243 results about "Infrared spectroscopy" patented technology

The invention discloses a method for detecting the nitrogen content of organ tissues of different varieties of oilseed rapes based on visible near-infrared spectroscopy, which comprises the following steps: firstly, collecting oilseed rape leaf, shell, stalk and root system samples under the conditions of multiple varieties and multiple nitrogen fertilizer levels, and acquiring spectral data within the range of 430-2500nm by using a visible near-infrared spectroscopy; and a Kjeldahl method is synchronously adopted to measure the real nitrogen content as a reference value. Preprocessing the spectral data, including de-noising, standard normal variable transformation, multivariate scatter correction and derivative processing, so as to weaken the influence of scattering and baseline drift; characteristic wavelengths related to the nitrogen content are screened through stepwise regression, variable projection importance, competitive self-adaptive reweighted sampling, a continuous projection algorithm and other methods, and a random forest model, a support vector machine model, a partial least squares discriminant analysis model, a partial least squares regression model, a support vector regression model, an XGBoost model and other models are combined. And respectively constructing a classification identification model and a regression prediction model.

The invention relates to the technical field of attention deficit hyperactivity disorder detection, and discloses a device for detecting cognitive and developmental conditions of children with hyperactivity disorder, which comprises a handle, a head-mounted device, a bracelet, a hierarchical adaptive algorithm module, a multi-dimensional execution module and a data fusion and analysis module, a multi-mode sensing module is arranged in each of the handle, the head-mounted device and the bracelet; a motion capture unit, a high-sensitivity key array, a tactile feedback module and a wireless transmission module are integrated in the handle, and a wireless electroencephalogram acquisition module, a miniature near infrared spectrum module and an eye movement tracking module are integrated in the head-mounted device. According to the invention, through deep fusion of a multi-dimensional cognitive evaluation system and gamepad hardware, the device not only breaks through the limitation of the traditional neuropsychological test in methodology, but also realizes refined capture of ADHD heterogeneity characteristics in the technical level, and provides a hardware basis for establishing an objective and quantitative diagnostic tool with high ecological efficiency.

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 provides a method for rapidly and non-destructively detecting the quality of beet seeds based on a near infrared spectrum technology, and relates to the technical field of non-destructive detection of the quality of the seeds, the near infrared spectrum of the beet seeds is collected, and the characteristic wavelength is extracted through an improved competitive self-adaptive reweighted sampling algorithm; meanwhile, depth features are extracted by using a customized convolutional neural network, and the depth features and the depth features are fused to form a fusion feature vector with high characterization force. Secondly, establishing a quality scoring system based on key agronomic characters after single seed sowing, and constructing a spectral feature and quality score contrast database; for to-be-tested seeds, the most reliable reference seed group is screened out from the database by calculating the weighted similarity and adopting a dual dynamic threshold strategy. And finally, in combination with the local space density of the reference seed and the correlation degree between the reference seed and the to-be-detected seed, carrying out credibility weighted local regression calculation, accurately predicting the final quality score of the to-be-detected seed, and realizing grading judgment.

The invention relates to a method for detecting the INDF content in TMR of lactating cattle based on a near infrared spectrum. The method comprises the following steps: constructing a near infrared spectrum model capable of being used for detecting the INDF content; wherein a sample set for constructing the near infrared spectrum model comprises near infrared spectrum data corresponding to a lactating cattle TMR sample and an INDF actual value; the method comprises the following steps: extracting a wavelength point with a non-zero coefficient in near infrared spectrum data, and taking the wavelength point as a characteristic variable; constructing a near infrared spectrum model based on the characteristic variables and the corresponding INDF actual values by adopting a partial least squares regression algorithm; model parameters are optimized through a cross validation method, an optimal model parameter combination is determined by combining a cross validation root mean square error RMSECV and an external validation root mean square error RMSEP, and a near infrared spectrum model capable of being used for INDF content detection is obtained; and inputting near infrared spectrum data of a to-be-detected lactating cattle TMR sample into the near infrared spectrum model to obtain an INDF content detection result.

