374results about How to "The identification method is simple" patented technology

The invention discloses a horizontal well logging while drilling geo-steering method, and relates to the technical field of drilling, exploration and development of petroleum, natural gas and the like, in particular to a logging while drilling geo-steering method suitable for the drilling process of a horizontal section of a horizontal well. The method is characterized by comprising the following steps of: interpreting and making a logging curve graph and a well track profile graph by using real-time data obtained by logging while drilling and measurement while drilling, defining logging curve marking points on the logging curve graph and marking on the well track profile graph, further defining symmetrical marking points, analyzing and interpreting the symmetrical marking points to obtain the average formation dip and formation dip variation trend of each section of a well track, and redrawing a top boundary and a bottom boundary of a target layer by combining drilling points of the top boundary and the bottom boundary of the target layer; and predicting the altitude depth of a drill position according to the last measuring point, and determining the actual position of a drill in the target layer to provide a basis for next-step geo-steering decision making.

The invention discloses a self-adaption Kalman filtering method for autonomous navigation positioning of pedestrians. The method comprises the following steps: connecting an MEMS-IMU system integrating an accelerometer, a gyroscope and a magnetometer to a human body, and carrying out IMU data acquisition during movement of pedestrians; and establishing a self-adaption filtering model containing eighteen-dimensional state variables and nine-dimensional observed quantity, and carrying out recursive filtering while meeting four conditions, wherein a time varying noise statistical estimator is used for estimating and correcting system noise and observing the statistical character of noise in real time. According to the invention, on the basis of using zero-speed correction as error compensation correcting algorithm, a self-adaption filtering method fusing human body moving character is designed, noise interference signals caused by shake of the human body can be processed in real time, and the precision of autonomous navigation positioning of the pedestrians is effectively increased. The method disclosed by the invention is strong in stability and good in real-time property, and no extra hardware cost is increased.

The invention provides a method for identifying traditional Chinese medicinal materials by combining infra-red spectra with cluster analysis, which includes the following steps of: (1) selecting a same traditional Chinese medicinal material as a standard sample; (2) detecting the standard sample by infra-red spectra to obtain an infra-red spectrogram; (3) establishing a standard infra-red model of the traditional Chinese medicinal material by a cluster analysis method with the obtained infra-red spectrogram; and (4) comparing the standard infra-red model with the infra-red spectrogram of the sample of traditional Chinese medicinal material to be identified and directly analyzing and identifying the traditional Chinese medicinal material. The method is simple, convenient, and rapid, and can keep the integrity of the traditional Chinese medicinal material and directly determine the quality of the traditional Chinese medicinal material and identify whether the traditional Chinese medicinal material is authentic or not.

The invention discloses a noise separation-based power transformer noise assessment method. The steps include: 1) building a voiceprint feature database in advance according to voiceprint feature information corresponding to noise signals generated by a fan component, an iron core component and a winding component when a standard power transformer is in different running states; 2) collecting in real time sound wave signals sent when a transformer to be tested runs, so as to obtain noise signals to be assessed; 3) separating noise signals generated by the fan component, the iron core component and the winding component from the noise signals to be assessed; and 4) extracting voiceprint feature information of each noise signal, identifying the running state of the transformer to be tested, and assessing the noise level of each component according to the running state. The noise separation-based power transformer noise assessment method provided by the invention can realize assessment of the noise level of each component in the power transformer utilizing acoustic characteristics, and has the advantages of easy operation implementation and high assessment precision and efficiency.

A method for identifying geometric errors with respect to at least two translational axes and at least one rotational axis of a machine using a control device is disclosed. The method comprises the steps of: measuring positions of a jig in three-dimensional space using a position measurement sensor, wherein a measurement is carried out when the jig being indexed around the rotational axis by a plurality of angles is located at the positions; approximating a plurality of measured values of the positions measured in the measuring step to a circular arc; and calculating an error in regard to a center position of the rotational axis and / or a tilt error in the rotational axis, and tilt errors in the translational axes, based on the circular arc resulting from the approximating step.

