1846results about How to "Solve efficiency problems" patented technology

The invention relates to a temperature control intelligent optimization method and system for adhesive tape production. The method comprises the following steps that S1, production data in the drying process are collected through a multi-mode sensor; s2, constructing a state prediction model based on GNN and LSTM, inputting the collected production data into the prediction model, and dynamically predicting the state of each temperature control area; s3, modeling each temperature control area into an intelligent agent based on the predicted state between the temperature control areas, and realizing dynamic distribution of heat resources of each heating interval by training a cooperative control strategy between the intelligent agents; s4, a fuzzy control optimization scheme incorporating environment compensation: for short-term changes of environment temperature and humidity, dynamically adjusting temperature zone gradient distribution between drying sections by using fuzzy control, and optimizing energy efficiency; and S5, the temperature control module adjusts the temperature and the wind speed of the temperature control area in real time according to the optimization schemes obtained in the steps S3 and S4. The intelligent level of the temperature control system in the adhesive tape production drying process is comprehensively improved.

The invention discloses a CCER forestry carbon sink project development system based on artificial intelligence technology monitoring, and relates to the technical field of carbon sink monitoring and optimization. According to the CCER forestry carbon sink project development system based on artificial intelligence technology monitoring, space-time estimation is carried out on CCER forestry carbon sink project data through the deep learning model, and the dynamic change of the carbon sink amount is accurately predicted. Spatial features are extracted through a convolutional neural network, time sequence data are analyzed in combination with a long-short-term memory network, and a carbon sink prediction model is constructed. And through statistical analysis and a spatial interpolation algorithm, carbon sink quantity change is monitored in real time, an abnormal trend is identified, and early warning is provided. Based on a mixed integer linear programming algorithm, forest land resource allocation and vegetation types are optimized, a carbon sink optimization scheme is generated, and carbon sink benefit maximization is promoted. And through an intelligent carbon sink management scheme, sustainable ecological development and green and economic popularization are assisted.

The invention discloses an electric vehicle dynamic balance charging method and system with a double-gun structure. The method comprises the steps that vehicle charging requirements, vehicle battery state information and charging pile state information are collected; determining an overall charging strategy; based on the overall charging strategy, the charging parameters of each charging gun are dynamically adjusted in combination with the real-time state change of the vehicle battery in the charging process and the power output capacity of the vehicle charging pile; monitoring partition parameter detection information in the charging process, comparing the partition parameter detection information with a corresponding preset safety threshold, and if the partition parameter detection information is out of the range of the corresponding preset safety threshold, triggering a partition load change information collection instruction; acquiring double-gun adjustment parameter information according to the partition load change information collection instruction; according to the double-gun adjustment parameter information, a charging pile adjustment instruction is triggered; the dual-gun dynamic balance charging system effectively solves the problems of low charging efficiency and load balance of the existing dual-gun dynamic balance charging system, and improves the charging efficiency.

The invention provides a feature-enhanced advertisement service scene image generation method. The method comprises the following steps: S1, training data set preparation: collecting and preprocessing advertisement and e-commerce picture data sets; s2, selecting and initializing a basic model: selecting an appropriate stable diffusion large model as the basic model, and carrying out initial testing on the basic model; s3, Lora model training: training a Lora model on the basis of the stable diffusion large model; s4, model integration: integrating the trained Lora model parameters into a stable diffusion large model to realize characteristic enhanced image generation; and S5, generating and optimizing an image. According to the method, a customized feature enhancement model is efficiently trained at low cost, and then the model is integrated to a diffusion model to realize an image generation method of an advertising service scene, so that the problems of deficiencies in feature extraction and personalized generation of a traditional method and the problems of low efficiency and large resource consumption in fine adjustment of a large model are solved.

