63 results about "Offline analysis" patented technology

The invention discloses a natural resource big data off-line comprehensive analysis, annotation and proof system and method, and belongs to the technical field of natural resource informatization and geographic information processing. The system comprises the following components: a spatial data fusion module, which is used for realizing unified management and efficient processing of heterogeneous spatial data; the spatial index optimization module is used for realizing quick retrieval and high-performance query optimization of spatial data; the intelligent annotation and arrangement module is used for realizing low-code rapid configuration and business process automatic arrangement of different natural resource investigation scenes; the off-line analysis module is used for realizing buffer area analysis, space superposition and terrain analysis in an off-line environment; the real-time visualization module is used for realizing multi-level map display, track recording, vector element editing and multimedia evidence collection; and the data quality management module is used for realizing automatic quality inspection of geometry, topology and attributes and statistical analysis, version control and export management of annotation results.

This invention belongs to the field of ship shafting condition monitoring and fault diagnosis technology, specifically relating to a bearing load measurement device and its data acquisition and transmission method. This invention effectively suppresses temperature drift, mechanical vibration, and electromagnetic interference by rationally arranging strain gauges, employing high-precision synchronous sampling, and combined denoising processing, thereby improving the accuracy of signal acquisition. Embedding moment balance and beam strain consistency equations into the machine learning model significantly improves the accuracy of load prediction. High-speed multi-channel synchronous sampling technology ensures data time alignment, and a multi-algorithm denoising scheme combining wavelet thresholding and bandpass filtering effectively filters out mechanical vibration and electromagnetic interference. A multi-mode communication module enables separate channel transmission of real-time load data and raw strain data, balancing the low-latency requirements of online monitoring with the large-scale data archiving requirements of offline analysis. The introduction of edge computing significantly reduces cloud transmission pressure and improves the real-time performance of load measurement.

The invention provides a performance testing method and device and a storage medium. The method comprises the steps that all executable programs of a software system submitted by a user and modified program files in the software system are received; based on the program file and all executable programs of the software system, performing a performance test to obtain a test report; and sending the test report to the user. According to the application, a user only needs to send all the executable programs of the software system and the currently modified program file to the server. And the server automatically completes the performance test of the software system and returns a test report to the user. Automatic testing of the whole process of the software system is achieved, the automation degree is high, and the testing efficiency is improved. And the test is performed only when the modified program file appears, so that the incremental performance test is realized, the performance test is more targeted, and the test efficiency and accuracy are improved. And tests in the aspects of off-line analysis, on-line analysis, integration test and the like can be carried out, and the performance test is more comprehensive, efficient and accurate.

This invention discloses a real-time detection method and system for abnormal behavior based on micro-execution state sequences, relating to the field of computer-related technologies. The method includes: offline analysis of the binary code of embedded firmware to generate a legitimate fingerprint database of micro-execution state sequences; non-intrusive sniffing of the CPU's instruction bus and real-time classification of executed instructions via a hardware monitoring unit; calculation of real-time fingerprints based on instruction type sequences; extraction of legitimate fingerprints from the legitimate fingerprint database; synchronization with a fingerprint comparator for comparison; and generation of fingerprint comparison results; and triggering an abnormal response unit based on the fingerprint comparison results. This invention solves the technical problems in existing technologies where low-overhead, fine-grained, and broad-spectrum defense capabilities for embedded firmware runtime behavior monitoring cannot be achieved in resource-constrained environments, resulting in poor real-time detection performance, sensitivity, and protection coverage. It achieves the technical effect of improving the real-time performance and sensitivity of embedded firmware runtime integrity detection, as well as the protection coverage and system energy efficiency.

The invention discloses a data storage query method and system for industrial automation. The method comprises the following steps: defining a synchronization process from a cache layer to a real-time analysis layer, from the real-time analysis layer to an offline analysis layer and from a metadatabase to each layer, and determining a data flow direction and a trigger condition; consistency and integrity of cross-layer data are ensured through mechanisms such as version control, transactional messages and account checking compensation; the metadatabase records each layer of metadata, such as a data version, a synchronization state and a timestamp, drives a synchronization process and verifies consistency. According to the scheme of the invention, full-link collaboration of industrial automation data is realized.

