2662results about How to "Reduce load" patented technology

The invention relates to the technical field of power management, in particular to a charging pile group energy management method, which comprises the following steps: S1, predicting the power demand of each charging pile in a short period and the available amount of renewable energy; s2, adjusting the charging power of each charging pile through a dynamic allocation algorithm; s3, encouraging a user to charge in an off-peak period based on a preset pricing algorithm; s4, predicting a user charging demand mode; s5, monitoring electric energy quality in a charging process in real time, and automatically adjusting parameters of charging equipment by using a preset electric energy adjusting technology; and S6, automatically activating a preset standby energy supply scheme under the emergency condition of the power grid fault. According to the invention, energy distribution is optimized through real-time monitoring and intelligent adjustment of the charging strategy, the power grid efficiency is improved, the cost is reduced, and the continuity and safety of the charging service are ensured through the standby energy system, so that the operation efficiency of the charging infrastructure and the user satisfaction are remarkably improved.

The invention relates to the technical field of industrial internet, in particular to a smart energy management method and system based on the industrial internet, and the method comprises the following steps: S1, data collection: collecting energy consumption data and environment data in a production process in real time; s2, data fusion: carrying out fusion processing on multi-source data by adopting a data fusion technology; s3, distributed energy optimization: optimizing the energy consumption of each node on the distributed nodes in real time by using an edge computing technology; s4, intelligent load balance optimization: dynamically adjusting the operation load of each industrial production device; s5, multi-level fault prediction: performing fault prediction on the industrial production equipment; and S6, control strategy generation: generating a self-adaptive control strategy in combination with the fault prediction result of the industrial production equipment. According to the method, the lowest energy consumption of the optimization result is ensured, the load is uniformly distributed, local overload and energy waste are avoided, and the overall energy utilization efficiency is improved.

The invention discloses an intelligent job shop scheduling method. The method comprises the following steps: S1, establishing a personalized improved NSGA-II algorithm module and a DQN-based adaptive decision algorithm module; s2, establishing a mathematical model taking the maximum completion time, the total load of equipment and the total energy consumption of a workshop as optimization targets; s3, in a personalized improved NSGA-II algorithm module, considering a workshop optimization target, adopting multiple strategies for initialization, and adding a user personalized demand to screen a target population; s4, in a DQN-based adaptive decision algorithm module, population features are extracted to construct an agent state space, and a deep Q network experience playback mechanism is utilized to train the relationship between agent capture scheduling information and a scheduling target to perform adaptive action decision; and S5, returning the optimal action predicted by the DQN model to the NSGA-II, adjusting the optimal parameter proportion according to the real-time state, and improving the multi-target solution quality.

The invention relates to the technical field of information processing, in particular to an electronic information dynamic scheduling and management system and method, and the system comprises a data flow dynamic monitoring module, a dynamic window adjustment module, a data distribution module and an instruction flow recombination module. According to the invention, the adaptability and flexibility of data processing are improved by monitoring the data flow in the electronic information in real time and carefully analyzing the size and type change, and the dynamic adjustment of the data processing window is realized by identifying the peak value and valley value of the flow and analyzing the flow fluctuation amplitude. By analyzing the dependency relationship and potential delay between execution instructions and re-arranging the instruction execution sequence, the system can more effectively distribute the load of a processor core, reduce the delay and enhance the processing speed, thereby not only optimizing the management of electronic information flow, but also enhancing the adaptive capacity of the system to a complex data environment, and improving the user experience. And a more efficient and safer information processing platform is provided.

