568 results about "Kinetics equation" patented technology

A balance control method for a wheel-legged robot is provided. The robot includes a moving wheel, n links, and n rotating joints, the moving wheel being connected to a first link through a first rotating joint of the n rotating joints, and the n links being connected in series through n−1 rotating joints other than the first rotating joint, n being a positive integer greater than 1. The method includes: acquiring a state quantity of the wheel-legged robot at a first moment; determining dynamics model parameters according to a dynamics equation of the wheel-legged robot and the state quantity at the first moment; establishing a sliding surface according to the state quantity at the first moment; calculating rotation torques of the n rotating joints according to the sliding surface and the dynamics model parameters; and controlling the rotating joints according to the rotation torques of the n rotating joints.

The invention relates to an optimization design method for a multi-fulcrum elastic ring supporting structure of an aero-engine rotor system, and belongs to the technical field of aero-engine vibration control and rotor dynamics simulation. Firstly, a finite element or lumped unit model is adopted to establish a coupling kinetic equation of a rotor and an elastic ring, and fluid-solid coupling factors such as inner and outer oil films of the elastic ring and orifice flow are considered; then, through critical rotating speed and vibration harmonic response analysis, sensitivity evaluation is carried out on rigidity and damping characteristics of different supporting positions, and target vibration reduction modes corresponding to all fulcrums are identified; then, coupling simulation and multi-objective optimization are carried out around the number of bosses of the elastic ring, the height of the bosses, the damping aperture, the thickness of a thin wall and other key structure parameters, and the optimal design meeting the vibration reduction requirement of a rotor system and the strength reliability requirement of the elastic ring is obtained through iteration; and finally, an optimization result is applied to structure manufacturing and assembling. The method can effectively reduce the vibration amplitude of the rotor when the rotor crosses the multi-order critical rotating speed.

The invention relates to the technical field of belt conveyor dynamic characteristic research, in particular to a trailer type belt conveyor dynamic characteristic simulation method, which comprises the following steps: respectively carrying out stress analysis on a trailer frame, each wheel and a conveying belt unit in a trailer unit, and sorting the degree of freedom; establishing an overall coordinate system, a vehicle body coordinate system, a contact coordinate system and a conversion relation; respectively establishing kinetic equations of the wheel pair and the vehicle supporting frame; kinetic parameters of the trailer unit are determined; according to the Hamiltonian principle, a vehicle supporting frame vertical motion equation and a vehicle supporting frame nodding motion equation are established, and then a linear second-order differential equation of a vehicle supporting unit is obtained; and compiling a calculation program by using numerical calculation software, and simulating the wheel-rail vibration characteristics of the trailer unit in the straight-line-segment advancing process. On the basis of the multi-degree-of-freedom multi-body dynamics theory, a trailer type belt conveyor system nonlinear dynamics equation is constructed, and a wheel pair, a trailer frame and a six-degree-of-freedom motion equation for coupling the wheel pair and the trailer frame are analyzed.

The invention relates to the technical field of power equipment fault diagnosis, in particular to a transformer overheating fault intelligent diagnosis system based on a physical information neural network. According to the invention, physical constraint filtering is carried out on signals through the adaptive noise suppression module; a loss function fusing a heat conduction equation, a gas decomposition kinetic equation and an insulation aging kinetic equation is constructed through a physical information neural network, and coupling modeling of temperature and gas and collaborative prediction of the aging state of insulation paper are achieved; spatial topological features and time sequence features are extracted through a multi-modal feature fusion module, and cross-modal association is established by adopting an attention mechanism; predicting a future feature trajectory through a fault evolution prediction module and outputting hierarchical early warning; and finally, outputting fault types, severity and maintenance suggestions. According to the method, a physical mechanism and data intelligence are deeply fused, advanced early warning and accurate positioning of an overheat fault are realized, and meanwhile, the blank that insulation failure cannot be pre-judged in the prior art is filled.

The invention discloses a simulation method, device and equipment for predicting flow and deformation of a porous medium and the medium. The method comprises the steps that a computational domain is selected, a corresponding computational grid is generated, and porosity initialization is conducted on the computational domain; determining a time step length and a discrete format, and setting a non-uniform factor to solve a control equation set which comprises a continuity equation, a fluid dynamics equation, a skeleton mechanics equation and a porosity updating equation; and analyzing and displaying a solving result. According to the porous medium flow and deformation simulation method independent of hypothesis and empirical parameters, the method is based on the basic principle of the microcosmic fluid-solid coupling effect, a porous medium fluid-solid coupling body kinetic equation is adopted, the situation that a traditional modeling method depends on volume averaging hypothesis and depends on a multi-phase interaction model is avoided, and the modeling efficiency is improved. The method has cross-scale applicability, and provides a new theoretical basis and prediction means for the development of technologies related to porous medium multiphase dynamics and multi-field coupling problems.

