406results about How to "Prevent crash" patented technology

The invention relates to a heat dissipation control method, device and equipment of a storage server and a storage medium, and aims to optimize the heat dissipation performance of the server by monitoring working characteristic parameters and power consumption data of a chip in real time. The method comprises the following steps: firstly, acquiring working load and power consumption information of each chip in a server, calculating temperature distribution of each chip, and generating an initial temperature data set; then, heat generation characteristic analysis is carried out on the set, and a heat generation model under the current load is obtained; then, a heat transfer path model is established based on the model and a server structure, and heat transfer among the chips is analyzed. And according to the heat transfer path, optimizing configuration parameters of an air cooling system and a liquid cooling system in the server, and generating optimized cooling parameter settings. And finally, the optimized parameters are applied to a heat dissipation control system of the server, dynamic adjustment is performed according to real-time load and temperature feedback, and a self-adaptive heat dissipation strategy is formed, so that the heat dissipation efficiency is improved, and stable operation of the server is ensured.

The invention belongs to the technical field of front-end development, and particularly relates to a React framework-based tree component optimization method fusing virtualization rendering and increment rendering. Comprising the steps of S1, data preprocessing; S2, dynamic virtualization rendering: dynamically calculating a node index range in a visible area according to a real-time scrolling position of a user viewport, only rendering nodes in the range, and realizing seamless lazy loading of data through scrolling event monitoring; s3, intelligent incremental updating: identifying changed nodes through a state change comparison algorithm, and executing local re-rendering only for the changed nodes based on a component life cycle control mechanism of a React framework; and S4, lazy loading cooperative control. The method aims at solving the problems in the aspects of performance, memory management, user experience and the like when a tree component in a React ecological system processes large-scale data, and is widely applied to various Web application program development scenes needing to display and operate a large-scale tree data structure.

A self-adaptive multi-sensor fusion method using radar, laser radar, IMU and GPS in a complex environment comprises the following steps: receiving radar point clouds, and preliminarily distinguishing dynamic point clouds and static point clouds in a single frame; the dynamic point cloud and the static point cloud are processed respectively, and the absolute speed of the robot is obtained; receiving point cloud data through the laser radar, and performing time synchronization and space calibration on each frame of data of the millimeter wave radar and the laser radar; dynamic points in each frame are removed in real time, and laser radar point cloud data only containing static points and static millimeter wave radar point cloud data are obtained; geometric feature extraction is carried out on the static laser radar point cloud data, and whether the robot enters a degradation area or not is judged; laser radar or millimeter-wave radar point cloud data are selected according to the number of feature points of the laser radar point cloud for matching of scanned sub-maps; the pose and the speed of the robot are obtained through a GPS, the reliability of GPS data is judged through the speed estimated by the millimeter wave radar and the pose obtained by the front-end odometer, the weight of the GPS data in rear-end optimization is determined by calculating the residual error of the speed estimated by the millimeter wave radar and the pose obtained by the front-end odometer, and the weight is added into a factor graph to be jointly optimized with the front-end odometer.

The invention relates to the technical field of synchronous positioning and map construction, and discloses a multi-sensor fusion SLAM method and system based on data quality comprehensive evaluation, and the method comprises the steps: carrying out the multi-dimensional quality evaluation of laser radar point cloud data and camera image data, and enabling the evaluation indexes to comprise the scene degradation degree, the view field integrity and the intensity information entropy of a point cloud, according to the point cloud data and the definition, self similarity and natural quality of the image, calculating the comprehensive weight of each index by adopting a subjective and objective weight fusion method, and dynamically selecting a laser radar pose, a visual sensor pose or an IMU integral pose increment as an initial value according to the comprehensive quality score of the point cloud data and the image data; and matching optimization of the point cloud and the map and global pose map optimization are carried out. According to the method, the sensor data quality is evaluated in real time, and the fusion strategy is dynamically adjusted, so that the positioning precision and robustness of the SLAM system in a complex environment are remarkably improved, and meanwhile, the calculation complexity is reduced.

