783results about How to "Verify feasibility" patented technology

The invention provides an underactuated autonomous underwater vehicle (AUV) adaptive trajectory tracking control device and a control method. The practical positions and the course angles of an AUV which are acquired to a measurement element (3) and reference positions and reference course angle information which are generated by a reference path generator (1) are converted through a diffeomorphism converter (6) to obtain new state variables, then the new state variables and speed and angular speed information which is acquired by a sensor (5) are transmitted to a parameter estimator (11) anda longitudinal thrust and course changing moment controller (14), and a control command is obtained through resolving to drive an actuating mechanism to adjust the longitudinal thrust and the course changing moment of the AUV. By using the underactuated AUV adaptive trajectory tracking control device, the inertial mass parameters of the AUV and hydrodynamic damping parameters are not required to be known and the goal of arriving at designated positions at designated time according to designated speed is realized. Since the AUV considered in the invention is underactuated, the energy consumption and the manufacturing cost of a system can be reduced, the weight of the system can be reduced and the propulsion efficiency can be improved.

The invention relates to an electric-automobile-contained micro electric network multi-target optimization scheduling method. The method is characterized by comprising steps that, 1), a mode of access of an electric automobile to a micro electrical network is determined, discharging and charging load distribution characteristic superposition of a single electric automobile under different access modes is carried out to obtain discharging and charging load distribution characteristics of the electric automobile; (2), the electric automobile is taken as a micro electric network scheduling object which is added for electric network optimization scheduling, and an micro electric network scheduling model in consideration of large-scale electric automobile access is established according to the discharging and charging load distribution characteristics of the electric automobile; and 3), a particle swarm optimization algorithm based on the automatic recombination mechanism is employed to solve the micro electric network scheduling model in consideration of large-scale electric automobile access, economical efficiency of micro electric network scheduling under various scheduling strategies is compared and analyzed, and thereby the optimum scheduling strategy is obtained. Compared with the prior art, the method further has advantages of comprehensive consideration and effective and feasible performance.

The invention discloses an under-actuated surface vehicle trajectory tracking control system based on a self-adaptive fuzzy observer. A sensor module collects position and course information y of a surface vehicle and outputs the position and course information y to the self-adaptive fuzzy observer; the self-adaptive fuzzy observer receives output of a controller, obtains position and heading estimation, speed estimation, slow varying disturbance force estimation and unknown nonlinear term estimation (please see the expressions in the specification) and respectively transmits the position and heading estimation, the speed estimation, the slow varying disturbance force estimation and the unknown nonlinear term estimation to a trajectory tracking error generator and the controller; a guide system obtains expected speed and accelerated speed information in a hull coordinate system through calculation and respectively transmits the expected speed and accelerated speed information to the trajectory tracking error generator and the controller; the trajectory tracking error generator obtains error information of all states of trajectory tracking and transmits the error information to the controller; the controller calculates a longitudinal thrust and course changing torque control instruction of the current moment and transmits the control instruction to a thrust system, and the thrust system executes the control instruction. The under-actuated surface vehicle trajectory tracking control system can perform fast tracking under the conditions that only the position and the heading angle are measurable and a model has indeterminacy.

The invention provides a method for precisely editing a genome DNA sequence. A TALEN, CRISPR/Cas9 and other gene targeting technologies and homologous recombination technologies are utilized in a combined mode for precisely editing the genome DNA sequence. According to the method, the technical problem that in the prior art, a specific sequence cannot be deleted is solved, the specific base sequence can be seamlessly inserted or deleted in a fixed point mode, and seamless free modification of the genome DNA sequence of eukaryocyte is achieved for the first time.

The invention relates to an RGB-D image classification method and system. The method comprises the steps of: S1, utilizing a convolution neural network (CNN) to process a source RGB image and a Depth image respectively, and extracting low level characteristics; S2, utilizing a recursion neural network (RNN) to carry out feedback learning on the image low level characteristics, and extracting image middle level characteristics; S3, adopting a block interior constraint dictionary learning method, carrying out characteristic set sparse expression on the image middle level characteristics, and obtaining high level characteristics of the RGB-D images; and S4, inputting the high level characteristics of the RGB-D images into a linear SVM to complete the classified identification of the RGB-D images. According to the invention, automatic characteristic extraction of the images is realized, learning RGB-D image characteristic expressions can effectively distinguish classification of noise data from high similarity images, and the classification precision of the RGB-D images is improved; in addition, the linear SVM is utilized, and the image classification speed is improved.

