Why is it hard to identify the onset of chatter? A stochastic resonance perspective

Bachrathy, Dániel; Sykora, Henrik T; Hajdu, Dávid; Béri, Bence; Stépàn, Gábor

doi:10.1016/j.cirp.2021.04.080

Cited by 5 publications

(4 citation statements)

References 15 publications

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“…That is, the stability limit is detected by interval halving, which leads to a significant decrease in the number of measurement points. This method is applicable even in the presence of measurement noise because it does not rely on derivatives [19].…”

Section: Discussionmentioning

confidence: 99%

“…The emulated turning process is said to be unstable when the amplitude of the arising oscillations, that is, the subtraction of the workpiece response signal and the run-out of the workpiece, reaches the level of 3 μm (see the upper panel of Fig. 2) at the chatter frequency, which is detected to be around the dominant natural frequency f n = 3.05 kHz of the setup (see [11,19]). This way, the effective experimental identification of the stability boundary of the cutting process is carried out according to two different techniques: the brute force method and the bisection method detailed in Section 4.…”

Section: Experimental Chatter Testsmentioning

confidence: 99%

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Multi-Dimensional Bisection Method in HIL Environment: Stability and Chatter Prediction in Turning

Béri

Bachrathy

Stépàn

2023

Period. Polytech. Mech. Eng.

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In turning operations, the harmful small-amplitude but high-frequency chatter vibrations are identified in hardware-in-the-loop (HIL) experimental environment by means of the application of a multi-dimensional bisection method. The dummy workpiece clamped to the real main spindle is excited by contactless electromagnetic actuators and the response of the workpiece is detected by laser-based sensors. According to the present and the stored previous positions of the rotating workpiece, the desired cutting force characteristic along with the surface regeneration effect can be emulated by means of a high-performance real target computer. While the conventional experimental results in the HIL environment identify the stability limits of the cutting operation accurately only in a high-resolution grid of the technological parameters, the embedded bisection method reduces significantly both the size of the required grid and the time duration of the measurement by path following the boundaries of the linear loss of stability. Based on this technique, the experimental stability boundary of the emulated turning process is presented in a wide range of spindle speeds.

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Section: Discussionmentioning

confidence: 99%

Section: Experimental Chatter Testsmentioning

confidence: 99%

Multi-Dimensional Bisection Method in HIL Environment: Stability and Chatter Prediction in Turning

Béri

Bachrathy

Stépàn

2023

Period. Polytech. Mech. Eng.

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“…However, in real turning measurements chatter detection is challenging in machining [9]. On one hand, when the process is unstable the exponentially increasing amplitude saturates at some point due to nonlinear effects (e.g.…”

Section: Introductionmentioning

confidence: 99%

“…There are very sophisticated FEM-based models to describe these behaviors [13,14], that include chip fragmentation and material inhomogeneities but these are complicated, computationally very demanding, and hard to validate. Another way of explaining the increasing variance is using stochastic cutting force models [15], because it properly predicts stochastic resonance characteristics, unlike deterministic models [9].…”

Section: Introductionmentioning

confidence: 99%

Efficient approximation of stochastic turning process based on power spectral density

Fodor,

Bachrathy

2024

Preprint

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In this study, we utilize stochastic cutting force to enhance the existing 1-degree-of-freedom turning model. We adopt a stochastic model to address the stochastic resonance phenomenon occurring near stability boundaries. Additionally, we introduce a simplified stochastic model with additive noise only. Our investigations reveal that, with the recommended noise intensity of 0.1% to 1%, there is no significant difference in the stability charts and mean square characteristics between the two models. As a result, we can bypass time-consuming numerical methods, as the simplified model offers an analytical approach to compute variance based on power spectral density (PSD). By combining efficient techniques such as D-separation to determine stability boundaries and the PSD-based variance calculation, we construct a heatmap that clearly outlines dangerous stochastic resonance regions within the stable domain.

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Efficient approximation of stochastic turning process based on power spectral density

Fodor,

Bachrathy

2024

Int J Adv Manuf Technol

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Turning is one of the most important material removal processes in manufacturing, where the proper understanding of the process is crucial for the quality of the final product. In this study, the stochastic cutting force is utilized to enhance the existing 1-degree-of-freedom turning model. A stochastic model is adopted to address the stochastic resonance phenomenon occurring near stability boundaries. Additionally, a novel simplified stochastic model is introduced with additive noise only. The comparison of the two models reveals that, with the recommended noise intensity of 0.1 to 1%, there is no significant difference in the stability charts and mean square characteristics between the two models. As a result, the time-consuming numerical methods can be bypassed, as the simplified model offers a computationally more efficient analytical approach to compute variance based on power spectral density (PSD). By combining techniques such as D-separation to determine stability boundaries and the PSD-based variance calculation, it only takes a minute instead of hours to construct a heatmap using the introduced simplified stochastic turning model that clearly outlines dangerous stochastic resonance regions inside the stable domain.

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Why is it hard to identify the onset of chatter? A stochastic resonance perspective

Cited by 5 publications

References 15 publications

Multi-Dimensional Bisection Method in HIL Environment: Stability and Chatter Prediction in Turning

Multi-Dimensional Bisection Method in HIL Environment: Stability and Chatter Prediction in Turning

Efficient approximation of stochastic turning process based on power spectral density

Efficient approximation of stochastic turning process based on power spectral density

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