Multisensor approaches for chatter detection in milling

Kuljanić, Elso; Sortino, Marco; Totis, Giovanni

doi:10.1016/j.jsv.2007.11.006

Cited by 186 publications

(76 citation statements)

References 17 publications

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“…Kuljanic et al [163] analyse chatter identification methods used in research and investigate an industrial chatter detection system by comparing several sensors: the best results were given by a multi-sensor system using an axial force sensor and two accelerometers. Berger et al [164] apply wavelet decomposition of cutting force signals to discriminate between chatter and non chatter states.…”

Section: Chatter Detectionmentioning

confidence: 99%

Advanced monitoring of machining operations

et al. 2010

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Section: Chatter Detectionmentioning

confidence: 99%

Advanced monitoring of machining operations

et al. 2010

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“…Consequently, the precise identification of the realized tooth passing frequency f tp (or the realized spindle speed Ω) is required for appropriate filtering (see [19]). An initial estimation for the realized spindle speed can be calculated from the first dominant harmonic of the measured signal in frequency domain (see red triangles in Fig.…”

Section: Comb Filtermentioning

confidence: 99%

“…p, t k = kh, τ = ph, h is the discretization step and p is the number of the discretization steps over the principal period τ . Based on the discretized solution of (19), assuming piecewise constant coefficient matrices, the linear mapping which projects the solution to the next time step can be formulated as…”

Section: Appendix: Semi-discretizationmentioning

confidence: 99%

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Operational stability prediction in milling based on impact tests

Kiss

Hajdu

Bachrathy

et al. 2018

Mechanical Systems and Signal Processing

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Chatter detection is usually based on the analysis of measured signals captured during cutting processes. These techniques, however, often give ambiguous results close to the stability boundaries, which is a major limitation in industrial applications. In this paper, an experimental chatter detection method is proposed based on the system's response for perturbations during the machining process, and no system parameter identification is required. The proposed method identifies the dominant characteristic multiplier of the periodic dynamical system that models the milling process. The variation of the modulus of the largest characteristic multiplier can also be monitored, the stability boundary can precisely be extrapolated, while the manufacturing parameters are still kept in the chatter-free region. The method is derived in details, and also verified experimentally in laboratory environment.

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“…Researches on chatter detection have been developed by monitoring certain signals from different types of sensors in the past years, such as cutting forces [15], vibration [16], and sound [17]. The acquired signals are analyzed by different methods so as to find chatter features.…”

Section: Introductionmentioning

confidence: 99%

Three-dimensional stability prediction and chatter analysis in milling of thin-walled plate

Zhao

Wang

2016

Int J Adv Manuf Technol

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Stability lobe diagram can be used for selecting proper milling parameters to perform chatter-free operations and improve productivity during milling of thin-walled plates. This paper studies the machining stability in milling of thin-walled plates and develops a three-dimensional stability lobe diagram of the spindle speed, tool position, and axial depth of cut. The workpiece-holder system is modeled as a 2-degree-of-freedom system considering that the tool system is much more rigid than the thin-walled plate, and dynamic equations of motion described for the workpieceholder system are solved numerically in time domain to compute the dynamic displacements of the thin-walled plate. Statistical variances of the dynamic displacements are then employed as a chatter detection criterion to acquire the stability lobe diagram. The experimentally obtained stability limits correspond well with the predicted stability limits. In addition, influence of feed rate on stability limits is also investigated. By performing frequency analysis of the measured cutting forces to judge if chatter occurs, it is found that feed per tooth has little influence on the stability limits. However, feed per tooth impacts the machined surface quality. The results show that the surface quality drops by increasing feed per tooth.

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Multisensor approaches for chatter detection in milling

Cited by 186 publications

References 17 publications

Advanced monitoring of machining operations

Advanced monitoring of machining operations

Operational stability prediction in milling based on impact tests

Three-dimensional stability prediction and chatter analysis in milling of thin-walled plate

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