88results about How to "Guaranteed smooth execution" patented technology

The invention relates to the technical field of production scheduling of manufacturing workshops, in particular to a distributed intelligent production scheduling decision-making system based on cloud computing. The system is composed of a cloud computing platform, a data acquisition module, a data processing module, an intelligent production scheduling engine and a distributed execution control module. The problems of performance bottleneck, data acquisition limitation, lack of flexibility and adaptability of a production scheduling scheme and the like in a traditional production scheduling system are solved, intelligent distribution and scheduling of production tasks can be realized through fusion application of advanced technologies such as cloud computing, big data and artificial intelligence, the production efficiency and the product quality are improved, and the production cost is reduced. And greater economic benefits and social benefits are created for enterprises.

The invention relates to the technical field of sickbed control, in particular to a control system of an intelligent bed and a control method thereof. The method comprises the following steps: acquiring structural data of the intelligent bed; carrying out human body fitting area gravity sensor deployment on the intelligent bed structure data to obtain sickbed sensor deployment data; performing gravity sensor data acquisition on the sickbed sensor deployment data to obtain an initial gravity sensor data set; carrying out data matrix processing on the gravity sensor data set to generate a multi-dimensional pressure sensing matrix; acquiring user pain part data and bed board motor initial position data; and performing pressure distribution mode recognition on the multi-dimensional pressure sensing matrix to obtain a uniform distribution mode and a concentrated distribution mode. According to the invention, through the personalized support regulation, global attitude optimization and real-time feedback mechanism of the intelligent bed, the control accuracy and intelligence of the intelligent bed are improved.

The invention discloses a power distribution room remote monitoring and fire-fighting inspection system based on a cloud platform, and relates to the technical field of fire-fighting safety monitoring. The system comprises a remote monitoring module, a fire safety monitoring module and an inspection task scheduling module. And the remote monitoring module acquires and stores the running state data of the power distribution equipment in real time to realize continuous monitoring. The fire safety monitoring module obtains environment data of a power distribution room through an environment sensing unit, establishes a fire prediction model through a random forest algorithm in combination with an equipment operation state, and generates a fire prediction index. And the early warning unit simulates a fire spreading process based on the fire prediction index and predicts a fire spreading direction and an influence area. And the inspection task scheduling module intelligently distributes inspection tasks and adjusts task execution strategies in real time according to the fire risk assessment result in combination with the geographic position and the working load of the inspection personnel. The fire risk is accurately predicted and the inspection task is dynamically scheduled, so that the fire-fighting potential safety hazard of the power distribution room can be timely found and eliminated.

The invention discloses an underwater robot intelligent control method and system based on deep learning, and relates to the technical field of underwater obstacle avoidance of underwater robotics.The method comprises the steps that a deep learning calibration model is established through a deep learning algorithm, and the avoidance rate index BrsL in the underwater robot avoidance process is constructed; the ocean current speed and direction of the area where the underwater robot is located and the real-time vertical descending depth, the underwater temperature value and the submerging seawater pressure value of the propeller in the obstacle avoiding process are monitored and monitored, an ocean current influence index YL and a relative strength index Xd are calculated and evaluated, and the ocean current influence index YL and the relative strength index Xd are evaluated; if a multi-stage calibration control strategy of the first calibration instruction and the second calibration instruction is triggered, the power of the propeller and the posture of the underwater robot are adjusted, and timely adjustment is carried out according to the change of the vertical descending depth so as to adapt to the ocean current environment, and it is guaranteed that the underwater robot stably moves in the obstacle avoidance process.

The invention discloses an unmanned aerial vehicle flight path planning method based on an improved Harris eagle optimization algorithm, and the method comprises the steps: setting peak parameter information, constructing a threat equivalent terrain simulation map through a peak function, and carrying out the modeling of a flight environment; establishing a corresponding cost function according to the length cost, the threat cost and the smoothness cost of the flight path, and converting a flight path planning problem into an optimization problem of minimizing the cost function; and solving the optimization problem of the minimum cost function by using an improved Harris eagle optimization algorithm fusing a labor division mechanism and an elimination selection strategy, and carrying out iterative optimization to obtain the optimal flight path of the unmanned aerial vehicle. According to the invention, the feasible track can be explored and developed as much as possible in the flight space, collision and track jitter can be avoided, and smooth execution of the flight task of the unmanned aerial vehicle is facilitated.

