277 results about "Kinetic analysis" patented technology

The invention is an advanced deep learning system that combines a latent transformer core with a latent dynamics analyzer. This system processes input data into latent space vectors, which are then analyzed in parallel for both prediction and dynamic modeling. The latent transformer generates short-term predictions, while the latent dynamics analyzer derives equations of motion describing the underlying system dynamics. By integrating spectral analysis and change detection, the system can identify significant shifts in behavior, particularly useful for complex systems like financial markets. The invention enables more accurate predictions, interpretable insights, and early detection of regime changes. Its end-to-end training approach ensures all components work harmoniously, balancing predictive accuracy with physical plausibility and interpretability.

The invention belongs to the technical field of multi-body dynamics analysis, and discloses a wind driven generator transmission chain rigid-flexible coupling multi-body dynamics analysis method based on dynamic mode decomposition, and the method comprises the steps: firstly, enabling multi-degree-of-freedom time series data to be non-linearly embedded into a high-dimensional feature space through an encoder neural network; extracting a dominant mode by utilizing intrinsic orthogonal decomposition (POD), and constructing a low-dimensional feature space; parameterized dynamic mode decomposition and radial basis function regression are adopted, a mapping relation between system parameters and Koopman operators is established, and accurate prediction of dynamic characteristics under variable working conditions is achieved; and finally, reconstructing a physical response through a decoder, and optimizing model parameters in combination with an error driving mechanism. The problems that a traditional method is low in calculation efficiency, poor in nonlinear adaptability and difficult in multi-parameter coupling prediction are effectively solved, the efficiency and precision of transmission chain dynamic analysis are remarkably improved, and reliable technical support is provided for state monitoring and service life prediction of the wind turbine generator.

The invention discloses a digital twinborn model construction method, a life prediction method, a model construction device and equipment of a crane, and relates to the technical field of industrial Internet of Things, the method comprises the following steps: constructing a multi-dimensional digital twinborn model, the multi-dimensional digital twinborn model comprises a physical entity layer, a connection layer, a virtual model layer, a twinborn data layer and a service function layer, the virtual model layer comprises a target twin model, and the service function layer corrects key components of the crane; transmitting the physical parameters of the crane to a connection layer for preprocessing to obtain a physical data set; the physical data set is transmitted to a virtual model layer, and an initial twin model is obtained through kinetic analysis and knowledge graph processing; and transmitting the virtual data set to a twin data layer, calculating target correction parameters according to the physical data set and the virtual data set, and correcting model parameters of the initial twin model to obtain a target twin model. According to the method, the problem of insufficient physical mapping precision of the existing virtual model is solved.

The present application provides a dynamics analysis method for an ammonia combustion refrigeration system in large park cooling. The method comprises: on the basis of a geometric structure of an ammonia combustion chamber and a fuel supply amount, calculating the heat generated by ammonia combustion and analyzing the heat transfer mode between the combustion chamber and a desorption tower, the heat transfer mode comprising direct contact type heat transfer and partition type heat transfer, and simulating the heat transfer process to obtain and draw the heat flux distribution of the tower wall surface; on the basis of the flow state and a relationship curve between the pressure drop and the flow velocity, analyzing the desorption process of a refrigerant in a solution, and on the basis of the concentration of the solution, a boiling point of the refrigerant, and the vapor pressure, calculating local desorption rates at different positions in the desorption tower and the refrigerant vapor generation amount; and on the basis of the heat flux distribution, calculating the temperature distribution of the solution, and analyzing the heat transfer and mass transfer processes in the desorption tower to obtain a local heat transfer coefficient and the mass transfer efficiency distribution of the surface of a filler.

