15results about How to "Realize intelligent analysis" patented technology

This invention relates to the field of electricity meter operation monitoring technology, specifically to an intelligent analysis system for electricity meter operation faults based on sensor monitoring. The system includes: an operation status acquisition module, which collects the voltage, current, active power, reactive power, and power factor of the electricity meter and obtains the operation status at each moment; a periodic analysis module, which uses active power as a load parameter and obtains a basic period based on the load parameters within a preset time period, then segments the preset time period to obtain different time periods and obtains the period fit at each moment; and a fault monitoring module, which obtains the comprehensive rationality of the load linkage deviation at each moment; and uses the comprehensive rationality of the load linkage deviation at a moment and the period fit to correct the squared Mahalanobis distance corresponding to the data points composed of voltage, current, reactive power, and power factor at that moment, and uses the corrected squared Mahalanobis distance for fault monitoring. This application can effectively monitor the operation faults of electricity meters.

The invention provides an intelligent breeding behavior analysis system and method based on edge calculation and AI vision, relates to the technical field of intelligent breeding and computer vision, and solves the technical problems of low efficiency, poor behavior recognition accuracy and abnormal early warning lag caused by dependence on manual and cloud processing in existing breeding management. The system comprises an edge end device which is used for collecting a video stream in real time and carrying out target detection and key point identification on the video stream through a lightweight deep learning model to obtain a preliminary behavior classification result; the fog end server is used for gathering a plurality of preliminary behavior classification results, performing complex behavior recognition, behavior time sequence analysis and abnormal behavior detection, obtaining an abnormal behavior result and triggering real-time early warning; and the cloud platform is used for receiving and storing all data of the farm, performing long-term data mining, multi-source data association analysis and model training and updating, and generating decision support information. The method is used in the intelligent breeding process.

The application discloses a blood flow velocity measurement method based on a light flow method area tracking, relates to the blood flow velocity measurement technical field, and comprises the following steps: extracting multiple frames of blood vessel images from a blood vessel video, and determining a ROI area in each frame of the blood vessel images according to a predetermined ROI area division rule; performing movement estimation on adjacent two frames of the blood vessel images by using a DIS light flow method to obtain blood flow data of the adjacent two frames of the blood vessel images; performing area tracking on the blood flow data by using an affine transformation to obtain affine transformation parameters of each frame of the blood vessel images; inputting the affine transformation parameters into a preset movement amount prediction model, predicting movement amounts of ROI areas of multiple groups of adjacent frames of the blood vessel images, and performing velocity estimation according to the multiple groups of the movement amounts to output blood flow velocities; the application performs movement estimation on the adjacent two frames of the blood vessel images by using the DIS light flow method, improves the response capability of a system to dynamic changes of blood flow in a complex blood vessel structure, and thus ensures accurate measurement under different blood vessel conditions.

The application relates to the technical field of data processing, and relates to an Excel data emergency reporting and processing method based on dynamic mapping, which comprises the following steps: receiving an emergency reporting instruction, confirming an emergency processing system and a to-be-processed Excel file based on the emergency reporting instruction, performing structural analysis on the to-be-processed Excel file to obtain a table header field set and a data region set, constructing a field mapping rule library by using a dynamic mapping unit and the table header field set, generating a dynamic filling report template set based on the field mapping rule library and the data region set, checking a backfill data set by using the field mapping rule library to obtain a check result set, performing data aggregation by using a data aggregation unit based on the check result set and the backfill data set to obtain an aggregated data table, and sending the aggregated data table to an initiating end of the emergency reporting instruction, so that the emergency reporting and processing of Excel data are realized. The application can improve the accuracy and efficiency of the emergency reporting and processing of Excel data.

The invention discloses a mental health service system and method, electronic equipment and a storage medium, and relates to the technical field of artificial intelligence and health cross, and the system comprises an emotion analysis module, an intelligent pre-inquiry module and an analysis report generation module. And the emotion analysis module processes emotion-related multi-modal data provided by the target user by using the trained multi-modal large model to generate an emotion analysis result. And the intelligent pre-inquiry module performs multiple rounds of dialogues with the target user based on a natural language understanding technology, collects information related to mental health of the target user and generates a questionnaire. And the analysis report generation module performs joint reasoning on the information acquired by the intelligent pre-inquiry module and response information of the target user to the questionnaire to generate an analysis report. According to the invention, objective emotion analysis is provided through the emotion analysis module, standardized information collection is realized through the intelligent pre-inquiry module, and a scientific report is generated through combined reasoning by the analysis report generation module, so that the service accessibility and efficiency are improved.

