694results about How to "Achieve precision" patented technology

The invention discloses a transmission line three-dimensional reconstruction method and system based on a monocular channel monitoring camera, and the method comprises the steps: obtaining compensation image data through adaptive illumination compensation processing, obtaining direction feature data based on frequency domain feature analysis, constructing a texture enhancement model through a graph theory, generating enhanced image data, and carrying out the reconstruction of a transmission line. Outputting feature aggregation data through time sequence feature aggregation; generating three-dimensional contour data in combination with multi-wire topology analysis and geometric constraint optimization; depth probability modeling and multi-scale consistency processing are adopted to obtain optimized depth data; and outputting system state data, three-dimensional point cloud data and deformation parameter data through physical model construction and space-time constraint fusion. According to the method, high-precision three-dimensional reconstruction of the power transmission conductor is realized, and the method has relatively high environmental adaptability and calculation efficiency.

The invention provides a sensitive data identification protection method and system based on intelligent matching, and relates to the technical field of data processing, and the method comprises the steps: carrying out the semantic analysis of sensitive data through a natural language processing model, and constructing a multi-level knowledge graph; performing node coding and relation intensity calculation by using a graph neural network and an attention mechanism; a graph structure importance degree evaluation algorithm is adopted to calculate node sensitivity weights and grade the node sensitivity weights; and applying a corresponding data protection scheme according to the sensitivity level, and identifying associated nodes through a graph traversal algorithm to perform hierarchical protection. According to the method, intelligent identification, accurate grading and comprehensive protection of sensitive data are realized, and the data security is improved.

The invention provides a multi-AGV path planning and obstacle avoidance method based on an improved artificial bee colony algorithm, and aims to solve the key technical challenges of multi-AGV system path planning and obstacle avoidance in modern industrial automation. According to the method, a dynamic updatable gridding environment model is constructed to accurately represent a starting point, an end point, static obstacles and dynamic obstacles in a working environment, an improved artificial bee colony algorithm is adopted to globally optimize path planning of multiple AGVs, constraint conditions of obstacle avoidance and multi-AGV path conflicts are met, and the optimal path planning of the multiple AGVs is realized. And the efficient operation of the system and the path collision-free property are ensured. In addition, the method further comprises path tracking control and conflict detection and obstacle avoidance control so as to ensure that the AGVs can accurately run along the planned path, conflict points in the paths of the multiple AGVs are detected in real time, and different coping strategies are adopted to achieve path coordination and scheduling. Finally, the cooperation efficiency and safety of the multi-AGV system can be effectively improved.

The invention discloses an automatic quality-supplementing correction method and system for the unbalance amount of a fan, and the method comprises the following steps: collecting geometric parameters and material characteristics in a static state of the fan, and constructing a mechanical distribution model of the fan; the method comprises the following steps: collecting vibration signals and airflow characteristics in real time in a dynamic operation state, calculating the amount of unbalance in operation and decomposing the amount of unbalance into a primary component and a secondary component; on the basis of the unbalance prediction trend, determining a quality supplementing range, carrying out multi-point quality supplementing operation through a dispensing technology, and monitoring a quality supplementing effect by using an optical fiber sensor; and if the residual unbalance amount after quality supplementation still exceeds the standard, real-time compensation adjustment is carried out through the electromagnetic torque regulation and control module. Full-process automatic correction from static state to dynamic state and from quality supplement to fine adjustment is achieved, the method has the advantages of being real-time, accurate and intelligent, vibration and noise in the fan operation process can be effectively reduced, the operation stability of equipment is improved, and the service life of the equipment is prolonged.

The invention provides an LCM module aging test method, device and equipment and a storage medium, and the method comprises the steps: obtaining the initial state data and initial environment parameter combination of an LCM module through intelligent environment simulation and initialization processing, and carrying out the multi-mode alternate aging test and real-time monitoring processing of the module through an intelligent environment simulation system, and obtaining performance data in a dynamic environment, and carrying out surface periodic scanning and working sound recording to obtain microstructure data and acoustic data. Through intelligent fault detection and deep analysis processing, fault features and reasons of the module are identified, predictive analysis is performed on the fault in combination with a machine learning algorithm, and a predictive fault trend and an optimized environmental parameter combination are generated. And performing comprehensive performance evaluation on the module according to the fault features, the reason analysis, the prediction trend and the optimization parameters. According to the invention, through combination of intelligent environment simulation, real-time monitoring and deep analysis, accurate performance evaluation and fault prediction of the LCM are realized.

