9results about How to "Avoid heavy computation" patented technology

This invention provides a radiometric calibration and temperature inversion method for a cooled infrared thermal imager, comprising: constructing a temperature calibration device, acquiring multiple calibration temperature points and their corresponding blackbody radiance to obtain corresponding datasets, acquiring two sets of response image grayscale value datasets to obtain a radiometric calibration model; plotting response curves to simultaneously solve for unknown parameters in the radiometric calibration model to obtain a near-range radiometric calibration model; using the modified radiometric calibration model for back-calculation to obtain the actual radiance of the target; pre-setting the constructed lookup table in the embedded processing unit of the infrared thermal imager to perform online temperature inversion output to obtain the absolute temperature of the measured target, and then outputting the absolute temperature of the measured target to a host computer display module. This invention can significantly reduce the calibration workload, enabling the infrared thermal imager to flexibly adjust the integration time and maintain high-precision temperature measurement in complex scenarios, significantly improving its engineering practicality and environmental adaptability.

The invention discloses a large-range collaborative navigation method for an extraterrestrial patroller, and relates to the field of computer vision, visual navigation and map splicing. The method comprises the following steps: performing significance analysis based on spectral residual for a right monocular camera, focusing on sight capture of a typical feature region, establishing a visual odometer model of inertial IMU pre-integration, and performing back-end optimization driven by a factor graph; establishing a plurality of extraterrestrial patroller similar region search models based on an improved bag-of-words model, introducing a similarity relative scoring function based on a norm form, setting a relative threshold value of a similarity suppression function, and obtaining an image overlapping region; according to the method, the calculation capability of an airborne computer is considered, a sparse feature point map and patroller pose splicing model is established, complete splicing of overlapped area maps is completed through splicing of small sparse feature point maps, and the splicing precision and the splicing efficiency are improved.

The invention relates to a VSP missing data reconstruction method and device based on a self-supervised deep learning model, and the method comprises the steps: inputting a VSP common detection point gather containing shot missing data into a deep convolutional neural network model; reconstructing the shot-lacking data by using a deep convolutional neural network model, and outputting a reconstructed complete VSP common detection point gather; wherein the deep convolutional neural network model is obtained by training in a self-supervised learning mode by adopting an original complete VSP common detection point gather in a target work area; according to the method, a self-supervised learning normal form is adopted, an existing complete gather data training model in a target work area is directly utilized, additional labeling or complex speed model construction is not needed, and the data preparation cost and dependence on prior knowledge are remarkably reduced; the trained model can perform end-to-end intelligent reconstruction on the input incomplete gather, the complete gather is quickly output, and the problems of complex iteration and large calculation amount in a traditional method based on a wave equation or matrix completion are avoided.

The invention belongs to the technical field of wind field feature analysis, and discloses a CFD-based complex mountain terrain wind field feature analysis method and system, and the method comprises the steps: obtaining mountain curved surface terrain data of a target site, and constructing a wind field model based on the mountain curved surface terrain data; setting a turbulence model, a boundary condition and a grid of the wind field model based on the wind field model; acquiring a plurality of feature observation points from the wind field model, and determining a change rule of the wind speed along with the height based on simulation data of the feature observation points; extracting wind speed and wind pressure characteristics of different characteristic observation points at different heights, determining a wind speed correction coefficient of a mountain curved surface based on a change rule of the wind speed along with the height, performing full-process simulation analysis on a complex mountain wind field through a wind field model, and converting mountain curved surface topographic data of a target field to obtain a mountain curved surface topographic data model; compared with traditional field measurement and wind tunnel tests, the cost is reduced, the method is not limited by weather and physical models, and continuous wind field information in the whole target area can be efficiently obtained.

