• International Journal of Precision Engineering and Manufacturing
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• v.3 no.3
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• pp.82-89
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• 2002

The need of ultra-precision machine tools, which manufacture and machine the high precision parts used in computers, semi-conductors and other precision machines, has been increased over years. Therefore it is important to design the driving parts, which affect significantly on their performances. In this paper, the dynamic analyses on the belt-driven system were explored. Relation of the acoustical natural frequency and the tension of belt was derived and presented through experiments. Also, while the dynamic loads on motor system were changed, dynamic deflections were calculated through finite element analysis. Nonlinear characteristics of the bearings having an effect on the dynamic performance were studied and the belt connecting the motor (driving part) to spindle of a machine tool (driven part) was modeled as truss and beam elements fur simulations under various conditions, and a beam element model was verified to be more useful.

• Safety and Health at Work
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• v.6 no.4
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• pp.268-278
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• 2015

Background: This study aimed to assess the whole-body vibration (WBV) exposure among large blast hole drill machine operators with regard to the International Organization for Standardization (ISO) recommended threshold values and its association with machine- and rock-related factors and workers' individual characteristics. Methods: The study population included 28 drill machine operators who had worked in four opencast iron ore mines in eastern India. The study protocol comprised the following: measurements of WBV exposure [frequency weighted root mean square (RMS) acceleration ($m/s^2$)], machine-related data (manufacturer of machine, age of machine, seat height, thickness, and rest height) collected from mine management offices, measurements of rock hardness, uniaxial compressive strength and density, and workers' characteristics via face-to-face interviews. Results: More than 90% of the operators were exposed to a higher level WBV than the ISO upper limit and only 3.6% between the lower and upper limits, mainly in the vertical axis. Bivariate correlations revealed that potential predictors of total WBV exposure were: machine manufacturer (r = 0.453, p = 0.015), age of drill (r = 0.533, p = 0.003), and hardness of rock (r = 0.561, p = 0.002). The stepwise multiple regression model revealed that the potential predictors are age of operator (regression coefficient ${\beta}=-0.052$, standard error SE = 0.023), manufacturer (${\beta}=1.093$, SE = 0.227), rock hardness (${\beta}=0.045$, SE = 0.018), uniaxial compressive strength (${\beta}=0.027$, SE = 0.009), and density (${\beta}=-1.135$, SE = 0.235). Conclusion: Prevention should include using appropriate machines to handle rock hardness, rock uniaxial compressive strength and density, and seat improvement using ergonomic approaches such as including a suspension system.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.63 no.8
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• pp.1098-1103
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• 2014

This study deals with the development of an electrofusion welding machine that is capable of joining plastic pipes using a recently developed electrofusion fitting. This fitting has built-in conductive plastics that are used to weld the joint together as a heating element. In order to explain the mechanism of the new machine, 1) the resistance characteristics of the heating element were explained, 2) the method of electric welding that uses the electrofusion fitting was described, and 3) the method of power supply based on controlling the firing angle was explained. A control system for an intelligent electrofusion welding machine was proposed. This system has the ability to recognize the diameter of an electrofusion fitting using a lookup-table based on the difference of resistance curves according to fitting types, and it is able to weld the fittings regardless of the ambient temperature. A new algorithm was developed to control the power of electric welding through the recognition of feature points from the resistance curve of the heating element. In order to evaluate the performance of the developed welding machine, tests involving the welding of 16 mm- and 20 mm-type fittings were carried out. Examining the welding results, we concluded that the proposed welding machine will offer high productivity and reliability in the field of electrofusion welding.

