366results about How to "Reliable results" patented technology

The invention discloses a multi-working-condition-oriented equipment fault diagnosis method based on unbalanced learning, and the method comprises the following steps: collecting the operation data of equipment under different working conditions through a plurality of sensors, carrying out the preprocessing, feature extraction and feature selection of the collected original operation data, and obtaining a feature set; processing the feature set by adopting an unbalanced learning technology and a cost-sensitive learning algorithm to obtain a balanced data set; constructing a multi-working-condition fault diagnosis model based on learning, and optimizing model parameters by adopting a method of combining cross validation and grid search according to a balanced data set in a model training process; deploying a multi-working-condition fault diagnosis model obtained through training, carrying out the online diagnosis of equipment faults, and continuously updating and optimizing the model through a continuous learning mechanism. According to the method, the unbalanced learning technology is applied to multi-working-condition fault diagnosis, the accuracy and robustness of diagnosis can be remarkably improved, and real-time monitoring and predictive maintenance of the equipment health state are achieved.

The invention discloses a channel flow evolution method and system based on a physical mechanism collaborative deep learning algorithm, and relates to the technical field of channel flow evolution, and the method comprises the steps: carrying out the data collection and preprocessing; carrying out feature extraction and constructing an evolution model; deducing a hydrological physical model through simultaneous operation of a Muskinggen tank storage curve equation and a river reach water balance equation; the section flow of each river reach is predicted through the hydrological physical model and the evolution model; and through the prediction result of the index evaluation model in each river reach, carrying out collaborative optimization intelligent evolution of each river reach through the evaluation result. The method guides the establishment of the constrained deep learning neural network model through a hydrological physical mechanism, organically fuses the hydrological physical model and the deep learning algorithm model, comprehensively applies the physical model and the mathematical model to better solve the hydrological problem of a complex system, gives full play to the respective advantages, and improves the reliability of the system. The method is suitable for flow simulation prediction of various river channels, operation is easy and convenient, training is fast, and results are reliable.

The invention relates to the technical field of satellite power supply management and life prediction, and discloses a solar environment characteristic-based satellite battery life prediction method, which comprises the following steps of: generating and preprocessing satellite battery data for training and solar panel data for training, the satellite battery data for training comprises satellite battery state data and satellite battery actual life data; building a CNN-Transform model, and training the CNN-Transform model by taking the satellite battery state data and the solar panel data for training as the input of the CNN-Transform model, and taking the satellite battery actual life data as the output of the CNN-Transform model; and inputting actual satellite battery state data and actual solar panel data, which are acquired in real time, into the trained CNN-Transformer model so as to output predicted satellite battery remaining life data. According to the invention, a more accurate and reliable result is provided for the residual life prediction of the satellite battery.

The invention discloses a rapid automatic focusing module and method suitable for a fluorescence microscope. The automatic focusing module comprises a laser, a diaphragm, a collimating lens group, a reflector, a dichroic mirror, an objective lens, a sample to be measured, a telescope lens group, a CCD2 detector, a control system and a displacement platform which are sequentially arranged along a focusing light path, and the sample to be measured, the objective lens, the dichroic mirror, a tube lens and the CCD2 detector which are sequentially arranged along an imaging light path; the collimated laser beam is emitted to the plane where the sample to be detected is located through the objective lens, and then the laser beam is reflected back to the telephoto lens group and converged to the CCD2 detector. According to the offset of the center of the reflected light beam, the relative distance between the objective lens and the to-be-tested sample is moved through a control system, and automatic focusing of a single view field of the to-be-tested sample is achieved; the to-be-measured sample is moved to the focal planes of different object view fields in the X direction and the Y direction and is quickly focused in real time, so that the large-size to-be-measured sample is always kept at the focal plane position, and the image quality and the working efficiency are improved.