The invention discloses a closed-loop control digital microfluidic system and a method thereof, and relates to the technical field of microfluidics, and the method comprises the following steps: initializing a digital microfluidic chip electrode array, setting an electrode spacing, an electrode size and a voltage upper limit, collecting a no-load state signal, and generating initial reference data; liquid drops are formed at the preset position of the digital micro-fluidic chip, and according to the initial reference data, the initial position, the volume and the form information of the liquid drops are collected, and a liquid drop initial state data set is generated; inputting the initial state data set of the liquid drop into a pre-trained closed-loop prediction model, performing kinetic analysis and trajectory prediction calculation, generating an expected motion trajectory of the liquid drop, and comparing the expected motion trajectory with the real-time state data flow of the liquid drop to generate deviation feedback data of the liquid drop; and dynamically adjusting the initial driving voltage parameter according to the droplet deviation feedback data to generate a closed-loop driving voltage sequence. The liquid drop trajectory control precision is improved, and motion errors caused by environmental disturbance and electrode response differences are reduced.

The invention relates to the technical field of compressors, and discloses a scroll compressor shafting dynamic balance simulation method, device and equipment and a medium, and the method comprises the following steps: carrying out fluid mechanics analysis based on a movable scroll plate model to obtain initial three-way gas force; performing dynamic analysis based on a scroll compressor model by taking the initial three-way gas force as a boundary condition to obtain a displacement result of a movable scroll plate; inputting the displacement result into the movable scroll plate model, updating the position and the motion state of the movable scroll plate, and carrying out fluid mechanics analysis again to obtain a new three-way gas force; and performing dynamic balance optimization on the scroll compressor model by taking the new three-way gas force as a boundary condition until a preset condition is met, and obtaining a target dynamic balance result. According to the technical scheme, the precision of dynamic balance simulation of the shaft system of the scroll compressor can be improved, and therefore the product reliability is improved through optimization of dynamic balance.

The invention discloses a tower crane motion planning method and device in a complex environment, and the method comprises the steps: building a nonlinear model for comprehensively describing the motion characteristics and transient behaviors of a crane-load system on the basis of kinetic analysis, and carrying out differential flat analysis; a BiRRT * algorithm based on direction bias is provided, a node expansion process is optimized by introducing a target bias mechanism of fusion region probability sampling and based on an improved potential field function direction guiding mechanism, and the efficiency and quality of path planning are improved. An improved random tree extension mechanism is combined with a depth deterministic policy gradient (DDPG) of reinforcement learning, and adaptive adjustment of sampling direction and step length parameters is realized. Path points obtained through path planning serve as profile value points of trajectory planning, system full-state constraint conditions such as load obstacle avoidance and shimmy reduction are fully considered, multi-target trajectory planning is carried out based on an NURBS curve, and a multi-target comprehensive optimal trajectory on the aspects of total hoisting time, operation energy consumption and load shimmy suppression is obtained.

The invention provides a gear contact fatigue life prediction method considering macro-micro geometric parameter influence. The method comprises the following steps: firstly, establishing a tooth surface contact-dynamics analysis model considering macro-micro geometric parameter influence, and calculating tooth surface dynamic load distribution; secondly, establishing a calculation model of the stress on the surface and below the surface of the gear considering the influence of lubrication and surface roughness, and calculating the oil film pressure and the stress on the surface and below the surface of the gear; and finally, establishing a gear contact fatigue life prediction model considering the influence of macro and micro geometric parameters, and calculating the contact fatigue life of the gear. According to the method, the influence of the rigidity change of the gear on the contact fatigue life of the gear is considered, the contact fatigue life of gears with different web structures is predicted, and the deviation between the contact fatigue life obtained through theoretical calculation and the actual contact fatigue life is reduced. Meanwhile, the method considers the influence of the error on the contact fatigue life of the gear, so that the prediction of the contact fatigue life of the gear with the modification and the error is realized.

