A machine learning-based method, device and system for controlling the discharge speed

Abstract

The invention discloses a method, device and system for controlling the exit speed based on machine learning, and belongs to the technical field of electrical appliances. The time and speed corresponding to the preset position and the second preset position (t 1 ,v 1 ,t 2 ,v 2 ) and the corresponding trigger signal (n 0 ,t 0 ); S2: the moment velocity signal corresponding to various exit states (t 1 ,v 1 ,t 2 ,v 2 ) as the dependent variable, the trigger signals (n 0 ,t 0 ) as an independent variable to train the machine learning model; S3: Obtain the moment velocity signal corresponding to the current exit state (t 1 * ,v 1 * ,t 2 * ,v 2 * ), using the trained machine learning model pair (t 1 * ,v 1 * ,t 2 * ,v 2 * ) to get the current trigger signal (n 0 * ,t 0 * ); S4: When the trigger time t is reached 0 * , control n 0 * A pulsed power supply drives the armature of an electromagnetic railgun. Using the trained machine learning model to solve the trigger signal of the exit speed can improve the control accuracy of the exit speed.

Description

technical field [0001] The invention belongs to the technical field of electrical and electrical appliances, and more particularly, relates to a method, device and system for controlling the speed of burring based on machine learning. Background technique [0002] With the development of modern artillery launching technology, many new problems have been raised in the study of internal ballistics. For artillery weapons, whether it is to improve the effective combat capability of air defense weapons, or to develop anti-tank weapons to deal with new types of armored targets in the future, and to suppress weapons that provide fire support to infantry on a large depth and wide front, it is required to greatly increase the projectile. muzzle velocity and muzzle kinetic energy. The traditional artillery firing technology uses the chemical energy released by the combustion of the propellant to drive the projectile. Due to the limitation of the energy density of the chemical propell...

AI Technical Summary

Problems solved by technology

[0004] Aiming at the above defects or improvement needs of the prior art, the present invention provides a machine learning-based method, device and system for controlling the speed of the chamber, the purpose of which is to use the machine learning algorithm to learn the collected speed time signal and trigger signal, Then use the trained machine learning model to process the collected current speed and time signal to obtain the current trigger signal, and then use the current trigger signal to discharge and drive the armature, thereby solving the technical problem of low launch accuracy of the existing electromagnetic launch system

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