633 results about "Adaptive switching" patented technology

The invention discloses a self-adaptive focal length control method and system of a laser cutting machine, particularly relates to the technical field of laser processing, and is used for solving the problem of insufficient laser focus control precision caused by separation of a detection point and a processing point and geometric mutation of a curved surface in the prior art. Instantaneous distance information is continuously obtained in the moving process of a cutting head, the curvature change characteristics of the surface of a workpiece are calculated according to the instantaneous distance information, inertial load and dynamic load risks caused by geometrical morphology sudden change are comprehensively evaluated, and a path risk section and a non-path risk section are intelligently recognized. A conservative prediction mode and a conventional prediction mode are adaptively switched according to different risk sections, the normal vector of the surface of a workpiece at a laser machining point is accurately predicted, then the posture adjustment amount of the cutting head is calculated according to the normal vector, and finally real-time and smooth posture adjustment of the cutting head in the movement process is achieved through multi-axis synchronous interpolation control. And the laser beam is always vertical to the surface of the workpiece.

The invention discloses a shield tunneling intelligent control method and system based on a ground-tunnel-machine-information-human adaptation level, and relates to the crossing field of underground engineering intelligent construction and information technology. Setting a first-level index and a second-level index; dividing the shield construction state into three levels of intelligent adaptation levels by combining the total score of the construction state with a dynamic threshold value; setting four targets of attitude intelligent control, settlement intelligent control, tunneling efficiency optimization and construction abnormity diagnosis; a machine learning prediction model is constructed, and the construction state parameters corresponding to the targets are predicted in real time; according to the shield intelligent adaptation level, the man-machine cooperation modes are divided into three classes of A level, B level and C level; and comparing actual data with a prediction result of the machine learning model, and dynamically correcting the control target parameters. Through real-time sensing of geological, mechanical and environmental multi-dimensional construction states and in combination with a dynamic weight distribution strategy, precise evaluation of the shield construction state is achieved, and meanwhile self-adaptive switching of the man-machine control right is achieved.

The invention relates to the technical field of micro-grid control, and discloses a micro-grid adaptive switching control method and system based on multi-source information fusion, and the method comprises the steps: obtaining the internal operation parameters of a micro-grid, and the state parameters of an external large power grid connected with the micro-grid; the internal operation parameters and the external large power grid state parameters are fused, and a real-time comprehensive operation state model of the micro-grid is constructed; based on the real-time comprehensive operation state model, adaptively determining a target operation mode of the micro-grid; and according to the target operation mode, generating and executing a smooth switching control instruction of the micro-grid. According to the method, the multi-source operation information of the large power grid inside and outside the microgrid is fused, the comprehensive operation state model is constructed in real time, the target operation mode is adaptively selected, and switching control is smoothly executed, so that efficient and stable switching of the microgrid between multiple modes such as grid connection and island can be realized, and the power supply reliability, the system stability and the electric energy quality are improved.

The invention relates to the technical field of pipeline construction, and discloses a water supply pipeline installation auxiliary method and system based on multi-source positioning and digital twinning, and the method comprises the steps: constructing a digital twinning model based on a three-dimensional point cloud modeling technology, and integrating the geographic information of a construction area, high-voltage line corridor parameters and pipeline installation path planning data; a multi-source positioning sensor group is arranged on hoisting equipment and a pipeline, and spatial position, attitude and environmental electric field data are collected in real time and transmitted to a data fusion processing module; multi-source data are fused through a Kalman filtering algorithm, and high-precision positioning is realized in combination with a digital twinborn model; dynamically adjusting a positioning mode based on an adaptive switching mechanism; construction parameters are generated in real time, dynamic monitoring and early warning are conducted, and when a safety threshold value is exceeded, alarm is triggered and operation is suspended. The system corresponds to the method. By the adoption of the method, the positioning precision and environmental adaptability of water supply pipeline installation are improved, the construction safety risk of complex scenes is reduced, and the construction efficiency is improved.

