22results about How to "Reduce calculation steps" patented technology

The present invention relates to the field of chip placement machine control technology, and specifically discloses a trigonometric function curve planning method and system with continuous jerk, and a chip placement machine. The method includes the following steps: dividing the curve planning into an acceleration section, a uniform speed section, and a deceleration section, and the acceleration section and the deceleration section are respectively divided into a jerk section, a uniform acceleration section, and a deceleration section; setting and initializing the motion parameters of the curve planning; defining the average acceleration ratio of the deceleration section to the acceleration section as a softening factor, and defining the maximum acceleration in the deceleration section or the acceleration section to the average acceleration ratio as an acceleration coefficient; calculating the time nodes of each stage of the curve planning according to the motion parameters, the softening factor, and the acceleration coefficient; and updating the state of each stage of the curve planning according to the time nodes. In combination with the continuous characteristics of the second-order derivative of the trigonometric function, an S-curve planning with continuous jerk is designed, which effectively reduces the motion impact, ensures the stable time in place, and is simple to operate.

The invention discloses a three-dimensional target detection method based on a stereoscopic vision technology, and the method comprises the following steps: obtaining a to-be-detected target image, and carrying out the preprocessing of the to-be-detected target image; acquiring depth information of the target image to be detected by adopting a binocular stereoscopic vision technology; extracting target features in the preprocessed to-be-detected target image by using the optimized CNN model; fusing the depth information of the to-be-detected target image with the target features; and identifying the fused target features by using an RPN algorithm based on a regional proposal network. The method solves the problems that in an existing three-dimensional target detection method, when depth information in an image is obtained, the image and point cloud information of the environment where a target object is located need to be obtained firstly, then coordinate information of the point cloud information in the image is obtained, and then the coordinate information is combined with 2D and 3D bounding box information in the image, so that the depth information in the image cannot be obtained. The process relates to a large amount of calculation, so that the calculation complexity is increased, and the efficiency of obtaining the depth information is reduced.

The invention discloses a geographic information data acquisition vehicle, relates to the technical field of geographic information data acquisition vehicles, and aims to solve the problem that data acquisition is incomplete when a data acquisition vehicle performs geographic information acquisition. According to the method, data from different sensors are fused by using a particle filtering method, advantages of various sensors can be comprehensively considered, uncertainty and errors of single sensor data are reduced, scene model construction is performed on fused feature information by using a neural network model algorithm, and the accuracy of scene modeling is improved. The standard geographic data model of the data acquisition area can be quickly and accurately generated. The system can reflect the change of an actual scene in real time, can adapt to various complex environments and scenes, and combines a satellite navigation sensor, a laser radar sensor, a camera, a millimeter wave radar and inertial navigation. Data including geographic positions, environment information, images and videos, dynamic states of target objects, body motion states and the like can be obtained.

The invention discloses an intelligent driving front-view image perception algorithm based on heterogeneous convolution, and the algorithm comprises the steps: S1, carrying out the basic feature extraction of an original image through an initial convolution layer, and enabling the original image to enter a plurality of parallel convolution units which are integrated together; s2, performing feature fusion on the output of the plurality of parallel convolution units in a weighted fusion mode; s3, stacking a plurality of parallel convolution units into a backbone network, and performing multi-scale target detection through an FPN feature pyramid; and S4, after the detection of the targets of multiple scales is finished, completing the training of the intelligent driving front-view image perception algorithm model. According to the intelligent driving front-view image perception algorithm based on heterogeneous convolution, the reasoning efficiency and the feature extraction capability of the model can be remarkably improved, and the balance problem of the lightweight target detection model between the calculation complexity and the feature extraction capability is solved.