The invention discloses a spring operating mechanism fault detection and optimization method and a related device, and the method comprises the steps: carrying out the real-time collection of key data of a spring operating mechanism through a stress sensor, a speed sensor and a vibration sensor; based on the collected key data, constructing a multi-dimensional data framework to obtain a multi-dimensional data set; fault feature extraction and data analysis are carried out on the obtained multi-dimensional data set, an adaptive fault model is constructed based on the extracted fault features, and then a real-time fault detection result is obtained through multi-modal data fusion; and optimizing a stress sensor, a speed sensor and a vibration sensor by utilizing automatic calibration and optimization of reinforcement learning according to the real-time fault detection result. Compared with a traditional fault detection method, high-precision real-time monitoring and fault prediction of the spring operating mechanism are achieved through the multi-modal data fusion and deep learning technology, and comprehensive and reliable technical support is provided for safe operation and maintenance optimization of equipment.

The invention discloses a prostate cancer segmentation method based on multi-parameter magnetic resonance imaging and deep learning, and relates to the technical field of image segmentation, and the method comprises the steps: carrying out the preprocessing of collected multi-parameter magnetic resonance image original data, and dividing the data into a training set, a test set and a verification set; the method comprises the following steps: respectively constructing an attention-unet network used for prostate segmentation and a Multi-attention-unet network used for prostate cancer segmentation; training and selecting an optimal prostate segmentation model by using the verification set; inputting the multi-parameter magnetic resonance images of the test set into the optimal prostate segmentation model to obtain the multi-parameter magnetic resonance images in the set training set for training after the gland optimal prediction mask is obtained, and selecting the optimal prostate cancer segmentation model by using the verification set; and inputting the multi-parameter magnetic resonance image of the test set and the gland optimal prediction mask into the optimal prostate cancer segmentation model to obtain a prostate cancer segmentation result, thereby improving the segmentation precision and robustness.

The invention discloses a wind power blade unmanned aerial vehicle inspection method and device, and belongs to the technical field of wind driven generators, and the wind power blade unmanned aerial vehicle inspection method comprises the steps: carrying out the unmanned aerial vehicle inspection of the front surface of a wind power blade to form first inspection information, and carrying out the unmanned aerial vehicle inspection of the back surface of the wind power blade to form second inspection information, the first inspection information comprises a first track point data set and a blade front image set, and the second inspection information comprises a second track point data set and a blade back image set; according to the first inspection information and the second inspection information, in combination with a wind power blade defect judgment condition, obtaining a wind power blade unmanned aerial vehicle inspection result; according to the wind power blade unmanned aerial vehicle inspection result, whether an unmanned aerial vehicle re-inspection mode is started is judged, if yes, the unmanned aerial vehicle re-inspection mode is started, and the wind power blade unmanned aerial vehicle inspection result is updated; and if not, the re-inspection mode is not started. The method can reduce the influence on the wind power plant operation and power generation efficiency, and improves the accuracy of the wind power blade unmanned aerial vehicle inspection result.

The invention relates to building structure monitoring, in particular to a monitoring device for health of a large-span building structure and an Internet of Things system. Which comprises an unmanned aerial vehicle and a monitoring server, and is characterized by further comprising a passive sensor and a reading transmission module, and the passive sensor is used for collecting state information of a building structure and wirelessly uploading the state information to the reading transmission module; the reading transmission module wirelessly uploads the state information of the building structure to the monitoring server. According to the invention, the RFID is combined with the sensor, so that the wiring work is omitted, and the workload of implementation and maintenance is greatly reduced; data are obtained through automatic cruise of the unmanned aerial vehicle, labor is saved, and punctual data are obtained; the Internet of Things is further wireless, the sensor at the tail end supplies power and obtains data in an RFID wireless mode, the most tedious wiring work is omitted, and arrangement and compensation of the Internet of Things sensors are facilitated.

