122 results about "Differential spectrum" patented technology

The invention discloses a multiaxis differential spectrum absorbing method and device for vertically distribution detection of atmospheric components. Wherein, a plurality of telescopes are arranged to observe the space from the ground in different angles of pitch, so as to detect and collect sun lights scattered by the atmosphere; the surfaces of the telescopes' lens cones are blackened to reduce stray light, the scattered sun light is converged at the ends of optic fibers after passing the lens and light filters in the telescopes; the optic fibers at the tail ends of the telescopes are combined and guide the scattered sun lights into the incident slit of an imaging spectrometer, which first disperses the scattered sun lights, and then concentrate them on a photosensitive surface of a face array imaging CCD detector; the spectral signals go through data analysis and treatment after A / D conversion and inputting into a computer. The invention is applicable for chemical research of atmosphere, provides input data and model verification for chemical model of atmosphere; and is applicable for verifying the results of atmospheric components detected by a satellite.

The invention provides an ultrasonic echo signal online preprocessing method based on singular spectrum analysis. The method is used for echo signal preprocessing in the ultrasonic online detection technology. The method includes the steps that a rail matrix is constructed according to measured ultrasonic echo signals, and proper matrix parameters are automatically determined through the inset window length selection algorithm; the ultrasonic echo signal rail matrix is subjected to singular value decomposition, and a singular value spectrum is obtained; a feature value spectrum and a singular value differential spectrum of the ultrasonic echo signal rail matrix are calculated; a reconstruction group number for singular spectrum analysis is determined through a self-adaptive reconstruction algorithm, and then a denoised reconstruction ultrasonic echo sequence is constructed; a reconstruction principal component sequence corresponding to a signal component is further subjected to frequency domain analysis.

A method for determining the substitutional carbon content (Cs) of a monocrystalline or polycrystalline silicon sample comprises measuring an absorption spectrum of the silicon sample to be studied and of a reference sample and calculatng a differential spectrum from them, wherein the calculated differential spectrum provides a detection threshold of <5 ppba Cs.

The invention discloses a portable differential spectrum absorbing method and device, where to-be-tested gas is charged in a multiple reflecting tank, the light emitted from a light source is gathered by lens to enter the multiple reflecting bank to be reflected many times in the multiple reflecting bank and then be led through optical fiber into a spectrum meter by the actions of lens and optical fiber coupler, and then the spectrum meter makes spectrum signal conversion, and finally transmits the converted signal to a computer. And the invention replaces open light path with multiple reflecting bank to complete monitoring polluted gas in atmosphere without telescope and angle reflector.

An object of the present invention is to provide a spectroscopic method and an apparatus which can measure a trace element accurately with high sensitivity. In order to achieve this object, for example, in Fourier transformation infrared spectroscopy (FT-IR), a reference spectrum and a measurement spectrum including an impurity spectrum are measured in order to obtain a differential spectrum comprising the impurity spectrum and a flat baseline, correction including a frequency shift of the reference spectrum before calculating a differential spectrum, is performed on the reference spectrum. This makes it possible to remove baseline deformation due to phonon absorbance of silicon included in the conventional differential spectrum, and to obtain an infrared absorption spectrum of the substitutional carbon with high accuracy and high sensitivity.

A titanium oxide dispersion composition is provides, the composition comprising a solvent and a titanium oxide with an average secondary particle diameter of 100 nm or smaller, the dispersion composition having a maximum intensity within the range of from 435 nm to 700 nm of a primary differential spectrum of a transmittance spectrum, wherein the transmittance spectrum is measured using an ultraviolet-visible spectrophotometer after adjusting a solid content of the dispersion composition to be about 2% by weight. The composition provides a film having a high hydrophilicity under the irradiation of a visible light.

