57 results about "Differential spectrum" patented technology

The invention provides a mechanical rotating member acoustic emission fault diagnosis method based on bidirectional weighted cyclostationary, and the method comprises the steps: collecting a to-be-diagnosed acoustic emission signal, obtaining a cyclic spectrum coherence function, and obtaining baseline discrete spectrum coherence mapping and to-be-diagnosed discrete spectrum coherence mapping; obtaining a spectrum frequency weight redistribution vector based on the baseline discrete spectrum coherent mapping and the discrete spectrum coherent mapping to be diagnosed; obtaining a differential spectrum coherence matrix based on the cyclic spectrum coherence function; and obtaining a bidirectional reweighted differential spectrum coherence matrix based on the spectrum frequency weight redistribution vector and the differential spectrum coherence matrix. According to the method, health baseline data is used as prior information to be fused into a cyclostationary analysis framework, difference and weighting thoughts are creatively fused, unique advantages and potential of an acoustic emission technology in the field of fault diagnosis are deeply excavated, complex and changeable industrial application scene requirements are fully met, and the method has practical application value.

The invention relates to the technical field of chemistry and material science, in particular to a regenerant aging failure behavior identification method and system based on differential spectrum extraction. The method comprises the following steps: acquiring infrared spectrum data of a regenerated asphalt sample and an aged asphalt sample at the same stage; carrying out pretreatment on the infrared spectrum data; constructing a characteristic difference spectrum library of the regenerant; extracting a characteristic peak area variation; and obtaining an identification result of the regenerant aging failure behavior by establishing a correlation model of the characteristic peak area variation and the macroscopic performance index. According to the method, high-sensitivity extraction of 3% low-dosage regenerant signals is realized by combining adaptive morphology-quantile regression baseline correction, peak entropy weighted normalization and differential spectrum data enhancement algorithms; a Gaussian-Lorentz mixed peak dividing model and an aging response index model are adopted, microscopic functional group change and macroscopic performance are associated, the aging process of the regenerant is accurately tracked, and a universal technical framework is provided for failure judgment and performance optimization of the regenerant.

The invention provides a power distribution equipment self-checking method and system based on an intelligent circuit breaker, and the method comprises the steps: calculating all-phase frequency spectrums of current data of two continuous full-period alternating currents, and obtaining a differential frequency spectrum matrix through calculation based on the two all-phase frequency spectrums; current data of the full-period alternating current corresponding to the all-phase frequency spectrum with the maximum frequency spectrum energy serves as target current data, a time-frequency two-dimensional energy distribution diagram of the target current data is generated, and a time-frequency information entropy value is obtained through calculation based on the time-frequency two-dimensional energy distribution diagram; obtaining a differential frequency spectrum matrix sequence and a time-frequency two-dimensional energy distribution diagram sequence according to a preset sliding window length and step length, and extracting features of the differential frequency spectrum matrix sequence and the time-frequency two-dimensional energy distribution diagram sequence; and determining a fusion weight based on the fundamental wave amplitude of the current data in the sliding window and the total harmonic distortion degree, carrying out weighted fusion on the features of the differential frequency spectrum matrix sequence and the features of the time-frequency two-dimensional energy distribution diagram sequence by using the fusion weight, and obtaining a self-inspection result based on a weighted fusion result.

The invention discloses a differential absorption spectrum detection system and method, and belongs to the technical field of flue gas detection. The differential absorption spectrum detection system comprises a gas absorption cell and a monochromator; the gas absorption cell and the monochromator are designed in a common optical path; the gas absorption tank is a flue gas channel; the monochromator is used for detecting the flue gas entering the gas absorption tank. Light energy of the light source does not need to be coupled for multiple times and transmitted through optical fibers, and the energy utilization rate is increased; the gas absorption cell and the monochromator share the same light path, and light passes through the monochromator and the gas absorption cell at the same time, so that the structure of the ultraviolet differential spectrum detector is simplified, the weight of the detector is reduced, and the size of the detector is reduced.

