352 results about "Mechanical models" patented technology

The invention relates to the technical field of medical robot systems, and discloses a nerve plexus intelligent positioning anesthesia puncture robot system based on multi-modal fusion, which performs time-space synchronization on ultrasonic image flow and contact force data. The frequency domain analysis module extracts a main peak frequency by using optical flow field frequency domain transformation, and generates a probability mask for marking pulsatile tissues. The viscoelasticity verification module calculates phase lag parameters of visual deformation and contact force, identifies tissue rheological properties and calculates a dynamic damping coefficient. The deformation compensation module calculates a mechanical residual error based on a reference mechanical model, and inversely calculates the mechanical residual error into space deformation displacement of the tissue. The feedback control module combines the probability mask and the deformation displacement to generate a motion instruction. According to the invention, through multi-modal data fusion, precise identification of tiny blood vessels, dynamic identification of tissue attributes and real-time compensation of soft tissue conceding deformation are realized.

The invention belongs to the technical field of civil engineering monitoring, and discloses an optical fiber strain sensor performance verification method and system for highway infrastructure monitoring, and the method comprises the steps: analyzing the influence rule of the parameter change of a coupling layer on the strain transmission efficiency of a measured sensor based on a layered material coupling mechanical model; based on the three-dimensional entity numerical model, analyzing an influence rule of layout process parameters of the tested sensor on the strain transmissibility; verifying the performance of the sensor in a laboratory environment by using a reduced scale model; on a real highway infrastructure or a constructed full-scale model, the performance of the sensor on an actual structure is verified through monitoring data. According to the invention, by constructing an integrity performance verification system from a theoretical model to numerical simulation and then to a reduced scale model test and entity structure verification, multi-dimensional and progressive performance verification of the performance of the optical fiber strain sensor for highway infrastructure monitoring is realized.

The invention relates to a biomimetic robot control system based on digital human action mapping, in particular to the technical field of robot control, solves the problem that a biomimetic robot is difficult to perceive physical attributes only by means of vision, achieves accurate pre-judgment of contact force and material attributes by analyzing digital human fingertip microscopic color change and object texture deformation, and improves the accuracy of the biomimetic robot control system. A robot can establish an adaptive mechanical model before contact, the system dynamically adjusts the flexibility and damping of a mechanical arm according to the environment rigidity and friction characteristics, soft grabbing of hard objects and stable grabbing of sliding objects are achieved, the hysteresis quality of traditional feedback control is effectively overcome, meanwhile, the time sequence feed-forward and energy monitoring mechanism is combined, and the control precision is improved. Collision protection is provided while zero-delay synchronization of actions is ensured, and the operation stability and safety of the robot for fragile and flexible objects in a complex environment are remarkably improved.

The invention discloses a dual-motor driving system of a variable-stiffness robot joint and a dual-motor cooperative variable-stiffness control method of the dual-motor driving system. The dual-motor cooperative variable-stiffness control method comprises the steps that motor parameters of a first motor and a second motor and joint parameters of the variable-stiffness robot joint are obtained; constructing a motor electrical model, a motor mechanical model, a joint mechanical model and a spring-damping model of the backlash according to the motor parameters and the joint parameters; determining a total optimization objective function, and solving the total optimization objective function according to the motor electrical model, the motor mechanical model, the joint mechanical model and the spring-damping model to obtain a first current error and a second current error; designing a cooperative controller according to the first current error and the second current error, and outputting a control quantity; and performing dual-motor cooperative variable stiffness control on the first motor and the second motor according to the control quantity. The response speed and rigidity flexibility of the variable-rigidity robot joint can be improved, and the variable-rigidity robot joint can be widely applied to the technical field of motor control.