The invention relates to the technical field of power construction, discloses a multi-system coupling control crossing frame erection collaborative operation method and system, and aims to improve the stability and collaborative efficiency of an erection process. The method comprises the following steps: establishing a three-dimensional digital model of a spanning structure body, synchronously accessing a plurality of sensor acquisition systems, and acquiring space coordinates of key nodes of the spanning structure body, environmental wind load and operation state information of construction equipment in real time; dynamically generating an anti-overturning constraint condition based on space coordinates and wind load information, and generating a cooperative scheduling strategy in combination with an equipment state; and constructing a space pose matching model to output deviation correction parameters. The stability of the frame body is evaluated through the dynamic analysis model, a load early warning index is generated, and an equipment action instruction is generated through the path optimization model. And adjusting the operation priority according to the early warning index, and synchronously sending the updated priority and the action instruction to the terminal to realize multi-system closed-loop control.

The invention provides a method for determining the working load environment of an aero-engine rotor connection structure, belongs to the field of dynamic analysis and design of aero-engine rotors, and aims at a rotor structure system with a connection structure in an advanced aero-engine to determine the type of a load possibly borne by the connection structure. Based on a rotor finite element model and aerodynamic thermodynamic parameter input of an engine, aerodynamic load analysis, temperature distribution simulation, rotor dynamic characteristic simulation and the like are carried out respectively, and working load amplitudes of a connection structure under different working conditions are obtained. The energy differential method is innovatively adopted to obtain the bending moment at the connecting structure, and the accuracy of bending moment calculation is improved. According to the method, the working load environment of the rotor connection structure can be accurately obtained, accurate load boundary conditions are provided for mechanical property simulation of the rotor connection structure, so that the simulation analysis precision is improved, and meanwhile, reliable data support can be provided for the mechanical property of the connection structure and rotor dynamics optimization design.

The invention discloses an order-lifting sliding mode robust control method for an active-passive vibration isolation system, and belongs to the technical field of vibration isolation system control, and the method comprises the steps: introducing a feed-forward control path, predicting the vibration frequency and amplitude at a future moment based on the historical state information of a controlled system, building an overall vibration isolation target model based on the prediction, and carrying out the control of the overall vibration isolation target model. Resolving a target transfer function of an active execution mechanism through kinetic analysis of the active-passive vibration isolation system, so as to calculate a feedforward control signal; the method comprises the following steps: modeling an active-passive vibration isolation system, constructing a nonsingular terminal sliding mode surface, collecting system state error information, and generating a feedback control signal of an actual controlled system through integral controller design; a feedforward control signal and a feedback control signal are reasonably coupled and superposed to serve as control input of a controlled system. According to the order-lifting sliding mode robust control method for the active-passive vibration isolation system provided by the invention, the anti-interference capability and the stability of the active-passive vibration isolation system are improved.

The invention discloses a new energy electricity price accurate prediction method and system based on virtual power plant aggregation regulation and control, and relates to the technical field of industrial data processing. The method comprises the steps: S1, carrying out the preprocessing of meteorological environment data, output equipment data and battery power grid operation data; s2, constructing a variation dynamics analysis and mutation depth discrimination mechanism based on the meteorological environment data, and entering an output prediction and optimization process and a scheduling load response process in a layered manner; s3, executing energy storage collaborative optimization scheduling and parameter correction according to a meteorological output regression prediction analysis result; and S4, performing electricity price time sequence multi-source driving analysis, and reconstructing an electricity price fluctuation response strategy. The problems that new energy output violently fluctuates within a minute level due to sudden weather change, and electricity price prediction lags due to the fact that an existing prediction model depends on too low weather data updating frequency and cannot capture the rapid change in time are solved.

The invention discloses a semi-active suspension attitude coordination method based on a suspension controller, and belongs to the technical field of attitude coordination, and the method comprises the following steps: S1, carrying out kinetic analysis on a whole vehicle suspension; s2, determining the control force of the vehicle body suspension based on the kinetic analysis result; and S3, according to the control force of the vehicle body suspension, a vehicle body posture coordination controller is used for completing posture control. The dynamic response of the pitch angle and the roll angle of the vehicle body is considered, the vehicle body attitude compensation strategy is constructed to restrain the vehicle body attitude change, and the vehicle stability and comfort are improved; the vehicle body attitude compensation controller is designed, accurate adjustment of pitching and roll is achieved, and the vehicle body attitude compensation method has good application value and development prospects.

