52 results about "High resolution spectra" patented technology

The invention relates to the technical field of spectral analysis, in particular to a fabric fiber component high-resolution spectral rapid analysis method which comprises the following steps: S1, acquiring three-dimensional shape data of a fabric surface through laser scanning, and identifying a fiber arrangement direction and a surface curvature characteristic based on the three-dimensional shape data; s2, dynamically adjusting the incident angle and the focusing depth of a spectrum probe according to the fiber arrangement direction and the surface curvature characteristics identified in S1, and selecting a corresponding spectrum excitation mode; s3, performing feature extraction on the multi-mode spectral data acquired in the S2, and fusing feature vectors of different spectral modes through a deep learning algorithm; s4, analyzing the fused feature vector based on a transfer learning model, and outputting a fiber component type and a proportion thereof; and S5, associating the component data output in the step S4 with space coordinates, and generating a component distribution visualization map. By dynamically adjusting the spectrum probe, fusing multi-mode spectrum data and the like, the analysis precision and speed are remarkably improved.

The invention provides an underwater target identification method and system based on 4K visible light polarization imaging, and relates to the technical field of underwater target identification. High-resolution spectral intensity information and polarization physical characteristics of a target are synchronously captured by using a pixel-level registration RGB and polarization four-dimensional light field tensor coding technology; the limitation of information loss of single-mode data in a low-illumination or high-turbidity scene is overcome; the polar coordinate symmetry design of the annular direction sensitive convolution kernel is combined with the polarization degree matrix decomposition technology of the Fresnel reflection law to accurately quantify the optical reflection characteristic difference of the material; based on a cross-modal attention mechanism, dynamically learning a correlation weight of a spatial feature and a polarization feature, and strengthening a joint response of a target edge contour and an internal texture; a lightweight recognition network architecture is adopted, a polarization sensitive convolution kernel and a dynamic channel re-parameterization module are integrated, parallel efficient reasoning of target position, category and material information is achieved, and accurate recognition of an underwater target is achieved.

The invention discloses a calibration device with a spectrum self-calibration function and a high-resolution spectrum calibration method thereof. The device comprises a narrow-band light source, a broadband light source, an optical fiber isolator, a coupler, an interference system, a multi-way switch, an FP (Fabry-Perot) cavity, a collimator, an orthogonal dispersion system and a computer, wherein the orthogonal dispersion system consists of a cylindrical lens, a reflector, a virtual phase array, a grating, a focusing lens and an industrial camera; according to the device, different light source paths are gated, FP cavity modulation and orthogonal dispersion system light splitting are utilized, and an industrial camera is combined to receive light signals. According to the method, the mapping relation between pixels and wavelengths can be established, the two-dimensional spectrum is compressed into the one-dimensional calibration spectrum through light intensity modulation and normalization processing, the calibration process of the orthogonal dispersion system is simplified, and the measurement precision is improved; and system drift can be compensated in real time through self-checking calibration, and the reliability of a measurement result is ensured, so that accurate calibration and measurement of a high-resolution spectrum can be realized.

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 method for measuring fan blade root stress based on a fiber bragg grating sensor. According to the method, 6-10 key measurement points are selected in a blade root area of a fan blade, a pair of FBG sensors is installed at each measurement point, one FBG sensor is used for stress measurement (affected by strain and temperature at the same time), the other FBG sensor is used for temperature compensation, and decoupling of temperature and strain signals is achieved. The system adopts a single-mode optical fiber, a broadband light source (the wave band is 1525-1565 nm, and the power is 10-20 mW) and a high-resolution spectrum analyzer (the resolution is smaller than or equal to 1 pm, and the sampling rate is larger than or equal to 100 Hz or 1 kHz) to collect optical signals reflected by an FBG sensor in real time, measured wavelength shift is converted into accurate strain data through temperature compensation and a strain calculation formula, and the optical signals are transmitted to the FBG sensor. And calculating a stress value by combining the Young modulus and Poisson's ratio of the material. The method has the advantages of being high in precision, high in real-time performance, resistant to electromagnetic interference and suitable for seaborne, high-altitude and other severe environments, and reliable data support can be provided for dynamic stress monitoring, fatigue life prediction and fault early warning of the fan blade.

