413results about How to "Improve processing speed" patented technology

The invention discloses a self-adaptive power grid state court intelligent fusion terminal and a control method thereof, relates to the technical field of intelligent power grids, and solves the defects that an existing fusion terminal is insufficient in self-adaptive capability and limited in data processing and analysis capability. Learning power grid state change in real time through a deep power grid dynamic control algorithm and a prediction analysis engine combining LSTM and random forest, and autonomously adjusting a control strategy; the edge calculation and distributed processing module is utilized, so that the data processing flow is optimized, and the data processing speed and efficiency are greatly improved; the application of time sequence analysis and a machine learning model further excavates and understands a complex data mode; the resource configuration efficiency is improved through an intelligent scheduling algorithm, and a cross-layer coordination mechanism is established through a distributed coordination algorithm, so that rapid issuing and feedback collection of a control instruction are ensured; according to the invention, the intelligent degree of the existing fusion terminal is greatly improved.

The invention provides a central air-conditioning system real-time fault prediction method and system based on digital twinning, and the method comprises the steps: deploying various types of sensors for multi-dimensional detection, and collecting the data of the sensors; edge computing nodes are deployed around the central air conditioning unit; a digital twinborn model based on the central air conditioning unit is constructed according to the preprocessed data, a dynamic view of key performance indexes is provided, and the state of the central air conditioning unit is mapped and simulated in real time; designing a fault prediction model, and predicting and identifying faults; deploying the fault prediction model at an edge computing node and operating the fault prediction model, and performing real-time fault monitoring and diagnosis; when a fault is found, the AI-drive maintains decision support, and automatically adjusts a fault prediction model parameter or arranges a maintenance strategy; and constructing a learning loop based on performance feedback, and optimizing a fault prediction model and a maintenance strategy. Quantum calculation, the digital twinning technology and edge calculation are fused, and the operation efficiency and reliability of the central air conditioning system are remarkably improved.

The invention discloses a robot pose estimation method based on laser point cloud and visual SLAM, and relates to the technical field of robot sensing and positioning, and the method comprises the steps: in a data collection and integration link, installing a specific camera and a radar to collect and compress data; a data preprocessing and feature strengthening stage: processing the image and the point cloud to improve the quality and extract the features; a cross-modal network is constructed through feature fusion and accurate matching, and a special matching mode is adopted; space-time calibration and coordinate unification are realized by means of a high-precision circuit; multi-modal fusion and reinforcement learning are applied to loop detection and intelligent optimization; correcting filtering and visualizing uncertainty by combining pose smoothing and intelligent output with a prediction model; according to the method, the pose estimation precision, reliability and environmental adaptability of the robot are effectively improved, resource utilization is optimized, the pose uncertainty is visually evaluated, and the overall performance and the intelligent level of the robot are improved.

The invention relates to the technical field of disease and pest identification and control, in particular to a disease and pest identification and control early warning system and method, and the system comprises a data collection module, a polarization data analysis module, an image super-resolution processing module, a feature extraction module, a disease prediction module and a decision support module. According to the method, early recognition and accurate prediction of plant diseases and insect pests are achieved by integrating capture and analysis of spectrum polarization data, image super-resolution processing and time sequence analysis, fine structural changes of plant leaves are accurately captured through the polarized light technology, fine lesion features can be revealed by deeply analyzing the polarization data, and the accuracy of the plant diseases and insect pests is improved. The local spectrum enhancement technology further refines the image quality, it is ensured that the change of the cellular level can be accurately recognized, deep learning analysis is carried out in combination with environmental data, the disease development trend can be effectively predicted, and the processing speed and accuracy are improved.

The invention discloses a long time sequence information prediction method based on a multi-scale double-source fusion network model, time domain and frequency domain features are modeled at the same time, the ability to understand a complex time sequence is enhanced, an efficient multi-scale attention module of cross-space learning can capture short-term and long-term dependency relationships at the same time, and the prediction accuracy is improved. The modeling capability of different time scale information is improved, dynamic weighted fusion of time domain and frequency domain features is realized by a gating mechanism, and the flexibility and robustness of the model are improved. And through standardization and size projection, feature deviation and memory occupation are reduced, model convergence is accelerated, and the overall memory demand is reduced. The efficient multi-scale attention module accurately captures features, weakens noise and abnormal value influences, and reduces unnecessary calculation and memory consumption. The gating mechanism dynamically adjusts the feature weight, preferentially processes key information, and reduces the memory demand.

