Experimental and fuzzy modelling analysis on dynamic cutting force in micro milling
Ren Qun , Marek Bałaziński , Krzysztof Jemielniak , Luc Baron , Sofiane Achiche
AbstractPrediction of cutting forces is very important for the design of cutting tools and for process planning. This paper presents a fuzzy modelling method of cutting forces based on subtractive clustering. The subtractive clustering combined with the least-square algorithm identifies the fuzzy prediction model directly from the information obtained from the sensors. In the micro-milling experimental case study, four sets of cutting force data are used to generate the learning systems. The systems are tested against each other to choose the best model. The obtained results prove that the proposed solution has the capability to model the cutting force in spite of uncertainties in the micromilling process.
|Journal series||Soft Computing, ISSN 1432-7643|
|Publication size in sheets||0.5|
|Keywords in English||fuzzy logic, cutting force, subtractive clustering, micromilling, fuzzy modelling|
|ASJC Classification||; ;|
|Score|| = 25.0, 31-01-2020, ArticleFromJournal|
= 25.0, 31-01-2020, ArticleFromJournal
|Publication indicators||= 19; : 2013 = 1.45; : 2013 = 1.304 (2) - 2013=1.492 (5)|
|Citation count*||36 (2020-09-02)|
* presented citation count is obtained through Internet information analysis and it is close to the number calculated by the Publish or Perish system.