41results about How to "Does not increase the amount of calculation" patented technology

The invention provides a power lithium battery thermal runaway fault classification and risk prediction method and system. The system comprises a module-level power battery model fault injection mode, a random fault generation and labeling mode, a power lithium ion battery fault multi-classification model based on a deep learning method and a transfer learning method for applying the model to a real vehicle. According to the invention, the real fault condition of the battery can be accurately expressed and transferred to the specific real vehicle working condition. The trained deep learning algorithm model can be successfully deployed in a real vehicle environment through mathematical processing and code conversion, faults are diagnosed in real time, the additional calculation amount of a battery management system is not increased, and high estimation precision is achieved.

The invention discloses digital substation testing simulation method. In the method, an IEC61850 standard digital dynamic testing simulation technology-based substation system testing method is adopted, namely a substation simulation model is established, and the actual motion is simulated for system closed-loop testing so as to detect the dynamic characteristics of a device to be detected. For the integrated design of the system, a frame structure consisting of a PCI board card and a multi-CPU desktop is adopted, and a system simulation testing device consisting of the multi-CPU desktop, a PCI bus-based IEC61850 communication card and a small signal and switching value interface card is established, wherein the multi-CPU desktop is a system control platform, and is used for performing processing such as drawing, simulation computation, man-machine interaction and the like; the PCI bus-based IEC61850 communication card provides a plurality of optical Ethernet ports to connect a plurality of protective devices and control equipment; and the protective devices receive MU data of the communication card, and the generated information such as switch position change and the like is returned to the desktop through the communication card to participate in electromagnetism transient calculation for the simulation model.

The invention discloses a simplified calculation method for dynamic windage yaw of an iced conductor. The simplified calculation method comprises the following steps: solving an equivalent static windload of the iced conductor based on a gust load envelope line method (GLE); instroducing A height difference correction coefficient, so that the problem that a rigid straight rod method is inaccuratein gravity load estimation when the height difference of a line hanging point is large is solved; Taking the circular-section ice-coated wire as an example, carrying out verification and parametric analysis on the effectiveness of the simplified calculation method by adopting a time domain method to obtain a change rule of the windage yaw angle of the ice-coated wire along with wind speed, ice coating density and ice coating thickness. According to the calculation method, the pulsation effect of the wind load can be accurately considered, excessive calculated amount cannot be increased, calculation errors of the gravity load of the wire caused by large height difference of line hanging points are avoided, and the calculation method is suitable for batch analysis of multiple parameters such as the icing shape, density, thickness and aerodynamic coefficient of the wire.

The invention discloses a target trajectory prediction method based on Kalman filtering multi-motion model switching. The method comprises the following steps: establishing a Kalman filtering multi-motion model; collecting motion information of the target in a period of time during a motion period, wherein the motion information at least comprises a target initial coordinate, a target real-time speed and a target real-time acceleration; obtaining the motion state of the target according to the motion information of the target, and switching the Kalman filtering motion model according to the change of the motion state, wherein the motion state at least comprises deceleration straight movement, constant-speed straight movement, acceleration straight movement, deceleration lane changing, constant-speed lane changing and acceleration lane changing; and substituting the motion information of the target into different Kalman filtering motion models which are switched according to the motion state change, and calculating to obtain a prediction track of the target. According to the invention, the target is tracked by using the multi-motion model, and the estimation precision of the filter is improved.

The invention discloses a millimeter wave radar two-dimensional angle calculation method, a millimeter wave radar two-dimensional angle calculation device and related equipment. The millimeter wave radar two-dimensional angle calculation method comprises the steps of selecting a plurality of virtual array elements from a target virtual array to form three groups of target array elements; based on the echo data matrix of each virtual array element in each group of target array elements, determining an angle set of each target in a corresponding direction, and obtaining a first angle set of each target in a horizontal direction, a second angle set of each target in a vertical direction and a third angle set of each target in an inclined direction; and finally, determining the angle of each target based on a preset echo signal calculation formula, the first angle set, the second angle set and the third angle set. According to the method, calculation is carried out by only adopting part of virtual array elements, calculation of unnecessary information is reduced to a great extent, the calculation amount is not increased by increasing the number of the array elements in the target virtual array, the calculation process is simple, and two-dimensional angle estimation of the target angle can be efficiently completed.

The invention provides a power lithium battery thermal runaway fault classification and risk prediction method and system, including: a module-level power battery model fault injection method, a random fault generation and labeling method, and a power lithium-ion battery based on a deep learning method A multi-classification model for faults and a transfer learning method for applying the model to real vehicles. The invention can accurately express the real fault condition of the battery, and migrate to the specific actual vehicle working condition. The trained deep learning algorithm model can be successfully deployed in the real vehicle environment through mathematical processing and code conversion, and can diagnose faults in real time without adding additional calculations to the battery management system, while achieving high estimation accuracy.

The invention discloses a polar coordinate Newton method load flow calculation method suitable for research purposes, and provides a Newton method load flow calculation method which is easy to modify and maintain for researchers performing further research on the basis of polar coordinate Newton method load flow calculation. For a power system with n nodes, node numbers are irrelevant to node types, a Jacobian matrix for load flow calculation is stored according to (2n) * (2n), elements of rows corresponding to delta Q and columns corresponding to delta U of PV nodes are 0, elements of rows and columns related to balance nodes are 0, but diagonal elements are not reset, and original calculation values are reserved. Therefore, a linear equation solving function with excellent performance provided by a programming language can be used for solving a correction equation for load flow calculation, the programming difficulty is reduced, the calculation speed is improved, and the reliability of the algorithm is ensured. Implementation examples show that the correction equation can be solved by using a linear equation solving function provided by a programming language, the load flow calculation speed is increased, and the programming difficulty is reduced.

