41results about How to "Relatively small error" patented technology

The invention discloses a characteristic higher harmonic low-frequency sampling method, an APF, equipment and a storage medium, belongs to the technical field of power system harmonic detection, and solves the problem of how to reduce the sampling frequency of characteristic higher harmonics. According to the method, the characteristic higher harmonic signal is sampled into the fundamental wave signal by adopting the sampling frequency with lower frequency, so that the amplitude of the characteristic higher harmonic signal is obtained; meanwhile, sampling the characteristic higher harmonic signal into a direct current signal by adopting a second sampling frequency with a relatively low frequency, so as to obtain the phase of the characteristic higher harmonic signal; combining the known angular frequency of the characteristic higher harmonic signal to obtain all characteristics of the characteristic higher harmonic signal; the sampling frequency is reduced to a fraction or even lower than that of a traditional method, and the sampling frequency requirement is remarkably reduced; a high-frequency sampling chip does not need to be upgraded, and system modification cost is reduced; the phase relative error is greatly reduced in a low-order harmonic band, the overall phase error is controlled within 5%, and the phase detection precision is improved.

The invention discloses a trajectory prediction system based on convolution and self-attention. The trajectory prediction system comprises an overall network architecture, a training method and a reasoning output algorithm. The whole network architecture takes a road grating map, a vehicle motion state and target information as inputs, the inputs are processed through a DenseNet layer, a self-attention coding layer, a full-connection coding layer and a decoding output layer in sequence, and a prediction track is output; according to the method, a road grating map containing information such as a collision box and a road marking and a vehicle motion state are used as input, road environment constraints are associated with a self-attention mechanism, a polar coordinate track description mode fitting vehicle kinematics characteristics is adopted, a track parameter value range is limited, common errors and abnormal tracks are effectively avoided, and the method is suitable for popularization and application. Traffic rules and driving safety requirements are met, and the reasonability and safety of formed track prediction are prominent; based on 16000-frame multi-dimensional training data collected by a Carla simulator, errors are reduced in a verification set after optimization training, and errors in a crossing turning scene are reduced.

The invention relates to a dynamic weighing method based on a piezoelectric acceleration sensor, and belongs to the technical field of dynamic weighing systems, and the method comprises the following steps: S1, installing at least one piezoelectric acceleration sensor on a structural body bearing an object to be weighed, and collecting a vibration acceleration signal of the structural body under a dynamic load in real time; s2, applying an active excitation signal with a preset frequency and a preset amplitude to the structural body through an actuator; s3, acquiring an output signal of the piezoelectric acceleration sensor under the active excitation, and extracting a vibration response component in the output signal; s4, calculating the dynamic mass of the to-be-weighed object based on the vibration response component; and S5, outputting a calculation result of the dynamic quality. According to the dynamic weighing method based on the piezoelectric acceleration sensor, vibration interference is effectively separated and compensated through an active excitation and response analysis mechanism, and the weighing precision in non-static states such as vibration and movement is remarkably improved.

The invention relates to the technical field of electrochemical energy storage safety, and discloses a battery energy state estimation method and device, electronic equipment and a storage medium, and the method comprises the steps: obtaining an open-circuit voltage-state-of-charge curve of a battery; calculating an integral value of the open-circuit voltage-state-of-charge curve in a full-state-of-charge range; and estimating the real-time charge state of the battery at any moment, and calculating the energy state of the battery based on the integral value and the real-time charge state. According to the method, the open-circuit voltage-state-of-charge curve of the battery is obtained, the integral value of the curve in the full-state-of-charge range is calculated, and the energy state is calculated based on the integral value after the instant state-of-charge is estimated, so that the influence of internal resistance polarization on energy state estimation is effectively eliminated, and the precision and reliability of SOE estimation are remarkably improved; the problem of large error caused by internal resistance polarization is solved.

The invention discloses an image translation-based inclined view angle rotator vibration displacement measurement method. The method comprises the following steps of: performing cutting operation on an acquired rotator vibration image under a standard view angle and an acquired rotator vibration image under L random view angles; randomly extracting a preset number of random view angle cutting images and standard view angle cutting images of matched frames from the L random view angles, and taking the standard view angle cutting images as labels of the random view angle cutting images to construct a data set; training and verifying the image translation model through the training set and the verification set to obtain a trained image translation model; selecting one of the obtained rotating body vibration images of the preset time length under the L random view angles, inputting the selected rotating body vibration images into a trained image translation model, and obtaining a standard view angle image of a frame number corresponding to the preset time length; carrying out image splicing operation according to the standard view angle images with the frame number corresponding to the preset duration to obtain a spliced image; and performing edge detection on the spliced image, extracting an edge contour of the rotating body, obtaining sub-pixel-level displacement data, and converting the sub-pixel-level displacement data into a displacement value under a world coordinate system. According to the invention, the vibration displacement of the rotor can be effectively and accurately extracted from a plurality of shooting angles, and a more reliable and accurate scheme is provided for the measurement of the vibration displacement of the rotating body.

