• Journal of the Korean Society for Precision Engineering
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• v.12 no.10
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• pp.50-56
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• 1995

Chatter Vibration is an unwanted phenomenon in metal cutting and it always affects surface finish, tool life, machine life and the productivity of machining process. The real-time detection of the chatter vibration is is necessarily required to automation system. In this study, we constructed the multi-sensing system using Tool Dynamometer, Accelermeter and AE sensor. Especially, Acoustic Emission(AE) generated during turning was investigated the possibility for real-time detection of chatter vibration. Turning experiments were performed using carbide insert tip under realistic cutting conditions and tapered workpiece of SM45C. Consquently, the real-time detection using multi-sensing system can be used for Inprocess monitoring of chatter vibration.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2014.10a
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• pp.745-750
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• 2014

The chatter vibration in the machining process plays bad role in machining quality such as high roughness as well as tool life and machine failure. And the grinding process under this risk in the fully automated factory is exposed to the unexpected mass machining quality problem. Studying the vibration signal of the hub bearing grinding process, the reason of chatter vibration was explained with the specific machining pattern of chatter. And this study suggests the chatter detecting method in the production line, which is monitoring the peak acceleration level around the natural frequencies of the specimen, and calculating kurtosis value by assuming the chatter is related to the resonance of the specimen. The suggested method was applied to the vehicle hub bearing grinding process and proved good to detecting the chatter induced machining quality problem.

• Journal of the Korean Society for Precision Engineering
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• v.8 no.3
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• pp.73-81
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• 1991

There have been many studies on chatter vibration in machining but there seems to be no regulations to decide the commencing point of chatter objectively. The development of an objective method which can estimate and detect chatter commencement is very much in need for automatic manufacturing systems, dynamic performance tests for machine tools, so on. In this study, therefore, the estimation and the in-process detection of chatter have been experi- mentally investigated for the turning process. As a result, the commencing point of chatter can be decided from the behavior of the maximum amplitude of the dynamic component of cutting force, where the maximum amplitude is suddenly increasing with the chatter commencement. Then the commencing point of chatter can be estimated practically by this method before the occurrence of excessive vibration. Also, it is possible to detect the occurence of chatter vibration through the in-process measurement, by monitoring the maximum amplitude of the dynamic component of cutting force.

• Journal of the Korean Society for Precision Engineering
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• v.9 no.3
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• pp.117-121
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• 1992

There have been many studies on chatter vibration in machining but there seems to be no regulations to decide the commencing point of chatter objectively. The development of an objective method which can estimate and detect chatter commencement is very much in need for automatic manufacturing systems, dynamic performance tests for machine tools, and so on. In this study, an approach for in-process monitoring and for deciding commencing point of the chatter vibration using the frequency band-energy method was proposed. From this method, in-process monitoring system for detection the chatter vibration was developed, and investigated its practical possibility. As a result, it is shown by experiments that the chatter vibtation can be detected accurately. Since the changing pattern of the signal energy in certain frequency band during chattering is seldom affected by the variation of cutting conditions, if adequate pre-measures are taken, this method can be widely used in most machining processes.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.23 no.3
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• pp.273-278
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• 2014

This study presents a chatter vibration avoidance program for the milling process. Chatter vibration has a negative effect on workpieces and spindle-tools. When chatter vibration occurs, the cutting tool is loaded dynamically, a chatter pattern is generated on the workpiece, and the tool life is reduced. The developed program is composed of various modules such as an FFT analyzer, an impact test analyzer, a chatter vibration indicator, and a spindle speed recommender. The proposed program is verified using an AISI D2 cutting experiment in milling process. The effect of chatter vibration on the machining condition can be simulated by the suggested method, and successfully exploited to avoid chatter vibration.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.9 no.3
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• pp.150-159
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• 2000

In-process diagnosis of the cutting state is essential for the automation of manufacturing systems. Especially when the cutting process becomes unstable it induces self-exited vibrations a frequent case of poor tool life rough surface finish damage to the workpiece and the machine tool itself and excessive down time. To ensure that the cutting process main-tains stable it is highly desirable to have the capability of real-time. To ensure that the cutting process main-tains stable it is highly desirable to have the capability of real-time monitoring and controlling chatter. This paper describes the detection method of chatter vibration using cutting force in turning process. In order to detect a chatter vibra-tion the dynamic fluctuation of radial force is analyzed since this components is sensitive to the chatter. The envelope sig-nal of radial force has been calculated by the use of FIR Hilbert transformer and it was useful to classify the chatter signal from the dynamically unstable circumstances. It was found that the mode and the mode width were closely correlated with the chatter amplitude was well. Finally back propagation(BP) neural network have been applied to the pattern recognition for the classification of chatter signal in various cutting conditions. The validity of this systed was confirmed by the experiments under the various cutting conditions.

• Journal of the Korean Society for Precision Engineering
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• v.12 no.12
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• pp.100-108
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• 1995

The In-process minitoring of the chatter vibration is necessarily required to an automatic manufacturing system. In this study, we constructed a multi-sensing system using tool dynamoneter, accelerometer and AE(Acoustic Emission) sensor for a more credible detection of chatter vibration. And a new approach using a multiple neural network to extract the features of multi-sensor for the recognition chatter vibration is proposed. With the Back-propagation training process, the neural network memorize and classify the features of multi-sensor signals. As a result, it is shown by multiple neural network that the chatter vibration can be monitored accurately, and it can be widely used in practical unmanned system.

• Journal of the Korean Society for Precision Engineering
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• v.12 no.10
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• pp.149-156
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• 1995

This paper presents a method of detecting chatter vibration in end-mill process. The detecting system consists of an adaptive signal processing scheme which uses an autore- gressive time-series model and a neural network is proposed and is verified its effectiveness by using acceleration and cutting force signals recorded during slotting in end-mill operations. Expeerimental results indicate that the proposed system provides excellent detection when chatter is occured within the ranges of cutting conditions considered in this study and an effectiveness of the integration of signals is confirmed.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2010.11a
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• pp.455-456
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• 2010

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1993.10a
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• pp.70-75
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• 1993

Chatter vibration is an unwanted phenomenon in metal cutting and it always affects surface finish, tool life machine life and the productivity of machining process. The In-process monitoring & control of chatter vibration is necessarily required to automation system. In this study, we constructed the multi-sensing system using Tool Dynamometer,Accelerometer and AE(Acoustic Emission) sensor for the credible detection of chatter vibration. And a new approach using a neural network to process the features of multi-sensor for the recognition of chatter vibration in turning operation is proposed. With the back propagation training process, the neural network memorize and classify the feature difference of multi-sensor signals.