7results about How to "Reliable early warning" patented technology

The invention discloses a venous transfusion intelligent speed regulation anti-leakage device and a working control method thereof, and the device comprises a speed regulation module, an anti-leakage monitoring module, a pressure protection module, a control module and an interaction module. Accurate adjustment of infusion flow speed, real-time monitoring and early warning of leakage and dynamic control of infusion pressure are achieved. The speed regulation module covers mechanical precise speed regulation and intelligent closed-loop speed control and adapts to multi-scene infusion requirements; the anti-leakage monitoring module realizes rapid identification and alarm of leakage through a conductivity sensing, pressure sensing or infrared imaging technology; and the pressure protection module avoids the risk of high-pressure leakage through a pressure release valve or pressure self-adaptive adjustment. The device is adaptive to traditional infusion equipment, is simple and convenient to operate, is controllable in cost, can remarkably improve the infusion safety and accuracy, reduces the nursing workload, and is suitable for the scenes of conventional infusion, special precise infusion and the like of medical institutions at all levels.

The application discloses a kind of mechanism and data double-constrained drilling gas invasion early warning method and device, comprising: drilling engineering parameter is input to wellbore hydraulics model, generates virtual sensing data in well, and with wellhead ground measured data fusion forms multi-source fusion data, multi-source fusion data are used to train physical information neural network, and gas invasion early warning prediction model is obtained;Real-time fusion feature vector is input to gas invasion early warning prediction model, and wellhead pressure prediction value is output;According to wellhead pressure prediction value and wellhead ground measured data calculation physical error, and wellhead ground measured data are input to self-encoder calculation data reconstruction error, and physical error and data reconstruction error are fused into comprehensive anomaly index;Comprehensive anomaly index is compared with preset grading early warning threshold value, to carry out drilling gas invasion grading early warning according to comparison result.The application can realize complex drilling gas invasion risk early, accurate, reliable early warning.

This invention discloses an intelligent analysis method for low-altitude remote sensing data from low-altitude unmanned aerial vehicle (UAV) hangars, belonging to the field of intelligent control technology. This scheme first collects multi-source heterogeneous data through timestamp alignment and hardware-triggered synchronization mechanisms; then, geometric correction is achieved through joint optimization of the RPC model and GCP, and image stitching is completed by combining SIFT feature matching and graph cut algorithms; subsequently, an improved YOLOv8 model is constructed to achieve multimodal fusion target detection, and semantically guided change detection is completed based on the Transformer algorithm; a high-precision 3D model is generated by fusing multi-source data using an enhanced NeRF algorithm, and vegetation analysis and trend prediction are completed using a dynamic weighting algorithm and an LSTM network; finally, a comprehensive report is generated based on a knowledge graph and interactive visualization output is provided. This invention effectively solves the problems of inefficient multi-source data processing and insufficient core detection accuracy in existing technologies, significantly improving data processing efficiency, detection accuracy, and analytical practicality, and is applicable to multiple scenarios such as ecological monitoring and resource exploration.

This invention relates to the field of complex human-machine systems technology, and particularly to an early warning method and device for detecting poor mental workload in operators. The method includes: determining the output state of a target mental workload recognition model to obtain a mental workload state result; determining whether the proportion of the same abnormal state in the mental workload state result exceeds a preset threshold; if not, no early warning response is triggered; otherwise, performance monitoring of the target operator is performed to obtain a performance state result; determining whether the performance state result deviates from the individual's historical performance range; if it deviates, an intervention response is triggered; otherwise, a prompt-level response is triggered. This solves the problems of existing early warning methods, such as difficulty in adaptively adjusting to changes in the operational context, leading to a high risk of false alarms or missed alarms, and difficulty in achieving targeted, sensitive, and effective support, thus affecting the intervention effect.

According to the dangerous goods transportation carrier real-time monitoring system, the transportation environment detection module adopts a sensor to detect environment parameter information during dangerous goods transportation, electrostatic protection output is performed through electrostatic protection and range adjustment, the carrier electrostatic detection module detects static electricity generated during dangerous goods transportation, static electricity is conducted according to the magnitude of electrostatic voltage, and then the dangerous goods transportation carrier is monitored. The fire hazard early warning module receives environment parameter information, compares the environment parameter information with a threshold value signal through a differential comparator, carries out early warning through inverse time limit triggering, and sends an early warning signal to the field monitoring host. The change rate of the environmental parameter information adjusts the size of a threshold signal, the signal after electrostatic conversion adjusts the comparison value of the differential comparator, and the on-site monitoring host performs fire alarm, automatically analyzes a fire source and takes linkage measures in combination with an early warning signal and a video camera, and remotely transmits positioning information to the monitoring terminal according to the early warning level.

This specification provides an energy-saving early warning management method and an Internet of Things (IoT) system for smart gas flow meters. The energy-saving early warning management method based on a smart gas flow meter is executed by a smart gas management platform and includes: acquiring the remaining power of the smart gas flow meter; determining the confidence level of the remaining power based at least on environmental data; calibrating the remaining power based on the confidence level to determine the calibrated power; determining whether to issue a power consumption warning to the gas user based on the calibrated power, smart gas flow meter operating data, and at least one reference correspondence, wherein the reference correspondence represents the relationship between the smart gas flow meter's behavior and power consumption; and generating a smart gas flow meter operating plan in response to issuing a power consumption warning to the gas user.

The application discloses a kind of monitoring method and monitoring system of partial discharge of current collection circuit, the method comprises: installing high-frequency pulse monitoring device at each section of current collection circuit two ends;Real-time signal acquisition, when detecting that pulse amplitude exceeds starting threshold, trigger recording wave, record waveform in time window and form pulse sequence;Similarity is calculated to the pulse sequence captured by the same device, determine effective event;If there is effective event in the same time window at both ends of the same section, calculate the maximum similarity between the corresponding pulse waveforms of both ends, determine the discharge fault type of the section according to this;Traverse all sections, determine fault location according to adjacent section discharge fault type.The application carries out discharge fault monitoring based on time-domain waveform similarity and maximum similarity, does not rely on line topological structure, can adapt to parameter change, satisfies long-term on-line monitoring, realizes reliable identification of intra-zone and extra-zone discharge, achieves the effect of timely early warning and accurate positioning to discharge fault.