This application discloses a method for offline analysis of powder ionization conditions, comprising the following steps: placing a silicon wafer on a target plate of a plasma device; generating a plasma beam under preset powder ionization conditions using the plasma device; injecting powder into the plasma device so that the plasma beam bombards the powder until powder injection is complete; detecting whether a first condition and a second condition are met, wherein the first condition includes at least 70% of the powder injected into the plasma device ablation and brightening upon bombardment by the plasma beam and / or forming a coating on the silicon wafer; the second condition includes the coating containing chemical bonds formed by elements of the powder and / or detecting spectral lines generated by ionization of the powder upon bombardment by the plasma beam. If the first and second conditions are met, the powder is determined to be effectively ionized. Otherwise, the powder is determined to be ineffectively ionized. The method of this application can obtain basic research data on the boronization of boron powder.

This invention discloses a method for real-time monitoring and offline correction of wind tunnel pressure test data. The aim is to solve a series of problems encountered during pressure testing, such as the inability to monitor the operating status of the pressure acquisition system, the inability to compare unknown data values, and the difficulty in determining the quality of test data. Without adding peripheral equipment, this invention fully utilizes the potential of existing pressure acquisition system equipment to achieve real-time dynamic monitoring of pressure data and provides a basis for offline data analysis and correction. Through analogy comparison, real-time monitoring of the operating status of the pressure acquisition system is achieved, reducing the risks of test run scrapping and data invalidation due to equipment failure. This invention requires minimal system modifications, is flexible and convenient to operate, and is economical and practical. The difference between the synchronously acquired set constant pressure and the measured constant pressure provides a basis for subsequent offline correction of the test data, improving data accuracy.

A computer-implemented method, system and computer program product for recommending design changes in designing a digital integrated circuit. An analysis of the digital integrated circuit being designed is performed, where the result of such an analysis involves violations being identified and stored. A stored violation, such as a cross-domain, cross-hierarchy and multi-cycle violation, may then be analyzed to identify a root cause of the violation using a rule. Such a rule may be used for triaging various failures in the cross-domain, cross-hierarchy and / or multi-cycle violation of the digital integrated circuit. A design change in the design of the digital integrated circuit may then be recommended based on the identified root cause of the violation. In this manner, the root cause of failures are effectively identified in the design of digital integrated circuits using an offline analysis of cross-domain, cross-hierarchy and / or multi-cycle violations using a rules-based approach.

This invention discloses an automated tuning method and system for large language model service configurations, belonging to the fields of artificial intelligence and cloud computing technology. The invention includes an offline analysis module for performance profiling of the large language model (LLM) service system under a finite configuration set and for collecting training data; an online search module for exploring and evaluating the performance of different configurations in the configuration space based on a Monte Carlo tree search algorithm; and a simulator module for receiving the configurations generated by the online search module and predicting the performance metrics of the configurations under a target workload based on a logical step simulation model. This invention effectively solves the problems of low search efficiency and poor performance of existing automatic tuning methods in existing large language model service frameworks (such as vLLM, SGLang, etc.) due to the huge number of configuration parameters (reaching a petabyte-scale search space) and the complex dependencies and mutual exclusion relationships between parameters.

This invention provides a gear power transmission device for a speed reducer, relating to the field of gear reducer technology. The device includes a speed reducer body and an intelligent monitoring and self-cleaning system mounted on a base plate. This invention, through real-time monitoring of multiple parameters such as oil viscosity, abrasive particle concentration, and morphology, can accurately capture early anomalies and effectively distinguish wear types. After diagnosing anomalies, it can automatically purify the lubricating oil online, removing harmful abrasive particles without stopping the machine, effectively extending the lifespan of the oil and equipment. The highly integrated multi-functional modules within a unified detection box result in a compact structure, improving the overall reliability of the system and avoiding the looseness and unreliability issues of external structures in harsh industrial environments, thus enhancing the intelligence level of fault diagnosis. The introduction of machine learning-based automatic particle morphology recognition technology replaces offline analysis relying on professionals, lowering the technical threshold and making fault diagnosis more intuitive and efficient.

