108 results about "Analysis working" patented technology

A modular open system architecture for common intelligence picture generation is disclosed. The system receives intelligence requirements through a multimodal artificial intelligence system and calculates collection feasibility across multiple intelligence sources based on physical and temporal conditions. The system develops integrated collection plans through the containerized analytics workbench using containerized analytics modules and processes intelligence through GPU-accelerated deep learning models for automated target recognition. Satellite collection is orchestrated through satellite data acquisition optimization platform by evaluating weather conditions, orbital parameters, and sensor capabilities, while space domain awareness is maintained through space domain awareness system for real-time collection asset management. Multi-source intelligence data is fused through multi-source intelligence fusion system to populate a common intelligence picture. The system implements automated workflows for intelligence analysis and dissemination while maintaining security controls, with the containerized analytics workbench providing pattern of life analysis and dynamic exploitation through containerized microservices.

The invention provides a planning analysis workflow intelligent arrangement method and device based on a natural language instruction, and the method and device can deeply understand the complex analysis intention of a plan in a natural language through a mixed analysis engine comprising a large-scale language model and a named entity recognition model. And according to the understood intention, a proper operator and a proper model are autonomously selected from a tool library in combination with a planning analysis knowledge graph, so that a complete, logic self-consistent and executable multi-step analysis workflow can be autonomously and dynamically arranged, the workflow is automatically executed, and multi-modal data is collected. According to the method and the device, the technical problems in multiple aspects from keyword matching to composite intention deep understanding, from artificial process design to knowledge-driven intelligent arrangement and from one-way instruction execution to interactive exploration analysis in the prior art are solved, and the method and the device have the advantages that the technical problems in multiple aspects from keyword matching to composite intention deep understanding, from artificial process design to knowledge-driven intelligent arrangement and from one-way instruction execution to interactive exploration analysis are solved; the planning work efficiency can be improved, the technical threshold is reduced, and industry digital transformation is promoted.

Embodiments facilitate software analysis by machine learning (ML) models, through extensible software analysis architecture (ESAA) or software analysis work allocation (SAWA). Pluggable ESAA ML modules include a vetted prompt which is actionable for software analysis, with a vetting certification. Some ML modules contain computational cost information such as a token count or model round trip time. Tools are tailored to ML analyzers to control background execution, availability offerings, and results displays. SAWA determines how well a software analyzer meets a prompt's software analysis requirements, and an ML planning model generates an analysis plan that balances software analysis workloads among ML analyzers and non-ML analyzers. ML analyzers are favored for summarization, task decomposition, task scheduling, and source code change review, while non-ML analyzers are otherwise favored. Non-ML analyzers gather control flow, data flow, internal structure, and similar context which is then supplied to an ML analyzer.

The invention provides a creative video understanding and analyzing system and a creative video understanding and analyzing method, which relate to the technical field of image video processing and adopt a collaborative architecture formed by sequentially connecting intelligent agents in five stages of video sub-mirror identification, video outline extraction, creative factor analysis, shooting logic induction and audio rhythm analysis in series. The full-process end-to-end automatic analysis and generation of the creative videos from original input to structured creative video scripts are realized, and through professional division and collaboration of multiple agents, deep mirror segmentation, plot logic carding, creative bright spot extraction, shooting technique induction and sound and picture rhythm matching of the videos can be automatically completed; according to the method, manual analysis work which needs multi-field experts to consume several hours and even several days originally is compressed to be completed in minutes, the creative video generation efficiency is improved, the professionality and consistency of output results in the aspects of mirror splitting, narration, vision and audio are guaranteed, and the manpower and time cost of advertisement creative analysis and script generation is reduced.

