23 results about "Data continuity" patented technology

The application discloses an axial projection wind speed measurement method and system of a wind turbine unit, relates to the field of laser radars, and alleviates the problems of insufficient data continuity, incapability of providing stable wind speed data, easy interference of blade false signal and inaccurate measurement of the existing axial projection wind speed measurement technology.A kind of axial projection wind speed measurement method obtains multiple sets of measurement data, for each distance gate number, traverses each kind of beam number, obtains effective radial wind speed value and radial wind speed state bit, and then obtains axial projection wind speed.The method disclosed by the application is suitable for the field of wind turbine unit control, and the axial projection wind speed measurement system of the wind turbine unit disclosed by the application is suitable for being embedded in existing wind turbine unit control equipment.

This utility model discloses a data processing board for trackside equipment, belonging to the technical field of subway trackside equipment. It includes a data processing module, a soft-start output module, a power-down voltage monitoring module, an RTC real-time clock module with a first energy storage capacitor, a power supply module with a second energy storage capacitor, and a data interface module. The data processing module is electrically connected to the other modules. The power supply module provides the operating voltage to the board, and its second energy storage capacitor temporarily supplies power to the data processing module during brief external power outages to record the voltage status data at the moment of power failure. The first energy storage capacitor of the RTC real-time clock module maintains clock operation for a preset duration after power failure. This utility model solves the problems of easy data loss and clock failure during power failures in traditional boards. It features high structural integration, stable operation, and accurate recording of power-down fault conditions, meeting the data continuity requirements of subway trackside equipment.

The invention discloses an electromagnetic shielding device for simulating a climatic environment, which is characterized in that an electromagnetic shielding structure, a temperature adjusting module and a humidity adjusting module are integrated in the same shell to form a closed test cavity and are uniformly coordinated by a control system, so that the radio frequency conduction performance of wireless equipment in different temperature and humidity environments can be detected in real time. According to the structure, the tedious operation that in the prior art, testing needs to be carried out in a high-low temperature box and an electromagnetic shielding box in sequence is avoided, the testing efficiency is improved, interference to a testing result in the equipment transferring process is reduced, and continuity and accuracy of data are guaranteed; meanwhile, the control system supports automatic setting and switching of various test working conditions, can comprehensively evaluate the communication stability of the wireless equipment in a complex environment, is suitable for efficient testing of various communication terminals in research and development verification and production quality inspection links, and has the remarkable technical advantages of integrated test process, accurate result and intelligent operation.

The application provides an infant education intelligent bracelet and a data processing method, and belongs to the technical field of wearable devices. The infant education intelligent bracelet comprises a main control processing module, a multi-source sensing module, a 4G communication module and a low-power control module. The multi-source sensing module comprises at least a three-axis acceleration sensor and a three-axis gyroscope, and is used for continuously collecting motion data and posture data of the infant. The 4G communication module is used for establishing a direct data communication connection between the intelligent bracelet and a cloud server, so that the data is directly transmitted to the cloud server. The main control processing module is used for data collection scheduling, data preprocessing and communication control logic. The low-power control module is used for dynamically adjusting the sampling frequency of the multi-source sensing module and the data upload period of the 4G communication module according to the behavior state of the infant. The application can solve the problems of low behavior recognition accuracy, high positioning error rate, insufficient data continuity and weak data fusion capability in the prior art.

The embodiment of the specification discloses a data aggregation method, device, equipment, medium and program product, which can improve the efficiency and accuracy of data aggregation. Wherein, the method comprises: acquiring data flow transfer files of multiple different formats; performing semantic analysis on the text content of each data flow transfer file by a large language model to obtain at least one data flow transfer record corresponding to each data flow transfer file; checking each data flow transfer record based on a preset data checking rule; the data checking rule comprises a data consistency checking rule, a data repeatability checking rule and a data continuity checking rule; and generating a data aggregation file according to each data flow transfer record that passes the check.

This invention discloses a multi-mode intelligent management method and system for IoT mesh network pivots. Based on an Adaptive Energy-Balancing Model (AEBM) and a Dynamic Mode-Switching Threshold (DMST), the method defines a default mode (Mesh + 12 + 1 + 23) and several configurable self-navigation modes (F7 reusable mode, F5 non-reusable mode, and F4 storage mode) for the pivot. When the pivot goes offline, it can automatically switch between these modes according to preset strategies and commands. This invention solves the problem of how to achieve ultra-low power operation while ensuring data continuity in the absence of network coverage or gateway failure by introducing a Cyclic Overwrite Storage Strategy (COSS) and a Multi-Mode State Machine (MMSM) model. It also provides flexible deployment methods such as mobile data acquisition and wireless sleep management, significantly improving the robustness, flexibility, and management convenience of the mesh network.