The invention discloses a one-dimensional ultra-wide field-of-view ultra-high spectral resolution dispersion coherent imaging spectrometer, which belongs to the technical field of spectral imaging, and comprises a first microlens array used for obtaining incident light of a one-dimensional ultra-wide field-of-view in a horizontal plane; the plurality of optical fibers are used for transmitting incident light of a one-dimensional ultra-wide field of view; the second micro lens array is used for collimating incident light from each optical fiber into broadband parallel light beams; the grating beam splitter interferometer is used for dispersing the broadband parallel light beams into a plurality of narrow-band parallel light beams with different propagation directions; the cylindrical lens is used for converging the two paths of coherent light of each narrow-band parallel light beam to a target block of the detector, and converging the narrow-band parallel light beams with different propagation directions to different target blocks respectively; and the detector is used for obtaining a continuous broadband ultra-high resolution spectrum according to the two paths of coherent light received by each target block. According to the invention, a one-dimensional ultra-wide field of view is obtained in a horizontal plane, and ultra-high spectral resolution can be obtained.

The utility model provides a high-resolution spectral confocal measurement device, which includes a light source, a fiber coupler, a spectral confocal lens, a spectral analysis unit and a data processing unit. The spectral confocal lens is arranged between the fiber coupler and the sample to be measured. The spectral confocal lens includes a first lens, a second lens, a third lens, a fourth lens, a fifth lens and a sixth lens arranged in sequence. The first lens is a double concave lens, the second lens is a meniscus lens, the third lens is a plano-convex lens, the fourth lens is a double-cemented lens, the fifth lens is a meniscus lens, and the sixth lens is a meniscus lens. With such an arrangement, the spectral confocal lens is improved from multiple aspects such as expanding the incident light beam, correcting aberrations, reducing spherical aberrations, and correcting coma and chromatic aberration, thereby greatly improving the resolution of the lens. The light source is further connected to the spectral confocal lens through a fiber coupler, so that the entire device has a compact structure and is easy to integrate and install.

The invention discloses an optical fiber sensing precision enhancement method for high-resolution spectrum subdivision. According to the invention, the spectrum subdivision algorithm based on Fourier transform is applied, so that spectrum subdivision and resolution enhancement are realized, and the optical fiber sensing precision enhancement method based on high-resolution spectrum subdivision has remarkable beneficial effects on the whole optical fiber sensing precision enhancement method based on high-resolution spectrum subdivision. Fourier transform can convert a time domain signal into a frequency domain signal, high-frequency noise and low-frequency interference are effectively removed through frequency domain filtering, and frequency components in a target spectral range are reserved, so that the purity of the spectral signal is improved. And the filtered frequency domain signal is restored into a time domain signal through inverse Fourier transform, so that the integrity of the signal is kept. Furthermore, the time domain signals are subdivided through a linear interpolation algorithm, the data point density is increased, and the spectral resolution is remarkably improved. And a more accurate and detailed data basis is provided for recognition and analysis of subsequent characteristic spectrums, so that the measurement precision and reliability of the optical fiber sensor are enhanced.

The invention relates to the technical field of mineral analysis, and discloses a mineral trace element detection method which comprises the following steps: S1, sample preparation; s2, spectrum acquisition; s3, processing spectral data; s4, selecting a characteristic wavelength; s5, constructing a spectral analysis model; s6, model training and verification; s7, trace element content prediction; and S8, outputting a result. According to the mineral trace element detection method, a large amount of spectral data can be rapidly collected by adopting the high-resolution spectrometer and the Fourier transform infrared spectrum technology, background noise is removed and the data quality is improved through the preprocessing step, the detection speed is increased, and the detection accuracy is improved. The method also improves the accuracy of a detection result through precise characteristic wavelength selection and optimization of a support vector machine algorithm, and particularly guarantees the generalization capability and prediction precision of the model through five-fold cross validation and grid search optimization of model parameters, thereby improving the detection efficiency while guaranteeing the accuracy and reliability of the detection method.

The invention discloses a spectral super-resolution model training method, a spectral super-resolution measurement method and a spectral super-resolution measurement device. The method comprises the following steps: acquiring multiple groups of low-resolution spectral data and corresponding high-resolution spectral data; constructing a spectral super-resolution model fusing the three-dimensional convolutional layer and the spectral physical constraint term; and training the spectral super-resolution model by taking each group of low-resolution spectral data as input and taking the group of high-resolution spectral data as a label as a training sample in sequence until an error between the high-resolution spectral data output by the spectral super-resolution model and the high-resolution spectral data as the label meets a preset threshold value. Through the spectrum super-resolution model, the efficiency of spectrum measurement can be improved in a disguised manner, and the accuracy of parameter inversion can be ensured.