The invention discloses a non-destructive inspection method of total amount of meat bacteria, comprising the following steps: S1, obtaining an original reflection spectrum image Rs of a sample to be detected and storing the image; S2, detecting the TVC of the sample as standard reference data with a standard plate colony counting method according to National Standard; S3, obtaining a relative reflection spectrum image R of the sample according to the FORMULA that R=(Rs-Rd) / (Rr-Rd), wherein Rd is a black image when an image obtaining system works with dark current, and Rr is a reflection spectrum image of a standard reference whiteboard; S4, correcting the image with an SNV method; S5, choosing a second-order differential spectrum for the image R after being corrected, and selecting the best wavelength representing the TVC of the sample to be detected with a step-by-step regression method; S6, extracting the data and TVC detection result of the second-order differential spectrum relative to the best wavelength, and dividing the data and TVC detection result into two sets respectively as correction set data and validation set data; S7, establishing an LS-SVM data model, and detecting the value of the TVC of the sample to be detected. The method is human-oriented and advanced with quick and pollution-free detection process so that our country is in line with developed countries in the field of food quality and safety.

The invention discloses a petroleum drilling fluid nuclear magnetic resonance while-drilling analytic method which is characterized in that the method comprises the following steps of: sampling, serial sampling is respectively carried out at a drilling fluid inlet and at a drilling fluid outlet; map collection, relaxation maps of 1 H and 13 C are drawn; map transformation, the two relaxation maps are processed by pulse fourier transformation to form a rameau frequency spectrum; differential spectrum processing, a stratum fluid resonance spectrum is obtained; the synthesized geological interpretation is carried out, and a map library is established; a synthesized interpretation map is drawn up; the related data in a logging database, a 1H nuclear magnetic resonance map and a 13C nuclear magnetic resonance map are combined to form a petroleum drilling fluid nuclear magnetic resonance while-drilling analytic map. The method has the obvious effects that the drilling fluid is continously and quickly analyzed in an oil drilling field on line; and the characteristics of the stratum fluid carried over in the drilling fluid is determined; the characteristics of the stratum fluid can be precisely judged in the while-drilling process without needing sampling the contents of oil gas in a core or rock debris; and the method is suitable for the requirements of the modern drilling technique.

The invention provides a reservoir fluid recognizing method. The reservoir fluid recognizing method includes: logging a reservoir layer by double TE modes in long wait time, acquiring echo strings in long echo interval and short echo interval, inverting the echo strings to obtain a long echo interval T2 spectrum and a short echo interval T2 spectrum; shifting the short echo interval T2 spectrum to generate a simulating water spectrum according to the long echo interval supposing the short echo interval T2 spectrum measured under the condition of the short echo interval is all water course; subjecting the long echo interval T2 spectrum and the simulating water spectrum to spectrum differencing to generate a differential spectrum delta M, and judging the type of the reservoir fluid according to the differential spectrum delta M. Supposing the T2 spectrum under the condition of the short echo interval as the water spectrum, the long echo interval T2 spectrum is simulated, and oil gas water fluid in a pore medium in the reservoir layer can be recognized by subjecting the measured T2 spectrum and the simulated water spectrum at the long echo interval to differential spectrum processing and analyzing.

The invention relates to a method for predicting the properties of an oil product through the near-infrared spectrum of the oil product. The method comprises: classifying oil products according to types, collecting a group of samples from each class of the oil products, determining the near-infrared spectrums of each sample, and determining the property data of each sample by using a standard method according to the classification of the oil products; carrying out second-order differentiation on the near-infrared spectrums of the samples, and establishing a database from absorbance and the determined property data; fitting the differential spectrum of the sample to be determined by using the differential spectrum of the sample spectrum of the database, and calculating the fitting degree ofthe fitted differential spectrum and the differential spectrum of the spectrum to be determined; and predicting the properties of the oil product to be determined by comparing the fitting degree to athreshold value through the property data of the database spectrum participating the fitting, wherein the oil product to be determined is subjected to complete spectrum fitting. With the method of the present invention, the properties of the oil product to be determined can be rapidly and accurately predicted.