The invention discloses an integrated navigation method based on deep learning and improved Kalman filtering, belongs to the technical field of artificial intelligence and integrated navigation, and is used for processing integrated navigation data, including using GPS / INS integrated navigation when a GPS signal is available, and using angular velocity and acceleration output by an inertial measurement unit IMU to determine whether the GPS signal is available or not. Calculating and estimating the attitude, position and speed of the object, and fusing the attitude, position and speed with GPS data to obtain a final combined navigation result; and when the GPS signal is unavailable, predicting a pseudo position and a pseudo speed when the GPS signal is unavailable through the neural network model, and inputting the pseudo position and the pseudo speed into the adaptive square root volume Kalman filter for data fusion to obtain a predicted position and a predicted speed when the GPS signal is unavailable. According to the invention, the prediction precision of the neural network model is improved, the robustness of the filtering algorithm is optimized, and the method has real-time performance; the influence of noise on the system is reduced, and data fusion of the GPS and the INS and a high-precision solution are realized.

The invention belongs to the technical field of a computer system based on a specific calculation model, relates to a virtual and real dynamic interaction-based digital twin bearing fault diagnosis method, and aims to solve the problem that a bearing system in large rotary mechanical equipment is large in fault hidden danger and avoid serious consequences caused by faults. A generally used bearing is in a high-precision standard, so that system signal data under bearing fault operation is not easy to collect in a factory, and the unbalanced data sample distribution directly leads to finiteness of fault diagnosis in a real scene only based on a big data driving mode classification method, so that the system signal data cannot be easily collected in the factory. The method has good scene working condition self-adaption, can be applied to fault diagnosis of a bearing system in different industrial scenes, fully excavates limited industrial data information and rich physical priori knowledge, and ensures safe and reliable operation of an important rotating mechanical system through a digital twinning technology.

The invention relates to the technical field of substation operation and maintenance, in particular to a substation communication power supply storage battery internal resistance detection method and system, electronic equipment and a storage medium, which can ensure the stable operation of a substation communication power supply system and improve the operation safety of a power network. The method comprises the following steps: collecting storage battery multi-element characteristic parameter information, storage battery multi-element external cause parameter information and a storage battery real-time internal resistance value of the substation communication power supply; performing data processing on the multivariate characteristic parameter information of the storage battery, and inputting the processed multivariate characteristic parameter information into a pre-constructed storage battery characteristic parameter analysis model to obtain a storage battery theoretical internal resistance value corresponding to the multivariate characteristic parameter information of the storage battery; performing external cause influence error compensation on the real-time internal resistance value of the storage battery based on the multi-element external cause parameter information of the storage battery to obtain a corrected internal resistance value of the storage battery; and calculating the internal resistance deviation amplitude between the storage battery correction internal resistance value and the storage battery theoretical internal resistance value.

The invention relates to the technical field of computer vision and natural language processing, and discloses an image-based cue word generation method, which comprises the following steps of: obtaining non-text vision elements, text elements and position information thereof from a cue image, screening and processing the elements, removing text contents in the image and generating a cue image without characters. And based on the target non-text visual elements, cutting out corresponding image areas from the prompt image without characters, inputting the image areas into the multi-modal model, and generating prompt words related to the visual elements. According to the method, the non-text visual elements and the text elements in the image are automatically recognized, the image without characters is generated, and character interference is avoided. The cue word highly related to the image content is generated, the cue word generation accuracy and automation are achieved, and the processing efficiency and the cue word quality are improved. The complexity of writing the cue word by the user is effectively reduced, so that the user can generate the cue word with high quality and accurate semantics through simple image interaction.

The invention discloses an automatic control method for tipping paper printing based on image detection, and relates to the technical field of tipping paper printing, and the method specifically comprises the following steps: obtaining surface feature information of each sub-region in a wrinkling region in a tipping paper printing process in real time, and analyzing the surface feature information after obtaining, respectively generating a light intensity anomaly index and a tension instability index of each sub-region; and constructing a wrinkling influence evaluation model for the light intensity anomaly index and the tension instability index of each generated sub-region, respectively generating a comprehensive evaluation coefficient of each sub-region, performing analysis after generation, and evaluating the influence degree of each sub-region in the wrinkling region on the generated printing alignment parameter. And dividing each sub-region in the wrinkling region into a non-influence region, a low-influence region and a high-influence region according to an evaluation result. According to the invention, the problem of insufficient characteristic identification and evaluation of the wrinkling area is solved, and intelligent improvement of printing alignment precision and finished product quality is realized.