The invention relates to a method, a system and equipment for predicting creep stress at a joint of a concrete structure and a medium. The method comprises the following steps: testing a concrete structure material and a concrete structure joint filling material, and constructing a joint material performance database based on test data; constructing a multi-scale mechanical model comprising a macrostructure model and a microcosmic interface model based on the seam material performance database; constructing an interface constitutive relationship based on the seam material performance database and the multi-scale mechanical model; and predicting the creep stress at the joint of the concrete structure based on the material performance database at the joint, the multi-scale mechanical model and the interface constitutive relationship. The method can fully consider the sudden change of the performance of the material at the joint and the interface effect, provides reliable technical support for the safety evaluation and maintenance of the concrete structure, and is particularly suitable for engineering application of large-span and high-rise buildings and the like with higher requirements on the long-term performance of the structure.

The invention discloses an aggregate random distribution concrete PFC (Power Factor Correction) simulation method, which comprises the following steps: a model selection step: determining a parallel bonding model as a mechanical model for concrete material simulation; a cement mortar matrix generation step of generating a cement mortar matrix by using particles in a set size range in a set space range based on the model, and setting pore density, particle density and contact model parameters; a coarse aggregate random distribution simulation step: randomly covering and grouping original particles in the matrix in a grouping and range mode; a concrete numerical model construction step: determining particle classification so as to distinguish cement mortar and coarse aggregate; and a model reliability verification step: comparing indoor test results through a uniaxial compression test. According to the method, the simulation accuracy is improved, the randomness of aggregate is reduced, the model reliability is ensured, the matrix simulation refinement degree is improved, and a method is provided for concrete modeling and performance research.

The invention discloses a vehicle network interaction intelligent scheduling optimization method and system fused with elastic optimization. The method comprises the following steps: acquiring a power grid state, an electricity price, an electric vehicle state and user behavior information in real time; determining a plurality of scheduling targets and constraint conditions; constructing elastic energy functions with rigidity coefficients for the scheduling targets respectively, and coupling the elastic energy functions to construct a total elastic energy function; defining a state vector reflecting the real-time state of the current system, and dynamically adjusting a coupling structure and a rigidity coefficient of the coupling structure between the elastic energy functions based on the state vector; and finally, on the premise of meeting constraint conditions, solving an optimal scheduling strategy for minimizing the total elastic energy. Through the bionic elastic mechanical model, adaptive coordination and optimization of multiple conflict targets are realized, the flexibility and stability of the electric vehicle participating in power grid adjustment are improved, and the elasticity and reliability of the whole vehicle network interaction system are enhanced.

The invention relates to the technical field of general control or regulation systems, in particular to a critical patient respirator parameter adaptive optimization control method, which comprises the following steps of: acquiring and processing physiological signals; constructing a dynamic respiration mechanical model based on a sliding time window recursive recognition algorithm; a man-machine coordination index is calculated, and the desynchrony degree is quantified; generating a ventilation parameter adjustment scheme through the reinforcement learning strategy network; and executing smoothing parameter adjustment, and introducing a safety boundary and a secondary fine adjustment mechanism. The breathing state of the critical patient can be accurately perceived and intelligently regulated and controlled, the ventilation efficiency is guaranteed, meanwhile, the man-machine synchronism and safety are improved, the medical care burden is relieved, and the prognosis of the patient is improved.

The invention discloses a blasting funnel volume solving method based on an improved physical information neural network. The method comprises the following steps: step 1, establishing a mechanical model of blast hole wall blasting load; 2, establishing a blasting physical model in which a columnar cartridge bag is equivalent to a spherical cartridge bag by using a Starfied superposition method; step 3, constructing a blasting funnel volume prediction model based on the wavelet multi-scale synchronous compression transformation enhanced physical information neural network, constructing a solution space of a physical field by using the wavelet multi-scale synchronous compression transformation, and training the physical information neural network in which a blasting funnel physical control equation, an initial condition and a boundary condition are loss functions; and 4, intelligently predicting the volume of the blasting funnel by adopting the trained enhanced physical information neural network. The trained physical information neural network enhances the robustness and generalization ability of the blasting funnel volume prediction model, and provides high-precision theoretical support for blasting design optimization in engineering blasting.