A target detection apparatus is provided which can detect and quantitatively measure various detection targets such as pathogens. For this purpose, the apparatus comprises an optical irradiation unit which irradiates light; an optical interference unit which can interact with the detection target, interferes with the light irradiated from the optical irradiation unit and radiates it as interference light and change the wavelength of the interference light after interaction with the detection target; and an wavelength change detecting unit which detects the wavelength change of the interference light radiated by the optical interference unit. The wavelength change detecting unit preferably measures spectrums before and after wavelength change of the interference light, and their differential spectrum. Also provided is a target detection substrate comprising a film-like material on a substrate which, when interacting with a detection target, changes the wavelength of the interference light.

The invention discloses a data filtering method applied to ultrasonic partial discharge detection. A median filter which is an atypical nonlinear filter for completing signal recovery based on sequence statistics is used, aiming at pulse interference possibly existing in the ultrasonic partial discharge detection. Under the one-dimensional condition, the essence is a sliding window with a certainlength, and a signal at the central position of the window is replaced by a median after all values in the window are sorted. When the pulse width is less than half of the window width, the median filtering is very effective to narrow pulse interference. Then, for processing of random noise, after wavelet packet threshold function denoising and singular value decomposition algorithms are compared,a singular value decomposition filtering algorithm based on a singular value energy difference spectrum is provided. The singular value energy differential spectrum defined in the algorithm can welldetermine the order of a reconstruction matrix, so that the singular value contributed by random noise and the singular value contributed by partial discharge signals are distinguished, and a good filtering effect is achieved.

The invention discloses a mixed noise reduction method for underwater acoustic signals. VMD decomposition is conducted on the underwater acoustic signals containing noises, wherein the VMD decomposition quantity is determined by an EMD decomposition result; a correlation coefficient between each variation modal function decomposed by VMD and the original signal is calculated, and according to a threshold value of the correlation coefficient, noise variation modal functions are screened; summation is carried out on all the noise variation modal functions, and SVD differential spectrum noise reduction is carried out; signals are reconstructed, Savitzky-Golay filter is carried out, and the underwater acoustic signals after the noise reduction are obtained; correlation dimension and noise intensity of the underwater acoustic signals before and after the noise reduction are calculated, and timing sequence waveforms and two-dimensional phase diagrams before and after the noise reduction aregiven; The method can further eliminate noises, the phase diagrams of the underwater acoustic signals after the noise reduction have a more smooth rail, and attractors have a better regularity of geometric structures.

The invention discloses a method for extracting the fault signal feature information of an aero-engine rotor system, and the method comprises the steps: collecting a rotor rub-impact vibration signal,and carrying out the FDM decomposition of the collected rotor rub-impact vibration signal to obtain complete rotor rub-impact vibration signal FIBFs components; constructing a Hankel matrix of the rotor rub-impact vibration signal after noise reduction, and drawing a singular value curve of the rotor rub-impact vibration signal after noise reduction; determining a singular value catastrophe point, carrying out the reconstruction of an order number, and carrying out the envelope spectrum analysis, thereby achieving the effective extraction of fault information. According to the invention, themethod achieves the reasonable extraction of the fault feature frequency of a rotor system based on the FDM decomposition and singular value differential spectrum analysis, and achieves the efficientfiltering of the noise signal component in the rub-impact vibration signal, thereby achieving the extraction of the weak fault feature information from the low-frequency strong noise background, and achieving the effective extraction of the fault information.

The invention discloses an oil and water layer recognition method suitable for a volcanic reservoir. The oil and water layer recognition method comprises the following steps of performing inversion processing on an echo string by using nuclear magnetic logging data in a dual waiting time mode to obtain a long waiting time T2 spectrum and a short waiting time T2 spectrum; then performing differential spectrum processing to obtain a difference spectrum reflecting oil and gas information; performing integral processing on the difference spectrum to obtain difference spectrum porosity (Diff_Por); determining sensibility of various hydrocarbon components on an oil and water layer by gas logging data establishing a hydrocarbon characteristic ratio (Ratio_C); establishing a cross plot of the difference spectrum porosity and the hydrocarbon characteristic ratio according to existing oil testing data and determining a distinguishing boundary of the oil and water layer; extracting the difference spectrum porosity and the hydrocarbon characteristic ratio of a stratum of which oil and water are about to be recognized according to the previous steps; and effectively recognizing the oil and water layer by using the established cross plot. On the basis of nuclear magnetic differential spectrum processing, processing is carried out further to obtain the difference spectrum porosity, the cross plot is established by the difference spectrum porosity and the hydrocarbon characteristic ratio obtained by the gas logging data, and then the oil and water layer of the volcanic reservoir can be recognized.