The embodiment of the invention discloses a near field communication control method, a near field communication control device and near field communication equipment. The success rate and the efficiency of near field communication between the near field communication equipment of a merchant and a mobile phone of a user can be improved. According to the scheme, the method comprises the following steps: acquiring a near field communication signal of a currently approaching induction object through one or more near field communication antennas deployed on near field communication equipment; according to the near field communication signal, performing working mode judgment on the sensing object; if it is judged that the induction object is in the unfriendly working mode, an excitation signal is sent to the induction object through at least one near field communication antenna, so that the induction object quits the unfriendly working mode in response to the excitation signal; and establishing a communication connection with the sensing object through at least one near field communication antenna, and executing a target service through the communication connection.

The invention relates to the technical field of automatic control systems, in particular to an intelligent substation sequence control method and system, and the method comprises the following steps: based on an equipment operation instruction of an intelligent substation, analyzing the logic sequence of equipment operation, extracting the state change information of equipment, and carrying out the operation analysis of equipment state and time correlation; and judging the dependency relationship through the time difference of the equipment state, and generating an equipment operation dependency model. According to the method, the resource occupation condition of the equipment is monitored through a data stream compression algorithm, load balancing is carried out, the load level of the equipment is evaluated in real time, dynamic distribution and adjustment of loads are achieved, the pressure of high-load equipment is effectively relieved, potential conflicts of the equipment during parallel execution are recognized and solved in real time by introducing an operation conflict judgment mechanism, and the safety of the equipment is improved. Smooth execution of parallel tasks is guaranteed, delay and conflict possibly occurring in the equipment execution process are effectively reduced, and continuity and reliability of a power system are guaranteed.

The invention discloses an intelligent warehousing operation auxiliary system and method based on mixed reality, and relates to the technical field of warehousing management, and the system comprises a storage stack point pre-screening module, an intelligent task planning module, a task execution monitoring module, an abnormal task execution adjustment module, and an optimal carrying equipment screening module. According to the method, the optimal storage stack point can be screened, the utilization rate of the storage space is improved, cargo extrusion or space waste caused by space mismatching is avoided, the transportation efficiency is improved, the energy consumption is reduced, abnormal conditions can be found in time, and the reliability of task execution is guaranteed. When abnormity occurs, early warning can be triggered quickly, the replacement mode of the carrying equipment can be judged reasonably, continuity and high efficiency of warehousing operation are ensured, and the overall operation efficiency of the intelligent warehousing system, the goods storage quality and the scientificity of management decision are improved.

The invention discloses a reinforcement engineering whole-process management system and method based on an intelligent contract, and belongs to the technical field of engineering management. In order to solve the problems of low management efficiency, inconsistent data and difficult tracing, through a contract deployment execution module, an intelligent contract can be automatically executed based on a block chain technology, the construction process of the reinforcement engineering is managed according to preset rules and conditions, a construction plan management module can set a construction plan and resource management logic in the intelligent contract, and the management efficiency is improved. The purchase order traceability module realizes automation of purchase order generation, auditing, execution and settlement processes through an intelligent contract, the management efficiency is improved, the traceability information of the reinforcing steel bar material is recorded by using the Internet of Things technology, the traceability information is associated with the purchase order, and the management efficiency is improved. The retrospective management of the source of the reinforcing steel bar material is realized, the quality of the reinforcing steel bar is ensured, the responsible party can be quickly positioned when a problem occurs, and the risk is reduced.

The invention relates to the technical field of large model application, in particular to an automatic mobile phone operation method, device and equipment based on a multi-modal agent and a computer storage medium. According to the automatic operation method of the mobile phone, the task disassembly and execution process is optimized by introducing the planning agent, the memory unit and the reflection agent, and the multi-agent cooperation architecture is beneficial to improving the task execution efficiency and reducing the processing time; a clarification agent is introduced, unnecessary interaction is greatly reduced through a probability prediction mode, a user can insert a decision-making process of an agent framework as little as possible, meanwhile, the agent can timely inquire the user when encountering problems which cannot be solved, and it is ensured that tasks can be smoothly executed; according to the invention, the user interaction performance of mobile phone operation is greatly improved.