The invention discloses a power transmission line unmanned aerial vehicle autonomous inspection adaptive optimization method based on AI assistance, which is used in the field of artificial intelligence, and comprises the following steps: collecting environmental parameter data of a power transmission line, and carrying out data labeling; training a power line distance and light sensing and identifying module by using the marked data, and identifying the distance and light change of the power transmission line; adjusting the position and the flight path of the unmanned aerial vehicle according to the environment data collected in real time and the distance of the power transmission line; and generating an optimal inspection route based on the environment data and the position and the flight path of the unmanned aerial vehicle, and performing autonomous inspection according to the optimal inspection route in the inspection process. According to the method, heuristic path planning and statistical optimization are combined, and the accuracy and adaptability of path planning are realized.

The invention relates to the technical field of electrical fire early warning detection, and discloses a method and a system for detecting electrical fire risk hidden dangers. The method comprises the following steps: collecting current, voltage and temperature signals through a sensor, and generating a multi-dimensional original data set; extracting spectrum features and mutation features; inputting the feature vector into a trained model for risk trend prediction; and smoke features and flame features are detected and analyzed in combination with a video image recognition algorithm. Compared with the prior art that fire hazards are judged only depending on a fixed threshold value, and particularly, accurate recognition and real-time early warning of the fire hazards cannot be achieved in a complex electrical environment, the method adopts a cooperative mode of multi-source data acquisition, intelligent algorithm analysis and video image recognition; high-precision prediction and real-time alarm of the electrical fire risk are realized, so that the problem of false alarm or missing alarm is avoided, and the real-time performance and the stability of the system are improved.

The invention discloses a fabricated curtain wall construction method, system and equipment based on a BIM technology and a storage medium. The method comprises the following steps: performing virtual paying-off on a building main body structure to obtain paying-off data; acquiring curtain wall information of the fabricated curtain wall; performing hoisting path simulation on the fabricated curtain wall according to the curtain wall information and the pay-off data, and adjusting the simulated hoisting path in a BIM model including the building main body structure to obtain an adjusted BIM model; the assembled curtain wall is temporarily fixed through the adjusted BIM model; performing error detection on the temporarily fixed fabricated curtain wall to obtain an error report, performing position adjustment on the temporarily fixed fabricated curtain wall according to the error report, and stopping adjustment when an error value is within a preset range to complete installation. By implementing the technical scheme provided by the invention, the construction precision of the fabricated curtain wall is improved.

The invention relates to the field of unmanned underwater vehicles, and discloses an unmanned underwater vehicle finite time trajectory tracking control method based on event triggering, which comprises the following steps: establishing two coordinate systems to describe the motion state of an unmanned underwater vehicle, and constructing a kinematical equation and a kinetic equation of a six-degree-of-freedom full-drive unmanned underwater vehicle; the method comprises the following steps: establishing an underwater unmanned vehicle kinematics and dynamics model, determining a control target, setting an event triggering finite time backstepping controller and event triggering conditions in combination with the underwater unmanned vehicle kinematics and dynamics model, and adopting a virtual controller of the event triggering finite time backstepping controller and the event triggering controller to control the event triggering conditions. Enabling the kinematics and dynamics model of the underwater unmanned vehicle to reach a stable state within the convergence time, and enabling the trajectory tracking error of the underwater unmanned vehicle to obtain a convergence time upper bound within the convergence time; according to the method, rapid convergence in finite time is realized, so that the accuracy and rapidity of trajectory tracking control of the underwater vehicle are realized.

The invention discloses a static forest fire risk assessment method and system based on multi-source data and a remote sensing technology. The method comprises the following steps: establishing an index system of a target area and carrying out data acquisition; the collected data are preprocessed; calculating influence factors and index weights by using the preprocessed data, determining spatial and temporal distribution of calculation results of different influence factors, and calculating a comprehensive factor result by using each single influence factor according to a set weight; and evaluating the forest fire risk based on the obtained comprehensive factor result, and realizing dynamic monitoring of the forest fire risk value. According to the method, the accuracy and the real-time performance of forest fire space-time risk prediction are improved; and theoretical support is provided for follow-up forest fire risk prevention and control of electric power companies.

