40 results about "Asynchronous data" patented technology

This invention discloses a method and system for identifying safety hazards in power equipment, specifically relating to the field of intelligent operation and maintenance technology for power equipment. It addresses the hidden operational risks caused by the mismatch between equipment aging characteristics and generalized strategies in existing technologies. By collecting multi-source operating status data of power equipment and constructing an asynchronous dataset, it dynamically identifies spatial electric field distortion gradients and contact resistance fluctuations as abnormal parameters. Based on equipment structural characteristics, it assigns differentiated weights to these abnormal parameters, quantifying the risk levels of different areas. It analyzes the temporal correlation between contact resistance and electric field response to determine the breakdown risk caused by insulation degradation. Combining the risk levels, it generates maintenance cycle optimization schemes and electric field compensation parameters, and dynamically updates the aging model based on execution feedback. Through dynamic adaptation of equipment status and control strategies, it achieves early warning and precise intervention for potential hazards, effectively solving the control mismatch problem caused by neglecting material degradation characteristics in traditional methods.

This invention discloses a testing device for the operating performance of a lever mechanism simulating load, belonging to the field of high-end equipment performance testing. The core innovation of the device lies in the sequential connection of the lever, crank, connecting rod, slider, and frame assembly to form a crank-connecting rod-slider core transmission and load simulation mechanism. This mechanism integrates adjustable load simulation and integrated synchronous measurement functions. By configuring counterweights, replacing elastic elements, and adjusting connection angles and lever arms, it can accurately simulate nonlinear, multi-dimensional coupled actual operating loads. Simultaneously, a sensor network composed of force sensors, tilt sensors, and acceleration sensors respectively set at key nodes such as the lever and crank synchronously collects multi-dimensional force / torque, displacement, and acceleration parameters throughout the entire operating process. This invention solves the problems of load distortion, single measurement, and asynchronous data in traditional testing, achieving accurate and universal testing of the operating performance of lever mechanisms.

This invention discloses a cloud-edge-device collaborative intelligent panoramic perception and target tracking system, including an image processing layer comprising an NPU acceleration module and an image stitching module. The NPU acceleration module is used to extract multi-scale defect features from the panoramic video data using a lightweight convolutional neural network and output feature vectors. This invention achieves real-time edge processing of multiple video streams from the data acquisition layer via the NPU acceleration module and the key-value binding-based image stitching module at the image processing layer. This enables precise alignment and seamless fusion of images from multiple cameras, effectively solving the problems of poor stitching quality caused by large image distortion and asynchronous data frames in existing technologies. Furthermore, the system utilizes YOLO11m as the detection engine and an incremental learning interface at the server layer to perform high-precision target recognition and continuous cross-lens tracking of the panoramic image stream, allowing the system to dynamically expand its recognition capabilities and achieve low-latency intelligent perception.

The application provides a meteorological anchor point-based cross-modal asynchronous data alignment method, system, device and storage medium, which comprises the following steps: acquiring multi-modal data of a target area, and performing spatial alignment on the multi-modal data; constructing a unified anchor point time axis based on the meteorological predicted water depth grid sequence; based on the unified anchor point time axis, performing nearest time point matching and time decay on a remote sensing grid observation sequence and a GIS risk grid observation sequence respectively to obtain a time-aligned remote sensing grid observation sequence and a time-aligned GIS risk grid observation sequence; based on the unified anchor point time axis, performing time window aggregation on a social crowdsourcing point observation sequence to obtain a time-aligned social crowdsourcing point observation sequence; generating metadata of each modal data for each anchor point timestamp on the unified anchor point time axis, and outputting the time-aligned multi-modal data and the metadata.

This invention discloses a combined shear-resistivity testing device and method for soil-rock mixed fillers, belonging to the field of geotechnical engineering testing technology. It addresses the shortcomings of existing combined testing methods, such as unstable contact resistance, fluctuating electrical signals, and asynchronous data. The device includes a direct shear test, resistivity test, and data acquisition and control system. The shear test chamber has a multi-layered composite structure integrated electrode embedded in its inner wall, coupled with an array of spring needles, and features a stress-driven electrical connection and hardware synchronous triggering structure. The method completes the test through steps including sample preparation, system initialization, stress-driven electrical connection establishment, and synchronous triggering of the combined test. This invention achieves synchronous and accurate acquisition of shear mechanics and resistivity data, enabling real-time non-destructive characterization of the internal structural damage evolution of the sample, significantly improving testing accuracy and stability, and providing reliable technical support for the mechanical research and engineering applications of soil-rock mixed fillers.

