Expedient identification of the dynamics of ball-screw drives using online-validation

Ashraf Hatwesh; Simon Fletcher; Andrew Longstaff; Wencheng Pan; Fengshou Gu

doi:10.23919/IConAC.2017.8082054

Expedient identification of the dynamics of ball-screw drives using online-validation

Ashraf Hatwesh, Simon Fletcher, Andrew Longstaff, Wencheng Pan, Fengshou Gu

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

2 Citations (Scopus)

Abstract

Knowledge of machine tool drive dynamics is imperative to achieve optimal, robust performance with precision and productivity. Modelling ball-screw drives is vital in order to have a feasible insight into the structural vibration modes of the mechanical assembly, which typically limits the bandwidth of developed controllers. In this paper, an output-only modal identification, Operational Modal Analysis (OMA), is used to validate a ball-screw feed drive model while running without cutting. The experimental results indicate that the identified parameters on the running state are different from those of static state and mathematical modelling. Furthermore, it is possible to validate and calibrate dynamic models using OMA by measuring the table structure responses without knowing the excitation input.

Original language	English
Title of host publication	2017 23rd International Conference on Automation and Computing (ICAC)
Publisher	Institute of Electrical and Electronics Engineers Inc.
Number of pages	6
ISBN (Electronic)	9780701702601
DOIs	https://doi.org/10.23919/IConAC.2017.8082054
Publication status	Published - 26 Oct 2017

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

Access to Document

10.23919/IConAC.2017.8082054Licence: Unspecified

Wencheng Pan
- W.Panhud.acuk
- Department of Engineering - Research Fellow
- School of Computing and Engineering
- Centre for Precision Technologies - Member
Person: Academic

Cite this

@inproceedings{c2d6df1999564e91bb3a7a94652cd9df,

title = "Expedient identification of the dynamics of ball-screw drives using online-validation",

abstract = "Knowledge of machine tool drive dynamics is imperative to achieve optimal, robust performance with precision and productivity. Modelling ball-screw drives is vital in order to have a feasible insight into the structural vibration modes of the mechanical assembly, which typically limits the bandwidth of developed controllers. In this paper, an output-only modal identification, Operational Modal Analysis (OMA), is used to validate a ball-screw feed drive model while running without cutting. The experimental results indicate that the identified parameters on the running state are different from those of static state and mathematical modelling. Furthermore, it is possible to validate and calibrate dynamic models using OMA by measuring the table structure responses without knowing the excitation input.",

keywords = "damping, dynamics, feeds, machine tools, mathematical model, shafts, vibrations",

author = "Ashraf Hatwesh and Simon Fletcher and Andrew Longstaff and Wencheng Pan and Fengshou Gu",

year = "2017",

month = oct,

day = "26",

doi = "10.23919/IConAC.2017.8082054",

language = "English",

booktitle = "2017 23rd International Conference on Automation and Computing (ICAC)",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

address = "United States",

}

Expedient identification of the dynamics of ball-screw drives using online-validation. / Hatwesh, Ashraf; Fletcher, Simon ; Longstaff, Andrew et al.

2017 23rd International Conference on Automation and Computing (ICAC). Institute of Electrical and Electronics Engineers Inc., 2017.

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - Expedient identification of the dynamics of ball-screw drives using online-validation

AU - Hatwesh, Ashraf

AU - Fletcher, Simon

AU - Longstaff, Andrew

AU - Pan, Wencheng

AU - Gu, Fengshou

PY - 2017/10/26

Y1 - 2017/10/26

N2 - Knowledge of machine tool drive dynamics is imperative to achieve optimal, robust performance with precision and productivity. Modelling ball-screw drives is vital in order to have a feasible insight into the structural vibration modes of the mechanical assembly, which typically limits the bandwidth of developed controllers. In this paper, an output-only modal identification, Operational Modal Analysis (OMA), is used to validate a ball-screw feed drive model while running without cutting. The experimental results indicate that the identified parameters on the running state are different from those of static state and mathematical modelling. Furthermore, it is possible to validate and calibrate dynamic models using OMA by measuring the table structure responses without knowing the excitation input.

AB - Knowledge of machine tool drive dynamics is imperative to achieve optimal, robust performance with precision and productivity. Modelling ball-screw drives is vital in order to have a feasible insight into the structural vibration modes of the mechanical assembly, which typically limits the bandwidth of developed controllers. In this paper, an output-only modal identification, Operational Modal Analysis (OMA), is used to validate a ball-screw feed drive model while running without cutting. The experimental results indicate that the identified parameters on the running state are different from those of static state and mathematical modelling. Furthermore, it is possible to validate and calibrate dynamic models using OMA by measuring the table structure responses without knowing the excitation input.

KW - damping

KW - dynamics

KW - feeds

KW - machine tools

KW - mathematical model

KW - shafts

KW - vibrations

U2 - 10.23919/IConAC.2017.8082054

DO - 10.23919/IConAC.2017.8082054

M3 - Conference contribution

BT - 2017 23rd International Conference on Automation and Computing (ICAC)

PB - Institute of Electrical and Electronics Engineers Inc.

ER -

Expedient identification of the dynamics of ball-screw drives using online-validation

Abstract

UN SDGs

Access to Document

Fingerprint

Profiles

Wencheng Pan

Cite this