Fractal estimation of flank wear in turning Academic Article

abstract

• A novel fractal estimation methodology, that usesfor the first time in metal cutting literaturefractal properties of machining dynamics for online estimation of cutting tool flank wear, is presented. The fractal dimensions of the attractor of machining dynamics are extracted from a collection of sensor signals using a suite of signal processing methods comprising wavelet representation and signal separation, and are related to the instantaneous flank wear using a recurrent neural network. The performance of the resulting estimator, evaluated using actual experimental data, establishes our methodology to be viable for online flank wear estimation. This methodology is adequately generic for sensor-based prediction of gradual damage in mechanical systems, specifically manufacturing processes. [S0022-0434(00)02401-1]

authors

• Bukkapatnam, Satish

published proceedings

• JOURNAL OF DYNAMIC SYSTEMS MEASUREMENT AND CONTROL-TRANSACTIONS OF THE ASME

author list (cited authors)

• Bukkapatnam, S., Kumara, S., & Lakhtakia, A.

citation count

• 54

complete list of authors

• Bukkapatnam, STS||Kumara, SRT||Lakhtakia, A

publication date

• March 2000

publisher

• ASME International  Publisher

published in

• Journal of Dynamic Systems Measurement and Control: Transactions of the ASME  Journal

keywords

• 40 Engineering
• 4014 Manufacturing Engineering

Digital Object Identifier (DOI)

• 10.1115/1.482446

start page

• 89

end page

• 94

volume

• 122

issue

• 1

URL

• http://dx.doi.org/10.1115/1.482446