Hidden Markov Model-Based Tool Wear Monitoring in Turning  

Oleh:

Mehrabi, Mostafa G. ; Litao, Wang ; Kannatey-Asibu, Elijah, [Jr.]

Jenis: Article from Journal - ilmiah internasional
Dalam koleksi: Journal of Manufacturing Science and Engineering vol. 124 no. 3 (Aug. 2002), page 651-658.
Topik: Tool Wear; markov model - based; tool wear; monitoring; turning

Ketersediaan

Perpustakaan Pusat (Semanggi) Nomor Panggil: JJ93.3 Non-tandon: 1 (dapat dipinjam: 0) Tandon: tidak ada

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Isi artikel

This paper presents a new modeling framework for tool wear monitoring in machining processes using hidden Markov models (HMM s). Feature vectors are extracted from vibration signals measured during turning. A codebook is designed and used for vector quantization to convert the feature vectors into a symbol sequence for the hidden Markov model. A series of experiments are conducted to evaluate the effectiveness of the approach for different lengths of training data and observation sequence. Experimental results show that successful tool state detection rates as high as 97 % can be achieved by using this approach.

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