1513 results about "Spectral analysis" patented technology

The invention relates to a method and a system for monitoring and analyzing regional noise. The method comprises the following steps: carrying out partition processing on a target area according to an acoustic environment function standard to obtain acoustic environment function area division data and determine a monitoring point position distribution matrix; noise data and environment parameter data are collected, timestamp alignment is carried out, and a multi-dimensional associated data set is obtained; performing spectral analysis and data compensation to obtain a noise feature vector, and performing standard exceeding judgment to generate audio recording data; inputting a voiceprint recognition model for classification to obtain a noise source type identifier, and performing positioning calculation to obtain a noise source space coordinate; carrying out space-time distribution statistics to obtain a functional area noise standard-reaching rate and calculating contribution degrees of various noise sources; and carrying out graded early warning judgment, and generating alarm information and a noise pollution prevention and control instruction. According to the embodiment of the invention, the whole-process automatic management of monitoring and early warning of regional noise is realized.

The invention relates to the technical field of radar signal processing, in particular to a radar target analytical calculation method based on multi-dimensional data fusion and a radar device. Comprising the following steps: deploying a multi-band radar sensor array comprising an X band, a C band and a Ku band in a radar monitoring area; performing pulse compression and Doppler processing on the time domain echo signal, and extracting a time domain feature; spectral analysis is carried out on the frequency domain signals, and frequency domain features are extracted; performing angle estimation on the spatial signals, and extracting spatial features; a dynamic weight distribution model is constructed, a fusion weight is calculated through an adaptive algorithm based on three-dimensional quality indexes of a real-time signal-to-noise ratio (SNR), feature stability (SI) and data integrity (CI), and a joint representation vector containing time domain, frequency domain and space multi-dimensional information is generated. According to the invention, by deploying the multi-band radar sensor array, the recognition capability of the subtle feature difference of the target is improved.

The invention relates to the technical field of fault positioning, and discloses a power distribution network grounding fault positioning method and system. The method comprises the following steps: acquiring a fault initial transient section signal, an arcing continuous section signal and an arc quenching recovery section signal of the power distribution network, and executing spectral analysis to obtain a fault feature matrix; performing zero-sequence transient frequency spectrum reconstruction on the fault feature matrix to obtain reconstructed frequency spectrum features and time-varying frequency spectrum features; calculating a transient characteristic index and a fault type based on the reconstructed spectrum characteristic and the time-varying spectrum characteristic; performing fault positioning calculation on the power distribution network according to the transient characteristic index and the fault type to obtain an initial fault point position; and performing transient fingerprint matching and probability density accumulation compensation on the initial fault point position to obtain a target fault point position. According to the method, high-precision characterization of the rapid change signal in the short time window is realized, interference of the compensation state on fault positioning is eliminated, and the grounding fault positioning accuracy of the power distribution network is improved.

The invention provides a meteorological element three-dimensional analysis method combining remote sensing and ground observation, and relates to the technical field of meteorological monitoring, and the method comprises the steps: obtaining remote sensing and ground observation data, and obtaining meteorological element data of a unified space-time reference; dividing the data into space-time grid units and performing quality evaluation to obtain a quality evaluation index; calculating a fusion weight coefficient according to the quality evaluation index based on an adaptive fusion algorithm of a dynamic weight, and performing weighted fusion on the meteorological element data in the grid units to generate an initial three-dimensional meteorological field; performing scale decomposition and reconstruction by adopting a spectrum analysis method to obtain an optimal three-dimensional meteorological field, constructing a self-adaptive tree-shaped composite analysis grid, analyzing evolution characteristics of a weather system in a multi-layer progressive mode, determining topological evolution parameters, and outputting a three-dimensional analysis result of meteorological elements.

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 LED light source uniformity and color deviation detection method, which comprises the following steps: setting environmental parameters of a constant temperature and humidity test box, monitoring the environment in the box in real time through a temperature and humidity sensor, and triggering a temperature and humidity control system to adjust when detecting that the temperature and humidity deviate from a set value; according to the initial color characteristic database, placing an LED light source in the constant-temperature and constant-humidity test box for an accelerated aging test, and obtaining spectral data of the light source at different time points by adopting a spectrum analyzer; calculating chromaticity coordinates, color temperatures and color rendering indexes corresponding to the spectral data at different time points, calculating a color deviation value of the LED light source, and fitting a change curve of the color deviation along with time; and according to an accelerated aging test result of the LED light source, calculating the color maintenance life of the light source in a high-temperature and high-humidity environment, and completing color deviation detection through a color stability uniformity index of the LED light source.