The invention discloses a gear service life prediction method based on a lubrication-vibration coupling model and a related device, and relates to the technical field of gear service life prediction.The method comprises the steps that firstly, according to gear transmission input data, a three-dimensional mixed lubrication model containing a Reynolds equation coupling solving system is established, and meanwhile system excitation is calculated; then the oil film and the meshing rigidity are connected in parallel to form comprehensive rigidity, a bending-torsion coupling kinetic equation containing torsion and transverse freedom degrees is established, and a lubrication-vibration coupling model is constructed; finally, by means of coupling model output, the lubrication state is evaluated, the vibration characteristic is optimized, and the fatigue and abrasion life is predicted. According to the method, the three-dimensional mixed lubrication model and the system excitation calculation and coupling dynamics model are integrated, the lubrication and vibration coupling effect is considered, the limitation of independent analysis is overcome, the evaluation precision is improved, gear parameter optimization, lubrication scheme making and fault diagnosis can be guided, and the method has engineering application value.

The invention discloses a strict safety trajectory optimization control method and system for an under-actuated bridge crane. The method comprises the following steps: constructing a variable rope length kinetic equation model of the bridge crane; setting an end point constraint, a speed constraint and an acceleration constraint for a given initial trolley and rope length expected running track; respectively optimizing a trolley reference speed and a rope length reference speed based on the end point constraint, the speed constraint and the acceleration constraint; performing angle constraint by using a first control obstacle function, and setting an upper bound and a lower bound of a swing angle state variable; performing obstacle avoidance constraint by using a second control obstacle function; obtaining a cost function according to the first control barrier function and the second control barrier function; and solving the QP problem to obtain the corrected control input mu meeting the angle constraint and the obstacle avoidance constraint. According to the strict safe trajectory optimization control method and system for the under-actuated bridge crane, the moving trajectory is optimized, meanwhile, obstacles can be effectively avoided, and swing of the load is reduced.

The invention discloses a hydraulic arm safety control method and device based on parallel learning and a high-order CBF, and the method comprises the steps: building a kinetic equation of a hydraulic mechanical arm through a Lagrange method, integrating unmodeled dynamics, structural parameter change and external interference into an uncertain item, and describing the generalized uncertainty of the uncertain item in a linear parameterization form; for the problem of insufficient excitation in a complex environment task, a parallel learning mechanism is introduced, and historical data and real-time data are combined to realize parameter identification. For high relative order safety constraints (such as obstacle distance constraints and joint limiting constraints) in a task space, an obstacle function family is constructed. A dynamic error buffer function is introduced, and a high-order adaptive control barrier function condition is designed. The high-order self-adaptive control obstacle function constraint is embedded into a real-time quadratic programming solving problem, input obtained through optimization solving can keep the track precision, meanwhile, a joint instruction is automatically corrected to prevent constraint failure, and minimum intervention type safety control is achieved.

The invention discloses a flexible finger friction contact collision dynamics simulation method based on an absolute node coordinate method, which comprises the following steps: simplifying a finger of a flexible manipulator into a connecting rod system, taking a tail end knuckle as a flexible beam for consideration, and carrying out unit division on the flexible beam system based on the absolute node coordinate method; a contact collision process is described by using an additional constraint method, meanwhile, switching of a viscous state and a sliding state is considered, a friction-containing flexible finger contact collision dynamic model is established, and a dynamic equation of a system is solved by adopting a double-circulation implicit integral algorithm; and obtaining a curve graph that the flexible finger tail end displacement changes along with time and the finger tail end contact force changes along with time. The invention provides a new frictional contact collision dynamic model for a flexible manipulator system, and provides more perfect data information and image information for researchers in the field.