The invention belongs to the technical field of stratum recognition, and particularly relates to a shield parameter geological recognition calculation method and system based on an unsupervised clustering algorithm, and the method comprises the steps: selecting a plurality of groups of data containing factors affecting stratum category recognition; pCA converts a group of complex related variables into fewer and irrelevant variables, and the new variables are called as main components and can capture most of information in original data; determining the clustering number of K-means + + by adopting an elbow method; determining the clustering number of a hierarchical clustering method by adopting a hierarchical tree; k-means + + and hierarchical clustering are respectively used for clustering the data, and evaluation indexes such as identification precision or contour coefficients of the data and the data are calculated, so that potential modes in the data are analyzed and mined more comprehensively. The invention aims to deeply explore the internal relevance between shield tunnel parameters and geological types, provides an innovative and robust solution for real-time detection of geological features in shield construction by overcoming the limitation of the prior art, and has wide application potential.

The present invention discloses a method and device for positioning and orienting a tunnel boring machine. The method comprises: when the tunnel boring machine is moving and excavating in a tunnel, a multi-beam laser radar installed at its rear end is used to scan a guide rod at the top of the tunnel to obtain relevant parameters of the guide rod, and according to the relevant parameters, the body offset angle and offset distance of the tunnel boring machine relative to the central axis of the tunnel are obtained, thereby controlling the tunnel boring machine walking system to adjust the walking direction and position, so that the tunnel boring machine can automatically walk along the central axis of the tunnel. During the automatic walking of the tunnel boring machine, whenever the guide rod is out of the laser radar scanning area, the guide rod is moved forward along the walking direction of the tunnel boring machine, so that the laser radar can scan the guide rod in real time, so that the tunnel boring machine can always walk automatically along the central axis. The method of the present invention calculates the offset distance and angle between the tunnel boring machine and the central axis of the tunnel through the guide rod, so as to realize that the tunnel boring machine automatically walks along the central axis in the tunnel, and the implementation method is simple and the result is accurate and reliable.

The invention discloses a generator set multi-target maintenance optimization scheduling method considering renewable energy access. The method comprises the following steps: establishing an uncertain model of renewable energy output and load; considering an economy target, a reliability target and a renewable energy consumption target, selecting a minimum total cost, a minimum standby capacity sum of squares and a minimum wind curtailment and light curtailment amount for comprehensive evaluation, and constructing a multi-target unit maintenance optimization model; converting a system power balance constraint and a reserve capacity constraint into a deterministic constraint with clear equivalence; selecting a membership function of each target based on a fuzzy theory, and converting the multi-target unit maintenance optimization model into a single-target unit maintenance optimization model; and solving the single-target unit maintenance optimization model converted based on the fuzzy theory by using an improved ant colony algorithm, and obtaining the maintenance and operation conditions of each unit while obtaining the maximum satisfaction degree. The method is applied to a power grid to arrange maintenance scheduling of the generator set, and economic benefits, reliability and renewable energy consumption are improved.

The invention relates to a mechanical arm repeated positioning accuracy index evaluation method based on normal random distribution. According to the method, normal random distribution repeated positioning errors are given to all joints of the mechanical arm, calculation of index confidence is achieved, and then evaluation work of the repeated positioning precision index of the mechanical arm is completed, and the method comprises the following steps that firstly, a mechanical arm kinematics model is established based on an improved DH method, and then the constant working condition and the extreme working condition of the mechanical arm are determined; and calculating the tail end direction and position of the working condition under the error-free condition. Next, joint errors are set based on normal random distribution, a tail end pose matrix is calculated, and then corresponding positions and pose errors are obtained; and finally, defining the proportion meeting the index under the repeated positioning of the mechanical arm as the index confidence coefficient, and further realizing the evaluation of the repeated positioning precision index of the mechanical arm.

