205 results about "Spectral database" patented technology

A hyperspectral image sparse unmixing method based on random projection includes the following four main steps: (1) data are read by a computer under the environment of MATLAB R2008b; (2) the hyperspectral image data and the hyperspectral library data are randomly projected by the computer; (3) a target function for sparse unmixing is constructed, and the split Bregman algorithm is used for optimizing the target function and working out an extremum until reaching convergence and stopping conditions; (4) an appropriate threshold value is set to process a abundance fraction matrix, so that a final abundance fraction graph and end members can be obtained. The hyperspectral image sparse unmixing method based on random projection utilizes a hyperspectral database to choose the end members, and overcomes the defect that the end members worked out by the conventional algorithm cannot strictly correspond to the spectra of pure materials in the standard hyperspectral database; and moreover, the hyperspectral image sparse unmixing method based on random projection uses the random projection technology to carry out dimensionality reduction on raw data, thus achieving the effects of saving memories and reducing the calculation load. The hyperspectral image sparse unmixing method based on random projection realizes rapid quantitative analysis on hyperspectral images, and has practical value and a broad application prospect in the field of hyperspectral remote sensing image analysis.

The invention discloses a method for determining the character parameters of a eutrophia water body by adopting a spectrum technology. The steps of the method are as follows: building a spectrum database of corrected sample collection; pretreating the spectrum; building a correcting module; distilling spectrum characteristics; determining the water quality character parameters of an unknown sample. The method has the following advantages of (1) utilizing the spectrum technology for analyzing the character parameters of the eutrophia water body and greatly accelerating the analyzing speed; (2) using no chemical reagents, thus reducing detecting cost and not polluting environment; (3) compared with a chemical method, system errors and artificial errors are reduced greatly, thus improving measuring precision; (4) being capable of simultaneously analyzing and detecting a plurality of water quality parameters, thus saving time and a real-time detecting technology can be better applied to environment monitoring; (5) having excellent social and economic benefits. By being further popularized, the method has good effects on solving the escalating eutrophia problems of lakes and marsh water-area environment at present.

A method for multivariate adulteration detection on an edible oil includes (1) construction of a model: S1, acquiring near-infrared spectra of edible oils; S2, establishing a near-infrared spectral database of the edible oils; S3, establishing a multivariate adulteration detection model for a type of edible oil; and (2) application of the model: acquiring spectra of a sample to be tested according to the near-infrared spectral signal acquisition method in step S1, preprocessing the obtained near-infrared spectra by using the method in step S2 to obtain near-infrared spectral data of the sample, and determining the authenticity of the sample to be tested by using the multivariate adulteration detection model for the edible oil established in step S3. The method is simple and rapid in operation, can effectively and rapidly screen the authenticity of an edible vegetable oil, and has strong practicability.

The invention provides a cloud spectrum database-based miniature spectrometer and a spectrum detection method. The miniature spectrometer comprises a power supply, a light source, a spectroscopic imaging module, a control module, a communication module, and an intelligent mobile terminal provided with a display assembly, the intelligent mobile terminal is connected with the communication module to communicate with the control module and is suitable for connecting with a cloud processor including a cloud spectrum database, spectrum information of a sample on the cloud processor is compared with the spectrum database, and a comparison result is displayed on the display module of the intelligent mobile terminal. The spectrum database is arranged on the cloud processor, so the spectrum database chip and the processing module group of the miniature spectrometer have small size, and the dimension of the miniature spectrometer is shortened, thereby the miniature spectrometer is convenient to carry.

The invention provides an oil gas prospecting method and system, and the method comprises the steps of: using ground spectrometer to measure ground object spectrum data in study region; using digital camera to collect ground object description data in the study region; collecting ground surface sample data and measuring condition data; using portable GPS to collect measured ground object coordinate data in the study region; according to the ground object spectrum data, ground object description data, ground surface sample data, measuring condition data and measured ground object coordinate data to generate ground object spectrum database in the study region; using satellite or airplane-carried high spectrum imager to collect ground object high spectrum remotely sensed image data in the study region; processing the data in the ground object spectrum database and ground object high spectrum remotely sensed image data to obtain oil gas prospecting target region data.

