41results about How to "Quick estimate" patented technology

The invention belongs to the field of wind power plant grid-connected control, particularly relates to a wind power plant active power efficient distribution method considering the fatigue damage degree of fans, and aims to solve the problem that scheduling instruction power is uniformly distributed to all fans in the prior art. And the fan fault probability is increased due to the fact that the influence of power adjustment on fan fatigue damage is not considered. The method comprises the steps of fan load estimation based on stress analysis and energy conservation, low-complexity fatigue damage quantification based on an improved energy method, and construction of a multi-target optimization model with the minimum total fatigue load of a wind power plant and the most uniform fatigue load distribution between fans as targets based on a Gulin method, an entropy weight method and an improved matter element extension model. According to the method, rapid and accurate power distribution is realized, so that the fan runs in a proper state, the accumulation of fatigue damage and the risk of failure occurrence are reduced, and the overall running efficiency and economic benefit of a wind power plant are improved.

The invention provides a complete machine load estimation control method for a wind turbine generator. The method comprises the steps that S1, original data are collected and preprocessed; s2, establishing a load model of the wind generating set based on stress analysis; s3, establishing a load prediction model of the wind generating set based on the variable-pitch motor data; s4, constructing a neural network prediction model; s5, using a genetic algorithm to optimize the weight and the threshold of the neural network for training; and S6, adjusting. Through one-time sensor investment and calculation of a large amount of calculation and training work in the early stage, an actual model for reversely deducing a fan load from parameters of a variable-pitch motor and a generator is obtained and is transmitted to a main controller, so that convenient load reduction control can be realized, subsequent repeated investment can be omitted at a wind turbine generator, a large amount of hardware investment is saved, and the cost is reduced. Adjustment is carried out through continuous monitoring and continuous verification modeling in the later period, and rapid load estimation and control of the whole life cycle of the wind turbine generator can be achieved.

The present invention is a method for measuring the remaining amount of a liquid in a liquid storage container, the method comprising the steps of: discharging the liquid in the liquid storage container to the outside through a suction tube inserted into the liquid storage container; the size or number of bubbles contained in the liquid penetrating through the light-transmitting part is observed through a visual device pointing to the light-transmitting part of the suction pipe; and estimating the remaining amount of the liquid based on the observed size and number of bubbles. Further, the method includes a remaining amount estimation step using the return ultrasonic waves, and the remaining amount estimation step using the return ultrasonic waves includes the steps of: oscillating the ultrasonic waves from the ultrasonic generator into the interior of the liquid storage container; receiving the ultrasonic wave returned after oscillation and analyzing the waveform of the ultrasonic wave; and estimating the remaining amount of the liquid by comparing the waveform of the ultrasonic wave with previously provided reference data.

The invention relates to an industrial wireless network technology, in particular to a radio frequency map estimation method for an industrial indoor scene. The invention is suitable for a radio frequency estimation (RME) problem in an industrial indoor scene, and specifically, the method comprises the following steps: firstly, constructing a radio frequency map simulation data set by using a ray tracing technology to train a Conditional Generative Advanced Network (CGAN), and efficiently generating a large number of new radio frequency map samples; according to the method, a large number of radio frequency map samples generated by the CGAN are used for training a ViT model, important features most related to path loss can be extracted, and finally, a corresponding high-precision radio frequency map can be quickly estimated on line according to an input industrial indoor scene planar graph.

The invention relates to the technical field of wind power generation, and provides a mountain wind power plant developable capacity estimation method, device and equipment and a medium, and the method comprises the steps: obtaining dot matrix data, wind speed grid point data, ground feature coverage data and limiting factor range data of a target mountain wind power plant; according to the dot matrix data, generating initial ridge line data; based on the wind speed grid point data, the ground feature coverage data and the limiting factor range data, performing spatial analysis on the initial ridge line data to obtain target ridge line data; and obtaining the impeller diameter and the rated power of the wind driven generator, and estimating the developable capacity of the target mountain wind power plant according to the impeller diameter, the rated power and the target ridge line data. In the application, key factors such as terrain, wind speed and ground feature coverage are comprehensively considered, and spatial analysis is performed on the initial ridge line data, so that the estimation result of the developable capacity of the target mountain wind power plant is closer to the actual situation, and the estimation accuracy is improved.

