19results about How to "Real-time capture" patented technology

The invention relates to an identification method, in particular to a photovoltaic panel dust deposition detection and pollutant identification method based on an unmanned aerial vehicle-mounted hyperspectrum. The method comprises the following steps: collecting spectral data; preprocessing the spectral data; extracting effective spectral features; change detection; judging whether pollutants exist or not; carrying out pollutant comparison; and evaluating ash deposition and giving an alarm. According to the invention, through combination of hyperspectral imaging and spectral variation analysis, automatic and non-contact monitoring of the accumulated dust and pollutants on the photovoltaic panel is realized, and tiny spectral change on the surface of the photovoltaic panel can be captured in real time and with high precision, so that the degree and the type of the accumulated dust and pollutants are accurately detected, the detection precision and the real-time performance are improved, and the detection efficiency is improved. And the maintenance cost is effectively reduced, unnecessary cleaning operation is avoided, and maintenance suggestions can be provided in time according to the detection result, so that the energy conversion efficiency of the photovoltaic panel is further improved.

The invention discloses a man-machine collaborative public opinion monitoring method and system based on reinforcement learning. The system comprises a allusion, television and harmonic reference analysis module, a public opinion data processing module, a model recognition module, a public opinion risk assessment module, a public opinion propagation analysis module, a learning optimization module and a deployment configuration module. The public opinion data processing module is used for collecting, cleaning, sorting, storing and preprocessing public opinion related data; the public opinion data storage module is used for managing and storing a large amount of public opinion data; through a reinforcement learning algorithm, the model can adapt to different public opinion environments, through repeated annotation and feedback of public opinions identification experts, the expert ability is solidified, dependence on manual annotation of the experts is reduced, through continuous iterative optimization, the model performance can be continuously improved, the model adapts to changes of the public opinion environments, and the method is suitable for popularization and application. Modern technical means such as deep pre-training, reinforcement learning and reward models are adopted, and innovation and breakthrough of the public opinion monitoring technology are achieved.

A material arranging device is fixed to a workbench and arranged at the output end of a conveying part and comprises a channel assembly, a sorting sensor set and at least one distribution mechanism, and the channel assembly is communicated with the conveying part and extends in the advancing direction of workpieces; the distribution mechanism is fixed above the transmission part and is movably arranged relative to the transmission part; the conveyed workpieces are divided through the channel assembly arranged at the output end of the conveying part, so that the requirement that the multiple overturning parts work at the same time is met; by means of the distributing mechanism arranged above the conveying part, the workpieces in the conveying process can be distributed, then conveying channels and parallel conveying of the multiple workpieces are achieved, parallel operation of multiple operation procedures is achieved, and the efficiency of the machining equipment is remarkably improved.

The present invention provides a DRAM test machine and method based on embedded logic analysis. An embedded logic analyzer is integrated in an ATE test control chip. The embedded logic analyzer is integrated in an ATE test control chip having a main control unit, a test vector generator, and a test result processor. The defects in the prior art are overcome, and the signals of the DRAM chip can be captured and analyzed in real time, so as to help test engineers quickly find problems and improve test efficiency. A plurality of signal channels can be monitored at the same time, so as to improve in-depth analysis capability, and specific trigger conditions can be set to capture key data. The complex timing behaviors of various DRAMs can be decoded and analyzed, so as to save test time. The machine is compactly integrated, does not occupy additional space, reduces costs, and improves benefits. The machine can quickly provide test results and feedback, and is helpful to shorten the test time of the DRAM chip and accelerate the test progress.

The invention provides an online fault early warning method and system based on fluid dynamics of a storage tank floating disc and spectral analysis of a sealing device of the storage tank floating disc, and the method comprises the steps: collecting structure parameters and operation parameters of the storage tank floating disc, and calculating fluid dynamics parameters for the quantitative evaluation of an inclination state, a buoyancy state and a friction state of the storage tank floating disc; collecting a plurality of vibration time domain signals of the sealing device on the floating disc, and converting the vibration time domain signals into frequency domain signals to obtain a frequency spectrum curve; constructing a frequency spectrum feature library based on the frequency spectrum curves in different operation states, comparing the actually monitored frequency spectrum curves with the frequency spectrum feature library, and identifying differentiated frequency spectrum features and corresponding fault types; and performing comprehensive evaluation by combining a quantitative evaluation result of the hydrodynamic parameters and a spectral analysis identification result, thereby realizing intelligent fault early warning of the storage tank floating tray system. The method solves the technical problems that the existing storage tank floating disc operation state monitoring cannot accurately find the early-stage potential fault hidden danger of the floating disc in real time, and floating disc faults and even safety accidents are easily caused.