The invention relates to the technical field of power supplies, and discloses a high-precision power supply control method based on a digital signal processor, which comprises the following steps of: acquiring data such as voltage, current, temperature, load parameters and the like of a power supply at a high frequency of kHz-level sampling frequency by using a high-precision sensor, transmitting the data to a DSP (Digital Signal Processor), and removing noise interference by applying wavelet transform. Sample quality is improved through high-frequency data acquisition and wavelet denoising, nonlinear and time-varying characteristics of a power supply system are identified by using a lightweight CNN and an LSTM, a reinforcement learning dynamic optimization control strategy is combined, self-adaptive switching between traditional control and an intelligent algorithm is realized through working condition identification, and the power supply system control method based on the LSTM is realized. The problems that noise interference influences data quality, system characteristic recognition is inaccurate, complex working condition control strategy optimization is insufficient, and output precision is unstable due to the fact that a control mode cannot be switched in a self-adaptive mode in an existing power supply can be effectively solved, and control precision, efficiency and device loss can be considered. And the stable operation requirement of the high-precision power supply under multiple working conditions is met.

The invention relates to the technical field of vehicle-mounted communication, and provides a 5G network optimization method and system based on an intelligent dynamic multi-band adaptive switching system, and the method comprises the steps: obtaining network signal quality data, environment perception data and a communication task demand set; dynamic obstacle features are extracted based on environmental perception data, and signal occlusion prediction is output through a double-branch mixed deep learning model; screening qualified candidate links to construct a candidate set, generating a dynamic weight by using a deep Q network, calculating a comprehensive score of the candidate links, determining a main communication link under a hard constraint condition, and generating a communication strategy instruction; and according to the instruction type of the communication strategy instruction, performing dynamic fragmentation and multi-path distribution on the data stream, performing verification, recombination and intelligent delivery by a receiving end, and collecting a feedback data packet for network closed-loop feedback. According to the method, multi-mode sensing and signal shielding prediction are fused, and a self-adaptive switching and cooperative transmission mechanism of multi-band communication is constructed.

The invention relates to the technical field of digital communication, in particular to an intelligent electric meter dual-mode communication self-adaptive switching method, and provides the following scheme that operation data are divided into a plurality of data units at a sending end, priority evaluation is carried out, and the time delay, the packet loss, the energy consumption and the bandwidth state of two links are combined, so that the intelligent electric meter dual-mode communication self-adaptive switching method is realized. Positioning clearing cut points in the priority sequence so as to realize differentiated distribution of data between a high-speed link and a low-speed link; when the data is distributed to a low-speed link, sparse coding is carried out by adopting a preset dictionary, and differential updating is triggered when an error exceeds a limit, so that decoding consistency is ensured; a receiving end realizes unified analysis of the original message and the sparse message through cross-link association, dictionary updating and residual synthesis; according to the invention, the timeliness of the key message can be guaranteed, the communication energy consumption and cost can be reduced, and the cooperation efficiency of the dual-mode link can be improved.

The invention relates to the technical field of network switching, in particular to a heterogeneous network dual-mode self-adaptive switching method and system. According to the method, the multi-dimensional environment sensing data and the initial signal intensity are acquired, the signal intensity is calibrated in a dynamic environment, the dynamic response of the network state to real-time change is realized, and the connection state characteristic and the side network consumption index of the dual-mode network are acquired by combining the calibrated signal intensity. The switching demand can be evaluated on the basis of the data, the switching demand can be judged more accurately through the multi-dimensional evaluation mechanism, the limitation that a traditional method only depends on signal strength is avoided, and the switching demand can be evaluated by generating an optimized directed time sequence graph and a network performance data set. According to the technical scheme, the equipment can make a scientific and reasonable switching decision according to the real-time network state snapshot data and the preset optimization time sequence graph, and the connection requirements of the equipment can be dynamically adapted under the variable network conditions, so that the optimal network experience is kept, and the network connection quality is improved.