The utility model relates to the technical field of cold box interlayer gas oxygen content analysis, in particular to a cold box interlayer gas oxygen content on-line analysis device which comprises a sampling pump, a three-way electromagnetic valve, a pretreatment box, an analysis instrument and a control system, wherein the sampling pump is used for pressurizing and introducing interlayer gas of the cold box into the analysis device; the analysis instrument is used for analyzing the oxygen content in the pretreated gas; the three-way electromagnetic valve is arranged between the sampling pump and the analysis instrument and is used for remotely switching and analyzing the waste nitrogen and the cold box interlayer gas; the pretreatment box is connected between the three-way electromagnetic valve and the sampling pump. Through remote switching of the three-way solenoid valve and automatic logic setting of the DCS, online intelligent analysis of the oxygen content of the interlayer gas of the cold box is achieved, and the analysis accuracy and efficiency are improved; and an operator can finish the analysis work of the waste nitrogen and the interlayer gas of the cold box without frequently and manually switching an analysis instrument, so that the operation burden is reduced.

The invention discloses an energy data classification and grading method, system, equipment and medium based on a BERT model, and relates to the technical field of power system data grading and classification, and the method comprises the specific steps: making a data classification and grading rule, collecting a data set, carrying out the preprocessing of the data set, constructing an energy data classification and grading model, and carrying out the classification and grading of the energy data according to the data characteristics of the energy industry; and inputting the preprocessed data set, evaluating and optimizing the model, and executing an energy data classification and grading task according to the model. The method does not need to depend on traditional manual rules or tedious feature engineering, and is suitable for classification and grading scenes of massive and multi-type energy data of an energy big data center. The method has the advantages of being high in energy data classification and grading efficiency, high in recognition precision, adaptive to energy industry data characteristics and low in operation and maintenance cost, and can effectively support subsequent data processing and analysis work of an energy data center.

The present invention discloses a method, system, and device for mouse event interaction based on a general gyroscope, belonging to the technical field of mouse event interaction. The method includes the following steps: monitoring the output data of the gyroscope in a stationary state, and processing the output data of the gyroscope in a stationary state to obtain an evaluation value of the static offset degree of the gyroscope; collecting the output data of the gyroscope, and performing initial data calibration on the output data of the gyroscope according to the evaluation value of the static offset degree of the gyroscope; monitoring the working environment data and the working state data of the gyroscope, comprehensively analyzing the working environment data, the working state data, and the evaluation value of the static offset degree of the gyroscope to obtain an evaluation value of the dynamic offset degree of the gyroscope.

The invention discloses a log parameter semantic analysis method and device and a storage medium. The method comprises the steps of obtaining initial log data; extracting a target log parameter in the initial log data, and determining a target clustering template corresponding to the target log parameter; determining N candidate tags corresponding to the target log parameter according to the initial log data, the target clustering template and a first preset large language model; based on the N candidate tags, determining the similarity between the target log parameter and m-1 log parameters to obtain m-1 tag similarities; and determining a target tag according to the target clustering template, the N candidate tags, the m-1 tag similarities, the m-1 log parameters and a second preset large language model. By adopting the embodiment of the invention, the efficiency of log analysis work is improved.

The invention discloses a rock core CT image crack segmentation method and device based on deep learning. The method comprises the following steps: making a training data set; expanding the number of training samples in the training data set to form a new data set; a deep learning network model is constructed, the deep learning network model comprises a U-Net network, a contraction path for feature extraction in the U-Net network adopts a feature extraction network based on a VGG-16 network, and an up-sampling expansion path in the U-Net network is added with a CBMA attention module. The CBMA attention module is used for changing the attention of the model to different spatial positions and different channels in the feature map and improving the weight of the area where the rock core crack is located; performing training and parameter adjustment on the deep learning network model by using the training set until the model converges; and testing the trained deep learning network model by using the test set, and evaluating the crack segmentation effect of the deep learning network model. According to the invention, the efficiency of rock core CT image automatic analysis work can be improved.