The invention discloses a structure and method for testing the pressure between iron core sheets, the structure for testing the pressure between the iron core sheets comprises a pressure applying assembly, a plurality of measuring modules and two punching sheets, the axial outer side of each punching sheet is provided with the pressure applying assembly, and the plurality of measuring modules are respectively arranged between the two punching sheets; the measuring module comprises an upper mounting plate, a lower mounting plate and a pressure sensor, the upper mounting plate and the lower mounting plate are respectively abutted against one punching sheet, and the pressure sensor is fixed between the upper mounting plate and the lower mounting plate. According to the structure, the plurality of measuring modules are arranged between the two punching sheets, namely, the pressure sensors are arranged between the upper mounting plate and the lower mounting plate, so that the pressure state of each position between the punching sheets in the whole laminating process can be measured, the measuring result is not influenced by buckling deformation of an applying assembly, the measuring error is small, and the result is accurate and reliable. After the rib plates are welded on the peripheral sides of the punching sheets, the pressure sensors can also measure the pressure value between the punching sheets, and the multiple pressure sensors can measure the pressure distribution between the welded punching sheets.

The invention discloses a thermal infrared imager measurement angle compensation method, and belongs to the technical field of infrared temperature measurement, and the method comprises the steps: determining a target object needing temperature measurement, carrying out the temperature measurement of the target object based on the initial measurement angle of a thermal infrared imager and the target object, and obtaining a reference temperature; setting an angle range and a preset value, taking the preset value as an interval, selecting a plurality of measurement angles in the angle range, rotating the target object, obtaining measurement temperatures of the target object by the thermal infrared imager under the plurality of measurement angles, and defining the measurement temperatures as first measurement temperatures; converting the first measurement temperature based on the Planck's law of radiation to obtain radiation power; and calculating a compensation coefficient of each measurement angle, compensating the radiation power based on the compensation coefficients to obtain standard radiation power, and converting the standard radiation power into a compensated target temperature based on a preset temperature radiation quantity relation table. According to the invention, the temperature measurement precision of the thermal infrared imager is improved.

The invention relates to the technical field of motor testing, and provides a rack testing method and device for a motor and a motor testing rack. The method comprises the steps of outputting test result data of a to-be-tested motor according to at least one group of preset target test data under the condition that a console rack tests the to-be-tested motor, the test result data comprising test data of the to-be-tested motor at a plurality of continuous time points; screening out test data of the to-be-tested motor with the running state stabilized under each group of target test data from the test result data as target test result data; and outputting the target test result data. According to the method, the effective test result data of the motor running stably under the target test data are automatically screened out, so that the result is accurate and reliable, human intervention is avoided, and the test efficiency is improved.

The invention discloses an environmental chemistry research automation system and method based on a large language model, and relates to the technical field of environmental chemistry automatic research. The environmental chemistry research automation system based on the large language model comprises a key information extraction module, a structure generation and optimization module, an experiment scheme generation module, an experiment management module and a visual editing module. According to the method, full-automatic workflow from experimental design to data analysis is achieved, the research efficiency and accuracy are remarkably improved, through the method, complex scientific problems can be converted into understandable input of a language model, complex analysis and reasoning processes are completed through the model, and a physical and chemical calculation tool is combined, so that the research efficiency is improved. According to the method and the system, comprehensive simulation and calculation of a research object are realized, the degree of human participation is effectively reduced, subjective deviation caused by human decision is reduced, and scientific research becomes more systematized and accurate.

The invention discloses a tight-lock coupler intelligent tensile testing machine and a testing method thereof, and belongs to the technical field of tight-lock coupler test.The tight-lock coupler intelligent tensile testing machine comprises a mounting bottom plate and an electric control cabinet, and a support for supporting a tight-lock coupler to be detected is mounted on the surface of the mounting bottom plate; a tensile connecting frame for connecting the tight-lock coupler is mounted on the surface of the bottom plate on one side of the support, an integrated design of'tensile force detection and visual detection 'is innovatively adopted, mechanical parameter acquisition and visual deformation observation are combined, traditional mechanical data such as tensile force and displacement are obtained, and visual characteristics such as fine deformation and crack initiation are captured; precise synchronization of pulling force application, displacement collection and camera shooting is achieved through the synchronous controller, the real-time corresponding relation of pulling force-displacement-visual deformation is established, the problems that an existing device is single in detection dimension and poor in data relevance are solved, and the potential quality hazard checking capacity and the persuasion of a detection result are improved.