This invention provides a fault identification method for test equipment based on diagnostic semantic adaptation, belonging to the field of test equipment operation status monitoring technology. It includes: S1, collecting multi-measurement channel sensor signals and image information generated during the test and performing preprocessing; S2, performing measurement channel mapping, unit conversion, range matching, and normalization processing on multi-source asynchronous data; S3, determining the fault probability of the test equipment, obtaining the fused fault confidence level, and generating a structured test equipment fault diagnosis record package; S4, analyzing the fault types of the test equipment and executing the test equipment fault identification alarm program. This invention uses an edge-side temporal fault discrimination network to perform real-time fault screening on a unified state vector, and employs a multimodal transfer diagnostic network for fault verification and incremental learning, forming a parameter optimization closed loop to improve the accuracy and robustness of fault identification.

This invention relates to the field of production data analysis technology, specifically disclosing a method and system for analyzing production data of a trademark die-cutting machine. The method involves identifying the movement trajectories of production actions during the die-cutting process as presented in various production inspection data curves, and acquiring production inspection data curves collected by each production inspection unit when a production action occurs. Subsequently, production information segments associated with the movement trajectories are identified from these data curves, and their timestamps are obtained. Based on these timestamps, the timestamps of the data curves collected by each production inspection unit are adjusted, and finally, the presence of product quality defects is identified based on the adjusted data curves. This solves the problem of asynchronous data timestamps caused by internal clock drift in existing technologies.

The application discloses a kind of asynchronous fusion method and system of deep-sea biological space-time trajectory analysis, the method is extracted from the single video data stream collected by underwater equipment biological target using visual detection module concurrently, and using video text recognition module extracts the space-time metadata superimposed in video picture;Then using asynchronous data fusion module based on a confidence-aware asynchronous extended Kalman filtering algorithm, the visual feature information and space-time metadata are fused, and the unified space-time trajectory point with geographic registration is generated.The application solves the technical problems that biological visual information and accurate space-time information are difficult to automatically integrate from single video source in the prior art, and through innovative asynchronous data fusion algorithm and diversified visualization output, the robustness, accuracy and application breadth of the automatic ecological monitoring and analysis system are significantly improved.

The application provides a diversion tunnel surrounding rock mechanics parameter inversion method and device based on multi-target learning, and the method comprises the following steps: a sampling method containing directional number disturbance low difference sampling sequence is adopted to construct a parameter-response sample data set of the diversion tunnel surrounding rock; a multi-penalty item loss function is used for model training on a multi-target machine learning algorithm to construct a diversion tunnel surrounding rock response multi-output proxy model; the multi-penalty item loss function comprises an observation error item, a time sequence monotonic-stable penalty item and a cross-measurement point collaborative penalty item; the proxy model is used for parameter inversion to generate an optimal mechanics parameter solution; the precision and generalization ability of the surrounding rock mechanics parameter inversion can be significantly improved under the condition of a small sample; the physical consistency of the inversion result is ensured through time sequence monotonic and cross-measurement point collaborative constraints; the method has good noise resistance and asynchronous data robustness, can realize optimal parameter output under multi-target weighting, and forms a closed-loop verification from inversion to numerical review.

The utility model discloses a kind of PCIE optical fiber communication boards for special components, including FPGA, FPGA is integrally connected with synchronous clock input interface, three-way digital optical fiber receiving interface, SMA input interface, TypeC interface group, independent SDRAM storage unit and optical signal output port by function interface;FPGA is coordinated each above-mentioned component module work, realizes the protocol conversion of PCIE protocol and optical fiber communication, data encoding and decoding, cache management function.The utility model innovatively adopts mixed clock domain architecture, organically combines synchronous clock tree and asynchronous data channel, simultaneously supports the mixed networking mode of copper cable and optical fiber through photoelectric composite interface design, while guaranteeing high-speed data transmission, effectively reduce the electromagnetic interference influence in transmission path;In addition, the multi-protocol conversion engine and hardware acceleration module integrated in FPGA further improve the processing efficiency and flexibility of system.

