14results about How to "Quick estimate" patented technology

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 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 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 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 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 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 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 belongs to the technical field of optical fiber temperature measurement, and particularly relates to an overhead line composite optical fiber temperature measurement method, device and equipment and a medium. The method comprises the following steps: firstly, acquiring Brillouin gain spectrum data along the axial direction of an optical fiber; then, the Brillouin frequency shift is directly calculated by adopting a gravity center method, iterative fitting is not needed, and the processing speed is remarkably improved; further, an error estimation formula is obtained through theoretical derivation, and the measurement error is rapidly evaluated according to the sweep frequency center frequency, the frequency shift value and the line width; and finally, temperature distribution is demodulated based on the linear relationship between the frequency shift and the temperature, and a temperature measurement error is calculated in combination with a frequency shift error. The method solves the problem that the traditional method is difficult to balance among speed, precision and efficiency, realizes rapid and reliable temperature measurement with an evaluable result, and is suitable for occasions needing real-time monitoring, such as overhead lines.

The invention discloses a method for calculating the water entry slamming pressure of an open cavity in waves, relates to the technical field of ocean engineering, is used for predicting the water entry process of the open cavity, and comprises the steps of constructing a geometric model of the open cavity, constructing a wave field, and simulating the movement process of a target cavity entering the wave field and the movement process of the target cavity in the wave field. Constructing a time domain motion equation of the target cavity, solving the time domain motion equation of the target cavity by adopting a numerical integration method, and calculating a hydrostatic pressure component, an entry water impact dynamic pressure component, an in-cavity air fluctuation pressure component and a wave induction dynamic pressure component of the target cavity; and performing decoupling calculation on the water entry slamming pressure of the target cavity based on the four sub-components. According to the method, the coupling dynamic model of the wave field and the water entry process of the open cavity is established by combining a multi-phase coupling action mechanism, and the calculation precision of slamming pressure distribution and time history characteristics of the open cylindrical cavity at the water entry moment and in the subsequent process under the wave condition is improved.

The embodiment of the application provides a kind of fast estimation method, device, equipment and storage medium of wind resistance coefficient, comprising: the target vehicle windward area, the test mass of the target vehicle and the target vehicle sliding resistance coefficient are obtained;The target vehicle windward area, the test mass of the target vehicle and the target vehicle sliding resistance coefficient are input into wind resistance coefficient prediction model, and the wind resistance coefficient of the target vehicle is obtained.To realize fast and high-precision estimation wind resistance coefficient.