1637 results about "Safety control" patented technology

The invention relates to the field of cableway transportation safety control, in particular to a cableway lift carriage operation deflection attitude monitoring device and a control method, and the method comprises the steps: collecting the position, speed, attitude angle and local micro deflection disturbance information of a lift carriage in real time by constructing a multi-mode sensing network; the frequency of the sensor is dynamically adjusted by adopting an adaptive sampling mechanism, and space-time alignment and fusion of heterogeneous data are completed in combination with dynamic time warping and minimum mean square estimation; strengthening the key disturbance dimension based on a disturbance-driven attention mechanism, and predicting a future deflection angle sequence; a decoupling torque is generated through spatial deflection vector field modeling, regional coupling tensor analysis and a dynamic direction alignment matrix, and power consumption constraint and a dynamic environment parameter optimization control instruction are fused; and finally, driving the quadrilateral moment gyroscope to execute correction, and constructing a multi-dimensional evaluation index based on the attitude response residual error. According to the method, adaptive closed-loop adjustment of the control strategy is realized, and the robustness under wind speed disturbance and load variation is improved.

The invention discloses a child electric motorcycle intelligent safety control system based on the Internet of Things, and relates to the technical field of electric motorcycle safety control. The problem of insufficient driving risk perception and control response of children is solved. The method comprises the following steps: firstly, fusing obstacle trajectory prediction, a road adhesion coefficient and an environment contour, constructing a dynamic risk vector field, and generating a collision probability and out-of-control coefficient fused risk assessment matrix; then, the matching degree of handle operation and vehicle body response is calculated through cross attention, and a third-level behavior label is output; according to the behavior level and the risk direction, anti-sideslip control or progressive power limitation is executed, and intervention characteristics are recorded; and finally, constructing a virtual training task by using parent operation data, extracting a personalized control threshold, dynamically optimizing system parameters, and realizing a child driving behavior-oriented closed-loop safety control system.

The invention discloses an intelligent automobile cooperative cruise safety control method under Dos attacks and physical faults, and relates to automobile intelligent safety and automatic driving. A hierarchical control framework is adopted and comprises an observer layer and a tracking layer. The method comprises the following steps: establishing a vehicle longitudinal dynamics model and a DoS attack model for DoS attack in a V2X communication network and the problems of sensor and actuator faults and parameter isomerism of a vehicle; a completely distributed self-adaptive preset time observer based on event triggering is designed for each following vehicle in the observer layer, and rapid and accurate estimation of the state of the pilot vehicle is achieved; the method comprises the following steps: constructing an augmentation system at a tracking layer, designing a distributed intermediate observer, carrying out online estimation and compensation on faults of a sensor and an actuator, designing a distributed active fault-tolerant controller based on a fault estimation value and a pilot vehicle state estimation value, and calculating a wheel driving torque to realize safe cruise control. Multiple threats of coexistence of network attacks and physical faults are effectively handled, and the stability and safety of the cooperative cruise system are ensured.

The invention provides an unmanned system security monitoring method based on multi-modal perception and autonomous decision discrimination, belongs to the technical field of artificial intelligence and industrial automation crossing, and aims to solve the problem that a machine learning decision security monitoring system of an existing unmanned system is difficult to quickly perceive environment change and make accurate response. The method solves the problems that in a high-dynamic scene, recognition of sudden risks is lagged, decision adjustment is slow, and the safety and stability of task execution are affected in the prior art, and comprises the steps that S1, key parameters of an unmanned autonomous system are screened; s2, modeling a parameter coupling relation; s3, time sequence driven key parameter extreme value boundary modeling and statistical analysis are carried out; s4, discovering danger cognition; s5, building a real-time prediction framework; s6, constructing a risk assessment model; and S7, determining an optimal safety switching mechanism. The method is suitable for real-time safety control of unmanned equipment such as an unmanned aerial vehicle, an automatic driving vehicle and an industrial robot.

The invention discloses a capacity adaptive coordination control system and method for distributed energy storage charging equipment, and relates to the technical field of charging safety control. The method is used for solving the problems of capacity sudden drop, vehicle charging delay and power grid interference caused by lithium precipitation. The method comprises the following steps: firstly, applying micro-current excitation in a charging pulse turn-off period by using a lithium precipitation characteristic monitoring module, extracting a phase deviation angle in a voltage relaxation curve, judging a lithium precipitation risk and generating a risk tag; then, the risk decision-making module calculates a charge migration proportionality coefficient and a floating coefficient in combination with the battery type and infrared thermal imaging information; then, the demand coupling module fuses the departure moment, the electric quantity gap and the power grid frequency fluctuation to generate a urgency degree weight and a pulse compensation parameter; and finally, the power reconstruction module completes charge migration and pulse sequence reconstruction according to the weight and the compensation parameter, triggers relaxation retest, and constructs a whole-flow dynamic coordination mechanism of the energy storage system.

