66 results about "Peak analysis" patented technology

The invention relates to the technical field of power line communication, and discloses a frame synchronization method and device for broadband power line communication, and the method comprises the steps: carrying out the symbolization cross-correlation operation of a received signal, and obtaining a cross-correlation result sequence; performing secondary autocorrelation analysis and accumulation processing on the cross-correlation values in the sequence to generate an autocorrelation accumulated value sequence; screening candidate peak positions according to absolute values of the self-correlation accumulated values; defining a synchronous peak analysis window around the candidate peak position, and setting a noise reference window in an area far away from the window; verifying the validity of the candidate peak based on the difference between the autocorrelation accumulated values of the synchronization peak window and the noise reference window; and if the verification is valid, calculating and determining a final synchronization position through a mean value of a plurality of peak value positions in the synchronization peak window. According to the method, the problem of inaccurate synchronization peak positioning under the multipath effect and noise interference in the existing method is solved through the self-correlation accumulation and noise separation mechanism, and the reliability of frame synchronization is improved.

The invention provides an AGV navigation texture feature extraction and identification method, which comprises the following steps: analyzing the spatial distribution position of a plurality of extracted matching peak values according to the matching peak values, counting the number of the peak values and the repeated spacing between the peak values, and identifying a positioning fuzzy region caused by texture cycle repetition; scanning a local aperiodic mark position according to the identified positioning fuzzy region, and performing uniqueness verification based on the geometric shape feature and color attribute of the mark to obtain a unique anchor point coordinate and a mark type; according to the unique anchor point coordinate, combining with the tile texture data to extract a texture repetition interval, analyzing the size of the texture repetition interval and a preset threshold value, and determining a periodic intensity value; dynamically adjusting a position screening range according to the periodic intensity value, establishing a screening constraint condition, and applying the screening constraint condition to a phase correlation method to obtain a preliminary positioning candidate point set;

The invention provides a tip Raman-based metal oxide nanoparticle in-situ detection method, which comprises: S1, dispersing metal oxide nanoparticles in a nanoparticle dispersion liquid, focusing laser to the tip of a nanometer tip through an objective lens, capturing a single nanoparticle by using an optical tweezers technology, and attaching the single nanoparticle to the nanometer tip; s2, focusing Raman laser on a nano needle tip-particle interface, generating a local high-temperature field through a photo-thermal near-field coupling effect, triggering a thermal chemical reaction of nano particles, and synchronously collecting a Raman spectrum; and S3, carrying out pretreatment and characteristic peak analysis on the collected Raman signal of the Raman spectrum, and determining the reaction critical temperature and the dynamic process in combination with temperature calibration data. According to the invention, capture and accurate heating of the nanoparticles are realized through photo-thermal coupling of the optical tweezers and the needle tip, and thermal chemical reaction monitoring of the nanoparticles is realized.

The invention discloses a liquid chromatographic peak intelligent analysis method and system based on deep learning, and relates to the technical field of data processing. The method comprises the following steps: constructing a chromatographic peak intelligent analysis network based on deep learning, and training the network by using a sample chromatogram until convergence; inputting a to-be-analyzed chromatographic signal into the chromatographic peak intelligent analysis network, and evaluating the reliability of a prediction result based on the probability distribution of the key physical parameters output by the chromatographic peak intelligent analysis network to obtain a result confidence coefficient; dynamically adjusting the number and composition of the sample chromatograms based on the result confidence and a preset confidence threshold, and continuously updating the chromatographic peak intelligent analysis network; and recording an attention mechanism of the chromatographic peak intelligent analysis network as a weight fraction allocated to each data point, mapping the weight fractions back to a time sequence of an original chromatographic signal, carrying out visualization through a color gradient, and superposing the weight fractions on an original chromatographic curve in a semitransparent layer form to generate a chromatographic peak thermodynamic diagram. According to the invention, the efficiency and precision of liquid chromatography analysis are effectively improved.

