10results about How to "Implement data storage" patented technology

The invention provides a high-throughput multi-view automatic positioning light sheet microscopic imaging method. The method comprises the following steps: automatically identifying the size of a sample, presetting parameters, and carrying out preliminary scanning; splicing imaging data in real time; globally and automatically positioning a sample area; planning a shooting path; and multi-target area high-throughput shooting parameters are optimized. A microscope large-view high-flux rapid imaging method based on a real-time image automatic splicing and positioning technology is combined with a real-time splicing function of shot imaging data and an automatic positioning function of a sample position in an image to rapidly search specific position area information of a sample; and shooting imaging and data storage of the experimental sample are realized by automatically optimizing shooting configuration parameters. The invention further provides a high-throughput multi-view automatic positioning light sheet microscopic imaging system adopting the method, and shooting imaging and data processing can be rapidly and accurately carried out on a target large sample.

The hydropower station perimeter intrusion detection system comprises a radar monitoring module, a video monitoring module, a data processing module, a communication module, a control module, a power supply module, an early warning module, a data storage module and a compatible integration module. The radar monitoring module adopts laser radar equipment, and targets such as intruded foreign personnel in the surrounding environment are obtained by transmitting radar waves to the surrounding environment of the hydropower station and receiving and reflecting the radar waves. The accuracy and reliability of the hydropower station perimeter intrusion detection system are improved by adopting the Leiyu fusion technology and combining various technical means, so that the perimeter safety of the hydropower station is guaranteed. Meanwhile, the system has the advantages of real-time performance and reliability, the system can be compatibly integrated to a hydropower station electronic precaution system platform, new technical means and support are provided for hydropower station safety management, and the system has great significance in improving the safety level and accuracy of a hydropower station perimeter intrusion detection system.

The invention provides a shield tunneling machine fault prediction method based on cloud edge-end cooperation, and belongs to the technical field of shield tunneling, and the method comprises the following steps: S1, a sensor as end equipment collects the data of shield equipment in real time, and uploads the collected data to edge equipment; s2, after the edge device carries out data fusion, the fused data are uploaded to the cloud; s3, using the uploaded fused data to train a fault recognition model at the cloud, and then issuing the generated fault recognition model to an edge device; according to the method, data services are reasonably divided through edge cloud collaborative operation, and a part of functions are distributed to edge equipment, so that real-time data services are provided for an opposite end, real-time identification is divided to the edge, the data transmission distance is shortened, faults can be identified more quickly, and the data transmission efficiency is improved through a self-adaptive data acquisition method. The situation that too much redundant information is collected is avoided, waste of storage resources is reduced, and meanwhile more useful information can be collected.

The utility model discloses a remote reclosing control device of miniature circuit breaker with energy metering remote transmission, including casing, display screen, motor, output shaft, motor drive gear, variable speed gear group, output drive gear and circuit board, casing is fixed through bolt connection on the lateral wall of the shell of miniature circuit breaker, and the outer end portion of output shaft passes through the lateral wall of casing and miniature circuit breaker, and after, with the rotating shaft fixed connection of the opening and closing mechanism in the chamber of miniature circuit breaker, the motor drive gear on motor rotating shaft is connected with the output drive gear of output shaft through the meshing transmission of variable speed gear group, be equipped with MCU central processing unit, clock module, AD sampling module, 4G communication module, power module, storage module, motor drive module and display unit on the circuit board, and the power cord of power module is connected with the wiring terminal of miniature circuit breaker, and AD sampling module is connected with miniature circuit breaker through wire, and the working state signal of miniature circuit breaker is gathered.

The invention discloses a rotor unmanned aerial vehicle cluster real-time simulation method. According to the technology, a regional sub-cluster edge distributed interaction rule is designed, and the problems of overlarge simulation communication pressure and cluster scale amplification are solved; designing a cluster grouping hardware simulation environment and a software function according to a target simulation scene requirement; a clock synchronization method for master clock synchronization and sub-clock interval verification is provided, and the clock synchronization problem in the cluster simulation process is solved. Through a database storage mechanism in which a cache array and an inline array are fused, data partition management and data interaction of multiple unmanned aerial vehicles are realized; and a sub-task operation mechanism is planned according to frequencies and execution points, so that multi-sub-task cooperative operation is realized, and the requirement of large-scale cluster unmanned aerial vehicle simulation is met.