The invention relates to a method for testing random vibration structure damage based on cross-correlation function peak value vector. It uses the relation between the frequency respond function of the cross-correlation function of the two points respond signal of the vibration structure and the structure out-exiting frequency spectrum to collect the respond signal of a period times of a plurality of measuring points, it dose cross-correlation function computing to one point respond signal with other points respond signals, it uses the largest peak of each cross-correlation function to construct the cross-correlation function peak value vector, it compares the relative factor of the intact structure and the current structure cross-correlation function peak value vector to quote weather the structure is damaged, it analyzes the content change of the corresponding elements to ascertain the damaged location.

The invention provides an equivalent modal strain energy damage identification method. The method comprises the following steps of: respectively solving corresponding modal strain energy by using a modal shape generated before and after being damaged; and then judging the damage position and the damage degree of the unit by using an strain energy equivalent index of each damage unit; if an index value is approximate to zero or has a negative value, expressing that no damage exists; and if the index value is a positive value, expressing that the unit has the damage, wherein the damage degree of the unit is the size of the equivalent index value. Compared with the strain energy variation rate method, a strain energy equivalent index method has the advantage of quantitative identification; and compared with the strain energy dissipation rating method, the strain energy equivalent index method has the advantage of higher identification precision.

The invention discloses separation, purification and identification methods of human amnion mesenchymal stem cells. The separation method of hAMSCs (human amnion mesenchymal stem cells) comprises the following steps: fragmentating human amnion; and carrying out two-step rotating digestion with trypsin of EDTA (ethylene diamine tetra-acetic acid) and collagenase of DNaseI, filtering with a steel mesh and collecting cell filtrate namely separated original hAMSCs. The purification method of hAMSCs comprises the following steps: incubating original hAMSCs with an LG (low glucose)-DMEM (dulbecco modified eagle medium) culture medium in a CO2 incubator; removing amnion epithelial cells which do not perform complete adherence growth under an inverted microscope; replacing a new culture medium on the third day; digesting with a trypsin-EDTA solution after cell converge degree reaches 80-90%; and collecting cells so as to obtain high-purity hAMSCs. The identification method of hAMSCs comprises the following steps: identifying hAMSCs and the amnion epithelial cells by adopting immunocytochemical staining vimentin and CK19; and detecting expressions of CD29, CD44, CD166, CD34 and CD45 by adopting a flow cytometry. The separation and purification methods disclosed by the invention have the advantages of high yield, high activity and high purity of hAMSCs; and the identification method is simple, convenient and precise.

The invention discloses a method for realizing semi-quantitative analysis to trace mixture by use of the surface enhanced raman spectroscopy, and in particular relates to a qualitative identification method for carrying out semiquantitative analysis on a trace mixture by determinng Raman spectrum of a trace chemical substance based on surface enhanced Raman scattering effect and improving main component analysis. The method discosed by the invention adopts a lever law and a triangle parapllel line reading method to realize the semiquantitative analysis of the mixture components. The method can be used for analyzing mixture of entirely different chemical substances and can be used for analyzing mixture of homologous series. The method can realize semi-quantitative analysis to components of mixture based on the PCA (Principal Component Analysis) qualitative analysis and is a simple, rapid and accurate mixture identification method.

The invention discloses an asynchronous motor parameter offline identification method comprising a stator resistor identification step including selecting two random phases of an asynchronous motor to serve as two tested phases, injecting a DC signal to windings of the two tested phases, and executing a one-time single phase DC test; the method also comprises the following steps: adjusting a test current value of the injected DC signal, collecting a phase current value and a corresponding phase voltage value of one tested phase at different test current values, thus obtaining a plurality of data points formed by phase current values and phase voltage values; carrying out curve fitting according to the collected data points so as to obtain a fitting relation curve between the phase current value and the phase voltage value, thus identifying a stator resistance Rs value according to a gradient of the fitting relation curve. The asynchronous motor parameter offline identification method is simple in identification process, high in identification result precision, and small in identification error.

