348 results about "Curve analysis" patented technology

The invention provides a fuzzy curve analysis based soft sensor modeling method using time difference Gaussian process regression, it is suitable for application in chemical process with time delay characteristics. This method can extract stable delay information from the historical database of process and introduce more relevant modeling data sequence to the dominant variable sequence. First of all, the method of fuzzy curve analysis (FCA) can intuitively judge the importance of the input sequence to the output sequence, estimate the time-delay parameters of process, and such offline time-delay parameter set can be utilized to restructure the modeling data. For the new input data, based on the historical variable value before a certain time, the current dominant value can be predicted by time difference Gaussian Process Regression (TDGPR) model. This method does not encounter the problem of model updating and can effectively track the drift between input and output data. Compared with steady-state modeling methods, this invention can achieve more accurate predictions of the key variable, thus improving product quality and reducing production costs.

The invention discloses a method for the geometric transformation calibration and the curved surface interpolation modification of a laser line scanning probe, and a device; the noncontact measurement technology is adopted to be used for the accurate calibration and further modification of the probe of a laser line scanning three-dimensional profile measuring system; the method carries out calculation on the basis of the basic measuring principle of a probe system and completely eliminates calibration theory errors brought by the traditional calibration method (such as a polyfit calculation method, etc.). In the detailed parameter calculating process, the statistical analysis technologies of curve analysis and least squares, etc., are adopted by the algorithm; therefore, the requirement of multiscale calibration caused by the related factors of lens distortion, probe assembly and adjustment error, etc. to different calibration areas is fully considered on the basis that the basic principle is fully met, thus leading the probe to have excellent stability and operability.

The invention relates to method, wherein the number of repeat sequences which are present in a sample is detemined by means of melting temperature analysis. More precisely, the invention relates to a method for analysis of a target nucleic acid consisting of repetitive and non repetitive sequences comprising (i) hybridization of at least one polynucleotide hybridization probe comprising a first segment which is complementary to a non repetitive region and a second segment which is compementary to an adjacent repetitive region, said second segment consisting of a defined number of repeats and (ii) determination of the melting point temperature of the hybrid which has been formed between the target nucleic acid and the at least one hybridization probe.

The invention discloses a power industry low-voltage transformer area line loss analysis method based on big data. The method comprises the following steps: 1, extracting high-load loss and uncalculable transformer areas in synchronous line loss of an acquisition system to construct basic line loss archive data; 2, analyzing and collecting abnormal archive factors by combining the archive data ofthe collection system; 3, analyzing abnormal work order information by combining the work order data of the acquisition system; 4, combining the curve data of the acquisition system, and counting metering abnormal factors; 5, analyzing the abnormity of the electricity stealing factor by combining the power current curve data and related ammeter reporting events; 6, analyzing on-site wiring abnormity in combination with the current and power curves; and 7, carrying out line loss abnormal district intelligent diagnosis through various abnormal detail data, and collecting a feedback abnormal defect elimination result. The invention also discloses a related analysis processing system.

Bandwidth expansion for audio signals by frequency band translations plus adaptive gains to create higher frequencies; use of a common channel for both stereo channels limits computational complexity. Adaptive cut-off frequency determination by power spectrum curve analysis, and bass expansion by both fundamental frequency illusion and equalization.

The invention provides a measurement and analysis system of the voltage and frequency and its analysis method. The invention can be applied in the fields of the detection, data acquisition and analysis, and the frequency conversion technology. The device can measure the voltage signal and the frequency signal, and the precision can reach as high as 10<-6>. The invention provides a calculation and analysis method of the linearity of the voltage-frequency curve Alpha out, the ratio of the voltage and frequency Kout and the base point of the voltage and frequency V50Hz, coordinates with the drawing and analysis method of the voltage-time, the frequency-time and the voltage-frequency curve, to provide the effective auxiliary analysis method for the operation condition of the variable frequency equipment, thereby realizing the function of low cost, high precise, wide-range measurement on the voltage and frequency and intelligent analysis function of the measurement results.

The invention discloses a micro-indentation-based method for testing residual stress of a tiny area of a tough block material and belongs to the technical field of nondestructively testing the residual stress of the tiny area. The method comprises the following steps: performing micro-indentation experiment on a test sample block and a standard sample block to obtain a loading-unloading curve; according to the loading-unloading curve, obtaining parameters for calculating the residual stress under the combination of a dimensionless function; and analyzing the types of the residual stress according to the loading-unloading curve and calculating the residual stress by virtue of average contact pressure and a residual stress expression. The method is used for testing the residual stress of a tiny area of a tough block material.

