• Journal of Bio-Environment Control
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• v.8 no.4
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• pp.232-241
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• 1999

The automatic irrigation system using the stem diameter monitoring and the transpiration model for the determination, respectively, of irrigation timing and amount was designed and evaluated for its applicability in pot and field culture of greenhouse tomato. In the pot culture condition, the yield and quality of greenhouse tomato were improved when irrigation was practiced based on the stem diameter monitoring and the transpiration model as compared to the irrigation practice based on soil moisture monitoring. However, the effects were not significant in the field culture condition.

• Agricultural and Biosystems Engineering
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• v.4 no.1
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• pp.8-15
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• 2003

In Korea, quality evaluation of dried oak mushrooms are done first by classifying them into more than 10 different categories based on the state of opening of the cap, surface pattern, and colors. And mushrooms of each category are further classified into 3 or 4 groups based on its shape and size, resulting into total 30 to 40 different grades. Quality evaluation and sorting based on the external visual features are usually done manually. Since visual features of mushroom affecting quality grades are distributed over the entire surface of the mushroom, both front (cap) and back (stem and gill) surfaces should be inspected thoroughly. In fact, it is almost impossible for human to inspect every mushroom, especially when they are fed continuously via conveyor. In this paper, considering real time on-line system implementation, image processing algorithms utilizing artificial neural network have been developed for the quality grading of a mushroom. The neural network based image processing utilized the raw gray value image of fed mushrooms captured by the camera without any complex image processing such as feature enhancement and extraction to identify the feeding state and to grade the quality of a mushroom. Developed algorithms were implemented to the prototype on-line grading and sorting system. The prototype was developed to simplify the system requirement and the overall mechanism. The system was composed of automatic devices for mushroom feeding and handling, a set of computer vision system with lighting chamber, one chip microprocessor based controller, and pneumatic actuators. The proposed grading scheme was tested using the prototype. Network training for the feeding state recognition and grading was done using static images. 200 samples (20 grade levels and 10 per each grade) were used for training. 300 samples (20 grade levels and 15 per each grade) were used to validate the trained network. By changing orientation of each sample, 600 data sets were made for the test and the trained network showed around 91 % of the grading accuracy. Though image processing itself required approximately less than 0.3 second depending on a mushroom, because of the actuating device and control response, average 0.6 to 0.7 second was required for grading and sorting of a mushroom resulting into the processing capability of 5,000/hr to 6,000/hr.

• Journal of Biosystems Engineering
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• v.30 no.3 s.110
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• pp.172-178
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• 2005

Grading and sorting an indeterminate form of agricultural products such as sweet potatoes and potatoes are a labor intensive job because its shape and size are various and complicate. It costs a great deal to sort sweet potato in an indeterminate forms. There is a great need for an automatic grader fur the potatoes. Machine vision is the promising solution for this purpose. The optical indices for qualifying weight and appearance quality such as shape, color, defects, etc. were obtained and an on-line sorting system was developed. The results are summarized as follows. Sorting system combined with an on-line inspection device was composed of 5 sections, human inspection, feeding, illumination chamber, image processing & control, and grading & discharging. The algorithms to compute geometrical parameters related to the external guality were developed and implemented for sorting the deformed sweet potatoes. Grading accuracy by image processing was $96.4\%$ and the processing capacity was 10,800 pieces per hour.

• Journal of the Korean Society for Railway
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• v.14 no.5
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• pp.404-410
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• 2011

In AC feeding system, the fault location is calculated by using ratio of current absorbed in the neutral point of AT(Automatic Transformer) or by measuring reactance. In this way, however, an estimation error can be happened due to the many reasons. In addition, for measuring currents in the neutral point of AT, other measuring devices and communication equipments are additionally required. In order to solve the disadvantages, this paper suggests a novel technique using the distribution ratio of catenary current. The proposed technique uses existing protective relays and measures catenary current. With the measured data, we can calculate the distribution ratio of catenary current and determine fault location. Through the simulated results, we derived the correlation between current ratio and fault location. Using this technique, additional equipments and expenses can be reduced. Besides, fault location can be determined more correctly.

• International Journal of Control, Automation, and Systems
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• v.5 no.6
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• pp.643-651
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• 2007

The various blood pressure simulators have been proposed to evaluate and improve the performance of the automatic sphygmomanometer. These have some problems such as the deviation of the actual blood pressure waveform, limitation in the blood pressure condition of the simulator, or difficulty in displaying the blood flow. An improved simulator using disturbance observer is proposed to supplement the current problems of the blood pressure simulator. The proposed simulator has an artificial arm model capable of feeding appropriate fluids that can generate the blood pressure waveform to evaluate the automatic sphygmomanometer. A controller was designed and thereafter, simulation was performed to control the output signal with respect to the reference input in the fluid dynamic model using the proposed proportional control valve. To minimize the external fluctuation of pressure applied to the artificial arm, a disturbance observer was designed on the plant. A hybrid controller combined with a proportional controller and feed-forward controller was fabricated after applying a disturbance observer to the control plant. Comparison of the simulations between the conventional proportional controller and the proposed hybrid controller indicated that even though the former showed good control performance without disturbance, it was affected by the disturbance signal induced by the cuff. The latter exhibited an excellent performance under both situations.

