7results about How to "Avoid covering up" patented technology

The application provides a power distribution network fault abnormality monitoring and early warning method based on multi-source operation data fusion, and relates to the technical field of power system distribution network fault monitoring and early warning. The application obtains distribution network equipment operation data, defect abnormality data, equipment abnormality data, heavy overload data, low voltage data and three-phase imbalance data in a marketing system, a production system, a safety monitoring system and a dispatching system, forms multi-source abnormality data, classifies and aggregates the multi-source abnormality data according to line area, abnormality type and collection time, and performs same-source deduplication and cross-source merging to obtain fused abnormality data, analyzes and processes the fused abnormality data, identifies data representing distribution network fault abnormality and generates a fault abnormality event, and then determines a responsible unit and a line area person in charge according to the corresponding relationship between the line area and the person in charge and dispatches them, so that the monitoring and early warning of the distribution network fault abnormality are realized, and the pertinence and accuracy of the monitoring and early warning are improved.

This invention discloses a gas pipeline leak detection method based on the random forest algorithm, relating to the field of gas leak detection. The invention first collects and preprocesses monitoring data from combustible gas sensors in the gas pipeline, then extracts features from the preprocessed data and assigns classification labels based on actual leak conditions, constructing a gas pipeline leak detection dataset. Using this dataset as training samples, a model is trained based on the random forest algorithm to obtain a gas pipeline leak detection classification model. Finally, real-time monitoring data from each combustible gas sensor during gas pipeline operation is input into the trained classification model, and the pipeline leak status is determined based on the model's output. This invention, through standardized data preprocessing, feature engineering, model training, and parameter optimization processes, can achieve accurate identification and early warning of gas pipeline leak status, effectively improving the accuracy and efficiency of leak detection.

This invention discloses an in-vehicle selective noise reduction method based on sound field reconstruction, relating to the field of in-vehicle safety warning technology. The method includes: collaboratively collecting in-vehicle acoustic and vibration data through sensors; separating the acoustic and vibration data using a blind source separation algorithm to obtain a voiceprint feature tensor; inputting the voiceprint feature tensor into a convolutional neural network for voiceprint recognition, outputting a safety sound category and a safety sound hazard level; generating adaptive noise reduction parameters based on vehicle speed and safety sound category; assigning the final adaptive noise reduction parameters to seats in different regions; and issuing a physical vibration warning based on the safety sound hazard level to complete the in-vehicle selective noise reduction. This invention significantly improves the detection and recognition accuracy of critical safety sounds in road noise environments; it balances noise suppression and active safety assurance, effectively enhancing the vehicle's perception and response capabilities to emergency sound sources while improving passenger comfort.

The present application relates to the technical field of dissolved oxygen monitoring, and specifically relates to a complex water body dissolved oxygen differential monitoring method. Current water area data corresponding to each initial sub-water area in a target water area is obtained, and the current water area data includes current hydrological data, current meteorological data, and current water quality data. Based on the current water area data corresponding to each initial sub-water area, the current target dissolved oxygen corresponding to each initial sub-water area is determined. According to the current target dissolved oxygen corresponding to each initial sub-water area, the preset measures corresponding to each initial sub-water area are determined. The real state of dissolved oxygen in different sub-water areas can be accurately reflected, and the sub-water area level fine calculation of dissolved oxygen is realized. Based on the actual dissolved oxygen state of the initial sub-water area, the differential preset measures are accurately matched, the precise control of "one area one strategy" is realized, and the over-intervention or insufficient intervention caused by undifferentiated control is avoided, and the occurrence of ecological risks such as low dissolved oxygen is effectively prevented.

This invention provides a data analysis-based method and system for compliant registration and identification of tenants in rental properties, relating to the field of data processing technology. The method includes: mapping each behavioral record in each property identifier to a tenant occupancy marker at each time point; constructing a tenant occupancy continuity relationship between adjacent time points; identifying whether each person is stably residing in the rental property, obtaining an occupancy disturbance value; identifying and separating the portion of a person's continuous trajectory belonging to the registered tenant identifier; splicing together the temporally adjacent portions of different people's continuous trajectories with the same tenant identifier; identifying the duration of each person's presence in the rental property, obtaining an occupancy duration value; and filtering out trajectories from unregistered occupancy trajectories where both the occupancy duration value and the occupancy disturbance value meet a preset stability value, thus obtaining differential tenant trajectories. This invention can accurately identify the actual residents of rental properties, avoiding identification errors caused by delayed or incomplete registration information.

This invention relates to the field of computer technology and discloses a personnel allocation decision-making method, system, electronic device, and storage medium based on working hour data. The method includes acquiring working hour data, classifying and structuring it, and performing multi-dimensional statistical analysis on the classified working hour data to generate a working hour distribution map; calculating the maximum number of personnel at full capacity based on the total annual working hour demand and the standard working hours available per person per year; acquiring data on the difference between actual working hours and statutory standard working hours, as well as unused leave, and calculating the equivalent personnel shortage based on an overtime compensation model; establishing a resource balance model that includes constraints such as shift work, skill level matching, time period distribution, and management redundancy, calculating the resource balance coefficient, and correcting the maximum number of personnel at full capacity to obtain an executable personnel allocation base; and determining the personnel allocation plan by combining the equivalent personnel shortage, the personnel allocation base, and future working hour demand. This invention can improve the executability of personnel allocation decisions.

The application discloses a zero-carbon park inter-energy fusion-oriented charging load and industrial load collaborative optimization method, relates to the technical field of energy internet and power system optimization control, acquires park multi-source data, constructs a double-network model of a traffic network and a power distribution network, and takes a charging station as a shared node; a site side and a power grid side risk field is inferred based on a space-time graph neural network; an inter-energy consistency checker IEC is constructed to generate a zero setting gate matrix to form a feasible candidate set; a multi-objective mixed integer programming collaborative scheduling model is solved under the constraint of the feasible candidate set, a bilateral trigger type safety valve slack variable is introduced to generate a bottleneck evidence bag; a key bottleneck object set is determined based on a constraint shadow price distribution and a zero setting ratio distribution, an expansion candidate set is generated, an evidence chain expansion planning model is constructed to obtain an expansion scheme, a feasible region improvement constraint judgment is executed, and rewriting is performed into rolling optimization.