The invention discloses a multi-dimensional physical simulation method and system based on large construction equipment, and relates to the technical field of digital assembly type construction. The method comprises the following steps: acquiring dynamic parameters of large-scale construction equipment and physical attribute parameters of prefabricated parts, constructing a multi-dimensional physical simulation model based on MATLAB, and constructing a high-fidelity virtual construction environment containing a construction site model, an equipment model and a component model through IsaacSim; a simulation model is used for calculating a hoisting track and load data, and the hoisting track and the load data are transmitted to IsaacSim through ROS standardization to complete virtual simulation; real data are collected through a multi-mode sensor and transmitted to a digital twin platform through a cloud server, the platform fuses simulation and real data, and a deviation calculation and dynamic calibration algorithm is adopted to carry out comparative analysis to generate a safety assessment result and early warning information. The system correspondingly comprises a multi-dimensional physical modeling unit, a virtual simulation unit, a sensor unit, a cloud server unit, a communication transmission unit and a digital twin platform unit, precise simulation, real-time monitoring and intelligent early warning of hoisting operation are achieved, and support is provided for construction safety and fine management.

The invention discloses a parking charge intelligent analysis method and system based on a full-link log and a large model, and relates to the technical field of intelligent parking management. The method comprises the following steps: identifying a user question through an intention identification engine, and outputting an intention label, a user ID and a time range; generating a function calling instruction by the large model agent; retrieving a structured log from a distributed database according to the instruction; carrying out vectorization questioning and retrieving similar rule fragments in the Milvus; performing deduction analysis in combination with the rule and the log to generate explanatory output; and outputting a readable report after presentation adaptation, and feeding back the readable report to the user from multiple terminals. The technical problems of low bill explanation efficiency, poor accuracy and poor user experience caused by the fact that automatic association and deep semantic understanding cannot be carried out on full-link behaviors of a user due to dependence on manual cross-system checking in an existing parking charging scene are solved, and the technical effect of improving the user experience and the operation efficiency is achieved.

The application discloses a kind of deep optimization deep-sea ecological monitoring method and system, comprising: first, obtain deep-sea image or video data and carry out pre-processing, carry out denoising and detail enhancement;Second, a kind of integrated Swin Transformer main part, BiFPN neck and target detection architecture of combined query decoder are used, high-precision, anti-interference target detection is carried out to enhanced image;Then, the structured target data detected is inputted with original image into multimodal large language model, carries out the inference and analysis of deep ecological semantics such as species attribute, behavior mode;Finally, multi-frame aggregation and community analysis are carried out to video data, and structured deep-sea ecological monitoring report is automatically generated according to detection and analysis result.The application solves the problems of small target detection difficulty, serious background noise interference, low data analysis efficiency, lack of semantic understanding and automation capability in deep-sea environment through model innovation and fusion.

The invention relates to the field of physical testing technologies and systems, and discloses a bridge steel structure defect nondestructive testing system based on infrared thermal imaging, which comprises an unmanned aerial vehicle integrated with an infrared thermal imaging detection device and a ground computing station. The unmanned aerial vehicle flies along a planned path, transient thermal excitation is applied through a thermal excitation device, and dynamic thermal response data of the surface of a pre-coated infrared coating is collected by synchronously utilizing an infrared thermal imager. And the ground computing station performs space-time fusion preprocessing on the returned data to obtain a standardized panoramic temperature field image, and inputs the standardized panoramic temperature field image into a convolutional neural network model which fuses physical mechanism constraints and has an online self-optimization function for intelligent analysis. According to the method, signals are enhanced through the coating, efficient inspection is achieved through the unmanned aerial vehicle, the recognition precision and generalization ability are guaranteed through the physical information fusion model, continuous evolution is achieved in combination with online self-optimization, and a high-sensitivity, full-automatic and quantitative bridge steel structure defect intelligent detection solution is formed.

