• Transactions of the Korean Society of Mechanical Engineers A
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• v.29 no.5 s.236
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• pp.726-733
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• 2005

A spherical surface referenced Shack-Hartmann method is studied for inspecting machining accuracy of large concave mirror This method is so strong to the vibration environment for using as an on-machine inspection system during polishing process of large optics comparing with the interferometry. The measuring uncertainty of the system is shown as less than p-v 150 m. On-machine measured surface profile data with this method is used for feed back control of the polishing time or depth to improve the surface profile accuracy of large concave mirror. Also, the spherical surface referenced Shack-Hartmann method is useful for measuring aspheric such as parabolic or hyperbolic surface profile, comparing that the interferomehy needs a special null lens, which is to be a reference and difficult to fabricate.

• Transactions of The Korea Fluid Power Systems Society
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• v.7 no.1
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• pp.6-10
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• 2010

A measurement of very high torque for track drive unit in construction equipment is usually in difficulties due to the requirement of a torque meter with high capacity, and the limitation of geometry for an experimental set-up. To improve the troublesome problem, a new device was proposed, where a torque transmitted through the torque arm can be measured by load cells attached at each torque arm. The experimental set-up of the new device was carried out in order to measure the torque values for a mechanical feedback type planetary gear box, in which the power flow circulates itself in a closed-loop. The new device enables to measure torque values of 60,000Nm. Additionally, the measured values were estimated statistically in the aspect of their repeatability and reproducibility, so that an acceptable behaviour as a measuring device can be confirmed.

• Journal of the Korean Society for Precision Engineering
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• v.34 no.1
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• pp.23-27
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• 2017

This paper aims to develop a prediction model for the product quality of a casting process. Prediction of the product quality utilizes an artificial neural network (ANN) in order to renovate the manufacturing technology of the root industry. Various aspects of the research on the prediction algorithm for the casting process using an ANN have been investigated. First, the key process parameters have been selected by means of a statistics analysis of the process data. Then, the optimal number of the layers and neurons in the ANN structure is established. Next, feed-forward back propagation and the Levenberg-Marquardt algorithm are selected to be used for training. Simulation of the predicted product quality shows that the prediction is accurate. Finally, the proposed method shows that use of the ANN can be an effective tool for predicting the results of the casting process.

• Animal cells and systems
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• v.16 no.2
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• pp.121-126
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• 2012

In this study, a neural network (NN) modeling approach has been used to predict the mechanical and geometrical behaviors of mouse embryo cells. Two NN models have been implemented. In the first NN model dimple depth (w), dimple radius (a) and radius of the semi-circular curved surface of the cell (R) were used as inputs of the model while indentation force (f) was considered as output. In the second NN model, indentation force (f), dimple radius (a) and radius of the semi-circular curved surface of the cell (R) were considered as inputs of the model and dimple depth was predicted as the output of the model. In addition, sensitivity analysis has been carried out to investigate the influence of the significance of input parameters on the mechanical behavior of mouse embryos. Experimental data deduced by Fl$\ddot{u}$ckiger (2004) were collected to obtain training and test data for the NN. The results of these investigations show that the correlation values of the test and training data sets are between 0.9988 and 1.0000, and are in good agreement with the experimental observations.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.31 no.1 s.256
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• pp.26-35
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• 2007

The vehicle of urban transit is a complex system that consists of various electric, electronic, and mechanical equipments, and the maintenance cost of this complex and large-scale system generally occupies sixty percent of the LCC (Life Cycle Cost). For reasonable establishing of maintenance strategies, safety security and cost limitation must be considered at the same time. The concept of system reliability has been introduced and optimized as the key of reasonable maintenance strategies. For optimization, three preceding studies were accomplished; standardizing a maintenance classification, constructing RBD (Reliability Block Diagram) of VVVF (Variable Voltage Variable Frequency) urban transit, and developing a web based reliability evaluation system. Historical maintenance data in terms of reliability index can be derived from the web based reliability evaluation system. In this paper, we propose applying inverse problem analysis method and hybrid neuro-genetic algorithm to system reliability optimization for using historical maintenance data in database of web based system. Feed-forward multi-layer neural networks trained by back propagation are used to find out the relationship between several component reliability (input) and system reliability (output) of structural system. The inverse problem can be formulated by using neural network. One of the neural network training algorithms, the back propagation algorithm, can attain stable and quick convergence during training process. Genetic algorithm is used to find the minimum square error.