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

• Textile Coloration and Finishing
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• v.11 no.2
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• pp.64-74
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• 1999

The driving characteristics of the 1 tube 2 chamber bent silkworm type dyeing machine are reported. This dyeing machine is a newly developed energy saving machine. In this study, the driving characteristics of the 1 tube 2 chamber bent silkworm type dyeing machine are examined. Specially the relationship between main body pressure and the electric current of the blower motor, the relationship between main body pressure and the air pressure of the blower nozzle, the effect of the air pressure of the blower on the running speed of the fabric, and the effect of main body temperature were discussed experimentally. Through the experimental data, the following results were obtained. 1. Blower motor electric current and blower nozzle air pressure increased as main body pressure increased due to the temperature increase of the main body. 2. The running speed of the fabric increased as blower nozzle air pressure increased. The difference in running speed between winch reel driving and no winch reel driving at a blower frequency of 60Hz was higher than that of 70Hz. 3. The electric current of the blower rioter and blower nozzle air pressure increased rapidly at the initial state. As the experimental time passed, the main body pressure increased slowly. as the main body temperature increased.

• Geomechanics and Engineering
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• v.34 no.5
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• pp.547-559
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• 2023

We evaluated the applicability of machine learning techniques and the Kuz-Ram model for predicting the mean fragmentation size in open-pit mines. The characteristics of the in-situ rock considered here were uniaxial compressive strength, tensile strength, rock factor, and mean in-situ block size. Seventy field datasets that included these characteristics were collected to predict the mean fragmentation size. Deep neural network, support vector machine, and extreme gradient boosting (XGBoost) models were trained using the data. The performance was evaluated using the root mean squared error (RMSE) and the coefficient of determination (r²). The XGBoost model had the smallest RMSE and the highest r² value compared with the other models. Additionally, when analyzing the error rate between the measured and predicted values, XGBoost had the lowest error rate. When the Kuz-Ram model was applied, low accuracy was observed owing to the differences in the characteristics of data used for model development. Consequently, the proposed XGBoost model predicted the mean fragmentation size more accurately than other models. If its performance is improved by securing sufficient data in the future, it will be useful for improving the blasting efficiency at the target site.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 1996.03a
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• pp.56-60
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• 1996

• Transactions of the Korean Society of Machine Tool Engineers
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• v.12 no.4
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• pp.77-84
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• 2003

The properties of a machine tool greatly affect machining quality since a machine tool has large variance in its features. Machine tool makers want to find best machining condition with the one that they have built. Machine builders need to develop test specimen since it helps finding characteristics of machine tools when the machining properties of the specimen are analyzed. This paper develops test specimen to identify features of the main spindle, the feeding device, and the frame of a machine tool. The specimen is machined with a high speed machine and the features of the machine are analyzed with test items. They are surface roughness, overshoot in axial movement, errors in circular movement, feeding with small movement and compensational error. This work can improve usability for a machine tool in machining practice.

• Journal of Electrical Engineering and Technology
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• v.13 no.4
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• pp.1596-1603
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• 2018

This paper presents the new design and validation process of the linear transverse flux machine of the stelzer machine for hybrid vehicle application. A linear transverse flux machine is a novel electric machine that has higher force density and power than conventional electric machine. The process concentrates on 2-dimensional and 3-dimensional analysis using equivalent magnetic circuit method considering leakage elements and it is verified by finite element analysis. Besides the force characteristics of all axis of each direction are analyzed. The study is considered by dividing the transverse flux electric excited type and the transverse flux permanent magnet excited type. Additionally three-dimensional analysis in this machine is accomplished due to asymmetric structure with another three axes. Finally, it suggests the new design and validation process of linear transverse flux machine for stelzer machine.

• Transactions of the Korean Society of Machine Tool Engineers
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• v.14 no.2
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• pp.8-13
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• 2005

This study proposes the construction of 2-3 dimensional attractor system for cutting characteristics evaluation of metals. Also this paper aims to find the optimal cutting conditions of diamond turning machine by measuring surface form and roughness to perform the cutting experiment of metals, which are aluminum, with diamond tool. As well, according to change cutting conditions such as feed rate, using diamond turning machine to perform cutting processing, by measuring cutting force and surface roughness and according to cutting conditions the aluminum about cutting properties. Trajectory changes in the attractor indicated a substantial difference in attractor characteristics. Constructed 2-3 dimensional attractor system in this study can be used for cutting characteristics evaluation of metals.