The invention relates to a measuring point deployment and fault diagnosis method for cooperative monitoring of multiple components of an electric shovel. According to the method, firstly, a key vibration measurement surface is selected through kinetic analysis, the optimal measurement point deployment position is selected based on the effective vibration information proportion and the relative effective information amount, and the scheme reasonability is evaluated through information entropy. Then, vibration measuring points are installed on key components such as a driving motor, a disc brake and a reduction gearbox, the vibration state of the system is comprehensively obtained, and a single fault feature extractor is further constructed; then, a system-level fault diagnosis model is constructed, the model comprises a single fault feature extractor, a component space relation graph, a classifier and the like, and cooperative fault diagnosis of the key components of the electric shovel lifting mechanism transmission system is achieved through the training model. According to the method, the accuracy and comprehensiveness of fault diagnosis are improved, the downtime and maintenance cost caused by faults are reduced, effective technical support is provided for safe operation of mining machinery, and the method has important practical application value.

The invention discloses an aviation kerosene quality online detection and optimization system based on a green hydrogen substitution technology, and relates to the technical field of quality detection, and the aviation kerosene quality online detection and optimization system comprises a quality monitoring module, an optimization control module and a carbon footprint tracking and verification module. The quality monitoring module monitors the purity of sulfide, aromatic hydrocarbon and hydrogen in real time through a multispectral and electrochemical sensor, determines the optimal mounting position of the sensor by combining hydrodynamic analysis, triggers early warning when the sensor exceeds the standard, and pushes the sensor to the optimization module. The optimization control module dynamically adjusts temperature, pressure and green hydrogen flow based on a deep reinforcement learning algorithm, constructs a multi-objective optimization model, maximizes sulfur removal efficiency, reduces energy consumption and carbon emission, and realizes closed-loop intelligent regulation and control; according to the method, the accuracy and real-time performance of aviation kerosene quality detection and regulation are improved, effective tracking and verification of the green hydrogen full-life-cycle carbon footprint are realized, and the green sustainable development of aviation kerosene production is promoted.

The invention relates to the technical field of respirators, and discloses a respirator flow dynamic adjusting system based on airflow sensing, which is characterized in that after starting, a multi-mode sensing module acquires spatial flow velocity distribution and dynamic characteristics of respiratory airflow, and generates a composite data flow fused with flow field information; the composite data flow is subjected to nonlinear analysis to generate a state vector representing breathing stability, and the state vector is used for identifying fluid abnormal risks; the state vector generates an optimized execution instruction set by the self-adaptive control engine in combination with the energy state of thermoelectric conversion; the execution instruction set drives the piezoelectric valve and the shear response humidifying layer to cooperatively adjust the flow and the humidity, and outputs physiologically matched breathing gas; fusion collection of spatial flow velocity distribution and dynamic characteristics of respiratory airflow is achieved through the multi-mode sensing module, the limitation of traditional single-point measurement is broken through, and the sensing precision is remarkably improved; a breathing chaos index is constructed through nonlinear kinetic analysis, and early warning of the breathing rhythm stability and the fluid abnormal risk is achieved.

The invention discloses a sleeve-shaped tuned mass damper mounting method based on parameter design calculation. The sleeve-shaped tuned mass damper mounting method comprises the following steps that S1, parameters of a single-column wind turbine platform and a whole machine structure are calculated; s2, calculating parameters of the sleeve-shaped tuned mass damper according to the structural parameters of the wind turbine; s3, the sleeve-shaped tuned mass damper is installed on the single-column type wind turbine platform; in the step S2, a kinetic equation is established through a kinetic analysis model, the optimal damping coefficient cd and the distance d of the translational and rotational freedom degrees are solved, and the step S2 comprises the substeps that S21, the single-column wind turbine platform and the sleeve-shaped tuned mass damper are simplified into equivalent four-freedom-degree models; s22, assuming that external excitation is a simple harmonic load, and deducing translation response and rotation response of the sleeve-shaped mass body and the single-column type wind turbine platform; s23, determining a damping tuning parameter and a frequency tuning parameter; s24, solving an optimal damping coefficient copt by a simultaneous equation in combination with a branch resonance point condition; and S25, calculating the distance d according to the rotation radius ratio rho.

