• Structural Engineering and Mechanics
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• v.49 no.5
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• pp.645-660
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• 2014

This paper presents the design and project of an innovative concept for a Single Point Incremental Forming (SPIF) Machine. Nowadays, equipment currently available for conducting SPIF result mostly from the adaptation of conventional CNC machine tools that results in a limited range of applications in terms of materials and geometries. There is also a limited market supply of equipment dedicated to Incremental Sheet Forming (ISF), that are costly considering low batches, making it unattractive for industry. Other factors impairing a quicker spread of SPIF are large forming times and poor geometrical accuracy of parts. The following sections will depict the development of a new equipment, designed to overcome some of the limitations of machines currently used, allowing the development of a sounding basis for further studies on the particular features of this process. The equipment here described possesses six-degrees-of freedom for the tool, for the sake of improved flexibility in terms of achievable tool-paths and an extra stiffness provided by a parallel kinematics scheme. A brief state of the art about the existing SPIF machines is provided to support the project's guidelines.

• Korean Journal of Agricultural and Forest Meteorology
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• v.19 no.3
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• pp.86-92
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• 2017

In this study, a model to classify frost occurrence and frost free day was developed using the digital weather forecast data provided by Korea Meteorological Administration (KMA). The minimum temperature, average wind speed, relative humidity, and dew point temperature were identified as the meteorological variables useful for classification frost occurrence and frost-free days. It was found that frost-occurrence date tended to have relatively low values of the minimum temperature, dew point temperature, and average wind speed. On the other hand, relatively humidity on frost-free days was higher than on frost-occurrence dates. Models based on machine learning methods including Artificial Neural Network (ANN), Random Forest(RF), Support Vector Machine(SVM) with those meteorological factors had >70% of accuracy. This results suggested that these models would be useful to predict the occurrence of frost using a digital weather forecast data.

• Journal of Biosystems Engineering
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• v.26 no.1
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• pp.29-38
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• 2001

A navigation system was developed for autonomous guidance of a combine. It consisted of a DGPS, a machine vision system, a gyro sensor and an ultrasonic sensor. For an autonomous operation of the combine, target points were determined at first. Secondly, heading angle and offset were calculated by comparing current positions obtained from the DGPS with the target points. Thirdly, the fuzzy controller decided steering angle by the fuzzy inference that took 3 inputs of heading angle, offset and distance to the bank around the rice field. Finally, the hydraulic system was actuated for the combine steering. In the case of the misbehavior of the DGPS, the machine vision system found the desired travel path. In this way, the combine traveled straight paths to the traget point and then turned to the next target point. The gyro sensor was used to check the turning angle. The autonomous combine traveled within 31.11cm deviation(RMS) on the straight paths and harvested up to 96% of the whole rice field. The field experiments proved a possibility of autonomous harvesting. Improvement of the DGPS accuracy should be studied further by compensation variations of combines attitude due to unevenness of the rice field.

• Korean Journal of Agricultural Science
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• v.46 no.1
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• pp.67-78
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• 2019

The purpose of this study was to predict the water quality using the RNN (recurrent neutral network) and LSTM (long short-term memory). These are advanced forms of machine learning algorithms that are better suited for time series learning compared to artificial neural networks; however, they have not been investigated before for water quality prediction. Three water quality indexes, the BOD (biochemical oxygen demand), COD (chemical oxygen demand), and SS (suspended solids) are predicted by the RNN and LSTM. TensorFlow, an open source library developed by Google, was used to implement the machine learning algorithm. The Okcheon observation point in the Geum River basin in the Republic of Korea was selected as the target point for the prediction of the water quality. Ten years of daily observed meteorological (daily temperature and daily wind speed) and hydrological (water level and flow discharge) data were used as the inputs, and irregularly observed water quality (BOD, COD, and SS) data were used as the learning materials. The irregularly observed water quality data were converted into daily data with the linear interpolation method. The water quality after one day was predicted by the machine learning algorithm, and it was found that a water quality prediction is possible with high accuracy compared to existing physical modeling results in the prediction of the BOD, COD, and SS, which are very non-linear. The sequence length and iteration were changed to compare the performances of the algorithms.

