10results about How to "Effective early warning" patented technology

The embodiment of the invention provides a task early warning method, device, system and equipment for animal physiological statuses, and relates to the technical field of data processing, the method comprises the following steps: responding to a condition for triggering task analysis, and aiming at each monitoring period in a plurality of continuous monitoring periods, performing task analysis according to the condition for triggering task analysis; determining each multi-dimensional feature of the target animal in the monitoring period; for each monitoring period, based on each multi-dimensional feature in the monitoring period, constructing a target time sequence feature sequence corresponding to the monitoring period; and inputting each target time sequence feature sequence into a prediction model to obtain a prediction result about whether a task set for the specified physiological state of the target animal needs to be executed or not in the candidate task execution time period to which the current time belongs. According to the scheme, effective early warning can be carried out on the task set according to the specified physiological state of the animal.

This invention discloses a method and system for accident rescue risk early warning based on real-time calculation. The method includes: when a collapse accident occurs and rescue is required, acquiring surrounding rock parameters, collapse body parameters, and a expected rescue plan; constructing a finite element model based on the surrounding rock parameters, collapse body parameters, and expected rescue plan, and using the excavation advance of the expected rescue plan as the calculation advance; loading a seepage model onto the finite element model based on the expected groundwater level and initializing the steady-state seepage field, and then performing excavation simulation calculations through the finite element model; performing excavation simulation calculations in each round using the calculation advance; conducting rescue operations according to the expected rescue plan, and adjusting and recalculating the parameters of the finite element model and seepage model based on data detected during the rescue operation; when the calculation result of the finite element model exceeds the warning value, determining that there is a risk in the current rescue operation.

The application discloses a low-voltage distribution area electric leakage fault positioning and early warning method and product based on edge calculation, and relates to the technical field of area operation and maintenance.The application deploys a data collection unit integrated with an edge calculation module on the low-voltage side of a transformer, supports data analysis and processing at the edge, effectively reduces delay to improve response, deploys corresponding branch detection units on each branch line, deploys corresponding intelligent circuit breakers on each user meter, and through multi-point synchronous sampling and analysis, can position electric leakage faults to specific user meter boxes.The application constructs a tree topology of the entire area and real-time monitors the total residual current of the area, through the cooperation of setting early warning conditions and early warning pre-judgment, effectively realizes early warning while reducing false signal false positives.

The invention provides a dual-heart health early warning system and method based on millimeter wave radar and electronic equipment, and relates to the technical field of non-contact physiological signal processing, the system comprises a signal acquisition and processing module used for extracting a target respiration signal and a target heartbeat signal in an original echo signal; the multi-parameter adaptive classification module is used for carrying out heart function parameter extraction processing to obtain a target respiratory rate, a target heart rate, target heart rate variability and target cardiopulmonary coupling; the psychological and emotion evaluation module is used for obtaining a target psychological state evaluation result and a target emotion state evaluation result; and the fusion decision module is used for inputting the target respiratory rate, the target heart rate, the target heart rate variability, the target cardiopulmonary coupling, the target psychological state evaluation result and the target emotional state evaluation result into the double-heart linkage early warning model to obtain a physiological parameter early warning result. According to the method, physiological signals with higher precision are extracted, and effective early warning of psychological and heart parameters is realized.

The present application provides a kind of wetland ecological security early warning method and system based on remote sensing analysis, first, obtain the multi-dimensional remote sensing data set of target wetland area including multi-temporal imaging, spectral radiation and microwave scattering data, and obtain the ecological process signal set by interpretation;Establish the mapping relationship model of ecological process signal and wetland ecological security state, obtain the current ecological security state description;Cross-process correlation analysis is carried out on the ecological process signal, and the abnormal conduction chain of ecological process is formed;Construct early warning trigger node system and generate early warning rules;Real-time multi-dimensional remote sensing data is obtained, and after interpretation, it is matched with early warning rules, and wetland ecological security early warning information including abnormal ecological process link, abnormal conduction path and early warning response node is generated.The present application can accurately and comprehensively early warn wetland ecological security risk, and protect the stability of wetland ecosystem.