This invention provides a vehicle simulation speed correction method and system, relating to the field of vehicle intelligent dynamics modeling technology. The correction method includes the following steps: S1: Input and process simulation data output from the vehicle dynamics simulation model and corresponding real vehicle test data; S2: Construct a dynamic graph structure representing the interaction between state variables based on a preset physical coupling relationship of the vehicle powertrain; S3: Input the simulation data into a GCN and perform graph convolution operations under the constraints of the dynamic graph structure to extract graph embedding feature sequences representing the spatial dependencies between state variables; S4: Input the graph embedding feature sequences into a TCN and perform temporal convolution operations to learn the dynamic evolution law of state variables in the time dimension and output the correction amount of the vehicle simulation speed; S5: Output the result. Based on this, this invention solves the problem that existing correction methods have various limitations in practical applications.

The present application relates to the technical field of electrochemistry, and in particular to a fast-charging numerical simulation method, device and medium for thick electrodes of lithium ion batteries, the method comprising: constructing an electrochemical model of a lithium ion battery based on a pseudo two-dimensional model; loading basic parameters of the lithium ion battery, spatially discretizing according to the battery structure, and initializing an array of physical quantities required for simulation; using a Bayesian optimization algorithm, determining the charge-discharge curve of the lithium ion battery based on experiments, and calibrating the kinetic parameters of the battery cell; switching the charge-discharge mode according to the state of the lithium ion battery, performing cycle simulation, outputting simulation data, and completing fast-charging numerical simulation. The method overcomes the problems of the prior art, such as the inability of the pseudo two-dimensional model to accurately simulate the low-temperature fast-charging process of thick electrodes, the lack of an efficient and accurate method for obtaining kinetic parameters, and the difficulty in predicting battery aging caused by SEI growth.

This invention relates to the field of black carbon aging research technology, and more particularly to an experimental apparatus for black carbon aging research, comprising: a sample introduction system, including a heating tube, a pretreatment tube, an oxidizing gas removal tube, and a drying tube connected in series; a black carbon coating device, including an injection assembly, a coating chamber, a first absorption chamber, a heating removal assembly, and a second absorption chamber connected in sequence; a detection system, connected to the first absorption chamber, the heating removal assembly, and the second absorption chamber; an integrated device, including a mounting box and an aerosol charging device, a first differential migration particle size analyzer, a second differential migration particle size analyzer, and a condensed particulate matter counter disposed within the mounting box; and a control system, disposed within the mounting box, for regulating the sample introduction system, the black carbon coating device, the detection system, and the integrated device. This invention improves the convenience of black carbon research.

The application discloses a cable life prediction method based on an improved electromagnetic-thermal field coupling model, and comprises the following steps: firstly, a temperature coefficient and a proportional coefficient are used to respectively establish an insulation material thermal conductivity coefficient and temperature relationship and a convection heat transfer coefficient and temperature relationship, and the two relationships are used together with a conductor resistivity and temperature relationship as an electromagnetic-thermal field coupling relationship, thereby forming an improved electromagnetic-thermal field coupling model; then, a chaotic grey wolf optimization algorithm is used to identify the optimal temperature coefficient and the proportional coefficient of the insulation material in the improved electromagnetic-thermal field coupling model, and on this basis, the conductor temperature is calculated; finally, a multivariate linear regression is used to establish a conductor temperature analytical model, and an Arrhenius model is used to establish a cable life analytical model. The application solves the problem of large error of a traditional electromagnetic-thermal field coupling calculation method under a high temperature operation condition of a cable, and realizes online prediction of the cable life.

