Chatter reliability prediction of turning process system with uncertainties

Liu, Yu; Li, Tian-xiang; Liu, Kuo; Zhang, Yimin

doi:10.1016/j.ymssp.2015.06.030

Cited by 50 publications

(24 citation statements)

References 18 publications

(19 reference statements)

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“…Aspects such as uncertainty or the relative randomness of process parameters was studied in some works. For instance, Liu et al [97] calculated the reliability probability of chatter in a turning system. They used the first order second moment method (FOSM) and fourth moment method and compared with Monte Carlo simulation presenting a modified version of traditional stability lobes.…”

Section: On-line Chatter Classification Detection and Monitoringmentioning

confidence: 99%

Prediction Methods and Experimental Techniques for Chatter Avoidance in Turning Systems: A Review

et al. 2019

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The general trend towards lightweight components and stronger but difficult to machine materials leads to a higher probability of vibrations in machining systems. Amongst them, chatter vibrations are an old enemy for machinists with the most dramatic cases resulting in machine-tool failure, accelerated tool wear and tool breakage or part rejection due to unacceptable surface finish. To avoid vibrations, process designers tend to command conservative parameters limiting productivity. Among the different machining processes, turning is responsible of a great amount of the chip volume removed worldwide. This paper reports some of the main efforts from the scientific literature to predict stability and to avoid chatter with special emphasis on turning systems. There are different techniques and approaches to reduce and to avoid chatter effects. The objective of the paper is to summarize the current state of research in this hot topic, particularly (1) the mechanistic, analytical, and numerical methods for stability prediction in turning; (2) the available techniques for chatter detection and control; (3) the main active and passive techniques.

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Section: On-line Chatter Classification Detection and Monitoringmentioning

confidence: 99%

Prediction Methods and Experimental Techniques for Chatter Avoidance in Turning Systems: A Review

et al. 2019

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“…The theory was validated with experimental robotic machining trials. Liu et al [11] investigated the probability of stability for turning. The authors defined and represented a reliability lobe diagram to identify stable and unstable zones, rather than the traditional stability lobe diagram (SLD).…”

Section: Introductionmentioning

confidence: 99%

Machining Chatter Prediction Using a Data Learning Model

Cherukuri

Perez‐Bernabeu

Sellès

et al. 2019

JMMP

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Machining processes, including turning, are a critical capability for discrete part production. One limitation to high material removal rates and reduced cost in these processes is chatter, or unstable spindle speed-chip width combinations that exhibit a self-excited vibration. In this paper, an artificial neural network (ANN)—a data learning model—is applied to model turning stability. The novel approach is to use a physics-based process model—the analytical stability limit—to generate a (synthetic) data set that trains the ANN. This enables the process physics to be combined with data learning in a hybrid approach. As anticipated, it is observed that the number and distribution of training points influences the ability of the ANN model to capture the smaller, more closely spaced lobes that occur at lower spindle speeds. Overall, the ANN is successful (>90% accuracy) at predicting the stability behavior after appropriate training.

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“…However, according to [5], the structural parameters attained by this method are just an estimation of the real coefficients and therefore, always an uncertainty should be considered in the derived model. Otherwise, it is possible that a set of depth of cut and spindle speed located in the stale zone leads to an unusable process because of not considering the uncertainty [6]. Therefore, for a certain turning operation especially when the surface finish has a great importance, an online system identification model along with a reliable control approach is vital for coping with system nonlinearities and other uncertainties.…”

Section: Introductionmentioning

confidence: 99%

System Identification and Model Predictive Control of the Chatter Phenomenon in Turning Process

Karimipour¹,

Emami²

2019

Adv. Sci. Technol. Res. J.

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Chatter is a series of unwanted and extreme vibrations which frequently happens during different machining processes and impose variety of adverse effects on the machine-tool and surface finish. Chatter has two main types namely forced-chatter and self-existed chatter. The forced-chatter has an external cause; however, self-exited chatter has no external stimuli, rather it is created due to the phase difference between the previous and current waves on the surface of the workpiece. Due to the self-generative nature of this type of chatter, its recognition and prevention is much more difficult. For preventing self-exited chatter its model should be available first. The chatter is usually simulated as a one degree of freedom mass-spring-damper model with unknown parameters that they should be determined somehow. In this paper, the parameters of the tool equation of motion i.e. mass, damping, and stiffness coefficients of the system are predicted through a wavelet-based method online, and then based on the achieved parameters, the system is controlled via Model Predictive Control (MPC) approach. For the validation, the algorithm is applied to 25 different experimental tests in which the acceleration of the tool and cutting force are measured via an accelerometer and a dynamometer. By investigation of the SLDs generated by the predicted parameters, the presented system identification method is validated. Also, it is shown that the chatter vibration is completely restrained by means of MPC. For investigation of the MPC performance, MPC algorithm is compared with PID controller and simulations has indicated a much stronger performance of MPC rather than PID controller in terms of vibration attenuation and control effort.

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Chatter reliability prediction of turning process system with uncertainties

Cited by 50 publications

References 18 publications

Prediction Methods and Experimental Techniques for Chatter Avoidance in Turning Systems: A Review

Prediction Methods and Experimental Techniques for Chatter Avoidance in Turning Systems: A Review

Machining Chatter Prediction Using a Data Learning Model

System Identification and Model Predictive Control of the Chatter Phenomenon in Turning Process

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