The embodiment of the invention provides a method for forecasting reservoir fluid property through earthquake attenuation attribute. The method comprises the following steps of: determining the relation between a reservoir saturation degree and a stratum quality factor, wherein the relation between the reservoir saturation degree and the stratum quality factor comprises a variation curve between the reservoir saturation degree and the stratum quality factor, and a saturation degree position when the attenuation peak appears; performing reservoir reflecting interface structure explanation in earthquake result data, and determining a reflecting time position of a reservoir in an earthquake section plane; determining the magnitude of the stratum quality factor; smoothing and processing the stratum quality factor along a reflecting interface, and adopting a differential computing method on an earthquake quality factor to determine the magnitude of differential attenuation attribute; and analyzing the variation curve between the reservoir saturation degree and the stratum quality factor to determine reservoir fluid property distribution. The reliability and the precision of prediction on the earthquake reservoir property can be improved through the embodiment of the invention.

The invention discloses a power curve analysis based wind generating set yaw error inherent deviation recognition and compensation method. In the method, based on wind generating set data supervisorycontrol and data acquisition (SCADA) system real-time operation data including a wind speed, an active power, a yaw error, an environment temperature and an ambient air pressure, firstly, wind speed and power data are divided according to a certain yaw error interval after the data is preprocessed to a certain extent, fitting is performed on power curves under different yaw error intervals througha standard power curve fitting flow, quantitative analysis on different power curves is further performed, a yaw error inherent deviation value interval range is determined based on an interval judgment criterion, and finally, an inherent deviation value obtained through identification is directly compensated for a yaw error actual measurement value in an incremental form. The method is based ondata drive, does not have special requirement for wind generating set operation data, has relatively strong universality and has very strong application value on improvement on the wind generating setperformance.

An anemometer and method for analyzing fluid flow is described. In one embodiment, a transistor sensor is heated by applying power to cause its base-emitter junction to rise from an ambient first temperature to a second temperature. The power is removed, and the Vbe is measured at intervals as the junction cools. The Vbe equates to a temperature of the junction. The temperature exponentially decreases, and the time constant of the decay corresponds to the fluid flow velocity. A best fit curve analysis is performed on the temperature decay curve, and the time constant of the exponential decay is derived by a data processor. A transfer function correlates the time constant to the fluid flow velocity. The transistor is thermally coupled to a metal rod heat sink extending from the package, and the characteristics of the rod are controlled to adjust the performance of the anemometer.

The invention relates to a power curve-based speed-raising turnout fault information processing method, which comprises the following steps of: (1) storing a standard three-phase power curve in a standard curve database in sections as a normal curve; (2) performing feature extraction on the three-phase power curve during failure of a turnout in each section process, and storing an abnormal curve in an abnormal curve database; (3) transmitting the three-phase power curve acquired by a turnout curve acquisition device to a turnout curve analysis processor; and (4) sectioning the received three-phase power curve by the turnout curve analysis processor, performing feature matching with the standard curve and the abnormal curve section by section, and the like. Compared with the prior art, the method has the advantages of effectively recognizing normal and abnormal features of the three-phase power curve in a speed-raising turnout operation process and the like.

The invention relates to a method and a kit for detecting gene mutation, in particular to a method and a kit for detecting the mutation of BRAF gene. The invention is characterized in that the kit comprises a specific probe used for carrying out genotyping on No. 15 exon codon V600E of the BRAF gene, wherein the specific probe of the No. 15 exon codon V600E comprises a nucleotide sequence of V600E codon. by the technology combining the conventional polymerase chain reaction (PCR) amplification with a Cold-PCR enrichment amplification product and a high resolution melting curve analysis technology, the kit provided by the invention can be used for completing the judgment on sample genotyping.

The invention relates to a method for analyzing and processing turnout curves. The method comprises the following steps: judging standard fault curves in a turnout curve polling and calling standard fault curve database one by one; if the standard fault curves conform to a standard fault result, displaying the fault content; if no fault is found during the polling of all the standard fault curves, calling a non-standard fault experience database; if non-standard fault curves which are matched with the current curves are directly found in the non-standard fault experience database, determining that the current curves have the faults; if the current curves cannot be matched with the non-standard fault curves in the non-standard fault experience database, and cannot be matched with the standard curves at the same time, determining that the curves have a novel fault type; and storing the current curves in the non-standard fault experience database. The accuracy of the standard fault curve database of the method is higher, but the application range is narrower; while the accuracy of the non-standard fault experience database is not very high, but the non-standard fault experience database can judge whether the curves have the faults or not within a wider range, and the accuracy and the wider range. The standard fault curve database and the non-standard fault experience database complement each other to achieve high efficiency.