The invention relates to the technical field of front-end development, in particular to an application fusion method based on a micro-front-end technology, which comprises the steps of sub-application registration, state management and synchronization, dynamic routing and navigation, cross-platform compatibility and adaptive design, resource optimization and loading strategy, performance monitoring, fault processing and the like. Registration and management of a plurality of sub-applications are realized through a uniform interface specification, a distributed state management mechanism is adopted to update and synchronize a global state, a dynamic routing system loads and renders the sub-applications as required according to user operation, and a cross-platform compatible design ensures consistent experience on different devices. According to the resource loading strategy, pre-loading and lazy loading are carried out by intelligently predicting user behaviors, unnecessary resource consumption is reduced, and the performance monitoring module monitors the running state of the system, automatically processes exceptions and provides a fault recovery mechanism. According to the method, the performance and the cross-platform adaptation capability of the micro-front-end application are effectively improved, and the method is suitable for development and deployment of complex enterprise-level applications.

The invention discloses an abnormal data prediction method and system based on a dynamic threshold value and pattern mining, and the method comprises the steps: carrying out the mining of an association rule and a sequence pattern of historical monitoring data, recognizing the association relationship among a plurality of monitoring indexes under different data collection sources, and extracting a frequently appearing sequence pattern; setting a dynamic threshold range based on the mean value and the standard deviation of the historical monitoring data; dynamically adjusting the threshold range according to the real-time operation state and the change trend of the historical monitoring data; and through matching the real-time data with the historical mode, predicting a potential anomaly, and giving out an early warning. According to the method and the system, through adaptive dynamic threshold and abnormal mode mining, intelligent prediction and early warning of anomalies in a data acquisition process are realized, and post-processing is converted into beforehand early warning; through real-time monitoring and model analysis, the system can detect potential anomalies in advance, optimize data quality, improve operation and maintenance efficiency and reduce manual intervention.

The invention relates to the technical field of WAPI communication management, in particular to a monitoring terminal wireless access communication management system based on WAPI, which comprises a WAPI route optimization module, a signal monitoring module, a bandwidth prediction module, a bandwidth resource management module, a flow regulation and control module and a data performance feedback module. According to the method, the data routing is dynamically adjusted by analyzing the network delay and the bandwidth utilization rate in real time, so that the delay and the packet loss rate in data transmission are remarkably reduced, the system can intelligently adjust according to the real-time change of the network condition, the overall operation efficiency of the network is improved, and the bandwidth utilization trend is analyzed, so that the bandwidth utilization rate is improved. According to the method and the system, future requirements are predicted, resource allocation is optimized according to the future requirements, the bandwidth resource overload condition is relieved, system collapse is prevented, the LSTM model predicts the peak value and the valley value of the network flow, the accuracy and the efficiency of channel allocation are improved, and a WAPI wireless communication main body is safer, more efficient and wider in channel.

The invention discloses a construction method and system for a membrane material database, and relates to the technical field of database construction.The construction method comprises the following steps that in the operation process of a database management system, multi-dimensional parameter information generated by the system is collected in real time, collected original data is cleaned and preprocessed, different types of data are normalized, and a database management result is obtained; and the consistency and the validity of the data are ensured. According to the method, the multi-dimensional parameters of the database management system are collected in real time, cleaning and anomaly analysis are carried out, the system intelligently evaluates the operation state, the operation anomaly coefficient is generated, and early warning and fault prediction are achieved. Based on the comparison between the abnormal coefficient and the multi-level threshold, the system divides the risk into low, middle and high levels, and takes corresponding measures. According to the refined management mechanism, the stability of the database is effectively improved, data loss, inconsistency and crash are prevented, and the accuracy and efficiency of fault processing are improved.

The invention belongs to the technical field of cloud storage, and particularly relates to an enterprise service management cloud storage system which comprises a system initialization module, a distributed data storage module, a data encryption module, an authority control module, a multi-level cache module, a data backup and recovery module, a log monitoring module and a task scheduling and dynamic extension module. The distributed data storage module is responsible for dividing data in enterprise service management into a plurality of data blocks; the data encryption module is used for encrypting the enterprise service data stored in the cloud; the authority control module is responsible for managing the access authority of the user to the data; the multi-level cache module accelerates data access by configuring a local cache and a global cache; the data backup and recovery module is responsible for backing up the stored data regularly; the log monitoring module records various operation logs of the system; and the task scheduling and dynamic extension module is used for dynamically distributing calculation and storage resources according to the priority of the task and the utilization rate of the system resources.

