476 results about "Ir microscope" patented technology

The invention relates to the crossing field of precision agriculture and artificial intelligence technology, in particular to a soil component detection system based on machine learning and infrared spectroscopy, which is characterized in that a soil spectrum is acquired on site through a portable Fourier infrared spectrometer, and after pretreatment, feature vectors are constructed by fusing climate, soil and crop data; the deep learning decision-making module extracts spectral features by using one-dimensional convolution, fuses multi-dimensional information through an attention mechanism, synchronously outputs a fertilization scheme, crop suitability scores and soil improvement measures by a multi-task learning sub-network, and finally, verifies by combining an agronomic knowledge base so as to obtain a fertilization result. According to the method, a comprehensive decision report containing a quantitative fertilization formula, a crop suitability sequence and a soil improvement scheme is generated, precise agricultural guidance is realized, spectral features are automatically extracted by adopting a one-dimensional convolutional neural network, and a multi-modal data fusion and multi-task learning framework is combined, so that the system achieves relatively high precision in the aspect of soil nutrient prediction.

The invention is suitable for the technical field of filters, and particularly relates to a manufacturing method of a linear gradient filter and the linear gradient filter. The manufacturing method of the linear gradient filter comprises the following steps that a glass wafer serves as a substrate, and a lower reflecting layer is plated on the surface of the glass wafer; wherein the lower reflecting layer is formed by alternately stacking a plurality of layers of low-refractive-index materials and a plurality of layers of high-refractive-index materials; coating a resonant cavity layer on one side, far away from the glass wafer, of the lower reflecting layer through a stepped coating process; plating a reflecting layer on one side, far away from the glass wafer, of the resonant cavity layer; and plating a long-wave-pass layer on one side, far away from the glass wafer, of the upper reflecting layer and in an area larger than the central wavelength to obtain the linear gradient filter. Compared with the prior art, the linear gradient filter provided by the invention is better in spectral resolution in a long wave band, smaller in energy difference of channels, excellent in wavelength selection performance and capable of being applied to spectrum applications such as a miniaturized infrared spectrometer and the like.

The invention discloses a primary tea grade screening method, a medium and equipment. The method comprises the following steps: acquiring original primary tea information containing a first visible light image, first near infrared spectrum information and first three-dimensional form information according to a preset sampling frequency; performing illumination compensation, geometric correction and multi-source registration processing on the original raw tea information to obtain standard raw tea information; extracting static quality parameters such as strip crimpness from the registered second visible light image, analyzing and acquiring physical and chemical quality parameters from the second near infrared spectrum information, and extracting structural features such as strip compactness from the second three-dimensional form information; finally, grade judgment is conducted through the cascade decision model, and the sorting device is controlled to execute corresponding sorting actions. Fusion analysis and intelligent grading of multi-dimensional features of the raw tea are achieved, and the sorting precision and efficiency are effectively improved.

The invention relates to the technical field of monitoring light supplement adjustment, and discloses a monitoring light supplement automatic adjustment system based on ambient light detection. An ambient light dynamic sensing module of the system captures visible light and infrared spectrum components of a monitoring area in real time through a multispectral sensor array, constructs a light intensity distribution model in combination with illumination intensity historical data, and outputs a theoretical illumination distribution diagram; the spectral feature analysis module compares the theoretical distribution map with the actually measured light field data in a multi-dimensional manner, performs spectral deviation detection and generates a spectral difference feature tensor; the light supplement demand mapping module inputs the tensor into a space illumination analysis network, and generates a light supplement coverage demand thermodynamic diagram and calibrates the boundary of a low-illumination area in combination with a field angle of monitoring equipment and position coordinates of a light supplement lamp; and the self-adaptive light supplement strategy execution module starts a multi-band mixed light supplement mode for a high-demand area according to the thermodynamic diagram, and performs phase cooperative control on adjacent light supplement lamp groups. The system realizes dynamic and accurate adjustment of light supplement, and can effectively adapt to complex ambient light changes.

