4results about How to "Valid input" patented technology

The invention provides a dripping speed detection and alarm device for an infusion apparatus, and belongs to the technical field of medical instruments. The device comprises a fixing frame, a clamping assembly is installed on one side of the fixing frame, the clamping assembly is used for clamping a drip cup part on an infusion tube, the clamping assembly comprises two clamping plates, and a piezoelectric sensor is embedded in the inner wall of one clamping plate; a spring rope is fixedly installed at the lower end of the fixing frame, a connecting block is fixedly installed at the lower end of the spring rope, a single-chip microcomputer is installed on the upper side in the connecting block, and the piezoelectric sensor is connected with the single-chip microcomputer through a wire. A cavity is formed in the lower side in the connecting block, a trigger assembly is installed in the cavity, the single-chip microcomputer is in linkage with the trigger assembly, and first switches are fixedly installed at the two ends of the inner wall of the cavity; an alarm is fixedly mounted at the upper end of the connecting block; a body temperature detection assembly is installed at the lower end of the connecting block and is in linkage with the triggering assembly. The dripping speed of the liquid medicine or the detected body temperature can trigger the first switch, so that the alarm gives an alarm to remind to adjust the dripping speed, and the risk is reduced.

The invention is suitable for the technical field of automobile aerodynamics, and provides a self-adaptive flexible spoiler experimental development method under a yaw working condition, and the method comprises the steps: arranging and driving a flexible spoiler in a wind tunnel; the parameters of the spoiler are optimized with the wind resistance coefficient as the target at the multiple yaw angles; designing a piecewise linear rule controller based on an optimization result; pressure monitoring points are arranged on the two sides of a vehicle body, the regression relation between the pressure difference and the yaw angle is established, and the yaw angle is recognized in real time; developing a self-adaptive resistance reduction optimization program, driving the spoiler to be adjusted to the optimal form in real time according to the identified yaw angle, and verifying the resistance reduction effect of the spoiler; a mathematical method is used for calculating the curved surface shape of the spoiler, and reference is provided for automobile appearance design. Aerodynamic configuration self-adaptive adjustment of the vehicle under the crosswind working condition can be achieved, the wind resistance optimization capacity of the real vehicle in the running process is remarkably improved, and an effective experimental method and design basis are provided for low-wind-resistance development of the vehicle.

A method for profiling chlorophyll a concentration in open water bodies based on photon-counting lidar is proposed to accurately obtain the profile concentration distribution of chlorophyll a in water. Combining ICESat-2 photon-counting lidar data with MODIS satellite remote sensing imagery, Monte Carlo simulation is used to model the photon propagation process, calculate the energy attenuation and scattering characteristics of photons in the water, and further derive the extinction coefficient and backscattering coefficient. Based on these parameters, the chlorophyll a concentration distribution is retrieved. By accurately simulating the photon propagation process in water, considering the optical properties and environmental factors of the water body, high-precision chlorophyll a concentration profile data can be provided. The use of MODIS remote sensing data further improves the accuracy and reliability of the retrieval results, enabling precise chlorophyll concentration detection in different open water areas. This method is applicable to chlorophyll concentration monitoring in oceans, lakes, rivers, and other water bodies, and provides a scientific basis for aquatic ecological environment assessment.

This invention relates to the field of machine learning and equipment health monitoring technology, and discloses an efficient method and system for storing vibration data based on machine learning-based sensitive monitoring. The method includes: setting up a parameter-locked anchor point model and an online learning buoy model in parallel; simultaneously inputting real-time vibration data into both models, calculating the benchmark drift based on the difference in their errors, and simultaneously calculating the instability index based on the dispersion of the anchor point model error sequence; triggering data storage when any index exceeds a preset threshold. This invention solves the technical problem that monitoring models cannot detect long-term slow degradation and early instability precursors of equipment due to continuous adaptation by constructing a differential reference system between a static health benchmark and a dynamic current benchmark, combined with the analysis of error sequence stability. It can distinguish between real fault trends and normal operating condition fluctuations, and avoids contamination of the monitoring benchmark.