The invention provides a workpiece table assembly and semiconductor production equipment and method. The workpiece table assembly comprises a workpiece table body and an edge pressing mechanism. The workpiece table body comprises a suction cup base and a suction cup, and the suction cup is arranged on the suction cup base. The multiple edge pressing mechanisms are arranged on the periphery of the suction cup in a surrounding mode. The edge pressing mechanism comprises a horizontal driving piece, a vertical driving piece and a pressing plate part, the horizontal driving piece is connected with the suction cup base, the vertical driving piece is connected with the horizontal driving piece, and the pressing plate part is connected with the vertical driving piece; when the horizontal driving piece and the vertical driving piece are kept in the state, the pressing plate part and the suction cup are relatively static. The workpiece table assembly is used for the semiconductor production equipment. When the semiconductor production equipment works, the following steps are executed: sucking a substrate by a sucking disc; and detecting whether the state of the substrate meets a preset application condition or not, if so, executing a preset operation, and if not, carrying out online blank pressing by utilizing a blank pressing mechanism, and then executing the preset operation to ensure that the preset operation is smoothly carried out.

The invention discloses a train direction changing control method, device and equipment, and relates to the technical field of rail transit. The method comprises the steps that whether a direction changing instruction is received or not is detected from a signal receiver of a current section, wherein the direction changing instruction is used for changing the running direction of a train; when the direction changing instruction is detected, the state of the current section is determined based on the operation state of the parallel track relays; if it is determined that the state of the current section is the occupied state, a first control instruction is generated and sent to a signal receiver of a target section, so that the running state of the track relay is shielded, and it is prompted that the current section is in the non-occupied state; wherein the target section is the next section of the current section in the advancing direction of the train after the direction is changed. The method and device are used for achieving the train direction changing control function.

The invention discloses an embedded system multi-task scheduling method based on timer clock control. According to the functions realized by embedded software, the whole program is divided into a plurality of task function modules with a single specific function, a delay clock and a minimum base time of the delay clock are set, a clock sequence corresponding to each task mark is marked in an enumeration type in a delay clock list, the task marks are sequentially encapsulated in the clock list according to the execution order of the tasks, and a predetermined delay time corresponding to the task execution is defined. Two pointers are defined in a timer interrupt service subroutine, the first pointer points to an array storing whether the delay clock mark of each task is enabled, and the second pointer points to an array storing the predetermined delay time; according to the clock sequence and the predetermined delay time corresponding to each task, each task is polled and executed in turn, so that when a task blocks or occupies the CPU, it will not cause resource waste and time waste.

The invention relates to a resource allocation method and device, computer equipment, a computer readable storage medium and a computer program product. The method comprises the steps that in response to an arrangement operation for an assembly line, an assembly line task is constructed and obtained, and the assembly line task comprises at least one execution step, target assembly line components associated with all the execution steps and target machine architectures corresponding to all the target assembly line components; obtaining a resource group corresponding to each execution step in the pipeline task, wherein the resource group comprises at least one building machine; target building machines corresponding to the assembly line tasks are determined from all the resource groups, corresponding task instructions are issued to all the target building machines based on the execution steps corresponding to all the resource groups, service software corresponding to the target assembly line assemblies is deployed in the target building machines, and the service software corresponds to a target machine architecture. By adopting the method, the resource utilization rate and the assembly line task execution efficiency can be improved.

The invention discloses a relay tracking application method and system for large and medium-sized ships in open seas, and the method comprises the following steps: S1, obtaining the current position information of a target ship, and delimiting a circular region of interest based on the current position information; s2, performing overhead satellite calculation within half an hour based on the region of interest; the current position of the target ship is determined for uploading tasks to satellites passing through the top attention area in a short time; after receiving the AIS signal of the target ship, the micro-nano satellite transmits the AIS signal to the ground; and S3, selecting to enter a regular imaging tracking mode under the condition of stable AIS signal receiving or a search imaging tracking mode under the condition of short-time AIS signal loss according to the AIS signal receiving condition, and carrying out relay tracking on the target ship. The method has the advantages that the remote sensing image data transmission quantity for carrying out the tasks and the time consumed for completing the tasks can be greatly compressed, and the requirements of high-timeliness tasks such as high-sea far-field ship escorting and marine ship searching and rescuing are met.