The invention relates to a three-waveband medium-long wave infrared optical filter and a preparation method, the three-waveband medium-long wave infrared optical filter comprises a front film system, a substrate and a back film system, and the substrate is located between the front film system and the back film system; the front film system is formed by alternately overlapping germanium layers and zinc selenide film layers; and the back film system is formed by alternately overlapping germanium layers and zinc selenide film layers. According to the invention, the light energy of three wave bands of 3780-4000 nm, 4500-4900 nm and 7850-9500 nm is improved, the luminous flux of other wave bands is well inhibited, the technical problem of infrared filtering windows in some special infrared spectrum detection systems is solved, and a new scheme is provided for the application of the infrared spectrum detection systems.

The invention relates to the technical field of component analysis, in particular to an intermediate infrared spectrometer sensor verification system which comprises the following steps: acquiring spatial distribution information of a target sample through an automatic sampling module, and generating a corresponding first feature group based on the spatial distribution information; adjusting an emission wave band and a modulation strategy corresponding to a mid-infrared light source, converting mid-infrared photons into visible light signals, and generating a corresponding second feature group; performing down-sampling processing on the original spectral data to generate a corresponding third feature group; inputting the sparse spectral coefficient into a pre-trained deep learning reconstruction model, and dynamically correcting the reconstruction process in combination with an environment temperature compensation parameter to generate reconstructed spectral data corresponding to high resolution; and analyzing the reconstructed spectrum data, matching a preset substance spectrum database, extracting a characteristic absorption peak position and an intensity ratio of the target substance, and generating a corresponding final analysis result. According to the invention, the intelligence of the sensor verification system can be improved.

The invention relates to the technical field of electron microscope sample pretreatment, and discloses a critical point drying control method and device based on online near-infrared monitoring, and the method comprises the steps: obtaining infrared spectrum data, and unmixing the spectrum data to obtain a feature data set of a solvent; outputting a to-be-corrected signal according to the feature data set, correcting the to-be-corrected signal with preset data, and determining a signal feature of the solvent; carrying out dynamic correction on the signal characteristics and a preset characteristic matrix, outputting concentration time sequence data of the solvent, carrying out steady state judgment by combining a preset convergence threshold value, and determining a critical state of the solvent; acquiring control strategy data according to the critical state, analyzing the control strategy data into execution response characteristics, performing multi-channel mapping and correction processing, and outputting a process control signal; and performing control gain correction on the process control signal to finish closed-loop feedback control of the final drying process. The method is based on multi-solvent spectrum sensing and concentration dynamic analysis, and self-adaptive closed-loop control of the critical point drying process is achieved.

The invention discloses a method for detecting aspergillus flavus and aflatoxin B1 of crops based on an infrared spectrum. The method comprises the steps of crop sample material collection, rice multi-strain mould infection, spectrum collection, crop sample aflatoxin B1 determination, spectrum pretreatment, correction model construction and model verification. The invention aims at detecting the content of aspergillus flavus infection and toxin B1 thereof in crops by combining a near-infrared spectrometer and a stoichiometric method. The method has the advantages of being simple and easy to implement, high in analysis speed, high in detection precision, low in analysis cost, free of any pollution to the environment and the like, samples do not need any pretreatment, and the method has important practical value for guaranteeing the quality safety of agricultural products and reducing the carcinogenic risk of people.

