17results about How to "Achieve optimal distribution" patented technology

The invention relates to the field of box transformer substation temperature monitoring, in particular to a box transformer substation temperature monitoring method and system based on wireless sensing. A box transformer substation temperature monitoring system based on wireless sensing comprises a risk value acquisition module, an interference value acquisition module and a temperature monitoring module. By adopting the wireless sensing technology, the system can comprehensively cover all temperature monitoring points in the box-type substation, real-time and continuous monitoring of temperature data is achieved, the system can also calculate the comprehensive risk value of each monitoring point, the monitoring frequency is dynamically adjusted according to the comprehensive risk value of each monitoring point, and optimal distribution of resources is achieved; meanwhile, for the monitoring point with the comprehensive risk value larger than the preset deviation value, whether abnormity exists or not can be further judged based on the difference value between the ideal temperature and the actual temperature, the accuracy of temperature data is improved, and the intelligent level of box transformer substation temperature monitoring is greatly improved.

The invention relates to an AI-based CDN resource intelligent scheduling cost optimization method and device. Obtaining the current resource use condition of each resource node in the distribution network and the cost strategy of each resource affiliation party to which each resource node belongs; adopting an AI cost strategy model to analyze an estimated resource demand required by a demand side in a prediction time period, a current resource use condition of each resource node and a cost strategy of each resource affiliation side to which each resource node belongs, and obtaining a target node selected by the AI cost model from each resource node; and providing corresponding resources for the demand side in the prediction time period by adopting the target node.

The invention relates to the technical field of energy management, and particularly discloses a photovoltaic off-grid coupling PEM water electrolysis hydrogen production EMS energy management system, which comprises an energy acquisition module for dividing a PEM water electrolysis hydrogen production system into a plurality of units according to functions and acquiring time interval distribution power; the power analysis module is used for comparing and analyzing the time interval distribution power and the required power range of the units to obtain input over-energy units, and judging whether the power matching of each unit needs to be analyzed or not; the model building module is used for building an energy efficiency evaluation model of each unit if the power matching of the units needs to be analyzed; the energy efficiency analysis unit is used for calculating an energy efficiency evaluation value and judging whether the power input into the over-energy unit needs to be regulated or not; and if the power of the input over-energy unit needs to be regulated and controlled and the input power needs to be adjusted, the system can find the stability problem of the system in advance, and the power distribution of each unit of the PEM hydrogen production system is optimized.

The invention discloses an ordered charging control system and method based on network communication, and belongs to the technical field of ordered charging control. The method comprises the steps of obtaining charging pile operation data in a station, power utilization data in the station and station output power threshold data, and calculating total controllable power P, direct current charging pile controllable power M and alternating current charging pile controllable power N; the operation data of the charging pile in the station comprises the current output power P1 of the charging pile and the output power P2 of the charging pile; when the current output power P1 of the charging pile is larger than the output power P2 of the charging pile, the power is limited; when the current output power P1 of the charging pile is smaller than or equal to the output power P2 of the charging pile, the power is released; and based on the size relation between the total controllable power P and the sum of the direct current charging pile controllable power M and the alternating current charging pile controllable power N, respectively determining the output power of each charging pile under different working conditions when the power is released and the power is limited.

The invention discloses a real-time sensing and dynamic regulation and control method and system for the state of an interface between a shield tunnel and a surrounding soil body. The method comprises the steps that S1, contact pressure and slurry filling state data of the interface between the tunnel and the surrounding soil body are collected in real time; s2, the edge computing node performs real-time diagnosis and trend prediction on the interface contact state based on the collected data; when the diagnosis result is that the interface pressure is abnormal, a regulation and control instruction of the distributed bionic actuator array is triggered; s3, the bionic actuator in the interface pressure abnormal area receives the regulation and control instruction to operate, and active remodeling and redistribution of an interface stress field are achieved; s4, performing effect evaluation based on the real-time sensing data to form a control closed loop; and S5-S6, operating the high-fidelity multi-physics field coupling model based on the regulation and control case data, and performing self-learning optimization and updating on the interface mechanical model parameters, the regulation and control strategy and the decision threshold. According to the invention, global real-time sensing and dynamic active regulation and control of the state of the interface between the shield tunnel and the surrounding soil body can be realized.

The application discloses a kind of discrete series low distributed capacitance liquid cooling heat dissipation device and method, it belongs to electronic device heat dissipation technical field, heat dissipation device includes several heat dissipation units, the top of each heat dissipation unit is used to set power device, and two adjacent heat dissipation units are connected by cooling liquid pipeline;Each heat dissipation unit includes matrix and radiator, cooling liquid pipeline is through the inside of matrix, the top center of matrix is equipped with mounting hole, and mounting hole is equipped with radiator, and the lower half of radiator is inserted into the inside flow channel of cooling liquid pipeline, and the top of radiator is used to place power device.The application adopts discrete series heat dissipation unit structure, cooling liquid pipeline is through each unit matrix, and the lower half of radiator is inserted into the inside flow channel of pipeline, and each unit independently corresponds a power device.Solve the parasitic distributed capacitance problem caused by shared metal radiator, eliminate resonance loop, inhibit switching oscillation, reduce loss, ensure that heat dissipation is uniform and dynamic equalization, improve the stability and service life of high-voltage series module.