The invention relates to the technical field of electrical variable measurement, in particular to a high-frequency partial discharge signal intelligent identification method, which comprises the following steps of: monitoring a partial discharge signal, and performing real-time calculation on signal frequency and energy to obtain frequency distribution data and energy data; and determining a main frequency band according to the peak value of the frequency distribution data, and generating main frequency band data. According to the invention, by monitoring the partial discharge signal in real time and calculating the frequency and energy of the partial discharge signal, frequency distribution data and energy data are provided, so that the signal processing is more accurate. Through peak analysis of frequency distribution data, a main frequency band can be determined more accurately, and the filter and transformation parameters are further optimized. The dynamic parameter adjustment enhances the response capability to the signal change, and improves the accuracy of signal classification. A new signal processing strategy can keep efficient operation in a constantly changing operation environment, the accuracy of fault prediction is enhanced, and health monitoring and maintenance decision making of power equipment are supported.

The invention relates to the technical field of agricultural product safety detection, in particular to an agricultural product veterinary drug residue high-throughput detection method and system based on spectrum peak analysis. The method comprises the following steps: acquiring multiple batches of spectral data, and performing cross-batch pre-alignment according to the multiple batches of spectral data to obtain cross-batch alignment data; performing background baseline estimation according to the cross-batch alignment data to obtain background baseline data; congestion detection area extraction is carried out according to the cross-batch alignment data to obtain congestion detection area data; performing common-peak decoupling according to the congestion detection area data to obtain common-peak decoupling data; performing residual image construction on the common peak decoupling data according to the background baseline data to obtain residual image data; performing image feature extraction according to the residual image data to obtain image feature data; and performing residual judgment according to the graph feature data to obtain residual judgment data. According to the method, the identification accuracy of spectrum peak pseudo-congestion and residual abnormity in a high-throughput mixed agricultural product detection scene is improved.

The invention provides a traditional Chinese medicine formula granule spectrum similarity evaluation system, and relates to the technical field of traditional Chinese medicine, and the system comprises: a spectrum acquisition module, which is used for separating active components with similar polarity in a compound salvia miltiorrhiza formula granule test solution by gradient elution based on chromatographic conditions to obtain a characteristic spectrum; and the analysis processing module is used for carrying out analysis processing on overlapped chromatographic peaks in the characteristic spectrum, distinguishing characteristic signals corresponding to main active components and trace components, and realizing separation and identification of characteristic peaks of different components in the mixture so as to obtain a characteristic peak analysis result. According to the method, the standard characteristic chromatogram database is constructed through gradient elution and deconvolution processing, and the accuracy and standardization of quality evaluation of the traditional Chinese medicine formula granules are improved.

The invention discloses an LVDT sensor precision correction method based on machine learning, and relates to the technical field of LVDT sensors. The method comprises the following steps: collecting an LVDT sensor response signal and a disturbance source parameter; obtaining a sub-band of an LVDT sensor response signal through a multi-level wavelet packet decomposition algorithm, calculating a sub-band energy index and a sub-band energy entropy, and obtaining an energy concentration index in combination with the maximum value of the sub-band energy index and the sub-band energy entropy; obtaining a sub-band peak factor through peak analysis, and obtaining a sub-band comprehensive peak index in combination with the sub-band energy index; clustering response signal features of the combination of the energy concentration index and the sub-band comprehensive peak index through a KMEANS algorithm to obtain a response signal cluster, and adding an interference feature tag through a disturbance parameter; constructing a sensor precision error prediction model; and collecting an LVDT original signal in real time and inputting the LVDT original signal into the sensor precision error prediction model of the corresponding interference label to obtain an LVDT signal error result, thereby realizing precision correction.

The invention relates to a Rydberg atomic communication receiving system and method based on AT split peak value analysis, and belongs to the technical field of quantum communication. The system comprises a detection laser, a coupling laser, an AOM / EOM, a function generator, a high-frequency signal generator, a cesium atom gas chamber, a photoelectric detector, a lock-in amplifier, a data acquisition module and a microwave signal output module. The AOM / EOM modulates the frequency of the detection laser; the microwave signal output module generates an AM modulation microwave signal and transmits the AM modulation microwave signal to the cesium atom gas chamber, so that the target Rydberg state atoms generate an AT splitting effect to calibrate system parameters; the photoelectric detector and the lock-in amplifier obtain a first harmonic component based on the transmission light. During communication, the system is arranged in a microwave electric field received by communication, and the data acquisition and processing module outputs AM modulation microwave signals received by the recovered cesium atom gas chamber based on calibrated system parameters and phase locking. The method solves the problem of signal distortion existing in EIT-AT direct communication transmission and the problem of tedious operation of a heterodyne method.