The invention discloses an event-assisted unmanned aerial vehicle night precise landing system and method. The system comprises a high-frequency dynamic infrared sign array module, an event camera module, a pose resolving module and a landing control module. The system takes a high-frequency dynamic infrared mark array as a positioning reference, an event camera carried on the unmanned aerial vehicle captures an optical event flow with unique time sequence characteristics by accurately controlling the independent flicker frequency of each infrared light source, then the pose of the unmanned aerial vehicle is calculated by using an N-point perspective method, and finally accurate landing is realized by a landing control module. According to the invention, the event camera and the high-frequency dynamic infrared sign array are innovatively combined, the cooperative working mechanism of the event camera and the high-frequency dynamic infrared sign array is utilized, sub-millisecond-level positioning feedback is realized in a complex environment, the limitation of a traditional static optical sign is broken through, the positioning precision and reliability are improved, and the method is suitable for accurate take-off, landing and positioning of the unmanned aerial vehicle at night and in the complex environment.

The invention relates to a water transmission and distribution dynamic scheduling optimization method, which comprises the following steps that a water transmission and distribution test area is established, the water transmission and distribution test area comprises a test branch pipe, a gas pumping unit and a test user side, and two ends of the test branch pipe are respectively connected with a target water plant and the test user side; performing water hammer disturbance effect analysis on the test branch pipe to obtain a water hammer focus of the test branch pipe; air is pumped into the test branch pipe based on the air pumping unit, and vibration parameters and cutoff parameters of the water hammer focus are obtained through strain vibration monitoring and underwater sound cutoff monitoring; establishing an interference factor modulation unit, and performing interference parameter correction on the vibration parameter and the cutoff parameter based on the interference factor modulation unit to obtain a training parameter; circularly executing the previous step to obtain multiple groups of training data, and constructing and training based on the obtained training data to obtain a filtering matching unit; establishing a water transmission and distribution optimization network in the target pipe network area; and managing and optimizing water supply scheduling in the target pipe network domain based on the water transmission and distribution optimization network.

This invention relates to an efficient intelligent material library retrieval method and system based on multimodal vector fusion, applied in the field of information retrieval technology. The method includes: responding to user queries and displaying a result set; monitoring implicit interaction behaviors to generate behavioral sequence features; determining the target modality of the user's intent through an intent determination network; synchronously performing dynamic weight coordination and incremental index updates based on this; fusing behavioral features and queries to generate a refined query vector; and using the new weights to retrieve the main index and incremental index in parallel, then merging and sorting the results before outputting the final result. The system includes functional modules corresponding to the method, such as an initial retrieval module, a behavior monitoring and feature extraction module, and a real-time intent determination module. This invention achieves real-time personalized retrieval and system self-evolution by analyzing implicit behaviors and utilizing synchronous coordination and incremental indexing mechanisms, thereby improving retrieval accuracy and long-term performance.

The invention provides an epilepsy clinical nursing early warning method and system, and relates to the technical field of medical information processing, the epilepsy clinical nursing early warning method comprises the following steps: obtaining multi-modal physiological signal data of an epilepsy patient, the multi-modal physiological signal data comprising electroencephalogram signal data and limb movement signal data; performing principal component analysis processing on the electroencephalogram signal data to obtain dimensionality-reduced electroencephalogram characteristic data; performing time-frequency decomposition on the dimensionality-reduced electroencephalogram characteristic data to obtain energy distribution of a plurality of frequency bands; calculating an information entropy value based on the energy distribution of the plurality of frequency bands; according to the information entropy and the limb movement signal data, the current state of the epileptic is judged through a decision tree model; determining a corresponding hidden danger level according to the current state and generating early warning information; according to the method, electroencephalogram artifacts are eliminated through principal component analysis, the state of the threatened period is recognized before epileptic seizure, and the problems of early warning lag and unstable response in the prior art are solved.