This invention relates to the field of electronic circuit breaker protection technology, specifically to an intelligent overload protection and fault diagnosis method and device for electronic circuit breakers. The device includes: a multi-source data acquisition unit, an edge processing unit, a protection drive execution unit, a human-machine interaction unit, a cloud interaction unit, and a power management unit. This invention solves the problem of existing electronic circuit breaker protection schemes considering only a single factor. By using a dynamic thermal balance equation and a modified inverse-time action expression, it comprehensively considers the effects of ambient temperature, conductor aging, power grid harmonics, and load type, reducing protection action errors. In nonlinear load scenarios, the protection action error is small, avoiding false tripping or failure to trip, and balancing speed and power supply selectivity.

The utility model relates to a parking space anti -collision technical field especially, it is a kind of electric vehicle charging positioning anti -collision mechanism, its technical scheme includes: underframe, the underframe is installed with fender subassembly, warning subassembly is installed on the fender subassembly, the fender subassembly is rotatably installed with underframe, adjusting subassembly is installed on the fender subassembly, and the adjusting subassembly is used to adjust the rotation angle of fender subassembly on underframe;The warning subassembly includes pressurized air bag, and pneumatic horn is installed on the pressurized air bag.The utility model has the advantages of effective early warning and buffer collision, solves the problem that vehicle tail and charging pile collide and cause vehicle and equipment damage and security risk.

Embodiments of the present application provide a task early warning method, device, system and equipment for animal physiological state, which relates to the technical field of data processing. The method comprises: in response to meeting a condition for triggering task analysis, determining, for each monitoring period in a plurality of continuous monitoring periods, each multi-dimensional feature of a target animal in the monitoring period; for each monitoring period, constructing a target time sequence feature sequence corresponding to the monitoring period based on each multi-dimensional feature in the monitoring period; and inputting each target time sequence feature sequence into a prediction model to obtain a prediction result of whether a task set for a specified physiological state of the target animal needs to be performed in a candidate task execution period to which a current time belongs. It can be seen that the present solution can effectively warn the task set for the specified physiological state of the animal.

This invention discloses a product appearance defect detection system and method based on image semantics, belonging to the field of defect detection technology. The system includes: an image acquisition module for acquiring real-time images of the product appearance; an image processing module for processing the real-time images of the product appearance; an image semantics module for extracting features and performing semantic segmentation on the real-time images of the product appearance to generate a semantic image of the product appearance; and a defect detection module for detecting defects in the product appearance, determining whether defects exist, and providing early warnings and visual displays of defect conditions. This invention solves the problem of existing methods that cannot effectively detect product appearance defects based on image semantics, resulting in poor defect detection performance. This invention can effectively detect product appearance defects based on image semantics and can provide timely early warnings based on defect detection results, thus improving the overall defect detection effect.

The utility model provides a self-adaptive near-electricity voice alarm and a safety helmet, the alarm comprises a master control module, a near-electricity alarm module and a self-adaptive voltage detection channel selection module, the master control module and the self-adaptive voltage detection channel selection module are respectively electrically connected with the near-electricity alarm module, and the near-electricity alarm module is electrically connected with the self-adaptive voltage detection channel selection module. The main control module is electrically connected with the adaptive voltage detection channel selection module; the adaptive voltage detection channel selection module comprises a detection matching circuit, a plurality of voltage detection circuits and a gating control circuit, one end of the detection matching circuit is electrically connected with the near-electricity alarm module, and the other end of the detection matching circuit is electrically connected with the plurality of voltage detection circuits; and the plurality of voltage detection circuits are electrically connected with the gating control circuit respectively. According to the technical scheme of the utility model, a plurality of different voltage grades can be detected adaptively, and the alarm threshold value can be adjusted automatically and accurately according to the electric field intensity monitored in real time, so that effective early warning of a multi-stage voltage environment can be realized.