27807results about How to "Reduce mistakes" patented technology

The invention relates to a micro-interface enhanced reactor bubble scale structure-activity regulation and control model building method. The diameter dmax of the largest bubble of a micro-interface enhanced reactor and the diameter dmin of the smallest bubble of the micro-interface enhanced reactor serve as independent variables, the average diameter d32 of the bubble Sauter serve as a dependentvariable, and a numerical relationship is built; based on the Kolmogorov-Hinze theory, the relationship between the diameter dmax of the largest bubble of the micro-interface enhanced reactor, the diameter dmin of the smallest bubble and the parameters of the reactor is built. According to the method, the reactor bubble scale is associated with the structural parameter, the operation parameter andthe physical property parameter of the reactor by using specific numerical relationship, the numerical relationship has the guiding significance for the design of the reactor and can be applied to avariety of reactors, the versatility is good, by means of a bubble scale regulation and control model built through the method, by adjusting the structural parameter and the operation parameter of thereactor, and the maximization of energy efficiency and material efficiency in the reaction process can be achieved, or under the condition that reaction targets, energy consumption and material consumption are given, a high-efficiency reactor structure is designed.

The invention discloses a zero sample image classification method based on combination of a variational autocoder and an adversarial network. Samples of a known category are input during model training; category mapping of samples of a training set serves as a condition for guidance; the network is subjected to back propagation of optimization parameters through five loss functions of reconstruction loss, generation loss, discrimination loss, divergence loss and classification loss; pseudo-samples of a corresponding unknown category are generated through guidance of category mapping of the unknown category; and a pseudo-sample training classifier is used for testing on the samples of the unknown category. The high-quality samples beneficial to image classification are generated through theguidance of the category mapping, so that the problem of lack of the training samples of the unknown category in a zero sample scene is solved; and zero sample learning is converted into supervised learning in traditional machine learning, so that the classification accuracy of traditional zero sample learning is improved, the classification accuracy is obviously improved in generalized zero sample learning, and an idea for efficiently generating the samples to improve the classification accuracy is provided for the zero sample learning.

The invention discloses a regional depth edge detection and binocular stereo matching-based three-dimensional reconstruction method, which is implemented by the following steps: (1) shooting a calibration plate image with a mark point at two proper angles by using two black and white cameras; (2) keeping the shooting angles constant and shooting two images of a shooting target object at the same time by using the same camera; (3) performing the epipolar line rectification of the two images of the target objects according to the nominal data of the camera; (4) searching the neighbor regions of each pixel of the two rectified images for a closed region depth edge and building a supporting window; (5) in the built window, computing a normalized cross-correlation coefficient of supported pixels and acquiring the matching price of a central pixel; (6) acquiring a parallax by using a confidence transmission optimization method having an acceleration updating system; (7) estimating an accurate parallax by a subpixel; and (8) computing the three-dimensional coordinates of an actual object point according to the matching relationship between the nominal data of the camera and the pixel and consequently reconstructing the three-dimensional point cloud of the object and reducing the three-dimensional information of a target.

The invention discloses a calibration method of correlation between a single line laser radar and a CCD (Charge Coupled Device) camera, which is based on the condition that the CCD camera can carry out weak imaging on an infrared light source used by the single line laser radar. The calibration method comprises the steps of: firstly, extracting a virtual control point in a scanning plane under the assistance of a cubic calibration key; and then filtering visible light by using an infrared filter to image infrared light only, carrying out enhancement, binarization treatment and Hough transformation on an infrared image with scanning line information, and extracting two laser scanning lines, wherein the intersection point of the two scanning lines is the image coordinate of the virtual control point in the image. After acquiring multiple groups of corresponding points through the steps, a correlation parameter between the laser radar and the camera can be solved by adopting an optimization method for minimizing a reprojection error. Because the invention acquires the information of the corresponding points directly, the calibration process becomes simpler and the precision is greatly improved with a calibrated angle error smaller than 0.3 degree and a position error smaller than 0.5cm.

To decode a representation of a codeword that encodes K information bits as N>K codeword bits, messages are exchanged between N bit nodes and N−K check nodes of a graph in which E edges connect the bit nodes and the check nodes. While messages are exchanged, fewer than E of the messages are stored, and/or fewer than N soft estimates of the codeword bits are stored. In some embodiments, the messages are exchanged only within sub-graphs and between the sub-graphs and one or more external check nodes. While messages are exchanged, the largest number of stored messages is the number of edges in the sub-graph with the most edges plus the number of edges that connect the sub-graphs to the external check node(s), and/or the largest number of stored soft estimates is the number of bit nodes in the sub-graph with the most bit nodes.