The application discloses a three-dimensional pathological marking data acquisition method and system based on two-dimensional key frames and electronic equipment. The two-dimensional pathological section with sparse marking is used as a key frame, a machine learning algorithm is combined, classification data of a lesion area and a non-lesion area covered in the key frame are used for training a foreground-background classifier, the two-dimensional pathological section is automatically marked by using the foreground-background classifier, and only a number of optional key frames need to be marked manually, so that the marking workload is greatly reduced. After automatic marking based on the key frames, three-dimensional reconstruction is carried out in combination with morphology, the problems of poor data continuity and structural distortion are avoided, and the quality of three-dimensional marking pathological data is improved.

The present application relates to the technical field of monitoring and early warning, in particular to a laboratory safety state monitoring and early warning system, which comprises a periodic acquisition module, a concentration comparison module, a rate judgment module, a grade mapping module and an early warning pushing module.In the present application, the change of gas concentration is recorded periodically and a time series index is established, so that the concentration amplitude information can be obtained while maintaining data continuity.Combined with the comparison and marking method of concentration fluctuation, the abnormal state can be dynamically identified without relying on fixed threshold triggering.The superimposed judgment of continuous amplitude trend and diffusion rate reference enables potential risks to be discovered early and the corresponding gas and time period to be determined.Further, through risk grade interval mapping, the present application realizes accurate matching with the alarm channel, so that the early warning pushing is hierarchical and targeted, thereby improving the sensitivity and timeliness of risk identification, reducing false positives and false negatives, and achieving active identification and efficient disposal of potential dangers in the laboratory environment.

This application discloses a data processing method, apparatus, and storage medium based on dynamic resource adaptation, relating to the field of data processing technology. The method includes: accessing rule execution result data under different rule development modes through a pre-configured unified data service registration interface; obtaining business source fields and establishing a mapping relationship between them and preset physical storage fields in the database using a dynamic field mapping algorithm. This algorithm allocates target physical fields based on the physical field resource pool status, combined with the business field type and length characteristics, while ensuring the continuity of historical data; initiating a rule trial run early warning process, calling the summary data query service, and intercepting anomalies in the summary record data according to monitoring thresholds; and dynamically generating rule execution task packages based on the data volume when no interception is triggered, calling the detailed data query service to obtain, parse, and display the data. This achieves efficient data adaptation and stable system operation in complex environments.

The application relates to the technical field of intelligent warehousing, and particularly discloses an ETV non-inductive weighing method and system based on multilevel checking, which comprises the following steps: deploying a sensor network in an ETV channel, collecting container weight and position data, constructing a transportation digital track and visually displaying the track, fusing and analyzing weight mutation, track deviation and time deviation indexes, generating a hierarchical early warning through an adaptive threshold model, generating a TV vehicle scheduling scheme and an optimal path through a multi-objective optimization algorithm according to the early warning level and the site condition, establishing a full-process data chain, ensuring data continuity through an automatic repair mechanism, providing multi-dimensional traceability query, and regularly evaluating system performance and self-diagnosing based on a historical data machine learning optimization model and strategy. The application solves the problems of data faults in the checking and transfer link and the coordination blind area between levels in the prior art, realizes real-time detection, efficient processing and data traceability of the whole process of the multilevel freight station ETV non-inductive weighing, and improves the transfer efficiency and reliability of the container.

This invention relates to the field of data transmission technology, and more particularly to a method and system for digital twin data transmission in a distribution network. The method includes the following steps: acquiring distribution network operation data through a data acquisition terminal; performing time alignment, protocol conversion, and anomaly removal via an edge gateway; and generating a corresponding digital twin data sequence based on topology relationships. In the event of link anomalies, a state latching and interval numbering mechanism is introduced to ensure data continuity, and state continuation and recovery updates are performed at the master station to achieve data synchronization. This invention, by introducing a state latching, interval numbering, and sequence identifier reconstruction mechanism, ensures the continuity, integrity, and traceability of data transmission in the distribution network under link anomaly conditions.

This utility model relates to the field of multi-source sensing equipment technology for intelligent transportation, and particularly to an adjustable bracket and a trajectory splicing device for the multi-source sensing equipment used therein. The adjustable bracket includes: a column composed of upper and lower telescopic sections with a telescopic height of 2.5m to 4m; a sensing equipment installation interface at the top of the column; and a wiring cavity inside the column to accommodate power cables, data cables, and grounding wires; a pitch angle adjustment component disposed between the column and the sensing equipment; a horizontal base connecting the sensing equipment and the pitch angle adjustment component, with the sensing equipment mounted on the horizontal base; and a vibration damping component disposed at the bottom of the column and connected to the ground. This utility model eliminates the need for secondary welding or on-site hole modification during installation, enabling rapid positioning and locking, and significantly shortening maintenance and replacement time; it comprehensively improves the detection accuracy, data continuity, and system reliability of the sensing equipment, reduces operation and maintenance costs, and meets the needs of intelligent transportation for all-weather, high-precision vehicle trajectory sensing.