The invention relates to a resource-limited large model heterogeneous training method, computer equipment and a storage medium, and the method comprises the steps: determining a first activation amount according to a dependency relationship between calculated amounts corresponding to the activation amounts and / or the calculated amount and the storage amount of each activation amount in the activation amounts generated when an image processor carries out model forward propagation, the first activation amount is asynchronously transmitted to the central processing unit; loading a first activation amount to the image processor from the central processing unit in a model back propagation process; obtaining the gradient of the model parameter calculated by the image processor based on the first activation amount, and asynchronously transmitting the gradient to the central processing unit; and determining an optimizer obtained based on gradient updating in the central processing unit, obtaining model parameters obtained by adjustment of the updated optimizer, and asynchronously transmitting the model parameters to the image processor. By adopting the method, the problems that a large model with limited video memory resources is difficult to train and the computing efficiency of a video card is low can be solved.

The invention provides a computing power network task scheduling method and device, a storage medium and a program product, and relates to the technical field of computers.The method comprises the steps that a task scheduling optimization problem is obtained by defining an objective function between network energy consumption of a computing power network and network carbon emission of the computing power network and constraint conditions corresponding to the objective function; the optimization objective of the objective function is to reduce the network energy consumption and the network carbon emission by optimizing the computing power node, the forwarding path and the forwarding time corresponding to the computing power task; solving the task scheduling optimization problem through a preset optimization algorithm to obtain a task scheduling method of the computing power network; the task scheduling method is used for indicating a forwarding path of a computing power task in a computing power network, a computing power node for executing the computing power task and forwarding time corresponding to the computing power node; according to the method, the problems of relatively low expandability and management efficiency of task allocation can be solved; and the task allocation flexibility and management efficiency are improved.

The invention relates to the technical field of electric power risk control, and discloses an anti-bidding risk control system platform based on a large model technology, and the system platform comprises the steps: collecting bidding data, splitting the bidding data into bidding text data, behavior data and enterprise background data, carrying out the semantic extraction of the bidding text data, obtaining a core data set, and carrying out the calculation of the core data set; performing similarity score calculation on the core data set to obtain a similarity score; constructing a bidding relationship network by utilizing the behavior data and the enterprise background data; performing data synthesis by using the bidding relationship network, the similarity score and the core data set to obtain contrast data; and performing comparative analysis on the comparison data and the bidding data to obtain an abnormal behavior, and performing risk control scoring on the abnormal behavior to obtain an anti-bidding risk control result. According to the invention, the problems of low efficiency and poor adaptability of an existing anti-flipping risk control system platform based on a large model technology can be solved.

The invention discloses a vehicle battery feed risk identification method and device. The method relates to the field of new energy vehicles, and comprises the following steps: when it is detected that a target vehicle is in a standing state, obtaining an accumulated standing time length when the target vehicle is in the standing state; obtaining the total discharge rate of the vehicle battery of the target vehicle in the target time period; the actual SOC capacity of the vehicle battery in the standing state is determined; based on the total discharge rate and the actual SOC capacity, the residual discharge duration of the vehicle battery is determined; and determining a feed risk identification result of the vehicle battery based on the residual discharge duration and the accumulated standing duration. According to the method and the device, the technical problem that the accuracy and the efficiency of feed risk prediction are relatively low when the feed risk of the vehicle battery is identified in the vehicle standing state in the related technology is solved.

A mirror surface defect detection system imaging simulation method based on a structured light field comprises the steps that S1, system parameters are calibrated and serve as simulation model input; and S2, deducing a light propagation model of the light field camera, performing light tracing from a sensor, performing parallel calculation on the light field sub-graph array, and solving an incident light vector of the light field camera. And S3, designing a three-dimensional surface shape of a function fitting deformation defect, solving an incident light vector at the defect, and tracing light to obtain a light source point coordinate and illumination intensity. And S4, based on a Lambert diffuse reflection model, introducing a coefficient representing scratch roughness / stain opacity, and establishing a diffuse reflection non-deformation defect gray model. And S5, generating a simulation image and a label thereof. And comparing the simulation image with the real shot image, and evaluating the reliability of the simulation model. And evaluating the operation efficiency of the simulation model. According to the method, the precision and speed of mirror surface defect light field detection imaging simulation are effectively improved, and the method can be applied to parameter optimization, simulation image data set generation and the like before construction of a detection system.

