Tool Deflection Control by a Sensory Spindle Slide for Milling Machine Tools

Denkena, Berend; Dahlmann, Dominik; Boujnah, Haythem

doi:10.1016/j.procir.2016.06.059

Cited by 27 publications

(11 citation statements)

References 6 publications

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“…When the frequency is sufficiently small, the response of the system will be a simple harmonic motion, that is, the phase plane will be an ellipse. For large frequency, additional harmonics beyond the fundamental are detected and the phase plane will be distorted from a simple ellipse and the nonlinearities in equation (15) enormously amplify the errors in the initial conditions of the system.…”

Section: Analysis Of Dynamic Model Vibration Resultsmentioning

confidence: 99%

“…Results showed that cutting forces obtained by the proposed method are close to the reference values. B Denkena et al 15 presented an approach for a monitoring and control system for the tool deflection for milling machine tools. The results showed that the deflection control increases significantly not only the milling accuracy but also the machining time.…”

Section: Introductionmentioning

confidence: 99%

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Stability analysis for a single-point cutting tool deflection in turning operation

Gasagara

Jin

Uwimbabazi

2019

Advances in Mechanical Engineering

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In this article, a new model of regenerative vibrations due to the deflection of the cutting tool in turning is proposed. The previous study reported chatter as a result of cutting a wavy surface of the previous cut. The proposed model takes into account cutting forces as the main factor of tool deflection. A cantilever beam model is used to establish a numerical model of the tool deflection. Three-dimensional finite element method is used to estimate the tool permissible deflection under the action of the cutting load. To analyze the system dynamic behavior, 1-degree-of-freedom model is used. MATLAB is used to compute the system time series from the initial value using fourth-order Runge-Kutta numerical integration. A straight hard turning with minimal fluid application experiment is used to obtain cutting forces under stable and chatter conditions. A single-point cutting tool made from high-speed steel is used for cutting. Experiment results showed that for the cutting parameters above 0.1mm/rev feed and 1:5mm depth of cut, the system develops fluctuations and higher chatter vibration frequency. Dynamic model vibration results showed that the cutting tool deflection induces chatter vibrations which transit from periodic, quasi-periodic, and chaotic type.

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Section: Analysis Of Dynamic Model Vibration Resultsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Stability analysis for a single-point cutting tool deflection in turning operation

Gasagara

Jin

Uwimbabazi

2019

Advances in Mechanical Engineering

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“…The Leibniz University Hannover has also written a number of papers on similar topics. A paper recently published presents an approach for a monitoring and control system for tool deflection [9]. FEA methods were employed to determine the optimum positions of strain gauges on the sensory spindle slide with a control system implemented to maintain and measure tool deflection.…”

Section: State Of the Artmentioning

confidence: 99%

In-Process Control With a Sensory Tool Holder to Avoid Chatter

Bleicher

Schörghofer

Habersohn

2018

Journal of Machine Engineering

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Hydro-, steam- and gas- turbines, aircraft components or moulds are milled parts with complex geometries and high requirements for surface quality. The production of such industry components often necessitates the use of long and slender tools. However, instable machining situations together with work pieces with thin wall thickness can lead to dynamic instabilities in the milling processes. Resulting chatter vibrations cause chatter marks on the work piece surface and have influence on the tool lifetime. In order to detect and avoid the occurrence of process instabilities or process failures in an early stage, the Institute for Production Engineering and Laser Technology (IFT) developed an active control system to allow an in-process adaption of machining parameters. This system consists of a sensory tool holder with an integrated low cost acceleration sensor and wireless data transmission under real time conditions. A condition monitoring system using a signal-processing algorithm, which analyses the received acceleration values, is coupled to the NC- control system of the machine tool to apply new set points for feed rate and rotational speed depending on defined optimisation strategies. By the implementation of this system process instabilities can be avoided.

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“…Different sensors have been utilized to overcome these limitations. For example, Denkena et al installed strain gauges within small notches on the axis slide, to further increase sensitivity [5]. Compared to a dynamometer the maximal deviation of this approach is 10%.…”

Section: Introductionmentioning

confidence: 99%

Reconstruction of Process Forces in a Five-Axis Milling Center with a LSTM Neural Network in Comparison to a Model-Based Approach

Denkena

Bergmann

Stoppel

2020

JMMP

Self Cite

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Based on the drive signals of a milling center, process forces can be reconstructed. Therefore, a novel approach is presented to reconstruct the process forces with a long short-term memory neural network (LSTM) using drive signals as an input. The LSTM is evaluated and compared to a model-based approach. The latter compensates nonlinearities and disturbances such as friction and inertia. For training of the LSTM, multiple milling processes are considered to enhance the generalizability. Training data is generated by recording drive signals and process forces measured by a dynamometer. The LSTM is then evaluated using a test set, which comprises new process parameters. It is shown that the LSTM has a lower root mean square error (RMSE) in comparison to the model-based approach. Especially, when changing the feed motion direction during milling, the neural network clearly outperforms the model-based approach. Nevertheless, there are processes, where the LSTM induced oscillations, which do not correspond to the measured forces.

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Tool Deflection Control by a Sensory Spindle Slide for Milling Machine Tools

Cited by 27 publications

References 6 publications

Stability analysis for a single-point cutting tool deflection in turning operation

Stability analysis for a single-point cutting tool deflection in turning operation

In-Process Control With a Sensory Tool Holder to Avoid Chatter

Reconstruction of Process Forces in a Five-Axis Milling Center with a LSTM Neural Network in Comparison to a Model-Based Approach

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