The invention relates to a system and a method for verifying visual autonomous landing simulation of an unmanned aerial vehicle. Virtual reality technology and visualization technology are utilized, a real unmanned aerial vehicle flying environment is simulated, immersion-type sense of reality is provided, the problem of visual simulation and camera simulation of autonomous landing of the unmanned aerial vehicle is solved, a visual landing algorithm and VegaPrime are combined, and data needed for visual landing navigation are calculated and displayed in real time through multichannel demonstrating of the whole landing period. Simulation results show that by the system, landing landmarks can be effectively detected, estimated values of poses can be visually displayed in real time, a function of simulation verifying is realized, and a good simulation platform is provided for actual engineering application.

The invention provides a fault line selection method of a low current grounding system using a time-frequency atom decomposition theory. The method comprises the following steps of: based on the time-frequency atom decomposition theory, performing sparse decomposition on zero-sequence current data in a Gabor over-complete dictionary, and then obtaining matched attenuation sinusoidal quantity atoms through optimizing and solving relevant parameters. By the time-frequency atom decomposition method, the disturbance characteristics such as start/stop moments, amplitudes, frequencies and change rules of fundamental wave and each subharmonic can be exactly obtained, and interference signals can be effectively filtered. Energy entropies of the atoms decomposed by time-frequency atoms are arranged from large to small; except from the zero-sequence transient current fundamental wave atom, atom phase angles (polarity) similar with zero-sequence current frequency of each line are compared; if the atom phase angle (polarity) similar with the zero-sequence transient frequency of the line is opposite to that of other lines, the line is the fault line; and if the atom phase angle (polarity) of each line is the same, the fault is bus fault, and the fault line is determined by the comparison result of each frequency phase angle.

An autonomous mission planning method for earth remote sensing satellites with multiple planning modes. First, the Earth observation targets to be planned are selected, so that a task set to be plan is obtained, and the Earth observation targets included in the planning task set are preprocessed, and then according to the task set to be planned after preprocessing, a long-period pre-coarse missionplan scheme sequence is obtained by carrying out long-period pre-coarse mission planning, and finally, short-period local window rolling planning is carried out on the long-period pre-coarse missionplanning scheme sequence according to the real-time updated environmental information and satellite maneuverability, and the emergency mission dynamic planning is carried out according to the high-priority ground emergency observation mission. The long-period pre-coarse mission planning scheme sequence is obtained by carrying out long-period pre-coarse mission planning.

The invention relates to an active power distribution network transient state real-time simulation system designing method based on an FPGA. The active power distribution network transient state real-time simulation system designing method can be implemented in an off-line simulation environment and an on-line simulation environment in a dividing mode, the off-line simulation environment is responsible for calculating the total clock period number-n<total> and simulation using time-t<total> calculated in each time step, the simulation step size deltat is set according to the real-time simulation using time-t<total>, relevant parameters calculated according to the simulation step size deltat and the read basic parameter information are uploaded to the on-line simulation environment based on the FPGA. Real-time simulation calculation is completed in the on-line simulation environment, the simulation state is controlled through a finite-state machine, each time step includes the steps of historical item current source column vector calculation of all elements, total historical item current source column vector formation of the elements and linear equation system solving and updating of the elements, and the historical item current source column vector calculation step of the elements and the updating step are completely independent and can be processed in a concurrent mode. According to the active power distribution network transient state real-time simulation system designing method based on the FPGA, the real-time performance of the transient state simulation process of the whole system is guaranteed, and the good feasibility and the good applicability are achieved.

The invention discloses an analysis method of high-speed compressible supercavity flow characteristics and belongs to the field of fluid mechanical engineering. The analysis method comprises the stepsas follows: step 1, establishing a geometric model; step 2, performing mesh division on the geometric model established in step 1 and a fluid computational domain; step 3, setting boundary conditionsand a computing method; step 4, performing secondary development through CFD software to realize compressible correction of physical attributes of water; step 5, conducting numerical computation analysis on the high-speed compressible supercavity flow characteristics; step 6, performing numerical simulation analysis and comparing a numerical simulation result with an experiment result to verify accuracy and feasibility of the analysis method. The high-speed compressible supercavity flow law and mechanism can be revealed, so that a theoretical foundation is laid for structural design of underwater high-speed navigation bodies, and the actual application engineering problems of the high-speed navigation bodies can be solved.

