425 results about "Data interpretation" patented technology

The invention relates to the technical field of intelligent fault diagnosis systems, in particular to an intelligent fault diagnosis system and method for multi-sensor data fusion, and the system comprises an online diagnosis module and an offline training module, the online diagnosis module comprises a self-adaptive balance sub-module and a prototype network sub-module, and is used for processing sensor data in real time and carrying out fault diagnosis; the offline training module comprises a data preprocessing sub-module, a data fusion sub-module, a fault diagnosis sub-module, a data balance sub-module and a data interpretation sub-module, and is used for optimizing a diagnosis model; the data interpretation sub-module comprises an SHAP value extraction unit which is used for interpreting a diagnosis result; an online diagnosis module and an offline training module of the system form a closed-loop optimization mechanism, so that the diagnosis model can continuously learn and adapt to a new fault mode. The design ingeniously balances the requirement of real-time diagnosis and the requirement of continuous optimization of the model, and the long-term effectiveness of the system is greatly improved.

The invention relates to the technical field of remote monitoring, in particular to a remote monitoring method and system for intelligent water purification equipment. The system comprises a sensing execution unit, a data routing unit, an intelligent central unit and an interactive service unit. The intelligent central unit is used for comparing underground water quality data collected in real time with corresponding month threshold values over the years, water quality fluctuation caused by natural changes such as seasonal replacement can be accurately distinguished, the water quality data interpretation accuracy is improved, when the water quality data deviates from a normal range and influences of natural laws are eliminated, the system introduces real-time weather data, and the water quality data interpretation accuracy is improved. And the analysis module considers the effect of weather on water quality by means of a dynamic structure equation model and resets a threshold value. The intelligent self-adaptive mechanism can effectively distinguish water quality abnormity caused by non-natural laws, for example, normal fluctuation of water quality after rainstorm is recognized, accuracy and intelligence of water quality monitoring are enhanced through multiple times of accurate judgment, and abnormity can be quickly recognized and early warned.

The invention discloses a geophysical prospecting system and method for seismic survey. The system comprises a seismic source and receiving point laying module, a data acquisition module, a data processing module, a three-dimensional imaging module, a data interpretation module, a comprehensive analysis module, auxiliary equipment and an early warning module. The data processing module comprises a preprocessing module, a speed analysis superposition processing module and an offset processing module. According to the invention, data with high quality, signal-to-noise ratio and accuracy can be obtained by adding the density of the receiving points and combining the speed analysis superposition processing module to carry out superposition correction processing on the data, and meanwhile, by combining the reverse time migration technology, an underground structure can be accurately recovered, the imaging quality is improved, the subsequent interpretation and analysis work of personnel is facilitated, and the working efficiency is improved. The exploration accuracy is improved, and personnel can more accurately reveal the underground geologic structure conveniently.

The present invention discloses an artificial intelligence-based (AI-based) system and method for generating optimised operation planning and scheduling output. The AI-based system obtains at least one of: one or more data explanation videos, one or more process understanding videos, and unconstrained operational planning data, along with one or more prompts as an input. The AI-based system extracts one or more informative image frames and audio data, to train the one or more AI models and generate a planning standard operating procedure (SOP). The AI-based system processes the planning SOP, the constrained operational planning data, and the one or more prompts to generate the optimised operation planning and scheduling output based on an optimised function with a continuous feedback loop in response to at least one of: the one or more prompts, updated planning SOP, and real-time changes in the constrained operational planning data.

A conversation agent is described. An example method includes receiving a user request from a user interface of a conversation agent; determining a predicted intent of the user request; selecting a prompt template from a plurality of prompt templates corresponding to respective intents based on the predicted intent of the user request; generating a prompt using the prompt template and the user request; processing the prompt using a generative language model to generate an output; and displaying, on the user interface, a response to the user request generated based on the output.