The invention discloses a calibration-free laser absorption spectrum signal processing method based on double spectral lines, which comprises the following steps of: utilizing a polynomial fitting algorithm and a multi-peak analysis algorithm and combining known wavelengths or wave number positions of two adjacent spectral lines of a molecular absorption spectral line; according to the invention, rapid pickup of original light intensity background signals of a laser light source and absolute calibration of emission wavelength of a laser in a tunable laser absorption spectrum system are realized respectively, and the defect that background signals are obtained by using high-purity nitrogen or zero air in a traditional method is overcome. The method has the advantages that the response time is short, the reliability is high, and the reliability problem of long-term measurement results of a tunable laser absorption spectrum technology or a gas sensor in an actual external field environment is effectively solved; the important defects in the prior art are overcome, and the practical value is wide.

The invention provides an m6A online analysis platform based on bioinformatics, which comprises a grouping scheme module, a Peak set screening module, a sample relation module, a Peak feature analysis module, a methylation difference analysis module and a target Peak analysis module, and is characterized in that the Peak set screening module is used for screening a sample; according to the grouping scheme, sample grouping names are modified according to experimental design, grouping is eliminated, and the grouping scheme is determined and comprises the function of newly establishing the grouping scheme; peak set screening is to screen the peak according to a certain condition to form a peak set so as to carry out targeted analysis, including generation of a new peak set and combination of peak set functions; the sample relationship comprises PCA, a correlation heat map and a sample clustering map; the peak feature analysis comprises peak distribution analysis, Motif analysis, enrichment of a related gene GO and enrichment of a related gene KEGG; the methylation difference analysis comprises difference peak analysis, Motif analysis, enrichment of a related gene GO and enrichment of a related gene KEGG; the target Peak analysis comprises a target Peak Wehn diagram, a related gene Wehn diagram, Motif analysis, related gene GO enrichment and related gene KEGG enrichment. The online analysis platform and the generation method are user-friendly, powerful in function and visual in result, and have the advantages that the operation process is simplified, the analysis precision is improved, and result display is enriched.

The present application relates to the technical field of power line communication, and discloses a frame synchronization method and device for broadband power line communication. The method includes: obtaining a cross-correlation result sequence by performing symbolized cross-correlation operation on a received signal; performing secondary autocorrelation analysis and accumulation processing on the cross-correlation values in the sequence to generate an autocorrelation accumulation value sequence; screening candidate peak positions according to the absolute values of the autocorrelation accumulation values; defining a synchronization peak analysis window around the candidate peak positions, and setting a noise reference window in a region far from the window; verifying the effectiveness of the candidate peaks based on the difference in autocorrelation accumulation values between the synchronization peak window and the noise reference window; if the verification is effective, determining the final synchronization position by calculating the mean value of multiple peak positions within the synchronization peak window. This method solves the problem of inaccurate synchronization peak positioning in the existing methods under multipath effects and noise interference through an autocorrelation accumulation and noise separation mechanism, and improves the reliability of frame synchronization.

The invention relates to the technical field of data processing, and discloses a bandwidth traffic peak analysis method and system based on time series data and a storage medium, and the method comprises the steps: preprocessing service data to obtain a to-be-predicted sample Y and a training library B; randomly extracting n1 samples from the B, and calculating the distance between each sample and the Y; in n1 samples, arranging in a descending order to form a set Ct1; circularly calculating to obtain a plurality of Ct1 and taking a union set as CT; calculating to-be-predicted data in Y as Y1 according to CT; calculating delta y = Y1-y1, wherein y1 is a true value; random samples of the CT are removed, delta y is updated, and the sample with the minimum delta y in the CT is deleted; updating the CT, moving the data to be measured forward, and circulating to form a CTm sequence; calculating a Ym value of the current to-be-measured data; according to the Ym value, the bandwidth is adjusted in a positive correlation mode, and the bandwidth is automatically adjusted through flow prediction.

The application provides a kind of multi-agent-based spectral data autonomous analysis method, it is related to the technical field of data processing, method includes: through multi-agent cooperation mechanism, the whole process of spectral data from acquisition, quality evaluation, pretreatment, spectral peak analysis to phase inference is unified modeling and scheduling, data quality information is converted into constraintable pretreatment strategy by central coordination agent, and consistency check and conflict arbitration are implemented on spectral peak parameters and phase inference results at the end of analysis, so that adaptive processing and result check are realized under the premise of maintaining spectral structure correlation relationship.The application can improve the accuracy of spectral data analysis.