The invention relates to a frictional wear CAE (Computer Aided Engineering) analysis-based mold optimization method, and belongs to the technical field of stamping dies of automotive structural parts. The method comprises the following steps: (1) establishing a mesh model and determining a material model of a plate and a mold and an Archard wear model; (2) defining conditions such as a material parameter, a motion parameter, a constraint condition, simulation steps and working environment parameters by combining actual working conditions; (3) performing simulation calculation under the conditions defined in the step (2) to obtain a plate forming result and a model wear result; (4) changing a mold hardness parameter, a mold material parameter and the motion parameter respectively under the condition that other simulation conditions are not changed to perform calculation so as to obtain wearing capacity of the mold and analyze the influence of different parameters on mold wear; (5) supposing the mold wear every thousand times as a constant value, predicting service life before mold repair; (6) obtaining actual wear after the mold wear in production through a test method and verifying the feasibility of the CAE analysis method.

An information channel and power combined self-configuration method for APs (Access Points) in wireless local area network comprises the steps as follows: the area where the APs to be configured are located is selected as a local network, and the local network is divided into a plurality of grids according to practical conditions; each AP sends out a self-configuration request to a server and simultaneously reports the position coordinate of the AP and the scanned frequency spectrum use information of the ambient environment of the AP; the server analyzes the positions and the ambient environments of the APs according to the self-configuration requests of the APs, and allocates information channels and power parameters to the APs to be configured in combination with the use conditions of AP information channels in neighbor cells under the premises of meeting the coverage rate requirement and minimizing same frequency interference, that is, first the signal energy of each grid is estimated according to a path loss empirical model to learn the network coverage condition, and then the information channel and the power parameter eventually configured for each AP is obtained through calculation based on the principle that the energy efficiency ratio is highest, and are sent to the AP to be configured. The method provided by the invention is quick and effective, guarantees the region coverage requirement, avoids same frequency interference to the maximum extent and guarantees that the energy efficiency ratio of the network is highest.

The invention provides an obstacle avoidance method for soft landing of an object outside the earth under a multi-obstacle constraint environment, and belongs to the technical field of navigation, guidance and control. The invention provides an improved optimum soft landing guidance method based on convex optimization for the problem of optimum guidance under the multi-obstacle constraint environment on the basis of the previous achievements. The method is characterized by, to begin with, establishing an optimal second-order cone programming model without obstacle constraint, and standardizing the model; then, carrying out analysis modeling on bulge obstacles on the surface of the Mars, and carrying out linear conversion to enable nonconvex constraints to be converted into convex constraints; fusing an obtained bulge obstacle mathematical model into second-order cone programming problems, and establishing a complete optimal second-order cone programming model with the obstacle constraints being taken into consideration; and finally, verifying the correctness of the algorithm through simulation analysis of three different types of obstacle constraints. The method can be applied to the study of lunar soft landing; the simulation result shows that the new algorithm realizes effective avoidance of three-dimensional space obstacles; available space for flying above and surrounding the obstacles is utilized reasonably; and fuel minimization is met simultaneously.

The invention discloses a modular multi-level current converter passivity modeling and control method which mainly comprises the following steps: step 1, a modular multi-level current converter passivity mathematic model is established, and an equalization state-space equation within a switching period is obtained; step 2, a modular multi-level current converter energy forming method algorithm model based on the equalization state-space equation is established, and a passive system from an input state variable Xi to an output state variable X is defined; step 3, a current converter damping injection algorithm model is established; step 4, a current converter control model based on all module switching functions is established. The modular multi-level current converter passivity modeling and control method has the advantages that stabilized and balanced control over capacitance and voltages on the direct current sides of upper bridge arms and lower bridges arms and quick tracking control over currents on the alternating current sides of all the bridges arms can be realized rapidly, the defects of a traditional modular multi-level current converter control strategy are overcome, and a feasible means is provided for the design of a control strategy of a flexible direct current transmission system.

