155 results about "Interaction forces" patented technology

The invention discloses a force / position hybrid control method for a dexterous arm-hand robot, and aims to improve the tracking precision and flexibility of a high-degree-of-freedom robot in a complex interaction task. The method comprises the following steps: constructing a complete kinematics and dynamics model; designing a self-adaptive sliding mode impedance controller, converting an impedance equation into a system taking interaction force as a state, and introducing a sliding mode variable to realize stable tracking of expected force; a preset performance boundary function and a synchronization error are introduced to realize cooperative control and performance constraint; and finally, a force / position hybrid control structure is constructed, the outer ring adjusts the expected trajectory, the inner ring achieves accurate tracking, and therefore smooth interaction between the robot and the complex environment is achieved. The method has good robustness and adaptability, and is suitable for tasks such as grabbing and operation.

The invention provides a clamping-driving-wrist multi-dimensional force optical fiber self-decoupling sensing device and method, and relates to the field of multi-dimensional force optical fiber sensing detection.The device comprises a clamp head, a clamp wrist, a clamp tail and a movable arm mechanism which are fixedly connected in sequence; the force sensing driving mechanism is connected with the clamp head and drives the clamp head to be opened and closed to measure driving force; a wrist three-dimensional force sensing mechanism is arranged at the wrist part of the clamp and is used for measuring resultant force formed by three-dimensional interaction force during cavity tissue interaction and driving force transmitted to the wrist part of the clamp by the head part of the clamp; a clamping force sensing mechanism is arranged in the clamp head, and the resultant force formed by the three-dimensional interaction force and the clamping force when the clamping force sensing mechanism interacts with the cavity tissue is measured; an angle adjusting mechanism is arranged in the movable arm mechanism, drives the movable arm mechanism to bend or unbend and senses a resultant force formed by a three-dimensional interaction force, a clamping force and a lifting force in a cavity tissue lifting state; according to the invention, the multi-dimensional force is measured, and an accurate result is obtained through decoupling.

The invention provides an optical fiber force-shape sensing device and method through a natural orifice, and relates to the technical field of optical fiber sensing, the device comprises an operation arm mechanism, and specifically comprises a front end connecting joint, a plurality of movable joints and a tail end connecting joint which are sequentially and rotatably connected through a ball head and a ball socket, at least one limiting bulge is distributed on the circumferential surface of the ball head, and the limiting bulge is connected with the front end connecting joint; limiting grooves in one-to-one correspondence with the limiting protrusions are formed in the ball socket, and the limiting protrusions are in sliding fit with the limiting grooves so as to limit in-situ torsion between the adjacent joints. Through mutual cooperation of the limiting grooves and the limiting protrusions, in-situ torsion is reduced, torsional strength is improved, a shape-following embedded optical fiber sensor integration method is provided, shape reconstruction errors caused by movement dislocation are reduced, and protection of optical fibers is achieved. A first driving wire, four second driving wires, two optical fiber shape sensing modules and four optical fiber force sensing modules are embedded in the operation arm mechanism, and real-time accurate measurement of interaction force and the bending shape of the operation arm mechanism can be achieved.

Provided is a robot teaching device including an end effector that can be intuitively operated by a teacher, and the robot teaching device can accurately measure an interaction force between the end effector and a work object.In a robot teaching device 5 including a first end effector 1 that is gripped and operated by a teacher, the first end effector 1 includes a first claw portion 10 capable of switching between an openable and closable state and an opening-closing fixing state, a handle 12, and a first force sensor 11 that measures a force and torque between the first claw portion 10 and the handle 12, and generates teaching data based on an output of the first force sensor 11 when the first claw portion 10 is in the opening-closing fixing state and the handle 12 is gripped by the teacher.

The technology disclosed relates to using virtual attraction between hand or other control object in a three-dimensional (3D) sensory space and a virtual object in a virtual space. In particular, it relates to defining a virtual attraction zone of a hand or other control object that is tracked in a three-dimensional (3D) sensory space and generating one or more interaction forces between the control object and a virtual object in a virtual space that cause motion of the virtual object responsive to proximity of the control object to the virtual object and escalation with a virtual pinch or grasp action of the control object directed to a manipulation point of the virtual object.