The invention discloses a method of recognizing asynchronous vibration parameters of blades under variable speed excitation. According to the method, aliasing frequency is acquired by means of increasing sampling rate by interpolation of measurement data of adjacent two blades, vibration aliasing frequency and phase is acquired by full-phase FFT (fast Fourier transform), and a fractional part of non-integer order is acquired; order tracking is performed according to a relation between the phase and the sensor mounting angle, and an integral part of asynchronous vibration order of the blades is recognized; an algorithm is verified by deceleration multi-octave asynchronous vibration data generated by a four-blade simulation model, simulation data is vibration data of the single blade measured by a single sensor, recognition results are compared to simulation parameters, and the ability of the algorithm to correctly recognize the asynchronous vibration parameters of the blades is verified. The method is correct, reliable, simple and feasible.

The invention relates to a compound anti-counterfeiting element, which is provided with at least one liquid crystal material with optical properties, and at least one functional material with machine-readable properties, so that the element simultaneously has the optical properties, machine-readable infrared properties and machine-readable magnetic properties. Combining the optical variable anti-counterfeiting properties for mass recognition, infrared anti-counterfeiting properties for machine-readable recognition, and magnetic properties, the anti-counterfeiting element remarkably improves anti-counterfeiting safety, and has a higher anti-counterfeiting effect and a simpler identification method compared with a single anti-counterfeiting element. The invention also provides a valuable commodity which is provided with the compound anti-counterfeiting element.

The invention belongs to the technical field of driverless vehicles, and particularly relates to a traffic signal lamp identification system based on a video signal image processing technology and anidentification method thereof. The system comprises a vehicle-mounted front camera, an Image recognition device, a Voice chip, a loudspeaker, an accelerator pedal and a brake; an image recognition device is used for judging a signal acquired by the vehicle-mounted front camera; The image recognition device is composed of color recognition, shape recognition, shape secondary confirmation and continuous image recognition result verification, and images collected by the vehicle-mounted front camera are recognized in a double-rail mode based on RGB space on the whole and locally recognized based on HSL space. The traffic signal lamp identification method provided by the invention is simple and efficient, the identification result is confirmed and verified for multiple times, the reliability isvery high, experiments show that the design method is high in accuracy, has the capability of detecting the traffic signal lamp in real time, and can meet the working requirement of traffic signal lamp identification under the actual road traffic condition.

The invention discloses a characteristic nucleotide sequence, as well as a nucleic acid molecular probe and a method for identifying ganoderma leucocontextum. The characteristic nucleotide sequence is shown in SEQ ID NO.1, wherein the nucleic acid molecular probe comprises BRLZ-F:5'-AGATCTGCGAAGCGTGCT-3' and BRLZ-R:5'-AGAGGAGCCGACCGACAG-3'. The identifying method comprises the steps of identifying through a PCR method by taking the nucleic acid molecular probe BRLZ-F and BRLZ-R as primers. Based on the characteristic nucleotide sequence SEQ ID NO.1 of the ganoderma leucocontextum, the specific nucleic acid probe BRLZ-F and BRLZ-R are designed and taken as the primers, the PCR amplification is performed by taking the DNA of the ganoderma leucocontextum as a template and the rapid identification of the ganoderma leucocontextum is realized. The nucleic acid molecular probe provided by the invention is strong in selectivity, rapid and accurate in identifying method and good in specificity.