The invention relates to the technical field of integrated circuit design and artificial intelligence hardware acceleration, and particularly discloses a quantization precision adaptive switching hardware acceleration architecture. Hardware is divided into a static area and a dynamic area, wherein the static area comprises a pre-processing module, a post-processing module, a control module and a reconfigurable logic loading control block which run all the time; the dynamic region bears a quantization and inverse quantization module composed of a plurality of reconfigurable logic units. The method is characterized in that a model precision instruction is analyzed through a control module, and a reconfigurable logic file with corresponding precision is dynamically loaded to a dynamic area from external starting equipment by a loading control block according to an internal address mapping table, so that seamless switching of different quantization precision is realized on the hardware level, and the whole chip does not need to be burnt again. According to the design, through a modularized and reconfigurable hardware structure, the limitation of fixed-precision hardware in coping with diversified AI models is effectively solved, and the deployment flexibility and energy efficiency are remarkably improved.

The invention discloses a source-grid-load-storage integrated coordinated management and control system for an intelligent micro-grid, and relates to the technical field of intelligent micro-grids and comprehensive energy regulation and control. The system comprises the following components: a multi-energy-flow data acquisition unit, a multi-energy-flow coupling modeling and optimizing unit, a multi-energy-flow gradient utilization execution unit, a mode self-adaptive switching unit and a main control unit, according to the invention, through a multi-energy flow coupling modeling and optimization unit, an electric-thermal-gas multi-energy flow coupling model comprising a heat supply network transmission loss calculation sub-model is constructed, a renewable energy consumption constraint sub-model is additionally arranged, and an improved hybrid particle swarm optimization algorithm is adopted to carry out dynamic optimization solution, so that an optimal scheduling strategy is generated; according to the strategy, the consumption rate of renewable energy sources is increased, electricity-heat gradient utilization and efficient configuration are achieved through a heat energy distribution priority regulation and control mechanism and efficiency optimization control of the waste heat recovery module, and dependence of heat loads on electric energy is remarkably reduced.

The invention provides a sea area digital twinning method and system based on buoy and station data fusion, belongs to the related technical field of sea area digital twinning, and establishes a data quality evaluation mechanism and a similarity data compression mechanism by constructing a multi-source heterogeneous ocean data acquisition system. Intelligent fusion processing of buoy data and station data is achieved, and the problem that in the prior art, the data fusion precision is low is solved; through the self-organizing growth network structure of the ocean dynamic response enhancement model, neuron connection can be automatically adjusted according to the spatial-temporal variation degree of training data, an optimal topological structure is formed, and the defect that a traditional fixed parameter model cannot adaptively process a complex ocean environment is effectively overcome; by establishing a dynamic parameter adjustment mechanism and a multi-algorithm adaptive switching strategy, the most suitable prediction algorithm is automatically selected according to the correlation characteristics of the ocean data sequence, and high-precision digital reproduction of the complex ocean environment is realized.

The invention relates to the technical field of power conversion, in particular to a collaborative optimization control method, system and equipment of a multi-mode power conversion device and a storage medium. The method comprises the following steps: constructing a double-layer collaborative architecture by collecting multi-source heterogeneous operation parameters, obtaining a device operation state, power grid dynamic characteristics and environment change information, establishing a cross-level communication protocol to realize data synchronization, and outputting a real-time working condition feature vector; deploying a dynamic mode switching engine based on a real-time working condition feature vector, triggering multi-mode operation strategy reconstruction through a state transition probability model, constructing a self-adaptive switching mechanism comprising a parallel power supply mode, an island operation mode and a hybrid modulation mode, and establishing a composite fault response system to realize pre-diagnosis and grading disposal of an abnormal state; millisecond-level real-time control is implemented in the edge control layer to generate a pulse width modulation driving signal, multi-target global optimization is implemented in the cloud optimization layer to dynamically adjust an operation parameter combination, and closed-loop control is formed through bidirectional data interaction and strategy feedback.

