• Journal of Drive and Control
• /
• v.17 no.1
• /
• pp.27-36
• /
• 2020

The aim of this study is to design a simulation model for an electric All-Wheel-Drive (AWD) tractor to evaluate the performance of the selected component and agricultural work ability. The electric AWD tractor consists of four motors independently for each drive wheel, and each motor is combined with an engine generator, a battery pack, and reducers. The torque data of a 78 kW-class tractor was measured during plow tillage and driving operation to develop a workload cycle. A simulation model was developed by using commercial software, Simulation X, and it used the workload as the simulation condition. As a result of simulation analysis, the drive system, including an electric motor and reducers, was able to cope with high load during plow tillage. The SOC (State of Charge) level was influenced by the output power of the motor, and it was maintained in the range of 50~80%. The fuel consumed by the engine was about 18.23 L during working on a total of 8 fields. The electric AWD tractor was able to perform agricultural work for about 7 hours. In the future study, the electric AWD tractor will be developed reflecting the simulation condition. Research on the comparison between the simulation model and the electric AWD tractor should be performed.

• Journal of the Korea Society of Computer and Information
• /
• v.3 no.1
• /
• pp.95-112
• /
• 1998

The Error Backpropagation algorithm is widely used in various areas such as associative memory, speech recognition, pattern recognition, robotics and so on. However, if and when a new leaning pattern has to be added in order to drill, it will have to accomplish a new learning with all previous learning pattern and added pattern from the very beginning. Somehow, it brings about a result which is that the more it increases the number of pattern, the longer it geometrically progress the time required by leaning. Therefore, a so-called Incremental Learning Method has to be solved the point at issue all by means in case of situation which is periodically and additionally learned by numerous data. In this study, not only the existing neural network construction is still remained, but it also suggests a method which means executing through added leaning by a model pattern. Eventually, for a efficiency of suggested technique, both Monk's data and Iris data are applied to make use of benchmark on machine learning field.

• Ocean and Polar Research
• /
• v.39 no.4
• /
• pp.293-300
• /
• 2017

Various approaches have been tried in an effort to improve the power performance of a flapping tidal stream turbine after it was introduced as an alternative to conventional rotary turbines. Among the different approaches, researches on mimicking the morphology and behavior of animals have been conducted. In this study, we utilized a flapper to mimic the multi-joint pectoral fin of a Manta-ray and investigated its effect on power generation. Experiments were conducted by a dual flapping apparatus with rigid and flexible flappers in a towing tank facility. First, in order to determine the conditions that can produce high power generation, the performances of the dual rigid flappers were compared when input arm angles and frequencies are changed, and the two conditions $40^{\circ}$, 0.2 Hz and $40^{\circ}$, 0.3 Hz for the input arm angle, frequency were selected. When the mimicked flexible flapper was used instead of the front rigid flapper and the rear one, the power was improved by an average of 22% and 38% in the experimental conditions, respectively. Moreover, it was recognized from the apparent camber observed during the experiment that the flexible flapper had been successfully applied. If the feasibility of the Manta-Ray mimicked flapper is improved through subsequent researches, the flapping tidal turbine can be a viable alternative to rotary turbines in the near future.

• 제어로봇시스템학회:학술대회논문집
• /
• 2005.06a
• /
• pp.1439-1444
• /
• 2005

Induction motors are the most commonly used electrical drives because they are rugged, mechanically simple, adaptable to widely different operating conditions, and simple to control. The most common faults in squirrel-cage induction motors are bearing, stator and rotor faults. Surveys conducted by the IEEE and EPRI show that the most common fault in induction motor is bearing failure (${\sim}$40% of failure). Thence, this paper addresses experimental results for diagnosing faults with different rolling element bearing damage via motor current spectral analysis. Rolling element bearings generally consist of two rings, an inner and outer, between which a set of balls or rollers rotate in raceways. We set the experimental test bed to detect the rolling-element bearing misalignment of 3 type induction motors with normal condition bearing system, shaft deflection system by external force and a hole drilled through the outer race of the shaft end bearing of the four pole test motor. This paper takes the initial step of investigating the efficacy of current monitoring for bearing fault detection by incipient bearing failure. The failure modes are reviewed and the characteristics of bearing frequency associated with the physical construction of the bearings are defined. The effects on the stator current spectrum are described and related frequencies are also determined. This is an important result in the formulation of a fault detection scheme that monitors the stator currents. We utilized the FFT, Wavelet analysis and averaging signal pattern by inner product tool to analyze stator current components. The test results clearly illustrate that the stator signature can be used to identify the presence of a bearing fault.

• Journal of the Korean Society for Aeronautical & Space Sciences
• /
• v.43 no.2
• /
• pp.172-178
• /
• 2015

The control moment gyroscope(CMG) which is well known as an effective high-torque-generating device is applicable to space vehicles, airplanes, ships, automobiles, robotics, etc. for attitude stabilization and maneuver. This paper deals with the overall details of 100Nm-class CMG development for various industrial applications, and provides the activities and results associated with the CMG system-level requirement analysis, the motor subsystem design/manufacturing/integration, the construction of ground support equipment, and the performance test and evaluation. The performance test reveals that the CMG generates the torque output more than 120Nm in as-designed operation of spin motor and gimbal motor.