The invention discloses a chip testing method, system, medium and equipment, and relates to the technical field of chip testing electrical digital data processing. The method comprises the following steps: judging a chip to carry out an aging test or repair according to a first performance comparative analysis result of the chip; judging and determining an aging test process or repair of the chip according to a second performance comparative analysis result of the chip; and judging and determining a chip aging test result level according to the third performance comparative analysis result of the chip. According to the invention, performance evaluation analysis, stability analysis and evaluation and comprehensive test analysis and evaluation are respectively carried out on the dynamic random access memory chip, and the chip aging test result level is comprehensively judged according to the comparative analysis of the analysis and evaluation result and the corresponding threshold value. The effect of improving the aging test evaluation and judgment accuracy of the chip of the dynamic random access memory is achieved, and the problem that the aging test evaluation and judgment accuracy of the chip of the dynamic random access memory is insufficient in the prior art is solved.

The invention relates to the technical field of insulin needle processing devices, in particular to an insulin needle assembling device. Compared with the prior art, the automatic assembling machine has the advantages that the automatic assembling machine is high in automation and modular design, the complete process from needle head supply to precise combination of needle heads and needle bases is achieved through close fit of the needle supply part, the needle taking part, the needle inserting part and the base supply part, the assembling efficiency and accuracy are improved, and sanitation and safety of the whole process are guaranteed.

The invention discloses a vehicle lane changing track high-precision redrawing and key parameter accelerated extrapolation method. The method comprises the following steps: acquiring a sampling data set of a real-time dynamic driving scene; screening a complete lane changing scene of multi-vehicle interaction; filtering preprocessing is carried out on the original noisy data; a lane changing track model is constructed based on a midpoint step-by-step lane changing hypothesis, a lane changing process is modeled in a segmented manner by taking a lane line crossing moment as a node, track characteristic parameter identification is carried out based on the lane changing track model of transverse and longitudinal decoupling, a track characteristic parameter distribution rule is mined, and lane changing scene parameter distribution characteristics are condensed; extracting parameter distribution characteristics of the lane changing scene based on a Gaussian mixture model, and proposing a joint probability model of scene multi-dimensional parameters; extracting lane changing scene distribution gradient information; carrying out Hamilton Monte Carlo sampling; and forming a lane changing acceleration test scene library. According to the invention, dimensionality reduction and high-precision redrawing of the lane changing track are realized, and extrapolation of key scene parameters and construction of a high-precision and high-efficiency lane changing acceleration test scene library are completed.

The invention provides a fracture reduction path auxiliary planning method and system based on an augmented reality technology, and relates to the technical field of intelligent medical systems. The method comprises the following steps: acquiring fracture image data for a fracture area of a patient, wherein the fracture image data comprises CT data and X-ray data; reconstructing a fracture part three-dimensional model based on the fracture part image data; matching and calibrating the three-dimensional model of the fracture part and the fracture area of the patient in the actual scene; the calibrated three-dimensional model of the fracture part and the corresponding fracture type and fracture operation requirements are input into a fracture reduction path planning model to determine at least one corresponding optimized fracture reduction path, and the fracture reduction path planning model comprises a reinforcement learning module and a multi-physics field simulation optimization module which are cascaded; and rendering each fracture reduction path, and determining a target fracture reduction path according to the detected interaction instruction. Therefore, the augmented reality technology is applied to the fracture reduction scene, and the success rate of the operation and the postoperative rehabilitation effect of the patient can be improved.

The invention relates to the technical field of robot control, in particular to a robot rescue emergency control system based on voice interaction. The system is used for performing control voice signal acquisition and rescue emergency voice control task structured analysis by using a built-in voice receiving function of a robot, and generating rescue emergency voice control task structured data; acquiring panoramic image data, environment sensing data and long-distance laser radar data monitored by the robot; the method comprises the following steps: performing global image point cloud model construction and multi-level environment change collaborative optimization processing based on panoramic image data, environment perception data and long-distance laser radar data monitored by a robot, and generating an optimized global image perception model; and performing rescue emergency intelligent control operation on the robot based on the rescue emergency voice control task structured data and the optimized global image perception model. According to the invention, the voice instruction is received through the voice interaction function, so that automatic and efficient robot rescue emergency control is realized.