The invention discloses a virtual simulation teaching method, device and equipment for cattle pregnancy diagnosis, and the method comprises the steps: constructing a three-dimensional geometric model of a cattle pelvic cavity anatomical structure, obtaining a cattle pelvic cavity model, configuring corresponding physical attribute parameters, and generating a virtual anatomical environment; receiving palpation operation of a user through force feedback equipment, driving a virtual fingertip to move in a virtual anatomy environment, and collecting user interaction data in real time; based on the motion, the operation pressure and the physical attribute parameters of the virtual fingertip, calculating an interaction force of an anatomical structure on the virtual fingertip through soft tissue physical simulation, generating a tactile feedback signal according to the interaction force, and outputting the tactile feedback signal to a user through force feedback equipment; comparing the operation track with an expert standard operation model, and guiding an operation path of the user in real time through force feedback equipment according to a comparison result; and performing skill assessment according to the diagnosis conclusion submitted by the user after completing the palpation operation and the user interaction data, and generating a diagnosis practical training report.

A human body assisting apparatus and an accessory motion testing platform, comprising: a mobile motion platform (2), a multi-degree-of-freedom robotic arm (5), a motion capture system (8), a ground acting force measurement table (1), and a controller. By controlling the mobile motion platform (2) and the multi-degree-of-freedom robotic arm (5), the testing platform reproduces three-dimensional trajectories and postures of some limbs of a human body in a motion process and an interaction force between the limbs of the human body, so as to quickly verify some motion functions of an artificial limb, and shorten a research and development period of a human body assisting apparatus (7) comprising the artificial limb. In addition, the motion capture system (8) is used for measuring three-dimensional trajectories and postures of the multi-degree-of-freedom robotic arm (5) and the human body assisting apparatus (7), and the ground acting force measurement table (1) is used for measuring an interaction force between the human body assisting apparatus (7) and the ground. The motion testing platform can accurately reproduce motion trajectories and motion postures of limbs of a human body and an interaction force between the limbs, thereby improving the motion testing efficiency and accuracy of the human body assisting apparatus, and significantly reducing the human body testing cost. Further provided is an operation method for a human body assisting apparatus and an accessory motion testing platform.

The invention belongs to the technical field of man-machine cooperative interaction, and relates to a man-machine cooperative compliant interaction method based on fuzzy variable admittance and human body motion prediction, which comprises the following steps: step 1, establishing a man-machine cooperative interaction admittance model, and converting the interaction force applied to an end effector of a mechanical arm by a collaborator into the end speed of the mechanical arm; 2, designing an admittance model parameter adaptive law based on a fuzzy theory, dynamically adjusting a virtual damping parameter, and designing a virtual mass adaptive law based on a virtual damping change condition, so that an admittance model dynamically adapts to a movement mode of a collaborator; and step 3, predicting a human body motion intention based on the LSTM network, generating an auxiliary speed item, and jointly generating an optimal man-machine compliant interaction speed in combination with an admittance reference speed obtained based on admittance model transformation. According to the method, the robot body motion information and the human body motion intention in a man-machine system are fully utilized, the self-adaptive admittance interaction device fused with the motion intention of the human operator is designed, and the naturalness and smoothness of man-machine interaction are improved.

The invention relates to a data acquisition method and system based on a rehabilitation device, and relates to the field of data acquisition and processing.The method comprises the steps that man-machine interaction force data and plantar pressure distribution data are acquired; obtaining a man-machine interaction force value based on the man-machine interaction force data; if the human-computer interaction force value exceeds a preset human-computer interaction force threshold value, an active auxiliary mode of the rehabilitation device is triggered; if the human-computer interaction force value does not exceed the preset human-computer interaction force threshold value, obtaining plantar pressure distribution characteristics from the plantar pressure distribution data; generating a control feedback signal in combination with the human-computer interaction force value and the plantar pressure distribution characteristics; and controlling the rehabilitation device to perform auxiliary operation based on the control feedback signal. The training effect evaluation method and device have the effect of improving the accuracy of training effect evaluation.

The invention discloses a method and system for driving and controlling a lower limb exoskeleton through brain-computer interface intention confidence, and relates to the technical field of medical rehabilitation. The method comprises the following steps: firstly, identifying an original electroencephalogram signal to obtain intention confidence, and mapping an impedance parameter group containing joint stiffness and a damping coefficient in combination with gait phase information; secondly, extracting a motion position and an interaction force error, comparing an intention confidence coefficient with an actual execution state by using a sliding time window to obtain a nerve matching error, and fusing the three into a total composite error; meanwhile, the human-machine coupling compliance is evaluated based on the human body joint angle and the exoskeleton torque variation, and a safety gain coefficient is discriminated and generated; and finally, performing gain operation on the total composite error based on the impedance parameter group, and performing safety gain coefficient correction to obtain a target control torque to be output to a driving actuator. In this way, a nerve-force-motion three-closed-loop framework is constructed, and compliant self-adaptive on-demand assistance and high-safety man-machine collaborative rehabilitation with defense protection are achieved.