The invention discloses an intelligent fault tree generation method based on cooperation of a multi-modal large model and a large language model, and relates to the field of fault tree analysis. In order to solve the defects of low tree building efficiency, insufficient cross-modal information processing and incomplete fault causal chain reasoning in the prior art, the technical scheme provided by the invention comprises the following steps: carrying out topological structure analysis on a system flow chart by adopting a multi-modal large model to obtain an equipment network table; taking the equipment network list as input, and performing fault mode directional retrieval on the equipment information base by adopting a large language model to obtain a fault mode list; taking the equipment network list and the fault mode list as input, performing failure reason reasoning by adopting a large language model, and establishing a fault causal chain from a system layer to an equipment layer; and taking the fault causal chain as input, constructing a fault tree by adopting a large language model, and generating a complete fault tree structure from a system top event to an equipment basic event. The method is suitable for safety and reliability analysis work of a complex industrial system.

The invention relates to the technical field of petrochemical engineering analysis, and provides a form analysis method and system for sulfides in a sulfuric acid alkylation working solution, and the analysis method comprises the following steps: S1, sample collection and pretreatment; s2, carrying out derivatization reaction; s3, separating and detecting; s4, data processing and analysis; the system comprises a sample pretreatment module, a derivatization reaction module, a separation detection module and a data processing and analysis module, and the analysis method provided by the invention can accurately and quickly analyze the forms and contents of various sulfides in the working solution, is high in sensitivity and accuracy, simple, convenient and quick to operate, has good universality and expansibility, and can be widely applied to industrial production. The method is suitable for qualitative and quantitative analysis of various sulfide forms in the field of petrochemical engineering, and has important industrial application value.

The technical scheme of the present application discloses a kidney transplantation single disease follow-up database system based on a hospital intranet environment, comprising a data integration layer, an intelligent analysis layer and a doctor-patient linkage layer. Through the cooperative operation of the three-layer technical architecture designed by the present application, the three core problems of the prior art are comprehensively solved, and the following technical effects are achieved: at the data integration level, automatic and real-time integration of multi-port medical data of kidney transplantation patients is realized, the data integration efficiency is improved by 90%, the accuracy rate reaches 99.5%, and the traceability and privacy security are significantly improved; at the data analysis level, the AI-driven analysis model realizes automatic generation of patient whole-cycle health reports, large-sample group feature mining and real-time abnormality early warning, and the doctor data analysis workload is reduced by 80%, and the abnormal data response time is shortened to the minute level.

The invention provides a goaf intelligent drilling system and method. The goaf intelligent drilling method comprises the following steps that datum holes and engineering holes are formed in an exploration area according to a preset proportion; a rock core sample is obtained through datum hole construction; various parameters are collected in real time in the construction process; a convolutional neural network model is constructed, and the mapping relation between the drilling parameters, the image features, the stratum physical property parameters and the logging data and the geological database is established; constructing a geological reference database; engineering hole drilling construction is carried out, and various data are collected in real time in the construction process; inputting a neural network model, and carrying out lithology identification, stratigraphic division and mining-induced fracture prediction analysis work; constructing a three-dimensional geologic model based on mining data, drilling results, fusion logging data and lithology inversion results; and predicting the drilling efficiency. And the abnormal drilling fluid consumption, pressure fluctuation and vibration spectrum characteristics are analyzed, so that accident advanced early warning is realized. According to the system and the method, the exploration efficiency is remarkably improved, and in-hole accidents can be early warned through abnormal drilling parameters.

The invention discloses a power investment modeling system, and relates to the technical field of power investment modeling system design, and the system comprises an application layer which is used for processing system-level function and business service coordination; the data layer is responsible for storage, management and efficient access of various data, and the data layer is connected with the application layer; the infrastructure layer is used for providing technical basic support required by system operation, and the infrastructure layer is connected with the data layer; the service layer is used for realizing core logic and a calculation model of the power investment business, and the service layer is connected with the infrastructure layer; through data driving and a professional model, an experience decision is converted into quantitative analysis, scientization and precision of investment decision are achieved, and the investment success rate and the risk resisting capacity are remarkably improved; through automatic process integration, the analysis work of several weeks is shortened to the hour level, automation and intelligentization of the whole process are achieved, the analysis efficiency is improved, and rapid market decision and response are supported.