The invention provides a ventilation system optimization method and system based on the air quality of an industrial aquaculture workshop, and relates to the technical field of environment regulation and ventilation system.The method includes the steps that aquaculture workshop gas is analyzed through an infrared spectrometer, the spectral intensity of the characteristic absorption wavelength of a target pollutant is obtained, and then the accurate concentration of the pollutant is analyzed according to the spectral intensity; and calculating a ventilation parameter reference value and controlling a fan to adjust the air supply amount. An air treatment device in the ventilation system can determine the optimal working time according to the air supply amount so as to decompose pollutants and continuously monitor the concentration of the pollutants at the inlet and the outlet of the device. Subsequently, the air quality deterioration index is predicted by analyzing the concentration change trend, and the current overall purification efficiency is calculated. When the purification efficiency deviates from the range or the deterioration index exceeds the threshold value, the running state of the device is dynamically adjusted and fed back to the system, self-adaptive optimization of the ventilation system of the industrial aquaculture workshop can be achieved, and it is guaranteed that the workshop air quality is stable and the purification efficiency reaches the standard.

The invention relates to the technical field of numerical control, in particular to an engraving and milling machine machining track control method based on machine vision. Comprising the steps of receiving an operation task instruction, collecting a reflected light intensity matrix and processing thermal field data, and generating a source data packet; obtaining a fusion heat distribution matrix through the homography matrix; based on the friction thermal response coefficient, a physical tool nose contact area is judged, a dynamic feature mask is generated, the dynamic feature mask and the reflected light intensity matrix are operated, and a monitoring area is output; executing end coordinates are output through least square ellipse fitting, and sensor calibration parameters are inversely transformed into tool nose feedback coordinates; and reading interpolation instruction coordinates, calculating a differential vector, and driving a feed shaft motor to execute displacement compensation. According to the method, deep space-time coupling is performed on the physical cut-off characteristic of the infrared spectrum, the high-frequency texture characteristic of the visible light and the kinematics constraint of a numerical control system, so that a real tool nose hot spot and an optical virtual image are distinguished, and the uniqueness and authenticity of track identification are ensured.

The invention discloses a cordyceps sinensis intelligent bionic cultivation control system and method based on the Internet of Things, and the method comprises the steps: collecting the temperature and humidity, gas concentration, illumination intensity and larva behavior data of a cordyceps sinensis matrix through a sensor network, and carrying out the fusion through an edge calculation gateway, and generating a dynamic environment map; constructing a plateau ecological digital twinborn model based on the dynamic environment map in combination with historical meteorological data and a host-strain interaction rule, and generating a staged control time sequence; based on a staged control time sequence, temperature and humidity coupling compensation is carried out through a feedforward-feedback composite algorithm, and actuator linkage is adjusted through fuzzy PID; aI vision is used for identifying a larva infection window period and accurate spraying is carried out, and hypha infection is monitored in combination with a near infrared spectrum to dynamically adjust the CO2 concentration; and constructing an LSTM (Long Short Term Memory) model to predict the growth risk in combination with a dynamic environment map and insect body monitoring data, and actively intervening in an abnormal environment. According to the invention, high-precision, dynamic and intelligent regulation and control of the growth environment of cordyceps sinensis are realized.

Apparatuses, systems, and techniques for reliable image data capture are disclosed herein. A system includes a sensor configured to receive light reflected off one or more objects in an environment. The sensor includes a first set of sensor pixels configured to detect a portion of the received light having wavelengths in the visible light spectrum. The sensor further includes a second set of sensor pixels configured to detect an additional portion of the received light having wavelengths in an infrared spectrum. The system further includes a filter component configured to reduce an intensity of the portion of the received light detected by the first set of sensor pixels while maintaining at least a minimum intensity of the additional portion of the received light detected by the second set of sensor pixels.

The invention discloses an imaging type optical system for a high-intensity magnetic field Fourier infrared spectrum device, which comprises a solenoid superconducting magnet tubular sample cavity for the high-intensity magnetic field Fourier infrared spectrum device, and a non-magnetic damping sleeve arranged in the solenoid superconducting magnet tubular sample cavity, a non-magnetic mirror surface gold-plated optical waveguide is arranged at the upper part in the non-magnetic damping sleeve, a Faraday optical module is arranged at the lower part in the non-magnetic damping sleeve, and an adjustable sample bearing table and a low-temperature thermometer and magnetometer assembly are arranged below the non-magnetic mirror surface gold-plated optical waveguide; the non-magnetic mirror surface gold-plated optical waveguide comprises a light-in waveguide and a light-out waveguide, and the Faraday optical module integrates a switchable reflection module and a transmission module which are respectively adapted to different strong magnetic field Fourier infrared spectrum measurement requirements. The optical efficiency of the high-intensity magnetic field Fourier infrared spectrum device is improved, the problems of high optical loss and scattering interference of a traditional device are solved, and the signal-to-noise ratio is increased.