The invention discloses a rope traction parallel robot reconstruction planning method for man-machine interaction, which belongs to the field of rope traction parallel robot configuration planning and comprises the following steps: step 1, setting parameters of a rope traction parallel robot and establishing a kinetic equation of a movable platform; 2, setting an admittance model between the mobile platform and the interactive person, and establishing a dynamic relationship between the mobile platform and the interactive person; 3, setting parameters and a kinetic equation according to the step 1, and establishing a mathematical model of a force feasible working space; step 4, dividing the man-machine interaction process into an interaction force stage and a non-interaction force stage according to the magnitude and duration of the force applied to the robot by the interaction person, and setting evaluation indexes of the two stages according to the mathematical model in the step 3; and step 5, according to the evaluation index and in combination with an admittance model, solving an optimal rope leading-out point position by using a reconstruction strategy, and completing reconstruction planning. According to the method, the rope leading-out point position can be solved in real time, and the working space size and the operation freedom in the man-machine interaction process are improved.

The invention discloses a force feedback teleoperation control system and method based on a continuum surgical actuator, and belongs to the technical field of medical surgical robots. The system comprises a master end driving part and a slave end following operation part; the master end driving part is used for acquiring hand action data of an operator in real time, converting the acquired hand action data into a corresponding control signal, and sending the control signal to the slave end following operation part through a preset communication protocol; the slave end following operation part is used for generating a corresponding driving signal and transmitting the generated driving signal to the servo motor so as to control the operation actuator to move; and in the movement process of the operation executor, the interaction force of the operation executor and the target object is sensed in real time, and the interaction force of the operation executor and the target object is fed back to the main end driving part in real time so that an operator can sense the interaction force. According to the scheme, the teleoperation precision can be guaranteed, and meanwhile the telepresence of a doctor is enhanced.

The invention relates to the technical field of retainer motion stability analysis, in particular to a rolling bearing variable speed working condition-based retainer motion stability analysis method, which comprises the following steps of: S1, determining relative positions and motion initial values of each calculation parameter and each part of a bearing; S2, calculating a position angle of a rolling body at each moment; s3, calculating contact deformation among the rolling body, the inner ring, the outer ring and the retainer at each moment; s4, solving contact deformation at each moment according to the step S3; s5, calculating the interaction force among the rolling body, the inner ring, the outer ring and the retainer; s6, establishing a multi-degree-of-freedom dynamic differential equation; s7, solving a rolling bearing dynamic differential equation considering the three degrees of freedom of the retainer; s8, carrying out iterative calculation on the motion differential equations of the roller, the retainer, the inner ring, the outer ring and the bearing seat within the time t; and S9, analyzing the stability of the retainer, so that the simulation of the retainer is more and more close to the actual working condition, and the stability analysis of the retainer is favorably carried out.

The utility model discloses a stability monitoring device and system for coal and rock mass exploitation. The stability monitoring device comprises a stressometer, a vibration sensor, a transmission module used for transmitting interaction force and vibration frequency to the stressometer and the vibration sensor, and a fixing module arranged below the transmission module and used for fixing the stressometer. The stability monitoring system comprises the coal and rock mass stability monitoring device and an early warning platform arranged on the ground and connected with the coal and rock mass stability monitoring device. In the technical scheme of the utility model, the transmission module is in rigid contact with the inner wall of the drill hole of the coal and rock mass, thereby greatly reducing the loss of transmitting the internal interaction force and vibration frequency of the coal and rock mass around the drill hole to the stressometer and the vibration sensor, and avoiding the flexible contact between the stressometer or the vibration sensor and the inner wall of the drill hole in the prior art. Therefore, the internal interaction force and the vibration frequency are greatly lost. Therefore, measured data can be more accurate and comprehensive.