The invention discloses an aircraft skin assembly control method and system, and the method comprises the following steps: segmenting a skin and a frame from an image based on a skin surface image through employing a deep learning segmentation model; registering and splicing the images captured by different spectrum cameras to obtain a complete skin image; based on the complete skin image, using a region expansion method to identify and track a skin surface deformation region; preprocessing the original skin model through a finite element method to obtain a corresponding grid model; estimating stress distribution in the current assembly state based on the force haptic image and a stress transfer model; and based on the deformation area and the stress distribution, generating an assembly path and a pressure adjustment instruction by adopting a self-adaptive control strategy, and controlling the assembly process. Through fusion of a multispectral vision technology and a high-precision force tactile perception technology and combination of a deep learning algorithm and a nonlinear mechanical model, accurate identification of skin surface features and accurate positioning of a deformation area are realized, and the assembly control precision is improved.

The invention relates to the technical field of rock mechanics and deep stratum reconstruction engineering, and discloses a method for determining a roof rock stratum fracturing horizon based on multi-scale rock mechanics characterization, and the method comprises the following steps: firstly, obtaining drilling cuttings to prepare a nanoindentation test piece, and carrying out gridding dotting test and mineral scanning; secondly, calculating micromechanical parameters such as reduction modulus, fracture toughness, elastic index and plastic work ratio based on test data; constructing a macroscopic mechanical model by utilizing the microscopic parameters and the mineral distribution characteristics to carry out numerical simulation to obtain a macroscopic elastic modulus and uniaxial compressive strength; and finally, performing normalization and weighting processing on macro and micro parameters, constructing a comprehensive compressibility index and a comprehensive brittleness index, and optimizing a target fracturing layer position and a perforation position according to the comprehensive compressibility index and the comprehensive brittleness index. According to the method, cross-scale coupling of microscopic component attributes and macromechanical response is achieved, the problem of parameter acquisition caused by heterogeneity of deep rock strata is solved, the limitation of single-scale evaluation is overcome, and the fracture horizon identification precision and the engineering success rate are improved.

The invention discloses a prediction method and a prediction system for fracture risk of an osteoporosis patient. The method comprises the following steps: firstly, collecting a plurality of parameters such as age, bone mineral density, vitamin D level and the like of the patient; constructing a bone time-varying factor and dynamic prediction model, and determining the influence weight of each parameter on the bone condition at different time nodes; then, a three-dimensional mechanical model is constructed through mechanical simulation of the skeleton microstructure, stress distribution, strain states and structural stability of the skeleton under different loads are simulated, and the model is corrected by fusing parameters to influence weights; then the fracture probability in a future preset time period is calculated; and finally, a result is presented through a nomogram visualization model. The system realizes the above method, can predict the fracture risk more accurately, and provides powerful support for clinical diagnosis and treatment.

The invention relates to the technical field of tunnel and underground engineering construction, and particularly discloses a complex variable stratum shield tunnel dynamic regulation and control tunneling method which comprises the following steps: S1, performing multi-dimensional data acquisition by utilizing a sensor array; s2, carrying out preprocessing operation on the collected multi-dimensional data; s3, constructing a shield tunneling-based mechanical model, a stratum three-dimensional geologic model and a tunneling parameter optimization model; s4, utilizing a CNN-LSTM machine learning network to predict the tunneling posture of the shield tunneling machine, the cutter abrasion loss and the stratum response; s5, dynamically regulating and controlling tunneling parameters in different scenes according to a prediction result; and S6, updating model parameters by using a gradient descent method, and optimizing machine learning network performance by using RMSprop. By the adoption of the shield tunnel dynamic regulation and control tunneling method for the complex and changeable stratums, the construction efficiency can be effectively improved, the construction safety is enhanced, and the shield tunnel tunneling problem in the complex and changeable stratums is solved.