The application discloses a kind of meteorological data verification method and system for weather station, and the present application relates to meteorological data verification technical field.It includes data acquisition module, data preprocessing module, adaptive calibration module, correlation verification module, abnormal processing module;When data preprocessing, uniform format is convenient for subsequent operation, is filled or triggered to supplement sampling according to missing rate, guarantee data continuity and integrity, can also preliminarily screen abnormal value;Adaptive segmented calibration is combined with sliding time window, AdaCalib realizes local accurate calibration, NeuCalib is globally distributed with the aid of neural network, and the result is intelligently selected by fluctuation coefficient, so that calibration has local details and global trend;Multi-parameter correlation verification utilizes physical correlation to retest data rationality, and abnormal data classification processing can accurately respond to different abnormal conditions, fault anomaly triggers repair and replaces data, environmental interference anomaly is retained and marked low weight, which ensures verification accuracy.

The application provides a grounding wire state monitoring and early warning system and method based on a random forest algorithm, relates to the technical field of power safety monitoring, and solves the problems of low efficiency, poor data continuity, inaccurate early warning judgment and other limitations in the prior art. In the system, a multi-source sensor network collects multi-dimensional operation data corresponding to the grounding wire and transmits the data to a data acquisition terminal; the data acquisition terminal performs feature extraction processing, generates a feature vector set, and uploads the feature vector set to a cloud data processing platform; the cloud data processing platform uses a random forest classification model, based on the feature vector set, adjusts the dynamic feature weight through feature importance analysis, constructs a hierarchical decision tree structure, identifies and outputs the grounding wire fault mode, and issues the grounding wire fault mode to a local early warning terminal; the local early warning terminal adopts a hierarchical differentiated early warning mode and provides early warning information to the grounding wire site. The application effectively realizes high-precision early warning and predictive maintenance of the grounding wire state.

This invention provides a method and system for intelligent monitoring and early warning of VOCs incinerator operating conditions. The method includes: collecting operating condition data such as combustion chamber temperature, system pressure, inlet and outlet VOCs concentrations, key actuator status, and bypass valve status based on edge monitoring nodes deployed on-site; aligning the sampling period of the multi-source data and generating timestamps to form a time-ordered original operating condition data stream; filtering key operating data from the data stream and encapsulating it into key operating data frames; calculating derived indicators such as purification efficiency; generating data integrity identification information corresponding one-to-one with the key operating data frames; further constructing a tamper-proof evidence chain containing chained summaries to achieve traceable verification of the continuity of operating data; and, under the premise that the evidence chain consistency verification is passed, constructing a consistency feature vector and calculating the consistency deviation, and introducing an ant colony algorithm on the operating mode diagram for multi-path consistency evaluation.

This invention discloses a dynamic monitoring system for garden soil layers based on a multi-parameter soil sensor network, relating to the fields of environmental monitoring and smart gardening. By deploying multi-parameter sensor nodes with integrated microcontroller units at different regions and depths of the garden soil, it achieves hierarchical acquisition of environmental parameters such as temperature, humidity, conductivity, and pH. Simultaneously, it collects real-time data on changes in power supply voltage and peripheral current before and after MCU wake-up, calculates the dynamic wake-up voltage gradient and instantaneous load initiation factor, inputs these into a nonlinear prediction model, assesses the probability of reset risk, and dynamically adjusts the peripheral startup sequence during high-risk periods to avoid reset events. Combined with rolling learning, the model is adaptively updated to improve the operational stability and data continuity of the monitoring nodes. This invention possesses advantages such as low power consumption, high reliability, and intelligent control, making it suitable for long-term soil monitoring applications in complex garden environments.

This invention relates to the field of enterprise management technology, specifically to a big data-based enterprise financial shared assessment method and system, comprising the following steps: acquiring and sorting procurement and acceptance data for cumulative comparison; determining settlement quantities based on amount and unit price to screen discrepancy nodes; locating acceptance intervals and associating them with cost centers and suppliers; combining multiple time periods to divide segments and merge data; and associating business segments with cost categories to calculate indicators. In this invention, by constructing a continuous sequence around acceptance time and quantity and performing cumulative verification, introducing settlement amount and unit price to derive quantity identifiers and identify discrepancy nodes, extracting acceptance segments by procurement batch and time interval and fusing associated identifiers, and dividing business segments according to multiple time nodes for integration and mapping, business events are aligned and linked within a unified time framework, strengthening data continuity and node traceability capabilities, improving anomaly identification capabilities and segment attribution consistency, and enhancing the stability and analytical consistency of assessment results.

