Morphological Filtering Algorithm for Estimation of Tool Wear in CNC Milling Machining

Abstract:

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Estimation of tool condition has very important meaning to improve the product quality, continuous machining ability and reliability of the manufacturing system. Based on mathematical morphology, a systematic approach is developed to implement online estimation of tool wear in this paper. As the nonlinear filter, morphological filter is selected to reduce the higher frequency noises before feature values extraction. The feature vector consists of original characteristics of vibration signal and cutting force signal. Then, they are input into SVM for training and testing. Experiments show that this method can achieve tool wear estimation effectively.

Info:

Periodical:

Materials Science Forum (Volumes 697-698)

Edited by:

Tian Huang, Dawei Zhang, Bin Lin, Anping Xu, Yanling Tian and Weiguo Gao

Pages:

566-569

DOI:

10.4028/www.scientific.net/MSF.697-698.566

Citation:

Q. Ning and T. Y. Wang, "Morphological Filtering Algorithm for Estimation of Tool Wear in CNC Milling Machining", Materials Science Forum, Vols. 697-698, pp. 566-569, 2012

Online since:

September 2011

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Price:

$35.00

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