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Tool Condition Monitoring with Sparse Decomposition

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Part of the Springer Series in Advanced Manufacturing book series (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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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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