Methods and systems for using multiple hyperspectral cameras sensitive to different wavelengths to predict characteristics of objects for further processing, including recycling, are described. The multiple hyperspectral images can be used to predict higher resolution spectra by using a trained machine learning model. The higher resolution spectra may be more easily analyzed to sort plastics into a recyclability category. The hyperspectral images may also be used to identify and analyze dark or black plastics, which are challenging for SWIR, MWIR, and other wavelengths. The machine learning model may also predict the base polymers and contaminants of plastic objects for recycling. The hyperspectral images may be used to predict recyclability and other characteristics using a trained machine learning model.

The invention discloses a temperature-pressure-resistant vibration methane carbon isotope detection system for oil and gas logging, which belongs to the technical field of oil and gas logging and comprises a gas sample pretreatment module, an optical sensing module, a driving and temperature control module and a core control and algorithm module. The core control module is realized by an FPGA (Field Programmable Gate Array) and is integrated with a self-adaptive multi-resolution scanning and compressed sensing reconstruction algorithm. The method comprises the following steps: performing current segmented scanning and wavelength modulation on the laser; light path anti-vibration coupling is realized through closed-loop control of the MEMS galvanometer; acquiring sparse sampling spectrum data; reconstructing a high-resolution spectrum by using compressed sensing; and inversing CH4 and CH4 concentrations by adopting Voigt linear fitting, and calculating a delta C value. The precision, the speed and the long-term stability of methane carbon isotope detection in a logging site temperature-pressure vibration coupling disturbance environment are remarkably improved.

The utility model discloses a Lamberg distribution tester which comprises an instrument cabin, a diaphragm is arranged in the instrument cabin, a spectrograph is arranged on one side of the diaphragm and connected with the diaphragm through an optical fiber, a rotating table is arranged on the other side of the diaphragm, a light-emitting device is arranged on the rotating table, and the rotating table drives the light-emitting device to rotate. And light emitted by the light-emitting device passes through the diaphragm and then is input into the spectrograph. Furthermore, a calibration light source is arranged on one side of the diaphragm, the calibration light source is connected with the diaphragm through an optical fiber, and light emitted by the calibration light source passes through the optical fiber, penetrates through the diaphragm and reaches a light emitting point of the light emitting device. In conclusion, according to the Lamberg distribution tester provided by the embodiment of the invention, through the innovative designs such as the subdivision design, the high-precision diaphragm, the high-resolution spectrometer and the rotatable light-emitting device, the stability, flexibility and accuracy of a test system are remarkably improved, and an efficient and reliable solution is provided for the test of light source characteristics.

The application provides an underwater target recognition method and system based on 4K visible light polarization imaging, and relates to the technical field of underwater target recognition.The application uses pixel-level registration RGB and polarization four-dimensional light field tensor encoding technology to synchronously capture high-resolution spectral intensity information and polarization physical characteristics of a target, overcomes the limitation of information loss of single modal data in low-light or high-turbidity scenes, designs polar coordinate symmetry of a ring-shaped direction-sensitive convolution kernel, combines polarization degree matrix decomposition technology of the Fresnel reflection law, accurately quantifies the optical reflection characteristic difference of a material, dynamically learns the correlation weight of spatial features and polarization features based on a cross-modal attention mechanism, strengthens the joint response of target edge contours and internal textures, adopts a lightweight recognition network architecture, integrates a polarization-sensitive convolution kernel and a dynamic channel reparameterization module, realizes parallel and efficient inference of target position, category and material information, and realizes accurate recognition of underwater targets.

The invention discloses a spectrum super-resolution method and system based on an FP cavity and deep learning, and the method comprises the steps: S1, carrying out the initialization of spectrum collection, and selecting light with a specific wavelength after the light is acted with a target detection object; s2, performing photoelectric conversion and digitization to generate low-resolution original discrete spectrum data of corresponding wavelengths; s3, continuous spectrum scanning is carried out, and original discrete spectrum data collection of the whole target wave band is completed; and S4, performing super-resolution spectrum reconstruction, and judging whether cyclic reconstruction is performed or not based on a reconstruction data quality evaluation result until the quality is qualified. According to the method, an accurate mapping model from a low-resolution spectrum to a high-resolution spectrum is established through a pre-trained deep neural network, and an original spectrum which is collected by an FP cavity and is limited by the theoretical limit optical resolution of the FP cavity can be reconstructed into a super-resolution spectrum of which the resolution remarkably exceeds the theoretical limit. The problem that the resolution of an FP cavity in a long-wave region is sharply reduced is effectively solved, and the full-wave-band uniform high resolution is realized.