The invention relates to the technical field of trace detection, in particular to a rapid nondestructive detection method for phellinus igniarius polysaccharide content based on a near infrared spectrum technology. The method comprises the following steps: acquiring an original spectrum set of phellinus igniarius samples from various sources under a near infrared spectrum, and dividing the samples from the same source into the same group of original spectrum curves; evaluating the stability and distinguishing capability of light absorption change in different wavelength intervals, and obtaining the light absorption credibility of each target wavelength of the original spectrum curve; analyzing the morphological difference of a single curve in each group of spectrum curves relative to the whole group of curves, and obtaining an initial judgment coefficient for curve smoothing processing; and combining the light absorption credibility with the initial judgment coefficient, performing corresponding smoothing processing on each original spectrum curve according to the determined window length and processing order, and analyzing the actual polysaccharide content of the phellinus igniarius sample of the corresponding type. According to the technical scheme, the accuracy of polysaccharide content detection of phellinus igniarius through near infrared spectroscopy is improved.

The invention relates to the technical field of gas leakage detection, and discloses a gas sensor-based gas leakage detection system and method. The system comprises a dynamic gas concentration acquisition module, a leakage feature extraction module, a risk area modeling module, a multi-mode verification module and a grading response control module. The acquisition module acquires multi-dimensional concentration data through a distributed sensor array and a self-adaptive sampling mechanism; the feature extraction module separates steady-state background and transient leakage features through spatial-temporal feature decomposition and generates feature vectors; the risk modeling module constructs a three-dimensional diffusion model, and outputs potential leakage point coordinates with confidence in combination with a hydrodynamic equation; the multi-modal verification module generates a fusion result through infrared spectrum and sound wave detection cross validation; and the grading response module is matched with the strategy library to dynamically generate a gradient control instruction. According to the system, accurate detection, positioning and graded response of gas leakage are realized, and the comprehensiveness of leakage monitoring and the pertinence of emergency treatment are improved.

The invention relates to an all-solid-state battery thin-layer electrode device for multi-mode in-situ interface research. The all-solid-state battery thin-layer electrode device comprises the following components: a solid electrolyte substrate; the functional thin layer is arranged on the surface of the solid electrolyte substrate; the functional thin layer has conductivity; the functionalized thin layer allows a detection signal of an in-situ characterization technology to effectively penetrate or be reflected from the surface of the functionalized thin layer; the in-situ characterization techniques include atomic force microscopes, optical microscopes, and Raman spectroscopy, X-ray photoelectron spectroscopy, infrared spectroscopy, or X-ray diffraction. The invention provides a universal thin-layer electrode design and system and a thin-layer electrode in-situ imaging and spectroscopic characterization method for all-solid-state battery interface reaction. The objective of the invention is to expose a solid electrolyte-electrode interface reaction process which is difficult to observe in an effective detection range of various characterization technologies so as to realize real-time and in-situ visualization and accurate analysis of a dynamic evolution process of an internal interface of an all-solid-state battery.

The invention discloses a method for detecting the water absorption rate of silicone rubber by combining near infrared spectroscopy with CPO-SVM, and belongs to the technical field of detection of high- The invention aims to solve the problems of destructive sampling, complex operation, sensitivity interference, strong subjectivity of indirect evaluation and the like in the traditional detection method. The method comprises the following steps: firstly, obtaining a composite insulator silicone rubber sample, and collecting near infrared spectrum data of the composite insulator silicone rubber sample; then, carrying out standard normal variable transformation pretreatment on the spectroscopic data to eliminate interference caused by physical property difference on the surface of the sample; then, accurately extracting a key wavelength from the high-dimensional spectral data by using a competitive self-adaptive reweighting algorithm; and finally, establishing a support vector machine model optimized by a crown porcupine optimization algorithm, and carrying out quantitative analysis on the water absorption rate of the silicone rubber. According to the method, rapid, accurate and nondestructive detection of the water absorption rate of the silicone rubber is realized, real-time and reliable data support is provided for operation and maintenance of a high-voltage insulating material, safe and stable operation of a power grid is effectively guaranteed, and the method has a wide application prospect.