The invention discloses an optimized fault-tolerant control method suitable for a cascaded solid-state transformer. On the basis of the basic control link of the cascade converter, the bus voltage of each normally operating cascade module in the switching process and the bus voltage of the redundant module are detected, and according to the current modulation signal of each cascade module, the new modulation signal of each cascade module is dynamically calculated and obtained; the fluctuation of voltage and current in each stage of the switching process can be reduced. According to the invention, the problem that the current impact is too large when the whole system is switched due to the fault of one cascade module in the cascade converter is solved. According to the method, no additional circuit needs to be added, smooth switching of the cascade converter can be achieved when the fault occurs, the whole system can continue to work stably, and collapse of the whole system caused by over-current protection is prevented.

The invention relates to the technical field of electronic digital data processing, in particular to a memory bank initialization failure processing method which comprises the following steps: judging whether a memory bank fails to be read or not, if an error memory signal is detected, indicating that the memory bank fails to be read, and marking the memory bank as a memory bank to be detected; running state data, including memory bank performance data and aging condition data, of the to-be-tested memory bank is collected, and a memory bank performance evaluation index and a memory bank aging degree evaluation index are obtained through comprehensive analysis; and comprehensively analyzing to obtain a memory bank exception evaluation index, judging whether the memory bank has a fault according to the memory bank exception evaluation index, and processing the memory bank according to a judgment result. According to the method for processing the initialization failure of the memory bank, provided by the invention, data loss can be prevented, data security can be guaranteed, and system stability and performance optimization can be improved, so that dissatisfaction and troubles caused by system problems of users can be reduced, and the satisfaction degree of the users can be improved.

The invention discloses a knowledge distillation method driven by an interference generative adversarial network. The method comprises the following steps of: firstly, acquiring an image classification data set formed by three-channel RGB (Red, Green, Blue) format images; secondly, an interference generative adversarial network AD-GAN is constructed, the AD-GAN comprises a teacher model, a student model and an interference generation model, input of the three models is images in the image classification data set, output of the teacher model and the student model is confidence vectors of image category prediction, and output of the interference generation model is images with interference; finally, adversarial training is conducted on the three models, one training batch is divided into an interference generation model training stage and a student model distillation training stage, independent optimizers are used for training of the interference generation model training stage and the student model distillation training stage respectively, the interference generation model serves as a generator in adversarial training, and the teacher model and the student model serve as a discriminator together. According to the method, the generalization ability and the anti-noise performance of the student model are enhanced, and a practical and efficient solution is provided for a resource-limited scene.

The invention relates to the technical field of digital video devices, in particular to a digital video device control method and device. The method comprises the following steps: acquiring digital monitoring data, performing real-time scene acquisition and dynamic region optimization according to the data, and generating optimized dynamic region data; video frames are read based on the dynamic region optimization data, and abnormal behavior analysis and behavior intention evaluation are carried out; calculating the complexity of monitoring behaviors by combining video frame data and behavior intention data, and evaluating resource consumption increase; the processing bottleneck is evaluated according to the resource consumption growth data, and the processing capability attenuation analysis is carried out, so that the monitoring device is adjusted, and the system performance is optimized; according to the method, the resource allocation and processing capability of the video device is dynamically adjusted through real-time analysis and processing of monitoring data. According to the invention, the digital video device is adjusted, so that the prediction identification of the digital video device is more accurate and efficient.