This invention relates to a temperature-controlled stress electrochemical metal hydrogen permeation testing device and method. The testing device includes a hydrogen permeation electrolytic cell, a hydrogen efflux electrolytic cell, a first temperature control mechanism, a second temperature control mechanism, a tensile testing machine, a potentiostat, an auxiliary electrode, a reference electrode, and a working electrode. The hydrogen permeation electrolytic cell is equipped with a first temperature control mechanism for controlling the temperature of the hydrogen permeation electrolytic cell, and the hydrogen efflux electrolytic cell is equipped with a second temperature control mechanism for controlling the temperature of the hydrogen efflux electrolytic cell. The sidewalls of the hydrogen permeation electrolytic cell and the hydrogen efflux electrolytic cell are respectively provided with a first connecting pipe and a second connecting pipe. Both the hydrogen permeation electrolytic cell and the hydrogen efflux electrolytic cell are equipped with an auxiliary electrode and a reference electrode. The two ends of the working electrode are respectively connected to the tensile testing machine. The working electrode, the reference electrode, and the auxiliary electrode are respectively connected to the potentiostat. A sample is welded onto the working electrode. The hydrogen-filled surface and the hydrogen-effluxed surface of the sample are sealed to the first connecting pipe and the second connecting pipe through sealing gaskets.

This application discloses a clock synchronization method, apparatus, board, and computer-readable storage medium, relating to the field of network time synchronization technology. The service card encapsulates a device sending timestamp in a first NTP request message sent by the main control card based on the first current service system time to obtain a second NTP request message, which is then sent to the NTP server. Based on the second current service system time, the service card encapsulates a device receiving timestamp in a second NTP response message sent by the NTP server to obtain a first NTP response message. The first NTP response message is then sent to the main control card, allowing the main control card to calculate the network clock deviation between itself and the NTP server based on the first NTP response message, and adjust the main control system time accordingly. This method avoids the problem of large errors between the device sending timestamp and the device receiving timestamp, thus ensuring that the network clock deviation calculated by the main control card will not have significant errors.

This invention discloses a method and system for synchronous inversion of multiple atmospheric parameters, belonging to the field of atmospheric laser remote sensing technology. The probe light and the reference light are obtained by splitting laser pulses; the probe light is expanded, reflected, and then perpendicularly incident into the atmosphere, where it is scattered by the atmosphere to obtain the echo light. That is, all parameters originate from the same measurement and the same spectrum, resulting in perfect spatiotemporal consistency of the data, efficient measurement methods, and accurate measurement results. The temperature and pressure parameters in the atmosphere are calculated using the normalized scattering spectrum, and then aerosol and wind speed parameters are obtained, achieving true synchronous inversion of the four key parameters of temperature, pressure, wind speed, and aerosols for the first time. Furthermore, in applications such as meteorological forecasting, achieving synchronous measurement of atmospheric temperature, pressure, wind speed, and aerosols can save costs and improve efficiency, which has significant practical implications.

The application discloses a kind of equipment and control method for automatically fish slice defect finishing.The equipment includes fish slice single piece loading unit, image acquisition and processing unit and finishing unit.Fish slice single piece loading unit utilizes the action of gravity to disperse and load the fish slice overlapping to image acquisition area;Image acquisition and processing unit, image acquisition and processing unit are used to collect fish slice defect image, and real-time picture information is transmitted to industrial computer, and the fish slice defect detection network based on YOLOv8 model improved in the middle part of industrial computer is used to identify defect area and plan defect finishing track;Finishing unit receives track and posture information from industrial computer, and accurately finishes fish slice, so as to complete the process of fish slice loading, detection and finishing.The application replaces traditional manual finishing mode by automatic processing, realizes real-time finishing of fish slice defect, effectively improves the operation efficiency and product quality of fish slice processing.

The invention discloses a fuse online monitoring method and system based on the Internet of Things. The system comprises a sensor module, a remote terminal module, a fuse state monitoring module, an electric power Internet of Things local server module, an intelligent terminal device / APP module, a background analysis system module, a LoRaWAN module and an Internet of Things cloud server. The method comprises the following steps: evaluating the condition of a fuse through a fuzzy set theory to obtain a qualitative weight, determining a quantitative weight by evaluating the influence of the fuse on the reliability of an overall system, then determining the priority of the fuse in online monitoring by adopting qualitative and quantitative standards, and detecting the fuse according to the priority; according to the invention, each fuse drop point in the regional power distribution network can be rapidly and accurately positioned, real-time on-line monitoring of the state of each fuse in the regional power distribution network is realized, and operation maintenance and equipment replacement of the fuses are guided.