The invention discloses an automatic driving safety operation system integrating environmental perception and decision reasoning. The system generates and dynamically updates a security risk map covering an operation area by fusing real-time environment perception, historical operation data and traffic management information. On the basis, the collaborative safety decision-making module further carries out behavior modeling and intention prediction on other traffic participants, and in combination with map risks and traffic instructions, a driving strategy is actively adjusted under a dynamic game framework. According to the invention, the safety control is improved from passive response to an active mode of behavior pre-judgment and game dominance, and the safety and reliability of the operating vehicle in a complex environment and the cooperative capability of the operating vehicle and traffic management are obviously enhanced.

The invention relates to a safety air bag ignition control method and device, computer equipment, a storage medium and a computer program product. The method comprises the steps that the running state of the automobile safety air bag control system is configured through the safety control state machine; under the condition that the running state is the normal state, the ignition function of the automobile safety air bag control system is configured to be in a forbidden state through a safety control state machine; in response to the fact that the automobile safety air bag control system is powered on for the first time and / or a watchdog error is detected, the running state is switched to a watchdog error protection state from a normal state through a safety control state machine; and under the condition that the operation result of the sensor data processing unit exceeds a preset threshold value, the operation state is switched from the normal state to the safety air bag ignition enabling state through the safety control state machine, and the ignition function is switched to the starting state. By adopting the method, the low-delay and high-precision response requirements of the chip on the ignition control instruction can be met.

The invention is suitable for the technical field of automatic driving, and provides an automatic driving vehicle blind area track prediction and planning method based on Transform, and the method comprises the steps: firstly constructing a key entrance point, calculating a shielding region, and then generating and maintaining a belief state of a ghost target in combination with a risk score; then, real and ghost targets are coded into Token in a unified mode, the Token is input into Transform for interactive modeling, and multi-modal track distribution is output; and finally, a variable anisotropic repulsive force potential field is constructed based on the predicted risk, and a safety control instruction is obtained through optimization solution and hard safety filtering. According to the method, continuous probabilistic estimation and interactive reasoning of the potential risk of the blind area are realized, a flexible defensive track can be generated according to the risk confidence and the dynamic state of the vehicle, and the traffic efficiency is guaranteed while the safety is improved.

The invention discloses a catastrophe rescue robot digital twin control method and system, and belongs to the technical field of robot intelligent control. Comprising a virtual-real mapping module which processes the body state of a robot and catastrophe scene point cloud data in real time, and constructs and synchronously updates a digital twinborn body containing a terrain elevation map at a cloud end; the hierarchical decision-making module is used for making a decision in the digital twinborn body by utilizing a hierarchical reinforcement learning model, and outputting a wheel-leg movement mode and an excavation arm cooperation instruction by a high-level strategy network according to the terrain complexity; and the safety deduction module introduces a safety reinforcement learning mechanism, deduces and verifies the generated action instruction in the virtual environment, and restrains the dangerous action by controlling a barrier function. According to the method, the decision risk of the heavy robot in the unstructured catastrophic terrain can be reduced, the stability of motion control is improved, and a high-safety control strategy is provided for various complex obstacle crossing actions based on simulation prediction.

The invention discloses a double-seat cooperative safety control method and system for engineering machinery, relates to the technical field of engineering machinery control, and provides the following scheme that the method comprises the steps that a first operation instruction stream of a main driving seat and a second operation instruction stream of a co-driving seat are collected in real time, and a working condition parameter set of the engineering machinery is synchronously obtained; the operation instruction stream comprises all degree-of-freedom motion parameters of the engineering machinery, inputting the first operation instruction stream into a pre-constructed long-short-term memory model, outputting a prediction operation instruction stream in a future time window, and based on a difference vector of the first operation instruction stream and a second operation instruction stream on each degree-of-freedom motion parameter. According to the method, through the index curve fitting model and Simpson integral calculation, the defect that the co-pilot intervention weight is difficult to quantify is overcome, the dynamic intervention weight based on the physical equidistant interval absolute integral value is realized, and the accuracy of the control signal of the engineering machinery is improved.