The invention relates to the technical field of building materials, and particularly discloses high-strength lightweight concrete containing hollow glass beads and a preparation method of the high-strength lightweight concrete. The high-strength lightweight concrete containing the hollow glass beads is prepared from cement, fly ash, carbon fiber grafted hollow glass beads, lightweight sand, deionized water, polypropylene fiber grafted rubber particles and a water reducing agent according to the mass ratio of (58-75): (25-38): (45-65): (20-40): (42-55): (35-55): (5-12) through mixing, mold filling, vibration molding, covering and demolding. The addition amount of the hollow glass beads is strictly controlled, the influence on the overall strength of the concrete is avoided, the density and weight of the concrete are reduced due to the addition of the light sand and the hollow glass beads, the compactness and integrity of the concrete are improved due to the synergistic effect of the two added fibers, and the raw materials have excellent cohesiveness; the concrete can effectively absorb and disperse stress, and has the advantages of excellent strength, light weight, good durability and excellent comprehensive performance.

The invention discloses a multi-dimensional comprehensive online monitoring and fault early warning platform for a main transformer of a gas turbine power plant, and relates to the technical field of power transformer monitoring. In order to solve the problems that in the prior art, the accuracy of a monitoring result highly depends on the quality of collected data and the reliability of a sensor, wrong early warning is possibly caused when the sensor breaks down or data is inaccurate, specific adjustment and calibration cannot be carried out aiming at different transformers and environmental conditions, and the environmental adaptability is low. Multi-dimensional monitoring is carried out on the main transformer based on the sensor assembly, the load of data transmission is reduced through edge side processing, integrity verification is carried out on received dynamic monitoring data, meanwhile, the real-time performance and integrity of the data are ensured, and the transformer health degree evaluation model carries out comprehensive evaluation on the operation state of the main transformer. The health state and the fault type of the main transformer can be accurately judged, and timely and accurate fault information is provided for operation and maintenance personnel.

The invention provides a data acquisition method and device based on a multi-order queue and electronic equipment, and the method comprises the steps: obtaining production data generated by industrial control equipment; according to the acquisition frequency, the production data is distributed to each level queue of the multi-level queue, the queue number of each level queue is adjusted according to the real-time data volume of each queue in each level queue, and each level queue is used for caching the production data of different acquisition frequencies; according to a data packaging strategy, the production data in the multi-order queue is packaged, and the data packaging strategy comprises a timing packaging strategy and a quantitative packaging strategy; and uploading the packaged production data to an industrial Internet of Things platform. Production data acquisition is performed through the multi-order queue, so that the processing pressure of a single queue can be effectively relieved, the data transmission frequency is reduced, and the resource consumption is reduced, thereby improving the efficiency and reliability of data acquisition.

The invention provides a biological signal analysis method and system, a storage medium and electronic equipment. The method comprises the following steps: acquiring a biological signal of a testee; extracting a spectrum feature of the biological signal in a first specified frequency band; optimizing the spectrum features to obtain a second specified frequency band; and obtaining trigger time of a target phase in the second specified frequency band based on a prediction model so as to stimulate the biological signal based on the trigger time. According to the biological signal analysis method and system, the storage medium and the electronic equipment, the prediction precision of the specific phase point of the biological signal is effectively improved.

The invention relates to the technical field of peanut oil production control, in particular to an intelligent optimization system for a peanut oil production control process, which comprises a process parameter modeling module for collecting peanut oil production parameters, performing linear combination on the peanut oil production parameters, analyzing the correlation of the peanut oil production parameters to quality indexes, and calculating the quality indexes of the peanut oil production parameters; and obtaining a process parameter mapping matrix. According to the method, through deep correlation analysis of multiple parameters in the production process, the mapping relation between the process parameters and the oil quality indexes is established, and the precision and reliability of quality control are improved. In the process control, the specific influence of each production link on the quality index is accurately reflected through standardized and linear combinatorial analysis on the parameters such as squeezing temperature, pressure, time, stirring speed and the like. By predicting the quality index under the current production condition, the response speed to the quality change is improved, so that the quality index deviation can be quickly analyzed and evaluated in real-time data monitoring.