The invention discloses a superfluid helium second sound wave attenuation measurement system. The system comprises a signal generation module, a transducer module, a signal conditioning module, a bias power supply module, a protection isolation module, a data processing module, a temperature control module and a pressure control module. The signal generation module outputs AC excitation signals, the transducer module converts electric signals and second sound waves mutually, the signal conditioning module extracts effective signals and outputs direct-current signals, the bias power supply module provides direct-current bias voltage, the protection isolation module guarantees equipment safety and signal isolation, and the temperature and pressure control module maintains the superfluid helium state to be stable. The data processing module supports a steady state measurement mode and a transient state measurement mode, and vortex line density is analyzed and calculated through harmonic peaks. Compared with an existing measurement system, the system is high in signal stability, standard in calibration process, suitable for various measurement scenes, convenient to operate and wide in applicability, and high-precision quantitative measurement of superfluid helium second sound wave attenuation is achieved.

The embodiment of the invention discloses a VOCs data digital intelligent quality control auditing and processing method and system and electronic equipment. A specific embodiment of the method comprises the following steps: preprocessing acquired volatile organic compound spectrogram data; performing peak analysis on the preprocessed spectrogram data; performing substance matching on the chemical peak characteristic data set; obtaining a chemical peak concentration set based on a substance matching result; based on a multi-stage abnormal data analysis algorithm, obtaining an abnormal analysis result; and obtaining an anomaly correction result based on a preset anomaly correction model. According to the embodiment, the effect that equipment abnormity correction cannot be carried out according to the abnormity analysis result is achieved.

A chromatogram analyzer having a function for automatically excluding noise peaks from analysis targets is provided. [Solution] In a fluid chromatograph (100), a sample arrival time, which is the time required for a sample injected into a mobile phase to reach a detector (108), and a mobile phase arrival time, which is the time required for the mobile phase delivered from a liquid delivery device (102) to reach the detector (108), are calculated based on system information, which is the capacity of the piping, flow rate information related to the flow rate of the mobile phase, and composition information for each time period during analysis. A target range determination unit (8) determines these based on the mobile phase arrival time and the sample arrival time so that composition-related peaks, which are peaks caused by a sudden change in the composition of the mobile phase, and injection-related peaks, which are peaks caused by the injection of the sample, are excluded from the analysis target. The system is configured to perform peak analysis within the target range determined by the target range determination unit (8).

The invention provides a microbial pollution source tracing method based on Sanger sequencing overlapping peak analysis, which comprises the following steps: analyzing and enumerating multi-base overlapping peaks in a sequencing peak graph to generate all possible base combination sequences, comparing with a microbial database, and screening effective sequences to identify bacterial strain types. And high-threshold homologous comparison is further carried out on the identified mixed strains and a pre-constructed pollution source standard gene sequence library, so that the pollution source is accurately traced. According to the method, original invalid sequencing data is fully utilized, repeated experiments are avoided, and accurate identification of main strains and systematic tracing of pollution sources are realized.

This application discloses a method, apparatus, device, and storage medium for identifying population changes, applied in the field of population census. The method includes: acquiring initial height data of rented rooms collected by an ultrasonic device in the current period; performing density distribution analysis on the initial height data using a kernel density estimation algorithm to obtain a height distribution probability formula; fitting the height distribution probability formula into a height curve using a grid data cross-validation method; performing peak analysis on the height curve to determine the number and height of people in the rented room; and determining whether population change has occurred based on the number and height. This application utilizes density distribution analysis and grid data cross-validation to overcome the inaccuracies in detecting multiple people in existing technologies. Specifically, when multiple people are present in a rented room, this method can accurately detect the number and height of people in the room, and determine whether there has been a change in the number of people or population movement based on their height and number of people in the room.