The invention discloses a real-time virtual environment view layout algorithm based on spherical space guidance. The algorithm comprises the following steps that an original view is acquired and preprocessed; abstracting into a circular structure and completely mapping to a constructed spherical view projection structure; weight analysis is carried out, a preset threshold value is compared, a high-weight standard view set and a low-weight standard view set are divided, and dynamic batch layout optimization processing is carried out on the high-weight standard view set; constructing a space pressure function field for the low-weight standard view set, and determining a target position by using a space pressure field guiding method; smooth movement from the current position to the target position is achieved through a Bezier curve interpolation method; and when the viewpoint or view angle change exceeds the threshold value, re-calculating the layout until the change amplitude is smaller than the threshold value, and generating a final layout. According to the method, the spherical space projection and the adaptive mechanical model are combined, the large-scale view layout is optimized, the method has the advantages of being efficient, stable and real-time, and the data visualization effect in the virtual environment is improved.

The invention discloses a non-contact ice friction coefficient measuring method and device, and relates to the tribology testing technology, and the method comprises the following steps: obtaining a motion image of a slide block on an artificial ice rink by using a camera system; performing preprocessing and target detection on the acquired image to obtain coordinate information of the sliding block in a world coordinate system; and based on the coordinate data of the sliding block, fitting and solving the acceleration of the sliding block by adopting primary function expansion in combination with a Tikhonov regularization method, and carrying out inversion in combination with a friction mechanical model and a kinematic model to obtain an ice friction coefficient. Compared with a traditional contact type method, the in-situ high-precision measurement of the ice friction coefficient can be realized under the condition of no sensor attachment or external force interference, the defects of low measurement precision and strong invasiveness in the prior art are effectively overcome, and the method can be applied to the fields of winter road safety detection and ice and snow sports.

The invention discloses a train wheel set rapid detection and maintenance positioning device and method for a train factory, and belongs to the technical field of train wheel set detection. A rotary jacking mechanism abuts against a wheel shaft of a wheel set to jack the wheel set up from a rail of a maintenance platform and drive the wheel set to rotate, and a rim detection assembly is arranged between the rail and the wheel; the wheel rim detection assembly can conduct continuous inspection and probing through a mechanical probe rod and an ultrasonic probe, the wheel side detection assembly is arranged on the rotary jacking mechanism and detects the side face of a wheel through a laser scanning detector, and the wheel rim detection assembly and the wheel side detection assembly transmit probing results to the upper computer. A mechanical model of wheels on the two sides is formed in the upper computer, a damage point is displayed, the upper computer controls a stepping motor of the rotary jacking mechanism to move, the damage point can be selected through a screen of the upper computer, the rotary jacking mechanism is controlled to rotate slowly, and finally the damage point stays at a probing point of an ultrasonic probe or a laser scanning detector. And maintenance personnel can identify suspicious damage points conveniently.

The invention provides a highway bridge bearing capacity calculation method and system, and relates to the technical field of bearing capacity calculation, and the method comprises the steps: obtaining basic parameters of a target highway bridge; performing model construction according to the basic parameters to obtain a bridge three-dimensional mechanical model; carrying out load mode analysis according to the bridge three-dimensional mechanical model, and carrying out space distribution on a dead load standard value and a live load dynamic effect based on the number of lanes and a load action area to obtain a total load value; stress field solving is conducted according to the total load value and the bridge three-dimensional mechanical model, and stress-strain distribution data are obtained by calculating stress-strain distribution of the main beam midspan section and the pier beam connection area section; calculating the ultimate bearing capacity according to the stress-strain distribution data, and evaluating the bearing capacity based on the relationship between the allowable stress and the maximum stress of the material to obtain the ultimate bearing capacity value of the bridge; and correcting the ultimate bearing capacity value of the bridge based on the service life and the current damage degree to obtain a highway bridge bearing capacity evaluation result.

