Abstract

Relevance. The problem of controlling complex technological machines such as machines with mechanisms based on kinematics with parallel structure is given consideration in the article in order to improve accuracy of positioning of actuators, to ensure their dynamic adjustment and optimization of trajectories of displacement of operating elements of the equipment (cutting tools, assembling or controlling instruments). The object of the study is the model of the operating area of a mobile robotic machine tool. Objective. The goal of the work is to create a concept for controlling a mobile robotic machine tool applying acoustic control on the basis of a reference model based on deep neural networks. Method. A method of identification and control of a mobile robotic machine tool using spectral description of absorption of acoustic wave with further processing of obtained information is offered. This method allows determining accuracy of positioning of actuators, as well as conducting dynamic adjustment and optimization of trajectories of displacement of operating elements of the equipment. A method of acoustic analysis for precision machining on machine tools with parallel kinematics has been developed. Results. A neural network reference model has been constructed, which allows to diagnose current characteristics of the state of objects in different conditions, namely mechanism’s configuration, mechanism’s geometric parameters while running motor-spindle, dynamics of displacement of mechanism’s nodes of the experimental stand with variable velocities and load on the drive, as well as temperature changes of the object. The developed neural network models also were tested for adequacy. Conclusions. The experiments on the study of the dependency between the parameters of the spectrum of the acoustic signal with a given discreteness disturbed by excitatory effect in the form of “white noise” confirmed efficiency of this approach. Prospects for further research may consist in creation of methods for optimal control of complex technological machines to improve accuracy of positioning of actuators and to improve their dynamic settings.

Highlights

  • A neural network reference model has been constructed, which allows to diagnose current characteristics of the state of objects in different conditions, namely mechanism’s configuration, mechanism’s geometric parameters while running motor-spindle, dynamics of displacement of mechanism’s nodes of the experimental stand with variable velocities and load on the drive, as well as temperature changes of the object

  • The problem of controlling complex technological machines such as machines with mechanisms based on kinematics with parallel structure is given consideration in the article in order to improve accuracy of positioning of actuators, to ensure their dynamic adjustment and optimization of trajectories of displacement of operating elements of the equipment

  • The object of the study is the model of the operating area of a mobile robotic machine tool

Read more

Summary

Methods

Given the special importance of the issue, the authors of the article offer a comprehensive approach, in which the processes of control and analysis are a procedure for creating a reference model of controlling an object and keeping this model current during the technological operation. The basis of this approach is the acoustic signal spectrum, reflected from the elements of the technological system and the system of its transformation (Fig. 5).

Results
Discussion
Conclusion
Full Text
Published version (Free)

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call