Method for controlling consistency of vibration of surfaces of shell structures on basis of neural networks

Abstract

The invention discloses a method for controlling the consistency of vibration of the surfaces of shell structures on the basis of neural networks. The method includes firstly, constructing vibration consistency control architectures on the basis of a neural network optimization algorithm; secondly, deducing weight and threshold iterative formulas of identifiers and controllers on the basis of a gradient descent process; thirdly, further computing global errors and frequency-point errors, combining the global errors and the frequency-point errors with one another and creating a novel error judgment criterion for judging difference between control effects and targets; fourthly, synchronously controlling the consistency of vibration response of multiple points of the surfaces of the shell structures so as to cooperatively controlling the vibration response of the multiple points of the surfaces of the shell structures. Each control architecture mainly comprises two core modules which are the corresponding identifier and the corresponding controller respectively, the identifiers are used for identifying controlled shell models and predicting the vibration response, and the controllers are used for implementing excitation parameter optimization and control targets. The weight and threshold iterative formulas are used for optimizing and updating loop parameters.

Description

technical field [0001] The invention belongs to the field of optimization control of vibration response of mechanical structures, and in particular relates to a neural network-based method for controlling surface vibration consistency of shell structures. Background technique [0002] At present, vibration optimization control mainly focuses on structural modification, passive control and active control. Structural transformation is highly reproducible, but it is highly restrictive, poor in flexibility, and high in replacement costs; passive control is at the expense of increasing equipment quality, and the effect of low-frequency vibration suppression is limited; active control uses real-time control strategies based on detected vibration signals , to drive the actuator to apply force or torque to the control object, so as to achieve the vibration optimization goal. It has the characteristics of strong adaptability, low cost and high efficiency, so it has attracted extensiv...

AI Technical Summary

Problems solved by technology

Structural transformation is highly reproducible, but it is highly restrictive, poor in flexibility, and high in replacement costs; passive control is at the expense of increasing equipment quality, and the effect of low-frequency vibration suppression is limited; active control uses real-time control strategies based on detected vibration signals , to drive the actuator to apply force or torque to the control object, so as to achieve the vibration optimization goal. It has the characteristics of strong adaptability, low cost and high efficiency, so it has received extensive attention

[0003] The research on active vibration control is currently mainly focused on the suppression of vibration, that is, the use of external forces to minimize the vibration of the controlled equipment. However, with the development requirements of high-speed, precision and quiet mechanical equipment, active Vibration control is facing new challenges: How to ensure the maximization of the power source of mechanical equipment and the minimization of vibration and noise become a pair of contradictions

Images