14results about How to "Realize intelligent early warning" patented technology

The present application relates to a kind of biological base micro needle sensor-based crop health nondestructive testing method, belong to agricultural information technology and biosensor field.The method is intelligently analyzed to crop surface microstructure by convolutional neural network, realize the accurate arrangement of microneedle array and customized nondestructive adaptation.Microneedle multimodal sensing unit can synchronously real-time acquisition crop internal multidimensional physiological parameters, and signal quality is improved using adaptive filtering and standardization processing.Combined with multivariate anomaly detection algorithm of self-supervised and contrast learning, health status is unsupervised clustering and early abnormal screening, and environmental and management information is fused, realize whole plant multiscale health evaluation, abnormal risk distribution analysis and dynamic traceability.System can intelligently output differentiated farm work suggestions, realize the high accuracy, nondestructive, real-time monitoring and intelligent management of crop health.

The present invention discloses a method and system for super-resolution reconstruction and recognition of faces used in video surveillance, and belongs to the field of deep learning super-resolution reconstruction of faces. The method of the present invention first obtains the original video stream collected in real time and preprocesses it, then locates the face position of the preprocessed video stream in the target area, then inputs the low-resolution face image into the trained face super-resolution reconstruction network for reconstruction, outputs the reconstructed super-resolution face image, and finally performs face recognition on the reconstructed super-resolution face image, outputs the face recognition result and visualizes it, and stores the recognized personnel for later auditing. The present invention aims to efficiently and accurately restore high-quality face images from low-quality face images through the powerful learning ability of the face super-resolution reconstruction network, thereby providing a clearer and more reliable input for the face recognition system, and improving the overall recognition accuracy and robustness.

The utility model relates to the technical field of electrical safety. The hydropower station inspection device comprises a guide assembly, a sliding mechanism, a base, a rotating assembly and a monitoring mechanism, the sliding mechanism is slidably connected with the guide assembly, the base is installed on the sliding mechanism, the rotating assembly is rotatably connected with the base, and the monitoring mechanism is installed on the rotating assembly; wherein the monitoring mechanism is used for monitoring the field working state of the hydropower station and collecting the field working state information. By integrating the guiding assembly, the sliding mechanism, the base, the rotating assembly and the monitoring mechanism, automatic inspection of hydropower station equipment is achieved, and the problems that in existing hydropower station equipment inspection, the inspection efficiency is low, data is inaccurate, potential safety hazards are large, and comprehensive and real-time monitoring is difficult to achieve due to the fact that manpower is relied on are solved.

This invention relates to an intelligent screen printing device, a screen printing system, a control method, and a computer-readable storage medium, belonging to the field of thin-film battery manufacturing technology. The intelligent screen printing device is used for perovskite thin film screen printing and includes: a screen frame for supporting the screen; a tension sensing module disposed on the screen frame for real-time monitoring of the tension distribution in various areas of the screen; a temperature regulation module disposed on the screen frame for heating or cooling the screen; an electrostatic control module disposed above the intelligent screen printing device for generating an ion flow to eliminate static electricity accumulation during the printing process; and a control unit electrically connected to the tension sensing module, the temperature regulation module, and the electrostatic control module, respectively, for receiving monitoring signals and outputting control commands to achieve coordinated closed-loop regulation of tension, temperature, and electrostatics.

The invention discloses a rare earth magnesium alloy wire material electroplastic roller breaking early warning and alarming device for electric arc additive materials. The device comprises a closed box body, a sliding guide rail module, a multi-dimensional detection module, a main control unit and a sound-light alarming assembly. The sliding guide rail module adopts a modular design and can flexibly adjust the position of the sensor; the multi-dimensional detection module collects wire operation parameters in real time, and the main control unit analyzes data through a multi-source information fusion algorithm and accurately recognizes wire breakage and potential risks. The device has high sensitivity and high reliability, can realize wire breakage early warning and instant alarm shutdown, effectively reduces material waste and equipment damage, improves the stability and automation level of the magnesium alloy wire electroplastic roller drawing process, and provides high-quality wire guarantee for electric arc additive manufacturing.

The application discloses a cyanobacterial community succession prediction method and device fusing ecological mechanism and causal enhancement. The method comprises the following steps: collecting multi-source high-frequency monitoring data of a target water area, and constructing an environmental driving factor characteristic matrix; constructing a causal weight matrix through causal relationship aggregation analysis, and outputting a causal enhancement characteristic matrix; constructing a species ecological strategy embedding matrix; performing multi-scale decomposition on algal density time series data; constructing a multi-species interaction prediction model based on a multi-head self-attention mechanism, fusing environmental characteristics, causal enhancement characteristics, ecological strategy embedding and multi-scale time series characteristics, and predicting the biomass and relative abundance of each dominant cyanobacterial species; and outputting a cyanobacterial community succession process and a water bloom risk grade. Through deep fusion of causal enhancement, ecological strategy embedding and multi-head attention mechanism, the precision, stability and ecological interpretability of cyanobacterial community succession prediction are significantly improved, and the application is suitable for water bloom early warning and ecological management of lakes, reservoirs and rivers.

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 present invention discloses an evaluation system and method for analyzing the degree of marine pollution based on buoys, and relates to the technical field of marine pollution analysis. The evaluation system comprises functional modules that run in sequence, including: a buoy deployment module, a determination and collection module, an early warning and reporting module, a pollution analysis module, a pollution evaluation module, and an analysis and governance module. The scenario targeted by the system is a bay. Considering the existence of high tide and low tide in the bay, the system can complete the evaluation and analysis of the degree of seawater pollution in the target bay within a cycle of high tide and low tide, and a corresponding number of buoys need to be arranged in response to the actual area of ​​the target bay. The technical key points are: the system can realize real-time monitoring, intelligent early warning, accurate evaluation and dynamic governance of the water quality of the target bay; by giving priority to dispatching personnel to the marked position, dynamically adjusting the estimated value of the governance dispatch, and other measures, the pertinence and efficiency of the governance work are improved.