The present application relates to the technical field of intelligent sorting and industrial process control in coal mine, and particularly relates to a coal gangue intelligent rejection control method based on asynchronous data flow compensation. The technical scheme comprises asynchronous data acquisition, time stamp virtual queue establishment, dynamic space-time mapping, rejection advance calculation, rejection control execution, end feedback measurement, error self-correction, and the asynchronous data acquisition acquires a first data flow and a second data flow respectively, the first data flow is the target category, target coordinates and corresponding time stamp output by an X-ray identification device, and the second data flow is the speed, displacement or beat information and corresponding time stamp output by a belt or cloth device running state detection device. The present application solves the technical problems of asynchronous data registration, space-time dislocation in identification and execution, and time-varying delay compensation of the execution chain in the coal gangue rejection control, and realizes stable, high-precision and self-correctable rejection control of the online coal gangue sorting equipment.

The application relates to the Internet of Vehicles technology field and provides a roadside parking resource sensing and distribution method and system based on cloud-edge cooperation. The method comprises the following steps: constructing a regionalized cooperative sensing grid facing a continuous roadside space and establishing a dynamic benchmark calibration system; calculating a vehicle existence probability field of the continuous roadside space based on asynchronous data streams from multiple types of sensing terminals; based on gradient analysis and morphological processing of the probability field, dynamically extracting and fitting the profile of a virtual parking unit; based on conflict prediction of the space-time distribution of the virtual parking unit, generating a regional elastic distribution strategy based on game equilibrium; compiling the regional elastic distribution strategy into a space strategy code and an individualized guidance code, coupling based on vehicle identity and performing distributed cooperative guidance. The method can realize elastic, high-fault-tolerant and adaptive distribution of parking resources in a complex and dynamic urban roadside environment.

The present application relates to geotechnical exploration equipment, in particular to an intelligent high-precision geotechnological multifunctional static sounding system and its exploration method. A pore water pressure sensor is installed between the cone tip and the intermediate connecting rod. A cone tip resistance sensor, a sidewall friction sensor and an acoustic emission sensing unit are sequentially arranged from bottom to top between the friction cylinder and the intermediate connecting rod. An inclination sensor, a multi-parameter synchronous acquisition module, a data processing unit and an FPGA control unit are sequentially embedded from bottom to top on the tail connecting rod. The pore water pressure sensor, the cone tip resistance sensor, the sidewall friction sensor, the acoustic emission sensing unit and the inclination sensor are electrically connected with the multi-parameter synchronous acquisition module. The multi-parameter synchronous acquisition module, the data processing unit and the FPGA control unit are electrically connected with the digital-analog conversion device. The digital-analog conversion device is electrically connected with the remote data acquisition device. The present application solves the problems of asynchronous data, spatial dislocation, low interpretation accuracy and single function of the exploration equipment.

The application discloses a fault root cause positioning method and system based on PLC log deep mining, which decomposes original PLC logs into continuous data streams and discrete event streams through a heterogeneous data shunting mechanism. A time series convolution network is used to capture the time series dynamic changes of high-frequency analog data, and a Transformer encoder is used to extract the semantic logical association of asynchronous discrete events, thereby avoiding the loss of time series accuracy and semantic confusion caused by forced time alignment. On this basis, a multi-level attention fusion mechanism is introduced to preserve the characteristics of each mode while realizing deep interaction and alignment of cross-modal features, and a unified feature representation containing rich space-time dependencies is constructed. The method effectively solves the technical problem of deep fusion of heterogeneous asynchronous data in industrial scenes, and realizes accurate positioning of fault root causes and visualization of fault propagation path.