The invention belongs to but not limited to the technical field of text extraction, and particularly relates to an automatic construction method and system for a process industry text knowledge extraction dataset. Firstly, based on a word segmentation tool and a TF-IDF algorithm, an unlabeled text in the process industry field is converted into a large language model fine tuning dataset, and a large language model is subjected to fine tuning; the system has specific knowledge of the field; then, generating an initial knowledge extraction sample set with confidence through multi-stage exploration-utilization ratio adjustment based on the fine-tuned large language model; and finally, through a confidence-based large-scale sample set error detection and correction method, obtaining a sample data set which is finally used for domain knowledge extraction model training. Through the low-cost and high-efficiency industrial text knowledge extraction sample set construction and application method, the input-output ratio of resources is increased to the maximum extent, and the construction and application efficiency of an industrial safety knowledge extraction algorithm is improved.

The invention discloses high-precision laser cutting equipment suitable for a complex circuit board, and relates to the technical field of circuit board cutting, the high-precision laser cutting equipment comprises a ceramic table top, a base, a cooling assembly and a waste collecting assembly, the ceramic table top is fixedly mounted at the top end of the outer wall of the base; a cooling assembly and a waste collecting assembly are fixedly installed on the side face of the base through a conveying mechanism. The cooling assembly comprises a nozzle, a liquid box and a radiator, the nozzle is fixedly installed on the side face of the top end of the outer wall of the base through a supporting piece, the liquid box is fixedly installed on the side face of the outer wall of the base, the radiator is fixedly installed on the side face of the inner wall of the base, an impeller is fixedly installed at the bottom of the inner wall of the radiator, and a ventilation opening is formed below the impeller. And a dustproof net is fixedly mounted at the ventilation opening through a bolt. By installing the cooling assembly, the cutting temperature is reduced, the problem of material deformation caused by the heat effect is solved, and it is helpful for guaranteeing the flatness and smoothness of the cutting face and the overall integrity of the circuit board.

The invention discloses a fabric setting equipment running machine parameter optimization recommendation method and device, equipment and a medium, and the method comprises the steps: carrying out the preprocessing and standardization operation of collected fabric setting equipment running machine parameter data, extracting batch process characteristic data, calculating an optimal parameter value according to the process characteristic data of a stable interval, and carrying out the calculation of the optimal parameter value; and associating the optimal parameter value with fabric category information of a batch, matching the fabric category information with process data items in a process library when a new production batch is detected, if the matching is successful, recommending line machine parameter data, and if the matching is not successful, performing prediction through an equipment learning model. According to the technical scheme of the invention, the technological parameters can be quickly output through the system recommendation, and meanwhile, the quality problem caused by personal errors is reduced.

The invention discloses a training method and device of a distributed computing system, a program product and a medium, which are used for solving the problems of performance difference and low communication efficiency of heterogeneous computing nodes. According to the scheme, the calculation capability of each calculation node is fully considered, so that dynamic allocation and iterative optimization of tasks are realized; specifically, the problems of idle resources and low efficiency are avoided by acquiring the computing power of each computing node and allocating the training task matched with the computing power to the computing node; the time length of single iteration is determined, and the number of iterations in the communication interval is adjusted according to the time length, so that each computing node can perform data exchange at a proper time, network bandwidth occupation and delay caused by frequent communication are reduced, the overall efficiency of the training process is optimized, mutual waiting between the computing nodes is avoided, and the network performance is improved. When the computing node runs the training process, the power consumption and heat generation are reduced, and the communication overhead is also reduced, so that the long-term stability and reliability of the computing node are improved.

