• Journal of the Korean Society of Manufacturing Technology Engineers
• /
• v.25 no.5
• /
• pp.313-320
• /
• 2016

The need for high-strength, multi-axis, and multi-functional machine tools has recently increased because of part complexity and workpiece strength. However, most of the machine tool manufacturers rely on experience for a detailed design because of the shortcomings in the existing design technology. This study uses a topology optimization method to more effectively design a large multi-functional machine tool considering static stiffness. The ram, saddle, and column parts are important structures in a machine tool. Hence, they are selected for the finite element method analysis. Based on this analysis, the optimized internal rib structure for those parts is designed for desirable rigidity and weight. This structure could possibly provide the required design technology for machine tool manufacturers.

• Journal of the Korean Society of Industry Convergence
• /
• v.17 no.3
• /
• pp.84-92
• /
• 2014

In this paper, a novel 5-axis hybrid-kinematic machine tool is introduced and the research results on accuracy improvement of the prototype machine tool are presented. The 5-axis hybrid machine tool is made up of a 3-DOF parallel manipulator and a 2-DOF serial one connected in series. The machine tool maintains high ratio of stiffness to mass due to the parallel structure and high orientation capability due to the serial-type wrist. In order to acquire high accuracy, the methodology of measuring the output shafts by additional sensors instead of using encoder outputs at the motor shafts is proposed. In the kinematic view point, the hybrid manipulator reduces to a serial one, if the passive joints in the U-P serial chain at the center of the parallel manipulator are directly measured by additional sensors. Using the method of successive screw displacements, the kinematic error model is derived. Since a ball-bar is less expensive than a full position measurement device and sufficiently accurate for calibration, the kinematic calibration method of using a ball-bar is presented. The effectiveness of the calibration method has been verified through the simulations. Finally, the calibration experiment shows that the position accuracy of the prototype machine tool has been improved from 153 to $86{\mu}m$.

• International Journal of Computer Science & Network Security
• /
• v.23 no.7
• /
• pp.202-209
• /
• 2023

Android malware is now on the rise, because of the rising interest in the Android operating system. Machine learning models may be used to classify unknown Android malware utilizing characteristics gathered from the dynamic and static analysis of an Android applications. Anti-virus software simply searches for the signs of the virus instance in a specific programme to detect it while scanning. Anti-virus software that competes with it keeps these in large databases and examines each file for all existing virus and malware signatures. The proposed model aims to provide a machine learning method that depend on the malware detection method for Android inability to detect malware apps and improve phone users' security and privacy. This system tracks numerous permission-based characteristics and events collected from Android apps and analyses them using a classifier model to determine whether the program is good ware or malware. This method used the machine learning techniques KNN-SVM, DBN, and GRU in which help to find the accuracy which gives the different values like KNN gives 87.20 percents accuracy, SVM gives 91.40 accuracy, Naive Bayes gives 85.10 and DBN-GRU Gives 97.90. Furthermore, in this paper, we simply employ standard machine learning techniques; but, in future work, we will attempt to improve those machine learning algorithms in order to develop a better detection algorithm.

• Progress in Medical Physics
• /
• v.28 no.3
• /
• pp.129-133
• /
• 2017

The machine log files recorded by a scanning control unit in proton beam therapy system have been studied to be used as a quality assurance method of scanning beam deliveries. The accuracy of the data in the log files have been evaluated with a standard calibration beam scan pattern. The proton beam scan pattern has been delivered on a gafchromic film located at the isocenter plane of the proton beam treatment nozzle and found to agree within ${\pm}1.0mm$. The machine data accumulated for the scanning beam proton therapy of five different cases have been analyzed using a statistical method to estimate any systematic error in the data. The high-precision scanning beam log files in line scanning proton therapy system have been validated to be used for off-line scanning beam monitoring and thus as a patient-specific quality assurance method. The use of the machine log files for patient-specific quality assurance would simplify the quality assurance procedure with accurate scanning beam data.