The invention discloses a system for measuring position of a marine seismic streamer based on one-way hydroacoustic ranging and belongs to the technical field of marine seismic survey. The system comprises a ship-borne system of a marine seismic survey ship, water surface units, underwater units, a dada cable and a power supply cable. The system adopts the position data of any three water surface units, the vertical position data of an underwater unit to be measured and the distances between the three water surface units and the underwater unit to be measured to calculate the position data of the underwater unit to be measured; and the system uses the position data of the underwater units to obtain the positions of points of the marine seismic streamer by interpolation calculation. The system adopts the one-way hydroacoustic ranging, namely, the water surface units are only provided with acoustic wave launchers and the underwater units are only provided with acoustic wave receivers, thus increasing the operating range of the hydroacoustic ranging and reducing the interference of the acoustic wave launchers in a hydrophone group; and by adopting ranging acoustic wave signals of characteristic spectra, the recognition method of the ranging acoustic wave signals by the underwater units is simplified, and the system complexity is reduced.

The invention relates to a method for marking gold sepia, wherein the invention is characterized in that: cultivating the hatched sepia for 5-20 days, dissolving coloring agent into fresh water, adding the water solution into the container with sepia and seawater, to make its coloring agent content as 60-80ppm; emerging and coloring for 20-28hours; said coloring agent is alizarin complex instructor. The invention has simple process without toxic and hurt, while it can color many types of sepia at one time.

The invention discloses a dynamic identifying method for instant contact loss of a wheel rail under an impact effect of the wheel rail and belongs to a traffic information safety technology. The dynamic identifying method comprises the following steps: firstly, mounting a vibration acceleration sensor above a wheel axle box; collecting axle box vibration acceleration information measured by the vibration acceleration sensor through a background collector; extracting a time-frequency feature for the axle box vibration acceleration, thereby obtaining a time-frequency distribution feature; and drawing a contour map for the time-frequency distribution feature and judging if the wheel rail instantly loses the contact. According to the scheme, the purpose of immediately detecting the ultra-large hidden danger of the instant contact loss of the wheel rail under the impact effect of the wheel rail is achieved according to the dynamic identifying method provided by the invention; the possibility of derailing of a vehicle is eliminated; the technology is mature; the reliability is high; the cost is low; the quantity of the channels is less; the system is simple; the anti-interference property is high; and the social and economical benefits are very obvious.

The invention provides an off-line recognition method for alternating current asynchronous motor mutual inductance parameters. An inverter based on an alternating current asynchronous motor and connected with the input end of the alternating current asynchronous motor, a controller controlling the inverter to output currents through PWN signals and a sensor used for detecting currents of the alternating current asynchronous motor are included. The sensor transmits detected currents to the controller for adjusting the PWM signals. The alternating current asynchronous motor comprises a stator and a rotor. According to the off-line recognition method for alternating current asynchronous motor mutual inductance parameters, no extra devices or circuits are needed, only the resistance value of the fixed rotor of the alternating current asynchronous motor needs knowing, the measurement of the resistance value of the fixed rotor of the alternating current asynchronous motor is simple, the precision of parameters can meet FOC control requirements, and the purpose that the alternating current asynchronous motor recognizes mutual inductance parameters on the static condition is achieved. The recognition method is simple and brings convenience to project implementation.

The invention provides a motor system identification method. The method comprises the steps of building a functional series filter model for describing a motor system; generating a logarithmic swept-frequency signal; feeding the generated logarithmic swept-frequency signal to the motor system, and using an accelerometer to collect vibration acceleration output by the motor system; generating an inverse signal of the logarithmic swept-frequency signal; carrying out convolution on the collected vibration acceleration and the inverse signal to obtain a one-dimensional impulse response sequence; for the one-dimensional impulse response sequence, capturing all parts of the impulse response sequence by using a window function; and solving a kernel function according to all the parts of the impulse response sequence, substituting all parts of the solved kernel function into an identification formula of the motor system, and describing and identifying the motor system through the identification formula. Compared with the related art, the motor system identification method disclosed by the invention is simple and feasible, and high in reliability.