The invention provides an AIGC-based (advanced integrated gasification control-based) aisle deduction system and a use method thereof, and belongs to the technical field of non-abandoned inheritance, and the AIGC-based aisle deduction system and the use method thereof are characterized in that the AIGC-based aisle deduction system and the use method thereof are provided; comprising a creativity input and planning module, a music and sound effect generation module, a visual design and rendering module, a performance synthesis and director module, an interactive experience and user feedback module and an education and culture transmission module, and the whole system comprises creativity excitation, content generation, user interaction and culture transmission. According to the method, a closed loop is formed, creation efficiency and viewing experience of the aisle art are improved, content is continuously iterated and optimized through intelligent analysis and an instant feedback mechanism, tight fit between works and audience requirements is ensured, the problems of low efficiency and market competitiveness in a traditional supply chain are effectively solved, and the method is suitable for popularization and application. And the live inheritance and development of the traditional cultural form of the aisle in the modern society are promoted.

The invention belongs to the technical field of positioning and navigation, and particularly relates to a line inspection method and system for unmanned aerial vehicle airborne power grid X-ray detection equipment. According to the method, a positioning unmanned aerial vehicle is used for determining a hovering point of a transportation unmanned aerial vehicle on a power transmission line, after the hovering point is sent to a positioning navigation unit, the positioning navigation unit carries out coordinate system unification and flight path planning, and the transportation unmanned aerial vehicle receives a flight instruction sent by the positioning navigation unit; carrying the power grid X-ray detection equipment to fly to a hovering point according to the path planning of the positioning navigation unit; and releasing the power grid X-ray detection equipment, analyzing the acquired X-ray image by the power grid X-ray detection equipment, and transporting the unmanned aerial vehicle recovery equipment after the acquisition task is completed. According to the invention, the difficulty in releasing and recovering the power grid X-ray detection equipment can be reduced, and the detection efficiency is improved.

The invention discloses a metasurface reverse design method of a generative adversarial network based on anchor point network control. The method comprises the following steps: collecting metasurface design parameters and spectral response data, preprocessing, and encoding the data into a format which can be processed by a deep learning model; and analyzing the training data by using a K-means clustering algorithm to generate a structured control vector. And constructing an AcGAN framework, and integrating the spectrum similarity measurement SOC into a loss function of a generator and a discriminator to enhance the spectrum matching precision. Through an adversarial training method, a generator is trained to generate a design conforming to target spectral characteristics, and meanwhile, a discriminator and an anchor network AncorNet are optimized to quickly predict and evaluate spectral response. Candidate designs are generated using the trained generator in combination with control vectors and random noise. And screening the candidate design to select the optimal design. According to the method, the spectrum regulation and control precision and the design efficiency of the metasurface design are effectively improved, and the challenge faced by a traditional method when a complex spectrum requirement is processed is solved.

The invention discloses an equipment scheduling method and system based on dynamic priority and multi-objective optimization, and the method takes the minimization of a waiting time mean square error, the minimization of total waiting time and the minimization of maximum completion time as optimization objectives. A task dependency relationship, an equipment maintenance time window, a time window constraint, a student learning progress priority and a delay compensation mechanism constraint condition are comprehensively considered, a dynamic priority calculation mechanism is introduced, the priority is dynamically adjusted in real time according to task waiting time, deadline and urgency, and a high-quality initial population is generated through CMA-ES; a non-dominated sorting framework optimized by NSGA-II is combined, crossover variation of a traditional genetic algorithm is replaced by PSO updating, and an optimal solution is searched by using an elitism mechanism. The method can effectively improve the utilization rate of equipment resources, reduce the task completion time and optimize the fairness of task allocation, is suitable for equipment sharing and dynamic scheduling scenes, and has high practicability and popularization value.