The utility model discloses a grinding wheel feeding device of a lens grinding machine, which relates to the technical field of grinding machines and comprises a working table, a working bin is arranged on one side of the top end of the working table, a base and a vertical seat are arranged on the other side of the top end of the working table, and a movable clamping mechanism is arranged between the working bin and the base. An angle turnover mechanism is arranged at the top end of the base, a grinding wheel driving mechanism is arranged at the top end of the angle turnover mechanism, and a pushing and abutting positioning mechanism is arranged at the top end of the vertical base. The angle of the grinding wheel driving mechanism can be manually adjusted by arranging the pushing and abutting positioning mechanism and the angle overturning mechanism, so that the angle and the position of the grinding wheel before and after grinding or in the grinding process are changed, high-precision feeding and adjusting of the grinding wheel can be achieved by means of calibrated scale marks, and different grinding machining scenes are met.

The invention provides a mesenchymal stem cell confluence degree calculation method and system based on image semantic segmentation, and the method comprises the steps: training a cell image semantic segmentation model through a training set, and carrying out the test screening of the trained cell image semantic segmentation model through a test set, obtaining an optimal cell image semantic segmentation model; performing preprocessing operation including scale transformation and gray level normalization on the to-be-calculated mesenchymal stem cell phase contrast microimage; and segmenting the to-be-calculated mesenchymal stem cell phase contrast microscopic image into cells and a background by using the optimal cell image semantic segmentation model, and summarizing and counting the pixel proportions of the segmented cells to obtain the mesenchymal stem cell confluence degree so as to realize automatic identification and separation of the mesenchymal stem cells. The method is used for assisting cell culture quality evaluation in medical and biological research.

The invention relates to the technical field of visual health management, in particular to a ciliary muscle adjustment training system and method based on eye movement tracking, and the method comprises the steps: collecting eye movement data of a fixation point track, an adjustment amplitude change rate and pupil response time in real time, and combining personalized parameters such as the age of a user, diopter and a training target; inputting a ciliary muscle training dynamic planning algorithm module, dynamically generating a stage scheme containing a training action type, a single-group duration, a stimulation interval and a focal length adjustment strategy, and adaptively adjusting the strategy according to real-time adjustment stability and a historical ability curve; through multi-dimensional matching analysis of a pre-stored standard eye movement template, a training specification score is calculated from the track goodness of fit, speed uniformity, amplitude standard-reaching rate and binocular coordination, visual fatigue parameters are obtained based on continuous training duration, pupil fluctuation and retina reflex change, a scoring result is dynamically corrected, and a visual fatigue evaluation result is obtained. Personalized, self-adaptive and quantitative safety control of the training process is realized.

The invention discloses a gear cutting expansion cutting geometric model building system in the technical field of numerical control machining. The gear cutting expansion cutting geometric model building system comprises an acquisition module, a modeling module, a monitoring module, a checking module and an updating module. The acquisition module is used for acquiring cutting parameters of machining equipment and a to-be-machined workpiece model; the modeling module is used for constructing a three-dimensional cutting geometric model based on the cutting parameters and the workpiece model; the monitoring module is used for obtaining the actual characteristics of cuttings generated in the machining process of a workpiece in real time. The checking module is used for comparing the actual features with theoretical features predicted in the three-dimensional cutting geometric model, and if the difference between the actual features and the theoretical features exceeds a preset threshold value, cutting parameters of follow-up work of the machining equipment are adjusted till the actual features are matched with the theoretical features; and the updating module is used for updating the three-dimensional cutting geometric model based on the checking result of the checking module. According to the scheme, cuttings can be monitored in real time, and the difference between a model prediction result and an actual result is corrected in time.

The invention relates to the technical field of mine blasting construction, in particular to a lumpiness control method, system and equipment for mine blasting construction and a medium. The method comprises the following steps: firstly, determining an initial blocking length based on early-stage trial explosion data, then forming an axial non-coupling structure by arranging a plurality of sections of PVC interval air columns with different lengths, loading explosive cartridges with different diameters to form a radial non-coupling structure, and finally, performing quantitative analysis and parameter optimization by utilizing lumpiness analysis software. Through the synergistic effect of the double uncoupled structures, quantitative analysis and parameter optimization, blasting energy distribution can be more effectively controlled, and an ideal lumpiness control effect is achieved.