The present application provides a kind of energy consumption prediction and optimization control method and device in coal conveying process, by deploying fiber bragg grating sensing network, integration raman scattering and polarization state analysis module, real-time acquisition phase shift, temperature, humidity and polarization change data, construct multi-resolution phase mapping model, combined with environmental compensation and torsion force, accurately predict friction power consumption and total energy consumption.System uses ring optical fiber topology structure and loop switching protocol, automatically switches standby path when optical path is locally damaged, guarantees data continuity;And through the environment drift and torsion threshold abnormal detection mechanism, timely trigger alarm and pause optimization, ensure stable operation.Further, based on energy consumption heat map, construct phase synchronization control loop, dynamically adjust the driving frequency and tension of each section of equipment by programmable logic controller, fuse temperature and humidity gradient and polarization data for real-time compensation and calibration, minimize phase mismatch, realize multi-section cooperation, energy-efficient operation.

The application provides a kind of intelligent three-dimensional positioning method and system based on Bluetooth beacon and LoRa ad hoc network, belongs to the field of building construction safety.The technical scheme is: S1, establish the three-dimensional positioning constraint model of tunnel construction area and complete node system configuration;S2, positioning terminal collects and pre-processes multi-source observation data to generate unified observation package;S3, based on LoRa ad hoc network, unified observation package is cooperated, converged and reliably transmitted;S4, execute semantic constraint multi-source fusion three-dimensional positioning solution;S5, execute three-dimensional ambiguity resolution and output positioning result and closed loop update.The beneficial effects of the application are: the application improves alignment accuracy through ad hoc network time synchronization and windowed fusion, and guarantees data continuity through multi-hop reliable transmission and confidence retransmission;three-dimensional reachable domain and connectivity rules are used to resolve ambiguity and reduce cross-zone and cross-height misjudgment;confidence is output, and constraints are calibrated and dynamically updated online, so that positioning is long-term stable and reliable.

The application discloses the technical field of low-voltage draw-out type switch cabinet, and particularly relates to a low-voltage draw-out type switch cabinet monitoring system and method. First, based on the structure and key components of the switch cabinet, electrical, temperature, mechanical, insulation, environmental and image data are collected in full dimensions to provide comprehensive and accurate support for subsequent transmission and analysis. Then, through preprocessing, encrypted transmission and local caching, the data can be reliably transferred in the industrial environment through double links, and the data continuity is ensured when the network is interrupted. Based on this, through deep linkage analysis of multi-dimensional data, the application breaks through the limitation of traditional monitoring which only focuses on a single parameter, realizes complementary verification and correlation analysis of multiple types of data such as electrical, temperature, mechanical, insulation and environment, and effectively solves the pain point of isolated monitoring dimension.

This application discloses a method and system for acquiring dynamic information of equipment based on the Industrial Internet of Things (IIoT), relating to the field of IIoT technology. Specifically targeting the dynamic information acquisition scenario of factory industrial equipment, this application improves upon existing fixed-frequency acquisition technology by implementing time-block scheduling and dual-channel parallel discrimination. In state discrimination, it considers the relationship between steady-state trend shifts and transient abrupt changes in physical quantities. Through joint decision-making via steady-state feature analysis and transient disturbance detection, it dynamically adjusts the sampling frequency and sensor channel activation strategy for the next time block. It integrates cloud-based and field-based collaborative prediction into the acquisition method and employs seamless switching between dual buffers to ensure data continuity, providing a high-fidelity, energy-saving industrial equipment state perception solution adaptable to all operating conditions.

The invention discloses a multi-machine collaborative passenger flow statistical method and system based on pedestrian re-identification, and relates to the field of computer vision and intelligent video monitoring, and the method comprises the following steps: deploying at least two pedestrian re-identification vision collection devices, configuring a master machine and a slave machine, establishing a communication link, and carrying out heartbeat monitoring based on a user datagram protocol; each device tracks a personnel trajectory and extracts a feature vector; in a normal mode, the slave uploads feature vectors, and the host integrates features and performs cross-device identity de-duplication according to a joint confidence scoring model; when the host is offline, the slave is automatically switched to the temporary host based on a preset arbitration function to take over and deduplication, and after the original host is recovered, the slave is automatically switched back and data is complementarily transmitted; and packaging and outputting the passenger flow data after deduplication. According to the invention, multi-machine collaborative passenger flow statistics, cross-mirror duplicate removal and fault automatic disaster recovery are realized, the problems of repeated counting, easy interruption of a single-point fault and insufficient data continuity and accuracy of a traditional scheme are solved, and the accuracy and continuity of passenger flow statistics are improved.