The invention relates to the technical field of composite material structure dynamics analysis, and provides a method and system for predicting the inherent frequency of a three-phase functionally graded composite material conical plate, and the method comprises the steps: employing an improved Halpin-Tsai model to calculate the equivalent parameters of a GPL-containing two-phase composite matrix, solving the equivalent parameters of a three-phase composite layer, and calculating the inherent frequency of the three-phase composite material conical plate. The method comprises the following steps: constructing a nonlinear geometrical relationship between a displacement field and a strain field, calculating a stiffness coefficient of each layer, constructing kinetic energy of the three-phase composite material conical plate, calculating an energy coefficient according to the stiffness coefficient of each layer, constructing potential energy of the conical plate according to the energy coefficient, and constructing a modal displacement function by adopting a Chebyshev polynomial and a boundary function. And establishing a characteristic equation based on a minimum potential energy principle and solving to obtain the inherent frequency of the three-phase composite material conical plate. According to the method, efficient calculation of the inherent frequency of the three-phase composite material conical plate is achieved, and the reliability and engineering application value of structural dynamics analysis are remarkably improved.

The invention is suitable for the field of portal frames, and discloses a portal frame dynamics analysis method which comprises the following steps: establishing a full-order finite element model of a portal frame, and obtaining a mass matrix and a stiffness matrix of the full-order finite element model; dividing the full-order finite element model into a plurality of substructures based on the modular structure characteristics of the portal frame, and decomposing the degree of freedom of each substructure into an internal degree of freedom and a boundary degree of freedom; constructing a fixed boundary main modal matrix and a constraint modal matrix of each substructure, and constructing a reduced-order basis matrix; performing modal polycondensation on a mass matrix and a stiffness matrix of the full-order finite element model by using the reduced-order basis matrix to generate a reduced-order mass matrix and a reduced-order stiffness matrix, and constructing a reduced-order kinetic equation; and solving the reduced-order kinetic equation to obtain reduced-order modal coordinates, carrying out inversion reduction in combination with the reduced-order basis matrix and the reduced-order modal coordinates to obtain a displacement response vector of the full-order finite element model, and retaining key kinetic information of the portal frame to the greatest extent through reduced-order efficiency improvement.

The invention discloses a signal fusion processing method for a motor imagery training brain-computer interface, and particularly relates to the technical field of neural signal processing. Multi-channel scalp electroencephalogram data of a user are collected in real time, a time-varying space covariance matrix sequence is constructed through Riemannian geometric space mapping analysis, and a phase amplitude coupling index sequence between different brain rhythms is analyzed and calculated through cross-band coupling dynamics; performing feature hierarchy joint coding on the spatial covariance matrix sequence and the phase amplitude coupling index sequence to generate a real-time neural representation tensor; calculating the distribution divergence of the real-time neural representation tensor relative to the static reference feature manifold in the initial training stage so as to quantitatively represent the mismatch degree; and finally, dynamically adjusting a weighting coefficient and a fusion structure of the multi-modal signal fusion device according to the characterization mismatching degree, and outputting a motion control instruction matched with the current brain state of the user in real time. According to the method, the motion intention decoding precision and stability in the motion imagination training process are improved.

The invention discloses a sliding bearing service life prediction method, and relates to the technical field of sliding bearing intelligent monitoring, and the method comprises the steps: an edge calculation node uses a quantum decryption algorithm to decrypt multi-modal time series data, and carries out the fractional order chaotic dynamics analysis, thereby achieving the prediction of the service life of a sliding bearing. Performing phase-space reconstruction on the multi-modal time sequence data, extracting fractal dimensions of phase-space attractors, and fusing chemical and crystal data to a quantum entanglement space by adopting a quantum variational auto-encoder to generate a high-dimensional data set fusing macroscopic and microscopic features; constructing a quantum enhanced life prediction model, performing parameter calibration by adopting quantum Bayesian optimization, and predicting a bearing health index according to the high-dimensional data set; according to the invention, the quantum-enhanced life prediction model is constructed through the quantum variational auto-encoder, and the model parameters are dynamically calibrated in combination with the quantum Bayesian optimization algorithm, so that the accuracy and reliability of bearing life prediction are improved.