The invention relates to the technical field of intelligent detection, in particular to a feed mycotoxin detection method and system based on spectral analysis. The method comprises the following steps: acquiring a near-infrared diffuse reflection spectrum of a feed sample to be detected, constructing an original spectrum vector based on absorbance data of the near-infrared diffuse reflection spectrum, and determining a projection component of the original spectrum vector on a pre-constructed qualified matrix space; subtracting the projection component from the original spectrum vector to obtain a residual vector, and calculating a first-order difference spectrum of the residual vector based on a preset sensitivity weight; and performing local feature weighting on the first-order difference spectrum to determine a weighted feature value, determining a residual entropy value of the residual vector and a range value of the residual vector, and determining a detection result of the to-be-detected feed sample by using the weighted feature value, the residual entropy value and the range value. According to the technical scheme, a more accurate detection result of the mycotoxin of the feed can be obtained.

The invention discloses a satellite hyperspectral coastal saline-alkali soil salinity inversion method based on a machine learning model, and the method comprises the steps: S1, collecting an original multispectral image and ground actual measurement data, and obtaining standardized initial feature space data through the radiometric calibration correction preprocessing operation; s2, performing fractional order differential spectrum enhancement on the initial feature space data to obtain an enhanced high-dimensional feature set, and performing importance adaptive optimization on the enhanced high-dimensional feature set by adopting a Boruta feature selection algorithm to obtain an optimal high-dimensional feature subset; s3, based on the optimal high-dimensional feature subset, an initial inversion model is obtained by integrating Optuna hyper-parameter automatic optimization, and based on the initial inversion model, a salinity inversion model is obtained through feature contribution degree analysis optimization and embedding of an SHAP interpreter; and S4, performing salinity prediction on the global remote sensing image based on the salinity inversion model to realize sea saline-alkali land salinity inversion.

The application relates to a visual identification method and system of a liquid crystal angle color-changing material. Specifically, optical images of a material at a preset angle sequence are collected, Lab chroma and rotation-invariant uniform LBP texture features of each image are extracted, and a multi-dimensional initial feature sequence is formed. A double-branch identification model is constructed. One branch performs differential spectrum analysis on the feature sequence, and then extracts features through a multilayer perception machine. The other branch encodes contexts through a bidirectional GRU, and enhances key information by using angle-channel correlation attention, and then pools the key information into a context vector. The outputs of the two branches are concatenated, and are mapped into an encoding vector through a classifier. During training, a polarization loss function is used to drive the encoding vectors of the genuine product and the fake product to converge to two preset opposite polarization directions. During identification, the distances between the encoding vector of a material to be tested and the two polarization vectors are calculated, and the one with a shorter distance is determined as the genuine or fake product.

A first difference spectrum between a sample spectrum of a test sample and a reference spectrum of a reference sample of which concentration of a specific component is lower than the test sample is calculated (S10); using multiple reference spectra acquired by measuring the reference sample for multiple times, a difference spectrum having a shape similar to the first difference spectrum is selected from multiple difference spectra between two reference spectra (S20); a second difference spectrum based on the selected difference spectrum and the first difference spectrum is calculated (S30); and a shape of an absorption band of the specific component is acquired from the second difference spectrum to determine the concentration of the specific component (S40).

The present application relates to the field of on-line analysis of material chemical composition, and discloses an on-line monitoring process for the composition of a lead frame electroplating solution, comprising: calculating the concentration of the electroplating solution by conventional monitoring of the spectrum; calculating a spectrum entropy index based on the degree of deviation of the real-time spectrum from a pre-established statistical baseline model, and comparing the spectrum entropy index with a pre-set failure trigger threshold; starting a dynamic calibration step only when the spectrum entropy index exceeds the pre-set failure trigger threshold, the dynamic calibration step generating a model error vector by comparing the physically real differential spectrum with the model virtual differential spectrum through injection of a standard pulse, and correcting the chemometrics model using the model error vector, so that the present application realizes on-demand calibration, ensures real-time accuracy of the model, and reduces the consumption of the standard.