• Proceedings of the Korean Society for Agricultural Machinery Conference
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• 2000.11b
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• pp.318-324
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• 2000

Ultrasonic and magnetic resonance imaging systems are used to visualize the interior states of biological objects. These nondestructive methods have many advantages but too much expensive. And they do not give exact color information and may miss some details. If it is allowed to destruct some biological objects to get the interior and exterior information, constructing 3D image from the series of the sliced sectional images gives more useful information with relatively low cost. In this paper, PC based automatic 3D model generator was developed. The system was composed of three modules. One is the object handling and image acquisition module, which feeds and slices objects sequentially and maintains the paraffin cool to be in solid state and captures the sectional image consecutively. The second is the system control and interface module, which controls actuators for feeding, slicing, and image capturing. And the last is the image processing and visualization module, which processes a series of acquired sectional images and generates 3D graphic model. The handling module was composed of the gripper, which grasps and feeds the object and the cutting device, which cuts the object by moving cutting edge forward and backward. Sliced sectional images were acquired and saved in the form of bitmap file. The 3D model was generated to obtain the volumetric information using these 2D sectional image files after being segmented from the background paraffin. Once 3-D model was constructed on the computer, user could manipulate it with various transformation methods such as translation, rotation, scaling including arbitrary sectional view.

• Agricultural and Biosystems Engineering
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• v.1 no.2
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• pp.95-99
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• 2000

Nondestructive methods such as ultrasonic and magnetic resonance imaging systems have many advantages but still much expensive. And they do not give exact color information and may miss some details. If it is allowed to destruct some biological objects to get interior and exterior informations, constructing 3D image form a series of slices sectional images gives more useful information with relatively low cost. In this paper, a PC based automatic 3D model generator was developed. The system was composed of three modules. The first module was the object handling and image acquisition module, which fed and sliced the object sequentially and maintains the paraffine cool to be in solid state and captures the sectional image consecutively. The second one was the system control and interface module, which controls actuators for feeding, slicing, and image capturing. And the last was the image processing and visualization module, which processed a series of acquired sectional images and generated 3D volumetric model. Handling module was composed of the gripper, which grasped and fed the object and the cutting device, which cuts the object by moving cutting edge forward and backward. sliced sectional images were acquired and saved in a form of bitmap file. 2D sectional image files were segmented from the background paraffine and utilized to generate the 3D model. Once 3-D model was constructed on the computer, user could manipulated it with various transformation methods such as translation, rotation, scaling including arbitrary sectional view.

• Journal of the Korean Society for Precision Engineering
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• v.21 no.12
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• pp.84-91
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• 2004

A CCD camera with a laser stripe was applied to realize the automatic weld seam tracking in GMAW. It takes relatively long time to process image on-line control using the basic Hough transformation, but it has a tendency of robustness over the noises such as spatter and arc tight. For this reason, it was complemented with adaptive Hough transformation to have an on-line processing ability for scanning specific weld points. The adaptive Hough transformation was used to extract laser stripes and to obtain specific weld points. The 3-dimensional information obtained from the vision system made it possible to generate the weld torch path and to obtain the information such as width and depth of weld line. In this study, a neural network based on the generalized delta rule algorithm was adapted for the process control of GMA, such as welding speed, arc voltage and wire feeding speed.

• Journal of Biosystems Engineering
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• v.35 no.3
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• pp.197-205
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• 2010

An automatic echelon feeder of brown rice was presented for quality inspection system using color image processing. A echelon feeder was developed with vibratory feeder and cylindrical indent singulator having oblique light. The vibratory feeder consisted of a hopper, electromagnetic vibrator and multichannel grooves and supply the grain sample to the singulator. The feeding performance such as feed rate, blocking frequency of the channel was dependent on the size of groove and vibration pattern. A cylindrical indent singulator consisted of a rotating cylinder, prisms and a tungsten-halogen light source. It delivered grain kernels under the camera in a echelon form and illuminate the kernels with oblique ray and ambient light. The size of the indents installed on the surface of the rotating cylinder was determined by the dimensions of the paddy and a small triangular prism was placed in each indent to apply $ 20^{\circ}$ oblique light to the grain kernel.

• Proceedings of the Korean Society for Agricultural Machinery Conference
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• 1993.10a
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• pp.779-790
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• 1993

A prototype of the feeding-milking robot was developed in the Hungarian Institute of Agricultural Engineering in 1988-89. Before starting with the operation tests the cleaning system had to be elaborated . The cleaning system has two parts. Those are the complete cleaning of the system, producing a practically sterile state, as well as flushing through the milking device between milking of two cows. Separate electronic sensor development was necessary for both system which can connect to the control system of the robot. To clean the system pneumatic air input was applied. As an effect of the local adjustment of the electronic control system optimal flow conditions can be formed what is more favourable comparing to the earlier solutions of cleaning due to the mechanical effect. In the flushing through overpressure air is applied. The air and the cleaning liquid input duration can be adjusted to the local conditions. The electronic control unit can be connected to the electric ircuits of robot.