Methods, systems, and devices for data management are described. A first application in a destination computing environment of a data management system (DMS) may determine that a bulk-push criterion is satisfied for a second application in a source computing environment of the DMS. The first application may transmit, to an asynchronous metadata service, a request indicating the second application for which the bulk-push criterion is satisfied. The request may be configured to cause the asynchronous metadata service to query a database in the source computing environment, identify a latest version of one or more rows that include metadata associated with the second application, and generate data records indicating the latest version of the one or more rows that include the metadata associated with the second application. The first application may receive the data records via an asynchronous data stream between the first application and the second application.

This application provides a method and system for detecting anomalies in Linux kernel I / O event handling. The method includes: collecting the I / O request dwell time without locks through percpu variables at preset I / O blocking nodes in the Linux kernel storage stack bio and request stages; creating file nodes in debugfs to summarize and output the time-consuming data in response to user-space read requests; and creating an I / O tracking structure for each I / O stage of each block device to manage the entry and exit of instances in the I / O request stage. It can also track the I / O context by registering hooks in the Device Mapper framework, and achieve asynchronous data interaction between the kernel and user space using a lock-free circular buffer and the io_uring interface. This application achieves layered observation of the entire I / O chain, low-overhead lock-free operation, and can locate abnormal I / O in seconds, balancing observation accuracy and business I / O performance, without affecting business operations.

A kind of data system implementation method of urban three-dimensional geological modeling system, comprising the following steps: importing city survey data, groundwater survey data and groundwater model data into geological big data center;The geological big data center is based on distributed asynchronous data synchronous transmission technology to realize the functions of statistical analysis, information mapping, achievement generation, instant archiving and external data docking, quality control;After the city survey data, groundwater survey data and groundwater model data are fused with the basic data layer of city-level three-dimensional geological model, visual display is carried out;The technical scheme of the application can meet the needs of providing data sharing for multiple systems, support building information model software, numerical simulation software, OGC standard, support fast import modeling software, effectively meet the needs of collaborative processing of multi-source heterogeneous data under complex conditions such as multiple people, multiple places, online and offline in actual projects.

The application relates to a kind of traditional Chinese medicine moxa point adaptive control method, system, equipment and medium based on agent, the method comprises: obtaining patient multimodal synchronous perception data, and obtaining multimodal perception data stream by spatiotemporal joint calibration and asynchronous data flow alignment;Reconstruct the three-dimensional skeletal model of patient based on multimodal perception data stream, and solve the initial coordinates of the moxa point to be moxa by bone degree minute method;Combine syndrome observation information and pre-constructed traditional Chinese medicine syndrome differentiation knowledge graph to construct dynamic state space;The dynamic state space is input into the pre-trained fast adaptive reinforcement learning model, and the matched treatment strategy is obtained;Generate multi-point collaborative control sequence based on treatment strategy and initial coordinates of point. By using the method, dynamic syndrome differentiation moxa can be realized, and the accuracy, clinical adaptability and treatment effectiveness of intelligent moxa control can be improved.

A tremor treatment data acquisition and analysis system and method integrating inertia and pressure includes the following steps: identifying the scene context label corresponding to the current acquisition task, wherein the context label includes outpatient examination state, inpatient treatment state, and post-treatment observation state; dynamically rewriting the acquisition logic according to the scene context label, and simultaneously acquiring the subject's tremor motion data and contact pressure data under each rewritten time sequence task, and generating a corresponding scene state mapping handle to construct a standardized time sequence across physical time and space; after the unified standard analysis model is invoked, asynchronous data packets generated by the same object at different physical time points are retrieved and extracted through the scene state mapping handle, and data logic alignment is performed based on the configuration parameters and timestamp offset recorded in the scene state mapping handle; and combined with the characteristic parameters of the three time periods before treatment, during treatment, and after treatment, a quantitative report on tremor evolution across outpatient and inpatient cycles is generated.