The invention relates to the technical field of data supervision, in particular to a data security protection supervision system, which comprises an access monitoring module, a behavior abnormity monitoring module, a security configuration module and a data risk management module, and is characterized in that based on user access behavior data, access frequency and security level information are collected, and user behavior characteristics are automatically extracted; an access control snapshot is obtained. According to the method, through dynamic permission configuration and real-time abnormal activity monitoring, data access safety is remarkably improved, user behavior characteristics are automatically extracted, behavior deviation is analyzed, quick response to potential risks is ensured, and through the continuously-updated safety strategy and risk assessment, the safety of data access is greatly improved. The security measures are allowed to timely adapt to the constantly changing threat environment, and through detailed risk management, the processing speed and accuracy are improved, so that the data supervision is more efficient, the possibility of data leakage and abuse is reduced, and the flexibility and reliability of the system in the aspect of protecting data privacy and integrity are ensured.

The invention discloses a power grid fault online identification system and method based on big data, and relates to the technical field of power systems, and the method comprises the steps: collecting multi-source data of a power grid system through a sensor; data filtering is performed through a hierarchical storage strategy, a data lake is constructed in combination with multi-dimensional data indexes, and multi-source data is stored in a classified manner; aggregating and converting data in a data lake by adopting a real-time stream processing framework, and extracting high-dimensional features related to a fault by combining wavelet transform with principal component analysis; based on the high-dimensional features, identifying the real-time state of the power grid by using a graph neural network in combination with a deep learning model; and according to the identification result of the real-time state, combining a power grid topological structure, and carrying out fault positioning through a time difference method and a graph theory algorithm. The power grid fault on-line identification system based on big data provided by the invention can efficiently manage and store a large amount of multi-source data in a power grid, and improves the data processing and access speed.

The invention relates to the technical field of financial data processing, in particular to a data processing method and system based on financial information bills. The data processing method comprises the following steps: acquiring multi-modal financial information bill data; and performing bill modal decomposition on the multi-modal financial information bill data to generate financial information bill modal decomposition data. Bond information price income prediction needs a large amount of financial data, such as market interest rate, bond expiration date, face interest rate and the like, the data are similar to the data form of bill modal decomposition, and a more accurate model can be obtained through standardization and feature extraction of multi-modal data. Therefore, valuable input is provided for bond price and income prediction. According to the invention, through multi-modal data fusion, counterfeited feature comparison modeling, abnormal bill clustering analysis and dynamic risk assessment, the security and accuracy of financial bill identification are improved.

The invention relates to the technical field of high polymer materials and preparation thereof, and discloses a wet anti-slip bionic friction pad on a glass surface, which is inspired by a micro-nano structure of toe pads of organisms such as tree frogs and long-horned grasshoppers with wet friction increasing characteristics, and a bulge array is added on the surface of a high-friction material, so that the friction coefficient of the friction pad is increased; the microstructure arrays can discharge a water film on the surface of the friction pad under the capillary action in a wet environment, and the effective contact area between solids is increased, so that the friction pad and a friction surface are always kept in a dry friction state, and stable friction force is ensured. The friction pad comprises a connecting layer, a supporting layer and a tail end protruding straight column array, a tail end contact layer is in a hexagonal straight column shape, the diameter of an inscribed circle of a hexagonal micro-column structure ranges from 5 micrometers to 5000 micrometers, column bodies are densely arranged in a hexagonal mode, the height of the column bodies ranges from 10 micrometers to 1500 micrometers, the tail ends of the column bodies are planes, the interval between every two column bodies ranges from 2 micrometers to 600 micrometers, and tight drainage grooves are formed.