The invention discloses a tunneling equipment high-speed sampling health diagnosis and protection method and an electric control system thereof, and relates to the field of tunneling equipment electric control systems, and the tunneling equipment high-speed sampling health diagnosis and protection method comprises a multi-loop three-phase current transformer, a common-bus three-phase voltage transformer, a high-speed sampler, a processing analyzer, a transmitter, an embedded industrial personal computer and an electric component formed by a controller. By high-speed acquisition and processing of original multi-electric-quantity signals, a traditional electric control system electric quantity sampling analysis mode is replaced, fault pre-warning, fault post-protection and original electric quantity information real-time storage are realized, online advanced pre-warning and protection are realized, offline analysis of high-speed sampled original large-capacity data is realized, functions of a small oscilloscope are integrated, and the system is simple in structure and convenient to use. The tunneling equipment electric control system is innovated, and the tunneling equipment electric control system has new functions of key transmission part degradation condition prediction, power supply network harmonic content analysis, ultra-high-speed original signal sampling, large-capacity data real-time transmission and storage and the like.

The application provides a risk early warning method and device for a hydrogen storage bottle group for vehicles. The method fuses multi-dimensional state information of the hydrogen storage bottle group, uniformly and correlatively analyzes hydrogen remaining amount, thermal state, safety state, health state, and residual life information, and determines corresponding risk early warning information, thereby comprehensively characterizing the operation state of the hydrogen storage bottle group, and improving the integrity and accuracy of risk identification. Meanwhile, the application performs dynamic analysis based on real-time collected state information, so that risk judgment is more timely, effectively reduces the lag and misjudgment problems caused by traditional single threshold or offline analysis methods, and further generates predicted risk early warning information by introducing historical state information to construct a time sequence, combining a trained prediction model to predict future states, improving risk early warning from passive response to active prediction, thereby enhancing the foresight and active safety capability of the system.

The application discloses a kind of whole process state analysis methods of grounding resistor, comprising the following steps: S1.grounding resistor state acquisition device collects the real-time running condition data of grounding resistor, and the real-time running condition data is transmitted to embedded processor;S2.embedded processor stores and processes the real-time running condition data of grounding resistor, and the real-time running condition data of grounding resistor is uploaded to station end server;S3.cloud server carries out offline analysis and test to the state of grounding resistor, obtains the state transition data of grounding resistor, and updates offline database;S4.according to the real-time running condition data of grounding resistor and state transition data, the state of grounding resistor is analyzed in real time by station end server, and real-time database is updated.Temperature evaluation is used for early warning of abnormal state, resistance value evaluation is used to determine whether the current state of resistor is stable, energy loss is used to determine the service life of resistor, to improve the safe and stable operation of distribution network.

The invention discloses a high and cold pasturing area greenhouse gas automatic acquisition and analysis static box, the static box comprises a box cover and a base which are connected through a sealing mechanism and form an airtight space, and an in-situ multi-gas analysis module, a multi-parameter environment sensor, a control and edge calculation unit and a wireless transmission module are integrated in the box; according to the invention, the high-precision multi-gas in-situ analysis module, the distributed environmental factor sensing network and the edge calculation unit are highly integrated in the box body, so that the system can synchronously collect key environmental parameters such as gas concentration data and soil temperature and humidity at high frequency during each automatic closed measurement period; flux calculation and data standardization processing are completed at an equipment end in real time, and finally, a result is remotely transmitted through a wireless network, so that the requirements of manual on-site sampling, air bag storage and transportation and laboratory off-line analysis are eliminated.

The invention discloses a boiler combustion performance testing system, and relates to the technical field of boiler performance testing, and the system comprises a data collection module which collects test data in real time in a boiler combustion test process; the data transmission module receives the test data, forwards the test data through the wired communication link, and switches to the wireless communication link to forward the test data when identifying that the wired communication link has a fault; the data storage module stores the test data; and the data analysis and feedback module calls the test data stored in the data storage module, and performs deep analysis and analysis result feedback on the test data in combination with real-time monitoring, off-line analysis and report generation functions. Therefore, the system can realize real-time synchronous acquisition, automatic transmission, intelligent analysis and safe storage of test data, provides data support for boiler combustion performance optimization and fault diagnosis, and improves the test efficiency and test precision of boiler combustion performance.

