335results 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 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 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 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 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 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 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.

The invention provides a roadbed water stabilizing layer material based on modified roasted electrolytic manganese slag, a method and application. The roadbed water stable layer material is applied to the technical field of resource utilization of industrial waste residues and comprises the following raw materials in percentage by mass: 3.0%-4.5% of cement, 40%-60% of coarse aggregate, 14%-27% of roasted electrolytic manganese residues, 1.12%-2.7% of a curing agent, 0.4%-0.75% of a stabilizer, 0.4%-0.7% of an exciting agent and 1.93%-3.73% of water. In this way, the water stable layer material prepared through the method has the advantages of being high in curing effect, strength and stability, and high in replicability and generalization performance.

The invention relates to a method and a device for determining the organic carbon content of marsh hydrocarbon source rock, and the method comprises the following steps: obtaining the organic carbon content and a plurality of mineral component parameters of a series of rock cores of a sea-land transition phase hydrocarbon source rock stratum section, and determining the correlation between the organic carbon content and each mineral component parameter; screening at least one target mineral component parameter related to the organic carbon content based on the correlation; fitting to obtain a function relation between the organic carbon content and the core logging response value and at least one target mineral component parameter; determining at least one target mineral component parameter of the to-be-measured rock core based on the logging curve; and determining the organic carbon content according to the target logging response value of the to-be-measured rock core, the at least one target mineral component parameter and the function relation. The organic carbon content of the margarious hydrocarbon source rock calculated by the method has the characteristics of high accuracy and reliable result, and effective technical support is provided for logging evaluation of the organic carbon content of the margarious hydrocarbon source rock in exploration and development of shale oil and gas and compact oil and gas.

The utility model relates to the technical field of automatic testing of sensors, and discloses an automatic testing mechanism of a current sensor, which comprises a deck plate, a testing assembly is mounted on the deck plate, and a pressure head and a probe assembly are arranged at the top of the testing assembly. According to the utility model, the test assembly and the pressure head and probe assembly are arranged on the countertop and work together, so that parameters of the current sensor can be automatically tested, and the current sensor parameter testing device has the advantages of simple operation, high test efficiency, high precision, high automation degree, good safety, reliable result, simple mechanism, low equipment cost, convenience and rapidness, and the like. Therefore, the trouble that multiple sets of equipment such as a digital oscilloscope, a program-controlled voltage-stabilized source and a desk-type digital multimeter are needed to test each current sensor in the traditional mode is avoided, the time is effectively saved, and the labor cost is greatly reduced.

The invention discloses a complex interlaced channel type shallow water delta reservoir configuration prediction method based on a CNN convolutional neural network algorithm. The method comprises the following steps: establishing a configuration unit sample data set; preferably selecting effective sample points; seismic attribute and spectrum feature extraction; preferably selecting attributes which are highly related to the configuration units; preferably selecting a machine learning algorithm; constructing a convolutional neural network prediction model; inputting seismic attributes into the trained network model, outputting a configuration unit prediction model, and predicting the configuration unit distribution of the well control-free area; and identifying and dividing a single split-flow river channel and the like. According to the method, the plane contact relation and the vertical combination style of the composite sand body are finely dissected, so that the fine description of the single river channel in the multi-stage stacked complex interlaced composite river channel is realized, the reservoir recognition precision is improved, the fine implementation of an offshore oilfield horizontal well and the efficient development of an oilfield are guided, and the development of the offshore oilfield horizontal well is facilitated. The result of the prediction method is not greatly different due to subjectivity of researchers, and the prediction result is more reasonable and reliable.

The invention discloses an unmanned aerial vehicle signal detection and identification method based on spectrum feature enhancement. The method comprises the following steps: firstly, carrying out time-frequency transformation on a received signal to obtain an original time-frequency graph; performing learning enhancement on the degenerated time-frequency graph by adopting a coding-decoding type deep neural network, and realizing noise suppression and structure recovery by combining pixel reconstruction, structural similarity and a texture perception loss function; and finally, performing target area detection and positioning on the enhanced time-frequency graph, directly outputting a structured result containing a time-frequency range, a category and confidence, and completing conversion from a frequency spectrum to a linkable engineering target. According to the unmanned aerial vehicle signal detection and recognition method based on spectrum feature enhancement, a spectrum feature enhancement mechanism is introduced before traditional spectrum analysis and feature recognition processing, and region-level detection and judgment are executed under the enhanced spectrum constraint condition; reliable discovery, positioning and identification of an unmanned aerial vehicle control link and an image transmission link in a complex electromagnetic environment are realized.

The invention relates to the technical field of high-voltage direct-current power transmission, and discloses a same-tower double-circuit direct-current line bipolar fault line selection and type identification method, which comprises the following steps of: decoupling differential current of each pole line to obtain modulus current of each pole line, and identifying a fault line according to a ratio between moduli; bipolar fault line selection can be carried out only by collecting the current of each polar line, and the result is accurate and reliable. Compared with a conventional fault line selection method, a criterion adopts a ratio mode, a setting value is larger, and the influence of transition resistance is small; whether the fault type is a line touch fault can be identified according to the voltage variation of the fault line selection; compared with an existing fault line selection method, the fault line selection method not only can identify whether a bipolar line fault occurs, but also can further identify whether the fault type is a single-circuit direct current bipolar line fault or a double-circuit direct current touch line fault. According to the method, a same-tower double-circuit direct current line protection system is supplemented and perfected, the problem of same-tower double-circuit direct current line collision fault identification is solved, and reliable operation of same-tower double-circuit direct current is guaranteed.

The invention discloses a method and a device for calculating distributed capacitance of an electromagnetic voltage transformer. The method comprises the following steps: constructing a capacitance parameter correlation constraint equation of the electromagnetic voltage transformer; opening a primary terminal of the electromagnetic voltage transformer, applying excitation of different frequencies to a secondary terminal of the electromagnetic voltage transformer, and obtaining iron core equivalent excitation impedance, open-circuit parallel resonant frequency and open-circuit series resonant frequency of the electromagnetic voltage transformer; performing short circuit on a primary terminal of the electromagnetic voltage transformer, applying excitation of different frequencies to a secondary terminal of the electromagnetic voltage transformer, and obtaining primary and secondary winding equivalent impedance and short circuit parallel resonant frequency of the electromagnetic voltage transformer; and substituting the iron core equivalent excitation impedance, the primary and secondary winding equivalent impedance, the open-circuit parallel resonant frequency, the open-circuit series resonant frequency and the short-circuit parallel resonant frequency into a capacitance parameter correlation constraint equation, and calculating the distributed capacitance of the electromagnetic capacitance transformer.

The invention discloses an SINS / DME / DME integrated navigation system performance evaluation method, which comprises the following steps: according to a state equation and a measurement equation of an SINS / DME / DME integrated navigation system, calculating slope distance data calculated by a position through a strapdown inertial navigation system SINS and slope distance data measured by a distance meter DME, and fusing by adopting a Kalman filtering algorithm, specifically comprising two parts of time updating and measurement updating; evaluating the performance of the SINS / DME / DME integrated navigation system based on the actual navigation performance ANP calculation model of the filtering covariance; the method has the advantages of simple calculation, credible result and the like.