The invention provides a material dryness and humidity prediction method and device based on a discrete element method and data driving, and relates to the technical field of material detection.According to the method, the change of interaction force between particles generated due to the change of the moisture content in the stirring process of materials is analyzed and converted into measurable engineering parameters, and the material dryness and humidity prediction result is obtained. And a quantitative mapping relation is established. According to the method, a particle system model is constructed by using a discrete element method, stirring mechanical behaviors under different water content conditions are simulated, and the accuracy of the model is verified by combining experimental data. On the basis, simulation and experimental data are trained by utilizing a machine learning algorithm, so that an intelligent model capable of predicting the water content of the material in real time is formed. The invention aims to realize efficient and accurate monitoring of the moisture content of the material.

The invention provides a preparation and application method of a solid super-lubricating two-dimensional material, the two-dimensional material is prepared through a one-dimensional amorphous crystal self-stripping layer, the preparation process is very simple and environment-friendly, water can be used as a solvent, low-cost large-scale preparation is easy to realize, and the solid super-lubricating two-dimensional material has very high quality and monolayer property. The two-dimensional material has extremely weak interlayer acting force, shows excellent solid super-lubrication performance, and can realize the super-lubrication behavior that the friction coefficient of a sliding part is lower than 0.01 in an atmospheric environment, and the interlayer adhesive force is 40-80% of that of graphite. The friction wear of the sliding part can be greatly reduced, and the friction material is suitable for various sliding friction parts, such as bearings, sliding blocks and micro-electro-mechanical systems.

The application provides a kind of compaction quality continuous detection evaluation method based on the extent of hunting, comprising: carrying out compaction test: real-time collection of vertical vibration acceleration of vibrating wheel, vertical vibration acceleration of upper rack and eccentric block position data;Calculate the vibrating wheel-filler interaction force of each detection period per hour;Vibrating wheel-filler interaction force curve is analyzed, to determine whether hunting phenomenon occurs in the detection period, and the compaction hunting value CJV calculation model of different working conditions is used to calculate the compaction hunting value CJV corresponding to the detection period;Establish compaction quality detection evaluation model based on CJV. The compaction quality of rolling surface is continuously detected and evaluated by using CJV. The application realizes real-time, continuous and full coverage detection of compaction quality, which can effectively guarantee the compaction quality. The continuous detection and evaluation method provided by the application is suitable for continuous detection and evaluation of compaction quality of various fillers.

This application belongs to the field of collaborative robot control technology, specifically disclosing a human-machine compliant interactive stability control method and system for achieving stiffness jumps. The method includes: real-time acquisition of the collaborative robot's end-effector interaction force and end-effector Cartesian velocity input to a fuzzy inference function to obtain human intention coefficients; calculation of the desired total stiffness and desired total damping at the current moment based on the human intention coefficients, and decomposition them into time-varying components and time-invariant basis components, respectively; employing an energy tank method to ensure system stability, calculating the filling rate of the energy tank based on the power dissipated by the basis damping when the energy tank is not full; if the energy tank is not depleted, using an energy exchange control method to replenish the collaborative robot with the energy required for time-varying stiffness and time-varying damping, and obtaining the desired velocity, desired position, and joint angle of the collaborative robot at the next moment. This method can dynamically and rapidly adjust admittance parameters according to the operator's intentions while ensuring the collaborative robot system remains strictly passive.

The invention discloses an experimental measurement test bed for interaction force between a retainer and a guide surface. The test bed comprises a base, a displacement loading device, an acting force measuring device, a tested unit, an inner ring loading device and a driving device, the tested unit comprises a tested retainer, a tested bearing inner ring, a tested bearing outer ring and a bearing seat; the acting force measuring device is used for measuring the force / torque borne by the measured retainer; the displacement loading device is used for adjusting the spatial position of the measured retainer through the acting force measuring device and positioning the measured retainer; the inner ring loading device is used for applying a static radial load to the inner ring of the tested bearing; the driving device is used for driving the tested bearing inner ring to rotate. The test bed can directly and accurately measure the interaction force between the retainer and the guide surface in the rolling bearing.

The invention belongs to the technical field of training robots, and particularly discloses a double upper limb robot interaction method and system based on motion performance adaptive assistance, and the method comprises the steps: S1, obtaining interaction data of each user during training; s2, generating a motion intention parameter, dynamically adjusting an impedance compensation parameter based on the motion intention parameter, and generating a variable impedance compensation force; s3, quantifying the exercise performance of the user according to the exercise state data of the user in the task cycle, and generating an exercise performance score; s4, obtaining the difference degree of the exercise performance between the users; s5, the ideal auxiliary force provided for each user in the next training period is dynamically adjusted; s6, generating a self-adaptive auxiliary force pointing to the training target; and S7, the real-time interaction force, the variable impedance compensation force and the self-adaptive auxiliary force of the corresponding user are fused to serve as input of a training robot admittance control scheme corresponding to the user, the expected speed and motion instruction of the mechanical arm are generated, and the mechanical arm is controlled to execute corresponding operation.