The invention relates to the technical field of power transmission line verification, and discloses a point cloud-based power transmission line windage yaw double-parabola verification method, system and device and a medium, and the method comprises the steps: obtaining three-dimensional point cloud data of a power transmission line corridor, and extracting key ground feature parameters; according to the input target simulation working condition parameters, applying a wire state equation to iteratively solve the dynamic horizontal tension of the wire under the corresponding working condition, and combining a double-parabola mechanical model to calculate a three-dimensional space curve of the power transmission line under the windage yaw state; inputting a three-dimensional space curve and key ground feature parameters, and calculating a three-dimensional space minimum clearance distance between the power transmission line and a key ground feature in a simulated windage yaw state; and after comparison, a verification result is output. According to the method, the wind deflection and sag forms are accurately reconstructed by applying a double-parabola mechanical model, and dynamic simulation of different working conditions is realized in combination with a wire state equation. By combining high-precision mechanical analysis with an automatic verification process, the stability and safety of power grid operation can be improved.

The invention relates to an aluminum plate casting and rolling control method and system, and the method comprises the steps: collecting real-time technological parameters, including molten aluminum temperature, aluminum plate thickness, rolling speed, rolling pressure, cooling speed and surface quality information, in an aluminum plate casting and rolling process, and predicting aluminum plate temperature distribution, stress strain, thickness change and potential defects based on thermodynamics and mechanical models; the casting speed, the rolling speed, the rolling pressure and the cooling condition of the molten aluminum are dynamically adjusted, closed-loop control is achieved, the system comprises a data acquisition module, a data processing and analysis module, a control and execution module and a man-machine interaction and visualization module, and the system supports automatic correction of thickness deviation and surface defects, abnormal alarm and historical data analysis. The method adopts model predictive control, an artificial intelligence algorithm or a hybrid optimization algorithm to realize adaptive control. The method has the advantages that the thickness uniformity and the surface quality are optimized, the production efficiency and reliability are improved, and the safe, intelligent and efficient operation effect in the aluminum plate casting and rolling process is achieved.

The invention relates to the technical field of urban municipal engineering safety, and provides an urban gas pipe network space-time risk assessment method and system, and the method comprises the steps: constructing a pipe network digital twinborn model fusing multi-source data; aiming at the metal pipeline, calculating the effective wall thickness of the pipeline by applying the nonlinear time-varying corrosion model corrected by the soil corrosivity index; calculating the biaxial stress of the pipe wall through a mechanical model considering the coupling effect of internal pressure, soil, traffic, temperature and frost load based on the effective wall thickness; according to the material of the pipeline, calculating a dynamic safety coefficient by adopting a criterion based on fracture mechanics or allowable stress; and finally, risk levels are divided according to the safety coefficient, and space-time visual display is carried out on a GIS platform. According to the method, the defects that a traditional method depends on historical data, models are simplified and space-time dynamic analysis is lacked are overcome, the pipe network risk can be accurately quantified and predicted, and a scientific basis is provided for preventive maintenance.

The invention belongs to the technical field of intelligent crack detection, and relates to an intelligent bridge pavement crack detection and analysis method based on machine vision. According to the method, candidate crack areas are identified through image acquisition and processing, real crack areas are determined through division calculation, then space areas are divided, adjacent crack relations are classified, and finally a crack propagation rate distribution diagram is generated. According to the method, the real crack is identified by confirming the crack convergence point and combining the geometrical morphology characteristics of the neighborhood, so that the problem of false edge false detection caused by neglecting the crack convergence characteristics in the prior art is effectively solved, the false detection rate is remarkably reduced, and the accuracy and robustness of crack detection are greatly improved; and the expansion rate distribution diagram is generated by dividing space areas, classifying adjacent crack relationships and combining a mechanical model, so that the limitation that an expansion driving mechanism is difficult to analyze due to lack of adjacent crack space relationship identification in the prior art is overcome, the crack expansion behavior can be accurately judged, and a solid basis is provided for an engineering structure operation and maintenance decision.

