• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.47 no.4
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• pp.300-308
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• 2019

For drones to be used for industrial or agricultural applications, it is necessary to increase the payload and endurance. Currently, the payload and endurance are limited by the battery technology for electric powered drones. In addition, charging or replacing the batteries may not be a practical solution at the field that requires near continuous operation. In this paper, a procedure to optimize the power system of an electric hybrid drone that consists of an internal combustion engine, a generator, a battery, and electric motors is presented. The example drone for crop dusting is sized for easy transportation with a maximum takeoff weight of 200 kg. The two main rotors that are mechanically connected to the internal combustion engine provides most of the lift. The drone is controled by four electric motors that are driven by the generator. By analyzing the flow of the energy, a methodology to select the optimum propeller and motor among the commercially available models is described. Then, a procedure of finding the optimum operational condition along with the proper gear reduction ratios for the internal combustion engine based on the test data is presented.

• Journal of Advanced Navigation Technology
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• v.15 no.2
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• pp.181-188
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• 2011

A small UAVs(Unmaned Aerial Vehicles) have limited by the payload capacity which requires miniaturization of a navigation system. In this paper, the performance of the lightweight and small sized AHRS(Attitude Heading Reference System), which is self-developed, is evaluated at low acceleration environment. The designed AHRS adopts the commercial low-cost MEMS sensors. A quaternion-based attitude calculation method, which eliminates singularity with relatively simple algebra, is used. In an attitude correction algorithm, the Kalman filter is used with accelerometers and magnetometers combined. The fabricated AHRS is also evaluated with reference to a COTS(Commercial Off-The-Shelf) AHRS which reports a number of successful applications to a small UAVs. The test results show that the measurements from the fabricated AHRS provide proper attitude output data with acceptable amount of differences(horizontal axis 0.5$^{\circ}$, vertical axis 1.5$^{\circ}$) in test environment.

• Journal of the Korean Association of Geographic Information Studies
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• v.23 no.4
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• pp.234-252
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• 2020

This paper is to verify the effectiveness of 'Hybrid Disaster Management Strategy' that integrates 'RTM(Real-time Monitoring) based On-line' and 'UAV based Off-line' system. For landslide prone area where sensors were installed, the conventional way of risk management so far has entirely relied on RTM data collected from the field through the instrumentation devices. But it's not enough due to the limitation of'Pin-point sensor'which tend to provide with only the localized information where sensors have stayed fixed. It lacks, therefore, the whole picture to be grasped. In this paper, utilizing 'Digital Photogrammetry Software Pix4D', the possibility of inference for the deformation of ungauged area has been reviewed. For this purpose, actual measurement data from RTM were compared with the estimated value from 3D point cloud outcome by UAV, and the consequent results has shown very accurate in terms of RMSE.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.39 no.11
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• pp.1052-1059
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• 2011

It is conducted that power characteristic variation simulation of electric propulsion system that uses fuel cells, solar cells and a battery as power sources. Combining each power source, 400W electric propulsion system have been modeled and verified. In result, without active control logic, it is confirmed that battery's power response is faster than other power sources at starting and transient condition, fuel cell and solar cell are a major electrical power during cruise condition. After completing flight, SOC is 24.2% at the winter solstice and is 93% at the summer solstice, It is revealed that active power control for sustaining proper SOC is necessary as a securing the system safety and effective power distribution.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.44 no.9
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• pp.833-841
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• 2016

The 200 W electrically powered unmanned aerial vehicle, which is studied in this research, uses solar cells, a fuel cell and batteries as the main power source simultaneously. The output of each power source performs power control for each power source by the active power control method so that an adequate capacity of the battery could be maintained while limiting the maximum output of the fuel cell. The output variation for each power source under the active power control method was identified through an integrated ground test. In addition, the effect of limiting the maximum output of the fuel cell on the output variation of the entire system was experimentally identified, and it was confirmed that the adequate maximum output value of the fuel cell for preventing the overdischarge of six series-connected, small size batteries for fuel cell systems is 150 W.

• International Journal of Aeronautical and Space Sciences
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• v.9 no.1
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• pp.100-110
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• 2008

It is not easy to monitor and identify all engine faults and conditions using conventional fault detection approaches like the GPA (Gas Path Analysis) method due to the nature and complexity of the faults. This study therefore focuses on a model based diagnostic method using Neural Network algorithms proposed for fault detection on a turbo shaft engine (PW 206C) selected as the power plant for a tilt rotor type unmanned aerial vehicle (Smart UAV). The model based diagnosis should be performed by a precise performance model. However component maps for the performance model were not provided by the engine manufacturer. Therefore they were generated by a new component map generation method, namely hybrid method using system identification and genetic algorithms that identifies inversely component characteristics from limited performance deck data provided by the engine manufacturer. Performance simulations at different operating conditions were performed on the PW206C turbo shaft engine using SIMULINK. In order to train the proposed BPNN (Back Propagation Neural Network), performance data sets obtained from performance analysis results using various implanted component degradations were used. The trained NN system could reasonably detect the faulted components including the fault pattern and quantity of the study engine at various operating conditions.

• Journal of Aerospace System Engineering
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• v.14 no.spc
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• pp.39-48
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• 2020

This paper deals with the process of estimating the environmental noise generated from the actual flying aircraft using the noise measurement results obtained through the wind tunnel test and verifying it through flight tests. In order to evaluate the environmental noise of an aircraft, noise tests and evaluations are generally conducted according to the procedures prescribed by the International Civil Aviation Organization (ICAO). In this paper, we introduced environmental noise evaluation method that can be applied to composite both fixed-wing aircraft and multi-copter, and introduced the evaluation method by experiment. This paper introduces the process of simulating the noise test results measured in the wind tunnel test using real flight test results. In addition, in consideration of flight operating conditions and noise measurement methods proposed by the ICAO, the effective perceived noise level (EPNL) was predicted by performing both the wind tunnel test and the aircraft flight test.