A user interface system enables communication through inaudible speech by detecting physiological signals associated with inner voice communication. The system includes a wearable device positioned in, on, or around a user's ear, housing one or more sensor modalities such as electromyography (EMG) sensors for detecting muscle movements, functional near-infrared spectroscopy (fNIR) sensors for brain activity, and / or detection-and-ranging systems using sonar or radar for micro-deformations. Pre-processing modules condition the sensor data, which is then analyzed by one or more machine learning models to reconstruct the content of the user's inaudible communication and produce output representations. The system enables high-bandwidth natural language interaction without audible vocalization, maintaining privacy while supporting applications including AI assistant interaction, real-time translation, secure authentication, and inter-party communication.

To provide a toner that achieves both low-temperature fixation and storage stability in high-temperature environments. [Solution] A toner containing a graft polymer resin including a polyolefin resin and a styrene-based resin, a polyester resin, and a release agent, wherein when the toner heated to 50°C is measured by FTIR-ATR (total internal reflection absorption infrared spectroscopy), the peak intensity derived from the release agent is set to Wk-50 and the peak intensity derived from the polyester resin is set to RK-50; when the toner heated to 70°C is measured by FTIR-ATR, the peak intensity derived from the release agent is set to Wk-70 and the peak intensity derived from the polyester resin is set to RK-70; and when the toner heated to 90°C is measured by FTIR-ATR, the peak intensity derived from the release agent is set to Wk-90 and the peak intensity derived from the polyester resin is set to RK-90, the toner satisfies the following formulas (1) and (2). (Wk-70 / RK-70) / (Wk-50 / RK-50)≦1.1···(1) 1.5≦(Wk-90 / RK-90) / (Wk-50 / RK-50) (2)

Provided are a non-ribosomal antifungal peptide MaAFP1, a preparation method therefor and a use thereof. The molecular formula of the antifungal peptide MaAFP1 is C41H74N18O12, wherein an amino acid sequence from the N-terminus to the C-terminus is (D)Arg-(L)Arg(OH)-(D)Orn-(L)Thr-(D)Orn-(L)Arg(OH)-(D)Tyr. Fermentation is performed by using Metarhizium anisopliae CQMa421, a fermentation broth is collected, and separation and purification are performed by means of ion exchange chromatography and high performance liquid chromatography so as to obtain the antifungal peptide MaAFP1. The structure of MaAFP1 is analyzed by comprehensively using an Edman degradation method, mass spectrometry, infrared spectroscopy, nuclear magnetic resonance spectroscopy, and circular dichroism spectroscopy. By performing an in vitro bacteriostatic test, it is found that MaAFP1 has a good inhibitory effect on a variety of animal and plant pathogenic fungi, and has the value of the development of a novel antibacterial drug.

Disclosed is a method for characterising tinnitus in a subject using functional near-infrared spectroscopy (fNIRS). The method comprises receiving data comprising fNIRS signals indicative of cortical activity in one or more regions of the subject's brain at a processing device. The received data is processed using the processor device by inputting one or more feature values into a model, where the feature values include one or more features of the received data. The model is configured to provide one or more classification results based on the one or more feature values, the classification results being indicative of at least one characteristic of tinnitus in the subject. Also disclosed is a system for applying the disclosed method.

