, gravity, magnetic force and electrical parameters of the target area are extracted, and a geophysical feature model is established; and carrying out data fusion on the geochemical features and the geophysical feature model, and extracting key feature variables in multi-source information by adopting a principal component analysis method.

The utility model discloses a single-point infrared temperature measuring device for a hot end part of an aero-engine, and relates to the field of temperature in-situ detection of engine blades. The device mainly comprises an optical probe with a cooling function, a spectrograph, a photoelectric detector, a high-precision motion positioning platform and a data processing system. The front end of the optical probe reflects radiation energy on the surface of the blade into the collecting lens set through the reflector, the spectrograph divides spectral energy into three different wave bands, signals are collected through the photoelectric detector and the high-speed data collector, and temperature information is obtained through calibration and analysis. The high-precision motion positioning platform adopts a sliding table and a rotating mechanism, and can control the adjustment of the angle of a reflector and the stretching of an optical probe, thereby achieving the precise measurement of the temperatures of different target positions. The whole device is compact in structure, and has the characteristics of high measurement precision, flexible position, low energy loss and the like, and can resist high temperature of 1500 DEG C.

The invention discloses an atomic absorption spectrometer for new material detection, and relates to the technical field of atomic absorption spectrometers, the atomic absorption spectrometer comprises a spectrometer body; a liquid supply mechanism is arranged below the front surface of the spectrograph body, the liquid supply mechanism comprises a liquid supply bearing table, and a liquid supply rotating disc is rotationally arranged in the liquid supply bearing table through a motor; wherein an absorption mechanism is arranged at the lower part in the spectrograph body, the absorption mechanism comprises a liquid taking sliding plate, and a liquid taking corrugated pipe is arranged in the middle of the front end of the liquid taking sliding plate in a penetrating manner. According to the atomic absorption spectrometer for new material detection, a liquid supply bearing table drives a liquid supply rotating disc to rotate, a standard reagent bottle and a solution reagent bottle are borne, a liquid taking sliding plate and a lifting strip plate which slide forwards drive a liquid taking corrugated pipe to move and then descend, and the liquid taking corrugated pipe ascends and descends in a reciprocating mode during rotation; therefore, repeated operation of calibration and detection during detection is realized, and the accuracy of atom detection is improved.

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 provides an imaging spectrometer motion compensation imaging model construction method, an imaging model and a device, and relates to the technical field of space remote sensing. The method comprises the following steps: establishing a satellite orbit model, and defining a plurality of coordinate systems such as a detector coordinate system and a spectrometer imaging coordinate system and a conversion relation thereof; constructing a detector-scanning mirror-lunar surface ideal geometric mapping model based on the load optical parameters and a ray tracing method; determining the relation between the rotation angle of the scanning mirror and imaging spectrum view field positioning by using a reflecting prism conjugation theory; a quantitative relation is established by combining parameters such as satellite orbits and position postures, and finally a motion compensation imaging model is established. According to the method, the influence of the on-orbit error on the compensation imaging model is analyzed, and the error is used as an uncertainty component to be coupled into the model. According to the method, the problems of low model precision, neglect of influence of orbit observation parameters on imaging and the like in the prior art are solved, high-precision motion estimation and compensation can be realized, and the quality of data acquired by an imaging spectrometer is remarkably improved.

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.