The present application relates to the field of hydraulic engineering, particularly to a distributed reservoir group joint scheduling signal transmission and intelligent decision system, comprising a hydrological monitoring layer, a data transmission layer and a scheduling decision layer. The hydrological monitoring layer is composed of multiple hydrological monitoring terminals distributed around the reservoir group, using an ARM Cortex-M4 processor and a ZigBee communication protocol; the data transmission layer uses edge computing nodes and self-organizing networks to realize data preprocessing, encryption and reliable transmission; the scheduling decision layer includes a probability statistics prediction engine and a risk perception decision unit, which realizes the paradigm shift from deterministic prediction to probabilistic prediction through multi-dimensional conditional probability distribution model, uncertainty quantification, multi-time scale prediction integration, probability constraint optimization and stochastic dynamic programming, etc. The system introduces an adaptive learning mechanism to continuously optimize the prediction and decision model, which can reduce the short-term prediction error.

The invention discloses battery cell detection equipment for energy storage module production and a detection method thereof, and belongs to the technical field of battery production, the battery cell detection equipment comprises a conveyor belt, a detection mechanism is mounted at the starting end of the conveyor belt, and the detection mechanism comprises a first mounting box and a second mounting box which are mounted at the front and rear parts of the starting end of the conveyor belt respectively; a lead screw is rotationally installed in the first installation box, a nut sliding block matched with the lead screw is connected to the exterior of the lead screw, a guide rod is fixedly installed in the second installation box, a guide block is slidably connected to the exterior of the guide rod, a supporting rod is jointly connected between the nut sliding block and the top of the guide block, and a transverse plate is slidably installed on the inner side of the supporting rod. A plurality of rotating discs are rotatably installed on the inner side of the transverse plate, a fixing plate is fixedly installed in the middle of the outer portion of each rotating disc, and the upper portion and the lower portion of each fixing plate are connected with testing clamp bodies with conducting strips through electric telescopic rods; the device can be applied to detection of columnar battery cells and square battery cells, and has a better detection effect.

This application provides a core-shell structure microwave absorbing material and its thickness optimization design method and application, relating to the field of electromagnetic wave absorbing materials technology. The core-shell structure microwave absorbing material comprises a sheet-like magnetic metal core and a silica shell covering the core, the silica shell being prepared via a sol-gel method. The optimization design method includes: obtaining the intrinsic electromagnetic parameters of the constituent materials; constructing a single-particle simulation model with shell thickness as the variable; calibrating the simulation parameters through a decoupling-testing-verification iterative process; optimizing the solution for the optimal thickness based on the calibration model with the goal of maximizing the effective absorption bandwidth of reflection loss; and finally determining the optimal thickness range through experimental verification. This application achieves synergistic optimization of microwave absorption performance and corrosion resistance, solving the problems of long development cycles and high costs associated with traditional trial-and-error methods. The designed core-shell structure microwave absorbing material can be widely used in fields such as electronic equipment shielding, stealth technology, and microwave anechoic chambers.

The present application belongs to the technical field of material calculation and high-throughput screening, and particularly relates to a kind of ABN2 type silicon nitride sintering aid thermal conductivity prediction screening method. Wherein, the prediction method comprises: obtaining ABN2 type nitride data, screening stable structure according to formation energy threshold value;Adopt "labeled training-unlabeled prediction" phased strategy, utilize graph neural network to fill in the missing B and G;Introduce the improved Slack model based on elastic anisotropy structure correction factor fs Calculation of lattice thermal conductivity κ. The screening method is based on the predicted κ value, and the thermal performance of silicon nitride ceramic is sorted according to the regulation and control requirements of output. The present application designs the correction factor for the strong anisotropic structure characteristics of ABN2 type nitride, significantly improves the prediction accuracy of thermal conductivity, and greatly improves the data coverage by machine learning to fill in the parameters, forming a complete high-throughput screening scheme from parameter filling, thermal conductivity calculation to sintering aid application output.

This invention provides an air conditioning load forecasting method based on eigenvalue selection, belonging to the fields of machine learning and building energy conservation technology. This eigenvalue-based air conditioning load forecasting method selects eigenvalues ​​through the coordinated integration of mathematical mutual information and physical redundancy, and evaluates the selected eigenvalues ​​using a posterior method of the prediction model, accurately determining the optimal input eigenvalues ​​for the model. This eigenvalue-based air conditioning load forecasting method can quantitatively capture the dynamic characteristics affecting real-time air conditioning load values, ensuring high prediction accuracy. It can improve the accuracy of the air conditioning load forecasting model by 5.62% in the correlation coefficient and reduce the average error by approximately 16%–22%, while essentially without increasing computational costs, demonstrating significant practical application value.