The invention provides a production management system based on a low-code platform, and relates to the technical field of data processing, and the system comprises a data collection module which is used for collecting production resource state data, order task data and process parameter data; the task decomposition module is used for decomposing the production task to generate task unit data; the configuration generation module is used for generating initial task configuration data according to the task unit data; the task scheduling module is used for receiving the initial task configuration data and generating a task scheduling scheme; the execution control module is used for distributing a production instruction to production equipment according to the task scheduling scheme and controlling the execution process of the production task; the dynamic updating module is used for dynamically adjusting task configuration and feeding back to the task scheduling module when a production task adjusting request is received in the production task execution process; the resource allocation scheme of the production management system can be automatically updated based on the data feedback of the production resources.

The invention relates to an enterprise project informatization management method, device and system and a storage medium. The method comprises the steps of obtaining enterprise project internal data, enterprise project external data, initial fuzzy reasoning parameters and project execution historical data corresponding to a target enterprise; performing dynamic fuzzy reasoning on the enterprise project internal data and the enterprise project external data according to the initial fuzzy reasoning parameters to obtain dynamic fuzzy reasoning data; according to the dynamic fuzzy reasoning data and project execution historical data, identifying a relationship between each execution object and each task detail in the target enterprise to obtain project behavior analysis data; performing structured fusion on the dynamic fuzzy reasoning data and the project behavior analysis data to obtain enterprise project fusion data; and scheduling fixed resources and human resources of the target enterprise according to the enterprise project fusion data to obtain enterprise project management information. By adopting the method, the resource scheduling efficiency of the enterprise management project can be improved.

The invention discloses a multi-underwater robot cooperative path planning method and system and a storage medium, and relates to the technical field of underwater robos.The method comprises the steps that S1, an underwater distribution electronic graph is obtained in advance, a plurality of sets of underwater charging station areas are locked, and meanwhile serial number marking is conducted on the charging station areas and the robots; accurate positioning of the robots and the charging stations in the path planning process is further ensured, the initial precision of path planning is improved through the process, and a reliable data basis is provided for subsequent steps. In the steps S2 and S3, electric energy state data information of a plurality of groups of robots is monitored in real time, an electric energy set is generated, a to-be-charged robot is determined, a task state set is constructed according to related task processing data information, and a relative task urgency coefficient Rhxs is generated, so that the electric energy state and the task urgency degree of the robots are comprehensively considered; and the reasonable arrangement of the charging demand in the path planning process is further ensured.

The invention provides a mining equipment power intelligent control method and system, and relates to the technical field of mining equipment. The method comprises the following steps: acquiring power and multiple current data of mining equipment and environment data of a mining area; determining an overload score; determining a safety score; obtaining a mining quantity and a residual target mining quantity; determining a completion score; determining whether the power of the mining equipment in the next control period needs to be adjusted according to the overload score, the safety score and the completion score; if the power of the mining equipment in the next control period needs to be adjusted, the adjusted power of the mining equipment is determined according to the power of the mining equipment in the current control period, the current data, the environment data, the mining quantity and the remaining target mining quantity; and setting the power of the mining equipment as the adjusted power of the mining equipment at the starting moment of the next control period. According to the invention, the power of the mining equipment can be adjusted, and the efficiency of the mining equipment is improved.

