• Proceedings of the KSME Conference
• /
• 2008.11a
• /
• pp.1588-1593
• /
• 2008

This paper describes a real-time isometric pinch force prediction algorithm from surface electromyogram (sEMG) using multilayer perceptron (MLP) for human robot interactive applications. The activities of seven muscles which are observable from surface electrodes and also related to the movements of the thumb and index finger joints were recorded during pinch force experiments. For the successful implementation of the real-time prediction algorithm, an off-line analysis was performed using the recorded activities. Four muscles were selected for the force prediction by using the Fisher linear discriminant analysis among seven muscles, and the four muscle activities provided effective information for mapping sEMG to the pinch force. The MLP structure was designed to make training efficient and to avoid both under- and over-fitting problems. The pinch force prediction algorithm was tested on five volunteers and the results were evaluated using two criteria: normalized root mean squared error (NRMSE) and correlation (CORR). The training time for the subjects was only 2 min 29 sec, but the prediction results were successful with NRMSE = 0.112 ${\pm}$ 0.082 and CORR = 0.932 ${\pm}$ 0.058. These results imply that the proposed algorithm is useful to measure the produced pinch force without force sensors in real-time. The possible applications include controlling bionic finger robot systems to overcome finger paralysis or amputation.

• Proceedings of the Korean Society of Precision Engineering Conference
• /
• 1997.04a
• /
• pp.1003-1008
• /
• 1997

In this paper, the prediction of cutting force and tool deflection in the ball-end milling process are studied. Identifying various cutting region using Z-map, cutting force in the ball-end milling process can be predicted. Cutting force deflects the tool and the tool deflection changes the cutting force. Tool deflection is included in the cutting force prediction. Tool deflecition also causes machining error of the machined surface. A series of experiments were performed to verify the simulated cutting force and machining error.

• Transactions of Materials Processing
• /
• v.6 no.6
• /
• pp.482-488
• /
• 1997

New carbon equivalent equation for the better prediction for the better prediction of roll force in a continuous hot strip mill has been formulated by applying a neural network method. In predicting roll force of steel strip, carbon equivalent equation which normalize the effects of various alloying elements by a carbon equivalent content is very critical for the accurate prediction of roll force. To overcome the complex relationships between alloying elements and operational variables such as temperature, strain, strain rate and so forth, a neural network method which is effective for multi-variable analysis was adopted in the present work as a tool to determine a proper carbon equivalent equation. The application of newly formulated carbon equivalent equation has increased prediction accuracy of roll force significantly and the effectiveness of neural network method is well confirmed in this study.

• Journal of the Korean Society of Manufacturing Technology Engineers
• /
• v.22 no.3_1spc
• /
• pp.489-495
• /
• 2013

This study analyzed thevariation in the cutting force when the cutting area of a terrace volume is machined, which is generally left after the rough cutting of a sculptured surface. The numerically simulated results for the cutting forces are compared with cutting force measurements by considering the theoretical prediction of the cutting area formation and specific cutting volume. The variation in the cutting force is measured using a dynamometer installed on a machining center for 19 different kinds of test pieces, which are selected according to the variation in the terrace volume factor, tool diameter factor, and cutting depth factor. As a result, it is verified that the cutting forces evaluated by the numerical analysis coincide with the measured cutting forces, and it is proposed as a practical cutting force prediction model.

• Proceedings of the Korean Society of Precision Engineering Conference
• /
• 2011.06a
• /
• pp.557-558
• /
• 2011

• Proceedings of the Korean Society of Precision Engineering Conference
• /
• 1994.10a
• /
• pp.15-19
• /
• 1994

The application of neural network for fault dection of cutting force in turning was introduced. This monitoring system consist of a RBF predicton model and a ART-1 pattern classifier. RBF prediction model predict a cutting force signal. Prediction error of predictor is used for a input vector of ART-1 pattern classifier. Prediction error could be successfully performed to fault signal monitoring of ART-1 pattern classifier.

• Proceedings of the Korean Society of Precision Engineering Conference
• /
• 2000.05a
• /
• pp.907-911
• /
• 2000

In this study, a modified model for prediction of cutting force components in down end milling process is presented. Using this cutting force components of 4-tooth endmills with various helix angles have been predicted. Predicted values of cutting force components are well coincide with the measured ones. As helix angle increases overlapping effects of the active cutting edges increase and as a result the amplitudes of cutting force components decrease.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
• /
• 2000.04a
• /
• pp.3-7
• /
• 2000

In this study, a modified model for prediction of cutting force components in up end milling process is presented. Using this cutting force components of 4-tooth endmils with various helix angles have been predicted. Predicted value of cutting force components are well coincide with the measured ones. As helix angle increases overlapping effects of the active cutting edges increase and as a result the amplitudes of cutting force components decrease and the specific cutting energy consumed also decreases

• Journal of the Korean Society of Manufacturing Technology Engineers
• /
• v.20 no.3
• /
• pp.225-231
• /
• 2011

In this paper, a new end-milling force modelling technique was suggested by considering runout, and its result was compared with real measured force. The specific cutting force is the multiplication of cutting force coefficient and uncut chip thickness. This parameter was used for experimental modelling and prediction of theoretical force. These coefficients, which can be obtained by fitting measured average forces in several conditions, were used for the formulation of theoretical force. The mechanism of end-milling force with runout was developed in this research and its result was verified by comparing the fluctuating theoretical force and its measured one. The fluctuation of force was incurred by a geometric shape of workpiece and its runout in holding. The result of suggested force considering runout shows a good consistency with measured one. So this modelling method can be used effectively for a prediction of end-milling force with runout effect.

• Proceedings of the KSR Conference
• /
• 2003.10b
• /
• pp.538-543
• /
• 2003

This study is the developed prediction of residual effective prestress force of prestressed concrete beam bridges. Developed prediction method is based on the center camber of prestressed concrete beam, structural design. report of various PSC beams, construction reference materials of PSC beams. Evaluation of residual effective prestress force by developed method is compared with evaluation by structural design. This comparison results shows that this developed method is very effective method. Therefore prediction of residual effective prestress force by this developed method will be used for evaluation of the rating of various PSC beam bridges(road bridges and railway bridges).