The present application relates to the technical field of nondestructive testing and intelligent sorting of agricultural products, in particular to a kind of soybean based on hyperspectral image nondestructive testing method, comprising: collecting the original hyperspectral image data of soybean sample, generate pre-processing hyperspectral data cube;Calculate spatial gradient field, and apply gradient partition threshold to construct morphological distribution model;Spectrum-morphology coupling operator is constructed, and the output self-referenced differential spectrum feature set;For long-wave band spectral response, execute anomaly detection, generate internal state determination result output detection classification data;According to error distribution characteristics, update the gradient partition threshold of morphological distribution model and the weight parameter of spectrum-morphology coupling operator, generate final detection result for downstream sorting equipment to call;The present application solves the problem that fixed model produces performance drift with sample change, ensures the stability of sorting precision.

The purpose of the present disclosure is to reduce erroneous detection of a false image caused by sidelobes and also minimize the deterioration of angular resolution by appropriately using a window function when detecting a target using a radar.　A target angle detection device 2 comprises: an angle spectrum calculation unit 21 that performs digital beamforming on the same reception signal of a radar array antenna by using first and second window functions having different sidelobe suppression levels, and calculates first and second angle spectra, respectively; a differential spectrum calculation unit 22 that calculates a differential-intensity spectrum on the basis of the first and second angle spectra; and a target angle detection unit 23 that detects a target at a spectral angle where the spectral intensity lies within a predetermined range on the basis of the differential-intensity spectrum, and determines that what is detected is a false image rather than the target at spectral angles where the spectral intensity lies outside the predetermined range.

Differential spectrum analysis and filtering method for vibration signals, which characterizes and extracts damage components in signals based on the frequency-domain differences between the signal to be evaluated and the reference signal. First, the signal to be evaluated and the reference signal are subjected to discrete Fourier transform, then frequency-domain subtraction is performed to obtain a differential spectrum diagram, and then the damage components in the signal are reconstructed through inverse discrete Fourier transform. Finally, based on the time-domain characteristics of the damage components and the frequency-domain characteristics of the differential spectrum diagram, the occurrence and severity of damage are judged. The present invention can effectively suppress the conventional components in vibration signals, targetedly extract damage information, improve the sensitivity for detecting early damage, and has important engineering application value.

The invention relates to the technical field of communication, discloses an electromagnetic spectrum abnormal signal monitoring method and system based on double acquisition and comparison, and aims to solve the problems of asynchronous double-channel sampling and high abnormal signal omission ratio and false alarm rate caused by clock drift and physical path delay in the prior art. According to the method, a hardware-level self-adaptive clock synchronization compensation circuit is constructed, clock path delay is quantized and offset in real time before analog-to-digital conversion, and a first sampling clock and a second sampling clock which are accurately synchronized are generated; a dual-channel ADC is used for synchronously collecting the same radio frequency signal, and abnormal signals are judged and identified through spectrum coherence analysis and differential spectrum threshold. The system comprises a main clock unit, a self-adaptive synchronous compensation circuit, a dual-channel ADC module and a data processing comparison module. The picosecond-level synchronization precision is achieved, external time service is not needed, the missing detection and false alarm rate is remarkably reduced, and the method is suitable for high-reliability frequency spectrum monitoring in the complex electromagnetic environment.