The invention relates to the technical field of spectral signal processing, in particular to a high-precision spectral signal peak detection method and system. According to the technical scheme, the method comprises the following steps: denoising and smoothing spectral data; dividing a spectrum curve by adopting a dynamic partitioning strategy; generating candidate partitioning points based on various local features, and generating feature blocks through optimization processing; according to the method, the influence of feature differences of different regions on a detection algorithm is reduced through a dynamic partitioning strategy, a multi-scale morphological feature system is constructed to comprehensively describe spectral curve morphological characteristics, potential peaks are gradually mined by applying a layered iteration peak detection algorithm, and local characteristics of spectral signals are adapted by means of an adaptive parameter adjustment mechanism, so that the spectral curve morphological characteristics are accurately detected. The peak value correction and fusion mechanism is utilized to improve the quality and reliability of a detection result, spectral data with a complex structure and a high noise level can be effectively dealt with, an efficient and reliable solution is provided for the field of spectral analysis, and the accuracy and robustness of peak value detection and the conciseness and reliability of the result are improved.

The invention provides a seawater parameter calibration system, and belongs to the technical field of seawater parameter measurement. A thermohaline depth device is used for constructing a three-dimensional structure model to identify a spring layer position, a multi-parameter water quality sensing device is used for collecting data to establish a correlation model, and a dissolved oxygen analysis device is combined with thermohaline data to calculate a correction coefficient; and the spectral analysis device extracts feature recognition chemical components. The method comprises the key steps that a parameter interaction compensation function and an OceanParamNet model are adopted to construct a seawater comprehensive parameter calibration model, original data are corrected, and abnormal values are detected. The system realizes layered storage and wireless transmission of data, dynamically adjusts sampling frequency and power consumption, periodically executes a self-calibration program to compensate aging drift of a sensor, realizes high-precision self-adaptive calibration of seawater parameters, and solves the technical problems of low precision and poor environmental adaptability of seawater multi-parameter collaborative calibration in the prior art.

The invention relates to the technical field of water quality detection, and discloses a water quality pollutant detection method, system and equipment based on spectral analysis, and the method comprises the following steps: carrying out real-time spectral data acquisition on a water body sample in a vehicle driving process through a multispectral sensor array in a vehicle-mounted water quality detection device; obtaining a water body spectrum three-dimensional data cube; carrying out anti-vibration wavelength calibration and ambient light source interference elimination processing to obtain a preprocessed spectrum data set; performing standard multivariate decomposition processing and horizontal local constraint optimization of a pollutant target wave band on the preprocessed spectrum data set to obtain enhanced feature fingerprint spectrums for different types of water quality pollutants; and inputting the enhanced feature fingerprint spectrum into a deep belief network model to perform pollutant feature matching analysis to obtain various pollutant types and corresponding concentration values in the water body sample, thereby effectively eliminating ambient light changes and other background interferences, not only determining the pollutant types, but also accurately quantifying the concentration values.

The invention relates to the technical field of laser etching, and discloses a laser double-sided etching stress control method and system for a quartz crystal, and the method comprises the steps: generating a double-sided complementary etching path based on the initial stress distribution of the quartz crystal; and front and back laser energy input is synchronously controlled, so that a double-sided thermal stress field forms dynamic balance. And obtaining the stress gradient distribution of the etching area in real time based on spectral analysis. And according to the deviation value of the stress gradient and a target threshold value, a laser processing parameter combination is dynamically adjusted, and a morphology-stress coupling optimization mode is started in a final processing stage. By accurately controlling the thermal stress balance and the stress gradient distribution in the laser processing process, the residual stress of the quartz crystal can be effectively reduced, and the shape and the performance of the quartz crystal are optimized, so that the processing precision, the material stability and the device reliability are improved.

The invention provides a multi-source data fusion modeling method and system in an aeration process, and is applied to the field of intelligent aeration control in sewage treatment. The method comprises the steps that multi-source time sequence data such as dissolved oxygen, turbidity, flow, temperature, power and pool bottom pressure pulsation signals are collected, dissolved oxygen response lag is calculated through cross-correlation analysis with power change as the reference, time sequence alignment is carried out, and a dissolved oxygen reference interval is predicted by utilizing calibration data in combination with a physical constraint LSTM model; performing spectral analysis on the pressure pulsation signal to extract a gas-liquid coupling characteristic value, and generating a cooperative regulation instruction of the frequency of the blower and the rotating speed of the stirrer based on the information; by means of the scheme, control oscillation caused by lag of the dissolved oxygen sensor can be effectively overcome, online monitoring of bubble form distribution is achieved, the gas-liquid mass transfer efficiency is improved, invalid aeration is avoided, and system energy consumption is remarkably reduced on the premise that stable effluent quality is guaranteed.