The application relates to a method for rapidly and automatically distinguishing components in a mixed solution based on a TLC-SERS technology, and relates to the field of spectral detection; the application aims to solve the problems that TLC-SERS cannot accurately analyze substances with similar structures and is too dependent on subjective interpretation and ability of operators; the application assembles silver sol nanoparticles on the surface of a TLC plate, and a large-area TLC-SERS substrate with high sensitivity and repeatable detection is prepared; spectral collection is carried out, and TLC-SERS spectra of all target substances are generated; then, two machine learning algorithms are adopted to analyze the TLC-SERS spectral data; compared with a conventional manual SERS peak analysis method, the proposed machine learning algorithm depends on overall analysis of spatial information and spectral information of the TLC-SERS spectral data, instead of spectral information determined by main characteristic SERS peaks, so that the accuracy of SERS peak identification of different substances is greatly improved.

The invention discloses a method for measuring the original austenite grain size of high alloy steel through an X-ray diffractometer method, and belongs to the technical field of metal material detection. According to the method provided by the invention, nondestructive testing is realized by establishing the quantitative relation model of the martensite phase change product and the original grain size, chemical erosion and mechanical damage of a traditional metallographic method to a sample are avoided, the method can be directly used for quality inspection of a finished product, and a new technical means is provided for whole-process quality control of a steel product; an optimized diffraction peak analysis algorithm is combined, so that the measurement precision is remarkably improved; the detection process is simple, convenient and efficient, the single detection time can be shortened to be within 30 minutes, the detection efficiency is greatly improved, and the method is particularly suitable for rapid detection requirements of batch samples.

The invention discloses a mass spectrometric detection method for bisphenol A in milk through rotary evaporation pretreatment and multi-charge peak analysis. The mass spectrometric detection method comprises the following steps: step 1, carrying out rotary evaporation pretreatment on fresh milk; step 2, carrying out rotary evaporation treatment on the milk sample; 3, omics analysis of lipid, metabolites and protein is completed, and UHPLC-Q-Orbitrap HRMS strategy processing based on vDIA is achieved; and 4, analyzing the group database by adopting a multi-charge overlapping peak extraction algorithm and a graph neural network strategy to realize substance identification. The invention belongs to the technical field of mass spectrometry, and solves the problems that the detection error is large when microgram / L-level trace detection of bisphenol A in milk is carried out in the prior art, and false positive is easy to occur due to a wide mass window in the traditional extraction ion chromatography.

A chromatography analysis device is provided with: a system information storage unit (2) for storing a system capacity, which is the capacity of a pipe through which a sample of a fluid chromatograph (100) passes; an analysis information storage unit (4) that stores a chromatogram obtained by the analysis performed by the fluid chromatograph, flow rate information relating to the flow rate of the mobile phase at the time of analysis, and composition information relating to the composition of the mobile phase at each time period at the time of analysis; a time calculation unit (6) that calculates, on the basis of the system capacity, the flow rate information, and the composition information, a mobile phase arrival time required for a mobile phase delivered from a liquid delivery device (102) of the fluid chromatograph to reach a detector (108), and a sample arrival time required for a sample into which the mobile phase is injected to reach the detector; a target range determination unit (8) that determines a target range for peak analysis on the chromatogram on the basis of the mobile phase arrival time and the sample arrival time so as to exclude composition-caused peaks and injection-caused peaks from analysis targets; and a peak analysis unit (10) that performs peak analysis in the target range determined by the target range determination unit.

To detect a solid such as an aggregate contained in a liquid specimen with high accuracy.SOLUTION: An aggregate detecting device includes a light source configured to irradiate light to a specimen sealing tube in which a liquid specimen is sealed, a light receiving unit configured to detect polarized light transmitted through the specimen sealing tube, and a processor, wherein the processor calculates a polarization intensity value from image data of the polarized light detected by the light receiving unit, and performs peak analysis from a distribution of the polarization intensity value to determine presence or absence of a solid material.SELECTED DRAWING: Figure 4

According to examples, a fiber element offset length-based optical reflector peak analysis apparatus may include an optical element optically connected to a laser source that emits a laser beam. The optical element may include a pre-set offset length between a plurality of adjacent branches. The fiber element offset length-based optical reflector peak analysis apparatus may further include an optical time-domain reflectometer (OTDR) to generate, based on optical reflection signals received from corresponding optical reflectors attached to devices under test (DUTs) that are attached to the plurality of adjacent branches, an OTDR trace that qualifies each of the DUTs.

