Theoretical and Experimental Identification of Frequency Characteristics and Control Signals of a Dynamic System in the Process of Turning.

Antoni Świć,Arkadiusz Gola

doi:10.3390/ma14092260

Abstract

The article presents the results of the experimental validation of the developed static, time and frequency characteristics under interference and longitudinal feed control of a dynamic system in the process of turning axisymmetric parts. The experiments were conducted on a test bench, consisting of a 16B16P center lathe, a measuring system and a PC with a measurement card. The experiments were carried out to verify the assumptions of the baseline model of the turning process. As part of the study, we determined the static characteristics of the machining process, the time characteristics of the object under interference and under longitudinal feed rate control, and the frequency characteristics of the machine tool system under longitudinal feed rate control. During the experiments, we recorded the observed input and output signal curves and the observed characteristics of the interferences acting on the object, as well as the numerical values of the parameters of the equations describing the model, and in particular the gain of the elastic system, which is difficult to determine by analytical methods. The positive results of the experiments confirm the effectiveness of the proposed models and their usefulness for automation of machining processes.

Highlights

Process automation is one of the key megatrends that drive Industry 4.0 [1]. This applies to the integration and complete automation of control of production processes to the extent that decisions are made by machines, with humans playing a supervisory role [2]
As Industry 4.0 is a challenge and a goal pursued by the world’s leading economies, there is large demand for research geared towards improving existing and developing new methods and models that can assist in automating technological processes [3]
The automation of machining process requires the development of specific optimization and control criteria suitable for the individual classes of machine tools

Summary

Introduction

Process automation is one of the key megatrends that drive Industry 4.0 [1]. This applies to the integration and complete automation of control of production processes to the extent that decisions are made by machines, with humans playing a supervisory role [2]. As Industry 4.0 is a challenge and a goal pursued by the world’s leading economies, there is large demand for research geared towards improving existing and developing new methods and models that can assist in automating technological processes [3]. There are many factors that determine the quality of parts. They include, among others, high dimensional accuracy [4] and low surface roughness [5]

Objectives

Methods

Results

Conclusion