Method for rapidly measuring dropping speed of liquid drops of mobile equipment based on deep learning

Abstract

The invention relates to a method for rapidly measuring the dripping speed of liquid drops of mobile equipment based on deep learning. The method comprises: acquiring an image of a droplet dropping process to construct an image data set, and constructing a droplet image training set and a droplet image test set through image preprocessing and manual marking methods; selecting a binary classification neural network model, and training the binary classification neural network model through the droplet image training set to obtain a trained binary classification neural network model; preprocessing an image acquired by an intelligent terminal to obtain a to-be-detected droplet image; predicting through a trained binary classification neural network model; and if the second dripping state is predicted to be the dripping state, continuously predicting through the trained binary neural network model after a plurality of frames of images are spaced until the next dripping state is predicted tobe the dripping state, calculating to obtain the time length for the interval between two adjacent dripping states, and further calculating the current dripping speed. The drop speed of the liquid drops is measured quickly and accurately, and the measurement efficiency of the drop speed of the liquid drops is greatly improved.

Description

technical field [0001] The invention relates to the fields of neural network transfer learning and image classification, and specifically designs a method for quickly measuring the droplet velocity of a mobile device based on deep learning. Background technique [0002] In the intravenous infusion of certain special drugs such as potassium, vasopressors, etc. or special populations such as the elderly and children, or in some chemical reactions that have strict requirements on the drip rate of reactants, the measurement of droplet velocity and Monitoring is very important, especially in hospitals. Intravenous infusion therapy is an extremely common medical method. Manual measurement is time-consuming and laborious, which will bring a great burden to medical workers. The use of infusion pumps is expensive and inconvenient to move, so it is fast and easy. , Accurate detection of drop rate has become an urgent need in the infusion process. [0003] With the wave of artificial ...

AI Technical Summary

Problems solved by technology

[0002] In the intravenous infusion of certain special drugs such as potassium, vasopressors, etc. or special populations such as the elderly and children, or in some chemical reactions that have strict requirements on the drip rate of reactants, the measurement of droplet velocity and Monitoring is very important, especially in hospitals. Intravenous infusion therapy is an extremely common medical method. Manual measurement is time-consuming and laborious, which will bring a great burden to medical workers. The use of infusion pumps is expensive and inconvenient to move, so it is fast and easy. , Accurate detection of drop rate has become an urgent need in the infusion process

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