• 제어로봇시스템학회:학술대회논문집
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• 1991.10b
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• pp.1904-1909
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• 1991

Software linear and exponential acceleration/deceleration algorithms for control of machine axes of motion in industrial robots and CNC machine tools are proposed. Typical hardware systems used to accelerate and decelerate axes of motion are mathematically analyzed. Discrete-time state equations are derived from the mathematical analyses for the development of software acceleration/deceleration algorithms. Synchronous control method of multiple axes of motion in industrial robots and CNC machine tools is shown to be easily obtained on the basis of the proposed acceleration/deceleration algorithms. The path error analyses are carried out for the case where the software linear and exponential acceleration/deceleration algorithms are applied to a circular interpolator. A motion control system based on a floating point digital signal processor (DSP) TMS 320C30 is developed in order to implement the proposed algorithms. Experimental results demonstrate that the developed algorithms and the motion control system are available for control of multiple axes and nonlinear motion composed of a combination of lines and circles which industrial robots and CNC machine tools require.

• Journal of Korean Society of Environmental Engineers
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• v.33 no.10
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• pp.748-755
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• 2011

After the Industrialization of 1960s, while it has greatly contributed to the industrial development owing to acceleration of mechanization, but it is real situation that the countermeasure to noise damage generating at the loud noise workshop is scarcely made. Especially, the machine noise made at factory and workplace is so shocking and repeatedly reiterating terrible noise that most of the spot workers are forcedly imposing such dangers as the severe unpleasant feeling and hearing impairments. On such point of view, this research has attempted to extract the proper rating vocabulary in order for evaluation on machine noise made at the high noisy workshop, therefore it is considering that those extracted vocabularies could be utilized as the useful psycho-acoustic experiment for evaluation on machine noise, also for establishment of regulation standard in domestic high noisy workshop.

• The Transactions of the Korean Institute of Power Electronics
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• v.10 no.1
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• pp.29-37
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• 2005

This paper presents a tuning-free conditional integration anti-windup strategy for induction machine with Proportional-Integral(PI) type speed controller. The on/off condition of integral action is determined by the frequency domain analysis of machine torque command without a prior knowledge of set-point changes. There are no tuning parameters to be selected by users for anti-windup scheme. In addition, the dynamic performance of the proposed scheme assures a desired tracking response curve with minimal oscillation and settling time even in the change of operating conditions. This algorithm is useful in many high performance induction machine applications not to allow the oscillation and overshoot of speed/torque responses. The main idea can be extended to general applications such as chemical processes and industrial robots.

• Journal of Biosystems Engineering
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• v.27 no.2
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• pp.143-150
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• 2002

Several researches for site-specific weed control have tried to increase accuracy of weed detection with machine vision technique. However, there is a problem which needs substantial time to perform site-specific spraying. Therefore, new technology for real-time precision spraying system is needed. This research was executed to develope the new technology to estimate weed density and size in real time, and to conduct a real-time site-specific spraying. It would effectively reduce herbicide amounts applied for a crop field. The real-time precision spraying system consisted of a Differential Global Positioning System (DGPS) with an error of 2 cm, a machine vision system, a geomagnetic sensor for correction of view point of CCD camera and an automatic sprayer with separately controlled nozzle. The weed density was calculated with comparison between position information and a pre-designed electronic map. The position information was obtained in real time using the DGPS and the machine vision. The electronic map contained a position database of crops automatically constructed when seeding. The developed system was tested on an experimental field of Seoul National University. Success rate of the spraying was about 61%.

• Journal of the Architectural Institute of Korea Structure & Construction
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• v.34 no.4
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• pp.65-74
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• 2018

The primary objective of this study is to develop a conceptual design of automated pothole patching machine that improves the conventional work in safety, quality, and productivity. For this, the following research works are conducted sequentially; 1)literature review, 2)selection of element technology for conceptual design, 3)deduction of work process and conceptual design, 4)life cycle cost analysis of the conceptual design. As a result, X-Y table telescopic manipulator, pothole patching end effector, realtime pothole recognizer, 3D pothole volume profiler, automated pothole patching machine controller are selected as core technologies. Furthermore, a conceptual design and working process of an automated pothole patching machine are developed based on the core technologies. According to the life cycle cost analysis result, the cost of the automated method was 38.3% less than that of the conventional method, and the economic efficiency was also superior(ROR 77.1%, Break-even Point 23.8month). It is expected that the application range and impact on the construction industry will be enormous due to the increasing trend of road maintenance market.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 2002.04a
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• pp.53-58
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• 2002

This paper aims to synthesize the research on fatigue mechanisms of high strength aluminum alloys which are widely used in motorcars or airplanes to prevent accidents. To measure the data of crack opening ratio, the same materials and methods are used for evaluating the fatigue crack propagation rate as an effective stress intensity factor. But, many researchers have brought different results. An exact crack opening ratio was, therefore, proposed for getting a more accurate fatigue crack propagation rate.