An internal peeping detection-while-drilling system includes an intelligent probing rod, cable drill pipes, a signal relay sub, a ground control terminal, a data interpretation and goaf reconstruction imaging software system, and a remote data transmission system, where the intelligent probing rod includes an up-down separated protective transmission mechanism and an instrument cabin; the intelligent probing rod includes a lower end connected to a drilling bit, and an upper end connected to each of the cable drill pipes; the instrument cabin is provided in the up-down separated protective transmission mechanism, and provided with a sonar-lidar-audio / video sensor assembly; the cable drill pipes are connected to each other to form a cable and data transmission channel; the signal relay sub is provided between the cable drill pipes at intervals; and an uppermost end of the cable drill pipe is connected to the ground control terminal.

The invention discloses a soil pollution accurate positioning method based on a geophysical exploration technology. The method comprises the following steps: S1, analyzing geologic features of a research area: analyzing the geologic features of the research area; s2, constructing a geological model; s3, measuring line arrangement and data acquisition; s4, data processing: obtaining a two-dimensional resistivity and polarizability image and an internal structure image of ground penetrating radar data by adopting least square inversion, training an anomalous body recognition model by utilizing a convolutional neural network, automatically recognizing anomalous body features in ERT and GPR data, and automatically screening out potential pollution areas; s5, data explanation: performing comprehensive analysis on inversion results of ERT and GPR, constructing an intelligent explanation model, automatically adjusting explanation parameters by the intelligent explanation model according to data features, and providing a plurality of explanation schemes; and S6, establishing a three-dimensional electrical structure model: establishing the three-dimensional electrical structure model of the research area by adopting a Kriging interpolation method according to the ERT inversion result and the earth surface coordinate data.

The invention relates to a multi-polarization radar geological structure analysis method, device and equipment and a storage medium, and the method comprises the steps: carrying out the detection operation along a target measuring line in a detection region through a multi-polarization radar, so as to obtain the multi-polarization radar data of an underground target body and a geological structure; performing standardization processing on the multi-polarization radar data by using the sample database to obtain an ordered sample data set; performing pixel-level fusion on the multi-polarization radar data according to the ordered sample data set to generate a multi-polarization radar sample data set with the resolution greater than a preset resolution; and inputting the sample data set into a preset pulse neural network to output an intelligent identification result of the underground target body and the geological structure, and extracting categories and potential relationships of the underground target body and the geological structure according to the intelligent identification result. Therefore, the problems that the workload of multi-polarization radar data interpretation analysis is large, the recognition precision and efficiency are low, and the professional ability of employees is excessively depended in the prior art are solved.

The invention relates to the technical field of unmanned aerial vehicle video data interpretation, in particular to an unmanned aerial vehicle video abstract semantic description method and system based on a multi-modal large model, and the method comprises the steps: obtaining a plurality of segmented video frame images of unmanned aerial vehicle video data; extracting image features by using a multi-modal large model, wherein the multi-modal large model adopts an image encoder in a visual language basic model to encode the input segmented video frame images and extract the corresponding image features; performing adaptive clustering on the image features to obtain a clustering center of each segmented video, and generating an unmanned aerial vehicle video abstract by taking a frame position where the clustering center is located as a frame position where the video abstract is located; and acquiring scene semantic description of the unmanned aerial vehicle video abstract by utilizing a semantic description model, wherein the semantic description model is obtained by finely adjusting a large model by utilizing an unmanned aerial vehicle image semantic description data set. The core intelligence information can be accurately and efficiently extracted from the unmanned aerial vehicle video data, and the utilization efficiency of the unmanned aerial vehicle video data is improved.

The invention provides a hydraulic fracturing fracture net distribution form near-field monitoring method, which comprises the following steps of: arranging a plurality of roof monitoring holes in roadways on two sides of an underground coal mine working surface, installing electromagnetic signal sensors in each roof monitoring hole and on anchor rods of roadway stoping sides, and constructing a full-space monitoring network covering a hydraulic fracturing layer; a data interpretation processing module of the electromagnetic signal time-shifting imaging analysis system comprises a multi-field coupling mathematical model for analyzing and deducing real-time imaging of electromagnetic signals; in the hydraulic fracturing process, an electromagnetic signal sensor is used for monitoring a current field, an electromagnetic field and an ion diffusion field in the rock mass fracture development and expansion process, a monitoring result is substituted into an electromagnetic signal time-shifting imaging analysis system for calculation and feature value extraction, and the fracture net distribution form is deduced through the feature value. According to the invention, the expansion path of the fracturing fluid in the rock stratum can be monitored in real time, the three-dimensional distribution form of the hydraulic fracturing fracture network can be inverted, and a new technical support is provided for the inspection of the hydraulic fracturing pressure relief effect of the underground coal mine.