The invention relates to a mechanism sealing controllable testing device that includes sealing system, driving system, end face specific pressure loading and servo feed back system, end face attrition torque and end face specific pressure testing system, film thickness testing system, leakage testing system, static loop temperature feedback system, medium temperature and pressure measuring system, experiment medium pressurizing recycling system, data collection and control system. The invention has wide application range, and would be researched under different conditions.

A synchronous quick calibration method of a plurality of video cameras in a three-dimensional scanning system, which includes: (1) setting a regular truncated rectangular pyramid calibration object, setting eight calibration balls at the vertexes of the truncated rectangular pyramid, and respectively setting two reference calibration balls at the upper and lower planes; (2) using the video cameras to pick-up the calibration object, adopting the two-threshold segmentation method to respectively obtain the corresponding circles of the upper and lower planes, extracting centers of the circles, obtaining three groups of corresponding relationships between circle center points in the image and the centres of calibration ball in the space, solving the homography matrix to obtain the internal parameter matrix and external parameter matrix and obtaining the distortion coefficient, taking the solved video camera parameter as the initial values, and then using a non-linear optimization method to obtain the optimum solution of a single video camera parameter; (3) obtaining in sequence the external parameter matrix between a plurality of video cameras and a certain video camera in the space, using the polar curve geometric constraint relationship of the binocular stereo vision to establish an optimizing object function, and then adopting a non-linear optimization method to solve to get the optimum solution of the external parameter matrix between two video cameras.

The invention provides a joint measurement method based on a laser radar and a binocular visible light camera to obtain accurate and dense three-dimensional information simply and efficiently. The joint measurement method comprises assuming that the laser radar is a camera device with a fixed internal reference; directly projecting three-dimensional point cloud data into a two-dimensional image, calculating rotation and translation relationships between the laser radar device and the binocular camera by using an image processing method and the matching between the two-dimensional images; creatively introducing an idea for obtaining a matrix norm and a matrix trace to solve a rotation matrix; finally fusing laser radar and binocular stereo vision point cloud data. The method not only can obtain an accurate position and attitude information, but also can reconstruct the special texture and feature information of a target surface, which has a high application value for spacecraft dockingand hostile satellite capture in the military field and workpiece measurement and unmanned driving in the civilian field.

A method for recognition of an input human motion as being the most similar to one model human motion out of a collection of stored model human motions. In the preferred method, both the input and the model human motions are represented by vector sequences that are derived from samples of angular poses of body parts. The input and model motions are sampled at substantially different rates. A special optimization algorithm that employs sequencing constraints and dynamic programming, is used for finding the optimal input-model matching scores. When only partial body pose information is available, candidate matching vector pairs for the optimization are found by indexing into a set of hash tables, where each table pertains to a sub-set of body parts. The invention also includes methods for recognition of vector sequences and for speech recognition.

The invention provides a finger-vein image quality evaluation method and system based on a convolutional neural network. The method includes: labeling the quality of finger-vein gray images, building a training sample set, and using the training sample set to train the convolutional neural network; inputting one optional gray image and a binary image into trained models, selecting the output of second full connection layers in two convolutional neural network models as the depth feature vectors of the input gray image and the binary image; connecting the two depth feature vectors to form a united expression vector, inputting the united expression vector into a support vector machine for training, and using a probability support vector machine to calculate the quality of a predicted finger-vein image. By the evaluation method and system, finger-vein image quality evaluation precision can be increased to a large extent, and the identification performance of a certification system can be improved.

The invention provides an active reliability analyzing and evaluating method for highly-reliable mechanical products. The active reliability analyzing and evaluating method for the highly-reliable mechanical products includes: firstly, establishing ultimate state functions of mechanical products, utilizing a Monte Carlo simulation method to produce sample points conforming to parameter distribution, utilizing a Kriging meta-model to simulate the ultimate state functions, improving simulation precision and confirming an optimal sampling radius by automatically updating DOE (design of experiment), constructing important sampling density functions, producing random sample points through the important sampling density functions, updating the DOE continually, then extracting radius random sample points obeying chi-square distribution, confirming failure probability and failure coefficient of variation of the mechanical products, and limiting whether updating finishes or not by the failure coefficient of variation so as to obtain reliability of the mechanical products finally. The active reliability analyzing and evaluating method for the highly-reliable mechanical products has the advantages of high efficiency, good robustness and high simulation precision, comprehensive design and analysis of rail wear life and reliability to spatial mechanisms are achieved, and the active reliability analyzing and evaluating method for the highly-reliable mechanical products is significant to reliability design technology engineering of complex mechanisms of aerospace equipment.