The invention relates to HMM decoding compensation for speech recognition and multi-structure decoding for low resource command recognition. Techniques are described for recognizing spoken wakeup words (WWs) or commands for human machine interfaces using a speech recognition system that does not require any WW / command matched speech data for training. The system is trained using textual or graphical representations of WWs or commands prior to deployment. The technique includes receiving a target phrase for recognition by a speech recognition model. The technique includes analyzing a sequence of acoustic units representing a target phrase when the target phrase is spoken to generate offline analysis data. The technique further includes constructing a speech recognition model based on the offline analysis data to decode the speech signal of the target phrase according to the acoustic unit. The technique further includes processing the speech based on the speech recognition model to detect the presence of the target phrase.

The invention relates to the field of e-commerce, and discloses an optimization method and system for an e-commerce transaction platform, and the method comprises the following steps: carrying out the dynamic service management; s1, real-time data processing; s3, user intention modeling is carried out; s4, dynamically arranging a strategy; and S5, full-link monitoring is carried out, in the aspect of system architecture, an innovative dynamic management framework reconstructs a traditional service management mode through a service grid technology, and automatic sensing of micro-service topology and intelligent distribution of flow are achieved. A self-adaptive fusing and service degradation mechanism guarantees the service continuity in a high-concurrency scene, a multi-dimensional gray release function remarkably reduces the online risk of a new function, the platform has excellent elasticity and stability, a data processing level and a streaming batch integrated architecture break through the limitation of traditional offline analysis, second-level response is achieved through a unified data pipeline, and the service performance of the platform is improved. Data consistency is ensured through real-time ETL and dimension association, real-time data support is provided for precision marketing through online feature engineering, and the operation decision-making efficiency is greatly improved.

The invention relates to a marigold extraction process intelligent control method, device and equipment and a medium thereof. The method comprises the following steps: establishing an accurate calibration model between the concentration of a key oxidation byproduct and spectral characteristics offline, and applying the model to an online monitoring system to obtain the concentration data of the byproduct in real time; the instantaneous generation rate is obtained through time sequence differential calculation on the basis of real-time concentration data, intelligent correlation analysis is conducted on the generation rate and extraction process parameters, and therefore the root cause of generation of the by-product is accurately deduced; finally, the targeted suppression operation is automatically triggered according to the diagnosis result, and the control effect is verified by monitoring the generation rate change in real time, so that the complete closed-loop control from byproduct monitoring, tracing to suppression is realized, the hysteresis problem of traditional offline analysis is effectively solved, and the method is suitable for popularization and application. The quality control level and the product stability in the marigold extraction process are obviously improved.

The present application relates to the technical field of heat analysis, in particular to a kind of aluminum alloy melt quality detection method, device and system.The method is based on temperature time series data to calculate the instantaneous cooling rate of each monitoring point at each collection time;According to the instantaneous cooling rate of each monitoring point, the current process risk index is determined;According to the preset hydrogen sensitivity weight, the current hydrogen content, the current process risk index and the preset risk baseline value are fused, and the comprehensive risk score of each monitoring point is determined;Wherein, hydrogen sensitivity weight and risk baseline value are obtained by the following offline analysis process: according to the correlation between the historical process risk index of each monitoring point and corresponding historical hydrogen content, the hydrogen sensitivity weight of each monitoring point is determined, and the risk baseline value is determined based on the historical process risk index of each monitoring point, so as to accurately locate the potential pore risk area.

The utility model discloses a kind of networkable data acquisition devices for rail transit vehicle, solve the problem that rail transit vehicle test equipment cannot simultaneously have effective communication with vehicle, offline analysis of data, multiple car data synchronous analysis;The utility model includes cabinet, power module, MVB communication module, data acquisition component, main processor, network communication module are fixedly connected in cabinet;Power module is powered for data acquisition component, main processor;The input end of data acquisition component is connected rail transit vehicle, for collecting the operation data of traffic vehicle, output end connects main processor;Main processor is connected host computer by network communication module;The main processor and host computer of rail transit vehicle are connected by MVB communication module, the operation data of rail transit vehicle is driven to be collected by host computer, and data transmission is carried out by MVB communication module.