This utility model discloses a functional testing device for a mechanical massage mechanism component, including a worktable, several load units, a mounting mold, a rotation measuring instrument, and a displacement measuring instrument. The worktable includes an upper plate, a lower plate, and several support columns. The upper and lower ends of the support columns are fixedly connected to the upper and lower plates, respectively. The load unit includes a rotating shaft, a mounting plate, a stop block, and several counterweights. The lower end of the rotating shaft passes through the upper plate and is fixedly connected to the mounting plate. The stop block is installed on the rotating shaft above the upper plate, and the counterweights are sleeved on the rotating shaft above the stop block. The mounting mold includes several upper molds and lower molds. The upper mold is installed at the lower end of the mounting plate, and the lower mold is installed on the lower plate. The lower end of the upper mold is provided with an upper mounting groove, and the upper end of the lower mold is provided with a lower mounting groove. An installation rod is rotatably mounted on the upper end of the rotating shaft. A rotation measuring instrument is mounted on the installation rod. A displacement measuring instrument is mounted on the upper plate above the mounting plate.

The invention belongs to the technical field of aircraft cargo compartment smoke detection, and particularly relates to an airborne video monitoring system suitable for aircraft cargo compartment smoke detection. The system comprises a visible light / infrared video monitoring camera, a humidity sensor, an infrared thermal imaging detector, an infrared supplementary lighting device, a video processing computer, a cockpit display, a cockpit control panel and the like. The system has cargo hold video monitoring functions such as cargo hold cargo loading and unloading process monitoring, flight process cargo hold video monitoring and the like, and also can realize cargo hold smoke detection function by analyzing multi-source data, namely visible light / infrared video images, infrared thermal imaging images and humidity sensor data. Compared with a traditional airborne photoelectric smoke detector, the smoke detection response time is effectively shortened, the false alarm rate can be reduced, and the comprehensive performance of a smoke detection system is improved.

The utility model discloses an online automatic screw locking machine belongs to the technical field of automation equipment, and it includes work plane, intelligent electric screwdriver and product positioning system, including Y axis positioning mechanism, it is by Y axis positioning cylinder one drive Y axis positioning long piece, Y axis positioning cylinder two drive Y axis positioning block constitutes, and the product is clamped in cooperation, X axis positioning mechanism, and it is by X axis positioning cylinder drive X axis positioning block and is positioned, still includes pressing material mechanism, and pressing material lifting motor passes through the belt drive pressing material lifting plate lifting, and pressing material stretches out cylinder drive pressing material rod and stretches out and presses the product tightly. The utility model discloses through the cooperative work of X-Y axis self -adaptation positioning mechanism and Z axis pressing material mechanism, and the vision system is matched, has solved the problem that equipment compatibility is poor, and the problem that the replacement adjustment is complicated, can carry out the full -automatic screw locking of quick, accurate to different length width height's product on line, and production efficiency and automation level are high.

The invention discloses an intelligent port and navigation management service integrated platform system. The platform system comprises a port and navigation operation monitoring module, a navigation channel integrated management module, a navigation intelligent transaction module and a port intelligent service module. The port navigation operation monitoring module is used for realizing unified operation monitoring of safety, production, scheduling and operation conditions of subordinate ports, channels, ship locks and logistics parks of the port affair group; the channel comprehensive management module is used for coordinating a channel maintenance project, a channel construction project and a related safety supervision project; the shipping smart transaction is used for optimizing the whole process of shipping transaction by creating a shipping transaction management platform; and the port intelligent service module is used for comprehensively supporting service requests of different business modes and different customer types of each business unit. According to the method, a unified data architecture and a business portal are constructed, cross-link and cross-system data sharing and one-stop operation are supported, and the problem that traditional business systems run independently and are difficult to co-schedule is solved.

This invention discloses a multi-source low-oxygen heat pump device for fruits and vegetables and its usage method, belonging to the field of fruit and vegetable drying technology. The device includes a multi-source gas supply system, a low-oxygen drying chamber, a heat pump temperature and humidity control system, an online weighing system, a material morphology detection system, and an intelligent control system. The multi-source gas supply system injects nitrogen, carbon dioxide, and air. The intelligent control system calculates the drying rate and shrinkage rate based on data from various sensors, dynamically adjusting the gas composition and the temperature and humidity inside the chamber to maintain an oxygen concentration of 1-11%, a temperature of 30-70℃, and a relative humidity of 10-40%. This invention enables precise and coordinated control of the fruit and vegetable drying process, mainly used for drying leafy vegetables and fruits, reducing oxidative deterioration and shrinkage, and improving drying quality.

