6results about How to "High acquisition frequency" patented technology

This invention relates to the field of pipe wall monitoring technology, and discloses an intelligent pipe wall thickness monitoring system, method, device, medium, and product. The system includes: a data acquisition unit configured to acquire electrical level data to obtain a first dataset; a second dataset acquired by acquiring electrical level data from each Hall sensor; a judgment unit configured to compare the electrical level data corresponding to each sensor array in the second dataset with the electrical level data corresponding to each sensor array in the first dataset, and determine whether corrosion exists in the monitored pipe based on the comparison result; a processing unit configured to adjust the acquisition time interval according to an adjustment coefficient; and an adjustment unit configured to determine whether to adjust the adjustment coefficient of the acquisition time interval. This invention solves the problem of large errors caused by reliance on manual labor, improves the efficiency and accuracy of pipe monitoring, and enhances its adaptability and intelligence.

The invention provides a competition risk-based sow reproduction dynamic early warning regulation and control method and system, and the method comprises the steps: collecting the basic data of a sow at a current observation moment t, extracting a feature vector, calculating the risk ratio of an individual sow to a standard sow based on the feature vector, calculating the accumulated morbidity of each reproduction abnormality event from breeding to the current observation moment t, and carrying out the early warning regulation and control. Calculating the predicted cumulative morbidity of the sow from the current observation moment t to a period of time in the future, determining a risk level according to the predicted cumulative morbidity, generating a control instruction, sending the control instruction to a hardware execution layer through a communication bus, driving the hardware execution layer to execute intervention, and dynamically adjusting the acquisition frequency of a sensor according to the risk level; and body weight and backfat feedback data are obtained after intervention, and if a preset threshold value is not reached, intervention parameters are automatically upgraded, so that closed-loop regulation and control are realized. According to the method, the competing risk model is constructed by taking the abnormal reproduction events as the mutual exclusion events, so that the risk probability is more accurate, and the sow breeding process can be accurately intervened.

The invention relates to the technical field of quality prediction, in particular to a fermentation quality prediction management system for enzyme production based on data processing. The system comprises the following modules: an environmental parameter acquisition module, a microbial activity monitoring module, a fermentation state identification module and a prediction regulation and control module, wherein the environmental parameter acquisition module acquires environmental condition parameters in a fermentation tank in real time through a multi-parameter sensor array; an enzyme activity index and nutrition consumption rate data are obtained from the microbial activity monitoring module; the microbial activity monitoring module is used for judging a microbial behavior track, correcting track offset and identifying characteristics of each fermentation stage; and the prediction regulation and control module predicts the product quality, and optimizes fermentation process parameters according to the deviation between the prediction result and the target quality. According to the method, prospective control over the enzyme production quality is achieved, the intelligent level of the whole fermentation process is improved, and a flexible and efficient fermentation quality control mechanism is formed.

This application provides a control method, device, smart glasses, medium, and program product for smart glasses. The control method includes: periodically acquiring eye-tracking images of the wearer according to a default cycle using an eye-tracking device during the wearing of the smart glasses; determining the wearer's eye usage data based on the eye-tracking images; adjusting the acquisition cycle of the eye-tracking images based on the eye usage data; and providing eye health reminders. By combining real-time eye usage information with eye health reminders, it is beneficial to improve the eye habits of smart glasses wearers and enhance eye protection. Simultaneously, by dynamically adjusting the acquisition cycle of the eye-tracking images based on eye usage information, eye-tracking image acquisition can be performed at a lower frequency when eye usage is healthy, thereby reducing the power consumption of eye monitoring.

The application introduces a roadside traffic signal data acquisition and processing system and method, wherein the roadside traffic signal data acquisition and processing system comprises: a traffic signal controller for controlling the traffic light at the road intersection; and a signal protocol conversion device for acquiring the data of the traffic signal controller and sending the acquired data to a data center. The signal protocol conversion device comprises a voltage acquisition unit for acquiring the voltage data in the traffic signal controller and a pulse detection unit for acquiring the pulse data in the traffic signal controller, and the voltage acquisition unit and the pulse detection unit are connected with the traffic signal controller respectively. Based on the above system design, the roadside traffic signal data acquisition and processing method designed by the application has the advantages of wide voltage acquisition range, high acquisition frequency, short processing time, wide adaptability and high reliability.

The invention discloses a real-time monitoring and early warning method and device for an electrochemical energy storage power station. The method comprises the following steps: acquiring multi-parameter time sequence data; carrying out fusion analysis and state prediction on the data; establishing and online updating a self-adaptive safety threshold value of each parameter; matching the real-time observation sequence with a pre-constructed multi-mode fault evolution knowledge graph to obtain a mode matching confidence coefficient; predicting the probability that the battery is in a dangerous state in the future, and taking the probability as state prediction confidence; calculating the standard exceeding amplitude and duration of the current parameter value relative to the safety threshold, and obtaining threshold standard exceeding confidence; carrying out weighted fusion on the mode matching confidence coefficient, the state prediction confidence coefficient and the threshold exceeding confidence coefficient, and calculating to obtain a comprehensive risk confidence coefficient; and according to the comprehensive risk confidence, triggering an early warning signal and an emergency response measure of a corresponding level. According to the invention, the safety of the energy storage power station is effectively improved, the stable operation of the energy storage power station is ensured, and the accuracy, robustness and adaptability of early warning are improved.