The invention relates to a television box intelligent interaction control unit image processing method and device. The method comprises the following steps: carrying out feature analysis on an input video stream of the television box to obtain an enhanced video stream; the method comprises the following steps: collecting visual and voice interaction information of a user based on an intelligent interaction control unit, and inputting the visual and voice interaction information into a double-branch Transform model for multi-modal information fusion to obtain a fusion feature vector; performing conjoint analysis to obtain a user interaction intention and an interaction response strategy; performing local contrast enhancement and motion compensation to obtain a high-quality video frame sequence; and performing scene adaptive color space mapping and dynamic color temperature adjustment on the high-quality video frame sequence according to the environment light information acquired in real time and the pre-stored color characteristics of the display device to obtain an output video stream. According to the implementation of the method, limited computing resources can be fully utilized, efficient video processing and natural man-machine interaction are achieved, and meanwhile the display effect is dynamically optimized according to environmental changes.

The invention relates to the field of intelligent carbon reserve estimation, and particularly discloses a wetland carbon reserve estimation method and system based on a remote sensing technology. And performing local area segmentation and image semantic feature association on the remote sensing image of the wetland area by using an image analysis and processing algorithm based on deep learning so as to intelligently obtain the vegetation type and quantity of each area, and obtaining a carbon reserve estimated value of the wetland based on the vegetation type and quantity of each area. In this way, the remote sensing technology can be utilized to cover a wide-range wetland area. Meanwhile, the deep learning algorithm can extract accurate features from the remote sensing image, the automatic image processing flow reduces manual intervention, the efficiency and processing speed of wetland carbon reserve estimation are improved, and the accuracy of carbon reserve estimation is also improved.

The invention relates to a communication device compatible with a hybrid network of Ethernet and FC-AE-1553, belongs to the technical field of hybrid network communication of FC-AE-1553 and Ethernet, and solves the problems of complex structure, large size and high cost of the FC-AE-1553 and Ethernet communication network in the prior art. The communication device comprises an Ethernet interface conversion module, an Ethernet data exchange module, a protocol processing module, an FC data exchange module and an FC transceiver module. The Ethernet interface conversion module receives an Ethernet data frame sent by an Ethernet node and forwards the Ethernet data frame to the Ethernet data exchange module or the protocol processing module; the FC transceiver module receives an FC-AE-1553 frame sent by an FC-AE-1553 node, and forwards the FC-AE-1553 frame to the FC data exchange module; the FC data exchange module forwards the FC-AE-1553 frame to the FC transceiver module or the protocol processing module; and the protocol processing module is used for realizing mutual conversion between an Ethernet frame and an FC-AE-1553 frame and sending the Ethernet frame and the FC-AE-1553 frame to an Ethernet node. The communication network of the Ethernet and the FC-AE-1553 is simple in structure, small in occupied volume and low in cost.

The invention provides a keratoconus image classification method based on an improved deep learning self-attention mechanism, and the method comprises the steps: obtaining a four-refraction report graph through a three-dimensional anterior segment analysis and diagnosis system, carrying out the image preprocessing of the four-refraction report graph through employing a method for extracting a region of interest, and obtaining a four-refraction report graph data set; constructing a network model based on a multi-directional axis attention mechanism, and inputting the four-refraction report graph data set into the constructed network model based on the multi-directional axis attention mechanism for training to obtain a trained network model based on the multi-directional axis attention mechanism; and carrying out image preprocessing and data enhancement on the four-refraction report graph to be processed, and inputting the four-refraction report graph to be processed into the trained network model based on the multi-directional axis attention mechanism to carry out cornea conus classification. According to the method, unique directional feature information in the corneal topographic map is efficiently captured, the information of the whole image can be comprehensively considered, and the diagnosis accuracy is improved.

The invention relates to the technical field of material transfer, in particular to a warehouse material intelligent carrying system and method.The warehouse material intelligent carrying system comprises an intelligent dispatching module, an automatic carrying device and a real-time monitoring module; the real-time monitoring module is responsible for collecting real-time data in the carrying process, wherein the real-time data comprise the running state of a conveying belt, the material type and workshop environment parameters. The intelligent scheduling module is responsible for sending a carrying instruction, planning a material carrying route and a scheduling strategy, planning an optimal material carrying route by utilizing an optimization algorithm, and automatically sending the carrying instruction to the automatic carrying device based on a planning result; the automatic carrying device is composed of a conveying belt network, executes a material carrying task according to an instruction of the intelligent dispatching module and is used for carrying materials in a workshop. According to the method, it is ensured that the material carrying path is optimized under various conditions, so that the carrying time is effectively shortened, the cost is reduced, and the risk in the transportation process is minimized.