The utility model discloses a Coriolis force effect demonstration device based on double visual angles, and belongs to the technical field of Coriolis force effect demonstration devices. Comprising a small ball for simulating a mass point; a base; a horizontally arranged rotating assembly is arranged on the base plate; a supporting plate is horizontally arranged on the rotating assembly; a simulation disc is horizontally arranged on the supporting plate, and the top surface of the simulation disc is provided with a paraboloid. The driving assembly drives the rotating assembly to rotate, the supporting plate is driven to rotate, and then the simulation disc is driven to rotate. Wherein the top surface of the simulation disc is provided with a paraboloid, so that simulation of an earth rotation environment is realized. When the Coriolis force effect demonstration device is used, the driving assembly drives the simulation disc to rotate, then the small balls are placed in from the edge of the simulation disc at a certain speed, the small balls are affected by Coriolis force, the motion trails of the small balls are changed, and therefore the purpose of Coriolis force effect demonstration is achieved. And the image or video data of the motion trail of the small ball on the simulation disc is acquired by the camera assembly, so that subsequent comparative analysis work is facilitated.

We provide the system. [Solution] A device for analyzing visual and auditory information collected in the work environment, A device that identifies tasks that can be automated based on the aforementioned analysis, A device that proposes an optimal automation method for the aforementioned task, A system that includes this.

The utility model discloses a facial emotion monitoring and analyzing device, which comprises a monitoring device main body, a data switch, a data analyzing computer and a main monitoring camera, and is characterized in that the monitoring device main body comprises a fixed mounting base, a disc is arranged at the top of the fixed mounting base in an electric driving manner, and support frame plates are arranged on two sides of the top of the disc; a main frame is arranged on the top of the inner side of the supporting frame plate, an auxiliary frame is arranged on the inner side of the main frame, a first electric push rod for driving the auxiliary frame to be vertically adjusted is arranged on the top of the main frame, an auxiliary monitoring camera is arranged on the inner side of the auxiliary frame, and a second electric push rod for driving the auxiliary monitoring camera to be transversely adjusted is arranged on one side of the auxiliary frame. Compared with the prior art, the face emotion monitoring system has the advantages that an identified person is anchored and monitored through the main monitoring camera, then the auxiliary monitoring camera with the adjustable top is matched to capture tiny shaking of the identified person, and therefore face emotion monitoring analysis work can be conducted on the identified person to the maximum extent.

The embodiment of the invention provides a log analysis and risk analysis method and system. The method comprises the following steps: pre-compiling a rule configuration file to generate a regular object, and storing the regular object in a pre-compiled rule list; wherein the regular object is packaged with a plurality of fields; performing log format adaptive analysis on the to-be-analyzed data source text to generate a log message; cyclically traversing the rule list, searching content matched with the regular object in the to-be-analyzed data source text so as to filter repeated results and determine to generate alarm description; constructing the log message and the alarm description into a de-duplicated data pair; performing cache check operation on the data pair to generate a first cache result; performing prediction operation on the data pair batch calling AI model to generate a second cache result; and generating a prediction result based on the first cache result and the second cache result. The problem that the efficiency of log analysis and risk analysis work is low in the prior art is solved.

The invention provides an airborne software structure incremental coverage rate analysis system and analysis method. The airborne software structure incremental coverage rate analysis system comprises a self-adaptive baseline management module, a change influence domain analysis module, an incremental coverage rate calculation module and an automatic report generation module. The method comprises the following steps: establishing a tracing relation among requirements, codes and use cases, capturing code version change to construct a change influence domain, carrying out change difference analysis in combination with historical version coverage rate data, identifying and running use cases which need to be additionally and independently executed in a current version, and obtaining a newest code structure coverage rate. And a coverage rate analysis report can be automatically updated and generated. By applying the analysis system and the analysis method, the technical bottlenecks in the aspects of large coverage analysis difficulty of an airborne software verification structure, redundant analysis work and the like can be solved.