The invention belongs to the technical field of synthesis of organic compounds, and particularly relates to a process for preparing fipronil and an intermediate thereof. Toxic 1, 2-dichloroethane is comprehensively replaced by bio-based gamma-valerolactone, low-toxicity cyclopentyl methyl ether is matched, and N, N-dimethylformamide necessary for the process is recycled, so that consumption is greatly reduced; the continuous processes of amination, diazotization and the like are realized through a tubular reactor, a micro-reactor and a static mixer, and separation technologies such as pervaporation membrane and vacuum distillation are combined, so that the reaction time is shortened, the solvent recovery rate is increased, and the production is promoted to be continuously transformed to green. The supported FeCl3 / SiO2-NH2 catalyst disclosed by the invention can be repeatedly used, and byproducts and tail gas can be recycled and reused. In addition, diazonium salt residues are controlled to be smaller than or equal to 0.5% through near infrared spectroscopy, citric acid is subjected to stable oxidation reaction, a purification process is combined, it is ensured that the finished product is high in purity, excellent in yield and small in batch fluctuation, and efficiency and safety are both considered.

The invention discloses a soil micro-plastic microscopic Fourier infrared spectrum rapid detection method, and relates to the technical field of environmental pollutant analysis and detection.The method comprises the steps that a soil sample of a target area is collected; performing micro-plastic separation and extraction on the soil sample to obtain a micro-plastic sample; performing vacuum filtration on the micro-plastic sample and transferring the micro-plastic sample to a to-be-detected filter membrane; performing Fourier infrared microscopic scanning on the filter membrane to be detected to obtain a Mosaic image; carrying out particle point positioning on the Mosaic image by adopting a Fourier infrared detection method, and collecting spectral information of each particle point; the spectrum information of each particle point is matched with a micro-plastic standard spectrum library, micro-plastic type information of each particle point is determined, and a detection report is generated and comprises the point position matching rate, the area ratio, the particle length, the particle width and the content of different types of micro-plastics. According to the invention, rapid and accurate detection of the soil micro-plastic can be realized, and the detection precision and efficiency of the soil micro-plastic can be improved.

This invention discloses a method for identifying waste textiles based on near-infrared spectroscopy, comprising: constructing a near-infrared spectral sequence set; denoising and smoothing, and sample expansion; training an autoencoder; using the autoencoder to extract features from the near-infrared spectral sequences to obtain reconstructed spectra; using a dual-threshold method to screen key bands in the reconstructed spectra; constructing a dataset using key bands and waste textile type labels; training a classifier using K-fold cross-validation, with K independent classifiers forming a classification model; and collecting near-infrared spectral sequences of the waste textiles to be detected to obtain the identification results. The autoencoder can filter out the most discriminative bands from the data itself while reducing dimensionality; the screening of key bands reduces redundancy in spectral data; and the classification model can more comprehensively capture the correlation between spectral data and waste textile type labels, making the classification and identification of waste textiles suitable for large-scale recycling needs.

The present invention relates to a method for detecting and removing a motion artifact of a functional near-infrared spectroscopy signal. Disclosed are a method and a device for detecting and removing a motion artifact of a near-infrared spectroscopy signal in real time on the basis of an artificial neural network model, the method comprising: a conversion step of converting time series data of functional near-infrared spectroscopy signals measured through a plurality of channels from a target into image data; a detection step of detecting whether noise is present in the converted image data using a pretrained detection model; and a removal step of removing noise from image data where noise has been detected using a pretrained noise removal model.

The invention relates to a method and an apparatus for the process-optimized production of manufactured wood boards, in particular oriented strand boards. In order to provide a method and an apparatus for the process-optimized production of manufactured wood products which make it possible to optimize quality while providing continuous quality assurance, which allow the best possible control variables to be determined particularly easily and quickly, and which also guarantee continuous production that results in the lowest possible wastage while maintaining the highest possible level of process stability, the invention provides the following: at least one process parameter, in particular the water content and / or the quantity of adhesive applied to the raw chip material, is measured in the course of the method by means of near-infrared spectroscopy; the measured values of the at least one process parameter are then sent to a control unit for process optimization and / or process-optimized control of the method, wherein the measurement of the at least one process parameter is taken at one or more positions, selected from: a position immediately upstream of the gluing, in particular between a dry raw chip hopper and the gluing station; a position immediately downstream of the gluing, in particular between the gluing station and a chip material distributor and / or a dispersing station; a position in the provision phase immediately downstream of a timber yard, in particular between the timber yard and a subsequent dryer; and / or a position in the provision phase immediately downstream of a dryer, in particular between the dryer and a sieving station and / or a dry raw chip hopper.