The invention discloses a bolt pre-tightening force testing method based on an electromagnetic ultrasonic pre-tightening force measuring system, and the method comprises the steps: collecting the waveform data of transverse and longitudinal waves generated by an electromagnetic ultrasonic probe, and only processing the current frame echo data and historical accumulated data each time through a data averaging algorithm. The storage space only needs to store the historical accumulated data received by the electromagnetic ultrasonic probe once, so that the processing speed and the signal-to-noise ratio of the data are improved; and automatically identifying and calculating the wave peak sound time enveloped by the transverse and longitudinal wave echoes of the bolt through a peak value algorithm, fitting to obtain a calibration curve corresponding to the bolt of the model specification through the ratio of the transverse and longitudinal wave sound time to the bolt pre-tightening force corresponding to the time period, and measuring the pre-tightening force of other bolts of the same model specification by using the calibration curve. The method is easy and convenient to operate, effective transverse waves and longitudinal waves can be excited at the same time, and measurement precision and accuracy are high.

The invention discloses a digital audio watermark processing method and device, equipment and a storage medium, and belongs to the technical field of artificial intelligence. The method comprises the following steps: receiving a watermark adding instruction, and carrying out Fourier transform on original host voice to obtain an audio signal; identifying a watermark information adding bit in the audio signal through the audio watermark model, and embedding a watermark message in the watermark information adding bit; the interfering audio signal and the audio signal carrying the watermark message are combined. Receiving the message extraction signal, and separating an interference audio signal in the combined audio signal; a watermark information adding bit in the audio signal is identified, and a watermark message is extracted from the watermark information adding bit. The invention also relates to the technical field of block chains, and the host voice is stored on a block chain network. According to the method, the watermark information adding position is automatically identified through the audio watermark model, so that the watermark information is added and extracted, the dependence on expert knowledge is remarkably reduced, and the watermark processing speed and efficiency are improved.

The invention provides a measurement method and device based on an unmanned aerial vehicle and edge computing equipment. The measurement method comprises the steps of controlling the unmanned aerial vehicle to cruise a distribution wire according to a preset route; the unmanned aerial vehicle is controlled to carry out image acquisition on the power distribution wire through a camera in the cruising process to obtain a line image; the unmanned aerial vehicle is controlled to obtain spatial position coordinates of at least three key points on the power distribution wire and spatial position coordinates of base poles located at the two ends of the at least three key points in the cruising process; and preprocessing the line image to obtain a processed image. The technical problem solved by the invention is that sag measurement of a power distribution wire generally depends on a traditional manual measurement method in the power industry. Although the method meets the basic measurement requirement to a certain extent, the inherent limitation of the method is increasingly prominent, and the method becomes an important bottleneck restricting the improvement of the power operation and maintenance efficiency and precision.

The invention discloses a landing typhoon residual vortex detection method based on YOLOv5, and the method comprises the steps: employing ERA5 data and landing typhoon optimal path data, screening a convolutional neural network YOLOv5 model, carrying out the screening of initial data based on a potential height field, taking the screened data as a model sample set, building a typhoon residual vortex detection model, and achieving the detection of weak vortexes. In the life stage after the landing typhoon is weakened into tropical low-voltage shutdown, the existence and development conditions of the landing typhoon residual vortex are accurately detected and monitored, accurate reference is provided for meteorological early warning and disaster management, and the accuracy rate of a test set is as high as 70.08%.

The invention discloses a surveying and mapping geographic information data acquisition system based on cloud computing, and relates to the technical field of natural resource management, a data acquisition module is used for acquiring observation point height G, observation point latitude W and adjacent point data, a data processing module is used for operating a data processing algorithm and outputting evaluation data of surveying and mapping geographic information, and the surveying and mapping geographic information is acquired based on the evaluation data. The data processing module is used for processing the real elevation of the ground and deeply analyzing the processed data, the data visual module is used for displaying a data acquisition result and an evaluation report, the system is optimized and adjusted, and the data processing module comprises a unit for reflecting the corrected real elevation of the ground, a unit for comprehensively evaluating the horizontal position precision and a unit for comprehensively evaluating the geographic information data quality. The surveying and mapping geographic information data acquisition system has the beneficial effects of improving the data precision, optimizing the data processing flow, enhancing the system adaptability and improving the decision support capability, and the effects jointly promote the intelligent and modern development of the surveying and mapping geographic information data acquisition system.