The invention discloses primers, a kit and a detection method for detecting the genders of cotuenix coturnix, and belongs to the technical field of molecular biology. According to the invention, specific primers are designed by using length difference of CHD1 (Chromodomain-Helicase-DNA-binding protein 1) genes of the cotuenix coturnix on Z chromosome and W chromosome; genome DNAs of the cotuenix coturnix are taken as templates for performing PCR (Polymerase Chain Reaction) amplification and dissolution curve analysis; the karyotype of female cotuenix coturnix is ZW type, a PCR product contains two fragments with different sizes, and the sizes of strips are 470bp and 638bp respectively, so that the dissolution curve has two peaks; the karyotype of male cotuenix coturnix is ZZ type, a PCR product only contains one fragment, and the size of the strip is 638bp, so that the dissolution curve has one peak; the male cotuenix coturnix and the female cotuenix coturnix can be clearly distinguished by using the difference of the dissolution curve. The detection method for the genders of the cotuenix coturnix, disclosed by the invention, has the characteristics of quickness, accuracy, economy and practicality, and is suitable for high-throughput operation.

The invention discloses a monitoring system and method for key parameters of pig growth based on NB-IoT. The monitoring system includes a field device side, a remote server and a mobile client. The field device side comprises an information identification module, a PLC, a parameter acquisition module, a feeding drive module and a feeding device, which can realize automatic feeding and automatic acquisition of pig weight, body temperature, feed intake, feeding frequency and field temperature and humidity information. The collected data are uploaded to the NB-IoT connection management platform through NB-IoT, and the data are parsed and pushed to the remote server by the platform. The remote server processes the data collected in the field and determines whether an exception has occurred. The mobile client comprises a login module, a monitoring node management module, an early warning module, an information monitoring module, and a historical curve analysis module. The monitoring systemand method for key parameters of pig growth based on NB-IoT can effectively obtain the growth parameters of the pigs, and monitor the body temperature and the feeding information which have a great relationship with the health of the pigs throughout the day, and the breeders can timely find the pigs with abnormal health and obtain the early warning information through the mobile phone.

The invention relates to a sliding window time difference-Gaussian process regression modeling method based on local time lag reconstruction. The method is suitable for chemical processes with time lag, nonlinear and time-variant characteristics. By means of the method, the latest process time-variant dynamic state can be tracked step by step through a sliding window strategy; meanwhile, parameters are extracted from process periodical time lag characteristics through a fuzzy curve analysis method in a sliding window and used for time lag reconstruction of local model training samples and testing samples; the variable drift characteristics on the locally-reconstructed sliding window are depicted through a time difference-Gaussian process regression (TDGPR) model. An effective real-time prediction and control technical support means is provided for the industrial process, product quality can be easily improved, production cost is controlled, and potential safety hazards are avoided.

The invention discloses a serum miRNAs specific expression profile for early colonic adenocarcinoma and rectal adenocarcinoma, which is formed by up-regulated expressed miR-19a-3p, miR-92a-3p and miR223-3p and down-regulated expressed miR422a. A reverse transcription primer and a detection primer, which are shown as SEQ ID NO: 1-9, of the miRNAs are specifically expressed in the serum miRNAs specific expression profile for the early colonic adenocarcinoma and rectal adenocarcinoma. The invention also provides a serum miRNAs disgnosis model for the early colonic adenocarcinoma and rectal adenocarcinoma, the following formula of logit(P=CAC)=0.4424-0.0092*(miR-19a-3p)-0.0368*(miR-92a-3p)-0.0517*(miR-223-3p)+0.2439*(miR-422a) is used for calculation and for the diagnosis on the early colonic adenocarcinoma and rectal adenocarcinoma, the diagnosis efficiency of the serum miRNAs model on the colonic adenocarcinoma and rectal adenocarcinoma is higher and is higher than that of the traditional tumor marker CEA through ROC (Receiver Operating Characteristic) curve analysis, and the model can used for the diagnosis on the early colonic adenocarcinoma and rectal adenocarcinoma patient (TNM I / II period).