The invention provides an intelligent assessment method for cervical lateral deviation based on multi-modal fusion and deep learning, and solves the technical problems of single data source, weak feature generalization ability and large assessment result error caused by only analysis of a static single frame in existing cervical lateral deviation assessment. The method comprises the steps of obtaining multi-modal data, performing preprocessing, attitude normalization and feature weighted fusion to obtain fused multi-scale features, performing mapping to generate a heat map, and performing peak retrieval on the heat map to output key points; tracking time sequence tracks of the key points, correcting abnormal key points, and collecting continuous multi-frame key points for key point detection to obtain target key points; and constructing a cervical vertebra trunk coupling mechanical model, dynamically optimizing a gravity line reference axis, correcting pelvic inclination attitude deviation, and optimally solving the optimal offset through a Lagrange multiplication method and a least square method. The method can be widely applied to the technical field of medical image analysis and computer-aided diagnosis.

The invention provides a cross-scale model enhanced fatigue damage prediction method and system, and belongs to the field of material fatigue performance prediction. The method comprises the following steps: constructing a discrete dislocation kinetic model and a cyclic crystal plastic model, and calibrating parameters of the discrete dislocation kinetic model; determining to-be-optimized parameters of the cyclic crystal plastic model and inverting the optimal values of the to-be-optimized parameters to obtain a calibrated cross-scale mechanical model; importing the initial microstructure features of the material into a cross-scale mechanical model to obtain an extended data set containing multi-scale features and fatigue damage results; and constructing a full-connection neural network prediction model, carrying out training based on the extended data set, calculating the Shapley value of the input feature by using a model interpretability tool, and outputting the contribution degree of the multi-scale microstructure feature to the fatigue damage. According to the method, cross-scale interpretable prediction from a micromechanism to macroscopic performance is realized, and a new direction is provided for accurate evaluation of the fatigue life of the heterogeneous material and optimization design of a microstructure.

The invention provides a single building earthquake damage assessment method, system and device and a medium, and relates to the technical field of building engineering earthquake resistance, and the method comprises the steps: obtaining the attribute data and earthquake motion parameters of each building in an assessment region; dividing the evaluation area into a plurality of seismic oscillation input blocks according to the spatial distribution of each seismic monitoring station; aiming at each single building in the vibration input block of each place, according to the attribute data of the single building, constructing a finite element mechanical model; inputting the seismic oscillation parameters corresponding to the single building into the finite element mechanical model, executing dynamic time-history analysis and calculation, and generating structural response parameters of the single building; and in combination with the structural response parameters and the attribute data of the single building, calculating a damage index of the single building, and according to the damage index, generating an earthquake damage assessment result of the single building. The technical effect of the invention is that the accuracy of the earthquake damage assessment result is improved.

The invention discloses a roadway support digital design method and system based on surrounding rock fracture evolution simulation, particularly relates to the technical field of roadway engineering digital twin modeling and optical fiber stress sensing, and is used for solving the problems that in an existing support design method, the evolution process of a digital model and a physical entity is asynchronous, and the simulation precision is insufficient. Real-time surrounding rock strain data are obtained through a distributed optical fiber sensor, actual ground stress field distribution is obtained based on strain data inversion, the dominant direction of a potential fracture surface is identified, an anisotropic strength parameter field of a mechanical model is updated, and the updated model is operated to simulate the surrounding rock fracture evolution process. And identifying a composite high-risk area by combining strain energy density distribution and crustal stress field characteristics, and finally generating accurate digital support design parameters to realize dynamic optimization and accurate design of a roadway support scheme.

The application discloses a kind of depot train wheelset rapid detection and maintenance positioning device and method, belong to train wheelset detection technical field, rotating jacking mechanism will be contacted with wheelset axle and lift wheelset from the rail of maintenance platform, and drive its rotation, rail and wheel are provided with flange detection component, flange detection component can be continuously checked and explored by mechanical probe rod and ultrasonic probe, wheel side detection component is set on rotating jacking mechanism, wheel side detection component is detected to wheel side by laser scanning detector, flange detection component and wheel side detection component are transmitted to host computer, and the mechanical model of both sides wheel is formed in host computer and shows damage point, host computer controls the stepping motor movement of rotating jacking mechanism, damage point can be selected by host computer screen, and rotating jacking mechanism is controlled to rotate slowly, finally make damage point stay to the exploration point of ultrasonic probe or laser scanning detector, it is convenient for maintenance personnel to identify suspicious damage point.