The invention discloses a tensile testing machine for artificial leather processing and a detection process thereof, and belongs to the technical field of artificial leather processing.The tensile testing machine comprises a machine base placed above a workbench, a guide base is fixedly installed at the upper end of the machine base, a sliding way is formed in the guide base, and a motor is fixedly installed on the inner side of the machine base; a threaded rod is fixedly mounted at the output end of the motor; the sliding seat is arranged on the inner side of the sliding way in a sliding mode, a monitor is fixedly installed on the outer side of the sliding seat, and a first clamping assembly is fixedly installed at the detection end of the monitor; the second clamping assembly is fixedly mounted on the upper surface of the machine base; and the two winding pieces are elastically and rotationally mounted on the first clamping assembly and the second clamping assembly correspondingly. According to the tensile testing machine for artificial leather processing and the detection process thereof, the end part of artificial leather can be stably clamped, the detection stroke can be shortened in the detection process, meanwhile, an operator can be prevented from being hurt after the artificial leather is broken, and the use safety is high.

The utility model relates to the technical field of tractor equipment, and discloses a width-adjustable amplitude-variable crawler-type tractor which comprises a box body, an upper crawler belt structure and a lower crawler belt structure, an operation panel is arranged on the front face of the box body, a rectangular plate is fixedly installed on the front face of the box body, an adjusting mechanism is arranged in the box body, and the upper crawler belt structure and the lower crawler belt structure are arranged in the box body. A limiting mechanism is arranged in the rectangular plate, the distance between the upper crawler belt structure and the lower crawler belt structure can be adjusted, traction and transportation of to-be-dragged objects of various thicknesses are facilitated, and when the upper crawler belt structure and the lower crawler belt structure are abraded for a long time and clamping force is insufficient, the clamping force is not enough. The upper crawler belt structure and the lower crawler belt structure can still keep stable clamping force under the action of the rolling wheels, slipping is avoided, stability is kept, the limiting column A and the limiting column B can be adjusted according to adjustment of the upper crawler belt structure, a traction object is limited up and down, the distance between the two limiting columns C is adjustable, and the space between the two limiting columns C is adjustable. Limiting can be achieved by adjusting according to the width of an object to be dragged.

The invention relates to the field of intelligent traffic management, and discloses an efficient road obstacle clearance rescue worker automatic scheduling method comprising the following steps: (a) deploying at least one message queue to cache rescue related data; (b) storing and querying rescue tasks and resource state data through a distributed database system; (c) collecting data from the rescue vehicle and the accident site in real time, and performing preprocessing; (d) asynchronously processing the collected data through a message queue according to the priority and the task type; (e) dynamically scheduling rescue resources by using a multi-factor decision algorithm; the message queue adopts a Kafka cluster and is configured with at least three partitions and at least two copies so as to ensure that a single server or partition fails. Through combination of a multi-factor decision scheduling algorithm and real-time traffic flow prediction, the system can dynamically adjust the scheduling route of the rescue vehicle, and the rescue vehicle is prevented from entering a congested road section, so that the time for arriving at an accident scene is remarkably shortened, and the overall rescue efficiency is improved.

The invention discloses a transaction consistency verification method and device of a distributed system, electronic equipment and a storage medium, and relates to the technical field of data management, and the disclosed transaction consistency verification method of the distributed system comprises the steps that when an execution request of a target transaction is received, a state flag of the target transaction is updated in a preset transaction coordination table; sending transaction execution data to a target server corresponding to the target transaction according to the execution request, and monitoring whether response data returned by the target server is received within a preset time; when the response data is not received, sending inquiry information for the target transaction to a transaction checking interface of the target server, and receiving a transaction landing state returned by the target server; and updating a state flag of the target transaction in the transaction coordination table according to the transaction landing state. The stability and reliability of the distributed system can be improved.

The invention relates to a frequency converter hot redundancy control method and system, computer equipment and a storage medium, and the method comprises the steps: monitoring the real-time operation states of all frequency converters in a frequency converter system in real time, and carrying out the fault prediction according to an artificial intelligence algorithm and the real-time operation states; dynamically adjusting the load conditions of all the frequency converters according to the corresponding fault prediction results; under the condition that any frequency converter breaks down, the fault frequency converter is automatically isolated, and load redistribution is carried out on the frequency converter which does not break down through a load balancing algorithm; obtaining the fault type of the fault frequency converter, and executing a local repair mechanism to recover the function of the fault frequency converter when the fault type is self-repairable; and after the fault frequency converter is successfully repaired, executing a self-adaptive stable switching-in algorithm, and gradually switching the repaired frequency converter into the system again. The method has the effect of improving the recovery efficiency of the frequency converter system after the fault occurs.

