39 results about "Near infrared reflectance spectroscopy" patented technology

A device and method for identifying solid and powdered materials use near-infrared reflection spectroscopy combined with multivariate calibration methods for analysis of the spectral data. Near-infrared reflection spectroscopy is employed within either the 700-1100 nm or the 900-1700 nm wavelength range to identify solid or powdered materials and determine whether they match specific known materials. Uses include identifying solid and powdered materials with a fast measurement cycle time of about 2 to 15 seconds and with a method that requires no sample preparation, as well as quantitative analysis to determine the concentration of one or more chemical components in a solid or powdered sample that consists of a mixture of components. A primary application involving identification analysis verification of the identify and purity of powdered materials used for fabricating drug tablets and capsules for quality control purposes.

The invention discloses a method for rapid detection and authenticity identification of fatty acid of racy camellia oil by near infrared transmission spectroscopy (NITS). The method comprises the steps of: screening high quality varieties with oil content of 30%-60% from more than 130 camellia seed varieties, wherein in the camellia oil, the content of oleinic acid is 65%-85%, the content of linoleic acid is 5%-20%, the content of palmitic acid is 3%-15%, and the content of stearic acid is 1%-5%; establishing a near infrared transmission spectroscopy (NITS) model of the main fatty acids (oleinic acid, linoleic acid, palmitic acid, stearic acid and total unsaturated fatty acid) with a partial least squares (PLS) method by adopting the Fourier near infrared transmission spectroscopy (NITS), wherein the determination coefficients of the correction models of the oleinic acid, the linoleic acid and the palmitic acid respectively are 0.93446, 0.96538 and 0.88789, and the determination coefficients of cross validation respectively are 0.91987, 0.95755 and 0.84447; further verifying accuracy and reliability of five NIRS (Near Infrared Reflectance Spectroscopy) models by external verification so as to obtain related coefficients of the external verification, which respectively are 0.9424, 0.9682, 0.8862, 0.6834 and 0.7587; and evaluating doped camellia oil by establishing the NIRS model of binary system miscella of the camellia oil. The method is applicable to rapid measurement of the content of main fatty acids of the camellia oil and the doped camellia oil, has the characteristics of simplicity, convenience, rapidness and economy, and is suitable for industrial application.

The invention relates to a method for establishing a model for rapidly detecting the quality of synthetic borneol through near infrared reflectance spectroscopy. By means of the method, the problems about detection of authenticity of synthetic borneol variety and quality of synthetic borneol can be effectively solved. According to the technical scheme, the method comprises steps as follows: 1), a synthetic borneol sample is collected, original spectrums are collected, and the average spectrum is acquired; 2), a synthetic borneol water content consistency check model is established; 3), a first synthetic borneol identification consistency model is established; 4), a second synthetic borneol identification consistency model is established; and 5), a quantitative analysis model of borneol in synthetic borneol is established. According to the method, rapid detection of the quality of synthetic borneol is effectively guaranteed, fake and shoddy products are prevented, large-scale industrial production of synthetic borneol and body health of people are facilitated, and the method has an actual application value, can accurately detect the authenticity and quality of synthetic borneol, is good in use effect and is an innovation method for detecting authenticity of synthetic borneol variety and quality of synthetic borneol.

The invention discloses a soil heavy metal visible and near infrared reflection spectrum feature diagnosing method, comprising first selecting to measure a visible-near infrared reflection spectrum of a heavy metal compound; associating the heavy metal reflection spectrum with an external electron configuration of a heavy metal element; observing a reflection spectrum feature of the heavy metal compound; using a crystal field theory for analyzing wave band positions and reasons occurring at the feature reflection peak of the heavy metal; adding heavy metal compounds at different concentration gradients in a soil sample, and studying influences of the heavy metals with different types and different concentrations on the soil reflection spectrum; performing different spectra pretreatments on the sample reflection spectrum; researching linear correlation between the heavy metal concentration and soil reflection spectrum and position and potential theory for the occurrence of the obviously associated (p is smaller than 0.05) wave band. The studying method provides theoretical basis and experimental reference for qualitative and quantitive reflection spectrum analysis of soil heavy metal.

The invention discloses a method for measuring cellulose of a reconstituted tobacco by virtue of a near infrared reflectance spectroscopy technique. The method comprises the following steps: (1) collecting and preparing a representative sample; (2) collecting an original spectrum; (3) selecting a correcting sample set and a verifying sample set; (4) measuring a reference value of the sample; (5) carrying out pretreatment on spectrum; (6) establishing a PLC model; (7) verifying the model; and (8) measuring cellulose. The method disclosed by the invention is simple, feasible and fast. By adopting a near infrared spectrum nondestructive detection technology, not only can the analytical efficiency be enhanced and the cost be lowered, but the method also has obvious practicality for accurately measuring the cellulose of the reconstituted tobacco, improving the detection efficiency and objectively reflecting the product quality. The method disclosed by the invention has the advantages of high detection speed, no pollution, greenness and environmental protection, high accuracy, good repeatability and the like, and is suitable for on-site analysis and fast detection of the cellulose of a reconstituted tobacco product as well as online monitoring of fluctuation of product quality.