The invention relates to the technical field of unmanned ship autonomous control, in particular to an unmanned ship obstacle clearance task allocation method based on an improved genetic algorithm. According to the invention, through comprehensive consideration of factors such as obstacle target position distribution, the navigation speed of each boat, the number of carried blasting objects and the like, a task target is reasonably determined, task constraints are accurately analyzed, a multi-boat cooperative task allocation mathematical model fitting an actual use scene is constructed, an obstacle removal target sequence is reasonably allocated for each unmanned boat, and the unmanned boat cooperative task allocation efficiency is improved. And smooth execution of the obstacle clearing task is ensured. According to the invention, the improved genetic algorithm is adopted to solve the multi-boat collaborative obstacle clearance task allocation problem, and the comprehensiveness of individual information is ensured by adding a breeding selection strategy; through local mutation operation, the local search capability of the algorithm is enhanced; and the task execution time of each boat is balanced while the shortest obstacle clearance total route of the unmanned boat is ensured, collaborative allocation of targets of each boat is realized, and the overall task execution efficiency is greatly improved.

The application discloses an AI identification and driving control system and method of a mobile inspection device, and relates to the technical field of driving control.The system comprises an image acquisition module, a biological identification and orientation analysis module, a same-direction pursuit judgment module, a driving direction execution module, and a continuous tracking and speed adjustment module;inspection images are acquired, target organisms are identified, and escape directions are predicted according to orientation information;whether a same-direction pursuit state is formed is determined by combining the moving direction of the device and the path area position;the driving direction is adjusted so that the included angle meets the threshold requirement and driving is performed;meanwhile, the position of the organism is continuously tracked;and collaborative control is realized by adjusting the speed and dynamically updating the driving direction.The application can effectively break the same-direction pursuit phenomenon, quickly drive the organism away from the inspection path, avoid the obstruction of the inspection process, and improve the continuous inspection operation efficiency and operation stability.

The present application discloses a control method and system for wireless network equipment, which relates to the field of communication technology, including: collecting user data from different areas in the network; obtaining the coordinate position and transmission power parameters of the network equipment, and calculating the wireless coverage area according to the wireless signal propagation model, which includes the SCHEMA model, the Okumura model and the Hata model; determining the target area by generating a heat map according to the collected user data and the wireless coverage area; calculating the minimum transmission power value that satisfies the wireless coverage and throughput of users in the target area according to the heat map, the wireless coverage area and the user data, and the transmission power parameters; generating a control instruction to adjust the transmission power of the network equipment according to the calculated minimum transmission power value; and adjusting the transmission power of the network equipment according to the generated control instruction. In view of the problem of high energy consumption of network equipment in the prior art, the present application dynamically adjusts the transmission power of the equipment based on the user distribution, etc., thereby reducing energy consumption.

The invention relates to a double-recording data matching method and device, equipment, a storage medium and a program product. The double-recording data matching method comprises the following steps: acquiring double-recording data of a target product and index information of the double-recording data from a target product agent; screening out index information of at least one to-be-matched index from the index information of the double-entry data; determining a matching sequence of the to-be-matched indexes; and according to the matching sequence of the to-be-matched indexes, matching the index information of the corresponding to-be-matched indexes with the index information of the reference indexes corresponding to the signed file. By adopting the method, the workload in the matching process can be reduced, repeated matching is avoided, and the matching efficiency is improved.

The application discloses a multi-unmanned aerial vehicle cooperative search method based on a memory-enhanced artificial honeybird algorithm, and the method comprises the following steps: a mixed space environment model containing a continuous dynamics domain and a discrete probability perception domain is constructed; environment information of neighbor nodes is acquired through an established local data link, a local map fusion strategy based on a clearance priority principle is adopted, and a local discrete probability grid map is updated; the output local discrete probability grid map, output distributed dynamic communication topology and current unmanned aerial vehicle state are taken as inputs, a multi-target fitness function is constructed, a memory-enhanced MA-AHA path planning algorithm is executed, and an optimal navigation target point is generated; the optimal navigation target point is converted into a speed control instruction to drive the unmanned aerial vehicle to move; and when it is detected that the unmanned aerial vehicle appears in a motion deadlock, a multimode deadlock recovery mechanism is used to correct the speed instruction. The application can significantly reduce the average flight path length of the unmanned aerial vehicle group and effectively save the energy consumption of maneuvering.

