4results about How to "Accurate decision basis" patented technology

This invention discloses an AI-based intelligent safety monitoring method and system for coal bunkers in thermal power plants, belonging to the field of thermal power plant monitoring technology. The method includes: dividing the thermal power plant into coal bunker operating areas and non-operating areas based on a 3D visualization model; collecting video data from the coal bunker operating areas and preprocessing the video data; using anomaly recognition technology to analyze the preprocessed video data frame by frame to identify potential safety hazards in the coal bunker operating areas; these hazards include improper wearing of safety helmets, improper wearing of work clothes, and improper deployment of fire extinguishing equipment; constructing a risk level assessment model and using this model to assess the risks of potential safety hazards; and generating a multi-level early warning mechanism for the thermal power plant's coal bunker based on the risk assessment results. This invention achieves comprehensive and refined intelligent monitoring of the safety status of personnel operating in the thermal power plant's coal bunker and the deployment of fire extinguishing equipment.

The application discloses a kind of aviation flight state monitoring and fault early warning method based on multi-source data fusion, including multi-source data fusion, the data of same time period in flight state is collected, the influence of removing noise is adopted Kalman filtering algorithm, and according to 3 guidelines removes outlier, and the main characteristic parameters are extracted using grey correlation analysis method and are fused with multi-source data;Flight state monitoring and fault early warning, select the main characteristic parameter monitoring data of flight state related fault as the target parameter and model output of prediction model, and the state input of high correlation degree is used as input, and a support vector machine prediction model is established to predict the main characteristic parameters, compare the predicted value with the actual value, and realize its fault early warning through trend analysis.

The utility model relates to photovoltaic power plant monitoring technical field, specifically disclose the monitoring device for photovoltaic power plant cleaning data collection, including the main rod and install the auxiliary rod of main rod one side, the auxiliary rod top installs the crosspiece, the crosspiece top installs the environmental monitoring mechanism, the main rod top installs the fixed link, and the fixed link far from the bottom of auxiliary rod one end installs thermal imaging appearance, main rod one side is equipped with the engagement frame, and the engagement frame is equipped with the butt joint groove with photovoltaic board butt joint in, and the engagement frame top connects the tilt angle sensor, and the tilt angle sensor engagement frame one side is connected with the rotation axis of rotation cooperation with main rod, the utility model has the real -time monitoring function, and the device is installed in photovoltaic power plant, and is installed on photovoltaic support one side, and the surrounding environmental data collection of photovoltaic board is provided with more scientific, accurate decision basis for the cleaning time through real -time acquisition and analysis these data, and the subsequent cleaning frequency setting is convenient, can realize the comprehensive monitoring and management to photovoltaic power plant cleaning work.

The application discloses a surface cover change detection method based on multi-temporal remote sensing images and relates to the technical field of natural resource law enforcement and ecological protection supervision; the method comprises the following steps: obtaining monthly multi-temporal remote sensing images covering 12-24 months, basic geographic information data and ecological function regionalization data and performing pretreatment; performing per-pixel time series decomposition on the standardized images, extracting change starting time, duration, change rate and stage spectral characteristics, and constructing change behavior fingerprints of each pixel; generating to-be-detected change map spots through spatial clustering; performing similarity matching on the change behavior fingerprints of the map spots and a pre-trained standard behavior fingerprint library, identifying surface cover change types; and finally, calculating the severity of illegal activities and evaluating ecological hazards, and generating a dynamic law enforcement report. The application breaks through the static thinking of traditional double-temporal change detection, can automatically identify multiple illegal activity types and evaluate ecological hazards.