The invention discloses an automatic balance adjusting method for a deviation rectifying device of a belt conveyor, and relates to the technical field related to conveyors. The method comprises the steps that basic information of a conveying belt of a target belt conveyor is obtained; correcting node optimization of the correcting device is carried out, and optimal correcting point location distribution is generated; a plurality of deviation rectifying devices located at a plurality of point positions are distributed and configured according to the optimal deviation rectifying point position; belt deviation monitoring is carried out at a plurality of point positions through a transmission roller, and deviation point positions, corresponding belt deviation amounts and corresponding target deviation correcting devices are generated; generating a balance pilot control vector; and driving the corresponding electric push rod to carry out deviation correction according to the balance guide control vector. The technical problems that due to the fact that deviation of a conveyor belt is difficult to accurately monitor in real time in an existing conveyor deviation rectifying device, the balance adjustment response speed is low, the adjustment precision is limited, and the deviation rectifying efficiency and accuracy of the conveyor deviation rectifying device are insufficient are solved, and the technical effect of improving the deviation rectifying efficiency and accuracy of the deviation rectifying device is achieved.

The invention relates to a volatile organic waste gas collecting and purifying device, and belongs to the technical field of waste gas purification, the volatile organic waste gas collecting and purifying device comprises a purifying device for collecting and purifying waste gas, a filtering device and a filtering cylinder arranged in the filtering device and used for filtering gas, and the filtering device is provided with a cleaning mechanism for cleaning the filtering cylinder; the cleaning mechanism comprises a rotating disc arranged above the filtering device, a vibrating plate connected to the outer surface of the filtering cylinder in a sleeving mode and a connecting rod hinged to the outer portion of the rotating disc, extending into the filtering device and rotationally connected with the vibrating plate. According to the volatile organic waste gas collecting and purifying device, the rotating disc and the water sprinkling structure are linked and matched for use through the transmission mechanism, so that the synchronous operation of gas filtering, reciprocating cleaning and water sprinkling can ensure that the surface of the filter cartridge is always kept in a clean state while the filter device continuously works, and the synchronism improves the dust cleaning efficiency; the reduction of the filtering efficiency and the increase of the energy consumption caused by excessive accumulated dust are reduced.

The invention discloses a general thermal power plant machine room DCS equipment data transmission method, equipment, a medium and a product, and relates to the field of data transmission, and the method comprises the steps: after a configuration file is defined, analyzing the configuration file, building a connection with general thermal power plant machine room DCS equipment according to a communication parameter and a mapping table, and based on a user request, according to a to-be-acquired data item list, obtaining a data item list; and reading data from the general thermal power plant machine room DCS equipment to obtain original data, processing the original data based on regulations of a communication protocol, and setting a retransmission mechanism and an error processing mechanism to obtain a data reading result. According to the application, the increase and decrease of the data volume become more convenient, the problems of delay and low efficiency in the big data transmission process can be solved, and the problem of data loss or damage caused by the influence of noise and interference is avoided.

The invention relates to the technical field of electric power operation and maintenance, and particularly discloses an unmanned aerial vehicle insulator defect identification method based on improved yov8n, and the method comprises the steps: firstly, improving a down-sampling module and feature map processing, enhancing the capability of a model for extracting insulator defect features, and improving the detection accuracy; and secondly, a Focaler-SIoU loss function is introduced, the target positioning performance is optimized, and particularly, the robustness of the model is improved when samples difficult to classify are processed. In addition, the model is lightened through the LAMP algorithm, and the parameters and the calculation amount of the model are reduced, so that the model is more suitable for running on mobile equipment such as an unmanned aerial vehicle and the like. And finally, through training verification and deployment into an unmanned aerial vehicle detection system, real-time and efficient defect identification is realized, so that the problems of low efficiency, poor real-time performance and the like in the prior art are solved, the insulator defect detection precision can be improved, and meanwhile, the complexity and the calculation amount of the model are reduced so as to adapt to the real-time detection requirement of an unmanned aerial vehicle platform.