The present invention relates to the field of industrial Internet technology, and in particular to a data processing method based on an industrial Internet data platform. The method comprises the following steps: using the industrial Internet data platform to process industrial production context and generate real-time industrial production context data; constructing a production process constraint knowledge graph based on the real-time industrial production context data; using the production process constraint knowledge graph to match order priorities and generate order priority allocation data; performing production plan conflict detection based on the order priority allocation data to obtain subtask production conflict data; performing flexible scheduling processing based on the subtask production conflict data to generate conflict-free production subtask network data; performing key task path chain identification based on the conflict-free production subtask network data to obtain final production plan data. The present invention eliminates conflicts in production plans and significantly improves production efficiency through flexible scheduling of task chains.

The utility model discloses an efficient plate labeling machine with an automatic decontamination mechanism, which relates to the technical field of plate processing equipment and comprises a labeling machine body and a transmission belt arranged on the labeling machine body. A protection shell is arranged on the right side of the upper end of the transmission belt, a plate body is arranged in the protection shell, a reciprocating sweeping mechanism is arranged on the protection shell, and a driving gear is fixedly installed at the output end of the motor. The utility model discloses an efficient plate labeling machine with an automatic decontamination mechanism. The driving gear and the driven gear are meshed with each other so as to drive the driven gear to rotate, the driven gear further drives the rotating shaft to rotate, the rotating shaft drives the sweeping rod to rotate along with the rotating shaft, the driving gear further drives the straight tooth rack to rotate, the straight tooth rack moves in the guide groove, and the straight tooth rack and the driven gear are meshed with each other. And the driven gear can move in a reciprocating mode, so that the plate body is repeatedly cleaned, and it can be ensured that dust on the surface of the plate is thoroughly cleaned.

The invention discloses a weight matrix processing method and device, equipment, a storage medium and a product. The method comprises the steps that a target weight matrix is loaded; wherein the target weight matrix is a third-precision weight matrix which is arranged in a preset format and is formed by packaging a first-precision weight matrix; carrying out unpacking and inverse quantization processing on the target weight matrix to obtain a weight matrix with second precision; wherein the third precision is higher than the second precision, and the second precision is higher than the first precision; and storing the weight matrix with the second precision to an on-chip storage unit so as to be loaded to a tensor core to execute matrix multiplication operation. According to the embodiment of the invention, the weight matrix can be compatible with the operation logic of tcore, so that the matrix multiplication operation can be smoothly completed in the tcore.

The present invention provides a fusion scheduling method and device based on graph data lineage in a full-load scenario, the method comprising: when a source table triggers an update, querying the sub-tables of the source table level by level, treating the multi-level sub-tables triggered this time as the first task batch; obtaining at least one first task batch; performing a first rule check on the sub-tables in the same first task batch before scheduling execution, and the sub-tables that pass the first rule check will be scheduled for execution; for tasks in the pre-execution queue, according to the configuration rules, the N first task batches in the queue are merged to obtain a second task batch; after the task batches in the queue to be executed are completed, the second task batch is pulled for execution. The fusion scheduling method and device based on graph data lineage in a full-load scenario provided by the present invention optimize the task scheduling execution strategy according to lineage information, reduce repeated execution, and ensure the smooth operation of more tasks under limited resources.

The invention provides a system restart control device and method and network equipment. The system restart control device comprises a CPU (Central Processing Unit) and a logic processing control module, the CPU is connected with the logic processing control module through a management bus; the logic processing control module is used for transmitting the hot restart instruction to the CPU when the remote restart instruction is identified to be the hot restart instruction; the CPU is used for controlling and executing a hot restart process through the software which obtains the soft restart instruction; and the logic processing control module is also used for controlling the execution of a cold restart process when the identified remote restart instruction is the cold restart instruction. According to the method, the cold restart process can be directly executed through the logic processing control module, manual intervention is avoided, and the problem that a remote restart instruction cannot be responded due to system software abnormity is effectively solved.

A method and an apparatus for low power operation in a wireless LAN supporting multiple links are disclosed. The method of a first device comprises the steps of: a first STA associated with the first device performing communication with a first AP on a first link; a second STA associated with the first device performs a power reduction operation on the second link during a period of performing communication on the first link; and after the communication on the first link has been completed, the second STA operates in a wake-up state on the second link without performing a power reduction operation.