This invention discloses a non-inertial navigation mobile indoor volume measurement and 3D reconstruction method, equipment, and computer-readable medium, belonging to the interdisciplinary field of precision engineering measurement, computer vision, and digital twin technology. The method includes the following steps: S1, dynamic scanning data acquisition; S2, adaptive data augmentation and cleaning; S3, trajectory and depth calculation based on motion continuity constraints; S4, cross-sectional topology construction and closure constraints; S5, 3D solid modeling preserving volume characteristics; and S6, precise volume calculation based on the solid model. This invention employs the aforementioned non-inertial navigation mobile indoor volume measurement and 3D reconstruction method, equipment, and computer-readable medium, and through a single-line 2D LiDAR combined with innovative algorithms, achieves mobile high-precision volume measurement and high-fidelity 3D reconstruction of irregular indoor spaces under low-cost hardware conditions.

The present application relates to the technical field of carbon footprint accounting and low-carbon management, and specifically provides a warehouse carbon emission factor dynamic calibration and adaptive allocation method and system, which comprises the following steps: collecting multi-dimensional data affecting warehouse carbon emission in a target warehouse in real time and quantifying the data to obtain a dynamic warehouse feature vector; generating an initial carbon emission factor from a pre-constructed carbon emission base factor library, and performing Bayesian calibration on the initial carbon emission factor to obtain a precise carbon emission factor; allocating carbon emission at the cargo level according to the data availability and business scenarios of the target warehouse; and then updating the precise carbon emission factor to the carbon emission base factor library based on the preset update trigger condition. The present application can realize scenario-based precise generation, dynamic calibration and cargo-level adaptive allocation of warehouse carbon emission factors, and significantly improve the accuracy and flexibility of warehouse carbon accounting.

This utility model discloses a rice cooker temperature detection device, relating to the field of rice cooker temperature detection technology, including a temperature sensor, a rice cooker lid, and a rice cooker ECU. This utility model uses a temperature sensor sealed to the lid, with the sensor probe extending into the pot. After being sealed to the lid by a sealing ring, the internal temperature is not leaked out, ensuring a small error between the temperature detected by the sensor and the actual temperature inside the pot. The sensor probe is a high-precision NTC thermistor, encased in a high-efficiency stainless steel probe shell. A shell fixing plate is provided on the probe shell to fix it to the rice cooker lid, ensuring accurate positioning of the temperature sensor probe. The other end is connected to the rice cooker ECU via a wiring harness connector, feeding back the temperature detected by the sensor probe to the ECU. The ECU then instructs the thermostat to adjust the internal temperature of the rice cooker during operation, facilitating precise control of the internal temperature, improving the fluffiness and texture of the rice.

The application discloses a kind of big diameter shield tunnel segment fine model manufacturing device and method, the manufacturing device includes A type component, B type component, C type component and D type component, the A type component, B type component, C type component and D type component are assembled to form ring cavity;Multiple combined components for simulating shield segment detail structure are arranged in the cavity, including rubber core mold, ring (longitudinal) boss component, ring (longitudinal) convex component, ring (longitudinal) concave component, concave (convex) groove component, ring (longitudinal) T component, sleeve.The manufacturing device is prepared based on 3D printing technology, overcome the low degree of detail component fine of the existing conventional manufacturing device It is short of the shortcoming, and size deviation caused by partition plate in integrated mold pouring can be effectively reduced, and the model produced accurately simulates the detail structure characteristics of prototype structure.

The application discloses a new energy automobile low-voltage lithium battery charging control method, comprising the following steps: constructing a lithium battery charging control system; performing battery health state estimation calculation; performing residual power estimation calculation; realizing state switching of a DC / DC control module; and regulating the DC / DC output voltage in a proportional regulation mode to avoid overcharging of the battery in the regulation process. The above technical scheme realizes the cooperation among a battery health state estimation module, a residual power estimation module and a DC / DC control module, estimates the battery health state, triggers full charging calibration SOC when the SOC cumulative error is too large, ensures that the SOC estimation error is within a controllable range, regulates the DC / DC output voltage in a proportional regulation mode to avoid the overcharging problem of the battery in the regulation of the DC / DC voltage, and realizes the optimization of the lithium battery charging control.