The invention provides a farmland disease and pest monitoring method and device and a storage medium, and relates to the technical field of agriculture, the method comprises the steps: dividing a farmland into a plurality of sub-regions, obtaining an infrared spectrum image, and segmenting the infrared spectrum image into corresponding sub-images; and calculating a vegetation stress index based on the reflectivity of the insect pest related characteristic wave band, and screening high-risk sub-regions. Risk plants are randomly extracted in a high-risk area, physiological parameters of leaves are collected, physiological health indexes of the leaves are constructed, and dynamic correction is carried out through an environment regulation coefficient according to environment data. Using the trained network model to identify the risk sample leaf scab, and calculating the scab area index. And finally, fusing the corrected leaf physiological health index and the scab area index, calculating a normalized risk value through a risk assessment function, and dividing the normalized risk value into four risk levels. Through multi-stage fusion of spectral analysis, physiological parameter correction and deep learning scab detection, accurate early warning of diseases and insect pests is realized, and the monitoring efficiency is improved.

The invention relates to the technical field of medicine quality detection, and particularly discloses an optical detection method and system for the content of vitamin tablets. The method comprises the following steps: driving an optical fiber probe array to carry out three-dimensional multi-angle near-infrared scanning through a multi-axis mechanical arm, and collecting reflection spectrum data; a weighted spectrum is generated through derivative spectrum analysis and double evaluation, and auxiliary material noise is corrected and separated in combination with subspace projection and a dynamic kernel function; performing spectral vector projection and regression coefficient iterative optimization through an online PLS model, and synthesizing an error coefficient based on a four-level index retrieval standard library to perform dual-channel feedback; and finally, fusing the credibility weight to output a detection result of the binding confidence. The method realizes nondestructive and high-precision detection of the vitamin tablets, has the beneficial effects of multi-dimensional data fusion, dynamic error compensation and high model adaptability, and remarkably improves the detection accuracy and reliability.

The invention relates to the technical field of spectral analysis, and discloses a spectral analysis-based gas component detection method, device and equipment and a medium, the method comprises the following steps: carrying out axial scanning on a gas storage device to obtain hyperspectral image data; performing preprocessing and spectrum standardization on the hyperspectral image data to obtain preprocessed spectrum data; carrying out waveband selection on the preprocessed spectral data to obtain a characteristic waveband; performing abundance estimation on the characteristic wave band to obtain initial gas component content data; optimizing the initial gas component content data to obtain target gas component content data; and performing gas component anomaly detection on the target gas component content data to obtain a gas component anomaly detection report, thereby improving the accuracy of gas component anomaly detection.

Methods and apparatus are disclosed for assessment of microstructural defects in a large structure. Third order elastic constants engender nonlinear excitation of acoustic modes particularly at points of local stiffness changes or stress concentration such as ends of microcracks. A broadband multimode acoustic signal is transmitted through an interrogation region from a first transducer, whereby a second transducer receives an acoustic signal containing linear and nonlinear components. Linear terms are canceled, and a magnitude of the nonlinear acoustic response is measured using time-resolved spectral analysis, to determine a coefficient for acoustic nonlinearity of the interrogation region that serves as a qualitative or quantitative representation of microcrack damage. Broadband signals avoid mode-specific effects such as shadowing or phase mismatch. Damage location can be identified by region or time-of-flight. Portable or dedicated embodiments can be deployed on a wide range of structures of arbitrary shape.

The invention provides a rice seed vigor rapid detection method based on near infrared spectrum, and belongs to the technical field of spectral analysis. The method comprises the following steps: performing different degrees of aging treatment on rice seeds in a high-temperature and high-humidity environment, taking unaged rice seeds as a control group, collecting spectral data of the rice seeds subjected to different degrees of aging treatment, and preprocessing the data; taking out the seeds of each treatment group, and measuring physiological indexes including germination rate, germination potential and the like; based on the preprocessed spectral data, a data enhancement method is adopted to fully embody internal characteristics and category differences of sample data; a Conv1D-GRU framework is applied, the model can capture spatial features and time sequence information in spectral data at the same time, a full-connection layer predicts extracted comprehensive features by means of vitality, a classification result is output through a softmax layer, a hybrid optimization population search algorithm is used for further optimizing the performance of the model, and the performance of the model is improved. Therefore, the activity of the rice seeds can be rapidly detected according to different aging degrees of the rice seeds.