The application discloses a kind of autonomous integrity monitoring methods for satellite navigation receiver, convolutional neural network is used in the present application and the slope weighted least square RAIM combined algorithm of optimization.The combined algorithm includes: first, the characteristic slope of satellite is calculated to select satellite, after eliminating the satellite with the largest characteristic slope, when the number of satellites is greater than or equal to 5, the optimized slope weighted least square RAIM algorithm is used, and the corresponding weight matrix is constructed based on the RAIM algorithm based on least square residual;When the number of satellites is less than 5, data regression learning prediction is carried out using convolutional neural network, to determine whether there is a faulty satellite.The present application has the function of more accurate monitoring whether satellite signal is faulty, to achieve fault monitoring and troubleshooting, so as to realize the autonomous integrity monitoring of satellite navigation receiver.

The invention provides a range radar device based on ultra-wideband resolvable chaotic synchronization, which relates to the technical field of radar range finding and comprises a first ultra-wideband resolvable chaotic signal generation circuit unit, a second digital excitation circuit unit, a third ultra-wideband resolvable chaotic signal synchronization circuit unit and a fourth wideband related receiving circuit unit. According to the invention, the problem of radar real-time ranging with high resolution and high measurement signal-to-noise ratio is solved, high-resolution real-time correlation ranging is realized through the generation circuit and the receiving circuit of the ultra-wideband analyzable chaotic signal, correlation receiving is completed only by simulating a matched filter, and high-sampling-rate data pressure and large correlation calculation amount are avoided. In addition, a receiving end can analyze synchronization of chaotic signals through driving of a digital excitation circuit, and chaotic echo signals are accurately reconstructed to improve the signal-to-noise ratio of distance measurement.

The present application relates to a kind of high voltage direct current transmission inverter side receiving end system small signal stability evaluation method, system, electronic equipment and computer readable storage medium, wherein method includes: gathering commutation bus steady-state operating parameter to construct inverter side nonlinear control equation group;Small disturbance response characteristics are extracted at system steady-state operating point, and linear equation group is established;Linear equation group is decoupled in combination with feedback control loop parameter, and aggregated to build transfer function admittance model;Based on the model, time-domain dynamic response curve is obtained, and the small signal stability evaluation index of system is output.The present application avoids complex electromagnetic transient modeling process, can intuitively, accurately reflect the time sequence dynamic characteristics of system under actual power grid fluctuation, greatly improve the efficiency of small signal stability analysis and evaluation of direct current transmission system.

The invention discloses a two-stage compression denoising imaging method for a large-area array Geiger mode APD (avalanche photo diode). The method comprises the following steps: intercepting photon events in a pre-sampling time window at the front part of a data block to carry out global histogram statistics, fitting and estimating time domain characteristics of background noise based on Poisson distribution, screening and compressing full-frame data, and eliminating most noise; carrying out local joint histogram statistics and peak value extraction on the compressed data based on a pixel space neighborhood, and reconstructing a preliminary distance image and a preliminary intensity image; if the effective data in the neighborhood of the data meets the flat area condition, standard median filtering is executed; otherwise, starting a robust filtering algorithm based on absolute median difference MAD for processing. According to the method, the cooperation of front-end data efficient compression and rear-end accurate denoising and edge preserving is realized, and the method has the advantages of high compression ratio, high adaptability and excellent imaging quality, and is particularly suitable for real-time three-dimensional imaging of a large-area-array GM-APD laser radar system.

The application discloses a method for measuring catalyst pore defects, which comprises the following steps: mixing molten paraffin with a catalyst, stirring and ultrasonic dispersing simultaneously; rapidly cooling the mixture of the paraffin and the catalyst by using liquid nitrogen; analyzing the three-dimensional structure of the catalyst by using X-ray computed tomography; processing the three-dimensional scanning original data by using data processing software, and the program is sequentially median filtering, threshold segmentation, boundary particle removal, filling the catalyst image holes by using a morphological hole filling algorithm, particle marking and screening, taking an image difference set, and statistically calculating data, and finally obtaining the catalyst pore rate. Compared with the traditional measurement method, the method can more accurately observe the catalyst structure from the three-dimensional angle, and provides data for the manufacture and evaluation of the catalyst.