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Smart Machining Systems pp 235–266Cite as

Tool Condition Monitoring with Sparse Decomposition

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Part of the book series: Springer Series in Advanced Manufacturing ((SSAM))

Abstract

In modern CNC machining, an effective tool condition monitoring (TCM) system can improve productivity, ensure workpiece quality and enhance the manufacturing intelligence (Dornfeld and Lee in Precision manufacturing. Springer, 2007; Teti et al., CIRP Annals-Manuf Tech 59:717–739, 2010). Due to its importance, tool condition monitoring (TCM) has been extensively studied (Teti et al., in CIRP Annals-Manuf Tech 59:717–739, 2010). The earlier study on TCM is mainly carried out with time series analysis, such as (Altintas in Int J Mach Tool Manuf 28:157–172, 1987) and (Kumar et al. in Int J Prod Res 35:739–751, 1997). With these methods, a threshold was set for binary state detection. However, the threshold value varies with cutting conditions and is difficult to determine.

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Authors and Affiliations

  1. Precision Manufacturing Laboratory, Institute of Advanced Manufacturing Technology, Chinese Academy of Sciences, Changzhou, Jiangsu, China

    Kunpeng Zhu

  2. Institute of Precision Manufacturing, Wuhan University of Science and Technology, Wuhan, Hubei, China

    Kunpeng Zhu

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  1. Kunpeng Zhu
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Correspondence to Kunpeng Zhu .

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Zhu, K. (2022). Tool Condition Monitoring with Sparse Decomposition. In: Smart Machining Systems. Springer Series in Advanced Manufacturing. Springer, Cham. https://doi.org/10.1007/978-3-030-87878-8_7

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  • DOI: https://doi.org/10.1007/978-3-030-87878-8_7

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  • Print ISBN: 978-3-030-87877-1

  • Online ISBN: 978-3-030-87878-8

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