According to the ginseng extraction system and method provided by the invention, the dual goals of high purity and high yield of ginsenoside extraction are achieved through raw material adaptive parameter pre-optimization, self-adaptive cascade purification and activity protection, the enrichment effect of high-value monomer saponin is remarkable, and the loss of active ingredients is accurately controlled. According to the application, a detection-decision-regulation full-process closed-loop intelligent control system is constructed, near infrared spectrum rapid screening and HPLC-MS / MS accurate quantitative dual-mode online detection are fused, real-time and accurate monitoring of the saponin content is realized, and off-line detection and artificial experience parameters are not needed; the multi-target central control unit can automatically decide a purification path and process parameters according to detection data, and designs such as membrane pollution on-line monitoring, automatic backwashing and solvent circulating preheating are combined, so that continuous operation of the process is ensured, and production interruption caused by equipment failure and process fluctuation is avoided.

The invention relates to the technical field of wheat quality detection, and discloses a wheat quality rapid detection system based on a near infrared spectrum. The system comprises five modules: a spectral feature dynamic acquisition module, an environmental parameter coupling analysis module, a spectral precision evaluation module, a detection state control module and a spectral resource optimization module. The spectral characteristic dynamic acquisition module acquires near infrared spectral reflectivity data of a wheat sample, and divides sample areas with different detection attention degrees; the environment parameter coupling analysis module collects growth environment parameters, and integrates the growth environment parameters with the spectral data of the corresponding region to generate an environment coupling analysis data set; the spectral precision evaluation module calculates the real-time detection accuracy according to the difference between the historical reference of the sample area in the data set and the real-time detection quality index; the detection state control module switches the load state of the spectrum acquisition channel in combination with the accuracy and a preset threshold value; and the spectrum resource optimization module allocates resources according to the load state. The system improves detection pertinence, reliability and resource utilization rate, and meets rapid detection requirements.

The present application relates to the field of crop genetic breeding and molecular biology, and particularly relates to a highland barley beta-glucan screening index system and a major gene positioning method, which comprises the following steps: firstly, a three-dimensional coupling screening system of genetic stability, functional activity and agronomic adaptability is constructed, the index combination weight is determined by using an entropy weight method and an analytic hierarchy process, and an AMMI model is combined to correct the environmental effect and calculate the comprehensive score of the germplasm; secondly, a recombinant inbred line and a natural germplasm double positioning population is constructed, and near-infrared spectroscopy is combined with a Transformer model to quickly obtain phenotype data; thirdly, a candidate major effective segment is obtained through double population joint positioning, a major effective gene is screened out by combining a transcriptome and a metabolome co-expression network, and a functional molecular marker is developed. The present application realizes accurate evaluation of highland barley germplasm and accurate positioning of major effective genes, and the phenotype detection is efficient and lossless, the molecular marker selection is accurate, and the present application can also be applied to other cereal crops.