The invention discloses a feature extraction method and system based on heterogeneous multi-modal information fusion, and the method comprises the steps: constructing a spectrum reference system through synchronously collecting the data of an image sensor, a laser radar and an infrared spectrometer carried by an unmanned plane, achieving the unified calibration of image data, and generating a unified image reference through employing a feature field fusion technology; extracting multi-modal characteristic spectral lines, performing complementary analysis to confirm fusion characteristics, and establishing a dynamic weight table by matching working frequency bands; a separation factor is generated based on correlation analysis of a point cloud density field and a modal characteristic spectral line, a correction coefficient is generated in combination with characteristic fluctuation analysis, and a pure visual characteristic signal is identified; a mapping transformation kernel is constructed to realize standardized conversion of feature data, a migration coefficient is generated through spatial positioning analysis and feature intensity analysis, a regulation and control instruction is generated through multi-level feature processing, a weight table is adjusted based on the regulation and control instruction to form closed-loop optimization, a hierarchical feature extraction signal is generated, and deep fusion and intelligent extraction of features are realized.

The invention relates to the technical field of intelligent inspection, in particular to an intelligent inspection system and method for a wind power plant based on multispectral camera shooting and thermal imaging, and the system comprises a multispectral camera shooting module which is used for collecting visible light and infrared spectrum images of wind power plant equipment; the thermal imaging module is used for monitoring surface temperature distribution of the equipment and generating a thermal imaging map; the edge calculation unit is used for analyzing the collected data in real time and identifying the abnormal state of the equipment; the intelligent analysis platform is used for receiving the data processed by the edge calculation unit, generating an inspection report and triggering an alarm; the communication network is used for realizing data transmission among the multispectral camera module, the thermal imaging module, the edge calculation unit and the intelligent analysis platform; according to the invention, edge calculation enabling is carried out on field equipment, the equipment state, the disconnecting link state, the foreign matter condition and the like in a monitoring picture are processed on site, the equipment operation state is identified in real time, and a fault is found and directly fed back to the intelligent inspection system of the new energy station, so that the inspection efficiency is improved.

The invention relates to the technical field of traditional Chinese medicine decoction piece screening, and discloses an intelligent traditional Chinese medicine decoction piece screening method based on multi-modal data fusion. The method comprises the following steps: synchronously acquiring visible light image data, near infrared spectrum data and smell volatile matter data of a target traditional Chinese medicine decoction piece through a multi-source sensor array; respectively performing morphological cleaning, baseline drift correction and environmental interference elimination operations on the three types of data; extracting a form feature set, a chemical component feature set and a volatile substance feature set of the decoction pieces from the preprocessed data; calculating morphological stability factors, component stability factors and volatilization stability factors corresponding to the three types of feature sets; constructing a three-dimensional feature fusion space, and mapping the three types of feature sets into fusion feature vectors; executing centralized search in the space by taking the fusion feature vector as a starting point, and determining an optimal screening decision vector; therefore, more accurate grade classification and quality screening are realized, and the screening efficiency of the traditional Chinese medicine decoction pieces can be remarkably improved.