The invention belongs to the field of space target imaging, and discloses a space target three-dimensional reconstruction method for inhibiting dark color interference through combination of brightness and transparency, which is used for solving the problems of poor imaging quality and inaccurate pose estimation of a space target. According to the method, multiple requirements of improving the quality of an input image, adjusting a pose and training a three-dimensional model are jointly completed, and low-quality imaging of an incomplete imaging system is preprocessed based on lucky imaging; and then, dense feature points are extracted by using a pre-training network based on no detector, estimation of a three-dimensional initial point cloud and an initial pose of a camera is carried out, and pose joint adjustment is carried out by combining RANSAC and Bundle AdJustlement. During training, an MLP-based optimizer is used for calculating the deviation of pose adjustment, meanwhile, training of parameters of three-dimensional Gaussian primitives is carried out, and after various physical constraints are added, a one-stop assembly line can be implemented. According to the method, the good basic shape and the sharp edge of the model are kept, the good anti-noise capability is achieved, and meanwhile the real-time performance and the robustness are achieved.

The present invention belongs to the field of wind farm grid-connected control, and specifically relates to a method for efficiently distributing active power of a wind farm taking into account the degree of fatigue damage of wind turbines, aiming to solve the problem that the traditional method evenly distributes the dispatching command power to all wind turbines without considering the influence of power regulation on fatigue damage of wind turbines, which leads to an increase in the probability of wind turbine failure. The present invention includes: wind turbine load estimation based on force analysis and energy conservation, low-complexity fatigue damage quantification based on improved energy method, and a multi-objective optimization model based on Gulin method, entropy weight method and improved matter-element extension model with the goal of minimizing the total fatigue load of the wind farm and the most uniform distribution of fatigue loads between wind turbines. The present invention realizes fast and accurate power distribution, enables wind turbines to operate in a suitable state, reduces the accumulation of fatigue damage and the risk of failure, and improves the overall operating efficiency and economic benefits of the wind farm.

The application provides a soil organic carbon estimation method based on a Sentinel-2 image, and steps include sample collection, remote sensing data processing, feature screening, model building, training and testing, and optimal model inversion. The application aims to solve the problems of insufficient precision and interpretability of existing estimation methods, and constructs a high-precision estimation technology system that fuses multispectral data and stacking model algorithms. Only small-scale sample collection is required to train the model, without the need for repeated field sampling and laboratory analysis, which greatly reduces the cost, has small external constraints and is environmentally friendly. The application can efficiently realize large-scale continuous estimation, and the estimation result has high precision and strong stability, which can accurately depict the spatial distribution of carbon content and provide reliable technical support and data guarantee for related work.

This invention discloses a target localization method for multiple-transmitter, multiple-receiver passive multistatic radar under interference conditions. The method includes: acquiring reference channel signals and echo signals and performing signal characterization preprocessing to obtain reference channel signal matrices and echo signal matrices; estimating channel parameters based on the reference channel signal matrices and echo signal matrices using the generalized likelihood ratio principle to construct a DPI-GRLT detector; solving the DPI-GRLT detector and calculating the detection statistics at each grid point to obtain the radar target information estimation result. This invention can maintain high localization accuracy and achieve rapid estimation and resolution of multiple targets even under weak signal conditions. As a target localization method for multiple-transmitter, multiple-receiver passive multistatic radar under interference conditions, this invention can be widely applied in the field of radar target localization technology.

The present invention relates to an adaptive anti-interference control method for a hydrogen fuel cell DC / DC element, which belongs to the field of DC / DC control of a hydrogen fuel cell system, and includes: first, considering parameter perturbation and harmonic interference to establish a Boost type DC / DC dynamic model; second, defining the tracking error of the system, designing a specified performance function and performing error conversion to obtain a first unconstrained error model; third, designing a virtual control variable, and designing an interference observer to obtain an estimated value of the harmonic interference; finally, defining a second error model, designing a DC / DC duty cycle adaptive control instruction, and completing the adaptive anti-interference control of the DC / DC element. The present invention realizes the inductor current control of the DC / DC element under the condition of parameter perturbation and double frequency harmonic interference, and has the characteristics of high robustness and easy engineering implementation.