The application provides a three-dimensional model deformation simulation method and device and a storage medium, and belongs to the technical field of three-dimensional model simulation, and comprises the following steps: acquiring deformation weights of all vertices of a three-dimensional model and interaction forces borne by the vertices; wherein the deformation weights of the vertices in flexible regions, transition regions and rigid regions of the three-dimensional model are different; determining displacement amounts of the vertices according to the deformation weights and the interaction forces; and controlling movement of the vertices according to the displacement amounts. The deformation weights of the vertices in the flexible regions, the transition regions and the rigid regions of the three-dimensional model are different, so that controlling movement of the vertices according to the displacement amounts can make the flexible regions, the transition regions and the rigid regions of the three-dimensional model deform to different degrees, the three-dimensional model deformation simulation is more realistic, and the effect of the three-dimensional model deformation simulation is improved.

The invention discloses an AFM (atomic force microscope) and a piezoelectric ceramic driving method applied to high-speed feedback of an AFM (atomic force microscope) system, interaction force borne by a probe is enabled to be the same as preset interaction force by controlling the motion depth of piezoelectric ceramic, and the motion depth change of hardness detection piezoelectric ceramic is controlled to accord with a sine curve. Therefore, the movement depth change of the probe is a superposition waveform curve of the movement depth change of the two piezoelectric ceramics. Therefore, surface fluctuation detection and hardness detection of the to-be-detected surface are realized. According to the invention, the motion depth changes of the two piezoelectric ceramics are controlled to be non-interfering motion depth changes, so that the motion depth change (i.e., sinusoidal vibration) for detecting the viscosity of the surface to be detected and the motion depth change for feedback tracking of the appearance of the surface to be detected are two non-interfering motion depth changes. And the stroke of feedback tracking of the to-be-measured surface topography is ensured. Therefore, under the condition that the scanning speed of the atomic force microscope is high, a sample with large surface fluctuation can be measured.

This embodiment provides a control method and system for a non-grasping mobile pushing operation task of a humanoid robot, including: establishing a system interaction force model based on the pose information of pairwise interactions among the humanoid robot, the target object, and the environment, and then respectively establishing the dynamic models of the humanoid robot and the target object; establishing a system velocity constraint model and a system force constraint model based on the velocity and force constraint conditions satisfied by the pairwise interactions among the humanoid robot, the target object, and the environment, and obtaining the robot joint angular acceleration constraint conditions according to the established system velocity constraint model, system force constraint model, and the dynamic models of the humanoid robot and the target object; obtaining the system motion boundary conditions based on the established robot joint angular acceleration constraint conditions, and performing a non-grasping mobile operation task according to the motion trajectory of the humanoid robot under the condition of satisfying the system motion boundary conditions.

The invention discloses an intermolecular interaction force prediction method, device and equipment. The method comprises the following steps: calculating the similarity between atoms contained in each molecule through a truncation attention network; truncating each molecule according to the similarity by adopting a pre-configured truncating coefficient to obtain a substructure corresponding to each molecule; performing interaction force calculation according to the substructures corresponding to different molecules to obtain acting force between the substructures; and obtaining an interaction probability of the to-be-predicted molecule pair according to the acting force between the substructures, and determining an interaction force condition between the molecules according to the interaction force probability. According to the method, a substructure corresponding to each molecule is obtained by adopting a truncation coefficient for truncation according to the similarity, so that interference of irrelevant atoms in the substructures is avoided, the purity and the integrity of the substructures are kept, the situation of the intermolecular interaction force is obtained according to the acting force between the substructures determined by the accurately extracted substructures, and the accuracy of the intermolecular interaction force is improved. And the predicted condition of the intermolecular interaction force is more accurate.

Surgical systems and methods involving machine learning models to characterize tool interactions. A tool may be coupled to the robotic manipulator and configured to manipulate tissue. The sensing system measures a displacement of the tool, a speed of the tool, and an interaction force applied to the tool. A control system controls the manipulator to move the tool to interact with the tissue. In response to interaction of the tool with tissue over time, the control system obtains measurements of displacement, speed, and interaction force from the sensing system. The control system implements a machine-learned model for receiving and processing the measurements to estimate stiffness / damping parameters of the tissue, and evaluating variations in the estimated stiffness / damping parameters to generate a characterization regarding the tissue or tool interaction with the tissue. The control system controls the manipulator and / or the tool based on the characterization.