The invention provides a low-code enterprise-level intelligent assistant development platform, and relates to the field of intelligent assistant development. The low-code enterprise-level intelligent assistant development platform comprises an application layer, a platform layer, a capability layer and an underlying service. According to the low-code enterprise-level intelligent assistant development platform, a low-code enterprise-level intelligent assistant development platform is realized, and by means of the platform, a user can develop enterprise-level intelligent assistants suitable for various industries, thereby helping enterprises to realize cost reduction and benefit increase; a user can complete the creation of a knowledge base, a workflow and an intelligent agent only through simple configuration or arrangement, a low use threshold is achieved, enterprise internal services or third-party MCP services can be accessed by means of a plug-in tool and a platform, uploading and publishing of user-defined tools are supported at the same time, high expandability is achieved, and the method can be widely applied to the field of enterprise management. The platform supports high-order functions such as multi-person collaborative development, multi-modal knowledge base construction, multi-modal data interpretation and processing and construction of multiple types of agents, and can meet complex enterprise-level application scenes.

The invention relates to the technical field of pipeline anomaly detection, in particular to a petroleum pipeline network anomaly recognition and early warning system which comprises a pressure fluctuation monitoring module, a flow anomaly analysis module, a state association optimization module, an early warning strategy adjustment module and an anomaly early warning generation module. According to the method, deep correlation analysis is carried out on the relation between pressure fluctuation and flow abnormity, the change trend of pipeline pressure and flow can be accurately captured, the abnormal state in pipe network operation can be recognized in time, the abnormity early warning structure is dynamically adjusted, the early warning strategy can be flexibly optimized along with the change of the working condition, and therefore the detection precision and the response speed are improved; the state can be mastered in real time in a complex pipe network environment, missing detection and false alarm phenomena caused by insufficient data interpretation or early warning strategy solidification are effectively reduced, the adaptability of the system to emergency situations is enhanced, and the problems of response lag and insufficient sensitivity caused by single data source under variable working conditions are avoided.

In embodiments, an apparatus includes a user data interpretation circuit structured to interpret user data corresponding to a first user; a bootstrap circuit structured to: match the first user to a second user via querying one or more databases based at least in part on the user data; retrieve historical time sequence data associated with the second user via querying the one or more databases; extract a time sequence trend from the historical time sequence data; identify a portion of the historical time sequence data corresponding to the extracted time sequence trend; and generate, based at least in part on the identified portion, time sequence data corresponding to the first user; and a time sequence data provisioning circuit structured to transmit the time sequence data.

Example embodiments provide a method for improved commissioning, interpretation, and automated or remote operation of a methane density camera designed for monitoring of gas emissions. In some embodiments, the method consists of three related but independent steps including commissioning, remote operation, and data interpretation.

The invention relates to the technical field of seismic data interpretation, and discloses a method and system for recovering a three-dimensional paleostructure, and the method comprises the steps: constructing an isochronous stratigraphic framework according to a three-dimensional seismic data body and logging data, estimating and supplementing the denudation thickness of a target horizon interface, and restoring the target horizon interface. A plurality of longitudinal sections vertically penetrating through a fault are taken on an isochronous stratigraphic framework, on the longitudinal sections, a target horizon interface is leveled in a sliding mode along the sections, whether seismic reflection events of other stratigraphic interfaces on the two sides of the sections have coordination consistency or not is judged, and when the seismic reflection events of the other stratigraphic interfaces on the two sides of the sections have coordination consistency, the target horizon interface is judged to be in a normal state. And sliding the target horizon interface along the section body space until the target horizon interface is leveled to obtain a paleotectonic geologic model of horizon below the target horizon interface. According to the method, the three-dimensional paleostructure can be accurately recovered by establishing the effective isochronous stratigraphic framework.