The invention discloses a starling group-based unmanned aerial vehicle cluster safety control and steering consensus method, which comprises the following steps of: firstly, constructing a three-layer leader-follower network simulating a pigeon group hierarchical structure, and establishing a dynamic physical neighbor topology in combination with a communication radius; an improved artificial potential field method is designed, a damage area, a rejection area, an alignment area and an attraction area are divided, a smooth concave-convex function is introduced to adjust a potential field, and cooperative force and obstacle rejection force for maintaining an expected distance are generated; an inertial spin mechanism is introduced, when a maneuvering intention is detected, expected spin and perceptual spin are calculated, a spin kinetic equation is utilized to update a state, and a transverse consensus coupling force for driving a cluster to rapidly and synchronously steer is generated. And finally, for different levels of unmanned aerial vehicles, differentially fusing the control force, and updating the cluster state through numerical integration. According to the method, the internal safety distance of cluster high-density flight is guaranteed, the overall steering speed and consistency of the cluster facing sudden obstacles are remarkably improved, and the robustness of the system in a dynamic environment is enhanced.

The invention discloses an electric motorcycle intelligent safety control system based on multi-sensor fusion. The system comprises a sensor module, a data processing unit, a target detection and classification module, a danger level evaluation module and a motor control module, and realizes all-weather and all-around environmental perception and target detection through data fusion of a millimeter wave radar, a visible light camera and an infrared camera. And the power output of the motor is intelligently regulated and controlled according to the detected danger level, so that the driving safety of the electric motorcycle is improved. The problem of limitation of a single sensor of an existing electric motorcycle safety system is solved, the stability and reliability of the system in a complex environment are improved, and early warning and intelligent prevention and control of potential risks are achieved.

The invention discloses an AGV safety control method for intelligent warehousing, and relates to the technical field of intelligent warehousing, and the method comprises the following steps: constructing a global three-dimensional load distribution diagram of an automatic guided vehicle in real time through the fusion of a laser radar and an inertial measurement unit, and outputting a mass distribution matrix; based on the mass distribution matrix, millimeter wave Doppler tomography is superposed, the barycentric coordinates are dynamically corrected, and a corrected mass distribution matrix is obtained; and inputting the corrected mass distribution matrix into a braking dynamic prediction engine, and generating a prediction curve of an adaptive braking distance and braking response time in combination with online inversion estimation of a ground friction coefficient. Through the digital twin simulation and micro-pulse pre-braking strategy, the risk of inertial collision and cargo overturning is effectively reduced, a storage scheduling system is controlled in parallel, path reconstruction and driving priority dynamic adjustment are achieved, and global safety and efficient scheduling of intelligent storage are guaranteed.

The invention belongs to the technical field of vehicle safety control and man-machine interaction, and particularly relates to a man-machine co-driving takeover decision-making, stability control and optimization method, which comprises the following steps of: A, constructing a driving safety field model, reflecting the influence of a dynamic environment and road elements on a vehicle by constructing the safety field model, and providing a real-time basis for takeover decision-making; b, constructing a driver human factor capability field, and evaluating the takeover capability of the driver through multi-modal data acquisition and real-time analysis; c, dynamically coupling a safety field and a human factor capability field in the takeover decision; d, a man-machine takeover mode judgment and control power distribution method; e, the takeover scheme is screened and optimized, and further screening and adjustment are carried out through the comprehensive cost function of the optimization algorithm and used for being executed in actual operation. The method has the advantages that the handover between the automatic driving system and the driver is intelligently controlled by evaluating the environmental risk, the driver ability and the take-over time in real time, and it is ensured that driving right transfer is safely, timely and efficiently completed.

The invention belongs to the technical field of stage equipment boundary safety protection control, and particularly relates to a variable constraint control method for stage equipment based on risk perception and a dynamic safety domain. The characteristic that stage equipment is usually in a fixed application scene in the performance process is utilized, the inherent safety level and active protection capacity of a stage equipment system are greatly improved through tight combination of real-time collection and variable constraint, and therefore safer, more accurate and more smooth control is achieved. According to the method, a construction algorithm is embedded in software, a dynamic region division and segmentation threshold adjustment strategy is utilized, and a multi-stage braking redundancy cooperation mechanism is triggered, so that the anti-interference capability and fault tolerance performance of the control system are effectively enhanced, the implementation cost is low, a large amount of manpower and material debugging can be saved, and the system is suitable for large-scale popularization and application. And a high-precision and high-robustness safety control scheme is provided for large stage machinery such as a seat vehicle platform and a rotating stage.