The invention discloses a novel method for rapidly detecting total sulfur in coal samples. The method comprises the following steps: S1. collecting and preparing a plurality of coal samples, and measuring the content of total sulfur in each sample by a conventional method; S2. scanning the coal samples with an NIRS (near infrared reflectance spectroscopy) analyzer, and collecting the spectral data and curves of the coal samples; S3. processing the spectral data of the samples, obtained in the S2, obtaining calibration equations of total sulfur through regression calculation, correcting and verifying the calibration equations of total sulphur, and building detection models; S4. directly filling a sample injector of the NIR instrument with the coal samples to be detected in sequence, starting a scan key, automatically recording and storing the spectra of the samples by the NIR instrument, determining the types of the attributive spectrograms of the samples, selecting corresponding detection models, and obtaining detection results. The method provided by the invention has the beneficial effects that the accuracy of the method meets the requirements of the reproducibility tolerance of current standard methods; the method is quite easy, convenient and rapid to operate, and scan detection of one sample can be completed in about 50 seconds, including data output; sample weighing and addition of any chemical reagent are not needed in the whole detection operation process, so that the method has the characteristics of high speed, convenience and no pollution.

The invention relates to a split pork carcass fat and lean thickness nondestructive measurement system based on near-infrared light.The system comprises a near-infrared emission light source, a near-infrared reflection spectrum acquisition instrument, an emitted and reflected light conduction module, a probe, a pork carcass clamping device, a displacement detection device and a controller module; emitted light emitted by the near-infrared emission light source and reflected light of the near-infrared reflection spectrum acquisition instrument are subjected to conduction through optical fibers of the emitted and reflected light conduction module; the optical fibers are encapsulated inside the probe; the pork carcass clamping device is used for positioning and clamping a split pork carcass which is on the slaughtering production line and is in a moving state; the controller is used for processing a spectrum signal output by the near-infrared reflection spectrum acquisition instrument and a signal output by the displacement detection device, and non-contact and nondestructive measurement with line is conducted on fat and lean thickness of live pigs on the production line.The split pork carcass fat and lean thickness nondestructive measurement system based on the near-infrared light has the advantages of being low in power consumption, long in service life, easy to operate and the like.

The invention discloses a seed vigor determining method and system based on NIRS and a storage medium. The method comprises the following steps: obtaining an index component measured value according to sample seeds and original near infrared transmitted spectra of the sample seeds; pre-processing the original near infrared transmitted spectra of the sample seeds, including detrending and mean centralizing; determining a modeling method according to the index component measured value; constructing a PLSR model according to the pre-processed result based on the determined modeling method; and determining the seed vigor through the PLSR model. The PLSR model capable of predicting the seed vigor is established based on near-infrared reflectance spectroscopy, so that the seed vigor predicting speed is accelerated greatly and the seed vigor predicting accuracy is improved. In addition, a lot of detection equipment is not used, so that the cost is lowered. The method and system can be widelyapplied to the technical field of infrared analysis.

The invention discloses a method for recognizing the walking intention based on brain hemoglobin information. The method for recognizing the walking intention based on the brain hemoglobin informationcomprises the steps that (1) cerebral cortex hemoglobin concentration signals are obtained, specifically, the cerebral cortex hemoglobin concentration signals are obtained in the mode that a testingexperiment is conducted by applying a near infrared reflectance spectroscopy (NIRS) brain imaging technology, and a subject completes the corresponding walking task in a fixed area; and (2) through aband-pass filtering technology, the cerebral cortex hemoglobin concentration signals recorded in the experiment are subjected to data pre-processing, and the cerebral cortex hemoglobin concentration signals with multiple frequency bands are extracted. The method has the beneficial effects that the NIRS brain imaging technology is applied for the testing experiment, and the method is easy and convenient to operate and has the portable advantage.

The invention discloses NIRS technology based muscle oxygenation detection equipment, which comprises an electrode, a light source, a proximal receiving end, a distal receiving end, a temperature sensor, a microprocessor, and a power supply. The provided NIRS based muscle oxygenation detection equipment has the characteristics of small volume, simple control and stable performance.

The present invention discloses a three-dimensional multispectral insect distinguishing device and an identifying method thereof. The three-dimensional multispectral insect distinguishing device includes: a handheld probe, which is provided with a first camera, a second camera, a first video interface, a second video interface, a white-light source, an LED light, a first switch, a control module, and a battery; and dual-channel video glasses. The three-dimensional multispectral insect distinguishing device further includes a processing apparatus used obtain a disparity spectrum between the insect and a near infrared reflectivity spectrum of the visible light of the background object according to the insect and the near infrared reflectivity spectrum of the visible light of the background object, to get the wavelength of a preset scope of the peak value of the disparity spectrum. Upon inspection, the tested object is illuminated by the ray of light within the maximum disparity spectrum scope output by the LED light, to enhance the contrast between the insect and the background, which greatly improves the positive rate of the insect. In addition, a three-dimensional image is generated by the dual-channel video glasses, which may reduce confusion between planar plaque or cavity and three-dimensional objects, thereby further increasing the positive rate of the insect.

The invention discloses a waste plastic spectrum identification method based on an XGBoost model. The method comprises the following steps: acquiring near-infrared reflectivity spectrum data of various plastics by using a near-infrared spectrometer; pCA analysis is carried out on the original spectral data, and the data dimension is reduced; an XGBoost algorithm is used to establish a waste plastic algorithm identification model; optimizing the performance of the recognition model by adopting grid search and K-fold cross validation, and finally establishing the recognition model; and based on the trained identification model, extracting the near infrared spectrum of the to-be-identified plastic sample, and identifying the near infrared reflection spectrum of the to-be-identified plastic sample according to the identification model to obtain an identification result of the to-be-identified plastic sample. According to the method, the data processing time is shortened, meanwhile, the accuracy of identifying various common plastics is improved, and application in actual production is facilitated.