The utility model provides an asynchronous data access method and interface device, end side equipment, asynchronous data access method includes: based on the rising and falling edge of clock respectively to read data effective signal sampling, generates rising edge sampling sequence and falling edge sampling sequence, based on first effective data of rising edge sampling sequence and falling edge sampling sequence judges, and generates trigger signal, and based on trigger signal, to read data signal sampling to obtain with the stable data of clock synchronization. Can be realized in the continuous asynchronous data reading of no clock data source scene, and in the case of not needing to the multi bit read data pre sampling, realized the reading of asynchronous data, effectively reduced the power consumption. The device is especially suitable for the near storage calculation architecture of end side equipment, can improve the performance and energy efficiency of big model inference significantly, is applicable to AI cell -phone and AI PC and so on end side equipment.

This invention relates to the intersection of Industrial Internet and data management technologies, and particularly to a coal preparation plant data center management system and method. It includes the following components: a data acquisition module for acquiring various types of data from the coal preparation plant data center; a process tensor module for constructing a process state tensor from the various types of data according to the timeline of the coal preparation plant data center and extracting keywords; a data value module for constructing a fractal recursive tree using keywords as nodes to acquire the data flow and value flow of the coal preparation plant data center, and filtering out abnormal data flow and abnormal value flow; a loss function module for calculating the loss function that minimizes the abnormal value flow of the coal preparation plant data center based on the asynchronous data flow and asynchronous value flow; and a feedforward adjustment module for managing the coal preparation plant data center by feedforward adjustment based on the minimized abnormal value flow loss function. This invention performs feedforward adjustment and management of the coal preparation plant data center through abnormal data flow and abnormal value flow.

The present application relates to the technical field of excavation and filling, and discloses a fat groove backfill construction method for building backfill engineering, which comprises the following steps: obtaining the geometric characteristics of a space to be backfilled and initial rheological parameters of a filling medium; injecting the filling medium and collecting rheological data of a phase change process thereof; establishing a double-buffering space-time index structure based on a phase change gradient; using asynchronous scheduling of an active index buffer and a background overwriting buffer to match a pre-stored template to generate a synchronous pressure control instruction; and applying a low-frequency pulse pressure wave according to the pressure control instruction. The present application eliminates database read-write lock conflicts through asynchronous data processing, keeps the pressure regulation and the transient evolution law of the rheological properties of the filling medium in synchronization, destroys the internal arching structure and induces in-situ reorganization of the material by using a shear strain field, and improves the compactness of the backfill body and the interface sealing efficiency.

This disclosure relates generally to a method and system for the automated farm management by utilizing connected graphs to navigate through unexpected future events affecting the farm. State-of-art methods for prediction of the unexpected future events is based a vast asynchronous data distributed across various complex data analytics tools. And it becomes difficult to choose most suitable actions to be taken to navigate the future event based on the asynchronous data. The present disclosure addresses these problems through a method that utilizes a graphical form of a plurality of sensor data collected from the farm to derive refined multi-contextual intelligent queries. The refined multi-contextual intelligent query is provided to a remotely located LLM model to generate a set of recommendations. The most suitable recommendation is transmitted to an associated autonomous farm machinery to take a suitable action. The method utilizes a feedback mechanism to improve future query generation.

This invention relates to the field of electronic digital data processing technology and discloses a construction management method based on the jacking of steel box girders. The method includes: establishing a logical association matrix based on the layout parameters of the sampling nodes of the monitored object; extracting the driving characteristic signals generated by the power excitation source to establish a global logical reference benchmark; calculating the cross-correlation function between the monitored data stream and the benchmark and determining the logical phase difference; using the logical phase difference to perform phase alignment compensation and mapping the data to the state vector space; using the logical association matrix to perform consistency verification and calculate the association residual; and real-time monitoring of the energy accumulation characteristics of the residual in the frequency domain to determine the physical causal logical state. This invention establishes a logical phase self-locking mechanism based on the physical load rhythm to solve the logical phase distortion caused by the time sequence offset of the asynchronous data stream and improve the collaborative stability between the digital image and the physical entity.

A device comprising an image sensor for capturing a stream of asynchronous data representing per-pixel changes in radiance within a scene over an acquisition cycle and processing circuitry communicatively coupled to at least one light source positioned to illuminate at least an area of the scene, the processing circuitry configured to modulate output of the at least one light source over the acquisition cycle.