The invention discloses a traffic sign detection and identification method based on collaborative bionic vision in a complex city scene, which includes the following steps: A, obtaining multiple to-be-detected images in a continuous scene; B, obtaining a cluster collaboration map of the to-be-detected image set; C, obtaining an attention saliency map of each to-be-detected image; D, obtaining a collaboration saliency map corresponding to each to-be-detected image; E, locating a sign ROI (Region of Interest); F, carrying out two-level biologically inspired transformation on the sign ROI by using a forward channel; and H, using a feature transformation map and traffic sign template images pre-stored in a database to carry out Pearson correlation calculation to complete the identification ofthe to-be-detected images. In the method, visual processing of a target by the human brain is simulated, and bottom-up visual processing and top-down visual processing processes are integrated. The collaborative nature of global images is considered, so that image location is accurate, and the robustness of identification is strong.

The invention relates to a the field of biomedicine, and specifically relates to a model for predicting prognosis of lung squamous cell carcinoma with seven genes as biomarkers, and an establishing method thereof. The model for predicting prognosis of lung squamous cell carcinoma includes seven genes related to prognosis of lung squamous cell carcinoma: CSRNP1, CLEC18B, MIR27A, AC130456.4, DEFA6,ARL14EPL and ZFP42, wherein expressions of CSRNP1 and CLEC18B are positively correlated with a survival rate while expressions of MIR27A, AC130456.4, DEFA6, ARL14EPL and ZFP42 are negatively correlated with the survival rate. The model for predicting prognosis of lung squamous cell carcinoma provides a plurality of genes as biomarkers, and improves the prognosis sensitivity and accuracy for predicting lung squamous cell carcinoma, thereby reducing mortality and local recurrence rate in patients with lung squamous cell carcinoma, and improving the prognosis of patients through the risk prediction model.

The invention features: less energy expenses, less complexity, and compensation function for the drift and offset. It uses PLL (phase locked loop) principal and a single-way broadcast synchronous mechanism to scheme out a solution which simultaneously has the compensation function for the drift and offset and the time synchronization function of radio sensor network.

The invention discloses a virtual debugging system based on an OPC UA industrial communication protocol. Modules of the virtual debugging system are mainly divided into a data acquisition layer, a data interaction layer and a simulation equipment layer. The data acquisition layer comprises an industrial robot, a PLC and an OPC UA acquisition module; the data interaction layer comprises a data processing module, a Redis database module and an interaction interface module; the simulation equipment layer comprises a RoboDK simulation robot and a RoboDK simulation machining center; the data acquisition layer acquires output data of the PLC and the industrial robot through an OPC UA protocol, transmits the data as input to the data interaction layer, and writes the data transmitted by the datainteraction layer into equipment; the data interaction layer transmits data into the simulation equipment layer according to a data address configured by the interaction interface module and transmitsthe data of the simulation equipment layer to the data acquisition layer; the simulation equipment layer transmits data of the data interaction layer to the simulation model through an API, and transmits a signal of simulation equipment to the data interaction layer; and the system completes a virtual debugging function by controlling input and output of the simulation equipment.

The invention discloses an underwater acoustic communication method for simulating a dolphin whistle signal via segmented LFM signals. According to the property that the frequency of the dolphin whistle signal changes with time, a plurality of LFM signals are segmented and combined to simulate the dolphin whistle signal, and a BOK method is used for achieving information modulation on the LFM signals to achieve bionic underwater acoustic communication modulation based on the dolphin whistle signal and the LFM signals. The central frequency and modulation frequency of each segment of LFM signals in balanced receiving data are estimated at a receiving end and are demodulated according to a dolphin whistle signal sample adopted during modulation to obtain demodulation information. The underwater acoustic communication method for simulating dolphin whistle signal via segmented LFM signals can be used for achieving bionic simulate underwater acoustic communication with high reality through a single linear frequency modulated signal and enhancing the communication imperceptibility and practicability.