The invention provides an information personalized interpretation method and a related device, and relates to the field of data interpretation. Responding to the information recommendation instruction, obtaining target information to be recommended to a target user, determining an initial user portrait of the target user, adjusting the weight of a user tag in the initial user portrait according to a content portrait of the target information to obtain a target user portrait, constructing a prompt word based on the target user portrait, and recommending the prompt word to the target user. And performing personalized interpretation on the target information by using the cue word to obtain a personalized interpretation result of the target information, the personalized interpretation result comprising influence information of the target information on the target user, and outputting the personalized interpretation result of the target information. According to the method, after the target information which the user is interested in is screened out, the target information is interpreted based on the target user portrait to obtain the influence of the target information on the user, namely, the value of the content of the target information on the user is obtained, the user does not need to perform information extraction by himself, the reading efficiency of the user is improved, and the user experience is improved.

The invention relates to the technical field of intelligent interaction, and particularly discloses an intelligent dialogue virtual robot interaction system and method based on AI artificial intelligence, and the system comprises a dialogue data interpretation module which is used for extracting the latest multi-dimensional expression state features and core content texts of a user from dialogue data input by the user; the weight matrix building module is used for building an evaluation assignment conversion matrix of the latest multi-dimensional expression state characteristics of the user; the weight vector determination module is used for generating influence weight vectors of all latest single-dimensional expression state characteristics of the user based on the evaluation assignment conversion matrix of the latest multi-dimensional expression state characteristics of the user; the intelligent dialogue response module is used for obtaining response information of dialogue data input by the user based on the influence weight vector and the core content text of all latest single-dimensional expression state characteristics of the user and an AI dialogue response model; and the response effect of the intelligent dialogue virtual robot is improved.

The invention discloses a structural plane network sequence modeling method and system suitable for layered rock mass, and relates to the technical field of rock mass engineering, and the method comprises the steps: obtaining layered rock mass outcrop data as basic data, and obtaining basic data interpretation representation after processing; determining a rock mass outcrop homogeneous region division result according to the type attribute of the basic data; according to the interpreted occurrence data in combination with a rock mass outcrop homogeneous region division result, correcting the occurrence data in each homogeneous region by using a weighting function, and grouping the structural surfaces by using a K-mean particle swarm algorithm to obtain grouped structural surfaces; determining the density of the distribution space of each group of structural surfaces according to the spacing, occurrence, size and survey line trend data of each group of structural surfaces; determining the position and size of a layer in the layer structure space according to the determined distribution position of the structural surface; and randomly combining parameters of each group of structural surfaces, and constructing a stratified rock mass structure spatial network model in combination with sequence modeling and Monte Carlo simulation methods.

The invention discloses a seismic fault identification method based on a Dual-Attention mechanism and a multi-scale fusion network, and belongs to the technical field of seismic data interpretation, and the method comprises the following steps: S1, obtaining three-dimensional post-stack seismic data, and carrying out the slicing of a seismic data body, and obtaining multi-channel seismic data; s2, a DAMFault Net fault recognition model is constructed; s3, completing fault feature extraction in a coding stage; s4, obtaining an intermediate aggregation feature and an original same-scale feature from an encoder in a decoding stage; s5, adding a depth supervision mechanism to a tail end decoder; and S6, splicing and recovering prediction results to the size of the original seismic section. According to the seismic fault identification method based on the Dual-Attention mechanism and the multi-scale fusion network, excellent accuracy and fault continuity identification capability are shown in a fault identification task, and automatic, efficient and accurate identification of the fault in the seismic image is realized; and powerful technical support is provided for seismic analysis and research.