The invention discloses a vehicle speed detection method based on a target motion track. The method includes the steps of target segmentation, target tracking conducted on the basis of Kalman filtering and speed calculation, wherein the combination of an inter-frame difference method and a fixed threshold value method is mainly adopted in target segmentation, and a segmentation result is acquired; target tracking conducted on the basis of Kalman filtering is divided into the processes of mass center acquisition, motion model establishment, motion target feature extraction and state vector updating, and therefore the target motion track is acquired; a speed calculation method mainly refers to track related point information acquisition, mapping relation establishment, speed calculation and speed correction, the mapping relation establishment mainly refers to conversion from pixel coordinates in an image to actual distances, in other words, the actual distance, corresponding to an actual coordinate system, of each pixel point in the image is calculated, speed calculation mainly refers to calculation of related information provided by the vehicle track in the mode that the distances are divided by time according to a speed calculation formula and a result is corrected according to the actual condition.

The invention belongs to the field of satellite navigation and particularly relates to a terminal positioning track fitting method based on a Bezier curve. The terminal positioning track fitting method comprises: step 1, a curvilinear function of a third-order Bezier curve is as follows: two adjacent sampling points Pn and P(n+1) serve as the starting point and the final point of the third-order Bezier curve, namely P0=Pn, and P3=P(n+1); step 2, P1 is enabled to be equal to a control point Pn' of the Bezier curve of the sampling point Pn; step 3, P2 is enabled to be equal to a control point P(n+1)' of the Bezier curve of the sampling point P(n+1); and step 4, the control point Pn' of the Bezier curve of the sampling point Pn, the sampling point P(n+1) and the sampling point Pn and the control point P(n+1)' of the Bezier curve of the sampling point P(n+1) are substituted into the third-order Bezier curve to obtain: B(t)=Pn(1-t)3+3Pn' t(1-t)2+3P(n+1)'t2(1-5)+Pn+1t3, t belongs to (0,1), and the fitted curve function of the actual track of the positioning terminal can be obtained, and the function is an interpolation function of the function; and step 5, the step1, step2, step3 and step 4 are repeated to calculate the fitted curve function of the next pair of adjacent sampling points until the final sampling point.

The invention provides a power battery electric charge quantity estimation method. The method includes the following steps of firstly, obtaining the function relationship between the SOC and an open-circuit voltage through an open-circuit voltage method; secondly, measuring the initial value of the SOC; thirdly, sampling and obtaining the SOC estimated initial value of an unscented Kalman filter; fourthly, conducting Sigma point sampling of UT conversion of the unscented Kalman filter according to a battery state equation and an observation equation, obtaining an estimated value of the observation quantity, and estimating an SOC estimated value and a covariance of a power battery at the next moment. According to the method, the open-circuit voltage method and the unscented Kalman filter are used in cooperation for conducting SOC estimation, the estimation accuracy is high, the SOC initial value is obtained through the open-circuit voltage method, SOC estimation modification is conducted, the estimation accuracy is improved, and in the unscented Kalman filter non-linearization approximation process, errors are reduced, the calculation speed is high, and the SOC estimation efficiency is improved.

The invention provides a method for estimating a charge state of a power battery with relatively less errors, which includes the following steps: through fitting of measured data, a Ki curve of correction coefficient of charging-discharging efficiency at different rates, a Kw curve of the correction coefficient of the charging-discharging efficiency under different temperature as well as a Kc curve of the correction coefficient of actual electric quantity are obtained and a Kc value can be obtained through a historical record; according to the state of the power, the following formulas are applied: in the working state, Ct = (KCC0 + sigma KiIiti) Kw is applied; in the non-working state and when a self-recovery effect is completed, C = KWKCC0t is applied; in the non-working state and when the self-recovery effect is not completed, Ct = Cm is applied; Ki, Kw, Kc are called from the curves to obtain remaining capacity Ct at the moment of obtaining the power battery so as to complete the estimation of a SOC battery. The invention with easy industrial application of models is applicable to both working state and non-working state of the battery; the errors of the estimation result are relatively less and the relevant curves are established.

The invention belongs to the meteorological service technical field and relates to a rainfall prediction method, a rainfall prediction system and an electronic device. The method comprises the following steps that: a) radar maps of different heights in different time periods and meteorological information sequences in the corresponding time periods are extracted; b) a deep neural network-based rainfall prediction model is constructed; and c) the extracted radar maps and the meteorological information sequences are inputted the rainfall prediction model, time series analysis is performed on theinputted radar maps and meteorological information sequences through the rainfall prediction model, so that radar map space-time characteristics and meteorological information time-series features corresponding to the time periods are obtained, and rainfall prediction values corresponding to the time periods are outputted according to the radar map space-time characteristics and the meteorological information time-series features. According to the rainfall prediction method, the rainfall prediction system and the electronic device of the invention, long-term and short-term time series dependencies in the trend of the change of the radar maps over time are fully utilized; other meteorological information is incorporated; a variety of data sources are synthesized; and therefore, short-termfuture rainfall can be accurately predicted.