The invention discloses a capacitor coupling noncontact conductance measurement device and method. The device comprises an alternating-current excitation source, an insulated measurement pipeline, an excitation electrode, a detection electrode, a range resistor, a virtual inductor, a differential amplifier module and a signal processing module, wherein one end of the virtual inductor is connected with the range resistor, while the other end is grounded, meanwhile, two ends of the range resistor are connected with the differential amplifier module. The virtual inductor substitutes an actual inductor, thus effectively overcoming the adverse effect of a coupled capacitor on the measurement result according to the series resonance principle. The virtual inductor is a grounding inductor, and compared with a floating inductor, the virtual inductor is good in working stability and simple in circuit structure; compared with an actual inductor, the virtual inductor capable of adjusting the equivalent inductance value reduces the requirement for the frequency of the excitation source. In addition, different from a noncontact conductance measurement method adopting a current method, the capacitor coupling noncontact conductance measurement method adopts a voltage method to obtain the equivalent conductance value of measured conductive fluid, thus providing helpful reference for solving the conductance measurement problem of conductive fluid in a pipeline.

The invention discloses a deep learning-based face recognition and face verification supervised learning method. The method comprises the following steps: a soft maximum loss function is used to increase a between-class distance for full connection layer output characteristics of a convolutional neural network model, a center is learnt for the depth characteristics of each class through a centralloss function, a super parameter is used to balance the two functions to thus jointly supervise the learning characteristics; backward propagation of the convolution neural network model is calculated, a stochastic gradient descent algorithm based on minimum batch processing is adopted to optimize the convolutional neural network model, and a weight matrix and the depth characteristic center of each class are updated; and after the depth characteristics are subjected to principal component analysis and dimension reduction, the cosine distance between each two characteristics is calculated to calculate a score, wherein the score is used for target matching in nearest neighbor and threshold comparison, and a face is recognized and verified. The identification ability of the neural network learning characteristics can be effectively improved, and a face characteristic recognition and face verification mode with robustness is acquired.

The invention provides a small binocular stereoscopic vision ranging system. The system comprises calibrating cameras (1), an image acquiring module (2), an image preprocessing module (3), a feature extracting module (4), an image stereoscopic matching module (5) and a three-dimensional rebuilding ranging module (6). The system is characterized in that the modules are sequentially connected; the two cameras are used for synchronously acquiring two images; the images are preprocessed to inhibit noise and highlight usable information; the preprocessing of the image includes the following steps: 1, performing grey processing on the images to reduce information contents of the images; 2, performing smoothing filtering on the images through a gaussian filter to remove the influence of noise on the experiment; 3, detecting the image contours through a canny edge detection operator so as to guarantee simple, convenient and clear angle point detection; 4, guaranteeing clear image features and removing small textures and noise by an algorithm of corrosion and expansion. According to the system, the images are preprocessed to verify the feasibility of binocular ranging.

The invention discloses a regulation and control method for improving transient frequency stability of a low-voltage micro-grid, and provides a control strategy for improving transient frequency response for the problem of transient impact on a system due to quick frequency change caused by disturbance of the low-voltage micro-grid, such as sudden load change. According to the method, on the basis of a virtual synchronous power generator model, an electrical angular speed deviation delta omega and a virtual damping coefficient D are taken as regulating indexes for P/omega droop control in an isolated island running state of the low-voltage micro-grid, the low-voltage micro-grid adopts different droop coefficients under different frequency deviation conditions, the impact on the system caused by transient response of an inverter after disturbance is reduced, and the frequency change rate is delayed; meanwhile, a secondary frequency modulation module for Q-omega and Q/T coordinated control is designed, so that no-deviating frequency regulation can be realized, control reference voltage can be provided for the inverter, and power oscillation is inhibited; the method is suitable for reducing the influence of the frequency on the system due to quick change under the circumstance that the low-voltage micro-grid is disturbed by sudden load change, state transition and the like, and is favorable for stable running of the low-voltage micro-grid.

The invention discloses an eye tracking method for human-computer interaction of a mobile device. The system is moderately comfortable, and has high precision and robustness, and high feasibility and effectiveness. The system comprises an eye image processing layer, an eye feature detection layer, an eye data calculation layer and an eye interactive application layer. The eye image processing layer comprises image acquisition and image preprocessing, namely, filtering or binarization. The eye feature detection layer comprises pupil detection, pupil location, pupil edge fitting, Pu Chin spot detection and template matching. The eye data calculation layer comprises point of fixation coordinates, pupil-conea reflection vector, point of fixation calibration, other data and pupil diameter. The eye interactive application layer comprises region of interest selection or switching, and specific interactive application.