The application relates to the technical field of metal mine development, and discloses a soil heavy metal content estimation method, device, equipment and medium, the method comprising the following steps: collecting soil samples in a target area, and determining the contents of various heavy metal elements in the soil samples; acquiring visible light-near infrared hyperspectral reflectance data and X-ray fluorescence spectrum data of the soil samples; calculating competition coefficients among the heavy metal elements by using an L-V competition model, and determining a competition element set of a target heavy metal element; based on band importance of a random forest, a multi-objective optimization function is constructed, the function aims to maximize spectral response differences of the target heavy metal element and minimize spectral response differences of competition elements of the target heavy metal element, and the NSGA-II algorithm is adopted to screen an optimal band bit feature set in combination with wavelength interval constraints, and a machine learning regression model is trained to estimate the heavy metal content of soil in a to-be-measured area. Through the scheme, the inversion precision and stability of the model are significantly improved.

The invention provides a method for estimating characteristic parameters of a wireless battery charging system with variable frequency control, which is simple in process, small in calculation amount and easy to implement, provides an analytic expression of the relationship between the characteristic parameters of the system and the working frequency, and can be used for quickly estimating the characteristic parameters by using the analytic expression; frequency range limitation is avoided, and frequency range solving is not needed; the pre-estimation result is highly matched with the result of a circuit simulation method, and the precision is high. The method is suitable for S / S compensation battery wireless charging systems of automatic guided vehicles, electric vehicles and the like.

The invention relates to the technical field of proton exchange membrane fuel cells, and discloses a method for estimating nonlinear parameters of a proton exchange membrane fuel cell based on a preset time estimator. According to the method, the output form of an electrochemical model of the proton exchange membrane fuel cell is converted into a linear system model through filtering operation, and a strong nonlinear system is rewritten into a linear parameterization form; a decoupled linearization system is obtained by defining an auxiliary variable and a decoupling algorithm, and the problem of system parameter coupling is solved; finally, preset time convergence of unknown nonlinear parameters in the model is achieved through a preset time parameter estimation method, online and rapid estimation of the nonlinear parameters of the proton exchange membrane fuel cell is achieved in the process, and the estimation speed of the nonlinear parameters is greatly increased; on-line estimation of unknown nonlinear parameters of the proton exchange membrane fuel cell can be realized only through input-output signals of an on-line measurement system.

The invention discloses a four-rotor unmanned aerial vehicle anti-interference tracking control method based on a double-dynamic event triggering mechanism in the technical field of unmanned aerial vehicle control, and the method comprises the following steps: 1), building a kinematic equation of a four-rotor unmanned aerial vehicle, and carrying out the modeling of an unmanned aerial vehicle model; 2) combining state information with a proportional-integral structure, carrying out augmentation and expansion on the system, and designing a composite dynamic tracking controller; 3) based on a disturbance observer control strategy, designing a dual-dynamic event triggering mechanism of a system feedback state and disturbance estimation, and realizing compensation of the unmanned aerial vehicle system on disturbance and reducing data transmission between the unmanned aerial vehicle system and a ground station; and 4) solving the linear matrix inequality equation through a Lyapunov stability analysis method and a convex optimization algorithm to obtain the controller gain, and reducing the data transmission and bandwidth waste of the input end of the unmanned aerial vehicle on the basis of solving the design of the anti-interference observer, and ensuring that the controlled system has good synchronism and system stability.

The invention relates to the technical field of ship electrical and anti-corrosion system design, in particular to a rapid design method for parameters of a ship impressed current cathodic protection system. Based on the electromagnetic field theory, the invention provides a method for quickly calculating the resistance of the auxiliary anode and the metal hull in the seawater medium, and based on the calculation method, a method for calculating the effective action boundary of the anti-corrosion current of the auxiliary anode is provided. Therefore, rapid calculation of impressed current cathodic protection system key parameters such as the number of auxiliary anodes, potentiostat voltage and power capacity is achieved, compared with a traditional finite element method, the parameter calculation time can be greatly shortened, and the design efficiency is greatly improved.