The present invention belongs to the field of lifting equipment control technology, and specifically relates to a dynamic modeling method and control method for double-bridge lifting equipment. The dynamic equations of a five-degree-of-freedom double-bridge crane are constructed using the Lagrangian method, and the geometric constraint relationships between trolley I and trolley II in the direction parallel to the bridge and the vertical direction are constructed. The dynamic model of the double-bridge crane is constructed by combining the dynamic equations and the geometric constraint relationships, and the dynamic model is transformed into a general model. Based on the general model, a first error function is constructed based on the difference between the actual position and the expected position, and a virtual controller is constructed based on the first error function. A second error function is constructed based on the virtual controller, and an actual controller is constructed based on the first error function, the virtual controller, and the second error function. This technical solution models the system as a whole through the constraint relationship between the two trolleys, taking the mass of the hook into consideration during the modeling process, and solving the singularity problem.

The invention belongs to the related technical field of robot machining deformation optimization, and discloses a redundant angle and process parameter joint optimization method and device for complex curved surface robot machining, and the method comprises the steps: (1) forming a multi-domain composite constraint by a joint movement limit constraint, a pose singularity constraint and a machining deformation error constraint corresponding to a robot machining system; carrying out fusion modeling in the redundant angular space based on multi-domain composite constraints so as to map constraints of different dimensions in different spaces into a unified fusion potential field; (2) establishing a kinetic equation taking a virtual torque generated by the fusion potential field as driving input, sequentially solving based on the obtained kinetic equation and a numerical solution method to obtain a redundant angle of each cutter location point, and then obtaining a continuous and smooth redundant angle track; and (3) based on the obtained redundant angular trajectory, performing iterative solution on the optimization model by using an optimization algorithm to obtain an optimal processing parameter combination. According to the method, collaborative optimization of the process parameters and the redundant corners is realized.

The invention relates to the technical field of belt conveyor dynamic characteristic research, in particular to a rail type belt conveyor turning section dynamic characteristic simulation method, which comprises the following steps: carrying out stress analysis on a trailer unit and arranging the degree of freedom; establishing an overall coordinate system, a vehicle body coordinate system, a contact coordinate system and a conversion relation; establishing a kinetic equation of the trailer unit; kinetic parameters of the trailer unit are determined; establishing a left and right wheel set motion equation of the trailer unit according to the Hamiltonian principle, and further obtaining a linear second-order differential equation of the trailer unit; and compiling a calculation program by using numerical calculation software, and simulating the wheel-rail vibration characteristics of the trailer unit in the advancing process of the turning section. Based on a multi-degree-of-freedom multi-body dynamics theory, a nonlinear kinetic equation of a belt conveyor system is constructed, and a six-degree-of-freedom motion equation of a trailer unit is analyzed.

The invention discloses a fluid-structure interaction numerical simulation method, device and equipment and a medium, and the method comprises the steps: selecting a fluid-structure interaction computational domain, generating a computational grid, and marking the computational domain according to fluid and solid distribution information; determining a solving time step length and a discrete format, and selecting a control equation set for solving, the control equation set comprising a continuity equation, a fluid dynamics equation, a solid dynamics equation and a phase transfer equation; and analyzing and displaying a solving result. According to the efficient fluid-solid coupling numerical simulation method, global unified calculation is achieved, explicit fluid-solid decoupling is not needed, a global fluid-solid coupling body kinetic equation is adopted, errors caused by fluid-solid decoupling processing in a traditional split-phase solving method are avoided, and the method does not need to depend on and repeatedly generate a complex body-fitted grid; the control equation is based on each phase conservation equation on a physical continuous domain and realizes interphase accurate association through an interface continuity condition, and the fluid-solid coupling problem can be accurately and quickly solved.

The invention provides a glyceryl triacetate production parameter control method and system based on reinforcement learning, and relates to the technical field of optimization control methods, and the method comprises the steps: obtaining the production parameters of glyceryl triacetate; based on the kinetic model, constructing a kinetic equation of the esterification reaction of glycerol and acetic acid; constructing a digital twinborn simulation environment of the glyceryl triacetate production process; defining a reinforcement learning framework by taking a digital twin simulation environment as a scene; according to the reinforcement learning framework, taking the Elman neural network as a state predictor, and predicting the state of the glyceryl triacetate; solving the reinforcement learning framework through an MO-MPO algorithm, and determining an optimal control strategy and an optimal production parameter sequence corresponding to the optimal control strategy; judging whether the process capability index is smaller than a process capability index threshold value or not; if yes, continuing to solve the reinforcement learning framework; otherwise, outputting an optimal production parameter sequence; and controlling the optimal production parameter sequence through a PID (Proportion Integration Differentiation) control algorithm.