A machine-learning system and method for engineering and optimizing meetings. The method includes defining a meeting agenda comprising agenda items, generating prompts to solicit structured participant inputs, and enforcing contribution thresholds to ensure sufficient input. Participant inputs are integrated with internal organizational information and external information sources and analyzed using machine-learning techniques to generate results for each agenda item, including predictions, recommendations, and other optimized meeting products. Each completed meeting is stored as a structured dataset, and machine learning is applied across multiple completed meeting datasets over time to generate emergent knowledge and build an organization foundation model. The organization foundation model supports evaluation of participant and information source contributions, informs subsequent meetings, and enables time-based analysis. The system enables asynchronous, data-driven meetings that improve efficiency, accountability, and knowledge generation within and across organizations.

This invention relates to the field of bulk cargo compliance flow control, and discloses a method and system for multi-source detection data fusion and risk management of iron ore, including: retrieving contract data and regulatory standards to construct a dynamic monitoring baseline; acquiring an asynchronous monitoring evidence stream composed of high-frequency radioactive dose rate stream, image foreign object identification parameter stream, and time-delay spectral grade analysis parameter stream; when the high-frequency radioactive dose rate stream or image foreign object identification parameter stream touches the red line, abandoning the full set waiting and triggering a high-priority early warning response mechanism to output flow control instructions; extracting the image foreign object identification parameter stream residual within the synchronous time window within the safe range as a dynamic penalty factor to tighten the baseline threshold. This invention reconstructs the asynchronous data adjudication boundary, eliminates information timing obstruction caused by waiting for time-delayed data, and improves the accuracy of risk decision-making state inference under continuous flow conditions.

This application provides a service-aware Bluetooth HCI interface dynamic flow control optimization method and device, relating to the field of wireless communication technology. The method includes: a host in a Bluetooth communication device communicates with a controller via an HCI interface; based on the total buffer capacity of the controller and combined with the available audio context declared in the published audio capability service, it dynamically calculates and configures independent credit pools with different weights for isochronous streams (ISO) and asynchronous data streams (ACLs); based on link quality and data queue status, the controller performs predictive credit early return for ISO services before sending an acknowledgment response at the physical layer, so that the host can send the next frame of audio data in advance; and it uses byte-block granularity for buffer idle state reporting and flow control scheduling. This application solves the problems of delayed credit return and coarse flow control granularity in traditional Bluetooth HCI flow control mechanisms, ensuring low-latency, low-jitter transmission of real-time services while improving the utilization rate of the controller buffer.

This invention proposes a system architecture for an online monitoring service for pressure plates based on dynamic plug-ins. The system includes a script monitoring module, a startup module, a dynamic plug-in management and data processing module, a database module, an HTTP module, and a dynamic plug-in communication module. The script monitoring module enables the service to start automatically with the system. The startup module monitors the system's CPU, disk, and memory, recording and statistically analyzing runtime. The dynamic plug-in management and data processing module loads each module, enabling pressure plate host communication status and data business analysis and processing. The database module supports communication, data saving, updating, and viewing between multiple databases. The HTTP module enables one-way asynchronous transmission of platform commands. The dynamic plug-in communication module enables bidirectional asynchronous data interaction with the pressure plate monitoring host. This system architecture constructs a four-layer modular architecture and a dynamic plug-in mechanism, addressing several technical deficiencies in existing online pressure plate monitoring systems.

The application discloses a kind of rail turnout life prediction method and system based on multi-modal deep learning, the method includes collecting the current data and vibration data of turnout, carries out asynchronous data mixing with synchronization;Local space features of turnout multi-source sensing synchronization data are extracted using CNN network, and the timing variation law of local space features is captured through LSTM network;Local space features and timing features are fused based on cross-modal feature attention fusion network, and the model is pre-trained using the contrast training method of self-supervised learning, and the turnout life prediction model is obtained by fine-tuning using turnout fault data;The penalty term embedded model loss function with physical constraints is constructed using turnout mechanical dynamics model, and the turnout life prediction model is trained;Finally, the probability distribution of turnout remaining life is output, and the explainability report is generated by SHAP tool.Application of the application can effectively improve the precision and reliability of turnout life prediction.