The invention relates to the technical field of power internet of things, in particular to a broadband / narrowband self-adaptive switching power internet of things communication system and a control method, which intelligently identify the priority and quality of service (QoS) requirements of different services by collecting network states, terminal states and service flow data in real time. And an optimal communication mode switching strategy is dynamically generated based on a pre-trained machine learning model, seamless switching of broadband and narrowband communication links is realized, and the decision accuracy is continuously improved through a feedback optimization mechanism. According to the method, the problems that a traditional electric power Internet of Things communication mode is fixed and single and cannot intelligently adapt to services and network states are effectively solved, the system communication reliability is remarkably improved, the transmission time delay and energy consumption are reduced, and high-adaptability and high-reliability intelligent communication guarantee in a complex electric power scene is achieved.

The utility model discloses an intelligent communication antenna system capable of self-adapting to signal intensity, which is characterized by comprising an environment sensing module, a signal processing module and a fuzzy calculation adaptation module, and the environment sensing module, the signal processing module and the fuzzy calculation adaptation module are electrically connected. The environment sensing module comprises a signal state monitoring unit and a physical environment sensing unit; according to the utility model, through the arrangement of the environment sensing module and the fuzzy calculation adaptation module, if the attitude of the unmanned aerial vehicle changes in the driving process, the system can realize the dynamic prediction of the unmanned aerial vehicle according to fuzzy calculation in combination with the effects of multiple sensors such as a radar and a sensor, and can adjust the antenna parameters in time; according to the device, dynamic adaptation is realized through closed-loop feedback and sensing-processing-adjustment, so that the antenna signal strength can be adaptively switched when the attitude of the unmanned aerial vehicle changes quickly.

The invention provides a data center interconnection link fault self-healing and path switching method, which comprises the following steps of: acquiring multi-dimensional link performance monitoring data, establishing a standardized time sequence database, realizing link health degree multi-index trend prediction by combining an LSTM-Attention model, and determining the link health degree according to the LSTM-Attention model. Risk-aware dynamic path selection and switching for multiple business scenes are realized by combining business service sensitivity modeling, path inherent stability quantification, nonlinear adaptive switching criteria and a debounce switching process, the response accuracy and the business adaptation degree of path switching are improved, false triggering and service interruption risks can be remarkably reduced, and the path switching efficiency is improved. And the high availability and robustness of routing in a complex network environment are enhanced.

The invention discloses an unmanned aerial vehicle-unmanned agricultural machine collaborative operation staged scheduling method under energy consumption constraint, belongs to the technical field of intelligent scheduling, and innovatively designs a three-stage dynamic scheduling mechanism based on operation urgency, and realizes stage adaptive switching through real-time energy consumption monitoring. And an unmanned aerial vehicle-agricultural machinery energy consumption prediction model considering flight conditions and operation parameters is established, and accurate prediction of the residual endurance time is realized by using an LSTM network. An improved NSGA-II multi-objective optimization algorithm is provided, and under a three-objective Pareto optimization framework of total energy consumption minimization, task completion rate maximization and time cost minimization, an energy consumption perception auction mechanism is combined to realize intelligent distribution of emergency tasks to high-electric-quantity equipment. A distributed real-time scheduling system based on edge computing is developed, an edge server is deployed to run a lightweight algorithm, and a real-time scheduling algorithm and a dynamic task conflict resolution mechanism are combined, so that the task redistribution delay is controlled within 500ms, and the conflict resolution success rate is increased to 92.3%.

The invention discloses an AGV-six-degree-of-freedom mechanical arm operating system and method based on double-vision fusion, the system comprises a control system and a six-degree-of-freedom mechanical arm, and the control system comprises a master control unit, a slave control unit and a dynamic error compensation module; the method comprises the steps of AGV autonomous navigation and material transfer, cross-station accurate docking and dynamic error compensation, high-precision biological medicine operation under double-vision fusion guidance, and material recovery and circulation. According to the invention, through dual-vision dynamic fusion of eyes outside the hand and eyes on the hand, adaptive switching from global coarse positioning to local fine positioning is realized; due to the integrated design of the AGV and the six-degree-of-freedom mechanical arm, the operation flexibility is greatly improved; an extended Kalman filtering dynamic error compensation algorithm is innovatively adopted, so that the comprehensive error of the AGV, the mechanical arm and the visual system can be corrected in real time; and by combining with a double-layer distributed control architecture, the system realizes multi-task intelligent scheduling and modular collaboration.