The invention provides a method for predicting hydrophilicity and hydrophobicity of an organic matter and membrane pollution potential based on a differential spectrum, and belongs to the technical field of water quality monitoring, and the method comprises the following steps: titrating a water sample to be detected by using perchlorate, and predicting based on an ultraviolet visible light differential spectrum before and after titration of the water sample; the inlet water of the membrane system passes through a filter and is subjected to spectrum full scanning to obtain an ultraviolet visible light reference spectrum; the water sample enters a titration system, a perchlorate solution is dropwise added and uniformly mixed, spectrum full scanning is carried out, and volume concentration correction is carried out on the spectrum; performing total organic carbon normalization and difference on the ultraviolet visible spectrum of the sample before and after titration to obtain a difference spectrum, performing Gaussian peak division on the difference spectrum to obtain a Gaussian energy band, and determining the hydrophilicity and hydrophobicity of the organic matters in the water sample and the membrane pollution potential according to the energy band ratio. The problems that an existing method for predicting the hydrophilicity and hydrophobicity of the organic matter and the membrane pollution potential is tedious in pretreatment, complex in analysis procedure, long in time consumption and difficult to meet analysis of large-batch samples are solved.

The invention relates to the technical field of agricultural product nondestructive testing and intelligent sorting, in particular to a green soy bean nondestructive testing method based on a hyperspectral image, which comprises the following steps: collecting original hyperspectral image data of a green soy bean sample, and generating a preprocessed hyperspectral data cube; calculating a space gradient field, and constructing a morphological distribution model by applying a gradient partition threshold value; constructing a spectrum-form coupling operator, and outputting a self-reference differential spectrum feature set; performing anomaly detection on the long-band spectral response, generating an internal state judgment result, and outputting detection grading data; updating a gradient partition threshold value of the morphological distribution model and a weight parameter of a spectrum-morphological coupling operator according to the error distribution characteristics, and generating a final detection result to be called by downstream sorting equipment; the problem that a fixed model generates performance drift along with sample change is solved, and the stability of sorting precision is guaranteed.

A method for diagnosing the noise level of a transformer comprises: a step of acquiring a frequency spectrum of noise from a stacked iron core 21 contained in a transformer, the stacked iron core 21 being formed by stacking electrical steel laminations; a step in which, for the calculation of the excitation vibration of the stacked iron core 21, the transverse moduli of elasticity are determined in two planes, each including a stacking direction of the stacked iron core 21; a step in which the excitation vibration for the stacked iron core 21 is calculated using a constitutive equation that includes an elasticity matrix comprising the determined transverse moduli of elasticity as elements, and a frequency spectrum of an excitation vibration of the stacked iron core 21 is acquired;a calculation stage of the difference between the excitation noise spectrum of the stacked iron core 21 and the excitation vibration frequency spectrum of the stacked iron core 21 as a differential spectrum; and a transformer noise level diagnostic stage based on the differential spectrum.

The invention relates to the technical field of drug component detection, in particular to a Raman spectrum-based method for detecting the concentration of multiple drug components in blood, which comprises the following steps: acquiring differential spectrum data corresponding to Raman spectrum data of a serum sample of a patient before and after administration of a target drug; correcting a differential signal corresponding to the target drug in each frame of differential spectrum in the differential spectrum data based on the difference between differential signals corresponding to each endogenous substance in adjacent frames of differential spectrums in the differential spectrum data to obtain a corrected differential signal corresponding to the target drug in each frame of differential spectrum; based on the fusion weight corresponding to each endogenous substance, performing weighted fusion on the correction differential signals corresponding to all the target drugs to obtain fusion differential signals of the target drugs, and finally determining the drug concentration of the target drugs in each frame of Raman spectrum based on the fusion differential signals of the target drugs. According to the invention, the drug concentration detection precision is effectively improved.

A method for measuring anisotropic film based on zero reflection difference differential signal relates to the field of film thickness detection, and comprises the following steps: measuring wide-band reflection difference spectrum of a sample by using a reflection difference spectrometer and a photoelastic modulation reflection difference spectrometer; determining an incident wavelength corresponding to a zero reflection difference signal: traversing all wavelength channels in the wide-band reflection difference spectrum, and determining a wavelength corresponding to a zero-crossing of the reflection difference signal; determining the thickness of the anisotropic film: determining the thickness of the anisotropic film according to a mapping relationship between the wavelength corresponding to the zero reflection difference signal and the film thickness. The application proposes using the position of the zero-crossing point of the reflection difference signal ΔR / R=0 to determine the thickness of the anisotropic film, so that the error introduced by the difference between the polarization angle of incident light and the crystal axis angle of the anisotropic film can be removed, and further, the time for determining the crystal axis can be saved.