This document relates to melting curve analysis of nucleic acids. The method according to first aspect of the invention comprises analyzing a nucleic acid melting curve measured from a sample, the melting curve comprising a sum signal of at least two nucleic acid melt signals and a background signal as a function of temperature. The method further comprises optimizing at least one constant in a temperature-dependent exponential correction function so as to minimize the variation of the nucleic acid melting curve at a temperature region where the target nucleic acids in the sample remain essentially double stranded, and generating a corrected nucleic acid melting curve representative of the nucleic acid melt signal by applying said exponential correction function over the region of the measured melting curve where the strands of the nucleic acids dissociate. According to further aspects, the invention relates to a curve fitting algorithm for precise estimation of melting peak areas and a mathematical transformation for linearization of calibration curve data to enhance the linear measuring range of a competitive PCR assay. The invention provides a powerful tool for analyzing PCR-amplified sample containing two or more different nucleic acids having similar but distinguishable melting temperature.

Embodiments of the invention are directed to a method of estimating the physical stability of a protein formulation. A particular embodiment of the invention places the protein formulation under an agitational stress that causes the protein to aggregate at an accelerated rate. In one embodiment, the change in protein aggregation is monitored spectroscopically using Thioflavin-T. Embodiments of the invention then utilize a survival curve analysis to ascertain the relative physical stability of the different protein formulations under study. This method was used to develop novel surfactant-stabilized insulin formulations in a rapid, cost efficient manner, thus illustrating the utility of the inventive method to the discovery and development of pharmaceutical protein formulations.

The invention discloses an early bladder cancer serum miRNAs specific expression profile. The early bladder cancer serum miRNAs specific expression profile is composed of miR-152 and miR-148b-3p which are used for expressing up regulation as well as miR-3187-3p, miR-15b-5p, miR-27a-3p and miR-30a-5p which are used for expressing down regulation. A reverse transcription primer and a detection primer which are used for specifically expressing miRNAs in the early bladder cancer serum miRNAs specific expression profile are shown in SEQIDNO:1-13. The invention also provides an early bladder cancer serum miRNAs diagnostic model. The early bladder cancer serum miRNAs diagnostic model is calculated by utilizing the following formula: logit(P=BC)=0.439+0.1775*(miR-152)+0.0767*(miR-148b-3p)-0.475*(miR-3187-3p)-0.2395*(miR-15b-5p)-0.625*(miR-27a-3p)-0.1693*(miR-30a-5p), can be used for early diagnosis of bladder cancer and has higher diagnosis efficiency to the bladder cancer as compared with the traditional urine exfoliative cytology through ROC (receiver operating characteristic) curve analysis, and the early bladder cancer serum miRNAs diagnostic model can diagnose patients with early bladder cancer (Ta and T1).

The invention provides a short-term power prediction method used for a newly-built wind farm. The short-term power prediction method comprises steps that A: by using a BP neural network, a historical data relation between a scale value weather forecast prediction factor in the newly-built wind farm and a wind farm early-stage anemometer tower actually-measured wind speed is established, and a wind speed statistic downscaling model of an anemometer tower position draught fan hub height is generated; B: the short-term prediction wind speed of the anemometer tower position draught fan hub height is generated according to the prediction factor of the scale value weather forecast in the wind farm area and the wind speed statistic downscaling model of the anemometer tower position draught fan hub height of the step A; C: a newly-built wind farm short-term power prediction model is established according to a wind speed-power characteristic curve analysis data and a wind farm integrated factory electricity loss proportion, and newly-built wind farm short-term prediction power is calculated. Newly-built wind farm integrated output short-term prediction is realized.

The invention discloses a biomarker for gastric adenocarcinoma diagnosis. The biomarker is LINC01234. The expression level of the LINC01234 in a gastric adenocarcinoma patient is remarkably improved, and a TCGA database performs cross validation on the difference expression. The LINC01234 is subjected to ROC curve analysis to find out that the LINC01234 has a higher AUC value and higher accuracy and specificity, and to prompt that the LINC01234 can be applied to early diagnosis on gastric adenocarcinoma by serving as a potential marker.

The invention provides an expansion curve analysis method for a steel critical point test and a use thereof. The expansion curve analysis method comprises drawing an expansion curve by temperatures T as horizontal coordinates and expansion amounts L as vertical coordinates in data recorded by a dilatometer, respectively carrying out linear fitting on linear expansion parts at the left and right sides of the expansion curve to obtain straight line equations L alpha and L gamma of the corresponding expansion amounts and temperatures, calculating a high temperature phase (gamma phase) volume fraction X gamma, drawing a curve by T as a horizontal coordinate and X gamma as a vertical coordinate, selecting an appropriate critical volume fraction C according to concrete experimental requirements, finding temperatures T respectively corresponding to two points with X gamma equal to C and X gamma equal to 100%-C from the X gamma-T curve, wherein the temperatures T are used as critical points, and expressing test results comprising the transformation critical points and critical volume fractions C. The expansion curve analysis method solves the problem that the tangent method, the extremum method, the angular cut method and the average method have undefined physical significance or easily is influenced by a subjective factor, and improves an objective quantification degree of expansion curve analysis.

