• Journal of Ocean Engineering and Technology
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• v.34 no.6
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• pp.377-386
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• 2020

This paper discusses the effectiveness of onboard measurements and data extracted from weather information for speed-power analysis. Furthermore, validation results of hull and propeller cleaning and painting during dry-docking are discussed. Wind and wave information can be obtained from onboard measurements or weather information from the National Oceanic and Atmospheric Administration (NOAA). The weather information of a specified position and time is extracted from NOAA weather data and compared with onboard measurements. In addition, to validate the effects of hull cleaning and painting during dry-docking, speed-power analysis results of before and after dry-docking are compared. The results show that both onboard measurements and weather information show acceptable reliability when added resistance and speed-power analysis results are compared with each other. Moreover, the ship performance analysis (SPA) software clearly shows the effects of hull cleaning and painting, and it can provide reliable analysis results with either onboard measurements or weather information. In conclusion, it is confirmed that the analysis method and SPA software used in this study are effective in analyzing the ship's speed-power performance.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.10 no.3
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• pp.599-607
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• 2006

The ship radiated noise appear the various characteristic signals due to the mechanic system in the ship, the propeller and the interaction between ship body and sea water. Generally, it is classified two main components: the speed dependent signal and the speed independent signal. It is required that very complex procedure to classify the signal origin from the ship-radiated noise. This paper presents techniques to automatically detect and classify the tonal signals ken the ship-radiated noise, using the Q factor and the neural network.

• Journal of the Society of Naval Architects of Korea
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• v.59 no.2
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• pp.125-133
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• 2022

This paper proposes a fault detection method for a Unmanned Surface Vehicle (USV) with overactuated system. Current status information for fault detection is expressed as a scalogram image. The scalogram image is obtained by wavelet-transforming the USV's control input and sensor information. The fault detection scheme is based on Convolutional Neural Network (CNN) algorithm. The previously generated scalogram data was transferred learning to GoogLeNet algorithm. The data are generated as scalogram images in real time, and fault is detected through a learning model. The result of fault detection is very robust and highly accurate.

• Journal of Aerospace System Engineering
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• v.12 no.6
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• pp.23-31
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• 2018

In the present work, the thrust and torque of multicopter propellers in hovering are predicted based on BET method. The geometry information of the propellers is obtained using a three dimensional scanner and the airfoil section is extracted using CATIA. EDISON CFD is adopted to calculate the drag and lift of airfoil at a given geometry and flow conditions and then thrust is calculated with respect to a given RPMs based on BET. Two simulations with laminar and turbulent flows are considered. The predicted value is compared with the performance data from the Product Company and results from JavaProp software, which is used in the design and prediction of propellers. In the case of a 9-inch propeller, the thrust from the product company is corresponding to the results between the laminar and turbulent flow conditions. In the 16-inch case, the predicted thrust at turbulent flow conditions conformed well with reference one. The predicted torque shows a big difference with the reference data.

• Journal of the Society of Naval Architects of Korea
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• v.35 no.3
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• pp.71-78
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• 1998

Recently, modern long-stroke diesel engines with small number of cylinders have been installed for energy saving and simpler maintenance. These kinds of low speed diesel engine produce large torsional vibration in the shafting, which induces the excessive vibratory stresses in the shafting and large propeller thrust variation. This thrust variation excites vibrations of the shafting and superstructure in the longitudinal direction. Up to now the deteriministic analysis of coupled vibration of marine shafting system has been performed. In this paper probabilistic analysis method of the marine diesel propulsion shafting system under coupled axial and torsional vibrations is presented. For the purpose of this work, the torsional and axial vibration excitations of engine and propeller are assumed to be probabilistic while the lateral excitation is assumed to be deterministic. The probabilistic analysis is based on a response surface and Monte-Carlo simulation. Numerical results based on the proposed method are compared with results calculated using the conventional deterministic analysis method. The results obtained make it clear that the proposed method gives a substantial increase in information about shafting behaviour as compared with the deterministic method.

• Journal of Advanced Navigation Technology
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• v.22 no.6
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• pp.551-556
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• 2018

In recent years, drones have been used to measure aircraft flights data and weather information. Related applications include the measure for low-altitude atmospheric data, the measure for atmospheric fine dust, and the measure for air pollution. However, the mounting position of the atmospheric measurement sensor should be mounted by considering the effects of propeller flow, the EMI effects, and the changes in the weight of the drone. Among these, the upper flow of the propeller affects the wind speed and direction, so the optimal position should be selected. This study deals with the proper height of the atmospheric data measurement sensor. Through the flow analysis, we study the flow characteristics of around a drone and suggest the proper sensor mounting height.

• Journal of Internet Computing and Services
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• v.22 no.3
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• pp.67-73
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• 2021

In this paper, in order to prevent the fall of the drone, a study was conducted to collect vibration data from the motor connected to the propeller of the drone, and to predict the abnormal vibration of the drone using recurrent neural network (RNN) and long short term memory (LSTM). In order to collect the vibration data of the drone, a vibration sensor is attached to the motor connected to the propeller of the drone to collect vibration data on normal, bar damage, rotor damage, and shaft deflection, and abnormal vibration data are collected through LSTM and RNN. The root mean square error (RMSE) value of the vibration prediction result were compared and analyzed. As a result of the comparative simulation, it was confirmed that both the predicted result through RNN and LSTM predicted the abnormal vibration pattern very accurately. However, the vibration predicted by the LSTM was found to be 15.4% lower on average than the vibration predicted by the RNN.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.40 no.12
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• pp.2476-2484
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• 2015

Narrow band signal estimation and broad band signal estimation can be used to detect the ship-radiated noise. The broad band signal estimation method to detect the ship-radiated noise is called DEMON (Detection of Envelop Modulation On Noise). This paper proposes a new DEMON algorithm applying compressed sensing algorithm to filter bank and autocorrelation. We show the proposed algorithm estimates the hidden period in the wide band signal better than the conventional DEMON algorithm and the recently proposed filter-bank based DEMON algorithm. Especially we show that the proposed algorithm needs shorter data length than the conventional DEMON algorithm.

• International Journal of Aeronautical and Space Sciences
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• v.11 no.4
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• pp.338-344
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• 2010

This paper discusses the development of the control system of a mini quadrotor in Konkuk University for indoor applications. The attitude control system consists of a stability augmentation system, which acts as the inner loop control, and a modern control approach based on modeling will be implemented as the outer loop. The inner loop control was experimentally satisfied by a proportional-derivative controller; this was used to support the flight test in order to validate the modeling. This paper introduces the mathematical model for the simulation and design of the optimal control on the outer loop control. To perform the experimental tests, basic electronic hardware was developed using simple configurations; a microcontroller used as the embedded controller, a low-cost 100 Hz inertial sensors used for the inertial sensing, infra-red sensors were employed for horizontal ranging, an ultrasonic sensor was used for ground ranging and a high performance propeller system built on an quadrotor airframe was also employed. The results acquired from this compilation of hardware produced an automatic hovering ability of the system with ground control system support for the monitoring and fail-safe system.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.39B no.8
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• pp.538-543
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• 2014

Narrow band signal estimation and broad band signal estimation can be used to detect the ship-radiated noise. The broad band signal estimation method to detect the ship-radiated noise is called DEMON (Detection of Envelop Modulation On Noise). This paper proposes a new DEMON algorithm using filter bank and autocorrelation. We show the proposed algorithm estimates the hidden period in the wide band signal better than the conventional DEMON algorithm and the recently proposed filter-bank based DEMON algorithm.