The invention relates to the technical field of photovoltaic voltage regulation, and discloses a distributed photovoltaic power distribution network voltage control system and method. According to the system and the method, voltage and power information of each measurement point is acquired through a data acquisition module, related data of the photovoltaic inverter is collected, and a communication module receives the data and transmits the data to a control module and a monitoring management module; the control module calculates voltage-power sensitivity, a power factor, voltage deviation, power loss and reactive power compensation requirements according to the data, evaluates the running state of the current power grid and judges whether reactive voltage regulation is needed or not, and the monitoring and management module calculates system response time and fault occurrence probability and controls the system response time and the fault occurrence probability. And judging whether the control effect reaches the expectation or not, analyzing faults and abnormities, providing an adjustment strategy for the voltage stability and the photovoltaic power generation efficiency by the optimization scheduling module, acting on the control module again, optimizing system operation by issuing a new control signal, generating a system optimization report and sending the system optimization report to a display end.

The invention provides an axially parallel split permanent magnet-water lubricated composite bearing, which belongs to the technical field of bearing design, is applied to a ship propulsion shafting, and comprises a magnetic force bearing module, a magnetic shaft sleeve, a magnet mounting base and a water lubricated bearing. The magnetic force bearing module and the water lubricated bearing are arranged in parallel in the axial direction of the stern shaft. The water-lubricated bearing is arranged on one side close to the propeller and is wholly soaked in a working medium; the magnetic shaft sleeve of a cylindrical structure is installed on a stern shaft, and a stern bearing is attracted under the action of a permanent magnet array in the magnetic force bearing module. And the magnet mounting base is used for supporting the magnetic force bearing module and regulating and controlling the magnetic force. According to the integral permanent magnet-water lubricated composite bearing, the permanent magnets and the water lubricated bearing in the integral permanent magnet-water lubricated composite bearing are structurally split, the mutual restriction of a magnetic force bearing module and a water lubricated bearing module in the aspects of space, size and performance can be effectively eliminated, and the use flexibility is enhanced; the bearing distribution of the shaft system can be optimized, and it is ensured that the tail shaft system has good dynamic stability.

The invention discloses an extensible content interactive display method and system based on streaming media playing, the extensible content interactive display method based on streaming media playing belongs to the field of streaming media, and the method comprises the following steps: S1, dynamically adjusting the resolution and code rate of content under different network conditions; dynamic self-adaptive stream transmission is realized; s2, directly acquiring data through the nearest edge node when the content is requested, and caching high-frequency interaction data at the edge node; s3, the user request is routed to the optimal node; s4, adopting a predictive buffering and preloading mechanism; s5, predicting user interaction behaviors by using a deep reinforcement learning algorithm; and S6, adopting H.265, and combining the characteristics of low delay and high reliability of the QUIC protocol to carry out transmission. The extensible content interactive display system based on streaming media playing comprises a user behavior analysis module, a content management and distribution module, an interactive prediction and recommendation module, a preloading and cache management module, a network transmission and optimization module and the like.

The invention provides a southern red soil dry land deacidification soil conditioner and a preparation method thereof, and belongs to the technical field of soil conditioners. The preparation method comprises the following steps: embedding bacillus subtilis, bacillus licheniformis and bacillus amyloliquefaciens to prepare bacterial microspheres, adding the bacterial microspheres into gel formed by carboxymethyl chitosan and silk fibroin peptide to prepare sustained-release bacterial microsphere gel, uniformly mixing the sustained-release bacterial microsphere gel with porous silicon dioxide loaded with basalt and charcoal, and drying to prepare the acid-reducing soil conditioner for the southern red soil dry land. The acid-reducing soil conditioner for the southern red soil dry land not only improves the pH value of the soil, but also can loosen the soil and improve the air permeability of the soil to a certain extent, and promotes the absorption of crops to moisture and nutrient elements by improving the physical and chemical properties of the soil, so that the normal growth of the crops is ensured, and the acid-reducing soil conditioner has a wide application prospect.