The invention discloses a method for detecting moisture content of wood on the basis of an infrared differential spectrum technology. The method is characterized by comprising the steps of selecting wood to be detected, preparing an absolutely-dry sample and balance samples of different relative humidity by utilizing the selected wood; measuring an infrared spectrogram I<o> of the absolutely-dry sample and an infrared spectrogram I<w> of each balance sample by utilizing an infrared spectrometer; subtracting the infrared spectrogram I<o> of the absolutely-dry sample from the infrared spectrogram I<w> of the balance sample to obtain an infrared differential spectrogram I<w-o>; solving an area A<w-o> in the range of 2900 to 3750 cm<-1> in the infrared differential spectrogram; determining the moisture content W of the wood samples of different relative humidity by utilizing a traditional drying method; linearly regressing the moisture content W and the area A<w-o> of each sample by utilizing a least square method to establish a model for detecting the moisture content of the wood by utilizing the infrared differential spectrum technology. The model can be used for the mass detection of the wood samples to be detected, each sample is detected only for one second, and the detection time of the wood moisture content is greatly shortened. The method has advantages of short period, rapidness in detection and micro scale and even trace amount of needed sample, is a nondestructive detection technique and can be applied to the field of the evaluation of wood.

A fluorescence intensity correction method including: receiving fluorescence emitted from fluorescent pigments, collecting detected values from each light detector, and obtaining a fluorescence spectrum of each fluorescent pigment as one spectrum group; separating the obtained spectrum group into a plurality of small spectrum groups; comparing the separated small spectrum groups with a fluorescence wavelength distribution of each fluorescent pigment obtained in advance and specifying the small spectrum groups as the fluorescence spectrum of any fluorescent pigment; comparing a differential spectrum between small spectrum groups that are not specified and one or more specified small spectrum groups with the fluorescence wavelength distribution of unspecified fluorescent pigments obtained in advance, and specifying the differential spectrum as the fluorescence spectrum of any fluorescent pigment; and calculating the intensity of fluorescence emitted from each fluorescent pigment.

The invention relates to a heavy ion testing data based device proton overturning cross section retrieving method. The method comprises the following steps that proton energy is confirmed; the material type and the thickness of a metal wiring layer and an oxidation layer of a device are confirmed; materials and the thickness of a sensitive area of the device are confirmed; an energy deposition differential spectrum of a proton in the sensitive area is analyzed; the energy deposition differential spectrum in the sensitive area is converted into an equivalent LET differential spectrum; the overturning cross section of the device under the proton irradiation is calculated. The influence of the nuclear reaction in the metal wiring layer and the oxidation layer of the device is considered, the method is more suitable for a device under a modern technological condition, the calculation of the influence exerted on the proton by the device is more accurate, and the reliability is greatly enhanced.

The invention relates to a mechanical part fault diagnosis method based on SVD and VMD. The method comprises the following steps: acquiring a vibration signal of a mechanical part; comparing the mechanical part with a fault-free mechanical part, and judging whether abnormity exists or not; performing singular value decomposition on the vibration signal, and calculating a difference value of adjacent singular values of a singular value sequence to obtain a difference spectrum; analyzing the differential spectrum, determining a reconstruction order, and reconstructing the vibration signal of the mechanical part; decomposing the reconstructed signal into modal components, and determining the optimal number of the modal components; carrying out variational mode decomposition on the vibration signal of the mechanical part subjected to original fault diagnosis; selecting a modal component with a relatively large weighted kurtosis index value for signal synthesis; generating an envelope spectrum by using the synthesized signal; and judging the fault type of the mechanical part according to the envelope spectrum. The problem that the decomposition parameters of the variational mode decomposition method are difficult to determine is solved, the correlation between the modal components and the original signal is considered in the process of determining the optimal modal component number through variational mode decomposition of the reconstructed signal, and the determined decomposition parameters are better.