The invention discloses an unmanned aerial vehicle positioning method based on a Bayesian network, and the method comprises the steps: collecting unmanned aerial vehicle data, carrying out the preprocessing, obtaining sound wave data, motion data, infrared image data and environment data, carrying out the spectrum analysis based on the sound wave data, obtaining sound spectrum time sequence data, and carrying out the positioning of the unmanned aerial vehicle. Constructing a probability density thermodynamic diagram and extracting a first range through a sparse variational Gaussian process according to time, frequency and energy three-dimensional information of the sound spectrum time sequence data and environment data, and obtaining first positioning data through a Bayesian network according to the first range and motion data, and performing adaptive wavelet down-sampling on the infrared image data and the sound spectrum time sequence data in the lateral direction to obtain lateral positioning data, and performing deviation correction on the first positioning data by using the lateral positioning data to obtain second positioning. According to the method, through space-time synchronization, adaptive processing and probabilistic reasoning of sound spectrum time sequence data, the positioning precision and stability in a complex environment are improved.

The invention discloses a high-precision three-degree-of-freedom attitude adjustment platform for a spectrometer, which is based on a simplified design of a Stewart platform and comprises a movable platform, a static platform and a three-degree-of-freedom driving mechanism connected between the movable platform and the static platform. The driving mechanism is composed of three sets of servo electric cylinders, telescopic rods and servo motors and is driven by a ball screw, and posture adjustment of the platform is achieved. According to the platform, a laser interferometer is adopted as a high-precision sensor, a closed-loop feedback control system is combined, and submicron displacement measurement and attitude control are achieved. The platform can achieve translation in the Z-axis direction and rotation around the X axis and the Y axis, the rotation angle can reach + / -15 degrees, and the precision can reach 0.02 mm. According to the invention, the device ensures high precision and stability in a complex working environment, has the characteristics of stable movement, quick response, easy maintenance and the like, and is suitable for the fields of optical experiments, spectral analysis and attitude adjustment and error compensation of precise instruments.

The invention relates to the technical field of big data service, in particular to a chemical fiber raw material impurity spectrum intelligent analysis system which comprises a spectrum feature deconstruction module, an impurity feature modeling module, a periodic drift analysis module and a component quantification output module. According to the method, noise is suppressed through moving window scanning in combination with Savitzky-Golay filtering, peak shape features are reserved, the signal-to-noise ratio is increased, feature distortion caused by mean filtering is avoided, segments are divided through extreme value density, weak impurity recognition is enhanced in combination with a dynamic threshold value, and a multi-dimensional fusion model is established through peak width change rate and baseline offset convolution. Linear dimension reduction limitation is broken through to improve discrimination precision, dynamic time warping is used for aligning peak height difference and symmetry degree time sequence, drift and interference influences are eliminated, periodic error accumulation is solved, Kalman filtering is used for carrying out recursive optimization on compensated concentration, model lag is reduced, and a closed-loop optimization system is constructed through multi-stage feature decoupling and dynamic compensation. The sensitivity is improved; and the misjudgment rate is reduced.

The invention discloses a laser processing method and device for a special shell, and the method comprises the steps: S1, obtaining the structural feature data of the shell through three-dimensional scanning, planning a laser processing path according to the structural feature data, and generating a processing path file; s2, starting a dust removal assembly, emitting positioning laser at the same time, measuring the optical path offset through a photoelectric detection assembly, and generating calibration parameters; s3, the light transmittance change of the light blocking assembly is controlled based on the calibration parameters, and a stable laser beam is formed by adopting a closed-loop control strategy; s4, a stable laser beam irradiates the surface of the shell along the machining path, and the irradiation position is dynamically corrected in combination with the deformation prediction model; s5, local laser strengthening is conducted on the machined key area, and meanwhile the machining path file of the next period is optimized; a light blocking assembly with adjustable light transmittance is combined with a closed-loop control strategy to dynamically adjust laser energy, deformation prediction and spectral analysis provide real-time quality guarantee, the process is continuously optimized through iterative optimization of a digital model, and a high-quality shell finished product is obtained.