The application discloses a kind of underwater vehicle propeller shaft frequency and blade frequency variational holographic spectrum identification method and device, variational holographic spectrum method utilizes the thought of holographic representation, realizes the robust high-dimensional holographic representation of nonlinear non-stationary signal, obtains variational holographic spectrum diagram, by feature extraction to variational holographic spectrum diagram, realize the identification and estimation of underwater vehicle propeller shaft frequency, blade frequency and blade number;The method introduces variational mode decomposition, effectively solves the mode aliasing problem of EMD in holographic hilbert spectrum analysis method;According to the characteristics that propeller modulation signal in underwater vehicle radiation noise is low frequency slow change, segmented fourier transform is introduced, the problem that there is large error when hilbert spectrum analysis method is processed low frequency slow change signal is solved.The method solves the problem of insufficient representation when the commonly used radiation noise analysis method LOFAR analysis, DEMON analysis and various improved algorithms are analyzed in nonlinear non-stationary signal.

The application discloses a kind of steel bottle filling port pose detection methods, the image of different pose of steel bottle filling port obtained is preliminary processed;The image after pre-processing is carried out block segmentation, different blocks are encoded, the coordinate on object coordinate system is converted into the encoding coordinate of encoding image, and each dimension block number mask is obtained, then steel bottle filling port pose detection model is established;The image of real-time acquisition steel bottle filling port is preliminary processed, then block number mask is obtained by detection model;Real coordinate feature map is obtained by decoding;Two-dimensional coordinate and corresponding three-dimensional coordinate are extracted;The correspondence between two-dimensional coordinate and three-dimensional coordinate obtained by EPnP algorithm is converted into the pose information of filling port.The feature map of new partition encoding coordinate is used to predict deep neural network, the average error on all pixels of feature map can be reduced proportionally, and its accuracy is improved.

The utility model relates to the technical field of building construction, in particular to a reinforcement cage elevation auxiliary control device for a long spiral pressure filling process, which comprises a stand column and a supporting arm, and is characterized in that the bottom of the stand column is fixedly connected with a base, the bottom of the base is fixedly connected with a positioning column, and the top of the stand column is hinged with a limiting rod; a groove is formed in the top of the limiting rod, a cylindrical level bubble is fixedly installed in the groove, and a supporting plate is fixedly connected to one side of the stand column. The lifting device has the advantages that the stand column is fixed to the ground on one side of a pile hole, after the supporting arm is fixed to a main reinforcement of the reinforcement cage, the reinforcement cage is lifted and put into the pile hole, and descending of the reinforcement cage can be stopped until the lower portion of the connecting arm abuts against the limiting rod, so that the elevation of the reinforcement cage can be strictly controlled, and the construction efficiency is improved. The problem of large errors caused by eye observation of constructors is avoided, the elevation control precision is improved, the problem of later-stage work release is avoided, and the rework cost is saved.

The invention discloses a robot obstacle avoidance method based on point cloud space-time correlation clustering and multi-model fusion prediction. The method comprises the following steps: firstly, completing ground segmentation by using an improved RANSAC algorithm for adaptively calculating sampling times according to an interior point proportion; secondly, a DBSCAN-T algorithm based on space-time correlation is adopted, and stable tracking and dynamic judgment of the obstacle are achieved by calculating the intersection-to-union ratio of front and back frame clusters; next, track prediction is carried out by using Kalman filtering and an LSTM model, and a fusion weight is calculated based on a variance of a historical prediction error to obtain a final prediction track; and finally, generating a virtual target point according to the movement trend of the obstacle, and generating a local obstacle avoidance path in combination with an improved dynamic window method and an artificial potential field method. According to the method, the problems of dynamic obstacle sensing lag and insufficient nonlinear trajectory prediction precision in a complex scene are effectively solved, and the obstacle avoidance safety and smoothness of the robot are remarkably improved.

This application relates to the field of powder metallurgy technology, specifically disclosing a method for preparing diamond / copper composite materials, including the following steps: powder pretreatment, green compact pressing, green compact assembly, hot pressing sintering, gradient cooling, stress relief, slitting, and finishing; the green compact pressing includes: pressing diamond / copper sheet green compacts and pressing copper sheet green compacts; the specific steps of the green compact assembly are: stacking in the order of "copper sheet green compact - diamond / copper sheet green compact - copper sheet green compact - thin iron sheet" to form an assembly. The diamond / copper composite material prepared by the method provided in this application has small planarity error and dimensional tolerance, and excellent thermal conductivity, which can provide a reliable process guarantee for meeting the high-end market's demand for large-volume, highly consistent diamond / copper composite materials.