The invention discloses a system and a method for resisting a pseudo link layer protocol attack in an electric power communication network, and relates to the technical field of communication. The system comprises: a switching unit, which is used for receiving all data frames transmitted from an Ethernet port; the data identification module analyzes the protocol type and the destination address of the data frame, and forwards the data frame to the service processing unit or directly discards the data frame; the buffer area module sets an independent buffer area for each link layer protocol, and dynamically adjusts the size of the buffer area based on the protocol characteristic weight and the equipment memory resource through the configuration unit; the buffer area management module monitors the state of a buffer area in real time and triggers data discarding operation when the buffer area is fully loaded; and the data extraction module extracts the data frames from the buffer area according to a set time interval and analyzes and forwards the data frames in combination with a priority rule. According to the method, the size and the time interval of the buffer area can be dynamically adjusted, the resource utilization efficiency is improved, the pseudo link layer protocol attack is effectively resisted, and the security and the real-time performance of an electric power communication network are guaranteed.

The invention relates to the technical field of valves, in particular to a combined high-temperature and high-pressure valve which comprises a valve body, a valve seat and a valve element. The flow slowing mechanism is used for slowing down the flow speed of fluid, and the outer wall of the flow slowing mechanism is fixedly connected with the inner wall of the valve body; the check mechanism is used for preventing fluid from flowing back, and the outer wall of the check mechanism is fixedly connected with the inner wall of the side, away from the flow slowing mechanism, of the valve body. By arranging the flow slowing mechanism, in the flowing process of the fluid, the fluid impacts the flow baffle and flows through a gap between the flow baffle and the flow baffle ring, so that the flow direction of the fluid is disturbed, and therefore the flow direction of the fluid is disturbed; by arranging the flow disturbing assembly, the flow velocity of the fluid can be further reduced, impurities doped in the fluid can be filtered out, the flow velocity of the fluid can be further reduced by arranging the flow disturbing assembly, the valve element is protected, and the valve element is prevented from being damaged due to the water hammer effect at the moment when the valve is opened.

The invention relates to the field of big data super-concurrent processing, in particular to an education big data super-concurrent processing system and method. The method comprises the following steps: collecting and preprocessing original request data to obtain actual request traffic; using historical data in actual request traffic to train a weighted autoregression model, and predicting the traffic; dynamically adjusting the concurrency based on the obtained flow prediction value, calculating the scheduling priority of the data packets, and sorting and distributing the data packets; a dynamic back pressure control mechanism based on flow prediction is introduced, flow input is dynamically adjusted, and overload is prevented. The problems that a traditional scheduling algorithm and a traditional load control strategy lack enough accurate flow prediction, concurrency cannot be adjusted in time, and system resources are excessively distributed or insufficient are solved; the priority processing of the key task cannot be ensured because the flow fluctuation and the scheduling priority are not fully considered; the problems that flexibility and self-adaptive capacity are lacked, the flow cannot be effectively limited when the load is too high, and the overload risk of the system is increased are solved.

The invention relates to the technical field of servers, in particular to a server hardware state monitoring and alarming device which comprises a shell, a controller and an alarming module, sliding grooves are formed in the two sides of the shell, and a first monitoring module and a second monitoring module are arranged in the sliding grooves; the first monitoring module comprises a first monitoring plate, the first monitoring plate is provided with a mounting port and a mounting chamber, the bottom wall of the mounting chamber is provided with a vertical rod, the vertical rod is provided with a first spring, the first spring is connected with a mounting plate, the mounting plate is fixedly connected with a limiting ball, a bimetallic strip is arranged in the mounting chamber, and the bimetallic strip is in contact with the mounting plate to form a series circuit; when the transmission line at the transmission port is loosened, the mounting plate is in contact with the bimetallic strip, the series circuit is connected, the controller receives a circuit signal, and the alarm module is started; when the operation temperature is too high, the controller receives abnormal monitoring data of the second monitoring module, and the alarm module is started. The invention aims to improve the monitoring level of the hardware state of the server and guarantee the stable operation of the server through a real-time monitoring and automatic alarm mechanism.