The invention relates to a differential spectrum driven short-time Fourier window length dynamic adjustment method and device and a storage medium. The method comprises the following steps: determining an initial value of an adaptive window length; converting a first frame of the to-be-analyzed signal based on the adaptive window length to obtain an amplitude spectrum corresponding to the first frame; a second frame of the signal to be analyzed is transformed based on the adaptive window length, an amplitude spectrum corresponding to the second frame is obtained, and the second frame and the first frame are overlapped in a preset proportion; determining a difference spectrum between the second frame and the first frame based on the amplitude spectrum corresponding to the second frame and the amplitude spectrum corresponding to the first frame, and updating the adaptive window length based on the difference spectrum; on the basis of the updated adaptive window length, sequentially transforming the residual frames of the signal to be analyzed, and after each transformation, updating the adaptive window length again; and generating a time-frequency analysis result under the condition that all frames of the to-be-analyzed signal are transformed. According to the invention, the time-frequency characteristic of the signal can be rapidly and accurately obtained.

The present invention provides a method and device for identifying parameters of the polarization equivalent circuit of oil-paper insulation equipment. The method comprises characterizing the insulation system of the oil-paper insulation equipment using an extended Debye equivalent circuit model to obtain an equivalent circuit based on the extended Debye model; obtaining a measured complex capacitance real part spectrum line, removing the geometric capacitance from the measured complex capacitance real part spectrum line to obtain a polarization complex capacitance real part spectrum line; differentiating the polarization complex capacitance real part of the polarization equivalent circuit; analyzing and processing the polarization complex capacitance real part quadratic molecular spectrum line function based on the peak point coordinates of each sub-spectral line in the actual coordinate axis; and selecting the peak point coordinates of the polarization complex capacitance real part quadratic differential spectrum line for identification processing to generate a parameter identification result. This method identifies polarization equivalent circuit parameters using unique and accurate peak point coordinates, rather than randomly selecting two points at the end of a sub-spectral line, effectively ensuring the uniqueness and accuracy of the parameter identification result.

The application provides a kind of optical sensing component differential spectral responsivity test system, belongs to the technical field of spectral responsivity test, comprising: modulation light source, for emitting modulation light;Bias light source, for emitting bias light, bias light and modulation light form superimposed light;Standard optical sensing module, obtains the standard value of superimposed light intensity;Measured optical sensing module, obtains the measured value of superimposed light intensity;Signal and control unit calculates the differential spectral responsivity of measured optical sensing module under superimposed light.The application also provides a kind of optical sensing component differential spectral responsivity test method, solves the problem that the test method under darkroom condition in prior art is difficult to test and calibrate the spectral responsivity of optical sensing component under actual application scene condition, realizes the spectral responsivity of measured optical sensing module in the case of background light, and evaluates the anti-interference ability of measured optical sensing module.

The invention discloses a vibration densification process reasoning and mapping system based on decision tree machine learning, and relates to the technical field of machine learning, and the system comprises a data collection unit which is used for carrying out the differential spectrum matching of a target object spectrum at a frequency band of 900nm to 1950nm; the double-domain residual machine learning unit is used for extracting abnormal characteristic parameters window by window by taking the zero pulse of the vibration exciter as a reference signal, judging item by item according to a decision tree model, outputting a continuous strip-shaped result through track constraint and morphological opening and closing operation, and generating a continuous quality map; and the output and feedback unit is used for outputting a continuous compact quality index and speed regulation, pass increasing, vibration switching and water replenishing prompts through a decision tree classifier according to the implicit under-compact probability grid and the water content suitability by taking the vertical acceleration clock of the roller as a unified reference, and writing the continuous compact quality index and the speed regulation, pass increasing, vibration switching and water replenishing prompts into a continuous quality map. According to the invention, the dual-suitable monitoring of the density and the water-containing state is realized, and the problems of unstable abnormal identification and difficult data alignment in the prior art are solved.