The invention discloses a fuel gas safety linkage control method and system based on a multistage alarm threshold value, and relates to the technical field of industrial safety control, and the method comprises the following steps: obtaining the operation data of a to-be-detected target, forming an operation feature vector, and carrying out the dynamic correction of a standard explosion lower limit concentration threshold value based on the operation feature vector; comparing the real-time gas concentration with the corrected concentration threshold value, and generating an initial grading judgment result in combination with the concentration change rate and the duration parameter; trend prediction is carried out according to time sequence data in the operation feature vector, and an initial grading judgment result is corrected; performing spatial fusion on the corrected grading judgment result, performing cross validation in combination with the running state and the credibility of the monitoring unit, and generating a final risk grade; according to the final risk level, a progressive linkage control action is triggered; according to the invention, through multi-level threshold value dynamic correction and trend prediction, the problems of missed report, false report and response lag in gas safety monitoring are solved.

The invention discloses an ABS real-time self-adaptive control method and system based on hub sensing signal fusion, and relates to the field of automobile safety control. The method comprises the steps that S1, multi-source hub sensing signals of all wheels are synchronously collected; s2, calculating a hub response coupling factor based on the multi-source hub sensing signal; s3, calculating an instantaneous slip rate based on the coupling factor and the wheel speed in combination with vehicle dynamic parameters; s4, on the basis of the wheel speed, the braking torque and the tangential acceleration, the coupling factor and the instantaneous slip rate are combined, and the normal load is calculated; s5, calculating an adhesion coefficient according to the instantaneous slip rate, the normal load and the wheel speed; s6, according to the slip rate deviation, a fusion weight is generated in combination with the coupling factor, and the adhesion capacity of the whole vehicle is calculated; and S7, according to the adhesion coefficient, the normal load, the slip rate and the adhesion capacity of the whole vehicle, the target braking force is calculated, and the wheel braking strength is adjusted. By monitoring the state of the wheels in real time, the slip rate is accurately controlled, braking force distribution is optimized, and the response precision and stability of the ABS are improved.

The invention relates to a vehicle active safety control method and system, a storage medium and a vehicle, and belongs to the field of intelligent driving control. The vehicle active safety control method comprises the steps that driving state information is obtained in real time; calculating a longitudinal risk avoidance determination threshold based on the driving state information, and setting a first trigger condition based on the longitudinal risk avoidance determination threshold; if the longitudinal distance between the vehicle and the target vehicle meets the first triggering condition, an automatic emergency braking system is activated, and a first deceleration used for controlling longitudinal braking of the vehicle is generated; after the automatic emergency braking system is activated, a transverse risk avoiding judgment threshold value is calculated on the basis of the driving state information updated in real time, and a second triggering condition is set on the basis of the transverse risk avoiding judgment threshold value; if the longitudinal distance between the vehicle and the target vehicle meets a second triggering condition, an automatic emergency steering system is activated, and a second control instruction is generated; wherein the second control instruction is used for controlling the automatic emergency steering system to execute the cooperative steering angle and controlling the automatic emergency braking system to execute third deceleration cooperating with the cooperative steering angle.

The invention discloses a mechanical arm path planning system, and relates to the technical field of man-machine interaction and safety control, the mechanical arm path planning system comprises a sensing module, a man-machine cooperation module, an optimization module and a regulation and control module, the man-machine cooperation module identifies the behavior intention and the working state of an operator to generate second data, and the optimization module fuses the first data, the second data and the state data of the mechanical arm body, selects a path planning strategy in a grading manner according to the environmental complexity, generates and optimizes a target path, and outputs an optimization result comprising a standard path and an alternative path. And the regulation and control module dynamically regulates and controls the optimization result, generates a regulation and control result through instruction conversion, deviation compensation and multi-stage response and feeds back the regulation and control result, the dynamic environment can be accurately dealt with, man-machine safety cooperation is achieved, the efficiency, safety and adaptability of mechanical arm path planning are improved, and the method is suitable for complex man-machine cooperation scenes.