The invention discloses a remote sensing image sea surface ship detection method based on visual attention mechanism and information entropy, including the steps of collecting an optical remote sensing image, carrying out the wavelet decomposition, reconstructing a feature map, calculating a saliency map, counting thesaliency degree of corresponding position pixels in all feature maps based on themultivariable Gaussian probability density function, calculating a global saliency map of the inputted images, reserving the ship target area, carrying out the threshold segmentation and the slice extraction which are used for extracting the slices of the suspected ship target area; obtaining the discriminant entropy which is used to improve the deficiency of traditional entropy definition which depends on the spatial structure information of the image and to obtain the discriminant entropy which can better describe the content of the target slice; identifying the ship targets and false alarms: using the improved identification entropy to characterize the slice features of ship targets, thereby effectively distinguishing the ship targets and the false alarms. The method of the invention can detect and confirm the ship target on the sea surface of the optical remote sensing image from coarse to fine.

A molecular marker primer for identifying Shao's Sillago and Sillago sihama belongs to the technical field of biology, and sequences of the primer include L5979: 5'-TTTAGTATTCGGAGCCTGAG-3' and H6241: 5'-CCTCAACACCTGATGAGGCC-3'. The invention also provides a method for identifying Shao's Sillago and Sillago sihama by using the primer, comprising the steps of extracting DNA from Shao's Sillago and Sillago sihama, using DNAs of the two species as templates to perform PCR (polymerase chain reaction) amplification, purifying and sequencing amplification results, and comparing sequencing results to determine that intraspecific genetic difference is not greater than 1%; molecular marker sequence of Shao's Sillago is SEQ NO. 3 and molecular marker sequence of Sillago sihama is SEQ NO. 4; the method of the invention helps solve the problem of germplasm mixing of Sillago fishes, and is simple to perform, easy to master and high in accuracy.

A system for a two dimension bar code for synchronous omni-directional information and its identifying method are disclosed with advantages of simple in identifying, low requirement on scanner synchronization and high in ability to identifying with anti-aberration. The system for the two dimension bar code is composed of units aligned in a matrix form and comprises a pair of vertical synchronous information units at two opposing borders in said matrix; a pair of horizontal synchronous information units at another two opposing border in said matrix; a directing information unit having a characteristic shape and / or optic characteristics for identifying a scanning direction and having a specific relative positional relationship between said vertical information synchronous units and horizontal information synchronous units; and a coding information unit inside said matrix, wherein the base of each unit is in the vicinity of the intersection of the central linking line of a pair of the vertical synchronous information units and the central linking line of a pair of horizontal synchronous information units.

The invention discloses a high-speed airflow dispersion-based stem content and threshing parameter detection and removing method, which includes the following steps: a belt conveyer is utilized to spread and convey tobacco leaves into a high-speed air duct; high-speed airflow is utilized to further uniformly disperse the tobacco leaves in the high-speed air duct, and at the same time, the tobacco leaves are sent into a detection area along with the airflow; a high-definition tobacco leave perspective is acquired in the detection area; the textural features of the tobacco leaves are extracted from the perspective, an algorithm is utilized to identify the laminae and the stems in the tobacco leaves, and the tobacco leaves containing the stems are removed; the shapes and sizes of the tobacco leaves are analyzed, so that tobacco leaf areas are obtained, and threshing parameters are calculated. By analyzing the acquired tobacco leave perspective image, the textural features are extracted, a binary tree is adopted to accurately distinguish the stems from the laminae, consequently, the invention solves the current complex problems of redrying factories, such as off-line stem content detection and long detection period, and thereby the product quality and efficiency of redrying factories can be remarkably increased.