The invention discloses an intelligent report generation method based on a big language model, which comprises the following steps of: obtaining report data interpretation by utilizing the big language model and combining industry knowledge according to original data for generating a report; according to report data interpretation, a report is intelligently generated in combination with mode requirements; and adjusting the content and / or mode of the report according to the user input. According to the method, highly automatic and intelligent data processing is realized by utilizing the large language model, manual intervention is not needed in the whole process from data collection to report generation, time and cost are remarkably reduced, and data analysis depth and accuracy are improved. And performing context analysis in combination with industry knowledge, identifying key business driving factors and potential risk points, and generating a high-quality report. Through a user input function, report content and format can be adjusted in real time, and user experience and decision effectiveness are greatly enhanced.

The invention discloses a tectonic fracture development degree evaluation method and device, electronic equipment and a storage medium, and the method comprises the steps: obtaining the historical exploration information of each target well in a target region, and the historical exploration information comprises logging data, logging data and a data interpretation result; determining a target brittleness index ratio and a target rock stratum thickness value corresponding to the target area based on the historical exploration information; and determining a fracture development degree evaluation standard based on the target brittleness index ratio and the target rock stratum thickness value, and evaluating the tectonic fracture development degree based on the fracture development degree evaluation standard. Based on the above technical scheme, the evaluation parameters are determined based on the historical exploration information in the target area, and the evaluation standard of the fracture development degree is constructed based on the evaluation parameters, so that reasonable prediction and evaluation of the fracture development degree are realized based on the evaluation standard. The technical effect of improving the accuracy of predicting the development degree of the tectonic fracture is achieved.

The invention discloses a BiLSTM-based while-drilling electromagnetic wave logging data rapid inversion method and system, and the method achieves the efficient processing of logging data through constructing a deep network structure composed of four BiLSTM layers and a full-connection layer. According to the method, ideal magnetic dipole response is adopted as training data, and the problem that local minimum is likely to occur in traditional data interpretation is solved. And the recurrent dropout technology is utilized to reduce overfitting, so that the generalization ability of the model is improved. The technology not only can accurately classify the stratum model, but also can predict various stratum parameters, so that the accuracy and processing speed of data interpretation are remarkably improved, and powerful technical support is provided for geological exploration and stratum evaluation.

The invention discloses a hidden danger identification marking method for a ground subsidence disaster of a power transmission line tower foundation. Comprising the steps of power transmission line tower foundation land subsidence disaster investigation, research area remote sensing image data query, optical remote sensing data interpretation, InSAR data interpretation, field investigation, optical image data interpretation mark analysis, InSAR interpretation mark analysis and field investigation mark analysis. According to the method, the multi-source remote sensing technology and the field investigation are utilized to carry out the method for identifying the potential ground subsidence hazard of the power transmission line tower foundation on the regional scale, and each step and the adopted method in identifying the potential ground subsidence hazard hazard of the power transmission line tower foundation by utilizing the multi-source remote sensing technology and the field investigation are standardized; the working efficiency, the recognition precision and the economic benefit of the hidden danger recognition of the ground subsidence of the power transmission line tower foundation can be practically and effectively improved; and the technical process of power transmission line tower foundation land subsidence disaster investigation can be effectively standardized.

The invention discloses a transient electromagnetic global apparent resistivity definition method based on differential pulses, and relates to the technical field of artificial source electromagnetic detection, and the method comprises a transient electromagnetic field response calculation method based on a step wave emission waveform, and an electromagnetic forward modeling method for obtaining the differential pulses by adopting a time shift method. Based on a differential pulse transient electromagnetic forward modeling method, electromagnetic fields under different pulse widths, different flight heights and different offsets are calculated, and curve characteristics of the electromagnetic fields changing along with resistivity are analyzed; selecting a target electromagnetic field component, and adopting an inverse function theorem to obtain a global apparent resistivity iteration expression based on a differential pulse emission waveform; according to the transient electromagnetic global apparent resistivity defining method, the global apparent resistivity of multiple pulse width differential pulses is calculated through a global apparent resistivity iteration expression, underground comprehensive electrical characteristics are obtained through a correlation superposition algorithm, and the transient electromagnetic data interpretation capacity is improved through the transient electromagnetic global apparent resistivity defining method.