The application relates to the technical field of direction of arrival estimation, and specifically discloses a cross-platform complex domain feature enhancement coherent super-resolution DOA estimation method, which comprises the following steps: firstly, a complex domain CVSIMO learning model is constructed; sampling data is preprocessed; forward propagation of the CVSIMO learning model is carried out; backward propagation and parameter optimization of the CVSIMO learning model are carried out; data reconstruction and signal separation are carried out; cross-platform super-resolution DOA estimation is carried out; and finally, model simulation experiments are carried out. The cross-platform complex domain feature enhancement coherent super-resolution DOA estimation method can realize feature mining of multiple point source signals, converts a multi-source estimation problem into a single point source DOA estimation problem by using a complex domain neural network model, enhances the features of coherent signals by using the advantages of the complex domain neural network, improves the performance and precision of the super-resolution DOA estimation algorithm, can also realize data separation of multiple coherent signals and cross-platform DOA estimation, and realizes real angle estimation through ingenious feature solving.

The embodiment of the present invention provides a method, device, equipment, medium and product for estimating the aerodynamic characteristics of a bionic aircraft, and relates to the field of data processing technology. The method includes: inputting initial parameters into the wing geometry model of the bionic aircraft, outputting the aerodynamic resultant force perpendicular to the wing of the bionic aircraft at the current moment; determining the torsion angle of the chord-wise load-bearing rod of the wing around the leading edge of the wing according to the aerodynamic resultant force; if the current moment has not reached the termination moment, updating the wing geometry model according to the torsion angle, and outputting the aerodynamic resultant force perpendicular to the wing of the bionic aircraft at the current moment based on the updated wing geometry model after the interval time interval step, and executing the step of determining the torsion angle of the chord-wise load-bearing rod of the wing around the leading edge of the wing according to the aerodynamic resultant force; if the current moment reaches the termination moment, decomposing the aerodynamic resultant force. The present invention can estimate the aerodynamic characteristics of the bionic aircraft more accurately and quickly.

The invention discloses a probability transient stability evaluation method considering wind power output random and correlation. The method comprises the following steps: determining the optimal sampling point number of a wind power output random variable by adopting a practical dynamic security domain (PDSR) and an ant colony optimization algorithm; a multi-layer perceptron (MLP) is introduced to predict quantiles of future wind power generation output, so that the randomness of actual wind power generation output is described; according to the optimal sampling point and the quantile, Gaussian-Hermite integration is adopted to obtain wind power output uncorrelated original state variable distribution; adopting Nataf inverse transformation to process the correlation between the wind power plants; and performing calculation based on Cornish-Fisher expansion to obtain a transient stability probability. According to the method, the precision requirement of transient stability evaluation of the current wind power grid-connected power system can be met, and transient stable and safe operation of the wind power grid-connected system is guaranteed.

The invention discloses a lithium iron phosphate battery remaining capacity calibration method and device, and the method mainly comprises the steps: obtaining the spectrum data of a battery at different SOC and temperatures through an offline electrochemical impedance spectroscopy test, carrying out the inversion to obtain a relaxation time distribution DRT function, and building a detailed SOC-T-DRT feature database; during online estimation, the system collects a relaxation voltage time sequence after the vehicle stands; meanwhile, the current temperature, the SOC estimation value and a priori DRT feature vector obtained through interpolation in an offline database are input into a BiLSTM bidirectional long short-term memory network together, and the network inverts a high-precision SOC estimation value from the input through a mapping relation obtained through training learning. According to the method and the device, the relaxation time distribution characteristics and the deep learning model are introduced, so that the problem of insufficient SOC estimation precision in a lithium iron phosphate platform area in a traditional method is solved, and high-precision and robust SOC estimation is realized.

The device for active roll stabilization of a vehicle includes a chassis having at least two laterally opposed wheel suspensions (10a, 10b), a body supported thereon, and an actively adjustable roll stabilizer (1), the roll stabilizer having an actuator (3) and two stabilizer sections (8a, 8b) connected thereto, the stabilizer sections being able to be twisted relative to each other by a certain system angle () about the axis of rotation (4) by means of the actuator (3), each of the two stabilizer sections (8a, 8b) being radially away from the axis of rotation (4) and respectively connected to one of the wheel suspensions (10a, 10b) such that the roll behavior of the body can be affected by adjusting the actuator (3), the device also includes a means for determining the torque (M1) acting on the actuator (3), the actuator (3) being operable (within the framework for roll stabilization adjustment) taking into account the determined torque (M1), the means for determining the torque (M1) being a virtual sensor (20).