The invention discloses a permanent magnet synchronous motor sensorless control method based on a dynamic position error. A transition stage is provided, per-unit estimation position errors between a first position error signal obtained based on a high-frequency signal injection method and a second position error signal obtained based on a sliding mode observer are compared, an optimal switching speed point is dynamically determined, smooth fusion is carried out on the two position errors by using a nonlinear weighting function, and the optimal switching speed point is obtained. And finally, the estimated position and rotating speed are obtained through a phase-locked loop. And finally, position tracking is carried out by adopting different error signals according to the estimated rotating speed. According to the method, the problem of estimation value pulsation and jump caused by the fact that a traditional method depends on fixed experience switching points is solved, smooth and self-adaptive switching of the two estimation methods in the full-speed domain range is achieved, the control precision and operation stability of the system are remarkably improved, the structure is simple, and engineering implementation is easy.

The invention relates to an aggregation scene unmanned aerial vehicle cluster three-dimensional deployment method and device based on cyclic segmentation and multi-objective optimization. The method comprises the following steps: designing a cyclic segmentation optimization framework and a self-adaptive switching mechanism oriented to an aggregation scene; performing cyclic segmentation optimization on the unmanned aerial vehicle cluster based on a cyclic segmentation optimization framework and an adaptive switching mechanism, and updating a Pareto file; designing a comprehensive fitness function, screening out elite parent individuals based on the Pareto file, and performing cyclic segmentation optimization on the unmanned aerial vehicle cluster by using the elite parent individuals; and performing three-dimensional deployment of the unmanned aerial vehicle cluster in the aggregation scene according to a cyclic segmentation optimization result. According to the method, through multi-objective optimization based on Pareto and an innovative segmented optimization framework, and through dynamic switching of level and height optimization stages, astringency and global diversity of understanding are remarkably improved, optimal deployment of a multi-unmanned aerial vehicle communication system can be realized in a complex scene, and theoretical and method support is provided for practical engineering application.

The invention provides an MMPC-based sedimentation tank intelligent dosing control system and method, and relates to the technical field of water treatment.The MMPC-based sedimentation tank intelligent dosing control system comprises a fixing frame and a sedimentation tank, and a water inlet pipe is fixedly installed at the top of the fixing frame; the left end of the water inlet pipe is fixedly connected with a flow instrument; the left end of the flow instrument is fixedly connected with a filter pipe; a water inlet detection pipe is slidably mounted on the left side of the filter pipe; and four mounting seats B are fixedly mounted at the top of the water inlet detection pipe. Based on a multi-model self-adaptive switching structure, the problem of mismatching of a traditional single model under variable working conditions is solved, when the inflow flow fluctuates or the turbidity changes suddenly, the system automatically calls a prediction model matched with the current working condition, the change of the effluent turbidity is predicted in advance, the dosage is adjusted in time, and the effluent turbidity is stably controlled within a target range, so that the stability of the system is improved. The safety of water consumption of residents is guaranteed, and the problem of out-of-control risk caused by time delay is solved.

The invention relates to a servo hydraulic multi-working-condition parameter self-adaptive switching and correcting method. The method comprises the steps that system real-time data flow including real-time hydraulic pressure, executing mechanism speed and control response deviation is monitored and collected; identifying the current working condition based on the real-time data and indexing the reference control parameters; running a parallel response evaluation program to generate a dynamic stability indicator and determine an expected performance threshold; the dynamic stability index is compared with an expected performance threshold value, and when parameter mismatch is confirmed, a temporary compensation coefficient is generated to correct the reference control parameter in real time; and monitoring the correction offset, and updating the working condition-parameter mapping database when the aging judgment condition is met. The method has the advantages that manual parameter adjustment can be replaced, automatic switching of millisecond-level working conditions is achieved, the problem of parameter mismatching caused by equipment aging is effectively solved through a model self-evolution mechanism, and the control precision and stability of the servo hydraulic system in the whole life cycle are ensured.

