• 한국공작기계학회:학술대회논문집
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• 한국공작기계학회 1999년도 추계학술대회 논문집 - 한국공작기계학회
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• pp.507-512
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• 1999

In modern engineering practice, the grinding process is one of the most important and widely used operations for the precision finishing of components. In this paper, machining characteristics of external plunge grinding were investigated by using spindle motor current signal through hall sensor. Grinding experiments were performed in terms of various grinding conditions such as wheel speed, workpiece speed, infeed rate and spark-out time with conventional vitrified bonded WA wheel. The relationship between spindle motor current signal and metal removal rate in terms of infeed rate was induced the by analyzing spindle motor current signal.

• 한국정밀공학회지
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• 제17권6호
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• pp.76-82
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• 2000

This paper describes the machining characteristics of cylindrical plunge grinding. The study investigates the process using the current signals of a spindle motor through a hall sensor. Grinding experiments were conducted under various conditions such as wheel speeds, workpiece speeds and infeed rates with a conventional vitrified bonded wheel. Analyzing the current signal of the spindle motor, a relationship between current signals and the metal removal rate in terms of the in(red rate is induced. It was also shown that a hall sensor has similar capabilities in evaluation of grinding behavior compared to the AE signals, which are useful far monitoring the grinding process.

• 센서학회지
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• 제31권1호
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• pp.57-63
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• 2022

This study describes a system that monitors the tool and cutting state of automatic beveling operation in real time. As a signal for cutting state monitoring, a motor current detected from the spindle drive system of the automatic beveling machine is used to monitor abnormal state. Because automatic beveling is processed using a face milling cutter, the cutting force mechanism is the same as the milling process. The predicted cutting torque is obtained using a cutting force model based on specific cutting resistance. Then, the predicted cutting torque is converted into the spindle motor current value, and cutting state stability is diagnosed by comparing it with the motor current value detected during beveling operation. The experimental results show that the spindle motor current can detect abnormal cutting state such as overload and tool wear during beveling operation, and can diagnose the cutting stability using the proposed equip-current line diagram.

• 전력전자학회논문지
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• 제10권2호
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• pp.186-193
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• 2005

본 논문에서는 산업체 CNC(Computer Numerical Control) 분야에서 사용되는 빌트인 타입 스핀들 모터를 구동하기 위한 기법을 제시하였다. 저속 영역에서 유리한 전류 모델과 고속 영역에서 유리한 전압 모델을 혼합해서 사용하는 고피나스 모델 자속추정기는 회전자 자속추정을 위하여 이용하였다. 그리고 약계자 제어를 사용하여 스핀들 모터를 고속 운전하였다. 시뮬레이션과 실험을 통해 약계자 영역에서의 스핀들 모터 고속운전을 확인하였다.

• 한국기계가공학회지
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• 제14권6호
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• pp.1-6
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• 2015

Tool condition monitoring plays one of the most important roles in the improvement of both machining quality and productivity. In this regard, various process signals and monitoring methods have been developed. However, most of the existing studies used cutting force or acoustic emission signals, which posed risks of interference with the machining system in dynamics, fixturing, and machining configuration. In this study, a feed motor current signal is used as a process signal representing process and tool states in tool breakage monitoring based on an adaptive autoregressive model and unsupervised neural network. From the experimental results using various cases of tool breakage, it is shown that the developed system can successfully detect tool breakage before two revolutions of the spindle after tool breakage.

• 한국정밀공학회지
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• 제13권9호
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• pp.31-37
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• 1996

This Paper is concerned with effective signal identification method for tool breakage and micro chipping using discrete wavelet transform of feed motor current in milling operations. The wavelet transform uses an analyzing waveletfunction which is localized in both frequency and time domain to detect subtle time localized changes in input signals. The changing pattern of wavelet coefficient is continuously compared to detect tool breakage and micro chipping over one spindle revolution. The results indicate that the wavelet transform can identify tool failure with much greater sensi- tivity than the time domain monitoring and frequency domain monitoring such as FFT. Experimental results are presented to support the proposed scheme.

• 한국정밀공학회지
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• 제12권2호
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• pp.23-34
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• 1995

This paper is concerned with effective and reliable tool breakage detection method using pattern characteristics of feed motor current in milling operations. Correlation coefficient is derived from the feature vector of signal for two consecutive which are extracted feed motor current over three spindle revolutions. The changing pattern of correlation coefficient is continuously compared to detect tool breakage and monitor cutting conditions. This proposed monitoring scheme is not affected by different tools, friction of motion, and varying cutting conditions and material shapes. Experimental results are presented to support the proposed monitoring scheme.

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 1997년도 추계학술대회 논문집
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• pp.319-322
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• 1997

In vector control technique, stator currents of an induction motor are transformed to equivalent d-q currents in reference frame consist of d and q axis, each of which is coincide with flux and torque direction respectively. In this paper, the new algorithm is suggested where the stator current through an induction motor torque is monitored by using a vector control method where an additional equipment is not need. The G-programming is used to apply the suggested algorithm in the experiment and this is applied to an actual system to monitor the torque value of an induction motor on real time. To solve the vibration trouble of estimated torque caused from an unbalanced real rotating speed of an induction motor and measured rotating speed by suggesting the reconstructed in a method based on measurement current signal. This produced system testifies an accuracy of an induction motor through the experiment by comparing the reference value of the control method.

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 2000년도 추계학술대회 논문집
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• pp.148-152
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• 2000

Detection of tool wear is very important in automated manufacturing. This paper presents tool condition monitoring system based on the wavelet analysis of the AC servo motro current in drilling and milling process. The current measurement system is relatively simple and its mounting will not affect machining operations. The discrete wavelet transform was used to decompose the current signal of a spindle AC servo motor in time - frequency domain. The feature vectors were extracted from the decomposed signals and compared for normal and wear condition. The results show the possibility for the effective application of wavelet analysis to tool condition monitoring.

• 한국정밀공학회지
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• 제19권12호
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• pp.57-63
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• 2002

In this paper, the feedforward control with least mean square (LMS) adaptive algorithm is proposed and examined to reduce rotating error by runout of an active magnetic bearing system. Using eddy-current type gap sensor fur control, the electrical runout caused by non-uniform material properties of sensor target produces rotational error amplified in feedback control loop, so this runout should be eliminated to increase rotating accuracy. The adaptive feedforward controller is designed and examined its tracking and stability performances numerically with established frequency response function. The tested grinding spindle system is manufactured with a 5.5 ㎾ internal motor and 5-axis active magnetic bearing system including 5 eddy current gap sensors which have approximately 15 ~ 30 ${\mu}{\textrm}{m}$ of electrical runout. According to the experimental analysis, the error signal in radial bearings is reduced to less than 5 ${\mu}{\textrm}{m}$ when it is rotating up to 50,000 rpm due to applying the feedforward control for first order harmonic frequency, and vibration of the spindle base is also reduced about same frequency.