• Transactions of the Korean Society of Automotive Engineers
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• v.20 no.6
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• pp.52-60
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• 2012

Minimizing the cylinder wear and the consumption rate of cylinder oil in a large two-stroke diesel engine is of great economic importance. A motor-driven cylinder lubricator for Sulzer RT-flex large two-stroke diesel engines developed by authors is in need of modifying the lubricating system to lubricate cylinder parts optimally by an electronically controlled quill device according to changes of engine load and revolution speed. In order to apply the developed accumulating distributor to an integrated cylinder lubricator by the electronically controlled system as the third research stage, the lubricating system is improved in the electronically controlled quill device with a solenoid valve. In this study, the effects of lubricator revolution speed, driving pressure and cylinder back pressure on oil feed rate, maximum discharge and delivery pressures are experimentally investigated by using the integrated cylinder lubricator system with an accumulated distribution by the electronic control. It is found that the oil feed rate of the developed integral cylinder lubricator system is less than that of the motor-driven cylinder lubricator by the electronically controlled quill system equipped with an accumulating distributor because of the decrease of delivery speed by increasing the maximum delivery pressure in the same experimental condition.

• Transactions of Materials Processing
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• v.30 no.3
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• pp.125-133
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• 2021

In this study, response surface method (RSM), back propagation neural network (BPNN), and genetic algorithm (GA) were used for modeling and multi-objective optimization of the parameters of AA5052-H32 in incremental sheet forming (ISF). The goal of optimization is to determine the maximum forming angle and minimum surface roughness, while varying the production process parameters, such as tool diameter, tool spindle speed, step depth, and tool feed rate. A Box-Behnken experimental design (BBD) was used to develop an RSM model and BPNN model to model the variations in the forming angle and surface roughness based on variations in process parameters. Subsequently, the RSM model was used as the fitness function for multi-objective optimization of the ISF process the GA. The results showed that RSM and BPNN can be effectively used to control the forming angle and surface roughness. The optimized Pareto front produced by the GA can be utilized as a rational design guide for practical applications of AA5052 in the ISF process

• Proceedings of the KSME Conference
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• 2007.05b
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• pp.2250-2254
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• 2007

Comprehensive analytical models focusing on the anode water loss, the cathode flooding, water equilibrium, and water management strategy are developed for polymer electrolyte fuel cells. Analytical solutions presented in this study are compared with two-dimensional computational results and shows a good agreement in predicting those critical characteristics of water. General features of water concentration profile as a function of membrane thickness and current density are presented to illustrate the net effect of the back-diffusion of water from the cathode to anode and the water production by the cathode catalytic reaction on water transport over a fuel cell domain. As one of practical applications, the required humidity level of feed streams for full saturation at the channel outlets are investigated as a function of the physical operating condition. These analytical models can provide good understanding on the characteristic water

• Korean Journal of Remote Sensing
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• v.26 no.6
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• pp.721-730
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• 2010

In satellite remote sensing, irregular temporal sampling is a common feature of geophysical and biological process on the earth's surface. Lee (2008) proposed a feed-back system using a harmonic model of single period to adaptively reconstruct observation image series contaminated by noises resulted from mechanical problems or environmental conditions. However, the simple sinusoidal model of single period may not be appropriate for temporal physical processes of land surface. A complex model of multiple periods would be more proper to represent inter-annual and inner-annual variations of surface parameters. This study extended to use a multi-periodic harmonic model, which is expressed as the sum of a series of sine waves, for the adaptive system. For the system assessment, simulation data were generated from a model of negative errors, based on the fact that the observation is mainly suppressed by bad weather. The experimental results of this simulation study show the potentiality of the proposed system for real-time monitoring on the image series observed by imperfect sensing technology from the environment which are frequently influenced by bad weather.

• 제어로봇시스템학회:학술대회논문집
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• 1987.10b
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• pp.631-636
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• 1987

The design of ultrasonic transducer energy processing systems requires highly reliable command featuring mechanical frequency tracking and constant velocity control of the ultrasonic transducer with an acoustic load. This paper presents a new conceptional instantaneous current resultant control base high-frequency inverter using self turn-off devices driving an electrostrictive ultrasonic transducer system and its optimum control technique, which is implemented by feed-back of the ultrasonic transducer applied voltage and instantaneous velocity of the transducer vibrating system through a Phase-Locked-Loop control scheme. The feedback voltage corresponding to instantaneous velocity is averaged over a half-period with respect to constant amplitude/constant velocity control strategy. Described are the theory of this signal detection technique and the experimental set-up.