The invention belongs to the technical field of composting fertilizers, and particularly relates to a production method of an organic fertilizer prepared from agricultural wastes, the organic fertilizer is prepared by a windrow composting method, and the composting method is characterized by comprising the following steps: 1, preparing chopped straws, soil and livestock excrement according to a ratio of 6: 1: 2, and uniformly mixing; the appropriate ratio of the straw to the water is 1: 3; the method comprises the following steps: firstly wetting straws, detecting the ratio of straw to water to be 1: 1.6, spreading a layer of the wetted straws with the thickness of 15-20cm, spraying a decomposition agent once, dissolving the decomposition agent in water according to the weight ratio of the decomposition agent to the water of 1: 50, adding 0.3 kg of the decomposition agent for 250kg of straws until all the straws are stacked, and detecting the carbon-nitrogen ratio in a stack; detecting the carbon-nitrogen ratio of the compost, and taking targeted measures according to the detection result of the carbon-nitrogen ratio; when the compost temperature is too low or the temperature does not reach the standard, the carbon-nitrogen ratio of the compost is detected at first, and then targeted measures are taken according to the detection result, so that the fermentation effect is improved.

The present invention discloses a method for estimating a rendezvous pulse using a neural network. First, a training data set with one-to-one correspondence between the initial and target orbits, the rendezvous duration and the velocity increment is obtained. Then, a neural network structure is designed, including the number of layers of the neural network, the number of nodes in each layer, and the data type of the input layer. The neural network is trained using sampled data to obtain the optimal weight of the network. Finally, the rendezvous pulse size is calculated using the trained neural network. The present invention is able to quickly calculate the optimal velocity increment size of a pulse rendezvous considering perturbations, given the rendezvous moment and the transfer flight duration, and given the number of roots of the initial and target orbits.

The invention discloses a transient electric energy quality detection method for wide-area protection of a power grid. The method comprises the following steps: acquiring a fault signal containing a fundamental wave, a harmonic wave, an inter-harmonic wave and an attenuation direct current component; performing frequency spectrum estimation to obtain an estimated value of a fuzzy attenuation direct-current component, establishing an exponential function model to iteratively calculate a reconstructed attenuation direct-current component, solving a least square problem, taking the reconstructed attenuation direct-current component with the minimum error with the fuzzy attenuation direct-current component as final estimation, and removing the reconstructed attenuation direct-current component from a fault signal; a Taylor Fourier multi-frequency model is reconstructed for a fault signal without an attenuation direct current component to change the frequency resolution, then a dynamic phasor estimation problem is converted into a compressed sensing solving problem, and finally an improved sparsity self-adaptive matching pursuit algorithm is used for solving to obtain estimated values of phasor, frequency and frequency change rate. According to the method, the attenuation direct current component can be quickly estimated, and accurate voltage and current phasors can be calculated within an extremely short time window after a fault occurs.

The present application provides a method and device for measuring the frequency of an electric power system based on iterative optimization, and the measuring device includes: obtaining a sampling signal of the electric power system signal to be measured, and calculating a discrete spectrum sequence after windowing and truncating the sampling signal to form a discrete sinusoidal signal sequence; calculating the spectrum position corresponding to the maximum value of the modulus sequence in the discrete spectrum sequence; determining the three spectrum line parameters required for iteration according to the spectrum position; constructing a loss function of the frequency estimation position based on the sampling signal based on the three spectrum lines according to the three spectrum line parameters; iterating with the minimum constructed loss function as the optimization goal until the iteration termination condition is met to obtain the optimal frequency estimation position output; calculating the frequency measurement result of the electric power system signal to be measured according to the found optimal frequency estimation position. The present application can improve the efficiency, accuracy and robustness of the frequency measurement of the electric power system.

The invention relates to the technical field of temporary building energy conservation, in particular to a modular temporary building energy consumption prediction method and system and a medium, and the method comprises the following steps: obtaining basic information of a target building, including a geographic position and an enclosure structure thermal insulation parameter; according to the geographic position, determining a thermal climate zone to which the geographic position belongs, and selecting a corresponding reference energy consumption calculation formula; calculating an energy consumption adjustment coefficient according to the local climate data and the building characteristic parameters; and calculating a predicted energy consumption value of the target building based on the reference energy consumption and the adjustment coefficient. According to the method, the energy consumption prediction model and the economical efficiency analysis model are established, so that the energy consumption of the modular temporary building can be quickly and accurately estimated, an optimization scheme is provided, the energy consumption and carbon emission of the temporary building are effectively reduced, economical efficiency is considered, and a scientific basis is provided for energy conservation and carbon reduction of a construction site.

