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.

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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

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Citation Formats

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.