The invention relates to a respirable dust concentration measuring method based on particle counting, and belongs to the field of environment monitoring. Existing respirable dust measuring methods are either long in offline analysis period and incapable of real-time monitoring, or depend on a mechanical hierarchical structure, so that equipment is complex, maintenance is frequent, and power consumption is high. Multi-channel particle size distribution data are obtained through an optical particle counter, optical equivalent particle sizes are converted into aerodynamic particle sizes through an iterative algorithm based on Canningham slip correction, and then the number correction coefficient of each channel is calculated according to a BMRC curve fitting formula formulated by the British Medical Research Committee. And converting to obtain the mass concentration of the respirable dust. The method does not need any mechanical classifier, the whole process is realized through optical measurement and algorithm, the equipment structure is obviously simplified, the maintenance difficulty and power consumption are reduced, the time resolution and the measurement stability are improved, and the method is particularly suitable for real-time continuous monitoring of narrow spaces such as mine underground and tunnels.

The invention relates to the technical field of industrial process monitoring and anomaly detection, in particular to a cyclone anomaly detection method, system and equipment in the ore grinding and grading process, and the method comprises the steps that multi-dimensional working condition data generated in the operation process of a cyclone is collected, the working condition data is preprocessed, and key features are extracted; a probability distribution model of the normal operation condition of the cyclone is constructed based on the key features, and monitoring statistics reflecting the deviation degree of the current operation state and the normal condition are calculated; according to the historical operation data, adaptively determining an abnormal judgment control limit, and combining monitoring statistics to realize abnormal detection of the operation state of the cyclone; and when an abnormal working condition is detected, identifying and diagnosing an abnormal type. Therefore, stable detection and diagnosis of the abnormal working condition of the swirler in the ore grinding and grading process can be achieved without depending on manual experience, the accuracy and reliability of abnormal recognition are improved, and the method is suitable for off-line analysis and operation state evaluation of the production process of a dressing plant.

The invention relates to the technical field of information security, in particular to a chaos-based script code protection method and device, a computer readable storage medium and computer equipment, and the method comprises the following steps: S1, performing flow segmentation and simulation on a protected script: giving a web front-end script, and firstly performing abstract syntax tree level analysis on the web front-end script; according to the method, the PWLCM chaotic mapping is introduced, so that the context relation, which is easy to reverse, of the script code is successfully disorganized in a static state and conditionally submitted to a plurality of index sequences to be controlled; an attacker cannot correctly analyze correct sources and directions of parameters and return values associated with key system calling in protected script codes only by off-line analysis in a static state, an introspection integrity self-checking logic is embedded in each sub-process, and encryption protection is performed on communication between the front end and the rear end of a web system. Therefore, the protected script can actively resist reverse analysis and protect the security of end-to-end data.

The invention relates to a cabin man-machine work efficiency comprehensive evaluation system and method. Comprising a time synchronization controller and a test work station, the test work station comprises a data synchronization module used for receiving signals and data forwarded by the time synchronization controller, performing time synchronization processing based on clock source signals, forming synchronous data frames with timestamps, and sending the synchronous data frames to a comprehensive processing module and a test task module; the comprehensive processing module is used for processing and analyzing the physiological data and the task data in a real-time mode and an offline mode; the test task module is used for performing test task configuration, visual monitoring and data acquisition control; the analysis result module is used for visually displaying the offline analysis result; the comprehensive evaluation module is used for comprehensively evaluating man-machine work efficiency indexes based on the offline analysis result and a preset evaluation index system; and the data management module is used for storing and managing configuration data, test data and evaluation results required by the system. A unified clock reference is provided through the time synchronization controller, nanosecond-level or microsecond-level time synchronization of multi-source heterogeneous data such as eye movement, physiology and tasks is achieved, and a foundation is laid for follow-up accurate causal correlation analysis.

The invention relates to the technical field of semiconductor packaging, in particular to a crimping quality real-time detection method and system.The method comprises the steps that pressure sensor data and displacement encoder data in the crimping process are collected in real time, and a pressure-displacement curve is generated; characteristic parameters of the pressure-displacement curve are extracted, wherein the characteristic parameters comprise the pressure fluctuation amplitude of the contact stage, the local slope change value of the main pressure interval and the high-frequency oscillation frequency of the pressure maintaining stage; synchronously normalizing the pressure fluctuation amplitude, the local slope change value and the high-frequency oscillation frequency into dimensionless risk values; and respectively carrying out weighted fusion on the risk values through respective weight coefficients, calculating a comprehensive quality score, and judging the crimping quality according to the comprehensive quality score. According to the method, the three-stage characteristic parameters are extracted through the pressure-displacement curve, a traditional single-point threshold value method is replaced, transient abnormity is accurately captured, rapid response can be achieved, and the hysteresis problem of crimping quality offline analysis is solved.