The invention provides an AI-based ChatBI platform design and implementation method, which comprises the following core steps of: constructing a first semantic layer database, receiving a natural language problem of a user, and generating an executable SQL (Structured Query Language) statement through an NL2DSL engine; extracting keywords and performing vector similarity calculation on the keywords and the first semantic layer database to generate a second semantic layer knowledge base; judging query complexity according to the quantity of the knowledge bases, and scheduling corresponding processing engines; checking the user access authority, and automatically generating a chart configuration template and recommending an adaptive chart type when the user access authority exists; based on user selection, data interpretation and a core conclusion are generated through a large model in combination with SQL statements and a knowledge base, and an output result is integrated. According to the invention, by optimizing the platform architecture, accurate data insight can be obtained by non-technical personnel in a dialogue manner, the use threshold is reduced, terms are unified, and the result accuracy is improved; meanwhile, operation efficiency is improved, and waiting time is shortened; and the data security is enhanced through permission setting.

The invention mainly relates to the technical field of spectral analysis, and provides a white spirit brewing spectral analysis method and system based on a multi-modal large language model in order to efficiently and accurately obtain white spirit brewing information according to multi-modal spectral data of all links of white spirit brewing. The method is characterized by comprising the following steps of: collecting multi-mode spectrum data including gas chromatography data, infrared spectrum data and Raman spectrum data in each link of white spirit brewing; converting the multi-modal spectral data and the natural language instruction into a feature embedding vector which can be recognized by a large language model to train the large language model which is finely adjusted based on professional knowledge in the field of white spirit, and receiving a question of a user in a natural language instruction form by the trained large language model; wine making analysis tasks such as flavor compound identification, key microorganism detection, fermentation state evaluation and base wine quality grading are carried out, and finally analysis results and wine making process optimization suggestions are output in a natural language form, so that the accuracy and efficiency of spectrum data interpretation in the white wine making process are improved.

The invention relates to the technical field of flexible riser motion analysis, in particular to a marine dynamic flexible riser motion response reconstruction method based on monitoring data, which comprises the following steps of: arranging sensors in a flexible riser system by adopting a structure embedded type arrangement method or an external attachment type arrangement method, and optimizing a sensor arrangement mode; a data acquisition and transmission system is arranged on an ocean platform to obtain flexible riser motion response data, the flexible riser motion response data is converted into flexible riser displacement data based on a Timoshenko beam model and Tikhonov regularization, the flexible riser displacement data is subjected to noise reduction processing based on a wavelet threshold noise reduction method to obtain flexible riser displacement noise reduction data, and the flexible riser displacement noise reduction data is subjected to flexible riser displacement noise reduction. And motion response reconstruction is performed on the flexible riser displacement noise reduction data based on variational mode decomposition (VMD). According to the method, the data interpretability, the data reconstruction precision and the real-time performance of motion reconstruction of the flexible riser can be effectively improved.

A system or method of secure data entry can include one or more processors and memory having computer instructions which when executed by the one or more processors causes the one or more processors to perform the operations at a client edge device of executing a user interface data entry application on the client edge device, receiving data by the user interface data entry application, wherein the data entered is a graphic input pattern corresponding to characters, communicating the data entered to a server, and receiving access to the server if a data processing application at the server interprets the data entered as a credential based on rules negotiated between the data entry application and the data processing application and a template for the graphic input pattern.

The invention provides a data display method and device and a computer storage medium. The method comprises the steps of determining at least one item of to-be-displayed data; determining the corresponding proportion of each item of to-be-displayed data in each item of to-be-displayed data; the minimum proportion of all the proportions is determined, and the minimum proportion is not larger than the proportions of other all the proportions; based on the minimum proportion, determining a display area of each item of to-be-displayed data in a cylinder; on the basis of the cylinders, the proportions corresponding to the to-be-displayed data and the corresponding display areas, a histogram is generated, and the display areas corresponding to the to-be-displayed data cover the display areas of the cylinders; and displaying the generated histogram. According to the scheme, a user can conveniently and quickly know and judge the proportion condition of each item of to-be-displayed data. The comparison condition of each item of to-be-displayed data can be displayed more visually, and the data interpretation time is shortened, so that the data expression effect of the cylindrical object is improved.