The invention discloses a thermal infrared high spectral remote sensing data on-track spectral calibration method, comprising steps of (1) inputting an atmosphere parameter and an imaging parameter to MODTRAN atmosphere radiation transmission simulation software to obtain a simulated 1nm ultrahigh resolution entrance pupil brightness spectrum, wherein the atmosphere parameter and the imaging parameter are obtained during a process of obtaining thermal infrared high spectral remote sensing data; (2) taking center wavelengths lambda i and FWHM delta lambda i which are obtained by laboratory spectrum calibration as initial values, and constantly regulating center wavelengths (lambda i+delta lambda i) and FWHM (delta lambda i+delta delta lambda i) to perform convolution operation on the ultrahigh resolution entrance pupil radiation brightness spectrum to obtain a simulated sensor entrance pupil brightness spectrum; and (3) choosing a simulated atmosphere absorption band and a near entrance pupil radiation brightness spectrum and a radiation brightness spectrum obtained by a sensor, performing NODD conversion on the near entrance pupil radiation brightness spectrum and the radiation brightness spectrum, comparing normalized optical thickness differential spectrums obtained through NODD conversion, obtaining optimal variables delta lambda i and delta delta lambda i of the center wavelength and the FWHM through an optimal algorithm and finally obtaining the optimal center wavelength and the FWHM. The thermal infrared high spectral remote sensing data on-track spectrum calibration method is accurate, fast and easy to operate.

A preparative separation chromatograph system having a column for temporally separating components in a sample and for discharging an eluate fluid with the components, a detector for obtaining an absorbance spectrum of the eluate fluid, and a fraction collector for continuously creating a chromatogram. The system further includes: a peak section determiner; a differential value determiner for calculating a differential spectrum value and for determining whether or not the absolute value of the differential spectrum value is equal to or less than a predetermined value; and a fraction collector controller for controlling the fraction collector so as to fractionate the eluate fluid during a period of time for which it is determined that the chromatogram peak of the target component is present and for which it is also determined the absolute value of the differential spectrum value is equal to or less than the predetermined value.

The invention discloses a data processing method for effectively solving a multi-component overlapped three-dimensional fluorescence spectrum based on differential spectrum. The method comprises the following steps of: by carrying out two-dimensional expansion on a three-dimensional fluorescence spectrum and expanding the three-dimensional fluorescence spectrum into a excitation spectrum and a transmission spectrum; respectively calculating differential spectrums of the excitation spectrum and the transmission spectrum; before carrying out the differential spectrum calculation on the excitation spectrum and the transmission spectrum, carrying out cubic spline interpolation on the excitation spectrum, and carrying out roughness punishment smoothing treatment on the transmission spectrum; and finally carrying out independent component analysis to realize the accurate component identification and single component extraction of a multi-component mixture, thereby realizing the precise separation of a multi-component three-dimensional fluorescence severe overlapped spectrum and the accurate identification and extraction of the components. The method is applicable to data processing on all multi-component three-dimensional fluorescence aliasing spectrums which use a three-dimensional fluorescence spectrum technique as analysis means; method basis for further application of the three-dimensional fluorescence spectrum technique is provided, and the method has very wide application prospect.

The invention discloses a method for identifying multi-element characteristic spectrum peaks in an energy dispersion X-ray fluorescence spectrum. The method comprises the following steps: carrying out independent component analysis on an XRF two-dimensional spectrum measured from an actual sample, utilizing an obtained preliminary analysis result as an initial solution of non-negative matrix factorization, carrying out precise solving by virtue of iteration correction of the non-negative matrix factorization, carrying out contrastive analysis on a differential spectrum of a solved single-element calculation spectrum and a differential spectrum of a standard spectrum, and determining the similarity of the two differential spectrums by virtue of Pearson's correlation coefficient, so as to accurately identify element characteristic spectrum peaks; and obtaining the concentration values of corresponding elements according to the solved single-element calculation spectrum and an established standard curve, and realizing quantitative analysis. The method can be effectively applied to the effective identification of the multi-element characteristic spectrum peaks in the energy dispersion XRF spectrum and the quantitative detection of the elements.