The invention relates to the technical field of engineering machinery, and discloses an engineering machinery active safety control method and device based on multi-parameter analysis, and the method comprises the steps: collecting the multi-modal data of an environment where the engineering machinery is located based on a multi-modal data collection device, and constructing a dynamic model of the engineering machinery and the environment according to the multi-modal data, analyzing the multi-modal data through a dynamic model to obtain an environment data analysis result and an equipment data analysis result, determining an operation risk level of the engineering machinery according to the environment data analysis result and the equipment data analysis result, and determining an optimal working path of the engineering machinery according to the multi-modal data. And generating a safety control strategy according to the operation risk level and the optimal working path. Therefore, by implementing the method, the evaluation accuracy of the operation risk can be improved, the probability of misoperation of operators is reduced, the operation accuracy and reliability of the engineering machinery are enhanced, and the operation efficiency, the operation stability and the operation safety of the engineering machinery are further improved.

The invention discloses a multi-degree-of-freedom clamping mechanism of an industrial robot. The multi-degree-of-freedom clamping mechanism comprises a control base, a shaft base set and a clamping assembly. A first driving motor and a second driving motor are mounted on the bottom surface of the control seat; the shaft seat group is rotationally mounted on the inner side of the control seat and consists of a ring seat, a first transmission gear, a second transmission gear, a roll shaft and a shaft rod, the first transmission gear is meshed with the first driving motor to realize integral deflection, and the second transmission gear is meshed with the roll shaft through a bevel gear to realize rotary transmission; the clamping assembly comprises a swing seat, a clamping seat and a clamping lug, and a crank gear is driven by a shaft rod and a worm to drive the clamping lug to be opened and closed. And a touch switch is arranged on the guide cover and is matched with the servo control module to realize limiting protection and automatic resetting. The multi-posture clamping mechanism is compact in structure, high in degree of freedom and stable in transmission, multi-posture clamping and intelligent safety control of workpieces can be achieved, and the operation flexibility and safety of the industrial robot are remarkably improved.

The invention discloses a moored ship motion state prediction and anti-collision early warning system, particularly relates to the field of traffic control and anti-collision early warning, and is used for solving the problems that ship motion state accurate prediction and anti-collision scheduling response lag cannot be realized in existing port mooring operation. According to the system, ship trajectory, port operation and environment monitoring data are acquired in real time through a data acquisition module, and a fusion data stream with consistent time-space attributes is generated; constructing a space-time diagram structure by using a feature extraction module, extracting traffic flow dynamic features, and calculating a short-term conflict probability, a trajectory convergence risk value and a mooring risk value; the risk early warning module generates a collision risk index based on risk level mapping and triggers graded early warning; the mooring decision-making module sets a key control leg according to the early warning level and generates a dynamic decision-making scheme; the anti-collision scheduling module executes actual channel passing, speed adjustment and track change, and dynamic coordination and safety management and control of port mooring anti-collision are achieved.

The invention discloses a distributed driving electric vehicle path tracking and stability control method and system, and belongs to the technical field of electric vehicle active safety control. The method comprises the following steps: constructing a state-space equation based on a driver path tracking model and a vehicle three-degree-of-freedom motion model; establishing a dynamic envelope region based on a phase plane method, inputting the current parameters of the vehicle into the dynamic stable envelope region, and outputting a weight; constructing a controller based on the state-space equation, and taking the weight output by the dynamic stable envelope region as the control weight of the controller; inputting the vehicle state variables and the vehicle parameters into a controller, and outputting a longitudinal driving torque, an additional yaw torque, an additional front wheel turning angle and a driver intention turning angle required by driving; the additional front wheel turning angle and the driver intention turning angle are superposed to serve as input of a steering motor; a torque distributor is designed to distribute a longitudinal driving torque and an additional yaw torque, and the distributed torques are used as given values of the four hub motors.

An autonomous vehicle can include multiple low voltage power domains. Each low voltage power domain can comprise a low voltage power distribution unit (LVPDU). An LVPDU can include a failsafe switch that can selectively couple or de-couple the low voltage power domain from a shared backup low voltage power source, which can be configured to concurrently supply backup power multiple low voltage power domains or LVPDUs. A first LVPDU of a first low voltage power domain can generate a control signal to control the failsafe switch of a second LVPDU of the second low voltage power domain to disconnect the second low voltage power domain from the shared low voltage backup power source, and vice versa.

The invention discloses a vehicle queue preset time output feedback safety control method and system, and belongs to the field of intelligent network connection multi-vehicle queue control, the control method comprises the following steps: designing a non-linear vehicle queue model, designing a fuzzy observer, combining with a fuzzy logic system to approximate an unknown non-linear function in the vehicle queue model, and calculating the preset time output feedback safety of the vehicle queue. Outputting an estimated displacement, an estimated speed, and an estimated acceleration of the following vehicle; mapping the error transformation of the finite time domain to an infinite time domain to obtain infinite time domain error transformation; designing a Lyapunov function, and performing derivation on the Lyapunov function to finally obtain a following vehicle brake input signal; designing a false data injection FDI attack model for injecting an attack signal into the following vehicle brake input signal to obtain an input with an attack; the invention provides a cooperative control architecture based on a time domain mapping mechanism, and tracking errors under any initial condition can be asymptotically converged to zero within preset time.