The invention relates to the technical field of information, in particular to a method for detecting and monitoring the cleaning effect of a semiconductor wafer in real time in the technical field of semiconductor wafer manufacturing, which comprises the following steps: introducing a rapid chemical analysis technology, combining an electrochemical sensor and spectral analysis, monitoring metal ion residues on the surface of the wafer in real time, and shortening the detection period; instant feedback on a production line is realized; a real-time feedback control system is constructed, according to the output of the comprehensive evaluation model, the working parameters of the cleaning equipment are automatically adjusted, the cleaning process is optimized, and the usage amount of cleaning liquid and the environmental influence are reduced; an edge computing technology is integrated, data processing and analysis tasks are sunk to a cleaning equipment end, data transmission delay is reduced, and the response speed of real-time monitoring and feedback control is increased; a visual monitoring platform is developed, key parameters, detection results and prediction trends in the cleaning process are displayed in a graphical mode, and operators can conveniently master the cleaning state in real time and quickly respond to abnormal conditions.

The invention relates to the technical field of heart sound signal processing, and discloses a heart sound feature recognition method based on wavelet spectral analysis. The method comprises the following steps: collecting heart sound signal data and carrying out signal filtering and segmentation processing to obtain segmented cardiac cycle signals; performing n-level discrete wavelet transform decomposition to obtain an approximation coefficient and n detail coefficients; performing multi-dimensional statistical feature calculation to obtain a multi-dimensional feature vector; performing principal component analysis dimension reduction processing to obtain a dimension reduction feature vector; fitting feature distribution by using a Gaussian mixture model and introducing a dynamic adjustment factor to obtain an adaptive classification threshold; the hidden Markov model is constructed through the dimension reduction feature vectors, the likelihood probability is calculated through a forward algorithm, the likelihood probability is compared with a self-adaptive classification threshold value, and the heart sound feature recognition result is output. The time-frequency features of the heart sound signals are fully utilized, the feature distinction degree and the recognition accuracy are improved, and the recognition accuracy is improved. And meanwhile, the method has good robustness and generalization ability.

The present invention relates to the technical field of food quality detection, and in particular to a quality assessment system and method for Xanthoceras sorbifolia oil based on spectral analysis, comprising a spectral acquisition module, a data preprocessing module, a feature extraction module and a quality assessment module; wherein: the spectral acquisition module is used to collect spectral data of Xanthoceras sorbifolia oil samples, including reflection spectrum and transmission spectrum information; the data preprocessing module is used to preprocess the spectral data collected by the spectral acquisition module; the feature extraction module is used to extract feature data related to the quality of Xanthoceras sorbifolia oil from the preprocessed spectral data; the quality assessment module is used to construct a quality assessment model, assess the quality of Xanthoceras sorbifolia oil samples, and output the quality grade. The present invention provides an efficient, non-destructive and real-time quality assessment system and method for Xanthoceras sorbifolia oil by combining near infrared spectroscopy technology with a support vector machine regression algorithm, which significantly improves the assessment accuracy.

The invention discloses a multi-point spectrum confocal measurement method, which comprises the following steps of: transmitting broadband light to an optical fiber light-emitting aperture through an optical fiber network by using a group of broadband light sources to form multi-point irradiation; the broadband light is dispersed through a dispersion lens and is decomposed into dispersion light rays with different wavelengths, and a plurality of groups of dispersion light rays form focused multi-point light beams to irradiate different positions of the workpiece to be measured; receiving reflected light rays from the surface of the workpiece to be detected through at least three optical fiber channels of the multi-channel spectrum analysis device, and analyzing a spectrum signal of each return channel; on the basis of the spectral signals of at least three measurement points, the inclination angle of the plane of the measured workpiece is calculated by adopting the relative height difference between multiple point positions and combining the triangular geometrical relationship with the light path reflection angle; in the whole operation process, the measurement device does not need to be moved, the measurement precision and stability are kept, the method effectively avoids errors caused by a moving shaft in a traditional method, and the measurement efficiency and precision are integrally improved.

The invention relates to the technical field of metal structure detection, in particular to an intelligent special-shaped aluminum plate structure parameter detection method and system based on spectral analysis, and solves the problems of multi-parameter splitting, poor complex structure adaptability and inaccurate risk assessment in traditional detection. According to the method, data are synchronously collected through multi-spectral imaging and line laser scanning, surface component parameters such as the thickness gradient of an oxide film are inverted, the local curvature is calculated based on three-dimensional point cloud, a spiral encryption or grid sparse scanning track is dynamically switched, differential detection of a complex structure and a plane area is achieved, and the detection precision is improved. And then a space correlation model of the oxidation film thickness and the hole deformation quantity is constructed, a structure failure risk area is accurately recognized by combining a three-level risk judgment rule and cross-regional influence analysis, and the system effectively improves the accuracy and detection efficiency of defect recognition of the special-shaped aluminum plate through cooperation of dynamic scanning control, component deformation correlation and a composite structure decision unit.