The invention belongs to the technical field of iron core grounding current monitoring of transformers, and particularly relates to an iron core grounding current recording method based on precise time synchronization. Comprising the following steps: collecting a current signal through an iron core and a clamp grounding current sensor; time deviation caused by RTC is calibrated continuously in the collection process; performing cyclic sampling and calculation on an output signal of the sensor, sending total current and multiple harmonic waves obtained by Fourier calculation to a display end of an upper computer, and starting fault recording when the value of the total current meets a fault judgment threshold value; when it is judged that a fault occurs, an accurate time mark is provided through an accurate time synchronization function, reserved historical data and collected real-time data are spliced into a wave recording graph during the fault period, and the wave recording graph is backed up and transmitted to a display end of an upper computer to be stored and displayed. According to the invention, some fault phenomena which are short in duration and rapid in generation and disappearance can be effectively monitored, and the change trend of iron core and clamp current when faults occur can be effectively monitored.

The invention relates to the technical field of automatic testing, in particular to an automatic testing method and system based on artificial intelligence, and the method comprises the steps: collecting to-be-tested data of a to-be-tested system connected with a plurality of to-be-tested interfaces; through the signal conditioning module and the filtering gating module, performance indexes such as the signal-to-noise ratio, the spurious-free dynamic range and the common-mode rejection ratio of signals to be detected are improved, high-precision collection is achieved, and multi-channel parallel sampling is achieved through the ADC collection module. Input signal gating and power supply on-off control of tested equipment are realized through the gating switch control module, so that tested data can safely and quickly enter a monitoring state and are uploaded to the FPGA core control module, real-time data uploading and acquisition are completed, control and data storage of multiple pieces of test data are realized, and the data are combined and sent to the automatic test module. And automatic testing is carried out. Automatic test control of artificial intelligence is realized, and the efficiency of automatic test is improved.

The invention belongs to the technical field of environmental protection, and particularly relates to an aluminum product machining waste gas recovery device to solve the technical problem that the exhaust speed cannot be adjusted, the aluminum product machining waste gas recovery device comprises a power assembly, the power assembly comprises an execution motor, a clutch sliding rod, a second clutch disc and a clutch push spring, and an output shaft of the execution motor is in key connection with the clutch sliding rod; a second clutch disc is installed on the clutch sliding rod in a sliding mode, a clutch push spring is arranged between the second clutch disc and the clutch sliding rod, and the second clutch disc is in meshing transmission with the first clutch disc under the action of the clutch push spring. The first clutch disc, the clutch sliding rod and the execution motor are connected with the exhaust pump assembly at the same time, the middle-end rotating column and the adjusting disc are relatively rotated, then through relative sliding between the second waist groove opening and the first sliding column, the distance of the circulating blades sliding out of the middle-end rotating wheel is changed, and then the exhaust speed is adjusted.

The invention provides an intelligent grounding wire device, which is used for automatically monitoring a grounding wire, and comprises a grounding wire unit, a grounding unit and a control unit, the current sensor is connected with the ground wire unit and used for measuring current flowing through the ground wire unit; and the pulse generation unit is connected with the grounding wire unit and is used for periodically providing a pulse signal. The current sensor is arranged on the grounding wire unit, so that whether electric leakage occurs in the electrical equipment connected with the grounding wire unit or not can be detected; in addition, by arranging the pulse generation unit, whether the grounding wire works normally or not can be automatically judged. Therefore, the self-monitoring of the grounding wire and the automatic leakage monitoring of the electrical equipment are realized, and the labor cost is saved.

The invention discloses a multi-mode hybrid memristor neural network edge computing terminal system and method, and belongs to the technical field of artificial intelligence. According to the system, the defects of existing edge calculation in the aspects of high energy efficiency and real-time multi-modal data processing are overcome, fusion of storage and calculation is achieved through the memristor, and the bottleneck generated by separation of storage and calculation in a traditional calculation structure is reduced; fusion and self-adaptive learning of multi-modal data are realized by utilizing the self-adaptive conductivity characteristic and the Hertz plasticity of the bionic memristor neural network structure, and the method adapts to a complex and changeable application environment; the core module can directly input a voltage analog quantity matrix collected by the multi-modal sensor module into the memristor neural network in the edge calculation module through the servo light source training module, and then fusion and classification are carried out on multi-modal sensor data through the memristor neural networks of different dimensions, and a reliable decision is generated. The method is suitable for intelligent edge applications with high efficiency and low power consumption.