The invention discloses an Android device wireless fidelity (WiFi) indoor locating method based on a position fingerprint identification algorithm. The Android device WiFi indoor locating method based on the position fingerprint identification algorithm aims at solving the problems that when a terminal receiver works in a city with dense building clusters or indoors, signal strength is greatly reduced due to influence by buildings, thus locating accuracy is low and location even can not be completed. Based on the foundation of the traditional position fingerprint identification algorithm, a k-nearest neighbor (KNN) matching algorithm and a coordinate computing method based on weight are adopted so that the position of a point to be measured is obtained, errors brought by signal fluctuation is effectively reduced, the position of the terminal receiver can be accurately located, and reaction is fast. Compared with a tradition indoor locating method, the Android device WiFi indoor locating method based on the position fingerprint identification algorithm can accurately locate the position of a requester in the condition of a complex environment, and is fast in reaction, efficient, accurate and especially suitable for indoor position location of an Android device terminal.

The invention discloses a full automatic biochip detection system belonging to the clinical detection field of multi-marker biochips. The system adopts modular structure and comprises an automatic sample processing module, a reaction washing module, a detection module, a Tip head storage module, a reagent storage module, a biochip storage module, a sample storage module, a system base, an electric control box and a computer, the electric control box and all the modules are operated under the control of software, so as to realize the automatic sampling, the sample adding, the reaction, the washing, the detection and other processes. All the modules can work independently and can also be combined together and matched for work. The full automatic biochip detection system can overcome the shortcomings of the existing biochip detector and reduce the errors caused by human operation, and has stable and reliable detection result and good flexibility, so that the full automatic biochip detection system can not only greatly improve the detection efficiency, but also can be conductive to the accuracy of the detection result; the system has simple operation, therefore, the system is not only applicable to the scientific research and the applications of laboratories and hospitals, but also can be used for large-scale sample screening of large-scale hospitals and blood stations.

The invention discloses an integrated navigation system applied to a pilotless aircraft, which adopts a sensor comprising an inertial sensor, a radio altimeter, a communication module, a camera and the like, wherein the inertial sensor is used for acquiring motion acceleration and angular velocity of a carrier, and providing the motion acceleration and the angular velocity for an inertial navigation system and a vision navigation system in the unknown environment for setting up a system equation, thus further providing the current location information and matched trigger signals for scene matching navigation. The method integrates four combination ways which are inertial navigation, cellular wireless location navigation, vision navigation in the unknown environment and the scene matching navigation, and the four combination ways form each subsystem of the integrated navigation system and can be independently used for estimating the state of the aircraft; then, fault diagnosis and fusion estimation are carried out on the data output by the subsystems by a main filter, so that the accurate estimation of the state of the aircraft is obtained.

The invention belongs to the field of power converter control and relates to a model prediction control method of a voltage source type rectifier when a network voltage is unbalanced. The model prediction control method of the voltage source type rectifier when the network voltage is unbalanced comprises the steps of converting three-phase network voltage and a three-phase current into network voltage and a current which are under a two-phase static coordinate system through an abc / alpha beta coordinate, obtaining network positive sequence voltage and negative sequence voltage by carrying positive and negative sequence component separation of the network voltage under the two-phase static coordinate system, calculating reference values of active power, calculating current reference values of the rectifier under the two-phase static coordinate system, and carrying out model prediction current control and selecting an optimal on-off state. The model prediction control method of the voltage source type rectifier when the network voltage is unbalanced is capable of quickly and precisely tracing the current under the two-phase static coordinate and effectively eliminating fluctuation of direct current side voltage at the same time, power quality of the system is improved, a reliable network-connected operation of the rectifier when transient state network voltage is unbalance is achieved, and dynamics and stability of the whole system are improved.

The invention discloses a broadband signal DOA estimation method based on a co-prime array, and the method comprises the steps: S1, designing a co-prime array structure through an antenna; S2, carrying out the sampling and discrete Fourier transform of a broadband signal received by an antenna in the co-prime array, and obtaining a frequency domain signal output model; S3, calculating an autocorrelation matrix of the frequency domain signal output model, carrying out the vectorization of the frequency domain signal output model, and obtaining a new signal model; S4, carrying out the processing of the new signal model, and obtaining a spatial smooth covariance matrix of the broadband signal; Sa5, dividing a space domain grid, constructing a dictionary, carrying out the sparse representation of the spatial smooth covariance matrix through employing the dictionaries of a plurality of frequency points of the broadband signal, and forming a multi-measurement-vector sparse representation model of a plurality of dictionaries of the broadband signal; S6, achieving the arrival direction estimation of the broadband signal in a mode of solving a sparse inverse problem through the joint sparse constraint of the sparse representation coefficients of the plurality of dictionaries. The method can improve the estimation precision of the direction angle of the broadband signal under the condition of low signal to noise ratio, and reduces the direction finding error.