The invention belongs to the technical field of ship and ocean engineering, and discloses a ship seakeeping intelligent forecasting method and system based on a physical information neural network. According to the method, a CFD-RAO method is combined with PINNs, and rapid and high-precision prediction of ship seakeeping is realized by constructing a coupling model of a physical equation and a neural network loss function. According to the invention, rapid and high-precision prediction of ship seakeeping is realized. The method not only can effectively cope with multi-degree-of-freedom coupling motion under complex sea conditions, but also has high real-time performance and adaptability, and provides more scientific and reliable technical support for ship design and navigation safety.

The invention discloses a test question data generation method, electronic equipment, a storage medium and electronic equipment, and relates to the field of large model technology and text data processing. The method comprises the steps that in response to a first input instruction acting on an operation interface, a target document corresponding to the input instruction is displayed on the operation interface, and the target document comprises multi-modal data; in response to a conversion instruction acting on the operation interface, displaying target text data corresponding to the conversion instruction on the operation interface; in response to a second input instruction acting on the operation interface, a generation condition corresponding to the second input instruction is displayed on the operation interface, and the generation condition comprises at least one of a target type, a target difficulty level and a target dimension; and in response to a generation instruction acting on the operation interface, displaying the target test question data on the operation interface. The technical problem of low efficiency and diversity of test question data generation in related technologies is solved.

The invention provides a coalescence-selective filtration-deep bed filtration efficient oil-water separation system which comprises a coalescence system, a selective filtration system and a deep bed filtration system, oily wastewater enters a coalescer, and tiny oil droplets are coalesced into larger oil droplets through wetting coalescence and collision coalescence; the coalesced wastewater enters a selective filter, oil droplets and water respectively flow out through an oil channel and a water channel, and primary separation is realized; according to the present invention, the water after the primary separation enters the deep bed filter to achieve the deep separation, the efficient oil-water separation and the water quality standard discharge or reuse are achieved through the combination process of coalescence, selective filtration and deep bed filtration, and the system has advantages of high treatment efficiency, low energy consumption, less carbon emission, oil and water recycling, or water standard discharge.

The invention discloses a photoetching method and system for holographic anti-counterfeiting printing, and relates to the field of printing data processing, and the method comprises the steps: receiving at least one grayscale image, coding preset holographic anti-counterfeiting information into the grayscale image, obtaining a holographic anti-counterfeiting grayscale image, and determining the spatial frequency and pattern complexity of the holographic anti-counterfeiting grayscale image; determining the frequency of the laser according to the spatial frequency and the pattern complexity; determining an exposure angle range of a laser and a scanning path on the substrate according to the fine pattern of the holographic anti-counterfeiting grayscale image; receiving a first instruction, and acquiring the intensity of reflected light on the substrate and the definition of an interference pattern on the substrate in real time according to the frequency and the exposure angle range of the laser; determining the optimal focal length position of the optical system according to the intensity of the reflected light and the definition of the interference pattern on the substrate; generating a second instruction according to the optimal focal length position; and carrying out photoetching on the fixed substrate through a laser to obtain a three-dimensional holographic anti-counterfeiting pattern.

The invention belongs to but is not limited to the technical field of radio detection direction finding, and discloses a double-antenna three-dimensional rotating baseline direction finding method, device and system. Inter-channel phase deviation table compensation is carried out, equal-frequency-interval full-working-frequency-band measurement is carried out on phase deviation between two measurement channels in advance, and a channel phase deviation compensation table AB is formed; the compensation module is used for compensating inherent phase deviation between the channel A and the channel B; after the double-antenna three-dimensional rotating baseline direction finding device starts to work, a baseline formed by the antennas AB rotates anticlockwise at an angular velocity omega, two receiving channels synchronously collect data, and phase difference is calculated for the data corresponding to the baselines AB; based on a two-dimensional joint search method, through combination of coarse search and fine search, an azimuth angle and a pitch angle are estimated. According to the technical scheme provided by the invention, the direction finding range and reliability of a traditional system are greatly expanded, meanwhile, the cost is basically not increased, and the large-scale application of the technical system can be promoted.