The invention discloses an ethylene cracking device yield prediction method based on an ideal mechanism model and machine learning, and the prediction method comprises the steps: firstly confirming theoretical factors, and constructing an ideal mechanism model based on the theoretical factors to predict a first yield; secondly, obtaining residual absolute error data of the yield of the ethylene cracking device by subtracting the first yield from the actual value of the yield; constructing a machine learning model to predict a second yield based on the residual absolute error data of the yield of the ethylene cracking device; the final predicted yield = the first yield + the second yield. The method can be applied to most of prediction problems with physical significance, and is a universal strategy; an original machine learning model does not need to be changed, an ideal mechanism model based on kinetic analysis is constructed, and the yield prediction precision of the ethylene cracking device is greatly improved.

The invention discloses a dynamic simulation analysis method for a floating type offshore wind turbine generator, and the method comprises the steps: carrying out the simulation and mechanical analysis of all parts in the floating type offshore wind turbine generator through dynamic analysis software in combination with a topological structure diagram; the dynamic analysis software performs joint simulation on the variable pitch control model and the yaw control model and controls rotation of blades and a main frame, so that full-coupling dynamic analysis of the floating type wind turbine generator is realized; the situation that offshore wind power is in an unattended state for a long time when the floating type offshore wind turbine generator is subjected to the wind wave coupling effect is avoided, and it can be guaranteed that parts of the wind turbine generator run reliably for a long time under the complex working condition.

The invention relates to the technical field of automobile structures, in particular to a main and auxiliary plate spring suspension system, an anti-roll optimization design method thereof and a mobile carrier, and the method comprises the following steps: establishing a simulation model of a whole vehicle and the main and auxiliary plate spring suspension system, carrying out kinematics and dynamics analysis by using simulation software, calculating roll gradient indexes under different working conditions, and calculating the anti-roll optimization design of the main and auxiliary plate spring suspension system. Optimizing the structural parameters and the performance parameters and optimizing the parameters; and performing simulation model comparison test on the optimized whole vehicle and the main and auxiliary leaf spring suspension system and the whole vehicle and the main and auxiliary leaf spring suspension system before optimization, and determining the anti-roll reliability of the optimized whole vehicle and the main and auxiliary leaf spring suspension system. According to the optimization design method, an accurate simulation model is established, simulation software is utilized for analysis, the optimization direction is determined, parameters are optimized, and finally the optimization effect is verified through a comparison test, so that the problems existing in a traditional design method can be effectively solved, and the operation stability and safety of the vehicle can be remarkably improved.

The invention relates to the technical field of underwater towing, in particular to an underwater towed body towing performance design method, which comprises the following steps of: performing static dynamic analysis on a towed body; carrying out dragging dynamics analysis on the towed body; constructing a towed body structure model, and performing hydrodynamic simulation calculation; establishing a dynamic coupling numerical simulation model of the towing system; and carrying out dragging attitude simulation, and obtaining an optimal design scheme. According to the invention, key indexes such as trim and rolling of the towed body in the towing system are ensured to meet the stability standard, so that the urgent requirements of marine acoustic detection on high precision and high reliability are met.