The invention relates to a tensegrity shape finding method based on a two-stage optimization deep neural network, and the method comprises the following steps: constructing a constraint equation of a tensegrity structure according to the node residual force, the rod piece length of a cable rod unit and the node distance, and taking the constraint equation as a loss function of the deep neural network; taking a randomly generated node coordinate vector of the cable-strut unit as the input of the deep neural network, obtaining a cable-strut unit node coordinate vector output value enabling the loss function value to be minimum by adopting a two-stage optimization mode, and determining a steady-state configuration based on the cable-strut unit node coordinate vector output value; circulating to obtain a plurality of steady-state configurations; and judging the stability of each steady-state configuration to obtain a stable configuration meeting geometric stability, and completing tensegrity form finding. Compared with the prior art, the method has the advantages that the shape finding of a multistable complex tensegrity structure and the like can be carried out, the result is reliable, the shape finding process does not involve complex structure finite element calculation, and the shape finding efficiency is high.

The invention discloses a rapid three-dimensional imaging method based on tissue light transparency, and belongs to the technical field of biomedical optical imaging. The method comprises the following steps: placing a biological tissue sample in a staining solution, and carrying out oscillation treatment to obtain a stained tissue sample; sequentially putting the dyed tissue sample into a dehydration solution, a degreasing solution and a refractive index matching solution, and carrying out oscillation treatment to obtain a transparent tissue sample; performing three-dimensional imaging on the transparent tissue sample to obtain a three-dimensional fluorescence image of the tissue sample; and converting the three-dimensional fluorescence image of the tissue sample, and performing three-dimensional reconstruction on the obtained dyeing bright field image to obtain a three-dimensional dyeing image of the tissue sample. According to the method, after the tissue is subjected to dyeing, transparentizing, imaging and three-dimensional reconstruction and analysis, the complete three-dimensional information of the tissue can be obtained, the result is stable and reliable, and the whole method is rapid and simple, so that the method has a relatively good application prospect in tissue pathology detection.

The invention provides a virus RNAi inhibitor screening vector as well as a construction method and application thereof, and belongs to the technical field of viruses. The virus RNAi suppressor screening vector comprises a green fluorescent protein coding gene expression cassette and a shRNA expression cassette targeting a green fluorescent protein coding gene, the nucleotide sequence of the shRNA is as shown in SEQ ID NO: 2 or SEQ ID NO: 3. According to the invention, the green fluorescent protein coding gene and the shRNA are cloned into the same expression vector, so that the consistency of transfection efficiency is ensured. The invention further provides a screening method of the virus RNAi suppressor, the virus RNAi suppressor screening vector and the recombinant vector for expressing the virus RNAi suppressor to be screened are co-transfected into cells, and the screening result is judged according to the green fluorescence intensity. According to the technical scheme, operation is easy and convenient, the screening result is accurate and reliable, and wide application and popularization value is achieved.

The invention discloses an MMP2 gene promoter region SNP (Single Nucleotide Polymorphism) site and application thereof in pig breeding. According to the invention, an MMP2 gene promoter region is taken as a research object, and the relevance between the MMP2 gene promoter region and sow sexual maturity is researched by adopting a molecular and cell biology method, so that the situation that g.30088284G > A site and g.30088004C > T site are obviously related to the group maturity day age of Dumet black pigs is found; then different vectors are transfected, and different influences of different genotypes of the sites on the activity of the IRS1 gene promoter are studied. Further, sow ovarian granular cells are used as experimental materials, experimental technologies such as transcriptome sequencing, a total iron colorimetric method and a malondialdehyde colorimetric method are adopted, the influence of the MMP2 gene on the transcriptome level and ferroptosis of the sow ovarian granular cells is researched, and it is found that cell transcriptome differential genes influenced by the MMP2 gene are mainly enriched to signal channels such as cell differentiation; and ferroptosis of cells is promoted.