The utility model relates to the technical field of ham harmful ingredient detection, and discloses a ham harmful ingredient detection and analysis device which comprises an operation table, a placing table fixedly connected to the top of the operation table, a supporting pad fixedly connected to the top of the placing table, a solution bottle arranged at the top of the supporting pad, and two square grooves formed in the placing table. A first sliding plate is arranged in the placing table, guide grooves are formed in the two ends of the first sliding plate, sliding rods are arranged in the guide grooves and slidably connected with the first sliding plate, a square plate is fixedly connected to the tops of the sliding rods, the square plate is arranged in the square groove, and the two first guide rods are arranged on the square plate in a penetrating mode; the square plate is slidably connected with a first guide rod which is fixedly connected with the placing table, and the top of the square plate is fixedly connected with a clamping plate. The device is simple to operate, a solution bottle can be conveniently fixed and unfixed, the stability of the solution bottle during mixing can be ensured, and the normal detection and analysis work can be ensured.

The application discloses a kind of distributed systems, and its fault test method, device and medium, it is related to distributed system technical field, for realizing the fault test of distributed system, for the fault superposition problem that traditional fault test scheme is difficult to solve, provide a kind of distributed system fault test method, client / server architecture is adopted, the independent fault test of each node can be realized, whether the fault cause and fault processing meet the expectation are all in-depth to each node, so as to effectively avoid the problem that the fault between multiple nodes is difficult to judge because of superposition. Based on this, the fault test of distributed system is carried out by the method, can improve test efficiency and accuracy, so as to be favorable to improve the software quality of distributed system, reduce maintenance cost, reduce the additional analysis workload of development.

The application relates to the field of aluminum rod defect detection equipment, in particular to a defect detection equipment and detection process for recycled aluminum rod production, which comprises an aluminum rod defect detector, an aluminum rod body passes through the inside of the aluminum rod defect detector, the aluminum rod defect detector comprises a second detection part and a first detection part, one end of the second detection part is fixedly connected with the first detection part, one end, away from the second detection part, of the first detection part is provided with a mounting flange seat, the aluminum rod defect detector is mounted at the outlet end of a recycled aluminum rod extruder through the mounting flange seat, a second detection assembly is arranged in the inside of the second detection part, the second detection assembly comprises a second rotating frame, and both ends of the second rotating frame are fixedly connected with second fixed rings, the application can directly avoid the influence of most external factors on the detection result, source detection is carried out, the detection result can be more efficient and accurate, and the supervision and analysis work on the recycling equipment and recycling process are facilitated.

The utility model relates to the technical field of medicine inspection and analysis, and discloses an analysis titration device for medicine inspection, which comprises an operating table, a protective door is rotatably connected to the front side of the operating table, a fixing mechanism is arranged at the top of the operating table, a titration mechanism is arranged at the top of the operating table, and the fixing mechanism comprises a first servo motor. The first servo motor is fixedly connected to the inner bottom of the operation table, the rear side of the first servo motor is fixedly connected with a worm, the left side of the worm is meshed with a worm gear, the worm gear is internally and fixedly connected with a rotating rod, the top of the rotating rod is fixedly connected with a placement table, and the top of the placement table is provided with a volumetric flask. By means of the arranged fixing mechanism, when medicine needs to be inspected and analyzed, a first servo motor, a worm, a worm gear and a rotating rod are matched, rotation of the containing table can be achieved, a volumetric flask is conveniently driven to rotate, and a second servo motor drives a two-way threaded rod to rotate.

A search platform can receive a complex query, and generate raw data in response to the complex query, based on artificial intelligence searching of a semantic search space, relevant to the context of the complex query. The platform can obtain, generate and / or recommend analytical models capable of providing robust answers to the complex query. The platform can augment the semantic search space with analytical models and search the augmented search space for analytical models relevant to the complex query. The answers, provided by the platform to the complex query, can be the result of performing complex analytical workflows.