A method for detecting structural variations in chromosomes by labeling single-stranded chromatids with different colored probes is disclosed. The hybridization patterns of the labeled probes generate spectral profiles that enable high-resolution detection of structural variations, facilitating the distinction between benign and deleterious structural variations. Furthermore, the spectral profiles provide information about complex structural variations that may result from more than one rearrangement of chromosomal segments. The spectral profiles can be used to generate data tables, which can then be subjected to node analysis to identify structural features of interest.

The invention relates to the technical field of marine environment monitoring, in particular to a marine oil spill monitoring method and system based on a crude oil spectrum. Comprising the following steps: S1, identifying N marine oil spill positions by using a fuzzy reasoning model, and distributing monitoring points for the N marine oil spill positions to form a first monitoring sequence; s2, K important oil spill positions and monitoring points corresponding to the important oil spill positions are optimized through a genetic algorithm, a second monitoring sequence is formed, and K is smaller than N and is a positive integer larger than or equal to 1; s3, calculating the time when the crude oil reaches the sea surface and marking a path; a high-resolution spectrometer is used for collecting spectral data in visible light, near-infrared and middle-infrared wave bands, and features are screened after preprocessing. According to the method, the ocean oil spill monitoring path is optimized through fuzzy reasoning and a genetic algorithm, spectral data are predicted in combination with a Transform model, the path and the model are dynamically corrected, and the monitoring precision and the response efficiency are improved.

The present invention relates to the field of optical lenses, and provides a mid-wave infrared spectral imaging lens. From the object surface to the image surface, it sequentially includes a first lens, a second lens, a third lens, a Dewar window, and a filter, which are arranged coaxially; the first lens, the second lens, and the third lens are all aspherical lenses; the first lens has a positive optical power, and the focal length of the first lens satisfies 245 mm ≤ f1 ≤ 250 mm; the second lens has a negative optical power, and the focal length of the second lens satisfies -30 mm ≤ f2 ≤ -25 mm; the third lens has a positive optical power, and the focal length of the third lens satisfies 20 mm ≤ f3 ≤ 25 mm. The solution of this application reduces the number of lenses by introducing aspherical lenses, and solves the defect that the existing mid-wave infrared spectral imaging lens is difficult to simultaneously meet the requirements of large field of view, high energy utilization rate, and high-resolution spectral imaging.

The present invention provides a stimulated Brillouin spectrum analysis device and method, the device includes an optical circulator, a stimulated Brillouin medium, a probe light source, a double-sideband IQ modulator, an optical isolator, a dense wavelength division multiplexer, an up-down frequency conversion detector and a data acquisition board, the light to be measured is injected into the stimulated Brillouin medium through the optical circulator, the probe light is modulated by the double-sideband IQ modulator and enters the stimulated Brillouin medium, the modulated probe light and the light to be measured generate characteristic frequency signals distributed on both sides of the probe light frequency based on the stimulated Brillouin effect, the optical signal collected by the up-down frequency conversion detector is demodulated, the stimulated Brillouin complex gain is calculated, and the information of the light to be measured is obtained by inversion. Through this solution, high-resolution spectrum analysis without scanning can be realized, the dependence on the Brillouin frequency offset in the optical fiber is eliminated, and the real-time performance of stimulated Brillouin spectrum analysis is improved.

Molecular rotation resonance (MRR) spectroscopy is a structure-specific high-resolution spectroscopy technique that can identify chemical species, including enantiomers, that cannot be distinguished by other analytical techniques. In MRR spectroscopy measurements, a gas phase sample is injected into a vacuum chamber in which the gas phase sample is excited with millimeter wave or microwave radiation, and in response, the gas phase sample emits a free induction pulse (FID). The spectrum of the FID pulses provides information about the chemical structure of the sample. In MRR ratio method measurements, the sample is irradiated simultaneously by two excitation pulses at different frequencies (e.g., broadband pulses and narrowband pulses of different frequency bands or narrowband pulses at different frequencies). The pulses stimulate simultaneous or overlapping FID emissions of different components of the sample. The spectra of these FID emissions are compared, resulting in a ratio of the components in the sample.