The invention relates to the technical field of environment detection, in particular to a method for pre-enriching humic acid in a lake water body and determining molecular weight. The method comprises the following steps: (a) extracting and purifying humic acid in a lake water body; (b) preparing a lake water humic acid measured solution; (c) selecting a fluorescence peak position of a titration experiment; (d) fluorescence quenching titration of humic acid; and (e) calculating the molecular weight of humic acid. Tyrosine is used as a model compound and a humic acid standard sample for verification, and the accuracy and reliability of the method are proved.

A wind turbine lightning arrester detection device disclosed by the present invention comprises an unmanned aerial vehicle, the side wall of the unmanned aerial vehicle is connected with a plurality of direction adjusting assemblies, the plurality of direction adjusting assemblies are arranged opposite to the unmanned aerial vehicle, the direction adjusting assemblies are provided with cameras, the bottom of the unmanned aerial vehicle is connected with a rotating assembly, and the rotating assembly is connected with a fixing assembly. The side wall of the fixing assembly is connected with a rust removal assembly and a detection assembly, the rust removal assembly and the detection assembly are symmetrically arranged relative to the fixing assembly, a control assembly is arranged in the fixing assembly, and the control assembly is electrically connected with the direction adjusting assembly, the rotating assembly, the rust removal assembly, the camera and the detection assembly. The wind turbine lightning arrester detection device is used for detecting a lightning arrester, and the problems that in the prior art, a suction cup falls off due to vibration of a fan in the lightning arrester detection process, and hovering difficulty is large during unmanned aerial vehicle wired detection are solved.

The invention provides a mountain river fluid bed physical model bed load layering and zoning simulation method, which comprises the following steps: carrying out sediment sampling on a simulated river reach, dividing sediment types, and layering and zoning sediment distribution; calculating representative gradation of each type of sediment, dividing sediment components and counting the proportion of each component; constructing a sediment similarity scale calculation formula, calculating the particle size of the model sand of each component, and preparing the model sand of each type of sediment; a physical model is manufactured, pre-prepared model sand is laid according to the sediment type of each layer area, and movable bed test verification is carried out. According to the method, accurate simulation of the movement rule of the bed load under the complex substrate condition of the mountain river is achieved, the problems of model sand selection, model sand laying and accurate simulation of the bed load in the moving bed physical model are effectively solved, and the design method of the moving bed physical model is enriched and developed.

The invention discloses a circuit protection method based on fault current prediction and related products, and belongs to the technical field of circuit protection, and the method comprises the steps: obtaining a current instantaneous value at a current moment and a current instantaneous value at a corresponding historical moment in real time, and calculating a current value at the current moment and the measurement precision of the current value at the current moment in real time; when the measurement precision of the current value at the current moment is greater than the response precision of the current fault, the current fault is established, and the calculation of the measurement precision of the current value at the current moment is stopped; after the fault current fluctuation time is delayed, the stable fluctuation of the current value at the current moment is calculated in real time; when the stable fluctuation of the current value at the current moment is smaller than a preset value, entering a current fault stable state, and obtaining a predicted fault current value; based on the predicted fault current value, the circuit is protected; the accuracy and response speed of fault current prediction are improved, so that circuit protection can respond to faults in the shortest time, and meanwhile, false alarms and missing alarms are reduced.

The invention discloses a meter box impedance anomaly analysis method based on use and acquisition data, which comprises a data acquisition step, a data recording step, a data processing step, an impedance calculation step and an anomaly analysis step, can obtain the electric meter box impedance of each electric energy meter, can accurately position lines with line aging or device loosening conditions in the electric meter box, and improves the accuracy of the electric meter box impedance analysis. Therefore, the detection difficulty of the line impedance in the electric meter box can be reduced, the accuracy is improved, the connection relationship between each electric energy meter and each phase line at the inlet wire of the electric meter box is obtained by using the screened steady-state data, then the data corresponding to each electric energy meter is used for calculating the impedance of the electric meter box, and the result is stable and reliable. The method has the advantage that the detection of the impedance in the electric meter box is more accurate and simpler.