The application discloses an API granularity-based shared library deflation method and system, which comprises the following steps: clustering page-aligned dependent clusters by analyzing the function dependence of each exported API offline, and rewriting the binary layout; intercepting API calls by a customized dynamic linker at runtime, dynamically adjusting the code page execution authority in combination with metadata, and activating only the required page of the current API; the scheme can maintain the cross-process memory sharing of the shared library, avoid memory inflation caused by copy-on-write (CoW), reduce the number of available gadgets by more than 90%, and significantly improve the ROP / JOP attack resistance; the system supports multithreading safety, hot API optimization, is compatible with the standard ELF format, does not need to modify the application, is transparent in deployment, and is suitable for Linux high-security and high-density running environments; the application can maintain the cross-process memory sharing advantage of the shared library while significantly reducing the attack surface and memory inflation problem.

This application relates to a method, apparatus, and device for real-time wind field estimation and trajectory prediction for a parachute system. The method first analyzes historical wind field data of the target area offline, classifies wind field types, matches specific parameters, and trains a wind field classifier. In the online phase, it acquires real-time integrated radar data of the parachute system, identifies the current wind field observation vector using a dynamic model, matches the wind field type and parameters through the classifier, constructs an adaptive Kalman filter model based on the parameters to achieve optimal estimation of wind field disturbances, and fuses the background wind field and disturbances from an uncertain wind field model to obtain complete wind field estimates and future predictions, quantifying the uncertainty, and finally completing trajectory prediction. This method improves the real-time performance, accuracy, and robustness of wind field estimation and trajectory prediction, ensuring parachute landing accuracy and mission safety.

This invention discloses a method, terminal, medium, and product for processing and analyzing industrial process data, relating to the field of data analysis and processing technology. The method includes: exporting multi-source industrial process data into a common text format file; performing standardization adaptation, cleaning, completion, and time-series alignment and merging on the text data to obtain standardized data in a unified and compatible format; using professional analysis tools to conduct in-depth offline analysis of the standardized data, including periodic statistical analysis, customized signal processing, and mathematical operations oriented towards the process scenario; generating customized analysis reports according to preset templates based on different user groups and completing automated publishing; and exporting the standardized data into the native proprietary format of the analysis tools, archiving and storing it together with the analysis reports. This invention achieves unified processing and in-depth analysis of multi-source heterogeneous industrial data, improves the automation level and reusability of data analysis results, and constructs a complete closed loop from data to knowledge.

The invention relates to the technical field of heat analysis, in particular to an aluminum alloy melt quality detection method, device and system. The method comprises the following steps: calculating an instantaneous cooling rate of each monitoring point at each acquisition moment based on temperature time sequence data; determining a current process risk index according to the instantaneous cooling rate of each monitoring point; according to a preset hydrogen sensitivity weight, the current hydrogen content, the current process risk index and a preset risk baseline value are fused, and a comprehensive risk score of each monitoring point is determined; wherein the hydrogen sensitivity weight and the risk baseline value are obtained through the following offline analysis process: determining the hydrogen sensitivity weight of each monitoring point according to the relevance between the historical process risk index of each monitoring point and the corresponding historical hydrogen content, and determining the risk baseline value based on the historical process risk index of each monitoring point, so that the risk baseline value is obtained. And a potential pore risk area can be accurately positioned.

The application belongs to the field of data training, and particularly relates to a heterogeneous perception data parallel training method for a consumer-level GPU cluster. Resource self-adaptive sub-models are generated for heterogeneous consumer-level GPUs through model pruning to decouple layer-by-layer dependency, and then the gradients of the overlapping areas are synchronized across GPUs. Specifically, a sub-model generator and a cluster-based reduction mechanism are designed to quickly generate resource self-adaptive sub-models and realize efficient gradient synchronization. An efficient offline analyzer is designed to immediately determine the optimal configuration (micro-batch size and sub-model size) of parallel training, so as to balance memory utilization and computing efficiency and realize load balancing.