An anti-interference image reconstruction method, apparatus, medium, and electronic device are disclosed, relating to the fields of optoelectronic imaging and target detection technology; achieving anti-fish scale light and anti-backlight imaging under complex lighting environments. The anti-interference image reconstruction method includes: acquiring the infrared radiation light field of the target scene through an infrared optical lens; filtering interference light from the infrared radiation light field using a metasurface modulation module; acquiring multi-dimensional light field information after passing through the metasurface modulation module using an infrared imaging detector; the metasurface modulation module employs GSST phase change material, controlling the infrared spectral band and polarization state through switching between crystalline and amorphous states; and reconstructing the acquired multi-dimensional light field information using a multi-dimensional light field reconstruction module to obtain a high-resolution spectral image.

Methods and software applications for transmitting high-resolution spectral curve data to a tinter for generating a tint formula usable to custom-tint a base paint or coating to match the color of a sensed surface. The high-resolution spectral curve data is derived from low-resolution or wideband spectral data obtained via a low resolution or wideband spectrophotometer. Additional user information, order information, or location information may be transmitted to the tinter.

The invention discloses a 250-1700 nanometer six-wave-band switchable high-resolution thin-plate spectrometer, and belongs to the technical field of spectral measurement, the 250-1700 nanometer six-wave-band switchable high-resolution thin-plate spectrometer comprises a plurality of measurement assemblies which are sequentially arranged in the x direction, each measurement assembly comprises a micro lens, an optical filter, a plane transmission grating and a detector, the micro lens collimates incident light into parallel light beams, and the parallel light beams are transmitted to the optical filter; the optical filter transmits light beams in a specific wave band range in the parallel light beams; the plane transmission grating diffracts the filtered parallel light beams to generate primary diffraction light beams; a pixel array of the detector is divided into a plurality of blocks arranged in the y direction, and high-resolution spectral information, collected by the micro lens, of a detected object in a specific wave band is obtained in real time according to target blocks irradiated by first-order diffraction light beams with different wavelengths in the specific wave band. According to the spectrograph, the combination of all the measuring components can cover the ultra-wide wave band of 250-1700 nanometers, and switchable independent measurement or simultaneous measurement of multiple wave bands is supported.

This invention provides a food contamination detection method based on multi-wavelength spectrophotometry. In this embodiment, a tunable multi-wavelength light source system emits light within a series of wavelengths onto a food sample, generating a spectral response. This spectral response is collected using a high-resolution spectrometer to form a multi-dimensional spectral image. A deep learning algorithm is then used to analyze and identify subtle spectral differences between natural components and potential contaminants in the food sample, obtaining preliminary identification results. An adaptive wavelength selection mechanism is implemented to dynamically adjust the wavelength output of the light source, obtaining spectral response data. This data is then compared with a pre-set food safety standard database to generate a food safety assessment report. The food safety assessment report includes contaminant types and concentration distribution maps. The technical solution provided by this invention enables highly efficient and accurate identification of natural components and potential contaminants in food samples, significantly improving the sensitivity, specificity, and accuracy of contaminant detection.

The invention provides a rhododendron species identification method and device, terminal equipment and a readable medium, and is suitable for the technical field of data processing, and the method comprises the steps: obtaining a low-resolution spectral image of a to-be-identified rhododendron; performing spectral feature extraction on the low-resolution spectral image to match a plurality of high-resolution spectral features with the highest similarity, and calculating the weighted votes of the rhododendron species corresponding to the plurality of high-resolution spectral features; and determining the type with the highest weighted votes as the type of the rhododendron to be identified. According to the invention, based on the low-resolution spectral image of the to-be-identified azalea, through spectral feature extraction and matching of a plurality of high-resolution spectral features with the highest similarity, the azalea type identification is carried out, the identification efficiency is high, meanwhile, errors possibly brought by single high-resolution feature matching can be effectively avoided, and the identification accuracy is improved. The method fully considers the information of a plurality of similar features, and greatly improves the accuracy of rhododendron species determination.