The invention relates to the technical field of charging safety control, in particular to an efficient heat dissipation equalization system applied to a charging head in a new energy automobile, which comprises a data acquisition module, a thermal imaging spectrum generation module, a strategy generation module and an equalization heat dissipation module. The data acquisition module acquires temperature distribution data of a three-dimensional space in the charging head in real time through a multi-dimensional temperature sensing array; the thermal imaging spectrum generation module adopts a Kriging space interpolation algorithm to construct a real-time three-dimensional temperature field and generate a thermal imaging spectrum; the strategy generation module identifies a temperature abnormal area and calculates a differential heat dissipation strategy based on a dynamic safety threshold and a temperature gradient; and the balanced heat dissipation module drives the partition controllable heat dissipation execution mechanism to operate according to a strategy, and the feedback information is used for dynamic adjustment. According to the invention, precise heat dissipation of local hot spots and dynamic optimization of heat dissipation efficiency are realized.

The present invention relates to a safety steering device for manual intervention by a safety driver in an autonomous vehicle or a vehicle with a driver assistance system. The safety steering device comprises a control unit and a joystick operable by the safety driver, from which a steering intervention signal can be transmitted to the control unit, wherein the steering intervention signal overrides an autonomous steering signal. A safety control element is arranged on the joystick, which, when activated by the safety driver, generates a release signal to enable the transmission of the steering intervention signal to the control unit.

The invention discloses an AI-assisted self-adaptive control method and system for a gas safety valve, and relates to the technical field of gas safety control, and the method comprises the following steps: connecting the output end of an SEPIC circuit containing a continuous current mode and a discontinuous current mode with a coil of the gas safety valve; according to preset electrical and gas safety indexes, asynchronous data acquisition is carried out on the electrical and gas safety indexes, and an electrical and gas safety index sequence is obtained; utilizing an AI fusion analyzer on the edge MCU to perform interactive feature fusion analysis on the two types of sequences, and determining a self-adaptive control scheme of the gas safety valve; circuit modes are switched based on the control scheme, and the safety valve is driven to execute according to the switched SEPIC circuit. The technical problems that in traditional gas safety valve control, electric parameters and gas safety indexes are analyzed in a split mode, the circuit operation mode is single, and control response is inaccurate are solved, and the technical effects that efficient and reliable self-adaptive driving of the gas safety valve is achieved, and gas use safety and control flexibility are improved are achieved.

The invention discloses a real-time monitoring and safety early warning method for an anti-seismic structure of a fuel oil unit, belongs to the technical field of structural health monitoring and safety control, and aims to solve the problems that an existing monitoring method is passive and lagged, depends on artificial experience and cannot automatically, quickly and objectively evaluate the health condition of an anti-seismic system after an earthquake. A three-axis acceleration sensor is adopted to monitor vibration acceleration in real time, an edge computing gateway triggers an earthquake event when a vibration peak value exceeds a first preset threshold value, and a sensor array is controlled to be switched to a high-frequency recording mode; uploading the collected high-frequency data to a data processing platform, carrying out seismic design threshold comparison and machine learning model analysis, and fusing and outputting a part damage probability grade and a health assessment result; and based on the evaluation result, a targeted check list is generated through a preset mapping relation library and is pushed to the mobile terminal of the operation and maintenance personnel. The method is used for monitoring and early warning of an anti-seismic structure of a fuel unit, can realize rapid and reliable evaluation and accurate operation and maintenance guidance after an earthquake, and guarantees power supply recovery of key facilities.

The invention relates to the technical field of artificial intelligence, and more specifically discloses an artificial intelligence-based earthwork real-time dynamic monitoring system and method, and the method comprises the steps: obtaining an image of a to-be-detected earthwork region through satellite remote sensing data, extracting a feature vector and a feature matrix, constructing a classification feature vector, and finally obtaining a classification result through a classifier. Therefore, real-time monitoring of earthwork settlement and slope deformation is realized, a simple, convenient and rapid quality safety control means is provided for highway engineering construction, municipal roads, constructional engineering and landscape and garden engineering, the engineering construction efficiency is improved, and the engineering cost is reduced.