The invention belongs to the technical field of wind power generation, and discloses a wind power plant digital twin modeling system and a use method, the system comprises an equipment module, the equipment module comprises a biological bionic adaptive fan blade system, a quantum sensing network, a laser radar system, a high-resolution multi-modal imaging system and an intelligent autonomous flying robot group system; the network module comprises a 5G private network, a quantum communication network and an edge computing network; the data module comprises a distributed database system, a big data processing platform and an AI training platform; the AI module comprises a wind regime prediction model, a power prediction model, an equipment health state monitoring model and a self-adaptive control algorithm model; the application module comprises a digital twinborn visualization platform, a holographic mixed reality operation and maintenance system and an intelligent scheduling system. Modeling and intelligent management of the wind power plant can be realized, the power generation efficiency can be improved, the operation and maintenance cost can be reduced, and the service life of equipment can be prolonged.

The invention provides an Internet of Vehicles trust management method and system based on a block chain, and the method comprises the steps: dividing intelligent networked vehicles running on a road into a plurality of vehicle groups according to a preset region coverage range, calculating a group trust value set of vehicles in each group in a node dimension and a trust value offset set and a vehicle message score set in a message dimension in a vehicle group form, and calculating a global trust value and a total trust value offset amount of each vehicle in different vehicle groups based on the group trust value set, the trust value offset set and the vehicle message score set; carrying out weighted summation to obtain a comprehensive trust value of each vehicle; comparing a preset warning trust threshold value with a malicious trust threshold value based on the comprehensive trust value, and endowing each vehicle with a vehicle label; and performing communication management on the corresponding vehicle based on the vehicle management rule matched with the vehicle label. According to the invention, malicious nodes in the network can be effectively identified and processed in real time, the trust value is prevented from being maliciously tampered, the communication delay is reduced, the network load is reduced, and the vehicle privacy is protected.

The invention discloses low-drunkenness type Baijiu distiller's yeast and a preparation method and application thereof. The prepared distiller's yeast can be used for producing baijiu, the physical and chemical indexes of the baijiu are good, fusel oil is reduced by 30%-57%, the metabolism speed of yeast is controlled by controlling the saccharification speed, and the generation of the fusel oil is reduced; meanwhile, lactic acid bacteria and bacillus subtilis of the distiller's yeast and bacteria cultured in a high-temperature stage can effectively inhibit the path of fusel oil metabolized by yeast, generation of fusel oil is further reduced, total ester and total acid are slightly increased basically, the content of total dibasic acid is increased by 10 times, and the content of dibasic acid diethyl ester is increased by 2 times. After the wine liquid is aged, drunkenness detection is carried out, and the comprehensive drunkenness Q is 0.6815-0.8325 and is far lower than a variety of commercially available white spirits (the comprehensive drunkenness is greater than or equal to 1).

The invention provides an adsorption module and a motion system, and relates to the technical field of precision equipment. The adsorption module comprises an adsorption substrate, a rotating base, a rotating shaft module, a wafer bearing table and a suction cup. The rotating base is fixedly connected with the adsorption substrate, and the rotating shaft module can rotate relative to the rotating base; the rotating shaft module can move in the axial direction of the rotating shaft module relative to the rotating base; the rotating shaft module is configured to be connected with the suction cup or the rotating base in an air pressure connection mode. The wafer bearing table is configured to be capable of adsorbing the suction cup or supporting the suction cup in an air floatation mode.

The invention discloses a multi-module lithium battery pack system based on cloud computing management, relates to the technical field of cloud computing management, and is used for solving the problem of poor management precision of a multi-module lithium battery pack. Comprising a lithium battery data acquisition module, a battery degradation analysis module, a degradation acceleration point determination module and a strategy management module. According to the invention, data acquisition and preprocessing are carried out on a multi-module lithium battery pack through an Internet of Things sensor and an edge computing device, the data are transmitted to a cloud platform, Fourier transform is used to extract features, a nonlinear regression model is combined to evaluate the health state of the lithium battery, and a degradation speed is determined and a degradation acceleration phenomenon is identified through a segmented nonlinear regression model. Kalman filtering and nonlinear regression are combined, a degradation acceleration point is identified, load distribution is optimized through an intelligent scheduling algorithm after identification, the load of a degradation module is reduced, a scheduling signal is generated by analyzing load adjustment information, a system is guided to perform strategy scheduling management, and a scheduling strategy and energy management efficiency are optimized.