This invention discloses an endocrine rhythm-driven PPO full-spectrum intelligent dimming system, comprising a multi-dimensional data perception layer, an edge computing and core decision-making layer, and a light control execution layer. The multi-dimensional data perception layer includes a front-end high-resolution spectral sensing sensor module and a wearable device interface module; the edge computing and core decision-making layer includes a standardized feature dataset architecture unit, an endocrine multi-axis coupling prediction unit, and an AI decision model; the light control execution layer includes a five-channel visible light driving controller and a full-spectrum LED light-emitting module. This invention can offset rhythm deviations caused by environmental interference light sources in practical application scenarios, ensuring that the composite light entering the eye always conforms to the preset physiological regulation target, achieving the purpose of precise dimming, and can provide deep-level photoneurophysiological gains, synergistically improving the user's sleep quality and wakefulness.

The invention belongs to the technical field of spectrum calibration, and discloses a tunable optical frequency comb spectrum calibration method, which adopts a repetition frequency adjustable optical frequency comb as a calibration source, realizes flexible adjustment of comb tooth intervals by adjusting repetition frequency, and can accurately meet the requirements of spectrometers with different resolutions. The method mainly comprises the following steps: generating an offset frequency locking repetition frequency adjustable optical frequency comb, recording pixel positions of comb teeth of the optical frequency comb on a spectrometer CCD, establishing a wavelength-position mapping relation, optimizing a calibration model by applying machine learning, and carrying out error analysis and correction. Compared with a traditional spectrum calibration method, the method has the advantages of high-precision calibration, wide spectrum coverage range, flexible comb tooth intervals and adaptive optimization, is suitable for the fields of high-resolution spectrum analysis, scientific research and the like, and is particularly suitable for spectrum application scenes needing accurate wavelength calibration.

The invention discloses a plasma chyle degree detection method and system based on a spectrum principle, and relates to the technical field of medical examination, and the method comprises the following steps: using a multi-light source combination system to emit light in a wide spectral range covering ultraviolet light, visible light and near-infrared light to irradiate a to-be-detected plasma sample; the method comprises the following steps: synchronously acquiring absorption, scattering and transmission data of a plasma sample to light with different wavelengths through a high-resolution spectrum sensor to obtain multispectral data; and performing feature extraction on the acquired multispectral data by using a machine learning algorithm. According to the plasma chyle degree detection method and system based on the spectrum principle, richer information, such as detection of interaction between protein and nucleic acid and chyle particles by ultraviolet light and analysis of lipid structures by near-infrared light, can be obtained by utilizing specific response of different spectrum regions to components such as protein, nucleic acid and lipid in plasma and chyle particles. The multi-spectrum collaborative acquisition mode is a breakthrough of traditional single-spectrum detection.

The invention relates to the technical field of marine environment monitoring, in particular to a marine oil spill monitoring method and system based on a crude oil spectrum. Comprising the following steps: S1, identifying N marine oil spill positions by using a fuzzy reasoning model, and distributing monitoring points for the N marine oil spill positions to form a first monitoring sequence; s2, K important oil spill positions and corresponding monitoring points are optimized through a genetic algorithm, a second monitoring sequence is formed, and K is smaller than N and is a positive integer larger than or equal to 1; s3, calculating the time when the crude oil reaches the sea surface and marking a path; a high-resolution spectrometer is used to collect spectral data in visible light, near-infrared and mid-infrared bands. Marine oil spill is accurately positioned through fuzzy reasoning and a genetic algorithm, a high-resolution spectrometer and a Transform model are utilized to predict spectral data, a monitoring path is fused and optimized, energy loss and solar spectrum influence are considered, the model and the path are continuously corrected, and efficient and accurate monitoring is ensured.

The application provides an external cavity tuning semiconductor laser and a uniform wave number synchronous output method thereof, rapid and accurate modulation of the angle of a feedback light beam is realized through rapid deflection of an optical galvanometer, and the method specifically comprises the following steps: synchronously collecting the deflection angle of the optical galvanometer and the instantaneous output spectrum, accurately calculating the center wavelength of each sampling point by using a Gaussian fitting method, converting the center wavelength to the wave number domain for uniform processing, and obtaining the optimized driving curve of the deflection angle of the optical galvanometer changing with time through reverse calculation, so that the laser is finally synchronously and rapidly output according to the uniform wave number; the application can effectively overcome the deficiencies of traditional motor driving or piezoelectric ceramics in terms of precision, tuning speed and scanning stroke, significantly reduce the hardware cost of the core component, and has a wide application in the scenes of coherent tomography, high-resolution spectral analysis and precise laser radar.