• Journal of the Korean Institute of Intelligent Systems
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• v.26 no.3
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• pp.208-217
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• 2016

This paper describes a simulation method to generate sensor measurements for location estimation of an underwater robot. Field trial of a navigation method of an underwater robot takes much time and expenses and it is difficult to change the environment of the field trial as desired to test the method in various situations. Therefore, test and verification of a navigation method through simulation is inevitable for underwater environment. This paper proposes a method to generate sensor measurements of range, depth, velocity, and attitude taking the uncertainties of measurements into account through simulation. The uncertainties are Gaussian noise, outlier, and correlation between the measurement noise. Also, the method implements uncertainty in sampling time of measurements. The method is tested and verified by comparing the uncertainty parameters calculated statistically from the generated measurements with the designed uncertainty parameters. The practical feasibility of the measurement data is shown by applying the measurement data for location estimation of an underwater robot.

• Journal of Institute of Control, Robotics and Systems
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• v.17 no.8
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• pp.768-776
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• 2011

This paper considers a data fitting problem for rational function models using the LM (Levenberg-Marquardt) optimization method. Rational function models have various merits on representing a wide range of shapes and modeling complicated structures by polynomials of low degrees in both the numerator and denominator. However, rational functions are nonlinear in the parameter vector, thereby requiring nonlinear optimization methods to solve the fitting problem. In this paper, we propose a data fitting method for rational function models based on the LM algorithm which is renowned as an effective nonlinear optimization technique. Simulations show that the fitting results are robust against the measurement noises and uncertainties. The effectiveness of the proposed method is further demonstrated by the real application to a 3D depth camera calibration problem.

• Ocean and Polar Research
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• v.36 no.4
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• pp.487-494
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• 2014

Deep-seabed test miner operated by a self-propelled mining system moving on soft soil is an essential device to secure floating and towing performances. The performances of the tracked vehicle are seriously influenced by noise factors such as the shear strength of the seafloor, bottom current, seafloor slope, speed of tracked vehicle, reaction forces of flexible hose, steering ratio, etc. Due to uncertainties related to noise factors, the design of a deep-sea manganese nodules test miner that satisfies target reliabilities is difficult. Therefore, reliability-based design optimization (RBDO) is required to guarantee system reliability under circumstances where uncertainties related to noise factors prevail. Among noise factors, the bottom current, a bimodal distribution, is censored due to the observation limit of measurement devices. Therefore, estimated distribution of the bottom current is inaccurate without considering these characteristics and the result of RBDO cannot be guaranteed. In this paper, we define censored data as unknown values over the limit of observation. If this data is estimated by using Akaike information criterion (AIC) that cannot consider the characteristics of censored data, the distribution of estimated data cannot guarantee accurate reliability. Therefore, censored AIC that can consider the characteristics of data is used to estimate accurate distribution of the bottom current. Finally, RBDO, under circumstances where uncertainties related to noise factors combined censored data are present, is performed on the mobility of a deep-sea manganese nodules test miner.

• Wind and Structures
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• v.11 no.6
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• pp.427-440
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• 2008

Estimates of wind-induced wind effects on tall buildings are based largely on 1980s technology. Such estimates can vary significantly depending upon the wind engineering laboratory producing them. We describe an efficient database-assisted design (DAD) procedure allowing the realistic estimation of wind-induced internal forces with any mean recurrence interval in any individual member. The procedure makes use of (a) time series of directional aerodynamic pressures recorded simultaneously at typically hundreds of ports on the building surface, (b) directional wind climatological data, (c) micrometeorological modeling of ratios between wind speeds in open exposure and mean wind speeds at the top of the building, (d) a physically and probabilistically realistic aerodynamic/climatological interfacing model, and (e) modern computational resources for calculating internal forces and demand-to-capacity ratios for each member being designed. The procedure is applicable to tall buildings not susceptible to aeroelastic effects, and with sufficiently large dimensions to allow placement of the requisite pressure measurement tubes. The paper then addresses the issue of accounting explicitly for uncertainties in the factors that determine wind effects. Unlike for routine structures, for which simplifications inherent in standard provisions are acceptable, for tall buildings these uncertainties need to be considered with care, since over-simplified reliability estimates could defeat the purpose of ad-hoc wind tunnel tests.