The invention relates to the technical field of energy conservation, environmental protection and building energy management, and discloses a low-carbon high-speed service area system integrating waste heat recovery, photovoltaic power generation and intelligent energy storage, which comprises a waste heat recovery module, a photovoltaic power generation module, an energy storage module, an intelligent control module and a carbon emission reduction statistics and feedback module, all the modules work cooperatively to form an integrated energy-saving and carbon-reducing system, when the low-carbon high-speed service area system integrating waste heat recovery, photovoltaic power generation and intelligent energy storage is used, a stable heat source can be provided for domestic hot water through the waste heat recovery module, power self-supply of a service area is achieved through the photovoltaic power generation module, and energy conservation and emission reduction are achieved. The energy storage module stabilizes power supply during power generation fluctuation, the intelligent control module guarantees efficient cooperative work of all the modules, the autonomous learning module automatically distributes heat storage and power storage resources according to historical data and demand prediction, and the system stably operates under peak or fluctuation conditions. And the carbon emission reduction statistical module provides data support for low-carbon benefits of the system.

The invention discloses a sewage sludge advanced treatment device, which belongs to the technical field of sludge treatment, and comprises a flocculation basin and a dehydration device, a concentration adjusting tank is arranged between the flocculation basin and the dehydration device, the inside of the tank is divided into a high-concentration area and a low-concentration area through a filter plate, the high-concentration area is provided with a first liquid inlet pipe, and the low-concentration area is provided with a second liquid inlet pipe; flowing into a dehydration device through a mixing pump; the filter plate is controlled by a driving mechanism to move so as to change the volume of the high-concentration area, and a first concentration detector is mounted on the first liquid inlet pipe and is used for moving the filter plate to reduce the volume of the high-concentration area when the first concentration detector detects that the concentration is lower than a threshold value; a control valve is installed on the second liquid inlet pipe and used for opening the control valve when the first concentration detector detects that the concentration is larger than the threshold value. The concentration regulating tank is arranged between the flocculation tank and the dehydration device to regulate the concentration of the sludge, so that the concentration of the sludge input into the dehydration device is stable, and the qualified rate of sludge caking is ensured.

The invention discloses a task unloading method and computer equipment, and is applied to an edge computing system, and the method comprises the steps: obtaining a directed acyclic graph task of each terminal equipment, and determining a current subtask based on the directed acyclic graph task; for the current sub-task of each terminal device, obtaining state information of the edge computing system at the current moment, inputting the state information at the current moment into the multi-target reinforcement learning model, generating a task unloading strategy corresponding to the current sub-task, and based on the task unloading rate in the task unloading strategy corresponding to the current sub-task of each terminal device, the terminal device and / or the server execute a corresponding task unloading operation on the current sub-task. According to the method, the task unloading strategy of the directed acyclic graph task of the terminal equipment can be provided, so that the optimal task unloading decision and the optimal computing resource allocation decision can be obtained.