The invention discloses a secure startup method and system of a trusted controller, and belongs to the technical field of industrial control system security, and the method comprises the steps: configuring a secure startup strategy in U-Boot, and executing the secure startup strategy in the startup process of the trusted controller through a trusted controller drive; when the trusted controller is started, the security starting strategy is verified by adopting the first-level security strategy, and corresponding security check is executed according to the security starting strategy after verification is passed; after the trusted controller is started, the security starting strategy establishes a trusted chain according to the trusted files, measurement verification is carried out on all the trusted files of the trusted chain, and when all the trusted files pass verification, the trusted controller passes trusted verification; according to the secure starting method of the trusted controller, the reliability of the system is improved through establishment and verification of the trusted chain, a flexible protected area and comprehensive trusted file verification, and comprehensive security guarantee is provided for the system.

The invention discloses a crane collision early warning method and system based on Beidou positioning, and the method comprises the steps: S1, employing the Beidou positioning technology, and obtaining the real-time position information of a crane and obstacles in the surrounding environment; s2, constructing a three-dimensional motion model of the crane and the obstacles according to the real-time position information of the crane and the obstacles in the surrounding environment; s3, according to historical coordinate position information of the crane and obstacles in the surrounding environment in the three-dimensional motion model, a pre-judgment distance value between the crane and the obstacles is determined; and S4, when the pre-judged distance value between the crane and the obstacle is smaller than the pre-warning distance value, corresponding pre-warning prompt is carried out. The position information of the crane and the obstacle is acquired in real time through Beidou positioning, and the position of the target object is predicted in combination with the historical position information, so that the collision accident of the crane can be effectively avoided, the anti-collision safety of the crane is improved, and the method is suitable for further popularization and application.

The invention discloses a cross-platform operating system upgrade patch automatic deployment method and system, and relates to the technical field of operating system patch management, and the method comprises the following steps: analyzing a patch dependency relationship, and dynamically adjusting a deployment sequence; performing isolation deployment based on a containerization technology; and monitoring the state of each container in real time, and performing real-time monitoring and feedback optimization on a deployment result. By means of the method, accurate control over patch deployment in a complex heterogeneous environment is achieved, the failure rate caused by dependency conflicts is reduced, meanwhile, deployment time is shortened, stability and reliability of system operation are improved, independence between patches is ensured, and the service life of the system is prolonged. According to the method and the system, system crash caused by patch incompatibility or operation failure is avoided, the deployment efficiency is improved, the efficient container isolation and highly compatible patch deployment process is realized, the self-adaptability and long-term stability of the system are improved, and powerful technical support is provided for complex and changeable patch deployment scenes.

The invention belongs to the field of industrial control and computer data security, and particularly relates to a millisecond-level power failure data protection system for an industrial control panel. The invention discloses a millisecond power failure data protection system for an industrial control panel. The millisecond power failure data protection system comprises a core processing component, a real-time synchronous shadow memory component, a bus voltage monitoring component, a pre-entropy reduction logic control component, a nonvolatile storage component and a flight control bus arbitration component. The bus voltage monitoring assembly monitors a voltage drop trend and performs early warning, the pre-entropy reduction logic control assembly calculates a minimum data survival set according to energy entropy, the real-time synchronous shadow memory assembly constructs a synchronous shadow control domain and atomizes data, and the flight control bus arbitration assembly compulsively takes over a bus and freezes processor access at the moment of power failure. Atomized writing of data into the nonvolatile storage component is guaranteed. According to the invention, zero-delay data protection and millisecond-level hot start recovery at the moment of power failure are realized, and the data security and reliability of the industrial control equipment in a severe environment are enhanced.

