Show/Hide Menu
Hide/Show Apps
Logout
Türkçe
Türkçe
Search
Search
Login
Login
OpenMETU
OpenMETU
About
About
Open Science Policy
Open Science Policy
Open Access Guideline
Open Access Guideline
Postgraduate Thesis Guideline
Postgraduate Thesis Guideline
Communities & Collections
Communities & Collections
Help
Help
Frequently Asked Questions
Frequently Asked Questions
Guides
Guides
Thesis submission
Thesis submission
MS without thesis term project submission
MS without thesis term project submission
Publication submission with DOI
Publication submission with DOI
Publication submission
Publication submission
Supporting Information
Supporting Information
General Information
General Information
Copyright, Embargo and License
Copyright, Embargo and License
Contact us
Contact us
Output Only Functional Series Time Dependent AutoRegressive Moving Average (FS-TARMA) Modelling of Tool Acceleration Signals for Wear Estimation
Date
2015-02-05
Author
Aghdam, B. H.
Ciğeroğlu, Ender
Sadeghi, M. H.
Metadata
Show full item record
This work is licensed under a
Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License
.
Item Usage Stats
141
views
0
downloads
Cite This
In this paper, tool vibration signals obtained from a turning process are used for tool wear estimation purposes. During the cutting process, tool acceleration signals are recorded for different levels of wear. Due to non-stationarity of tool/holder system's response, Time dependent time series model of Functional Series Time dependent AutoRegressive Moving Average (FS-TARMA) type is used for modelling the signals and extraction of wear sensitive features that will be exploited in a wear estimation algorithm. Results of the analysis through FS-TARMA, reveals its higher accuracy with respect to stationary type models, since it captures time dependent properties as well, which can be used in an online tool wear estimation algorithm.
Subject Keywords
Tool wear
,
Turning
,
FS-TARMA
,
Time series
URI
https://hdl.handle.net/11511/43317
DOI
https://doi.org/10.1007/978-3-319-15230-1_11
Collections
Department of Mechanical Engineering, Conference / Seminar
Suggestions
OpenMETU
Core
Vibration-based tool wear estimation by using non-stationary Functional Series TARMA (FS-TARMA) models
Aghdam, Behrang Hosseini; Ciğeroğlu, Ender (2017-10-01)
Inverse problem of tool wear estimation using vibration signals is considered via non-stationary functional series time-dependent autoregressive moving average (FS-TARMA) model in this paper. The estimation procedure of FS-TARMA models is presented and through the obtained models, dynamics of the tool-holder system is identified. For finding a relationship between wear and the models, two wear sensitive features are used. First, the models are clustered considering autoregressive (AR) distance as a feature ...
Functional Series TARMA Models for Non stationary Tool Vibration Signals Representation and Wear Etimation
Aghdam, Behrang Hosseini; Ciğeroğlu, Ender (null; 2016-01-25)
This article addresses the problem of tool wear estimation using vibration signals. Time dependent time series models are suitable for extraction of time varying dynamics embedded in the non-stationary signals. A version of non-stationary time series known as Functional Series Time dependent AutoRegressive Moving Average (FS-TARMA) is employed for estimation of tool vibration signals and identification of the dynamics of tool/holder system. The obtained models associated with different levels of tool wear a...
Powder metal development for electrical motor applications
Bayramli, E; Golgelioglu, O; Ertan, Hulusi Bülent (2005-04-10)
In this paper, first the development process of a soft magnetic composite material for use in motor applications is described. Various mixtures are prepared to identify an optimum mix. It is found that highest packing is achieved for a mixing ratio of 45 % of 170 mesh particle size with 55 % 325 mesh particle size. The coating of the particles is obtained by using the "wetting method". The mechanical properties of the samples; such as stress versus strain, Strain% versus composition%, etc. are given, also s...
Analytical modeling of the machine tool spindle dynamics under operational conditions
Özşahin, Orkun; Özgüven, Hasan Nevzat (null; 2012-07-27)
Chatter is an important problem in machining operations, and can be avoided by utilizing stability diagrams which are generated using frequency response functions (FRF) at the tool tip. In general, tool point FRF is obtained experimentally or analytically for the idle state of the machine. However, during high speed cutting operations, gyroscopic effects and changes of contact stiffness and damping at the interfaces as well as the changes in the bearing properties may lead to variations in the tool point FR...
Functional Series TARMA Models for Non-stationary Tool Vibration Signals Representation and Wear Estimation
Aghdam, Behrang Hosseini; Ciğeroğlu, Ender (2016-01-28)
This article addresses the problem of tool wear estimation using vibration signals. Time dependent time series models are suitable for extraction of time varying dynamics embedded in the non-stationary signals. A version of non-stationary time series known as Functional Series Time dependent AutoRegressive Moving Average (FS-TARMA) is employed for estimation of tool vibration signals and identification of the dynamics of tool/holder system. The obtained models associated with different levels of tool wear a...
Citation Formats
IEEE
ACM
APA
CHICAGO
MLA
BibTeX
B. H. Aghdam, E. Ciğeroğlu, and M. H. Sadeghi, “Output Only Functional Series Time Dependent AutoRegressive Moving Average (FS-TARMA) Modelling of Tool Acceleration Signals for Wear Estimation,” 2015, Accessed: 00, 2020. [Online]. Available: https://hdl.handle.net/11511/43317.