The invention discloses a compensation method based on ultraviolet-visible spectrum interaction interference, which relates to the technical field of spectral analysis, and comprises the following steps: acquiring ultraviolet-visible spectrum data of turbidity, COD, nitrate single gradient solution and mixed solution of the turbidity, COD and nitrate single gradient solution, and preprocessing the data; constructing a mapping relation model of the turbidity and the spectral data; for spectral data within the wavelength range of 260-320nm, calculating interactive interference data, establishing a relationship between the turbidity and the interactive interference data, and performing interactive interference compensation and spectral analysis; for the spectral data in the wavelength range of 220-260nm, constructing a COD and spectral data relation model, and calculating interactive interference data; and based on the interactive interference data characteristics, establishing a regression model, analyzing the relationship between the interference spectrum characteristics and other substances, and performing interactive interference compensation and spectral analysis. According to the method, the resolution of the spectral signal is remarkably improved, the reliability of data analysis is improved, and the method has a wide application prospect.

The invention relates to the technical field of spectral analysis, in particular to an intelligent spectral pesticide residue detection system which comprises a spectral data acquisition module, a spectral feature analysis module, a pesticide spectral feature classification module, a spectral matching weight optimization module and a pesticide residue concentration analysis module. In the invention, by collecting spectral signals of a pesticide sample in different wavelength ranges and combining time, space and frequency dimension information, the comprehensiveness of data collection is ensured, spectral data is analyzed in multiple dimensions, mutation features are extracted, associated frequency bands are identified, angle deviation is eliminated, and the accuracy and reliability of spectral features are improved; classification is performed according to spectral distribution differences and change rates, detection resolution is improved, spectrum matching rules are optimized, high-contribution wavebands are screened, detection accuracy is improved, concentration normalization analysis is combined, key feature contribution values are adjusted, misjudgment risks are reduced, optical paths are optimized, optical loss is reduced, signal acquisition stability is improved, and adaptability of a detection system is enhanced.

An electronic interface device is configured for use with associated optics for employing coded light for illuminating a liquid, gaseous, or other analyte or target, such as for measuring or determining a composition or other property of the analyte or target. The arrangement can help enable a far higher level of performance, such as for spectral analysis, imaging, or both. A shared common clock on both the illumination and receive sides of the system can be included, such as together with one or more of reference detection, per-channel wavelength-dependent modulation, multiple concurrent feedback loops at different levels, orthogonal and circulant codes, phase-scrambling to better utilize ADC dynamic range, oversampling, and other signal processing can be provided.

The invention belongs to the technical field of pavement construction detection, and provides a municipal road asphalt concrete pavement construction detection method, which comprises the following steps: S1, installing a plurality of optical sensing devices, and collecting pavement images and spectral data in real time; s2, carrying out fusion processing on the collected data; s3, processing the three-dimensional data to generate a three-dimensional model of the road surface; s4, analyzing the image data, automatically identifying pavement defects and evaluating the severity of the pavement defects; s5, performing spectral analysis and fusing data to assist in judging the quality and uniformity of the material; s6, comparing a detection result with a design standard, and generating a construction quality evaluation report; according to the invention, construction detection is carried out by comprehensively applying an optical sensing technology and a data processing algorithm, the efficiency and quality of construction monitoring are improved, the maintenance cost is reduced, and the safety and durability of a road are guaranteed.

The invention discloses a snapshot type hyperspectral imaging industrial online sorting system which comprises a support assembly, an optical imaging assembly and a motion control assembly. The bracket assembly consists of a bottom plate, and an adjustable bracket and a fixed bracket which are fixed on the bottom plate; the optical imaging assembly comprises a lighting unit, an imaging objective lens and a snapshot type hyperspectral camera, and can synchronously obtain space image information of a measured object and spectral information of a continuous wave band in a single exposure process; the motion control assembly realizes automatic transmission of the measured object through the transmission platform; the data processing module is integrated with an image preprocessing unit, a spectral analysis unit and a spectral database, and is used for end-to-end closed-loop control from original hyperspectral data generation to sorting decision making; the system adopts a metasurface light splitting structure to realize real-time decoding, performs material or category identification by using a pre-trained classification model, and finally automatically generates a sorting decision signal according to an identification result to drive a motion control assembly to complete sorting operation.