This invention discloses a method for preparing selenized Ophiopogon japonicus polysaccharide, its structural characterization, and its applications. The preparation method includes: dissolving Ophiopogon japonicus polysaccharide in dilute nitric acid, adding sodium selenite, reacting at 50–90°C for 4–12 hours, adjusting the pH to neutral, and obtaining selenized Ophiopogon japonicus polysaccharide after dialysis, concentration, and freeze-drying. Structural characterization was performed using ultraviolet spectroscopy, infrared spectroscopy, and scanning electron microscopy, showing that selenium was successfully linked to the polysaccharide molecule in the form of selenite ester. Multiple cell experiments showed that: CCK-8 assay results indicated that the polysaccharide had no significant toxicity to RAW264.7 cells in the concentration range of 25–100 μg / mL; Griess assay and ELISA results showed that the polysaccharide significantly inhibited LPS-induced release of NO, TNF-α, and IL-6 from macrophages in a concentration-dependent manner; GC-MS analysis of the metabolite lactate revealed its anti-inflammatory mechanism at the metabolic level. Animal experiments showed that the selenized Ophiopogon japonicus polysaccharide significantly reduced the inflammatory response in a mouse skin burn model and promoted wound healing. The process of this invention is simple and the conditions are mild. The selenized Ophiopogon japonicus polysaccharide prepared has good anti-inflammatory activity and can be used to prepare drugs for treating skin burns and inflammation.

A surgical stapler system for real-time tissue perfusion assessment during clamping includes a powered surgical stapler with a handle assembly, adapter assembly, and an end effector comprising a reload assembly with staples and an anvil assembly. Integrated into the system is a near-infrared spectroscopy (NIRS) system featuring light sources and photodetectors. The method involves clamping tissue between the reload and anvil assemblies, transmitting near-infrared light through the clamped tissue, and detecting backscattered light to determine tissue perfusion levels. The perfusion data is processed and displayed in real-time, allowing adjustments to the clamping force to ensure adequate perfusion before stapling. The system enhances surgical outcomes by providing real-time feedback on tissue viability during critical phases of the stapling procedure.

This invention relates to the field of infrared spectroscopy detection technology, specifically an in-situ online infrared spectroscopy detection system and method. The system includes: a biomimetic dynamic response material module, used to enhance probe contact pressure through temperature-responsive deformation and specifically capture target molecules through a molecularly imprinted cavity; a quantum-enhanced detection module, composed of a quantum dot infrared enhancement array and an optical phased array spectral scanning module, used to complete spectral acquisition of the molecularly imprinted cavity capture region; an AI-driven closed-loop control module, used to predict reaction paths in real time, optimize temperature / pressure / flow rate parameters, and trigger millisecond-level emergency quenching in case of anomalies; and a self-powered wireless sensor network, used to collect vibrational energy and be self-powered by a supercapacitor, combined with terahertz wireless communication for data transmission. This invention solves the three major bottlenecks of traditional technologies—low sensitivity, high latency, and the need for perforated wiring—through a biomimetic interface quantum-enhanced detection → cableless power transmission → AI millisecond-level decision-making closed loop.

The utility model relates to a tabletting device for infrared spectroscopy, which belongs to the technical field of tabletting equipment and comprises a tabletting machine main body, a mounting plate is fixedly mounted at the upper end of the tabletting machine main body, a lead screw with a crank at one end is in threaded connection with the middle position of one end of the mounting plate, and a workbench for placing a tabletting die is fixedly mounted on the tabletting machine main body. Square grooves are formed in the two sides of the upper end of the workbench, movable arc-shaped limiting plates are installed in the square grooves through driving assemblies, a cleaning assembly used for cleaning the workbench is installed at one end of the installing plate, one end of the cleaning assembly is connected with the arc-shaped limiting plates, and an integrated control panel is fixedly installed at one end of the tablet press body. By simultaneously and oppositely moving the arc-shaped limiting plates, the tabletting die is automatically positioned, manual positioning by workers is not needed, the tabletting die is convenient and fast to use, the tabletting effect is improved, impurities such as powder attached to the surface of the workbench can be automatically cleaned through the dust collection holes, time and labor are saved, and the burden of the workers is relieved.