The invention relates to the technical field of new energy and electric vehicle charging facilities, and particularly discloses an optical storage and charging direct-flexible power supply system applied to a service area, which comprises a photovoltaic power generation unit, an energy storage unit, a charging unit and a bidirectional AC / DC converter interacting with a power grid, and the energy management unit carries out unified coordination control. The core of the system is that the loss of multiple times of electric energy conversion is reduced by using a flexible direct current bus, and a multi-mode flexible control strategy including peak load shifting, photovoltaic priority, power support and off-grid emergency is executed through an energy management unit. Therefore, the comprehensive benefits of improving the overall energy efficiency of the system, reducing the operation cost, stabilizing power grid impact and guaranteeing off-grid continuous power supply are achieved. Meanwhile, the system adopts a container type integrated energy storage design and supports networking operation of a plurality of service area subsystems, so that high integration, intelligent operation and maintenance and regional energy mutual aid are realized; the technical problem that a traditional service area power supply system is low in efficiency and poor in reliability is solved.

The invention discloses an intelligent monitoring system and method for a water-turbine generator set based on LSTM-Transform multi-modal fusion, and provides an innovative deep learning solution aiming at the defects of the existing monitoring technology in the aspects of multi-source data fusion, early fault recognition and cross-spatio-temporal scale feature extraction. According to the system, multi-modal monitoring data such as vibration signals, infrared thermal imaging and oil analysis are integrated, time sequence dynamic features are captured by using an LSTM network, cross-modal feature fusion is realized in combination with a Transform global attention mechanism, and a comprehensive unit health state evaluation model is constructed. According to the method, the early abnormal symptoms of unit operation can be effectively recognized, the accuracy and timeliness of fault early warning are remarkably improved, meanwhile, different working conditions are adapted through a self-adaptive learning mechanism, and reliable technical support is provided for intelligent operation and maintenance of the water-turbine generator set. The system has the characteristics of flexible deployment and strong expansibility, and can be widely applied to state monitoring and maintenance decision-making of various hydroelectric power generation equipment.

The application discloses an experimental animal whole life cycle data acquisition and tracing system based on Internet of Things linkage, which comprises a data acquisition module, an experimental design and resource management module, an ethics review and life cycle management module, a task execution module, a system security and permission management module and a data intelligent analysis module.The data acquisition module is used for acquiring animal identity and Internet of Things data; the experimental design and resource management module is used for experimental scheme design and resource scheduling; the ethics review and life cycle management module is used for animal ethics review and whole life cycle data management; the task execution module is used for task generation and execution; the system security and permission management module is used for security management of user permissions; and the data intelligent analysis module is used for intelligent analysis on animal behavior.The application proposes a multi-modal causal perception animal-device collaborative health monitoring algorithm for intelligent analysis on animal behavior, so that a more optimal scheme is provided for the experimental animal whole life cycle data acquisition and tracing system.

The invention relates to the technical field of industrial automation testing, in particular to an industrial control equipment interface testing system, method and platform, and the system comprises a unified configuration management module, a central test scheduling engine, a multi-source test adapter layer and a comprehensive analysis report module. The method comprises the following steps: acquiring configuration information of to-be-tested industrial control equipment, and identifying an interface type and a test parameter; based on the interface type and the test parameter, calling a corresponding interface test strategy for testing to obtain a test result; and generating a comprehensive test report according to the test result. The method has the effect of improving the comprehensiveness and accuracy of the interface test of the industrial control equipment.

This invention relates to an intelligent recommendation method for equipment fault repair. The method includes: constructing an initial equipment repair measure recommendation model; collecting historical fault data of the target equipment and training the initial model using this data to obtain a target equipment repair measure recommendation model; acquiring user-inputted target equipment fault information and inputting this information into the target equipment repair measure recommendation model to output a recommended repair measure scheme. This method, by constructing an initial equipment repair measure recommendation model, training it using historical fault data, and then acquiring user-inputted target equipment fault information and inputting it into the target equipment repair measure recommendation model to output a recommended repair measure scheme, achieves intelligent analysis of equipment faults and recommends repair strategies, improving repair efficiency and decision-making accuracy.

This invention discloses a network security analysis method and system based on a domain name monitoring mechanism, relating to the field of network security technology. This network security analysis method and system based on a domain name monitoring mechanism, through the setting of an emergency response system, can promptly issue alerts when a domain name is hijacked or misused, and lock stored data values ​​and control permissions in a timely manner, thereby effectively preventing data loss or theft. Simultaneously, it can automatically log in to the control panel through a DNS change unit to change DNS records to the correct server IP address, further enhancing network security. Through the setting of an inspection system, in conjunction with a DNS extension unit, it can provide an additional security layer for DNS queries, ensuring that the returned information has not been tampered with, and regularly monitor DNS queries and responses to promptly detect abnormal behavior.