This application provides a positioning method, apparatus, medium, and electronic device for a movable mechanism. The method includes: acquiring a first initial roll angle, a first initial pitch angle, and a first initial heading angle of an inertial measurement unit coordinate system relative to a mechanism coordinate system; performing coordinate transformation on the first initial roll angle, the first initial pitch angle, and the first initial heading angle to obtain a second initial roll angle, a second initial pitch angle, and a second initial heading angle of the mechanism coordinate system relative to the inertial measurement unit coordinate system; solving an error function to obtain a second target pitch angle and a second target heading angle of the mechanism coordinate system relative to the inertial measurement unit coordinate system; and generating an installation angle based on the second target pitch angle and the second target heading angle for positioning. This application embodiment can accurately position a movable mechanism. This application embodiment can be applied to various scenarios such as mapping, autonomous driving, intelligent transportation, and assisted driving.

The invention relates to an underground explosion equivalent estimation method based on Lg wave seismic moments, which comprises the following steps: aiming at a specific region, carrying out theoretical seismic map simulation and inverting an Lg wave Q value by utilizing a frequency-wave number integration method, inverting an Lg wave seismic moment source on the basis, calibrating the relationship between the Lg wave seismic moment source and the seismic moments, and combining the Lg wave seismic moments obtained by observing data inversion and a seismic source model to estimate the underground explosion equivalent. An equivalent estimation method based on Lg wave seismic moments can be established; according to the method, the advantage that the Lg wave seismic moment can be quickly inverted through the source frequency spectrum relative to the source seismic moment is fully utilized, the underground explosion equivalent is quickly estimated by pre-calibrating the relationship between the two different sites and combining the seismic source model, and the calibration result considers different seismic source type combinations and is suitable for various conditions; when the Lg wave seismic moment inversion equation is solved, an L-M algorithm is adopted, a hysteresis factor is introduced, non-convergence during solving is avoided, and the stability of the algorithm is improved. And rapid estimation of the underground explosion equivalent in a specific region is realized.

The present invention relates to a tumor imaging genomics prediction system based on IVIM quantitative parameter analysis, comprising: an image acquisition module for acquiring different b The DWI images of the target part are formed by using the image registration module. b The DWI image with a value of 0 is used as a reference to align all DWI images; the image processing module inputs the aligned DWI image set into the IVIM parameter estimation model to obtain the IVIM quantitative parameter estimation value, and obtains the IVIM parameter image set according to the IVIM quantitative parameter estimation value; the lesion prediction module obtains the disease prediction result of the target part of the patient through the SVM prediction model based on the IVIM parameter image set. The above system solution can achieve fast and more accurate IVIM parameter estimation, truly reflect the movement of water molecules in the tumor, reflect tumor heterogeneity, and combine impactomics for accurate prediction.

The present invention belongs to the technical field of battery testing, and discloses a method and system for estimating the ionic conductivity of a solid electrolyte. The differential change curve of the impedance modulus time function to the impedance modulus is obtained according to the electrochemical impedance spectrum of the solid electrolyte, and the impedance limit that can distinguish the solid electrolyte impedance from the diffusion impedance is obtained in the curve, and the total impedance contributed by the solid electrolyte is obtained and used as the impedance of the solid electrolyte. The ionic conductivity of the solid electrolyte is estimated according to the obtained impedance of the solid electrolyte. The method is simple to test and operate, does not require model fitting or complex analysis of the data, and has low test cost. It has important application value in high-throughput screening of solid electrolytes and rapid performance evaluation.

The present invention relates to techniques for estimating molecular structures, and provides a method for calculating the similarity between two spectrograms by using not only 1DNMR spectrogram information but also 2D NMR spectrogram information, in which spectrograms of an estimated target material are compared with spectrograms of candidate materials, determining similar candidate molecular structures, and calculating the similarity between the two spectrograms using not only 1DNMR spectrogram information but also 2D NMR spectrogram information. Therefore, the molecular structure of the estimated target material is estimated. Further, when calculating the similarity, an accurate molecular structure of a complex aromatic material can be provided.