The invention discloses a data security processing method, a client, electronic equipment and a storage medium, and relates to the technical field of information security. The method comprises the steps that a file uploading request of an application program is intercepted through an adaptation library of a user mode file system; obtaining a physically isolated master key in the hardware cryptographic device, and deriving a unique file encryption key in combination with the target file information; calling a national secret algorithm library, performing symmetric encryption on file data by using the file encryption key, and performing asymmetric encryption on the file encryption key by using a public key; and generating an encrypted file header containing the encryption parameter and the ciphertext file key, and uploading and storing the encrypted file header. Through deep fusion of the hardware cryptographic device and the user mode file system, hardware-level physical isolation protection of the key, national cryptographic algorithm compliance support and transparent encryption and decryption are realized, key leakage is effectively prevented, and data security is improved.

The invention relates to a design method for steel plate crack damage additive manufacturing single-side repair, which comprises the following steps of: setting geometric and material parameters of a crack damage steel plate and a repair body, and determining a load state to calculate von Mises stress distribution of the steel plate under an undamaged condition; then, calculating the maximum reference semi-elliptical section of the restoration body in the direction perpendicular to the crack based on the thickness, the strength ratio and the crack width of the steel plate; determining the overall length of the restoration body along the crack direction according to the crack length; and finally, in combination with the maximum reference section and the stress distribution, calculating the variable cross-section size distribution of the restoration in the crack direction through a stress ratio function, and generating a semi-elliptical variable cross-section three-dimensional restoration model matched with the internal stress of the steel plate. Compared with the prior art, the method solves the problems that when the crack damage of the steel structure is repaired through metal additive manufacturing, a restoration body lacks a unified geometric description model, and calculation and design are not reliable.

This invention relates to the field of metallurgical equipment condition monitoring, and discloses a method and apparatus for detecting and judging cracks in the refractory layer of a full-size molten iron ladle before it receives hot iron. The method includes: acquiring an image of the inner wall of the molten iron ladle; performing a first-stage processing on the image to quickly locate one or more suspected crack areas using a convolutional neural network; performing a second-stage processing on each suspected crack area by actively projecting an optical pattern and analyzing its geometric deformation to calculate the three-dimensional physical parameters of the crack, such as its physical width and depth; and comparing the calculated physical parameters with preset safety standards to automatically judge the molten iron ladle. This invention, through a two-stage processing strategy, combines the rapid recognition capability of deep learning with the precise quantification capability of active visual three-dimensional measurement, achieving accurate acquisition of the physical dimensions of cracks. This provides reliable data support for automated and objective ladle judgment decisions, significantly improving the accuracy and reliability of detection.

The present invention provides an N-cascade inverter SG model based on time division multiplexing, wherein the transformer model is used to adopt a time division multiplexing method to sequentially use N / 2 groups of transformation parameters as input parameters, and receive a second voltage fed back by a rectifier model, and output a first voltage and a first current after transformation adjustment of the second voltage and the input parameters; the transformer model is used to receive a first voltage and a first current and a third current fed back by an inverter model, and output a third voltage, a second current and a second voltage after rectification; the inverter model is used to receive a third voltage, a second current and a three-phase load current fed back by an external motor model, and output a fourth voltage and a third current after inversion, so that the N-cascade inverter model runs in a simulation cycle of 1e‑7s, and realizes the optimal allocation of FPGA resources while ensuring the correctness of the results, the simulation results are highly consistent with simpower, and the FPGA resource occupancy rate is relatively low.

The invention relates to the technical field of energy management, and specifically discloses an EMS energy management system for photovoltaic off-grid coupled PEM water electrolysis hydrogen production, comprising: an energy acquisition module, which divides a PEM water electrolysis hydrogen production system into multiple units according to functions, and obtains time period allocation power; a power analysis module, which compares and analyzes the time period allocation power of the unit with the required power range, obtains the input over-energy unit, and determines whether the power matching of each unit needs to be analyzed; a model construction module, which constructs an energy efficiency evaluation model for each unit if the power matching of the unit needs to be analyzed; an energy efficiency analysis unit, which calculates an energy efficiency evaluation value and determines whether the input over-energy unit power needs to be regulated; an energy regulation module, which adjusts the input power if the input over-energy unit power needs to be regulated. The system can discover system stability problems in advance and optimize the power distribution of each unit of the PEM hydrogen production system.