This application discloses a method and system for controlling a lower limb exoskeleton using a brain-computer interface based on intent confidence, relating to the field of medical rehabilitation technology. First, the system identifies the original electroencephalogram (EEG) signal to obtain intent confidence, and maps an impedance parameter set including joint stiffness and damping coefficients by combining gait phase information. Second, it extracts motion position and interaction force errors, compares the intent confidence with the actual execution state using a sliding time window to obtain neural matching errors, and merges these three into a total composite error. Simultaneously, it assesses human-machine coupling compliance based on changes in human joint angles and exoskeleton torque, and generates a safety gain coefficient. Finally, it performs gain calculations on the total composite error based on the impedance parameter set, and corrects it with the safety gain coefficient to obtain the target control torque for output to the actuator. This constructs a neural-force-motor three-loop architecture, achieving compliant and adaptive on-demand assistance and highly safe human-machine collaborative rehabilitation with defensive protection.

The application discloses an exoskeleton interactive force sensor based on an optical fiber grating, which comprises a sensitivity sensor I, a human-computer interaction binding structure and a sensitivity sensor II; the human-computer interaction binding structure is designed in a C-shaped hollow structure, and is used for realizing compliant binding with a human body; the sensitivity sensor I and the sensitivity sensor II are arranged at two ends of the outer side of the C-shaped hollow structure of the human-computer interaction binding structure respectively; the human-computer interaction binding structure comprises an arc-shaped binding structure and an arc-shaped binding structure, and two pairs of the arc-shaped binding structure and the arc-shaped binding structure are used for wrapping thighs; and the arc-shaped binding structure and the arc-shaped binding structure are connected through an adaptive adjustment structure. The application realizes high-sensitivity human-computer interaction force detection.

To provide a robot teaching device having an end effector operated by a teaching person intuitively, which can accurately measure interaction force between the end effector and a work object.SOLUTION: In a robot teaching device 5 equipped with a first end effector 1 gripped and operated by a teaching person, the first end effector 1 includes a first claw part 10 capable of switching its state between a state in which it can be opened and closed, and a state in which its opening or closing is fixed, a handle 12, and a first force sensor 11 for measuring force / torque between the first claw part 10 and the handle 12. Teaching data is generated on the basis of the output of the first force sensor 11 when the first claw part 10 is in the state in which the opening or closing is fixed and when the handle 12 is in the state in which it is gripped by the teaching person.SELECTED DRAWING: Figure 1

The invention discloses a device for reducing wheel-rail interaction force by magnetic repulsive force, which comprises a magnetic foot mounted on a wheel shaft system and a magnetic plate arranged on a track system, and the magnetic foot and the magnetic plate have the same magnetism to generate repulsive force. In the running process of the vehicle, the magnetic repulsive force between the magnetic feet and the magnetic plates balances part of the gravity of the vehicle, so that the interaction force between wheel rails is reduced, and meanwhile, the magnetic repulsive force can reduce impact vibration caused by geometric irregularity of the wheel rails. The device can eliminate related diseases of a vehicle system and a rail system caused by the wheel-rail dynamic effect, relieve the influence of vibration noise on the environment, and improve the service performance and the environment-friendly performance of rail traffic.

The invention provides a near-field dynamics GPU (Graphic Processing Unit) parallel simulation method for a quasi-brittle material and related equipment, which overcome the double defects in the aspects of mechanical modeling precision and calculation performance. The method comprises the following steps: constructing a near-field dynamic constitutive model; declaring a data structure based on the basic unit; initializing point coordinates of substance points; performing semi-neighborhood search according to the point coordinates and the near-field range to obtain a neighborhood information set; setting a prefabricated crack according to the neighborhood information set, and determining an initial key length, a material point volume correction coefficient, a surface correction coefficient and an initial crack; according to the displacement, the key data and the constitutive model, the near-field force and the substance point interaction pair fracture state are determined; the displacement state is updated according to the near-field force, the damage variable of the fracture state is updated according to the interaction of the material points, the steps of determining the near-field interaction force, updating the displacement state and updating the damage variable are iteratively executed until the termination condition is met, and the damage result and displacement state distribution are obtained.