The application discloses a kind of steel structure high-temperature corrosion fatigue damage evaluation methods, comprising the following steps: the unified continuous damage mechanics model of coupling high-temperature creep damage, corrosion damage and mechanical fatigue damage is established, and the total damage variable of the model is the function of environmental temperature, stress parameter, current damage state, corrosion medium concentration and time;Using the high-temperature effect factor and corrosion environment factor, the actual stress amplitude of structure is equivalently corrected, and the equivalent stress amplitude under high-temperature corrosion environment is obtained, and preliminary prediction of fatigue life is carried out based on the equivalent stress amplitude and material reference S-N curve.The steel structure high-temperature corrosion fatigue damage evaluation method quantifies the dynamic influence of corrosion on microdamage as a coupling parameter, breaks through the limitations of traditional evaluation methods, and realizes the whole-chain evaluation from macroscopic performance-microdamage-corrosion effect by combining multi-scale microcharacterization and theoretical model.

The invention provides a power plant intelligent early warning method based on data fusion. The power plant intelligent early warning method comprises the following steps: acquiring historical power generation amounts of a target power plant in a plurality of past fixed time periods; building a generating capacity model for the target power plant through the historical generating capacity, and extracting an overall factor about the generating capacity of the target power plant from the generating capacity model; acquiring a plurality of power generation units of the target power plant, wherein each power generation unit comprises power generation equipment and power generation energy; building a plurality of power generation sub-models according to the plurality of power generation units, and calculating a plurality of limiting factors corresponding to the plurality of power generation sub-models; calculating power generation factors of the plurality of power generation units according to the overall factor and the plurality of limiting factors; and inputting the plurality of power generation factors into a power generation amount model to estimate the current power generation amount of the target power plant so as to realize intelligent early warning of the target power plant. The accuracy of power plant safety early warning can be improved, the difficulty of power plant early warning is reduced, and therefore the power plant is safer in the power generation process.

The present invention discloses a multifunctional remote power management diagnosis method, system and device, which belongs to the field of data analysis technology. The present invention accurately captures subtle changes in power supply operation through state indicator identification, improves monitoring accuracy; deeply explores fault trends, generates forward-looking fault characterization knowledge, and realizes fault prediction; adopts feature adversarial processing, constructs authentication and adversarial trend characterization knowledge, enhances robustness and adapts to complex environments, and reduces maintenance costs; generates parameter-focused characterization knowledge chains, realizes effective association and traceability, and improves fault handling efficiency; finally, based on authentication and adversarial discrimination probabilities, accurately determines fault diagnosis viewpoints, improves accuracy and realizes intelligent early warning. The present invention realizes the intelligence, foresight and efficiency of multifunctional remote power fault diagnosis through innovative technical means.

The invention provides a method and a system for detecting abnormal vibration of a nuclear power cold source pump. The method comprises the following steps: acquiring an original vibration signal; in the start-stop stage of the cold source pump, the original vibration signal is processed through a Savitzky-Golay smooth function and dynamic polynomial regression, and a trend prediction value is obtained; calculating a fitting residual sequence according to the trend prediction value and the original vibration signal; calculating a dynamic standard deviation and a corresponding adaptive confidence interval; performing anomaly detection according to the adaptive confidence interval; after the cold source pump finishes the start-stop process and enters a relatively stable operation stage, performing dynamic weighted fusion on the predicted value of the time sequence feature, the predicted value of the multi-source collaborative feature and the theoretical predicted value to obtain a final predicted value; calculating a residual error according to the original vibration signal and the final predicted value; performing anomaly detection according to the dynamic threshold interval to obtain an anomaly judgment result; and real-time abnormity identification and intelligent early warning of the cold source pump in the start-stop and stable operation processes are realized.

This invention relates to an adaptive lateral internal support, intelligent early warning system, and early warning method for sheet piles in deep foundation pits. Symmetrical side support structures are installed on the inner wall of the foundation pit, with supporting structures and climbing structures between these symmetrical side support structures. The intelligent early warning system's data acquisition subsystem collects the strain of the sheet piles and the jacking force of the thrust jacks and structural jacks. The data analysis subsystem analyzes the stress on the sheet piles. The early warning subsystem provides timely warnings when the stress on the sheet piles exceeds limits. The intelligent correction subsystem adjusts the position and thrust of the supporting structures. The early warning method effectively combines structural stress monitoring with intelligent technology, achieving stress early warning and intelligent correction for sheet piles in deep foundation pits. This promotes the intelligent development of safe construction of sheet pile support structures and lateral internal supports in deep foundation pits, improving the construction safety of foundation pit support.

The application relates to the technical field of vehicles, in particular to a vehicle defrosting device, a vehicle defrosting method and a vehicle. The vehicle defrosting device comprises a detection unit, a control unit and a defrosting unit. The detection unit is arranged at each preset position on a vehicle body and is used for acquiring ice and frost accumulation information at each preset position and sending the ice and frost accumulation information to the control unit. The control unit is used for determining whether ice and frost accumulation occurs at the preset position on the vehicle body according to the ice and frost accumulation information, and controlling the defrosting unit to defrost when it is determined that defrosting needs to be performed. The defrosting unit is used for defrosting operation under the control of the control unit. The application integrates the detection unit, the control unit and the defrosting unit, realizes real-time monitoring and automatic defrosting of the ice and frost condition of the vehicle, can quickly and effectively remove the ice and frost on the surface of the vehicle, improves defrosting efficiency and convenience, and improves driving safety.