32results about How to "The method is accurate and efficient" patented technology

The invention relates to a method for predicting gas well bottom flow pressure, which belongs to the fields of gas well dynamic analysis and working system optimization. Including (1) measuring or collecting the casing pressure, formation depth, relative density of natural gas, reservoir temperature, gas production, natural gas compression factor, and measured gas well bottomhole pressure parameters of a certain block; (2) making a gas drilling well Underflow pressure SVM predictor; (3) Input the measured or collected parameters into the SVM predictor for self-learning to determine the key parameters of the SVM predictor, namely the kernel function parameters , insensitivity coefficient and penalty factor (4) Input the casing pressure of the well to be predicted, the middle depth of the formation, the relative density of natural gas, the reservoir temperature, the gas production rate, and the compressibility factor of natural gas into the SVM predictor to obtain the prediction result of the bottomhole flowing pressure of the gas well to be predicted. The method is accurate and efficient, and it is a new practical method for predicting the bottom hole pressure of gas wells.

The present disclosure generally relates to DNA-based data storage. An exemplary method for storing input data on nucleic acid comprises: converting the input data into a set of nucleotide sequences and synthesizing a set of nucleic acids comprising the set of nucleotide sequences. The converting comprises a data processing step comprising converting the input data into a binary string, and a nucleotide encoding step comprising converting the binary string using a 5-bit transcoding framework to obtain the set of nucleotide sequences.

The invention discloses a device and method for while-drilling detection of a formation interface through azimuthal resistivity. The device comprises a non-magnetic drill collar, a circuit unit, a plurality of antennas and antenna tuning units corresponding to the antennas, wherein the non-magnetic drill collar serves as a carrier of the whole device and is provided with a compensation resistivity detection point. The circuit unit is installed inside the non-magnetic drill collar. The antenna tuning units are distributed on the outer circular surface of the non-magnetic drill collar and connected with the circuit unit. The method includes common resistivity measurement and azimuthal resistivity measurement, the distance between the device and the formation interface is calculated through the azimuthal resistivity measured value, previous real-time geological data are provided for well drilling, and the purpose of optimizing the well drilling quality is realized.

The invention discloses an intelligent substation process layer physical link fault diagnosis method, and relates to the field of intelligent substations. The method comprises the steps of analyzing an SCD file, and obtaining related information of a logic link of a process layer of a whole station and switch configuration information; Obtaining a path node set of a whole station process layer logic link; Analyzing the chain scission signal, obtaining information related to the chain scission signal, and preliminarily screening out a path node set possibly having problems based on the information; Traversing other non-triggered chain scission signals; based on process layer message information related to the triggered chain scission signal, combining with network message analysis; path nodes possibly having problems are further eliminated based on the starting point port power information, the end point port power information and other means of the logic link related to the triggered broken link signal, and the rest path node sets are ranked according to the probability to obtain a final diagnosis result. On the basis of probability statistics, the fault diagnosis range is furtherreduced, and the positioning accuracy is enhanced.

The invention discloses a method for selecting nervous necrosis virus resistant individuals of epinephelus lanceolatus. The method comprises the following steps: (1) obtaining SNP site information of the epinephelus lanceolatus; (2) analyzing the disease resistance weight value of the SNP marker and selecting the SNP marker; (3) obtaining candidate epinephelus lanceolatus individual SNP site information and selecting individuals with nervous necrosis virus resistance; and (4) detecting the selection accuracy of disease-resistant individuals. According to the method, the SNP marker with the maximum nervous necrosis virus resisting weight is screened from the SNP markers of the epinephelus lanceolatus, so that a method capable of selecting nervous necrosis virus resisting individuals is established.

The invention discloses a device and method for fast measuring of heat capacity of a thin film material. In particular, the device includes a control device, a clock synchronizer, a flat peak laser device, a fast thermometer and a heat capacity output device; the control device is in signal connection with the clock synchronizer, and the clock synchronizer is in signal connection with the flat peak laser device and the fast thermometer; in a working state, the control device sends a starting signal to the clock synchronizer, the flat peak laser device and the fast thermometer are in coordinated interaction, and the flat peak laser device irradiates lasers having the energy space distribution of flat peaks to the sample surface; at the same time, the fast thermometer captures the surface temperature of a sample at a certain time point at the heating process of the sample, the test data are inputted into a heat capacity output device, and required heat capacity parameters are obtained. The device has simple structure, the method is high in efficiency and accurate, and reliable parameter data can be provided for setting of various thermophysical properties of ultra-thin semiconductorthin films.

The invention discloses an automatic laser shot device, a shot point identification method and an automatic shot point correction method. The automatic laser shot device comprises an automatic shot control system and an automatic shot point identification system. The automatic shot control system comprises a first wireless module, a matrix keyboard, a single chip microcomputer, a serve motor control table, a laser gun and the like. The single chip microcomputer is connected with the matrix keyboard and controlled by the matrix keyboard. The serve motor control table is connected with the matrix keyboard and controlled by the matrix keyboard. The laser gun is located on the serve motor control table. Based on the gray value of a pixel, the shot point identification method adopts a non-neighboring-group identification method. According to the automatic shot point correction method, the serve motor control table is adjusted according to the difference value of the coordinates of a shot point and the coordinates of a target, so that shot deviation is corrected. The automatic laser shot device is low in cost and danger, and high in objectivity and precision. The non-neighboring-group identification method based on the gray value of the pixel is adopted to determine the shot point, so that the method is more precise and more efficient, and the precision the method is up to 0.88%.