The invention discloses a kit for detecting the reproductive capacity of sheep and a using method thereof. The kit is internally provided with primer nucleotide sequences shown in SEQ ID NO:1, SEQ ID NO:2, SEQ ID NO:3 and SEQ ID NO:4 in a sequence table, probe nucleotide sequences shown in SEQ ID NO:5 and SEQ ID NO:6 as well as respectively placed FTA (Fault Tree Analysis) card and relevant reagents. The using method of the kit provided by the invention comprises the following steps: adding the primer nucleotide sequences, probe nucleotide sequences and relevant reagents in the kit into the DNA (Deoxyribose Nucleic Acid) of the sheep to be detected; then carrying out PCR (Polymerase Chain Reaction) amplification; carrying out fusion curve analysis on an amplification product in a high-resolution fusion curve analyzer; and forecasting the lambing situation of the sheep to be detected according to G, A, T and C peaks in the fusion curve.

The invention discloses a method for extracting failure characters of a rotary machine based on a Kalman order-domain-holo-spectrum theory. The capacity of processing unstable signals through Kalman order-domain analysis and the capacity of comprehensively and reliably reflecting the state of a unit through holo-spectrum are utilized in a composite mode. Through combination of the Kalman order-domain analysis and the holo-spectrum analysis, two-dimensional holo-spectrum can be used for failure diagnosis in fluctuation of speed, and force and couple decomposition, and holographic waterfall curve analysis of parking signals can be conveniently carried out. By means of the method, the application range of traditional holo-spectrum is greatly widened, various characteristic parameters of the parking signals are extracted, the defect that in the prior art, only bode plot analysis is overcome, the level and range for monitoring and diagnosing failures of the rotary machine are expanded, and powerful supporting is provided for healthy and reliable operation of the rotary machine.

The invention discloses a fast video key frame extraction method of the principle characteristic curve analysis. The method includes the steps that firstly, a visual characteristic expression is extracted from video image frames; secondly, PCA dimension reduction processing is performed on a characteristic matrix X composed of all video image frame characteristics, and an image low-dimension characteristic expression Y is obtained; thirdly, each characteristic curve in the Y is searched for a curve local extreme point, and the image low-dimension characteristic expression of the frames wherein the curve local extreme points exist is added into a candidate key frame low-dimension characteristic set T; finally, K mean value clustering is performed on the candidate key frame low-dimension characteristic set, the original video sequence image frame corresponding to the candidate key frame low-dimension characteristic and is closest to the clustering center is used as a final video key frame to be sent back, and therefore extraction of the video key frame is obtained. The fast video key frame extraction method of the principle characteristic curve analysis has the advantages of being small in calculation amount, simple and easy to achieved, and influences of variations of object movement, colors, illumination and the like existing in a video image sequence can be effectively resisted.

The invention discloses a multiplex PCR (Polymerase Chain Reaction) assay method for simultaneously assaying multiple respiratory viruses, which includes the following steps: design of probes, design of upstream and downstream primer sequences, multiplex PCR reaction and dissociation curve analysis. By designing Taqman probes for the conserved group sequences of the respiratory viruses and adopting different fluorophores when Tm phase difference is less than or equal to 6 DEG C, the method can assay a variety of respiratory viruses with high throughput and high accuracy. The invention further provides a multiplex PCR assay probe set and a corresponding kit for simultaneously assaying multiple respiratory viruses, which are convenient to apply and have a great market and application prospect.

The invention discloses primer, a reagent box and a method for detecting salmonella and integrin (int). The primer comprises upstream primer SLMF: TGCGTCAGGACCTCATAG, downstream primer SLMR: ATGCCTGGAGGAGTGTTT, upstream primer intF: TTTACGCTGCTGTATGGT, and downstream primer intR for detecting int: TTATTGCTGGGATTAGGC. The reagent box is filled with 10 uL of HRM reaction premix liquid, 0.2-3.4 uL of primer, 1 uL of DNA template and is filled into 20 uL by water. The detecting method includes extracting sample DNA and performing PCR amplification. After amplification, products are subjected to high-resolution melting curve analysis, and results are judged by an amplification curve. The reagent box is reasonable in component and proportion, is convenient to use and quick and accurate to detect, the method is convenient and quick to operate, and low in cost, and detecting results are accurate.