The invention relates to a dual-waveband medium-long wave infrared optical filter based on a germanium / zinc sulfide asymmetric film system and a preparation method of the dual-waveband medium-long wave infrared optical filter. The dual-waveband medium-long wave infrared optical filter comprises a front film system, a substrate and a back film system, the front film system and the back film system are formed by alternately overlapping germanium layers and zinc sulfide film layers; the average transmittance of the infrared optical filter in the wave band of 3800 nm to 4800 nm and the wave band of 8000 nm to 10000 nm is not lower than 91%. According to the two-waveband medium-long wave infrared optical filter disclosed by the invention, 3800 to 4800 nm amp is realized; according to the infrared filtering window, the light energy of medium waves and long waves of 8000-10000 nm is improved, the luminous flux of other wavebands is well inhibited, the technical problem of the infrared filtering window in some special infrared spectrum detection systems is solved, and a new scheme is provided for infrared application.

The invention discloses a data-driven high-infrared-radiation-characteristic high-entropy rare earth tantalate material screening method and application, and belongs to the technical field of thermal barrier coating materials. The method aims at breaking through the infrared radiation performance bottleneck of a traditional rare earth tantalate ceramic material, a high-precision prediction model of the infrared emissivity of the rare earth tantalate is innovatively developed by constructing a multi-system common data set, and rapid evaluation of the infrared spectral characteristics of the A-site high-entropy rare earth tantalate RE3TaO7 material is achieved. On the basis of the model, a multi-element rare earth tantalate system which comprises (Y < 0.2 > Dy < 0.2 > Gd < 0.2 > Sm < 0.2 > Nd < 0.2 >) < 3 > TaO7 and (Nd < 0.2 > Eu < 0.2 > Dy < 0.2 > Er < 0.2 > Yb < 0.2 >) < 3 > TaO7 and has excellent infrared radiation characteristics is successfully screened out. According to the method, the limitation of traditional small sample material research is broken through through big data modeling, and an efficient theoretical design normal form is provided for developing a novel high-entropy infrared radiation material.

The invention discloses a real-time dynamic monitoring method for a new energy carbon-based material purification process, and relates to the field of material processing monitoring, and the real-time dynamic monitoring method comprises the following steps: collecting pulse voltage signals, stripping current density and electrolyte conductivity data in a graphene powder purification process, and monitoring the change of functional groups on the surface of graphene on line through an infrared spectrometer; obtaining characteristic absorption peak intensity data; according to the method, multi-source data in the purification process is subjected to collaborative analysis and intelligent regulation and control, an electrochemical parameter and material structure evolution correlation model is established, the process stability is improved through parameter self-adaptive adjustment, a closed loop integrating data acquisition, feature analysis and dynamic control is constructed, and the purification efficiency and purity of the graphene powder are effectively improved.

According to the pressure damage dynamic risk assessment method based on multi-modal sensing, multi-physical field data is collected in real time through an MEMS piezoresistive array, a near infrared spectrum sensor and a flexible capacitance type humidity sensor, and early precise early warning and automatic grading intervention are achieved in combination with an LSTM neural network and dynamic threshold adjustment. According to the method, the early warning time of the stress injury is advanced by 4-6 hours, so that the clinical misjudgment rate is reduced to be less than 15% from 38%, and the problems that in the prior art, poor blood circulation of subcutaneous tissues cannot be accurately identified by traditional visual inspection, the hysteresis of the currently adopted preventive measures and the clinical accurate judgment error rate are relatively high, and the clinical accuracy is relatively low are solved. In order to solve the problem that the occurrence risk and the compression degree of the stress injury cannot be accurately judged due to the fact that the existing tissue ischemia assessment method is based on the three-layer architecture of'multi-modal sensing and dynamic modeling combined with intelligent closed loop ', the transformation from'passive discovery' to'active prevention 'is realized, and a more comprehensive tissue ischemia assessment system is constructed.