The invention discloses a firmware upgrading method based on fragmentation transmission under a Zigbee network, which comprises the following steps: S1, firmware fragmentation and storage: firstly, a firmware file is segmented into a plurality of 32-byte fragments, and the fragments are stored in a storage space of an upgrading system; s2, an OTA upgrade starting command is sent; s3, fragmented data is transmitted in a mode of sending fragmented data one by one, and a system sends one fragmented data each time and waits for a confirmation signal of equipment; s4, recording a transmission state; s5, a retransmission mechanism; s6, verification and installation are carried out; s7, upgrading completion and state feedback; the problems that in the prior art, the firmware transmission failure rate is high, and upgrading failure is uncontrollable can be effectively solved. The transmission reliability in a low-bandwidth network environment is ensured by a fragmented transmission and automatic retransmission mechanism; due to the limitation of breakpoint resume and retransmission times, the overall upgrading efficiency is optimized, and excessive consumption of system resources is avoided; the data transmission security is high, the reliability of equipment upgrading is enhanced, and the method is easy to expand and implement and suitable for large-scale equipment upgrading.

The invention provides a distributed compiling method and device, electronic equipment and a storage medium, and belongs to the technical field of data processing.The method comprises the steps that a source code file is sent to a server side to be compiled and assembled, a compiling result returned by the server side is obtained, and the compiling result comprises information of a compiled target file; based on the compiling result, a corresponding pseudo file is created, and the pseudo file comprises a rebuilding method of the compiling result file; after pseudo files corresponding to all the compiling results are obtained, a link command is sent to a server side, and the link command indicates the server side to conduct file link operation on all the target files; and receiving the executable file returned by the server. According to the method and the device, the intermediate file is prevented from being copied for multiple times between the client and the server, so that the network load required by file transmission is reduced, and the distributed compiling efficiency is improved.

The invention discloses comprehensive rock drift rapid tunneling equipment and a using method thereof.According to the tunneling equipment, a drilling and anchoring integrated multifunctional drilling machine is arranged on one side of a cantilever type tunneling machine body, and a temporary supporting mechanism is arranged above an oscillation cutting part; a deep hole is formed in a to-be-crushed rock by utilizing the multifunctional drilling machine, the deep hole is further expanded and cracked by utilizing the pulsating fracturing system, the strength of a rock mass is weakened, then the rock mass is milled by adopting the oscillating cutting part, and finally, the rock mass is anchored and protected by utilizing the multifunctional drilling machine and the temporary supporting device, so that a guarantee is provided for an operation environment. According to the equipment and the technology, a traditional roadway tunneling procedure is simplified into a continuous procedure, the tunneling efficiency of roadway rock mass is greatly improved, and meanwhile the cost is saved.

The invention discloses a steel slag whole-process dry treatment process, and belongs to the technical field of steel slag treatment. Comprising the following steps: S1, a rolling procedure: carrying out rolling crushing on liquid steel slag, and in the process, cooling by adopting an air cooling mode to solidify the liquid steel slag; s2, a cooling procedure, wherein the steel slag obtained in the step S1 is cooled to 100 DEG C or below in a non-air-cooling mode; s3, a grinding procedure; s4, a sorting procedure; and S5, a waste heat recovery process, wherein heat released by the steel slag in the rolling process and the cooling process is recycled. The invention further discloses a steel slag whole-process dry processing system. Through reasonable design, gradient cooling is formed in the rolling procedure and the cooling procedure, meanwhile, heat released by steel slag in the two procedures is recycled, and the problem that the steel slag treatment waste heat recovery rate is low is solved.

The invention provides a large road network multi-vehicle path load balancing method based on a reinforcement learning graph neural network, and the method comprises the steps: obtaining road network data in a real scene, carrying out the modeling of a road network, and representing the modeling as a graph structure; splitting the graph structure into a plurality of sub-graph structures, wherein each sub-graph structure corresponds to a sub-road network; constructing and training a reinforcement learning adaptive graph neural network; for each sub-road network of the road network, calling the trained reinforcement learning adaptive graph neural network to generate a corresponding road selection probability in parallel, combining the generated road selection probabilities of the sub-road networks according to the topological structure of the original road network, and recovering the road selection probabilities of all the roads in the original road network into complete road selection probabilities in the original road network; and realizing road load balancing based on the selection probability of each road in the complete original road network. In a large-scale road network scene, efficient path re-planning is realized, the road network load is reduced in real time, the problem of road congestion is solved, and the traffic efficiency is improved.