The invention relates to the technical field of electrochemical in-situ spectrum monitoring, in particular to a method for monitoring dynamic change of an electrocatalytic reaction intermediate product in real time by using SERS (Surface Enhanced Raman Scattering) spectrum.According to the method, an ultrathin catalytic layer is modified on a high-SERS activity nano substrate in situ, an integrated working electrode is constructed, and a monitoring interface, namely a real reaction interface, is ensured. Through a hardware synchronization system, when dynamic electrochemical excitation is applied, synchronous acquisition of SERS spectrums and electric signals of multiple time scales is implemented. The method comprises the following steps: analyzing fingerprint information, concentration dynamics and evolution sequence of different intermediate products from a spectrum sequence by using algorithms such as dynamic differential spectrum, multivariate curve resolution and two-dimensional correlation spectrum, and finally accurately associating with electrochemical response to construct a dynamic reaction mechanism diagram. According to the invention, real-time and high-sensitivity dynamic analysis on generation, consumption and path evolution of transient intermediate products at a real catalytic interface is realized, and a powerful tool at a molecular level is provided for research on an electro-catalysis mechanism.

The present invention relates to the technical field of chemistry and materials science, and particularly relates to a method and system for identifying the aging failure behavior of rejuvenators based on differential spectrum extraction. The method includes the following steps: obtaining the infrared spectral data of the recycled asphalt sample and the aged asphalt sample at the same stage; preprocessing the infrared spectral data; constructing a characteristic differential spectrum library of the rejuvenator; extracting the change amount of the characteristic peak area; and obtaining the identification result of the aging failure behavior of the rejuvenator by establishing a correlation model between the change amount of the characteristic peak area and the macroscopic performance index. By combining the adaptive morphology - quantile regression baseline correction, peak entropy weighted normalization, and differential spectrum data enhancement algorithms, the present invention realizes the high - sensitivity extraction of the signals of 3% low - dosage rejuvenators; adopts the Gaussian - Lorentz mixed peak - fitting model and the aging response index model to correlate the changes of microscopic functional groups with macroscopic properties, accurately tracking the aging process of rejuvenators, and providing a universal technical framework for the failure determination and performance optimization of rejuvenators.

Provided are an anti-reflection film having excellent scratch resistance and a method for producing the anti-reflection film. [Solution] An antireflection film 1 comprises a transparent substrate film 2, an antireflection layer 3, and an antifouling layer 4, in this order toward one side in the thickness direction. The transparent substrate film 2 comprises a transparent resin film 21. The antireflection layer 3 is an alternating laminate consisting of at least one niobium oxide layer 31 and at least one silicon oxide layer 32, and the layer in the antireflection layer 3 closest to the antifouling layer 4 is the silicon oxide layer 32. In addition, in a difference spectrum calculated by Fourier transform infrared spectrophotometer analysis (FT-IR analysis), -1 The maximum absorption peak intensity due to the Si-O-Si symmetric stretching near 1200 cm is normalized to 1. -1 When the absorption peak intensity resulting from the Si-O-Si asymmetric stretching is defined as X, 1 / X is 5.0 or more.