The invention discloses a linear mitochondrial separation method, which comprises the following steps: step one, expressing mitochondrial protein peptide with a modified amino acid sequence of NH2-Gly-Gly-Gly-Phe-(D) Arg-Phe-Lys-Phe-(D) Arg-Phe-Lys (Ac)-CON-H2 on a microsphere, so as to obtain a polypeptide modified microsphere with closed GLy, and modifying the mitochondrial protein peptide with the modified amino acid sequence of NH2-Gly-Gly-Gly-Phe-(D) Arg-Phe-Lys-Phe-(D) Arg-Phe-Lys (Ac)-CON-H2; and 2, carrying out mitochondrial extraction on a target tissue by using the GLy-closed polypeptide modified microspheres. The purity of the obtained mitochondria is high, pollution of subcellular organelles and cell debris except the mitochondria is avoided to a certain extent, and the phenomenon that the detection result deviates due to the purity of the mitochondria when the mitochondria with the high purity is detected by a high-sensitivity detection instrument is avoided. And the cost of the mitochondria obtained by the method is controllable, and stable and reliable results can be brought to experiments.

The invention discloses a rapid sex identification method for propylaea japonica adults, and relates to the technical field of insect sex identification. Collecting adult propylaea japonica; if triangular black spots or hourglass-shaped black spots exist in the middle of the forehead of the head of the adult, the adult is female; if the middle part of the forehead of the head of the adult has no triangular black spot and is yellow or milky copper bell-shaped, the adult is male; the propylaea japonica adults are adults within the third day to the thirtieth day of eclosion, the elytra color spots are in a turtle pattern shape, and the forehead of the head is yellow or milky white. According to the method disclosed by the invention, the cost is hardly needed, the operation is very simple, the sex of the propylaea japonica adults can be accurately identified under the condition of hardly damaging the propylaea japonica adults, and related researchers can completely grasp the sex of the propylaea japonica adults only by being slightly familiar with the forehead morphological characteristics of the adults.

The invention relates to the technical field of electric power, and discloses an electric energy meter measurement missing data complementing method based on univariate dynamic time warping, which comprises the following steps: constructing an initial time sequence INP from normal no-missing electric energy meter data, and determining missing data of a missing sequence; according to the length T of the missing data, combining with the new time sequence INP'to adaptively create a query subsequence, and based on the initial time sequence INP, constructing a reference database; calculating the similarity between the query sub-sequence and each candidate sub-sequence in the reference database by adopting a dynamic time warping algorithm so as to obtain a candidate sub-sequence most similar to the query sub-sequence; and filling missing data with the last T adjacent data of the most similar candidate subsequences. According to the method, the complex dynamic change of the data can be better captured, and a reliable result can still be obtained under the condition that nonlinear fluctuation is possibly caused by factors such as faults and interference in the measurement of the electric energy meter.

The invention discloses a molecular marker primer group for identifying an avocado variety Tenglong, a kit, a marking method and application, and belongs to the technical field of biology. The main identification method comprises the following steps: (1) extracting genome DNA of a sample to be detected; (2) taking the genome DNA as a template, and carrying out PCR (Polymerase Chain Reaction) amplification by utilizing five pairs of primers; (3) performing electrophoresis detection on the PCR amplification product to obtain a peak value of the amplification product of the sample to be detected; and (4) respectively comparing the peak values of the five amplification products of the sample to be detected with corresponding standard peak values so as to judge whether the sample to be detected is the avocado variety Tenglong or not. The five pairs of specific primers are utilized to perform PCR amplification on the genome DNA of the sample to be tested, and the peak value of the amplification product is compared with the standard peak, so that whether the test sample is the avocado variety Tenglong or not can be quickly and effectively judged, the operation is simple and convenient, and the protection, popularization and application of the variety are facilitated.