The present invention performs simulation for a case where a plurality of degrees are set for feedforward, and provides assistance in adjustment of an acceleration / deceleration time constant and a feedforward parameter. The present invention is provided with: a mechanical model creation unit that creates mechanical models of a motor and a mechanism portion of a machine tool, a robot, or an industrial machine; a simulation unit that includes the mechanical models and a feedforward processing section and that is for performing simulation of operation of a servo control device for controlling the motor; and an adjustment unit that adjusts an acceleration / deceleration time constant for generating a position command, and a parameter of the feedforward processing section. The adjustment unit adjusts a plurality the acceleration / deceleration time constants and parameters corresponding to when a plurality of degrees has been set for the feedforward processing section.

The invention discloses a method for rapidly generating non-uniform structure characteristics and mechanical properties of a weld zone, and belongs to the technical field of welding quality assessment, and the method comprises the following steps: S1, obtaining a characteristic temperature-time curve representing a weld thermal history through a dynamic temperature measurement method; s2, inputting the characteristic temperature-time curve and the chemical components of the base metal into a thermal-metallurgical coupling model, and predicting a non-uniform microstructure phase distribution diagram of the weld seam area; and S3, based on a semi-empirical mechanical model, mapping the non-uniform microstructure phase distribution diagram into a mechanical property distribution diagram of the welding seam area, and completing rapid identification of the microstructure characteristics and the mechanical properties. According to the rapid generation method for the non-uniform structure characteristics and the mechanical properties of the welding seam area, rapid and non-destructive identification of the non-uniform structure and the properties of the welding seam is achieved, the defects of lag and damage of a traditional method are overcome, and an effective means is provided for online evaluation of the welding quality and process optimization.

The invention relates to a method for optimizing the number of swing legs of passive deformation wheels of a bionic composite mobile robot, the robot is formed by connecting a plurality of sections of driving modules through a flexible hinge device, each driving module comprises two passive deformation wheels and a vehicle body, and each passive deformation wheel is independently driven by a stepping motor and comprises an inner ring, an outer ring and a spring set; wherein the cross rod and the spoke rods are fixed on the driving shaft, and the cross rod, the spoke rods and the driving shaft form an inner ring; the outer ring is composed of a hub and a plurality of arc-shaped swing legs, and the swing legs are distributed on the outer edge of the hub at intervals and rotationally connected with the hub through pin shafts. The spring group comprises a pressure spring and a tension spring, the pressure spring is connected with the cross rod and the hub, and the tension spring is connected with the spoke rod and the swing leg; the method comprises the following steps that mechanical property differences of different numbers are quantitatively compared through three constraints of anti-skidding, low oscillation and structure adaptation of an obstacle crossing mechanical model, the number of swing legs is determined, and stable obstacle crossing is achieved. The method helps to improve the stability of the whole vehicle body when the robot crosses obstacles.

The application discloses a design method of an integrated mechanical model of a compression-resistant composite anti-floating anchor rod, and specifically comprises the following steps: obtaining a parameter set of a multi-layer structure of a target geotechnical engineering anti-floating anchor rod, analyzing the hierarchical interface mechanical behavior, generating an interface shear stress transfer function, embedding the function into an axisymmetric stress analysis framework, obtaining an axial force and a side resistance distribution function of the whole length of the anchor rod, constructing an integrated mechanical balance equation set, segmentally numerically solving the equation set, outputting mechanical response characteristic curves at different depths, and finally determining a limit anti-floating bearing capacity prediction value according to the curves as a design output.