The invention provides a method and system for processing coal mine disaster data based on a PCA (principal component analysis) method. The method comprises the following steps: preprocessing and standardizing working data to obtain effective data, performing dimension reduction analysis on the effective data by using PCA to convert the effective data into a plurality of feature vectors, and constructing a dimension reduction space of the effective data, and respectively calculating a reconstruction error and an interpretation variance ratio corresponding to each feature vector in the dimension reduction space, constructing dimension information corresponding to each feature vector to adjust the dimension reduction space, inputting effective data into the adjusted dimension reduction space for processing, generating dimension reduction data of the coal mine, and storing the dimension reduction data of the coal mine. And abnormal dimension reduction data segments which do not conform to the specified interpretation variance ratio are screened to obtain corresponding disaster data of the coal mine under different detection dimensions, so that the calculation steps can be effectively reduced, the analysis cost is reduced, whole-course visual analysis is realized, managers can conveniently understand the data, and the data processing efficiency is improved. And a powerful reference is provided for the safety of coal miners and the environment.

The invention provides a method for predicting hydration expansibility of a compacted bentonite material, which comprises the following steps of: generalizing soil particles into a spherical shape, and dividing a compacted bentonite structure into a characteristic structure element consisting of four particles based on a space accumulation configuration; according to constraint conditions of apparent density, elastic deformation energy minimization and structural entropy maximization of the soil body structure, the distribution probability of each characteristic structure element is solved; a Hertz contact model is adopted to calculate the expansive force between particles in the characteristic structure elements; calculating the equivalent expansive force of each characteristic structure element through a finite element method; based on the Hill lemma, the macroscopic hydration expansibility of the compacted bentonite structure is predicted. According to the method, the prediction process is simple, the calculated amount is moderate, the hydration expansibility of the compacted bentonite structures with different dry densities can be accurately and theoretically predicted, and theoretical guidance can be provided for design and prediction of the hydration expansibility of the compacted bentonite structures in the environments of refuse landfills, nuclear waste repositories and the like.

The present application discloses a prediction method, device, medium and product for rotational equivariant physical quantities, and relates to the technical field of electrical digital data processing. Among them, the prediction method for rotational equivariant physical quantities includes: constructing and training a nonlinear equivariant deep learning model, the nonlinear equivariant deep learning model includes a graph neural network and a decoder with linear computational complexity; when the training of the nonlinear equivariant deep learning model is completed, the physical system model of the material structure to be tested is input into the nonlinear equivariant deep learning model; the graph neural network is used to extract rotational equivariant features; the nonlinear rotational invariant features corresponding to the rotational equivariant features are converted according to the gradient induction mechanism to obtain nonlinear rotational equivariant features; the decoder is used to decode the nonlinear rotational equivariant features to obtain the rotational equivariant physical quantities of the material structure to be tested. The present application can solve the technical problem that the prior art is difficult to simultaneously ensure the prediction accuracy and computational efficiency of rotational equivariant physical quantities, which limits the application of material structures.

The invention discloses a method for evaluating the TNT equivalent of a high-energy propellant. The method comprises the following specific steps: step 1, obtaining enthalpy of formation and an assumed chemical formula of a solid propellant; 2, according to the formation enthalpy of the known solid propellant, the assumed chemical formula and the product composition, the mole number of all combustion products at the adiabatic combustion temperature of 1 kg of the solid propellant is calculated; 3, calculating the total enthalpy of combustion product generation of 1kg of solid propellant under 298K; 4, subtracting the total enthalpy of the combustion product under 298K from the formation enthalpy of the known solid propellant to obtain a theoretical constant pressure detonation heat value QP of the propellant; 5, obtaining theoretical constant-volume explosion heat Qv by utilizing the theoretical constant-pressure explosion heat value of the propellant and the expansion work of the generated gas-phase component; 6, the theoretical constant volume explosion heat of the propellant is divided by the explosion heat of the standard TNT, and the theoretical TNT equivalent coefficient CTNT of the propellant is obtained. The evaluation method has the advantages of few calculation steps, high efficiency, high calculation precision and wide application range.