The invention discloses a proxy model auxiliary evolution method based on two-stage adaptive switching and Voronoi niche. The method comprises the steps of generating an initial sample by adopting optimal Latin hypercube sampling, obtaining a real fitness value through simulation, constructing an initial training data set, and setting an initial iteration counter k and an evaluation budget threshold value; training a proxy model based on the current data set, and executing evolutionary algorithm optimization by using the proxy model to obtain a current optimal individual; judging two stages according to an iteration counter k and a distance threshold value; the development execution stage comprises the following steps: evaluating the real fitness and updating a data set; the exploration execution stage comprises the steps of multi-modal approximate detection, Voronoi niche division, multi-modal collaborative search, real fitness evaluation and data set updating; judging a termination condition and outputting a result; according to the method, three core technologies of an adaptive stage switching mechanism, multi-modal approximate detection and Voronoi niche division and multi-extremum collaborative filling are creatively integrated, so that the defects of insufficient global exploration, low local development precision and poor convergence efficiency of a traditional method in a high-dimensional multi-modal expensive optimization problem are effectively overcome; and the solving efficiency and reliability of a complex and expensive optimization problem are remarkably improved.

The invention relates to the technical field of aircrafts, and discloses an aircraft wireless network adaptive switching method, an aircraft and a storage medium, and the method comprises the steps: obtaining the current speed of the aircraft; acquiring the current first signal intensity and the current signal quality of the aircraft; determining a first compensation value based on the current speed; if the current signal quality is greater than or equal to the preset threshold value, compensating the first compensation value to the current first signal strength to obtain the compensated current first signal strength; and the aircraft is dynamically triggered to be switched to the target base station based on the compensated current first signal intensity, so that the stability and reliability of the connection between the aircraft and the wireless network are improved.

The invention relates to the technical field of oilfield water injection, and discloses a water injection skid process system with self-adaptive switching and redundancy functions and a control method. The water injection skid process system comprises a main process unit which is formed by connecting a main centrifugal pump and a main plunger pump in series; the self-adaptive switching unit comprises a standby pump set branch, a bypass branch and a control module; and the redundancy design unit is used for carrying out double-valve parallel redundancy configuration on the key valves and carrying out double-path redundancy setting on the key sensors. According to the invention, a three-layer structure with a main process, self-adaptive switching and redundancy design is systematically constructed, and a hardware foundation of a high-reliability water injection system is laid. The structure not only realizes a conventional water injection function, but also remarkably reduces the risk of single-point failure by introducing redundancy and a self-adaptive mechanism, so that the system can keep continuous operation when equipment fails or working conditions are abnormal, the stability and production efficiency of oilfield water injection operation are greatly improved, and the economic benefit is increased. The problems of poor single-point fault resistance and lack of working condition self-adaption are solved.

The invention relates to the technical field of wireless communication, in particular to a public network interphone with a quantum chip. According to the interphone, a master control module and a quantum security chip work cooperatively, a quantum random number generator is used for dynamically deriving a session key, and offline security distribution of a group master key is realized by encrypting a two-dimensional code; in a communication process, a system adaptively switches a voice coding mode according to a network condition, end-to-end authentication encryption is carried out on voice data by using a hardware encryption engine, and low-delay transmission is guaranteed through a network priority mark; the device establishes a complete key life cycle management mechanism, supports regular update and forward security of session keys and instant update and backward security of a group master key when members change, and ensures that all key operations are completed in a quantum chip. According to the invention, various eavesdropping and tampering attacks are effectively resisted, and safe, real-time and clear high-confidentiality voice communication in a public network environment is realized.