The invention discloses an information abstract method and system based on large language model distillation. The information abstract method based on large language model distillation comprises the following steps: acquiring information text data; performing knowledge annotation on the information text data by using a large language model to form an information pre-abstract, prompting keywords of the information pre-abstract by using a lightweight language model, and performing distillation by using a preset template to form an information abstract, the lightweight language model is subjected to gradient updating through the difference between the information abstract and the information pre-abstract; and outputting the information abstract. According to the method, the processing speed and efficiency of extracting the intelligence abstract are well improved, the high-quality intelligence abstract can be obtained under the condition of low cost, and the requirements of various application scenes for efficient intelligence analysis are met.

The invention discloses an image processing method and device for a remote driving vehicle, and the method comprises the following steps: correcting a to-be-spliced image, and restoring the real scene information; projecting the corrected image to a cylindrical surface with the same focal length; feature point matching is carried out by using an SIFT algorithm, a coordinate conversion relation between the two images is calculated according to a matching result, and the two images are projected into the same coordinate system based on the coordinate conversion relation; brightness error correction is carried out on the image, an energy function used for searching for a suture line is optimized, the optimal suture line is obtained in combination with a dynamic programming algorithm, and the processing delay of the dynamic programming algorithm is optimized; carrying out image splicing; and according to the brightness difference of the image on the suture line, adjusting the splicing result image, and eliminating the suture line. According to the technical scheme disclosed by the invention, splicing seams can be effectively eliminated, the color consistency is ensured, image ghosting is thoroughly eradicated, the processing speed and the image quality of multi-view visual splicing are improved, and reliable visual support is provided for remote driving.

The invention relates to the technical field of adjusting valve machining, and particularly discloses an adjusting valve part cutting machining device and a machining method thereof.The adjusting valve part cutting machining device comprises a feeding platform capable of loading and controlling a valve rod to move and a fixing frame, and is characterized in that a fixing ring is fixedly installed in the fixing frame, and a plurality of sliding grooves are formed in the side wall of the fixing ring; a sliding block capable of sliding is arranged in each sliding groove, and the sliding blocks slide centripetally or centrifugally. The adjustable cutters are arranged to cut the outer wall of the valve rod, so that stress between the outer wall of the valve rod and the cutters can be shared by the cutters, abrasion of cutter heads of the cutters is reduced, the service life of the cutters is prolonged, heat generated by friction between a single cutter and the outer wall of the valve rod can be reduced, and the service life of the cutters is prolonged. Thermal deformation of the tool bit caused by overheating of the tool bit due to long-time high-temperature influence can be avoided, the machining speed of the machine tool on the valve rod can be increased, and the cutting precision of the machine tool on the valve rod can be improved.

The invention relates to the technical field of motor driving, and discloses a universal integrated motor driving device, which comprises an optocoupler isolation module, an integrated logic module, a power MOS (Metal Oxide Semiconductor) tube driving module, a power module and a current-limiting protection module, the optical coupler isolation module is connected with the integrated logic module; the integrated logic module is connected with the power MOS tube driving module; the power MOS tube driving module is connected with the power module; the power module is connected with a load motor; and the current-limiting protection module is connected with the power module. According to the invention, the optical coupler isolation module, the logic processing module, the MOS tube driving module and the current-limiting protection module are modularly integrated, so that the circuit design is simplified, and the reliability and maintainability of the system are improved.

The invention provides a remote sensing image slicing system and method based on an FPGA (Field Programmable Gate Array). The system comprises a CPU (Central Processing Unit) module and an FPGA module, the CPU module is used for decoding an input original image and transmitting decoded image data and a corresponding first configuration parameter to the FPGA module; the FPGA module comprises an image slicing module and a memory module; the image slicing module is used for segmenting the original image into a plurality of slice images based on the first configuration parameter, and the memory module is used for storing the original image and the generated slice images. A CPU module and an FPGA module are combined, a plurality of image slices can be processed at the same time by means of the parallel computing capacity of an FPGA, and the processing speed and efficiency are improved; and the method has relatively low processing delay and flexibility.