The invention discloses an LED agricultural lighting system based on a combined spectrum. The LED agricultural lighting system comprises an LED plant growth lamp, a light environment control module, a spectrum collection device, a light radiation illuminometer, a combined spectrum database and a processor. The processor is connected with the light environment control module, the spectrum collection device, the light radiation illuminometer and the combined spectrum database. The light environment control module is connected with the LED plant growth lamp. By means of the LED agricultural lighting system and method, a lighting light environment with the optimum spectrum can be provided for different plants at different growth periods, growth efficiency is improved, and the effects of energy conservation and environmental protection are achieved.

The invention relates to a method for measuring concentrations of sulfate, nitrate solutions by utilizing the terahertz time-domain spectroscopy. The method comprises the following steps: sample cells are selected, standard solution samples with different concentrations are prepared, terahertz time-domain spectra of the standard solution samples are measured, a terahertz time-domain spectra database of the standard solution samples is built, and the database comprises time-domain spectra, frequency-domain spectra, relation spectra of concentrations and absorption coefficients, relation spectra of concentrations and refractive indexes, relation spectra of concentrations and extinction coefficients of the standard solution samples. Terahertz time-domain spectra of the solutions to be measured are measured, the data is processed to obtain absorption coefficients of the solutions to be measured, and according to the terahertz time-domain spectra database of the standard solution samples, the concentrations of the solutions to be measured are analyzed and determined. The method utilizes the terahertz time-domain spectroscopy to measure solution concentrations, and is advantaged by simple operations, rapid measurement, simple data processing procedures, good repeatability, and high accuracy of results.

The invention discloses an oil type identification method. The oil spill fluorescence spectra of serial concentrations in a certain concentration range are taken as fingerprint identification indexes to identify oil types, and can be considered as a traditional fluorescence spectrum plus a dimensionality that is the concentration so as to obtain more fluorescence signals of an oil spill sample, thus improving capability of identifying the oil types. The identification method comprises the following steps: half-diluting the normal oil spill sample with a certain fixed original concentration to prepare extraction liquids of the serial concentrations, and measuring the fluorescence spectra of the extraction liquids; selecting a 3D fluorescence spectrum or a synchronous fluorescence spectrum according to requirements for detection precision and data processing speed, thus establishing a concentration parameter supplemental characteristic spectrum database of the normal oil spill samples of different oil sources sequentially. While identifying the oil type of a certain oil spill sample, the oil spill sample is extracted and diluted in the same way, and the corresponding characteristic spectrum is obtained and identified by being compared with the sample characteristic spectrum in the database, thus the optimal matched sample is the oil type of the oil spill sample.

The invention discloses a method and system for identifying an oil spilling target of a ship. The method comprises the following steps of: establishing a conventional oil type actual measurement spectrum database of the ship by use of actual measurement spectrum data of a conventional oil type through an ASD (Analytical Spectral Device) ground spectrometer; synchronously acquiring actual measurement spectrum data and imaging spectrum image data of different oil types by utilizing the ASD ground spectrometer and a vehicle-mounted high-spectrum sensor, acquiring rebuilt spectrum data by utilizing an experimental linear method, and carrying out precision evaluation on the rebuilt spectrum data by utilizing a similar coefficient method and optimizing a rebuilt scheme; and optimizing spectrum characteristics of an oil film according the actual measurement spectrum data and the rebuilt spectrum data, and selecting a spectrum section to carry out spectrum angle map identification. According to the invention, a problem that continuous spectrum data on the same ground can not match because absorption characteristics of multi-waveband images and satellite-mounted high-spectrum images are attenuated due to space scale change is solved, the oil spilling identification precision is improved to more than 85%, and fast identification of the oil spilling target based on a high-spectrum image is realized.

The invention discloses a textile component identification method based on hyperspectral imaging. The textile component identification method is characterized by comprising the following steps: 1) setting up a hyperspectral database of common textile raw materials, 2) acquiring the hyperspectral data of a to-be-tested textile, 3) preprocessing the obtained hyperspectral data and images, 4) comparing and matching the hyperspectral data of the to-be-tested textile with the database set up in the step 1), and 5) displaying the distribution of various components in the textile in an image. The textile component identification method based on hyperspectral imaging is used for identifying the raw material components in the textiles rapidly and nondestructively, and quantitatively analyzing the proportions of the components in the textile.