This invention discloses a green synthesis process for 2-chloropyranose-1-yl)-4'-ethoxydiphenylmethane, belonging to the field of pharmaceutical intermediate preparation. The method involves forming a mixture of a substrate in the protected state of Formula I and a reducing agent containing siloxane bonds, which is continuously fed into a microreactor loaded with a confined-domain MOF (Metal-Oxide-Fractions) supported catalyst for room-temperature reduction. The MOF catalyst has a rigid pore size of 1.2~2.5 nm and internally coordinates and anchors metal trifluoromethanesulfonate. This invention utilizes the limiting confinement effect of rigid channels to lock the substrate conformation, blocking the surface attack of reactants and achieving extremely high configuration selectivity. Simultaneously, the efficient mass transfer of the continuous flow microchannel and the online infrared spectroscopy closed-loop control system completely eliminate the need for traditional cryogenic conditions, remove highly corrosive fluorine-containing waste liquid, significantly reduce synthesis costs, and achieve efficient, green, and stable continuous industrial production of this core intermediate.

The invention discloses a method for predicting solid content in a traditional Chinese medicine extraction process based on deep learning, which comprises the following steps of: collecting multiple variables such as ethyl acetate temperature, total liquid inlet flow velocity, total liquid inlet flow accumulation, total gate valve opening and the like in an extraction section, and synchronously aligning with the solid content obtained by near infrared spectrum conversion; performing exception handling, standardization and sliding time window sample establishment; constructing a'stacked GRU + feature attention + regression layer 'model, adopting gradient descent end-to-end training, and performing verification selection by using RMSE, R2 and MAPE; and after online, inputting by using a minute-level window to realize online and real-time prediction of the solid content. According to the method, an existing device does not need to be transformed, the prediction precision and robustness under complex working conditions are improved, and support is provided for extraction quality trend interpretation and early warning.

This invention belongs to the field of spectral detection technology, specifically relating to a method for detecting the nutritional status of honeysuckle plants based on near-infrared spectroscopy. It aims to solve the problems of strong specular reflection interference, moisture background shielding of nutrient signals, and insufficient applicability throughout the entire growth period in in-situ detection of live honeysuckle. The method suppresses specular reflection on the leaf surface through orthogonal extinction and collects deep diffuse reflectance spectra; it obtains standardized reflectance using real-time background difference and dark current compensation; it achieves moisture background decoupling through orthogonal signal correction and external parameter orthogonalization; it extracts feature wavelength vectors through multi-scale continuous wavelet transform; it inputs a deep residual network model with a self-attention mechanism and combines it with a phenological adaptive compensation algorithm to invert nutrient quality fractions; finally, it compares the results with a nutrient critical value database for the entire growth period to calculate the surplus / deficit index and complete nutrient diagnosis. This significantly improves the spectral signal-to-noise ratio and detection accuracy, achieving rapid and stable detection of the nutritional status of live honeysuckle throughout the entire growth period.

This invention relates to the field of near-infrared analysis technology, specifically to a system for analyzing the uniformity of multi-bin cotton blending in a cotton cleaning machine based on near-infrared spectroscopy. The system includes: acquiring near-infrared spectral curves and cotton bin humidity at different sampling times; analyzing the effects of baseline shifting and curve scaling based on fluctuations in the spectral curves to identify abnormal curves; determining the scattering coefficients of abnormal states based on the abnormal state parameters and humidity changes of all abnormal curves; removing the wavelength range absorbed by hydroxyl bonds from the abnormal curves to obtain de-hydroxyl bond curves; determining the degree of influence of hydroxyl bond absorption effect by combining the difference in scattering coefficients between the abnormal curves and the corresponding de-hydroxyl bond curves; and finally, adjusting the ventilation efficiency in the cotton bins according to the degree of influence to achieve uniformity analysis. This invention can effectively analyze the impact of cotton bin humidity on noise interference generated during spectral detection, improving the accuracy of detection results when detecting the uniformity of multi-bin cotton blending.