The invention provides a voltage regulation and control method and device for light-storage-vehicle multi-agent cooperation, and relates to the technical field of power distribution network operation and control. The method comprises the following steps: constructing a secure Markov game model based on a multi-agent collaborative voltage regulation process, the multi-agent comprising a photovoltaic inverter, a battery energy storage system and an electric vehicle cluster in a power distribution network, the secure Markov game model comprises an agent set, a state and observation set, an action set, a secure action set, a secure transfer function and a reward function; constructing a light-storage-vehicle multi-agent decision-making framework, wherein the light-storage-vehicle multi-agent decision-making framework comprises an encoder based on a self-attention mechanism, a strategy network based on encoder driving and an evaluation network based on the encoder; and solving the secure Markov game model by using a light-storage-vehicle multi-agent decision-making architecture to realize a multi-agent collaborative voltage regulation and control strategy. According to the invention, the regulation and control accuracy can be improved.

The present invention discloses a cargo volume calculation method and system based on panoramic video, which belongs to the field of machine vision technology, and specifically includes: obtaining a panoramic video of a warehouse through a panoramic camera, and using deep learning and spatiotemporal context analysis technology to detect and segment the two-dimensional contour of cargo in real time; using a binocular camera and active projection structured light technology to extract cargo depth information, convert it into three-dimensional point cloud data, and construct a high-quality three-dimensional model after radius filtering and optimization processing; using adaptive camera calibration and point cloud registration technology to optimize the three-dimensional model, and accurately calculating the cargo volume through volume integration and physical simulation models; the system also integrates multi-dimensional time series analysis and machine learning models, automatically learns measurement error patterns, and introduces an intelligent error correction mechanism to achieve dynamic adjustment of volume measurement values, thereby improving measurement accuracy and reliability, and enhancing the automation and intelligence level of cargo volume measurement.

The invention discloses an unmanned transportation forklift based on radar, a camera and infrared rays, and particularly relates to the field of unmanned transportation forklifts.The unmanned transportation forklift comprises a main body bin, a control motor is fixedly installed at the top end of the main body bin, and a rotating holder and a camera protection device installed on the outer surface of the top end of the rotating holder are installed at the top end of the control motor; and a miniature high-definition camera is fixedly mounted on the outer surface of the front end of the camera protection device. According to the automatic forklift, under different external influence factors, the center position of the tray hole can be predicted more accurately, rapidly and efficiently, corresponding cooperation is carried out, and rapid cargo transportation is achieved. Meanwhile, an automatic driving system is arranged in the system in a matched mode, and after an external instruction of goods transportation is received, a route can be automatically planned to reach a designated position to work. The labor cost is greatly reduced, and meanwhile the working efficiency of unmanned warehouse logistics is improved.

The invention provides a three-dimensional frequency spectrum prediction method, system and device based on a multi-scale map convolutional network and a medium, and belongs to the technical field of frequency spectrum prediction.The method comprises the steps that receiving power data of multiple frequency points are continuously collected with the resolution of preset duration, three-dimensional tensor data are formed, and a feature matrix is constructed; a learnable parameter matrix of a preset dimension is adopted to transform the feature matrix, a self-adaptive threshold value is set according to the median of scores of all nodes, and a weighted adjacency matrix is generated; performing first-order graph convolution operation and second-order graph convolution operation on the weighted adjacency matrix, and performing feature transformation by adopting a multi-dimensional learnable weight matrix to form multi-dimensional fusion features; and expanding the multi-dimensional fusion features according to a time sequence, constructing a gating mechanism through element multiplication and residual connection, and outputting a prediction result through a linear transformation layer. The accuracy of spectrum prediction is improved, and the model can output a more accurate prediction result when processing spectrum data of a long time sequence.

The invention belongs to the field of cable installation, and discloses an auxiliary assembly system and method for a high-voltage cable accessory sleeving process, the system can obtain an on-site cable image in real time through an image acquisition device, and terminal equipment compares the on-site cable image with preset cable pose data to determine the position of the cable accessory. According to the method, construction personnel are intelligently guided to carry out subsequent operation of each step, so that accurate sleeving step guidance is provided, the problem that construction is frequently paused to confirm a sleeving sequence in a traditional mode is avoided, meanwhile, the requirement for the skill level of the construction personnel is lowered, and construction errors caused by human factors are reduced; the next step is output in an image or voice form through the step guiding equipment, so that the construction process is more intuitive and understandable, an operator can orderly carry out each step of operation according to the image or voice step presented by the step guiding equipment, and the construction efficiency and the construction quality are greatly improved; therefore, the power supply reliability of the high-voltage cable line and the stable operation of the whole system are improved.