The invention discloses an accurate and rapid detection method for pesticide residues in fruits. The accurate and rapid detection method comprises the following steps of: (1) carrying out pulp refining on fruits by using a refiner, and adding water and acetonitrile into the pulp for dispersion; (2) adding a magnetic nano-material into the dispersed pulp and carrying out continuous oscillation extraction; (3) separating the magnetic nano-material for extracting and adsorbing the pesticide from the fruit solution by using a magnet; (4) carrying out ultrasonic elution on the pesticide adsorbed by the magnetic nano material by adopting a small amount of organic reagent, and adding anhydrous sodium sulfate into eluent for dehydration; (5) adding an internal standard compound solution; and (6) analyzing and detecting a to-be-detected liquid by using a gas chromatograph-mass spectrometer. The accurate and rapid detection method for pesticide residues in the fruits has the advantages of being short in operation time, low in organic reagent consumption, low in analysis cost, accurate in analysis result and easy to popularize.

The invention discloses a metal material surface microcrack identification and in-situ quantitative statistical distribution characterization method, which comprises the steps of metal material surface preparation, determination of gray threshold values of microcracks, inclusions and other feature structures, setting of energy disperse spectroscopy analysis parameters, scanning electron microscope full-automatic acquisition of feature structure images in a large-size range, and in-situ quantitative statistical distribution characterization of microcracks in a large-size range. Feature extraction and energy spectrum analysis, screening and identification of microcracks, and in-situ quantitative statistical distribution characterization of the number, the area fraction, the length and the like. According to the characteristic that grinding materials and polishing material components can be embedded into microcracks on the metal surface in the metallographic sample preparation process, data mining and screening are carried out by extracting a back scattering electron image of a metallographic surface characteristic object and combining an energy spectrum analysis result and morphological quantitative parameters; according to the method, the inclusion is analyzed, meanwhile, rapid positioning, recognition and quantitative statistics of the surface microcracks are achieved, the method is accurate and efficient, and meanwhile the detection resolution of the microcracks is greatly improved and can be as low as the micron level.

The invention relates to a method for detecting puff-by-puff stability of a blueberry-flavored heated cigarette by using a nuclear magnetic resonance hydrogen spectrum, which comprises the following steps of: smoking by using a rotary puff-by-puff smoking machine by taking the blueberry-flavored heated cigarette as an object, collecting aerosol of each puff of heated cigarette, extracting and concentrating by using a solvent, and detecting the puff-by-puff stability of the blueberry-flavored heated cigarette by using a deuterated reagent solvent. Nuclear magnetic hydrogen spectrums of corresponding samples are obtained through the nuclear magnetic resonance technology, and the similarity of spectrograms of all the samples is compared through information such as chemical shift, peak height and peak area on nuclear magnetic resonance hydrogen spectrum fingerprints, so that the puff-by-puff stability of the blueberry-flavored heated cigarettes is measured. The method is accurate and efficient, and is suitable for puff-by-puff stability analysis and detection of the blueberry-flavored heated cigarettes.

The invention discloses an early warning threshold setting method based on a moving interval relevance trend. The stable and sensitive relevance relationship between the monitoring data is utilized; arelevance trend line and a structural response normal value envelope line are obtained by adopting relevance movement interval probability statistical characteristics, and then a red early warning limit value is obtained according to a certain guarantee rate on the basis of the normal value envelope line based on a reliability theory, so that a 'two-line three-area ' relevance early warning mechanism is established, and relevance early warning of the system is realized. Compared with a fixed and single time-history early-warning threshold of structural response data, relevance trend early-warning belongs to a comprehensive early-warning system, and massive monitoring data of the bridge health monitoring system can be fully utilized and the internal change rule of the monitoring data can be mastered. The relevance trend early warning threshold value changes along with the change of relevance characteristics, and the dynamic threshold value has higher precision and sensitivity, so thatthe system can give an early warning more scientifically in real time. The method has been realized in a programmed manner, is simple and quick to operate, and has wide engineering application value.

The invention discloses a distributed energy storage user mining method and device, computer equipment and a storage medium. The method comprises the following steps: collecting a data set influencing energy storage construction and subjecting to importance grading; performing quantization processing on the data set; constructing an energy storage evaluation model based on the quantized data set; and evaluating the potential level of energy storage construction of the user based on the energy storage evaluation model. According to the invention, common data sets influencing energy storage construction are provided on the basis of consideration and analysis of different collected and investigated data of users, grading is carried out according to importance, each data set is subjected to quantitative processing, and the potential level of energy storage construction of the users is obtained through analysis and evaluation of the data. The invention is accurate and efficient in evaluation result, has relatively high universality and practicability, and is of great significance in mining the potential of energy storage customers and guiding the energy storage installation scale.