The invention relates to a shadow rocket launch control terminal, method and system, and belongs to the technical field of shadow rocket launch control, the launch control terminal comprises an identity authentication module, an operation information acquisition module, an operation control module, a launch control module and an operation log module; through whole-process management of identity authentication, data acquisition, attitude adjustment, state detection, ignition control and operation logs, safety, accuracy and data traceability of rocket launching operation are realized. Wherein the identity authentication ensures the safety of the operation authority, the data acquisition provides real-time information support for posture adjustment and state detection, the posture adjustment and the safe firing range judgment ensure the accuracy and the safety of launching, and the ignition control ensures that the launching is carried out under authorization; the recording and uploading of the job log enable the emission operation to have complete data record and traceability. The automation degree and reliability of figure rocket launching are improved.

The invention discloses a hydraulic mechanical transmission device control method based on optimal trajectory optimization, and relates to the technical field of equipment intelligent auxiliary operation and control, and the method comprises the following steps: S1, building a physical model of a hydraulic mechanical transmission device; s2, taking the shortest motion time, the most smooth trajectory and the minimum energy consumption as optimization objectives, and obtaining an optimal trajectory based on a trajectory planning algorithm combining an improved sparrow algorithm and a quintic non-uniform B-spline curve; s3, oil return control is optimized; and S4, oil inlet control is optimized, specifically, an oil inlet flow controller is optimized based on a time-varying secant obstacle Lyapunov function and an RBF neural network. According to the trajectory planning algorithm, the trajectory of the hydraulic transmission device can be optimized, oil return and oil inlet are optimized based on the optimal trajectory, and working trajectory planning and high-precision control over the hydraulic equipment executing mechanism are achieved.

The invention discloses a student development quality evaluation method and system based on artificial intelligence, and the method comprises the steps: multi-dimensional data collection, complex feature fusion, multi-level feature calculation, high-order feature generation, association rule mining and a real-time dynamic adjustment mechanism. The development conditions of students in five aspects of morality development, academic development, physical and mental development, aesthetic quality and labor and social practice are comprehensively and objectively evaluated; the method comprises the specific steps that subjective evaluation is replaced with multiple indirect data acquisition, and the influence of human subjective factors is reduced; through multi-level feature calculation and high-order feature generation, the depth and accuracy of data analysis are improved; analyzing the relationship among the high-order features by using an association rule mining technology, and carrying out ultimate feature fusion; calculating a comprehensive development evaluation coefficient through a comprehensive scoring formula, generating comprehensive development evaluation data, and performing personalized feedback and real-time dynamic adjustment; according to the invention, a scientific decision basis is provided for education management and personalized teaching.

The invention provides a deformable mirror assembly comprising a deformable mirror body, the back of which is provided with a telescopic piezoelectric actuator comprising a plurality of linearly arranged actuating units; the cushion block is arranged on the back surface of the deformable mirror body; the control system is used for providing actuating alternating current voltage for the telescopic piezoelectric actuator, so that sinusoidal vibration of different actuating units adopts random amplitude and random phase; the maximum peak-valley amplitude, caused by sinusoidal vibration, of the mirror surface of the deformable mirror body overcomes the Rayleigh criterion, the periodicity of the spatial frequency is destroyed through the randomness of the phase of the actuating unit, and therefore homogenization of light beam speckles is achieved when the deformable mirror body is used for light beam deflection. The invention also provides a corresponding two-dimensional optical system. According to the deformable mirror assembly, the speckle uniformity in the imaging process is improved, and the influence of speckles is reduced.

The invention provides a firmware online upgrading method, embedded equipment, a medium and a product, and relates to the technical field of intelligent terminals. The method comprises the following steps: after the embedded equipment is powered on, running a primary bootstrap program, and checking a first mark state: if the state is a state of updating a secondary bootstrap program, executing online updating of the program and resetting a system; and if the state is the default state, loading and running the secondary bootstrap program. Checking a second mark state; if the second mark state is an updating mirror image state, executing firmware mirror image online updating and resetting; and if the state is the default state, determining a target mirror image, copying the target mirror image from the nonvolatile memory to the random access memory, and skipping to run. And the equipment simultaneously monitors the running state of the target mirror image in real time, and executes successful confirmation or abnormal recovery operation according to the state. In this way, quick response of faults is achieved through running state feedback, the stability and reliability of firmware upgrading of the embedded device are effectively improved, and the risk of device paralysis in the upgrading process is reduced.