This utility model relates to a front wheel steering angle sensor with adjustable range, including a sensor body, a magnetic block, and a PCB board. The sensor body is connected to the vehicle body through mounting holes, and its built-in center calibration structure is aligned with the steering axis. The magnetic block contains a radially magnetized bare magnet, which forms a magnetic field with the Hall chip on the PCB board. The PCB board is rigidly fixed to the body and is detachable, integrating a Hall sensor chip with an SPI interface for programmable operation, supporting software configuration of the detection range and zero-point parameters. The signal is converted from 3.3V to 5V via a level conversion chip, and a multi-stage power supply module provides dual-channel regulated power. After the microprocessor calculates the angle data, it is output by the CAN bus controller. This sensor establishes an initial zero point through a zero-point calibration component, featuring a compact structure and convenient installation. The software configuration is flexible and adaptable to different range requirements, making it particularly suitable for autonomous driving systems in construction machinery and agricultural machinery, effectively improving steering angle detection accuracy and multi-platform compatibility.

The invention belongs to the technical field of signal processing, and discloses a radar real-time target detection method based on heterogeneous parallel computing. According to the method, through the steps of channel correction, pulse compression, moving target display, digital beam forming, coherent accumulation or non-coherent accumulation on multi-pulse signals including sum beams and difference beams, and constant false alarm processing, the problems of an existing radar real-time signal processing technology in the aspects of processing speed, accuracy, efficiency, flexibility and the like are solved. By adopting a domestic heterogeneous computing technology and applying a universal software technology, efficient and real-time processing of radar signals is realized, and the overall performance of a radar system is improved.

The application discloses a low-bit matrix calculation device with a floating-point scaling factor and a calculation method thereof. The device comprises a scaling factor processing module, an input module, a matrix calculation module, a floating-point accumulation module and an output module. The method first groups and quantizes weight and eigenvalue matrices to obtain quantization values and floating-point scaling factors; then, the scaling factor product is calculated in advance with a single accumulation length as a grouping unit; then, matrix multiplication and accumulation operation is performed, the result is multiplied by the scaling factor product after being converted into an fp16 or bfp16 format, and then accumulated into a final result; and finally, the result is output after being dequantized. The application simplifies the group-wise calculation process, saves hardware resources, guarantees calculation accuracy, meets different scene requirements and improves calculation efficiency by sharing the scaling factor product and using fp16 or bfp16 as an accumulator.

The invention belongs to the technical field of quantum computing, and particularly relates to a quantum circuit simulation method based on circuit cutting. By designing a cutting strategy, a complex quantum circuit is divided into a plurality of small sub-circuits, and each sub-circuit can be independently simulated; the method specifically comprises the steps of circuit preprocessing and dependency relationship analysis; sub-circuits are divided through circuit cutting, specifically, a heuristic cutting algorithm is adopted, and an optimal cutting point is determined according to the dependency relationship between the circuits; selecting a scheme capable of minimizing the overall simulation burden by evaluating the overhead of different cutting schemes to optimize the global calculation cost and resource allocation so as to ensure that the cut sub-circuits can be independently and efficiently simulated; and sub-circuit state vector multiplexing: storing the intermediate state vector of each sub-circuit, and searching similar state vectors for multiplexing when a new sub-circuit is calculated, so as to reduce the calculation amount and resource consumption. According to the method, the complexity of large-scale quantum circuit simulation can be reduced, and the calculation efficiency is improved.

The invention discloses a self-adaptive question answering method based on a large language model and an intelligent large language model. The method comprises the following steps: receiving a query text input by a user; analyzing the query text by using a preset query analysis model to determine the complexity of the query text; if the complexity is a first category, the query text is directly input into a large language model to generate an answer, and the first category corresponds to a preset low-complexity query; if the complexity is a second category, the retrieval process is executed, a reference document related to the query text is obtained from a preset data source, the query text and the reference document are jointly input into the large language model to generate answers, and the second category corresponds to preset high-complexity query. According to the method, query analysis is introduced, so that shunting processing, simple direct answering and answering after complex retrieval on queries with different complexities are realized. The self-adaptive mechanism maximizes the operation efficiency of the system while ensuring the answer quality.