The invention discloses a mine geological environment evaluation system based on multi-scale characteristics and an evaluation method thereof. The mine geological environment evaluation system comprises a remote sensing image acquisition unit, a mine geological environment problem analysis unit, a mine geological environment element extraction unit, a mine geological environment problem identification unit and a mine geological environment evaluation unit. The method comprises the following steps: collecting a remote sensing image of a target mine area, extracting mine geological environment elements, analyzing temporal and spatial change characteristics of the elements, performing similarity comparison calculation with change characterization of different mine geological environment problems, identifying the geological environment problems, and training an evaluation model to obtain a geological environment evaluation prediction result. According to the method, index factor characterization of different mine geological environment problems is analyzed from remote sensing image modal data, through automatic comparison and matching with target remote sensing image multi-scale features, the problem that the efficiency and quality of a mine geological environment investigation mode and a sample selection method are low is solved, and scientific evaluation of the mine geological environment is achieved.

The invention discloses a robot autonomous wire stroking method, system and device based on a tactile sensing multi-fingered dexterous hand and a storage medium, and belongs to the field of manipulator control. The robot autonomous wire stroking method comprises the steps that mechanical input data of finger tips of the tactile sensing multi-fingered dexterous hand is acquired and collected; generating pose estimation data of the cable according to the mechanical input data; according to the pose estimation data and / or the mechanical input data, dynamic expected data of the touch sensing multi-fingered dexterous hand is generated; according to the dynamics expected data, a control instruction for the touch sensing multi-fingered dexterous hand is generated so as to control the wire stroking process through the touch sensing multi-fingered dexterous hand. According to the multi-fingered dexterous hand, the touch sensing data is obtained and utilized in real time, accurate control over the multi-fingered dexterous hand is achieved, and finally stable and efficient grabbing and following of the cable are achieved. The problems that a manipulator is low in adaptability to a wire stroking task and low in operation efficiency are solved.

The invention provides an automatic management system and method for a steel plate warehouse area, and relates to the technical field of industrial automation and intelligent warehousing, and the system comprises a steel plate recognition warehousing module, a warehouse area division module, an informatization warehousing module, an automatic crane and a warehouse management system. Through an efficient automation technology and an intelligent management strategy, the operation efficiency and the storage utilization rate of a steel plate storage area are remarkably improved, the deflection problem caused by mixed storage of steel plates of multiple specifications is effectively avoided, accurate carrying is achieved, manual intervention is reduced, and the system is widely applied to the fields such as shipyards and steel mills with complex steel plate management requirements and has high popularization value. And the production efficiency and the operation safety are comprehensively improved.

The invention discloses an electric quantity loss compensation device and method for electric energy meter metering abnormity, and relates to the technical field of electric energy metering, and the method comprises the steps: obtaining an electric energy meter distributed network, carrying out the real-time monitoring, and generating an electric energy meter metering monitoring data set; analyzing the data set by using an abnormal probability identification model, and identifying an abnormal electric energy meter; the metering data of the abnormal electric energy meter is stored in a temporary storage module; and after the abnormal electric energy meter is recovered, the NB-IoT communication module uploads metering temporary data to the cloud database for loss compensation, so that the data integrity and metering accuracy during the abnormal period are ensured. According to the invention, the technical problem of low accuracy and efficiency of electric quantity loss compensation caused by difficulty in real-time monitoring and accurate compensation of metering abnormity of the electric energy meter in a traditional method in the prior art is solved, and the aim of quickly responding and accurately compensating the metering abnormity of the electric energy meter is achieved. And the accuracy and efficiency of power loss compensation are improved.