The invention relates to the technical field of electron energy measurement, and discloses an electron spectrometer and an electron energy spectrum measurement method and system.The electron spectrometer comprises a magnetic deflection unit used for receiving an incident to-be-measured electron beam, generating a magnetic field and applying the magnetic field to all to-be-measured electrons in the to-be-measured electron beam; the scintillator fluorescent screen is arranged at the downstream of the magnetic deflection unit and used for receiving the deflected electrons to be detected, and the electrons bombard the scintillator fluorescent screen and generate light spots; the optical acquisition unit is used for acquiring a light spot image on the scintillator fluorescent screen; and the signal processing unit is used for processing the light spot image so as to identify the spatial position information of the light spot in the light spot image and convert the spatial position information into electronic energy data. The method has the beneficial effects that the unification of high resolution and high measurement efficiency is realized, and the problem of signal accumulation under a high counting rate of a traditional direct measurement method and the inherent defect of low efficiency of a scanning type magnetic spectrometer are overcome.

The invention relates to a GPU (Graphics Processing Unit) image striping processing method and device and a storage medium, and the method comprises the steps: initializing striping collection video image frames, and pre-dividing each video image frame into at least two pieces of strip data which are connected in sequence; starting striping to collect the video image frame, storing one stripe of the video image frame into a DMA (Direct Memory Access) buffer area by a graphics processor after collecting data of one stripe of the video image frame, and updating a stripe index; a memory mapping address is obtained through a DMA buffer area, and an application program directly accesses and processes video image frame data through the memory mapping address and accesses each video image frame through memory mapping; and if the stripe data of the video image frame is readable, copying the stripe data through OpenCL and sending the stripe data to the encoder with the corresponding serial number for encoding processing. According to the GPU image striping processing method, continuous acquisition and efficient processing of image data can be ensured, and meanwhile, the stability of image quality and the real-time performance of processing are ensured.

According to the certificate picture sensitive information shielding coding processing method, system and device and the medium, based on the Baidu OCR character recognition technology, key information in a certificate can be automatically recognized, the accuracy and speed of information recognition are greatly improved, and compared with a traditional method, the processing efficiency is greatly improved; by analyzing and positioning the position of the extracted privacy information, automatic code printing processing can be accurately carried out on privacy contents such as photos and certificate numbers on certificates, privacy data security of users is effectively protected, and errors and information leakage risks possibly brought by manual operation are avoided; according to the method, the Internet development technology is combined, and corresponding program templates can be intelligently called for processing according to different types of certificate information uploaded by a user, so that automatic coding for privacy information of different certificate types becomes possible, and the processing flexibility and applicability are greatly improved; the method has the advantages of high identification efficiency, good safety, flexible processing and wide applicability.

The invention discloses an audio frame insertion method and device, equipment, a medium and a program product. The method comprises the steps of obtaining audio data; wherein the audio data comprises a plurality of audio frames; recognizing lost audio frame information based on the multiple audio frames through a preset audio frame recognition model; wherein the lost audio frame information comprises the position and the number of audio frames; predicting a to-be-inserted audio frame based on the multi-frame audio frame and the lost audio frame information through a preset prediction model; and performing frame insertion processing on the audio frame to be inserted according to the lost audio frame information. By adopting the method provided by the embodiment of the invention, the frame insertion processing speed and precision can be improved, and the problem of sound and picture desynchrony during video playing is effectively solved.

The invention relates to the technical field of chip verification, in particular to a cross-platform test scene reproduction method, which comprises the following steps of: S1, executing simulation of chip design on a first verification platform, and capturing and recording all related signal waveform data in a simulation process through a simulation tool; s2, converting the waveform data captured in the S1 into a text format by using a waveform conversion tool, wherein the text format comprises an input signal required by a second platform; s3, the second verification platform reads the text content converted in the step S2, state data of each signal at different time points are extracted from the text content, and an excitation signal sequence suitable for the second verification platform is generated according to the extracted information; s4, loading the excitation signal generated in the step S3 to an RTL model of a second verification platform; and S5, operating simulation on the second verification platform by using the excitation signal set in the step S4. According to the method, the flexibility, efficiency and reliability of chip verification are remarkably improved.