The invention relates to a particle-ball-based quantum HNSW graph KNN method, and belongs to the field of quantum calculation and machine learning. According to the method, firstly, a data set D is converted into a granular ball data set M through classical calculation, and the amount of data participating in calculation is effectively reduced; afterwards, by means of quantum computing parallelism, a QRAM algorithm and angle coding, the pellet data set is coded into a quantum state, Swap-test and iteration are used for comparing quantum circuits to calculate similarity, and a multilayer quantum HNSW graph is constructed; and finally, K nearest neighbors of the test data points are determined through quantum search and a priority queue, and the test data points are classified according to classification results of the neighbors. According to the method, the advantages of a classic computer and a quantum computer are combined, the calculation data volume and the time complexity are reduced, meanwhile, high classification precision is kept, and a new thought and method are provided for the quantum machine learning field.

The invention discloses a self-adaptive efficient CAN and Ethernet translation system and device and a storage medium, and the system comprises a data packet detection module, a data pre-shaping module, a data path analysis module, a data composition analysis module, a data load analysis module and a data transmission module. According to the system, feature identification code insertion, data field segmentation scribing and data flow direction path definition are carried out on data through the data pre-shaping module, data signal parameterization can replace addressing, data can be grabbed and taken away at the same time, the calculation step of the data forwarding routing process is greatly shortened, the forwarding communication overhead of non-demand data is reduced, and the data forwarding efficiency is improved. The routing translation efficiency is effectively improved; meanwhile, an upper computer interface is provided, effective data packet extraction is carried out during gateway forwarding, rapid and convenient dynamic configuration is provided, address information of bottom layer signals does not need to be concerned during dynamic configuration, decoupling of an application layer and a bottom layer is achieved, the dynamic configuration efficiency is high, technical operability is simple and practical, and actual requirements are better met.

The present invention discloses a method for quickly decomposing and typeset mixed contents of text, emoji expressions and emoticons, comprising the following steps: S1, decomposing input text character by character to form a plurality of independent and inseparable character groups; S2, traversing the character groups, and performing Unicode category calculation on the first character of each character group to determine its type; S3, marking each character group with a label attribute according to the contextual relationship and characteristics of the character group; S4, recombining into a plurality of inseparable character groups according to the label attribute according to the maximum width of a display text area; S5, placing the inseparable character groups into a display area. The method is a highly customized text typeset method based on Unicode character classification, and can process different character types to adapt to various situations and requirements. Because it is based on Unicode, the method supports the vast majority of languages, symbols and characters in the world, including special characters such as emoji expressions and emoticons, and is more extensive and flexible.

The invention relates to a visual drilling simulation test platform, and belongs to the technical field of drilling simulation, the visual drilling simulation test platform comprises a main platform, four main supports are fixedly mounted at the bottom of the main platform, four auxiliary supports are fixedly mounted at the top of the main platform, and an auxiliary platform is fixedly mounted among the tops of the four auxiliary supports; a drilling mechanism is fixedly installed at the top of the auxiliary platform, a display screen is fixedly installed at the top of the main platform, a camera is fixedly installed at the bottom of the auxiliary platform, a drill bit assembly is installed at the output end of the drilling mechanism, and a fixing frame is placed between the opposite sides of the main supports on the left side and the right side. A land simulation assembly is installed at the top of the fixing frame, a wellhead protection assembly is installed at the top of the land simulation assembly, and an emptying assembly is installed at the bottom of the fixing frame. According to the visual drilling simulation test platform, the compression condition and the appearance condition of a drill bit in the drilling process can be displayed more visually.