• Journal of the Korean Society for Precision Engineering
• /
• v.30 no.5
• /
• pp.461-466
• /
• 2013

In this paper, main mechanism and measurement method of energy consumption for machine tools are investigated by experiment and simulation. To evaluate total energy consumption of the machine tools, standard test workpiece and measuring method and test procedures are suggested. And, improvement of energy consumption evaluation by the motion kinematics theory is used. In addition, to estimate energy consumption of machine tools in design process, mass distribution of the structure and 5 axis motions are investigated and simulated by numerical analysis.

• Proceedings of the Korean Society of Precision Engineering Conference
• /
• 2001.04a
• /
• pp.501-504
• /
• 2001

The use of error compensation techniques has been recognized as an effective way in the improvement of the accuracy of a machine tool. The laser measurement method for identifying position errors of machine tool has the disadvantages such as high cost, long calibration time and usage of volumetric error synthesis model. Accordingly, this paper deals with analysis of the position errors of a machine tool using ball bar test without using complicated error synthesis model. Statistical analysis method was adopted in this paper for deriving position errors using hemispherical helix ball bar test.

• Journal of the Korean Data and Information Science Society
• /
• v.25 no.2
• /
• pp.455-464
• /
• 2014

Unlabeled examples are easier and less expensive to obtain than labeled examples. Semisupervised approaches are used to utilize such examples in an eort to boost the predictive performance. This paper proposes a novel semisupervised classication method named transductive least squares support vector machine (TLS-SVM), which is based on the least squares support vector machine. The proposed method utilizes the dierence convex algorithm to derive nonconvex minimization solutions for the TLS-SVM. A generalized cross validation method is also developed to choose the hyperparameters that aect the performance of the TLS-SVM. The experimental results conrm the successful performance of the proposed TLS-SVM.

• Journal of Electrical Engineering and Technology
• /
• v.10 no.3
• /
• pp.812-819
• /
• 2015

This paper presents a new approach for simulating the internal faults of synchronous machines using distributed computing and Large Change Sensitivity (LCS) analysis. LCS analysis caters for a parallel solution of 3-phase model of a faulted machine within the symmetrical component-based model of interconnected network. The proposed method considers dynamic behavior of the faulty machine and connected system and tries to accurately solve the synchronous machine’s internal fault conditions in the system. The proposed method is implemented in stand-alone FORTRAN-based phasor software and the results have been compared with available recordings from real networks and precisely simulated faults by use of the ATP/EMTP as a time domain software package. An encouraging correlation between the simulation results using proposed method, ATP simulation and measurements was observed and reported. The simplified approach also enables engineers to quickly investigate their particular cases with a reasonable precision.

• Journal of the Korean Society of Manufacturing Process Engineers
• /
• v.11 no.4
• /
• pp.154-159
• /
• 2012

Condition monitoring(CM) is a method based on Non-destructive test(NDT). Therefore, recently many kind of NDT were applied for CM. Acoustic emission(AE) is widely used for the early detection of faults in rotating machinery in these days also. Because its sensitivity is higher than normal accelerometers and it can detect low energy vibration signals. A machine tool consist of many parts such as the bearings, gears, process tools, shaft, hydro-system, and so on. Condition of Every part is connected with product quality finally. To increase the quality of products, condition monitoring of the components of machine tool is done completely. Therefore, in this paper, acoustic emission method is used to detect a machine fault seeded in a gearbox. The AE signals is saved, and power spectrums and feature values, peak value, mean value, RMS, skewness, kurtosis and shape factor, were determined through Matlab.

• Journal of Korean Institute of Industrial Engineers
• /
• v.39 no.3
• /
• pp.149-155
• /
• 2013

Electric discharging machining (EDM) is commonly adopted to machine the precise and tiny part when it is difficult to meet the productivity and the tolerance by the conventional cutting method. The die-sinking EDM method works well to machine the micro-parts and the perpendicular wall of die and mould, whereas EDM drilling, called super drill, is excellent to machine the deep and narrow hole regardless the material hardness and the hole location. However, the electrode wear is rapid compared to the conventional cutting tool and makes it difficult to control the electrode feeding and to machine precisely. This paper presents an efficient method to estimate the electrode wear using hole pass-through experiment while the stochastic method is used to compensate for the estimation model. To validate the proposed method, the commercial EDM drill machine is used. The experiment result shows that the electrode wear amount can be predicted very precisely.