The invention relates to a wide-temperature-range stable dual-band infrared optical filter for an extreme environment and a preparation method thereof. The wide-temperature-range stable dual-band infrared optical filter comprises a front film system, a substrate and a back film system, the front film system and the back film system are formed by alternately overlapping germanium layers and zinc sulfide film layers; the drift distance of the central wavelength of the passband of the infrared optical filter is less than 0.05% within the temperature range of-120 DEG C to + 85 DEG C. According to the invention, the internal stress of the film layer is obviously reduced through the optimized film system design, so that the excellent stability of the optical performance in an extreme temperature environment is realized, the technical problem that some special infrared spectrum detection systems work in a wide temperature range is solved, and a reliable solution is provided for high-end aerospace infrared application.

The invention discloses a honey adulteration detection method, which belongs to the technical field of food detection, and comprises the following steps: collecting an absorbance spectrum of a honey sample by using a near infrared spectrometer; extracting characteristic absorbance values A < lambda > 1 and A < lambda > 2 at a 1450 nm water molecule absorption peak and a 1490 nm saccharide molecule absorption peak; the ratio R is equal to A lambda 1 / A lambda 2; and comparing the R with a threshold range of 0.85-1.15 of pure honey so as to judge whether the honey is true or false. The portable device comprises a sample bin, a near infrared spectrum module, a control unit and a human-computer interaction interface, wherein a rotatable sample table is arranged in the sample bin to accommodate a plurality of disposable sample cups. The method abandons a complex black box model, adopts a characteristic wavelength ratio method with clear physical significance, has the outstanding advantages of simple principle, rapid detection (less than 30 seconds), high accuracy, low cost, simplicity and convenience in operation and the like, perfectly solves the problems of expensive equipment, long time consumption, limited identification capability and dependence on professionals in the prior art, and has a wide application prospect. The method is especially suitable for market on-site rapid screening.

The invention relates to the technical field of medical detection and spectral analysis, and discloses a spectrum detection method for microorganisms on a wound surface based on knowledge data dual-drive envelope fusion. The method comprises the following steps: firstly, acquiring a multi-band near-infrared spectrum signal of a wound surface through a fiber optic spectrometer, and carrying out normalization and smooth filtering pretreatment; analyzing optical characteristic parameters based on a diffuse reflection theory model, constructing a knowledge-driven characteristic sample space, extracting spectral high-order characteristics by using a one-dimensional deep convolutional neural network, and constructing a data-driven characteristic sample space; then generating a grain envelope sample through a double-flow feature fusion mechanism; and finally, constructing a lightweight dual-task classification model based on the particle envelope sample, and realizing rapid detection of fungal infection of the wound surface and identification of seven common bacteria. According to the method, the interpretability, the recognition precision and the robustness of characteristic pathology are considered, and an efficient and reliable technical scheme is provided for early clinical diagnosis of wound infection.

The invention belongs to the technical field of tea processing, and particularly relates to a high-precision grading and directional processing system for Qihong tea. The system comprises an intelligent tea leaf grading module based on hyperspectral imaging and machine vision, wherein the intelligent tea leaf grading module is used for realizing accurate classification of raw materials; an AI-controlled dynamic withering module is used for optimizing enzyme activity and water evaporation; a pressure-rotating speed self-adaptive intelligent rolling module ensures that cells are uniformly broken; an electronic nose is combined with a multispectral real-time fermentation monitoring module to accurately control the fermentation degree; a far infrared-hot air coupled precise drying module is used for realizing gradient dehydration; the near infrared spectrum and deep learning quality detection module is used for completing finished product quality evaluation; the data traceability module of the block chain technology is used for recording whole-process processing parameters; and a big data-driven process optimization module continuously improves the product stability. According to the invention, the intellectualization, precision and standardization of the Qihong Huang tea processing process are realized, and the consistency and the superior product rate of the product quality are obviously improved.