The invention provides an unmarked kinetic analysis method and system for real-time tracking and shooting of an unmanned aerial vehicle, and the method comprises the steps: carrying out the flight control of the unmanned aerial vehicle, and obtaining the dynamic image data, tracked and shot by the unmanned aerial vehicle, of a sporter running on a playground curve or a curve path; synchronizing and preprocessing the dynamic image data recorded by different cameras; extracting 2D key points of a human body from the preprocessed image, and reconstructing a three-dimensional motion track of the human body in a local coordinate system of the camera; carrying out posture compensation on the three-dimensional motion trail, ensuring the consistency of human body joint point trails under a ground world reference system, carrying out human body model scaling and muscle model scaling calculation, and carrying out inverse kinematics analysis; according to the inverse kinematics data, the centripetal acceleration of the sporter in the curve motion is calculated; and performing inverse dynamics calculation based on the centripetal acceleration, and calculating the ground support force. According to the invention, unmarked dynamic analysis of real-time tracking shooting of the unmanned aerial vehicle can be carried out.

A method for controlling a motion of a multi-jointed bionic dolphin relates to a technical field of damage detection using a bionic robot. The method comprises: constructing a three-dimensional model and a three-dimensional model in computational domain of the multi-jointed bionic dolphin, and performing pre-processing; importing the model file after the pre-processing into analysis software for computational fluid dynamics for the hydrodynamic simulation to obtain a thrust-time curve and a hydrodynamic curve under a specified underwater working condition, then finding a difference, and fitting to obtain velocity-resistance fitting curves; performing a kinetic analysis, and deducing a kinetic model; completing kinetic coupling to obtain kinetic parameters according to the kinetic model, the thrust-time curve, and the velocity-resistance fitting curves; and controlling output torques by a pulse width modulation (PWM) technique.

The application relates to the technical field of four-degree-of-freedom parallel mechanisms, in particular to a three-branch-chain space four-degree-of-freedom parallel mechanism which comprises a static platform, a mixed branch chain, a simple branch chain one, a simple branch chain two and a dynamic platform; the application has a mixed branch chain of a space sub-branch chain type and two simple branch chains, forms a basic motion chain containing three loops, thereby realizing the advantages of good rigidity and high precision, the displacement of the dynamic platform in the X-axis and Y-axis directions is controlled by two moving pairs respectively, the displacement in the Z-axis direction and the rotation around the Z-axis direction are controlled by four moving pairs, therefore, the application has good partial motion decoupling, the symbolic position direct solution is easy to obtain, thereby facilitating the motion control, trajectory planning and dynamics analysis of the parallel mechanism, and the three-dimensional position working space of the dynamic platform is large, the rotation capacity is strong, and the branch chains are not prone to interference.

The invention discloses a proportional valve control method based on high-pressure multi-medium annular gap flow prediction, and relates to the technical field of hydraulic control element dynamic analysis, and the proportional valve control method comprises the following steps: collecting a real-time state signal of a micro proportional valve; inputting the collected real-time state signal into a multiphase flow transient coupling equation, calculating a velocity field and a pressure field in the micro proportional valve, and correcting the velocity field; calculating gas phase distribution according to the corrected velocity field and the real-time state signal; calculating a transient fluid load according to the gas phase distribution and the pressure field; inputting the transient fluid load into a structural kinetic equation of the micro proportional valve, and calculating the structural displacement of the micro proportional valve; calculating an opening compensation value according to the structural displacement, and converting the opening compensation value into PWM duty ratio correction; and generating a proportional valve control instruction according to the PWM duty ratio correction. Efficient and accurate prediction of the flow characteristics under the high-pressure complex working condition is achieved, and therefore the proportional valve is accurately controlled.

The invention belongs to the field of complex engineering system design and kinetic analysis, and particularly discloses an analysis method for verifying complex system empirical tolerance rationality and application thereof, and the method specifically comprises the following steps: (1) establishing a parameterized model; (2) constructing a multi-physics field dynamics simulation model; (3) importing boundary conditions of operation conditions; (4) operation quality and performance index extraction; (5) data-driven correlation analysis; and (6) verifying and optimizing the reasonability of the empirical tolerance. The method has universality and expandability, can be widely applied to empirical tolerance verification and design optimization of complex systems in the fields of rail transit, aerospace, power transmission, precision manufacturing and the like, and provides a unified theory and calculation framework for tolerance rationality evaluation.