The invention provides a multi-prediction-frame real-time display method for target detection algorithm acceleration based on an FPGA, and relates to the technical field of target detection deep learning algorithms, and the method comprises the steps: carrying out the post-processing of each block feature map of a regression branch, and generating N prediction frames; the coordinate [(x11, y11), (x21, y21)] of the prediction frame bbox1 is analyzed, the original y11 row mask is read from the BRAM to the one-dimensional register set to serve as an initial value, and the y11 row mask is updated on the one-dimensional register set from the x11 column to the x21 column and written back to the BRAM; updating masks of all the remaining rows from y11 + 1 to y21 in the prediction frame bbox1 row by row and writing the masks back to the BRAM; according to the method, mask updating of the remaining bbox < 2 >-bbox < N > is completed one by one and written back to the BRAM; and carrying out picture drawing on the video stream according to all the updated masks, if the mask is 0, passing through the original picture data, and if the mask is 1, replacing the original picture data with the color of the prediction frame. According to the method, the mask of the picture can be generated in real time, the mask does not need to be generated after all prediction frames are generated, and the reasoning speed can be effectively improved.

The invention relates to the technical field of storage, and discloses a data processing method and system, the method is applied to storage equipment, according to the method, copying operation is carried out by obtaining a data copying instruction, a verification value of original data corresponding to a logic data block is calculated while decompression processing is carried out on the logic data block, and based on the verification value and a source logic address, the original data corresponding to the logic data block is obtained. And generating second protection information, comparing the first protection information with the second protection information according to the protection control information, if the comparison is passed, generating third protection information based on the verification value and the destination logic address, combining the logic data block and the third protection information to obtain first target data, and taking the first target data as data corresponding to the destination address. And the preset process is skipped to store the first target data in the storage device, so that the calculation step of data decompression can be reduced, and the data processing efficiency is improved.

The invention discloses an online data detection method for an NCUC bus type measurement system, and belongs to the technical field of data detection for NCUC bus type measurement system. S1, I / O data acquisition: using an I / O module to acquire sensor equipment data, including current, voltage and ambient temperature data; data transmission: transmitting the acquired data to a main control unit of the NCUC system through a communication module; temperature judgment and temperature compensation: setting an ambient temperature threshold, when the ambient temperature exceeds the threshold, turning on an exhaust fan for temperature compensation, lowering the ambient temperature, and returning the ambient temperature to normal; signal conversion: the main control unit converts the data into a digital signal, and then amplifies and filters the data; an NCUC bus type measurement system and an online data detection method are invented, which reduce the influence of the ambient temperature on the sensor, automatically calibrate the sensor, adjust the gain of the signal amplifier and the parameters of the filter, reduce the data error of the online detection, and make the data more accurate.

The present invention provides a verification calculation method, device, system and medium for a redundant braking system, wherein the verification calculation method includes: substituting the vehicle mass, wheel rolling radius and deceleration of the target vehicle into a first mathematical model to obtain a target braking torque; substituting the braking parameters and the target braking torque into a second mathematical model to obtain a target hydraulic pressure; substituting the first performance parameter into a third mathematical model to obtain the displacement of the plunger pump; establishing a simulation model and performing simulation based on the displacement, the second performance parameter and the required brake fluid volume to obtain a P-t relationship curve between the pressure-building hydraulic pressure and the pressure-building time; substituting the target hydraulic pressure into the P-t relationship curve to obtain a first time value corresponding to the target hydraulic pressure; when the first time value is less than the maximum time value required to reach the corresponding deceleration required by the working condition, it is determined that the plunger pump meets the working condition requirements. The present invention can perform verification calculations on the components of a redundant braking system, thereby determining whether the system meets the working condition requirements.

The invention relates to the technical field of pixel positioning, in particular to an IC chip sub-pixel precision positioning method and system corresponding to secondary matching, and the method comprises the steps: obtaining an initial image of an IC chip and a reference template image corresponding to the initial image; generating a rough positioning frame according to the initial image and the reference template image; cutting the reference template image by using the rough positioning frame to obtain a first target image area; calculating a gradient feature map of the first target image region; performing first matching in the reference template image according to the gradient feature map to obtain a corresponding point set and generate an initial offset; and updating a coordinate mapping table of the initial image by using the initial offset. According to the method, through back projection and real-time image slice extraction, the similarity between the positioning result and the standard template can be immediately verified after positioning, and the reliability of final positioning is ensured.