A method for identifying safety risk in a bridge construction period comprises the following steps: 1. building a n-row m-column matrix to each construction stage; 2. setting Xij to be an original value of jth index in ith danger source in a system according to LEC (likelihood exposure consequence) scoring method in construction, wherein i is equal to 1, 2, 3, ..., n, and j is equal to 1, 2, 3; 3. determining the most dangerous value set of the index to be X0=(x1, x2, x3), and performing standardization treatment on the most dangerous index value; 4. calculating gray associated coefficients of the jth index of the ith danger source and the jth most dangerous index after the treatment according to a formula (1); 5. calculating the weight of the jth index on the basis of the gray associated coefficients according to a formula (2); and 6. calculating the association degree between the ith danger source and the most dangerous state of the danger source according to the gray associated coefficients and the weight of the jth index. By using an improved gray association analysis method and introducing maximal deviation to calculate the weight so as to identify the risk source; and compared with the LEC multiplication of the prior art, the method provided by the invention is more objective and more scientific in identification.

The invention provides a touch recognition method and device and a touch display device. The method comprises the following steps: acquiring signal data when touch is not generated and processing thesignal data, receiving a coordinate report command transmitted by a master controller, and acquiring real-time signal data and processing the real-time signal data according to the coordinate report command; calculating obtained signal variation data according to the processed real-time signal data and basic signal data; finding out a touch region according to the signal variation data; calculating barycentric coordinates of the touch region; analyzing current obtained barycentric coordinates and barycentric coordinates obtained in a previous time period, and determining a touch operation track; carrying out smoothing treatment on the touch operation track; detecting whether the touch operation track passes through a preset edge region or not, and if the touch operation track passes through the preset edge region, carrying out edge stretching treatment; and reporting coordinates of the touch operation track to the master controller. The recognition method is simple, a calculating flowcan be effectively saved and simplified, and the calculated amount is reduced.

The invention provides a pair of PCR primers used for authenticating pork, beef, mutton and products thereof. The nucleotide sequences of the primers are represented by SEQ ID No.1 and No.2. The invention also provides a kit comprising the primers, and a method for authenticating pork, beef, mutton and products thereof. The method provided by the invention is characterized in accurate result and high sensitivity. With the method provided by the invention, adulterate fresh meats in markets can be rapidly detected. Also, the method plays an important role in individual discriminating and origintracing researches. According to the authenticating method provided by the invention, only one pair of PCR primers is required for authenticating fresh pork, beef, and mutton, such that the authentication is simple and rapid. With the method, adulterate fresh meats in markets can be rapidly and sensitively detected, and great significance is provided for pig individual discriminating and origin tracing researches.

The invention belongs to the field of utilization of biological discrimination and germplasm resources, and specifically relates to a method for rapidly and efficiently identifying rice and dry rice ecotype in places with cultivated rice. The invention utilizes five rice microsatellite (SSR) points with great difference in the rice and dry rice ecotype to design a molecular method for rapidly and efficiently identifying rice and dry rice ecotype. The method comprises the steps of sample DNA extraction, three-primer system PCR amplification and electrophoresis detection of amplification product, different genetypes are assigned according to results of a great deal of experiments, the integration judgement values of five points are calculated comprehensively, and the water and dying ecotype of cultivated rice is judged through a judging value. The method provided by the invention has the advantages that the accuracy rating is high, the adaptability is wide, the method is rapid and convenient, and the method has extensive application prospects on aspects of cultivated rice germplasm collection, judgment, research and utilization.

The invention discloses a human body emotion recognizing method based on real-time electroencephalography. The method comprises the following steps of 1, collecting electroencephalogram signals, wherein multi-channel electroencephalogram collecting equipment is adopted for collecting tested electroencephalogram signals; 2, preprocessing the electroencephalogram signals, wherein the electroencephalogram signals obtained in step 1 are compared to be preprocessed so that wake interference can be reduced, and the final classification recognition rate is increased; 3, extracting electroencephalogram signal sample characteristics; 4, classifying the electroencephalogram signals; 5 performing emotion recognition. The human body emotion recognizing method based on real-time electroencephalographyis simple in electroencephalogram signal collection, high in intelligent degree and capable of comprehensively, accurately and effectively recognizing the electroencephalogram signals.