The invention provides a control system and method for a Fourier interference infrared spectral imaging remote sensing instrument, and relates to the technical field of infrared remote sensing, and the system comprises a main control module, a sub-control module, a control interface, an execution element and a spectral imaging display system. And the main control module is used for controlling the sub-control module to control the execution element through the control interface according to a logic process set by a program so as to obtain Fourier interference infrared spectral imaging remote sensing data of an observation target, and completing display and control functions of a human-computer interaction interface through the spectral imaging display system. According to the invention, centralized control management of an optical-mechanical-electrical-thermal whole system of an instrument is realized, automatic work and operation of a remote sensing instrument system are realized, and rapid acquisition and analysis of Fourier interference infrared spectrum imaging are realized by using an area array detector.

The invention relates to the technical field of novel material chemical analysis, and discloses a triphenyl phosphate purity standard substance valuing method, which comprises the following steps: filtering, drying, dissolving and sterilizing a triphenyl phosphate sample; a triphenyl phosphate sample is comprehensively analyzed from different angles by comprehensively applying a GC-MS (Gas Chromatography-Mass Spectrometry) technology, an NMR (Nuclear Magnetic Resonance) technology, an infrared spectroscopy, a gas chromatography-flame ionization detector method, a Karl Fischer method and an inductively coupled plasma mass spectrometry, and finally, the purity value of the triphenyl phosphate purity standard substance is calculated by a mass balance method. The method provides a scientific and accurate technical means for quality control and standard formulation of the triphenyl phosphate product, has important practical application value for related industries in the fields of chemical engineering and material science, and is beneficial for improving the product quality and promoting industrial upgrading.

The invention discloses a fuel gas leakage detection system based on mid-infrared laser, relates to the technical field of fuel gas detection, and aims to solve the problems that a large-area region is difficult to cover quickly and only close-range detection can be carried out in an existing laser fuel gas leakage detection method. The gas leakage detection system comprises a laser emission module, an infrared imaging detector module and a data processing module, the laser emission module is used for emitting an intermediate infrared laser beam to a to-be-detected area; the infrared imaging detector module is used for collecting an infrared spectrum signal of the to-be-detected area in real time; the infrared spectrum transmitting module is used for transmitting the infrared spectrum signal to the data processing module; and the data processing module is used for processing the received infrared spectrum signal to obtain a gas leakage detection result of the to-be-detected area. The method is suitable for detecting gas leakage in a natural gas pipeline and a liquefied petroleum gas storage tank area.

The invention relates to the technical field of coal quality detection, in particular to a multi-source fusion spectrum coal quality rapid detection device and method. The near-infrared spectrum detection module is used for emitting near-infrared square light spots to the surface of the target coal sample so as to detect the overall spectrum characteristic data of the target coal sample; the X fluorescence spectrum detection module is used for performing multi-angle spectrum detection on the target coal sample to obtain element composition data in the target coal sample; the laser sensing module is used for vertically emitting a laser beam to the target coal sample and receiving corresponding reflected light so as to determine height information of the surface of the target coal sample; and the data processing module is used for fusing the overall spectral feature data and the element component data, calibrating fusion information according to the height information, and performing data processing operation on the spectral compensation information to calculate various coal quality indexes corresponding to the target coal sample, so that the adaptability to coal samples in different states is improved, and the coal quality index detection accuracy is improved. And the real-time detection requirement in the coal production process is met.

The invention discloses a near infrared spectrum reconstruction method based on stage perception mixed prior and a two-channel optical imaging system, and the method comprises the steps: constructing a deep expansion network model of stage perception mixed prior based on RGB guidance, and the network model comprises k cascade reconstruction stages, each reconstruction stage comprises a degradation perception residual gradient descent module and a near-end mapping module. According to the method, a degradation sensing residual error gradient descent module is introduced, the difference between a sensing matrix and an actual degradation process is effectively reduced through degradation learning, and the iteration process of a deep expansion network is divided into two stages of spectral space preliminary feature extraction and space detail deep extraction by applying a segmented optimization strategy; the network reconstruction precision is guaranteed, the optimization of the calculation efficiency is improved by adjusting the network complexity in stages, and the completeness and quality of the reconstructed image are guaranteed while the calculation overhead is reduced.