The invention discloses a Raman spectrum superposition-based method for quickly determining the content of methanol in methanol gasoline. The Raman spectrum superposition-based method comprises the following steps of: firstly, measuring a base oil spectrum, a pure methanol spectrum and a methanol gasoline spectrum with known methanol content; secondly, obtaining a spectrum superposing formula according to data and storing base oil and a corresponding spectrum superposition parameter in a spectrum database; and constructing the spectrum database and then estimating the content of the methanol from the methanol gasoline spectrum with the unknown methanol content by using the spectrum superposition formula. The invention provides the spectrum superposition formula from a view of spectrum soft processing as well as the formula-based method for quickly determining the content of the methanol in the methanol gasoline. According to the method, the quantity of samples required to be calibrated can be greatly reduced in the application process, the labor capacity of calibrating works is reduced and the problem that the measurement for low-content methanol is inaccurate or even cannot be measured in the traditional method is overcome; and in addition, the measurement precision of the unknown methanol gasoline prepared from the base oil can also be maintained.

The invention relates to the field of microalgae identification, and in particular relates to a method for rapid identification of microalgae on a single cell level based on a single cell Raman spectrum. The method comprises the following steps: collecting single cell Raman spectrums of microalgae cells, establishing a microalgae single cell Raman spectrum database, and comparing a single cell Raman spectrum of unknown microalgae with the established microalgae single cell Raman spectrum database, thus realizing microalgae identification or mutant screening on the single cell level. The method disclosed by the invention identifies the microalgae through a single cell Raman spectrum technology; a simple, rapid and non-invasive microalgae identification method on the single cell level is provided, thus providing an efficient discrimination method for microalgae identification and mutant screening.

The invention provides a detection method of gasoline properties based on weighted absorbance and similar samples, the detection method comprises the steps of calculating the correlation coefficient R between a sample to be detected and a known sample on basis of the gasoline properties and the absorbance of the known sample after the near infrared spectroscopy of the sample to be detected and the known sample is conventionally pretreated; taking the correlation coefficient R as a weight, the weighted sample absorbance is obtained and the weighted absorbance matrix is established; calculating the score matrix of the weighted absorbance matrix by adopting a principal component analytical method; selecting the first principal component and the second principal component in the score matrix to obtain a new score matrix; calculating the mahalanobis distance according the new score matrix, selecting the similar samples which are nearest to the mahalanobis distance of the sample to be detected in the known spectral database as modeling samples, and performing prediction on the sample to be detected. According to the detection method provided by the invention, the effect of gasoline properties on the spectral distance is fully considered, the phenomenon that the classification is not accurate can be effectively avoided, so that the prediction accuracy of a model is finally improved. An important guarantee can be provided for accurately measuring the gasoline properties and timely adjusting the operating parameters.

The invention discloses an on-line gas Raman analysis method for natural gas components based on the Raman spectrum superposition principle.The method comprises the following steps that a basic sample of pure methane or pure nitrogen or the like is prepared, and a modeling sample formed by pairwise mixing the basic sample and other gas according to a certain proportion is prepared; a Raman spectrum of the basic sample and a Raman spectrum of the modeling sample are measured, and a spectrum database containing various pure substance spectrums and parameters of the pure substance spectrums is established based on the double-component gas modeling sample with known composition; for natural gas with known composition, a Raman spectrum of the natural gas is measured firstly, spectrum pretreatment is carried out, and the established database and a least square method are utilized for obtaining the molar percentage of all the components.The method has the advantages that detection speed is high, accuracy is high, repeatability is good, contact with sample gas is avoided, maintenance on site is avoided, and on-line real-time detection of the natural gas can be achieved.By the adoption of the method, operation is easy and convenient, no damage is caused to the samples in the detection process, and cleanliness and environment friendliness are achieved.

The invention relates to an electrolyte measurement method and an electrolyte measurement device for a vanadium redox flow battery. The electrolyte measurement method comprises the following steps of: measuring the absorption or transmission spectra of a plurality of groups of electrolyte samples with known configuration parameters under the irradiation of a set light waveband, recording the absorption or transmission spectra of the groups of electrolyte samples, and establishing a standard spectral database; in the light waveband, measuring the absorption or transmission spectrum of an electrolyte to be measured; finding out a spectrum closest to the measured spectrum from the standard spectral database; and determining configuration parameters corresponding to the closest spectrum to be measured parameters of the electrolyte to be measured. With the adoption of the electrolyte measurement method and the electrolyte measurement device for the vanadium redox flow battery, the concentrations of vanadium ions of various valences in the electrolyte of the vanadium battery can be effectively measured in an on-line manner, the measurement manner is simple, and the speed is fast.