The invention relates to the technical field of geotechnical engineering and geological disaster monitoring, in particular to a rockburst tendency dynamic discrimination method, and aims to solve the limitation caused by the fact that a dynamic evolution process is simplified into a quasi-static attribute in traditional rockburst tendency evaluation. According to the method, rockburst tendency is defined as a hidden state variable evolved along with time, a physical constraint state space model containing a hidden state kinetic equation and a multi-modal observation equation is constructed, continuous stress-strain and discrete acoustic emission data are fused, hidden state probability distribution is estimated in real time through online Bayesian inference, and the probability distribution of the hidden state is estimated in real time. And in combination with adaptive information weight updating and physical consistency constraint, predicting a future state trajectory, calculating a risk probability exceeding a critical threshold, and outputting a dynamic rockburst tendency level. According to the scheme, continuous, dynamic and prospective judgment of the rockburst tendency is realized, and the accuracy and reliability of early warning are improved.

The invention discloses a confidence embedded model predictive control method, a medium and equipment, and belongs to the technical field of suspension control. According to the method, a kinetic equation of a suspension system is established, a data-mechanism dual-drive uncertainty quantification method is adopted, original operation data of a maglev train and suspension state information measured on line are utilized, and dynamic characteristic learning modeling is conducted on the suspension system under the constraint of the kinetic equation; state quantity distribution of suspension air gaps, vertical speed, electromagnet current and the like at future moments is predicted, and prediction mean values and prediction standard deviations of corresponding states are obtained. In model prediction control optimization, a nominal trajectory of the suspension system is constructed by a predicted state mean value, and a penalty term proportional to prediction uncertainty is added into a cost function; meanwhile, confidence coefficient constraint is constructed based on the predicted standard deviation, and dynamic constraint tightening of key physical quantities such as suspension air gaps, vertical speed and coil current is achieved. According to the invention, real-time sensing and self-adaptive closed-loop control of the operation risk of the suspension system are realized.

The invention discloses a floating fan aerodynamic load real-time mixing test method and system based on AI enhancement, and the method comprises the steps: calculating the six-degree-of-freedom motion information of a floating foundation through a numerical calculation model based on a real-time floating foundation kinetic equation; the method comprises the following steps: carrying a reduced-scale fan model on a six-degree-of-freedom motion platform, placing the six-degree-of-freedom motion platform on a wind tunnel atmospheric boundary layer, controlling the six-degree-of-freedom motion platform based on floating foundation six-degree-of-freedom motion information, driving the reduced-scale fan model to move, generating an aerodynamic load in a simulated wind environment, measuring an original load signal, and correcting the original load signal. Synchronously recording the actual pose of the six-degree-of-freedom platform; and AI correction is carried out on the corrected load signal and the actual pose of the six-degree-of-freedom platform to obtain a net aerodynamic load, the net aerodynamic load is fed back to the numerical calculation model, and closed-loop updating is carried out to realize coupling circulation. According to the method, the problem of interaction between numerical values and physical boundaries is solved, and the test precision of the large floating fan under the complex environment load can be remarkably improved.

The invention discloses a rigid chemical kinetic equation solving method based on a hard conservation constraint PINN model, and belongs to the technical field of chemical kinetic equation solving. According to the method, a hard conservation constraint strategy is introduced into the PINN, only calculation is carried out in the calculation process, s3 and s1 are indirectly deduced through a conservation expression, it is ensured that the PINN can conform to the solution of an equation set in the training process, meanwhile, the material conservation law is strictly obeyed, and the invariance of the material conservation quantity is ensured. Compared with a neural network model depending on pure data driving or a soft constraint mode adopted in a PINN, the method has the advantages that the prediction precision is improved on the basis of ensuring physical consistency, and the relative error between a prediction solution and a numerical solution is effectively reduced.

The invention provides a PINN-based natural epidemic disease transmission mechanism modeling method and system, which are used for mechanism deduction and space-time prediction of a natural epidemic disease transmission process. The method comprises the following steps: firstly, constructing a host population model and a host-population coupling propagation dynamics model; secondly, the dynamic equation set serves as a physical constraint to be embedded into the physical information neural network; and finally, through joint loss function optimization network learning, bidirectional driving of case data prediction and parameter inversion is realized. The method solves the problems that in the prior art, a host-crowd coupling mechanism is lacked, environmental factor modeling is insufficient, and data driving and mechanism modeling are separated, two-way driving of mechanism modeling and data learning is achieved, and space-time simulation precision, interpretability and model generalization ability are remarkably improved.