The application discloses a flange bolt abnormal installation sequence identification method, device, equipment and readable storage medium in the safety production technical field, and can complete all analysis work in a time much less than that required by manual review after the installation video is recorded, and automatically compares and checks the recorded actual operation sequence with the standard procedure, so that the abnormal installation sequence is detected. The application mode of the rapid verification ensures the quality and safety of the assembly process, can help the on-site managers and workers to immediately take corrective measures, and eliminates potential structural hidden dangers before the equipment is put into use.

We provide the system. [Solution] It has natural language processing capabilities and means for analyzing the content of work documents, A means for selecting an appropriate machine control tool based on the analyzed work documents, Means for generating control codes for selected machine control tools, A means for applying the generated control code to the execution environment and reporting the results, Means for automating the functions of industrial facilities, A system that includes this.

The invention relates to the cross technical field of artificial intelligence and reliability system engineering, and provides an MBSE-LLM-based functional danger intelligent analysis method and device. According to the method, an MBSE model is utilized to construct a function model of an analysis object, retrieval enhancement knowledge is injected to obtain an enhanced vector database, then basic description and associated documents of a target function are determined, the basic description and the associated documents are fused to obtain enhanced description, a risk factor list is generated based on the enhanced description, and the risk factor list is analyzed. According to the method, the defect that traditional FHA depends on manual completion of field experts is overcome, a model-based system engineering method and a large language model technology are comprehensively utilized, and the formed intelligent FHA method can significantly optimize the overall process of function risk analysis and improve the risk analysis efficiency. The accuracy of an FHA result and the efficiency of analysis work are effectively improved, and efficient iteration of traditional FHA can be guided.

The present invention provides a production system capable of making a production plan according to changes in work contents and resources and quickly and reasonably distributing the resources. This production system comprises: a resource information unit that includes resource information in a factory which produces a product on the basis of a production plan; a production planning unit that arranges workers suitable for the production plan on the basis of the content of the resource information unit; a plan inference and determination unit that observes and analyzes the progress status of work after personnel arrangement by the production planning unit; and a resource redistribution unit that reviews the production plan and adjusts resources when a delay in the work occurs or the work content has been changed, on the basis of the progress status.

The application provides a method, device, equipment and storage medium for improving simulation accuracy of a lower control arm. The method comprises the following steps: 1, importing a geometric model and dividing a grid; 2, establishing a Connector unit; 3, defining a direction of the Connector unit and correcting stiffness; 4, defining contact on the control arm; 5, restricting inner point and outer point degrees of freedom of the control arm; 6, defining different materials and properties according to an analysis working condition; 7, applying a decomposition load; 8, submitting finite element software analysis; 9, checking a result; 10, post-processing and evaluating the result. The application eliminates rigid body displacement through the restriction of the inner point and the outer point, thereby avoiding various restrictions caused by an inertia release algorithm; and through inner point and outer point bush stiffness correction and loading of all hard points, the application reduces load loss caused by bush stiffness to an acceptable range of accuracy, so that actual load of the control arm approaches the decomposition load, and the application can realize combined loading analysis of control arms in different spatial positions of multiple vehicle models in the same platform.

The invention discloses a multi-event failure mode FMEA analysis method for an optical fiber gyroscope, and relates to the technical field of optical fiber gyroscopes. Comprising the following steps: establishing a multi-event failure mode database and management software; clicking a plurality of failure modes by utilizing the management software, and generating a multi-top event failure mode assembly and a multi-top event fault tree; the multi-top event fault tree comprises a plurality of bottom events, a plurality of middle events and a plurality of top events; and based on the failure mode assembly and the multi-top event fault tree, performing troubleshooting and influence analysis on the failure mode in combination with troubleshooting priorities. The problem of FMEA analysis work when a plurality of top events occur on the optical fiber gyroscope at the same time is solved.