The invention discloses an energy efficiency optimization analysis method for sewage treatment, and particularly relates to the field of sewage energy efficiency data processing and signal transmission processing. Comprising the steps of data source signal integrity detection, input preparation of a three-dimensional evaluation model, three-dimensional analysis of energy efficiency data, generation of an energy efficiency evaluation value, comparison of the energy efficiency evaluation value and an energy efficiency threshold value, screening of a model sewage treatment plant and the like. Through signal integrity detection and a dynamic adjustment mechanism of data acquisition frequency, the data quality in the energy efficiency evaluation process is improved, so that the overall precision of energy efficiency evaluation is improved; under the support of system real-time monitoring and data quality control, high-reliability data sources can be effectively screened for evaluation and analysis, so that the energy efficiency evaluation result is more suitable for actual conditions and operation requirements.

The invention provides a dynamic random access communication method based on deep reinforcement learning, which belongs to the field of communication system access process control, and comprises the following steps: a user determines the number of data packets needing to be sent in the transmission according to the probability distribution of the number of sent data packets sent by a receiving end in a random access process in a current frame; the corresponding number of time slots are uniformly selected to send data packets one by one; in the receiving process of the receiver, firstly, data packets capable of being decoded are decoded one by one according to time slots, then the decoded data packets are utilized to eliminate interference in a current frame random access signal to obtain a signal after interference elimination, and the data packets capable of being decoded are continuously decoded one by one according to the time slots for the signal after interference elimination to obtain a random access signal after interference elimination. And repeating the steps continuously. According to the method, the problem of data packet collision among multiple users can be effectively solved, normal decoding can still be performed under the condition of collision, and the system throughput is remarkably improved.

The invention relates to the technical field of photovoltaic energy storage, in particular to a charging and discharging control method of a photovoltaic energy storage system, a product, equipment and a medium. The method comprises the following steps: predicting future illumination intensity and future power consumption load of a next period, wherein the future power consumption load comprises a power consumption time period and a non-power consumption time period; adjusting a charging parameter of a battery pack of the photovoltaic energy storage system based on the future illumination intensity; acquiring historical charging data of the battery pack, and determining a first corresponding relation between the illumination intensity and the charging rate based on the historical charging data; and making a charging and discharging strategy based on the future illumination intensity, the future electrical load, the charging parameter and the first corresponding relation, and controlling the photovoltaic energy storage system to charge and discharge based on the charging and discharging strategy. According to the invention, the flexible adaptability of the energy storage system under different illumination and power utilization conditions can be improved.

The application discloses a processing method suitable for large marine propellers and relates to the technical field of precise composite processing of large marine propellers, and comprises the following steps: installing a propeller and a standard ball on a rotating table of a machine tool, installing a high-precision calibration needle on a main shaft, establishing a positioning datum of a workpiece by using a fitting algorithm, constructing a workpiece coordinate system and a conversion relationship between the workpiece coordinate system and a machine tool coordinate system; acquiring point cloud data of each part of the propeller, and converting the point cloud data to the workpiece coordinate system by using coordinate conversion; performing coarse and fine splicing on blade root point cloud, combining data of the rest parts, and forming workpiece coordinate system point cloud data of the propeller; calculating polishing amount by using a normal projection algorithm based on the data; generating a machining track containing blade thickness calibration according to the polishing amount, and milling and polishing the propeller according to the machining track. The method significantly improves positioning accuracy, effectively eliminates clamping errors, is high in polishing amount calculation precision and efficiency and strong in self-adaptability, and significantly improves machining efficiency and shortens a production cycle.

The invention discloses a data processing method and device, a computer program product and electronic equipment, and relates to the field of financial science and technology, and the method comprises the steps: constructing a business constraint condition based on the business upper limit data of each website in a target region in each time period, constructing an employee constraint condition based on the total number of employees in the target region, and constructing a business constraint condition based on the business upper limit data; constructing a utility cost function to obtain a target function, performing iterative solution on the target function when a business constraint condition and an employee constraint condition are satisfied to obtain an initial business volume and an initial employee number, determining a mismatch value corresponding to each time period based on the total number of employees and the initial employee number, and determining a mismatch value corresponding to each time period; and when the mismatch value is smaller than a preset mismatch threshold value, taking the initial employee number as a target employee number. According to the method and the device, the technical problem that the service pressure of the network is too high in part of time periods but human resources are wasted in part of time periods due to the fact that the number of employees which should be allocated by each network in different time periods cannot be accurately determined in related technologies is solved.

This application discloses a laboratory personnel behavior perception system, including a positioning axis, a sensory neuron module, and a data coupling module. The positioning axis is linked with personnel positioning tags to update personnel positions in real time on an electronic map. Upon receiving a preparation command, when the distance between the personnel's position and at least one area to be prepared in the preparation command is less than a first distance threshold, a personnel behavior perception command is generated and sent to the sensory neuron module. The sensory neuron module creates a personnel movement trajectory and predicts future trajectories. After all personnel behavior perception commands and preparation commands have been received, personnel behavior perception is performed to enable or disable device operation permissions. The data coupling module determines whether there is an intersection between the future trajectory and the experimental area; if so, it identifies the area to be prepared, generates a preparation command, and simultaneously sends it to the positioning axis and the sensory neuron module. This application can achieve efficient and accurate management of laboratory equipment permissions.