The invention discloses a high-frequency vibration absorption fastener design method for restraining local bending mode vibration of a steel rail. The method comprises the following steps that a finite element analysis model of the steel rail is established according to the set length and steel rail parameters, a rail model under the harmonic excitation condition is established, and a relational expression met by the overall rigidity and damping of a double-layer fastener model is established; constructing a kinetic equation of vertical movement of the iron base plate; constructing a target optimization function for designing the track fastener system based on the error; and constructing a cost model of the fastener in the production process, optimizing cost control of fastener design, outputting the quality of the iron base plate, the rigidity of the upper layer structure and the rigidity of the lower layer structure under the optimal cost control, and designing the fastener system. According to the method, high-feasibility solutions are provided for relieving local bending modal vibration of the steel rail, high-order polygons of wheels and corrugation of the steel rail.

The invention provides a robot full-flexible rigid-flexible coupling parametric modeling method and system, and belongs to the technical field of robot modeling. According to the method, firstly, based on MDH flexible expansion parameters, a floating coordinate method, a finite element method and a Rayleigh beam model are combined, and a full-flexible kinematics model containing flexible deformation of a base, joints and connecting rods is established; secondly, the speed and acceleration of key nodes of the model and any point of the flexible connecting rod are calculated in a recursive mode; constructing a local kinetic equation of each concentrated mass component and each distributed mass component based on a virtual power principle, and converting the local kinetic equations into a generalized coordinate space through a generalized Jacobian matrix; and finally, assembling to form a unified robot rigid-flexible coupling kinetic equation. According to the method, high efficiency and automation of the modeling process are realized, the accuracy of the model for describing the dynamic characteristics of the robot is improved, and an accurate basic model is provided for high-precision dynamic analysis and control of the robot.

The invention discloses a complex terrain adaptability control system for a rescue robot, and belongs to the technical field of robots. According to the invention, full-closed-loop control is realized through the instruction layer, the hardware layer, the control layer and the monitoring layer. The control layer takes a posture adjusting module as a core, is linked with a PID (Proportion Integration Differentiation) and an impedance controller, and is combined with forward / reverse kinematics and suspension detection to realize accurate correction of a joint angle; the hardware layer feeds back attitude, joint movement and contact force data in real time by means of multiple sensors; meanwhile, a whole vehicle kinetic equation is established based on a spiral theory and a virtual work principle to deduce a contact force component, and a sliding rate is defined to quantify traction characteristics. According to the invention, through fusion of multi-module cooperation and mechanical modeling, organic unification of attitude control, force control flexibility and traction performance monitoring is systematically realized, and a complete attitude-force-traction cooperative control system is constructed.

The invention discloses a residual service life prediction method based on a variational auto-encoder lightweight physical information neural network. Firstly, input sensor signals are screened and preprocessed according to a signal change trend; inputting the processed data into a hidden state mapping module to extract a hidden state; inputting the time information and the extracted hidden state into a residual life prediction module, calculating a partial derivative of the residual life to the hidden state by using an automatic differential technology, and outputting a predicted residual life value; inputting the high-order partial derivative of the hidden state and the residual life into a physical information module approximation system degradation kinetic equation; a partial differential equation between sensor data and residual life is defined, a loss function is formed by weighting data fitting loss and physical constraint loss, and the physical constraint is embedded into the model to improve the reasonability of prediction; and finally, training the model to obtain a final predicted value. According to the method, the number of parameters is remarkably reduced, and meanwhile better prediction performance and higher interpretability are shown.

The invention relates to a self-adaptive fault-tolerant generalization control method for an autonomous underwater vehicle, which comprises the following steps of: considering primary and quadratic term damping effects of water, unknown constant matrixes of a mass matrix and an inertia matrix of the autonomous underwater vehicle and external interference factors; an actuator effectiveness index matrix is introduced to model the autonomous underwater vehicle into an under-actuated model, and meanwhile it is ensured that the resultant force of gravity and buoyancy is zero, and kinematics and dynamics equations of the autonomous underwater vehicle are obtained; a controller is designed based on a backstepping method, a position error and a saturation function are defined, a Lyapunov function is selected, the position error is driven to be within a preset fixed constant range, an estimation rule and a projection function are introduced for solving the problem of unknown parameters to calculate thrust and control input, and high-precision trajectory tracking control over the autonomous underwater vehicle is achieved. Compared with the prior art, the method does not need linearization or conversion dynamics, can solve the problems of fault tolerance and time-varying interference, is better in performance, and effectively improves the control precision and stability of the autonomous underwater vehicle.