• Analytical Science and Technology
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• v.25 no.6
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• pp.350-363
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• 2012

To determine ionic species in snowpit samples using ion chromatography system, we described the performance of ion chromatography(IC) system, cleaning method of bottle, and interference by filtering procedure. The limit of detection, reproducibilities, and accuracies determined with BCR$^{(R)}$-408 were 0.01-0.26 ${\mu}g$/L, 0.4-17.4%, 4.5-12.0% for cations and 0.02-0.26 ${\mu}g/L$, 0.1-27.6%, 1.3-5.6% for anions, respectively. Lab blank test for sample bottle indicated that $CH_3CO_2{^-}$, $HCO_2{^-}$, and $NH_4{^+}$ can be easily contaminated in the lab environment. The positive interferences of $NO_3{^-}$ were partly attributed to the cleaning method of bottle. The filtering of melted snow sample should be carefully applied because it can positively affect the concentration levels of some ionic species. Finally, this method was applied to measure ionic species in snowpit samples from the upward area near NEEM camp and the uncertainties of measurement data of $F^-$ were also estimated.

• The KSFM Journal of Fluid Machinery
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• v.16 no.4
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• pp.5-9
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• 2013

An experimental investigation has been carried out in order to evaluate characteristics of wetted-type multi-path ultrasonic flowmeters. The multi-path ultrasonic flowmeters were installed at various entrance and exit locations for several cases of pipe fitting(straight, $90^{\circ}$ double elbow) and valve(gate valve, butterfly valve). We measured the flow-rate at each location. The measurement data of test flowmeter were compared with the measured data of reference flowmeter. The uncertainties of reference flowmeter and test flowmeter are 0.3 %, 0.4 %, respectively. The results demonstrate the effects of flowmeter location as well as the measurement errors in flow rate. The distance between the flow disturbance factor and a flowmeter was an important element of the test.

• Journal of Korea Water Resources Association
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• v.55 no.spc1
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• pp.1295-1303
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• 2022

As the role of water distribution networks (WDNs) becomes more important, identifying abnormal events (e.g., pipe burst) rapidly and accurately is required. Since existing approaches such as field equipment-based detection methods have several limitations, model-based methods (e.g., machine learning based detection model) that identify abnormal events using hydraulic simulation models have been developed. However, no previous work has examined the impact of data uncertainties on the results. Thus, this study compares the effects of measurement error-induced pressure data uncertainty in WDNs. An artificial neural network (ANN) is used to predict nodal pressures and measurement errors are generated by using cumulative density function inverse sampling method that follows Gaussian distribution. Total of nine conditions (3 input datasets × 3 output datasets) are considered in the ANN model to investigate the impact of measurement error size on the prediction results. The results have shown that higher data uncertainty decreased ANN model's prediction accuracy. Also, the measurement error of output data had more impact on the model performance than input data that for a same measurement error size on the input and output data, the prediction accuracy was 72.25% and 38.61%, respectively. Thus, to increase ANN models prediction performance, reducing the magnitude of measurement errors of the output pressure node is considered to be more important than input node.

• Proceedings of the Korean Society of Agricultural Engineers Conference
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• 1998.10a
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• pp.425-430
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• 1998

The theory of consolidation has been achieved remarkable development, but associated properties are very difficult to determine in the laboratory. The theoretical shortcomings of those consolidation theories and uncertainties of associated properties make inevitably some discrepancy between theoretical and field settlements. Field settlement measurement by settlement plate is, therefore, widely used to overcome the discrepancy. Among the various methods of ultimate settlement predictions using field settlement data, hyperbolic method and Asaoka's method are most commonly used because of their simplicity and ability to give a reasonable estimate of consolidation settlement. In this paper, the applicability of hyperbolic method and Asaoka's method has been estimated by the analysis of the laboratory consolidation test and field measured data. It is shown that both hyperbolic method and Asaoka's method are significantly affected by the direction of drainage, and Asaoka's method is better to reflect the properties of the soft foundation than hyperbolic method.

• Transactions on Control, Automation and Systems Engineering
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• v.2 no.4
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• pp.235-243
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• 2000

The probabilistic data association filter(PDAF) is known to provide better tracking performance than the standard Kalman filter(KF) in a cluttered environment. In this paper, the stability of the PDAF of Fortmann et al[7], in the presence of uncertainties with regard to the origin of measurement, is investigated. The modified Riccati equation derived by approximating two random terms with their expectations is used to prove the stability of the PDAF. A new Lyapunov function based approach, which is different from the quantitative evaluation of Li and Bar-Shalom[7], is pursued. With the assumption that the system and observation noises are bounded, specific tracking error bounds are established.

• Proceedings of the Korean Nuclear Society Conference
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• 1996.05a
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• pp.244-250
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• 1996

Uncertainties in core neutronic calculations of CASMO-3/MASTER, which is a KAERI developed core nuclear design code system, were evaluated via comparisons with measured data. Comparisons were performed with plant measurement data from one Westinghouse type and one ABB-CE type plant and two Korean standard type plants. The CASMO-3/MASTER capability and levels of accuracy are concluded to be sufficient for the neutronics design including safety related parameters related with reactivity, power distributions, temperature and power coefficients, inverse boron worth and control bank worth.