The invention relates to a differential spectrum function peak valley point discriminating method for the aging condition of oil paper insulation equipment. According to the method, at first, a differential spectrum unfolding method is used for carrying out differential spectrum unfolding on depolarization current spectrum lines tested by the oil paper insulation equipment to obtain a primary differential spectrum function, and then the number of peak valley points of the primary differential spectrum function is observed; if the number of the peak valley points can not be identified in the primary differential spectrum function, secondary differential spectrum unfolding is carried out on the depolarization current spectrum lines for obtaining a secondary differential spectrum function, and the number of peak valley points of the secondary differential spectrum function is observed; finally, the aging condition of the oil paper insulation equipment is judged according to the number of the peak valley points of the primary or secondary differential spectrum function. According to the method, the differential spectrum unfolding method is used for highlighting the aging characteristic implied in the depolarization current spectrum lines of the oil paper insulation equipment in the peak valley point form, the peak valley point form is used for evaluating the aging condition of the oil paper insulation equipment, an intuitive, accurate and reliable analysis means is provided for judging the aging condition of the oil paper insulation equipment, and the blank in the field of oil paper insulating aging diagnosis research is filled.

The invention relates to a Beidou single frequency carrier phase cycle slip detection method and belongs to the field of Beidou navigation signal processing. The method comprises the steps of: firstly, constructing cycle slip signals by using phase reduce pseudo-range law computation and performing primary detection; setting matrix dimensions according to a singular value curve, constructing a Hankel matrix for the cycle slip signals and performing SVD on the cycle slip signals; finally, calculating correlation indexes of the primitive cycle slip signals and SVD component signals thereof and correlation indexes of the SVD component signals and single frequency carrier phase signals without cycle slips added, building sensitive factors and a differential spectrum thereof, and selecting sensitive SVD components on the basis, wherein locating factors are set because the sensitive factors disrupt the order of singular values, sudden change singular values corresponding to sensitive component signals are extracted via the locating factors and signal reconstruction is performed; determining the epoch when cycle slips occur according to sudden change positions in the reconstructed signals. The method not only can detect smaller cycle slip signals but also can more accurately locate epochs when cycle slips occur.

The invention relates to a fault feature extraction method of low-speed heavy-load parts of a portal crane. The method includes: decomposing acquired vibration signals of the low-speed heavy-load parts of the portal crane into components of different frequency bands through a dual-tree complex wavelet packet, and obtaining dual-tree complex wavelet packet decomposition coefficients corresponding to different frequency bands; performing singular value decomposition on the dual-tree complex wavelet packet decomposition coefficients of the frequency bands including fault feature information, calculating a singular value differential spectrum curve, and selecting the number of singular value reconstruction components according to a maximum catastrophe point thereof; then performing singular value reconstruction thereon, and performing noise reduction on the components; and performing dual-tree complex wavelet reconstruction thereon, calculating a Hilbert enveloping spectrum of reconstruction signals, and determining whether the low-speed heavy-load parts have faults according to the enveloping spectrum. According to the method, the problem of failure of noise reduction and fault feature extraction through singular value decomposition for the low-speed heavy-load parts of the conventional portal crane by the vibration signals for an ultra-long time is solved.

The invention discloses a Hankel matrix singular value decomposition based noise inhibition method of a ground penetrating radar. The ground penetrating radar B scans each channel of data in an imageto construct a Hankel matrix; singular value decomposition is carried out on the Hankel matrix; a differential spectrum of the singular values is calculated, and a mean value of the differential spectrum serves as a threshold to determine a boundary point between target and noise signal singular values; and the target signal singular value is used to implement reconstruction to obtain de-noised data. The method has the advantages that singular value distribution difference of the Hankel matrix of the target and noise signals is obtained, the mean value of the singular value differential spectrum serves as the threshold to determine the target signal singular value automatically, calculation is simple, the threshold stability is high, and noise in ground penetrating signals can be inhibitedeffectively.