The invention provides a method and a system for detecting the width and uniformity of a cigarette ash packing carbon thread, and belongs to the technical field of cigarette detection. The detection method comprises the following steps: acquiring a multi-angle initial image of a to-be-detected cigarette before combustion and a multi-angle sample image in a combustion stage; pixel difference is carried out on the initial image and the sample image, and a residual image is generated; performing binarization processing on the residual image through an adaptive threshold algorithm, and generating a binary image presenting a carbon wire region; processing the binary image by using a transverse projection method, determining the starting position and the ending position of the carbon thread, and automatically positioning and identifying a carbon thread area by using projection peak analysis; and segmenting the carbon wire region, and calculating the width and uniformity of the carbon wire in the segmented carbon wire region. Accurate and efficient detection of the width and uniformity of the cigarette ash packing carbon thread under the complex background and different illumination conditions is realized.

This invention relates to the field of artificial intelligence technology, and discloses a text content comparison and matching method, apparatus, device, and medium. The method includes sequentially performing character adaptation and normalization, phonological encoding conversion, segmentation processing, fuzzy weighted edit distance calculation, peak analysis and path backtracking, and jump threshold traversal judgment on template text and speech recognition text to obtain text comparison and matching result data. In this invention, addressing the problem that existing text content comparison and matching schemes struggle to accurately identify the continuous inclusion of speech recognition text in template text, character adaptation and normalization and phonological encoding conversion can eliminate character form differences; segmentation processing and fuzzy weighted edit distance calculation can suppress accumulated errors; and peak analysis, path backtracking, and jump threshold traversal judgment are then applied. This method can be applied to the financial and medical fields, thus accurately identifying the continuous inclusion of speech recognition text in template text at the character granularity.

This invention relates to the technical field of signal analysis and discloses a method for peak analysis of a primary frequency modulated (FM) large disturbance signal. The method includes: acquiring a FM large disturbance signal and performing filtering processing for multi-band noise separation; performing multi-scale decomposition on the filtered disturbance signal, extracting the dynamic entropy of the multi-scale signal sequence, and performing dynamic entropy denoising on the disturbance signal to obtain a denoised disturbance signal; calculating the potential peak position of the denoised disturbance signal, verifying the potential peak position under multiple conditions, and obtaining peak information for FM disturbance analysis. This invention is based on spectral energy distribution, selects specific wavelet bases for denoising different noise frequency bands, improves wavelet denoising performance, extracts the energy distribution complexity and structural complexity of the disturbance signal at different scales, more comprehensively captures the dynamic characteristics of the disturbance signal, improves denoising accuracy, and thus improves the accuracy of wind power grid connection fault identification and equipment life monitoring during peak analysis.

The invention relates to the technical field of intelligent sensors, in particular to a concrete stirring performance prediction method based on deep learning, which comprises the following steps: synchronously acquiring a concrete diffuse reflection spectrum and a friction acoustic emission signal in a pneumatic optical coupling flow environment; the chemical components of the expanding agent are represented by analyzing the differential form of a spectral absorption peak, and the particle rheological state is analyzed by combining the time-frequency energy entropy evolution law of the sound wave signal; performing physical verification and dynamic fusion on the chemical component characteristics according to the rheological state analysis result to generate an intermediate index reflecting the mixing uniformity; and thermodynamic dissipation equilibrium constraint of particle fluid dynamics is introduced to carry out energy consistency correction on the index, and finally the restricted expansion rate representing the volume stability of the material is calculated. According to the invention, real-time online prediction and analysis of the restrained expansion rate of concrete in a severe environment are realized through multi-dimensional collaborative perception of the intelligent sensor and heterogeneous signal analysis under physical constraints.

Provided are a peak analysis method and a peak analysis device that are capable of identifying, from a plurality of items of data obtained from a detection device, the number of peaks included in a spectrum required for performing peak separation processing and a target for the peak separation processing. This peak analysis method analyzes spectrum peaks in a plurality of items of data obtained from a detection device. The peak analysis method includes: a step for setting an analysis target spectrum vector and a non-target spectrum vector; a step for dividing the analysis target spectrum vector into components in the direction of the non-target spectrum vector; and a step for transferring prescribed proportions of the spectrum vectors between the non-target spectrum vector and the analysis target spectrum vector on the basis of comparison of components in the direction of the analysis target spectrum vector with the non-target spectrum vector.