The invention discloses a method for implementation of a spectral database for petroleum gas exploration. The method can be used for searching spectral information, spectral feature information and mineral content information. Through the method, an earth surface spectrum produced by petroleum gas micro-leakage is subjected to spectrum processing according to reflectance spectrometry knowledge so that data support and search support of petroleum gas exploration are improved. The method comprises the following steps of original data preparation, spectral data pre-treatment, spectral signature extraction and database building. In query of data in the spectral database, a user carries out a spectrum and mineral content query process, a spectrum and spectral signature query process, and a spectral signature and mineral content query process. After the each data query process, the spectral database outputs data comprising a spectrogram, spectrum information, spectral signature information and mineral content information.

The invention discloses a NIR method for fatty acid content of oilseeds, including: selection of oilseed samples, and analyzing the oilseed samples by an near infrared spectrometer to obtain NIR spectra; preprocessing of NIR spectra and establishment of a NIR spectral database of oilseeds; establishment of a fatty acid database of oilseeds based on gas chromatography; establishment of prediction model of fatty acids in oilseeds; acquiring NIR spectrum of a sample to be tested by the near infrared spectrometer, and importing the preprocessed NIR spectrum into the prediction model of fatty acids to obtain the predicted fatty acid content of the tested sample. The method is simple and rapid to operate and is non-destructive, and the detection time of the sample is greatly shortened and the detection cost is reduced.

The disclosed laser induced dissociation optical spectrum detection system comprises: a pulse laser, a focus lens, a spectrograph, a pulse delay generator, a computer, and a vacuum sample room. This invention recognizes element type by comparing acquired unknown sample atomic spectrum data and normal data, and reduces the error to zero in principle.

The invention provides a method for rapidly determining caffeine in a drink. The method comprises the steps as follows: acquiring multi-wavelength chromatographic data of drink samples and a caffeine standard solution; deducting data with the peak retention time identical with the caffeine standard solution from the chromatographic data of the drink samples; combining a plurality of drink samples and deducting chromatographic data of to-be-determined components, obtaining a background spectrum database containing no caffeine component, and calculating the amount of main components; reducing the dimension of the background database through singular value decomposition in combination with the amount of the main components to obtain a background database with a smaller data size; and calculating the content of the to-be-determined components in the drink samples by using space included angle criteria so as to realize quantification of the caffeine in the drink samples. The method is high in analysis efficiency, low in operation intensity, low in analysis cost, capable of reducing machine hours and reagent loss, good in robustness, simple and quite suitable for rapid assay determination of mass similar samples.

Based on support of prior knowledge such as spectra database, using calculation for simulating radioactive transfer in time of remote sensing imaging, the invention obtains simulated remote sensing images in each range of spectral band of remote sensing images in high spectral resolution on basis of image texture information and field information provided remote sensing data in low spectral resolution. Moreover, the invention avoids difficult acceptant amount of calculation. Before satellite emission or on-board examination, the simulated images can be viewed so that it is useful for decision maker to select proper operating mode and parameter. The invention can also be used for researching mechanism of electromagnetic transmission in procedure for capturing remote sensing image.

Embodiments of the invention provide a simple and robust system that allows non-resonant background to be removed from anti-Stokes signals generated during coherent anti-Stokes Raman spectroscopy (CARS) even when using cheaper laser systems, which do not have transform limited pulses. In particular, resonant CARS signals have a real and imaginary component. The imaginary component is directly related to the spontaneous Raman spectrum, for which there are already large spectral databases to allow chemical identification. The NRB signal, on the other hand, only has a real component. Within embodiments of the invention we recover the imaginary component of the entire CARS signal by simultaneously generating two CARS signals at orthogonal polarisations: one has the imaginary components destructively interfering with (i.e. subtracted from) the real components, the other has them constructively interfering. Measuring these two polarisations and subtracting them therefore cancels out the real part of the signal, leaving only the imaginary components.