The invention belongs to the field of computer aided design, and discloses a design method of a multistable metamaterial with an ideal energy absorption characteristic, which comprises the following steps of: firstly, carrying out theoretical analysis on a buckle to establish a mathematical model; then, according to the theoretical solution of the rigidity value of the buckle structure, reverse topological optimization design is carried out on the curved beam, so that a force displacement curve of the curved beam has negative rigidity and peak force corresponding to the buckle. The buckle structure and the optimized and customized curved beam are assembled through the functional part, and the multistable metamaterial unit cell with the ideal energy absorption characteristic can be obtained. And programming design is carried out on the unit cells, so that the required metamaterial can be constructed to meet the energy absorption requirement under the complex load. The technical scheme is widely applicable to the fields of aerospace, automobile industry, building protection and the like, and excessive rebound of impact energy is avoided while the impact resistance of equipment is improved.

The invention discloses an assembly type foundation pit support monitoring and early warning method and system for a soft soil area, and relates to the technical field of monitoring and early warning methods and systems.The assembly type foundation pit support monitoring and early warning system comprises an environment collection module, a stress collection module, a construction planning module, a dynamic monitoring module and a trend prediction module; by monitoring an environment influence value and a construction influence value established for the fabricated foundation pit support, drainage measures are added in a targeted manner in time to reduce the underground water level and strengthen waterproof measures around the foundation pit, meanwhile, the rainfall is closely concerned, people and equipment are evacuated in advance when the rainfall is continuously too large, and a construction plan is adjusted; on the basis of avoiding key operation, environment influence values and construction influence values in a high-temperature or high-humidity environment, a comprehensive influence value is established, the stability of the fabricated foundation pit support is dynamically monitored, a data table of the environment influence value m, the construction influence value n and the comprehensive influence value S is established according to a construction planning process, and prediction and early warning are performed on a support structure.

The invention discloses a large-scale data consistency method and device based on a multi-level tree structure cluster, and the method comprises the steps: constructing the multi-level tree structure cluster, distributing an i-level cluster for a follower in an i-1-level cluster as a corresponding subtree, and enabling a leader in the i-level cluster to be the follower in the i-1-level cluster; the i-level leader triggers own data collection according to the heartbeat detection message, and feeds back the collected data to the i-1-level leader; the (i-1)-level leader carries out consistency comparison on the collected data, if the collected data are not consistent, consistent data construction is carried out, a synchronization log of the constructed data is sent to the i-level leader, and the i-level leader carries out log synchronization after verification; and the i-level leader sends a log copy message to the i-level follower in the sub-tree where the i-level leader is located, and the i-level follower executes log synchronization after verification. The method has relatively low election performance loss, and realizes the capability of adapting to a large-scale distributed system.

The invention discloses an off-line and on-line combined unmanned aerial vehicle simulation flight path planning method, which belongs to the field of unmanned aerial vehicle flight path planning, and specifically comprises the following steps: obtaining a series of insertion waypoint longitudes and latitudes through a waypoint interpolation algorithm according to a selected route before a flight task is executed in an off-line mode; then altitude information stored in an elevation database is obtained in an elevation query mode, the target height of each waypoint of the unmanned aerial vehicle is calculated, and then route planning in the whole task process is completed; in the online mode, in the flight mission execution process, a real-time to-ground laser ranging system is adopted to obtain real-time to-ground height information of the unmanned aerial vehicle, after a measurement error is calibrated by combining flight attitude information of the unmanned aerial vehicle, the measurement error is compared with the actual flight height of the unmanned aerial vehicle, and the to-ground height of the unmanned aerial vehicle is calibrated on the basis of a pre-planned route; and the ground-imitating flight precision of the unmanned aerial vehicle is improved. According to the invention, high-precision ground-imitating equal-altitude flight route planning of the long-endurance unmanned aerial vehicle in a complex environment is realized.