• International Journal of Control, Automation, and Systems
• /
• v.2 no.4
• /
• pp.423-434
• /
• 2004

In this paper, we introduce a new topology of Self-Organizing Polynomial Neural Networks (SOPNN) based on genetically optimized Multi-Layer Perceptron (MLP) and discuss its comprehensive design methodology involving mechanisms of genetic optimization. Let us recall that the design of the 'conventional' SOPNN uses the extended Group Method of Data Handling (GMDH) technique to exploit polynomials as well as to consider a fixed number of input nodes at polynomial neurons (or nodes) located in each layer. However, this design process does not guarantee that the conventional SOPNN generated through learning results in optimal network architecture. The design procedure applied in the construction of each layer of the SOPNN deals with its structural optimization involving the selection of preferred nodes (or PNs) with specific local characteristics (such as the number of input variables, the order of the polynomials, and input variables) and addresses specific aspects of parametric optimization. An aggregate performance index with a weighting factor is proposed in order to achieve a sound balance between the approximation and generalization (predictive) abilities of the model. To evaluate the performance of the GA-based SOPNN, the model is experimented using pH neutralization process data as well as sewage treatment process data. A comparative analysis indicates that the proposed SOPNN is the model having higher accuracy as well as more superb predictive capability than other intelligent models presented previously.reviously.

• The Journal of the Korea Contents Association
• /
• v.22 no.3
• /
• pp.54-61
• /
• 2022

Ship is a huge system including a variety of pipe arrangements. Pipes are installed according to the design layout, however the end poistion of pipes are not well matched owing to its measurement and construction errors. In this situation, the customized pipe fitting is frequently designed to connect with both pipes, the position of which are manually measured. This paper focused that these two coordinates are measured by point cloud from RGBD sensor and the relative transformation induced by positional and orientational differences is calculated by inverse kinematics in robotics theory. Therefore, the result applies for the methodology of the pipe connection design. The pipe coordinate that is estimated by the matching and the probabilistic RANSAC method will be verified by experiments. The kinematic design parameters are computationally calculated by using the minimum degree of freedom that connects both pipe coordinates.

• Journal of Sensor Science and Technology
• /
• v.32 no.3
• /
• pp.174-179
• /
• 2023

Bulk trailers, used for the transportation of powdered materials, such as cement and fly ash, are crucial in the construction industry. The speedy exhaustion of powdered materials stored in the tank of bulk trailers is relevant to improving transportation efficiency and reducing transportation costs. The exhaust time can be reduced by developing an automatic control system to replace the manual exhaust operation. The instantaneous or accumulated exhausts of powdered materials must be measured for automatic control of the bulk trailer exhaust system. Accordingly, we previously proposed a recurrent neural network (RNN) model that estimated the instantaneous exhaust based on low-cost pressure sensor signals without an expensive flowmeter for powders. Although our previous study utilized only an RNN model, models such as multilayer perceptron (MLP) and convolutional neural network (CNN) are also widely utilized for time-series estimation. This study compares the performance of three neural network models (MLP, CNN, and RNN) in estimating instantaneous and accumulated exhausts. In terms of the instantaneous exhaust estimation, the difference in the performance of neural network models was insignificant (that is, 8.64, 8.62, and 8.56% for the MLP, CNN, and RNN, respectively, in terms of the normalized root mean squared error). However, in the case of the accumulated exhaust, the performance was excellent in the order of CNN (1.67%), MLP (2.03%), and RNN (2.20%).

• Journal of rehabilitation welfare engineering & assistive technology
• /
• v.9 no.1
• /
• pp.17-21
• /
• 2015

There have been sustained developments of advanced technologies using traffic safety facilities recently and techniques for identifying failure modes and devices which could result in fatal outcomes. The purpose of this research is aimed at improving the driving conditions in advance through analyzing the IT convergence, driving education, researches for vehicles, field of construction and robotics. The researchers evaluate on usability tests of the driving with 26 candidates through focusing on safety, convenience, efficiency, effectiveness. Using specialized LED panel to enhance driving performances of disabled people are for cautious road conditions like foggy weather or heavy rain. As a result, there were improvements in the driving conditions, and candidates reported this system was helpful. It allows them for maintaining proper driving all times and was especially informative for people with low vision or visually impaired. This system plays a pivotal role as a prevention mechanism not only for regular drivers but also for further delict of traffic violations or accident offenders who already have former record on tort.

• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.17 no.10
• /
• pp.678-684
• /
• 2016

The detection of an underwater work space boundary is very important when an underwater construction is carried out using seabed type underwater equipment, such as underwater machines for rubble mound leveling, because it can induce industrial disasters. Therefore, divers are needed to mark the underwater work space boundary. A nylon rope is used to improve the convenience during an underwater diver's work. The results showed that the work space boundary can be detected using a sonar system. Using these results, an efficient method to detect the underwater work space boundary can be obtained when an underwater construction is carried out using seabed type underwater equipment.