The invention belongs to the field of vehicle suspension system control, and particularly relates to vehicle suspension system control applying an inertial container device, in particular to a vehicle suspension control method based on dynamic surface control, which comprises the following steps of: establishing a whole vehicle controlled model; solving a strict feedback system of a whole vehicle kinetic equation; defining a position error; designing an intermediate virtual variable; dynamic surface control; and the electromagnetic thrust is solved. According to the method, coordination control of the vehicle suspension system can be achieved, the riding comfort of the vehicle is improved, and the method provides a new research thought and direction for design and application of the vehicle suspension.

The invention relates to a flight path tracking control method for an unmanned autonomous submersible vehicle, and belongs to the technical field of unmanned submersible vehicle control. The method comprises the following steps: firstly, establishing a nonlinear dynamic model of the submersible vehicle, analyzing kinematics and dynamic characteristics of the nonlinear dynamic model, considering various underwater forces and moments, and defining an inertial coordinate system and a submersible vehicle body coordinate system to obtain a kinematics equation and a dynamic equation so as to provide a basis for control design; secondly, a non-singular integral terminal sliding mode control method is adopted, a sliding mode surface is designed, the singular problem of traditional sliding mode control is avoided, a sliding mode control law is deduced, system finite time convergence to a balance point is achieved, and an expected state is rapidly tracked. And finally, a brand new and simple adaptive control strategy is provided, an adaptive law is designed according to system errors and sliding mode surface information, a gain matrix is adjusted in real time, and system uncertainty and external interference are compensated. The method has the advantages of being high in robustness, rapid in convergence, simple and easy to implement.

The invention relates to the technical field of education data analysis, and discloses a student development comprehensive evaluation method based on a multi-dimensional accomplishment index, and the method comprises the steps: obtaining the multi-dimensional performance data of a student, and constructing an N-dimensional state vector containing the position and speed; constructing an N-dimensional dynamic virtual potential energy field formed by superposing static potential energy representing an education target and dynamic potential energy reflecting individual history; simulating the evolution of an N-dimensional state vector in a field according to a kinetic equation in which dynamic inertial mass is introduced to generate a development trajectory; and finally, quantitatively analyzing the track characteristics, and outputting an evaluation result. According to the method, the historical intervention effect can be evaluated by comparing the actual trajectory with the reference trajectory, preferential selection can be carried out by simulating future trajectories under different interventions, and a basis is provided for formulating a personalized strategy. According to the method, the physical dynamics model is introduced into educational evaluation, dynamic, process and predictive evaluation is realized, static limitation of traditional evaluation is overcome, and evaluation is more scientific and objective and has prospective guiding significance.

The invention relates to the technical field of PTA production control, and discloses a PTA mixed feeding control method and system. The system comprises a mechanism modeling module, a data driving prediction module, a dynamic fusion module, a rolling optimization module and an online learning module. The mechanism modeling module constructs a sub-model based on a PTA mixed reaction kinetic equation, and outputs a theoretical feeding constraint value; the data driving prediction module receives temperature, pressure and raw material flow data collected by the real-time sensor and outputs a real-time feeding prediction value. The dynamic fusion module performs weighted fusion on the two values to generate a fused feeding prediction value; the rolling optimization module generates a feeding parameter adjustment instruction through a rolling optimization algorithm. And when the deviation between the adjusted sensor data and the fused predicted value exceeds a preset threshold value, the online learning module performs online fine adjustment on the parameters of the data driving model. The system combines a reaction mechanism and real-time working condition optimization feeding control, reduces manual intervention, and adapts to a complex production environment.

The invention discloses a multiphase mixed fluid monitoring and analyzing method for an oil and gas well exploitation process, which comprises the following steps of: aiming at separated signal characteristic distribution of each phase state, performing parameter matching by utilizing an established multiphase fluid model, and calculating an instantaneous flow value of each phase state by combining a hydrodynamic equation; obtaining respective flow parameter results of oil, gas and water; carrying out time sequence integration on the instantaneous flow parameter result, and carrying out continuity verification on the flow data by adopting a sliding window technology to obtain a flow time sequence data set subjected to smooth processing; and for the yield statistical result of each phase state, generating a dynamic characteristic curve by using a data visualization technology, and performing trend comparative analysis in combination with historical data to obtain the fluctuation rule description of the production dynamic characteristics. Accurate yield monitoring of oil and gas well multiphase fluid is achieved, reliable data support is provided for oil and gas field production management, production scheme optimization is facilitated, and oil and gas resource exploitation efficiency is improved.