The invention discloses a virtual reality-based space point mapping method of applying an anti-distortion grid. The method is characterized by changing a drawing time sequence of a gaze white point, and drawing the gaze white point in an asynchronous timewarp (ATW) thread. The method is based on asynchronous timewarp and other frame chasing algorithms, carries out deep optimization on drawing of the gaze white point on the basis of the algorithm, and will not increase a calculation amount on a current mainstream mobile-VR solution and also does not need to modify workflows of the current ATW and other frame chasing algorithms while the gaze white point can be smoothly drawn.

The invention provides a water sound frequency hopping communication method for linear modulation signal modulation and demodulation, and relates to a water sound frequency hopping communication. The water sound frequency hopping communication method comprises the following steps: carrying out source encoding on original information so as to obtain compressed digital signals; carrying out channel coding; using data obtained by the channel coding as a linear modulation signal control code; controlling to generate a linear modulation signal according to a frequency hopping sequence as a carrier for modulation, so as to obtain modulation signals; carrying out D / A (Digital / Analogue) conversion and power amplification on the modulation signals; converting the modulated signals into sound waves to spread in an ocean underwater acoustic channel through a transmission energy converter; receiving and converting acoustic signals spreading in the ocean underwater acoustic channel into electric signals through the receiving energy converter; obtaining stimulation signals through front amplification and band-pass filtering; carrying out A / D (Analogue / Digital) conversion on the received stimulation signals; after detecting that the digital signals after the A / D conversion are synchronous, carrying out linear modulation signal demodulation center frequency and demodulation frequency to obtain demodulation data; and carrying out channel decoding on the demodulation data; and carrying out source decoding on the digital signals to obtain information.

The invention proposes a method for compressing and calculating a hologram by using a quantum neural network with optimized initial weight, and belongs to the technical field of compression and transmission of a calculation hologram. On the basis of compressing and transmitting computational holograms in the quantum BP neural network, the method uses the computational hologram training set to pre-train to obtain the optimized initial weight of the quantum BP neural network, and accelerates the convergence process of the pre-trained network by setting the pre-trained parameters to randomly initialize the variance. , and then use the optimized initial weights obtained by pre-training to perform secondary network fine-tuning training for the given holographic compressed data, and at the same time dynamically adjust the network learning rate during the optimization process to accelerate the quantum BP neural network compression transmission process. The present invention can use fewer iterations to complete the training of the compressed transmission network structure without changing the basic structure of the original quantum BP neural network, speed up the compression speed of the quantum BP neural network to calculate the hologram and ensure the reproduction of the hologram image the quality of.

The invention discloses a particle filter tracking method for adaptively adjusting the tracking window size, which mainly solves the problem of real-time adaptive adjustment of the particle filter tracking window. The window adjustment method is: under the particle filter tracking framework, first establish the state transition equation of the moving target, initialize the target state; then use the state transition equation to predict the particle set at the next moment, calculate the particle likelihood function value and update it according to its value The weight of the particle, calculate the average distance d from the particle with a large weight to the center of the particle set; finally let the size of the window change linearly with the value of d, so as to realize the adaptive adjustment of the tracking window. This method realizes the adjustment of the particle filter tracking window with a small amount of calculation. Compared with similar methods, it has the advantages of simple calculation and fast tracking speed.

The invention discloses a dynamic process monitoring method based on dynamic orthogonal component analysis. On the basis of the traditional principal component analysis algorithm, the method of the invention further considers how to further consider the relationship between the latent feature components and the time-delay measurement data. Orthogonal properties. For this reason, the method of the invention deduces a dynamic orthogonal component analysis algorithm first, and then implements dynamic process monitoring on the basis of the algorithm. Compared with the traditional dynamic process monitoring method, the method of the present invention achieves an effect superior to the traditional PCA or dynamic PCA method in the monitoring effect of the dynamic process. In addition, the two stages of off-line modeling and on-line monitoring of the method of the present invention will not increase the amount of extra calculation. It can be said that the method of the present invention is a more preferred dynamic process monitoring method.

The invention discloses a rectangular coordinate Newton method load flow calculation method suitable for research purposes, and provides a Newton method load flow calculation method which is easy to modify and maintain for researchers performing further research on the basis of rectangular coordinate Newton method load flow calculation. For a power system with n nodes, node numbers are irrelevant to node types and can be numbered randomly, a Jacobian matrix in load flow calculation is stored according to (2n) * (2n), elements of rows and columns related to balance nodes are 0, but diagonal elements are not reset, and original calculation values are reserved. Therefore, a linear equation solving function with excellent performance provided by a programming language can be used for solving a correction equation for load flow calculation, the programming difficulty is reduced, the calculation speed is improved, and the reliability of the algorithm is ensured. Implementation examples show that a linear equation solving function provided by a programming language can be used for solving a correction equation of load flow calculation, the load flow calculation speed is increased, and the programming difficulty is reduced.