The invention discloses a fluid type identification method and system based on a nuclear magnetic resonance logging dual-acquisition mode, and the method comprises the steps: obtaining dual-TW logging data and dual-TE logging number according to a combined observation mode of nuclear magnetic resonance logging; based on a nuclear magnetic resonance relaxation theory, according to nuclear magnetic resonance logging data in a double-TW acquisition mode, obtaining a differential spectrum delta T2 and a differential spectrum porosity delta phi; according to the nuclear magnetic resonance logging data in the double-TE acquisition mode, T2 distribution under the double-echo interval is obtained, and the geometric mean difference value delta T2LM of the movable fluid under the T2 distribution under the double-echo interval is calculated; and according to the differential spectrum porosity delta phi and the geometric mean value difference delta T2LM, constructing a comprehensive fluid indication factor of a reservoir fluid identification standard, and carrying out comprehensive identification on the fluid type of the reservoir. According to the invention, two observation modes of nuclear magnetic resonance double TW and double TE are integrated together, the amount of observed data is large, the amount of information is rich, and the fluid type can be rapidly and visually identified.

Aspects of the technology provide a method / system of sensing a change in temperature and / or strain in an optical fibre comprising a substantially continuous or quasi-continuous fibre Bragg grating. A difference spectrum is determined between a reference reflected spectrum of the fibre Bragg grating and a monitored reflected spectrum. The difference spectrum is analysed to determine whether the optical fibre is experiencing a change of type a)—a temperature increase or an extension—or of type b)—a temperature decrease or a contraction. The technology may be applied to sensing a change in temperature and / or strain in a superconductor or detecting a risk of a quench in a superconductor.

To achieve both reducing false detection of false images due to side lobes and minimizing degradation of angular resolution when detecting targets using a radar, by appropriately using a window function.SOLUTION: A target angle detection device 2 includes: an angular spectrum calculation unit 21 that performs digital beamforming on the same received signal of a radar array antenna by using first and second window functions with different side lobe suppression levels to calculate first and second angular spectra, respectively; a difference spectrum calculation unit 22 that calculates an intensity difference spectrum for the first and second angular spectra; and a target angle detection unit 23 that detects a target at a spectral angle where the spectral intensity is within a predetermined interval for the intensity difference spectrum, and determines that it is not a target but a false image at a spectral angle where the spectral intensity is outside the predetermined interval.SELECTED DRAWING: Figure 2

Disclosed in the present invention are a spectral difference analysis method and device for gas-solid interface flashover. The method comprises: acquiring several pieces of gas-gas spectral data acquired by a gas-gas gap discharge experimental device; acquiring several pieces of gas-solid spectral data acquired by a gas-solid surface flashover experiment device; performing averaging operations on the several pieces of gas-gas spectral data and the several pieces of gas-solid spectral data to obtain background spectral data and gas-solid flashover spectral data, the gas-gas spectral data corresponding to the background spectral data, and the gas-solid spectral data corresponding to the gas-solid flashover spectral data; and, on the basis of the background spectral data and the gas-solid flashover spectral data, calculating a differential spectral signal, such that a user performs gas-solid interface flashover analysis on the basis of the differential spectral signal. The present invention analyzes the effect of a spectrum generated by a gas itself on a solid flashover spectrum during the experiment of the gas-solid surface flashover experimental device, thus rendering gas-solid interface flashover analysis more accurate.

The invention belongs to the technical field of biology, and particularly relates to a method for detecting magnetic resonance signals of glutaric acid molecules and application. The method comprises the following steps: firstly, positioning a target area by utilizing a magnetic resonance imaging sequence, and then respectively collecting magnetic resonance spectrograms of EditOn and EditOff states by adopting a water suppression sequence, a volume external suppression sequence and a J editing sequence and setting resonant frequencies of saturated pulses by the J editing sequence; and subtracting the spectrogram acquired in the EditOn state from the spectrogram acquired in the EditOff state to obtain a differential spectrum, so that a glutaric acid signal is selectively excited near 2.2 ppm and a lipid signal is inhibited. A good effect of rapidly and noninvasively measuring the magnetic resonance signal of the glutaric acid molecules in the living body muscle tissue is realized, and the method has important application value in the field of scientific research.