The invention discloses an intelligent rescue method for lost old people based on a PTS algorithm and an RF algorithm. The method comprises the steps that S1, family members of the lost old people rapidly record cases; s2, the command platform carries out task scheduling, carries out priority calculation on missing information of the old people according to a PTS algorithm, and sends rescue tasks to volunteers according to priorities; s3, the volunteer checks the current location, the position information of other volunteers and the thermodynamic diagram of people searching on the map according to the rescue system, and plans a people searching route, and S4, if a suspected lost person is found, the suspected lost person is photographed and uploaded, the suspected lost person is automatically compared with the lost person in the photo library, the information of the elder with the matching degree higher than 80% is synchronized to the family member end and the volunteer end, and the elder can search for the volunteer. After confirmation, the search and rescue task can be judged to be completed; s5, if abnormity occurs during search and rescue, the background can check task positioning and rescue details at any time, and rescue resources are manually adjusted and allocated; and S6, after the rescue task is finished, the system integrates, counts and stores related information, and subsequently assists prediction of the next search and rescue task through an RF machine learning algorithm.

The utility model discloses a novel unmanned aerial vehicle carrying platform, which belongs to the technical field of unmanned aerial vehicles and comprises an unmanned aerial vehicle main body, a connecting frame is fixedly connected to the bottom of the unmanned aerial vehicle main body, a connecting block is fixedly connected to the bottom of the connecting frame, and a carrying platform main body is rotatably connected to the outer side wall of the connecting block. The outer side wall of the carrying platform body is fixedly connected with a fixing column, the inner top of the fixing column is rotationally connected with a rotating column, the outer side wall of the rotating column is fixedly connected with an adjusting plate, and a sliding groove is formed in the outer side wall of the adjusting plate in a penetrating mode. According to the novel unmanned aerial vehicle carrying platform, through cooperative use of the connecting blocks, the carrying platform body, the fixing columns, the rotating columns, the adjusting plates, sliding grooves, sliding columns, plug pins, racks and gears, the carrying platform can be released emergently when an emergency release device fails, and the situation that after the gravity center of a carried object shifts in the transportation process, the carrying platform is damaged is avoided. And the flight attitude of the unmanned aerial vehicle is changed, so that the unmanned aerial vehicle is prevented from falling in the transportation process.

The invention relates to the field of industrial control, and discloses a control authority distribution system which comprises an authority request module, an authority distribution module, an authority release module and a safety fault-tolerant module. The permission request module is used for collecting control permission requests of the operation terminals; the authority distribution module dynamically processes the requests according to an M / M / 1 queuing model, a game theory model and a Markov decision process, determines the priorities of the operation terminals, and adopts the game theory model to solve conflicts if a plurality of operation terminals request simultaneously; the permission release module automatically releases the control permission under the condition that the operation is completed or overtime; and the security fault-tolerant module verifies the consistency and security in the permission allocation process through a Byzantine fault-tolerant algorithm. According to the invention, the response speed of the system can be improved, the security of multi-terminal operation and the resource utilization efficiency are ensured, and strong fault-tolerant capability and stability are provided.

The invention belongs to the technical field of cutting machining, and discloses a cutting tool which comprises a main body part and a cutting part, the axis direction of the cutting part is the same as that of the main body part, and the outer surface of the cutting part comprises an auxiliary rear tool face and an outer side tool face which are oppositely arranged in the thickness direction of the cutting part; a front tool face and a main rear tool face which are arranged in an included angle mode are arranged between the auxiliary rear tool face and the outer side tool face, the main rear tool face and the front tool face are connected to form a main cutting edge, a first chamfering face is arranged between the auxiliary rear tool face and the main rear tool face, and the first chamfering face extends towards the direction of the front tool face and is connected with the front tool face to form a first chamfering edge. A second chamfering face is arranged between the outer side tool face and the main rear tool face, the second chamfering face extends towards the front tool face and is connected with the front tool face to form a second chamfering edge, and the first chamfering edge and the second chamfering edge are connected with the main cutting edge. According to the cutting tool provided by the invention, the risks of cutting edge breakage and tool breakage can be reduced, and the service life can be longer.