The invention belongs to the technical field related to operation control of a power system, and provides a transient instability judgment method and system of a network-building type converter in order to solve the problem that an existing transient instability judgment method of the network-building type converter is prone to causing maloperation or missed judgment of a control strategy, and a nonlinear equivalent circuit model of the network-building type converter is established. Calculating transient total energy and critical instability energy of the system in real time, and adaptively switching a control mode according to the magnitude relationship of the transient total energy and the critical instability energy; during normal operation, an original control strategy of the virtual synchronous machine is maintained, and oscillation is suppressed by using the damping characteristic of the virtual synchronous machine, so that the voltage and frequency supporting capacity of a power grid is maximized; and when an instability risk is detected, entering a fault ride-through mode to realize rapid and accurate identification and control of the instability risk.

The invention provides a logic control-based self-adaptive optocoupler compensation circuit and a switching power supply. The logic control-based self-adaptive optocoupler compensation circuit comprises a first operational amplifier circuit, a second operational amplifier circuit, a third operational amplifier circuit and a fourth operational amplifier circuit, the switching tube circuit is used for switching on or switching off a corresponding switching tube according to the level signal to match impedance access of a corresponding size; the output end of the impedance matching circuit is connected with the first input end of the photoelectric coupler, the second input end of the photoelectric coupler is connected with the output end of the feedback compensation circuit, and the current of the input end of the photoelectric coupler and the total impedance of the self-adaptive feedback compensation loop are adjusted by automatically matching different impedances. Therefore, automatic switching of different gain and bandwidth working modes of the photoelectric coupler under wide-range output is realized. According to the invention, the working current of the optocoupler is adaptively switched through the logic control circuit, and the compensation parameter of the feedback loop is dynamically optimized, so that the switching power supply can achieve the effect of high stability under the working condition of full-range output adjustment.

The invention discloses a multi-source time consistency verification and traceability method in an electric power wide area system, and belongs to the technical field of electric power system automation. Comprising the following steps: generating a quantifiable time source health degree index, and determining the credibility grade of each time source; a distributed timestamp chain containing timestamps, quality rating and verification information is constructed, and time consistency verification among multiple nodes is achieved; advanced identification and self-adaptive switching of an abnormal time source are realized through fault prediction; complete tracking of a time data propagation path and a processing process is realized through timestamp records of key nodes; various time synchronization scenes and abnormal conditions are simulated in the virtual environment; when a time anomaly is detected, rapidly positioning a source and an influence range of the time anomaly in combination with the time traceability system and the digital twin time synchronization model; and if the key service is influenced by time abnormity, dynamic resource scheduling and priority safeguard measures are executed to ensure the time precision requirement of the key service.

The embodiment of the invention provides an audio synthesis method and device, a medium and equipment, and relates to the technical field of speech synthesis. The method comprises the steps of obtaining a target text to be subjected to audio synthesis; splitting the target text into a plurality of text units with complete semantics to obtain a task sequence; for the ith text unit in the task sequence, scheduling influence factors are obtained before the audio synthesis task is executed, the scheduling influence factors comprise application layer semantic information and / or equipment real-time performance indexes, and i is a positive integer; determining a target synthetic link from a cloud synthetic link and an end-side synthetic link based on the scheduling influence factors; and completing audio synthesis of the ith text unit through the target synthesis link. According to the scheme provided by the embodiment of the invention, in the audio synthesis process of the target text, adaptive switching between the cloud audio synthesis link and the end-side audio synthesis link can be realized in a low-delay manner.

The invention discloses an unmanned aerial vehicle multi-technology fusion intelligent control method. The method comprises the following steps: establishing serial port communication between an airborne terminal and an unmanned aerial vehicle; the airborne terminal acquires model information by receiving a heartbeat packet actively sent by the unmanned aerial vehicle, and switches to a corresponding control protocol according to the model information for controlling the unmanned aerial vehicle; and the airborne terminal is used for dynamically monitoring the signal quality of the communication link and adaptively switching the optimal communication link. According to the intelligent control system and method provided by the invention, intelligent switching can be performed according to indexes such as signal strength, delay and stability, and an early warning value is set to deal with a sudden communication loss problem, so that the communication continuity and the data transmission reliability of the unmanned aerial vehicle in a task execution process are ensured.